Dataset Information

Are Readmissions After THA Preventable?

ABSTRACT:

Background

Readmissions after total joint arthroplasty have become a key quality measure in elective surgery in the United States. The Affordable Care Act includes the Hospital Readmission Reduction Program, which calls for reduced payments to hospitals with excessive readmissions. This policy uses a method to determine excess readmission ratios and calculate readmission payment adjustments to hospitals, however, it is unclear whether readmission rates are an effective quality metric. The reasons or conditions associated with readmission after elective THA have been well established but the extent to which readmissions can be prevented after THA remains unclear.

Questions/purposes

(1) Are unplanned readmissions after THA associated with orthopaedic or medical causes? (2) Are these readmissions preventable? (3) When during the course of aftercare are orthopaedic versus medical readmissions more likely to occur?

Methods

We retrospectively evaluated all 1096 elective THAs for osteoarthritis performed between January 1, 2011 and June 30, 2014 at a major academic medical center. Of those, 69 patients (6%) who met inclusion criteria were readmitted in our healthcare system within 90 days of discharge after the index procedure during the study period. Fifty patients were readmitted within 30 days of discharge after the index procedure (5%). We defined a readmission as any unplanned inpatient or observation status admission to the hospital spanning at least one midnight. A panel of physicians not involved in the care of these patients used available criteria and existing consensus guidelines to evaluate the medical records, radiographs, and operative reports to identify whether the underlying reason for readmission was orthopaedic versus medical. They subsequently were classified as either nonpreventable or potentially preventable readmissions, based on any care that may have occurred during the index hospitalization. To make such determinations, consensus specialty society guidelines were used whenever possible for each readmission diagnosis.

Results

A total of 50 of 1096 patients (5% of those who underwent THA during the period in question) were readmitted within 30 days and 69 of 1096 (6%) were readmitted within 90 days of their index procedures. Thirty-one patients were readmitted for orthopaedic reasons (31/69; 45%) and 38 of 69 were readmitted for medical reasons (55%). Three readmissions (three of 69; 4%) were identified as potentially preventable. Of these potentially preventable readmissions, one was orthopaedic (hip dislocation) and two were medical. Thirty-day readmissions were more likely to be orthopaedic than 90-day readmissions (odds ratio, 4.06; 95% CI, 1.18-13.96; p = 0.026).

Conclusions

Using a panel of expert reviewers, available existing criteria, and consensus methodology, it appears only a small percentage of readmissions after THA are potentially preventable. Orthopaedic readmissions occur earlier during the postoperative course. Currently, existing policies and readmission penalties may not serve as valuable external quality metrics. The readmission rates in our study may represent the threshold for expected readmission rates after THA. Future studies should enroll larger numbers of patients and have independent review panels in efforts to refine criteria for what constitutes preventable readmissions.

Level of evidence

Level III, therapeutic study.

SUBMITTER: Weinberg DS

PROVIDER: S-EPMC5384913 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ObjectiveTo assess both the feasibility and potential impact of predicting preventable hospital readmissions using causal machine learning applied to data from the implementation of a readmissions prevention intervention (the Transitions Program).Data sourcesElectronic health records maintained by Kaiser Permanente Northern California (KPNC).Study designRetrospective causal forest analysis of postdischarge outcomes among KPNC inpatients. Using data from both before and after implementation, we apply causal forests to estimate individual-level treatment effects of the Transitions Program intervention on 30-day readmission. These estimates are used to characterize treatment effect heterogeneity and to assess the notional impacts of alternative targeting strategies in terms of the number of readmissions prevented.Data collection1 539 285 index hospitalizations meeting the inclusion criteria and occurring between June 2010 and December 2018 at 21 KPNC hospitals.Principal findingsThere appears to be substantial heterogeneity in patients' responses to the intervention (omnibus test for heterogeneity p = 2.23 × 10-7 ), particularly across levels of predicted risk. Notably, predicted treatment effects become more positive as predicted risk increases; patients at somewhat lower risk appear to have the largest predicted effects. Moreover, these estimates appear to be well calibrated, yielding the same estimate of annual readmissions prevented in the actual treatment subgroup (1246, 95% confidence interval [CI] 1110-1381) as did a formal evaluation of the Transitions Program (1210, 95% CI 990-1430). Estimates of the impacts of alternative targeting strategies suggest that as many as 4458 (95% CI 3925-4990) readmissions could be prevented annually, while decreasing the number needed to treat from 33 to 23, by targeting patients with the largest predicted effects rather than those at highest risk.ConclusionsCausal machine learning can be used to identify preventable hospital readmissions, if the requisite interventional data are available. Moreover, our results suggest a mismatch between risk and treatment effects.

