Capturing incarceration in the medical record: we cannot manage what we cannot measure

Area of Science:

• Public Health
• Health Informatics
• Health Services Research

Background:

• Nearly 2 million individuals are incarcerated in the US, facing higher rates of chronic disease, mental illness, and infectious diseases.
• The healthcare needs of incarcerated populations are often unmet due to poor documentation of incarceration status in community medical settings.
• Current methods for identifying incarcerated patients, such as ICD codes, are inconsistent, lack specificity, and offer minimal reimbursement incentives.

Purpose of the Study:

• To review current gaps in documenting incarceration status within community medical centers.
• To propose policy and infrastructure reforms to enhance the measurement and accountability of care for incarcerated individuals.
• To advocate for improved data collection and utilization for research and health equity initiatives.

Main Methods:

• Review of existing literature and identification strategies for documenting incarceration in healthcare settings.
• Analysis of the limitations of current data collection methods, including ICD codes and electronic health record workarounds.
• Proposal of policy and infrastructure reforms for improved documentation and data integration.

Main Results:

• Incarceration status is rarely captured in clinical or administrative data, making this population invisible to quality improvement and research.
• Existing identification strategies are inconsistently applied, lack specificity, and are not adequately incentivized.
• Incomplete and nonstandardized data hinder efforts to address the health disparities faced by incarcerated individuals.

Conclusions:

• Reforming healthcare data systems to include incarceration status is essential for improving care quality and health equity.
• Policy changes, such as reimbursable comorbid conditions for incarceration codes, can incentivize accurate documentation.
• Standardized guidance, ethical safeguards, and integration into national datasets are necessary to ensure comprehensive and ethical data collection.