Medicaid Value-Based Payments and Health Care Use for Patients With Mental Illness.

Importance: Medicaid patients with mental illness comprise one of the most high-need and complex patient populations. Value-based reforms aim to improve care, but their efficacy in the Medicaid program is unclear. Objective: To investigate if New York state's Medicaid value-based payment reform was associated with improved utilization patterns for patients with mental illness. Design, Setting, and Participants: This retrospective cohort study used a difference-in-differences analysis to compare changes in utilization between Medicaid beneficiaries whose outpatient practices participated in value-based payment reform and beneficiaries whose practices did not participate from before (July 1, 2013-June 30, 2015) to after reform (July 1, 2015-June 30, 2019). Participants were Medicaid beneficiaries in New York state aged 18 to 64 years with major depression disorder, bipolar disorder, and/or schizophrenia. Data analysis was performed from April 2021 to July 2023. Exposure: Beneficiaries were exposed to value-based payment reforms if their attributed outpatient practice participated in value-based payment reform at baseline (July 1, 2015). Main Outcomes and Measures: Primary outcomes were the number of outpatient primary care visits and the number of behavioral health visits per year. Secondary outcomes were the number of mental health emergency department visits and hospitalizations per year. Results: The analytic population comprised 306 290 individuals with depression (67.4% female; mean [SD] age, 38.6 [11.9] years), 85 105 patients with bipolar disorder (59.6% female; mean [SD] age, 38.0 [11.6] years), and 71 299 patients with schizophrenia (45.1% female; mean [SD] age, 40.3 [12.2] years). After adjustment, analyses estimated a statistically significant, positive association between value-based payments and behavioral health visits for patients with depression (0.91 visits; 95% CI, 0.51-1.30) and bipolar disorder (1.01 visits; 95% CI, 0.22-1.79). There was no statistically significant changes to primary care visits for patients with depression and bipolar disorder, but value-based payments were associated with reductions in primary care visits for patients with schizophrenia (-1.31 visits; 95% CI, -2.51 to -0.12). In every diagnostic population, value-based payment was associated with significant reductions in mental health emergency department visits (population with depression: -0.01 visits [95% CI, -0.02 to -0.002]; population with bipolar disorder: -0.02 visits [95% CI, -0.05 to -0.001]; population with schizophrenia: -0.04 visits [95% CI, -0.07 to -0.01]). Conclusions and Relevance: In this cohort study, Medicaid value-based payment reform was statistically significantly associated with an increase in behavioral health visits and a reduction in mental health emergency department visits for patients with mental illness. Medicaid value-based payment may be effective at altering health care utilization in patients with mental illness.

The Role Of Financial Incentives In Biosimilar Uptake In Medicare: Evidence From The 340B Program.

Biosimilar drugs-lower-cost alternatives to expensive biologic drugs-have the potential to slow the growth of US drug spending. However, rates of biosimilar uptake have varied across hospital outpatient providers. We investigated whether the 340B Drug Pricing Program, which offers eligible hospitals substantial discounts on drug purchases, inhibits biosimilar uptake. Almost one-third of US hospitals participate in the 340B program. Using a regression discontinuity design and two high-volume biologics with biosimilar competitors, filgrastim and infliximab, we estimated that 340B program eligibility was associated with a 22.9-percentage-point reduction in biosimilar adoption. In addition, 340B program eligibility was associated with 13.3 more biologic administrations annually per hospital and $17,919 more biologic revenue per hospital. Our findings suggest that the program inhibited biosimilar uptake, possibly as a result of financial incentives making reference drugs more profitable than biosimilar medications.

Hospital concentration and low-income populations: Evidence from New York State Medicaid.

While a large body of evidence has examined hospital concentration, its effects on health care for low-income populations are less explored. We use comprehensive discharge data from New York State to measure the effects of changes in market concentration on hospital-level inpatient Medicaid volumes. Holding fixed hospital factors constant, a one percent increase in HHI leads to a 0.6% (s.e. = 0.28%) decrease in the number of Medicaid admissions for the average hospital. The strongest effects are on admissions for birth (-1.3%, s.e. = 0.58%). These average hospital-level decreases largely reflect redistribution of Medicaid patients across hospitals, rather than overall reductions in hospitalizations for Medicaid patients. In particular, hospital concentration leads to a redistribution of admissions from non-profit hospitals to public hospitals. We find evidence that for births, physicians serving high shares of Medicaid beneficiaries in particular experience reduced admissions as concentration increased. These reductions may reflect preferences among these physicians or reduced admitting privileges by hospitals as a means to screen out Medicaid patients.

