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Use of a medical records linkage system to enumerate a dynamic population over time: the Rochester epidemiology project.

ABSTRACT: The Rochester Epidemiology Project (REP) is a unique research infrastructure in which the medical records of virtually all persons residing in Olmsted County, Minnesota, for over 40 years have been linked and archived. In the present article, the authors describe how the REP links medical records from multiple health care institutions to specific individuals and how residency is confirmed over time. Additionally, the authors provide evidence for the validity of the REP Census enumeration. Between 1966 and 2008, 1,145,856 medical records were linked to 486,564 individuals in the REP. The REP Census was found to be valid when compared with a list of residents obtained from random digit dialing, a list of residents of nursing homes and senior citizen complexes, a commercial list of residents, and a manual review of records. In addition, the REP Census counts were comparable to those of 4 decennial US censuses (e.g., it included 104.1% of 1970 and 102.7% of 2000 census counts). The duration for which each person was captured in the system varied greatly by age and calendar year; however, the duration was typically substantial. Comprehensive medical records linkage systems like the REP can be used to maintain a continuously updated census and to provide an optimal sampling framework for epidemiologic studies.

SUBMITTER: St Sauver JL

PROVIDER: S-EPMC3105274 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature

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Use of a medical records linkage system to enumerate a dynamic population over time: the Rochester epidemiology project.

St Sauver Jennifer L JL Grossardt Brandon R BR Yawn Barbara P BP Melton L Joseph LJ Rocca Walter A WA

American journal of epidemiology 20110323 9

The Rochester Epidemiology Project (REP) is a unique research infrastructure in which the medical records of virtually all persons residing in Olmsted County, Minnesota, for over 40 years have been linked and archived. In the present article, the authors describe how the REP links medical records from multiple health care institutions to specific individuals and how residency is confirmed over time. Additionally, the authors provide evidence for the validity of the REP Census enumeration. Betwee ...[more]

PMID: 21430193

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Project description:ObjectivesMedical behaviors are playing significant roles in the delivery of high quality and cost-effective health services. Timely discovery of changing frequencies of medical behaviors is beneficial for the improvement of health services. The main objective of this work is to discover the changing trends of medical behaviors over time.MethodsThis study proposes a two-steps approach to detect essential changing patterns of medical behaviors from Electronic Medical Records (EMRs). In detail, a probabilistic topic model, i.e., Latent Dirichlet allocation (LDA), is firstly applied to disclose yearly treatment patterns in regard to the risk stratification of patients from a large volume of EMRs. After that, the changing trends by comparing essential/critical medical behaviors in a specific time period are detected and analyzed, including changes of significant patient features with their values, and changes of critical treatment interventions with their occurring time stamps.ResultsWe verify the effectiveness of the proposed approach on a clinical dataset containing 12,152 patient cases with a time range of 10 years. Totally, 135 patients features and 234 treatment interventions in three treatment patterns were selected to detect their changing trends. In particular, evolving trends of yearly occurring probabilities of the selected medical behaviors were categorized into six content changing patterns (i.e, 112 growing, 123 declining, 43 up-down, 16 down-up, 35 steady, and 40 jumping), using the proposed approach. Besides, changing trends of execution time of treatment interventions were classified into three occurring time changing patterns (i.e., 175 early-implemented, 50 steady-implemented and 9 delay-implemented).ConclusionsExperimental results show that our approach has an ability to utilize EMRs to discover essential evolving trends of medical behaviors, and thus provide significant potential to be further explored for health services redesign and improvement.

Project description:PurposeThe Olmsted County hypertensive disorders of pregnancy (HDP) cohort is a population-based retrospective study designed to compare the incidence of HDP on a per-pregnancy and per-woman basis and to identify associations between HDP with ageing-related diseases, as well as accumulation of multimorbidity.ParticipantsUsing the Rochester Epidemiology Project (REP) medical records-linkage system, a cohort was collected consisting of women who gave birth in Olmsted County between 1976 and 1982. After exclusions, a per-pregnancy cohort of 7544 women with 9862 pregnancies between 1976 and 1982 was identified, and their delivery information was manually reviewed. A subset of these women comprised the per-woman cohort of 4322 pregnancies from 1839 women with delivery information available throughout the entirety of their childbearing years, along with decades of follow-up data available for research via the REP.Findings to dateBy constructing both per-pregnancy and per-woman cohorts, we reported a doubling of HDP incidence rates when assessed on a per-woman basis compared with rates observed on a per-pregnancy basis. Moreover, in addition to finding that women with a history of HDP developed specific diseases at higher rates and at early ages, we also discovered that a history of HDP is associated with accelerated ageing, through accumulation of multimorbidity.Future plansIn addition to these outcomes described above, many other potential outcomes of interest for studies of HDP can be ascertained from accessing the electronic health records (EHR) and billing systems available through the REP. These data can include all International Classification of Diseases (ICD)-9 and ICD-10 and Current Procedural Terminology coded diagnoses and procedures, healthcare utilisation, including office visits, hospitalisations and emergency room visits, and full text of the EHR that is available for chart abstraction or for natural language processing of the clinical notes.

Dataset Information

Use of a medical records linkage system to enumerate a dynamic population over time: the Rochester epidemiology project.

Publications

Use of a medical records linkage system to enumerate a dynamic population over time: the Rochester epidemiology project.

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