Risk Factors for Readmission After Knee Arthroplasty Based on Predictive Models: A Systematic Review.
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ABSTRACT: Background
An increase in the aging yet active US population will continue to make total knee arthroplasty (TKA) procedures routine in the coming decades. For such joint procedures, the Centers for Medicare and Medicaid Services introduced programs such as the Comprehensive Care for Joint Replacement to emphasize accountable and efficient transitions of care. Accordingly, many studies have proposed models using risk factors for predicting readmissions after the procedure. We performed a systematic review of TKA literature to identify such models and risk factors therein using a reliable appraisal tool for their quality assessment.Methods
Five databases were searched to identify studies that examined correlations between post-TKA readmission and risk factors using multivariate models. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis methodology and Transparent Reporting of a multivariate prediction model for Individual Prognosis Or Diagnosis criteria established for quality assessment of prognostic studies.Results
Of 29 models in the final selection, 6 models reported performance using a C-statistic, ranging from 0.51 to 0.76, and 2 studies used a validation cohort for assessment. The average 30-day and 90-day readmission rates across the studies were 5.33% and 7.12%, respectively. Three new significant risk factors were discovered.Conclusions
Current models for TKA readmissions lack in performance measurement and reporting when assessed with established criteria. In addition to using new techniques for better performance, work is needed to build models that follow the systematic process of calibration, external validation, and reporting for pursuing their deployment in clinical settings.
SUBMITTER: Mahajan SM
PROVIDER: S-EPMC7303919 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundAn aging United States population profoundly impacts healthcare from both a medical and financial standpoint, especially with an increase in related procedures such as Total Hip Arthroplasty (THA). The Hospital Readmission Reduction Program and Comprehensive Care for Joint Replacement Program incentivize hospitals to decrease post-operative readmissions by correlating reimbursements with smoother care transitions, thereby decreasing hospital burden and improving quantifiable patient outcomes. Many studies have proposed predictive models built upon risk factors for predicting 30-day THA readmissions.Questions(1) Are there validated statistical models that predict 30-day readmissions for THA patients when appraised with a standards-based, reliable assessment tool?. (2) Which evidence-based factors are significant and have support across models for predicting risk of 30-day readmissions post-THA?MethodsFive major electronic databases were searched to identify studies that examined correlations between post-THA readmission and risk factors using multivariate models. We rigorously applied the PRISMA methodology and TRIPOD criteria for assessment of the prognostic studies.ResultsWe found 26 studies that offered predictive models, of which two presented models tested with validation cohorts. In addition to the many factors grouped into demographic, administrative, and clinical categories, bleeding disorder, higher ASA status, discharge disposition, and functional status appeared to have broad and significant support across the studies.ConclusionsReporting of recent predictive models establishing risk factors for 30-day THA readmissions against the current standard could be improved. Aside from building better performing models, more work is needed to follow the thorough process of undergoing calibration, external validation, and integration with existing EHR systems for pursuing their use in clinical settings. There are several risk factors that are significant in multiple models; these factors should be closely examined clinically and leveraged in future risk modeling efforts.
| S-EPMC7139132 | biostudies-literature
Project description:BackgroundOsteoarthritis is a debilitating condition as well as a growing global health problem, and total knee arthroplasty is an effective treatment for advanced stages of disease. Unplanned 30-day hospital readmission is an indicator of complications, which is a significant financial burden on healthcare systems. The objective is to perform a systematic review of patient-related factors associated with unplanned 30-day readmission following total knee arthroplasty. This information will inform future strategies to improve health outcomes after knee arthroplasty surgery.MethodsMEDLINE and EMBASE will be systematically searched using a comprehensive search strategy. Studies of higher quality than case series will be included, in order to optimise the quality of the findings of this review. We will include studies reporting on patient-related risk factors for unplanned 30-day readmission following primary or revision total knee arthroplasty for any indication. Case series will be excluded, as will studies reporting exclusively on intraoperative, clinician, hospital, and health system risk factors. The reference lists of selected papers will then be screened for any additional literature. Two reviewers will independently apply stringent eligibility criteria to titles, abstracts, and full texts of studies identified in the literature search. They will then extract data from the final list of selected papers according to an agreed-upon taxonomy and vocabulary of the data to be extracted. Assessment of risk of bias and quality of evidence will then take place. Finally, the effect size of each identified risk factor will be determined; meta-analysis will be performed where adequate data is available.DiscussionThe findings of this review and subsequent meta-analysis will aid clinicians as they seek to understand the risk factors for 30-day readmission following total knee arthroplasty. Clinicians and patients will be able to use this information to align expectations of the postoperative course, which will enhance the recovery process, and aid in the development of strategies to mitigate identified risks. Another purpose of this review is to assist policy-makers in developing quality indicators for care and provide insights into the drivers of health costs.Systematic review registrationPROSPERO CRD42019118154.
