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Statistical Methods for Analyzing Epidemiological Data

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Using qualitative and quantitative methods to evaluate small-scale disease management pilot programs.

Dominick Esposito1, Erin Fries Taylor, Marsha Gold

  • 1Mathematica Policy Research, Inc., Princeton, New Jersey 08543, USA. desposito@mathematica-mpr.com

Population Health Management
|February 17, 2009
PubMed
Summary

Evaluating small disease management interventions for Medicaid beneficiaries with multiple chronic conditions requires a mixed-methods approach. Combining qualitative insights with quantitative process and outcome measures offers a comprehensive understanding of intervention success and challenges.

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Area of Science:

  • Health Services Research
  • Quality Improvement
  • Chronic Disease Management

Background:

  • Disease management programs are increasingly adopted to enhance healthcare quality and reduce costs.
  • Evaluating smaller interventions is crucial for understanding early-stage initiatives and informing larger programs.

Purpose of the Study:

  • To describe a multi-method approach for evaluating small interventions aimed at improving care quality for Medicaid beneficiaries with multiple chronic conditions.
  • To assess the promise of interventions and identify common themes and challenges.

Main Methods:

  • Utilized a combination of quantitative (process and outcome measures) and qualitative (interviews, logic models) data collection and analysis.
  • Logic models were developed to understand intervention activities and their intended effects on outcomes.
  • Quantitative data included process measures (e.g., case manager contacts) and outcome measures (e.g., hospital use).

Main Results:

  • Qualitative data provided insights into intervention implementation.
  • Process measures confirmed whether implementation aligned with expectations.
  • Outcome measures suggested potential long-term benefits, warranting further investigation.
  • Combined analysis of qualitative and quantitative data assessed intervention promise and identified cross-intervention themes.

Conclusions:

  • A multi-method approach is effective for evaluating small-scale health interventions.
  • Qualitative data is vital for understanding implementation fidelity and contextual factors.
  • Quantitative measures are necessary to assess process and potential outcomes.
  • Integrated analysis provides a holistic view of intervention effectiveness and areas for improvement.