Prescription Drug Dispensing and Patient Costs After Implementation of a No Behavioral Health Cost-Sharing Law.

Importance: On January 1, 2022, New Mexico implemented a No Behavioral Cost-Sharing (NCS) law that eliminated cost-sharing for mental health and substance use disorder (MH/SUD) treatments in plans regulated by the state, potentially reducing a barrier to treatment for MH/SUDs among the commercially insured; however, the outcomes of the law are unknown. Objective: To assess the association of implementation of the NCS with out-of-pocket spending for prescription for drugs primarily used to treat MH/SUDs and monthly volume of dispensed drugs. Design, Settings, and Participants: This retrospective cohort study used a difference-in-differences research design to examine trends in outcomes for New Mexico state employees, a population affected by the NCS, compared with federal employees in New Mexico who were unaffected by NCS. Data were collected on prescription drugs for MH/SUDs dispensed per month between January 2021 and June 2022 for New Mexico patients with a New Mexico state employee health plan and New Mexico patients with a federal employee health plan. Data analysis occurred from December 2022 to January 2024. Exposure: Enrollment in a state employee health plan or federal health plan. Main Outcomes and Measures: The primary outcomes were mean patient out-of-pocket spending per dispensed MH/SUD prescription and the monthly volume of dispensed MH/SUD prescriptions per 1000 employees. A difference-in-differences estimation approach was used. Results: The implementation of the NCS law was associated with a mean (SE) $6.37 ($0.30) reduction (corresponding to an 85.6% decrease) in mean out-of-pocket spending per dispensed MH/SUD medication (95% CI, -$7.00 to -$5.75). The association of implementation of NCS with the volume of prescriptions dispensed was not statistically significant. Conclusions and Relevance: These findings suggest that the implementation of the New Mexico NCS law was successful in lowering out-of-pocket spending on prescription medications for MH/SUDs, but that there was no association of NCS with the volume of medications dispensed in the first 6 months after implementation. A key challenge is to identify policies that protect from high out-of-pocket spending while also promoting access to needed care.

Georgia's Reinsurance Waiver Associated With Decreased Premium Affordability And Enrollment.

Sixteen states have used Section 1332 waivers to implement reinsurance programs that aim to reduce premiums and increase enrollment in the Affordable Care Act's health insurance Marketplaces. Although reinsurance programs have successfully reduced premiums for unsubsidized enrollees, little is known about how reinsurance affects Marketplace premiums, minimum cost of coverage, and enrollment for the large majority of Marketplace enrollees who receive premium subsidies. Using a difference-in-differences analysis of matched counties straddling Georgia's borders to examine Georgia's 2022 implementation of its reinsurance program, we found that reinsurance increased the minimum cost of enrolling in subsidized Marketplace coverage by approximately 30 percent and decreased enrollment by roughly a third for Marketplace enrollees with incomes of 251-400 percent of the federal poverty level. Marketplace reinsurance programs may have the unintended consequences of increasing the minimum cost of subsidized coverage and reducing enrollment. These outcomes are especially relevant in the present policy context of enhanced subsidies, which have substantially reduced the number of unsubsidized enrollees who would benefit most from reinsurance.

The extent and growth of prior authorization in Medicare Advantage.

OBJECTIVES: To assess trends in the use of prior authorization requirements among Medicare Advantage (MA) plans. STUDY DESIGN: Descriptive quantitative analysis. METHODS: Data were from the CMS MA benefit and enrollment files for 2009-2019, supplemented with area-level data on demographic and provider market characteristics. For each service category, we calculated the annual share of MA enrollees in plans requiring at least some prior authorization and plotted trends over time. We mapped the county-level share of MA enrollees exposed to prior authorization in 2009 vs 2019. We quantified the association between local share of MA enrollees exposed to prior authorization and characteristics of that county in the same year. Finally, we plotted the share of MA enrollees exposed to prior authorization requirements over time for the 6 largest MA carriers. RESULTS: From 2009 to 2019, the share of MA enrollees in plans requiring prior authorization for any service remained stable. By service category, the share of MA enrollees exposed to prior authorization ranged from 30.7% (physician specialist services) to 72.2% (durable medical equipment) in 2019, with most service categories requiring prior authorization more often over time. Several area-level demographic and provider market characteristics were associated with prior authorization requirements, but these associations weakened over time. The use of prior authorization varied widely across plans. CONCLUSIONS: In 2019, roughly 3 in 4 MA enrollees were in a plan requiring prior authorization. Service-level, area-level, and carrier-level patterns suggest a wide range of approaches to prior authorization requirements.

