Uncertainty as a Key Influence in the Decision To Admit Patients with Transient Ischemic Attack

Clinical risk calculators informing the decision to admit: A methodologic evaluation and assessment of applicability

INTRODUCTION

Clinical prediction and decision tools that generate outcome-based risk stratification and/or intervention recommendations are prevalent. Appropriate use and validity of these tools, especially those that inform complex clinical decisions, remains unclear. The objective of this study was to assess the methodologic quality and applicability of clinical risk scoring tools used to guide hospitalization decision-making.

METHODS

In February 2021, a comprehensive search was performed of a clinical calculator online database (mdcalc.com) that is publicly available and well-known to clinicians. The primary reference for any calculator tool informing outpatient versus inpatient disposition was considered for inclusion. Studies were restricted to the adult, acute care population. Those focused on obstetrics/gynecology or critical care admission were excluded. The Wasson-Laupacis framework of methodologic standards for clinical prediction rules was applied to each study.

RESULTS

A total of 22 calculators provided hospital admission recommendations for 9 discrete medical conditions using adverse events (14/22), mortality (6/22), or confirmatory diagnosis (2/22) as outcomes of interest. The most commonly met methodologic standards included mathematical technique description (22/22) and clinical sensibility (22/22) and least commonly met included reproducibility of the rule (1/22) and measurement of effect on clinical use (1/22). Description of the studied population was often lacking, especially patient race/ethnicity (2/22) and mental or behavioral health (0/22). Only one study reported any item related to social determinants of health.

CONCLUSION

Studies commonly do not meet rigorous methodologic standards and often fail to report pertinent details that would guide applicability. These clinical tools focus primarily on specific disease entities and clinical variables, missing the breadth of information necessary to make a disposition determination and raise significant validation and generalizability concerns.

Qualitative analysis of disposition decision making for patients referred for admission from the emergency department without definite medical acuity

OBJECTIVE

To map the physician approach when determining disposition for a patient who presents without the level of definite medical acuity that would generally warrant hospitalisation.

DATA SOURCES/STUDY SETTING

Since 2018, our US academic county hospital/trauma centre has maintained a database in which hospitalists ('triage physicians') document the rationale and outcomes of requests for admission to the acute care medical ward during each shift.

STUDY DESIGN

Narrative text from the database was analysed using a grounded theory approach to identify major themes and subthemes, and a conceptual model of the admission decision-making process was constructed.

PARTICIPANTS

Database entries were included (n=300) if the admission call originated from the emergency department and if the triage physician characterised the request as potentially inappropriate because the patient did not have definite medical acuity.

RESULTS

Admission decision making occurs in three main phases: evaluation of unmet needs, assessment of risk and re-evaluation. Importantly, admission decision making is not solely based on medical acuity or clinical algorithms, and patients without a definite medical need for admission are hospitalised when physicians believe a potential issue exists if discharged. In this way, factors such as homelessness, substance use disorder, frailty, etc, contribute to admission because they raise concern about patient safety and/or barriers to appropriate treatment. Physician decision making can be altered by activities such as care coordination, advocacy by the patient or surrogate, interactions with other physicians or a change in clinical trajectory.

CONCLUSIONS

The decision to admit ultimately remains a clinical determination constructed between physician and patient. Physicians use a holistic process that incorporates broad consideration of the patient's medical and social needs with emphasis on risk assessment; thus, any analysis of hospitalisation trends or efforts to impact such should seek to understand this individual-level decision making.

Hospital Factors, Performance on Process Measures After Transient Ischemic Attack, and 90-Day Ischemic Stroke Incidence

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Acceptability of a complex team-based quality improvement intervention for transient ischemic attack: a mixed-methods study

BACKGROUND

The Protocol-guided Rapid Evaluation of Veterans Experiencing New Transient Neurologic Symptoms (PREVENT) program was a complex quality improvement (QI) intervention targeting transient ischemic attack (TIA) evidence-based care. The aim of this study was to evaluate program acceptability among the QI teams and factors associated with degrees of acceptability.

