Dataset Information

Hospital length of stay and 30-day readmissions in older people: their association in a 20-year cohort study in Italy.

ABSTRACT:

Background

There are conflicting data on whether hospital length of stay (LOS) reduction affects readmission rates in older adults. We explored 20-year trends of hospital LOS and 30-day rehospitalizations in a cohort of Italian older people, and investigated their association.

Methods

Participants in the Pro.V.A. project (n = 3099) were followed-up from 1996 to 2018. LOS and 30-day rehospitalizations, i.e. new hospitalizations within 30 days from a previous discharge, were obtained from personal interviews and regional registers. Rehospitalizations in the 6 months before death were also assessed. Linear regressions evaluated the associations between LOS and the frequency of 30-day rehospitalizations, adjusting for the mean age of the cohort within each year.

Results

Over 20 years, 2320 (74.9%) participants were hospitalized. Mean LOS gradually decreased from 17.3 days in 1996 to 11.3 days in 2018, while 30-day rehospitalization rates increased from 6.6% in 1996 to 13.6% in 2018. LOS was inversely associated with 30-day rehospitalizations frequency over time (β = -2.33, p = 0.01), similarly in men and women. A total of 1506 individuals was hospitalized within 6 months before death. The frequency of 30-day readmissions at the end of life increased from 1.4% in 1997 to 8.3% in 2017 and was associated with mean LOS (β = -1.17, p = 0.03).

Conclusions

The gradual LOS reduction observed in the latter decades is associated with higher 30-day readmission rates in older patients in Italy. This suggests that a careful pre-discharge assessment is warranted in older people, and that community healthcare services should be improved to reduce the risk of readmission.

SUBMITTER: Trevisan C

PROVIDER: S-EPMC10029164 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Hospital length of stay and 30-day readmissions in older people: their association in a 20-year cohort study in Italy.

Trevisan Caterina C Noale Marianna M Zatti Giancarlo G Vetrano Davide Liborio DL Maggi Stefania S Sergi Giuseppe G

BMC geriatrics 20230321 1

<h4>Background</h4>There are conflicting data on whether hospital length of stay (LOS) reduction affects readmission rates in older adults. We explored 20-year trends of hospital LOS and 30-day rehospitalizations in a cohort of Italian older people, and investigated their association.<h4>Methods</h4>Participants in the Pro.V.A. project (n = 3099) were followed-up from 1996 to 2018. LOS and 30-day rehospitalizations, i.e. new hospitalizations within 30 days from a previous discharge, were obtaine ...[more]

PMID: 36941535

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Project description:BackgroundAlthough early follow-up after discharge from an index admission (IA) has been postulated to reduce 30-day readmission, some researchers have questioned its efficacy, which may depend upon the likelihood of readmission at a given time and the health conditions contributing to readmissions.ObjectiveTo investigate the relationship between post-discharge services utilization of different types and at different timepoints and unplanned 30-day readmission, length of stay (LOS), and inpatient costs.Design, setting, and participantsThe study sample included 583,199 all-cause IAs among 2014 Medicare fee-for-service beneficiaries that met IA inclusion criteria.Main measuresThe outcomes were probability of 30-day readmission, average readmission LOS per IA discharge, and average readmission inpatient cost per IA discharge. The primary independent variables were 7 post-discharge health services (institutional outpatient, primary care physician, specialist, non-physician provider, emergency department (ED), home health care, skilled nursing facility) utilized within 7 days, 14 days, and 30 days of IA discharge. To examine the association with post-discharge services utilization, we employed multivariable logistic regressions for 30-day readmissions and two-part models for LOS and inpatient costs.Key resultsAmong all IA discharges, the probability of unplanned 30-day readmission was 0.1176, the average readmission LOS per discharge was 0.67 days, and the average inpatient cost per discharge was $5648. Institutional outpatient, home health care, and primary care physician visits at all timepoints were associated with decreased readmission and resource utilization. Conversely, 7-day and 14-day specialist visits were positively associated with all three outcomes, while 30-day visits were negatively associated. ED visits were strongly associated with increases in all three outcomes at all timepoints.ConclusionPost-discharge services of different types and at different timepoints have varying impacts on 30-day readmission, LOS, and costs. These impacts should be considered when coordinating post-discharge follow-up, and their drivers should be further explored to reduce readmission throughout the health care system.

Project description:IntroductionNew financial incentives, such as reduced Medicare reimbursements, have led hospitals to closely monitor their readmission rates and initiate efforts aimed at reducing them. In this context, many surgical departments participate in the American College of Surgeons National Surgical Quality Improvement Program (NSQIP), which collects detailed demographic, laboratory, clinical, procedure and perioperative occurrence data. The availability of such data enables the development of data science methods which predict readmissions and, as done in this paper, offer specific recommendations aimed at preventing readmissions.Materials and methodsThis study leverages NSQIP data for 722,101 surgeries to develop predictive and prescriptive models, predicting readmissions and offering real-time, personalized treatment recommendations for surgical patients during their hospital stay, aimed at reducing the risk of a 30-day readmission. We applied a variety of classification methods to predict 30-day readmissions and developed two prescriptive methods to recommend pre-operative blood transfusions to increase the patient's hematocrit with the objective of preventing readmissions. The effect of these interventions was evaluated using several predictive models.ResultsPredictions of 30-day readmissions based on the entire collection of NSQIP variables achieve an out-of-sample accuracy of 87% (Area Under the Curve-AUC). Predictions based only on pre-operative variables have an accuracy of 74% AUC, out-of-sample. Personalized interventions, in the form of pre-operative blood transfusions identified by the prescriptive methods, reduce readmissions by 12%, on average, for patients considered as candidates for pre-operative transfusion (pre-operative hematoctic <30). The prediction accuracy of the proposed models exceeds results in the literature.ConclusionsThis study is among the first to develop a methodology for making specific, data-driven, personalized treatment recommendations to reduce the 30-day readmission rate. The reported predicted reduction in readmissions can lead to more than $20 million in savings in the U.S. annually.

Dataset Information

Hospital length of stay and 30-day readmissions in older people: their association in a 20-year cohort study in Italy.

Background

Methods

Results

Conclusions

Publications

Hospital length of stay and 30-day readmissions in older people: their association in a 20-year cohort study in Italy.

Similar Datasets

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