A validated preoperative risk prediction tool for extended inpatient length of stay following anatomic or reverse total shoulder arthroplasty.

BACKGROUND: Recent work has shown inpatient length of stay (LOS) following shoulder arthroplasty to hold the second strongest association with overall cost (after implant cost itself). In particular, a preoperative understanding for the patients at risk of extended inpatient stays (≥3 days) can allow for counseling, optimization, and anticipating postoperative adverse events. METHODS: A multicenter retrospective review was performed of 5410 anatomic (52%) and reverse (48%) total shoulder arthroplasties done at 2 large, tertiary referral health systems. The primary outcome was extended inpatient LOS of at least 3 days, and over 40 preoperative sociodemographic and comorbidity factors were tested for their predictive ability in a multivariable logistic regression model based on the patient cohort from institution 1 (derivation, N = 1773). External validation was performed using the patient cohort from institution 2 (validation, N = 3637), including area under the receiver operator characteristic curve (AUC), sensitivity, specificity, and positive and negative predictive values. RESULTS: A total of 814 patients, including 318 patients (18%) in the derivation cohort and 496 patients (14%) in the validation cohort, experienced an extended inpatient LOS of at least 3 days. Four hundred forty-five (55%) were discharged to a skilled nursing or rehabilitation facility. Following parameter selection, a multivariable logistic regression model based on the derivation cohort (institution 1) demonstrated excellent preliminary accuracy (AUC: 0.826), with minimal decrease in accuracy under external validation when tested against the patients from institution 2 (AUC: 0.816). The predictive model was composed of only preoperative factors, in descending predictive importance as follows: age, marital status, fracture case, ASA (American Society of Anesthesiologists) score, paralysis, electrolyte disorder, body mass index, gender, neurologic disease, coagulation deficiency, diabetes, chronic pulmonary disease, peripheral vascular disease, alcohol dependence, psychoses, smoking status, and revision case. CONCLUSION: A freely-available, preoperative online clinical decision tool for extended inpatient LOS (≥ 3 days) after shoulder arthroplasty reaches excellent predictive accuracy under external validation. As a result, this tool merits consideration for clinical implementation, as many risk factors are potentially modifiable as part of a preoperative optimization strategy.

A Validated Pre-operative Risk Prediction Tool for Extended Inpatient Length of Stay Following Primary Total Hip or Knee Arthroplasty.

BACKGROUND: As value-based reimbursement models mature, understanding the potential trade-off between inpatient lengths of stay and complications or need for costly postacute care becomes more pressing. Understanding and predicting a patient's expected baseline length of stay may help providers understand how best to decide optimal discharge timing for high-risk total joint arthroplasty (TJA) patients. METHODS: A retrospective review was conducted of 37,406 primary total hip (17,134, 46%) and knee (20,272, 54%) arthroplasties performed at two high-volume, geographically diverse, tertiary health systems during the study period. Patients were stratified by 3 binary outcomes for extended inpatient length of stay: 72 + hours (29%), 4 + days (11%), or 5 + days (5%). The predictive ability of over 50 sociodemographic/comorbidity variables was tested. Multivariable logistic regression models were created using institution #1 (derivation), with accuracy tested using the cohort from institution #2 (validation). RESULTS: During the study period, patients underwent an extended length of stay with a decreasing frequency over time, with privately insured patients having a significantly shorter length of stay relative to those with Medicare (1.9 versus 2.3 days, P < .0001). Extended stay patients also had significantly higher 90-day readmission rates (P < .0001), even when excluding those discharged to postacute care (P < .01). Multivariable logistic regression models created from the training cohort demonstrated excellent accuracy (area under the curve (AUC): 0.755, 0.783, 0.810) and performed well under external validation (AUC: 0.719, 0.743, 0.763). Many important variables were common to all 3 models, including age, sex, American Society of Anesthesiologists (ASA) score, body mass index, marital status, bilateral case, insurance type, and 13 comorbidities. DISCUSSION: An online, freely available, preoperative clinical decision tool accurately predicts risk of extended inpatient length of stay after TJA. Many risk factors are potentially modifiable, and these validated tools may help guide clinicians in preoperative patient counseling, medical optimization, and understanding optimal discharge timing.

