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Shojania KG. Is targeting healthcare's carbon footprint really the best we can do to help address the climate crisis? BMJ Qual Saf 2024; 33:205-208. [PMID: 37666662 DOI: 10.1136/bmjqs-2023-016312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 08/23/2023] [Indexed: 09/06/2023]
Affiliation(s)
- Kaveh G Shojania
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
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Verma AA, Trbovich P, Mamdani M, Shojania KG. Grand rounds in methodology: key considerations for implementing machine learning solutions in quality improvement initiatives. BMJ Qual Saf 2024; 33:121-131. [PMID: 38050138 DOI: 10.1136/bmjqs-2022-015713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 11/04/2023] [Indexed: 12/06/2023]
Abstract
Machine learning (ML) solutions are increasingly entering healthcare. They are complex, sociotechnical systems that include data inputs, ML models, technical infrastructure and human interactions. They have promise for improving care across a wide range of clinical applications but if poorly implemented, they may disrupt clinical workflows, exacerbate inequities in care and harm patients. Many aspects of ML solutions are similar to other digital technologies, which have well-established approaches to implementation. However, ML applications present distinct implementation challenges, given that their predictions are often complex and difficult to understand, they can be influenced by biases in the data sets used to develop them, and their impacts on human behaviour are poorly understood. This manuscript summarises the current state of knowledge about implementing ML solutions in clinical care and offers practical guidance for implementation. We propose three overarching questions for potential users to consider when deploying ML solutions in clinical care: (1) Is a clinical or operational problem likely to be addressed by an ML solution? (2) How can an ML solution be evaluated to determine its readiness for deployment? (3) How can an ML solution be deployed and maintained optimally? The Quality Improvement community has an essential role to play in ensuring that ML solutions are translated into clinical practice safely, effectively, and ethically.
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Affiliation(s)
- Amol A Verma
- Unity Health Toronto, Toronto, Ontario, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
- Medicine, University of Toronto Faculty of Medicine, Toronto, Ontario, Canada
| | - Patricia Trbovich
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Centre for Quality Improvement and Patient Safety, Department of Medicine, University of Toronto, Toronto, ON, Canada
- North York General Hospital, Toronto, ON, Canada
| | - Muhammad Mamdani
- Unity Health Toronto, Toronto, Ontario, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Medicine, University of Toronto Faculty of Medicine, Toronto, Ontario, Canada
| | - Kaveh G Shojania
- Medicine, University of Toronto Faculty of Medicine, Toronto, Ontario, Canada
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada
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Doshi S, Shin S, Lapointe-Shaw L, Fowler RA, Fralick M, Kwan JL, Shojania KG, Tang T, Razak F, Verma AA. Temporal Clustering of Critical Illness Events on Medical Wards. JAMA Intern Med 2023; 183:924-932. [PMID: 37428478 PMCID: PMC10334292 DOI: 10.1001/jamainternmed.2023.2629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 04/11/2023] [Indexed: 07/11/2023]
Abstract
Importance Recognizing and preventing patient deterioration is important for hospital safety. Objective To investigate whether critical illness events (in-hospital death or intensive care unit [ICU] transfer) are associated with greater risk of subsequent critical illness events for other patients on the same medical ward. Design, Setting, and Participants Retrospective cohort study in 5 hospitals in Toronto, Canada, including 118 529 hospitalizations. Patients were admitted to general internal medicine wards between April 1, 2010, and October 31, 2017. Data were analyzed between January 1, 2020, and April 10, 2023. Exposures Critical illness events (in-hospital death or ICU transfer). Main Outcomes and Measures The primary outcome was the composite of in-hospital death or ICU transfer. The association between critical illness events on the same ward across 6-hour intervals was studied using discrete-time survival analysis, adjusting for patient and situational factors. The association between critical illness events on different comparable wards in the same hospital was measured as a negative control. Results The cohort included 118 529 hospitalizations (median age, 72 years [IQR, 56-83 years]; 50.7% male). Death or ICU transfer occurred in 8785 hospitalizations (7.4%). Patients were more likely to experience the primary outcome after exposure to 1 prior event (adjusted odds ratio [AOR], 1.39; 95% CI, 1.30-1.48) and more than 1 prior event (AOR, 1.49; 95% CI, 1.33-1.68) in the prior 6-hour interval compared with no exposure. The exposure was associated with increased odds of subsequent ICU transfer (1 event: AOR, 1.67; 95% CI, 1.54-1.81; >1 event: AOR, 2.05; 95% CI, 1.79-2.36) but not death alone (1 event: AOR, 1.08; 95% CI, 0.97-1.19; >1 event: AOR, 0.88; 95% CI, 0.71-1.09). There was no significant association between critical illness events on different wards within the same hospital. Conclusions and Relevance Findings of this cohort study suggest that patients are more likely to be transferred to the ICU in the hours after another patient's critical illness event on the same ward. This phenomenon could have several explanations, including increased recognition of critical illness and preemptive ICU transfers, resource diversion to the first event, or fluctuations in ward or ICU capacity. Patient safety may be improved by better understanding the clustering of ICU transfers on medical wards.
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Affiliation(s)
- Samik Doshi
- General Internal Medicine and Li Ka Shing Knowledge Institute, St Michael’s Hospital, Unity Health Toronto, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Saeha Shin
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Lauren Lapointe-Shaw
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Department of Medicine, University Health Network, Toronto, Ontario, Canada
| | - Robert A. Fowler
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Michael Fralick
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Medicine, Sinai Health System, Toronto, Ontario, Canada
| | - Janice L. Kwan
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Medicine, Sinai Health System, Toronto, Ontario, Canada
| | - Kaveh G. Shojania
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Terence Tang
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Institute of Better Health, Trillium Health Partners, Mississauga, Ontario, Canada
| | - Fahad Razak
- General Internal Medicine and Li Ka Shing Knowledge Institute, St Michael’s Hospital, Unity Health Toronto, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Amol A. Verma
- General Internal Medicine and Li Ka Shing Knowledge Institute, St Michael’s Hospital, Unity Health Toronto, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
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Konnyu KJ, Yogasingam S, Lépine J, Sullivan K, Alabousi M, Edwards A, Hillmer M, Karunananthan S, Lavis JN, Linklater S, Manns BJ, Moher D, Mortazhejri S, Nazarali S, Paprica PA, Ramsay T, Ryan PM, Sargious P, Shojania KG, Straus SE, Tonelli M, Tricco A, Vachon B, Yu CH, Zahradnik M, Trikalinos TA, Grimshaw JM, Ivers N. Quality improvement strategies for diabetes care: Effects on outcomes for adults living with diabetes. Cochrane Database Syst Rev 2023; 5:CD014513. [PMID: 37254718 PMCID: PMC10233616 DOI: 10.1002/14651858.cd014513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
BACKGROUND There is a large body of evidence evaluating quality improvement (QI) programmes to improve care for adults living with diabetes. These programmes are often comprised of multiple QI strategies, which may be implemented in various combinations. Decision-makers planning to implement or evaluate a new QI programme, or both, need reliable evidence on the relative effectiveness of different QI strategies (individually and in combination) for different patient populations. OBJECTIVES To update existing systematic reviews of diabetes QI programmes and apply novel meta-analytical techniques to estimate the effectiveness of QI strategies (individually and in combination) on diabetes quality of care. SEARCH METHODS We searched databases (CENTRAL, MEDLINE, Embase and CINAHL) and trials registers (ClinicalTrials.gov and WHO ICTRP) to 4 June 2019. We conducted a top-up search to 23 September 2021; we screened these search results and 42 studies meeting our eligibility criteria are available in the awaiting classification section. SELECTION CRITERIA We included randomised trials that assessed a QI programme to improve care in outpatient settings for people living with diabetes. QI programmes needed to evaluate at least one system- or provider-targeted QI strategy alone or in combination with a patient-targeted strategy. - System-targeted: case management (CM); team changes (TC); electronic patient registry (EPR); facilitated relay of clinical information (FR); continuous quality improvement (CQI). - Provider-targeted: audit and feedback (AF); clinician education (CE); clinician reminders (CR); financial incentives (FI). - Patient-targeted: patient education (PE); promotion of self-management (PSM); patient reminders (PR). Patient-targeted QI strategies needed to occur with a minimum of one provider or system-targeted strategy. DATA COLLECTION AND ANALYSIS We dual-screened search results and abstracted data on study design, study population and QI strategies. We assessed the impact of the programmes on 13 measures of diabetes care, including: glycaemic control (e.g. mean glycated haemoglobin (HbA1c)); cardiovascular risk factor management (e.g. mean systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), proportion of people living with diabetes that quit smoking or receiving cardiovascular medications); and screening/prevention of microvascular complications (e.g. proportion of patients receiving retinopathy or foot screening); and harms (e.g. proportion of patients experiencing adverse hypoglycaemia or hyperglycaemia). We modelled the association of each QI strategy with outcomes using a series of hierarchical multivariable meta-regression models in a Bayesian framework. The previous version of this review identified that different strategies were more or less effective depending on baseline levels of outcomes. To explore this further, we extended the main additive model for continuous outcomes (HbA1c, SBP and LDL-C) to include an interaction term between each strategy and average baseline risk for each study (baseline thresholds were based on a data-driven approach; we used the median of all baseline values reported in the trials). Based on model diagnostics, the baseline interaction models for HbA1c, SBP and LDL-C performed better than the main model and are therefore presented as the primary analyses for these outcomes. Based on the model results, we qualitatively ordered each QI strategy within three tiers (Top, Middle, Bottom) based on its magnitude of effect relative to the other QI strategies, where 'Top' indicates that the QI strategy was likely one of the most effective strategies for that specific outcome. Secondary analyses explored the sensitivity of results to choices in model specification and priors. Additional information about the methods and results of the review are available as Appendices in an online repository. This review will be maintained as a living systematic review; we will update our syntheses as more data become available. MAIN RESULTS We identified 553 trials (428 patient-randomised and 125 cluster-randomised trials), including a total of 412,161 participants. Of the included studies, 66% involved people living with type 2 diabetes only. Participants were 50% female and the median age of participants was 58.4 years. The mean duration of follow-up was 12.5 months. HbA1c was the commonest reported outcome; screening outcomes and outcomes related to cardiovascular medications, smoking and harms were reported infrequently. The most frequently evaluated QI strategies across all study arms were PE, PSM and CM, while the least frequently evaluated QI strategies included AF, FI and CQI. Our confidence in the evidence is limited due to a lack of information on how studies were conducted. Four QI strategies (CM, TC, PE, PSM) were consistently identified as 'Top' across the majority of outcomes. All QI strategies were ranked as 'Top' for at least one key outcome. The majority of effects of individual QI strategies were modest, but when used in combination could result in meaningful population-level improvements across the majority of outcomes. The median number of QI strategies in multicomponent QI programmes was three. Combinations of the three most effective QI strategies were estimated to lead to the below effects: - PR + PSM + CE: decrease in HbA1c by 0.41% (credibility interval (CrI) -0.61 to -0.22) when baseline HbA1c < 8.3%; - CM + PE + EPR: decrease in HbA1c by 0.62% (CrI -0.84 to -0.39) when baseline HbA1c > 8.3%; - PE + TC + PSM: reduction in SBP by 2.14 mmHg (CrI -3.80 to -0.52) when baseline SBP < 136 mmHg; - CM + TC + PSM: reduction in SBP by 4.39 mmHg (CrI -6.20 to -2.56) when baseline SBP > 136 mmHg; - TC + PE + CM: LDL-C lowering of 5.73 mg/dL (CrI -7.93 to -3.61) when baseline LDL < 107 mg/dL; - TC + CM + CR: LDL-C lowering by 5.52 mg/dL (CrI -9.24 to -1.89) when baseline LDL > 107 mg/dL. Assuming a baseline screening rate of 50%, the three most effective QI strategies were estimated to lead to an absolute improvement of 33% in retinopathy screening (PE + PR + TC) and 38% absolute increase in foot screening (PE + TC + Other). AUTHORS' CONCLUSIONS There is a significant body of evidence about QI programmes to improve the management of diabetes. Multicomponent QI programmes for diabetes care (comprised of effective QI strategies) may achieve meaningful population-level improvements across the majority of outcomes. For health system decision-makers, the evidence summarised in this review can be used to identify strategies to include in QI programmes. For researchers, this synthesis identifies higher-priority QI strategies to examine in further research regarding how to optimise their evaluation and effects. We will maintain this as a living systematic review.
