Search

As Medicare Advantage increasingly becomes the dominant form of Medicare, meaningful and accurate comparisons with traditional fee-for-service Medicare will be increasingly important for both beneficiaries and policy makers. Recent debate among policy experts, government advisory bodies, and health plans highlights the need to create standardized comparison between the 2 Medicare programs. Supplemental benefits, Part B cost-sharing differences, and prescription drug benefits should be valued with a series of structured comparisons. Making this information transparent to beneficiaries through the plan finder would improve beneficiary decision-making. Finally, pragmatic comparisons would support policy makers in making improvements to Medicare Advantage program policy, undertaking comparative program evaluation, and engaging in Medigap plan oversight.

This cross-sectional study uses US Health Resources and Services Administration data to assess the distribution of claims reimbursement funds to health care professionals and facilities for uninsured patients with COVID-19.

Technological changes in medicine have created new opportunities to provide surgical care in lower cost, specialized facilities. This paper examines patient outcomes in ambulatory surgery centers (ASCs), which were developed as a low-cost alternative to outpatient surgery in hospitals. Because we are concerned that selection into ASCs may bias estimates of facility quality, we use predicted changes in federally set Medicare facility payment rates as an instrument for ASC utilization to estimate the effect of location of treatment on patient outcomes. We find that patients treated in an ASC are less likely to be admitted to a hospital or visit an emergency room a short time after outpatient surgery. The findings in this paper indicate that factors other than patient and physician heterogeneity contribute to the observed returns to specialization in the ASC market.

Background: We tested whether provider quality and cost information had a meaningful impact on health care quality and costs at two large employers that introduced a transparent provider profiling system in 2006. Using retrospective claims from enrollees representing 3,928 covered lives in these two firms where the insurer was the sole provider of health insurance, we addressed two questions: 1) Did patients switch to higher quality and more efficient doctors when the provider rankings became available? 2) What is the effect of switching on total expenditures, out-of-pocket expenditures, and use of preventive services? Methods: We used nonlinear regression to identify factors associated with improvement in quality and cost efficiency of providers seen by covered enrollees. We used difference-in-differences regression to test the impact on expenditures and use of preventive services of those who switched to higher-rated physicians. Results: Age, illness burden, and female are positively associated with improvement in provider quality and efficiency. Provider portfolio improvement had a negative impact on expenditures, but the story with respect to prevention is mixed: preventive visits go up when the patient has an improved provider portfolio, but utilization of diagnostic screening procedures goes down. Conclusions: A common concern in medical markets is the lack of information for consumers to shop for health care. We find consumers exhibit behaviors that suggest they use such information when it is available and useful. These results suggest that consumers could process additional price and quality information to gain more value from their health insurance benefits.

Background: Care bundling is an emerging health financing innovation to change the incentives of care, intended to improve quality of care and promote better resource use. In 2016, Medicare outlined a proposal for changing Medicare reimbursement for outpatient drugs through pre-determined care bundles. To gauge the potential for care bundling, we examine one of the first comprehensive efforts, the Oncology Care Model (OCM). This paper shows that the oncology care bundles likely used by OCM have large variation in cost per patient across the United States. Methods: For this analysis, we utilized five years (2010-2014) of the Medicare 5% limited data set (LDS) of fee for service claims. All seven claims segments were used in the analysis including: physician/carrier Part B, durable medical equipment,outpatient hospital, inpatient, skilled nursing facility, home health, and hospice. The 5% LDS sample of Medicare beneficiaries used to identify patients with cancer bundles totaled 17,143 in 2014. An approximate national estimate would be 20 times 17,143, yielding 342,860 beneficiaries. Results: Our analysis of Medicare claims for the three most expensive bundles (lung cancer, prostate cancer and lymphoma) from 2010 to 2014 shows over a 400% difference in per capita bundle reimbursement between US states. Furthermore, we found that the mix of reimbursements within all bundles of fee for service claim types varies meaningfully. Finally, we show that the rank order of most expensive cancers to treat at a patient level is not correlated with the most expensive cancers at a societal level. Conclusions: There is substantial geographic variation in per capita cancer costs that is not consistent for the top 3 cancer bundles. Therefore, policy-making based on system-wide geography will likely not produce a consistent solution. As a result, policy formulation will be challenging when patient cost management is a goal, especially in a healthcare sector where innovation is likely to move faster than robust and thoughtful cost containment strategies.

