Please review instructions listed below and read final paper. Comments or change/add things that you feel is appropriate that could also be missing. Right below is a link of the article associated with this assignment. Thank you very much for your time and help. Just wanted to make sure nothing is left out and completed appropriately.

https://onepercentsteps.com/policy-briefs/capping-provider-prices-and-price-growth-in-the-us-commercial-health-sector/

Final project assignment

Due May 1

Word limit: stay between 1500-2000 words (not including references). Please double space your project.

1. Choose a policy brief from theOne Percent Steps Project and ok it with me.
   1. Section 1: You will need to provide an executive summary of your project, including your research extension, think like an abstract (maybe 1 page max, ).
   2. Section 2: Full research paper (perhaps 4-5 pages)
      1. Explain what the policy proposal is
      2. Provide background research on the policy, why it was undertaken, what the intended effect of the policy is, what health economic concepts it touches on, if already implemented, what was the actual effect of the policy.
         1. You will need to include references from health economics, health service research, or medical journals. Minimum 10 outside references (no maximum), and minimum 8 from the economics literature. If you have any questions about whether a journal is an acceptable source, please email me. Not all journals are created equally and some are not necessarily good sources
      3. Really highlight the health economics concepts this policy touches on.
         1. Consider making the particular aspect of health care more like a competitive market, improving/worsening disparities, moral hazard, adverse selection, physician induced demand, pharmaceuticals, technological innovation, costs/benefits of the policy, unintended consequences if implemented.
   3. Section 3: Extension of proposal (REALLY FOCUS ON THIS!). Perhaps 2-3 pages
      1. Describe a research design that would test this proposal. How would you design this, what data would you use, what research method would you use (don't just say regression models, tell me if you would implement a randomized controlled trial, a difference in differences design, a regression discontinuity design, or some other form of analysis), what potential pitfalls do you foresee, and think about ways in which you could tinker with the proposal to make the proposal work better.
      2. For this, if your RCT would be super unethical, then you can describe it as the ideal experiment and explain how you could actually enact this using the constraints of the world that we live in.
      3. You do not need to enact this, but you have to give enough details so that I understand how one could enact this and what exactly your research design would be hoping to uncover (what is your research question, why is it an interesting extension of the proposal policy, what methods you would use, think about the 8 questions that you had to answer for the research articles you read for your problem sets).
      4. Tie your extension back to the proposal you are studying and be clear about why this would be a good test/extension for this policy.
   4. You are constrained by page count so you must be efficient in your writing!

I. Abstract

Healthcare costs in the United States have continued to rise over time in spite of our US health systems efforts and state/federal government's policy implementations to aid in the decrease of costs. Putting a cap on growth in the health sector, as well as capping prices could serve as a way to decrease what makes up 19.7% of the US gross domestic product (GDP). While capping provider prices and growth in the US commercial health sector would hypothetically decrease the cost of healthcare, this plan could lead to potential hazards post-implementation, including but not limited to physician induced demand, decreases in access to care, further consolidation, particularly amongst smaller hospitals and health systems, and a further decrease in the quality of care patients receive . To better understand the impact of the plan to cap provider pricing and growth we recommend a sample study be conducted to avoid possible negative outcomes as seen in the "Danish Concrete" Scenario. This study would allow us to see the effects of the implementations, as well as learn how we can adapt and control the multiple variables.

II. Proposal Explanation

Although the United States (US) will likely continue to rely on markets to allocate most healthcare resources, market competition has not been sufficient to control commercial provider prices.A policy has been proposed to regulate provider prices in the US to address this issue. It comprises three components that are collectively designed to address the market failures in the commercial sector which have resulted in extremely high prices for certain health care services. The first component is the local market- and service-specific price caps that regulate maximum prices providers can negotiate. The US should introduce "backstop" price caps, which prevent prices above 500% of the 20^th percentile of local prices, at the market level. The second component is service-, insurer-, and provider-specific price growth caps that restrict the annual growth in provider prices. The US should introduce a price growth regulation that limits provider price growth and allows higher growth caps for cheaper providers. The third component is oversight power for the state and federal authorities (Chernew et. al. 2020). These efforts should be supported with state and federal regulation and, if necessary, legislation to provide the data and resources to support enforcement.

This policy was undertaken because from 2008 to 2018, health insurance premiums grew approximately 4% per year as median household incomes stayed flat (Collins et al. 2019; U.S. Census Bureau 2020). By 2020, health insurance premiums for a family of four in the US were $21,342 (Kaiser Family Foundation 2020). Provider price growth is one of the largest drivers of health spending and premium growth in the US. From 2007 to 2014, for example, hospital prices for inpatient care grew by 42% (Cooper et al. 2019). The US Consumer Price Index (CPI) increased by 14% (Bureau of Labor Statistics 2020). In a well-functioning market, competition drives prices to efficient levels. However, in the health care sector, there are many deviations from competitive conditions that obstruct market forces. The goal of this policy is to cap prices. If the "backstop" price cap alone were introduced for inpatient hospital prices, it is estimated to reduce commercial inpatient spending by 8.7%. Capping commercial outpatient prices has a somewhat higher percentage impact and capping professional services has a bit lower percentage impact. Capping both inpatient and outpatient commercial hospital prices would save approximately $38 billion, reducing commercial health care spending by about 3.2% and total health care spending by about 1.0%. Capping professional service prices would save about $30 billion, which translates to 2.5% of commercial and 0.8% of total health care spending (CMS, 2020). Furthermore, the price growth cap would limit annual increases in health spending and consequently result in larger savings over time.