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Affiliation(s)
- Kristin J Konnyu
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Sharlini Yogasingam
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Johanie Lépine
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Katrina Sullivan
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | | | - Alun Edwards
- Department of Medicine, University of Calgary, Calgary, Canada
| | - Michael Hillmer
- Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada
| | - Sathya Karunananthan
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
- Interdisciplinary School of Health Sciences, University of Ottawa, Ottawa, Canada
| | - John N Lavis
- McMaster Health Forum, Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada
| | - Stefanie Linklater
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Braden J Manns
- Department of Medicine and Community Health Sciences, University of Calgary, Calgary, Canada
| | - David Moher
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Sameh Mortazhejri
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada
| | - Samir Nazarali
- Department of Ophthalmology and Visual Sciences, University of Alberta, Edmonton, Canada
| | - P Alison Paprica
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada
| | - Timothy Ramsay
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | | | - Peter Sargious
- Department of Medicine, University of Calgary, Calgary, Canada
| | - Kaveh G Shojania
- University of Toronto Centre for Patient Safety, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Sharon E Straus
- Knowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital and University of Toronto, Toronto, Canada
| | - Marcello Tonelli
- Department of Medicine and Community Health Sciences, University of Calgary, Calgary, Canada
| | - Andrea Tricco
- Knowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital and University of Toronto, Toronto, Canada
- Epidemiology Division and Institute of Health Policy, Management, and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
- Queen's Collaboration for Health Care Quality: A JBI Centre of Excellence, Queen's University, Kingston, Canada
| | - Brigitte Vachon
- School of Rehabilitation, Occupational Therapy Program, University of Montreal, Montreal, Canada
| | - Catherine Hy Yu
- Department of Medicine, St. Michael's Hospital, Toronto, Canada
| | - Michael Zahradnik
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Thomas A Trikalinos
- Departments of Health Services, Policy, and Practice and Biostatistics, Center for Evidence Synthesis in Health, Brown University School of Public Health, Providence, Rhode Island, USA
| | - Jeremy M Grimshaw
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
- Department of Medicine, University of Ottawa, Ottawa, Canada
| | - Noah Ivers
- Department of Family and Community Medicine, Women's College Hospital, Toronto, Canada
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Cressman AM, Purohit U, Shadowitz E, Etchells E, Weinerman A, Gerson D, Shojania KG, Stroud L, Wong BM, Shadowitz S. Potentially avoidable admissions to general internal medicine at an academic teaching hospital: an observational study. CMAJ Open 2023; 11:E201-E207. [PMID: 36854457 PMCID: PMC9981162 DOI: 10.9778/cmajo.20220020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/02/2023] Open
Abstract
BACKGROUND Identifying potentially avoidable admissions to Canadian hospitals is an important health system goal. With general internal medicine (GIM) accounting for 40% of hospital admissions, we sought to develop a method to identify potentially avoidable admissions and characterize patient, provider and health system factors. METHODS We conducted an observational study of GIM admissions at our institution from August 2019 to February 2020. We defined potentially avoidable admissions as admissions that could be managed in an appropriate and safe manner in the emergency department or ambulatory setting and asked staff physicians to screen admissions daily and flag candidates as potentially avoidable admissions. For each candidate, we prepared a case review and debriefed with members of the admitting team. We then reviewed each candidate with our research team, assigned an avoidability score (1 [low] to 4 [high]) and identified contributing factors for those with scores of 3 or more. RESULTS We screened 601 total admissions and staff physicians flagged 117 (19.5%) of these as candidate potential avoidable admissions. Consensus review identified 67 candidates as potentially avoidable admissions (11.1%, 95% confidence interval 8.8%-13.9%); these patients were younger (mean age 65 yr v. 72 yr), had fewer comorbidities (Canadian Institute for Health Information Case Mix Group+ 0.42 v. 1.14), had lower resource-intensity weighting scores (0.72 v. 1.50) and shorter hospital lengths of stay (29 h v. 105 h) (p < 0.01). Common factors included diagnostic and therapeutic uncertainty, perceived need for short-term monitoring, government directive of a 4-hour limit for admission decision-making and subspecialist request to admit. INTERPRETATION Our prospective method of screening, flagging and case review showed that 1 in 9 GIM admissions were potentially avoidable. Other institutions could consider adapting this methodology to ascertain their rate of potentially avoidable admissions and to understand contributing factors to inform improvement endeavours.
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Affiliation(s)
- Alex M Cressman
- Department of Medicine (Cressman, Purohit, Etchells, Weinerman, Gerson, Shojania, Stroud, Wong, S. Shadowitz), University of Toronto; Division of General Internal Medicine (Cressman, E. Shadowitz, Etchells, Weinerman, Shojania, Stroud, Wong, S. Shadowitz), Sunnybrook Health Sciences Centre; The Centre for Quality Improvement and Patient Safety (Etchells, Weinerman, Shojania, Wong); Wilson Centre for Education Research (Stroud); Toronto, Ont.
| | - Ushma Purohit
- Department of Medicine (Cressman, Purohit, Etchells, Weinerman, Gerson, Shojania, Stroud, Wong, S. Shadowitz), University of Toronto; Division of General Internal Medicine (Cressman, E. Shadowitz, Etchells, Weinerman, Shojania, Stroud, Wong, S. Shadowitz), Sunnybrook Health Sciences Centre; The Centre for Quality Improvement and Patient Safety (Etchells, Weinerman, Shojania, Wong); Wilson Centre for Education Research (Stroud); Toronto, Ont
| | - Ellen Shadowitz
- Department of Medicine (Cressman, Purohit, Etchells, Weinerman, Gerson, Shojania, Stroud, Wong, S. Shadowitz), University of Toronto; Division of General Internal Medicine (Cressman, E. Shadowitz, Etchells, Weinerman, Shojania, Stroud, Wong, S. Shadowitz), Sunnybrook Health Sciences Centre; The Centre for Quality Improvement and Patient Safety (Etchells, Weinerman, Shojania, Wong); Wilson Centre for Education Research (Stroud); Toronto, Ont
| | - Edward Etchells
- Department of Medicine (Cressman, Purohit, Etchells, Weinerman, Gerson, Shojania, Stroud, Wong, S. Shadowitz), University of Toronto; Division of General Internal Medicine (Cressman, E. Shadowitz, Etchells, Weinerman, Shojania, Stroud, Wong, S. Shadowitz), Sunnybrook Health Sciences Centre; The Centre for Quality Improvement and Patient Safety (Etchells, Weinerman, Shojania, Wong); Wilson Centre for Education Research (Stroud); Toronto, Ont
| | - Adina Weinerman
- Department of Medicine (Cressman, Purohit, Etchells, Weinerman, Gerson, Shojania, Stroud, Wong, S. Shadowitz), University of Toronto; Division of General Internal Medicine (Cressman, E. Shadowitz, Etchells, Weinerman, Shojania, Stroud, Wong, S. Shadowitz), Sunnybrook Health Sciences Centre; The Centre for Quality Improvement and Patient Safety (Etchells, Weinerman, Shojania, Wong); Wilson Centre for Education Research (Stroud); Toronto, Ont
| | - Darren Gerson
- Department of Medicine (Cressman, Purohit, Etchells, Weinerman, Gerson, Shojania, Stroud, Wong, S. Shadowitz), University of Toronto; Division of General Internal Medicine (Cressman, E. Shadowitz, Etchells, Weinerman, Shojania, Stroud, Wong, S. Shadowitz), Sunnybrook Health Sciences Centre; The Centre for Quality Improvement and Patient Safety (Etchells, Weinerman, Shojania, Wong); Wilson Centre for Education Research (Stroud); Toronto, Ont
| | - Kaveh G Shojania
- Department of Medicine (Cressman, Purohit, Etchells, Weinerman, Gerson, Shojania, Stroud, Wong, S. Shadowitz), University of Toronto; Division of General Internal Medicine (Cressman, E. Shadowitz, Etchells, Weinerman, Shojania, Stroud, Wong, S. Shadowitz), Sunnybrook Health Sciences Centre; The Centre for Quality Improvement and Patient Safety (Etchells, Weinerman, Shojania, Wong); Wilson Centre for Education Research (Stroud); Toronto, Ont
| | - Lynfa Stroud
- Department of Medicine (Cressman, Purohit, Etchells, Weinerman, Gerson, Shojania, Stroud, Wong, S. Shadowitz), University of Toronto; Division of General Internal Medicine (Cressman, E. Shadowitz, Etchells, Weinerman, Shojania, Stroud, Wong, S. Shadowitz), Sunnybrook Health Sciences Centre; The Centre for Quality Improvement and Patient Safety (Etchells, Weinerman, Shojania, Wong); Wilson Centre for Education Research (Stroud); Toronto, Ont
| | - Brian M Wong
- Department of Medicine (Cressman, Purohit, Etchells, Weinerman, Gerson, Shojania, Stroud, Wong, S. Shadowitz), University of Toronto; Division of General Internal Medicine (Cressman, E. Shadowitz, Etchells, Weinerman, Shojania, Stroud, Wong, S. Shadowitz), Sunnybrook Health Sciences Centre; The Centre for Quality Improvement and Patient Safety (Etchells, Weinerman, Shojania, Wong); Wilson Centre for Education Research (Stroud); Toronto, Ont
| | - Steve Shadowitz
- Department of Medicine (Cressman, Purohit, Etchells, Weinerman, Gerson, Shojania, Stroud, Wong, S. Shadowitz), University of Toronto; Division of General Internal Medicine (Cressman, E. Shadowitz, Etchells, Weinerman, Shojania, Stroud, Wong, S. Shadowitz), Sunnybrook Health Sciences Centre; The Centre for Quality Improvement and Patient Safety (Etchells, Weinerman, Shojania, Wong); Wilson Centre for Education Research (Stroud); Toronto, Ont
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Rotteau L, Goldman J, Shojania KG, Vogus TJ, Christianson M, Baker GR, Rowland P, Coffey M. Striving for high reliability in healthcare: a qualitative study of the implementation of a hospital safety programme. BMJ Qual Saf 2022; 31:867-877. [PMID: 35649697 DOI: 10.1136/bmjqs-2021-013938] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Accepted: 05/10/2022] [Indexed: 11/03/2022]
Abstract
BACKGROUND Healthcare leaders look to high-reliability organisations (HROs) for strategies to improve safety, despite questions about how to translate these strategies into practice. Weick and Sutcliffe describe five principles exhibited by HROs. Interventions aiming to foster these principles are common in healthcare; however, there have been few examinations of the perceptions of those who have planned or experienced these efforts. OBJECTIVE This single-site qualitative study explores how healthcare professionals understand and enact the HRO principles in response to an HRO-inspired hospital-wide safety programme. METHODS We interviewed 71 participants representing hospital executives, programme leadership, and staff and physicians from three clinical services. We observed and collected data from unit and hospital-wide quality and safety meetings and activities. We used thematic analysis to code and analyse the data. RESULTS Participants reported enactment of the HRO principles 'preoccupation with failure', 'reluctance to simplify interpretations' and 'sensitivity to operations', and described the programme as adding legitimacy, training, and support. However, the programme was more often targeted at, and taken up by, nurses compared with other groups. Participants were less able to identify interventions that supported the HRO principles 'commitment to resilience' and 'deference to expertise' and reported limited examples of changes in practices related to these principles. Moreover, we identified inconsistent, and even conflicting, understanding of concepts related to the HRO principles, often related to social and professional norms and practices. Finally, an individualised rather than systemic approach hindered collective actions underlying high reliability. CONCLUSION Our findings demonstrate that the safety programme supported some HRO principles more than others, and was targeted at, and perceived differently across professional groups leading to inconsistent understanding and enactments of the principles across the organisation. Combining HRO-inspired interventions with more targeted attention to each of the HRO principles could produce greater, more consistent high-reliability practices.
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Affiliation(s)
- Leahora Rotteau
- Centre for Quality Improvement and Patient Safety, University of Toronto, Toronto, Ontario, Canada
| | - Joanne Goldman
- Centre for Quality Improvement and Patient Safety, University of Toronto, Toronto, Ontario, Canada.,Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,Wilson Centre for Research in Education, University of Toronto, Toronto, Ontario, Canada
| | - Kaveh G Shojania
- Centre for Quality Improvement and Patient Safety, University of Toronto, Toronto, Ontario, Canada.,Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Timothy J Vogus
- Owen Graduate School of Management, Vanderbilt University, Nashville, Tennessee, USA
| | - Marlys Christianson
- Rotman School of Management, University of Toronto, Toronto, Ontario, Canada
| | - G Ross Baker
- Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Paula Rowland
- Wilson Centre for Research in Education, University of Toronto, Toronto, Ontario, Canada.,Department of Occupational Science and Occupational Therapy, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Maitreya Coffey
- The Hospital for Sick Children, Toronto, Ontario, Canada.,Children's Hospitals Solutions for Patient Safety, Cincinnati, Ohio, USA.,Department of Paediatrics, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
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7
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Affiliation(s)
- Kaveh G Shojania
- Department of Medicine, Sunnybrook Health Sciences Centre and University of Toronto, Toronto, Ont.
