scholarly journals A target product profile for electronic clinical decision support algorithms combined with point-of-care diagnostic test results to support evidence-based decisions during patient consultations by health workers

2019 ◽  
Author(s):  
Karell G. Pellé ◽  
Clotilde Rambaud-Althaus ◽  
Valérie D’Acremont ◽  
Gretchen Moran ◽  
Rangarajan Sampath ◽  
...  
Keyword(s):  
Decision Support ◽  
Health Workers ◽  
Point Of Care ◽  
Clinical Decision ◽  
Evidence Based ◽  
Target Product ◽  
Test Results ◽  
Target Product Profile ◽  
Product Profile ◽  
Electronic Clinical Decision Support

ABSTRACTHealth workers in low-resource settings often lack the support and tools to follow evidence-based clinical recommendations for diagnosing, treating and managing sick patients. Digital technologies, by combining patient health information and point of care diagnostics with evidence-based clinical protocols, can help improve the quality of care, the rational use of resources (humans, diagnostics and medicines) and save patient lives. The development of a target product profile for electronic clinical decision support algorithms (CDSAs) aimed at guiding preventive or curative consultations, and that integrate diagnostic test results will help align developer and implementer processes and specifications with the needs of end-users, in terms of quality, safety, performance and operational functionality. To identify characteristics for a CDSA, experts from academia, research institutions, and industry as well as policy makers with expertise in diagnostic and CDSA development, and implementation in LMICs were convened. Experts discussed the critical characteristics of a draft TPP which was revised and finalised through a Delphi process to facilitate consensus building. Experts were in overwhelming agreement that, given that CDSAs provide patients’ management recommendations, the underlying clinical algorithms should be available in human readable format and evidence-based. Whenever possible, the algorithm output should take into account pre-test disease probabilities, diagnostic likelihood ratios of clinical or laboratory predictors and disease probability thresholds to test and to treat. Validation processes should at a minimum ensure the CDSA are implementing faithfully the evidence-based algorithm they are based on (internal validation through clinical association and analytical validation). Additionally, clinical validation, bringing practice evidence about the impact of the CDSA use on health outcomes, was recognized as a good to have. The CDSAs should be designed to fit within clinic workflows, connectivity challenges and high volume settings. Data collected through the tool should conform to local patient privacy regulations and international data standards.

scholarly journals Electronic clinical decision support algorithms incorporating point-of-care diagnostic tests in low-resource settings: a target product profile

2020 ◽  
Vol 5 (2) ◽  
pp. e002067 ◽  
Author(s):  
Karell G Pellé ◽  
Clotilde Rambaud-Althaus ◽  
Valérie D'Acremont ◽  
Gretchen Moran ◽  
Rangarajan Sampath ◽  
...  
Keyword(s):  
Patient Management ◽  
Point Of Care ◽  
Clinical Decision ◽  
Evidence Based ◽  
Target Product Profile ◽  
Low Resource Settings ◽  
Low Resource ◽  
Product Profile ◽  
Patient Health ◽  
Electronic Clinical Decision Support

Health workers in low-resource settings often lack the support and tools to follow evidence-based clinical recommendations for diagnosing, treating and managing sick patients. Digital technologies, by combining patient health information and point-of-care diagnostics with evidence-based clinical protocols, can help improve the quality of care and the rational use of resources, and save patient lives. A growing number of electronic clinical decision support algorithms (CDSAs) on mobile devices are being developed and piloted without evidence of safety or impact. Here, we present a target product profile (TPP) for CDSAs aimed at guiding preventive or curative consultations in low-resource settings. This document will help align developer and implementer processes and product specifications with the needs of end users, in terms of quality, safety, performance and operational functionality. To identify the characteristics of CDSAs, a multidisciplinary group of experts (academia, industry and policy makers) with expertise in diagnostic and CDSA development and implementation in low-income and middle-income countries were convened to discuss a draft TPP. The TPP was finalised through a Delphi process to facilitate consensus building. An agreement greater than 75% was reached for all 40 TPP characteristics. In general, experts were in overwhelming agreement that, given that CDSAs provide patient management recommendations, the underlying clinical algorithms should be human-interpretable and evidence-based. Whenever possible, the algorithm’s patient management output should take into account pretest disease probabilities and likelihood ratios of clinical and diagnostic predictors. In addition, validation processes should at a minimum show that CDSAs are implementing faithfully the evidence they are based on, and ideally the impact on patient health outcomes. In terms of operational needs, CDSAs should be designed to fit within clinic workflows and function in connectivity-challenged and high-volume settings. Data collected through the tool should conform to local patient privacy regulations and international data standards.

