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Scholarly Works (15 results)

  • Article
  • Peer Reviewed
Western Journal of Emergency Medicine: Integrating Emergency Care with Population Health, Volume 22, Issue 2 (2021)

Introduction: Despite large-scale quality improvement initiatives, substantial proportions of patients with ST-elevation myocardial infarction (STEMI) transferred to percutaneous coronary intervention centers do not receive percutaneous coronary intervention within the recommended 120 minutes. We sought to examine the contributory role of emergency medical services (EMS) activation relative to percutaneous coronary intervention center activation in the timeliness of care for patients transferred with STEMI.

Methods: We conducted a retrospective analysis of interfacility transfers from emergency departments (ED) to a single percutaneous coronary intervention center between 2011–2014. We included emergency department (ED) patients transferred to the percutaneous coronary intervention center and excluded scene transfers and those given fibrinolytics. We calculated descriptive statistics and used multivariable linear regression to model the association of variables with ED time intervals (arrival to electrocardiogram [ECG], ECG-to-EMS activation, and ECG-to-STEMI alert) adjusting for patient age, gender, mode of arrival, weekday hour presentation, facility transfers in the past year, and transferring facility distance.

Results: We identified 159 patients who met inclusion criteria. Subjects were a mean of 59 years old (standard deviation 13), 22% female, and 93% White; 59% arrived by private vehicle, and 24% presented after weekday hours. EDs transferred a median of 9 STEMIs (interquartile range [IQR] 3, 15) in the past year and a median of 65 miles (IQR 35, 90) from the percutaneous coronary intervention center. Median ED length of stay was 65 minutes (IQR 51, 85). Among component intervals, arrival to ECG was 6%, ECG-to-EMS activation 32%, and ECG-to-STEMI alert was 49% of overall ED length of stay. Only 18% of transfers had EMS activation earlier than STEMI alert. ECG-to-EMS activation was shorter in EDs achieving length of stay ≤60 minutes compared to those >60 minutes (12 vs 31 minutes, P<0.001). Multivariable modeling showed that after-hours presentation was associated with longer ECG-to-EMS activation (adjusted relative risk [RR] 1.05, P<0.001). Female gender (adjusted RR 0.81, P<0.001), prior facility transfers (adjusted RR 0.84, P<0.001), and initial ambulance presentation (adjusted RR 0.93, P = 0.02) were associated with shorter ECG-to-EMS activation.

Conclusion: In STEMI transfers, faster EMS activation was more likely to achieve a shorter ED length of stay than a rapid, percutaneous coronary intervention center STEMI alert. Large-scale quality improvement efforts such as the American Heart Association’s Mission Lifeline that were designed to regionalize STEMI have improved the timeliness of reperfusion, but major gaps, particularly in interfacility transfers, remain. While the transferring EDs are recognized as the primary source of delay during interfacility STEMI transfers, the contributions to delays at transferring EDs remain poorly understood.

