scholarly journals The Population Health OutcomEs aNd Information Exchange (PHOENIX) Program - A Transformative Approach to Reduce the Burden of Chronic Disease

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Steven J. Korzeniewski ◽  
Carla Bezold ◽  
Jason T. Carbone ◽  
Shooshan Danagoulian ◽  
Bethany Foster ◽  
...  
Keyword(s):  
Chronic Disease ◽  
Health Outcomes ◽  
Population Health ◽  
Information Exchange ◽  
Health Information Exchange ◽  
Historical Context ◽  
State Level ◽  
Public Health Services ◽  
Multimodal Data ◽  
Transformative Approach

This concept article introduces a transformative vision to reduce the population burden of chronic disease by focusing on data integration, analytics, implementation and community engagement. Known as PHOENIX (The Population Health OutcomEs aNd Information EXchange), the approach leverages a state level health information exchange and multiple other resources to facilitate the integration of clinical and social determinants of health data with a goal of achieving true population health monitoring and management. After reviewing historical context, we describe how multilevel and multimodal data can be used to facilitate core public health services, before discussing the controversies and challenges that lie ahead.

scholarly journals A State-wide Health IT Infrastructure for Population Health: Building a Community-wide Electronic Platform for Maryland’s All-Payer Global Budget

2017 ◽  
Vol 9 (3) ◽  
Author(s):  
Elham Hatef ◽  
Hadi Kharrazi ◽  
Ed VanBaak ◽  
Marc Falcone ◽  
Lindsey Ferris ◽  
...  
Keyword(s):  
Data Collection ◽  
Real Time ◽  
Population Health ◽  
Information Exchange ◽  
Health Information Exchange ◽  
Smoking Status ◽  
Digital Data ◽  
Health It ◽  
Global Budget ◽  
Health Initiatives

Maryland Department of Health (MDH) has been preparing for alignment of its population health initiatives with Maryland’s unique All-Payer hospital global budget program. In order to operationalize population health initiatives, it is required to identify a starter set of measures addressing community level health interventions and to collect interoperable data for those measures. The broad adoption of electronic health records (EHRs) with ongoing data collection on almost all patients in the state, combined with hospital participation in health information exchange (HIE) initiatives, provides an unprecedented opportunity for near real-time assessment of the health of the communities. MDH’s EHR-based monitoring complements, and perhaps replaces, ad-hoc assessments based on limited surveys, billing, and other administrative data. This article explores the potential expansion of health IT capacity as a method to improve population health across Maryland.First, we propose a progression plan for four selected community-wide population health measures: body mass index, blood pressure, smoking status, and falls-related injuries. We then present an assessment of the current and near real-time availability of digital data in Maryland including the geographic granularity on which each measure can be assessed statewide. Finally, we provide general recommendations to improve interoperable data collection for selected measures over time via the Maryland HIE. This paper is intended to serve as a high- level guiding framework for communities across the US that are undergoing healthcare transformation toward integrated models of care using universal interoperable EHRs.

scholarly journals A “Swiss paradox” in the United States? Level of spatial aggregation changes the association between income inequality and morbidity for older Americans

2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Steven A. Cohen ◽  
Mary L. Greaney ◽  
Ann C. Klassen
Keyword(s):  
Older Adults ◽  
Income Inequality ◽  
Health Outcomes ◽  
Population Health ◽  
Smoking Status ◽  
State Level ◽  
The United States ◽  
Spatial Aggregation ◽  
County Level ◽  
Aggregation Level

AbstractAlthough a preponderance of research indicates that increased income inequality negatively impacts population health, several international studies found that a greater income inequality was associated with better population health when measured on a fine geographic level of aggregation. This finding is known as a “Swiss paradox”. To date, no studies have examined variability in the associations between income inequality and health outcomes by spatial aggregation level in the US. Therefore, this study examined associations between income inequality (Gini index, GI) and population health by geographic level using a large, nationally representative dataset of older adults. We geographically linked respondents’ county data from the 2012 Behavioral Risk Factor Surveillance System to 2012 American Community Survey data. Using generalized linear models, we estimated the association between GI decile on the state and county levels and five population health outcomes (diabetes, obesity, smoking, sedentary lifestyle and self-rated health), accounting for confounders and complex sampling. Although state-level GI was not significantly associated with obesity rates (b = − 0.245, 95% CI − 0.497, 0.008), there was a significant, negative association between county-level GI and obesity rates (b = − 0.416, 95% CI − 0.629, − 0.202). State-level GI also associated with an increased diabetes rate (b = 0.304, 95% CI 0.063, 0.546), but the association was not significant for county-level GI and diabetes rate (b = − 0.101, 95% CI − 0.305, 0.104). Associations between both county-level GI and state-level GI and current smoking status were also not significant. These findings show the associations between income inequality and health vary by spatial aggregation level and challenge the preponderance of evidence suggesting that income inequality is consistently associated with worse health. Further research is needed to understand the nuances behind these observed associations to design informed policies and programs designed to reduce socioeconomic health inequities among older adults.