A validated preoperative risk prediction tool for discharge to skilled nursing or rehabilitation facility following anatomic or reverse shoulder arthroplasty.

BACKGROUND: As bundled payment models continue to spread, understanding the primary drivers of cost excess helps providers avoid penalties and ensure equal health care access. Recent work has shown discharge to rehabilitation and skilled nursing facilities (SNFs) to be a primary cost driver in total joint arthroplasty, and an accurate preoperative risk calculator for shoulder arthroplasty would not only help counsel patients in clinic during shared decision-making conversations but also identify high-risk individuals who may benefit from preoperative optimization and discharge planning. METHODS: Anatomic and reverse total shoulder arthroplasty cohorts from 2 geographically diverse, high-volume centers were reviewed, including 1773 cases from institution 1 (56% anatomic) and 3637 from institution 2 (50% anatomic). The predictive ability of a variety of candidate variables for discharge to SNF/rehabilitation was tested, including case type, sociodemographic factors, and the 30 Elixhauser comorbidities. Variables surviving parameter selection were incorporated into a multivariable logistic regression model built from institution 1's cohort, with accuracy then validated using institution 2's cohort. RESULTS: A total of 485 (9%) shoulder arthroplasties overall were discharged to post-acute care (anatomic: 6%, reverse: 14%, P < .0001), and these patients had significantly higher rates of unplanned 90-day readmission (5% vs. 3%, P = .0492). Cases performed for preoperative fracture were more likely to require post-acute care (13% vs. 3%, P < .0001), whereas revision cases were not (10% vs. 10%, P = .8015). A multivariable logistic regression model derived from the institution 1 cohort demonstrated excellent preliminary accuracy (area under the receiver operating characteristic curve [AUC]: 0.87), requiring only 11 preoperative variables (in order of importance): age, marital status, fracture, neurologic disease, paralysis, American Society of Anesthesiologists physical status, gender, electrolyte disorder, chronic pulmonary disease, diabetes, and coagulation deficiency. This model performed exceptionally well during external validation using the institution 2 cohort (AUC: 0.84), and to facilitate convenient use was incorporated into a freely available, online prediction tool. A model built using the combined cohort demonstrated even higher accuracy (AUC: 0.89). CONCLUSIONS: This validated preoperative clinical decision tool reaches excellent predictive accuracy for discharge to SNF/rehabilitation following shoulder arthroplasty, providing a vital tool for both patient counseling and preoperative discharge planning. Further, model parameters should form the basis for reimbursement legislation adjusting for patient comorbidities, ensuring no disparities in access arise for at-risk populations.

Appropriate patient selection for outpatient shoulder arthroplasty: a risk prediction tool.

BACKGROUND: The transition from inpatient to outpatient shoulder arthroplasty critically depends on appropriate patient selection, both to ensure safety and to counsel patients preoperatively regarding individualized risk. Cost and patient demand for same-day discharge have encouraged this transition, and a validated predictive tool may help decrease surgeon liability for complications and help select patients appropriate for same-day discharge. We hypothesized that an accurate predictive model could be created for short inpatient length of stay (discharge at least by postoperative day 1), potentially serving as a useful proxy for identifying patients appropriate for true outpatient shoulder arthroplasty. METHODS: A multicenter cohort of 5410 shoulder arthroplasties (2805 anatomic and 2605 reverse shoulder arthroplasties) from 2 geographically diverse, high-volume health systems was reviewed. Short inpatient stay was the primary outcome, defined as discharge on either postoperative day 0 or 1, and 49 patient outcomes and factors including the Elixhauser Comorbidity Index, sociodemographic factors, and intraoperative parameters were examined as candidate predictors for a short stay. Factors surviving parameter selection were incorporated into a multivariable logistic regression model, which underwent internal validation using 10,000 bootstrapped samples. RESULTS: In total, 2238 patients (41.4%) were discharged at least by postoperative day 1, with no difference in rates of 90-day readmission (3.5% vs. 3.3%, P = .774) between cohorts with a short length of stay and an extended length of stay (discharge after postoperative day 1). A multivariable logistic regression model demonstrated high accuracy (area under the receiver operator characteristic curve, 0.762) for discharge by postoperative day 1 and was composed of 13 variables: surgery duration, age, sex, electrolyte disorder, marital status, American Society of Anesthesiologists score, paralysis, diabetes, neurologic disease, peripheral vascular disease, pulmonary circulation disease, cardiac arrhythmia, and coagulation deficiency. The percentage cutoff maximizing sensitivity and specificity was calculated to be 47%. Internal validation showed minimal loss of accuracy after bias correction for overfitting, and the predictive model was incorporated into a freely available online tool to facilitate easy clinical use. CONCLUSIONS: A risk prediction tool for short inpatient length of stay after shoulder arthroplasty reaches very good accuracy despite requiring only 13 variables and was derived from an underlying database with broad geographic diversity in the largest institutional shoulder arthroplasty cohort published to date. Short inpatient length of stay may serve as a proxy for identifying patients appropriate for same-day discharge, although perioperative care decisions should always be made on an individualized and holistic basis.