III. How the Proposal Relates to Health Economics Concepts

The primary concept impacted by this proposal is market power. "From 2010 to 2016 the number of mergers reported to the federal government increased by over 57% (Cooper & Gaynor, 2022)." This trend toward consolidation in the healthcare market has afforded many hospitals increased market power and therefore the ability to dictate prices. This power has led to increasing costs for medical care that are outpacing growth in wages and inflation (CRFB, 2021). Given that the FTC has had little success in stopping or slowing the consolidation within the healthcare market, price caps on what hospitals and providers can charge for services may be the only viable option for mitigating the increased market power that many hospitals are taking advantage of secondary to widespread consolidation (CRFB, 2021).

The obvious positive effect of this policy is that it will serve to decrease the cost of healthcare, which is necessary considering that healthcare spending now accounts for 19.7% of GDP. It could also help increase access to care by making it more affordable which would allow individuals of lower socioeconomic status to be more able to utilize healthcare services secondary to the increased affordability of care.

Despite the stated positives of this policy, there is still the potential for unintended consequences. First, this policy could lead to an increase in physician induced demand. Since this policy would cap what providers can charge for services, they would need to see higher patient volumes and provide an increasing number of services to generate revenues that are comparable to what they were able to earn prior to the implementation of price caps. The need for higher volumes and increased services rendered could lead to an increase in physician induced demand as a means for generating higher patient volumes and increasing billable services. Another potential impact of this policy is that it could lead to decreasing accessibility to care. The implementation of price caps would undoubtedly decrease the amount of revenue earned by many hospitals. This could negatively impact the ability of smaller facilities, like critical access hospitals, to maintain financial viability. If this occurs, it may lead to the closure of smaller hospitals which would decrease access to care, particularly in the rural setting. It could also lead to further increase in hospital consolidation because smaller hospitals might need to merge with larger hospitals or organizations just to keep their doors open. Additionally, the effect of further increasing the rate of hospital consolidation could lead to yet another unintended effect, decreasing quality of care. It has been found that areas of increased market concentration have a corresponding decrease in the quality of care offered, so if this policy were to cause an increase in hospital consolidation, it would likely lead to decreasing quality of care in areas where consolidation takes place (AHIP, 2021).

Finally, adverse selection has to also be considered with this policy considering the existence of a public option and how it affects the commercial insurance market. In the presence of a public option, the viability of commercial health plans will depend not only on whether they can negotiate competitive provider prices and offer desirable benefits, but more importantly on appropriate risk adjustment to avoid adverse selection. This may require additional government intervention into commercial insurance markets, and therefore more disruption.

IV. Research Design

This proposal aims at reducing the cost of care by utilizing backstop price caps which limit the maximum price that providers can negotiate. As much as it sounds like a good idea there are unknown caveats which may come to play when introduced into the system. The "Danish concrete regulation" is a great example as to how a theoretical concept may completely misfire. The demonstrative cost of rolling these behemoth projects are not inconsequential.

Due to the above reason, we propose that this concept be researched and tested before implementation. The most valid study to test this theory in our opinion would be a randomized control trial. Since there are currently no guidelines or regulations governing the negotiation for pricing the services, we do not see any ethical issues either at the institutional level or patient care level. However, we do recognize that randomizing patients in this study would be impossible. To navigate through this issue, we would prefer a cluster randomized control trial (Puffer, Torgerson, Watson, 2005).

In a cluster RCT instead of randomizing individuals we can randomize groups. The cluster could be defined as a group of hospitals or providers. To reduce bias, we could select a cluster in the same geographical area which would preserve the demographics and economic status in both groups.

If we were to enact this study, we would pick a geographical region with over four hospital providers. We would cluster randomize two hospitals to backstop price capping and two hospitals to business as usual (controls). The investigators would be blinded to the data from both institutions. We would then target a select group of common service lines where there is significant variation in pricing and collect data for over one calendar year. The end point would be cost of care per patient for specific service lines the capping was instituted (if not globally). Our research question would be observation of the cost differential between the clusters randomized to intervention (price capping) versus the control group with business as usual. Considering all other dynamics in the region being the same including patient demographics, we should be able to observe differences in cost between the hospitals with intervention versus controls.

