Creating a Comprehensive Database to Evaluate Health Coverage for Pregnant Women

Haas, JS; Ja, Brandenburg; Is, Udvarhelyi; Am, Epstein

doi:10.1097/00005650-199410000-00006

Cited by 8 publications

(4 citation statements)

References 10 publications

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“…For this reason, linkage errors affect statistical power and can directly affect calculations of prevalence and incidence rates, as well as modeling analysis results. 18 19 The linked rate of the data linked by deterministic linkage is represented by P(link), which includes false matches. By applying sophisticated association rules to identify entities, deterministic linkage reduces the number of false matches, but increases the number of missed matches.…”

Section: Methodsmentioning

confidence: 99%

Evaluating Linkage Quality of Population-Based Administrative Data for Health Service Research

Kim,

Choi,

Lim

et al. 2024

J Korean Med Sci

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Background To overcome the limitations of relying on data from a single institution, many researchers have studied data linkage methodologies. Data linkage includes errors owing to legal issues surrounding personal information and technical issues related to data processing. Linkage errors affect selection bias, and external and internal validity. Therefore, quality verification for each connection method with adherence to personal information protection is an important issue. This study evaluated the linkage quality of linked data and analyzed the potential bias resulting from linkage errors. Methods This study analyzed claims data submitted to the Health Insurance Review and Assessment Service (HIRA DATA). The linkage errors of the two deterministic linkage methods were evaluated based on the use of the match key. The first deterministic linkage uses a unique identification number, and the second deterministic linkage uses the name, gender, and date of birth as a set of partial identifiers. The linkage error included in this deterministic linkage method was compared with the absolute standardized difference (ASD) of Cohen’s according to the baseline characteristics, and the linkage quality was evaluated through the following indicators: linked rate, false match rate, missed match rate, positive predictive value, sensitivity, specificity, and F1-score. Results For the deterministic linkage method that used the name, gender, and date of birth as a set of partial identifiers, the true match rate was 83.5 and the missed match rate was 16.5. Although there was bias in some characteristics of the data, most of the ASD values were less than 0.1, with no case greater than 0.5. Therefore, it is difficult to determine whether linked data constructed with deterministic linkages have substantial differences. Conclusion This study confirms the possibility of building health and medical data at the national level as the first data linkage quality verification study using big data from the HIRA. Analyzing the quality of linkages is crucial for comprehending linkage errors and generating reliable analytical outcomes. Linkers should increase the reliability of linked data by providing linkage error-related information to researchers. The results of this study will serve as reference data to increase the reliability of multicenter data linkage studies.

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Section: Methodsmentioning

confidence: 99%

Evaluating Linkage Quality of Population-Based Administrative Data for Health Service Research

Kim,

Choi,

Lim

et al. 2024

J Korean Med Sci

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“…By exploiting a natural experiment from a change in the eligibility of pregnant women for Medicaid benefits, a few quasi-experimental studies have provided evidence of a causal relation between health insurance and health of newborns (Joyce, 1998;Epstein and Newhouse, 1998;Baldwin et al, 1998;Ray et al, 1997;Currie and Gruber, 1996a, 1996b, 1997Reichman and Florio, 1995;Haas et al, 1993;Fossett et al, 1992;Buescher et al, 1991;Piper et al, 1990). The findings generally suggest that health insurance does result in modest reductions in infant mortality.…”

Section: Literature On Health Insurance and Healthmentioning

confidence: 99%

The Health Effects of Medicare for the Near-Elderly Uninsured

Polsky

Doshi

Escarce

et al. 2006

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We study how the trajectory of health for the near-elderly uninsured changes upon enrolling into Medicare at the age of 65. We find that Medicare increases the probability of the previously uninsured having excellent or very good health, decreases their probability of being in good health, and has no discernable effects at lower health levels. Surprisingly, we found Medicare had a similar effect on health for the previously insured. This suggests that Medicare helps the relatively healthy 65 year olds, but does little for those who are already in declining health once they reach the age of 65. The improvement in health between the uninsured and insured were not statistically different from each other. The stability of insurance coverage afforded by Medicare may be the source of the health benefit suggesting that universal coverage at other ages may have similar health effects.

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“…Computerized record linkage has facilitated followup of clinical trials data [2], determination of insurance coverage for pregnant women [3], and evaluation of maternal mortality [4]. Linkage of maternal and newborn medical records has also been instrumental in evaluating the prevalence of birth defects and premature births [5].…”

Section: Introductionmentioning

confidence: 99%

A comparison of record linkage yield for health research using different variable sets

Simon

Mueller

Deapen

et al. 2005

Breast Cancer Res Treat

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As part of a study on childbearing and survival, we linked records of young women with invasive breast cancer identified through three population-based cancer registries, to state birth certificate records. In Michigan prior to 1989, only maternal social security number (SSN) was available for matching; other data became available in 1989 including name, birth date, address, and infant's surname. To examine the quality of the linkage using SSN as the sole matching criterion, we conducted two procedures using data for 1989-1994 to compare linkages identified by SSN, to linkages identified using other available variables. Linkage was conducted using a deterministic approach based on seven variables and 14 steps. In each step a string of relevant variables was created and in successive phases selected variables were substituted or removed with decreasingly stringent requirements. A manual review was done to check for accuracy. Utilizing all available variables, the linkage process yielded 793 matches (live births) among 4496 patients, 780 [98%] of which would have been identified using SSN alone. Five of seven matches identified by SSN were not confirmed by manual review. SSN appears to be fairly accurate for linkage and can be valuable for linking cancer registries to other data sources.

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Creating a Comprehensive Database to Evaluate Health Coverage for Pregnant Women

Cited by 8 publications

References 10 publications

Evaluating Linkage Quality of Population-Based Administrative Data for Health Service Research

Evaluating Linkage Quality of Population-Based Administrative Data for Health Service Research

The Health Effects of Medicare for the Near-Elderly Uninsured

A comparison of record linkage yield for health research using different variable sets

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