Scoping Review: Anesthesiologist Involvement in Alternative Payment Models, Value Measurement, and Nonclinical Capabilities for Success in the United States of America.

The US healthcare sector is undergoing significant payment reforms, leading to the emergence of Alternative Payment Models (APMs) aimed at improving clinical outcomes and patient experiences while reducing costs. This scoping review provides an overview of the involvement of anesthesiologists in APMs as found in published literature. It specifically aims to categorize and understand the breadth and depth of their participation, revolving around 3 main axes or "Aims": (1) shaping APMs through design and implementation, (2) gauging the value and quality of care provided by anesthesiologists within these models, and (3) enhancing nonclinical abilities of anesthesiologists for promoting more value in care. To map out the existing literature, a comprehensive search of relevant electronic databases was conducted, yielding a total of 2173 articles, of which 24 met the inclusion criteria, comprising 21 prospective or retrospective cohort studies, 2 surveys, and 1 case-control cohort study. Eleven publications (45%) discussed value-based, bundled, or episode-based payments, whereas the rest discussed non-payment-based models, such as Enhanced Recovery After Surgery (7 articles, 29%), Perioperative Surgical Home (4 articles, 17%), or other models (3 articles, 13%).The review identified key themes related to each aim. The most prominent themes for aim 1 included protocol standardization (16 articles, 67%), design and implementation leadership (8 articles, 33%), multidisciplinary collaboration (7 articles, 29%), and role expansion (5 articles, 21%). For aim 2, the common themes were Process-Based & Patient-Centric Metrics (1 article, 4%), Shared Accountability (3 articles, 13%), and Time-Driven Activity-Based Costing (TDABC) (3 articles, 13%). Furthermore, we identified a wide range of quality metrics, spanning 8 domains that were used in these studies to evaluate anesthesiologists' performance. For aim 3, the main extracted themes included Education on Healthcare Transformation and Policies (3 articles, 13%), Exploring Collaborative Leadership Skills (5 articles, 21%), and Embracing Advanced Analytics and Data Transparency (4 articles, 17%).Findings revealed the pivotal role of anesthesiologists in the design, implementation, and refinement of these emerging delivery and payment models. Our results highlight that while payment models are shifting toward value, patient-centered metrics have yet to be widely accepted for use in measuring quality and affecting payment for anesthesiologists. Gaps remain in understanding how anesthesiologists assess their direct impact and strategies for enhancing the sustainability of anesthesia practices. This review underscores the need for future research contributing to the successful adaptation of clinical practices in this new era of healthcare delivery.

Frameworks for value-based care in the nonoperating room setting.

PURPOSE OF REVIEW: Nonoperating room anesthesia (NORA) presents a unique opportunity for the application of value-based care (VBC) principles to procedures performed in the office-based and nonoperating room inpatient settings. The purpose of this article is to review how value is defined in NORA and enabling principles by which anesthesiologists can maximize value in NORA. RECENT FINDINGS: In order to drive value, NORA providers can target improvements in clinical outcomes where NORA lags behind operating room-based anesthesia (death, over-sedation, nerve injury), implement protocols focusing on intermediate outcomes/quality (postoperative nausea and vomiting, pain control, hypothermia, delirium), incorporate patient-reported outcomes (PROs) to assess the trajectory of a patient's perioperative care, and reduce costs (direct and indirect) through operational and supply-based efficiencies. Establishing a culture of patient and provider safety first, appropriate patient selection with targeted, perioperative optimization of comorbidities, and efficient deployment of staff, space, and resources are critical enablers for success. SUMMARY: Value in NORA can be defined as clinical outcomes, quality, patient-reported outcomes, and efficiency divided by the direct and indirect costs for achieving those outcomes. We present a novel framework adapting current VBC practices in operating room anesthesia to the NORA environment.

Comparison of machine learning techniques to predict unplanned readmission following total shoulder arthroplasty.

