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 analysis investigates and scores the impact of new health price transparency rules. Using a set of novel data sources, we estimate substantial savings are possible following the implementation of the insurer price transparency rule. Specifically, we estimate annual savings to consumers, employers, and insurers by 2025, assuming a robust set of tools to allow consumers to purchase medical services. We matched claims with 70 HHS defined shoppable services by CPT and DRG codes and replaced them with an estimated median commercial allowed payment multiplied by a reduced cost of 40% based on estimates found from literature for the difference in cost between negotiated and cash payment for medical services. We consider 40% to be an upper bound estimate of the potential savings based on existing literature. Several databases are used to estimate the potential benefits of insurer price transparency. Two different all-payer claim databases were used, representing the entire insured population in the US. For this analysis, only the private insurer commercial population was examined, comprised of over 200 million covered lives as of 2021. The estimated impact of price transparency will vary significantly by region and income level. The national upper bound estimate is $80.7 billion. The national lower bound estimate is $17.6 billion. For the upper bound, the region with the most significant impact in the US will be the Midwest, with $20 billion in potential savings and an 8% reduction in medical expenditure. The region with the lowest impact will be the South, with only a 5.8% reduction. Concerning income, those at lower levels of income will have the most significant impact with a −7.4% (

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.

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 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.

Billions of dollars have been spent on the goal of making healthcare data available to clinicians and researchers in the hopes of improving healthcare and lowering costs. However, the problems of data governance, distribution, and accessibility remain challenges for the healthcare system to overcome.In this study, we discuss some of the issues around holding, reporting, and distributing data, including the newest "big data" challenge: making the data accessible to researchers and policy makers.This article presents a case study in "big healthcare data" involving the Health Care Cost Institute (HCCI). HCCI is a nonprofit, nonpartisan, independent research institute that serves as a voluntary repository of national commercial healthcare claims data.Governance of large healthcare databases is complicated by the data-holding model and further complicated by issues related to distribution to research teams. For multi-payer healthcare claims databases, the 2 most common models of data holding (mandatory and voluntary) have different data security requirements. Furthermore, data transport and accessibility may require technological investment.HCCI's efforts offer insights from which other data managers and healthcare leaders may benefit when contemplating a data collaborative.

Objectives: This study aims to explore factors that influence progression of Diabetes complications among Medicare non-dual beneficiaries. Three Diabetes complications explored are retinopathy, nephropathy and neuropathy. A second objective of this study is to explore the impact that various patient management programs have on reducing the risk of development of Diabetes complications. Three patient management programs are explored, including total cost of treatment (for payer), total patient cost share and physician factors (rural vs. urban and primary care vs. specialist). Methods: Predictive and descriptive logistic regression models are used with each Diabetes complication as the outcome variable. For predictive models, the risk factors are obtained using stepwise logistics regression. For explanatory models, the risks factors are included with each of the analytical factors in order to risk adjust the impact of the analytical factors on the development of Diabetes complications. Results: Nephropathy is found to be the most predictive of the three Diabetes complications. For nephropathy, both total cost of treatment and total patient cost share show negative statistical relation with nephropathy development. For physician factors, rural and specialist physicians are found to be associated with lower rate of nephropathy development among beneficiaries. Conclusions: There is evidence that prediction and management of Diabetes complications can lead to improved outcomes among Medicare beneficiaries. Total cost of treatment, total patient cost share and physician factors (rural vs. urban and primary care vs. specialist) all appear to play a role in improved outcomes in nephropathy development among beneficiaries.

Objectives: U.S. Medicaid expansion has added over 11 Million new enrollees since 2010 and U.S. states are attempting to integrate the increased population as well as addressing fiscal constraints. Account based plans (such as Health Savings Accounts) have been successfully used to control utilization while providing enrollee flexibility. We suggest that a portion of the 55 million Medicaid beneficiary population can be enrolled in account based plans and assist state and federal Health Insurance Exchanges with the ‘churn’ that occurs between the two systems while controlling costs. Methods: We use publicly available per capita Medicaid spending in each state to estimate the population that could be enrolled in an account based plan and apply factors from previous private market research in estimating the reduction in utilization trend and spend for the selected population. Results: We find that using conservative enrollment and utilization trend assumptions that states could collectively see a reduction in spend of over $800 million to over $1 billion in a fiscal year. Conclusions: States can enroll select Medicaid populations that could benefit from having a potentially seamless product that would allow individuals to transition between Medicaid plans and state and federal Health Insurance Exchange products while reducing utilization and spend.

