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Hemmila MR, Neiman PU, Hoppe BL, Gerhardinger L, Kramer KA, Jakubus JL, Mikhail JN, Yang AY, Lindsey HJ, Golden RJ, Mitchell EJ, Scott JW, Napolitano LM. Improving outcomes in emergency general surgery: Construct of a collaborative quality initiative. J Trauma Acute Care Surg 2024; 96:715-726. [PMID: 38189669 PMCID: PMC11042990 DOI: 10.1097/ta.0000000000004248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
BACKGROUND Emergency general surgery conditions are common, costly, and highly morbid. The proportion of excess morbidity due to variation in health systems and processes of care is poorly understood. We constructed a collaborative quality initiative for emergency general surgery to investigate the emergency general surgery care provided and guide process improvements. METHODS We collected data at 10 hospitals from July 2019 to December 2022. Five cohorts were defined: acute appendicitis, acute gallbladder disease, small bowel obstruction, emergency laparotomy, and overall aggregate. Processes and inpatient outcomes investigated included operative versus nonoperative management, mortality, morbidity (mortality and/or complication), readmissions, and length of stay. Multivariable risk adjustment accounted for variations in demographic, comorbid, anatomic, and disease traits. RESULTS Of the 19,956 emergency general surgery patients, 56.8% were female and 82.8% were White, and the mean (SD) age was 53.3 (20.8) years. After accounting for patient and disease factors, the adjusted aggregate mortality rate was 3.5% (95% confidence interval [CI], 3.2-3.7), morbidity rate was 27.6% (95% CI, 27.0-28.3), and the readmission rate was 15.1% (95% CI, 14.6-15.6). Operative management varied between hospitals from 70.9% to 96.9% for acute appendicitis and 19.8% to 79.4% for small bowel obstruction. Significant differences in outcomes between hospitals were observed with high- and low-outlier performers identified after risk adjustment in the overall cohort for mortality, morbidity, and readmissions. The use of a Gastrografin challenge in patients with a small bowel obstruction ranged from 10.7% to 61.4% of patients. In patients who underwent initial nonoperative management of acute cholecystitis, 51.5% had a cholecystostomy tube placed. The cholecystostomy tube placement rate ranged from 23.5% to 62.1% across hospitals. CONCLUSION A multihospital emergency general surgery collaborative reveals high morbidity with substantial variability in processes and outcomes among hospitals. A targeted collaborative quality improvement effort can identify outliers in emergency general surgery care and may provide a mechanism to optimize outcomes. LEVEL OF EVIDENCE Therapeutic/Care Management; Level III.
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Affiliation(s)
- Mark R. Hemmila
- Department of Surgery, University of Michigan Medical School, Ann Arbor, MI
- Center for Healthcare Outcomes and Policy, University of Michigan, Ann Arbor, MI
| | - Pooja U. Neiman
- Center for Healthcare Outcomes and Policy, University of Michigan, Ann Arbor, MI
- National Clinical Scholars Program, University of Michigan, Ann Arbor, MI
- Department of Surgery, Brigham and Women’s Hospital, Boston, MA
| | - Beckie L. Hoppe
- Department of Surgery, University of Michigan Medical School, Ann Arbor, MI
| | - Laura Gerhardinger
- Department of Surgery, University of Michigan Medical School, Ann Arbor, MI
- Center for Healthcare Outcomes and Policy, University of Michigan, Ann Arbor, MI
| | - Kim A. Kramer
- Department of Surgery, University of Michigan Medical School, Ann Arbor, MI
| | - Jill L. Jakubus
- Department of Surgery, University of Michigan Medical School, Ann Arbor, MI
| | - Judy N. Mikhail
- Department of Surgery, University of Michigan Medical School, Ann Arbor, MI
| | - Amanda Y. Yang
- Department of Surgery, Corewell Health, Grand Rapids, MI
| | | | - Roy J. Golden
- Department of Surgery, Trinity Health Ann Arbor, Ann Arbor, MI
