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Objective: To understand the relative role of prices versus utilization in the variation in total spending per patient across medical groups. Data Sources: We conducted a cross-sectional analysis of medical claims for commercially insured adults from a large national insurer in 2018. Study Design: After assigning patients to a medical group based on primary care visits in 2018, we calculated total medical spending for each patient in that year. Total spending included care provided by clinicians within the medical group and care provided by other providers, including hospitals. It did not include drug spending. We estimated the case mix adjusted spending per patient for each medical group. Within each market, we categorized medical groups into quartiles based on the group's spending per patient. To decompose spending variation into price versus utilization, we compared spending differences between highest and lowest quartile medical groups under two scenarios: (1) using actual prices (2) using a standardized price (same price used for a given service across the nation). Principal Findings: In total, 3,921,736 patients were assigned to 7284 medical groups. Per-patient spending in the highest quartile of spending medical groups was $1813 higher than per-patient spending in the lowest spending quartile of medical groups (50% higher relative spending). This overall difference was primarily driven by differences in inpatient care, imaging, and specialty care. In the scenario where we used standardized prices, the difference in spending between medical groups in the top and bottom quartiles decreased to $1425, implying that 79% of the $1813 difference in spending between the top and bottom quartile groups is explained by utilization and the remaining 21% by prices. The likely explanation for the modest impact of prices is that patients cared for by a given medical group receive care across a wide range of providers. Conclusions: Prices explained a modest fraction of the differences in spending between medical groups. KEYWORDS health plans, medical groups, prices, public reporting, spending, 1 | INTRODUCTION Many strategies to improve health care value build on the profiling of clinicians on total costs of care. These profiles are used for a range of applications [...]

Objective: To compare direct-to-consumer (DTC) telemedicine and in-person visits in rates of testing, follow-up health care use, and quality for urinary tract infections (UTIs) and sinusitis. Data Source: The Minnesota All Payer Claims Data provided 2008-2015 administrative claims data. Study Design: Using a difference-in-differences approach, we compared episodes of care for UTIs and sinusitis among enrollees of health plans introducing coverage for DTC telemedicine relative to those without DTC telemedicine coverage. Primary outcomes included number of laboratory tests, antibiotics filled, office and outpatient visits, emergency department (ED) visits, and standardized spending, based on standardized prices of health services. Data Collection: The study sample included non-elderly enrollees of commercial health insurance plans. We constructed 30-day episodes of care initiated by a DTC telemedicine or in-person visit. Principal Findings: The UTI and sinusitis samples were comprised of 215,134 and 624,630 episodes of care, respectively. Following the introduction of coverage for DTC telemedicine, 15.7% of UTI episodes and 8.9% of sinusitis episodes were initiated with DTC telemedicine. Compared to episodes without coverage for DTC telemedicine, UTI episodes with coverage had 0.25 fewer lab tests (95% CI: -0.33, -0.18; p < 0.001), lower standardized spending for the first UTI visit (-$11.18 [95% CI: -$21.62, -$0.75]; p < 0.05), and no change in office and outpatient visits, ED visits, antibiotics filled, or standardized medical spending. Sinusitis episodes with coverage for DTC telemedicine had fewer antibiotics filled (-0.08 [95% CI: -0.14, -0.01]; p < 0.05) and a very small increase in ED visits (0.001 [95% CI: 0.001, 0.010]; p < 0.05), but no change in lab tests, office and outpatient visits, or standardized medical spending. Conclusions: Among commercially insured patients, coverage of DTC telemedicine was associated with reductions in antibiotics for sinusitis and laboratory tests for UTI without changes in downstream total office and outpatient visits or changes in ED visits. KEYWORDS direct-to-consumer telehealth, health insurance coverage, telemedicine What is known on this topic * Despite the rapid increase in direct-to-consumer (DTC) telemedicine coverage and use during the pandemic, there is mixed evidence on the quality of DTC telemedicine. * There is also limited evidence on the association between DTC telemedicine and downstream utilization of imaging services, outpatient visits, and inpatient visits. What this study adds * Using a quasi-experimental study design, we found that coverage of DTC telemedicine was associated with reductions in antibiotics for sinusitis and laboratory tests for urinary tract infections. * We did not find a relationship between DTC telemedicine and changes in imaging services, office and outpatient visits, or inpatient visits. * Coverage of DTC telemedicine services did not adversely impact outcomes for the two uncomplicated, non-emergent conditions studied., 1 | INTRODUCTION The use of direct-to-consumer (DTC) telemedicine visits has rapidly increased in recent years. (1-3) These patient-initiated, online medical evaluations are typically used for low-acuity, non-emergent conditions, allowing [...]

The title of this podcast is 'What's on Your Mind?' When you started thinking about healthcare this morning, what crossed your mind? My life has been quite consumed by things [...]

