Reductions in Diagnostic Imaging With High Deductible Health Plans.

BACKGROUND: Diagnostic imaging utilization grew rapidly over the past 2 decades. It remains unclear whether patient cost-sharing is an effective policy lever to reduce imaging utilization and spending. MATERIALS AND METHODS: Using 2010 commercial insurance claims data of >21 million individuals, we compared diagnostic imaging utilization and standardized payments between High Deductible Health Plan (HDHP) and non-HDHP enrollees. Negative binomial models were used to estimate associations between HDHP enrollment and utilization, and were repeated for standardized payments. A Hurdle model were used to estimate associations between HDHP enrollment and whether an enrollee had diagnostic imaging, and then the magnitude of associations for enrollees with imaging. Models with interaction terms were used to estimate associations between HDHP enrollment and imaging by risk score tercile. All models included controls for patient age, sex, geographic location, and health status. RESULTS: HDHP enrollment was associated with a 7.5% decrease in the number of imaging studies and a 10.2% decrease in standardized imaging payments. HDHP enrollees were 1.8% points less likely to use imaging; once an enrollee had at least 1 imaging study, differences in utilization and associated payments were small. Associations between HDHP and utilization were largest in the lowest (least sick) risk score tercile. CONCLUSIONS: Increased patient cost-sharing may contribute to reductions in diagnostic imaging utilization and spending. However, increased cost-sharing may not encourage patients to differentiate between high-value and low-value diagnostic imaging services; better patient awareness and education may be a crucial part of any reductions in diagnostic imaging utilization.

Bringing responsibility for small area variations in hospitalization rates back to the hospital: the propensity to hospitalize index and a test of the Roemer's Law.

OBJECTIVE: To assign responsibility for variations in small area hospitalization rates to specific hospitals and to evaluate the Roemer's Law in a way that does not artificially induce correlation between bed supply and utilization. DATA SOURCES/STUDY SETTING: We used data on hospitalizations and outpatient treatment for 15 medical conditions of nonmanaged care Part B eligible Medicare enrollees of 65 years and older in Massachusetts in 2000. STUDY DESIGN: We used a Bayesian model to estimate each hospital's pool of potential patients and the fraction of the pool hospitalized (its propensity to hospitalize, PTH). To evaluate the Roemer's Law, we calculated the correlation between hospitals' PTH and beds per potential patient. Patient severity was measured using All Patient Refined Diagnosis Related Groups. RESULTS: We show that our approach does not artificially induce a correlation between beds and utilization whereas the traditional approach does. Nevertheless, our approach indicates a strong relationship between PTH and beds (r=0.56). Eighteen (of 66) hospitals had a high PTH that differed significantly from 16 hospitals with a low PTH. Average patient severity in the high PTH hospitals was lower than in the low PTH hospitals. Although the difference was not statistically significant (P=0.12), there was a medium effect size (0.58). DISCUSSION: Variation across hospitals in the PTH index, the strong relationship between beds and the PTH, and the lack of relationship between severity and the PTH suggest the importance of policies that limit bed growth of high PTH hospitals and create incentives for high PTH hospitals to reduce hospitalizations.

Toward an effective strategy for the diffusion and use of clinical information systems.

The full impact of IT in health care has not been realized because of the failure to recognize that (1) the path from availability of applications to the anticipated benefits passes through a series of steps; and (2) progress can be stopped at any one of those steps. As a result, strategies for diffusion, adoption, and use have been incomplete and have produced disappointing results. In this paper, we present a comprehensive framework for identifying factors that affect the spread, use, and effects of IT in the U.S. health care sector. The framework can be used by researchers to focus their efforts on unanswered questions, by practitioners considering IT adoption, and by policymakers searching for ways to spread IT throughout the system.

Building the case for quality improvement in the health care industry: a focus on goals and training.