Medicaid and the State Children's Health Insurance Program need analytic tools to manage their programs. Drawing upon extensive discussions with experts in states, this article describes the state of the art in tool use, making several observations: (1) Several states have linked Medicaid/State Children's Health Insurance Program administrative data to other data (eg, birth and death records) to measure access to care. (2) Several states use managed care encounter data to set payment rates. (3) The analysis of pharmacy claims data appears widespread. The article also describes "lessons learned" regarding building capacity and improving data to support the implementation of management tools.

The authors use a two-part model of demand to model the impact of qualified Medicare beneficiary (QMB) enrollment on medical care use. Assuming QMB enrollment to be exogenous, they find Medicare Part B utilization to be 12 percent higher and Part B expenditures 44 percent greater among QMBs than among eligible non-enrollees. There is no difference between these two groups in overall Part A expenditures. Modeling the possibility that QMB enrollment is endogenous, the authors find qualitatively similar results, but the estimates are not precisely estimated.

The 2003 Medicare Prescription Drug, Improvement, and Modernization Act (MMA) approved tax-advantaged health savings accounts (HSAs) for certain high-deductible health insurance plans. We predict that MMA could lead to approximately 3.2 million HSA contracts among Americans ages 19-64 who are not students, not enrolled in public health insurance plans, and not eligible for group coverage as a dependent. We simulate the effect of several additional tax subsidies for HSAs. We predict that the Bush administration's refundable tax-credit proposal would double HSA take-up and reduce the number of uninsured people by 2.9 million, at an annual cost of $8.1 billion.

Objective. To compare medical care costs and utilization in a consumer-driven health plan (CDHP) to other health insurance plans. Study Design. We examine claims and employee demographic data from one large employer that adopted a CDHP in 2001. A quasi-experimental pre–post design is used to assign employees to three cohorts: (1) enrolled in a health maintenance organization (HMO) from 2000 to 2002, (2) enrolled in a preferred provider organization (PPO) from 2000 to 2002, or (3) enrolled in a CDHP in 2001 and 2002, after previously enrolling in either an HMO or PPO in 2000. Using this approach we estimate a difference-in-difference regression model for expenditure and utilization measures to identify the impact of CDHP. Principal Findings. By 2002, the CDHP cohort experienced lower total expenditures than the PPO cohort but higher expenditures than the HMO cohort. Physician visits and pharmaceutical use and costs were lower in the CDHP cohort compared to the other groups. Hospital costs and admission rates for CDHP enrollees, as well as total physician expenditures, were significantly higher than for enrollees in the HMO and PPO plans. Conclusions. An early evaluation of CDHP expenditures and utilization reveals that the new health plan is a viable alternative to existing health plan designs. Enrollees in the CDHP have lower total expenditures than PPO enrollees, but higher utilization of resource-intensive hospital admissions after an initially favorable selection.

“Consumer-driven” health plans (CDHPs) have moved beyond the concept stage and are now available to employees of many large companies. Established insurers, such as Aetna, Humana, Cigna, UnitedHealth Group, and WellPoint are introducing their own CDHPs to compete with products offered by start-up companies such as Definity Health, Luminos, MyHealthBank, and others (Freudenheim 2001). It appears that these products appeal to employers in a period when health insurance premiums are rising at double-digit rates (BNA 2001; Gabel, et al. 2001) and a return to more restrictive forms of managed care seems unpalatable to employees (Galvin and Milstein 2002; Iglehart 2002). A database now exists for assessing the early experience of employers and employees with these plans. Using data from a survey of employees at the University of Minnesota, matched to information from the university's payroll system, we address the question: Who chooses to join a CDHP and, specifically, does this plan attract the healthier employees in a company's risk pool? The research provides important, early information on the impact of CDHPs and the research and policy issues that are likely to arise if they become more commonly available as a health benefit option.