Characteristics and risk factors for 90-day readmission following shoulder arthroplasty.

BACKGROUND: Anatomic total shoulder arthroplasty (TSA) and reverse TSA are the standard of care for end-stage shoulder arthritis. Advancements in implant design, perioperative management, and patient selection have allowed shorter inpatient admissions. Unplanned readmissions remain a significant complication. Identification of risk factors for readmission is prudent as physicians and payers prepare for the adoption of bundled care reimbursement models. The purpose of this study was to identify characteristics and risk factors associated with readmission following shoulder arthroplasty using a large, bi-institutional cohort. METHODS: A total of 2805 anatomic TSAs and 2605 reverse TSAs drawn from 2 geographically diverse, tertiary health systems were examined for unplanned inpatient readmissions within 90 days following the index operation (primary outcome). Forty preoperative patient sociodemographic and comorbidity factors were tested for their significance using both univariable and multivariable logistic regression models, and backward stepwise elimination selected for the most important associations for 90-day readmission. Readmissions were characterized as either medical or surgical, and subgroup analysis was performed. A short length of stay (discharge by postoperative day 1) and discharge to a rehabilitation or skilled nursing facility were also examined as secondary outcomes. Parameters associated with increased readmission risk were included in a predictive model. RESULTS: Within 90 days of surgery, 175 patients (3.2%) experienced an unanticipated readmission, with no significant difference between institutions (P = .447). There were more readmissions for surgical complications than for medical complications (62.9% vs. 37.1%, P < .001). Patients discharged to a rehabilitation or skilled nursing facility were significantly more likely to be readmitted (13.1% vs. 8.8%, P = .049), but a short inpatient length of stay was not associated with an increased rate of 90-day readmission (42.9% vs. 41.3%, P = .684). Parameter selection based on predictive ability resulted in a multivariable logistic regression model composed of 16 preoperative patient factors, including reverse TSA, revision surgery, right-sided surgery, and various comorbidities. The area under the receiver operator characteristic curve for this multivariable logistic regression model was 0.716. CONCLUSION: Risk factors for unplanned 90-day readmission following shoulder arthroplasty include reverse shoulder arthroplasty, surgery for revision and fracture, and right-sided surgery. Additionally, there are several modifiable and nonmodifiable risk factors that can be used to ascertain a patient's readmission probability. A shorter inpatient stay is not associated with an increased risk of readmission, whereas discharge to post-acute care facilities does impose a greater risk of readmission. As scrutiny around health care cost increases, identifying and addressing risk factors for readmission following shoulder arthroplasty will become increasingly important.

Short stay after shoulder arthroplasty does not increase 90-day readmissions in Medicare patients compared with privately insured patients.

