Validating the Matching of Patients in the Linkage of a Large Hospital System's EHR with State and National Death Databases

Conway, Rebecca; Armistead, Matthew; Denney, Michael J.; Smith, Gordon S.

doi:10.1055/s-0040-1722220

Cited by 7 publications

(3 citation statements)

References 17 publications

(31 reference statements)

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“…As a federal patient registry, there is a high level of data completeness, however, the dataset has fewer matching fields relative to the other datasets. 26…”

Section: Methodsmentioning

confidence: 99%

“…The Social Security Number Death Master Registry (SSDMR) contains 89,556,520 records of national death data linked to all participating health information exchange organizations within the INPC database. As a federal patient registry, there is a high level of data completeness however the dataset has fewer matching fields relative to the other data sets 26 .…”

Section: Accepted Manuscriptmentioning

confidence: 99%

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Manual Evaluation of Record Linkage Algorithm Performance in Four Real-World Datasets

Gupta,

Xu,

et al. 2024

Appl Clin Inform

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Background: Patient data is fragmented across multiple repositories, yielding suboptimal and costly care. Record linkage algorithms are widely accepted solutions for improving completeness of patient records. However, studies often fail to fully describe their linkage techniques. Further, while many frameworks evaluate record linkage methods, few focus on producing gold standard datasets. This highlights a need to assess these frameworks and their real-world performance. Objective: We use real-world datasets and expand upon previous frameworks to evaluate a consistent approach to the manual review of gold standard datasets and measure its impact on algorithm performance. Methods: We applied the framework, which includes elements for data description, reviewer training and adjudication, and software and reviewer descriptions, to four datasets. Record-pairs were formed and 15,000 records were randomly sampled from these pairs. After training, two reviewers determined match status for each record-pair. If reviewers disagreed, a third reviewer was used for final adjudication. Results: Between the four datasets, the percent discordant rate ranged from 1.8-13.6%. While reviewers’ discordance rate typically ranged between 1% and 5%, one exhibited a 59% discordance rate, showing the importance of the third reviewer. The original analysis was compared to three sensitivity analyses. The original analysis most often exhibited the highest predictive values compared to the sensitivity analyses. Conclusion: Reviewers vary in their assessment of a gold standard, which can lead to variances in estimates for matching performance. Our analysis demonstrates how a multi-reviewer process can be applied to create gold standards, identify reviewer discrepancies, and evaluate algorithm performance.

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“…As a federal patient registry, there is a high level of data completeness, however, the dataset has fewer matching fields relative to the other datasets. 26…”

Section: Methodsmentioning

confidence: 99%

Section: Accepted Manuscriptmentioning

confidence: 99%

Manual Evaluation of Record Linkage Algorithm Performance in Four Real-World Datasets

Gupta,

Xu,

et al. 2024

Appl Clin Inform

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“…[9][10][11] RL refers to the technical and analytic methods for effectively and securely matching patient records from multiple distinct health systems and data platforms, such as electronic health records, administrative claims, patientreported outcomes measures, and digital health devices. [12][13][14] RL has several benefits for research, such as enhancing the amount and types of information available about each patient (e.g., information about all services a patient has received, what prescriptions have been filled, how much physical activity they have done, and their quality of life), which are not typically all included in one data source. This facilitates answering patient-centered research questions about the extent to which certain treatments and interventions impact objective patient behavior, self-reported outcomes, and clinical outcomes, and the relationships among these factors.…”

Section: Background and Significancementioning

confidence: 99%

Engaging Patients and Other Stakeholders in “Designing for Dissemination” of Record Linkage Methods and Tools

Reno,

Ong,

Voong

et al. 2023

Appl Clin Inform

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Background: Novel record linkage (RL) methods have the potential to enhance clinical informatics by integrating patient data from multiple sources—including electronic health records, insurance claims, and digital health devices—to inform patient-centered care. Engaging patients and other stakeholders in the use of RL methods in patient-centered outcomes research (PCOR) is a key step in ensuring RL methods are viewed as acceptable, appropriate, and useful. The CU Record Linkage (CURL) platform empowers the use of RL in PCOR. Objective: Describe the process of engaging patients and other stakeholders in the design of a RL dissemination package to support the use of RL methods in PCOR. Methods: Customer discovery, value proposition design, and user-experience methods were used to iteratively develop an RL dissemination package that includes animated explainer videos for patients and an RL research planning workbook for researchers. Patients and other stakeholders (researchers, data managers, and regulatory officials) were engaged in the RL dissemination package design. Results: Patient partners emphasized the importance of conveying how RL methods may benefit patients and the rules researchers must follow to protect the privacy and security of patient data. Other stakeholders described accuracy, flexibility, efficiency, and data security compared to other available RL solutions. Dissemination package communication products reflect the value propositions identified by key stakeholders. As prioritized by patients, the animated explainer videos emphasize the data privacy and security processes and procedures employed when performing research using RL. The RL workbook addresses researchers’ and data managers’ needs to iteratively design RL projects and provides accompanying resources to alleviate leadership and regulatory officials’ concerns about data regulation compliance. Conclusions: Dissemination products to promote adoption and use of CURL include materials to facilitate patient engagement in RL research and investigator step-by-step decision-making materials about the integration of RL methods in patient-centered outcomes research.

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Trends in the Completeness and Validity of Sources of Death Data Against the National Death Index From 2010 to 2018

Sponholtz,

Jamal‐Allial,

Vojjala

et al. 2024

Pharmacoepidemiology and Drug

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PurposeWe investigated time trends in validation performance characteristics for six sources of death data available within the Healthcare Integrated Research Database (HIRD) over 8 years.MethodsWe conducted a secondary analysis of a cohort of advanced cancer patients with linked National Death Index (NDI) data identified in the HIRD between 2010 and 2018. We calculated sensitivity, specificity, positive predictive value, and negative predictive value for six sources of death status data and an algorithm combining data from available sources using NDI data as the reference standard. Measures were calculated for each year of the study including all members in the cohort for at least 1 day in that year.ResultsWe identified 27 396 deaths from any source among 40 692 cohort members. Between 2010 and 2018, the sensitivity of the Death Master File (DMF) decreased from 0.77 (95% CI = 0.76, 0.79) to 0.12 (95% CI = 0.11, 0.14). In contrast, the sensitivity of online obituary data increased from 0.43 (95% CI = 0.41, 0.45) in 2012 to 0.71 (95% CI = 0.68, 0.73) in 2018. The sensitivity of the composite algorithm remained above 0.83 throughout the study period. PPV was observed to be high from 2010 to 2016 and decrease thereafter for all sources. Specificity and NPV remained at high levels throughout the study.ConclusionsWe observed that the sensitivity of mortality data sources compared with the NDI could change substantially between 2010 and 2018. Other validation characteristics were less variable. Combining multiple sources of mortality data may be necessary to achieve adequate performance particularly for multiyear studies.

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Validating the Matching of Patients in the Linkage of a Large Hospital System's EHR with State and National Death Databases

Cited by 7 publications

References 17 publications

Manual Evaluation of Record Linkage Algorithm Performance in Four Real-World Datasets

Manual Evaluation of Record Linkage Algorithm Performance in Four Real-World Datasets

Engaging Patients and Other Stakeholders in “Designing for Dissemination” of Record Linkage Methods and Tools

Trends in the Completeness and Validity of Sources of Death Data Against the National Death Index From 2010 to 2018

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