Playing by the Rules? Tracking U.S. Hospitals' Responses to Federal Price Transparency Regulation.

GOAL: As of January 1, 2021, the Centers for Medicare & Medicaid Services requires most U.S. hospitals to publish pricing information on their website to help consumers make decisions regarding services and to transform negotiations with health insurers. For this study, we evaluated changes in hospitals' compliance with the federal price transparency rule after the first year of enactment, during which the Centers for Medicare & Medicaid Services increased the penalty for noncompliance. METHODS: Using a nationally representative random sample of 470 hospitals, we assessed compliance with both parts of the hospital transparency rule (publishing a machine-readable price database and a consumer shopping tool) in the first quarter of 2022 and compared its baseline level in the first quarter of 2021. Using data from the American Hospital Association and Clarivate, we next assessed how compliance varied by hospital factors (ownership, number of beds, system membership, teaching status, type of electronic health record system), market factors (hospital and insurer market concentration), and the estimated change in penalty for noncompliance. PRINCIPAL FINDINGS: By early 2022, 46% of hospitals had posted both machine-readable and consumer-shoppable data, an increase of 24% from the prior year. Almost 9 in 10 hospitals had complied with the consumer-shoppable data requirement by early 2022. Larger hospitals and public hospitals had lower probabilities of baseline compliance with the machine-readable and consumer-shoppable requirements, respectively, although public hospitals were significantly more likely to become compliant with the consumer-shoppable requirement by 2022. Higher hospital market concentration was also associated with higher baseline compliance for both the machine-readable and consumer-shoppable requirements. Furthermore, our analyses found that hospitals with certain electronic health record systems were more likely to comply with the consumer-shoppable requirement in 2021 and became increasingly compliant with the machine-readable requirement in 2022. Finally, we found that hospitals with a larger estimated penalty were more likely to become compliant with the machine-readable requirement. PRACTICAL APPLICATIONS: Longitudinal analyses of compliance with the federal price transparency rule are valuable for monitoring changes in hospitals' behavior and assessing whether compliance changes vary systematically for specific types of hospitals and/or market structures. Our results suggest a trend toward increased hospital compliance between 2021 and 2022. Although hospitals perceive the consumer-shopping tools as being the most impactful, the value of this information depends on whether it is comprehensible and comparable across hospitals. The new price transparency rule has facilitated the creation of new data that have the potential to significantly alter the competitive landscape for hospitals and may require hospital leaders to consider how their organizational strategies change concerning their engagement with payers and patients. Finally, greater price transparency is likely to bolster national policy discussions related to price variation, affordability, and the role of regulation in healthcare markets.

Association of Primary Care Visit Length With Potentially Inappropriate Prescribing.

