Computer-generated reminders delivered on paper to healthcare professionals; effects on professional practice and health care outcomes

Abstract

Background Clinical practice does not always reflect best practice and evidence, partly because of unconscious acts of omission, information overload, or inaccessible information. Reminders may help clinicians overcome these problems by prompting them to recall information that they already know or would be expected to know and by providing information or guidance in a more accessible and relevant format, at a particularly appropriate time. This is an update of a previously published review. Objectives To evaluate the effects of reminders automatically generated through a computerized system (computer-generated) and delivered on paper to healthcare professionals on quality of care (outcomes related to healthcare professionals' practice) and patient outcomes (outcomes related to patients' health condition). Search methods We searched CENTRAL, MEDLINE, Embase, six other databases and two trials registers up to 21 September 2016 together with reference checking, citation searching and contact with study authors to identify additional studies. Selection criteria We included individual-or cluster-randomized and non-randomized trials that evaluated the impact of computer-generated reminders delivered on paper to healthcare professionals, alone (single-component intervention) or in addition to one or more co-interventions (multi-component intervention), compared with usual care or the co-intervention(s) without the reminder component. Data collection and analysis Review authors working in pairs independently screened studies for eligibility and abstracted data. For each study, we extracted the primary outcome when it was defined or calculated the median effect size across all reported outcomes. We then calculated the median improvement and interquartile range (IQR) across included studies using the primary outcome or median outcome as representative outcome. We assessed the certainty of the evidence according to the GRADE approach.

A Randomized Controlled Trial to Improve Colon Cancer Screening in Rural Family Medicine: An Iowa Research Network (IRENE) Study

“…Implementing reminders alone improved care by 11.2% (IQR, 6.5-19.6%); implementing reminders in addition to another intervention led to improved rates of 4% (IQR, 3-6%). 37 Providing an explanation of the content on the reminder seemed to improve the effect (median, 12.0% for explanation vs 4.2% for no explanation). 37 Our reminders provided a concise explanation of the need for CRC screening in asymptomatic individuals.…”

“…35 Two recent Cochrane reviews of physician chart reminders have shown minimal to moderate effects. 36,37 Computer reminders achieved an improvement of 3.8% (interquartile range [IQR], 0.4 -16.3%) for ordering tests. 36 Our chart reminder increased colonoscopy testing by 5.9% over usual care (not significant), which is similar to the median improvement in the review by Shojania et al, 36 but did not improve overall rates of CRC screening.…”

Access to fracture risk assessment by FRAX and linked National Osteoporosis Guideline Group (NOGG) guidance in the UK—an analysis of anonymous website activity

“…The wider use of electronic health care systems and health records may lead to improved adherence to clinical guidance due to automation. Certainly computer-generated reminders appear to improve adherence to protocols [23]. A number of guidelines also provide clinical decision support systems, usually in the form of software programs, to assist with uptake and implementation.…”

Development and Evaluation of a Mobile Decision Support System for Hypertension Management in the Primary Care Setting in Brazil: Mixed-Methods Field Study on Usability, Feasibility, and Utility (Preprint)

“…In this context, mobile health (mHealth) technologies might be used to ease the access of health programs to a large number of individuals at relatively low-cost [10,11]. When integrated to clinical decision support systems (CDSS), what provide recommendations and assists in clinical decision-making at the point of care, mHealth technologies might increase the accuracy in diagnosis and treatment, in an effort to improve quality of care [9].…”