JMIR Publications

ABSTRACT

Background:

Clinical decision support systems (CDSSs) are designed to assist in healthcare delivery by supporting medical practice with clinical knowledge, patient information, and other relevant types of health information. CDSSs are integral parts of healthcare technologies assisting in disease management, including diagnosis, treatment, and monitoring. While electronic medical records serve as data repositories, CDSSs are utilized to assist clinicians with matching individual patient data to an evidence database.

Objective:

This targeted literature review (TLR) was conducted to identify benefits of both standalone and electronic medical records (EMR)-integrated CDSSs and associated features reported in the published scientific literature that would impact their outcomes.

Methods:

A TLR was conducted using the Embase, MEDLINE, and Cochrane databases to identify data on CDSSs published in a 10-year frame (2012–2022). Studies reporting outcomes of CDSSs use based on specific selection criteria were eligible.

Results:

Forty-nine publications were included in the TLR. Studies predominantly reported on EMR-integrated CDSSs (i.e., connected to an EMR database; n=32, 65%). The use of CDSSs varied globally, with a substantial utilization in the US and within the domain of cardiorenal diseases. CDSSs were found to positively impact ‘quality assurance’ (n=35, 69%) and improve ‘clinical benefit’ (n=20, 41%), compared to usual care. Among CDSS features, treatment guidance and flagging were consistently reported as the most frequent elements for enhancing healthcare, followed by risk level estimation, diagnosis, education, and data export. Effectiveness of a CDSS was evaluated most frequently in primary-care settings (n=34, 69%) across cardiorenal disease areas (n=32, 65%), especially in diabetes (n=13, 26%). Studies reported CDSSs to be commonly used by a mixed group (n=27, 55%) of primary users including physicians, specialists, nurses/nurse practitioners, and allied healthcare professionals.

Conclusions:

Overall, both EMR-integrated and standalone CDSSs showed positive results, suggesting their potential for successful adoption and benefits to healthcare providers. Flagging and treatment recommendation features were commonly utilized in CDSSs to improve patient care; other features such as risk level estimation, diagnosis, education, and data export were tailored to specific requirements and collectively contributed to the efficiency of healthcare delivery. While this TLR yielded a high success rate of both standalone and EMR-integrated CDSSs in meeting clinical outcomes, further longitudinal studies are required to elucidate aspects that may impact their adoption in real-world scenarios.