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Feasibility and impact of an evidence-based electronic decision support system for diabetes care in family medicine: protocol for a cluster randomized controlled trial.

ABSTRACT: BACKGROUND: In Belgium, the construction of the national electronic point-of-care information service, EBMPracticeNet, was initiated in 2011 to optimize quality of care by promoting evidence-based decision-making. The collaboration of the government, healthcare providers, Evidence-Based Medicine (EBM) partners, and vendors of Electronic Health Records (EHR) is unique to this project. All Belgian healthcare professionals get free access to an up-to-date database of validated Belgian and nearly 1,000 international guidelines, incorporated in a portal that also provides EBM information from sources other than guidelines, including computerized clinical decision support that is integrated in the EHRs. METHODS: The study is a cluster-randomized trial with before/after measurements conducted in Belgian family medicine. Physicians' practices will be randomly assigned to the intervention or control group in a 1:1 ratio, to receive either the EBMeDS reminders or to follow the usual care process. Randomization will be performed by a statistical consultant with an electronic random list generator, anonymously for the researchers. The follow-up period of the study will be 12 months with interim analysis points at 3, 6 and 9 months. Primary outcome is the one-year pre- to post-implementation change in HbA1c. Patients will not be informed about the intervention. Data analysts will be kept blinded to the allocation. DISCUSSION: The knowledge obtained in this study will be useful for further integration in other Belgian software packages. Users' perceptions and process evaluation will provide information for improving the feasibility of the system. TRIAL REGISTRATION: The trial is registered with the ClinicalTrials.gov registry: NCT01830569.

SUBMITTER: Heselmans A

PROVIDER: S-EPMC3751256 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Feasibility and impact of an evidence-based electronic decision support system for diabetes care in family medicine: protocol for a cluster randomized controlled trial.

Heselmans Annemie A Van de Velde Stijn S Ramaekers Dirk D Vander Stichele Robert R Aertgeerts Bert B

Implementation science : IS 20130805

<h4>Background</h4>In Belgium, the construction of the national electronic point-of-care information service, EBMPracticeNet, was initiated in 2011 to optimize quality of care by promoting evidence-based decision-making. The collaboration of the government, healthcare providers, Evidence-Based Medicine (EBM) partners, and vendors of Electronic Health Records (EHR) is unique to this project. All Belgian healthcare professionals get free access to an up-to-date database of validated Belgian and ne ...[more]

PMID: 23915250

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Project description:BackgroundAcute diarrhoeal disease management often requires rehydration alone without antibiotics. However, non-indicated antibiotics are frequently ordered and this is an important driver of antimicrobial resistance. The mHealth Diarrhoea Management (mHDM) trial aimed to establish whether electronic decision support improves rehydration and antibiotic guideline adherence in resource-limited settings.MethodsA cluster randomised controlled trial was done at ten district hospitals in Bangladesh. Inclusion criteria were patients aged 2 months or older with uncomplicated acute diarrhoea. Admission orders were observed without intervention in the pre-intervention period, followed by randomisation to electronic (rehydration calculator) or paper formatted WHO guidelines for the intervention period. The primary outcome was rate of intravenous fluid ordered as a binary variable. Generalised linear mixed-effect models, accounting for hospital clustering, served as the analytical framework; the analysis was intention to treat. The trial is registered with ClinicalTrials.gov (NCT03154229) and is completed.FindingsFrom March 11 to Sept 10, 2018, 4975 patients (75·6%) of 6577 screened patients were enrolled. The intervention effect for the primary outcome showed no significant differences in rates of intravenous fluids ordered as a function of decision-support type. Intravenous fluid orders decreased by 0·9 percentage points for paper electronic decision support and 4·2 percentage points for electronic decision support, with a 4·2-point difference between decision-support types in the intervention period (paper 98·7% [95% CI 91·8-99·8] vs electronic 94·5% [72·2-99·1]; pinteraction=0·31). Adverse events such as complications and mortality events were uncommon and could not be statistically estimated.InterpretationAlthough intravenous fluid orders did not change, electronic decision support was associated with increases in the volume of intravenous fluid ordered and decreases in antibiotics ordered, which are consistent with WHO guidelines.FundingUS National Institutes of Health.