The label “consumer-driven health plan” (CDHP) has been used to describe a wide variety of different health benefit designs that shift more health care costs to consumers at the point of service, on the presumption that it is desirable to give consumers incentives to pay greater attention to the cost and quality consequences of their health care choices (Shaller et al. 2003). Recently, however, the most common use of the term has been in reference to benefit plans with three core features: a personal care account; insurance coverage designed to create a “gap” between the dollars in the account and the level at which a deductible is reached; and various Internet support tools intended to facilitate more extensive, better-informed consumer involvement in health care decisions (Christianson, Parente, and Taylor 2002). These features distinguish CDHPs from other benefit designs, such as tiered hospital networks, that also are intended to provide incentives for consumers to consider cost and quality in selecting providers. Consumer-driven health plans with these core features are offered now by a relatively small number of employers, but they seem to be gaining momentum, with several large national firms recently adding them as benefit options and established insurers expanding their product lines to include CDHPs (Davis 2003a). Consumer-driven health plans generally are not marketed to employers as an immediate “solution” to their rising health care costs, but rather as a constructive employer response to employee demands for more choice, fewer restrictions, and less involvement on the part of employers and health plans in health care decisions. Employer advocates of CDHPs believe the plans have the potential to moderate employer cost increases in the long run, as employees become more involved in their health care decisions, more conscious of prices and better equipped to make price–quality trade-offs (Gabel, Lo Sasso, and Rice 2002). From a broader perspective, some analysts forecast a “consumer revolution” in health care with CDHPs and similar insurance arrangements in the vanguard. They expect this revolution to eventually change traditional relationships between consumers and health care providers resulting in a more efficient, more responsive health care system (Davis 2003c). In contrast, skeptics see CDHPs as simply being vehicles for shifting a greater share of health care costs to consumers, especially consumers with high medical care needs (Swartz 2001/2002), and doubt the ability of a diffuse, consumer-driven market to create change in an increasingly concentrated provider system (Devers et al. 2003). They also point to the complexity of the CDHP benefit design as potentially impeding the ability of enrollees to act as aggressive, informed health care consumers, and they question whether consumers actually want to play this role (Gabel, Lo Sasso, and Rice 2002). Clearly, assumptions about consumers and their behaviors are central to how one views CDHPs and their potential impact on America's health care system. However, at this time, little data are available that relate directly to the experience of enrollees in CDHPs. How satisfied are they with these plans? How do they use the plan features touted by CDHPs, and how satisfied are they with these features? How does the experience of CDHP enrollees vary by individual characteristics? In this article, we begin to address these issues using data collected through a survey of employees at the University of Minnesota. Because our analysis is based on employees from one employed group enrolled in a single CDHP in one health care market at a specific point in time, it should be viewed as a first, limited attempt to shed light on the important consumer issues raised by CDHPs. In the concluding discussion, we suggest directions for future research, based on the results of our analysis.

In 1992, the United States Centers for Medicare and Medicaid Services (CMS) introduced new insurance coverage for two preventive services – influenza vaccinations and mammograms. Economists typically assume transactions occur with perfect information and foresight. As a test of the value of information, we estimate the effect of consumer knowledge of these benefits on their demand. Treating knowledge as endogenous in a two-part model of demand, we find that consumer knowledge has a substantial positive effect on the use of preventive services. Our findings suggest that strategies to educate the insured Medicare population about coverage of preventive services may have substantial social value. Copyright © 2004 John Wiley & Sons, Ltd.