METHODS

QI teams from six Veterans Administration facilities participated in active implementation for a one-year period. We employed a mixed methods study to evaluate program acceptability. Multiple data sources were collected over implementation phases and triangulated for this evaluation. First, we conducted 30 onsite, semi-structured interviews during active implementation with 35 participants at 6 months; 27 interviews with 28 participants at 12 months; and 19 participants during program sustainment. Second, we conducted debriefing meetings after onsite visits and monthly virtual collaborative calls. All interviews and debriefings were audiotaped, transcribed, and de-identified. De-identified files were qualitatively coded and analyzed for common themes and acceptability patterns. We conducted mixed-methods matrix analyses comparing acceptability by satisfaction ratings and by the Theoretical Framework of Acceptability (TFA).

RESULTS

Overall, the QI teams reported the PREVENT program was acceptable. The clinical champions reported high acceptability of the PREVENT program. At pre-implementation phase, reviewing quality data, team brainstorming solutions and development of action plans were rated as most useful during the team kickoff meetings. Program acceptability perceptions varied over time across active implementation and after teams accomplished actions plans and moved into sustainment. We observed team acceptability growth over a year of active implementation in concert with the QI team's self-efficacy to improve quality of care. Guided by the TFA, the QI teams' acceptability was represented by the respective seven components of the multifaceted acceptability construct.

CONCLUSIONS

Program acceptability varied by time, by champion role on QI team, by team self-efficacy, and by perceived effectiveness to improve quality of care aligned with the TFA. A complex quality improvement program that fostered flexibility in local adaptation and supported users with access to data, resources, and implementation strategies was deemed acceptable and appropriate by front-line clinicians implementing practice changes in a large, national healthcare organization.

TRIAL REGISTRATION

clinicaltrials.gov : NCT02769338 .

Implementation Evaluation of a Complex Intervention to Improve Timeliness of Care for Veterans with Transient Ischemic Attack

BACKGROUND

The Protocol-guided Rapid Evaluation of Veterans Experiencing New Transient Neurologic Symptoms (PREVENT) program was designed to address systemic barriers to providing timely guideline-concordant care for patients with transient ischemic attack (TIA).

OBJECTIVE

We evaluated an implementation bundle used to promote local adaptation and adoption of a multi-component, complex quality improvement (QI) intervention to improve the quality of TIA care Bravata et al. (BMC Neurology 19:294, 2019).

DESIGN

A stepped-wedge implementation trial with six geographically diverse sites.

PARTICIPANTS

The six facility QI teams were multi-disciplinary, clinical staff.

INTERVENTIONS

PREVENT employed a bundle of key implementation strategies: team activation; external facilitation; and a community of practice. This strategy bundle had direct ties to four constructs from the Consolidated Framework for Implementation Research (CFIR): Champions, Reflecting & Evaluating, Planning, and Goals & Feedback.

MAIN MEASURES

Using a mixed-methods approach guided by the CFIR and data matrix analyses, we evaluated the degree to which implementation success and clinical improvement were associated with implementation strategies. The primary outcomes were the number of completed implementation activities, the level of team organization and > 15 points improvement in the Without Fail Rate (WFR) over 1 year.

KEY RESULTS

Facility QI teams actively engaged in the implementation strategies with high utilization. Facilities with the greatest implementation success were those with central champions whose teams engaged in planning and goal setting, and regularly reflected upon their quality data and evaluated their progress against their QI plan. The strong presence of effective champions acted as a pre-condition for the strong presence of Reflecting & Evaluating, Goals & Feedback, and Planning (rather than the other way around), helping to explain how champions at the +2 level influenced ongoing implementation.

CONCLUSIONS

The CFIR-guided bundle of implementation strategies facilitated the local implementation of the PREVENT QI program and was associated with clinical improvement in the national VA healthcare system.

TRIAL REGISTRATION

clinicaltrials.gov: NCT02769338.

Assessment of the Protocol-Guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms (PREVENT) Program for Improving Quality of Care for Transient Ischemic Attack: A Nonrandomized Cluster Trial

IMPORTANCE

Patients with transient ischemic attack (TIA) are at high risk of recurrent vascular events. Timely management can reduce that risk by 70%; however, gaps in TIA quality of care exist.

OBJECTIVE

To assess the performance of the Protocol-Guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms (PREVENT) intervention to improve TIA quality of care.

