21. Observational evaluation of implementation strategies

  1. Richard Grol,
  2. Michel Wensing,
  3. Martin Eccles and
  4. David Davis
  1. Michel Wensing and
  2. Richard Grol

Published Online: 28 JUN 2013

DOI: 10.1002/9781118525975.ch21

Improving Patient Care: The Implementation of Change in Health Care, Second Edition

Improving Patient Care: The Implementation of Change in Health Care, Second Edition

How to Cite

Wensing, M. and Grol, R. (2013) Observational evaluation of implementation strategies, in Improving Patient Care: The Implementation of Change in Health Care, Second Edition (eds R. Grol, M. Wensing, M. Eccles and D. Davis), John Wiley & Sons, Ltd, Oxford, UK. doi: 10.1002/9781118525975.ch21

Author Information

  1. Department IQ healthcare, UMC St Radboud, Nijmegen, the Netherlands

Publication History

  1. Published Online: 28 JUN 2013
  2. Published Print: 20 MAY 2013

ISBN Information

Print ISBN: 9780470673386

Online ISBN: 9781118525975

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Keywords:

  • change implementation strategies;
  • cohort studies;
  • cross-sectional studies;
  • data analysis;
  • developmental research;
  • healthcare practice;
  • observational evaluation;
  • randomized trial

Summary

A randomized trial is the best study design for evaluating the effectiveness of implementation strategies of changes in healthcare practice, but this design is not always feasible in quality improvement or implementation research. This chapter describes a number of designs and methods for observational evaluations of implementation strategies. Observational evaluations can provide insight into the process, outcomes, and determinants of implementation activities. Attributing outcomes to interventions with a high degree of certainty is generally not possible in these evaluations. Observational evaluations may be descriptive (cross-sectional study, case study, developmental study), or comparative (study with few large clusters, cohort studies). Optimal data analysis in observational evaluations often requires the use of advanced statistical methods.