Inclusion of Veterans Health Administration hospitals in Centers for Medicare & Medicaid Services Overall Hospital Quality Star Ratings.

BACKGROUND/OBJECTIVE: The Centers for Medicare & Medicaid Services (CMS) Overall Hospital Quality Star Rating, established in 2016, is a summary of publicly available quality information for acute care hospitals. In July 2023, Veterans Health Administration (VHA) hospitals became eligible to receive a CMS Overall Hospital Quality Star Rating for the first time. Our objective was to compare performance in quality ratings among VHA and non-VHA hospitals. METHODS: We used the hospital quality measure scores posted to Care Compare on Medicare.gov as of January 2023 as our primary data set. We conducted a pair of analyses to characterize the performance of VHA hospitals compared to non-VHA hospitals: an overall analysis including all rated hospitals, and a matched analysis in which only a single nearby hospital was included for each VHA hospital. RESULTS: Of the 4518 non-VHA hospitals, 2962 (65.6%) received a Star Rating, compared to 114 (84%) of 136 VHA hospitals. VHA hospitals tended to receive higher ratings overall (one-star: 8%; two-star: 11%; three-star: 14%; four-star: 35%; five-star: 32%) than non-VHA (one-star: 8%; two-star: 22%; three-star: 29%; four-star: 26%; five-star: 15%). A similar pattern was observed in the matched analysis. CONCLUSIONS: VHA hospitals tended to perform better on the Overall Star Rating compared to non-VHA hospitals, as evidenced by being more likely to receive a four- or five-star rating. The eligibility of VHA hospitals to receive an Overall Star Rating signifies an important addition to the program that will allow Veterans to make more informed healthcare decisions.

Processing and validation of inpatient Medicare Advantage data for use in hospital outcome measures.

OBJECTIVE: To determine the feasibility of integrating Medicare Advantage (MA) admissions into the Centers for Medicare & Medicaid Services (CMS) hospital outcome measures through combining Medicare Advantage Organization (MAO) encounter- and hospital-submitted inpatient claims. DATA SOURCES AND STUDY SETTING: Beneficiary enrollment data and inpatient claims from the Integrated Data Repository for 2018 Medicare discharges. STUDY DESIGN: We examined timeliness of MA claims, compared diagnosis and procedure codes for admissions with claims submitted both by the hospital and the MAO (overlapping claims), and compared demographic characteristics and principal diagnosis codes for admissions with overlapping claims versus admissions with a single claim. DATA COLLECTION/EXTRACTION METHODS: We combined hospital- and MAO-submitted claims to capture MA admissions from all hospitals and identified overlapping claims. For admissions with only an MAO-submitted claim, we used provider history data to match the National Provider Identifier on the claim to the CMS Certification Number used for reporting purposes in CMS outcome measures. PRINCIPAL FINDINGS: After removing void and duplicate claims, identifying overlapped claims between the hospital- and MAO-submitted datasets, restricting claims to acute care and critical access hospitals, and bundling same admission claims, we identified 5,078,611 MA admissions. Of these, 76.1% were submitted by both the hospital and MAO, 14.2% were submitted only by MAOs, and 9.7% were submitted only by hospitals. Nearly all (96.6%) hospital-submitted claims were submitted within 3 months after a one-year performance period, versus 85.2% of MAO-submitted claims. Among the 3,864,524 admissions with overlapping claims, 98.9% shared the same principal diagnosis code between the two datasets, and 97.5% shared the same first procedure code. CONCLUSIONS: Inpatient MA data are feasible for use in CMS claims-based hospital outcome measures. We recommend prioritizing hospital-submitted over MAO-submitted claims for analyses. Monitoring, data audits, and ongoing policies to improve the quality of MA data are important approaches to address potential missing data and errors.

Incorporating Medicare Advantage Admissions Into the CMS Hospital-Wide Readmission Measure.

