A practical tool for community-oriented primary care community diagnosis using a personal computer.

BACKGROUND AND OBJECTIVES: Community-oriented primary care (COPC) is considered an attractive concept by many but has had limited implementation due to a lack of practical methodology. An important step in COPC is assessment of a community's health status, using health indicators as one means of assessment. Currently, there is no easy way to combine these indicators and examine their distribution over a community. This study analyzed a process for doing that by using a personal computer. METHODS: For the community studied, all available community-based health indicators were identified. A process for combining these indicators, using commonly available database and spreadsheet software, was developed and analyzed for cost, clinical utility, and problems encountered. RESULTS: Problems were encountered with collecting and combining some data, but a clinically useful tool was produced. Costs, including purchase of all software (with mapping software), were $1,500-$2,000. CONCLUSIONS: With efforts to reduce the initial costs, this is a practical and clinically useful tool for viewing the geographic distribution of community health indicators. Such practical methodology is essential for COPC development.

Tools for community-oriented primary care: a process for linking practice and community data.

BACKGROUND: Community-oriented primary care (COPC) is an increasingly attractive paradigm for primary care delivery. Further work is needed, however, to implement COPC in busy practice settings. This study reports a feasible method for linking practice and community health data for use in COPC. METHODS: Using one practice and its community as an example of the process, we sought data related to five common cancers. Data from readily accessible community sources were combined with practice morbidity data using commonly available computer hardware and software. RESULTS: We developed a user-friendly database and maps showing rates and distribution of the example diseases. We also developed strategies to obtain complete case identification and to address confidentiality and proprietary concerns. CONCLUSIONS: Understanding patterns of disease expression in the practice and the community is critical to the COPC process. Rapid, inexpensive methods for displaying these patterns, such as the database and maps described, must be accessible to clinicians if COPC is to move from theory into practice. Partnerships between health care providers and institutions can also help get this capability into the hands of clinicians.