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8
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Wong BM, Rotteau L, Feldman S, Lamb M, Liang K, Moser A, Mukerji G, Pariser P, Pus L, Razak F, Shojania KG, Verma A. A Novel Collaborative Care Program to Augment Nursing Home Care During and After the COVID-19 Pandemic. J Am Med Dir Assoc 2021; 23:304-307.e3. [PMID: 34922907 PMCID: PMC8610963 DOI: 10.1016/j.jamda.2021.11.018] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 11/17/2021] [Accepted: 11/18/2021] [Indexed: 10/29/2022]
Abstract
The 2019 novel coronavirus (COVID-19) pandemic created an immediate need to enhance current efforts to reduce transfers of nursing home (NH) residents to acute care. Long-Term Care Plus (LTC+), a collaborative care program developed and implemented during the COVID-19 pandemic, aimed to enhance care in the NH setting while also decreasing unnecessary acute care transfers. Using a hub-and-spoke model, LTC+ was implemented in 6 hospitals serving as central hubs to 54 geographically associated NHs with 9574 beds in Toronto, Canada. LTC+ provided NHs with the following: (1) virtual general internal medicine (GIM) consultations; (2) nursing navigator support; (3) rapid access to laboratory and diagnostic imaging services; and (4) educational resources. From April 2020 to June 2021, LTC+ provided 381 GIM consultations that addressed abnormal bloodwork (15%), cardiac problems (13%), and unexplained fever (11%) as the most common reasons for consultation. Sixty-five nurse navigator calls addressed requests for non-GIM specialist consultations (34%), wound care assessments (14%), and system navigation (12%). One hundred seventy-seven (46%, 95% CI 41%-52%) consults addressed care concerns sufficiently to avoid the need for acute care transfer. All 36 primary care physicians who consulted the LTC+ program reported strong satisfaction with the advice provided. Early results demonstrate the feasibility and acceptability of an integrated care model that enhances care delivery for NH residents where they reside and has the potential to positively impact the long-term care sector by ensuring equitable and timely access to care for people living in NHs. It represents an important step toward health system integration that values the expertise within the long-term care sector.
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Affiliation(s)
- Brian M Wong
- Centre for Quality Improvement and Patient Safety, University of Toronto, Toronto, Ontario, Canada; Division of General Internal Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada; Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Leahora Rotteau
- Centre for Quality Improvement and Patient Safety, University of Toronto, Toronto, Ontario, Canada.
| | - Sid Feldman
- Baycrest Health Sciences Centre, Toronto, Ontario, Canada; Department of Family and Community Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Michael Lamb
- Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Division of General Internal Medicine, North York General Hospital, North York, Ontario, Canada
| | - Kyle Liang
- Womens College Hospital Institute for Health System Solutions and Virtual Care, Toronto, Ontario, Canada
| | - Andrea Moser
- Department of Family and Community Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Sienna Senior Living Canada, Markham, Ontario, Canada
| | - Geetha Mukerji
- Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Womens College Hospital Institute for Health System Solutions and Virtual Care, Toronto, Ontario, Canada; Women's College Hospital, Toronto, Ontario, Canada; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Pauline Pariser
- Department of Family and Community Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Laura Pus
- Womens College Hospital Institute for Health System Solutions and Virtual Care, Toronto, Ontario, Canada
| | - Fahad Razak
- Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada; Division of General Internal Medicine and Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health, Toronto, Ontario, Canada
| | - Kaveh G Shojania
- Centre for Quality Improvement and Patient Safety, University of Toronto, Toronto, Ontario, Canada; Division of General Internal Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada; Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Amol Verma
- Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada; Division of General Internal Medicine and Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health, Toronto, Ontario, Canada
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9
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Verma AA, Murray J, Greiner R, Cohen JP, Shojania KG, Ghassemi M, Straus SE, Pou-Prom C, Mamdani M. Mise en œuvre de l’apprentissage machine en santé. CMAJ 2021; 193:E1708-E1715. [PMID: 34750183 PMCID: PMC8584368 DOI: 10.1503/cmaj.202434-f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Affiliation(s)
- Amol A Verma
- Réseau hospitalier Unity Health de Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Institut du savoir Li Ka Shing de l'Hôpital St. Michael (Verma, Straus, Pou-Prom, Mamdani); Département de médecine (Verma, Shojania, Straus, Mamdani) et Institut des politiques, de la gestion et de l'évaluation de la santé (Verma, Mamdani) et Département de statistique (Murray), Université de Toronto, Toronto, Ont.; Université de l'Alberta (Greiner); Institut d'intelligence machine de l'Alberta (Greiner), Edmonton, Alb.; Institut des algorithmes d'apprentissage de Montréal (Cohen), Montréal, Qc.; Centre pour l'amélioration de la qualité et la sécurité des patients (Shojania), Université de Toronto; Centre des sciences de la santé Sunnybrook (Shojania); Institut Vecteur (Ghassemi, Mamdani) et Département des sciences informatiques (Ghassemi); Faculté de pharmacie Leslie Dan (Mamdani), Université de Toronto, Toronto, Ont.; Département de radiologie, Université Stanford (Cohen), Stanford, Calif.
| | - Joshua Murray
- Réseau hospitalier Unity Health de Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Institut du savoir Li Ka Shing de l'Hôpital St. Michael (Verma, Straus, Pou-Prom, Mamdani); Département de médecine (Verma, Shojania, Straus, Mamdani) et Institut des politiques, de la gestion et de l'évaluation de la santé (Verma, Mamdani) et Département de statistique (Murray), Université de Toronto, Toronto, Ont.; Université de l'Alberta (Greiner); Institut d'intelligence machine de l'Alberta (Greiner), Edmonton, Alb.; Institut des algorithmes d'apprentissage de Montréal (Cohen), Montréal, Qc.; Centre pour l'amélioration de la qualité et la sécurité des patients (Shojania), Université de Toronto; Centre des sciences de la santé Sunnybrook (Shojania); Institut Vecteur (Ghassemi, Mamdani) et Département des sciences informatiques (Ghassemi); Faculté de pharmacie Leslie Dan (Mamdani), Université de Toronto, Toronto, Ont.; Département de radiologie, Université Stanford (Cohen), Stanford, Calif
| | - Russell Greiner
- Réseau hospitalier Unity Health de Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Institut du savoir Li Ka Shing de l'Hôpital St. Michael (Verma, Straus, Pou-Prom, Mamdani); Département de médecine (Verma, Shojania, Straus, Mamdani) et Institut des politiques, de la gestion et de l'évaluation de la santé (Verma, Mamdani) et Département de statistique (Murray), Université de Toronto, Toronto, Ont.; Université de l'Alberta (Greiner); Institut d'intelligence machine de l'Alberta (Greiner), Edmonton, Alb.; Institut des algorithmes d'apprentissage de Montréal (Cohen), Montréal, Qc.; Centre pour l'amélioration de la qualité et la sécurité des patients (Shojania), Université de Toronto; Centre des sciences de la santé Sunnybrook (Shojania); Institut Vecteur (Ghassemi, Mamdani) et Département des sciences informatiques (Ghassemi); Faculté de pharmacie Leslie Dan (Mamdani), Université de Toronto, Toronto, Ont.; Département de radiologie, Université Stanford (Cohen), Stanford, Calif
| | - Joseph Paul Cohen
- Réseau hospitalier Unity Health de Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Institut du savoir Li Ka Shing de l'Hôpital St. Michael (Verma, Straus, Pou-Prom, Mamdani); Département de médecine (Verma, Shojania, Straus, Mamdani) et Institut des politiques, de la gestion et de l'évaluation de la santé (Verma, Mamdani) et Département de statistique (Murray), Université de Toronto, Toronto, Ont.; Université de l'Alberta (Greiner); Institut d'intelligence machine de l'Alberta (Greiner), Edmonton, Alb.; Institut des algorithmes d'apprentissage de Montréal (Cohen), Montréal, Qc.; Centre pour l'amélioration de la qualité et la sécurité des patients (Shojania), Université de Toronto; Centre des sciences de la santé Sunnybrook (Shojania); Institut Vecteur (Ghassemi, Mamdani) et Département des sciences informatiques (Ghassemi); Faculté de pharmacie Leslie Dan (Mamdani), Université de Toronto, Toronto, Ont.; Département de radiologie, Université Stanford (Cohen), Stanford, Calif
| | - Kaveh G Shojania
- Réseau hospitalier Unity Health de Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Institut du savoir Li Ka Shing de l'Hôpital St. Michael (Verma, Straus, Pou-Prom, Mamdani); Département de médecine (Verma, Shojania, Straus, Mamdani) et Institut des politiques, de la gestion et de l'évaluation de la santé (Verma, Mamdani) et Département de statistique (Murray), Université de Toronto, Toronto, Ont.; Université de l'Alberta (Greiner); Institut d'intelligence machine de l'Alberta (Greiner), Edmonton, Alb.; Institut des algorithmes d'apprentissage de Montréal (Cohen), Montréal, Qc.; Centre pour l'amélioration de la qualité et la sécurité des patients (Shojania), Université de Toronto; Centre des sciences de la santé Sunnybrook (Shojania); Institut Vecteur (Ghassemi, Mamdani) et Département des sciences informatiques (Ghassemi); Faculté de pharmacie Leslie Dan (Mamdani), Université de Toronto, Toronto, Ont.; Département de radiologie, Université Stanford (Cohen), Stanford, Calif
| | - Marzyeh Ghassemi
- Réseau hospitalier Unity Health de Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Institut du savoir Li Ka Shing de l'Hôpital St. Michael (Verma, Straus, Pou-Prom, Mamdani); Département de médecine (Verma, Shojania, Straus, Mamdani) et Institut des politiques, de la gestion et de l'évaluation de la santé (Verma, Mamdani) et Département de statistique (Murray), Université de Toronto, Toronto, Ont.; Université de l'Alberta (Greiner); Institut d'intelligence machine de l'Alberta (Greiner), Edmonton, Alb.; Institut des algorithmes d'apprentissage de Montréal (Cohen), Montréal, Qc.; Centre pour l'amélioration de la qualité et la sécurité des patients (Shojania), Université de Toronto; Centre des sciences de la santé Sunnybrook (Shojania); Institut Vecteur (Ghassemi, Mamdani) et Département des sciences informatiques (Ghassemi); Faculté de pharmacie Leslie Dan (Mamdani), Université de Toronto, Toronto, Ont.; Département de radiologie, Université Stanford (Cohen), Stanford, Calif
| | - Sharon E Straus
- Réseau hospitalier Unity Health de Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Institut du savoir Li Ka Shing de l'Hôpital St. Michael (Verma, Straus, Pou-Prom, Mamdani); Département de médecine (Verma, Shojania, Straus, Mamdani) et Institut des politiques, de la gestion et de l'évaluation de la santé (Verma, Mamdani) et Département de statistique (Murray), Université de Toronto, Toronto, Ont.; Université de l'Alberta (Greiner); Institut d'intelligence machine de l'Alberta (Greiner), Edmonton, Alb.; Institut des algorithmes d'apprentissage de Montréal (Cohen), Montréal, Qc.; Centre pour l'amélioration de la qualité et la sécurité des patients (Shojania), Université de Toronto; Centre des sciences de la santé Sunnybrook (Shojania); Institut Vecteur (Ghassemi, Mamdani) et Département des sciences informatiques (Ghassemi); Faculté de pharmacie Leslie Dan (Mamdani), Université de Toronto, Toronto, Ont.; Département de radiologie, Université Stanford (Cohen), Stanford, Calif
| | - Chloé Pou-Prom
- Réseau hospitalier Unity Health de Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Institut du savoir Li Ka Shing de l'Hôpital St. Michael (Verma, Straus, Pou-Prom, Mamdani); Département de médecine (Verma, Shojania, Straus, Mamdani) et Institut des politiques, de la gestion et de l'évaluation de la santé (Verma, Mamdani) et Département de statistique (Murray), Université de Toronto, Toronto, Ont.; Université de l'Alberta (Greiner); Institut d'intelligence machine de l'Alberta (Greiner), Edmonton, Alb.; Institut des algorithmes d'apprentissage de Montréal (Cohen), Montréal, Qc.; Centre pour l'amélioration de la qualité et la sécurité des patients (Shojania), Université de Toronto; Centre des sciences de la santé Sunnybrook (Shojania); Institut Vecteur (Ghassemi, Mamdani) et Département des sciences informatiques (Ghassemi); Faculté de pharmacie Leslie Dan (Mamdani), Université de Toronto, Toronto, Ont.; Département de radiologie, Université Stanford (Cohen), Stanford, Calif
| | - Muhammad Mamdani
- Réseau hospitalier Unity Health de Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Institut du savoir Li Ka Shing de l'Hôpital St. Michael (Verma, Straus, Pou-Prom, Mamdani); Département de médecine (Verma, Shojania, Straus, Mamdani) et Institut des politiques, de la gestion et de l'évaluation de la santé (Verma, Mamdani) et Département de statistique (Murray), Université de Toronto, Toronto, Ont.; Université de l'Alberta (Greiner); Institut d'intelligence machine de l'Alberta (Greiner), Edmonton, Alb.; Institut des algorithmes d'apprentissage de Montréal (Cohen), Montréal, Qc.; Centre pour l'amélioration de la qualité et la sécurité des patients (Shojania), Université de Toronto; Centre des sciences de la santé Sunnybrook (Shojania); Institut Vecteur (Ghassemi, Mamdani) et Département des sciences informatiques (Ghassemi); Faculté de pharmacie Leslie Dan (Mamdani), Université de Toronto, Toronto, Ont.; Département de radiologie, Université Stanford (Cohen), Stanford, Calif.