Importance: Medicare Advantage (MA) enrollment is rapidly expanding, yet Centers for Medicare & Medicaid Services (CMS) claims-based hospital outcome measures, including readmission rates, have historically included only fee-for-service (FFS) beneficiaries. Objective: To assess the outcomes of incorporating MA data into the CMS claims-based FFS Hospital-Wide All-Cause Unplanned Readmission (HWR) measure. Design, Setting, and Participants: This cohort study assessed differences in 30-day unadjusted readmission rates and demographic and risk adjustment variables for MA vs FFS admissions. Inpatient FFS and MA administrative claims data were extracted from the Integrated Data Repository for all admissions for Medicare beneficiaries from July 1, 2018, to June 30, 2019. Measure reliability and risk-standardized readmission rates were calculated for the FFS and MA cohort vs the FFS-only cohort, overall and within specialty subgroups (cardiorespiratory, cardiovascular, medicine, surgery, neurology), then changes in hospital performance quintiles were assessed after adding MA admissions. Main Outcome and Measure: Risk-standardized readmission rates. Results: The cohort included 11 029 470 admissions (4 077 633 [37.0%] MA; 6 044 060 [54.8%] female; mean [SD] age, 77.7 [8.2] years). Unadjusted readmission rates were slightly higher for MA vs FFS admissions (15.7% vs 15.4%), yet comorbidities were generally lower among MA beneficiaries. Test-retest reliability for the FFS and MA cohort was higher than for the FFS-only cohort (0.78 vs 0.73) and signal-to-noise reliability increased in each specialty subgroup. Mean hospital risk-standardized readmission rates were similar for the FFS and MA cohort and FFS-only cohorts (15.5% vs 15.3%); this trend was consistent across the 5 specialty subgroups. After adding MA admissions to the FFS-only HWR measure, 1489 hospitals (33.1%) had their performance quintile ranking changed. As their proportion of MA admissions increased, more hospitals experienced a change in their performance quintile ranking (147 hospitals [16.3%] in the lowest quintile of percentage MA admissions; 408 [45.3%] in the highest). The combined cohort added 63 hospitals eligible for public reporting and more than 4 million admissions to the measure. Conclusions and Relevance: In this cohort study, adding MA admissions to the HWR measure was associated with improved measure reliability and precision and enabled the inclusion of more hospitals and beneficiaries. After MA admissions were included, 1 in 3 hospitals had their performance quintile changed, with the greatest shifts among hospitals with a high percentage of MA admissions.

Calculation of Overall Hospital Quality Star Ratings With and Without Inclusion of the Peer Grouping Step.

Importance: The Centers for Medicare & Medicaid Services (CMS) Overall Star Rating is widely used by patients and consumers, and there is continued stakeholder curiosity surrounding the inclusion of a peer grouping step, implemented to the 2021 Overall Star Rating methods. Objective: To calculate hospital star rating scores with and without the peer grouping step, with the former approach stratifying hospitals into 3-, 4-, and 5-measure group peer groups based on the number of measure groups with at least 3 reported measures. Design, Setting, and Participants: This cross-sectional study used Care Compare website data from January 2023 for 3076 hospitals that received a star rating in 2023. Data were analyzed from April 2023 to December 2023. Exposure: Peer grouping vs no peer grouping. Main Outcomes and Measures: The primary outcome was the distribution of star ratings, with 1 star being the lowest-performing hospitals and 5 stars, the highest. Analyses additionally identified the number of hospitals with a higher, lower, or identical star rating with the use of the peer grouping step compared with its nonuse, stratified by certain hospital characteristics. Results: Among 3076 hospitals that received a star rating in 2023, most were nonspecialty (1994 hospitals [64.8%]), nonteaching (1807 hospitals [58.7%]), non-safety net (2326 hospitals [75.6%]), non-critical access (2826 hospitals [91.9%]) hospitals with fewer than 200 beds (1822 hospitals [59.2%]) and located in an urban geographic designations (1935 hospitals [62.9%]). The presence of the peer grouping step resulted in 585 hospitals (19.0%) being assigned a different star rating than if the peer grouping step was absent, including considerably more hospitals receiving a higher star rating (517 hospitals) rather than a lower (68 hospitals) star rating. Hospital characteristics associated with a higher star rating included urbanicity (351 hospitals [67.9%]), non-safety net status (414 hospitals [80.1%]), and fewer than 200 beds (287 hospitals [55.6%]). Collectively, the presence of the peer grouping step supports a like-to-like comparison among hospitals and supports the ability of patients to assess overall hospital quality. Conclusions and Relevance: In this cross-sectional study, inclusion of the peer grouping in the CMS star rating method resulted in modest changes in hospital star ratings compared with application of the method without peer grouping. Given improvement in face validity and the close association between the current peer grouping approach and stakeholder needs for peer-comparison, the current CMS Overall Star Rating method allows for durable comparisons in hospital performance.

Pre-COVID-19 hospital quality and hospital response to COVID-19: examining associations between risk-adjusted mortality for patients hospitalised with COVID-19 and pre-COVID-19 hospital quality.