BACKGROUND: As of January 1, 2021, total shoulder arthroplasty was removed from the Medicare inpatient-only list, reflecting a growing belief in the potential merits of same-day discharge regardless of insurance type. It is yet unknown whether Medicare populations, which frequently have more severe comorbidity burdens, would experience higher complication rates relative to privately insured patients, who are often younger with fewer comorbidities. Given the limited number of true outpatient cohorts available to study, discharge at least by postoperative day 1 may serve as a useful proxy for true same-day discharge, and we hypothesized that these Medicare patients would have increased 90-day readmission rates compared with their privately insured counterparts. METHODS: Data on 4723 total shoulder arthroplasties (anatomic in 2459 and reverse in 2264) from 2 large, geographically diverse health systems in patients having either Medicare or private insurance were collected. The unplanned 90-day readmission rate was the primary outcome, and patients were stratified into those who were discharged at least by postoperative day 1 (short inpatient stay) and those who were not. Patients with private insurance (n = 1845) were directly compared with those with Medicare (n = 2878), whereas cohorts of workers' compensation (n = 198) and Medicaid (n = 58) patients were analyzed separately. Forty preoperative variables were examined to compare overall health burden, with the χ2 and Wilcoxon rank sum tests used to test for statistical significance. RESULTS: Medicare patients undergoing short-stay shoulder arthroplasty were not significantly more likely than those with private insurance to experience an unplanned 90-day readmission (3.6% vs. 2.5%, P = .14). This similarity existed despite a substantially worse comorbidity burden in the Medicare population (P < .05 for 26 of 40 factors). Furthermore, a short inpatient stay did not result in an increased 90-day readmission rate in either Medicare patients (3.6% vs. 3.4%, P = .77) or their privately insured counterparts (2.5% vs. 2.4%, P = .92). Notably, when the analysis was restricted to a single insurance type, readmission rates were significantly higher for reverse shoulder arthroplasty compared with total shoulder arthroplasty (P < .001 for both), but when the analysis was restricted to a single procedure (anatomic or reverse), readmission rates were similar between Medicare and privately insured patients, whether undergoing a short or extended length of stay. CONCLUSIONS: Despite a substantially more severe comorbidity profile, Medicare patients undergoing short-stay shoulder arthroplasty did not experience a significantly higher rate of unplanned 90-day readmission relative to privately insured patients. A higher incidence of reverse shoulder arthroplasty in Medicare patients does increase their overall readmission rate, but a similar increase also appears in privately-insured patients undergoing a reverse indicating that Medicare populations may be similarly appropriate for accelerated-care pathways.

No Changes in Patient Selection and Value-Based Metrics for Total Hip Arthroplasty After Comprehensive Care for Joint Replacement Bundle Implementation at a Single Center.

BACKGROUND: Alternative payment models for total hip arthroplasty (THA) were initiated by the Center for Medicare and Medicaid Services to decrease overall healthcare cost. The associated shift of financial risk to participating institutions may negatively influence patient selection to avoid high cost of care ("cherry picking," "lemon dropping"). This study evaluated the impact of the Comprehensive Care for Joint Replacement (CJR) model on patient selection, care delivery, and hospital costs at a single care center. METHODS: Patients undergoing a primary THA from 2015-2017 were stratified by insurance type (Medicare and commercial insurance) and whether care was provided before (pre-CJR) or after (post-CJR) CJR bundle implementation. Patient age, gender, and body mass index, Elixhauser comorbidities and American Society of Anesthesiologists scores, were analyzed. Delivery of care variables including surgery duration, discharge disposition, length of stay, and direct hospital costs were compared pre- and post-CJR. RESULTS: A total of 751 THA patients (273 Medicare and 478 commercial Insurance) were evaluated pre-CJR (29%) and post-CJR (71%). Patient demographics were similar (age, gender, BMI); however, commercially insured patients had less comorbidities pre-CJR (P = .033). Medicare patient post-CJR length of stay (P = .010) was reduced with a trend toward discharge to home (P = .019). Surgical time, operating room service time, 90-day readmissions and direct hospital costs were similar pre- and post-CJR. CONCLUSION: There was no differential patient selection after CJR bundle implementation and value-based metrics (surgical time, operating room service time) were not affected. Patients were discharged sooner and more often to home. However, overall direct hospital expenses remained unchanged revealing that any cost savings were for insurance providers, not participating hospitals.

Patients at Risk for Exceeding CJR Cost Targets After Total Ankle Arthroplasty.