Importance: Time is a valuable resource in primary care, and physicians and patients consistently raise concerns about inadequate time during visits. However, there is little evidence on whether shorter visits translate into lower-quality care. Objective: To investigate variations in primary care visit length and quantify the association between visit length and potentially inappropriate prescribing decisions by primary care physicians. Design, Setting, and Participants: This cross-sectional study used data from electronic health record systems in primary care offices across the US to analyze adult primary care visits occurring in calendar year 2017. Analysis was conducted from March 2022 through January 2023. Main Outcomes and Measures: Regression analyses quantified the association between patient visit characteristics and visit length (measured using time stamp data) and the association between visit length and potentially inappropriate prescribing decisions, including inappropriate antibiotic prescriptions for upper respiratory tract infections, coprescribing of opioids and benzodiazepines for painful conditions, and prescriptions that were potentially inappropriate for older adults (based on the Beers criteria). All rates were estimated using physician fixed effects and were adjusted for patient and visit characteristics. Results: This study included 8 119 161 primary care visits by 4 360 445 patients (56.6% women) with 8091 primary care physicians; 7.7% of patients were Hispanic, 10.4% were non-Hispanic Black, 68.2% were non-Hispanic White, 5.5% were other race and ethnicity, and 8.3% had missing race and ethnicity. Longer visits were more complex (ie, more diagnoses recorded and/or more chronic conditions coded). After controlling for scheduled visit duration and measures of visit complexity, younger, publicly insured, Hispanic, and non-Hispanic Black patients had shorter visits. For each additional minute of visit length, the likelihood that a visit resulted in an inappropriate antibiotic prescription changed by -0.11 percentage points (95% CI, -0.14 to -0.09 percentage points) and the likelihood of opioid and benzodiazepine coprescribing changed by -0.01 percentage points (95% CI, -0.01 to -0.009 percentage points). Visit length had a positive association with potentially inappropriate prescribing among older adults (0.004 percentage points; 95% CI, 0.003-0.006 percentage points). Conclusions and Relevance: In this cross-sectional study, shorter visit length was associated with a higher likelihood of inappropriate antibiotic prescribing for patients with upper respiratory tract infections and coprescribing of opioids and benzodiazepines for patients with painful conditions. These findings suggest opportunities for additional research and operational improvements to visit scheduling and quality of prescribing decisions in primary care.

Association of Evaluation and Management Payment Policy Changes With Medicare Payment to Physicians by Specialty.

Importance: US primary care physicians (PCPs) have lower mean incomes than specialists, likely contributing to workforce shortages. In 2021, the Centers for Medicare & Medicaid Services increased payment for evaluation and management (E/M) services and relaxed documentation requirements. These changes may have reduced the gap between primary care and specialist payment. Objectives: To simulate the effect of the E/M payment policy change on total Medicare physician payments while holding volume constant and to compare these simulated changes with observed changes in total Medicare payments and E/M coding intensity, before (July-December 2020) and after (July-December 2021) the E/M payment policy change. Design, Setting, and Participants: Retrospective observational study of US office-based physicians who were in specialties with 5000 or more physicians billing Medicare and who had 50 or more fee-for-service Medicare visits before and after the E/M payment policy change. Exposures: E/M payment policy changes. Main Outcomes and Measures: Outcomes included physician-level simulated volume-constant payment change, total observed Medicare payment change, and share of high-intensity (ie, level 4 or 5) E/M visits before and after the E/M payment policy change. For each specialty, the median change in each outcome was reported. The payment gap between primary care and specialty physicians was calculated as the difference between total Medicare payments to the median primary care and median specialty physician. Results: The study population included 180 624 physicians. Repricing 2020 services yielded a simulated volume-constant payment change ranging from a 3.3% (-$4557.0) decrease for the median radiologist to an 11.0% ($3683.1) increase for the median family practice physician. After the E/M payment change, the median high-intensity share of E/M visits increased for physicians of nearly all specialties, ranging from a -4.4 percentage point increase (dermatology) to a 17.8 percentage point increase (psychiatry). The median change in total Medicare payments by specialty ranged from -4.2% (-$1782.9) for general surgery to 12.1% ($3746.9) for family practice. From July-December 2020 to July-December 2021, the payment gap between the median primary care physician and the median specialist shrank by $825.1, from $40 259.8 to $39 434.7 (primary care, $41 193.3 in July-December 2020 and $45 962.4 in July-December 2021; specialist, $81 453.1 in July-December 2020 and $85 397.1 in July-December 2021)-a relative decrease of 2.0%. Conclusions and Relevance: Among US office-based physicians receiving Medicare payments in 2020 and 2021, E/M payment policy changes were associated with changes in Medicare payment by specialty, although the payment gap between primary care physicians and specialists decreased only modestly. The findings may have been influenced by the COVID-19 pandemic, and further research in subsequent years is needed.

PRescribing Interventions for Chronic pain using the Electronic health record (PRINCE): Study protocol.