Health information technology (IT) adoption, it is argued, will dramatically improve patient care. We study the impact of hospital IT adoption on patient outcomes focusing on the role of patient and organizational heterogeneity. We link detailed hospital discharge data on all Medicare fee-for-service admissions from 2002–2007 to detailed hospital-level IT adoption information. For all IT-sensitive conditions, we find that health IT adoption reduces mortality for the most complex patients but does not affect outcomes for the median patient. Benefits from health IT are primarily experienced by patients whose diagnoses require cross-specialty care coordination and extensive clinical information management.

Concern abounds about whether the health care workforce is sufficient to meet changing demands spurred by the Affordable Care Act (ACA). We project that by 2022 the health care industry needs three to four million additional workers, forty percent of which is related to demand growth under the ACA. We project faster job growth in the ambulatory care sector, especially in home health care. Given the current profile, we expect that the future health care workforce will be increasingly female, young, racially/ethnically diverse, not US-born, at or below the poverty level and at a low level of educational attainment.

On June 28, 2012, the Supreme Court of the United States (SCOTUS) upheld most of the provisions of the Patient Protection and Affordable Care Act and the health care provisions of the Health Care and Education Reconciliation Act (P.L. 111-148 and P.L. 111-152; henceforth referred to as the ACA).1 Starting in 2014, individuals without an offer of insurance from their employer and small businesses will be able to buy insurance on state and federal exchanges, with premium subsidies depending on their incomes. Certain employers that do not offer health insurance will be penalized, and individuals will be required to have coverage or pay a penalty. At the same time, however, the Supreme Court ruled that states could opt out of the ACA expansion of Medicaid coverage for all individuals up to age 65 with incomes less than 133 percent of poverty. Under the ACA as enacted, but before the Supreme Court ruling, the Medicaid expansion was mandatory for states that wanted to keep their federal matching funds for any part of the Medicaid program. The Supreme Court's decision immediately raised the prospect that some states might opt out of the Medicaid expansion. The U.S. Congressional Budget Office (CBO 2012) estimated that 6 million people previously covered by the Medicaid expansion in its March 2012 baseline would not be covered; some of these would enroll in exchanges, but the number of uninsured people would rise by 4 million. Our research has two goals. First, we predict how many people will take up private health insurance under provisions of the ACA. Second, we predict Medicaid take-up under several possible patterns for states opting out of the Medicaid expansion. Unlike the CBO, which did not make estimates for specific states but instead utilized average probabilities of opting out, we make predictions for specific states.2 We also predict enrollment in specific types of private plans (e.g., the “metallic” plans offered in health insurance exchanges). We find the ACA will increase coverage substantially in the private health insurance market and Medicaid. However, if states opt out of the Medicaid expansion, this could increase the federal cost of health reform, while reducing the number of newly covered lives. If six states (Florida, Louisiana, Mississippi, Nebraska, South Carolina, and Texas) opt out, the number of uninsured people will increase by 7.9 million with a drop in Medicaid coverage of 4.4 million by 2021, compared with the pre-SCOTUS situation. Our predictions are based on a microsimulation model of health plan choice that we originally developed to predict the effect of the Medicare Modernization Act of 2003 (MMA) on take-up of high-deductible health plans in the individual health insurance market (Feldman et al. 2005; Parente et al. 2005).3 We begin the study with a section that describes the model. This is followed by our simulation of the ACA effects on private health insurance and Medicaid take-up.

Objective To predict changes in wage growth for health care workers based on projections of insurance enrollment from the Affordable Care Act (ACA). Data Sources Enrollment data came from three large employers and a sampling of premiums from ehealthinsurance.com. Information on state Medicaid eligibility rules and costs were from the Kaiser Family Foundation. National predictions were based on the MEPS and Medicare Current Beneficiary surveys. Bureau of Labor Statistics data were used to estimate employment. Study Design We projected health insurance enrollment by plan type using a health plan choice model. Using claims data, we measured the services demanded for each plan choice and year. Projections of labor demand were based on current output/input ratios. Changes in wages resulting from changes in labor demand from 2014 to 2021 were based on labor supply and demand elasticities. Principal Findings Expenditures required to retain and grow the health care workforce will increase substantially. Wages will increase most for professions with the greatest training requirements (physicians and registered nurses). The largest impact will be felt in 2015. Conclusions Projected wage increases for health care workers may drive substantial growth in insurance premiums and reduce the affordability of health insurance.

