ArticleAnnals of epidemiology2011
Who doesn't authorize the linking of survey and administrative health data? A general population-based investigation.
Article in Annals of epidemiology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Trial
- Embedding research study recruitment within the patient portal preCheck-in.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- A systematic literature review of attitudes towards secondary use and sharing of health administrative and clinical trial data: a focus on consent.Systematic reviews · 2021Article
- Ethical and practical challenges to studying patients who opt out of large-scale biorepository research.Journal of the American Medical Informatics Association : JAMIA · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
purposeTo determine the extent of authorization bias in a study linking survey and medical record data in a general population-based investigation.
methodsAuthorization status (authorized data linkage vs. not) was ascertained through a sequential mixed mode mail and telephone survey conducted in Olmsted County, MN. Respondents (regardless of authorization status) were linked to the Rochester Epidemiology Project (REP), the medical record system for health care providers in Olmsted County. The REP provided data on gender, age, race, health status (co-morbid conditions), and health care utilization (ER admission, hospital admission, clinical office visits and procedures). Authorizers (n=1357) are compared to non-authorizers (n=217) with respect to these demographic and clinical characteristics.
results86.2% of respondents authorized data linkage. Non-authorizers were younger, healthier (lower Charlson score), and less likely to have 3 or more recent clinical office visits. In multivariate analysis, Charlson score was no longer a significant predictor of authorization while an ER visit did predict authorization.
conclusionsYounger subjects are less likely to authorize data linkages. As such, researchers should be aware of this source of potential bias when analyzing population-based linked survey and administrative data. The presence of bias with respect to health care use is more complicated. It is dependent on how the concept is operationalized with heavy clinical users more likely to authorize and those with ER visits less so.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.