    Cover page: Examining the Timeliness of ST-elevation Myocardial Infarction TransfersCreative Commons 'BY' version 4.0 license
    • Article
    • Peer Reviewed
    UC San Francisco Previously Published Works (2017)
    BACKGROUND/OBJECTIVES: New tools to accurately identify potentially preventable 30-day readmissions are needed. The HOSPITAL score has been internationally validated for medical inpatients, but its performance in select conditions targeted by the Hospital Readmission Reduction Program (HRRP) is unknown. DESIGN: Retrospective cohort study. SETTING: Six geographically diverse medical centers. PARTICIPANTS/EXPOSURES: All consecutive adult medical patients discharged alive in 2011 with 1 of the 4 medical conditions targeted by the HRRP (acute myocardial infarction, chronic obstructive pulmonary disease, pneumonia, and heart failure) were included. Potentially preventable 30-day readmissions were identified using the SQLape algorithm. The HOSPITAL score was calculated for all patients. MEASUREMENTS: A multivariable logistic regression model accounting for hospital effects was used to evaluate the accuracy (Brier score), discrimination (c-statistic), and calibration (Pearson goodness-of-fit) of the HOSPITAL score for each 4 medical conditions. RESULTS: Among the 9181 patients included, the overall 30-day potentially preventable readmission rate was 13.6%. Across all 4 diagnoses, the HOSPITAL score had very good accuracy (Brier score of 0.11), good discrimination (c-statistic of 0.68), and excellent calibration (Hosmer-Lemeshow goodness-of-fit test, P=0.77). Within each diagnosis, performance was similar. In sensitivity analyses, performance was similar for all readmissions (not just potentially preventable) and when restricted to patients age 65 and above. CONCLUSIONS: The HOSPITAL score identifies a high-risk cohort for potentially preventable readmissions in a variety of practice settings, including conditions targeted by the HRRP. It may be a valuable tool when included in interventions to reduce readmissions within or across these conditions.
      Cover page: The HOSPITAL Score Predicts Potentially Preventable 30-Day Readmissions in Conditions Targeted by the Hospital Readmissions Reduction Program.
      • Article
      • Peer Reviewed
      UC San Francisco Previously Published Works (2014)
      Converting the health care delivery system into a learning organization is a key strategy for improving health outcomes. Although the collaborative learning organization approach has been successful in neonatal intensive care units and disease-specific collaboratives, there are few examples in general medicine and none in adult medicine that have leveraged the role of hospitalists nationally across multiple institutions to implement improvements. The authors describe the rationale for and early work of the Hospital Medicine Reengineering Network (HOMERuN), a collaborative of hospitals, hospitalists, and multidisciplinary care teams founded in 2011 that seeks to measure, benchmark, and improve the efficiency, quality, and outcomes of care in the hospital and afterwards. Robust and timely evaluation, with learning and refinement of approaches across institutions, should accelerate improvement efforts. The authors review HOMERuN's collaborative model, which focuses on a community-based participatory approach modified to include hospital-based staff as well as the larger community. HOMERuN's initial project is described, focusing on care transition measurement using perspectives from the patient, caregiver, and providers. Next steps and sustainability of the organization are discussed, including benchmarking, collaboration, and effective dissemination of best practices to stakeholders.
        Cover page: The Hospital Medicine Reengineering Network (HOMERuN)
        • Article
        • Peer Reviewed
        UCLA Previously Published Works (2016)

        Purpose

        To highlight teaching hospitals' efforts to reduce readmissions by describing interventions implemented to improve care transitions for heart failure (HF) patients and the variability in implemented HF-specific and care transition interventions.

        Method

        In 2012, the authors surveyed a network of 17 teaching hospitals to capture information about the number, type, stage of implementation, and structure of 4 HF-specific and 21 care transition (predischarge, bridging, and postdischarge) interventions implemented to reduce readmissions among patients with HF. The authors summarized data using descriptive statistics, including the mean number of interventions implemented and the frequency and stage of specific interventions, and descriptive plots of the structure of two common interventions (multidisciplinary rounds and follow-up telephone calls).

        Results

        Sixteen hospitals (94%) responded. The number and stage of implementation of the HF-specific and care transition interventions implemented varied across institutions. The mean number of interventions at an advanced stage of implementation (i.e., implemented for ≥ 75% of HF patients on the cardiology service or on all services) was 10.9 (standard deviation = 4.3). Overall, predischarge interventions were more common than bridging or postdischarge interventions. There was variability in the personnel involved in multidisciplinary rounds and in the processes/content of follow-up telephone calls.

