Community Health Assessments: A Data Warehousing Approach.

摘要: The measurement and assessment of health status in communities throughout the world is a massive information technology challenge. Comprehensive Assessment for Tracking Community Health (CATCH) methodology provides systematic framework community-level that can be valuable tool resource allocation care policy formulation. CATCH utilizes indicators from multiple data sources, using an innovative comparative weighted evaluation process to produce rank-ordered list critical community challenges. focus intended empower local decision-makers provide clear organizing interpreting relevant data. effectiveness based on warehousing approach. warehouse allows core set reports produced at reasonable cost use. In addition, online analytic processing (OLAP) functionality used gain deeper understanding issues. conjunction with Internet-enabled dissemination methods will allow presented variety formats distributed more widely decision-making community. On-going research directions decision making conclude paper. I. COMMUNITY HEALTH ORGANIZATIONS It well documented considerable variation exists defined populations. This evident when we compare large population groups, such as separate nations, states, or regions within single country. Surprisingly, often persists smaller census tracts zip codes inside United States counties. These variations exist not only what would considered epidemiological outcomes (i.e., morbidity mortality rates), but also which could other dimensions domains socioeconomic demographic characteristics, availability resources, patterns behaviors, many factors. order improve populations, continuous monitoring improvement system must implemented. Such require comprehensive, objective, uniform defining characterizing comprise U.S., Institute Medicine (IOM) National Academy Sciences, its influential 1988 report Future Public Health, emphasized was one functions public recommended there should regular collection, assemblage, analysis needs [7]. 1997, IOM Committee Using Performance Monitoring Improve outlined through assess priorities, formulate strategy, use performance part continuing accountable [9]. called profile made up socio-demographic indicators, quality life risk factors, measures support priority setting, decisions, program impacts. As on-going clarification role level transition disease treatment prevention has been recognition partnerships collaboration are necessary effective action [8, 12]. organizations, sector agencies, medical providers, businesses, religious community, educational institutions, organizations interdependent components multi-sectoral organization. overall empowered make necessary, sometimes difficult, choices information, education, behavior change, social [3]. collaborative informed by unbiased describing community’s status, needs, resources. ability needed track progress over time meet goals. gap between current practice spending above goals vast. problematic. There little empirical evidence use, sharing, strategies integrate into guidance organizations. While most literature leadership engagement [1, 2], attention focussed effect common data, profile, inclusiveness decision-making. scant about monitor process. purpose this paper present outline implementation warehouse. various modes explored examples interfaces demonstrated. We examining important issues care. II. THE METHODOLOGY University South Florida’s Center Outcomes Research developed objective planning purposes. collects, organizes, analyzes, prioritizes, 225 basis. tested, refined, validated past nine years. Reports have prepared 15 U.S. counties both outside Florida. briefly described shown Fig. 1. indicator gathered sources. Secondary sources include reported hospitals, local, state, federal national groups. Primary involve door-to-door mail-in surveys. All normalized organized card listing values each indicator. Each value then compared against state average, peer group interesting (e.g., goal indicator). results these comparisons n-dimensional matrix favorable unfavorable comparison dimension. 1 shows 2-dimensional averages averages. demonstrate all highlighted Methodology C o m u nity H ealth d icators Ind icato r