Project description:ObjectiveTo determine the feasibility of a definitive trial in primary care of electronic clinical decision support (eCDS) for possible oesophago-gastric (O-G) cancer.Design and settingFeasibility study in 42 general practices in two regions of England, cluster randomised controlled trial design without blinding, nested qualitative and health economic evaluation.ParticipantsPatients aged 55 years or older, presenting to their general practitioner (GP) with symptoms associated with O-G cancer. 530 patients (mean age 68 years, 58% female) participated.InterventionPractices randomised 1:1 to usual care (control) or to receive a previously piloted eCDS tool for suspected cancer (intervention), for use at the discretion of the GPs, supported by a theory-based implementation package and ongoing support. We conducted semistructured interviews with GPs in intervention practices. Recruitment lasted 22 months.OutcomesPatient participation rate, use of eCDS, referrals and route to diagnosis, O-G cancer diagnoses; acceptability to GPs; cost-effectiveness. Participants followed up 6 months after index encounter.ResultsFrom control and intervention practices, we screened 3841 and 1303 patients, respectively; 1189 and 434 were eligible, 392 and 138 consented to participate. Ten patients (1.9%) had O-G cancer. eCDS was used eight times in total by five unique users. GPs experienced interoperability problems between the eCDS tool and their clinical system and also found it did not fit with their workflow. Unexpected restrictions on software installation caused major problems with implementation.ConclusionsThe conduct of this study was hampered by technical limitations not evident during an earlier pilot of the eCDS tool, and by regulatory controls on software installation introduced by primary care trusts early in the study. This eCDS tool needed to integrate better with clinical workflow; even then, its use for suspected cancer may be infrequent. Any definitive trial of eCDS for cancer diagnosis should only proceed after addressing these constraints.Trial registration numberISRCTN125595588.

Project description:ImportanceScalable deprescribing interventions may reduce polypharmacy and the use of potentially inappropriate medications (PIMs); however, few studies have been large enough to evaluate the impact that deprescribing may have on adverse drug events (ADEs).ObjectiveTo evaluate the effect of an electronic deprescribing decision support tool on ADEs after hospital discharge among older adults with polypharmacy.Design, setting, and participantsThis was a cluster randomized clinical trial of older (≥65 years) hospitalized patients with an expected survival of more than 3 months who were admitted to 1 of 11 acute care hospitals in Canada from August 22, 2017, to January 13, 2020. At admission, participants were taking 5 or more medications per day. Data analyses were performed from January 3, 2021, to September 23, 2021.InterventionsPersonalized reports of deprescribing opportunities generated by MedSafer software to address usual home medications and measures of prognosis and frailty. Deprescribing reports provided to the treating team were compared with usual care (medication reconciliation).Main outcomes and measuresThe primary outcome was a reduction of ADEs within the first 30 days postdischarge (including adverse drug withdrawal events) captured through structured telephone surveys and adjudicated blinded to intervention status. Secondary outcomes were the proportion of patients with 1 or more PIMs deprescribed at discharge and the proportion of patients with an adverse drug withdrawal event (ADWE).ResultsA total of 5698 participants (median [range] age, 78 [72-85] years; 2858 [50.2%] women; race and ethnicity data were not collected) were enrolled in 3 clusters and were adjudicated for the primary outcome (control, 3204; intervention, 2494). Despite cluster randomization, there were group imbalances, eg, the participants in the intervention arm were older and had more PIMS prescribed at baseline. After hospital discharge, 4989 (87.6%) participants completed an ADE interview. There was no significant difference in ADEs within 30 days of discharge (138 [5.0%] of 2742 control vs 111 [4.9%] of 2247 intervention participants; adjusted risk difference [aRD] -0.8%; 95% CI, -2.9% to 1.3%). Deprescribing increased from 795 (29.8%) of 2667 control to 1249 (55.4%) of 2256 intervention participants [aRD, 22.2%; 95% CI, 16.9% to 27.4%]. There was no difference in ADWEs between groups. Several post hoc sensitivity analyses, including the use of a nonparametric test to address the low cluster number, group imbalances, and potential biases, did not alter study conclusions.Conclusions and relevanceThis cluster randomized clinical trial showed that providing deprescribing clinical decision support during acute hospitalization had no demonstrable impact on ADEs, although the intervention was safe and led to improvements in deprescribing.Trial registrationClinicalTrials.gov Identifier: NCT03272607.

