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 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.

Design and Evaluation of a Computational Phenotype to Identify Patients With Metastatic Breast Cancer Within the Electronic Health Record.

PURPOSE: Outcomes for patients with metastatic breast cancer (MBC) are continually improving as more effective treatments become available. Granular data sets of this unique population are lacking, and the standard method for data collection relies largely on chart review. Therefore, using electronic health records (EHR) collected at a tertiary hospital system, we developed and evaluated a computational phenotype designed to identify all patients with MBC, and we compared the effectiveness of this algorithm against the gold standard, clinical chart review. METHODS: A cohort of patients with breast cancer were identified according to International Classification of Diseases codes, the institutional tumor registry, and SNOMED codes. Chart review was performed to determine whether distant metastases had occurred. We developed a computational phenotype, on the basis of SNOMED concept IDs, which was applied to the EHR to identify patients with MBC. Contingency tables were used to aggregate and compare results. RESULTS: A total of 1,741 patients with breast cancer were identified using data from International Classification of Diseases codes, the tumor registry, and/or SNOMED concept identifiers. Chart review of all patients classified each patient as having MBC (n = 416; 23.9%) versus not (n = 1,325; 75.9%). The final computational phenotype successfully classified 1,646 patients (95% accuracy; 82% sensitivity; 99% specificity). CONCLUSION: Hospital systems with robust EHRs and reliable mapping to SNOMED have the ability to use standard codes to derive computational phenotypes. These algorithms perform reasonably well and have the added ability to be run at disparate health care facilities. Better tooling to navigate the polyhierarchical structure of SNOMED ontology could yield better-performing computational phenotypes.

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.

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.

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.

Leveraging Clinical Informatics Tools to Extract Cumulative Anthracycline Exposure, Measure Cardiovascular Outcomes, and Assess Guideline Adherence for Children With Cancer.

PURPOSE: Cardiovascular disease is a significant cause of late morbidity and mortality in survivors of childhood cancer. Clinical informatics tools could enhance provider adherence to echocardiogram guidelines for early detection of late-onset cardiomyopathy. METHODS: Cancer registry data were linked to electronic health record data. Structured query language facilitated the construction of anthracycline-exposed cohorts at a single institution. Primary outcomes included the data quality from automatic anthracycline extraction, sensitivity of International Classification of Disease coding for heart failure, and adherence to echocardiogram guideline recommendations. RESULTS: The final analytic cohort included 385 pediatric oncology patients diagnosed between July 1, 2013, and December 31, 2018, among whom 194 were classified as no anthracycline exposure, 143 had low anthracycline exposure (< 250 mg/m2), and 48 had high anthracycline exposure (≥ 250 mg/m2). Manual review of anthracycline exposure was highly concordant (95%) with the automatic extraction. Among the unexposed group, 15% had an anthracycline administered at an outside institution not captured by standard query language coding. Manual review of echocardiogram parameters and clinic notes yielded a sensitivity of 75%, specificity of 98%, and positive predictive value of 68% for International Classification of Disease coding of heart failure. For patients with anthracycline exposure, 78.5% (n = 62) were adherent to guideline recommendations for echocardiogram surveillance. There were significant association with provider adherence and race and ethnicity (P = .047), and 50% of patients with Spanish as their primary language were adherent compared with 90% of patients with English as their primary language (P = .003). CONCLUSION: Extraction of treatment exposures from the electronic health record through clinical informatics and integration with cancer registry data represents a feasible approach to assess cardiovascular disease outcomes and adherence to guideline recommendations for survivors.

Inpatient palliative care utilization for patients with brain metastases.

