Impact of a computer-based diagnostic decision support tool on the differential diagnoses of medicine residents.
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ABSTRACT:
SUBMITTER: Feldman MJ
PROVIDER: S-EPMC3399617 | biostudies-other | 2012 Jun
REPOSITORIES: biostudies-other
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Project description:BACKGROUND:Physicians often find significant challenges in assessing automobile driving in persons with mild cognitive impairment and mild dementia and deciding when to report to transportation administrators. Care must be taken to balance the safety of patients and other road users with potential negative effects of issuing such reports. OBJECTIVE:The aim of this study was to assess whether a computer-based Driving in Dementia Decision Tool (DD-DT) increased appropriate reporting of patients with mild dementia or mild cognitive impairment to transportation administrators. METHODS:The study used a parallel-group cluster nonblinded randomized controlled trial design to test a multifaceted knowledge translation intervention. The intervention included a computer-based decision support system activated by the physician-user, which provides a recommendation about whether to report patients with mild dementia or mild cognitive impairment to transportation administrators, based on an algorithm derived from earlier work. The intervention also included a mailed educational package and Web-based specialized reporting forms. Specialists and family physicians with expertise in dementia or care of the elderly were stratified by sex and randomized to either use the DD-DT or a control version of the tool that required identical data input as the intervention group, but instead generated a generic reminder about the reporting legislation in Ontario, Canada. The trial ran from September 9, 2014 to January 29, 2016, and the primary outcome was the number of reports made to the transportation administrators concordant with the algorithm. RESULTS:A total of 69 participating physicians were randomized, and 36 of these used the DD-DT; 20 of the 35 randomized to the intervention group used DD-DT with 114 patients, and 16 of the 34 randomized to the control group used it with 103 patients. The proportion of all assessed patients reported to the transportation administrators concordant with recommendation did not differ between the intervention and the control groups (50% vs 49%; Z=-0.19, P=.85). Two variables predicted algorithm-based reporting-caregiver concern (odds ratio [OR]=5.8, 95% CI 2.5-13.6, P<.001) and abnormal clock drawing (OR 6.1, 95% CI 3.1-11.8, P<.001). CONCLUSIONS:On the basis of this quantitative analysis, in-office abnormal clock drawing and expressions of concern about driving from caregivers substantially influenced physicians to report patients with mild dementia or mild cognitive impairment to transportation administrators, but the DD-DT tool itself did not increase such reports among these expert physicians. TRIAL REGISTRATION:ClinicalTrials.gov NCT02036099; https://clinicaltrials.gov/ct2/show/NCT02036099 (Archived by WebCite at http://www.webcitation.org/6zGMF1ky8).
| S-EPMC5993977 | biostudies-literature
Project description:BackgroundLung cancer screening is a US Preventive Services Task Force Grade B recommendation that has been shown to decrease lung cancer-related mortality by approximately 20%. However, making the decision to screen, or not, for lung cancer is a complex decision because there are potential risks (eg, false positive results, overdiagnosis). Shared decision making was incorporated into the lung cancer screening guideline and, for the first time, is a requirement for reimbursement of a cancer screening test from Medicare. Awareness of lung cancer screening remains low in both the general and screening-eligible populations. When a screening-eligible person visits their clinician never having heard about lung cancer screening, engaging in shared decision making to arrive at an informed decision can be a challenge. Methods to effectively prepare patients for these clinical encounters and support both patients and clinicians to engage in these important discussions are needed.ObjectiveThe aim of the study was to estimate the effects of a computer-tailored decision support tool that meets the certification criteria of the International Patient Decision Aid Standards that will prepare individuals and support shared decision making in lung cancer screening decisions.MethodsA pilot randomized controlled trial with a community-based sample of 60 screening-eligible participants who have never been screened for lung cancer was conducted. Approximately half of the participants (n=31) were randomized to view LungTalk-a web-based tailored computer program-while the other half (n=29) viewed generic information about lung cancer screening from the American Cancer Society. The outcomes that were compared included lung cancer and screening knowledge, lung cancer screening health beliefs (perceived risk, perceived benefits, perceived barriers, and self-efficacy), and perception of being prepared to engage in a discussion about lung cancer screening with their clinician.ResultsKnowledge scores increased significantly for both groups with greater improvement noted in the group receiving LungTalk (2.33 vs 1.14 mean change). Perceived self-efficacy and perceived benefits improved in the theoretically expected directions.ConclusionsLungTalk goes beyond other decision tools by addressing lung health broadly, in the context of performing a low-dose computed tomography of the chest that has the potential to uncover other conditions of concern beyond lung cancer, to more comprehensively educate the individual, and extends the work of nontailored decision aids in the field by introducing tailoring algorithms and message framing based upon smoking status in order to determine what components of the intervention drive behavior change when an individual is informed and makes the decision whether to be screened or not to be screened for lung cancer.International registered report identifier (irrid)RR2-10.2196/resprot.8694.