BACKGROUND: Primary care is a frequent source of pain treatment and opioid prescribing. The objective of the Prescribing Interventions for Chronic Pain using the Electronic health record (PRINCE) study is to assess the effects of two behavioral economics-informed interventions embedded within the electronic health record (EHR) on guideline-concordant pain treatment and opioid prescribing decisions in primary care settings. METHODS: Setting: The setting for this study is 43 primary care clinics in Minnesota. DESIGN: The PRINCE study uses a cluster-randomized 2 × 2 factorial design to test the effects of two interventions. An adaptive design allows for the possibility of secondary randomization to test if interventions can be titrated while maintaining efficacy. INTERVENTIONS: One intervention alters the "choice architecture" within the EHR to nudge clinicians toward non-opioid treatments for opioid-naïve patients and toward tapering for patients currently receiving a "high risk" opioid. The other intervention integrates the prescription drug monitoring program (PDMP) directly within the EHR. OUTCOME: The primary outcome for opioid-naïve patients is whether an opioid is prescribed in a primary care visit without a non-opioid alternative pain treatment. The primary outcome for current opioid-using patients is whether opioid prescriptions were tapered with a documented rationale. DISCUSSION: The PRINCE study will provide real-world evidence on two approaches to improving pain treatment in primary care using the EHR. The adaptive study design strikes a balance between establishing intervention efficacy and testing whether efficacy varies with intervention intensity.

Effect of Integrating Access to a Prescription Drug Monitoring Program Within the Electronic Health Record on the Frequency of Queries by Primary Care Clinicians: A Cluster Randomized Clinical Trial.

Importance: Tools that are directly integrated with the electronic health record (EHR) workflow can reduce the hassle cost of certain guideline-concordant practices, such as querying a prescription drug monitoring program (PDMP) before prescribing opioids. Objective: To investigate the effect of integrating access to a PDMP within the EHR on the frequency of program queries by primary care clinicians. Design Settings and Participants: The PRINCE (Prescribing Interventions for Chronic Pain Using the Electronic Health Record) randomized trial used a factorial cluster design at the clinic level in 43 primary care clinics in Minnesota. In all, 309 clinicians participated; 161 clinicians were given EHR-integrated access to PDMP at the intervention clinics, and 148 clinicians had the usual access at the control clinics. The intervention went live on August 27, 2020, and data were collected through March 3, 2021. Intervention: Single sign-on access to the Minnesota PDMP was integrated into the EHR, allowing clinicians to query a patient's controlled substance prescription and dispensing history as recorded in the Minnesota PDMP directly from the patient's EHR record without logging into a separate web portal. Additionally, the integration tool alerted clinicians and reminded them to review the PDMP if a patient had 3 or more opioid prescriptions in the past year and 1 or more in the past 6 months. Clinics in the control group did not receive access to the EHR-integrated PDMP tool; instead, these participants logged into the PDMP web portal separately. Main Outcomes and Measures: Monthly PDMP query counts for primary care clinicians, overall and by modality (EHR-based, web-based, via a clinical delegate), adjusted for clinician characteristics, including type (physician, nurse practitioner, physician assistant), sex, and years in practice. Data were analyzed from August 2021 to May 2022. Results: Of the 43 participating clinics with 309 clinicians, 21 clinics with 161 clinicians (102 [63.4%] women; 114 [70.8%] physicians; tenure, 10.6 [4.4] years) received the PDMP integration intervention. Baseline unadjusted monthly PDMP query rates for the average clinician were 6.6 (95% CI, 4.4-9.9) vs 8.8 (95% CI, 6.0-13.1) queries in the control vs the PDMP integration group, respectively. During the intervention, PDMP query rates for the average clinician were 6.9 (95% CI, 4.7-10.3) vs 14.8 (95% CI, 10.0-22.0) queries among the control vs the PDMP integration group, respectively. Compared with the control group, the EHR-integrated PDMP tool produced a 60% greater increase in the relative change in monthly PDMP queries (95% CI, 51%-70%). An increase in PDMP queries via the EHR-integrated PDMP tool drove this increase, while web-based and delegate queries declined by 39% more among the intervention compared with the control group (95% CI, 34%-43%). Conclusions and Relevance: This cluster randomized clinical trial found that integrating access to the PDMP in the EHR increased PDMP-querying rates, suggesting that direct access reduced hassle costs and can dramatically improve adherence to guideline-concordant care practices among primary care clinicians. Trial Registration: ClinicalTrials.gov Identifier: NCT04601506.

