HBI Solutions has extensively published a series of papers in peer reviewed journals on its technology and methods. Below is a list of the publications and the associated journals with the most recent listed first. More publications will follow in the future. For PDF versions of the papers, please email email@example.com.
July 7, 2017
Summary: Analysis of a patient’s pre-disease clinical history can provide early warning of an impending Type 2 Diabetes diagnosis. This allows providers to take proactive steps to prevent or delay onset of the disease. In this study, HBI used longitudinal EHR data from the Maine State Health Information Exchange to identify a dynamic driver network (DDN) and associated critical transition state six months prior to diagnosis.
Web-based Real-Time Case Finding for the Population Health Management of Patients With Diabetes Mellitus: A Prospective Validation of the Natural Language Processing–Based Algorithm With Statewide Electronic Medical Records
November 11, 2016
Summary: Diabetes case finding based on structured medical records does not fully identify diabetic patients whose medical histories related to diabetes are available in the form of free text. Manual chart reviews have been used but involve high labor costs and long latency.
Prospective stratification of patients at risk for emergency department revisit: resource utilization and population management strategy implications
February 3, 2016
Summary: Estimating patient risk of future emergency department (ED) revisits can guide the allocation of resources, e.g. local primary care and/or specialty, to better manage ED high utilization patient populations and thereby improve patient life qualities.
November 12, 2015
Summary: Stroke is the second most frequent cause of death in the world. Assessing patient risk of stroke can help deliver the right interventions at the right time to improve patient health outcomes. In this paper, we proposed and validated a risk model predictive of stroke in the future 1 year period across all ages, all payors, and all disease groups in Maine.
November 12, 2015
Summary: Understanding the future healthcare service utilization cost of patients allows for better resource allocation. The aim of this study is to develop a risk stratification model for the future six month healthcare resource utilization for patients of the state of Maine. Additionally, potential economic impacts of the model on healthcare resource utilization were explored. Future applications of our model will enable efficient resource allocations and targeted care interventions.
Development, Validation and Deployment of a Real Time 30 Day Hospital Readmission Risk Assessment Tool in Maine Health Information Exchange
October 8, 2015 – PLOS One
Abstract: Identifying patients at risk of a 30-day readmission can help providers design interventions, and provide targeted care to improve clinical effectiveness. This study developed a risk model to predict a 30-day inpatient hospital readmission for patients in Maine, across all payers, all diseases and all demographic groups.
Online Prediction of Health Care Utilization in the Next Six Months Based on Electronic Health Record Information: A Cohort and Validation Study
September 22, 2015 – Journal of Medical Internet Research
Abstract: The increasing rate of health care expenditures in the United States has placed a significant burden on the nation’s economy. Predicting future health care utilization of patients can provide useful information to better understand and manage overall health care deliveries and clinical resource allocation.
NLP based congestive heart failure case finding: A prospective analysis on statewide electronic medical records
July 2, 2015 – International Journal of Medical Informatics
Abstract: In order to proactively manage congestive heart failure (CHF) patients, an effective CHF case finding algorithm is required to process both structured and unstructured electronic medical records (EMR) to allow complementary and cost-efficient identification of CHF patients.
Real-Time Web-Based Assessment of Total Population Risk of Future Emergency Department Utilization: Statewide Prospective Active Case Finding Study
January 13, 2015 – Journal of Medical Internet Research
Abstract: An easily accessible real-time Web-based utility to assess patient risks of future emergency department (ED) visits can help the health care provider guide the allocation of resources to better manage higher-risk patient populations and thereby reduce unnecessary use of EDs.
November 13, 2014 – PLOS One
Abstract: Among patients who are discharged from the Emergency Department (ED), about 3% return within 30 days. Revisits can be related to the nature of the disease, medical errors, and/or inadequate diagnoses and treatment during their initial ED visit. Identification of high-risk patient population can help device new strategies for improved ED care with reduced ED utilization.