| S-EPMC7671845 | biostudies-literature
Project description:BackgroundAwareness of lung cancer screening remains low in the screening-eligible population, and when patients visit their clinician never having heard of lung cancer screening, engaging in shared decision making to arrive at an informed decision can be a challenge. Therefore, methods to effectively support both patients and clinicians to engage in these important discussions are essential. To facilitate shared decision making about lung cancer screening, effective methods to prepare patients to have these important discussions with their clinician are needed.ObjectiveOur objective is to develop a computer-tailored decision support tool that meets the certification criteria of the International Patient Decision Aid Standards instrument version 4.0 that will support shared decision making in lung cancer screening decisions.MethodsUsing a 3-phase process, we will develop and test a prototype of a computer-tailored decision support tool in a sample of lung cancer screening-eligible individuals. In phase I, we assembled a community advisory board comprising 10 screening-eligible individuals to develop the prototype. In phase II, we recruited a sample of 13 screening-eligible individuals to test the prototype for usability, acceptability, and satisfaction. In phase III, we are conducting a pilot randomized controlled trial (RCT) with 60 screening-eligible participants who have never been screened for lung cancer. Outcomes tested include lung cancer and screening knowledge, lung cancer screening health beliefs (perceived risk, perceived benefits, perceived barriers, and self-efficacy), perception of being prepared to engage in a patient-clinician discussion about lung cancer screening, occurrence of a patient-clinician discussion about lung cancer screening, and stage of adoption for lung cancer screening.ResultsPhases I and II are complete. Phase III is underway. As of July 15, 2017, 60 participants have been enrolled into the study, and have completed the baseline survey, intervention, and first follow-up survey. We expect to have results by December 31, 2017 and to have data analysis completed by March 1, 2018.ConclusionsResults from usability testing indicate that the computer-tailored decision support tool is easy to use, is helpful, and provides a satisfactory experience for the user. At the conclusion of phase III (pilot RCT), we will have preliminary effect sizes to inform a future fully powered RCT on changes in (1) knowledge about lung cancer and screening, (2) perceived risk of lung cancer, (3) perceived benefits of lung cancer screening, (4) perceived barriers to lung cancer screening, (5) self-efficacy for lung cancer screening, and (6) perceptions of being adequately prepared to engage in a discussion with their clinician about lung cancer screening.
| S-EPMC5709657 | biostudies-literature
Project description:Lynch syndrome (LS) is a hereditary cancer susceptibility condition associated with varying cancer risks depending on which of the five causative genes harbors a pathogenic variant; however, lifestyle and medical interventions provide options to lower those risks. We developed MyLynch, a patient-facing clinical decision support (CDS) web application that applies genetically-guided personalized medicine (GPM) for individuals with LS. The tool was developed in R Shiny through a patient-focused iterative design process. The knowledge base used to estimate patient-specific risk leveraged a rigorously curated literature review. MyLynch informs LS patients of their personal cancer risks, educates patients on relevant interventions, and provides patients with adjusted risk estimates, depending on the interventions they choose to pursue. MyLynch can improve risk communication between patients and providers while also encouraging communication among relatives with the goal of increasing cascade testing. As genetic panel testing becomes more widely available, GPM will play an increasingly important role in patient care, and CDS tools offer patients and providers tailored information to inform decision-making. MyLynch provides personalized cancer risk estimates and interventions to lower these risks for patients with LS.
