48 research outputs found

    The GUIDES checklist: development of a tool to improve the successful use of guideline-based computerised clinical decision support

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    Background: Computerised decision support (CDS) based on trustworthy clinical guidelines is a key component of a learning healthcare system. Research shows that the effectiveness of CDS is mixed. Multifaceted context, system, recommendation and implementation factors may potentially affect the success of CDS interventions. This paper describes the development of a checklist that is intended to support professionals to implement CDS successfully. Methods: We developed the checklist through an iterative process that involved a systematic review of evidence and frameworks, a synthesis of the success factors identified in the review, feedback from an international expert panel that evaluated the checklist in relation to a list of desirable framework attributes, consultations with patients and healthcare consumers and pilot testing of the checklist. Results: We screened 5347 papers and selected 71 papers with relevant information on success factors for guideline-based CDS. From the selected papers, we developed a 16-factor checklist that is divided in four domains, i.e. the CDS context, content, system and implementation domains. The panel of experts evaluated the checklist positively as an instrument that could support people implementing guideline-based CDS across a wide range of settings globally. Patients and healthcare consumers identified guideline-based CDS as an important quality improvement intervention and perceived the GUIDES checklist as a suitable and useful strategy. Conclusions: The GUIDES checklist can support professionals in considering the factors that affect the success of CDS interventions. It may facilitate a deeper and more accurate understanding of the factors shaping CDS effectiveness. Relying on a structured approach may prevent that important factors are missed

    Features of effective computerised clinical decision support systems : meta-regression of 162 randomised trials.

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    Objectives To identify factors that differentiate between effective and ineffective computerised clinical decision support systems in terms of improvements in the process of care or in patient outcomes. Design Meta-regression analysis of randomised controlled trials. Data sources A database of features and effects of these support systems derived from 162 randomised controlled trials identified in a recent systematic review. Trialists were contacted to confirm the accuracy of data and to help prioritise features for testing. Main outcome measures ?Effective? systems were defined as those systems that improved primary (or 50% of secondary) reported outcomes of process of care or patient health. Simple and multiple logistic regression models were used to test characteristics for association with system effectiveness with several sensitivity analyses. Results Systems that presented advice in electronic charting or order entry system interfaces were less likely to be effective (odds ratio 0.37, 95% confidence interval 0.17 to 0.80). Systems more likely to succeed provided advice for patients in addition to practitioners (2.77, 1.07 to 7.17), required practitioners to supply a reason for over-riding advice (11.23, 1.98 to 63.72), or were evaluated by their developers (4.35, 1.66 to 11.44). These findings were robust across different statistical methods, in internal validation, and after adjustment for other potentially important factors. Conclusions We identified several factors that could partially explain why some systems succeed and others fail. Presenting decision support within electronic charting or order entry systems are associated with failure compared with other ways of delivering advice. Odds of success were greater for systems that required practitioners to provide reasons when over-riding advice than for systems that did not. Odds of success were also better for systems that provided advice concurrently to patients and practitioners. Finally, most systems were evaluated by their own developers and such evaluations were more likely to show benefit than those conducted by a third party

    Can computerized clinical decision support systems improve practitioners' diagnostic test ordering behavior? A decision-maker-researcher partnership systematic review

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    <p>Abstract</p> <p>Background</p> <p>Underuse and overuse of diagnostic tests have important implications for health outcomes and costs. Decision support technology purports to optimize the use of diagnostic tests in clinical practice. The objective of this review was to assess whether computerized clinical decision support systems (CCDSSs) are effective at improving ordering of tests for diagnosis, monitoring of disease, or monitoring of treatment. The outcome of interest was effect on the diagnostic test-ordering behavior of practitioners.</p> <p>Methods</p> <p>We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for eligible articles published up to January 2010. We included randomized controlled trials comparing the use of CCDSSs to usual practice or non-CCDSS controls in clinical care settings. Trials were eligible if at least one component of the CCDSS gave suggestions for ordering or performing a diagnostic procedure. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of test ordering outcomes.</p> <p>Results</p> <p>Thirty-five studies were identified, with significantly higher methodological quality in those published after the year 2000 (<it>p </it>= 0.002). Thirty-three trials reported evaluable data on diagnostic test ordering, and 55% (18/33) of CCDSSs improved testing behavior overall, including 83% (5/6) for diagnosis, 63% (5/8) for treatment monitoring, 35% (6/17) for disease monitoring, and 100% (3/3) for other purposes. Four of the systems explicitly attempted to reduce test ordering rates and all succeeded. Factors of particular interest to decision makers include costs, user satisfaction, and impact on workflow but were rarely investigated or reported.</p> <p>Conclusions</p> <p>Some CCDSSs can modify practitioner test-ordering behavior. To better inform development and implementation efforts, studies should describe in more detail potentially important factors such as system design, user interface, local context, implementation strategy, and evaluate impact on user satisfaction and workflow, costs, and unintended consequences.</p