| | - Eric J. Mitchell
- Department of Surgery, University of Michigan Health - West, Wyoming, MI
| | - John W. Scott
- Department of Surgery, University of Michigan Medical School, Ann Arbor, MI
- Center for Healthcare Outcomes and Policy, University of Michigan, Ann Arbor, MI
| | - Lena M. Napolitano
- Department of Surgery, University of Michigan Medical School, Ann Arbor, MI
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Azimuddin A, Tzeng CWD, Prakash LR, Bruno ML, Arvide EM, Dewhurst WL, Newhook TE, Kim MP, Ikoma N, Snyder RA, Lee JE, Perrier ND, Katz MH, Maxwell JE. Postoperative Global Period Cost Reduction Using 3 Successive Risk-Stratified Pancreatectomy Clinical Pathways. J Am Coll Surg 2024; 238:451-459. [PMID: 38180055 DOI: 10.1097/xcs.0000000000000944] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2024]
Abstract
BACKGROUND We hypothesized that iterative revisions of our original 2016 risk-stratified pancreatectomy clinical pathways would be associated with decreased 90-day perioperative costs. STUDY DESIGN From a single-institution retrospective cohort study of consecutive patients with 3 iterations: "version 1" (V1) (October 2016 to January 2019), V2 (February 2019 to October 2020), and V3 (November 2020 to February 2022), institutional data were aggregated using revenue codes and adjusted to constant 2022-dollar value. Grand total perioperative costs (primary endpoint) were the sum of pancreatectomy, inpatient care, readmission, and 90-day global outpatient care. Proprietary hospital-based costs were converted to ratios using the mean cost of all hospital operations as the denominator. RESULTS Of 814 patients, pathway V1 included 363, V2 229, and V3 222 patients. Accordion Grade 3+ complications decreased with each iteration (V1: 28.4%, V2: 22.7%, and V3: 15.3%). Median length of stay decreased (V1: 6 days, interquartile range [IQR] 5 to 8; V2: 5 [IQR 4 to 6]; and V3: 5 [IQR 4 to 6]) without an increase in readmissions. Ninety-day global perioperative costs decreased by 32% (V1 cost ratio 12.6, V2 10.9, and V3 8.6). Reduction of the index hospitalization cost was associated with the greatest savings (-31%: 9.4, 8.3, and 6.5). Outpatient care costs decreased consistently (1.58, 1.41, and 1.04). When combining readmission and all outpatient costs, total "postdischarge" costs decreased (3.17, 2.59, and 2.13). Component costs of the index hospitalization that were associated with the greatest savings were room or board costs (-55%: 1.74, 1.14, and 0.79) and pharmacy costs (-61%: 2.20, 1.61, and 0.87; all p < 0.001). CONCLUSIONS Three iterative risk-stratified pancreatectomy clinical pathway refinements were associated with a 32% global period cost savings, driven by reduced index hospitalization costs. This successful learning health system model could be externally validated at other institutions performing abdominal cancer surgery.
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Affiliation(s)
- Ahad Azimuddin
- From the Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX (Azimuddin, Tzeng, Prakash, Bruno, Arvide, Dewhurst, Newhook, Kim, Ikoma, Snyder, Lee, Perrier, Katz, Maxwell)
- Texas A&M School of Medicine, Houston, TX (Azimuddin)
| | - Ching-Wei D Tzeng
- From the Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX (Azimuddin, Tzeng, Prakash, Bruno, Arvide, Dewhurst, Newhook, Kim, Ikoma, Snyder, Lee, Perrier, Katz, Maxwell)
| | - Laura R Prakash
- From the Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX (Azimuddin, Tzeng, Prakash, Bruno, Arvide, Dewhurst, Newhook, Kim, Ikoma, Snyder, Lee, Perrier, Katz, Maxwell)
| | - Morgan L Bruno
- From the Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX (Azimuddin, Tzeng, Prakash, Bruno, Arvide, Dewhurst, Newhook, Kim, Ikoma, Snyder, Lee, Perrier, Katz, Maxwell)
| | - Elsa M Arvide
- From the Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX (Azimuddin, Tzeng, Prakash, Bruno, Arvide, Dewhurst, Newhook, Kim, Ikoma, Snyder, Lee, Perrier, Katz, Maxwell)
| | - Whitney L Dewhurst