OBJECTIVES: The extent to which care quality influenced outcomes for patients hospitalised with COVID-19 is unknown. Our objective was to determine if prepandemic hospital quality is associated with mortality among Medicare patients hospitalised with COVID-19. DESIGN: This is a retrospective observational study. We calculated hospital-level risk-standardised in-hospital and 30-day mortality rates (risk-standardised mortality rates, RSMRs) for patients hospitalised with COVID-19, and correlation coefficients between RSMRs and pre-COVID-19 hospital quality, overall and stratified by hospital characteristics. SETTING: Short-term acute care hospitals and critical access hospitals in the USA. PARTICIPANTS: Hospitalised Medicare beneficiaries (Fee-For-Service and Medicare Advantage) age 65 and older hospitalised with COVID-19, discharged between 1 April 2020 and 30 September 2021. INTERVENTION/EXPOSURE: Pre-COVID-19 hospital quality. OUTCOMES: Risk-standardised COVID-19 in-hospital and 30-day mortality rates (RSMRs). RESULTS: In-hospital (n=4256) RSMRs for Medicare patients hospitalised with COVID-19 (April 2020-September 2021) ranged from 4.5% to 59.9% (median 18.2%; IQR 14.7%-23.7%); 30-day RSMRs ranged from 12.9% to 56.2% (IQR 24.6%-30.6%). COVID-19 RSMRs were negatively correlated with star rating summary scores (in-hospital correlation coefficient -0.41, p<0.0001; 30 days -0.38, p<0.0001). Correlations with in-hospital RSMRs were strongest for patient experience (-0.39, p<0.0001) and timely and effective care (-0.30, p<0.0001) group scores; 30-day RSMRs were strongest for patient experience (-0.34, p<0.0001) and mortality (-0.33, p<0.0001) groups. Patients admitted to 1-star hospitals had higher odds of mortality (in-hospital OR 1.87, 95% CI 1.83 to 1.91; 30-day OR 1.46, 95% CI 1.43 to 1.48) compared with 5-star hospitals. If all hospitals performed like an average 5-star hospital, we estimate 38 000 fewer COVID-19-related deaths would have occurred between April 2020 and September 2021. CONCLUSIONS: Hospitals with better prepandemic quality may have care structures and processes that allowed for better care delivery and outcomes during the COVID-19 pandemic. Understanding the relationship between pre-COVID-19 hospital quality and COVID-19 outcomes will allow policy-makers and hospitals better prepare for future public health emergencies.

Patient-Reported Outcome-Based Performance Measures in Alternative Payment Models: Current Use, Implementation Barriers, and Principles to Succeed.

OBJECTIVES: Patient-reported outcome (PRO)-based performance measures (PRO-PMs) offer opportunities to aggregate survey data into a reliable and valid assessment of performance at the entity-level (eg, clinician, hospital, and accountable care organization). Our objective was to address the existing literature gap regarding the implementation barriers, current use, and principles for PRO-PMs to succeed. METHODS: As quality measurement experts, we first highlighted key principles of PRO-PMs and how alternative payment models (APMs) may be integral in promoting more widespread use. In May 2023, we reviewed the Centers for Medicare and Medicaid Services (CMS) Measures Inventory Tool for active PRO-PM usage within CMS programs. We finally present principles to prioritize as part PRO-PMs succeeding within APMs. RESULTS: We identified 5 implementation barriers to PRO-PM use: original development of instrument, response rate sufficiency, provider burden, hesitancy regarding fairness, and attribution of desired outcomes. There existed 54 instances of active PRO-PM usage across CMS programs, including 46 unique PRO-PMs within 14 CMS programs. Five principles to prioritize as part of greater PRO-PM development and incorporation within APMs include the following: (1) clinical salience, (2) adequate sample size, (3) meaningful range of performance among measured entities and the ability to detect performance change in a reasonable time frame, (4) equity focus, and (5) appropriate risk adjustment. CONCLUSIONS: Identified barriers and principles to prioritize should be considered during PRO-PM development and implementation phases to link available and novel measures to payment programs while ensuring provider and stakeholder engagement.

Implementation of a Best Practice Advisory to Improve Infection Screening Prior to New Prescriptions of Biologics and Targeted Synthetic Drugs.