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10
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Bhatia RS, Chu C, Kaoutskaia A, Ko DT, Shojania KG, Dorian P, Yu B, Shurrab M, Fang J, Ross H, Austin PC, Bouck Z, Goodman SG, Crystal E. Association of Cardiology Billing Amounts With Health Care Utilization and Clinical Outcomes in Patients With Atrial Fibrillation. J Am Heart Assoc 2021; 10:e020708. [PMID: 34668397 PMCID: PMC8751834 DOI: 10.1161/jaha.120.020708] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background The relationship between health care utilization and outcomes in patients with atrial fibrillation is unknown. The objective of this study was to investigate whether cardiologists' billing amounts in a fee-for-service environment are associated with better patient-level clinical outcomes. Methods and Results A retrospective cohort study was conducted using administrative claims data of cardiologists in Ontario, Canada between April 1, 2011 and March 31, 2016. The cardiologists were stratified into quintiles based on their median billing patterns per patient over the observation period. The primary outcomes were patient-level receipt of repeat visits, cardiac diagnostic tests, and medications ≤1 year of index date. The secondary clinical outcomes were death, emergency department visits, and all-cause hospitalization 1-year post-index visit. The patient cohort comprised 182 572 patients with atrial fibrillation (median age 74 years, 58% male) from 467 cardiologists. Patients with atrial fibrillation seen by higher-billing cardiologists were 26% more likely to have an echocardiogram (adjusted odds ratio [aOR], 1.26 [95% CI, 1.10-1.43] for quintile 5 versus 2), 28% a stress test (aOR, 1.28 [1.12-1.46] for quintile 5 versus 2), 25% continuous electrocardiographic monitoring (aOR, 1.25 [1.08-1.46] for quintile 4 versus 2), and 79% more likely to get a stress echocardiogram (aOR, 1.79 [1.32-2.42] for quintile 5 versus 2). They also had a higher rate of all-cause hospitalization (aOR, 1.13 [1.07-1.20]). Mortality rates were similar across cardiologists billing quintiles (eg, aOR, 0.98 [0.87-1.11] for quintile 4 versus 2). Conclusions Higher-billing cardiologists ordered more diagnostic tests per patient with atrial fibrillation but these are not associated with improvements in outcomes.
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Affiliation(s)
- R Sacha Bhatia
- Institute for Health Systems Solutions and Virtual CareWomen's College Hospital Toronto Ontario Canada.,Peter Munk Cardiac Centre University Health Network Toronto Ontario Canada
| | - Cherry Chu
- Institute for Health Systems Solutions and Virtual CareWomen's College Hospital Toronto Ontario Canada
| | - Anna Kaoutskaia
- St. Matthew's University School of Medicine Cayman Islands.,Sunnybrook Health Sciences Centre University of Toronto Toronto Ontario Canada
| | - Dennis T Ko
- ICES Toronto Ontario Canada.,Sunnybrook Health Sciences Centre University of Toronto Toronto Ontario Canada
| | - Kaveh G Shojania
- Sunnybrook Health Sciences Centre University of Toronto Toronto Ontario Canada.,Department of Medicine Faculty of Medicine University of Toronto Toronto Ontario Canada
| | - Paul Dorian
- Department of Medicine Faculty of Medicine University of Toronto Toronto Ontario Canada.,Division of Cardiology St. Michael's Hospital Toronto Ontario Canada
| | | | - Mohammed Shurrab
- Cardiology Department Health Sciences NorthHealth Sciences North Research InstituteNorthern Ontario School of Medicine Sudbury Ontario Canada
| | | | - Heather Ross
- Peter Munk Cardiac Centre University Health Network Toronto Ontario Canada.,Department of Medicine Faculty of Medicine University of Toronto Toronto Ontario Canada
| | - Peter C Austin
- ICES Toronto Ontario Canada.,Institute of Health Policy, Management and Evaluation University of Toronto Canada
| | - Zachary Bouck
- Institute for Health Systems Solutions and Virtual CareWomen's College Hospital Toronto Ontario Canada.,Epidemiology Division Dalla Lana School of Public Health University of Toronto Toronto Ontario Canada
| | - Shaun G Goodman
- Department of Medicine Faculty of Medicine University of Toronto Toronto Ontario Canada.,Division of Cardiology St. Michael's Hospital Toronto Ontario Canada
| | - Eugene Crystal
- Institute for Health Systems Solutions and Virtual CareWomen's College Hospital Toronto Ontario Canada.,Sunnybrook Health Sciences Centre University of Toronto Toronto Ontario Canada.,Department of Medicine Faculty of Medicine University of Toronto Toronto Ontario Canada
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11
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Schiff G, Shojania KG. Looking back on the history of patient safety: an opportunity to reflect and ponder future challenges. BMJ Qual Saf 2021; 31:148-152. [PMID: 34625484 PMCID: PMC8785050 DOI: 10.1136/bmjqs-2021-014163] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 09/27/2021] [Indexed: 12/20/2022]
Affiliation(s)
- Gordon Schiff
- General Medicine, Brigham and Women's Hospital Department of Medicine, Boston, Massachusetts, USA
| | - Kaveh G Shojania
- Department of Medicine and the Centre for Quality Improvement and Patient Safety, University of Toronto, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
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12
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Goldman J, Rotteau L, Shojania KG, Baker GR, Rowland P, Christianson MK, Vogus TJ, Cameron C, Coffey M. Implementation of a central-line bundle: a qualitative study of three clinical units. Implement Sci Commun 2021; 2:105. [PMID: 34530918 PMCID: PMC8447632 DOI: 10.1186/s43058-021-00204-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Accepted: 08/25/2021] [Indexed: 11/24/2022] Open
Abstract
Background Evidence for the central line-associated bloodstream infection (CLABSI) bundle effectiveness remains mixed, possibly reflecting implementation challenges and persistent ambiguities in how CLABSIs are counted and bundle adherence measured. In the context of a tertiary pediatric hospital that had reduced CLABSI by 30% as part of an international safety program, we aimed to examine unit-based socio-cultural factors influencing bundle practices and measurement, and how they come to be recognized and attended to by safety leaders over time in an organization-wide bundle implementation effort. Methods We used an interpretivist qualitative research approach, based on 74 interviews, approximately 50 h of observations, and documents. Data collection focused on hospital executives and safety leadership, and three clinical units: a medical specialty unit, an intensive care unit, and a surgical unit. We used thematic analysis and constant comparison methods for data analysis. Results Participants had variable beliefs about the central-line bundle as a quality improvement priority based on their professional roles and experiences and unit setting, which influenced their responses. Nursing leaders were particularly concerned about CLABSI being one of an overwhelming number of QI targets for which they were responsible. Bundle implementation strategies were initially reliant on unit-based nurse education. Over time there was recognition of the need for centralized education and reinforcement tactics. However, these interventions achieved limited impact given the influence of competing unit workflow demands and professional roles, interactions, and routines, which were variably targeted in the safety program. The auditing process, initially a responsibility of units, was performed in different ways based on individuals’ approaches to the process. Given concerns about auditing reliability, a centralized approach was implemented, which continued to have its own variability. Conclusions Our findings report on a contextualized, dynamic implementation approach that required movement between centralized and unit-based approaches and from a focus on standardization to some recognition of a role for customization. However, some factors related to bundle compliance and measurement remain unaddressed, including harder to change socio-cultural factors likely important to sustainability of the CLABSI reductions and fostering further improvements across a broader safety agenda.
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Affiliation(s)
- Joanne Goldman
- Centre for Quality Improvement and Patient Safety, Temerty Faculty of Medicine, University of Toronto, 630-525 University Ave., Toronto, M5G2L3, Canada. .,Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada. .,Wilson Centre for Research in Education, University of Toronto, 200 Elizabeth St., 1ES-565, Toronto, M5G 2C4, Canada.
| | - Leahora Rotteau
- Centre for Quality Improvement and Patient Safety, Temerty Faculty of Medicine, University of Toronto, 630-525 University Ave., Toronto, M5G2L3, Canada
| | - Kaveh G Shojania
- Centre for Quality Improvement and Patient Safety, Temerty Faculty of Medicine, University of Toronto, 630-525 University Ave., Toronto, M5G2L3, Canada.,Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada.,Division of General Internal Medicine, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - G Ross Baker
- Institute of Health Policy, Management and Evaluation, University of Toronto, Health Sciences Building, 155 College St., Suite 425, Toronto, M5T 3M6, Canada
| | - Paula Rowland
- Wilson Centre for Research in Education, University of Toronto, 200 Elizabeth St., 1ES-565, Toronto, M5G 2C4, Canada.,Department of Occupational Science and Occupational Therapy, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Marlys K Christianson
- Rotman School of Management, University of Toronto, 125 St. George St., Toronto, M5S 2E8, Canada
| | - Timothy J Vogus
- Owen Graduate School of Management, Vanderbilt University, 401 21st Avenue South, Nashville, TN, 37203, USA
| | - Connie Cameron
- The Hospital for Sick Children, 555 University Ave., Toronto, M5G 1X8, Canada
| | - Maitreya Coffey
- The Hospital for Sick Children, 555 University Ave., Toronto, M5G 1X8, Canada.,Department of Paediatrics, University of Toronto, Toronto, Canada.,Children's Hospitals Solutions for Patient Safety, Cincinnati, OH, USA
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13
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Verma AA, Murray J, Greiner R, Cohen JP, Shojania KG, Ghassemi M, Straus SE, Pou-Prom C, Mamdani M. Implementing machine learning in medicine. CMAJ 2021; 193:E1351-E1357. [PMID: 35213323 PMCID: PMC8432320 DOI: 10.1503/cmaj.202434] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Affiliation(s)
- Amol A Verma
- Unity Health Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Li Ka Shing Knowledge Institute of St. Michael's Hospital (Verma, Straus, Pou-Prom, Mamdani); Department of Medicine (Verma, Shojania, Straus, Mamdani) and Institute of Health Policy, Management, and Evaluation (Verma, Mamdani) and Department of Statistics (Murray), University of Toronto, Toronto, Ont.; University of Alberta (Greiner); Alberta Machine Intelligence Institute (Greiner), Edmonton, Alta.; Montreal Institute for Learning Algorithms (Cohen), Montréal, Que.; Centre for Quality Improvement and Patient Safety (Shojania), University of Toronto; Sunnybrook Health Sciences Centre (Shojania); Vector Institute (Ghassemi, Mamdani) and Department of Computer Science (Ghassemi); Leslie Dan Faculty of Pharmacy (Mamdani), University of Toronto, Toronto, Ont.; Department of Radiology, Stanford University (Cohen), Stanford, Calif.
