Impact of 2 employer-sponsored population health management programs on medical care cost and utilization.

BACKGROUND: Integrated health management programs combining disease prevention and disease management services, although popular with employers, have been insufficiently researched with respect to their effect on costs. OBJECTIVE: To estimate the overall impact of a population health management program and its components on cost and utilization. STUDY DESIGN, SETTING, AND PARTICIPANTS: Observational study of 2 employer-sponsored health management programs involving more than 200,000 health plan members. METHODS: We used claims data for the first program year and the 2 preceding years to calculate cost and utilization metrics, and program activity data to determine program uptake. Using an intent-to-treat approach and regression-based risk adjustment, we estimated whether the program was associated with changes in cost and utilization. Data on program fees were unavailable. RESULTS: Overall, the program was associated with a nonsignificant cost increase of $13.75 per member per month (PMPM). The wellness component alone was associated with a significant increase of $20.14 PMPM. Case and disease management were associated with a significant decrease in hospital admissions of 4 and 1 per 1000 patient-years, respectively. CONCLUSIONS: Our results suggest that the programs did not reduce medical cost in their first year, despite a beneficial effect on hospital admissions. If we had been able to include program fees, it is likely that the overall cost would have increased significantly. Although this study had important limitations, the results suggest that a belief that these programs will save money may be too optimistic and better evaluation is needed.

Testing the DMAA's recommendations for disease management program evaluation.

The objective of this study was to compare and contrast findings regarding the financial savings projections of the disease management (DM) programs of 2 large employers based on different evaluation methods. In particular, this research tests the impact of differences in assumptions on the underlying growth rate of group health costs, exclusions of high-cost conditions and claims, and the length of the baseline period for determined health care costs. A pre-post study design was used. The data for this research came from 2 large employers in the consumer goods industry with comprehensive Health and Productivity Management programs. It contained medical and prescription drug claims and health plan enrollment data as well as program activity data from 2001 to 2005, covering an average yearly sample size of 201,037 members with 12 consecutive months of enrollment. Analyses were done on group-level averages using nominal cost data and were run to reflect the impact of a DM-only intervention. While the trend estimate and length of baseline had the largest effects on estimated program impact, the use of exclusions had an important effect as well. These findings demonstrate the importance of developing and instituting a standardized evaluation methodology. Without increasing consistency in the way evaluators develop their methodologies, it will remain difficult to be able to compare one evaluation to another, or to have faith in the results at hand.

Community planning for pandemic influenza: lessons from the VA health care system.

BACKGROUND: Coordination and communication among community partners-including health departments, emergency management agencies, and hospitals-are essential for effective pandemic influenza planning and response. As the nation's largest integrated health care system, the US Department of Veterans Affairs (VA) could be a key component of community planning. PURPOSE: To identify issues relevant to VA-community pandemic influenza preparedness. METHODS: As part of a VA-community planning process, we developed and pilot-tested a series of tabletop exercises for use throughout the VA system. These included exercises for facilities, regions (Veterans Integrated Service Networks), and the VA Central Office. In each, VA and community participants, including representatives from local health care facilities and public health agencies, were presented with a 3-step scenario about an unfolding pandemic and were required to discuss issues and make decisions about how the situation would be handled. We report the lessons learned from these pilot tests. RESULTS: Existing communication and coordination for pandemic influenza between VA health care system representatives and local and regional emergency planners are limited. Areas identified that would benefit from better collaborative planning include response coordination, resource sharing, uneven resource distribution, surge capacity, standards of care, workforce policies, and communication with the public. CONCLUSIONS: The VA health system and communities throughout the United States have limited understanding of one another's plans and needs in the event of a pandemic. Proactive joint VA-community planning and coordination-including exercises, followed by deliberate actions to address the issues that arise-will likely improve pandemic influenza preparedness and will be mutually beneficial. Most of the issues identified are not unique to VA, but are applicable to all integrated care systems.

Measuring the performance of telephone-based disease surveillance systems in local health departments.

OBJECTIVES: We tested telephone-based disease surveillance systems in local health departments to identify system characteristics associated with consistent and timely responses to urgent case reports. METHODS: We identified a stratified random sample of 74 health departments and conducted a series of unannounced tests of their telephone-based surveillance systems. We used regression analyses to identify system characteristics that predicted fast connection with an action officer (an appropriate public health professional). RESULTS: Optimal performance in consistently connecting callers with an action officer in 30 minutes or less was achieved by 31% of participating health departments. Reaching a live person upon dialing, regardless of who that person was, was the strongest predictor of optimal performance both in being connected with an action officer and in consistency of connection times. CONCLUSIONS: Health departments can achieve optimal performance in consistently connecting a caller with an action officer in 30 minutes or less and may improve performance by using a telephone-based disease surveillance system in which the phone is answered by a live person at all times.