Enabling Health Care Decisionmaking through the Use of Health Information Technology

This project conducted a systematic literature review in order to catalogue the study designs used to evaluate the clinical effectiveness of clinical decision support systems (CDSSs) and knowledge management systems (KMSs). As part of the literature review, the study team also looked at features that influence the success of CDSSs/KMSs, evidence for impact of CDSSs/KMSs on outcomes, and any identified knowledge types that can be integrated into CDSSs/KMSs. The databases searched included MEDLINE®, CINAHL®, PsycINFO®, and Web of Science®. Studies published in English between January 1976 and December 2010 were included.

The main objectives of the project were to:

• Identify what evidence-based study designs can be used to determine the effectiveness of CDSS.
• Identify what contextual factors and features influence the implementation and use of electronic knowledge management and CDSS.
• Identify the impact of introducing electronic knowledge management and CDSS.
• Identify what generalizable knowledge can be integrated into electronic knowledge management and CDSS to improve health care quality.

A total of 15,176 articles were identified, from which 148 randomized control trials (RCTs) were selected for inclusion in the review. The RCTs were 47.5 percent of the comparative studies found on CDSSs/KMSs. The literature showed that commercially available and locally developed CDSSs improved health care process measures related to preventive services, ordering clinical studies, and prescribing therapies. Fourteen CDSS/KMS features were evaluated for correlation with success of CDSSs/KMSs. Six new success features were identified: 1) integration with charting or order-entry system; 2) promotion of action rather than inaction; 3) no need for additional clinician data entry; 4) justification of decision support via research evidence; 5) local user involvement; and 6) provision of decision support results to patients as well as providers.

Three features previously identified as having correlation with success were confirmed: 1) automatic provision of decision support as part of clinician workflow; 2) provision of decision support at time and location of decisionmaking; and 3) provision of a recommendation, not just an assessment. Only 29 RCTs assessed the impact of CDSSs on clinical outcomes, 22 assessed costs, and three assessed KMSs on any outcomes. The primary source of knowledge used in CDSSs was derived from structured care protocols.

The project team concluded that there is strong evidence that CDSSs/KMSs are effective in improving health care process measures across diverse settings using both commercially and locally developed systems. The evidence base for the effectiveness of CDSSs on clinical outcomes and costs - and for KMSs on any outcomes - is minimal.