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Related Experiment Video

Updated: Jun 25, 2026

Environmental Dynamic Mechanical Analysis to Predict the Softening Behavior of Neural Implants
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"Dial-an-ROI?" changing basic variables impacts cost trends in single-population pre-post ("DMAA type") savings

Iver A Juster1, Stephen N Rosenberg, Deeptimayee Senapati

  • 1ActiveHealth Management, Sausalito, California, USA. ijuster@comcast.net

Population Health Management
|February 17, 2009
PubMed
Summary

Disease management programs aim for cost savings, but proving them is hard without comparison groups. This study shows small changes in data analysis methods significantly alter cost trend results.

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Area of Science:

  • Health economics
  • Healthcare management
  • Biostatistics

Background:

  • Disease management (DM) programs are intended to reduce healthcare costs by improving clinical outcomes.
  • Demonstrating cost savings from DM programs is challenging, particularly without external comparison populations.
  • Single-population methodologies often assume similar cost trends between participants (chronics) and non-participants (non-chronics) in the absence of DM.

Purpose of the Study:

  • To assess the impact of key variable choices on the validity of single-population DM cost savings methodologies.
  • To evaluate the assumption of identical baseline trends between chronic and non-chronic populations under varying analytical parameters.

Main Methods:

  • Compared baseline cost trends for chronic (C) and non-chronic (NC) populations within a large telephonic DM program.
  • Analyzed 16 combinations of 4 key variables: identification look-back frame, identification threshold, claims runout, and minimum eligibility.
  • Assessed trends using annual qualification for 23 conditions affecting nearly 300,000 members.

Main Results:

  • Variations in the 4 key variables significantly altered baseline C and NC trends.
  • C trends ranged from 10.1% to 13.1%, while NC trends ranged from 5.2% to 12.8%.
  • The most convergent C and NC trends (10.4% and 10.7%) were achieved with specific parameter settings (24-month look-back, high threshold, 6-month runout, 6-month eligibility).

Conclusions:

  • Minor adjustments in analytical variables can substantially impact the perceived cost trends in single-population DM savings studies.
  • Reporting baseline trends for both chronic and non-chronic groups, along with specified variable values, is crucial when external comparisons are unavailable.
  • Utilizing plausibility metrics, such as hospitalizations, is recommended to validate DM program savings assessments.