OBJECTIVE: Use of biologic and targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) in patients with preexisting tuberculosis (TB), hepatitis B virus (HBV), or hepatitis C virus (HCV) infection can have serious consequences. Although various society guidelines recommend routine screening for these infections before initiating certain b/tsDMARDs, adherence to these recommendations varies widely. This quality improvement initiative evaluated local compliance with screening and assessed whether an automated computerized decision support system in the form of a best practice advisory (BPA) in the electronic health record could improve patient screening. METHODS: Established patients with autoimmune rheumatic disease (ARD) aged 18 years or older with at least one visit to our rheumatology practice between October 1, 2017, and March 3, 2022, were included. When prescribing a new b/tsDMARD, clinicians were alerted via a BPA that showed the most recent results for TB, HBV, and HCV. Screening proportions for TB, HBV, and HCV before BPA initiation were compared with those of eligible patients after the BPA implementation. RESULTS: A total of 711 patients pre-BPA and 257 patients post-BPA implementation were included in the study. The BPA implementation was associated with statistically significant improvement in screening for TB from 66% to 82% (P ≤ 0.001), HCV from 60% to 79% (P ≤ 0.001), hepatitis B core antibody 32% to 51% (P ≤ 0.001), and hepatitis B surface antigen from 51% to 70% (P ≤ 0.001). CONCLUSION: Implementation of a BPA can improve infectious disease screening for patients with ARD who are started on b/tsDMARDs and has potential to improve patient safety.

Development of American College of Rheumatology Quality Measures for Systemic Lupus Erythematosus: A Modified Delphi Process With Rheumatology Informatics System for Effectiveness (RISE) Registry Data Review.

OBJECTIVE: We aimed to develop readily measurable digital quality measure statements for clinical care in systemic lupus erythematosus (SLE) using a multistep process guided by consensus methods. METHODS: Using a modified Delphi process, an American College of Rheumatology (ACR) workgroup of SLE experts reviewed all North American and European guidelines from 2000 to 2020 on treatment, monitoring, and phenotyping of patients with lupus. Workgroup members extracted quality constructs from guidelines, rated these by importance and feasibility, and generated evidence-based quality measure statements. The ACR Rheumatology Informatics System for Effectiveness (RISE) Registry was queried for measurement data availability. In 3 consecutive Delphi sessions, a multidisciplinary Delphi panel voted on the importance and feasibility of each statement. Proposed measures with consensus on feasibility and importance were ranked to identify the top 3 measures. RESULTS: Review of guidelines and distillation of 57 quality constructs resulted in 15 quality measure statements. Among these, 5 met high consensus for importance and feasibility, including 2 on treatment and 3 on laboratory monitoring measures. The 3 highest-ranked statements were recommended for further measure specification as SLE digital quality measures: 1) hydroxychloroquine use, 2) limiting glucocorticoid use >7.5 mg/day to <6 months, and 3) end-organ monitoring of kidney function and urine protein excretion at least every 6 months. CONCLUSION: The Delphi process selected 3 quality measures for SLE care on hydroxychloroquine, glucocorticoid reduction, and kidney monitoring. Next, measures will undergo specification and validity testing in RISE and US rheumatology practices as the foundation for national implementation and use in quality improvement programs.

Cost-Effectiveness of Surgical Weight-Loss Interventions for Patients With Knee Osteoarthritis and Class III Obesity.

OBJECTIVE: Class III obesity (body mass index [BMI] ≥40 kg/m2 ) is associated with worse knee pain and total knee replacement (TKR) outcomes. Because bariatric surgery yields sustainable weight loss for individuals with BMI ≥40 kg/m2 , our objective was to establish the value of Roux-en-Y gastric bypass (RYGB) and laparoscopic sleeve gastrectomy (LSG) in conjunction with usual care for knee osteoarthritis (OA) patients with BMI ≥40 kg/m2 . METHODS: We used the Osteoarthritis Policy model to assess long-term clinical benefits, costs, and cost-effectiveness of RYGB and LSG. We derived model inputs for efficacy, costs, and complications associated with these treatments from published data. Primary outcomes included quality-adjusted life-years (QALYs), lifetime costs, and incremental cost-effectiveness ratios (ICERs), all discounted at 3%/year. This analysis was conducted from a health care sector perspective. We performed sensitivity analyses to evaluate uncertainty in input parameters. RESULTS: The usual care + RYGB strategy increased the quality-adjusted life expectancy by 1.35 years and lifetime costs by $7,209, compared to usual care alone (ICER = $5,300/QALY). The usual care + LSG strategy yielded less benefit than usual care + RYGB and was dominated. Relative to usual care alone, both usual care + RYGB and usual care + LSG reduced opioid use from 13% to 4%, and increased TKR usage from 30% to 50% and 41%, respectively. For cohorts with BMI between 38 and 41 kg/m2 , usual care + LSG dominated usual care + RYGB. In the probabilistic sensitivity analysis, at a willingness-to-pay threshold of $50,000/QALY, usual care + RYGB and usual care + LSG were cost-effective in 70% and 30% of iterations, respectively. CONCLUSION: RYGB offers good value among knee OA patients with BMI ≥40 kg/m2 , while LSG may provide good value among those with BMI between 35 and 41 kg/m2 .

