Enhancing an existing clinical information system to improve study recruitment and census gathering efficiency

Area of Science:

• Health Informatics
• Clinical Trial Management
• Healthcare Administration

Background:

• Information technology offers potential for enhancing healthcare operational efficiency.
• Manual methods for identifying patients for clinical trials and billing are time-consuming and costly.

Purpose of the Study:

• To develop and implement an inexpensive tool, the Automated Case Finding and Alerting System (ACAS).
• To assess ACAS's efficiency and cost-effectiveness in identifying patients for clinical trials and billing compared to manual methods.

Main Methods:

• Developed and implemented the Automated Case Finding and Alerting System (ACAS) using existing clinical information system data.
• Validated ACAS by comparing its patient identification results with manual identification methods using kappa statistics.

Main Results:

• Substantial agreement was found between ACAS and manual identification for clinical trials (kappa:0.84) and billing (kappa:0.97).
• Automated identification was instantaneous, contrasting with manual methods requiring hours daily.
• ACAS demonstrated significant cost savings compared to manual identification ($98.95 one-time fee vs. $1,870/month).

Conclusions:

• The Automated Case Finding and Alerting System (ACAS) is an efficient and cost-effective solution for patient identification in healthcare.
• Repurposing clinical information systems can enhance operational efficiency and reduce healthcare costs.