BACKGROUND: Machine learning (ML) techniques have been shown to successfully predict postoperative complications for high-volume orthopedic procedures such as hip and knee arthroplasty and to stratify patients for risk-adjusted bundled payments. The latter has not been done for more heterogeneous, lower-volume procedures such as total shoulder arthroplasty (TSA) with equally limited discussion around strategies to optimize the predictive ability of ML algorithms. The purpose of this study was to (1) assess which of 5 ML algorithms best predicts 30-day readmission, (2) test select ML strategies to optimize the algorithms, and (3) report on which patient variables contribute most to risk prediction in TSA across algorithms. METHODS: We identified 9043 patients in the American College of Surgeons National Surgical Quality Improvement Database who underwent primary TSA between 2011 and 2015. Predictors included demographics, comorbidities, laboratory data, and intraoperative variables. The outcome of interest was 30-day unplanned readmission. Five ML algorithms-support-vector machine (SVM), logistic regression, random forest (RF), an adaptive boosting algorithm, and neural network-were trained on the derivation cohort (2011-2014 TSA patients) to predict 30-day unplanned readmission rates. After training, weights for each respective model were fixed and the classifiers were evaluated on the 2015 TSA cohort to simulate a prospective evaluation. C-statistic and f1 scores were used to assess the performance of each classifier. After evaluation, features were removed independently to assess which features most affected classifier performance. RESULTS: The derivation and validation cohorts comprised 5857 and 3186 primary TSA patients, respectively, with similar demographics, comorbidities, and 30-day unplanned readmission rates (2.9% vs. 2.7%). Of the ML algorithms, SVM performed the worst with a c-statistic of 0.54 and an f1-score of 0.07, whereas the random-forest classifier performed the best with the highest c-statistic of 0.74 and an f1-score of 0.18. In addition, SVM was most sensitive to loss of single features, whereas the performance of RF did not dramatically decrease after loss of single features. Within the trained RF classifier, 5 variables achieved weights >0.5 in descending order: high bilirubin (>1.9 mg/dL), age >65, race, chronic obstructive pulmonary disease, and American Society of Anesthesiologists' scores ≥3. In our validation cohort, we observed a 2.7% readmission rate. From this cohort, using the RF classifier we were then able to identify 436 high-risk patients with a predicted risk score >0.6, of whom 36 were readmitted (readmission rate of 8.2%). CONCLUSION: Predictive analytics algorithms can achieve acceptable prediction of unplanned readmission for TSA with the RF classifier outperforming other common algorithms.

Metric Selection, Metric Targets, and Risk Adjustment Should be Considered in the Design of Gainsharing Models for Bundled Payment Programs in Total Joint Arthroplasty.

BACKGROUND: Under bundled payment models, gainsharing presents an important mechanism to ensure engagement and reward innovation. We hypothesized that metric selection, metric targets, and risk adjustment would impact surgeons' performance in gainsharing models. METHODS: Patients undergoing total joint arthroplasty at an urban health system from 2017 to September 2018 were included. Gainsharing metrics included the following: length of stay, % discharge-to-home, 90-day readmission rate, % of patients with episode spend under target price, and % of patients with patient-reported outcomes (PROs) collected. Four scenarios were created to evaluate how metric selection/adjustment impacted surgeons' performance designation: scenario 1 used "aspirational targets" (>60th percentile), scenario 2 used "acceptable targets" (>50th percentile), scenario 3 risk-adjusted surgeon performance prior to comparing aspirational targets, and scenario 4 included a PRO collection metric. Number of metrics achieved determined performance tier, with higher tiers getting a greater share of the gainsharing pool. RESULTS: In total, 2776 patients treated by 12 surgeons met inclusion criteria (mean length of stay 3.0 days, readmission rate 4.0%, discharge-to-home 74%, episode spend under target price 85%, PRO collection 56%). Lowering of metric targets (scenario 1 vs. 2) resulted in a 75% increase in the number of high performers and 98% of the gainsharing pool being eligible for distribution. Risk adjustment (scenario 3) caused 50% of providers to move to higher performance tiers and potential payments to increase by 28%. Adding the PRO metric did not change performance. CONCLUSION: Quality metric/target selection and risk adjustment profoundly impact surgeons' performance in gainsharing contracts. This impacts how successful these contracts can be in driving innovation and dis-incentivizing the "cherry picking" of patients. LEVEL OF EVIDENCE: Level III.

The Cost of Poor Mental Health in Total Joint Arthroplasty.

BACKGROUND: The purpose of this analysis was to evaluate (1) the impact of depression on resource utilization and financial outcomes in bundled total joint arthroplasty (TJA) and (2) whether similar effects are seen using baseline patient-reported outcome scores. METHODS: All elective bundled TJA cases from 2017 to 2018 at an academic system in the New York City area were included. We analyzed variables associated with cost differences seen between patients with and without depression, and between patients with low (<40th percentile) and high baseline (>60th percentile) Veterans RAND 12-Item Health Survey mental component scores (MCSs). We also analyzed whether depression or low MCS could predict worse financial outcomes. RESULTS: Our population included 825 patients, 418 with patient-reported outcome scores data. Depression was associated with higher rates of skilled nursing facility (SNF) discharge (42.7% vs 36.5%, P = .04), SNF payments ($16,200 vs $12,100, P = .0002), and average total episode costs ($31,000 vs $27,000, P = .04). Depression predicted bundle cost to be greater than target price (OR 1.82, 95% CI: 1.04-.16; P = .04) and SNF payment greater than 75th percentile (OR: 1.91; 95% CI: 1.00-3.65; P < .05). Similar effects were not seen using MCS. CONCLUSION: This is the first study to determine that depression predicts bundle cost greater than target price and SNF payment greater than 75th percentile. Our results emphasize the importance of accurate preoperative assessment of mental health in optimization of care, focusing on attenuating the increased SNF payments associated with depression. As similar effects were not seen using MCS, future studies should analyze the use of validated screening tools for depression, such as the PHQ-9, for more accurate assessments of patient mental health in TJA.

