The Detection of Date Shifting in Real-World Data
Laura Evans1, Jack W London1,2, Matvey B Palchuk1
1TriNetX, LLC., Boston, Massachusetts, United States.
Applied Clinical Informatics
|July 17, 2023
Summary
Researchers can detect shifted dates in health care real-world data (RWD) by analyzing patterns in routine medical exams. This method reliably identifies data integrity issues, ensuring more accurate patient health event analysis.
Area of Science:
- Health Informatics
- Data Science
- Epidemiology
Background:
- Real-world data (RWD) offers valuable insights into patient care but has limitations.
- Date shifting in RWD can compromise the validity of research findings.
- Accurate temporal data is crucial for reliable health research.
Purpose of the Study:
- To develop and validate a methodology for detecting date shifting in health care RWD.
- To assess the impact of date shifting on the integrity of patient diagnostic and treatment event analysis.
- To improve the reliability of RWD for clinical research and decision-making.
Main Methods:
- A novel methodology was developed to detect date shifting by analyzing temporal patterns in diagnoses and procedures.
- Data from 71 U.S. health care organizations (HCOs) within the TriNetX network were analyzed.
- Synthetic data with varying degrees of date shifting was generated for comparison with actual HCO data.
Main Results:
- The methodology successfully predicted date shifting in 28 out of 71 HCOs, confirmed by data providers.
- 39 HCOs were accurately predicted as having no date shifting.
- The occurrence of routine, weekday-only medical exams showed a high correlation (0.92) with the presence or absence of date shifting.
Conclusions:
- Date shifting in U.S. health care RWD can be reliably detected by examining patterns of routine medical exams.
- Assessing whether routine exams exclusively occur on weekdays is a key indicator of data integrity.
- This approach enhances the trustworthiness of RWD for health research.
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