BACKGROUND: The Comprehensive Care for Joint Replacement (CJR) model includes total ankle arthroplasty (TAA), under which a target reimbursement is established. Whether this reimbursement is sufficient to cover average cost remains unknown. We hypothesized that a substantial number of TAAs still exceed cost targets, and that risk factors associated with exceeding the target cost could be identified preoperatively. METHODS: Two hundred two primary TAAs performed at a single tertiary referral center under the CJR model from June 2013 to May 2017 were retrospectively reviewed. Patient demographics, comorbidities, outcomes, and costs were extracted from the electronic medical record using a validated structured query language (SQL) algorithm. A comparison cohort of 2084 CJR total hip arthroplasty (THA) and total knee arthroplasty (TKA) cases performed during the same period was also reviewed. RESULTS: Twenty TAAs (10%) exceeded the target cost of care, significantly fewer than CJR THAs/TKAs (29%) performed during the same period (P < .0001). These patients did not differ significantly in age, sex, body mass index, number of Elixhauser comorbidities, or the American Society of Anesthesiologists score. The average cost for these patients was $17 338 higher than those who did not exceed the target cost, and they were less likely to be married or have a partner (45% vs 79%, P = .001). Non-Caucasian status also reached significance (P < .0001). Those exceeding the target cost had a significantly longer length of stay (2.6 vs 1.5 days, P < .0001) and were more likely to be discharged to either skilled nursing or a rehabilitation facility (60% vs 1%, P < .0001). CONCLUSION: Even high-volume TAA centers still exceed target costs in up to 10% of cases, with length of stay, discharge location, and readmissions driving many of these events. Potential risk factors for excess cost include marital/partner status and non-Caucasian ethnicity, but further work is needed to clarify their effects and whether other risk factors exist. LEVEL OF EVIDENCE: Level III, comparative study.

Value-Based Care Has Not Resulted in Biased Patient Selection: Analysis of a Single Center's Experience in the Care for Joint Replacement Bundle.

BACKGROUND: Bundled reimbursement models for total knee arthroplasty (TKA) by the Center for Medicare and Medicaid Services have resulted in an effort to decrease the cost of care. However, these models may incentivize bias in patient selection to avoid excess cost of care. We sought to determine the impact of the Comprehensive Care for Joint Replacement (CJR) model at a single center. METHODS: This is a retrospective review of primary TKA patients from July 2015 to December 2017. Patients were stratified by whether or not their surgery was performed before or after implementation of the CJR bundle. Patient demographic data including age, sex, and body mass index were collected in addition to Elixhauser comorbidities and American Society of Anesthesiologists score. In-hospital outcomes were then examined including surgery duration, length of stay, discharge disposition, and direct cost of care. RESULTS: A total of 1248 TKA patients (546 Medicare and 702 commercial insurance) were evaluated, with 27.0% undergoing surgery before the start of the bundle. Compared to patients following implementation of the bundle, there was no significant difference in age, gender, or body mass index. However, pre-CJR Medicare patients were more likely to have fewer Elixhauser comorbidities (P < .001), prolonged length of stay (P < .001), and greater discharges to inpatient facilities (P = .019). There was no significant difference in direct hospital costs or operative service time comparing pre-bundle and post-bundle patients. CONCLUSION: Implementation of the bundled reimbursement model did not result in biased patient selection at our institution; importantly, it also did not result in decreased hospital costs despite apparent improvement in value-based outcome metrics. This should be taken into consideration as future adaptations to reimbursement are made by the Center for Medicare and Medicaid Services.

A Novel Risk Calculator Predicts 90-Day Readmission Following Total Joint Arthroplasty.

