Background: Computerised clinical decision support systems (CDSSs) are used widely to improve quality of care and patient outcomes. This systematic review evaluated the impact of CDSSs in targeting specific aspects of prescribing, namely initiating, monitoring and stopping therapy. We also examined the influence of clinical setting (institutional vs ambulatory care), system-or user-initiation of CDSS, multi-faceted vs stand alone CDSS interventions and clinical target on practice changes in line with the intent of the CDSS.

What is already known about this subject • Computerized prompts and reminders have been shown to be effective in changing the behaviour of health professionals in a variety of settings. • There is little literature describing or evaluating electronic decision‐support for pharmacists. What this study adds • An electronic prompt in dispensing software for a targeted clinical intervention has a significant effect on pharmacists' behaviour. A markedly increased rate of recording and performing the targeted clinical intervention was found. • The effect of the prompt reduces markedly once the prompt is deactivated. Aim To evaluate the effect of an electronic prompt in dispensing software on the frequency of clinical interventions recorded by community pharmacists. Method An electronic decision‐support prompt identifying patients for a targeted proactive clinical intervention was developed and implemented. Each time an oral antidiabetic agent was dispensed, a prompt was displayed reminding pharmacists to discuss the suitability of aspirin therapy in eligible patients with diabetes. The prompt was randomly assigned to 31 of 52 metropolitan pharmacies in Melbourne (Australia) for 6 weeks, with the remaining pharmacies as controls. Results One hundred and fifty pharmacists in 52 pharmacies recorded a total of 2396 clinical interventions at an intervention rate of 0.92 interventions per 100 patients [95% confidence interval (CI) 0.58, 1.23]. Pharmacists recorded a total of 201 target interventions related to aspirin therapy in diabetes at an intervention rate of 2.55 interventions per 100 diabetic patients (95% CI 0.85, 4.24). All of the targeted clinical interventions were recorded in the prompt arm; no targeted interventions were recorded in the control group. The effect of the prompt decreased over the study period and was not maintained after prompt deactivation. Conclusion An electronic prompt significantly increased pharmacists' recording of the targeted clinical intervention in diabetic patients. An electronic decision‐support prompt has significant potential to promote community pharmacists' contribution to the quality use of medicines.

Objective: To investigate the quality of drug interaction decision support in selected prescribing and dispensing software systems, and to compare this information with that found in a range of reference sources. Design and setting: A comparative study, conducted between June 2006 and February 2007, of the support provided for making decisions about 20 major and 20 minor drug interactions in six prescribing and three dispensing software systems used in primary care in Australia. Five electronic reference sources were evaluated for comparison. Main outcome measures: Sensitivity, specificity and quality of information; for major interactions: whether information on clinical effects, timeframe and pharmacological mechanism was included, whether management advice was helpful, and succinctness. Results: Six of the nine software systems had a sensitivity rate ≥ 90%, detecting most of the major interactions. Only 3/9 systems had a specificity rate of ≥ 80%, with other systems providing inappropriate or unhelpful alerts for many minor interactions. Only 2/9 systems provided adequate information about clinical effects for more than half the major drug interactions, and 1/9 provided useful management advice for more than half of these. The reference sources had high sensitivity and in general provided more comprehensive clinical information than the software systems. Conclusions: Drug interaction decision support in commonly used prescribing and dispensing software has significant shortcomings.

BackgroundElectronic prescribing is increasingly being used in primary care and in hospitals. Studies on the effects of e-prescribing systems have found evidence for both benefit and harm. The aim of this study was to identify features of e-prescribing software systems that support patient safety and quality of care and that are useful to the clinician and the patient, with a focus on improving the quality use of medicines.MethodsSoftware features were identified by a literature review, key informants and an expert group. A modified Delphi process was used with a 12-member multidisciplinary expert group to reach consensus on the expected impact of the features in four domains: patient safety, quality of care, usefulness to the clinician and usefulness to the patient. The setting was electronic prescribing in general practice in Australia.ResultsA list of 114 software features was developed. Most of the features relate to the recording and use of patient data, the medication selection process, prescribing decision support, monitoring drug therapy and clinical reports. The expert group rated 78 of the features (68%) as likely to have a high positive impact in at least one domain, 36 features (32%) as medium impact, and none as low or negative impact. Twenty seven features were rated as high positive impact across 3 or 4 domains including patient safety and quality of care. Ten features were considered "aspirational" because of a lack of agreed standards and/or suitable knowledge bases.ConclusionsThis study defines features of e-prescribing software systems that are expected to support safety and quality, especially in relation to prescribing and use of medicines in general practice. The features could be used to develop software standards, and could be adapted if necessary for use in other settings and countries.

BackgroundMany patients with back pain do not receive health care in accordance with best practice recommendations. Implementation trials to address this issue have had limited success. Despite the known effectiveness of clinical decision support systems (CDSS), none of these are available for back pain management.ObjectiveThe objective of our study was to develop a Web-based CDSS to support Australian general practitioners (GPs) to diagnose and manage back pain according to guidelines.MethodsAsking a panel of international experts to review recommendations for sixteen clinical vignettes validated the tool. It was then launched nationally as part of National Pain Week and promoted to GPs via a media release and clinic based visits. Following this, a mixed methods evaluation was conducted to determine tool feasibility, acceptability, and utility. The 12 month usage data were analyzed, and in-depth, semistructured interviews with 20 GPs were conducted to identify barriers and enablers to uptake.ResultsThe tool had acceptable face validity when reviewed by experts. Over a 12 month period there were 7125 website visits with 4503 (63.20%) unique users. Assuming most unique users are GPs, around one quarter of the country’s GPs may have used the tool at least once. Although usage was high, GP interviews highlighted the sometimes complex nature of management where the tool may not influence care. Conversely, several “touch-points”, whereby the tool may exert its influence, were identified, most notably patient engagement.ConclusionsA novel CDSS tool has the potential to assist with evidence-based management of back pain. A clinical trial is required to determine its impact on practitioner and patient outcomes.