        Conclusions

        Teaching hospitals have implemented a wide range of interventions aimed at reducing hospital readmissions, but there is substantial variability in the types, stages, and structure of their interventions. This heterogeneity highlights the need for collaborative efforts to improve understanding of intervention effectiveness.
          Cover page: Variability in Implementation of Interventions Aimed at Reducing Readmissions Among Patients With Heart Failure
          • Article
          • Peer Reviewed
          UC San Francisco Previously Published Works (2016)
          BACKGROUND: The transition out of the hospital is a vulnerable time for patients, relying heavily on communication and coordination of resources across care settings. Understanding the perspectives of inpatient and outpatient physicians regarding factors contributing to readmission and potential preventive strategies is crucial in designing appropriately targeted readmission prevention efforts. OBJECTIVE: To examine and compare inpatient and outpatient physician opinions regarding reasons for readmission and interventions that might have prevented readmission. DESIGN: Cross-sectional multicenter study. PARTICIPANTS: We identified patients readmitted to general medicine services within 30 days of discharge at 12 US academic medical centers, and surveyed the primary care physician (PCP), discharging physician from the index admission, and admitting physician from the readmission regarding their endorsement of pre-specified factors contributing to the readmission and potential preventive strategies. MAIN MEASURES: We calculated kappa statistics to gauge agreement between physician dyads (PCP-discharging physician, PCP-admitting physician, and admitting-discharging physician). KEY RESULTS: We evaluated 993 readmission events, which generated responses from 356 PCPs (36 % of readmissions), 675 discharging physicians (68 % of readmissions), and 737 admitting physicians (74 % of readmissions). The most commonly endorsed contributing factors by both PCPs and inpatient physicians related to patient understanding and ability to self-manage. The most commonly endorsed preventive strategies involved providing patients with enhanced post-discharge instructions and/or support. Although PCPs and inpatient physicians endorsed contributing factors and potential preventive strategies with similar frequencies, agreement among the three physicians on the specific factors and/or strategies that applied to individual readmission events was poor (maximum kappa 0.30). CONCLUSIONS: Differing opinions among physicians on factors contributing to individual readmissions highlights the importance of communication between inpatient and outpatient providers at discharge to share their different perspectives, and suggests that multi-faceted, broadly applied interventions may be more successful than those that rely on individual providers choosing specific services based on perceived risk factors.
            Cover page: Physician Perspectives on Factors Contributing to Readmissions and Potential Prevention Strategies: A Multicenter Survey.
            • Article
            • Peer Reviewed
            UC San Francisco Previously Published Works (2016)
            IMPORTANCE: Identification of patients at a high risk of potentially avoidable readmission allows hospitals to efficiently direct additional care transitions services to the patients most likely to benefit. OBJECTIVE: To externally validate the HOSPITAL score in an international multicenter study to assess its generalizability. DESIGN, SETTING, AND PARTICIPANTS: International retrospective cohort study of 117 065 adult patients consecutively discharged alive from the medical department of 9 large hospitals across 4 different countries between January 2011 and December 2011. Patients transferred to another acute care facility were excluded. EXPOSURES: The HOSPITAL score includes the following predictors at discharge: hemoglobin, discharge from an oncology service, sodium level, procedure during the index admission, index type of admission (urgent), number of admissions during the last 12 months, and length of stay. MAIN OUTCOMES AND MEASURES: 30-day potentially avoidable readmission to the index hospital using the SQLape algorithm. RESULTS: Overall, 117 065 adults consecutively discharged alive from a medical department between January 2011 and December 2011 were studied. Of all medical discharges, 16 992 of 117 065 (14.5%) were followed by a 30-day readmission, and 11 307 (9.7%) were followed by a 30-day potentially avoidable readmission. The discriminatory power of the HOSPITAL score to predict potentially avoidable readmission was good, with a C statistic of 0.72 (95% CI, 0.72-0.72). As in the derivation study, patients were classified into 3 risk categories: low (n = 73 031 [62.4%]), intermediate (n = 27 612 [23.6%]), and high risk (n = 16 422 [14.0%]). The estimated proportions of potentially avoidable readmission for each risk category matched the observed proportion, resulting in an excellent calibration (Pearson χ2 test P = .89). CONCLUSIONS AND RELEVANCE: The HOSPITAL score identified patients at high risk of 30-day potentially avoidable readmission with moderately high discrimination and excellent calibration when applied to a large international multicenter cohort of medical patients. This score has the potential to easily identify patients in need of more intensive transitional care interventions to prevent avoidable hospital readmissions.
              Cover page: International Validity of the HOSPITAL Score to Predict 30-Day Potentially Avoidable Hospital Readmissions.
              • Article
              • Peer Reviewed
              UC San Francisco Previously Published Works (2020)

              Importance

              Although intensive care unit (ICU) adaptations to the coronavirus disease of 2019 (COVID-19) pandemic have received substantial attention , most patients hospitalized with COVID-19 have been in general medical units.