How community health information exchanges can evolve to support population health and healthcare: The case study of the Indiana Network for Patient Care (Preprint)

2020 ◽  
Author(s):  
Karmen Williams ◽  
Saurabh Rahurkar ◽  
Brian Dixon ◽  
Shaun Grannis ◽  
Titus Schleyer
Keyword(s):  
Patient Care ◽  
Community Health ◽  
Health Information ◽  
Population Health ◽  
Information Exchange ◽  
Health Information Exchange ◽  
The United States ◽  
Clinical Applications ◽  
Data Sets ◽  
The Status

BACKGROUND Community Health Information Exchange (HIEs) organizations were originally designed to support individual patient care, but their ability to aggregate health and non-health information about populations offers significant opportunities. OBJECTIVE The aim of this paper is to discuss and illustrate current opportunities for HIEs using the status and trajectory of the Indiana Network for Patient Care (INPC), the oldest and one of the largest HIEs in the United States. METHODS We reviewed the research and clinical applications the INPC has developed and introduced numerous innovations and initiatives. RESULTS HIEs have the positioning and opportunity to provide highly relevant services in today’s healthcare, and public and population health contexts, such as research-ready data sets, state registry collaborations, data commons, population health applications, clinical applications, nationwide interoperability, and support of accountable care organizations. CONCLUSIONS Community HIEs can help advance the practice of medicine and population health and help shift sick-focused to health-focused care. To fully take advantage of their potential, community HIEs must continue to innovate and evolve.

Opioid Prescribing and Health Outcomes in Opioid Naive Patients: Analysis of A Statewide Health Information Exchange

2021 ◽  
Author(s):  
Sariya Udayachalerm ◽  
Matthew J. Bair ◽  
Kimberly S. Illingworth Plake ◽  
Chien-Yu Huang ◽  
Michael D. Murray ◽  
...  
Keyword(s):  
Health Outcomes ◽  
Health Information ◽  
Information Exchange ◽  
Health Information Exchange ◽  
Opioid Prescribing

scholarly journals Linkage of Chronic Disease Data from Provincial Sources for Strategic Decision Support and Population Health Surveillance in British Columbia (BC)

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Drona Rasali ◽  
Ognjenka Djurdjev ◽  
Crystal Li ◽  
Edward Ord ◽  
Carol Laberge ◽  
...  
Keyword(s):  
Decision Support ◽  
Chronic Disease ◽  
Health Outcomes ◽  
Population Health ◽  
Data Linkage ◽  
Healthcare Delivery ◽  
Health Surveillance ◽  
Strategic Decision ◽  
Data Sources ◽  
Disease Information

IntroductionBC Ministry of Health (MoH)’s health administrative data holdings for a variety of general health care data are not readily linked with various data registries maintained by specialized care agencies of the Provincial Health Services Authority (PHSA). These provincial data sources have rich chronic disease information for BC residents. Objectives and ApproachThe objective of this project is to develop a system for cross-agency linkage of provincial level chronic disease data to improve chronic disease information that would support the BC’s health system, MoH and PHSA agencies in particular, in healthcare delivery and chronic disease prevention planning. We aim to achieve linkage of data from various provincial chronic disease data sources of the MoH and PHSA, with further potential to link with variety of other external databases such as Census data for socio-economic determinants of health. We are reporting here the outcome of the first phase of this project. ResultsThe outcomes from the project to date were as follows: Data linkage between the MoH’s administrative databases, Chronic Disease Registries (CDRs) in particular and Census based socio-economic status (SES) data was achieved, providing the population level evidence of health outcomes such as health inequity, comorbidities and multimorbidities (sub-project # 1). Preliminary results on data quality and health outcomes by SES will be presented. This was followed by completion of securing approval to ensure data security compliance for data linkages of CDRs with the Provincial Renal Agency’s Registry called “PROMIS” (sub-project # 2), Cardiac Services BC’s Registry called “HEARTis” ((sub-project # 3), and BC Cancer Agency’s Registry and BC Generations Project data (sub-project # 4), for implementation to answer agency specific research questions. Conclusion/ImplicationsThis data linkage project to consolidate information from chronic disease and socio-economic databases for providing answers to various analytic questions posed will improve decision support and enhanced population health surveillance. The lessons learned from this multi-agency collaboration and their implications for other jurisdictions will be addressed.

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