Dataset Information

Time-to-readmission and Mortality After High-risk Surgery.

ABSTRACT:

Objectives

To determine if mortality varies by time-to-readmission (TTR).

Background

Although readmissions reduction is a national health care priority, little progress has been made toward understanding why only some readmissions lead to adverse outcomes.

Methods

In this retrospective cross-sectional cohort analysis, we used 2005-2009 Medicare data on beneficiaries undergoing colectomy, lung resection, or coronary artery bypass grafting (n = 1,033,255) to created 5 TTR groups: no 30-day readmission (n = 897,510), less than 6 days (n = 44,361), 6 to 10 days (n = 31,018), 11 to 15 days (n = 20,797), 16 to 20 days (n = 15,483), or more than 21 days (n = 24,086). Our analyses evaluated TTR groups for differences in risk-adjusted mortality (30, 60, and 90 days) and complications during the index admission.

Results

Increasing TTR was associated with a stepwise decline in mortality. For example, 90-day mortality rates in patients readmitted between 1 and 5 days, 6 and 10 days, and 11 and 15 days were 12.6%, 11.4%, and 10.4%, respectively (P < 0.001). Compared to nonreadmitted patients, the adjusted odds ratios (and 95% confidence intervals) were 4.88 (4.72-5.05), 4.20 (4.03-4.37), and 3.81 (3.63-3.99), respectively. Similar patterns were observed for 30- and 60-day mortality. There were no sizable differences in complication rates for patients readmitted within 5 days versus after 21 days (24.8% vs 26.2%, P < 0.001).

Conclusions

Surgical readmissions within 10 days of discharge are disproportionately common and associated with increased mortality independent of index complications. These findings suggest 10-day readmissions should be specially targeted by quality improvement efforts.

SUBMITTER: Gonzalez AA

PROVIDER: S-EPMC4362781 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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Publications

Time-to-readmission and Mortality After High-risk Surgery.

Gonzalez Andrew A AA Abdelsattar Zaid M ZM Dimick Justin B JB Dev Shantanu S Birkmeyer John D JD Ghaferi Amir A AA

Annals of surgery 20150701 1

<h4>Objectives</h4>To determine if mortality varies by time-to-readmission (TTR).<h4>Background</h4>Although readmissions reduction is a national health care priority, little progress has been made toward understanding why only some readmissions lead to adverse outcomes.<h4>Methods</h4>In this retrospective cross-sectional cohort analysis, we used 2005-2009 Medicare data on beneficiaries undergoing colectomy, lung resection, or coronary artery bypass grafting (n = 1,033,255) to created 5 TTR gro ...[more]

PMID: 25211274

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Project description:BackgroundHospital readmissions are common after major surgery, although it is unknown whether patients achieve improved outcomes when they are readmitted to, and receive care at, the index hospital where their surgical procedure was done. We examined the association between readmission destination and mortality risk in the USA in Medicare beneficiaries after a range of common operations.MethodsBy use of claims data from Medicare beneficiaries in the USA between Jan 1, 2001, and Nov 15, 2011, we assessed patients who needed hospital readmission within 30 days after open abdominal aortic aneurysm repair, infrainguinal arterial bypass, aortobifemoral bypass, coronary artery bypass surgery, oesophagectomy, colectomy, pancreatectomy, cholecystectomy, ventral hernia repair, craniotomy, hip replacement, or knee replacement. We used logistic regression models incorporating inverse probability weighting and instrumental variable analysis to measure associations between readmission destination (index vs non-index hospital) and risk of 90 day mortality for patients who underwent surgery who needed hospital readmission.Findings9,440,503 patients underwent one of 12 major operations, and the number of patients readmitted or transferred back to the index hospital where their operation was done varied from 186,336 (65·8%) of 283,131 patients who were readmitted after coronary artery bypass grafting, to 142,142 (83·2%) of 170,789 patients who were readmitted after colectomy. Readmission was more likely to be to the index hospital than to a non-index hospital if the readmission was for a surgical complication (189,384 [23%] of 834,070 patients readmitted to index hospital vs 36,792 [13%] of 276,976 patients readmitted non-index hospital, p<0·0001). Readmission to the index hospital was associated with a 26% lower risk of 90 day mortality than was readmission to a non-index hospital, with inverse probability weighting used to control for selection bias (odds ratio [OR] 0·74, 95% CI 0·66-0·83). This effect was significant (p<0·0001) for all procedures in inverse probability-weighted models, and was largest for patients who were readmitted after pancreatectomy (OR 0·56, 95% CI 0·45-0·69) and aortobifemoral bypass (OR 0·69, 95% CI 0·61-0·77). By use of hospital-level variation among regional index hospital readmission rates as an instrument, instrumental variable analysis showed that the patients with the highest probability of returning to the index hospital had 8% lower risk of mortality (OR 0·92 95% CI 0·91-0·94) than did patients who were less likely to be readmitted to the index hospital.InterpretationIn the USA, patients who are readmitted to hospital after various major operations consistently achieve improved survival if they return to the hospital where their surgery took place. These findings might have important implications for cost-effectiveness-driven regional centralisation of surgical care.FundingNone.