Association of Insurance Mix and Diagnostic Coding Practices in New York State Hospitals.

Importance: Given higher reimbursement rates, hospitals primarily serving privately insured patients may invest more in intensive coding than hospitals serving publicly insured patients. This may lead these hospitals to code more diagnoses for all patients. Objective: To estimate whether, for the same Medicaid enrollee with multiple hospitalizations, a hospital's share of privately insured patients is associated with the number of diagnoses on claims. Design, Setting, and Participants: This cross-sectional study used patient-level fixed effects regression models on inpatient Medicaid claims from Medicaid enrollees with at least 2 admissions in at least 2 different hospitals in New York State between 2010 and 2017. Analyses were conducted from 2019 to 2021. Exposures: The annual share of privately insured patients at the admitting hospital. Main Outcomes and Measures: Number of diagnostic codes per admission. Probability of diagnoses being from a list of conditions shown to be intensely coded in response to payment incentives. Results: This analysis included 1 614 630 hospitalizations for Medicaid-insured patients (mean [SD] age, 48.2 [20.1] years; 829 684 [51.4%] women and 784 946 [48.6%] men). Overall, 74 998 were Asian (4.6%), 462 259 Black (28.6%), 375 591 Hispanic (23.3%), 486 313 White (30.1%), 128 896 unknown (8.0%), and 86 573 other (5.4%). When the same patient was seen in a hospital with a higher share of privately insured patients, more diagnoses were recorded (0.03 diagnoses per percentage point [pp] increase in share of privately insured; 95% CI, 0.02-0.05; P < .001). Patients discharged from hospitals in the bottom quartile of privately insured patient share received 1.37 more diagnoses when they were subsequently discharged from hospitals in the top quartile, relative to patients whose admissions were both in the bottom quartile (95% CI, 1.21-1.53; P < .001). Those going from hospitals in the top quartile to the bottom had 1.67 fewer diagnoses (95% CI, -1.84 to -1.50; P < .001). Diagnoses in hospitals with a higher private payer share were more likely to be for conditions sensitive to payment incentives (0.08 pp increase for each pp increase in private share; 95% CI, 0.06-0.10; P < .001). These findings were replicated in 2016 to 2017 data. Conclusions and Relevance: In this cross-sectional study of Medicaid enrollees, admission to a hospital with a higher private payer share was associated with more diagnoses on Medicaid claims. This suggests payment policy may drive differential investments in infrastructure to document diagnoses. This may create a feedback loop that exacerbates resource inequity.

Effects of Real-time Prescription Benefit Recommendations on Patient Out-of-Pocket Costs: A Cluster Randomized Clinical Trial.

Importance: Rising drug costs contribute to medication nonadherence and adverse health outcomes. Real-time prescription benefit (RTPB) systems present prescribers with patient-specific out-of-pocket cost estimates and recommend lower-cost, clinically appropriate alternatives at the point of prescribing. Objective: To investigate whether RTPB recommendations lead to reduced patient out-of-pocket costs for medications. Design, Setting, and Participants: In this cluster randomized trial, medical practices in a large, urban academic health system were randomly assigned to RTPB recommendations from January 13 to July 31, 2021. Participants were adult patients receiving outpatient prescriptions during the study period. The analysis was limited to prescriptions for which RTPB could recommend an available alternative. Electronic health record data were used to analyze the intervention's effects on prescribing. Data analyses were performed from August 20, 2021, to June 8, 2022. Interventions: When a prescription was initiated in the electronic health record, the RTPB system recommended available lower-cost, clinically appropriate alternatives for a different medication, length of prescription, and/or choice of pharmacy. The prescriber could select either the initiated order or one of the recommended options. Main Outcomes and Measures: Patient out-of-pocket cost for a prescription. Secondary outcomes were whether a mail-order prescription and a 90-day supply were ordered. Results: Of 867 757 outpatient prescriptions at randomized practices, 36 419 (4.2%) met the inclusion criteria of having an available alternative. Out-of-pocket costs were $39.90 for a 30-day supply in the intervention group and $67.80 for a 30-day supply in the control group. The intervention led to an adjusted 11.2%; (95% CI, -15.7% to -6.4%) reduction in out-of-pocket costs. Mail-order pharmacy use was 9.6% and 7.6% in the intervention and control groups, respectively (adjusted 1.9 percentage point increase; 95% CI, 0.9 to 3.0). Rates of 90-day supply were not different. In high-cost drug classes, the intervention reduced out-of-pocket costs by 38.9%; 95% CI, -47.6% to -28.7%. Conclusions and Relevance: This cluster randomized clinical trial showed that RTPB recommendations led to lower patient out-of-pocket costs, with the largest savings occurring for high-cost medications. However, RTPB recommendations were made for only a small percentage of prescriptions. Trial Registration: ClinicalTrials.gov Identifier: NCT04940988; American Economic Association Registry: AEARCTR-0006909.