| | - Joshua Murray
- Unity Health Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Li Ka Shing Knowledge Institute of St. Michael's Hospital (Verma, Straus, Pou-Prom, Mamdani); Department of Medicine (Verma, Shojania, Straus, Mamdani) and Institute of Health Policy, Management, and Evaluation (Verma, Mamdani) and Department of Statistics (Murray), University of Toronto, Toronto, Ont.; University of Alberta (Greiner); Alberta Machine Intelligence Institute (Greiner), Edmonton, Alta.; Montreal Institute for Learning Algorithms (Cohen), Montréal, Que.; Centre for Quality Improvement and Patient Safety (Shojania), University of Toronto; Sunnybrook Health Sciences Centre (Shojania); Vector Institute (Ghassemi, Mamdani) and Department of Computer Science (Ghassemi); Leslie Dan Faculty of Pharmacy (Mamdani), University of Toronto, Toronto, Ont.; Department of Radiology, Stanford University (Cohen), Stanford, Calif
| | - Russell Greiner
- Unity Health Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Li Ka Shing Knowledge Institute of St. Michael's Hospital (Verma, Straus, Pou-Prom, Mamdani); Department of Medicine (Verma, Shojania, Straus, Mamdani) and Institute of Health Policy, Management, and Evaluation (Verma, Mamdani) and Department of Statistics (Murray), University of Toronto, Toronto, Ont.; University of Alberta (Greiner); Alberta Machine Intelligence Institute (Greiner), Edmonton, Alta.; Montreal Institute for Learning Algorithms (Cohen), Montréal, Que.; Centre for Quality Improvement and Patient Safety (Shojania), University of Toronto; Sunnybrook Health Sciences Centre (Shojania); Vector Institute (Ghassemi, Mamdani) and Department of Computer Science (Ghassemi); Leslie Dan Faculty of Pharmacy (Mamdani), University of Toronto, Toronto, Ont.; Department of Radiology, Stanford University (Cohen), Stanford, Calif
| | - Joseph Paul Cohen
- Unity Health Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Li Ka Shing Knowledge Institute of St. Michael's Hospital (Verma, Straus, Pou-Prom, Mamdani); Department of Medicine (Verma, Shojania, Straus, Mamdani) and Institute of Health Policy, Management, and Evaluation (Verma, Mamdani) and Department of Statistics (Murray), University of Toronto, Toronto, Ont.; University of Alberta (Greiner); Alberta Machine Intelligence Institute (Greiner), Edmonton, Alta.; Montreal Institute for Learning Algorithms (Cohen), Montréal, Que.; Centre for Quality Improvement and Patient Safety (Shojania), University of Toronto; Sunnybrook Health Sciences Centre (Shojania); Vector Institute (Ghassemi, Mamdani) and Department of Computer Science (Ghassemi); Leslie Dan Faculty of Pharmacy (Mamdani), University of Toronto, Toronto, Ont.; Department of Radiology, Stanford University (Cohen), Stanford, Calif
| | - Kaveh G Shojania
- Unity Health Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Li Ka Shing Knowledge Institute of St. Michael's Hospital (Verma, Straus, Pou-Prom, Mamdani); Department of Medicine (Verma, Shojania, Straus, Mamdani) and Institute of Health Policy, Management, and Evaluation (Verma, Mamdani) and Department of Statistics (Murray), University of Toronto, Toronto, Ont.; University of Alberta (Greiner); Alberta Machine Intelligence Institute (Greiner), Edmonton, Alta.; Montreal Institute for Learning Algorithms (Cohen), Montréal, Que.; Centre for Quality Improvement and Patient Safety (Shojania), University of Toronto; Sunnybrook Health Sciences Centre (Shojania); Vector Institute (Ghassemi, Mamdani) and Department of Computer Science (Ghassemi); Leslie Dan Faculty of Pharmacy (Mamdani), University of Toronto, Toronto, Ont.; Department of Radiology, Stanford University (Cohen), Stanford, Calif
| | - Marzyeh Ghassemi
- Unity Health Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Li Ka Shing Knowledge Institute of St. Michael's Hospital (Verma, Straus, Pou-Prom, Mamdani); Department of Medicine (Verma, Shojania, Straus, Mamdani) and Institute of Health Policy, Management, and Evaluation (Verma, Mamdani) and Department of Statistics (Murray), University of Toronto, Toronto, Ont.; University of Alberta (Greiner); Alberta Machine Intelligence Institute (Greiner), Edmonton, Alta.; Montreal Institute for Learning Algorithms (Cohen), Montréal, Que.; Centre for Quality Improvement and Patient Safety (Shojania), University of Toronto; Sunnybrook Health Sciences Centre (Shojania); Vector Institute (Ghassemi, Mamdani) and Department of Computer Science (Ghassemi); Leslie Dan Faculty of Pharmacy (Mamdani), University of Toronto, Toronto, Ont.; Department of Radiology, Stanford University (Cohen), Stanford, Calif
| | - Sharon E Straus
- Unity Health Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Li Ka Shing Knowledge Institute of St. Michael's Hospital (Verma, Straus, Pou-Prom, Mamdani); Department of Medicine (Verma, Shojania, Straus, Mamdani) and Institute of Health Policy, Management, and Evaluation (Verma, Mamdani) and Department of Statistics (Murray), University of Toronto, Toronto, Ont.; University of Alberta (Greiner); Alberta Machine Intelligence Institute (Greiner), Edmonton, Alta.; Montreal Institute for Learning Algorithms (Cohen), Montréal, Que.; Centre for Quality Improvement and Patient Safety (Shojania), University of Toronto; Sunnybrook Health Sciences Centre (Shojania); Vector Institute (Ghassemi, Mamdani) and Department of Computer Science (Ghassemi); Leslie Dan Faculty of Pharmacy (Mamdani), University of Toronto, Toronto, Ont.; Department of Radiology, Stanford University (Cohen), Stanford, Calif
| | - Chloe Pou-Prom
- Unity Health Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Li Ka Shing Knowledge Institute of St. Michael's Hospital (Verma, Straus, Pou-Prom, Mamdani); Department of Medicine (Verma, Shojania, Straus, Mamdani) and Institute of Health Policy, Management, and Evaluation (Verma, Mamdani) and Department of Statistics (Murray), University of Toronto, Toronto, Ont.; University of Alberta (Greiner); Alberta Machine Intelligence Institute (Greiner), Edmonton, Alta.; Montreal Institute for Learning Algorithms (Cohen), Montréal, Que.; Centre for Quality Improvement and Patient Safety (Shojania), University of Toronto; Sunnybrook Health Sciences Centre (Shojania); Vector Institute (Ghassemi, Mamdani) and Department of Computer Science (Ghassemi); Leslie Dan Faculty of Pharmacy (Mamdani), University of Toronto, Toronto, Ont.; Department of Radiology, Stanford University (Cohen), Stanford, Calif
| | - Muhammad Mamdani
- Unity Health Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Li Ka Shing Knowledge Institute of St. Michael's Hospital (Verma, Straus, Pou-Prom, Mamdani); Department of Medicine (Verma, Shojania, Straus, Mamdani) and Institute of Health Policy, Management, and Evaluation (Verma, Mamdani) and Department of Statistics (Murray), University of Toronto, Toronto, Ont.; University of Alberta (Greiner); Alberta Machine Intelligence Institute (Greiner), Edmonton, Alta.; Montreal Institute for Learning Algorithms (Cohen), Montréal, Que.; Centre for Quality Improvement and Patient Safety (Shojania), University of Toronto; Sunnybrook Health Sciences Centre (Shojania); Vector Institute (Ghassemi, Mamdani) and Department of Computer Science (Ghassemi); Leslie Dan Faculty of Pharmacy (Mamdani), University of Toronto, Toronto, Ont.; Department of Radiology, Stanford University (Cohen), Stanford, Calif.
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14
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Miller FA, Young SB, Dobrow M, Shojania KG. Vulnerability of the medical product supply chain: the wake-up call of COVID-19. BMJ Qual Saf 2020; 30:331-335. [PMID: 33139342 DOI: 10.1136/bmjqs-2020-012133] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Revised: 10/17/2020] [Accepted: 10/22/2020] [Indexed: 02/03/2023]
Affiliation(s)
- Fiona A Miller
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Steven B Young
- School of Environment, Enterprise and Development, University of Waterloo, Waterloo, Ontario, Canada
| | - Mark Dobrow
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Kaveh G Shojania
- Department of Medicine, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
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15
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Goldman J, Kuper A, Baker GR, Bulmer B, Coffey M, Jeffs L, Shea C, Whitehead C, Shojania KG, Wong B. Experiential Learning in Project-Based Quality Improvement Education: Questioning Assumptions and Identifying Future Directions. Acad Med 2020; 95:1745-1754. [PMID: 32079957 DOI: 10.1097/acm.0000000000003203] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
PURPOSE Project-based experiential learning is a defining element of quality improvement (QI) education despite ongoing challenges and uncertainties. The authors examined stakeholders' perceptions and experiences of QI project-based learning to increase understanding of factors that influence learning and project experiences. METHOD The authors used a case study approach to examine QI project-based learning in 3 advanced longitudinal QI programs, 2 at the University of Toronto and 1 at an academic tertiary-care hospital. From March 2016 to June 2017, they undertook 135 hours of education program observation and 58 interviews with learners, program directors, project coaches, and institutional leaders and reviewed relevant documents. They analyzed data using a conventional and directed data analysis approach. RESULTS The findings provide insight into 5 key factors that influenced participants' project-based learning experiences and outcomes: (1) variable emphasis on learning versus project objectives and resulting benefits, tensions, and consequences; (2) challenges integrating the QI project into the curriculum timeline; (3) project coaching factors (e.g., ability, capacity, role clarity); (4) participants' differing access to resources and ability to direct a QI project given their professional roles; and (5) workplace environment influence on project success. CONCLUSIONS The findings contribute to an empirical basis toward more effective experiential learning in QI by identifying factors to target and optimize. Expanding conceptualizations of project-based learning for QI education beyond learner-initiated, time-bound projects, which are at the core of many QI educational initiatives, may be necessary to improve learning and project outcomes.
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Affiliation(s)
- Joanne Goldman
- J. Goldman is assistant professor, Department of Medicine, scientist, Centre for Quality Improvement and Patient Safety, and cross-appointed researcher, Wilson Centre for Research in Education, University of Toronto, Toronto, Ontario, Canada; ORCID: http://orcid.org/0000-0003-1589-4070
| | - Ayelet Kuper
- A. Kuper is associate professor, Department of Medicine, scientist and associate director, Wilson Centre for Research in Education, University Health Network, University of Toronto, and staff physician, Division of General Internal Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - G Ross Baker
- G.R. Baker is professor and program lead, Quality Improvement and Patient Safety, Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Beverly Bulmer
- B. Bulmer is vice president, Education, St. Michael's Hospital, Unity Health Toronto, and lecturer, Department of Physical Therapy, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Maitreya Coffey
- M. Coffey is associate professor, Department of Paediatrics, University of Toronto, medical officer for patient safety, Hospital for Sick Children, Toronto, Ontario, Canada, and associate clinical director, Children's Hospitals Solutions for Patient Safety, Cincinnati, Ohio
| | - Lianne Jeffs
- L. Jeffs is research and innovation lead scholar in residence and senior clinician scientist, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, associate professor, Lawrence S. Bloomberg Faculty of Nursing, Institute of Health Policy, Management and Evaluation, Faculty of Medicine, University of Toronto, and affiliate scientist, Keenan Research Centre, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Christine Shea
- C. Shea is program director and lecturer, Quality Improvement and Patient Safety, Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Cynthia Whitehead
- C. Whitehead is professor, Department of Family and Community Medicine, director and scientist, Wilson Centre for Research in Education, University Health Network, University of Toronto, and vice president of education, Women's College Hospital, Toronto, Ontario, Canada
| | - Kaveh G Shojania
- K.G. Shojania is professor and vice chair, Department of Medicine, Faculty of Medicine, University of Toronto, and staff physician, Division of General Internal Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada; ORCID: http://orcid.org/0000-0002-9942-0130
| | - Brian Wong
- B. Wong is associate professor, Department of Medicine, University of Toronto, director, Centre for Quality Improvement and Patient Safety, Faculty of Medicine, University of Toronto, and staff physician, Division of General Internal Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
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16
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Kwan JL, Lo L, Ferguson J, Goldberg H, Diaz-Martinez JP, Tomlinson G, Grimshaw JM, Shojania KG. Computerised clinical decision support systems and absolute improvements in care: meta-analysis of controlled clinical trials. BMJ 2020; 370:m3216. [PMID: 32943437 PMCID: PMC7495041 DOI: 10.1136/bmj.m3216] [Citation(s) in RCA: 151] [Impact Index Per Article: 37.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
OBJECTIVE To report the improvements achieved with clinical decision support systems and examine the heterogeneity from pooling effects across diverse clinical settings and intervention targets. DESIGN Systematic review and meta-analysis. DATA SOURCES Medline up to August 2019. ELIGIBILITY CRITERIA FOR SELECTING STUDIES AND METHODS Randomised or quasi-randomised controlled trials reporting absolute improvements in the percentage of patients receiving care recommended by clinical decision support systems. Multilevel meta-analysis accounted for within study clustering. Meta-regression was used to assess the degree to which the features of clinical decision support systems and study characteristics reduced heterogeneity in effect sizes. Where reported, clinical endpoints were also captured. RESULTS In 108 studies (94 randomised, 14 quasi-randomised), reporting 122 trials that provided analysable data from 1 203 053 patients and 10 790 providers, clinical decision support systems increased the proportion of patients receiving desired care by 5.8% (95% confidence interval 4.0% to 7.6%). This pooled effect exhibited substantial heterogeneity (I2=76%), with the top quartile of reported improvements ranging from 10% to 62%. In 30 trials reporting clinical endpoints, clinical decision support systems increased the proportion of patients achieving guideline based targets (eg, blood pressure or lipid control) by a median of 0.3% (interquartile range -0.7% to 1.9%). Two study characteristics (low baseline adherence and paediatric settings) were associated with significantly larger effects. Inclusion of these covariates in the multivariable meta-regression, however, did not reduce heterogeneity. CONCLUSIONS Most interventions with clinical decision support systems appear to achieve small to moderate improvements in targeted processes of care, a finding confirmed by the small changes in clinical endpoints found in studies that reported them. A minority of studies achieved substantial increases in the delivery of recommended care, but predictors of these more meaningful improvements remain undefined.
