Rochester Epidemiology Project Data Exploration Portal.

INTRODUCTION: The goal of this project was to develop an interactive, web-based tool to explore patterns of prevalence and co-occurrence of diseases using data from the expanded Rochester Epidemiology Project (E-REP) medical records-linkage system. METHODS: We designed the REP Data Exploration Portal (REP DEP) to include summary information for people who lived in a 27-county region of southern Minnesota and western Wisconsin on January 1, 2014 (n = 694,506; 61% of the entire population). We obtained diagnostic codes of the International Classification of Diseases, 9th edition, from the medical records-linkage system in 2009 through 2013 (5 years) and grouped them into 717 disease categories. For each condition or combination of 2 conditions (dyad), we calculated prevalence by dividing the number of persons with a specified condition (numerator) by the total number of persons in the population (denominator). We calculated observed-to-expected ratios (OERs) to test whether 2 conditions co-occur more frequently than would co-occur as a result of chance alone. RESULTS: We launched the first version of the REP DEP in May 2017. The REP DEP can be accessed at http://rochesterproject.org/portal/. Users can select 2 conditions of interest, and the REP DEP displays the overall prevalence, age-specific prevalence, and sex-specific prevalence for each condition and dyad. Also displayed are OERs overall and by age and sex and maps of county-specific prevalence of each condition and OER. CONCLUSION: The REP DEP draws upon a medical records-linkage system to provide an innovative, rapid, interactive, free-of-charge method to examine the prevalence and co-occurrence of 717 diseases and conditions in a geographically defined population.

History of the Rochester Epidemiology Project: half a century of medical records linkage in a US population.

The Rochester Epidemiology Project (REP) has maintained a comprehensive medical records linkage system for nearly half a century for almost all persons residing in Olmsted County, Minnesota. Herein, we provide a brief history of the REP before and after 1966, the year in which the REP was officially established. The key protagonists before 1966 were Henry Plummer, Mabel Root, and Joseph Berkson, who developed a medical records linkage system at Mayo Clinic. In 1966, Leonard Kurland established collaborative agreements with other local health care providers (hospitals, physician groups, and clinics [primarily Olmsted Medical Center]) to develop a medical records linkage system that covered the entire population of Olmsted County, and he obtained funding from the National Institutes of Health to support the new system. In 1997, L. Joseph Melton III addressed emerging concerns about the confidentiality of medical record information by introducing a broad patient research authorization as per Minnesota state law. We describe how the key protagonists of the REP have responded to challenges posed by evolving medical knowledge, information technology, and public expectation and policy. In addition, we provide a general description of the system; discuss issues of data quality, reliability, and validity; describe the research team structure; provide information about funding; and compare the REP with other medical information systems. The REP can serve as a model for the development of similar research infrastructures in the United States and worldwide.

Data resource profile: the Rochester Epidemiology Project (REP) medical records-linkage system.

The Rochester Epidemiology Project (REP) medical records-linkage system was established in 1966 to capture health care information for the entire population of Olmsted County, MN, USA. The REP includes a dynamic cohort of 502 820 unique individuals who resided in Olmsted County at some point between 1966 and 2010, and received health care for any reason at a health care provider within the system. The data available electronically (electronic REP indexes) include demographic characteristics, medical diagnostic codes, surgical procedure codes and death information (including causes of death). In addition, for each resident, the system keeps a complete list of all paper records, electronic records and scanned documents that are available in full text for in-depth review and abstraction. The REP serves as the research infrastructure for studies of virtually all diseases that come to medical attention, and has supported over 2000 peer-reviewed publications since 1966. The system covers residents of all ages and both sexes, regardless of socio-economic status, ethnicity or insurance status. For further information regarding the use of the REP for a specific study, please visit our website at www.rochesterproject.org or contact us at info@rochesterproject.org. Our website also provides access to an introductory video in English and Spanish.

Generalizability of epidemiological findings and public health decisions: an illustration from the Rochester Epidemiology Project.

OBJECTIVE: To illustrate the problem of generalizability of epidemiological findings derived from a single population using data from the Rochester Epidemiology Project and from the US Census. METHODS: We compared the characteristics of the Olmsted County, Minnesota, population with the characteristics of populations residing in the state of Minnesota, the Upper Midwest, and the entire United States. RESULTS: Age, sex, and ethnic characteristics of Olmsted County were similar to those of the state of Minnesota and the Upper Midwest from 1970 to 2000. However, Olmsted County was less ethnically diverse than the entire US population (90.3% vs 75.1% white), more highly educated (91.1% vs 80.4% high school graduates), and wealthier ($51,316 vs $41,994 median household income; 2000 US Census data). Age- and sex-specific mortality rates were similar for Olmsted County, the state of Minnesota, and the entire United States. CONCLUSION: We provide an example of analyses and comparisons that may guide the generalization of epidemiological findings from a single population to other populations or to the entire United States.