Regenstrief Institute

About: Regenstrief Institute is a nonprofit organization based out in Indianapolis, Indiana, United States. It is known for research contribution in the topics: Health care & Population. The organization has 742 authors who have published 2042 publications receiving 96966 citations.

Which observations from the complete blood cell count predict mortality for hospitalized patients

Abstract: Background Information on the prognostic utility of the admission complete blood count (CBC) and differential count is lacking.

Predicting Dementia With Routine Care EMR Data

Abstract: Our aim is to develop a machine learning (ML) model that can predict dementia in a general patient population from multiple health care institutions one year and three years prior to the onset of the disease without any additional monitoring or screening. The purpose of the model is to automate the cost-effective, non-invasive, digital pre-screening of patients at risk for dementia. Towards this purpose, routine care data, which is widely available through Electronic Medical Record (EMR) systems is used as a data source. These data embody a rich knowledge and make related medical applications easy to deploy at scale in a cost-effective manner. Specifically, the model is trained by using structured and unstructured data from three EMR data sets: diagnosis, prescriptions, and medical notes. Each of these three data sets is used to construct an individual model along with a combined model which is derived by using all three data sets. Human-interpretable data processing and ML techniques are selected in order to facilitate adoption of the proposed model by health care providers from multiple institutions. The results show that the combined model is generalizable across multiple institutions and is able to predict dementia within one year of its onset with an accuracy of nearly 80% despite the fact that it was trained using routine care data. Moreover, the analysis of the models identified important predictors for dementia. Some of these predictors (e.g., age and hypertensive disorders) are already confirmed by the literature while others, especially the ones derived from the unstructured medical notes, require further clinical analysis.

Utilizing an integrated infrastructure for outcomes research: a systematic review.

Abstract: Objective To explore the ability of an integrated health information infrastructure to support outcomes research. Methods A systematic review of articles published from 1983 to 2012 by Regenstrief Institute investigators using data from an integrated electronic health record infrastructure involving multiple provider organisations was performed. Articles were independently assessed and classified by study design, disease and other metadata including bibliometrics. Results A total of 190 articles were identified. Diseases included cognitive, (16) cardiovascular, (16) infectious, (15) chronic illness (14) and cancer (12). Publications grew steadily (26 in the first decade vs. 100 in the last) as did the number of investigators (from 15 in 1983 to 62 in 2012). The proportion of articles involving non-Regenstrief authors also expanded from 54% in the first decade to 72% in the last decade. During this period, the infrastructure grew from a single health system into a health information exchange network covering more than 6 million patients. Analysis of journal and article metrics reveals high impact for clinical trials and comparative effectiveness research studies that utilised data available in the integrated infrastructure. Discussion Integrated information infrastructures support growth in high quality observational studies and diverse collaboration consistent with the goals for the learning health system. More recent publications demonstrate growing external collaborations facilitated by greater access to the infrastructure and improved opportunities to study broader disease and health outcomes. Conclusions Integrated information infrastructures can stimulate learning from electronic data captured during routine clinical care but require time and collaboration to reach full potential.

The Indiana Public Health Emergency Surveillance System: ongoing progress, early findings, and future directions.

Abstract: Beginning in 2004, the Indiana State Department of Health (ISDH) partnered with the Regenstrief Institute on a 4-year project to implement a statewide biosurveillance system incorporating more than 110 hospitals. This paper describes our evolving experience with the system including ongoing implementation challenges, how the system has helped to uncover events of public health significance, and future directions. The system currently receives emergency department visit data from 50 hospitals totaling nearly 5,000 visits per day, and is projected to have 65 hospitals connected by August 2006. Introduction Biosurveillance systems focus on the use of early disease indicators to identify outbreaks before definitive diagnoses are made. In the face of recent bioterrorism threats such as anthrax and current concerns about pandemic influenza, these systems are viewed as critical to the nation's health care infrastructure.