- From the Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX (Azimuddin, Tzeng, Prakash, Bruno, Arvide, Dewhurst, Newhook, Kim, Ikoma, Snyder, Lee, Perrier, Katz, Maxwell)
| | - Timothy E Newhook
- From the Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX (Azimuddin, Tzeng, Prakash, Bruno, Arvide, Dewhurst, Newhook, Kim, Ikoma, Snyder, Lee, Perrier, Katz, Maxwell)
| | - Michael P Kim
- From the Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX (Azimuddin, Tzeng, Prakash, Bruno, Arvide, Dewhurst, Newhook, Kim, Ikoma, Snyder, Lee, Perrier, Katz, Maxwell)
| | - Naruhiko Ikoma
- From the Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX (Azimuddin, Tzeng, Prakash, Bruno, Arvide, Dewhurst, Newhook, Kim, Ikoma, Snyder, Lee, Perrier, Katz, Maxwell)
| | - Rebecca A Snyder
- From the Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX (Azimuddin, Tzeng, Prakash, Bruno, Arvide, Dewhurst, Newhook, Kim, Ikoma, Snyder, Lee, Perrier, Katz, Maxwell)
| | - Jeffrey E Lee
- From the Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX (Azimuddin, Tzeng, Prakash, Bruno, Arvide, Dewhurst, Newhook, Kim, Ikoma, Snyder, Lee, Perrier, Katz, Maxwell)
| | - Nancy D Perrier
- From the Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX (Azimuddin, Tzeng, Prakash, Bruno, Arvide, Dewhurst, Newhook, Kim, Ikoma, Snyder, Lee, Perrier, Katz, Maxwell)
| | - Matthew Hg Katz
- From the Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX (Azimuddin, Tzeng, Prakash, Bruno, Arvide, Dewhurst, Newhook, Kim, Ikoma, Snyder, Lee, Perrier, Katz, Maxwell)
| | - Jessica E Maxwell
- From the Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX (Azimuddin, Tzeng, Prakash, Bruno, Arvide, Dewhurst, Newhook, Kim, Ikoma, Snyder, Lee, Perrier, Katz, Maxwell)
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McGowan JG, Martin GP, Krapohl GL, Campbell DA, Englesbe MJ, Dimick JB, Dixon-Woods M. What are the features of high-performing quality improvement collaboratives? A qualitative case study of a state-wide collaboratives programme. BMJ Open 2023; 13:e076648. [PMID: 38097243 PMCID: PMC10729078 DOI: 10.1136/bmjopen-2023-076648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 11/20/2023] [Indexed: 12/18/2023] Open
Abstract
OBJECTIVES Despite their widespread use, the evidence base for the effectiveness of quality improvement collaboratives remains mixed. Lack of clarity about 'what good looks like' in collaboratives remains a persistent problem. We aimed to identify the distinctive features of a state-wide collaboratives programme that has demonstrated sustained improvements in quality of care in a range of clinical specialties over a long period. DESIGN Qualitative case study involving interviews with purposively sampled participants, observations and analysis of documents. SETTING The Michigan Collaborative Quality Initiatives programme. PARTICIPANTS 38 participants, including clinicians and managers from 10 collaboratives, and staff from the University of Michigan and Blue Cross Blue Shield of Michigan. RESULTS We identified five features that characterised success in the collaboratives programme: learning from positive deviance; high-quality coordination; high-quality measurement and comparative performance feedback; careful use of motivational levers; and mobilising professional leadership and building community. Rigorous measurement, securing professional leadership and engagement, cultivating a collaborative culture, creating accountability for quality, and relieving participating sites of unnecessary burdens associated with programme participation were all important to high performance. CONCLUSIONS Our findings offer valuable learning for optimising collaboration-based approaches to improvement in healthcare, with implications for the design, structure and resourcing of quality improvement collaboratives. These findings are likely to be useful to clinicians, managers, policy-makers and health system leaders engaged in multiorganisational approaches to improving quality and safety.