| S-EPMC9856567 | biostudies-literature
Project description:BackgroundIncreasing use of electronic health records offers the potential to incorporate computer decision support systems (CDSSs) to prompt evidence-based actions within routine consultations.AimTo synthesise the evidence for the use of CDSSs by professionals managing people with asthma.Materials and methodsWe systematically searched Medline, Embase, Health Technology Assessment, Cochrane and Inspec databases (1990 to April 2012, no language restrictions) for trials, and four online repositories for unpublished studies. We also wrote to authors. Eligible studies were randomised controlled trials of CDSSs supporting professional management of asthma. Studies were appraised (Cochrane Risk of Bias Tool) and findings synthesised narratively.ResultsA total of 5787 articles were screened, and eight trials were found eligible, with six at high risk of bias. Overall, CDSSs for professionals were ineffective. Usage of the systems was generally low: in the only trial at low risk of bias the CDSS was not used at all. When a CDSS was used, compliance with the advice offered was also low. However, if actually used, CDSSs could result in closer guideline adherence (improve investigating, prescribing and issuing of action plans) and could improve some clinical outcomes. The study at moderate risk of bias showed increased prescribing of inhaled steroids.ConclusionsThe current generation of CDSSs is unlikely to result in improvements in outcomes for patients with asthma because they are rarely used and the advice is not followed. Future decision support systems need to align better with professional workflows so that pertinent and timely advice is easily accessible within the consultation.
| S-EPMC4373260 | biostudies-literature
Project description:Nowadays, the gold standard method for malaria diagnosis is a staining of thick and thin blood film examined by expert laboratorists. It requires well-trained laboratorists, which is a time consuming task, and is un-automated protocol. For this study, Maladiag Software was developed to predict malaria infection in suspected malaria patients. The demographic data of patients, examination for malaria parasites, and complete blood count (CBC) profiles were analyzed. Binary logistic regression was used to create the equation for the malaria diagnosis. The diagnostic parameters of the equation were tested on 4,985 samples (703 infected and 4,282 control samples). The equation indicated 81.2% sensitivity and 80.3% specificity for predicting infection of malaria. The positive likelihood and negative likelihood ratio were 4.12 (95% CI = 4.01-4.23) and 0.23 (95% CI = 0.22-0.25), respectively. This parameter also had odds ratios (P value < 0.0001, OR = 17.6, 95% CI = 16.0-19.3). The equation can predict malaria infection after adjust for age, gender, nationality, monocyte (%), platelet count, neutrophil (%), lymphocyte (%), and the RBC count of patients. The diagnostic accuracy was 0.877 (Area under curve, AUC) (95% CI = 0.871-0.883). The system, when used in combination with other clinical and microscopy methods, might improve malaria diagnoses and enhance prompt treatment.
| S-EPMC4642325 | biostudies-other
Project description:Appropriate thromboprophylaxis for patients with atrial fibrillation or atrial flutter (AF) remains a national challenge. The recent availability of direct oral anticoagulants (DOACs) with comparable efficacy and improved safety compared with warfarin alters the balance between risk factors for stroke and benefit of anticoagulation. Our objective was to examine the impact of DOACs as an alternative to warfarin on the net benefit of oral anticoagulant therapy (OAT) in a real-world population of AF patients.This is a retrospective cohort study of patients with paroxysmal or persistent nonvalvular AF. We updated an Atrial Fibrillation Decision Support Tool (AFDST) to include DOACs as treatment options. The tool generates patient-specific recommendations based upon individual patient risk factor profiles for stroke and major bleeding using quality-adjusted life-years (QALYs) calculated for each treatment strategy by a decision analytic model. The setting included inpatient and ambulatory sites in an academic health center in the midwestern United States. The study involved 5,121 adults with nonvalvular AF seen for any ambulatory visit or inpatient hospitalization over the 1-year period (January through December 2016). Outcome measure was net clinical benefit in QALYs.When DOACs are a therapeutic option, the AFDST recommends OAT for 4,134 (81%) patients and no antithrombotic therapy or aspirin for 489 (9%). A strong recommendation for OAT could not be made in 498 (10%) patients. When warfarin is the only option, OAT is recommended for 3,228 (63%) patients and no antithrombotic therapy or aspirin for 973 (19%). A strong recommendation for OAT could not be made in 920 (18%) patients. In total, 1,508 QALYs could be gained if treatment were changed to that recommended by the AFDST.Availability of DOACs increases the proportion of patients for whom oral anticoagulation therapy is recommended in a real-world cohort of AF patients and increased projected QALYs by more than 1,500 when all patients are receiving thromboprophylaxis as recommended by the AFDST compared with current treatment.