    Computerized clinical decision support systems for chronic disease management: A decision-maker-researcher partnership systematic review

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    <p>Abstract</p> <p>Background</p> <p>The use of computerized clinical decision support systems (CCDSSs) may improve chronic disease management, which requires recurrent visits to multiple health professionals, ongoing disease and treatment monitoring, and patient behavior modification. The objective of this review was to determine if CCDSSs improve the processes of chronic care (such as diagnosis, treatment, and monitoring of disease) and associated patient outcomes (such as effects on biomarkers and clinical exacerbations).</p> <p>Methods</p> <p>We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for potentially eligible articles published up to January 2010. We included randomized controlled trials that compared the use of CCDSSs to usual practice or non-CCDSS controls. Trials were eligible if at least one component of the CCDSS was designed to support chronic disease management. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of relevant outcomes.</p> <p>Results</p> <p>Of 55 included trials, 87% (n = 48) measured system impact on the process of care and 52% (n = 25) of those demonstrated statistically significant improvements. Sixty-five percent (36/55) of trials measured impact on, typically, non-major (surrogate) patient outcomes, and 31% (n = 11) of those demonstrated benefits. Factors of interest to decision makers, such as cost, user satisfaction, system interface and feature sets, unique design and deployment characteristics, and effects on user workflow were rarely investigated or reported.</p> <p>Conclusions</p> <p>A small majority (just over half) of CCDSSs improved care processes in chronic disease management and some improved patient health. Policy makers, healthcare administrators, and practitioners should be aware that the evidence of CCDSS effectiveness is limited, especially with respect to the small number and size of studies measuring patient outcomes.</p

    Aspirin and clonidine in non-cardiac surgery: acute kidney injury substudy protocol of the Perioperative Ischaemic Evaluation (POISE) 2 randomised controlled trial

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    IntroductionPerioperative Ischaemic Evaluation-2 (POISE-2) is an international 2×2 factorial randomised controlled trial of low-dose aspirin versus placebo and low-dose clonidine versus placebo in patients who undergo non-cardiac surgery. Perioperative aspirin (and possibly clonidine) may reduce the risk of postoperative acute kidney injury (AKI).Methods and analysisAfter receipt of grant funding, serial postoperative serum creatinine measurements began to be recorded in consecutive patients enrolled at substudy participating centres. With respect to the study schedule, the last of over 6500 substudy patients from 82 centres in 21 countries were randomised in December 2013. The authors will use logistic regression to estimate the adjusted OR of AKI following surgery (compared with the preoperative serum creatinine value, a postoperative increase ≥26.5 μmol/L in the 2 days following surgery or an increase of ≥50% in the 7 days following surgery) comparing each intervention to placebo, and will report the adjusted relative risk reduction. Alternate definitions of AKI will also be considered, as will the outcome of AKI in subgroups defined by the presence of preoperative chronic kidney disease and preoperative chronic aspirin use. At the time of randomisation, a subpopulation agreed to a single measurement of serum creatinine between 3 and 12 months after surgery, and the authors will examine intervention effects on this outcome.Ethics and disseminationThe authors were competitively awarded a grant from the Canadian Institutes of Health Research for this POISE-2 AKI substudy. Ethics approval was obtained for additional kidney data collection in consecutive patients enrolled at participating centres, which first began for patients enrolled after January 2011. In patients who provided consent, the remaining longer term serum creatinine data will be collected throughout 2014. The results of this study will be reported no later than 2015.Clinical Trial Registration NumberNCT01082874

    Rationale and design of the PeriOperative ISchemic Evaluation-3 (POISE-3): a randomized controlled trial evaluating tranexamic acid and a strategy to minimize hypotension in noncardiac surgery

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    Background For patients undergoing noncardiac surgery, bleeding and hypotension are frequent and associated with increased mortality and cardiovascular complications. Tranexamic acid (TXA) is an antifibrinolytic agent with the potential to reduce surgical bleeding; however, there is uncertainty about its efficacy and safety in noncardiac surgery. Although usual perioperative care is commonly consistent with a hypertension-avoidance strategy (i.e., most patients continue their antihypertensive medications throughout the perioperative period and intraoperative mean arterial pressures of 60 mmHg are commonly accepted), a hypotension-avoidance strategy may improve perioperative outcomes. Methods The PeriOperative Ischemic Evaluation (POISE)-3 Trial is a large international randomized controlled trial designed to determine if TXA is superior to placebo for the composite outcome of life-threatening, major, and critical organ bleeding, and non-inferior to placebo for the occurrence of major arterial and venous thrombotic events, at 30 days after randomization. Using a partial factorial design, POISE-3 will additionally determine the effect of a hypotension-avoidance strategy versus a hypertension-avoidance strategy on the risk of major cardiovascular events, at 30 days after randomization. The target sample size is 10,000 participants. Patients ≥45 years of age undergoing noncardiac surgery, with or at risk of cardiovascular and bleeding complications, are randomized to receive a TXA 1 g intravenous bolus or matching placebo at the start and at the end of surgery. Patients, health care providers, data collectors, outcome adjudicators, and investigators are blinded to the treatment allocation. Patients on ≥ 1 chronic antihypertensive medication are also randomized to either of the two blood pressure management strategies, which differ in the management of patient antihypertensive medications on the morning of surgery and on the first 2 days after surgery, and in the target mean arterial pressure during surgery. Outcome adjudicators are blinded to the blood pressure treatment allocation. Patients are followed up at 30 days and 1 year after randomization. Discussion Bleeding and hypotension in noncardiac surgery are common and have a substantial impact on patient prognosis. The POISE-3 trial will evaluate two interventions to determine their impact on bleeding, cardiovascular complications, and mortality. Trial registration ClinicalTrials.gov NCT03505723. Registered on 23 April 2018