Does Productivity-Based Physician Compensation Affect Surgical Rates for Elective Arthroplasty Surgery?

BACKGROUND: Surgeon compensation models could potentially influence the utilization of elective procedures. We assessed whether transitioning from salaried to a relative value unit (RVU) productivity-based physician compensation model changed the surgical rate and patient selection in elective total hip and knee arthroplasty (THA and TKA) procedures. METHODS: Our institution transitioned from salaried to RVU productivity-based reimbursement in July 2016. We performed a retrospective analysis on patients undergoing primary THA and TKA from July 2014 to July 2018 before and after the transition (salary period n = 820; RVU period n = 1188). Beta regression was used to determine the reimbursement structure as a predictor of surgery. The surgical rate was defined as the number of primary THA and TKA procedures per reimbursement period divided by all arthroplasty and osteoarthritis outpatient clinic encounters. RESULTS: There was a surgical rate of 15.8% (95% confidence interval [CI] 13.8%-17.8%) THA and 16.7% (95% CI 15.1%-18.1%) TKA procedures during RVU reimbursement compared to 11.1% (95% CI 9.8%-12.8%) THA and 11.7% (95% CI 10.5%-12.8%) TKA procedures during the salaried period (P < .001). The adjusted odds of undergoing a THA or TKA procedure increased in the RVU compared to the salaried model (THA odds ratio 1.48, 95% CI 1.43-1.53; TKA odds ratio 1.50, 95% CI 1.46-1.55; P < .001). There were no significant differences in patient age, gender, race, body mass index, or Charlson Comorbidity Index in salaried vs RVU productivity periods (P > .05 for all covariates). CONCLUSIONS: Productivity-based physician compensation may encourage higher rates of elective arthroplasty procedures without broadening patient selection.

Hospital-Specific Total Joint Arthroplasty Casemix and Patient Flows in the Era of Payment Reform: Impact on Resource Utilization Among New York State Hospitals.

BACKGROUND: Bundled payment models may lead to selection of healthier total joint arthroplasty (TJA) candidates resulting in comorbid patients being taken care of in fewer hospitals. We aimed to (1) evaluate hospital-specific TJA comorbidity burden ("casemix") over time and (2) associations with resource utilization. METHODS: This retrospective cohort study used 2011 and 2016 New York State data (n = 36,078 hip/knee arthroplasties). Comorbidity burden was estimated by the Charlson-Deyo Index; main outcomes were hospitalization cost and nonhome discharge. Hospitals were categorized into those with a decreased, stable (with a 5% buffer), or increased percentage of comorbidity-free patients (Charlson-Deyo = 0) between 2011 and 2016. Mixed-effects models measured the association between Charlson-Deyo Index category and outcomes, by hospital casemix categorization. Odds ratios and 95% confidence intervals (CIs) are reported. RESULTS: Overall, 29 (n = 8810), 37 (n = 16,297), and 46 (n = 10,971) hospitals were categorized into the decreased, stable, and increased Charlson-Deyo = 0 categories, respectively, with median annual TJA volumes of 499, 814, and 393 (P < .0001). Multivariable models demonstrated that-in hospitals with a stable patient casemix-increased patient comorbidity was associated with increased hospitalization costs (maximum 21.8%, CI 18.9-24.9, P < .0001). However, this effect was moderated (maximum 11.1%, CI 8.0-14.2) in hospitals that took on a more comorbid patient casemix. Similar patterns were observed for nonhome discharge. CONCLUSION: Most studied hospitals show an increase in comorbidity-free TJA patients, suggestive of patient selection. This redistribution of comorbid patients to select hospitals may not necessarily be a negative development as our results suggest more efficient resource utilization for comorbid patients in such hospitals.

Do Medicare's Patient-Reported Outcome Measures Collection Windows Accurately Reflect Academic Clinical Practice?