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Project description:BackgroundPredictive modeling promises to improve our understanding of what variables influence patient satisfaction after total knee arthroplasty (TKA). The purpose of this article was to systematically review the relevant literature using predictive models of clinical outcomes after TKA. The aim was to identify the predictor strategies used for systematic data collection with the highest likelihood of success in predicting clinical outcomes.MethodsA Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol systematic review was conducted using 3 databases (MEDLINE, EMBASE, and PubMed) to identify all clinical studies that had used predictive models or that assessed predictive features for outcomes after TKA between 1996 and 2020. The ROBINS-I tool was used to evaluate the quality of the studies and the risk of bias.ResultsA total of 75 studies were identified of which 48 met our inclusion criteria. Preoperative predictive factors strongly associated with postoperative clinical outcomes were knee pain, knee-specific Patient-Reported Outcome Measure (PROM) scores, and mental health scores. Demographic characteristics, pre-existing comorbidities, and knee alignment had an inconsistent association with outcomes. The outcome measures that correlated best with the predictive models were improvement of PROM scores, pain scores, and patient satisfaction.ConclusionsSeveral algorithms, based on PROM improvement, patient satisfaction, or pain after TKA, have been developed to improve decision-making regarding both indications for surgery and surgical strategy. Functional features such as preoperative pain and PROM scores were highly predictive for clinical outcomes after TKA. Some variables such as demographics data or knee alignment were less strongly correlated with TKA outcomes.Level of evidenceSystematic review - Level III.
| S-EPMC8099715 | biostudies-literature
Project description:Total knee arthroplasty (TKA) is a highly effective procedure for advanced osteoarthritis of the knee. Thirty-day hospital readmission is an adverse outcome related to complications, which can be mitigated by identifying associated risk factors. We aimed to identify patient-related characteristics associated with unplanned 30-day readmission following TKA, and to determine the effect size of the association between these risk factors and unplanned 30-day readmission. We searched MEDLINE and EMBASE from inception to 8 September 2020 for English language articles. Reference lists of included articles were searched for additional literature. Patients of interest were TKA recipients (primary and revision) compared for 30-day readmission to any institution, due to any cause, based on patient risk factors; case series were excluded. Two reviewers independently extracted data and carried out critical appraisal. In-hospital complications during the index admission were the strongest risk factors for 30-day readmission in both primary and revision TKA patients, suggesting discharge planning to include closer post-discharge monitoring to prevent avoidable readmission may be warranted. Further research could determine whether closer monitoring post-discharge would prevent unplanned but avoidable readmissions. Increased comorbidity burden correlated with increased risk, as did specific comorbidities. Body mass index was not strongly correlated with readmission risk. Demographic risk factors included low socioeconomic status, but the impact of age on readmission risk was less clear. These risk factors can also be included in predictive models for 30-day readmission in TKA patients to identify high-risk patients as part of risk reduction programs.
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Project description:BackgroundCardiac complication represents a major cause of morbidity and mortality after total joint arthroplasty, thus necessitating investigation into the associated risks in total hip arthroplasty and total knee arthroplasty. There remains a lack of clarity for many risk factors in the current literature. The aim of this systematic review is to assess the most recent published literature and identify the risk factors associated with cardiac complication in total hip arthroplasty and total knee arthroplasty.MethodsScopus, PubMed, CINHAL, and Cochrane were searched to identify studies published since 2008 reporting on risk factors associated with cardiac complication in elective primary in total hip arthroplasty and total knee arthroplasty in patients ?18?years old with osteoarthritis. Reported odds ratios, hazard ratios, and relative risk were the principal summary measures collected. The included studies were too heterogeneous to enable meta-analysis.ResultsFifteen studies were included in this systematic review. Increasing age and history of cardiac disease were found by most studies to be positively associated with risk of cardiac complication. There was no strong association found between obesity and cardiac complication. The evidence for other risk factors was less clear in the examined literature, although there is suggestive evidence for male gender and cerebrovascular disease increasing risk.ConclusionsIncreasing age and history of cardiac disease increases the risk of cardiac complication after total hip arthroplasty and total knee arthroplasty. Other risk factors commonly attributed to increased risk in non-cardiac surgery including hypertension and obesity require further evaluation in arthroplasty.Systematic review registrationA detailed protocol was published in the PROSPERO database (registration number CRD42018095887 ) for this systematic review.
