Excerpt

The purpose of this paper is to review the types of missing data in patient registries, discuss design and operational strategies for avoiding or minimizing missing data, explore analytic strategies for handling missing data, and consider the impact of missingness on the interpretation and reporting of registry findings. These concepts are discussed in the context of internal validity of studies, or the ability to draw conclusions on the study population, rather than generalizability of results to broader populations who were not enrolled and therefore not represented in the study. The topics discussed are applicable to both retrospective and prospective designs and cover both primary and secondary data sources. Where appropriate, reference is made to other chapters in the document, Registries for Evaluating Patient Outcomes: A User’s Guide.

Contents

• Reviewers (alphabetical)
• Introduction
• Reasons for Missing Data
  • Item Nonresponse
  • Threats From the Left: Truncation
  • Threats From the Right: Loss to Followup, Censoring, Competing Risks
• Approaches to Prevent Missing Data
  • Strategies in Study Design To Minimize Missing Data
  • Operational Strategies To Minimize Missing Data
• Types of Missing Data
• Analytic Implications and Management Strategies For Missing Data
  • Methods
  • Complete Case Analysis
  • Single and Multiple Imputation
  • Inverse Probability Weighting
  • Maximum Likelihood Methods
• Considerations for Reporting Findings From Studies With Missing Data
  • Reporting Guidelines
  • Recommended Sensitivity Analyses
  • Missing Potential Outcomes and Causal Inference
• Conclusions
• References

Suggested citation:

Mack C, Su Z, Westreich D. Managing Missing Patient Data in Patient Registries. White Paper, addendum to Registries for Evaluating Patient Outcomes: A User’s Guide, Third Edition. (Prepared by L&M Policy Research, LLC, under Contract No. 290-2014- 00004-C.) AHRQ Publication No. 17(18)-EHC015-EF. Rockville, MD: Agency for Healthcare Research and Quality; February 2018. www.effectivehealthcare.ahrq.gov. DOI: https://doi.org/10.23970/AHRQREGISTRIESMISSDATA.

This report is based on research conducted by L&M Policy Research, LLC, with partners OM1 and IQVIA, under contract to the Agency for Healthcare Research and Quality, Rockville, MD (Contract No. 290-2014-00004-C). The findings and conclusions in this document are those of the authors, who are responsible for its contents; the findings and conclusions do not necessarily represent the views of AHRQ. Therefore, no statement in this report should be construed as an official position of AHRQ or of the U.S. Department of Health and Human Services.

None of the authors have any affiliations or financial involvement that conflicts withthe material presented in this report.

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