BACKGROUND: The Comprehensive Care for Joint Replacement (CJR) mandates collection of patient-reported outcome measures (PROMs) for eligible total hip and total knee arthroplasty (THA and TKA) procedures during specific time periods that may not be attainable within routine academic practice. METHODS: We performed a retrospective analysis of prospectively collected PROM data from a 2017 cohort of primary THA and TKA patients who completed the Patient-Reported Outcomes Measurement Information System-10 global health survey in preoperative or postoperative time periods. The primary outcome was completion rates of Patient-Reported Outcomes Measurement Information System-10 per the CJR collection periods (90-0 days preoperative and 270-365 days postoperative) compared to an extended postoperative collection period of 270-396 days. Bivariate analysis and logistic regression were used to analyze the association between survey completion rates and patient characteristics. RESULTS: Of the 860 primary THAs and TKAs in 2017, 725 (84.3%) had preoperative surveys completed 90-0 days before surgery. Among the 725 patients, 215 (29.7%) completed postoperative surveys within the CJR timeline of 270-365 days. Completion increased by 120 additional surveys (+16.5%) in the additional postoperative time period of 270-396 days (P < .001). No patient or procedural factors significantly correlated with a higher likelihood of postoperative PROM completion (P > .05 for all covariates). CONCLUSION: In an academic clinical practice, completion rates of postoperative PROMs as part of routine clinical practice within the CJR mandated period was low for THA and TKA patients. CJR may consider additional time beyond 365 days to improve PROM completion rates.

What Are the Uses and Limitations of Time-driven Activity-based Costing in Total Joint Replacement?

BACKGROUND: With increasing emphasis on value-based payment models for primary total joint arthroplasty (TJA), there is greater need for orthopaedic surgeons and hospitals to better understand the actual costs and resource use of TJA. Time-driven activity-based costing (TDABC) is a methodology for accurate cost estimation, but its application in the TJA care pathway across institutions/regions has not yet been analyzed. QUESTIONS/PURPOSES: In this systematic review of studies applying TDABC to primary TJA, we investigated the following: (1) Is there variation in TDABC methodology and cost estimates across institutions? (2) Is a standard set of direct and indirect costs included across studies? (3) Is there a difference in cost estimates derived from TDABC and traditional hospital cost-accounting approaches? and (4) How are institutions using TDABC (process and outputs) with respect to the TJA care pathway? METHODS: A comprehensive search strategy was developed that included the keywords "TDABC," "time-driven activity-based cost," "THA," "TKA," "THR," "TKR," and "TJR" in the PubMed/MEDLINE, EMBASE, Web of Science, Ovid SP, Scopus, and ScienceDirect databases for articles published between 2004 and 2018 as well as extensive hand searching and citation mining. Relevant studies (n = 15) were screened to include THA or TKA as the focus of the TDABC model, full-text articles, TDABC-based cost estimates for TJA, and studies written in English (n = 8). Due to the heterogeneity of outcomes/methodology in TDABC studies involving TJA, quality assessment was based on each study's adherence to the seven steps delineated by Kaplan et al. in their original publication introducing TDABC in health care. RESULTS: There was substantial variation in TDABC methodology (especially in scope), adherence to the seven steps of TDABC, and data collection. Only five of eight studies incorporated indirect costs into their TDABC calculation, with notable differences in which direct and indirect expenses were included. TDABC-based cost estimates for TJA ranged from USD 7081 to USD 29,557, with variation driven by the TJA timeframe and whether implant costs were included in the costing calculation. TDABC was most frequently used to compare against traditional hospital accounting methods (n = 4), to increase operational efficiency (n = 4), to reduce wasted resources (n = 3), and to mitigate risk (n = 3). CONCLUSIONS: TDABC-based cost estimates are more granular and useful in practice than those calculated via traditional hospital accounting; however, there is a lack of standardized principles to guide TDABC implementation (especially for indirect costs) due to institutional and regional differences in TDABC application. Although TDABC methodology will likely continue to vary somewhat between studies, standardized principles are needed to guide the definition, estimation, and reporting of costs to enable detailed examination of study methodology and inputs by readers. LEVEL OF EVIDENCE: Level III, economic and decision analysis.

Designing and Implementing Value-Based Care Delivery and Payment Models for Musculoskeletal Care.

Payors, purchasers, health care providers, and patients are increasingly focused on improving the value-defined as health outcomes that matter to patients per dollar expended-of health care delivered to patients. Orthopaedic providers are in a unique position to pioneer this transition given the introduction of alternative payment models as well as the longitudinal, multidisciplinary, and relatively homogenous nature of high-cost, high-burden orthopaedic conditions (eg, osteoarthritis). First, doing so requires identifying and objectively measuring outcomes that are important to patients (eg, quality of life, pain, functional status) over time. Second, it requires applying value-based principles by reorganizing delivery systems into integrated practice units-a team-based, multidisciplinary model-focused on delivering longitudinal care in a method that is tailored to each patient's values, goals, and disease state. Third, providers must understand the true cost of delivering such care through time-driven activity-based costing approaches. With this knowledge of outcomes and cost, providers and payors/purchasers will be adequately equipped to develop contracts that reward providers for delivering better value (across an orthopaedic patient population) while minimizing risk. The transition to value-based health care is feasible regardless of practice setting.

