Effect of point-of-care computer reminders on physician behaviour: a systematic review

Abstract

Background: The opportunity to improve care using computer reminders is one of the main incentives for implementing sophisticated clinical information systems. We conducted a systematic review to quantify the expected magnitude of improvements in processes of care from computer reminders delivered to clinicians during their routine activities.

Methods: We searched the MEDLINE, Embase and CINAHL databases (to July 2008) and scanned the bibliographies of retrieved articles. We included studies in our review if they used a randomized or quasi-randomized design to evaluate improvements in processes or outcomes of care from computer reminders delivered to physicians during routine electronic ordering or charting activities.

Results: Among the 28 trials (reporting 32 comparisons) included in our study, we found that computer reminders improved adherence to processes of care by a median of 4.2% (interquartile range [IQR] 0.8%-18.8%). Using the best outcome from each study, we found that the median improvement was 5.6% (IQR 2.0%-19.2%). A minority of studies reported larger effects; however, no study characteristic or reminder feature significantly predicted the magnitude of effect except in one institution, where a well-developed, "homegrown" clinical information system achieved larger improvements than in all other studies (median 16.8% [IQR 8.7%-26.0%] v. 3.0% [IQR 0.5%-11.5%]; p = 0.04). A trend toward larger improvements was seen for reminders that required users to enter a response (median 12.9% [IQR 2.7%-22.8%] v. 2.7% [IQR 0.6%-5.6%]; p = 0.09).

Interpretation: Computer reminders produced much smaller improvements than those generally expected from the implementation of computerized order entry and electronic medical record systems. Further research is required to identify features of reminder systems consistently associated with clinically worthwhile improvements.

Figure 1

Results of literature search. *Excluded topics included expert systems (e.g., artificial intelligence or neural network applications) for facilitating diagnosis or for estimating prognosis; decision support not directly related to patient care (e.g., coding medical records); and reminders directed primarily at nonphysicians.

Figure 2

Median absolute improvements in adherence to processes of care between intervention and control groups in each study. Each study is represented by the median and interquartile range for its reported outcomes; studies with single data points reported only one eligible outcome.

Figure 3

Median effects for adherence to processes of care by study feature. *Kruskall–Wallis test; all other p values reflect Mann–Whitney test. †Quasi-RCT refers to randomized controlled trials in which intervention status was assigned on the basis of an arbitrary but not truly random process, such as even or odd patient (or provider) identification numbers. ‡The total number of comparisons for the analysis of sample size is 31 because one study did not report the number of patients. §Studies classified as having no cointervention were those in which a computer reminder alone was compared with usual care; studies classified as having co-interventions were those in which the intervention group received a computer reminder plus one or more other quality improvement interventions, while the control group received those same quality improvement interventions but no computer reminder.

Figure 4

Median effects for adherence to processes of care by reminder feature. *Underuse = targeting improvements to increase the percentage of patients who receive targeted process of care (e.g., increasing the percentage of patients receiving the influenza vaccine); overuse = targeting improvements to reduce the percentage of patients receiving inappropriate care (e.g., reducing the percentage of patients who receive antibiotics for viral upper respiratory tract infections). †Reminders with no patient-specific information were those triggered on the basis of demographic characteristics (e.g., age) or the intent to order a medication or investigation irrespective of any features of the patient involved or patient-specific laboratory results. The sample size is reduced because of the inability to accurately assess the presence or absence of the feature. ‡Active delivery refers to reminders that appeared automatically when triggering conditions were met, as opposed to passive reminders, where, for instance, users might be presented with the option to click on a link to receive decision support related to their current task. §CPOE = computerized order entry system; reminder systems without CPOE were typically electronic medical record systems.