BACKGROUND: A reliable prediction tool for 90-day adverse events not only would provide patients with valuable estimates of their individual risk perioperatively, but would also give health-care systems a method to enable them to anticipate and potentially mitigate postoperative complications. Predictive accuracy, however, has been challenging to achieve. We hypothesized that a broad range of patient and procedure characteristics could adequately predict 90-day readmission after total joint arthroplasty (TJA). METHODS: The electronic medical records on 10,155 primary unilateral total hip (4,585, 45%) and knee (5,570, 55%) arthroplasties performed at a single institution from June 2013 to January 2018 were retrospectively reviewed. In addition to 90-day readmission status, >50 candidate predictor variables were extracted from these records with use of structured query language (SQL). These variables included a wide variety of preoperative demographic/social factors, intraoperative metrics, postoperative laboratory results, and the 30 standardized Elixhauser comorbidity variables. The patient cohort was randomly divided into derivation (80%) and validation (20%) cohorts, and backward stepwise elimination identified important factors for subsequent inclusion in a multivariable logistic regression model. RESULTS: Overall, subsequent 90-day readmission was recorded for 503 cases (5.0%), and parameter selection identified 17 variables for inclusion in a multivariable logistic regression model on the basis of their predictive ability. These included 5 preoperative parameters (American Society of Anesthesiologists [ASA] score, age, operatively treated joint, insurance type, and smoking status), duration of surgery, 2 postoperative laboratory results (hemoglobin and blood-urea-nitrogen [BUN] level), and 9 Elixhauser comorbidities. The regression model demonstrated adequate predictive discrimination for 90-day readmission after TJA (area under the curve [AUC]: 0.7047) and was incorporated into static and dynamic nomograms for interactive visualization of patient risk in a clinical or administrative setting. CONCLUSIONS: A novel risk calculator incorporating a broad range of patient factors adequately predicts the likelihood of 90-day readmission following TJA. Identifying at-risk patients will allow providers to anticipate adverse outcomes and modulate postoperative care accordingly prior to discharge. LEVEL OF EVIDENCE: Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.

A Weighted Index of Elixhauser Comorbidities for Predicting 90-day Readmission After Total Joint Arthroplasty.

BACKGROUND: Evolving reimbursement models increasingly compel hospitals to assume costs for 90-day readmission after total joint arthroplasty. Although risk assessment tools exist, none currently reach the predictive performance required to accurately identify high-risk patients and modulate perioperative care accordingly. Although unlikely to perform adequately alone, the Elixhauser index is a set of 31 variables that may lend value in a broader model predicting 90-day readmission. METHODS: Elixhauser comorbidities were examined in 10,022 primary unilateral total joint replacements, of which 4535 were hip replacements and 5487 were knee replacements, all performed between June 2013 and January 2018 at a single tertiary referral center. Data were extracted from electronic medical records using structured query language. After randomizing to derivation (80%) and validation (20%) subgroups, predictive models for 90-day readmission were generated and transformed into a system of weights based on each parameter's relative performance. RESULTS: We observed 497 90-day readmissions (5.0%) during the study period, which demonstrated independent associations with 14 of the 31 Elixhauser comorbidity groups. A score created from the sum of each patient's weighted comorbidities did not lose substantial predictive discrimination (area under the curve: 0.653) compared to a comprehensive multivariable model containing all 31 unweighted Elixhauser parameters (area under the curve: 0.665). Readmission risk ranged from 3% for patients with a score of 0 to 27% for those with a score of 8 or higher. CONCLUSIONS: The Elixhauser comorbidity score already meets or exceeds the predictive discrimination of available risk calculators. Although insufficient by itself, this score represents a valuable summary of patient comorbidities and merits inclusion in any broader model predicting 90-day readmission risk after total joint arthroplasty. LEVEL OF EVIDENCE: III.

Predicting Inpatient Dissatisfaction Following Total Joint Arthroplasty: An Analysis of 3,593 Hospital Consumer Assessment of Healthcare Providers and Systems Survey Responses.