Taxonomy of Quality of Care Indicators: Tracing the Path from Clinical Practice Guidelines to Quality Measurement and Beyond.

Quality measures (QMs) are tools that help measure or quantify health care processes, outcomes, patient perceptions, and organizational structures and systems associated with the ability to provide high-quality health care. QMs are often developed from clinical practice guidelines (CPGs), as they summarize the best available evidence to create standards for optimizing patient care. The authors provide a framework for learners to understand the relevance, development, and testing of QMs in rheumatology, touching on their relationship to CPGs and appropriate use criteria. They describe measure implementation across different health care settings and reflect on challenges and opportunities associated with this process.

Cost-Effectiveness of Arthroscopic Partial Meniscectomy and Physical Therapy for Degenerative Meniscal Tear.

OBJECTIVE: We examined the cost-effectiveness of treatment strategies for concomitant meniscal tear and knee osteoarthritis (OA) involving arthroscopic partial meniscectomy surgery and physical therapy (PT). METHODS: We used the Osteoarthritis Policy Model, a validated Monte Carlo microsimulation, to compare three strategies, 1) PT-only, 2) immediate surgery, and 3) PT + optional surgery, for participants whose pain persists following initial PT. We modeled a cohort with baseline meniscal tear, OA, and demographics from the Meniscal Tear in Osteoarthritis Research (MeTeOR) trial of arthroscopic partial meniscectomy versus PT. We estimated risks and costs of arthroscopic partial meniscectomy complications and accounted for heightened OA progression post surgery using published data. We estimated surgery use rates and treatment efficacies using MeTeOR data. We considered a 5-year time horizon, discounted costs, and quality-adjusted life-years (QALYs) 3% per year and conducted sensitivity analyses. We report incremental cost-effectiveness ratios. RESULTS: Relative to PT-only, PT + optional surgery added 0.0651 QALY and $2,010 over 5 years (incremental cost-effectiveness ratio = $30,900 per QALY). Relative to PT + optional surgery, immediate surgery added 0.0065 QALY and $3080 (incremental cost-effectiveness ratio = $473,800 per QALY). Incremental cost-effectiveness ratios were sensitive to optional surgery efficacy in the PT + optional surgery strategy. In the probabilistic sensitivity analysis, PT + optional surgery was cost-effective in 51% of simulations at willingness-to-pay thresholds of both $50,000 per QALY and $100,000 per QALY. CONCLUSION: First-line arthroscopic partial meniscectomy has a prohibitively high incremental cost-effectiveness ratio. Under base case assumptions, second-line arthroscopic partial meniscectomy offered to participants with persistent pain following initial PT is cost-effective at willingness-to-pay thresholds between $31,000 and $473,000 per QALY. Our analyses suggest that arthroscopic partial meniscectomy can be a high-value treatment option for patients with meniscal tear and OA when performed following an initial PT course and should remain a covered treatment option.

Time Trends in Patient Characteristics and In-Hospital Adverse Events for Primary Total Knee Arthroplasty in the United States: 2010-2017.