scholarly journals Target Product Profile (TPP) for Chagas Disease Point-of-Care Diagnosis and Assessment of Response to Treatment

2015 ◽  
Vol 9 (6) ◽  
pp. e0003697 ◽  
Author(s):  
Analía I. Porrás ◽  
Zaida E. Yadon ◽  
Jaime Altcheh ◽  
Constança Britto ◽  
Gabriela C. Chaves ◽  
...  
Keyword(s):  
Chagas Disease ◽  
Point Of Care ◽  
Response To Treatment ◽  
Target Product ◽  
Target Product Profile ◽  
Product Profile

scholarly journals LO22: Implementation of an electronic clinical decision support tool to improve knowledge translation and imaging appropriateness for patients with mild traumatic brain injury and suspected pulmonary embolism

CJEM ◽  
2017 ◽  
Vol 19 (S1) ◽  
pp. S34-S35
Author(s):  
J. Andruchow ◽  
D. Grigat ◽  
A. McRae ◽  
G. Innes ◽  
E. Lang
Keyword(s):  
Pulmonary Embolism ◽  
Decision Support ◽  
Point Of Care ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Evidence Based ◽  
Support Tool ◽  
Imaging Appropriateness ◽  
Ct Head ◽  
Evidence Based Guidelines

Introduction/Innovation Concept: Utilization of CT imaging has increased dramatically over the past two decades, but has not necessarily improved patient outcomes. As healthcare spending grows unsustainably and evidence of harms from unnecessary testing accrues, there is pressure to improve imaging appropriateness. However, prior attempts to reduce unnecessary imaging using evidence-based guidelines have met with limited success, with common barriers cited including a lack of confidence in patient outcomes, medicolegal risk, and patient expectations. This project attempts to address these barriers through the development of an electronic clinical decision support (CDS) tool embedded in clinical practice. Methods: An interactive web-based point-of-care CDS tool was incorporated into computerized physician order entry software to provide real-time evidence-based guidance to emergency physicians for select clinical indications. For patients with mild traumatic brain injury (MTBI), decision support for the Canadian CT Head Rule pops up when a CT head is ordered. For patients with suspected pulmonary embolism (PE), the tool is triggered when a CT pulmonary angiogram is ordered and provides CDS for the Pulmonary Embolism Rule-out Criteria (PERC), Wells Score, age-adjusted D-dimer and CT imaging. To study the impact of the tool, all emergency physicians in the Calgary zone were randomized to receive voluntary decision support for either MTBI or PE. Curriculum, Tool, or Material: The tool uses a multifaceted approach to inform physician decision making, including visualization of risk and quantitative outcomes data and links to primary literature. The CDS tool simultaneously documents guideline compliance in the health record, generates printable patient education materials, and populates a REDCap™ database, enabling the creation of confidential physician report cards on CT utilization, appropriateness and diagnostic yield for both audit and feedback and research purposes. Preliminary data show that physicians are using the MTBI CDS approximately 30% of the time, and the PE CDS approximately 40% of the time. Evaluation of CDS impact on imaging utilization and appropriateness is ongoing. Conclusion: A voluntary web-based point-of-care decision support tool embedded in workflow has the potential to address many of the factors typically cited as barriers to use of evidence-based guidelines in practice. However, high rates of adherence to CDS will likely require physician incentives and appropriateness measures.

scholarly journals Target Product Profile for a point-of-care diagnostic test for dermal leishmaniases

2019 ◽  
Vol 5 ◽  
pp. e00103 ◽  
Author(s):  
Israel Cruz ◽  
Audrey Albertini ◽  
Mady Barbeitas ◽  
Byron Arana ◽  
Albert Picado ◽  
...  
Keyword(s):  
Diagnostic Test ◽  
Point Of Care ◽  
Target Product ◽  
Target Product Profile ◽  
Product Profile

scholarly journals Electronic Clinical Decision Support for Children with Minor Head Trauma and Intracranial Injuries: A Sociotechnical Analysis