Project description:BackgroundHealth worker compliance with established best-practice clinical and public health guidelines may be enhanced by customized checklists of care and clinical decision support driven by point-of-care data entry into an electronic health registry. The public health system of Palestine is currently implementing a national electronic registry (eRegistry) for maternal and child health. This trial is embedded in the national implementation and aims to assess the effectiveness of the eRegistry's interactive checklists and clinical decision support, compared with the existing paper based records, on improving the quality of care for pregnant women.MethodsThis two-arm cluster randomized controlled trial is conducted in the West Bank, Palestine, and includes 120 clusters (primary healthcare clinics) with an average annual enrollment of 60 pregnancies. The intervention tool is the eRegistry's interactive checklists and clinical decision support implemented within the District Health Information System 2 (DHIS2) Tracker software, developed and customized for the Palestinian context. The primary outcomes reflect the processes of essential interventions, namely timely and appropriate screening and management of: 1) anemia in pregnancy; 2) hypertension in pregnancy; 3) abnormal fetal growth; 4) and diabetes mellitus in pregnancy. The composite primary health outcome encompasses five conditions representing risk for the mother or baby that could have been detected or prevented by high-quality antenatal care: moderate or severe anemia at admission for labor; severe hypertension at admission for labor; malpresentation at delivery undetected during pregnancy; small for gestational age baby at delivery undetected during pregnancy; and large for gestational age baby at delivery. Primary analysis at the individual level taking the design effect of the clustering into account will be performed as intention-to-treat.DiscussionThis trial, embedded in the national implementation of the eRegistry in Palestine, allows the assessment of process and health outcomes in a large-scale pragmatic setting. Findings will inform the use of interactive checklists and clinical decision support driven by point-of-care data entry into an eRegistry as a health systems-strengthening approach.Trial registrationISRCTN trial registration number, ISRCTN18008445 . Registered on 6 April 2017.

Project description:BackgroundLarge gaps exist in the implementation of guideline recommendations for cardiovascular disease (CVD) risk management. Electronic decision support (EDS) systems are promising interventions to close these gaps but few have undergone clinical trial evaluation in Australia. We have developed HealthTracker, a multifaceted EDS and quality improvement intervention to improve the management of CVD risk.Methods/designIt is hypothesised that the use of HealthTracker over a 12-month period will result in: (1) an increased proportion of patients receiving guideline-indicated measurements of CVD risk factors and (2) an increased proportion of patients at high risk will receive guideline-indicated prescriptions for lowering their CVD risk. Sixty health services (40 general practices and 20 Aboriginal Community Controlled Health Services (ACCHSs) will be randomised in a 1:1 allocation to receive either the intervention package or continue with usual care, stratified by service type, size and participation in existing quality improvement initiatives. The intervention consists of point-of-care decision support; a risk communication interface; a clinical audit tool to assess performance on CVD-related indicators; a quality improvement component comprising peer-ranked data feedback and support to develop strategies to improve performance. The control arm will continue with usual care without access to these intervention components. Quantitative data will be derived from cross-sectional samples at baseline and end of study via automated data extraction. Detailed process and economic evaluations will also be conducted.Ethics and disseminationThe general practice component of the study is approved by the University of Sydney Human Research Ethics Committee (HREC) and the ACCHS component is approved by the Aboriginal Health and Medical Research Council HREC. Formal agreements with each of the participating sites have been signed. In addition to the usual scientific forums, results will be disseminated via newsletters, study websites, face-to-face feedback forums and workshops.Trial registrationThe trial is registered with the Australian Clinical Trials Registry ACTRN 12611000478910.

Project description:BACKGROUND:Decisional tools have demonstrated their importance in informing manufacturing and commercial decisions in the monoclonal antibody domain. Recent approved therapies in regenerative medicine have shown great clinical benefits to patients. OBJECTIVE:The objective of this review was to investigate what decisional tools are available and what issues and gaps have been raised for their use in regenerative medicine. METHODS:We systematically searched MEDLINE to identify articles on decision support tools relevant to tissue engineering, and cell and gene therapy, with the aim of identifying gaps for future decisional tool development. We included published studies in English including a description of decisional tools in regenerative medicines. We extracted data using a predesigned Excel table and assessed the data both quantitatively and qualitatively. RESULTS:We identified 9 articles addressing key decisions in manufacturing and product development challenges in cell therapies. The decision objectives, parameters, assumptions, and solution methods were analyzed in detail. We found that all decisional tools focused on cell therapies, and 6 of the 9 reviews focused on allogeneic cell therapy products. We identified no available tools on tissue-engineering and gene therapy products. These studies addressed key decisions in manufacturing and product development challenges in cell therapies, such as choice of technology, through modeling. CONCLUSIONS:Our review identified a limited number of decisional tools. While the monoclonal antibodies and biologics decisional tool domain has been well developed and has shown great importance in driving more cost-effective manufacturing processes and better investment decisions, there is a lot to be learned in the regenerative medicine domain. There is ample space for expansion, especially with regard to autologous cell therapies, tissue engineering, and gene therapies. To consider the problem more comprehensively, the full needle-to-needle process should be modeled and evaluated.

Dataset Information

Feasibility and impact of an evidence-based electronic decision support system for diabetes care in family medicine: protocol for a cluster randomized controlled trial.

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Feasibility and impact of an evidence-based electronic decision support system for diabetes care in family medicine: protocol for a cluster randomized controlled trial.

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