Article-at-a-Glance Background As payers, purchasers, and providers, both the public and private sectors have a stake in developing sound methods of measuring health care quality and patient safety. However, the role of the private sector in a national quality monitoring system remains largely underdeveloped. Private sector role in health care quality monitoring There have been some attempts to pool private-sector data through health care industry efforts to measure and monitor the quality of health care services. Yet despite a number of public/private partnerships, no standard method exists for measuring and monitoring health care quality and safety across public and private payers. The AHRQ workshop on private-sector quality monitoring The Agency for Healthcare Research and Quality (AHRQ) sponsored a workshop in fall 2000 to address the private sector's role in monitoring quality in the health care system. National experts developed a conceptual framework and recommendations on the design and scope of a private-sector data monitoring system. Ten key attributes of the monitoring system, such as timeliness of reports, flexibility, efficiency, and linkability, were identified. Barriers and gaps to the development of such a system include the cost of data collection, the diversity of the units of data collection, data privacy, and limitations of administrative data elements. Summary A comprehensive, public/private data collection system would address the multidimensional nature of quality and use data to effectively represent this complexity to the extent possible.

During the past thirty years outpatient surgery has become an increasingly important part of medical care in the United States. The number of outpatient procedures has risen dramatically since 1981, and the majority of surgeries performed in the United States now take place in outpatient settings. Using data on procedure length, we show that ambulatory surgery centers (ASCs) provide a lower-cost alternative to hospitals as venues for outpatient surgeries. On average, procedures performed in ASCs take 31.8 fewer minutes than those performed in hospitals--a 25 percent difference relative to the mean procedure time. Given the rapid growth in the number of surgeries performed in ASCs in recent years, our findings suggest that ASCs provide an efficient way to meet future growth in demand for outpatient surgeries and can help fulfill the Affordable Care Act's goals of reducing costs while improving the quality of health care delivery.

Retail clinics have the potential to reduce health spending by offering convenient, low-cost access to basic health care services. Retail clinics are often staffed by nurse practitioners (NPs), whose services are regulated by state scope-of-practice regulations. By limiting NPs' work scope, restrictive regulations could affect possible cost savings. Using multistate insurance claims data from 2004-07, a period in which many retail clinics opened, we analyzed whether the cost per episode associated with the use of retail clinics was lower in states where NPs are allowed to practice independently and to prescribe independently. We also examined whether retail clinic use and scope of practice were associated with emergency department visits and hospitalizations. We found that visits to retail clinics were associated with lower costs per episode, compared to episodes of care that did not begin with a retail clinic visit, and the costs were even lower when NPs practiced independently. Eliminating restrictions on NPs' scope of practice could have a large impact on the cost savings that can be achieved by retail clinics.

This paper describes a business model of e-commerce, its application to health care, and the reasons why the health policy community should monitor its development. The business model identifies the market barriers health e-commerce firms must overcome and provides perspective on opportunities for building a health care data infrastructure that is capable of delivering both a private and a public good.

Having a measure of productivity that relates funds and effort spent on medical treatment to health outcomes could help policymakers better understand whether they are getting value for the money spent on public health insurance programs. This article describes such a metric, the medical productivity index (MPI), and illustrates how it was used to analyze a sampling of Medicare claims from 2007 through 2009.

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 roles of technological and organizational complements in affecting IT's value and explore underlying mechanisms through which IT facilitates the coordination of labor inputs. We link detailed hospital discharge data on all Medicare fee-for-service admissions from 2002-2007 to detailed hospital-level IT adoption information. We employ a difference-in-differences strategy to identify the parameters of interest. 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. This implies that the benefits from IT adoption are skewed to large institutions with a severe case mix. We decompose the impact of health IT into care coordination, clinical information management, and other components. The benefits from health IT are primarily experienced by patients whose diagnoses require cross-specialty care coordination and extensive clinical information management.

Objectives: Physician payments from public and private payers are still largely paper-based, so significant payment lags are prevalent across all reimbursement systems. Electronic Medical Record use has the potential to reduce payment lag and improve health system performance. Methods: We use a claims data set of 100,000 covered lives from a national employer to examine mean accounts receivable (AR) payment times by provider type, physician specialty, and state. Eleven physician specialty disciplines are included in the analysis of mean AR and days of payment lag. We also include a coefficient of variation (CV) of physician claims processed by place of delivery and correlation (R2: r-squared) values between mean days of AR and mean CV. Results: We find significant variation in mean AR days by provider type and physician specialty. There is also a great deal of variation in payment processing lags by state. We find a range of correlations between mean AR days and mean CV by provider type of service (R2=0.6288), physician specialties (R2=0.662), and the state of service (R2=0.1247). Conclusions: Low EMR adoption rates impact how all payer types pay physicians. The elimination of paper-based claims (and their associated lag times) could be achieved through the adoption of basic practice management systems bundled with EMRs. There is sufficient health savings from shortening the AR lag time period for insurer payment to providers to finance EMR adoption even with without federal HITECH incentives to practices.

