Dataset Information

Incidence of Avoidable 30-Day Readmissions Following Hospitalization for Community-Acquired Pneumonia in France.

ABSTRACT:

Importance

Rates of 30-day readmissions following hospitalization for pneumonia are used to publicly report on hospital performance and to set financial penalties for the worst-performing hospitals. However, the rate of avoidable readmission following hospitalization for pneumonia is undefined.

Objective

To assess how often 30-day readmissions following hospitalization for community-acquired pneumonia (CAP) are avoidable.

Design, setting, and participants

This cohort study analyzed the results of an independent review of readmissions following hospitalization for CAP within 30 days among patients discharged from 2 large hospitals in France in 2014. Structured clinical records including clinical information (ie, baseline characteristics, physical examination, laboratory findings, x-ray or computed tomography scan findings, discharge plan, and treatments) for both index and readmission stays were independently reviewed by 4 certified board physicians. All consecutive adult patients hospitalized in 2014 with a diagnosis of CAP in our 2 eligible hospitals were eligible. All analyses presented were performed in March 2021.

Main outcomes and measures

Avoidable readmission within 30 days of discharge from index hospitalization. The likelihood that a readmission was avoidable was quantified using latent class analysis based on the independent reviews. A readmission was considered avoidable if Bayes posterior probability exceeded 50%.

Results

The total analytical sample consisted of 1150 index hospital stays with a diagnosis of CAP, which included 651 (56.6%) male patients. The median (IQR) age for all patients was 77.8 (IQR, 62.7-86.4) years. Out of the 1150 index hospital stays, 98 patients (8.5%) died in hospital, and 108 (9.4%) unplanned readmissions were found. Overall, 15 readmissions had a posterior probability of avoidability exceeding 0.50 (13.9% of the 108 unplanned readmissions; 95% CI, 8.0%-21.9%). The median (IQR) delay between the hospital discharge index and readmission was considerably shorter when readmission was deemed avoidable (4 [6-21] days vs 12 [2-18] days; P = .02).

Conclusions and relevance

Only a small number of readmissions following hospitalization for CAP were deemed avoidable, comprising less than 10% of all readmissions. Shorter time interval between hospitalization discharge and readmission was associated with avoidability.

SUBMITTER: Boussat B

PROVIDER: S-EPMC8994128 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Incidence of Avoidable 30-Day Readmissions Following Hospitalization for Community-Acquired Pneumonia in France.

Boussat Bastien B Cazzorla Fabiana F Le Marechal Marion M Pavese Patricia P Mounayar Anne-Laure AL Sellier Elodie E Gaillat Jacques J Camara Boubou B Degano Bruno B Maillet Mylène M Courtois Xavier X Bouisse Magali M Seigneurin Arnaud A François Patrice P

JAMA network open 20220401 4

<h4>Importance</h4>Rates of 30-day readmissions following hospitalization for pneumonia are used to publicly report on hospital performance and to set financial penalties for the worst-performing hospitals. However, the rate of avoidable readmission following hospitalization for pneumonia is undefined.<h4>Objective</h4>To assess how often 30-day readmissions following hospitalization for community-acquired pneumonia (CAP) are avoidable.<h4>Design, setting, and participants</h4>This cohort study ...[more]

PMID: 35394509

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Project description:ImportanceTo better guide strategies intended to reduce high rates of 30-day readmission after hospitalization for heart failure (HF), acute myocardial infarction (MI), or pneumonia, further information is needed about readmission diagnoses, readmission timing, and the relationship of both to patient age, sex, and race.ObjectiveTo examine readmission diagnoses and timing among Medicare beneficiaries readmitted within 30 days after hospitalization for HF, acute MI, or pneumonia.Design, setting, and patientsWe analyzed 2007-2009 Medicare fee-for-service claims data to identify patterns of 30-day readmission by patient demographic characteristics and time after hospitalization for HF, acute MI, or pneumonia. Readmission diagnoses were categorized using an aggregated version of the Centers for Medicare & Medicaid Services' Condition Categories. Readmission timing was determined by day after discharge.Main outcome measuresWe examined the percentage of 30-day readmissions occurring on each day (0-30) after discharge; the most common readmission diagnoses occurring during cumulative periods (days 0-3, 0-7, 0-15, and 0-30) and consecutive periods (days 0-3, 4-7, 8-15, and 16-30) after hospitalization; median time to readmission for common readmission diagnoses; and the relationship between patient demographic characteristics and readmission diagnoses and timing.ResultsFrom 2007 through 2009, we identified 329,308 30-day readmissions after 1,330,157 HF hospitalizations (24.8% readmitted), 108,992 30-day readmissions after 548,834 acute MI hospitalizations (19.9% readmitted), and 214,239 30-day readmissions after 1,168,624 pneumonia hospitalizations (18.3% readmitted). The proportion of patients readmitted for the same condition was 35.2% after the index HF hospitalization, 10.0% after the index acute MI hospitalization, and 22.4% after the index pneumonia hospitalization. Of all readmissions within 30 days of hospitalization, the majority occurred within 15 days of hospitalization: 61.0%, HF cohort; 67.6%, acute MI cohort; and 62.6%, pneumonia cohort. The diverse spectrum of readmission diagnoses was largely similar in both cumulative and consecutive periods after discharge. Median time to 30-day readmission was 12 days for patients initially hospitalized for HF, 10 days for patients initially hospitalized for acute MI, and 12 days for patients initially hospitalized for pneumonia and was comparable across common readmission diagnoses. Neither readmission diagnoses nor timing substantively varied by age, sex, or race.Conclusion and relevanceAmong Medicare fee-for-service beneficiaries hospitalized for HF, acute MI, or pneumonia, 30-day readmissions were frequent throughout the month after hospitalization and resulted from a similar spectrum of readmission diagnoses regardless of age, sex, race, or time after discharge.

