Comparative Performance of Three Claims-Based Frailty Measures Among Medicare Beneficiaries.

Frailty is an important predictor of mortality, health care costs and utilization, and health outcomes. Validated measures of frailty are not consistently collected during clinical encounters, making comparisons across populations challenging. However, several claims-based algorithms have been developed to predict frailty and related concepts. This study compares performance of three such algorithms among Medicare beneficiaries. Claims data from 12-month continuous enrollment periods were selected during 2014-2016. Frailty scores, calculated using previously developed algorithms from Faurot, Kim, and RAND, were added to baseline regression models to predict claims-based outcomes measured in the following year. Root mean square error and area under the receiver operating characteristic curve were calculated for each model and outcome combination and tested in subpopulations of interest. Overall, Kim models performed best across most outcomes, metrics, and subpopulations. Kim frailty scores may be used by health systems and researchers for risk adjustment or targeting interventions.

Development and Validation of Algorithms to Predict Activity, Mobility, and Memory Limitations Using Medicare Claims and Post-Acute Care Assessments.

Functional impairment predicts mortality and health care utilization. However, validated measures of functional impairment are not routinely collected during clinical encounters and are impractical to use for large-scale risk-adjustment or targeting interventions. This study's purpose was to develop and validate claims-based algorithms to predict functional impairment using Medicare Fee-for-Service (FFS) 2014-2017 claims data linked with post-acute care (PAC) assessment data and weighted to better represent the overall Medicare FFS population. Using supervised machine learning, predictors were identified that best predicted two functional impairment outcomes measured in PAC data-any memory limitation and a count of 0-6 activity/mobility limitations. The memory limitation algorithm had moderately high sensitivity and specificity. The activity/mobility limitations algorithm performed well in identifying beneficiaries with five or more limitations, but overall accuracy was poor. This dataset shows promise for use in PAC populations, though generalizability to broader older adult populations remains a challenge.

Understanding the social risk factor adjustment's effect on Star Ratings.

OBJECTIVES: CMS implemented the Categorical Adjustment Index (CAI) to address measurement bias in the Medicare Advantage (MA) Star Ratings, as unadjusted scores may disadvantage MA contracts serving more enrollees at greater social risk. CAI values are added to a contract's Star Ratings to adjust for the mean within-contract performance disparity associated with its percentage of enrollees with low socioeconomic status (ie, receipt of a Part D low-income subsidy or dual eligibility for Medicare and Medicaid [LIS/DE]) and who are disabled. We examined the CAI's effect on Star Ratings and the type of contracts affected. STUDY DESIGN: Observational study of MA contracts with health and prescription drug coverage. METHODS: We compared adjusted and unadjusted 2017-2020 Star Ratings overall and by contracts' proportion of LIS/DE and disabled enrollees. We assessed the CAI's effect on qualifying for quality bonus payments (QBPs), eligibility for rebate payments, and high-performing and low-performing designations. RESULTS: The CAI's impact was modest overall (3.2%-14.9% of contracts experienced one-half Star Rating changes). Upward changes were concentrated among contracts with high percentages of LIS/DE or disabled enrollees (7.7%-32.3% of these contracts saw increased Star Ratings). In 2020, 26.0% of contracts with a high proportion of LIS/DE or disabled enrollees that qualified for a QBP did so because of the CAI. CONCLUSIONS: The CAI primarily affected contracts with high LIS/DE or disabled enrollment, which received higher Star Ratings because of the CAI. The adjustment helps ensure that such contracts' performance is not understated and reduces incentives for MA contracts to avoid patients at greater social risk.

Imputation of Race and Ethnicity in Health Insurance Marketplace Enrollment Data, 2015-2022 Open Enrollment Periods.