| S-EPMC5726779 | biostudies-literature
Project description:ObjectiveFeedback is critical to the growth of learners. However, feedback quality can be variable in practice. Most feedback tools are generic, with few targeting emergency medicine. We created a feedback tool designed for emergency medicine residents, and this study aimed to evaluate the effectiveness of this tool.MethodsThis was a single-center, prospective cohort study comparing feedback quality before and after introducing a novel feedback tool. Residents and faculty completed a survey after each shift assessing feedback quality, feedback time, and the number of feedback episodes. Feedback quality was assessed using a composite score from seven questions, which were each scored 1 to 5 points (minimum total score, 7 points; maximum, 35 points). Preintervention and postintervention data were analyzed using a mixed-effects model that took into account the correlation of random effects between study participants.ResultsResidents completed 182 surveys and faculty members completed 158 surveys. The use of the tool was associated with improved consistency in the summative score of effective feedback attributes as assessed by residents (P=0.040) but not by faculty (P=0.259). However, most of the individual scores for attributes of good feedback did not reach statistical significance. With the tool, residents perceived that faculty spent more time providing feedback (P=0.040) and that the delivery of feedback was more ongoing throughout the shift (P=0.020). Faculty felt that the tool allowed for more ongoing feedback (P=0.002), with no perceived increase in the time spent delivering feedback (P=0.833).ConclusionThe use of a dedicated tool may help educators provide more meaningful and frequent feedback without impacting the perceived required time needed to provide feedback.
| S-EPMC10579731 | biostudies-literature
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.
| S-EPMC6315273 | biostudies-literature
Project description:IntroductionHyperglycemia during critical illness is common, and intravenous insulin therapy (IIT) to normalize blood glucose improves outcomes in selected populations. Methods differ widely in complexity, insulin dosing approaches, efficacy, and rates of hypoglycemia. We developed a simple bedside-computerized decision support protocol (eProtocol-insulin) that yields promising results in the development center. We examined the effectiveness and safety of this tool in six adult and five pediatric intensive care units (ICUs) in other centers.MethodsWe required attending physicians of eligible patients to independently intend to use intravenous insulin to normalize blood glucose. We used eProtocol-insulin for glucose control for a duration determined by the clinical caregivers. Adults had an anticipated length of stay of 3 or more days. In pediatric ICUs, we also required support or intended support with mechanical ventilation for greater than 24 hours or with a vasoactive infusion. We recorded all instances in which eProtocol-insulin instructions were not accepted and all blood glucose values. An independent data safety and monitoring board monitored study results and subject safety. Bedside nurses were selected randomly to complete a paper survey describing their perceptions of quality of care and workload related to eProtocol-insulin use.ResultsClinicians accepted 93% of eProtocol-insulin instructions (11,773/12,645) in 100 adult and 48 pediatric subjects. Forty-eight percent of glucose values were in the target range. Both of these results met a priori-defined efficacy thresholds. Only 0.18% of glucose values were < or =40 mg/dl. This is lower than values reported in prior IIT studies. Although nurses reported eProtocol-insulin required as much work as managing a mechanical ventilator, most nurses felt eProtocol-insulin had a low impact on their ability to complete non-IIT nursing activities.ConclusionsA multicenter validation demonstrated that eProtocol-insulin is a valid, exportable tool that can assist clinicians in achieving control of glucose in critically ill adults and children.
| S-EPMC2769731 | biostudies-literature