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Affiliation(s)
- James G McGowan
- The Healthcare Improvement Studies Institute (THIS Institute), Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Graham P Martin
- The Healthcare Improvement Studies Institute (THIS Institute), Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Greta L Krapohl
- Department of Surgery, University of Michigan, Ann Arbor, Michigan, USA
| | | | | | - Justin B Dimick
- Department of Surgery, University of Michigan, Ann Arbor, Michigan, USA
| | - Mary Dixon-Woods
- The Healthcare Improvement Studies Institute (THIS Institute), Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
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Somerville M, Cassidy C, Curran JA, Johnson C, Sinclair D, Elliott Rose A. Implementation strategies and outcome measures for advancing learning health systems: a mixed methods systematic review. Health Res Policy Syst 2023; 21:120. [PMID: 38012681 PMCID: PMC10680228 DOI: 10.1186/s12961-023-01071-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 11/09/2023] [Indexed: 11/29/2023] Open
Abstract
BACKGROUND Learning health systems strive to continuously integrate data and evidence into practice to improve patient outcomes and ensure value-based healthcare. While the LHS concept is gaining traction, the operationalization of LHSs is underexplored. OBJECTIVE To identify and synthesize the existing evidence on the implementation and evaluation of advancing learning health systems across international health care settings. METHODS A mixed methods systematic review was conducted. Six databases (CINAHL, Embase, Medline, PAIS, Scopus and Nursing at Allied Health Database) were searched up to July 2022 for terms related to learning health systems, implementation, and evaluation measures. Any study design, health care setting and population were considered for inclusion. No limitations were placed on language or date of publication. Two reviewers independently screened the titles, abstracts, and full texts of identified articles. Data were extracted and synthesized using a convergent integrated approach. Studies were critically appraised using relevant JBI critical appraisal checklists. RESULTS Thirty-five studies were included in the review. Most studies were conducted in the United States (n = 21) and published between 2019 and 2022 (n = 24). Digital data capture was the most common LHS characteristic reported across studies, while patient engagement, aligned governance and a culture of rapid learning and improvement were reported least often. We identified 33 unique strategies for implementing LHSs including: change record systems, conduct local consensus discussions and audit & provide feedback. A triangulation of quantitative and qualitative data revealed three integrated findings related to the implementation of LHSs: (1) The digital infrastructure of LHSs optimizes health service delivery; (2) LHSs have a positive impact on patient care and health outcomes; and (3) LHSs can influence health care providers and the health system. CONCLUSION This paper provides a comprehensive overview of the implementation of LHSs in various healthcare settings. While this review identified key implementation strategies, potential outcome measures, and components of functioning LHSs, further research is needed to better understand the impact of LHSs on patient, provider and population outcomes, and health system costs. Health systems researchers should continue to apply the LHS concept in practice, with a stronger focus on evaluation.
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Affiliation(s)
| | - Christine Cassidy
- Faculty of Health, School of Nursing, Dalhousie University, Halifax, NS, Canada
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Howard R, Thumma J, Englesbe M. The Measurement Reliability of Complications and Patient Satisfaction After Common Surgical Procedures. Ann Surg 2023; 277:775-780. [PMID: 35781523 DOI: 10.1097/sla.0000000000005451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE To evaluate the reliability of surgeon outcomes. BACKGROUND Surgeons' outcomes are now widely used in public reporting and value-based reimbursement, but the reliability of these measures continues to raise concerns. METHODS We performed a retrospective study of surgeons performing cholecystectomy, colectomy, and hernia repair on adult patients between January 1, 2017, and December 31, 2020. Outcomes were risk-adjusted rates of complications and high patient satisfaction. We estimated the reliability of each outcome, its relationship with case volume, and the number of surgeons who reached an acceptable level of reliability (≥0.70). RESULTS A total of 23,533 patients with a mean age of 56.8 (16.2) years and 10,191 (43.3%) females underwent operations by 333 surgeons. Risk-adjusted complication rate was 2.5% [95% confidence interval (CI): 2.2%-2.8%] and risk-adjusted high satisfaction rate was 79.9% (95% CI: 78.7%-81.0%). The reliability of the complication rate was 0.27 (95% CI: 0.25-0.29) and the reliability of the high satisfaction rate was 0.53 (95% CI: 0.50-0.55). Reliability increased with case volume; however, only 5 (1.5%) surgeons performed enough cases to reach acceptable reliability for their complication rate, while 86 (25.8%) surgeons reached acceptable reliability for their patient satisfaction rate. After adjustment for reliability, the range of complication rates decreased 29-fold from 0% to 14.3% to 2.4% to 2.9%, and the range of patient satisfaction decreased 2.6-fold from 25.3% to 100.0% to 64.9% to 92.4%. CONCLUSIONS Among surgeons performing common operations, complications and patient satisfaction had relatively low reliability. Although reliability increased with volume, most surgeons had insufficient case volume to achieve acceptable reliability of their outcomes. As such, these measures likely offer little to no meaningful information to inform decision-making.