Using a national multipayer commercial claims database containing allowed amounts, we examined variations in the prices for 242 common medical services in forty-one states and the District of Columbia. Ratios of average state prices to national prices ranged from a low of 0.79 in Florida to a high of 2.64 in Alaska. Two- to threefold variations in prices were identified within some states and Metropolitan Statistical Areas.

The objective of this analysis is to simulate the difference between national and state-specific individual insurance markets on take-up of individual health insurance. This simulation analysis was completed in three steps. First, we reviewed the literature to characterize the state-specific individ ual insurance markets with respect to state regulations and to identify the effect of those regulations on health insurance premiums. Second, we used empirical data to develop premium estimates for the simulation that reflect case-mix as well as state-specific differences in health care markets. Third, we used a revised version of the 2005 Medical Expenditure Panel Survey (MEPS) to complete a set of simulations to identify the impact of three differ ent scenarios for national market development. (National market estimates are based on the simulation model with competition among all 50 states and moderate impact assumptions.) We find evidence of a significant op portunity to reduce the number of uninsured under a proposal to allow the purchase of health insurance across state lines. The best scenario to reduce the uninsured, numerically, is competition among all 50 states with one clear winner. The most pragmatic scenario, with a good impact, is one winner in each regional market.

The potential of health information technology (IT) to transform health care delivery has spurred health IT adoption and will likely contribute to increased investments in coming years. Although an extensive literature shows the value of health IT at leading academic institutions, its broader value remains unknown. We sought to estimate IT's effect on key patient safety measures in a national sample. Using four years of Medicare inpatient data, we found that electronic medical records have a small, positive effect on patient safety. Although these results are encouraging, we suggest that investment in health IT should be accompanied by investment in the evidence base needed to evaluate it.

Calls to action for widespread adoption of electronic health records have come from a broad spectrum of the private and public sectors. The problem, to date, is not that information does not exist, as much as that the data have not been organized around the patient. An integrated Personal Health Record is a patient- or family-centered technology designed to capture not only the contacts with health care providers, but also personal information on insurance, diet, and personal preferences that a physician's health record will not capture. Medical banking, based on a new technology platform called the Integrated Health Card, is emerging as a solution to the problem of collecting and combining information from the electronic health record with personal health information. It may also be the only way for fledging health savings accounts to enable the price and quality transparency of the medical market that has been called for repeatedly in this decade. In analyzing the political and patient applications of widespread adoption of this new innovation, the positive contributions to social welfare are very likely to outweigh the negative.Business Economics (2009) 44, 41–50. doi:10.1057/be.2008.2

Using results from peer-reviewed empirical analyses we describe the development and impact of the consumer-driven health plan market over the last 5 years. The results of these analyses show that consumers are responding to the financial incentives of these new health insurance benefits. Although the results may not always be what the consumer-driven health plan developers intended, there is clear evidence of 'consumerism', where individuals act in a way that generally increases their access to healthcare or investments, if the opportunity is present. Just as Medicare Part D enrollment demonstrated consumers could identify differences in prescription drug plans and make rational choices, so too are prospective patients able to function as consumers in the medical marketplace when give the opportunity.

Objectives:The aim of this study was to examine the impact of the multi-hundred million dollar investment by the federal government in the developing Patient Outcomes Research Teams (PORTs) in over a dozen major academic medical centers in the United States throughout the 1990s. The objective of the PORTs was to reduce unnecessary clinical variation in medical treatment.Methods:Using an economic derivation of welfare loss attributable to medical practice variation and hospital admission claims data for 2 million elderly patients generalizable to the nation, we estimate the change in welfare between 1991 and 2000, the period within which the PORTs were designed and executed and their results disseminated.Results:Our results show inpatient admission types targeted by the PORTs did have less welfare loss relative to their total expenditure by 2000, but that there was not a net decrease in the welfare loss for all hospital admissions affected by the PORT.Conclusions:We conclude that PORTs may have had favorable effects on welfare, most likely by reducing variation in clinical care, but that causality cannot be proved, and the effects were not equal across all conditions targeted by PORTs. This research provides a methodological template that may be used to evaluate the impact of patient safety research on welfare loss and on variation in medical treatment in both hospital and ambulatory settings.

