Measuring Population Health in a Large Integrated Health System to Guide Goal Setting and Resource Allocation: A Proof of Concept.

In integrated health care systems, techniques that identify successes and opportunities for targeted improvement are needed. The authors propose a new method for estimating population health that provides a more accurate and dynamic assessment of performance and priority setting. Member data from a large integrated health system (n = 96,246, 73.8% female, mean age = 44 ± 0.01 years) were used to develop a mechanistic mathematical simulation, representing the top causes of US mortality in 2014 and their associated risk factors. An age- and sex-matched US cohort served as comparator group. The simulation was recalibrated and retested for validity employing the outcome measure of 5-year mortality. The authors sought to estimate potential population health that could be gained by improving health risk factors in the study population. Potential gains were assessed using both average life years (LY) gained and average quality-adjusted life years (QALYs) gained. The simulation validated well compared to integrated health system data, producing an AUC (area under the curve) of 0.88 for 5-year mortality. Current population health was estimated as a life expectancy of 84.7 years or 69.2 QALYs. Comparing potential health gain in the US cohort to the Kaiser Permanente cohort, eliminating physical inactivity, unhealthy diet, smoking, and uncontrolled diabetes resulted in an increase of 1.5 vs. 1.3 LY, 1.1 vs. 0.8 LY, 0.5 vs. 0.2 LY, and 0.5 vs. 0.5 LY on average per person, respectively. Using mathematical simulations may inform efforts by integrated health systems to target resources most effectively, and may facilitate goal setting.

Applying the WHO International Classification of Functioning, Disability and Health in Nursing Assessment of Population Health.

Classification systems constitute an important contribution to nursing practice, as they provide standardized frameworks for communication between nurses and other healthcare professionals. International Classification of Functioning, Disability and Health (ICF) provides a unified and standardized language, as well as a working structure, for the description of health and health-related states. This paper aims to describe some of the available classifications used in nursing practice and to identify the potential value provided by the application of the World Health Organization (WHO) International Classification of Functioning, Disability and Health by all healthcare professionals. With this purpose, a concept analysis was conducted. The relevant nursing classifications were analyzed and related evidence on the use of ICF classification was reviewed to provide a discussion on the application of ICF in nursing practice. The use of ICF could be beneficial in different areas of nursing practice, as it provides a more comprehensive framework to classify nursing outcomes and interventions, improving areas such as interprofessional communication and optimization of care. Although there is published evidence on the use of ICF core sets, further research is needed on this area.

How U.S. children's hospitals define population health: a qualitative, interview-based study.

BACKGROUND: The literature suggests that although adult hospitals are establishing population health programs around the country, there is considerable definitional ambiguity regarding whether interventions are aimed at the social determinants of health or the management of existing patient populations. U.S. children's hospitals also undertake population health programs, but less is known about how they define population health. The purpose of this study is to understand how U.S. children's hospitals define population health, and how institutions are adjusting to new preventive health care models. METHODS: We conducted semi-structured interviews with key stakeholders at ten hospitals with the highest amount of staff time dedicated to population health activities as reported in the 2016 Children's Hospital Association's population health survey. Using a semi-structured interview guide, we interviewed representatives from each hospital. Verbatim interview notes were coded and analyzed using the data analysis software Dedoose. Data analysis followed a modified constructivist grounded theory approach. RESULTS: Our results suggest that even population health innovators employ a variety of approaches that span both population health management and public health. We present further evidence that U.S. children's hospitals are actively debating the definition and focus of population health. CONCLUSIONS: Definitional debates are ongoing even within children's hospitals that are dedicating significant resources to population health. Increased clarity on the conceptual boundaries between population health and population health management could help preserve the theoretical differences between the two concepts, especially insofar as they mark two quite different long-term visions for health care. Without agreement about the meaning of population health within and among institutions, hospitals will not be able to know whether projects aimed at addressing the social determinants of health are likely to improve the health of populations.

Measuring Subcounty Differences in Population Health Using Hospital and Census-Derived Data Sets: The Missouri ZIP Health Rankings Project.

CONTEXT: Measures of population health at the subcounty level are needed to identify areas for focused interventions and to support local health improvement activities. OBJECTIVE: To extend the County Health Rankings population health measurement model to the ZIP code level using widely available hospital and census-derived data sources. DESIGN: Retrospective administrative data study. SETTING: Missouri. POPULATION: Missouri FY 2012-2014 hospital inpatient, outpatient, and emergency department discharge encounters (N = 36 176 377) and 2015 Nielsen data. MAIN OUTCOME MEASURES: ZIP code-level health factors and health outcomes indices. RESULTS: Statistically significant measures of association were observed between the ZIP code-level population health indices and published County Health Rankings indices. Variation within counties was observed in both urban and rural areas. Substantial variation of the derived measures was observed at the ZIP code level with 20 (17.4%) Missouri counties having ZIP codes in both the top and bottom quintiles of health factors and health outcomes. Thirty of the 46 (65.2%) counties in the top 2 county quintiles had ZIP codes in the bottom 2 quintiles. CONCLUSIONS: This proof-of-concept analysis suggests that readily available hospital and census-derived data can be used to create measures of population health at the subcounty level. These widely available data sources could be used to identify areas of potential need within counties, engage community stakeholders, and target interventions.