There are still some pitfalls that we anticipate. For one, the time for the study allotted may not be enough to determine benefit. This may occur if the said service line for price capping is not performed frequently enough, or there is unequal distribution of the service line between different hospitals. Secondly some bias may be introduced by regional variation of practice and patterns. There may further be hesitancy in the hospital being asked to selectively cap the prices. This may require incentivizing the hospital by subsidizing any real or perceived losses.

Although this does not guarantee that the trial results would be applicable across the country, they would provide a good insight on whether there is any merit to expanding it.

Other common pitfalls which may be less relevant to our study would be consenting (not required as the decision/intervention is not at the level of the patient), over matching and sub-sampling bias (Donner & Neil, 2004). Another downside is that this research model would not be able to test the impact of government regulation and the administrative cost involved with it.

References

AHIP, (2021, August 26).How Hospital Consolidation Hurts Americans.Retrieved Fromhttps://www.ahip.org/news/articles/how-hospital-consolidation-hurts-americans

Bailey, V., (2021, September 22).Rural Hospital Mergers Associated with Improved Patient Outcomes.Retrieved fromhttps://revcycleintelligence.com/news/rural-hospital-mergers-associated-with-improved-patient-outcomes

Bureau of Labor Statistics. 2020. "Consumer Price Index U.S. City Average All Urban Consumers (CPI-U): All Items." Bureau of Labor Statistics. Accessed April 25, 2022.https://www.bls.gov/regions/midwest/data/consumerpriceindexhistorical_us_table.pdf

Centers for Medicare and Medicaid Services. 2020. "2019 National Health Expenditure Fact Sheet." Centers for Medicare and Medicaid Services. Accessed April 25, 2022.https://www.cms.gov//Research-statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealth ExpendData.NationalHealthAccountsHistorical.

Chernew, Michael, Leemore Dafny, and Maximilian Pany. 2020. "A Proposal to Cap Provider Prices and Price Growth in the Commercial Health-Care Market." Brookings Institution. Accessed April 25, 2022.https://www.hamiltonproject.org/assets/files/CDP_PP_WEB_FINAL.pdf.

Collins, Sara, David Radley, and Jesse Baumgartner. 2019. "Trends in Employer Health Care Coverage 2008-2018. Higher Costs for Workers and Their Families." The Commonwealth Fund. Accessed April 25, 2022.https://www.commonwealthfund.org/publications/2019/nov/trends-employer-health-care-coverage-2008-2018.

Committee for a Responsible Federal Budget (CRFB), (2021, February 23).Capping Hospital Prices. Retrieved Fromhttps://www.crfb.org/papers/capping-hospital-prices

Cooper, Z., Gaynor, M., (2022)Addressing Hospital Concentration and Rising Consolidation in the United States.Retrieved Fromhttps://onepercentsteps.com/policy-briefs/addressing-hospital-concentration-and-rising-consolidation-in-the-united-states/

Cooper, Zack, Stuart V. Craig, Martin Gaynor, Nir J. Harish, Harlan M. Krumholz, and John Van Reenen. 2019a. "Hospital Prices Grew Substantially Faster Than Physician Prices for Hospital-Based Care in 2007-14." Health Affairs, 38(2): 184-189.

Cooper, Zack, Stuart V. Craig, Martin Gaynor, Nir J. Harish, Harlan M. Krumholz, and John Van Reenen. 2019b. "The Price Ain't Right? Hospital Prices and Health Spending on the Privately Insured." Quarterly Journal of Economics, 134 (1): 51-107.

Donner, A., and Neil Klar. "Pitfalls of and controversies in cluster randomization trials."American journal of public health 94.3 (2004): 416-422.

Kaiser Family Foundation. 2020. "Employer Health Benefits 2020 Summary of Findings."

https://files.kff.org/attachments/Summary-of-Findings-Employer-Health-Benefits-2020.pdf

Pearson, E., (2021, September 2).Hospital mergers and acquisitions are a bad deal for patients.Why aren't they being stopped?.Retrieved fromhttps://www.statnews.com/2021/09/02/hospital-mergers-more-oversight-federal-state-officials/

Pedersen LB, Hvidt EA, Waldorff FB, Andersen MK. Burnout of intrinsically motivated GPs when exposed to external regulation: A combined panel data survey and cluster randomized field experiment. Health Policy. 2021 Apr;125(4):459-466. doi: 10.1016/j.healthpol.2021.01.004. Epub 2021

Puffer, S., Torgerson, D., Watson, J. Cluster randomized controlled trials. J Eval Clin Pract. 2005 Oct;11(5):479-83. doi: 10.1111/j.1365-2753.2005.00568.x. PMID: 16164589.

Rabbani, M., (2021, December).Nonprofit Hospital Mergers: the Effect on Healthcare Costs and Utilization.Retrieved fromhttps://www.usf.edu/arts-sciences/departments/economics/documents/rabbani-jmp.pdf

U.S. Census Bureau, "Real Median Household Income in the United States [MEHOINUSA672N]." Retrieved from FRED, Federal Reserve Bank of St. Louis. Accessed April 25, 2022. https://fred.stlouisfed.org/series/MEHOINUSA672N