DESIGN, SETTING, AND PARTICIPANTS

This nonrandomized cluster trial with matched controls evaluated a multicomponent intervention to improve TIA quality of care at 6 diverse medical centers in 6 geographically diverse states in the US and assessed change over time in quality of care among 36 matched control sites (6 control sites matched to each PREVENT site on TIA patient volume, facility complexity, and quality of care). The study period (defined as the data period) started on August 21, 2015, and extended to May 12, 2019, including 1-year baseline and active implementation periods for each site. The intervention targeted clinical teams caring for patients with TIA.

INTERVENTION

The quality improvement (QI) intervention included the following 5 components: clinical programs, data feedback, professional education, electronic health record tools, and QI support.

MAIN OUTCOMES AND MEASURES

The primary outcome was the without-fail rate, which was calculated as the proportion of veterans with TIA at a specific facility who received all 7 guideline-recommended processes of care for which they were eligible (ie, anticoagulation for atrial fibrillation, antithrombotic use, brain imaging, carotid artery imaging, high- or moderate-potency statin therapy, hypertension control, and neurological consultation). Generalized mixed-effects models with multilevel hierarchical random effects were constructed to evaluate the intervention associations with the change in the mean without-fail rate from the 1-year baseline period to the 1-year intervention period.

RESULTS

Six facilities implemented the PREVENT QI intervention, and 36 facilities were identified as matched control sites. The mean (SD) age of patients at baseline was 69.85 (11.19) years at PREVENT sites and 71.66 (11.29) years at matched control sites. Most patients were male (95.1% [154 of 162] at PREVENT sites and 94.6% [920 of 973] at matched control sites at baseline). Among the PREVENT sites, the mean without-fail rate improved substantially from 36.7% (58 of 158 patients) at baseline to 54.0% (95 of 176 patients) during a 1-year implementation period (adjusted odds ratio, 2.10; 95% CI, 1.27-3.48; P = .004). Comparing the change in quality at the PREVENT sites with the matched control sites, the improvement in the mean without-fail rate was greater at the PREVENT sites than at the matched control sites (36.7% [58 of 158 patients] to 54.0% [95 of 176 patients] [17.3% absolute improvement] vs 38.6% [345 of 893 patients] to 41.8% [363 of 869 patients] [3.2% absolute improvement], respectively; absolute difference, 14%; P = .008).

CONCLUSIONS AND RELEVANCE

The implementation of this multifaceted program was associated with improved TIA quality of care across the participating sites. The PREVENT QI program is an example of a health care system using QI strategies to improve performance, and may serve as a model for other health systems seeking to provide better care.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02769338.

Modelling care quality for patients after a transient ischaemic attack within the US Veterans Health Administration

Objective

Timely preventive care can substantially reduce risk of recurrent vascular events or death after a transient ischaemic attack (TIA). Our objective was to understand patient and facility factors influencing preventive care quality for patients with TIA in the US Veterans Health Administration (VHA).

Methods

We analysed administrative data from a retrospective cohort of 3052 patients with TIA cared for in the emergency department (ED) or inpatient setting in 110 VHA facilities from October 2010 to September 2011. A composite quality indicator (QI score) pass rate was constructed from four process-related quality measures—carotid imaging, brain imaging, high or moderate potency statin and antithrombotic medication, associated with the ED visit or inpatient admission after the TIA. We tested a multilevel structural equation model where facility and patient characteristics, inpatient admission, and neurological consultation were predictors of the resident’s composite QI score.

Results

Presenting with a speech deficit and higher Charlson Comorbidity Index (CCI) were positively related to inpatient admission. Being admitted increased the likelihood of neurology consultation, whereas history of dementia, weekend arrival and a higher CCI score made neurological consultation less likely. Speech deficit, higher CCI, inpatient admission and neurological consultation had direct positive effects on the composite quality score. Patients in facilities with fewer full-time equivalent neurology staff were less likely to be admitted or to have a neurology consultation. Facilities having greater organisational complexity and with a VHA stroke centre designation were more likely to provide a neurology consultation.

Conclusions

Better TIA preventive care could be achieved through increased inpatient admissions, or through enhanced neurology and other care resources in the ED and during follow-up care.