Information on the race and ethnicity of individuals enrolled through the HealthCare.gov Health Insurance Marketplace is critical for assessing past enrollment efforts and determining whether outreach campaigns should be modified or tailored moving forward. However, approximately one-third of insurance applicants do not complete the race and Hispanic ethnicity questions on the Marketplace application. When self-reported race and ethnicity information is missing, other information about an individual can be used to infer race and ethnicity, such as surnames, first names, and addresses, with each characteristic contributing meaningfully to the identification of six mutually exclusive racial and ethnic groups: American Indian (AI)/Alaskan Native (AN); Asian American, Native Hawaiian, and Pacific Islander (AANHPI); Black; Hispanic; Multiracial; and White. Surnames are particularly useful for distinguishing people who identify as Hispanic and AANHPI from other racial and ethnic groups. Geocoded address information is particularly useful in distinguishing Black and White individuals who frequently reside in racially segregated neighborhoods. This article presents the results of imputing race and ethnicity for Marketplace enrollees from 2015 through 2022 using the modified Bayesian Improved First Name Surname and Geocoding (BIFSG) method, developed by the RAND Corporation, which uses surnames, first names, and residential addresses to indirectly estimate race and ethnicity.

Health Care Costs and Opioid Use Associated With High-impact Chronic Spinal Pain in the United States.

STUDY DESIGN: A descriptive analysis of secondary data. OBJECTIVE: The aim of this study was to estimate health care costs and opioid use for those with high-impact chronic spinal (back and neck) pain. SUMMARY OF BACKGROUND DATA: The US National Pain Strategy introduced a focus on high-impact chronic pain-that is, chronic pain associated with work, social, and self-care restrictions. Chronic neck and low-back pain are common, costly, and associated with long-term opioid use. Although chronic pain is not homogenous, most estimates of its costs are averages that ignore severity (impact). METHODS: We used 2003 to 2015 Medical Expenditures Panel Survey (MEPS) data to identify individuals with chronic spinal pain, their health care expenditures, and use of opioids. We developed prediction models to identify those with high- versus moderate- and low-impact chronic spinal pain based on the variables available in MEPS. RESULTS: We found that overall and spine-related health care costs, and the use and dosage of opioids increased significantly with chronic pain impact levels. Overall and spine-related annual per person health care costs for those with high-impact chronic pain ($14,661 SE: $814; and $5979 SE: $471, respectively) were more than double that of those with low-impact, but still clinically significant, chronic pain ($6371 SE: $557; and $2300 SE: $328). Those with high-impact chronic spinal pain also use spine-related opioids at a rate almost four times that of those with low-impact pain (48.4% vs. 12.4%), and on average use over five times the morphine equivalent daily dose (MEDD) in mg (15.3 SE: 1.4 vs. 2.7 SE: 0.6). Opioid use and dosing increased significantly across years, but the increase in inflation-adjusted health care costs was not statistically significant. CONCLUSION: Although most studies of chronic spinal pain do not differentiate participants by the impact of their chronic pain, these estimates highlight the importance of identifying chronic pain levels and focusing on those with high-impact chronic pain. LEVEL OF EVIDENCE: 3.

Perspectives on Opportunities and Challenges for Medicare Advantage Plans to Address Social Determinants of Health via the CHRONIC Care Act.

There is increasing recognition of the role of social determinants of health (SDOH) in the ability of Medicare Advantage (MA) enrollees to obtain needed care. The 2018 CHRONIC Care Act established Special Supplemental Benefits for the Chronically Ill (SSBCI), which for the first time gives MA plans the flexibility to provide supplemental benefits to enrollees to address SDOH. Given the role of SDOH in chronic disease, this represents an opportunity for MA plans to address underlying issues not strictly health care related with which MA enrollees struggle and that affect their overall health. MA plans have experimented with different approaches to address SDOH but have been limited by the lack of ability to offer services as part of covered benefits and reliance on partnerships, grants, and other funding sources to support the provision of these services. The effect of this policy and how it may evolve before implementation begins in 2020 remains uncertain as we wait to see how MA plans will interpret eligibility criteria and services offered without any additional allotted funding.