Skilled Nursing Facility Placement Process After Total Hip and Total Knee Arthroplasty: Revised Rating System and Opportunities for Intervention.

BACKGROUND: With the advent of bundled payment models, identifying high-performing skilled nursing facilities (SNFs) has become increasingly important. The goal of this study is to develop a rating system to rank SNFs within our health system and to use this system to improve the SNF discharge process at our institution. METHODS: All SNF-discharged primary total joint arthroplasty cases in 2017 at a multi-hospital academic health system were queried. Discharge patterns were assessed using heat map analysis. Regression analyses in conjunction with structured discussions with subject matter experts were used to identify measures of SNF efficiency and care quality. A revised rating system was developed and used to identify high-performing facilities within our health system. Opportunities to re-direct patients to higher performing facilities were identified. RESULTS: A revised rating system for SNFs was constructed based on risk-adjusted SNF length of stay, 30-day re-admission rate, and 30-day emergency department visit rate. As 82% of patients were discharged to SNFs in close proximity to their home, high-performing SNFs (according to the revised rating system) were identified by geographic region. Mapping of the discharge process revealed multiple opportunities where patients could be re-directed to a higher performing SNF in their area. Using conservative estimates (25% of discharges re-directed), this is expected to achieve a cost saving of $2,600,000 over a 5-year period, mainly through reductions in SNF length of stay. CONCLUSION: This study describes the development of a revised rating system for SNFs which, when implemented, is expected to achieve substantial cost savings over a 5-year period.

Preoperative Patient-Reported Outcomes and Clinical Characteristics as Predictors of 90-Day Cost/Utilization and Complications.

BACKGROUND: With the advent of mandatory bundle payments for total joint arthroplasty (TJA), assessing patients' risk for increased 90-day complications and resource utilization is crucial. This study assesses the degree to which preoperative patient-reported outcomes predict 90-day complications, episode costs, and utilization in TJA patients. METHODS: All TJA cases in 2017 at 2 high-volume hospitals were queried. Preoperative HOOS/KOOS JR (Hip Injury and Osteoarthritis Outcome Score/Knee Injury and Osteoarthritis Outcome Score) and Veterans RAND 12-item health survey (VR-12) were administered to patients preoperatively via e-collection platform. For patients enrolled in the Medicare bundle, cost data were extracted from claims. Bivariate and multivariate regression analyses were performed. RESULTS: In total, 2108 patients underwent TJA in 2017; 1182 (56%) were missing patient-reported outcome data and were excluded. The final study population included 926 patients, 199 (21%) of which had available cost data. Patients with high bundle costs tended to be older, suffer from vascular disease and anemia, and have higher Charlson scores (P < .05 for all). These patients also had lower baseline VR-12 Physical Component Summary Score (PCS; 24 vs 30, P ≤ .001) and higher rates of extended length of stay, skilled nursing facility discharge, 90-day complications, and 90-day readmission (P ≤ .04 for all). In multivariate analysis, higher baseline VR-12 PCS was protective against extended length of stay, skilled nursing facility discharge, >75th percentile bundle cost, and 90-day bundle cost exceeding target bundle price (P < .01 for all). Baseline VR-12 Mental Component Summary Score and HOOS/KOOS JR were not predictive of complications or bundle cost. CONCLUSION: Low baseline VR-12 PCS is predictive of high 90-day bundle costs. Baseline HOOS/KOOS JR scores were not predictive of utilization or cost. Neither VR-12 nor HOOS/KOOS JR was predictive of 90-day readmission or complications.

Are Medicare's Nursing Home Compare Ratings Accurate Predictors of 90-Day Complications, Readmission, and Bundle Cost for Patients Undergoing Primary Total Joint Arthroplasty?

BACKGROUND: Nursing Home Compare (NHC) ratings, created and maintained by Medicare, are used by both hospitals and consumers to aid in the skilled nursing facility (SNF) selection process. To date, no studies have linked NHC ratings to actual episode-based outcomes. The purpose of this study was to evaluate whether NHC ratings are valid predictors of 90-day complications, readmission, and bundle costs for patients discharged to an SNF after primary total joint arthroplasty (TJA). METHODS: All SNF-discharged primary TJA cases in 2017 at a multihospital academic health system were queried. Demographic, psychosocial, and clinical variables were manually extracted from the health record. Medicare NHC ratings were then collected for each SNF. For patients in the Medicare bundle, postacute and total bundle cost was extracted from claims. RESULTS: Four hundred eighty-eight patients were discharged to a total of 105 unique SNFs. In multivariate analysis, overall NHC rating was not predictive of 90-day readmission/major complications, >75th percentile postacute cost, or 90-day bundle cost exceeding the target price. SNF health inspection and quality measure ratings were also not predictive of 90-day readmission/major complications or bundle performance. A higher SNF staffing rating was independently associated with a decreased odds for >75th percentile 90-day postacute spend (odds ratio, 0.58; P = .01) and a 90-day bundle cost exceeding the target price (odds ratio = 0.69; P = .02) but was similarly not predictive of 90-day readmission/complications. CONCLUSION: Results of our study suggest that Medicare's NHC tool is not a useful predictor of 90-day costs, complications, or readmissions for SNFs within our health system.

