Optimizing the data in direct access testing: information technology to support an emerging care model

Area of Science:

• Health Informatics
• Laboratory Medicine
• Digital Health

Background:

• Direct Access Testing (DAT) is an innovative healthcare model offering on-demand laboratory services.
• DAT contrasts with conventional testing by utilizing virtual interactions, online ordering, and often at-home self-collection with virtual support.
• This model heavily relies on robust information technology (IT) and data utilization.

Purpose of the Study:

• To critically review the Direct Access Testing (DAT) landscape in the United States, focusing on IT challenges and opportunities.
• To identify barriers and potential solutions for integrating DAT into conventional patient-provider healthcare models.
• To explore DAT's role in enhancing consumer autonomy, transparency, and health equity.

Main Methods:

• A comprehensive review of the current Direct Access Testing (DAT) landscape in the US.
• Analysis of IT infrastructure, data utilization, and interoperability within the DAT model.
• Discussion of challenges and opportunities for consumers, providers, and health systems.

Main Results:

• DAT empowers consumers with greater control over testing, cost, and data sharing.
• Significant gaps exist in integrating DAT into the conventional patient-provider model, requiring innovative solutions.
• Transparency in DAT laboratory quality and clinical decision support are crucial for appropriate use.

Conclusions:

• Addressing interoperability barriers is essential for integrating DAT data into electronic health records and supporting population health initiatives.
• Despite IT and data challenges, DAT holds significant potential to improve health equity by offering accessible testing options.
• Innovative approaches are needed to fully incorporate Direct Access Testing into routine healthcare delivery.