Data Collection, EHRs, and Poverty Determinations.

Area of Science:

• Health Informatics
• Social Determinants of Health
• Precision Medicine

Background:

• Poverty-related data is vital for understanding social determinants of health (SDOH) in precision medicine.
• Current data collection methods are often imprecise and unsuitable for research purposes.
• A need exists to improve the quality and utility of poverty data for healthcare applications.

Purpose of the Study:

• To propose improved methods for collecting and deploying poverty-related data.
• To enhance the suitability of SDOH data for precision medicine research.
• To explore the application of improved data for individualized care and resource allocation.

Main Methods:

• Cross-referencing existing data sources (e.g., employers, public benefit programs).
• Incentivizing and encouraging patients and healthcare providers to supply more accurate information.
• Developing strategies for the deployment of enhanced poverty data in clinical and research settings.

Main Results:

• Proposed methods can yield more precise and research-ready poverty-related data.
• Enhanced data facilitates individualized clinical and non-clinical care.
• Improved data allows for systematic determination of healthcare's share of social resources.

Conclusions:

• Revising data collection and deployment strategies is essential for leveraging SDOH in precision medicine.
• Higher quality poverty data supports better patient care and informed resource allocation.
• This approach can advance the integration of social determinants into healthcare practices.