Regulating Hospital Prices Based On Market Concentration Is Likely To Leave High-Price Hospitals Unaffected

Performance of health care service area definitions for capturing variation in inpatient care and social determinants of health

OBJECTIVE

To quantify the degree to which health care service area (HCSA) definitions captured hospitalizations and heterogeneity in social determinants of health (SDOH).

DATA SOURCES AND STUDY SETTING

Geospatial data from the Centers for Medicare and Medicaid Services, the Census Bureau, and the Dartmouth Institute. Drive-time isochrones from MapBox. Area Deprivation Index (ADI) data. 2017 inpatient discharge data from Arizona, Florida, Iowa, Maryland, Nebraska, New Jersey, New York, and Wisconsin, State Emergency Department Databases and State Inpatient Databases, Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality; and Fee-For-Service Medicare data in 48 states.

STUDY DESIGN

Cross-sectional, descriptive analysis.

DATA COLLECTION/EXTRACTION METHODS

The capture rate was the percentage of inpatient discharges occurring in the same HCSA as the hospital. We compared capture rates for each HCSA definition for different populations and by hospital type. We measured SDOH heterogeneity using the coefficient of variation of the ADI among ZIP codes within each HCSA.

PRINCIPAL FINDINGS

HCSA definitions captured a wide range of inpatient discharges, ranging from 20% to 50% for Public Use Microdata Areas (PUMAs) to 93%-97% for Metropolitan Statistical Areas (MSAs). Three-quarters of inpatient discharges were from facilities within the same county as the patient's residential ZIP code, while nearly two-thirds were within the same Hospital Service Area. From the hospital perspective, 74.7% of inpatient discharges originated from within a 30-min drive and 90.1% within a 60-min drive. Capture rates were the lowest for teaching hospitals. PUMAs and drive-time-based HCSAs encompassed more homogenous populations while MSAs, Commuting Zones, and Hospital Referral Regions captured the most variation.

CONCLUSIONS

The proportion of hospital discharges captured by each HCSA varied, with MSAs capturing the highest proportion of discharges and PUMAs capturing the lowest. Additionally, researchers face a trade-off between capture rate and population homogeneity when deciding which HCSA to use.

A Competition Perspective on Physician Non-compete Agreements

Physician non-compete agreements may have significant competitive implications, and effects on both providers and patients, but they are treated variously under the law on a state-by-state basis. Reviewing the relevant law and the economic literature cannot identify with confidence the net effects of such agreements on either physicians or health care delivery with any generality. In addition to identifying future research projects to inform policy, it is argued that the antitrust "rule of reason" provides a useful and established framework with which to evaluate such agreements in specific health care markets and, potentially, to address those agreements most likely to do significant damage to health care competition and consumers.

Professional Fees for U.S. Hospital Care, 2016-2020

BACKGROUND

The latest comprehensive diagnosis-specific estimates of hospital professional fees relative to facility fees are from 2004 to 2012.

OBJECTIVE

Update professional fee ratio (PFR) estimates to improve cost analysis opportunities with hospital discharge data sources and compare them with previous PFR estimates.

SUBJECTS

2016-2020 MarketScan inpatient admissions and emergency department (ED) treat and release claims.

MEASURES

PFR was calculated as total admission or ED visit payment divided by facility-only payment. This measure can be multiplied by hospital facility costs to yield a total cost estimate.

RESEARCH DESIGN

Generalized linear regression models controlling for selected patient and service characteristics were used to calculate adjusted mean PFR per admission or ED visit by health payer type (commercial or Medicaid) and by selected diagnostic categories representing all clinical diagnoses (Major Diagnostic Category, Diagnostic Related Group, and Clinical Classification Software Revised).

RESULTS

Mean 2016-2020 PFR was 1.224 for admissions with commercial payers (n = 6.7 million admissions) and 1.178 for Medicaid (n = 4.2 million), indicating professional payments on average increased total payments by 22.4% and 17.8%, respectively, above facility-only payments. This is a 9% and 3% decline in PFR, respectively, compared with 2004 estimates. PFR for ED visits during 2016-2020 was 1.283 for commercial payers (n = 22.2 million visits) and 1.415 for Medicaid (n = 17.7 million). This is a 12% and 5% decline in PFR, respectively, compared with 2004 estimates.

CONCLUSIONS

Professional fees comprise a declining proportion of hospital-based care costs. Adjustments for professional fees are recommended when hospital facility-only financial data are used to estimate hospital care costs.

Hospital Survival In Rural Markets: Closures, Mergers, And Profitability

Financial distress among rural hospitals in the US has increased in recent years. Using national hospital data, we investigated how the decline in profitability has affected hospital survival, either independently or with a merger. The answer has direct implications for access to care and competition in rural markets. We assessed the rate of hospital closures and mergers in predominantly rural markets during the period 2010-18, focusing on hospitals that were unprofitable at baseline. A minority of unprofitable hospitals (7 percent) closed. A larger share (17 percent) merged, most commonly with organizations from outside of their local geographic market. Most unprofitable hospitals (77 percent) continued to operate through 2018 without closure or merger. About half of these hospitals returned to profitability. At the market level, 22 percent of markets served by unprofitable hospitals lost a competitor to closure or within-market merger. Out-of-market mergers affected 33 percent of markets with an unprofitable hospital. Overall, our results suggest that rural markets are experiencing meaningful rates of hospital closures and mergers, yet many hospitals have survived despite poor financial performance. Policies targeting access to care will continue to be important. Similar attention will be needed to address the competitive effects of hospital closures and mergers on prices and quality.