Patient Willingness to Pay for Reductions in Chronic Low Back Pain and Chronic Neck Pain.

Many recommended nonpharmacologic therapies for patients with chronic spinal pain require visits to providers such as acupuncturists and chiropractors. Little information is available to inform third-party payers' coverage policies regarding ongoing use of these therapies. This study offers contingent valuation-based estimates of patient willingness to pay (WTP) for pain reductions from a large (n = 1,583) sample of patients using ongoing chiropractic care to manage their chronic low back and neck pain. Average WTP estimates were $45.98 (45.8) per month per 1-point reduction in current pain for chronic low back pain and $37.32 (38.0) for chronic neck pain. These estimates met a variety of validity checks including that individuals' values define a downward-sloping demand curve for these services. Comparing these WTP estimates with patients' actual use of chiropractic care over the next 3 months indicates that these patients are likely "buying" perceived pain reductions from what they believe their pain would have been if they didn't see their chiropractor-that is, they value maintenance of their current mild pain levels. These results provide some evidence for copay levels and their relationship to patient demand, but call into question ongoing coverage policies that require the documentation of continued improvement or of experienced clinical deterioration with treatment withdrawal. PERSPECTIVE: This study provides estimates of reported WTP for pain reduction from a large sample of patients using chiropractic care to manage their chronic spinal pain and compares these estimates to what these patients do for care over the next 3 months, to inform coverage policies for ongoing care.

Are Nonpharmacologic Interventions for Chronic Low Back Pain More Cost Effective Than Usual Care? Proof of Concept Results From a Markov Model.

STUDY DESIGN: Markov model. OBJECTIVE: Examine the 1-year effectiveness and cost-effectiveness (societal and payer perspectives) of adding nonpharmacologic interventions for chronic low back pain (CLBP) to usual care using a decision analytic model-based approach. SUMMARY OF BACKGROUND DATA: Treatment guidelines now recommend many safe and effective nonpharmacologic interventions for CLBP. However, little is known regarding their effectiveness in subpopulations (e.g., high-impact chronic pain patients), nor about their cost-effectiveness. METHODS: The model included four health states: high-impact chronic pain (substantial activity limitations); no pain; and two others without activity limitations, but with higher (moderate-impact) or lower (low-impact) pain. We estimated intervention-specific transition probabilities for these health states using individual patient-level data from 10 large randomized trials covering 17 nonpharmacologic therapies. The model was run for nine 6-week cycles to approximate a 1-year time horizon. Quality-adjusted life-year weights were based on six-dimensional health state short form scores; healthcare costs were based on 2003 to 2015 Medical Expenditure Panel Survey data; and lost productivity costs used in the societal perspective were based on reported absenteeism. Results were generated for two target populations: (1) a typical baseline mix of patients with CLBP (25% low-impact, 35% moderate-impact, and 40% high-impact chronic pain) and (2) high-impact chronic pain patients. RESULTS: From the societal perspective, all but two of the therapies were cost effective (<$50,000/quality-adjusted life-year) for a typical patient mix and most were cost saving. From the payer perspective fewer were cost saving, but the same number was cost-effective. Assuming all patients in the model have high-impact chronic pain increases the effectiveness and cost-effectiveness of most, but not all, therapies indicating that substantial benefits are possible in this subpopulation. CONCLUSION: Modeling leverages the evidence produced from clinical trials to provide more information than is available in the published studies. We recommend modeling for all existing studies of nonpharmacologic interventions for CLBP. LEVEL OF EVIDENCE: 4.

Reducing disparities requires multiple strategies.

Disparities in care are a complex issue requiring multiple strategies to solve, including approaches to improve the measurement of quality and reporting stratified performance estimates.

Adjusting Medicare Advantage star ratings for socioeconomic status and disability.