The effect of a public transportation expansion on no-show appointments.

OBJECTIVE: To test whether there were fewer missed medical appointments ("no-shows") for patients and clinics affected by a significant public transportation expansion. STUDY SETTING: A new light rail line was opened in a major metropolitan area in June 2014. We obtained electronic health records data from an integrated health delivery system in the area with over three million appointments at 97 clinics between 2013 and 2016. STUDY DESIGN: We used a difference-in-differences research design to compare whether no-show appointment rates differentially changed among patients and clinics located near versus far from the new light rail line after it opened. Models included fixed effects to account for underlying differences across clinics, patient zip codes, and time. DATA EXTRACTION METHODS: We obtained data from an electronic health records system representing all appointments scheduled at 97 outpatient clinics in this system. We excluded same-day, urgent care, and canceled appointments. PRINCIPAL FINDINGS: The probability of no-show visits differentially declined by 0.5 percentage points (95% confidence interval [CI]: -0.9 to -0.1), or 4.5% relative to baseline, for patients living near the new light rail compared to those living far from it, after the light rail opened. The effects were stronger among patients covered by Medicaid (-1.6 percentage points [95% CI: -2.4 to -0.8] or 9.5% relative to baseline). CONCLUSIONS: Improvements to public transit may improve access to health care, especially for people with low incomes.

Taking the Pulse of Hospitals' Response to the New Price Transparency Rule.

As of January 1, 2021, most U.S. hospitals are required to publish pricing information on their website to promote more informed decision making by consumers regarding their care. In a nationally representative sample of 470 hospitals, we analyzed whether hospitals met price transparency information reporting requirements and the extent to which complete reporting was associated with ownership status, bed size category, system affiliation, and location in a metropolitan area. Fewer than one quarter of sampled hospitals met the price transparency information requirements of the new rule, which include five types of standard charges in machine-readable form and the consumer-shoppable display of 300 shoppable services. Our analyses of hospital reporting by organizational and market attributes revealed limited differences, with some exceptions for nonprofit and system-member hospitals demonstrating greater responsiveness with respect to the consumer-shoppable aspects of the rule.

Insurance Status and Continuity for Young Adults With First-Episode Psychosis.

OBJECTIVE: Insurance status and continuity may affect access to and quality of care. The authors characterized patterns of and changes in insurance status over 1 year among people with first-episode psychosis (FEP), comparing insurance patterns with adults of similar age in the general population. METHODS: Longitudinal data on insurance status and predictors of insurance status among adults with FEP were obtained from RAISE-ETP (Recovery After an Initial Schizophrenia Episode-Early Treatment Program) study participants with complete 1-year data (N=288). The frequencies of insurance status and transitions are presented. Bivariate comparisons were used to assess the impact of the comprehensive coordinated care intervention in RAISE-ETP on insurance changes. These data were compared with contemporaneous longitudinal data in the 2011 Medical Expenditures Panel Study. RESULTS: The RAISE-ETP experimental intervention did not significantly change insurance status. At baseline, levels of uninsurance (47%) and public insurance (31%) were higher among RAISE-ETP participants than among a similar age group in the general public (29% and 13%, respectively). Insurance transitions were common among people with FEP, although 79% of those with public insurance at baseline also had public insurance at 1 year. Of studied RAISE-ETP participants, 60% had a period of uninsurance during the year studied. CONCLUSIONS: Compared with a national sample, people with FEP were more likely to use public insurance but still had high persistence of 12-month uninsurance. That over half of the RAISE-ETP participants had a period of uninsurance suggests that more research is needed on whether these periods affect treatment continuity and medication adherence.