A famous quote from Winston Churchill is “Democracy is the worst form of government, except for all those other forms that have been tried from time to time”. With respect to health reform, I often paraphrase that market based health reform is the worse option given the alternatives. The history of “health reform” is really a timeline of failed national health insurance congressional proposals since the 1910s when the US began its 100 year deviation from European nation states that embraced some form of federal government financing of health insurance. Economics has always been at the heart of the US health policy debate over national health insurance. This essay sets out to provide a narrative foundation of health economic actors that have fought hard for their market dominance and will likely determine whether the US will finally join the ‘community of nations’ with federally financed compulsory national health insurance or continue to write the history towards an undiscovered country of market based health reform. Every health care markets class I’ve taught begins with an economic history of how physicians in the USwent from ‘doctors on horseback’ to the Uber monopolists of high technology craftsmen they are today. A key message can be found in the actions of organized medicine during the last 150 years. These actions have been anything but random in the profession’s desire to create a truly monopolist guild. Fortunately for me, one of the best texts on the subject by Paul Starr has been out of print since Starr won the Pulitzer for The Social Transformation of American Medicine in 1982. Since most of my students weren’t conceived until after 1982, the material is ‘new to them’ as well as critical to understanding why the US does not have a national health insurance program. Starr recounts how legislative attempts

Healthcare is an important social and economic component of modern society, and the effective use of information technology in this industry is critical to its success. As health insurance premiums continue to rise, competitive bidding may be useful in generating stronger price competition and lower premium costs for employers and possibly, government agencies. In this paper, we assess an endeavor by several Fortune 500 companies to reduce healthcare procurement costs for their employees by having HMOs compete in open electronic auctions. Although the auctions were successful in generating significant cost savings for the companies in the first year, i.e., 1999, they failed to replicate the success and were eventually discontinued after two more years. Over the past decade since the failed auction experiment, effective utilization of information technologies have led to significant advances in the design of complex electronic markets. Using this knowledge, and data from the auctions, we point out several shortcomings of the auction design that, we believe, led to the discontinuation of the market after three years. Based on our analysis, we propose several actionable recommendations that policy makers can use to design a sustainable electronic market for procuring health insurance.

We exploit the discontinuity in age when children start kindergarten generated by state eligibility laws to examine whether relative age is a significant determinant of ADHD diagnosis and treatment. Using a regression discontinuity model and exact dates of birth, we find that children born just after the cutoff, who are relatively old-for-grade, have a significantly lower incidence of ADHD diagnosis and treatment compared with similar children born just before the cutoff date, who are relatively young-for-grade. Since ADHD is an underlying neurological problem where incidence rates should not change dramatically from one birth date to the next, these results suggest that age relative to peers in class, and the resulting differences in behavior, directly affects a child's probability of being diagnosed with and treated for ADHD.

We propose a model of enrollee incentives in consumer directed health plans (CDHPs) and estimate the model with data from a large employer that offered a CDHP in addition to two traditional health insurance plans. In the CDHP a portion of the enrollee's pretax compensation is placed in an account that can be used to pay for out-of-pocket medical expenses or rolled over to the next year. In a multi-period model, healthy employees should save part of the account to pay for future medical contingencies. We measured health status by the employee's predicted medical spending in the year prior to the CDHP offering. We found that healthy CDHP enrollees tended to spend less in three post-enrollment years than a comparison group of healthy employees who elected to keep their traditional health insurance coverage. However, CDHP enrollees with high predicted spending—a measure of poorer health—spent more than their comparison group of traditional health insurance enrollees in the following three years.