OBJECTIVES: Studies have identified potential unintended effects of not adjusting clinical performance measures in value-based purchasing programs for socioeconomic status (SES) factors. We examine the impact of SES and disability adjustments on Medicare Advantage (MA) plans' and prescription drug plans' (PDPs') contract star ratings. These analyses informed the development of the Categorical Adjustment Index (CAI), which CMS implemented with the 2017 star ratings. STUDY DESIGN: Retrospective analyses of MA and PDP performance using 2012 Medicare beneficiary-level characteristics and performance data from the Star Rating Program. METHODS: We modeled within-contract associations of beneficiary SES (Medicaid and Medicare dual eligibility [DE] or receipt of a low-income subsidy [LIS]) and disability with performance on 16 clinical measures. We estimated variability in contract-level DE/LIS and disability disparities using mixed-effects regression models. We simulated the impact of applying the CAI to adjust star ratings for DE/LIS and disability to construct the 2017 star ratings. RESULTS: DE/LIS was negatively associated with performance for 12 of 16 measures and positively associated for 2 of 16 measures. Disability was negatively associated with performance for 11 of 15 measures and positively associated for 3 of 15 measures. Adjusting star ratings using the CAI resulted in half-star rating increases for 8.5% of MA and 33.3% of PDP contracts that exceeded 50% DE/LIS beneficiaries. CONCLUSIONS: Increases in star ratings following adjustment of clinical performance for SES and disability using the CAI focused on contracts with higher percentages of DE/LIS beneficiaries. Adjustment for enrollee characteristics may improve the accuracy of quality measurement and remove incentives for providers to avoid caring for more challenging patient populations.

The Quality of Medication Treatment for Mental Disorders in the Department of Veterans Affairs and in Private-Sector Plans.

OBJECTIVE: The quality of mental health care provided by the U.S. Department of Veterans Affairs (VA) was compared with care provided to a comparable population treated in the private sector. METHODS: Two cohorts of individuals with mental disorders (schizophrenia, bipolar disorder, posttraumatic stress disorder, major depression, and substance use disorders) were created with VA administrative data (N=836,519) and MarketScan data (N=545,484). The authors computed VA and MarketScan national means for seven process-based quality measures related to medication evaluation and management and estimated national-level performance by age and gender. RESULTS: In every case, VA performance was superior to that of the private sector by more than 30%. Compared with individuals in private plans, veterans with schizophrenia or major depression were more than twice as likely to receive appropriate initial medication treatment, and veterans with depression were more than twice as likely to receive appropriate long-term treatment. CONCLUSIONS: Findings demonstrate the significant advantages that accrue from an organized, nationwide system of care. The much higher performance of the VA has important clinical and policy implications.

Measuring Success in Health Care Value-Based Purchasing Programs: Findings from an Environmental Scan, Literature Review, and Expert Panel Discussions.

Value-based purchasing (VBP) refers to a broad set of performance-based payment strategies that link financial incentives to health care providers' performance on a set of defined measures in an effort to achieve better value. The U.S. Department of Health and Human Services is advancing the implementation of VBP across an array of health care settings in the Medicare program in response to requirements in the 2010 Patient Protection and Affordable Care Act, and policymakers are grappling with many decisions about how best to design and implement VBP programs so that they are successful in achieving stated goals. This article summarizes the current state of knowledge about VBP based on a review of the published literature, a review of publicly available documentation from VBP programs, and discussions with an expert panel composed of VBP program sponsors, health care providers and health systems, and academic researchers with VBP evaluation expertise. Three types of VBP models were the focus of the review: (1) pay-for-performance programs, (2) accountable care organizations, and (3) bundled payment programs. The authors report on VBP program goals and what constitutes success; the evidence on the impact of these programs; factors that characterize high- and low-performing providers in VBP programs; the measures, incentive structures, and benchmarks used by VBP programs; evidence on spillover effects and unintended consequences; and gaps in the knowledge base.

The quality of mental health care for veterans of Operation Enduring Freedom/Operation Iraqi Freedom.

