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Multilevel and Multi-method Designs

This presentation explores the influence of organizational context and processes on implementing healthcare practices. It highlights how clinicians' behaviors are shaped by their organizational environment and examines the variability of policy implementation effects at local levels. By utilizing multilevel and multi-method designs, the research provides a comprehensive analysis of the interactions between clinical teams, organizational characteristics, and external influences. Emphasizing the significance of context, it addresses challenges in measuring implementation while advocating for robust methodologies in healthcare research.

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Multilevel and Multi-method Designs

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  1. Multilevel and Multi-method Designs Capturing the Effects of Organizational Context and Process in Implementation Research AHRQ 2007 Annual Conference: Improving Healthcare, Improving Lives September 26, 2007 Jeff Alexander, Ph.D. Department of Health Management and Policy University of Michigan School of Public Health

  2. Background • Health care provided in organizational context • behavior of clinicians influenced by the organizations in which they work • policies (e.g. P4P) vary greatly in how they are implemented and what effects they have at the local level. • recognition of the interconnections among components of organizations (clinical teams function within hospitals, interact with other clinical teams, - embeddedness

  3. Implementation: the influence of content, context, and process Implementation Content Process • Opinion leaders, change champion • Systemic processes (e.g., supervisory practices, quality improvement) • Organizational learning • Triability • Innovation type • Evidence interpretation and packaging Context Internal: • Organizational culture • Organizational structure • Practice setting characteristics • Local stakeholders (e.g., attitudes and behaviors) • Resources External: • Networks • regulation • Economic (e.g., reimbursement) • Competition

  4. Problems with Implementation Context Measurement and Analyses • assigning the same group value to all members of a group • aggregating individual outcomes to the group level • Separate analyses of organizational and individual phenomena

  5. Advantages of Multilevel Designs • statistically efficient estimates of regression coefficients • Use of clustering information provides correct standard errors, confidence intervals and significance tests • Allows for uneven assessments and different program tenures (for longitudinal studies)

  6. Advantages of MLD • Measurement at any of the levels of a hierarchy enables examination of whether differences in average outcomes between organizations are explained by factors such as organizational practices/structures, or other characteristics of individual patients or providers

  7. In a multilevel analysis, variance in the dependent variable is decomposed into within and between group components. Two equations result; • a within-unit model: Yij=Boj +rij • and a between-unit model: Boj=Goo +Uoj

  8. Environmental Context • Market Conditions • Managed care penetration • Number of competitors • regulation QI/TQM Implementation • Scope • Number of participating units • % hospital staff on QI Teams • % hospital managers on QI Teams • % MD/FTEs in QI teams • Intensity _# of statistical process tools _#guidelines in use _Use of Quality of care data Potentially Avoidable Adverse Outcomes Risk adjusted mortality Organizational Context -Resources / Infrastructure for QI • financial resources/support • IT • Leadership support

  9. Potential applications of MLD • Effects of organizational infrastructure on implementation in micro teams • Effects of org. culture on individual provider attitudes and behavior (e.g. physician use of clinical guidelines) • Translational research • Effects of micro-team structure and process on patient outcomes

  10. Issues with Multilevel Analysis • Data requirements • Statistical power • Analysis and interpretation issues

  11. Multi-method Designs • Quantitative-Qualitative • RCTs-case study • Process studies-outcome studies • Sustainability- long term studies

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