BACKGROUND: The Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey, created by the Centers for Medicare and Medicaid, is directly tied to hospital reimbursement. The purpose of this study is to identify factors that are predictive HCAHPS survey responses following primary hip and knee arthroplasty. METHODS: Prospectively collected HCAHPS responses from patients undergoing elective hip and knee arthroplasty between January 2013 and October 2017 at our institution were analyzed. Patient age, gender, race, marital status, body mass index, American Society of Anesthesiologists score, preoperative pain score, smoking status, alcohol use, illegal drug use, socioeconomic quartile, insurance type, procedure type, hospital type (academic vs community), distance to medical center, length of stay (LOS), and discharge disposition were obtained and correlated with HCAHPS inpatient satisfaction scores. RESULTS: Responses from 3593 patients were obtained: 1546 total hip arthroplasties, 1899 total knee arthroplasties, and 148 unicompartmental knee arthroplasties. Mean overall HCAHPS score was 79.2. Women had lower inpatient satisfaction than men (77.6 vs 81.6, P < .001). Alcohol consumers had lower inpatient satisfaction than abstainers (77.7 vs 81.6, P < .001). Inpatient satisfaction varied by socioeconomic quartile (P < .001) with patients in the highest quartile having lower satisfaction than patients in all other quartiles (P < .001). Patients discharged to a facility had lower inpatient satisfaction than those discharged home (71.2 vs 80.2, P < .001). An inverse correlation between inpatient satisfaction and LOS (r = -0.19, P < .001) and a direct correlation between satisfaction and distance to medical center (r = 0.06, P < .001) were seen. CONCLUSION: Patients more likely to report lower levels of inpatient satisfaction after total joint arthroplasty are female, affluent, and alcohol consumers, who are discharged to postacute care facilities. Inpatient satisfaction was inversely correlated with LOS and positively correlated with distance from patient home to medical center. These findings provide targets for improvements in TJA inpatient care.

Preoperative Optimization Checklists Within the Comprehensive Care for Joint Replacement Bundle Have Not Decreased Hospital Returns for Total Knee Arthroplasty.

BACKGROUND: The Comprehensive Care for Joint Replacement (CJR) model has resulted in the evolution of preoperative optimization programs to decrease costs and hospital returns. At the investigating institution, one center was not within the CJR bundle and has dedicated fewer resources to this effort. The remaining centers have adopted an 11 metric checklist designed to identify and mitigate modifiable preoperative risks. We hypothesized that this checklist would improve postoperative metrics that impact costs for total knee arthroplasty (TKA) patients eligible for participation in CJR. METHODS: Patients undergoing TKA from 2014 to 2018 were retrospectively reviewed. Only patients with eligible participation in CJR were included. Outcome variables including length of stay, disposition, 90-day emergency department visits, and hospital readmissions were explored. Analysis was performed to determine differences in outcomes between CJR participating and non-CJR participating hospitals within the healthcare system. RESULTS: In total, 2308 TKA patients including 1564 from a CJR participating center and 744 from a non-CJR center were analyzed. There was no significant difference in patient age or gender. Patients at the non-CJR hospital had significantly higher body mass index (P < .001) and American Society of Anesthesiologists scores (P < .001), while those in the CJR network had fewer skilled nursing facility discharges (P = .028) and shorter length of stay (P < .001). However, there was no reduction in 90-day emergency department visits or readmissions. CONCLUSION: The resources utilized at CJR participating hospitals, including patient optimization checklists, did not effectively alter patient outcomes following discharge. Likely, a checklist alone is insufficient for risk mitigation and detailed optimization protocols for modifiable risk factors must be investigated.

Medicaid Insurance Correlates With Increased Resource Utilization Following Total Hip Arthroplasty.

BACKGROUND: With increased restraints and efforts to contain costs in total hip arthroplasty (THA), an emphasis has been placed on risk stratification. The purpose of this study was to determine whether Medicaid patients have increased resource utilization (including 90-day emergency department [ED] visits and readmissions) compared to Medicare or commercial insurance carriers. The study hypothesized that the Medicaid population would represent a high-risk cohort with increased resource utilization. METHODS: The institutional database was retrospectively queried for primary THAs from 2013 to 2017 based on Current Procedural Terminology codes and patients undergoing revision surgery were excluded. Demographic information including age, sex, and body mass index (BMI) and medical comorbidities including American Society of Anesthesiologists (ASA) scores were evaluated. Patients were stratified by insurance type and length of stay (LOS), and 90-day ED visits and 90-day readmissions were assessed in univariable and multivariable analysis. RESULTS: A total of 3674 primary THA patients were included in the analysis (including 116 with Medicaid, 1713 with Medicare, and 1845 with other insurance providers). Medicaid patients had significantly higher ASA scores (P < .001) and BMI (P < .001), with corresponding increase in procedure duration (115 vs 99 vs 105 minutes; P < .001). They had a prolonged LOS (2.5 vs 2.5 vs 1.5 days; P < .001) compared with other insurances, but similar to Medicare patients. Following discharge, in multivariable analysis controlling for age, BMI, and ASA score, Medicare patients were significantly more likely to return to the ED (odds ratio, 3.15; 95% confidence interval, 1.88-5.27; P < .001) and be readmitted (odds ratio, 2.46; 95% confidence interval, 1.26-4.81; P = .009). CONCLUSION: Medicaid patients represent a higher risk cohort with increased resource utilization perioperatively, including longer LOS, and more 90-day ED visits and readmissions. This should be considered in outcome assessments and alternative expectations for the episode of care should be set for this population.