              Objective

              To characterize inpatient adaptations to care for non-ICU COVID-19 patients.

              Design

              Cross-sectional survey.

              Setting

              A network of 72 hospital medicine groups at US academic centers.

              Main outcome measures

              COVID-19 testing, approaches to personal protective equipment (PPE), and features of respiratory isolation units (RIUs).

              Results

              Fifty-one of 72 sites responded (71%) between April 3 and April 5, 2020. At the time of our survey, only 15 (30%) reported COVID-19 test results being available in less than 6 hours. Half of sites with PPE data available reported PPE stockpiles of 2 weeks or less. Nearly all sites (90%) reported implementation of RIUs. RIUs primarily utilized attending physicians, with few incorporating residents and none incorporating students. Isolation and room-entry policies focused on grouping care activities and utilizing technology (such as video visits) to communicate with and evaluate patients. The vast majority of sites reported decreases in frequency of in-room encounters across provider or team types. Forty-six percent of respondents reported initially unrecognized non-COVID-19 diagnoses in patients admitted for COVID-19 evaluation; a similar number reported delayed identification of COVID-19 in patients admitted for other reasons.

              Conclusion

              The COVID-19 pandemic has required medical wards to rapidly adapt with expanding use of RIUs and use of technology emerging as critical approaches. Reports of unrecognized or delayed diagnoses highlight how such adaptations may produce potential adverse effects on care.
                Cover page: Hospital Ward Adaptation During the COVID‐19 Pandemic: A National Survey of Academic Medical Centers
                • Article
                • Peer Reviewed
                UC San Francisco Previously Published Works (2020)
                The aim of this study was to identify the combinations of chronic comorbidities associated with length of stay (LOS) among multimorbid medical inpatients.Multinational retrospective cohort of 126,828 medical inpatients with multimorbidity, defined as ≥2 chronic diseases (data collection: 2010-2011). We categorized the chronic diseases into comorbidities using the Clinical Classification Software. We described the 20 combinations of comorbidities with the strongest association with prolonged LOS, defined as longer than or equal to country-specific LOS, and reported the difference in median LOS for those combinations. We also assessed the association between the number of diseases or body systems involved and prolonged LOS.The strongest association with prolonged LOS (odds ratio [OR] 7.25, 95% confidence interval [CI] 6.64-7.91, P < 0.001) and the highest difference in median LOS (13 days, 95% CI 12.8-13.2, P < 0.001) were found for the combination of diseases of white blood cells and hematological malignancy. Other comorbidities found in the 20 top combinations had ORs between 2.37 and 3.65 (all with P < 0.001) and a difference in median LOS of 2 to 5 days (all with P < 0.001), and included mostly neurological disorders and chronic ulcer of skin. Prolonged LOS was associated with the number of chronic diseases and particularly with the number of body systems involved (≥7 body systems: OR 21.50, 95% CI 19.94-23.18, P < 0.001).LOS was strongly associated with specific combinations of comorbidities and particularly with the number of body systems involved. Describing patterns of multimorbidity associated with LOS may help hospitals anticipate resource utilization and judiciously allocate services to shorten LOS.
                  Cover page: Association of patterns of multimorbidity with length of stay
                  • Article
                  • Peer Reviewed
                  UC San Francisco Previously Published Works (2019)