Objectives To compare pharmaceutical spending and utilization in a consumer driven health plan (CDHP) with a three-tier pharmacy benefit design, and to examine whether the CDHP creates incentives to reduce pharmaceutical spending and utilization for chronically ill patients, generic or brand name drugs, and mail-order drugs.

The immune system is a powerful barrier to successful organ transplantation, but one that has been routinely thwarted through modern pharmacotherapeutics. Despite the benefits of immunosuppressive therapy, medication non-adherence leads to an increased risk of graft rejection, higher hospital utilization and costs, and poor outcomes. We conduct a scoping review following Arksey and O’Malley’s five-stage framework methodology to identify established or novel interventions that could be applied to kidney transplant recipients to improve medication adherence. As the desired outcome is a behavior (taking a pill), we assess three areas: behavioral-focused interventions in other industries, patient engagement theories, and behavioral economic principles. Search strategies included mining business, social sciences, and medical literature with additional guidance from six consultative interviews. Our review suggests that no intervention stands out as superior or likely to be more effective than any other intervention; yet promising strategies and interventions were identified across all three areas examined. Based on our findings, we believe there are five strategies that transplant centers and other organizations can implement to improve medication adherence: (1) Build a foundation of trust; (2) Employ multiple interventions; (3) Stratify the population; (4) Develop collaborative partnerships; and (5) Embed medication adherence into the organization’s culture. The effectiveness of these interventions will need to be investigated further, but we believe they are a step in the right direction for organizations to consider in their efforts to improve medication adherence.

The appropriateness of new consumer-directed health plan (CDHP) benefit designs for people with chronic illnesses has been questioned, but little information exists regarding the experience of chronically ill individuals in CDHPs. To contribute to a better understanding of the experience of people with chronic illnesses in CDHPs, this study analyzed survey and medical claims data from a large public employer that offered a CDHP as well as other benefit options. An analysis of combined survey, administrative records, and medical claims data was conducted for a sample of employees participating in a large public employer’s health benefits plan. The main outcome measures were plan enrollment decision, use of information, plan rating, and spending patterns. Employees with chronic illness are equally likely as other employees to join a CDHP, to understand key plan coverage features, and to report having a particularly positive or negative experience with their plan. However, CDHP enrollees with chronic illnesses assign higher ratings to their plan than do other CDHP enrollees (p < 0.07). They are more likely than other CDHP enrollees to use informational tools (p < 0.05), more likely to anticipate spending all of their savings account dollars (p < 0.05), and more likely actually to spend more than the deductible (particularly for prescription drug expenditures [p < 0.05]). Compared with other CDHP enrollees whose spending exceeds the deductible, enrollees with chronic illnesses spend significantly more on prescription drugs. Even though the CDHP benefit design was generous, relatively few employees chose the CDHP, and the CDHP was no more attractive to employees with chronic illnesses than to other employees. Furthermore, although people with chronic illnesses who chose CDHPs had some understanding of how their health savings accounts (HSAs) would work, they tended to exhaust those accounts and also spend more than the plan’s deductible. There is much more for employers to do if they want CHDP enrollees with chronic illnesses to ‘manage’ their conditions more effectively.

Background Rankings from the World Health Organization (WHO) place the US health care system as one of the least efficient among Organization for Economic Cooperation and Development (OECD) countries. Researchers have questioned this, noting simplistic or inappropriate methodologies, poor measurement choice, and poor control variables. Our objective is to re-visit this question by using newer modeling techniques and a large panel of OECD data. Methods We primarily use the OECD Health Data for 25 OECD countries. We compare results from stochastic frontier analysis (SFA) and fixed effects models. We estimate total life expectancy as well as life expectancy at age 60. We explore a combination of control variables reflecting health care resources, health behaviors, and economic and environmental factors. Results The US never ranks higher than fifth out of all 36 models, but is also never the very last ranked country though it was close in several models. The SFA estimation approach produces the most consistent lead country, but the remaining countries did not maintain a steady rank. Discussion Our study sheds light on the fragility of health system rankings by using a large panel and applying the latest efficiency modeling techniques. The rankings are not robust to different statistical approaches, nor to variable inclusion decisions. Conclusions Future international comparisons should employ a range of methodologies to generate a more nuanced portrait of health care system efficiency.