BACKGROUND: Some Operation Enduring Freedom/Operation Iraqi Freedom (OEF/OIF) veterans experience serious mental health (MH) problems. As OEF/OIF soldiers leave active military duty, their growing numbers pose a challenge to the Department of Veterans Affairs (VA) in delivering high-quality mental health/substance-use disorder (MH/SUD) care. OBJECTIVE: To determine whether the quality of MH/SUD care provided by the VA differs by OEF/OIF veteran status. METHODS: Veterans with selected MH/SUDs were identified from administrative records using diagnostic codes. OEF/OIF service was determined based on Defense Manpower Data Center separation files. Eleven processes of care and 7 utilization performance indicators were examined. Regression analyses were adjusted for veteran demographic and clinical characteristics to test for differences in care by OEF/OIF status. RESULTS: Of the 836,699 veterans with selected diagnoses who received MH/SUD treatment in FY2007, 52,870 (6.3%) were OEF/OIF veterans. In unadjusted analyses, OEF/OIF veterans were more likely to receive evidence-based care processes captured by 6 of the 11 dichotomous performance indicators examined; however, among those receiving psychotherapy encounters, OEF/OIF veterans received significantly fewer visits (6.9 vs. 9.7, P<0.0001). In adjusted analyses, only postdischarge follow-up remained meaningfully higher for OEF/OIF veterans. CONCLUSIONS: Efforts to maintain and/or increase OEF/OIF veteran participation in VA MH/SUD services should be informed by their characteristics, such as younger age and better physical health relative to other veterans.

Structural estimates of treatment effects on outcomes using retrospective data: an application to ductal carcinoma in situ.

Analysis of observational cohort data is subject to bias from unobservable risk selection. The authors compared econometric models and treatment effectiveness estimates using the linked Surveillance, Epidemiology, and End Results (SEER)-Medicare claims data for women diagnosed with ductal carcinoma in situ. Treatment effectiveness estimates for mastectomy and breast-conserving surgery (BCS) with or without radiotherapy were compared using three different models: simultaneous-equations model, discrete-time survival model with unobserved heterogeneity (frailty), and proportional hazards model. Overall trends in disease-free survival (DFS), or time to first subsequent breast event, by treatment are similar regardless of the model, with mastectomy yielding the highest DFS over 8 years of follow-up, followed by BCS with radiotherapy, and then BCS alone. Absolute rates and direction of bias varied substantially by treatment strategy. DFS was underestimated by single-equation and frailty models compared with the simultaneous-equations model and randomized controlled trial results for BCS with radiotherapy and overestimated for BCS alone.

Using the lessons of behavioral economics to design more effective pay-for-performance programs.

OBJECTIVES: To describe improvements in the design of pay-for-performance (P4P) programs that reflect the psychology of how people respond to incentives. STUDY DESIGN: Investigation of the behavioral economics literature. METHODS: We describe 7 ways to improve P4P program design in terms of frequency and types of incentive payments. After discussing why P4P incentives can have unintended adverse consequences, we outline potential ways to mitigate these. RESULTS: Although P4P incentives are increasingly popular, the healthcare literature shows that these have had minimal effect. Design improvements in P4P programs can enhance their effectiveness. CONCLUSION: Lessons from behavioral economics may greatly enhance the design and effectiveness of P4P programs in healthcare, but future work is needed to demonstrate this empirically.

Episode-based performance measurement and payment: making it a reality.

Proposals to use episodes of care as a basis for payment and performance measurement are largely conceptual at this stage, with little empirical work or experience in applied settings to guide their design. Based on analyses of Medicare data, we identified key issues that will need to be considered related to defining episodes and determining which provider is accountable for an episode. We suggest a number of applied studies and demonstrations that would facilitate more rapid movement of episode-based approaches from concept to implementation.

Race and sex differences in the receipt of timely and appropriate lung cancer treatment.