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Affiliation(s)
- Ryan Howard
- Department of Surgery, University of Michigan, Ann Arbor, MI
- Center for Healthcare Outcomes and Policy, University of Michigan, Ann Arbor, MI
| | - Jyothi Thumma
- Center for Healthcare Outcomes and Policy, University of Michigan, Ann Arbor, MI
| | - Michael Englesbe
- Department of Surgery, University of Michigan, Ann Arbor, MI
- Michigan Surgical Quality Collaborative, Ann Arbor, MI
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Jayaraman P, Crouse A, Nadkarni G, Might M. A Primer in Precision Nephrology: Optimizing Outcomes in Kidney Health and Disease through Data-Driven Medicine. KIDNEY360 2023; 4:e544-e554. [PMID: 36951457 PMCID: PMC10278804 DOI: 10.34067/kid.0000000000000089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 01/04/2023] [Indexed: 03/24/2023]
Abstract
This year marks the 63rd anniversary of the International Society of Nephrology, which signaled nephrology's emergence as a modern medical discipline. In this article, we briefly trace the course of nephrology's history to show a clear arc in its evolution-of increasing resolution in nephrological data-an arc that is converging with computational capabilities to enable precision nephrology. In general, precision medicine refers to tailoring treatment to the individual characteristics of patients. For an operational definition, this tailoring takes the form of an optimization, in which treatments are selected to maximize a patient's expected health with respect to all available data. Because modern health data are large and high resolution, this optimization process requires computational intervention, and it must be tuned to the contours of specific medical disciplines. An advantage of this operational definition for precision medicine is that it allows us to better understand what precision medicine means in the context of a specific medical discipline. The goal of this article was to demonstrate how to instantiate this definition of precision medicine for the field of nephrology. Correspondingly, the goal of precision nephrology was to answer two related questions: ( 1 ) How do we optimize kidney health with respect to all available data? and ( 2 ) How do we optimize general health with respect to kidney data?
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Affiliation(s)
- Pushkala Jayaraman
- The Charles Bronfman Institute for Personalized Medicine Icahn School of Medicine at Mount Sinai, New York, New York
| | - Andrew Crouse
- Hugh Kaul Precision Medicine Institute, University of Alabama at Birmingham, Birmingham, Alabama
| | - Girish Nadkarni
- The Charles Bronfman Institute for Personalized Medicine Icahn School of Medicine at Mount Sinai, New York, New York
- The Mount Sinai Clinical Intelligence Center (MSCIC), Icahn School of Medicine at Mount Sinai, New York, New York
- Division of Data Driven and Digital Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York
- Barbara T Murphy Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Matthew Might
- Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
- Department of Computer Science, University of Alabama at Birmingham, Birmingham, Alabama
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Trinkley KE, Ho PM, Glasgow RE, Huebschmann AG. How Dissemination and Implementation Science Can Contribute to the Advancement of Learning Health Systems. ACADEMIC MEDICINE : JOURNAL OF THE ASSOCIATION OF AMERICAN MEDICAL COLLEGES 2022; 97:1447-1458. [PMID: 35796045 PMCID: PMC9547828 DOI: 10.1097/acm.0000000000004801] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Many health systems are working to become learning health systems (LHSs), which aim to improve the value of health care by rapidly, continuously generating evidence to apply to practice. However, challenges remain to advance toward the aspirational goal of becoming a fully mature LHS. While some important challenges have been well described (i.e., building system-level supporting infrastructure and the accessibility of inclusive, integrated, and actionable data), other key challenges are underrecognized, including balancing evaluation rapidity with rigor, applying principles of health equity and classic ethics, focusing on external validity and reproducibility (generalizability), and designing for sustainability. Many LHSs focus on continuous learning cycles, but with limited consideration of issues related to the rapidity of these learning cycles, as well as the sustainability or generalizability of solutions. Some types of data have been consistently underrepresented, including patient-reported outcomes and preferences, social determinants, and behavioral and environmental data, the absence of which can exacerbate health disparities. A promising approach to addressing many challenges that LHSs face may be found in dissemination and implementation (D&I) science. With an emphasis on multilevel dynamic contextual factors, representation of implementation partner engagement, pragmatic research, sustainability, and generalizability, D&I science methods can assist in overcoming many of the challenges facing LHSs. In this article, the authors describe the current state of LHSs and challenges to becoming a mature LHS, propose solutions to current challenges, focusing on the contributions of D&I science with other methods, and propose key components and characteristics of a mature LHS model that others can use to plan and develop their LHSs.