Project description:There were numerous efforts in the United States during the previous decade to concentrate selected surgical procedures in high-volume hospitals. It remains unknown whether referral patterns for high-risk surgery have changed as a result and how operative mortality has been affected.We used national Medicare data to study patients undergoing one of eight different cancer and cardiovascular operations from 1999 through 2008. For each procedure, we examined trends in hospital volume and market concentration, defined as the proportion of Medicare patients undergoing surgery in the top decile of hospitals by volume per year. We used regression-based techniques to assess the effects of volume and market concentration on mortality over time, adjusting for case mix.Median hospital volumes of four cancer resections (lung, esophagus, pancreas, and bladder) and of repair of abdominal aortic aneurysm (AAA) rose substantially. Depending on the procedure, higher hospital volumes were attributable to an increasing number of cases nationwide, an increasing market concentration, or both. Hospital volumes rose slightly for aortic-valve replacement but fell for coronary-artery bypass grafting and carotid endarterectomy. Operative mortality declined for all eight procedures, ranging from a relative decline of 8% for carotid endarterectomy (1.3% mortality in 1999 and 1.2% in 2008) to 36% for AAA repair (4.4% in 1999 and 2.8% in 2008). Higher hospital volumes explained a large portion of the decline in mortality for pancreatectomy (67% of the decline), cystectomy (37%), and esophagectomy (32%), but not for the other procedures.Operative mortality with high-risk surgery fell substantially during the previous decade. Although increased market concentration and hospital volume have contributed to declining mortality with some high-risk cancer operations, declines in mortality with other procedures are largely attributable to other factors. (Funded by the National Institute on Aging.).

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Project description:BACKGROUND:High-risk patients are most vulnerable during transitions of care. Due to the high burden of resource allocation for such patients, we propose that segmentation of this heterogeneous population into distinct subgroups will enable improved healthcare resource planning. In this study, we segmented a high-risk population with the aim to identify and characterize a patient subgroup with the highest 30-day and 90-day hospital readmission and mortality. METHODS:We extracted data from our transitional care program (TCP), a Hospital-to-Home program launched by the Singapore Ministry of Health, from June to November 2018. Latent class analysis (LCA) was used to determine the optimal number and characteristics of latent subgroups, assessed based on model fit and clinical interpretability. Regression analysis was performed to assess the association of class membership on 30- and 90-day all-cause readmission and mortality. RESULTS:Among 752 patients, a 3-class best fit model was selected: Class 1 "Frail, cognitively impaired and physically dependent", Class 2 "Pre-frail, but largely physically independent" and Class 3 "Physically independent". The 3 classes have distinct demographics, medical and socioeconomic characteristics (p < 0.05), 30- and 90-day readmission (p < 0.05) and mortality (p < 0.01). Class 1 patients have the highest age-adjusted 90-day readmission (OR = 2.04, 95%CI: 1.21-3.46, p = 0.008), 30- (OR = 6.92, 95%CI: 1.76-27.21, p = 0.006) and 90-day mortality (OR = 11.51, 95%CI: 4.57-29.02, p < 0.001). CONCLUSIONS:We identified a subgroup with the highest readmission and mortality risk amongst high-risk patients. We also found a lack of interventions in our TCP that specifically addresses increased frailty and poor cognition, which are prominent features in this subgroup. These findings will help to inform future program modifications and strengthen existing transitional healthcare structures currently utilized in this patient cohort.

Dataset Information

Time-to-readmission and Mortality After High-risk Surgery.

Objectives

Background

Methods

Results

Conclusions

Publications

Time-to-readmission and Mortality After High-risk Surgery.

Similar Datasets

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