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Affiliation(s)
- Janice L Kwan
- Sinai Health System, Department of Medicine, 600 University Avenue, Toronto, ON M5G 1X5, Canada
- Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Lisha Lo
- Centre for Quality Improvement and Patient Safety, University of Toronto, Toronto, ON, Canada
| | - Jacob Ferguson
- Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Hanna Goldberg
- Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Juan Pablo Diaz-Martinez
- Biostatistics Research Unit, University Health Network and Sinai Health System, Toronto, ON, Canada
| | - George Tomlinson
- Biostatistics Research Unit, University Health Network and Sinai Health System, Toronto, ON, Canada
| | - Jeremy M Grimshaw
- Clinical Epidemiology Program, Ottawa Hospital Research Institute and Department of Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Kaveh G Shojania
- Department of Medicine, University of Toronto, Toronto, ON, Canada
- Centre for Quality Improvement and Patient Safety, University of Toronto, Toronto, ON, Canada
- Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
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17
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Bhatia RS, Shojania KG, Levinson W. Cost of contact: redesigning healthcare in the age of COVID. BMJ Qual Saf 2020; 30:236-239. [DOI: 10.1136/bmjqs-2020-011624] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 07/29/2020] [Accepted: 07/30/2020] [Indexed: 12/11/2022]
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Razak F, Shin S, Pogacar F, Jung HY, Pus L, Moser A, Lapointe-Shaw L, Tang T, Kwan JL, Weinerman A, Rawal S, Kushnir V, Mak D, Martin D, Shojania KG, Bhatia S, Agarwal P, Mukerji G, Fralick M, Kapral MK, Morgan M, Wong B, Chan TCY, Verma AA. Modelling resource requirements and physician staffing to provide virtual urgent medical care for residents of long-term care homes: a cross-sectional study. CMAJ Open 2020; 8:E514-E521. [PMID: 32819964 PMCID: PMC7850232 DOI: 10.9778/cmajo.20200098] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND The coronavirus disease 2019 (COVID-19) outbreak increases the importance of strategies to enhance urgent medical care delivery in long-term care (LTC) facilities that could potentially reduce transfers to emergency departments. The study objective was to model resource requirements to deliver virtual urgent medical care in LTC facilities. METHODS We used data from all general medicine inpatient admissions at 7 hospitals in the Greater Toronto Area, Ontario, Canada, over a 7.5-year period (Apr. 1, 2010, to Oct. 31, 2017) to estimate historical patterns of hospital resource use by LTC residents. We estimated an upper bound of potentially avoidable transfers by combining data on short admissions (≤ 72 h) with historical data on the proportion of transfers from LTC facilities for which patients were discharged from the emergency department without admission. Regression models were used to extrapolate future resource requirements, and queuing models were used to estimate physician staffing requirements to perform virtual assessments. RESULTS There were 235 375 admissions to general medicine wards, and residents of LTC facilities (age 16 yr or older) accounted for 9.3% (n = 21 948) of these admissions. Among the admissions of residents of LTC facilities, short admissions constituted 24.1% (n = 5297), and for 99.8% (n = 5284) of these admissions, the patient received laboratory testing, for 86.9% (n = 4604) the patient received plain radiography, for 41.5% (n = 2197) the patient received computed tomography and for 81.2% (n = 4300) the patient received intravenous medications. If all patients who have short admissions and are transferred from the emergency department were diverted to outpatient care, the average weekly demand for outpatient imaging per hospital would be 2.6 ultrasounds, 11.9 computed tomographic scans and 23.9 radiographs per week. The average daily volume of urgent medical virtual assessments would range from 2.0 to 5.8 per hospital. A single centralized virtual assessment centre staffed by 2 or 3 physicians would provide services similar in efficiency (measured by waiting time for physician assessment) to 7 separate centres staffed by 1 physician each. INTERPRETATION The provision of acute medical care to LTC residents at their facility would probably require rapid access to outpatient diagnostic imaging, within-facility access to laboratory services and intravenous medication and virtual consultations with physicians. The results of this study can inform efforts to deliver urgent medical care in LTC facilities in light of a potential surge in COVID-19 cases.
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Affiliation(s)
- Fahad Razak
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont.
| | - Saeha Shin
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Frances Pogacar
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Hae Young Jung
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Laura Pus
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Andrea Moser
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Lauren Lapointe-Shaw
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Terence Tang
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Janice L Kwan
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Adina Weinerman
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Shail Rawal
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Vladyslav Kushnir
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Denise Mak
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Danielle Martin
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Kaveh G Shojania
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Sacha Bhatia
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Payal Agarwal
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Geetha Mukerji
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Michael Fralick
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Moira K Kapral
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Matthew Morgan
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Brian Wong
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Timothy C Y Chan
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Amol A Verma
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
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Affiliation(s)
- Kaveh G Shojania
- Department of Medicine and the Centre for Quality Improvement and Patient Safety, University of Toronto, Toronto, ON M4N 3M5, Canada
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Shojania KG, Marang-van de Mheen PJ. Identifying adverse events: reflections on an imperfect gold standard after 20 years of patient safety research. BMJ Qual Saf 2020; 29:265-270. [DOI: 10.1136/bmjqs-2019-009731] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/30/2020] [Indexed: 12/16/2022]
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Wong BM, Baum KD, Headrick LA, Holmboe ES, Moss F, Ogrinc G, Shojania KG, Vaux E, Warm EJ, Frank JR. Building the Bridge to Quality: An Urgent Call to Integrate Quality Improvement and Patient Safety Education With Clinical Care. Acad Med 2020; 95:59-68. [PMID: 31397709 DOI: 10.1097/acm.0000000000002937] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Current models of quality improvement and patient safety (QIPS) education are not fully integrated with clinical care delivery, representing a major impediment toward achieving widespread QIPS competency among health professions learners and practitioners. The Royal College of Physicians and Surgeons of Canada organized a 2-day consensus conference in Niagara Falls, Ontario, Canada, called Building the Bridge to Quality, in September 2016. Its goal was to convene an international group of educational and health system leaders, educators, frontline clinicians, learners, and patients to engage in a consensus-building process and generate a list of actionable strategies that individuals and organizations can use to better integrate QIPS education with clinical care.Four strategic directions emerged: prioritize the integration of QIPS education and clinical care, build structures and implement processes to integrate QIPS education and clinical care, build capacity for QIPS education at multiple levels, and align educational and patient outcomes to improve quality and patient safety. Individuals and organizations can refer to the specific tactics associated with the 4 strategic directions to create a road map of targeted actions most relevant to their organizational starting point.To achieve widespread change, collaborative efforts and alignment of intrinsic and extrinsic motivators are needed on an international scale to shift the culture of educational and clinical environments and build bridges that connect training programs and clinical environments, align educational and health system priorities, and improve both learning and care, with the ultimate goal of achieving improved outcomes and experiences for patients, their families, and communities.
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Affiliation(s)
- Brian M Wong
- B.M. Wong is associate professor of medicine, Sunnybrook Health Sciences Centre, Department of Medicine, University of Toronto, and associate director, Centre for Quality Improvement and Patient Safety (C-QuIPS), Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada. K.D. Baum is professor of medicine and adjunct professor, School of Public Health, and associate chief medical officer, University of Minnesota, Minneapolis, Minnesota. L.A. Headrick is professor emerita of medicine, University of Missouri School of Medicine, Columbia, Missouri. E.S. Holmboe is senior vice president for milestones development and evaluation, Accreditation Council for Graduate Medical Education, Chicago, Illinois. F. Moss is dean, Royal Society of Medicine, and academic lead for collaboration, learning and partnerships, North West London Collaboration for Leadership in Applied Health Research and Care, London, United Kingdom. G. Ogrinc is professor of medicine, Dartmouth Institute, and senior associate dean for medical education, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire. K.G. Shojania is professor and vice chair of quality and innovation, Department of Medicine, University of Toronto and Sunnybrook Health Sciences Centre, and director, Centre for Quality Improvement and Patient Safety (C-QuIPS), Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada. E. Vaux is consultant nephrologist, Royal Berkshire National Health Service Foundation Trust, Reading, and vice president of education and training, Royal College of Physicians, London, United Kingdom. E.J. Warm is professor of medicine and program director, Department of Internal Medicine, University of Cincinnati College of Medicine, Cincinnati, Ohio; ORCID: https://orcid.org/0000-0002-6088-2434. J.R. Frank is associate professor, Department of Emergency Medicine, University of Ottawa, and director, Specialty Education, Strategy and Standards, Office of Specialty Education, Royal College of Physicians and Surgeons of Canada, Ottawa, Ontario, Canada
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Franklin BD, Abel G, Shojania KG. Medication non-adherence: an overlooked target for quality improvement interventions. BMJ Qual Saf 2019; 29:271-273. [DOI: 10.1136/bmjqs-2019-009984] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/06/2019] [Indexed: 01/24/2023]
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Affiliation(s)
| | - Kaveh G Shojania
- Department of Medicine, University of Toronto Faculty of Medicine, Toronto, Ontario, Canada
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Haghbayan H, Coomes EA, Cheema AN, Shojania KG. Media Dissemination of the Montreal Cognitive Assessment After President Donald Trump's Medical Evaluation. JAMA Neurol 2019; 75:1286-1287. [PMID: 30014152 DOI: 10.1001/jamaneurol.2018.1777] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Affiliation(s)
| | - Eric A Coomes
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Asim N Cheema
- Terrence Donnelly Heart Centre, Division of Cardiology, St Michael's Hospital, Toronto, Ontario, Canada
| | - Kaveh G Shojania
- Centre for Quality Improvement and Patient Safety, Department of Medicine, University of Toronto, Toronto, Ontario, Canada
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Mondoux S, Shojania KG. Evidence-based medicine: A cornerstone for clinical care but not for quality improvement. J Eval Clin Pract 2019; 25:363-368. [PMID: 30977249 DOI: 10.1111/jep.13135] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2019] [Accepted: 03/10/2019] [Indexed: 11/28/2022]
Abstract
Quality improvement (QI) as a clinical improvement science has been criticized for failing to deliver broad patient outcome improvement and for being a top-down regulatory and compliance construct. These critics have argued that the focus of QI should be on increasing adherence to clinical practice guidelines (CPGs) and, as a result, should be consolidated into research structures with the science of evidence-based medicine (EBM) at the helm. We argue that EBM often overestimates the role of knowledge as the root cause of quality problems and focuses almost exclusively on the effectiveness of care while often neglecting the domains of safety, efficiency, patient-centredness, and equity. Successfully addressing quality problems requires a much broader, systems-based view of health-care delivery. Although essential to clinical decision-making and practice, EBM cannot act as the cornerstone of health system improvement.
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Affiliation(s)
- Shawn Mondoux
- Department of Medicine, Division of Emergency Medicine, McMaster University, Hamilton, Canada
| | - Kaveh G Shojania
- Centre for Quality Improvement and Patient Safety and the Department of Medicine, University of Toronto, Toronto, Canada
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Kwan JL, Yermak D, Markell L, Paul NS, Shojania KG, Cram P. Follow Up of Incidental High-Risk Pulmonary Nodules on Computed Tomography Pulmonary Angiography at Care Transitions. J Hosp Med 2019; 14:349-352. [PMID: 30794133 PMCID: PMC6625441 DOI: 10.12788/jhm.3128] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2018] [Accepted: 11/18/2018] [Indexed: 12/21/2022]
Abstract
BACKGROUND Computed tomography pulmonary angiography (CTPA) detects incidental findings that require follow-up. In just over 50% of cases, those incidental findings are pulmonary nodules. Fleischner guidelines recommend that patients with nodules that have a high risk of malignancy should undergo CT follow-up within 3-12 months. OBJECTIVE We examined the proportion of patients with pulmonary nodules requiring follow up who received repeat imaging within six weeks of the time frame recommended by the radiologist. DESIGN This retrospective cohort study included all patients who underwent CTPA in the emergency department and inpatient settings at three teaching hospitals in Toronto, Canada between September 1, 2014, and August 31, 2015. Natural language processing software was applied to a linked radiology information system to identify all CTPAs that contained pulmonary nodules. Using manual review and prespecified exclusion criteria, we generated a cohort with possible new lung malignancy eligible for follow-up imaging; then we reviewed available health records to determine whether follow-up had occurred. RESULTS Of the 1,910 CTPAs performed over the study period, 674 (35.3%) contained pulmonary nodules. Of the 259 patients with new nodules eligible for follow-up imaging, 65 received an explicit suggestion for follow-up by radiology (25.1%). Of these 65 patients, 35 (53.8%) did not receive repeat imaging within the recommended time frame. Explicit mention that follow-up was required in the discharge summary (P = .03), attending an outpatient follow-up visit (P < .001), and younger age (P = .03) were associated with receiving timely follow-up imaging. CONCLUSIONS Over 50% of patients with new high-risk pulmonary nodules detected incidentally on CTPA did not receive timely follow-up imaging.