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Affiliation(s)
- Katy E Trinkley
- K.E. Trinkley is associate professor, Departments of Clinical Pharmacy and Medicine and Adult and Child Consortium for Outcomes Research and Delivery Science (ACCORDS), University of Colorado Anschutz Medical Center, and clinical informaticist, Department of Clinical Informatics, UCHealth, Aurora, Colorado; ORCID: http://orcid.org/0000-0003-2041-7404
| | - P Michael Ho
- P.M. Ho is professor, Department of Medicine, University of Colorado Anschutz Medical Campus, and professor, VA Eastern Colorado Health Care System, Aurora, Colorado; ORCID: http://orcid.org/0000-0002-7775-6266
| | - Russell E Glasgow
- R.E. Glasgow is research professor, Department of Family Medicine, and director, Dissemination and Implementation Science Program, ACCORDS, University of Colorado Anschutz Medical Center, Aurora, Colorado; ORCID: http://orcid.org/0000-0003-4218-3231
| | - Amy G Huebschmann
- A.G. Huebschmann is associate professor, Division of General Internal Medicine, ACCORDS and Ludeman Family Center for Women's Health Research, University of Colorado Anschutz Medical Center, Aurora, Colorado; ORCID: http://orcid.org/0000-0002-9329-3142
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Lattof SR, Maliqi B, Livesley N, Yaqub N, Naimy Z, Muzigaba M, Chowdhury M, Waiswa P, Were WM. National learning systems to sustain and scale up delivery of quality healthcare: a conceptual framework. BMJ Glob Health 2022; 7:bmjgh-2022-008664. [PMID: 35914831 PMCID: PMC9344983 DOI: 10.1136/bmjgh-2022-008664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 07/03/2022] [Indexed: 11/06/2022] Open
Abstract
All around the world, health systems fail to provide good quality of care (QoC). By developing learning systems, health systems are able to better identify good practices and to explain how to sustain and scale these good practices. To facilitate the operationalisation of national learning systems, the Network for Improving Quality of Care for Maternal Newborn and Child Health (the Network) developed a conceptual framework for national learning systems to support QoC at scale. The Network facilitated an iterative process to reach consensus on a conceptual framework for national learning systems to sustain and scale up delivery of quality healthcare. Following a landscape analysis, the Network Secretariat and WHO convened two consultative meetings with country partners, technical experts and stakeholders. Based on these inputs, we developed a conceptual framework for national learning systems to support QoC at scale. National learning systems use a variety of approaches to identify practices that have improved QoC at the patient and provider levels. They also facilitate scale up and sustain strategies used successfully to support quality improvement. Despite growing consensus on the importance of learning for QoC, no one has yet detailed how this learning should be operationalised nationally. Our conceptual framework is the first to facilitate the operationalisation of national learning systems so that health systems can begin to develop, adapt and implement mechanisms to learn about what works or fails and to scale up and sustain this learning for QoC.