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Project description:The number of older patients is constantly growing, and early hospital readmissions in this population represent a major problem from a health, social and economic point of view. Furthermore, the early readmission rate is often used as an indicator of the quality of care. We performed a systematic review of the literature to better understand the risk factors of early readmission (30 and 90 days) in the geriatric population and to update the existing evidence on this subject. The search was carried out on the MEDLINE, EMBASE and PsycINFO databases. Three independent reviewers assessed the potential inclusion of the studies, and then each study was independently assessed by two reviewers using Joanna Briggs Institute critical appraisal tools; any discrepancies were resolved by the third reviewer. Studies that included inpatients in surgical wards were excluded. Twenty-nine studies were included in the review. Risk factors of early readmission can be classified into socio-economic factors, factors relating to the patient's health characteristics, factors related to the use of the healthcare system and clinical factors. Among these risk factors, those linked to patient frailty play an important role, in particular malnutrition, reduced mobility, risk of falls, fatigue and functional dependence. The early identification of patients at higher risk of early readmission may allow for targeted interventions in view of discharge.
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Project description:BackgroundHospitals are subject to federal financial penalties for excessive 30-day hospital readmissions for acute myocardial infarction (AMI). Prospectively identifying patients hospitalized with AMI at high risk for readmission could help prevent 30-day readmissions by enabling targeted interventions. However, the performance of AMI-specific readmission risk prediction models is unknown.Methods and resultsWe systematically searched the published literature through March 2017 for studies of risk prediction models for 30-day hospital readmission among adults with AMI. We identified 11 studies of 18 unique risk prediction models across diverse settings primarily in the United States, of which 16 models were specific to AMI. The median overall observed all-cause 30-day readmission rate across studies was 16.3% (range, 10.6%-21.0%). Six models were based on administrative data; 4 on electronic health record data; 3 on clinical hospital data; and 5 on cardiac registry data. Models included 7 to 37 predictors, of which demographics, comorbidities, and utilization metrics were the most frequently included domains. Most models, including the Centers for Medicare and Medicaid Services AMI administrative model, had modest discrimination (median C statistic, 0.65; range, 0.53-0.79). Of the 16 reported AMI-specific models, only 8 models were assessed in a validation cohort, limiting generalizability. Observed risk-stratified readmission rates ranged from 3.0% among the lowest-risk individuals to 43.0% among the highest-risk individuals, suggesting good risk stratification across all models.ConclusionsCurrent AMI-specific readmission risk prediction models have modest predictive ability and uncertain generalizability given methodological limitations. No existing models provide actionable information in real time to enable early identification and risk-stratification of patients with AMI before hospital discharge, a functionality needed to optimize the potential effectiveness of readmission reduction interventions.