Defining and Optimizing Value in Total Joint Arthroplasty From the Patient, Payer, and Provider Perspectives.

BACKGROUND: The purpose of this study is to define value in bundled total joint arthroplasty (TJA) from the differing perspectives of the patient, payer/employer, and hospital/provider. METHODS: Demographic, psychosocial, clinical, financial, and patient-reported outcomes (PROs) data from 2017 to 2018 elective TJA cases at a multihospital academic health system were queried. Value was defined as improvement in PROs (preoperatively to 1 year postoperatively) for patients, improvement in PROs per $1000 of bundle cost for payers, and the normalized sum of improvement in PROs and hospital bundle margin for providers. Bivariate analysis was used to compare high value vs low value (>50th percentile vs <50th percentile). Multivariate analysis was performed to identify predictors. RESULTS: A total of 280 patients had PRO data, of which 71 had Medicare claims data. Diabetes (odds ratio [OR], 0.45; P = .02) predicted low value for patients; female gender (OR, 0.25), hypertension (OR, 0.17), pulmonary disease (OR, 0.12), and skilled nursing facility discharge (OR, 0.17) for payers (P ≤ .03 for all); and pulmonary disease (OR, 0.16) and skilled nursing facility discharge (OR, 0.19) for providers (P ≤ .04 for all). CONCLUSION: This is the first article to define value in TJA under a bundle payment model from multiple perspectives, providing a foundation for future studies analyzing value-based TJA.

Does physician leadership affect hospital quality, operational efficiency, and financial performance?

BACKGROUND: With payers and policymakers' focus on improving the value (health outcomes achieved per health care dollar spent) of health care delivery, physicians are increasingly taking on senior leadership/management positions in health care organizations (Carsen & Xia, 2006). Little research has been done to understand the impact of physician leadership on the delivery of care. PURPOSE: The aim of this study was to examine whether hospital systems led by physicians were associated with better U.S. News and World Report (USNWR) quality ratings, financial performance, and operating efficiency as compared with those led by nonphysician managers. METHODOLOGY: Cross-sectional analysis of nationally representative data from Medicare Cost Reports and the USNWR on the 115 largest U.S. hospitals was performed. Bivariate analysis of physician-led and non-physician-led hospital networks included three categories: USNWR quality ratings, hospital volume, and financial performance. Multivariate analysis of hospital leadership, percent operating margin, inpatient days per hospital bed, and average quality rating was subsequently performed. RESULTS: Hospitals in physician-led hospital systems had higher quality ratings across all specialties and more inpatient days per hospital bed than did non-physician-led hospitals; however, there were no differences in the total revenue or profit margins between the groups. Physician leadership was independently associated with higher average quality ratings and inpatient days per bed. CONCLUSIONS: Large hospital systems led by physicians in 2015 received higher USNWR ratings and bed usage rates than did hospitals led by nonphysicians, with no differences in financial performance. This study suggests that physician leaders may possess skills, qualities, or management approaches that positively affect hospital quality and the value of care delivered. PRACTICE IMPLICATIONS: Hospital quality and efficiency ratings vary significantly and can impact consumer decisions. Hospital systems may benefit from the presence of physician leadership to improve the quality and efficiency of care delivered to patients. In addition, medical education should help prepare physicians to take on leadership roles in hospitals and health systems.

Outcomes of displaced olecranon fractures treated with the Olecranon Sled.

BACKGROUND: Tension-band wiring is largely considered the gold standard for fixation of displaced olecranon fractures despite high rates of hardware complications. The purpose of this study was to report the outcomes of displaced olecranon fractures treated with the Olecranon Sled. METHODS: We retrospectively reviewed all displaced olecranon fractures from 2011-2015 treated with the Olecranon Sled. Inclusion was limited to functionally independent patients with Mayo type II fractures and minimum 12-month follow-up. We assessed clinical outcomes including range of motion; Disabilities of the Arm, Shoulder and Hand score; and Mayo Elbow Performance Score. RESULTS: Twenty-two patients with a mean follow-up period of 31.8 months (range, 12-71 months) were included in the study. All patients indicated satisfactory outcomes. The mean Mayo Elbow Performance Score was 95.5 (range, 70-100), and the mean Disabilities of the Arm, Shoulder and Hand score was 3.1 (range, 0-18.3). The mean total arc of elbow flexion was 145° (range, 134°-158°), and the mean total arc of forearm rotation was 175° (range, 160°-180°). There were no hardware-related complications. The overall complication rate was 4.5% (1 of 22) as significant heterotopic ossification developed in 1 patient, requiring contracture release. CONCLUSION: The Olecranon Sled is a reliable and well-tolerated implant for the treatment of olecranon fractures. This device results in excellent functional outcomes and may obviate hardware removal.