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Affiliation(s)
- Janice L Kwan
- Division of General Internal Medicine, Mount Sinai Hospital, Toronto, Ontario,
Canada
- Department of Medicine, University of Toronto, Toronto, Ontario,
Canada
- Corresponding Author: Janice L. Kwan; E-mail: ; Telephone: (416) 586-4800; Twitter: @KwanJanice
| | - Darya Yermak
- Department of Medicine, University of Toronto, Toronto, Ontario,
Canada
| | - Lezlie Markell
- Department of Medicine, University of Toronto, Toronto, Ontario,
Canada
| | - Narinder S Paul
- Department of Medical Imaging, Western University, London, Ontario,
Canada
| | - Kaveh G Shojania
- Department of Medicine, University of Toronto, Toronto, Ontario,
Canada
- Division of General Internal Medicine, Sunny-brook Health Sciences Centre, Toronto, Ontario,
Canada
| | - Peter Cram
- Division of General Internal Medicine, Mount Sinai Hospital, Toronto, Ontario,
Canada
- Department of Medicine, University of Toronto, Toronto, Ontario,
Canada
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Liu JJ, Rotteau L, Bell CM, Shojania KG. Putting out fires: a qualitative study exploring the use of patient complaints to drive improvement at three academic hospitals. BMJ Qual Saf 2019; 28:894-900. [PMID: 31123172 DOI: 10.1136/bmjqs-2018-008801] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Revised: 04/09/2019] [Accepted: 05/04/2019] [Indexed: 01/28/2023]
Abstract
BACKGROUND AND OBJECTIVES Recent years have seen increasing calls for more proactive use of patient complaints to develop effective system-wide changes, analogous to the intended functions of incident reporting and root cause analysis (RCA) to improve patient safety. Given recent questions regarding the impact of RCAs on patient safety, we sought to explore the degree to which current patient complaints processes generate solutions to recurring quality problems. DESIGN/SETTING Qualitative analysis of semistructured interviews with 21 patient relations personnel (PRP), nursing and physician leaders at three teaching hospitals (Toronto, Canada). RESULTS Challenges to using the patient complaints process to drive hospital-wide improvement included: (1) Complaints often reflect recalcitrant system-wide issues (eg, wait times) or well-known problems which require intensive efforts to address (eg, poor communication). (2) The use of weak change strategies (eg, one-off educational sessions). (3) The handling of complaints by unit managers so they never reach the patient relations office. PRP identified giving patients a voice as their primary goal. Yet their daily work, which they described as 'putting out fires', focused primarily on placating patients in order to resolve complaints as quickly as possible, which may in effect suppress the patient voice. CONCLUSIONS Using patient complaints to drive improvement faces many of the challenges affecting incident reporting and RCA. The emphasis on 'putting out fires' may further detract from efforts to improve care for future patients. Systemically incorporating patients' voices in clinical operations, as with co-design and other forms of authentic patient engagement, may hold greater promise for meaningful improvements in the patient experience than do RCA-like analyses of patient complaints.
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Affiliation(s)
- Jessica J Liu
- Division of Internal Medicine, University of Toronto Faculty of Medicine, Toronto, Ontario, Canada
| | - Leahora Rotteau
- Centre for Quality Improvment and Patient Safety (C-QuIPS), University of Toronto, Toronto, Ontario, Canada
| | - Chaim M Bell
- Division of Internal Medicine, University of Toronto Faculty of Medicine, Toronto, Ontario, Canada.,Centre for Quality Improvment and Patient Safety (C-QuIPS), University of Toronto, Toronto, Ontario, Canada
| | - Kaveh G Shojania
- Division of Internal Medicine, University of Toronto Faculty of Medicine, Toronto, Ontario, Canada.,Centre for Quality Improvment and Patient Safety (C-QuIPS), University of Toronto, Toronto, Ontario, Canada
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Shojania KG. Are increases in emergency use and hospitalisation always a bad thing? Reflections on unintended consequences and apparent backfires. BMJ Qual Saf 2019; 28:687-692. [DOI: 10.1136/bmjqs-2019-009406] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/11/2019] [Indexed: 11/04/2022]
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Marang-van de Mheen PJ, Abel GA, Shojania KG. Mortality alerts, actions taken and declining mortality: true effect or regression to the mean? BMJ Qual Saf 2018; 27:950-953. [DOI: 10.1136/bmjqs-2018-007984] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2018] [Accepted: 09/17/2018] [Indexed: 11/03/2022]
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Bouck Z, Ferguson J, Ivers NM, Kerr EA, Shojania KG, Kim M, Cram P, Pendrith C, Mecredy GC, Glazier RH, Tepper J, Austin PC, Martin D, Levinson W, Bhatia RS. Physician Characteristics Associated With Ordering 4 Low-Value Screening Tests in Primary Care. JAMA Netw Open 2018; 1:e183506. [PMID: 30646242 PMCID: PMC6324437 DOI: 10.1001/jamanetworkopen.2018.3506] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
IMPORTANCE Efforts to reduce low-value tests and treatments in primary care are often ineffective. These efforts typically target physicians broadly, most of whom order low-value care infrequently. OBJECTIVES To measure physician-level use rates of 4 low-value screening tests in primary care to investigate the presence and characteristics of primary care physicians who frequently order low-value care. DESIGN, SETTING, AND PARTICIPANTS A retrospective cohort study was conducted using administrative health care claims collected between April 1, 2012, and March 31, 2016, in Ontario, Canada. This study measured use of 4 low-value screening tests-repeated dual-energy x-ray absorptiometry (DXA) scans, electrocardiograms (ECGs), Papanicolaou (Pap) tests, and chest radiographs (CXRs)-among low-risk outpatients rostered to a common cohort of primary care physicians. EXPOSURES Physician sex, years since medical school graduation, and primary care model. MAIN OUTCOMES AND MEASURES This study measured the number of tests to which a given physician ranked in the top quintile by ordering rate. The resulting cross-test score (range, 0-4) reflects a physician's propensity to order low-value care across screening tests. Physicians were then dichotomized into infrequent or isolated frequent users (score, 0 or 1, respectively) or generalized frequent users for 2 or more tests (score, ≥2). RESULTS The final sample consisted of 2394 primary care physicians (mean [SD] age, 51.3 [10.0] years; 50.2% female), who were predominantly Canadian medical school graduates (1701 [71.1%]), far removed from medical school graduation (median, 25.3 years; interquartile range, 17.3-32.3 years), and reimbursed via fee-for-service in a family health group (1130 [47.2%]). They ordered 302 509 low-value screening tests (74 167 DXA scans, 179 855 ECGs, 19 906 Pap tests, and 28 581 CXRs) after 3 428 557 ordering opportunities. Within the cohort, generalized frequent users represented 18.4% (441 of 2394) of physicians but ordered 39.2% (118 665 of 302 509) of all low-value screening tests. Physicians who were male (odds ratio, 1.29; 95% CI, 1.01-1.64), further removed from medical school graduation (odds ratio, 1.03; 95% CI, 1.02-1.04), or in an enhanced fee-for-service payment model (family health group) vs a capitated payment model (family health team) (odds ratio, 2.04; 95% CI, 1.42-2.94) had increased odds of being generalized frequent users. CONCLUSIONS AND RELEVANCE This study identified a group of primary care physicians who frequently ordered low-value screening tests. Tailoring future interventions to these generalized frequent users might be an effective approach to reducing low-value care.
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Affiliation(s)
- Zachary Bouck
- Institute for Health Systems Solutions and Virtual Care, Women’s College Hospital, Toronto, Ontario, Canada
| | - Jacob Ferguson
- currently a student at Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada
| | - Noah M. Ivers
- Institute for Health Systems Solutions and Virtual Care, Women’s College Hospital, Toronto, Ontario, Canada
- Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada
- Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Eve A. Kerr
- Center for Clinical Management, Department of Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, Michigan
- Department of Internal Medicine and Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor
- Department of Internal Medicine and Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor
| | - Kaveh G. Shojania
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Min Kim
- Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada
| | - Peter Cram
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Division of General Internal Medicine and Geriatrics, Sinai Health System and Health Network, Toronto, Ontario, Canada
| | - Ciara Pendrith
- Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Graham C. Mecredy
- Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada
| | - Richard H. Glazier
- Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada
- Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Li Ka Shing Knowledge Institute, St Michael’s Hospital, Toronto, Ontario, Canada
- Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Joshua Tepper
- Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Peter C. Austin
- Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada
- Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Danielle Martin
- Institute for Health Systems Solutions and Virtual Care, Women’s College Hospital, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Wendy Levinson
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - R. Sacha Bhatia
- Institute for Health Systems Solutions and Virtual Care, Women’s College Hospital, Toronto, Ontario, Canada
- Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada
- Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
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Shojania KG. Identifying vendors in studies of electronic health records: the editor replies. BMJ Qual Saf 2018; 27:e1. [DOI: 10.1136/bmjqs-2017-007212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2017] [Accepted: 07/25/2017] [Indexed: 11/03/2022]
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Wong BM, Shojania KG. Rigor in Quality Improvement Studies and the Role of Time-Series Methodologies. JAMA Intern Med 2018; 178:724-725. [PMID: 29801128 DOI: 10.1001/jamainternmed.2018.0863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Affiliation(s)
- Brian M Wong
- Department of Medicine, Centre for Quality Improvement and Patient Safety (C-QuIPS), University of Toronto, Toronto, Ontario, Canada
| | - Kaveh G Shojania
- Department of Medicine, Centre for Quality Improvement and Patient Safety (C-QuIPS), University of Toronto, Toronto, Ontario, Canada.,Department of Medicine, University of Toronto, Toronto, Ontario, Canada
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Boozary AS, Shojania KG. Pathology of poverty: the need for quality improvement efforts to address social determinants of health. BMJ Qual Saf 2018; 27:421-424. [PMID: 29511090 DOI: 10.1136/bmjqs-2017-007552] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/15/2018] [Indexed: 11/03/2022]
Affiliation(s)
- Andrew S Boozary
- Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada.,Department of Health Policy and Management, Harvard School of Public Health, Boston, Massachusetts, USA
| | - Kaveh G Shojania
- Department of Medicine, Sunnybrook Health Sciences Centre and the University of Toronto, Toronto, Ontario, Canada
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Affiliation(s)
- Gurpreet Dhaliwal
- Department of Medicine, University of California, San Francisco, San Francisco, California, USA.,Medical Service, San Francisco VA Medical Center, San Francisco, California, USA
| | - Kaveh G Shojania
- Department of Medicine and Centre for Quality Improvement and Patient Safety, University of Toronto, Toronto, Ontario, Canada
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Baker M, Bell CM, Xiong W, Etchells E, Rossos PG, Shojania KG, Lane K, Tripp T, Lam M, Tiwana K, Leong D, Wong G, Huh JHH, Musing E, Fernandes O. Do Combined Pharmacist and Prescriber Efforts on Medication Reconciliation Reduce Postdischarge Patient Emergency Department Visits and Hospital Readmissions? J Hosp Med 2018; 13:152-157. [PMID: 29069119 DOI: 10.12788/jhm.2857] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
BACKGROUND Although medication reconciliation (Med Rec) has demonstrated a reduction in potential adverse drug events, its effect on hospital readmissions remains inconclusive. OBJECTIVE To evaluate the impact of an interprofessional Med Rec bundle from admission to discharge on patient emergency department visits and hospital readmissions (hospital visits). METHODS The design was a retrospective, cohort study. Patients discharged from general internal medicine over a 57-month interval were identified through administrative databases. Patients who received an enhanced, Gold level, Med Rec bundle (including both admission Med Rec and interprofessional pharmacist-prescriber collaboration on discharge Med Rec) were assigned to the intervention group. Patients who received partial Med Rec services, Silver and Bronze level, comprised the control group. The primary outcome was hospital visits within 30 days of discharge. RESULTS Over a 57-month period, 9931 unique patient visits (n = 8678 patients) met the study criteria. The main analysis did not detect a difference in 30-day hospital visits between the intervention (Gold level bundle) and control (21.25% vs 19.26%; adjusted odds ratio, 1.06; 95% confidence interval [CI], 0.95-1.19). Propensity score adjustment also did not detect an effect (16.7% vs18.9%; relative risk of readmission, 0.88; 95% CI, 0.59-1.32). CONCLUSION A long-term, observational evaluation of interprofessional Med Rec did not detect a difference in 30- day postdischarge patient hospital visits between patients who received enhanced versus partial Med Rec patient care bundles. In future prospective studies, researchers could focus on evaluating high-risk populations and specific elements of Med Rec services on avoidable, medication-related hospital admissions and postdischarge adverse drug events.
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Affiliation(s)
| | - Chaim M Bell
- Sinai Health System, Toronto, ON, Canada
- Department of Medicine-University of Toronto, Toronto ON, Canada
| | - Wei Xiong
- University Health Network, Toronto, ON, Canada
| | - Edward Etchells
- Department of Medicine-University of Toronto, Toronto ON, Canada
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Peter G Rossos
- University Health Network, Toronto, ON, Canada
- Department of Medicine-University of Toronto, Toronto ON, Canada
| | - Kaveh G Shojania
- Department of Medicine-University of Toronto, Toronto ON, Canada
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Kelly Lane
- University Health Network, Toronto, ON, Canada
| | - Tim Tripp
- University Health Network, Toronto, ON, Canada
| | - Mary Lam
- University Health Network, Toronto, ON, Canada
| | | | - Derek Leong
- University Health Network, Toronto, ON, Canada
| | - Gary Wong
- University Health Network, Toronto, ON, Canada
- Leslie Dan Faculty of Pharmacy-University of Toronto, Toronto ON, Canada
| | - Jin-Hyeun Huh Huh
- University Health Network, Toronto, ON, Canada
- Leslie Dan Faculty of Pharmacy-University of Toronto, Toronto ON, Canada
| | - Emily Musing
- University Health Network, Toronto, ON, Canada
- Leslie Dan Faculty of Pharmacy-University of Toronto, Toronto ON, Canada
| | - Olavo Fernandes
- University Health Network, Toronto, ON, Canada.