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Project description:BackgroundElective total knee arthroplasty (TKA) is a common surgery which has evolved rapidly. However, there are no recent large systematic reviews of serious adverse event (SAE) rate and 30-day readmission rate (30-dRR) or an indication of whether surgical methods have improved.MethodsTo obtain a pooled estimate of SAE rate and 30-dRR following TKA, we searched Medline, Web of Science, Cochrane Library, and Google Scholar databases. Data were extracted by two authors following PRISMA guidelines. Eligibility criteria were defined prior to a comprehensive search. Studies were eligible if they were published in 2007 or later, described sequelae of TKA with patient N > 1000, and the SAE or 30-dRR rate could be calculated. SAEs included return to operating room, death or coma, venous thromboembolism (VTE), deep infection or sepsis, myocardial infarction, heart failure or cardiac arrest, stroke or cerebrovascular accident, or pneumonia.ResultsOf 248 references reviewed, 28 are included, involving 10,153,503 patients; this includes 9,483,387 patients with primary TKA (pTKA), and 670,116 patients with revision TKA (rTKA). For pTKA, the SAE rate was 5.7% (95% CI 4.4-7.2%, I2 = 100%), and the 30-dRR was 4.8% (95% CI 4.3-5.4%, I2 = 100%). For rTKA, the SAE rate was 8.5% (95% CI 8.3-8.7%, I2 = 77%), while the 30-dRR was 7.2% (95% CI 6.4-8.0%, I2 = 81%). Odds of 30-dRR following pTKA were about half that of rTKA (OR 0.57, 95% CI 0.53-0.62%, p < 0.001, I2 = 45%). Of patients who received pTKA, the commonest SAEs were VTE (1.22%; 95% CI 0.83-1.70%) and genitourinary complications including renal insufficiency or renal failure (1.22%; 95% CI 0.83-1.67%). There has been significant improvement in SAE rate and 30-dRR since 2010 (χ2 test < 0.001).ConclusionsTKA procedures have a relatively low complication rate, and there has been a significant improvement in SAE rate and 30-dRR over the past decade.
| S-EPMC8011390 | biostudies-literature
Project description:BackgroundTotal knee arthroplasty is a commonly performed procedure and an important contributor to national health care spending. Reducing the incidence of readmission could have important consequences for patient well-being and relevant financial implications. Whether regional anesthesia techniques are associated with decreased readmission rates and costs among privately insured patients remains unknown.MethodsUsing administrative claims data, we identified 138,362 privately insured patients 18-64 years of age who underwent total knee arthroplasty between 2002 and 2013. We then examined whether the use of a nerve block was associated with decreases in readmission rates and related costs during the 90 days after discharge. Our analyses were adjusted for potential confounding variables including medical comorbidities and previous use of opioids and other medications.ResultsAfter adjusting for patient demographics, comorbidities, and preoperative medication use, the adjusted 90-day readmission rate was 1.8% (95% confidence interval [CI], 1.1-2.4) among patients who did not receive a block compared to 1.7% (95% CI, 1.1-2.4) among patients who did (odds ratio, 0.99; 95% CI, 0.91-1.09; P = .85). The adjusted readmission-related postoperative cost for patients who did not receive a block was $561 (95% CI, 502-619) and $574 (95% CI, 508-639) for patients who did (difference, $13; 95% CI, -75 to 102; P = .74). This lack of statistically significant differences held for subgroup and sensitivity analyses.ConclusionsNerve blocks were not associated with improved measures of long-term postoperative resource use in this younger, privately insured study population.
| S-EPMC6605076 | biostudies-literature
Project description:BackgroundThe Comprehensive Care for Joint Replacement bundle was created to decrease total knee arthroplasty (TKA) cost. To help accomplish this, there is a focus on reducing TKA readmissions. However, there is a lack of national representative sample of all-payer hospital admissions to direct strategy, identify risk factors for readmission, and understand actual readmission cost.MethodsWe used the Nationwide Readmission Database to examine national readmission rates, predictors of readmission, and associated readmission costs for elective TKA procedures. We fit a multivariable logistic regression model to examine factors associated with readmission. Then, we determined mean readmission costs and calculated the readmission cost when distributed across the entire TKA population.ResultsWe identified 224,465 patients having TKA across all states participating in the Nationwide Readmission Database. The mean unadjusted 30-day TKA readmission rate was 4%. The greatest predictors of readmission were congestive heart failure (odds ratio [OR] 2.51, 95% confidence interval [CI] 2.62-2.80), renal disease (OR 2.19, 95% CI 2.03-2.37), and length of stay greater than 4 days (OR 2.4, 95% CI 2.25-2.61). The overall median cost for each readmission was $6753 ± 175. Extrapolating the readmission cost for the entire TKA population resulted in the readmission cost being 2% of the overall 30-day procedure cost.ConclusionsA major focus of the Comprehensive Care for Joint Replacement bundle is improving cost and quality by limiting readmission rates. TKA readmissions are low and comprise a small percentage of total TKA cost, suggesting that they may not be the optimal measure of quality care or a significant driver of overall cost.
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