Docs with their eyes on the clock? The effect of time pressures on primary care productivity.

This paper examines how time pressure, an important constraint faced by medical care providers, affects productivity in primary care. We generate empirical predictions by incorporating time pressure into a model of physician behavior by Tai-Seale and McGuire (2012). We use data from the electronic health records of a large integrated delivery system and leverage unexpected schedule changes as variation in time pressure. We find that greater time pressure reduces the number of diagnoses recorded during a visit and increases both scheduled and unscheduled follow-up care. We also find some evidence of increased low-value care, decreased preventive care, and decreased opioid prescribing.

College roommates have a modest but significant influence on each other's political ideology.

Does college change students' political preferences? While existing research has documented associations between college education and political views, it remains unclear whether these associations reflect a causal relationship. We address this gap in previous research by analyzing a quasi-experiment in which university students are assigned to live together as roommates. While we find little evidence that college students as a whole become more liberal over time, we do find strong evidence of peer effects, in which students' political views become more in line with the views of their roommates over time. This effect is strongest for conservative students. These findings shed light on the role of higher education in an era of political polarization.

National Trends in Outpatient Mental Health Service Use Among Adults Between 2008 and 2015.

OBJECTIVE: This study sought to characterize recent trends in mental health visits of adult outpatients to primary care physicians (PCPs), specialty mental health providers (SMHPs), and other providers (non-primary care physicians, specialists other than SMHPs, nurse practitioners, and physician assistants). Trends determined by degree of patients' psychological distress and in the types of treatments received within different settings were also examined. METHODS: Data were from the household component of the nationally representative Medical Expenditure Panel Survey for the 2008-2011 and 2012-2015 periods for adults ages ≥18 years (N=13,111) who had a mental health outpatient visit. Bivariate logistic regression was used to compare means between the two periods. RESULTS: The percentage of adults having mental health outpatient visits increased between the two periods, largely driven by an increase in visits with providers other than SMHPs and PCPs, which rose from 11.9% (N=667) to 15.5% (N=1,048). Outpatient mental health visits with PCPs decreased from 29.0% (N=1,802) to 26.8% (N=1,945). The proportion of respondents with mental health outpatient visits increased both among those with high psychological distress and among those with low or no psychological distress (from 30.7% [N=1,332] to 36.2% [N=1,491] and from 6.0% [N=4,516] to 6.9% [N=5,772], respectively). The percentage of respondents receiving only psychotropic medication decreased over the two periods. CONCLUSIONS: Mental health outpatient visits for adults increased between 2008 and 2015, and visits with SMHPs remained relatively stable during that time. A greater understanding of recent trends in types of outpatient mental health services may help identify targets for future mental health workforce studies.

COVID-19 Has Increased Medicaid Enrollment, But Short-Term Enrollment Changes Are Unrelated To Job Losses.

The recent coronavirus disease 2019 (COVID-19) global pandemic has resulted in unprecedented job losses in the United States, disrupting health insurance coverage for millions of people. Several models have predicted large increases in Medicaid enrollment among those who have lost jobs, yet the number of Americans who have gained coverage since the pandemic began is unknown. We compiled Medicaid enrollment reports covering the period from March 1 through June 1, 2020, for twenty-six states. We found that in these twenty-six states, Medicaid covered more than 1.7 million additional Americans in roughly a three-month period. Relative changes in Medicaid enrollment differed significantly across states, although enrollment growth was not systemically related to job losses. Our results point to the important effects of state policy differences in the response to COVID-19.

Reading the Fine Print: State Considerations for Medicaid Buy-In Plans.

States that are pursuing Medicaid buy-in plans have considerable options in designing a plan to meet their goals. Buy-in plans will reflect key decisions on four major issues: 1) whether plans are sold on or off exchange, 2) whether plans are run by the state or a Medicaid Managed Care Organization, 3) who is eligible to purchase plans, and 4) which benefits and providers will be covered and at what payment rates. Our goal is to clarify the implications of these choices with respect to the goals and with respect to the tradeoffs each choice would involve.