This is a hedonic regression study of the 2001–2004 and 2004–2007 rent growth of 18,000 rental units. Which variables matter: Location? Age? Rent level? Occupancy duration? Structure type? The answers deepen understanding of the rental market and help guide statistical agency practice. We document significant rent stickiness. Initial relative rent level is the best predictor, mainly because of mean reversion. (This problem likely extends well beyond the present study.) “Location” comes in second, though often not statistically significant: the relative value of location is persistent. Age and occupancy duration are also notable. Our findings support statistical agency practices.
Research Objective Rising prices have been frequently cited as a primary driver of health care spending growth among the commercially insured. Concerns have been raised that the prices paid by commercial insurers for medical services have diverged from provider costs. We report the degree to which the prices paid for professional services by commercial insurers relative to Medicare benchmarks vary both across and within different markets in the United States. Further, we document how prices may vary within markets across physician specialties. Study Design We applied the Medicare physician fee schedule to re‐price commercial claims based on the specific service delivered and location of the provider listed on each claim. We then benchmarked commercial prices by comparing the allowed amount for each claim to the Medicare rate, as determined by the physician fee schedule. Using our sample of commercial claims, we computed a price index as a weighted average of commercial to Medicare price ratios for a common, robust set of professional services—accounting for more than 80% of claims and spending in our commercial sample. We separately compute indices by provider specialty—where we classify each provider as a primary care provider, hospitalist, or other specialty. Population Studied Using data from the Health Care Cost Institute, we studied the allowed amounts paid for more than 400 million professional service claims across 112 core‐based statistical areas across 43 states in 2017. Principal Findings Most conveys the intended meaning. everywhere the prices paid by commercial insurers for professional services were well in excess of Medicare prices. Further, we document wide variation in the wedge between commercial and Medicare prices across markets. At the low end, commercial prices were on average 25% above Medicare, compared to almost 500% at the high end. We also document how the disparity between commercial and Medicare prices varies within markets. Conclusions Our findings quantify the degree to which commercial insurers are paying higher prices than Medicare for the same professional services in metro areas around the country. Our findings are consistent with related work benchmarking the unit prices of inpatient and outpatient care paid by commercial insurers relative to Medicare. We also demonstrate that the gap between commercial and Medicare prices varies widely both across and within metro areas. Implications for Policy or Practice While commercial professional prices have not grown as quickly as inpatient and outpatient services, the prices paid for professional services by commercial insurers are still well in excess of Medicare. Understanding the difference between commercial and Medicare prices can help identify areas where provider prices have deviated from health care costs and can inform policy discussions. For example, this work may further an understanding of the impact of proposals to pay providers rates that are benchmarked to Medicare such as a Public Option or Medicare for All. Primary Fund...
Objective To compare different methods of indexing health care service prices for the commercially insured population across geographic markets. Data Sources Health Care Cost Institute commercial claims data from 2012 to 2016. Study Design We compare price indices computed using methods with differing levels of computational intensity: weighted‐average versus regression‐based methods. We separately compute indices of the prices paid for set of common inpatient and set of common outpatient services in different markets across the United States using each type of method. We subsequently examined the variation of and correlations between the resulting index values. Data Collection/Extraction Methods We computed health care service price indices separately using samples of inpatient and outpatient facility claims from 2012 to 2016 across 112 Core‐Based Statistical Areas. Within each category of services, claims were limited to members under the age of 65 with employer‐sponsored insurance. Both samples were limited to a common set of services that made up nearly 80 percent of the service use in the full sample every year. Principal Findings We found that the methods studied produced highly correlated price indices (r > .94) with similar distributions across years for both inpatient and outpatient services. Conclusions Our findings suggest that weighted‐average methods, which are much less computationally intensive, will generate results similar to regression‐based methods.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.