BACKGROUND: Perioperative care for total knee arthroplasty (TKA) has improved over time. We present an analysis of inpatient safety after TKA. METHODS: 14,057 primary TKAs captured by the Medicare Patient Safety Monitoring System between 2010 and 2017 were retrospectively reviewed. We calculated changes in demographics, comorbidities, and adverse events (AEs) over time. Risk factors for AEs were also assessed. RESULTS: Between 2010 and 2017, there was an increased prevalence of obesity (35.1% to 57.6%), tobacco smoking (12.5% to 17.8%), and renal disease (5.2% to 8.9%). There were reductions in coronary artery disease (17.3% to 13.4%) and chronic warfarin use (6.7% to 3.1%). Inpatient AEs decreased from 4.9% to 2.5%, (P < .01), primarily driven by reductions in anticoagulant-associated AEs, including major bleeding and hematomas (from 2.8% to 1.0%, P < .001), catheter-associated urinary tract infections (1.1% to 0.2%, P < .001), pressure ulcers (0.8% to 0.2%, P < .001), and venous thromboembolism (0.3% to 0.1%, P = .04). The adjusted annual decline in the risk of developing any in-hospital AE was 14% (95% confidence interval [CI] 10%-17%). Factors associated with developing an AE were advanced age (odds ratio [OR] = 1.01, 95% CI 1.00-1.01), male sex (OR = 1.21, 95% CI 1.02-1.44), coronary artery disease (OR = 1.35, 95% CI 1.07-1.70), heart failure (OR = 1.70, 95% CI 1.20-2.41), and renal disease (OR = 1.71, 95% CI 1.23-2.37). CONCLUSIONS: Despite increasing prevalence of obesity, tobacco smoking, and renal disease, inpatient AEs after primary TKA have decreased over the past several years. This improvement is despite the increasing complexity of the inpatient TKA population over time.

Socioeconomic Disparities in Functional Status in a National Sample of Patients With Rheumatoid Arthritis.

Importance: Little is known about the association of poverty with functional status (FS) in patients with rheumatoid arthritis (RA) who use rheumatology care. Objectives: To examine the association between socioeconomic status (SES) and FS among patients with RA and to evaluate the association between SES and functional declines over time in patients who received at least some rheumatology care. Design, Setting, and Participants: This cohort study used data from the American College of Rheumatology's Rheumatology Informatics System for Effectiveness (RISE) registry between January 1, 2016, and December 31, 2018. Analyses included all adult patients with a confirmed RA diagnosis (ie, had ≥2 encounters associated with RA International Classification of Diseases codes ≥30 days apart) and at least 1 FS score documented between 2016 and 2018 seen at participating rheumatology practices. Data analysis was conducted from April to December 2020. Exposures: The Area Deprivation Index (ADI), a zip code-based indicator of neighborhood poverty, was used as a proxy for SES. ADI scores were categorized into quintiles. Main Outcomes and Measures: FS measures included Multidimensional Health Assessment Questionnaire (MDHAQ), Health Assessment Questionnaire Disability index, and Health Assessment Questionnaire-II. Cross-sectionally, mean FS scores were compared across ADI quintiles. Longitudinally, among patients with at least 2 FS scores, multilevel multivariate regression computed the probability of functional decline, defined as a change greater than the minimum clinically important difference, across ADI quintiles. In a subgroup analysis, whether disease activity mediated the association between SES and functional decline was examined. Results: Of the 83 965 patients included in the study, 66 649 (77%) were women, and 60 037 (72%) were non-Hispanic White. Mean (SD) age was 63.4 (13.7) years. MDHAQ was the most reported FS measure (56 928 patients [67.8%]). For all measures, mean (SD) FS score was worse at lower SES levels (eg, for MDHAQ quintile 1: 1.79 [1.87]; quintile 5: 2.43 [2.17]). In longitudinal analyses, the probability of functional decline was 14.1% (95% CI, 12.5%-15.7%) in the highest SES quintile and 18.9% (95% CI, 17.1%-20.7%) in the lowest SES quintile. The association between SES and functional decline was partially mediated (7%; 95% CI, 4%-22%) by disease activity. Conclusions and Relevance: In this cohort study of patients with RA, worse FS and faster declines in functioning over time were observed in patients with lower SES. These findings provide a framework for monitoring disparities in RA and for generating evidence to spur action toward achieving health equity.

Administrative Claims Measure for Profiling Hospital Performance Based on 90-Day All-Cause Mortality Following Coronary Artery Bypass Graft Surgery.