Health care organizations are under intense pressure to improve the efficiency and effectiveness of care delivery and, increasingly, they are using quality improvement teams to identify and target projects to improve performance outcomes. This raises the question of what factors actually drive the performance of these projects in a health care environment. Using data from a survey of health care professionals acting as informants for 244 patient care, clinical-administrative, and nonclinical administrative quality improvement project types in 93 health care organizations, we focus on 2 factors--goal setting and quality training--as potential drivers of quality improvement project performance. We find that project-level goals and quality training have positive associations with process quality, while organizational-level goals have no impact. In addition, the relationship between project-level goals and process quality is stronger for patient care projects than for administrative projects. This indicates that the motivational and cognitive effects of goal setting are greater for projects that involve interactions with clinicians than for ones that involve interactions with other staff. Although project-level goal setting is beneficial for improving process quality overall, our findings suggest the importance of being especially attentive to goal setting for projects that impact direct patient care.

The accountable health care act of Massachusetts: mixed results for an experiment in universal health care coverage.

The affordable health care act of Massachusetts, signed into law in 2006, resulted in 98% of Massachusetts residents' having some form of insurance coverage by 2011, the highest coverage rate for residents of any state in the nation. With a strong economy, a low unemployment rate, a robust health care delivery system, an extremely low number of undocumented immigrants, and a low baseline uninsured rate, Massachusetts was well positioned for such an effort. Ingredients included mandates, the creation of separate insurance vehicles directed to both poverty-level and non-poverty-level residents, and the reallocation of the former free care pool. The mandates included consumer mandates and employer mandates; the consumer mandate applies to all Massachusetts residents at the risk of losing personal state tax exemptions, and the employer mandate applies to all Massachusetts businesses with 10 or more employees at the risk of per employee financial penalties. The insurance vehicles were created with premiums allocated on the basis of ability to pay by income classes. Unexpected effects included escalating taxpayer health care costs, with taxpayers shouldering the burden for the newly insured, continuing escalating health care costs at a rate greater than the national average, overburdening primary caregivers as newly insured sought new primary care gatekeepers in a system with primary caregiver shortages, and deprivation of support to the safety-net hospitals as a result of siphoned commonwealth free care pool funds. This exercise demonstrates specific benefits and shortfalls of the Massachusetts health care reform experiment, given the conditions and circumstances found in Massachusetts at the time of implementation.

Does more "appropriateness" explain higher rates of cardiac procedures among patients hospitalized with coronary heart disease?

BACKGROUND: There have been few studies of the extent to which differences in the pool of patients being managed might account for geographic variations in treatment rates. OBJECTIVE: For two cardiac procedures, cardiac catheterization and revascularization, we evaluate the hypothesis that differences in "the percentage of patients for whom the procedure is appropriate" is a factor explaining variations in use rates among those hospitalized with coronary heart disease (CHD). RESEARCH DESIGN: Based on hospital utilization patterns in Massachusetts in 1990, we created 70 small geographic areas. Using 1992 Massachusetts Peer Review Organization data, areas were ranked from highest to lowest based on (empirical-Bayes-adjusted) hospitalization rates for each procedure. One thousand seven hundred four cases from 43 hospitals were sampled, roughly half each from high and low use areas. Half had a procedure and half were candidates for the same procedure but did not have it. For each procedure, medical records were reviewed to determine whether the procedure was (or, for those not having it, would have been) appropriate, based on criteria developed using a modified Delphi approach. RESULTS: Among those having either procedure, appropriateness rates were similar in high and low rate areas (P = 0.59 for catheterization and P = 0.30 for revascularization). However, among candidates for either procedure who did not have it, appropriateness for performing the procedure was greater in high-rate areas (41.4% vs. 32.1%, P = 0.05 for catheterization; 71.2% vs. 57.2%, P = 0.003, for revascularization). CONCLUSION: Among those hospitalized with CHD, appropriateness rates for two cardiac procedures are higher in areas with higher use rates.