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Related Experiment Videos

Nonsampling measurement error in administrative data: implications for economic evaluations

N Wolff1, T W Helminiak

  • 1Department of Urban Studies and Community Health, Rutgers University, New Brunswick, NJ 08903, USA.

Health Economics
|November 1, 1996
PubMed
Summary
This summary is machine-generated.

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Measurement errors in administrative data can skew economic evaluations. This study found data quality varies by agency ownership and financial incentives, impacting cost estimates and treatment effect validity. Solutions are proposed.

Area of Science:

  • Health economics
  • Health services research
  • Data quality assessment

Background:

  • Administrative databases are crucial for measuring resource use in economic evaluations.
  • Traditional assumptions posit measurement error is random and uncorrelated with group assignment.
  • Systematic errors can confound treatment effects with data quality issues.

Purpose of the Study:

  • To investigate the impact of nonsampling measurement error on the validity of cost estimates derived from administrative records.
  • To examine how service delivery characteristics, such as ownership and financial incentives, influence data quality.
  • To propose methods for detecting and managing data quality variations in administrative datasets.

Main Methods:

  • Analysis of administrative data from three community mental health centers across different states.

Related Experiment Videos

  • Comparison of data quality based on agency ownership (public vs. private) and financial incentives (reimbursement property rights).
  • Development of tests to detect variations in service use and cost data.

    • Main Results:

    • Evidence of systematic differences in data quality was found, influenced by ownership and financial incentives.
    • Private agencies with reimbursement property rights demonstrated higher data quality compared to public agencies without these rights.
    • The study identified potential biases in cost estimates due to measurement error correlated with service delivery characteristics.

    Conclusions:

    • Nonsampling measurement error in administrative data can compromise the internal and external validity of economic evaluations.
    • Agency characteristics, particularly ownership and financial incentives, significantly affect data quality.
    • Simple tests and cost-effective solutions are needed to manage data quality issues in administrative datasets for reliable economic evaluations.