Trochanteric Bursitis Following Primary Total Hip Arthroplasty: Incidence, Predictors, and Treatment.

BACKGROUND: Trochanteric bursitis (TB) remains a common complication after total hip arthroplasty (THA), with an incidence between 3% and 17%, depending on the surgical approach, with the posterior approach (PA) being relatively protective compared to the lateral approach. The purposes of this study were to determine the incidence of TB after primary THA, identify potential risk factors for TB, and examine the utility of different modes of treatment. METHODS: Retrospective cohort data of 990 primary THAs performed in a single institution, including 613 PAs and 377 direct anterior approaches (DAAs), were analyzed. Data abstracted included demographic data, operative diagnosis, comorbidities, radiographic assessment, and other specific predictors of interest that were compared between patients diagnosed with TB following THA and controls. RESULTS: The incidence of TB following primary THA was 5.4% (54/990) for the entire cohort. The incidence did not differ significantly between the PA and DAA (5% vs 6.1%, respectively; P = .47). Charlson comorbidity index and American Society of Anesthesiology did not differ significantly in the TB group. Lumbar spinal stenosis and history of past smoking were significantly more common in patients who developed TB (P = .03, P = .01, respectively), but did not continue to be significant risk factors on multivariate analysis. All patients were treated nonoperatively by the time of final follow-up. Seventy-four percent required a local steroid injection and 30% required treatment with more than one modality. CONCLUSION: The occurrence of TB is not influenced by the surgical approach (PA or DAA), and could not be predicted by specific comorbidities or radiographic measurements. However, it can be effectively treated conservatively in most cases.

Perioperative Risk Adjustment for Total Shoulder Arthroplasty: Are Simple Clinically Driven Models Sufficient?

BACKGROUND: There is growing interest in value-based health care in the United States. Statistical analysis of large databases can inform us of the factors associated with and the probability of adverse events and unplanned readmissions that diminish quality and add expense. For example, increased operating time and high blood urea nitrogen (BUN) are associated with adverse events, whereas patients on antihypertensive medications were more likely to have an unplanned readmission. Many surgeons rely on their knowledge and intuition when assessing the risk of a procedure. Comparing clinically driven with statistically derived risk models of total shoulder arthroplasty (TSA) offers insight into potential gaps between common practice and evidence-based medicine. QUESTIONS/PURPOSES: (1) Does a statistically driven model better explain the variation in unplanned readmission within 30 days of discharge when compared with an a priori five-variable model selected based on expert orthopaedic surgeon opinion? (2) Does a statistically driven model better explain the variation in adverse events within 30 days of discharge when compared with an a priori five-variable model selected based on expert orthopaedic surgeon opinion? METHODS: Current Procedural Terminology codes were used to identify 4030 individuals older than 17 years of age who had TSA in which osteoarthritis was the primary etiology. A logistic regression model for adverse event and unplanned readmission within 30 days was constructed using (1) five variables chosen a priori based on clinic expertise (age, American Society of Anesthesiologists classification ≥ 3, body mass index, smoking status, and diabetes mellitus); and (2) by entering all variables with p < 0.10 in bivariate analysis. We then excluded 870 patients (22%) based on preoperative factors felt to make large discretionary surgery unwise to focus our research on appropriate procedures. Infirm patients have more pressing needs than alleviation of shoulder pain and stiffness. Among the remaining 3160 patients, logistic regression models for adverse event and unplanned readmission within 30 days were constructed in a similar manner to the complete models. The five a priori risk factors used in each model based on clinical expertise were selected by consensus of an expert orthopaedic surgeon panel. RESULTS: When patients unfit for discretionary surgery were excluded, the clinically driven model found no risk factors and accounted for 1.4% of the variation in unplanned readmission. In contrast, the statistically driven model explained 4.6% of the variation and found operating time (hours) (odds ratio [OR], 1.26; 95% confidence interval [CI], 1.04-1.53) and hypertension requiring medications (OR, 1.95; 95% CI, 1.01-3.76) were associated with unplanned readmission accounting for all other factors. However, neither the clinically driven model (pseudo R2, 1.4%) nor statistically driven model (pseudo R2, 4.6%) provided much explanatory power. When patients unfit for discretionary surgery were excluded, no factors in the clinically driven model were significant and the model accounted for 0.95% of the variation in adverse events. In the statistically driven model, age (OR, 1.03; 95% CI, 1.01-1.06), men (OR, 1.64; 95% CI, 1.05-2.57), operating time (hours) (OR, 1.27; 95% CI, 1.07-1.52), and high BUN (OR, 3.12; 95% CI, 1.35-7.21) were associated with adverse events when accounting for all other factors, explaining 3.3% of the variation. However, neither the clinically driven model (pseudo R2, 0.95%) nor the statistically driven model (pseudo R2, 3.3%) provided much explanatory power. CONCLUSIONS: The observation that a statistically derived risk model performs better than a clinically driven model affirms the value of research based on large databases, although the models derived need to be tested prospectively. CLINICAL RELEVANCE: Clinicians can utilize our results to understand that clinician intuition may not always offer the best risk adjustment and that factors impacting TSA unplanned readmission and adverse events may be best derived from large data sets. However, because current analyses explain limited variation in outcomes, future studies might look to better define what factors drive the variation in unplanned readmission and adverse events.