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Affiliation(s)
- Samantha R Lattof
- Department of Maternal, Newborn, Child and Adolescent Health and Ageing, World Health Organization, Geneve, Switzerland
| | - Blerta Maliqi
- Department of Maternal, Newborn, Child and Adolescent Health and Ageing, World Health Organization, Geneve, Switzerland
| | | | - Nuhu Yaqub
- World Health Organization Regional Office for Africa, Brazzaville, Congo
| | - Zainab Naimy
- Department of Maternal, Newborn, Child and Adolescent Health and Ageing, World Health Organization, Geneve, Switzerland
| | - Moise Muzigaba
- Department of Maternal, Newborn, Child and Adolescent Health and Ageing, World Health Organization, Geneve, Switzerland
| | - Minara Chowdhury
- Institute for Healthcare Improvement, Boston, Massachusetts, USA
| | - Peter Waiswa
- School of Public Health, Makerere University, Kampala, Uganda
| | - Wilson M Were
- Department of Maternal, Newborn, Child and Adolescent Health and Ageing, World Health Organization, Geneve, Switzerland
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Bravata DM, Miech EJ, Myers LJ, Perkins AJ, Zhang Y, Rattray NA, Baird SA, Penney LS, Austin C, Damush TM. The Perils of a "My Work Here is Done" perspective: a mixed methods evaluation of sustainment of an evidence-based intervention for transient ischemic attack. BMC Health Serv Res 2022; 22:857. [PMID: 35787273 PMCID: PMC9254423 DOI: 10.1186/s12913-022-08207-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 06/16/2022] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND To evaluate quality improvement sustainment for Transient Ischemic Attack (TIA) and identify factors influencing sustainment, which is a challenge for Learning Healthcare Systems. METHODS Mixed methods were used to assess changes in care quality across periods (baseline, implementation, sustainment) and identify factors promoting or hindering sustainment of care quality. PREVENT was a stepped-wedge trial at six US Department of Veterans Affairs implementation sites and 36 control sites (August 2015-September 2019). Quality of care was measured by the without-fail rate: proportion of TIA patients who received all of the care for which they were eligible among brain imaging, carotid artery imaging, neurology consultation, hypertension control, anticoagulation for atrial fibrillation, antithrombotics, and high/moderate potency statins. Key informant interviews were used to identify factors associated with sustainment. RESULTS The without-fail rate at PREVENT sites improved from 36.7% (baseline, 58/158) to 54.0% (implementation, 95/176) and settled at 48.3% (sustainment, 56/116). At control sites, the without-fail rate improved from 38.6% (baseline, 345/893) to 41.8% (implementation, 363/869) and remained at 43.0% (sustainment, 293/681). After adjustment, no statistically significant difference in sustainment quality between intervention and control sites was identified. Among PREVENT facilities, the without-fail rate improved ≥2% at 3 sites, declined ≥2% at two sites, and remained unchanged at one site during sustainment. Factors promoting sustainment were planning, motivation to sustain, integration of processes into routine practice, leadership engagement, and establishing systems for reflecting and evaluating on performance data. The only factor that was sufficient for improving quality of care during sustainment was the presence of a champion with plans for sustainment. Challenges during sustainment included competing demands, low volume, and potential problems with medical coding impairing use of performance data. Four factors were sufficient for declining quality of care during sustainment: low motivation, champion inactivity, no reflecting and evaluating on performance data, and absence of leadership engagement. CONCLUSIONS Although the intervention improved care quality during implementation; performance during sustainment was heterogeneous across intervention sites and not different from control sites. Learning Healthcare Systems seeking to sustain evidence-based practices should embed processes within routine care and establish systems for reviewing and reflecting upon performance. TRIAL REGISTRATION Clinicaltrials.gov ( NCT02769338 ).
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Affiliation(s)
- Dawn M Bravata
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA.
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA.
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA.
- Regenstrief Institute, Indianapolis, IN, USA.
| | - Edward J Miech
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Regenstrief Institute, Indianapolis, IN, USA
| | - Laura J Myers
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Regenstrief Institute, Indianapolis, IN, USA
| | - Anthony J Perkins
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- Department of Biostatistics, Indiana University School of Medicine, IN, Indianapolis, USA
| | - Ying Zhang
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- Department of Biostatistics, College of Public Health, University of Nebraska Medical Center, Omaha, NE, USA
| | - Nicholas A Rattray
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Regenstrief Institute, Indianapolis, IN, USA
| | - Sean A Baird
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
| | - Lauren S Penney
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Elizabeth Dole Center of Excellence for Veteran and Caregiver Research, South Texas Veterans Health Care System, San Antonio, TX, USA
- Department of Medicine, University of Texas Health San Antonio, San Antonio, TX, USA
| | - Curt Austin
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
| | - Teresa M Damush
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Regenstrief Institute, Indianapolis, IN, USA
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