- Leslie Dan Faculty of Pharmacy-University of Toronto, Toronto ON, Canada
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Burke RE, Shojania KG. Rigorous evaluations of evolving interventions: can we have our cake and eat it too? BMJ Qual Saf 2018; 27:254-257. [DOI: 10.1136/bmjqs-2017-007554] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/29/2018] [Indexed: 11/03/2022]
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McAlister FA, Shojania KG. Inpatient bedspacing: could a common response to hospital crowding cause increased patient mortality? BMJ Qual Saf 2017; 27:1-3. [DOI: 10.1136/bmjqs-2017-007524] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/27/2017] [Indexed: 11/04/2022]
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Wong BM, Goldman J, Goguen JM, Base C, Rotteau L, Van Melle E, Kuper A, Shojania KG. Faculty-Resident "Co-learning": A Longitudinal Exploration of an Innovative Model for Faculty Development in Quality Improvement. Acad Med 2017; 92:1151-1159. [PMID: 28746138 DOI: 10.1097/acm.0000000000001505] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
PURPOSE To examine the effectiveness of co-learning, wherein faculty and trainees learn together, as a novel approach for building quality improvement (QI) faculty capacity. METHOD From July 2012 through September 2015, the authors conducted 30 semistructured interviews with 23 faculty participants from the Co-Learning QI Curriculum of the Department of Medicine, Faculty of Medicine, University of Toronto, and collected descriptive data on faculty participation and resident evaluations of teaching effectiveness. Interviewees were from 13 subspecialty residency programs at their institution. RESULTS Of the 56 faculty participants, the Co-Learning QI Curriculum trained 29 faculty mentors, 14 of whom taught formally. Faculty leads with an academic QI role, many of whom had prior QI training, reinforced their QI knowledge while also developing QI mentorship and teaching skills. Co-learning elements that contributed to QI teaching skills development included seeing first how the QI content is taught, learning through project mentorship, building experience longitudinally over time, a graded transition toward independent teaching, and a supportive program lead. Faculty with limited QI experience reported improved QI knowledge, skills, and project facilitation but were ambivalent about assuming a teacher role. Unplanned outcomes for both groups included QI teaching outside of the curriculum, applying QI principles to other work, networking, and strengthening one's QI professional role. CONCLUSIONS The Co-Learning QI Curriculum was effective in improving faculty QI knowledge and skills and increased faculty capacity to teach and mentor QI. Findings suggest that a combination of curriculum and contextual factors were critical to realizing the curriculum's full potential.
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Affiliation(s)
- Brian M Wong
- B. Wong is associate professor, Department of Medicine, and associate director, Centre for Quality Improvement and Patient Safety, both at the University of Toronto, Toronto, Ontario, Canada. He is also staff physician, Division of General Internal Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.J. Goldman is research education lead, Centre for Quality Improvement and Patient Safety, University of Toronto, Toronto, Ontario, Canada.J. Goguen is associate professor, Department of Medicine, and director, Internal Medicine Program, both at the University of Toronto, Toronto, Ontario, Canada. She is also staff physician, Division of Endocrinology, St. Michael's Hospital, Toronto, Ontario, Canada.C. Base is administrative assistant and program administrator, Co-Learning Quality Improvement Curriculum, Department of Medicine, University of Toronto, Toronto, Ontario, Canada.L. Rotteau is program manager, Centre for Quality Improvement and Patient Safety, and doctoral candidate, Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada.E. Van Melle is senior education scientist, Royal College of Physicians and Surgeons of Canada, Ottawa, Ontario, Canada.A. Kuper is associate professor, Department of Medicine, and scientist, Wilson Centre for Research in Education, University Health Network, both at the University of Toronto, Toronto, Ontario, Canada. She is also staff physician, Division of General Internal Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.K. Shojania is professor, Department of Medicine, and director, Centre for Quality Improvement and Patient Safety, both at the University of Toronto, Toronto, Ontario, Canada. He is also staff physician, Division of General Internal Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
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Abstract
The commitment to improve care processes and patient outcomes is a professional mandate for clinicians and is also seen as an operational priority for institutions. Quality improvement now figures in the accreditation of training programs, specialty examinations, and hospital scorecards. Rheumatologists have traditionally focused primarily on quality problems such as guideline adherence; however, improvement goals should also include other aspects of care that are helpful to patients and are professionally rewarding for practitioners. This review makes use of improvement projects in outlining tangible tools rheumatologists can use to resolve quality concerns in their practices.
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Affiliation(s)
- Patricia Trbovich
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada.,North York General Hospital, Toronto, Ontario, Canada
| | - Kaveh G Shojania
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada.,Department of Medicine, Sunnybrook Health Sciences Centre and the University of Toronto, Toronto, Ontario, Canada.,University of Toronto Centre for Quality Improvement and Patient Safety, Toronto, Ontario, Canada
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Affiliation(s)
- Kaveh G Shojania
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Mary Dixon-Woods
- Primary Care Unit, University of Cambridge Institute of Public Health, Cambridge, UK
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Affiliation(s)
- Jerome A Leis
- Centre for Quality Improvement and Patient Safety, University of Toronto, Toronto, Ontario, Canada.,Divsion of Infectious Diseases, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Kaveh G Shojania
- Centre for Quality Improvement and Patient Safety, University of Toronto, Toronto, Ontario, Canada.,Department of Medicine, University of Toronto, Toronto, Ontario, Canada
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Kovacs-Litman A, Wong K, Shojania KG, Callery S, Vearncombe M, Leis JA. Do physicians clean their hands? Insights from a covert observational study. J Hosp Med 2016; 11:862-864. [PMID: 27378510 DOI: 10.1002/jhm.2632] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2016] [Revised: 05/29/2016] [Accepted: 05/31/2016] [Indexed: 11/09/2022]
Abstract
Physicians are notorious for poor hand hygiene (HH) compliance. We wondered if lower performance by physicians compared with other health professionals might reflect differences in the Hawthorne effect. We introduced covert HH observers to see if performance differences between physicians and nurses decreased and to gain further insights into physician HH behaviors. Following training and validation with a hospital HH auditor, 2 students covertly measured HH during clinical rotations. Students rotated off clinical services every week to increase exposure to different providers and minimize risk of exposing the covert observation. We compared covertly measured HH compliance with data from overt observation by hospital auditors during the same time period. Covert observation produced much lower HH compliance than recorded by hospital auditors during the same time period: 50.0% (799/1597) versus 83.7% (2769/3309) (P < 0.0002). The difference in physician compliance between hospital auditors and covert observers was 19.0% (73.2% vs 54.2%); for nurses this difference was much higher at 40.7% (85.8% vs 45.1%) (P < 0.0001). Physician trainees showed markedly better compliance when attending staff cleaned their hands compared with encounters when attending did not (79.5% vs 18.9%; P < 0.0002). Our study suggests that traditional HH audits not only overstate HH performance overall, but can lead to inaccurate inferences about performance by professional groupings due to relative differences in the Hawthorne effect. We suggest that future improvement efforts will rely on more accurate HH monitoring systems and strong attending physician leadership to set an example for trainees. Journal of Hospital Medicine 2015;11:862-864. © 2015 Society of Hospital Medicine.
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Affiliation(s)
- Adam Kovacs-Litman
- Centre for Quality Improvement and Patient Safety, University of Toronto, Toronto, Ontario, Canada
| | - Kimberly Wong
- Centre for Quality Improvement and Patient Safety, University of Toronto, Toronto, Ontario, Canada
| | - Kaveh G Shojania
- Centre for Quality Improvement and Patient Safety, University of Toronto, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Sandra Callery
- Department of Microbiology, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Mary Vearncombe
- Department of Microbiology, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Jerome A Leis
- Centre for Quality Improvement and Patient Safety, University of Toronto, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Divsion of Infectious Diseases, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
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Affiliation(s)
- Kaveh G Shojania
- Department of Medicine, Centre for Quality Improvement and Patient Safety, University of Toronto, Toronto, Ontario, Canada
| | - Mary Dixon-Woods
- Cambridge Centre for Health Services Research, University of Cambridge, Institute of Public Health, Cambridge, UK
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Affiliation(s)
- Tejal K Gandhi
- National Patient Safety Foundation, Boston, Massachusetts
| | - Donald M Berwick
- Institute for Healthcare Improvement, Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts
| | - Kaveh G Shojania
- Centre for Quality Improvement and Patient Safety, University of Toronto, Toronto, Canada
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Etchells E, Ho M, Shojania KG. Value of small sample sizes in rapid-cycle quality improvement projects: Table 1. BMJ Qual Saf 2015; 25:202-6. [DOI: 10.1136/bmjqs-2015-005094] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/27/2015] [Indexed: 11/03/2022]
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Levitt K, Shojania KG, Bhatia RS. Point-of-care decision support for reducing inappropriate test use: easier said than done. BMJ Qual Saf 2015; 25:6-8. [PMID: 26424763 DOI: 10.1136/bmjqs-2015-004785] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/14/2015] [Indexed: 11/04/2022]
Affiliation(s)
- Kevin Levitt
- Toronto East General Hospital, University of Toronto, Toronto, Ontario, Canada Women's College Hospital, University of Toronto, Toronto, Ontario, Canada Division of Cardiology, University of Toronto, Toronto, Ontario, Canada Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Kaveh G Shojania
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - R Sacha Bhatia
- Women's College Hospital, University of Toronto, Toronto, Ontario, Canada Division of Cardiology, University of Toronto, Toronto, Ontario, Canada Department of Medicine, University of Toronto, Toronto, Ontario, Canada
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Shojania KG, Marang-van de Mheen PJ. Temporal trends in patient safety in the Netherlands: reductions in preventable adverse events or the end of adverse events as a useful metric? BMJ Qual Saf 2015; 24:541-4. [DOI: 10.1136/bmjqs-2015-004461] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/03/2015] [Indexed: 11/04/2022]
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Amaral ACKB, McDonald A, Coburn NG, Xiong W, Shojania KG, Fowler RA, Chapman M, Adhikari NKJ. Expanding the scope of Critical Care Rapid Response Teams: a feasible approach to identify adverse events. A prospective observational cohort. BMJ Qual Saf 2015; 24:764-8. [PMID: 26056320 DOI: 10.1136/bmjqs-2014-003833] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2014] [Accepted: 05/24/2015] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Adverse events (AEs) affect 3-12% of hospitalised patients. These are estimates from a labour-intensive chart review process,which is not feasible outside research. Clinical deterioration on the wards triggers a rapid response teams (RRTs) consult and can be used to identify an AE prospectively. OBJECTIVES To demonstrate the feasibility of using RRT to detect AEs and compare this methodology to the rates reported using an electronic safety reporting system. METHODS Prospective observational cohort of RRT consults. Three independent physicians reviewed all cases for the occurrence of an AE and its preventability. We summarise AEs as rates per 1000 patient-days, and compared the rates between RRT and the safety reporting system using a Poisson model. RESULTS There were 8713 hospital admissions, with 531 RRT consults and 247 (2.8%) cases included. Forty-four (17.8%) and 35 cases (14.2%) were judged as AEs and preventable AEs, respectively. RRT identified 0.52 AE/1000 patient-days, compared with 0.21 AE/1000 patient-days detected through the electronic safety reporting system (rate ratio 2.4, 95% CI 1.4 to 4.2, p=0.0014). Patients in surgical wards had more AEs (0.83/1000 vs 0.36/1000, p<0.01) and preventable AEs (0.70 vs 0.21, p<0.01) than patients in medical wards. Agreement for AE (κ 0.46, 95% CI 0.39 to 0.53) and preventable AE (κ 0.47, 95% CI 0.40 to 0.53) was moderate among reviewers. CONCLUSIONS Reviewing RRT consults identified a high proportion of AEs and preventable AEs. This methodology detected twice as many AEs as the hospital's safety reporting system. RRT clinicians provide a complementary and more sensitive mechanism than traditional safety reporting systems to identify possible AEs in hospitals.
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Affiliation(s)
| | - Andrew McDonald
- Department of Emergency Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Natalie G Coburn
- Department of General Surgery, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Wei Xiong
- Department of Critical Care Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Kaveh G Shojania
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Robert A Fowler
- Interdepartmental Division of Critical Care, University of Toronto, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Martin Chapman
- Interdepartmental Division of Critical Care, University of Toronto, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Neill K J Adhikari
- Interdepartmental Division of Critical Care, University of Toronto, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
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