Prioritization in community health planning: combining methods to achieve implementable priorities

Area of Science:

• Public Health
• Health Policy
• Community Engagement

Background:

• Community Health Planning (CHP) is a critical tool for states and localities to formulate health policies and programs.
• Effective CHP necessitates the integration of diverse data types for comprehensive strategy development.

Purpose of the Study:

• To argue for the inclusion of both quantitative (positive/hierarchic) and qualitative (interpretive) data in Community Health Planning.
• To examine the State of Tennessee's public health mission revamp as a case study for data integration in CHP.

Main Methods:

• Analysis of data types used in Community Health Planning.
• Case study examination of Tennessee's public health strategy implementation in a single county.
• Contrasting epidemiological statistics with stakeholder participation data.

Main Results:

• "Positive" data, such as epidemiological statistics, are essential for informing stakeholders.
• "Interpretive" data, derived from stakeholder participation, fosters ownership of the planning process.
• Both data types hold legitimate and distinct claims within the CHP framework.

Conclusions:

• States and localities should leverage diverse information sources for improved public health services.
• Integrating epidemiological data with stakeholder input enhances the effectiveness and legitimacy of Community Health Planning.
• Successful CHP implementation relies on a balanced approach to data collection and utilization.