BACKGROUND: Coronary artery bypass graft (CABG) surgery is a focus of bundled and alternate payment models that capture outcomes up to 90 days postsurgery. While clinical registry risk models perform well, measures encompassing mortality beyond 30 days do not currently exist. We aimed to develop a risk-adjusted hospital-level 90-day all-cause mortality measure intended for assessing hospital performance in payment models of CABG surgery using administrative data. METHODS: Building upon Centers for Medicare and Medicaid Services hospital-level 30-day all-cause CABG mortality measure specifications, we extended the mortality timeframe to 90 days after surgery and developed a new hierarchical logistic regression model to calculate hospital risk-standardized 90-day all-cause mortality rates for patients hospitalized for isolated CABG. The model was derived from Medicare claims data for a 3-year cohort between July 2014 to June 2017. The data set was randomly split into 50:50 development and validation samples. The model performance was evaluated with C statistics, overfitting indices, and calibration plot. The empirical validity of the measure result at the hospital level was evaluated against the Society of Thoracic Surgeons composite star rating. RESULTS: Among 137 819 CABG procedures performed in 1183 hospitals, the unadjusted mortality rate within 30 and 90 days were 3.1% and 4.7%, respectively. The final model included 27 variables. Hospital-level 90-day risk-standardized mortality rates ranged between 2.04% and 11.26%, with a median of 4.67%. C statistics in the development and validation samples were 0.766 and 0.772, respectively. We identified a strong positive correlation between 30- and 90-day risk-standardized mortality rates, with a regression slope of 1.09. Risk-standardized mortality rates also showed a stepwise trend of lower 90-day mortality with higher Society of Thoracic Surgeons composite star ratings. CONCLUSIONS: We present a measure of hospital-level 90-day risk-standardized mortality rates following isolated CABG. This measure complements Centers for Medicare and Medicaid Services' existing 30-day CABG mortality measure by providing greater insight into the postacute recovery period. It offers a balancing measure to ensure efforts to reduce costs associated with CABG recovery and rehabilitation do not result in unintended consequences.

Identification of Hospitals That Care for a High Proportion of Patients With Social Risk Factors.

Importance: Hospitals can face significant clinical and financial challenges in caring for patients with social risk factors. Currently the Hospital Readmission Reduction Program stratifies hospitals by proportion of patients eligible for both Medicare and Medicaid when calculating payment penalties to account for the patient population. However, additional social risk factors should be considered. Objective: To evaluate 7 different definitions of social risk and understand the degree to which differing definitions identify the same hospitals caring for a high proportion of patients with social risk factors. Design Setting and Participants: Across 18 publicly reported Centers for Medicare & Medicaid Services (CMS) hospital performance measures, highly disadvantaged hospitals were identified by the the proportion of patients with social risk factors using the following 7 commonly used definitions of social risk: living below the US poverty line, educational attainment of less than high school, unemployment, living in a crowded household, African American race (as a proxy for the social risk factor of exposure to racism), Medicaid coverage, and Agency for Healthcare Research and Quality index of socioeconomic status score. In this cross-sectional study, social risk factors were evaluated by measure because hospitals may serve a disadvantaged patient population for one measure but not another. Data were collected from April 1, 2014, to June 30, 2017, and analyzed from July 25, 2019, to April 25, 2021. Main Outcomes and Measures: The proportion of hospitals identified as caring for patients with social risk factors using 7 definitions of social risk, across 18 publicly reported CMS hospital performance measures. Results: Among 4465 hospitals, a mean of 31.0% (range, 28.9%-32.3%) were identified at least once when using the 7 definitions of social risk as caring for a high proportion of patients with social risk factors. Among all hospitals meeting at least 1 definition of social risk, a mean of 0.7% (range, 0%-1.0%) were identified as highly disadvantaged by all 7 definitions. Among hospitals meeting at least 1 definition of social risk, a mean of 2.7% (range, 1.3%-5.1%) were identified by 6 definitions; 6.5% (range, 5.9%-7.1%), by 5 definitions; 10.4% (range, 9.5%-12.1%), by 4 definitions; 13.2% (range, 10.1%-14.4%), by 3 definitions; 21.4% (range, 20.1%-22.4%), by 2 definitions; and 45.2% (range, 42.6%-47.1%), by only 1 definition. This pattern was consistent across all 18 performance measures. Conclusions and Relevance: In this cross-sectional study, there were inconsistencies in the identification of hospitals caring for disadvantaged populations using different definitions of social risk factors. Without consensus on how to define disadvantaged hospitals, policies to support such hospitals may be applied inconsistently.

Adaptation of American College of Rheumatology Rheumatoid Arthritis Disease Activity and Functional Status Measures for Telehealth Visits.