    Opioid substitution and antagonist therapy trials exclude the common addiction patient: a systematic review and analysis of eligibility criteria

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    Risk and Timing of Major Bleeding Complications Requiring Intervention of the Percutaneous Kidney Biopsy With a Short Observation Protocol: A Retrospective Chart Review

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    Background: We previously published a retrospective study of kidney biopsies performed in a tertiary care hospital in London, Ontario from 2012 to 2017. This study resulted in a change of practice in our institution to shorter postbiopsy monitoring for outpatients as well as the development of a risk calculator to predict serious bleeding complications. Objective: The primary objective of this study was to determine whether this shorter monitoring time is adequate in the outpatient setting. A secondary objective was to validate the bleeding risk calculator in both inpatients and outpatients. Design: This was a retrospective chart review. Setting: This study was performed at a tertiary academic hospital in London, Ontario, Canada. Participants: This was a retrospective study of 400 adult patients who underwent kidney biopsy between April 30, 2018 and February 25, 2022 at a tertiary academic hospital in London, Canada. Methods: We retrospectively assessed frequency and timing of major bleeding complications in patients who underwent kidney biopsy. In secondary analyses, we examined the prediction performance of the risk calculator in discrimination and calibration. Results: Major bleeding occurred in 7 patients (1.8%). Five of these patients required blood transfusions (1.3%) and 2 required embolization (0.5%). In the outpatient setting, any major bleeding events were identified immediately (1 patient) or on the routine 2-hour ultrasounds (1 patient). The risk calculator showed good discrimination (C-statistic, 0.91, 95% confidence interval [CI] = [0.84 to 0.95]) and calibration (slope, 1.10, 95% CI = [0.47 to 1.74]; intercept, 95% CI = −0.02 [−0.79 to 0.75]), but with much uncertainty in the estimates. Limitations: The occurrence of only a few major bleeding events limits the reliability of our assessment of our risk calculator. Conclusions: There appears to be little yield in extending observation beyond 2 hours after an outpatient kidney biopsy with the use of immediate and 2-hour postbiopsy ultrasounds. The bleeding risk calculator ( http://perioperativerisk.com/kbrc ) warrants further validation

    Development of a Tailored Intervention With Computerized Clinical Decision Support to Improve Quality of Care for Patients With Knee Osteoarthritis: Multi-Method Study

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    BACKGROUND: Clinical practice patterns greatly diverge from evidence-based recommendations to manage knee osteoarthritis conservatively before resorting to surgery. OBJECTIVE: This study aimed to tailor a guideline-based computerized decision support (CDS) intervention that facilitates the conservative management of knee osteoarthritis. METHODS: Experts with backgrounds in clinical medicine, research, implementation, or health informatics suggested the most important recommendations for implementation, how to develop an implementation strategy, and how to form the CDS algorithms. In 6 focus group sessions, 8 general practitioners and 22 patients from Norway, Belgium, and Finland discussed the suggested CDS intervention and identified factors that would be most critical for the success of the intervention. The focus group moderators used the GUideline Implementation with DEcision Support checklist, which we developed to support consideration of CDS success factors. RESULTS: The experts prioritized 9 out of 22 recommendations for implementation. We formed the concept for 6 CDS algorithms to support implementation of these recommendations. The focus group suggested 59 unique factors that could affect the success of the presented CDS intervention. Five factors (out of the 59) were prioritized by focus group participants in every country, including the perceived potential to address the information needs of both patients and general practitioners; the credibility of CDS information; the timing of CDS for patients; and the need for personal dialogue about CDS between the general practitioner and the patient. CONCLUSIONS: The focus group participants supported the CDS intervention as a tool to improve the quality of care for patients with knee osteoarthritis through shared, evidence-based decision making. We aim to develop and implement the CDS based on these study results. Future research should address optimal ways to (1) provide patient-directed CDS, (2) enable more patient-specific CDS within the context of patient complexity, and (3) maintain user engagement with CDS over time.status: publishe
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