Assessment of US Pharmacies Contracted With Health Care Institutions Under the 340B Drug Pricing Program by Neighborhood Socioeconomic Characteristics.

This cross-sectional study assesses pharmacy participation in the 340B Drug Pricing Program following the 2010 expansion and the extent to which growth has occurred in socioeconomically disadvantaged neighborhoods.

Estimation of Potential Savings Associated With Switching Medication Formulation.

This cross-sectional study describes the price differences between capsule and tablet or ointment and cream forms of prescription drugs for insured patients.

Identifying high-value care for Medicare beneficiaries: a cross-sectional study of acute care hospitals in the USA.

OBJECTIVES: High-value care is providing high quality care at low cost; we sought to define hospital value and identify the characteristics of hospitals which provide high-value care. DESIGN: Retrospective observational study. SETTING: Acute care hospitals in the USA. PARTICIPANTS: All Medicare beneficiaries with claims included in Center for Medicare & Medicaid Services Overall Star Ratings or in publicly available Medicare spending per beneficiary data. PRIMARY AND SECONDARY OUTCOME MEASURES: Our primary outcome was value defined as the difference between Star Ratings quality score and Medicare spending; the secondary outcome was classification as a 4 or 5 star hospital with lowest quintile Medicare spending ('high value') or 1 or 2 star hospital with highest quintile spending ('low value'). RESULTS: Two thousand nine hundred and fourteen hospitals had both quality and spending data, and were included. The value score had a mean (SD) of 0.58 (1.79). A total of 286 hospitals were classified as high value; these represented 28.6% of 999 4 and 5 star hospitals and 46.8% of 611 low cost hospitals. A total of 258 hospitals were classified as low value; these represented 26.6% of 970 1 and 2 star hospitals and 49.3% of 523 high cost hospitals. In regression models ownership, non-teaching status, beds, urbanity, nurse to bed ratio, percentage of dual eligible Medicare patients and percentage of disproportionate share hospital payments were associated with the primary value score. CONCLUSIONS: There are high quality hospitals that are not high value, and a number of factors are strongly associated with being low or high value. These findings can inform efforts of policymakers and hospitals to increase the value of care.

340B Drug Pricing Program and hospital provision of uncompensated care.

OBJECTIVES: To evaluate whether hospital entry into the 340B Drug Pricing Program, which entitles eligible hospitals to discounts on drug purchases and intends for hospitals to use associated savings to devote more resources to the care of low-income populations, is associated with changes in hospital provision of uncompensated care. STUDY DESIGN: We analyzed secondary data on 340B participation and uncompensated care provision among general acute care hospitals and critical access hospitals from 2003 to 2015. We constructed an annual, hospital-level data set on hospital 340B participation from the Office of Pharmacy Information Systems and on uncompensated care provision from the Hospital Cost Reporting Information System. METHODS: Focusing on 2 periods of program expansion, we separately analyzed trends in uncompensated care costs for 340B-eligible general acute care hospitals and critical access hospitals, stratified by year of 340B program entry, including a stratum of eligible hospitals that never participated. We used a differences-in-differences approach to quantify whether there were differential changes in provision of uncompensated care after hospitals enter the 340B program relative to hospitals that did not participate or had not yet entered. RESULTS: We do not find evidence that hospitals increased provision of uncompensated care after entry into the 340B program differentially more than hospitals that never entered or had not yet entered the program. CONCLUSIONS: Relying on hospitals to invest surplus into care for the underserved without marginal incentives to do so or strong oversight may not be an effective strategy to expand safety-net care.