OBJECTIVE: To provide guidance on the implementation of recommended American College of Rheumatology (ACR) rheumatoid arthritis (RA) disease activity and functional status assessment measures in telehealth settings. METHODS: An expert panel was assembled from the recently convened ACR RA disease activity and functional status measures working groups to summarize strategies for implementation of ACR-recommended RA disease activity (the Clinical Disease Activity Index [CDAI], Disease Activity Score in 28 joints using the erythrocyte sedimentation rate or the C-reactive protein level [DAS28-ESR/CRP], Patient Activity Scale II [PAS-II], Simplified Disease Activity Index [SDAI], and Routine Assessment of Patient Index Data 3 [RAPID3]) and functional status (the Health Assessment Questionnaire II [HAQ-II], Multidimensional Health Assessment Questionnaire [MDHAQ], and PROMIS physical function 10-item short form [PROMIS PF-10]) measures in telehealth settings. RESULTS: Measures composed of patient-reported items (disease activity: PAS-II, RAPID3; functional status: HAQ-II, MDHAQ, PROMIS PF-10) require minimal modification for use in telehealth settings. Measures requiring formal joint counts (the CDAI, DAS28-ESR/CRP, and SDAI) can be calculated using patient-reported swollen and tender joint counts. When the feasibility of laboratory testing is limited, the CDAI can be used in place of the SDAI, and scoring modifications of the DAS28-ESR/CRP without the acute-phase reactant are available. Assessment of the validity of these modifications is limited. Implementation of these measures can be facilitated by electronic health record collection, mobile applications, and provider/staff administration during telehealth visits. CONCLUSION: The ACR-recommended RA disease activity and functional status measures can be adapted for use in telehealth settings to support high-quality clinical care. Research is needed to better understand how telehealth settings may impact the validity of these measures.

Quality Measure Public Reporting Is Associated with Improved Outcomes Following Hip and Knee Replacement.

BACKGROUND: Given the inclusion of orthopaedic quality measures in the Centers for Medicare & Medicaid Services national hospital payment programs, the present study sought to assess whether the public reporting of total hip arthroplasty (THA) and total knee arthroplasty (TKA) risk-standardized readmission rates (RSRRs) and complication rates (RSCRs) was temporally associated with a decrease in the rates of these outcomes among Medicare beneficiaries. METHODS: Annual trends in national observed and hospital-level RSRRs and RSCRs were evaluated for patients who underwent hospital-based inpatient hip and/or knee replacement procedures from fiscal year 2010 to fiscal year 2016. Hospital-level rates were calculated with use of the same measures and methodology that were utilized in public reporting. Annual trends in the distribution of hospital-level outcomes were then examined with use of density plots. RESULTS: Complication and readmission rates and variation declined steadily from fiscal year 2010 to fiscal year 2016. Reductions of 33% and 25% were noted in hospital-level RSCRs and RSRRs, respectively. The interquartile range decreased by 18% (relative reduction) for RSCRs and by 34% (relative reduction) for RSRRs. The frequency of risk variables in the complication and readmission models did not systematically change over time, suggesting no evidence of widespread bias or up-coding. CONCLUSIONS: This study showed that hospital-level complication and readmission rates following THA and TKA and the variation in hospital-level performance declined during a period coinciding with the start of public reporting and financial incentives associated with measurement. The consistently decreasing trend in rates of and variation in outcomes suggests steady improvements and greater consistency among hospitals in clinical outcomes for THA and TKA patients in the 2016 fiscal year compared with the 2010 fiscal year. The interactions between public reporting, payment, and hospital coding practices are complex and require further study. LEVEL OF EVIDENCE: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Timely estimation of National Admission, readmission, and observation-stay rates in medicare patients with acute myocardial infarction, heart failure, or pneumonia using near real-time claims data.

BACKGROUND: To estimate, prior to finalization of claims, the national monthly numbers of admissions and rates of 30-day readmissions and post-discharge observation-stays for Medicare fee-for-service beneficiaries hospitalized with acute myocardial infarction (AMI), heart failure (HF), or pneumonia. METHODS: The centers for Medicare & Medicaid Services (CMS) Integrated Data Repository, including the Medicare beneficiary enrollment database, was accessed in June 2015, February 2017, and February 2018. We evaluated patterns of delay in Medicare claims accrual, and used incomplete, non-final claims data to develop and validate models for real-time estimation of admissions, readmissions, and observation stays. RESULTS: These real-time reporting models accurately estimate, within 2 months from admission, the monthly numbers of admissions, 30-day readmission and observation-stay rates for patients with AMI, HF, or pneumonia. CONCLUSIONS: This work will allow CMS to track the impact of policy decisions in real time and enable hospitals to better monitor their performance nationally.