Hospital Performance Measures and 30-day Readmission Rates

Stefan, Mihaela; Pekow, Penelope S.; Nsa, Wato; Priya, Aruna; Miller, Lauren E.; Bratzler, Dale W.; Rothberg, Michael B.; Goldberg, Robert J.; Baus, Kristie; Lindenauer, Peter K.

doi:10.1007/s11606-012-2229-8

Cited by 79 publications

(64 citation statements)

References 32 publications

(34 reference statements)

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“…In addition, our riskstandardization models differed from those used by CMS (14) by inclusion of markers of socioeconomic status and markers of severity of acute illness, as well as methods for identifying chronic comorbidities that could affect our observed associations. However, readmission rates in our study were similar to reports in Medicare data (21,23,32,33), and use of risk-adjustment models more similar to CMS did not substantially alter our findings.…”

Section: Limitationssupporting

confidence: 85%

Association of Early Do-Not-Resuscitate Orders with Unplanned Readmissions among Patients Hospitalized for Pneumonia

et al. 2017

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Section: Limitationssupporting

confidence: 85%

Association of Early Do-Not-Resuscitate Orders with Unplanned Readmissions among Patients Hospitalized for Pneumonia

et al. 2017

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“…35 Reducing the occurrence of readmissions has been difficult to achieve. 36 To our knowledge, this is one the first studies that suggests a beneficial association between HIE system usage and hospital readmissions in the USA. Until now, the studies that have been published about HIE interventions have not reported any association with reductions in readmissions, 15 and in fact, only a few studies have shown that hospitalizations, in general, may be reduced with HIE.…”

Section: Discussionmentioning

confidence: 85%

The potential for community-based health information exchange systems to reduce hospital readmissions

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Kern

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et al. 2014

Journal of the American Medical Informatics Association

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Background Hospital readmissions are common, costly, and offer opportunities for utilization reduction. Electronic health information exchange (HIE) systems may help prevent readmissions by improving access to clinical data by ambulatory providers after discharge from the hospital. Objective We sought to determine the association between HIE system usage and 30-day same-cause hospital readmissions among patients who consented and participated in an operational community-wide HIE during a 6-month period in 2009–2010. Methods We identified a retrospective cohort of hospital readmissions among adult patients in the Rochester, New York area. We analyzed claims files from two health plans that insure more than 60% of the area population. To be included in the dataset, patients needed to be continuously enrolled in the health plan with at least one encounter with a participating provider in the 6 months following consent to be included in the HIE system. Each patient appeared in the dataset only once and each discharge could be followed for at least 30 days. Results We found that accessing patient information in the HIE system in the 30 days after discharge was associated with a 57% lower adjusted odds of readmission (OR 0.43; 95% CI 0.27 to 0.70). The estimated annual savings in the sample from averted readmissions associated with HIE usage was $605 000. Conclusions These findings indicate that usage of an electronic HIE system in the ambulatory setting within 30 days after hospital discharge may effectively prevent hospital readmissions, thereby supporting the need for ongoing HIE efforts.

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“…We also structured our model to account for the clustering of hospitals within states. 28,29 Finally, because we counted the number of consulting specialties, our results likely represent a lower bound, as multiple consultations may occur within a specialty (e.g., consulting both an interventional cardiologist and an electrophysiologist), but we had no way to accurately distinguish between cross-coverage within a new specialty and additional consultations. Further, we did not use evaluation and management codes for consultation, as these expired in 2009 and were used inconsistently in different regions and specialties, reflecting variation in billing practices rather than variation in consultation use.…”

Section: Discussionmentioning

confidence: 99%

Variation in Inpatient Consultation Among Older Adults in the United States

et al. 2015

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BACKGROUND: Differences among hospitals in the use of inpatient consultation may contribute to variation in outcomes and costs for hospitalized patients, but basic epidemiologic data on consultations nationally are lacking. OBJECTIVE: The purpose of the study was to identify physician, hospital, and geographic factors that explain variation in rates of inpatient consultation. The primary outcome measured was number of consultations conducted during the hospitalization, summarized at the hospital level as the number of consultations per 1,000 Medicare admissions, or Bconsultation density.K EY RESULTS: Consultations occurred 2.6 times per admission on average. Among non-critical access hospitals, use of consultation varied 3.6-fold across quintiles of hospitals (933 versus 3,390 consultations per 1,000 admissions, lowest versus highest quintiles, p<0.001). Sicker patients received greater intensity of consultation (rate ratio [RR] 1.18, 95 % CI 1.17-1.18 for patients admitted to ICU; and RR 1.19, 95 % CI 1.18-1.20 for patients who died). However, even after controlling for patient-level factors, hospital characteristics also predicted differences in rates of consultation. For example, hospital size (large versus small, RR 1.31, 95 % CI 1.25-1.37), rural location (rural versus urban, RR 0.78, CI 95 % 0.76-0.80), ownership status (public versus not-for-profit, RR 0.94, 95 % CI 0.91-0.97), and geographic quadrant (Northeast versus West, RR 1.17, 95 % CI 1.12-1.21) all influenced the intensity of consultation use. CONCLUSIONS: Hospitals exhibit marked variation in the number of consultations per admission in ways not fully explained by patient characteristics. Hospital Bconsultation density^may constitute an important focus for monitoring resource use for hospitals or health systems.

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Hospital Performance Measures and 30-day Readmission Rates

Abstract: Hospitals with greater adherence to recommended care processes did not achieve meaningfully better 30-day hospital readmission rates compared to those with lower levels of performance.

Cited by 79 publications

References 32 publications

Association of Early Do-Not-Resuscitate Orders with Unplanned Readmissions among Patients Hospitalized for Pneumonia

Association of Early Do-Not-Resuscitate Orders with Unplanned Readmissions among Patients Hospitalized for Pneumonia

The potential for community-based health information exchange systems to reduce hospital readmissions

Variation in Inpatient Consultation Among Older Adults in the United States

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