BACKGROUND: Previous research suggests that disparities in non-small-cell lung cancer (NSCLC) survival can be explained in part by disparities in the receipt of cancer treatment. Few studies, however, have considered race and sex disparities in the timing and appropriateness of treatment across stages of diagnosis. OBJECTIVE: To evaluate the relationship of sex and race with the receipt of timely and clinically appropriate NSCLC treatment for each stage of diagnosis. METHOD: Surveillance Epidemiology and End Result data linked to Medicare claims for beneficiaries diagnosed with NSCLC between 1995 and 1999 were used to evaluate the relationship between race and sex with timely and appropriate NSCLC treatment while controlling for other demographic characteristics, comorbidities, socioeconomic status, and provider supply (N = 22,145). RESULTS: Overall adjusted rates of timely and appropriate treatment are 37.2%, 58.1%, and 29.2% for Medicare beneficiaries diagnosed with stage I or II, III, and IV NSCLC, respectively. Among stage I or II patients, women were 25% less likely to receive timely surgical resection relative to men, and blacks were 66% less likely to receive timely and appropriate treatment than whites. Black men were least likely to receive resection (22.2% compared with 43.7% for white men). Blacks were 34% less likely to receive timely surgery, chemotherapy, or radiation for stage III disease and were 51% less likely to receive chemotherapy in a timely fashion for stage IV disease relative to whites. CONCLUSION: Significant variations in appropriate timely treatment were found within and across stages of diagnosis, confirming that sex and race differences in NSCLC treatment exist.

The pen and the scalpel: effect of diffusion of information on nonclinical variations in surgical treatment.

BACKGROUND: As information is disseminated about best practices, variations in patterns of care should diminish over time. OBJECTIVE: To test the hypotheses that differences in rates of a surgical procedure are associated with type of insurance in an era of evolving practice guidelines and that insurance and site differences diminish with time as consensus guidelines disseminate among the medical community. METHODS: We use lymph node dissection among women with ductal carcinoma in situ (DCIS) as an example of a procedure with uncertain benefit. Using a sample of 1051 women diagnosed from 1985 through 2000 at 2 geographic sites, we collected detailed demographic, clinical, pathologic, and treatment information through abstraction of multiple medical records. We specified multivariate logistic models with flexible functions of time and time interactions with insurance and treatment site to test hypotheses. RESULTS: Lymph node dissection rates varied significantly according to site of treatment and insurance status after controlling for clinical, pathologic, treatment, and demographic characteristics. Rates of lymph node dissection decreased over time, and differences in lymph node dissection rates according to site and generosity of insurance were no longer significant by the end of the study period. CONCLUSIONS: We have demonstrated that rates of a discretionary surgical procedure differ according to nonclinical factors, such as treatment site and type of insurance, and that such unwarranted variation decreases over time with diminishing uncertainty and in an era of diffusion of clinical guidelines.

Assessment of contributions to patient safety knowledge by the Agency for Healthcare Research and Quality-funded patient safety projects.

OBJECTIVE: To characterize the activities of projects funded in Agency for Healthcare Research and Quality (AHRQ)'s patient safety portfolio and assess their aggregate potential to contribute to knowledge development. DATA SOURCES: Information abstracted from proposals for projects funded in AHRQ's patient safety portfolio, information on safety practices from the AHRQ Evidence Report on Patient Safety Practices, and products produced by the projects. STUDY DESIGN: This represented one part of the process evaluation conducted as part of a longitudinal evaluation based on the Context­Input­Process­Product model. PRINCIPAL FINDINGS: The 234 projects funded through AHRQ's patient safety portfolio examined a wide variety of patient safety issues and extended their work beyond the hospital setting to less studied parts of the health care system. Many of the projects implemented and tested practices for which the patient safety evidence report identified a need for additional evidence. The funded projects also generated a substantial body of new patient safety knowledge through a growing number of journal articles and other products. CONCLUSIONS: The projects funded in AHRQ's patient safety portfolio have the potential to make substantial contributions to the knowledge base on patient safety. The full value of this new knowledge remains to be confirmed through the synthesis of results