Validation of EHR medication fill data obtained through electronic linkage with pharmacies.

BACKGROUND: Recent linkages between electronic health records (EHRs) and pharmacy data hold opportunity for up-to-date assessment of medication adherence at the point of care. OBJECTIVE: To validate linked EHR-pharmacy data, which can be used for point-of-care interventions for concordance with insurance claims data for patients in a large health care delivery system. METHODS: We performed a retrospective cohort study of adult patients with an active antihypertensive medication order and seen as outpatients between August 25, 2019, and August 31, 2019. Pharmacy fill information was obtained from the EHR via linkages with Surescripts pharmacy and pharmacy benefit manager data, as well as from insurance claims available at our institution. We matched antihypertensive medication fills observed in the linked EHR-pharmacy database with available fills in the insurance claims database and calculated the percentage of medication fills that were available in each database. We estimated medication adherence using proportion of days covered in the linked EHR-pharmacy database and in the insurance claims database. RESULTS: Of 26,679 patients with hypertension, 23,348 (87.5%) had at least 1 antihypertensive medication fill recorded in the linked EHR-pharmacy database. Of 1,501 patients matched with the insurance database and with a documented medication fill, a fill was present for 1,484 (98.9%) and 1,259 (83.9%) patients in the linked EHR-pharmacy and insurance databases, respectively. Of 12,109 medication fills recorded in the insurance data, we found an overlap of 11,060 (91.3%) fills with the linked EHR-pharmacy database. The linked EHR-pharmacy database also contained 18,232 of 19,281 (94.6%) medication fills present in either database. Measured medication adherence was higher for patients when based on linked EHR-pharmacy data compared with insurance claims data (42% vs 30%, P < 0.001). CONCLUSIONS: Linked EHR-pharmacy data captured medication fills for the vast majority of patients and resulted in higher estimates of adherence than insurance claims. Our results suggest that pharmacy fill data available in the EHR have sufficient reliability to be used for point-of-care assessment of medication adherence. DISCLOSURES: This study was supported by grant R01HL155149 from the National Heart, Lung, and Blood Institute. Allen Thorpe provided funding for the NYU Langone Health Learning Health System Program, which helped fund this project. The authors have nothing to disclose.

Does Medicaid coverage of Medicare cost sharing affect physician care for dual-eligible Medicare beneficiaries?

OBJECTIVE: To assess changes in physicians' provision of care to duals (low-income individuals with Medicare and Medicaid) in response to a policy that required Medicaid to fully pay Medicare's cost sharing for office visits with these patients. This policy-a provision of the Affordable Care Act-effectively increased payments for office visits with duals by 0%-20%, depending on the state, in 2013 and 2014. DATA SOURCES: Fee-for-service claims for a 5% random sample of Medicare beneficiaries in 2010-2016. STUDY DESIGN: We conducted a difference-in-differences analysis to compare changes in office visits among Qualified Medicare Beneficiaries (QMBs)-the largest subpopulation of duals for whom payment rates were affected by this policy-to changes among other low-income Medicare beneficiaries for whom payment rates were unaffected (pooled across all states). Next, we conducted a triple-differences analysis that compared changes between QMBs and other low-income beneficiaries in 33 states with payment rate increases of approximately 20% to analogous changes in 14 states without payment increases. DATA COLLECTION: The study included administrative Medicare enrollment and claims data for QMBs and a comparison group of other low-income Medicare beneficiaries (1 914 073 beneficiary-years from 2010 to 2016). PRINCIPAL FINDINGS: Nationally, we did not find a differential increase in office visits among QMBs versus other low-income beneficiaries that coincided with this payment change. In the triple-differences analysis, we did not observe a greater increase in visits among QMBs vs other low-income beneficiaries in states where the policy resulted in large (approximately 20%) increases in payment rates vs states where payment rates were unaffected (triple-differences estimate: -0.12 annual visits, 95% CI: -0.28, 0.04; P = 0.15). CONCLUSIONS: Physicians' provision of care to low-income Medicare beneficiaries may not be responsive to short-run payment changes.