INTRODUCTION: Given the high symptom burden and complex clinical decision making associated with a diagnosis of brain metastases (BM), specialty palliative care (PC) can meaningfully improve patient quality of life. However, no prior study has formally evaluated patient-specific factors associated with PC consultation among BM patients. METHODS: We examined the rates of PC consults in a cohort of 1303 patients with BM admitted to three tertiary medical centers from October 2015 to December 2018. Patient demographics, surgical status, 30-day readmission, and death data were collected via retrospective chart review. PC utilization was assessed by identifying encounters for which an inpatient consult to PC was placed. Statistical analyses were performed to compare characteristics and outcomes between patients who did and did not receive PC consults. RESULTS: We analyzed 1303 patients admitted to the hospital with BM. The average overall rate of inpatient PC consultation was 19.6%. Rates of PC utilization differed significantly by patient race (17.5% in White/Caucasian vs 26.0% in Black/African American patients, P = .0014). Patients who received surgery during their admission had significantly lower rates of PC consultation (3.9% vs 22.4%, P < .0001). Patients who either died during their admission or were discharged to hospice had significantly higher rates of PC than those who were discharged home or to rehabilitation (P < .0001). CONCLUSIONS: In our dataset, PC consultation rates varied by patient demographic, surgical status, discharging service, and practice setting. Further work is needed to identify the specific barriers to optimally utilizing specialty PC in this population.

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.

Immediate Physical Therapy following Total Joint Arthroplasty: Barriers and Impact on Short-Term Outcomes.

BACKGROUND: Recent evidence suggests benefit to receiving physical therapy (PT) the same day as total joint arthroplasty (TJA), but relatively little is known about barriers to providing PT in this constrained time period. We address the following questions: (1) Are there demographic or perioperative variables associated with receiving delayed PT following TJA? (2) Does receiving immediate PT following TJA affect short-term outcomes such as length of stay, discharge disposition, or 30-day readmission? Methods. Primary TJA procedures at a single center were retrospectively reviewed. Immediate PT was defined as within eight hours of surgery. Demographic and perioperative variables were compared between patients who received immediate PT and those who did not. We identified an appropriately matched control group of patients who received immediate PT. Postoperative length of stay, discharge disposition, and 30-day readmissions were compared between matched groups. RESULTS: In total, 2051 primary TJA procedures were reviewed. Of these, 226 (11.0%) received delayed PT. These patients had a higher rate of general anesthesia (25.2% versus 17.8%, p=0.006), later operative start time (13:26 [11:31-14:38] versus 9:36 [8:24-11:16], p<0.001), longer operative time (1.8 [1.5-2.2] versus 1.6 [1.4-1.8] hours, p=0.002), and higher overall caseload on the day of surgery (6 [4-9] versus 5 [4-8], p=0.002). A matched group of patients who received immediate PT was identified. There were no differences in postoperative length of stay or discharge disposition between matched immediate and delayed PT groups, but delayed PT (OR 4.54; 95% CI 1.61-12.84; p=0.004) was associated with a higher 30-day readmission rate. CONCLUSION: Barriers to receiving immediate PT following TJA included general anesthesia, later operative start time, longer operative time, and higher daily caseload. These factors present potential targets for improving the delivery of immediate postoperative PT. Early PT may help reduce 30-day readmissions, but additional research is necessary to further characterize this relationship.

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.

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.

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.

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.

Development and application of a qPCR assay targeting Ichthyophthirius multifiliis in environmental water samples.

Ichthyophthirius multifiliis (Ich) is a globally distributed, freshwater parasitic ciliate that infects wild and cultured fishes. It has a direct, temperature-dependent life cycle that enables rapid multiplication when hosts are plentiful and environmental conditions are favorable. Accurate detection is central to the control of Ich infections and prevention of host mortality, particularly in wild systems where chemical treatments are not feasible. In the Klamath River, California, USA, the parasite threatens pre-spawning adult salmon Oncorhynchus spp. Currently, Ich is monitored by lethal sampling of fish hosts and visual quantification of parasite load. This method is insensitive to light infections, contributes to pre-spawn mortality of wild salmon, and does not allow for population-level disease risk assessments. We developed and applied an alternate sampling method based on molecular analysis of water samples for parasite DNA. We sequenced the small subunit ribosomal DNA (ssrDNA) of Ich isolates collected from the Klamath River, and then developed and validated a novel qPCR assay (SYTO9) that targets Ich ssrDNA. Our assay has better specificity than previously published assays, with strong linearity, efficiency and repeatability. The limit of detection was 50 copies of ssrDNA, equivalent to ~2 theronts in a sample. We found that Ich abundance in environmental water samples collected from the lower Klamath River from July to October, 2014 through 2016, related to observed parasite load on salmon sampled concurrently, indicating that the qPCR assay could be a useful monitoring tool for Ich in the Klamath River, with applications beyond the region.

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.