Risk factors for and timing of adverse events after total shoulder arthroplasty.

BACKGROUND: Total shoulder arthroplasty (TSA) is a likely target for future bundled payment initiatives, necessitating accurate preoperative risk stratification. The purpose of this study was to identify risk factors for unplanned readmission and severe adverse events, to risk stratify TSA patients based on these risk factors, and to assess timing of complications after TSA. METHODS: Data were collected from patients undergoing TSA from 2009 to 2014 in the American College of Surgeons National Surgical Quality Improvement Program. Bivariate and multivariate analyses of risk factors for severe adverse events or readmission were assessed. Patients were risk stratified, and timing of severe adverse events and cause of readmission were evaluated. RESULTS: The analysis included 5801 TSA patients; 146 (2.5%) suffered severe adverse events, and 158 (2.7%) had a 30-day unplanned readmission. The most common severe adverse events were reoperation (40%), thrombolic event (deep venous thrombosis or pulmonary embolism; 14%), cardiac event (10%), and death (8.2%). Pneumonia (8.9%) and thrombolic event (7.6%) were the most common medically related causes, whereas dislocation (7.6%) and postoperative infection or wound complication (5.1%) were the most common surgical causes for readmission. Multivariate analysis identified inflammatory arthritis (P = .026), male gender (P = .019), age (P < .001), functional status (P = .024), and American Society of Anesthesiologists class 3/4 (P = .01) as independent predictors for unplanned 30-day readmission and all but inflammatory arthritis for severe adverse events (P ≤ .05 for all). Patients with ≥3 risk factors had an 11.56 (P = .002) and 3.43 (P = .013) times increased odds of unplanned readmission and severe adverse events occurring within 2 weeks after surgery, respectively, compared with patients with 0 risk factors. CONCLUSIONS: Patients at high risk of TSA complications and readmission should be identified preoperatively to improve outcomes and to lower costs. Bundled payment initiatives must account for both patient- and procedure-related risk factors.

Predictors of Same-Day Discharge in Primary Total Joint Arthroplasty Patients and Risk Factors for Post-Discharge Complications.

BACKGROUND: Same-day (<24 h) discharge total joint arthroplasty (TJA) may be a safe and effective option for certain patients with end-stage osteoarthritis. Given the growing pressure to improve quality and lower TJA episode costs, surgeons must identify which TJA patients can be appropriately discharged home quickly and safely. This study identifies characteristics associated with same-day discharge post-TJA as well as assesses risk factors for complications in this select patient population. METHODS: Bivariate and multivariate analyses were performed using perioperative variables from the 2011 to 2014 National Surgical Quality Improvement Program database. RESULTS: In total, 7474 primary TJAs among 120,847 TJA patients were discharged within 24 h post-surgery. These patients were more likely to be younger (<50 years), male sex, American Society of Anesthesiologists class 1 or 2, and less likely to be obese or taking steroids (P < .05 for all). They were also less likely to have co-morbidities. Rates of severe adverse event (SAE) or unplanned readmission post-discharge were 1.3% and 1.9%, respectively. Multivariate analysis identified age >80 (odds ratio [OR] 4.16, P = .001), smoking (OR 1.61, P = .03), bleeding-causing disorders (OR 2.56, P = .01), American Society of Anesthesiologists class 3 or 4 (OR 1.42, P < .05), and SAE pre-discharge (OR 13.13, P < .0001) as independent predictors for adverse events or readmission in this population. CONCLUSION: Patient characteristics, co-morbidities, and SAEs pre-discharge can be used to assess potential for discharge within 24 h. The results of our analysis may be used to develop risk stratification tools for identification of patients that are truly appropriate for same-day discharge TJA.