Online Advertising Increased New Hampshire Residents' Use Of Provider Price Tool But Not Use Of Lower-Price Providers.

Insurers and policy makers have created health care price transparency websites to facilitate price shopping and reduce spending. However, price transparency tools to date have been plagued by low use. It is unclear whether this low use reflects a lack of interest or a lack of awareness. We launched a large online advertising campaign to increase consumers' awareness about insurer-specific negotiated price information available on New Hampshire's public price transparency website. Our campaign led to a more than 600 percent increase in visits to the website. However, in our analysis of health plan claims, this increased use of the website did not translate to increased use of lower-price providers. Our findings imply that the limited success to date of price transparency tools in reducing health care spending is driven by structural factors that limit consumers' ability to use health care price information as opposed to only a lack of awareness about price transparency tools.

What are the potential savings from steering patients to lower-priced providers? a static analysis.

OBJECTIVES: Healthcare payers are increasingly using price transparency and benefit design to encourage patients to choose lower-priced providers. We quantify potential savings from shifting patients to lower-priced providers. If there is limited price variation or if higher-priced providers command little market share, savings could be minimal. STUDY DESIGN: Using 2013-2014 commercial claims for 697,381 enrollees in California, we characterized within-market price variation and the relationship between providers' market shares and relative prices for 3 nonemergent, shoppable outpatient services: laboratory tests, imaging services, and durable medical equipment (DME). In a stylized policy simulation that holds provider price and utilization constant, we computed potential savings if patients who visited providers with prices above the median price shifted to the median-priced provider in their geographic market for the same service. METHODS: Observational analyses. RESULTS: Of the service categories examined, laboratory tests had greatest within-market price variation (median coefficient of variation of 100% vs 87% for imaging services and 43% for DME). Roughly half of services (53%, 47%, and 54% for laboratory tests, imaging services, and DME, respectively) were billed by providers with prices above their market median. Shifting these patients to the median-priced provider in their markets could save 42%, 45%, and 15% of spending on laboratory tests, imaging services, and DME, respectively, together representing savings of 11% of total outpatient spending and 7% of the sum of inpatient and outpatient spending. CONCLUSIONS: Steering patients from higher- to lower-priced providers within geographic markets in targeted service categories could generate substantial healthcare savings.

Changes in Hospital Referral Patterns to Skilled Nursing Facilities Under the Hospital Readmissions Reduction Program.

BACKGROUND: The Hospital Readmissions Reduction Program (HRRP) penalizes hospitals for higher-than-expected readmission rates. Almost 20% of Medicare fee-for-service (FFS) patients receive postacute care in skilled nursing facilities (SNFs) after hospitalization. SNF patients have high readmission rates. OBJECTIVE: The objective of this study was to investigate the association between changes in hospital referral patterns to SNFs and HRRP penalty pressure. DESIGN: We examined changes in the relationship between penalty pressure and outcomes before versus after HRRP announcement among 2698 hospitals serving 6,936,393 Medicare FFS patients admitted for target conditions: acute myocardial infarction, heart failure, or pneumonia. Hospital-level penalty pressure was the expected penalty rate in the first year of the HRRP multiplied by Medicare discharge share. OUTCOMES: Informal integration measured by the percentage of referrals to hospitals' most referred SNF; formal integration measured by SNF acquisition; readmission-based quality index of the SNFs to which a hospital referred discharged patients; referral rate to any SNF. RESULTS: Hospitals facing the median level of penalty pressure had modest differential increases of 0.3 percentage points in the proportion of referrals to the most referred SNF and a 0.006 SD increase in the average quality index of SNFs referred to. There were no statistically significant differential increases in formal acquisition of SNFs or referral rate to SNF. CONCLUSIONS: HRRP did not prompt substantial changes in hospital referral patterns to SNFs, although readmissions for patients referred to SNF differentially decreased more than for other patients, warranting investigation of other mechanisms underlying readmissions reduction.