Project description:BackgroundReadmissions after hospitalization for pneumonia are common, but the few risk-prediction models have poor to modest predictive ability. Data routinely collected in the electronic health record (EHR) may improve prediction.ObjectiveTo develop pneumonia-specific readmission risk-prediction models using EHR data from the first day and from the entire hospital stay ("full stay").DesignObservational cohort study using stepwise-backward selection and cross-validation.SubjectsConsecutive pneumonia hospitalizations from 6 diverse hospitals in north Texas from 2009-2010.MeasuresAll-cause nonelective 30-day readmissions, ascertained from 75 regional hospitals.ResultsOf 1463 patients, 13.6% were readmitted. The first-day pneumonia-specific model included sociodemographic factors, prior hospitalizations, thrombocytosis, and a modified pneumonia severity index; the full-stay model included disposition status, vital sign instabilities on discharge, and an updated pneumonia severity index calculated using values from the day of discharge as additional predictors. The full-stay pneumonia-specific model outperformed the first-day model (C statistic 0.731 vs 0.695; P = 0.02; net reclassification index = 0.08). Compared to a validated multi-condition readmission model, the Centers for Medicare and Medicaid Services pneumonia model, and 2 commonly used pneumonia severity of illness scores, the full-stay pneumonia-specific model had better discrimination (C statistic range 0.604-0.681; P < 0.01 for all comparisons), predicted a broader range of risk, and better reclassified individuals by their true risk (net reclassification index range, 0.09-0.18).ConclusionsEHR data collected from the entire hospitalization can accurately predict readmission risk among patients hospitalized for pneumonia. This approach outperforms a first-day pneumonia-specific model, the Centers for Medicare and Medicaid Services pneumonia model, and 2 commonly used pneumonia severity of illness scores. Journal of Hospital Medicine 2017;12:209-216.

Project description:ImportanceIdentification 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.ObjectiveTo externally validate the HOSPITAL score in an international multicenter study to assess its generalizability.Design, setting, and participantsInternational 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.ExposuresThe 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 measures30-day potentially avoidable readmission to the index hospital using the SQLape algorithm.ResultsOverall, 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 relevanceThe 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.

Project description:ImportanceWith the approval of transcatheter aortic valve replacement (TAVR) for patients with severe symptomatic aortic stenosis at intermediate surgical risk, TAVR volume is projected to increase exponentially in the United States. The 30-day readmission rate for TAVR was recently reported at 17.9%. The association between institutional TAVR volume and the 30-day readmission metric has not been examined.ObjectiveTo assess the association between hospital TAVR volume and 30-day readmission.Design, setting, and participantsIn this observational study, we used the 2014 Nationwide Readmissions Database to identify hospitals with established TAVR programs (performing at least 5 TAVRs in the first quarter of 2014). Based on annual TAVR volume, hospitals were classified as low (<50), medium (≥50 to <100), and high (≥100) volume. Rates, causes, and costs of 30-day readmissions were compared between low-, medium-, and high-volume hospitals. Data were analyzed from November to December 2016.ExposureTranscatheter aortic valve replacement.Main outcomes and measuresThirty-day readmissions.ResultsOf 129 hospitals included in this study, 20 (15.5%) were categorized as low volume, 47 (36.4%) as medium volume, and 62 (48.1%) as high volume. Of 16 252 index TAVR procedures, 663 (4.1%), 3067 (18.9%), and 12 522 (77.0%) were performed at low-, medium-, and high-volume hospitals, respectively. Thirty-day readmission rates were significantly lower in high-volume compared with medium-volume (adjusted odds ratio, 0.76; 95% CI, 0.68-0.85; P < .001) and low-volume (adjusted odds ratio, 0.75; 95% CI, 0.60-0.92; P = .007) hospitals. Noncardiac readmissions were more common in low-volume hospitals (65.6% vs 60.6% in high-volume hospitals), whereas cardiac readmissions were more common in high-volume hospitals (39.4% vs 34.4% in low-volume hospitals). There were no significant differences in length of stay and costs per readmission among the 3 groups (mean [SD], 5.5 [5.0] days vs 5.9 [7.5] days vs 6.0 [5.8] days; P = .74, and $13 886 [18 333] vs $14 135 [17 939] vs $13 432 [15 725]; P = .63, respectively).Conclusions and relevanceWe report for the first time, to our knowledge, an inverse association between hospital TAVR volume and 30-day readmissions. Lower readmission at higher-volume hospitals was associated with significantly lower cost to the health care system.

Dataset Information

Incidence of Avoidable 30-Day Readmissions Following Hospitalization for Community-Acquired Pneumonia in France.

Importance

Objective

Design, setting, and participants

Main outcomes and measures

Results

Conclusions and relevance

Publications

Incidence of Avoidable 30-Day Readmissions Following Hospitalization for Community-Acquired Pneumonia in France.

Similar Datasets

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