                  BACKGROUND: Multimorbidity is associated with higher healthcare utilization; however, data exploring its association with readmission are scarce. We aimed to investigate which most important patterns of multimorbidity are associated with 30-day readmission. METHODS: We used a multinational retrospective cohort of 126,828 medical inpatients with multimorbidity defined as ≥2 chronic diseases. The primary and secondary outcomes were 30-day potentially avoidable readmission (PAR) and 30-day all-cause readmission (ACR), respectively. Only chronic diseases were included in the analyses. We presented the OR for readmission according to the number of diseases or body systems involved, and the combinations of diseases categories with the highest OR for readmission. RESULTS: Multimorbidity severity, assessed as number of chronic diseases or body systems involved, was strongly associated with PAR, and to a lesser extend with ACR. The strength of association steadily and linearly increased with each additional disease or body system involved. Patients with four body systems involved or nine diseases already had a more than doubled odds for PAR (OR 2.35, 95%CI 2.15-2.57, and OR 2.25, 95%CI 2.05-2.48, respectively). The combinations of diseases categories that were most strongly associated with PAR and ACR were chronic kidney disease with liver disease or chronic ulcer of skin, and hematological malignancy with esophageal disorders or mood disorders, respectively. CONCLUSIONS: Readmission was associated with the number of chronic diseases or body systems involved and with specific combinations of diseases categories. The number of body systems involved may be a particularly interesting measure of the risk for readmission in multimorbid patients.
                    Cover page: Patterns of multimorbidity associated with 30-day readmission: a multinational study.
                    • Article
                    • Peer Reviewed
                    UC San Francisco Previously Published Works (2016)
                    IMPORTANCE: Readmission penalties have catalyzed efforts to improve care transitions, but few programs have incorporated viewpoints of patients and health care professionals to determine readmission preventability or to prioritize opportunities for care improvement. OBJECTIVES: To determine preventability of readmissions and to use these estimates to prioritize areas for improvement. DESIGN, SETTING, AND PARTICIPANTS: An observational study was conducted of 1000 general medicine patients readmitted within 30 days of discharge to 12 US academic medical centers between April 1, 2012, and March 31, 2013. We surveyed patients and physicians, reviewed documentation, and performed 2-physician case review to determine preventability of and factors contributing to readmission. We used bivariable statistics to compare preventable and nonpreventable readmissions, multivariable models to identify factors associated with potential preventability, and baseline risk factor prevalence and adjusted odds ratios (aORs) to determine the proportion of readmissions affected by individual risk factors. MAIN OUTCOME AND MEASURE: Likelihood that a readmission could have been prevented. RESULTS: The study cohort comprised 1000 patients (median age was 55 years). Of these, 269 (26.9%) were considered potentially preventable. In multivariable models, factors most strongly associated with potential preventability included emergency department decision making regarding the readmission (aOR, 9.13; 95% CI, 5.23-15.95), failure to relay important information to outpatient health care professionals (aOR, 4.19; 95% CI, 2.17-8.09), discharge of patients too soon (aOR, 3.88; 95% CI, 2.44-6.17), and lack of discussions about care goals among patients with serious illnesses (aOR, 3.84; 95% CI, 1.39-10.64). The most common factors associated with potentially preventable readmissions included emergency department decision making (affecting 9.0%; 95% CI, 7.1%-10.3%), inability to keep appointments after discharge (affecting 8.3%; 95% CI, 4.1%-12.0%), premature discharge from the hospital (affecting 8.7%; 95% CI, 5.8%-11.3%), and patient lack of awareness of whom to contact after discharge (affecting 6.2%; 95% CI, 3.5%-8.7%). CONCLUSIONS AND RELEVANCE: Approximately one-quarter of readmissions are potentially preventable when assessed using multiple perspectives. High-priority areas for improvement efforts include improved communication among health care teams and between health care professionals and patients, greater attention to patients readiness for discharge, enhanced disease monitoring, and better support for patient self-management.
                      Cover page: Preventability and Causes of Readmissions in a National Cohort of General Medicine Patients.
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