Case Study: Jimmy, a 59-year-old white male, is brought to a hospital emergency department by EMTs for the third time this month. He is bleeding from his left temple and exhibits signs of intoxication, and his blood alcohol concentration (BAC) is 0.16. Jimmy was found lying on the street in the fabled Lower East Side of Manhattan, and is a known transient. He is infected with hepatitis C virus (HCV), has high blood pressure and high cholesterol, and he is a heavy smoker and drinker. Jimmy is a Gulf war veteran with no known supports and, while he denied depressive symptoms during past admissions, he reported experiencing flashbacks when he hears loud noises leading to feelings of disorientation and anxiety.
In Jimmy's case, several questions may come to mind:
- What is the cost to the system of Jimmy's repeated care?
- What plan can a provider system put in place to reduce this cycle of emergency department use?
- What are the identified clinical risks?
- How likely would it be for Jimmy to suffer a premature death, given that many with co-occurring disorders have a shorter life span by 25 year than the general public?
Medicare & Medicaid Research Review, 2014: Volume 4, Number 1
Population health management (PHM) demands system solutions to the information exchange process not only to reduce cost of care, improve quality, and ensure data exchange in a timely manner-but also to save lives acutely at risk due to poor health management and gaps in care. The national agenda for Healthy People 2020 establishes the goals for change and wellness as a Nation. The Centers for Medicaid and Medicare Innovation Awards continue to explore models to address unique population and regional needs that will move us, as a Nation, closer to population health goals. In the midst of these change drivers for population health goals, data integration is key to the communication of clinical risks, goals and outcomes for both individual and system providers. In order for Jimmy and others like him, who have traditionally been lost to care, to receive treatment that is patient-centered, providers need to report on clinical quality indicators, consider rate negotiation based on value- based payment, and ensure collaboration across multi-site functions. In this environment, the framework for data and information exchange must be utilized as a tool to advance the administrative, process management and, most importantly, the clinical impact of PHM. The Health Information Exchange (HIE) goals are to: avoid readmissions, avoid medication errors, improve diagnoses, and decrease duplicate testing. However, important challenges present both ongoing and urgent concerns: The lack of a seamless integration of data from disparate information systems or silos has been an ongoing concern for individual providers, systems of care, and population health stakeholders struggling with privacy regulations and the mapping of data elements for standard clinical value sets. At the same time, the epidemic ofchronic diseases and the need to implement clinical preventive services to stem the social burden cost on life and financial cost of care present urgent concerns that depend on PHM data.
To address these challenges, data warehouses with the nimble ability to tailor and configure special population health metrics provide solutions that can address avoidable admission goals, deliver gaps-in-care analysis, provide a toolset for collaborative and integrated care, and track identified risk populations at various points of care.
SAE & Associates is pleased to announce our latest push into PHM.