Project description:ObjectivesApproximately 14% of Medicare beneficiaries are readmitted to a hospital within 30 days of home health care admission. Individuals with dementia account for 30% of all home health care admissions and are at high risk for readmission. Our primary objective was to determine the association between dementia severity at admission to home health care and 30-day potentially preventable readmissions (PPR) during home health care. A secondary objective was to develop a dementia severity scale from Outcome and Assessment Information Set (OASIS) items based on the Functional Assessment Staging Tool (FAST).DesignRetrospective cohort study.Setting and participantsHome health care; 126,292 Medicare beneficiaries receiving home health care (July 1, 2013-June 1, 2015) diagnosed with dementia (ICD-9 codes).Measures30-day PPR during home health care. Dementia severity categorized into 6 levels (nonaffected to severe).ResultsThe overall rate of 30-day PPR was 7.6% [95% confidence interval (CI) 7.4, 7.7] but varied by patient and health care utilization characteristics. After adjusting for sociodemographic and clinical characteristics, the odds ratio (OR) for dementia severity category 6 was 1.37 (95% CI 1.29, 1.46) and the OR for category 7 was 1.94 (95% CI 1.64, 2.31) as compared to dementia severity category 1/2.Conclusions and implicationsDementia severity in the later stages is associated with increased risk for potentially preventable readmissions. Our findings suggest that individuals admitted to home health during the later stages of Alzheimer's disease and related dementias may require greater supports and specialized care to minimize negative outcomes such as readmissions. Development of a dementia severity scale based on OASIS items and the FAST is feasible. Future research is needed to determine effective strategies for decreasing potentially preventable readmissions of individuals with severe dementia who receive home health care. Future research is also needed to validate the proposed dementia severity categories used in this study.

Project description:BACKGROUND:Care transitions programs have been shown to reduce hospital readmissions. OBJECTIVES:The main objective of this study was to evaluate effects of the Mayo Clinic Care Transitions (MCCTs) Program on potentially preventable and nonpreventable 30-day unplanned readmissions among high-risk elders. RESEARCH DESIGN:This was a retrospective cohort study of patients enrolled in MCCT following hospitalization and propensity score-matched controls receiving usual primary care. SUBJECTS:The subjects were primary care patients, who were 60 years or older, at high-risk for readmission, and hospitalized for any cause between January 1, 2011 and June 30, 2013. MEASURES:Hospital readmission within 30 days. The 3M algorithm was used to identify potentially preventable readmissions. Readmissions for ambulatory care sensitive conditions, a subset of preventable readmissions identified by the 3M algorithm, were also assessed. RESULTS:The study cohort included 365 pairs of MCCT enrollees and propensity score-matched controls. Patients were similar in age (mean 83?y) and other baseline demographic and clinical characteristics, including reason for index hospitalization. MCCT enrollees had a significantly lower all-cause readmission rate [12.4% (95% confidence interval: CI, 8.9-15.7) vs. 20.1% (15.8-24.1); P=0.004] resulting from a decrease in potentially preventable readmissions [8.4% (95% CI, 5.5-11.3) vs. 14.3% (95% CI, 10.5-17.9); P=0.01]. Few potentially preventable readmissions were for ambulatory care sensitive conditions (6.7% vs. 12.0%). The rates of nonpotentially preventable readmissions were similar [4.3% (95% CI, 2.2-6.5) vs. 6.7% (95% CI, 4.0-9.4); P=0.16]. Potentially preventable readmissions were reduced by 44% (hazard ratio, 0.56; 95% CI, 0.36-0.88; P=0.01) with no change in other readmissions. CONCLUSIONS:The MCCT significantly reduces preventable readmissions, suggesting that access to multidisciplinary care can reduce readmissions and improve outcomes for high-risk elders.

Project description:ImportanceRehospitalization after major surgery is common and represents a significant cost to the health care system. Little is known regarding the causes of these readmissions and the degree to which they may be preventable.ObjectiveTo evaluate the degree to which readmissions after major surgery are potentially preventable.Design, setting, and participantsThis retrospective cohort study used a weighted sample of 1 937 354 patients from the 2017 National Readmissions Database to evaluate all adult inpatient hospitalizations for 1 of 7 common major surgical procedures. Statistical analysis was performed from January 14 to November 30, 2020.Main outcomes and measuresThe study calculated 90-day readmission rates as well as rates of readmissions that were considered potentially preventable. Potentially preventable readmissions (PPRs) were defined as those with a primary diagnosis code for superficial surgical site infection, acute kidney injury, aspiration pneumonitis, or any of the Agency for Healthcare Research and Quality-defined ambulatory care sensitive conditions. Multivariable logistic regression was used to identify factors associated with PPRs.ResultsA total weighted sample of 1 937 354 patients (1 048 046 women [54.1%]; mean age, 66.1 years [95% CI, 66.0-66.3 years]) underwent surgical procedures; 164 755 (8.5%) experienced a readmission within 90 days. Potentially preventable readmissions accounted for 29 321 (17.8%) of all 90-day readmissions, for an estimated total cost to the US health care system of approximately $296 million. The most common reasons for PPRs were congestive heart failure exacerbation (34.6%), pneumonia (12.0%), and acute kidney injury (22.5%). In a multivariable model of adults aged 18 to 64 years, patients with public health insurance (Medicare or Medicaid) had more than twice the odds of PPR compared with those with private insurance (adjusted odds ratio, 2.09; 95% CI, 1.94-2.25). Among patients aged 65 years or older, patients with private insured had 18% lower odds of PPR compared with patients with Medicare as the primary payer (adjusted odds ratio, 0.82; 95% CI, 0.74-0.90).Conclusions and relevanceThis study suggests that nearly 1 in 5 readmissions after surgery are potentially preventable and account for nearly $300 million in costs. In addition to better inpatient care, improved access to ambulatory care may represent an opportunity to reduce costly readmissions among surgical patients.