Predicting Costs Exceeding Bundled Payment Targets for Total Joint Arthroplasty.

BACKGROUND: The Center for Medicare and Medicaid Services has instituted bundled reimbursement models for total joint arthroplasty (TJA), which includes target prices for each procedure. Some patients exceed these targets; however, currently there are no tools to accurately predict this preoperatively. We hypothesized that a validated comorbidity index combined with patient demographics would adequately predict excess cost-of-care prior to hospitalization. METHODS: Two thousand eighty-four primary unilateral TJAs performed at a single tertiary center were retrospectively examined. Data were extracted from medical records and a predictive model was built from 30 comorbidities and 7 patient demographic factors (age, gender, race, body mass index, American Society of Anesthesiologists score, smoking status, and marital status). Following parameter selection, a final multivariable model was created, with a corresponding nomogram for interactive visualization of probability for excess cost. RESULTS: Six hundred twelve patients (29%) had cost-of-care exceeding the target price. The final model demonstrated adequate predictive discrimination for cost-of-care exceeding the target price (area under the receiver operator characteristic curve: 0.747). Factors associated with excess cost included age, gender, marital status, American Society of Anesthesiologists score, body mass index, and race, as well as 7 Elixhauser comorbidities (alcohol use, rheumatoid arthritis, diabetes, electrolyte disorders, neurodegenerative disorders, psychoses, and pulmonary circulatory disorders). CONCLUSION: A novel patient model composed of a subset of validated comorbidities and demographic variables provides adequate discrimination in predicting excess cost within bundled payment models for TJA. This not only helps identify patients who would benefit from preoperative optimization, but also provides evidence for modification of future bundled reimbursement models to adjust for nonmodifiable risk factors.

Skilled Nursing Facilities After Total Knee Arthroplasty: The Time for Selective Partnerships Is Now!

BACKGROUND: Bundled payment initiatives for total knee arthroplasty (TKA) patients are dramatically impacted by discharges to skilled nursing facilities (SNFs), making target prices set by the Center for Medicare and Medicaid Services difficult to achieve. However, we hypothesized that a granular examination of SNF discharges would reveal that some may disproportionately increase costs compared to others. METHODS: The institutional database was retrospectively queried for primary TKA patients under bundled payment initiatives. The 4 most common SNFs utilized by our patient population (A, B, C, and D) were investigated for length of stay, cost of care, and whether the overall target price for the episode of care (EOC) was reached. RESULTS: In total, 1223 TKA patients were analyzed, with 378 (30.9%) discharged to an SNF and 246 patients selecting one of the 4 most common SNFs (A: 198, B: 21, C: 15, D: 12). Each SNF represented a significant fiscal portion of the total EOC; however, SNF D had significantly longer length of stay (21 vs 13 days, P < .001) and cost of care ($11,805 vs $6015, P < .001) relative to the others, resulting in no EOC under the target price. SNF costs >24.6% of the total EOC were predictive of exceeding the target price. CONCLUSION: Bundled payment models are significantly impacted by SNF disposition; however, select facilities disproportionately impact this system. In order to maintain free patient selection for disposition, post-acute care facilities must be held accountable for controlling cost, or a separate bundled payment provided.