Objective (Study Question): Advanced practice registered nurses (APRNs) play an increased role in mental illness treatment. Health services research that uses claims to study mental health is often limited because behavioral health nurse practitioners (i.e., APRNs who specialize in mental illness, also known as psychiatric mental health APRNs) cannot be easily identified in claims data. We describe two methodologies to identify behavioral health APRNs in administrative claims. Data Sources/Study Setting (w/ Hospital/Institution Setting Anonymized): We use 2010-2018 claims from the traditional Medicare fee-for-service program along with 2010-2019 commercial claims and Medicare Advantage data from the OptumLabs Data Warehouse (OLDW). Self-reported specialty data from the National Plan & Provider Enumeration System (NPPES) were used for validation. Study Design: For each APRN, we calculated the percentage of visit diagnoses and of prescriptions in each database that were for mental health and classified those with [greater than or equal to]80% as behavioral health APRNs. We validated our definition with NPPES self-reported specialty for Medicare data. Data Collection/Extraction Methods: Not applicable. Principal Findings: Among APRNs with 10+ visits, 10,978 (8.1%) in Medicare and 9829 (11.7%) in commercial claims data met our visit-based criteria as behavioral health APRNs. Among APRNs with 10+ prescriptions, 8160 (6.2%) in Medicare and 16,538 (9.0%) in commercial claims data met our prescription-based criteria as behavioral health APRNs. Among the APRNs who self-reported they were behavioral health APRNs, 92.8% and 90.5% met our visit-based and prescription-based criteria, respectively. Conclusions: We present and validate two methods of identifying behavioral health APRNs in claims that can be used by other researchers. KEYWORDS administrative claims, advanced practice providers, advanced practice registered nurses, Medicare, mental health, methods What is known on this topic * Behavioral health APRNs provide a growing fraction of specialty mental health care in the United States. (*) Unfortunately, mental health services research and policy research that uses claims data often does not capture the care provided by these specialty APRNs because there is no methodology to identify these providers. What this study adds (*) This study provides a validated empirical method that other researchers can use to identify claims for services provided by behavioral health APRNs., 1 | INTRODUCTION Advanced practice registered nurses (APRNs) provide a growing fraction of patient care in the United States. (1-3) APRNs, either nurse practitioners or clinical nurse specialists, make up [...]

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. KEYWORDS access, demand, determinants of health, health care organizations and systems, population health, socioeconomic causes of health, utilization of services What is known on this topic * Missed medical appointments (i.e., 'no-shows') are harmful to patients and create inefficiencies in health care delivery. * Transportation barriers are frequently cited as a reason for no-shows, but little research has examined the causal effect of improved transportation options on no-shows. * Existing studies have focused on the effects of ridesharing interventions and have been limited to small patient samples. What this study adds * Using data reflecting over three million scheduled outpatient appointments, we found that the opening of a new light rail transit line led to relative reductions in rates of no-shows among patients living near it compared to those not living near it. * We found the effects of the new transit line were larger among patients covered by Medicaid. * Our findings suggest that improvements to public transit may improve access to care for patients., 1 | INTRODUCTION No-show medical appointments--when patients do not show up for their scheduled appointments--are common. Providers and delivery systems use many strategies to encourage patients to attend their appointments, [...]

Objective: Many employers have introduced rewards programs as a new benefit design in which employees are paid $25-$500 if they receive care from lower-priced providers. Our goal was to assess the impact of the rewards program on procedure prices and choice of provider and how these outcomes vary by length of exposure to the program and patient population. Study Setting: A total of 87 employers from across the nation with 563,000 employees and dependents who have introduced the rewards program in 2017 and 2018. Study Design: Difference-in-difference analysis comparing changes in average prices and market share of lower-priced providers among employers who introduced the reward program to those that did not. Data Collection Methods: We used claims data for 3.9 million enrollees of a large health plan. Principal Findings: Introduction of the program was associated with a 1.3% reduction in prices during the first year and a 3.7% reduction in the second year of access. Use of the program and price reductions are concentrated among magnetic resonance imaging (MRI) services, for which 30% of patients engaged with the program, 5.6% of patients received an incentive payment in the first year, and 7.8% received an incentive payment in the second year. MRI prices were 3.7% and 6.5% lower in the first and second years, respectively. We did not observe differential impacts related to enrollment in a consumer-directed health plan or the degree of market-level price variation. We also did not observe a change in utilization. Conclusions: The introduction of financial incentives to reward patients from receiving care from lower-priced providers is associated with modest price reductions, and savings are concentrated among MRI services. KEYWORDS price shopping, price variation, rewards programs, What is known on this topic * The wide variation in private insurance prices for common health services creates a potential opportunity for savings if programs can shift patients from [...]