2020 ◽  
Author(s):  
Jacob K Greenberg ◽  
Ayodamola Otun ◽  
Azzah Nasraddin ◽  
Ross C Brownson ◽  
Nathan Kuppermann ◽  
...  
Keyword(s):  
Information Technology ◽  
Decision Support ◽  
Focus Group ◽  
Clinical Decision Support ◽  
Thematic Analysis ◽  
Clinical Decision ◽  
Evidence Based ◽  
Minor Head Trauma ◽  
Technology Specialists ◽  
Electronic Clinical Decision Support

Abstract Background: Current management of children with minor head trauma (MHT) and intracranial injuries is not evidence-based and may place some children at risk of harm. Evidence-based electronic clinical decision support (CDS) for management of these children may improve patient safety and decrease resource use. To guide these efforts, we evaluated the sociotechnical environment impacting the implementation of electronic CDS, including workflow and communication, institutional culture, and hardware and software infrastructure, among other factors. Methods: Between March and May, 2020 semi-structured qualitative focus group interviews were conducted to identify sociotechnical influences on CDS implementation. Physicians from neurosurgery, emergency medicine, critical care, and pediatric general surgery were included, along with information technology specialists. Participants were recruited from nine health centers in the United States. Focus group transcripts were coded and analyzed using thematic analysis. The final themes were then cross-referenced with previously defined sociotechnical dimensions.Results: We included 28 physicians and four information technology specialists in seven focus groups (median five participants per group). Five physicians were trainees and 10 had administrative leadership positions. Through inductive thematic analysis, we identified five primary themes: 1) clinical impact; 2) stakeholders and users; 3) tool content; 4) clinical practice integration; and 5) post-implementation evaluation measures. Participants generally supported using CDS to determine an appropriate level-of-care for these children. However, some had mixed feelings regarding how the tool could best be used by different specialties (e.g. use by neurosurgeons versus non-neurosurgeons). Feedback from the interviews helped refine the tool content and also highlighted potential technical and workflow barriers to address prior to implementation. Conclusions: We identified key factors impacting the implementation of electronic CDS for children with MHT and intracranial injuries. These results have informed our implementation strategy and may also serve as a template for future efforts to implement health information technology in a multidisciplinary, emergency setting.

scholarly journals Development of a target product profile for a point-of-care cardiometabolic device

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Beatrice Vetter ◽  
David Beran ◽  
Philippa Boulle ◽  
Arlene Chua ◽  
Roberto de la Tour ◽  
...  
Keyword(s):  
Online Survey ◽  
Point Of Care ◽  
Random Access ◽  
Disease Diagnosis ◽  
Cardiometabolic Disease ◽  
Target Product ◽  
Expert Group ◽  
Target Product Profile ◽  
Cardiometabolic Disorders ◽  
Product Profile

Abstract Introduction Multi-parameter diagnostic devices can simplify cardiometabolic disease diagnosis. However, existing devices may not be suitable for use in low-resource settings, where the burden of non-communicable diseases is high. Here we describe the development of a target product profile (TPP) for a point-of-care multi-parameter device for detection of biomarkers for cardiovascular disease and metabolic disorders, including diabetes, in primary care settings in low- and middle-income countries (LMICs). Methods A draft TPP developed by an expert group was reviewed through an online survey and semi-structured expert interviews to identify device characteristics requiring refinement. The draft TPP included 41 characteristics with minimal and optimal requirements; characteristics with an agreement level for either requirement of ≤ 85% in either the survey or among interviewees were further discussed by the expert group and amended as appropriate. Results Twenty people responded to the online survey and 18 experts participated in the interviews. Twenty-two characteristics had an agreement level of ≤ 85% in either the online survey or interviews. The final TPP defines the device as intended to be used for basic diagnosis and management of cardiometabolic disorders (lipids, glucose, HbA1c, and creatinine) as minimal requirement, and offering an expanded test menu for wider cardiometabolic disease management as optimal requirement. To be suitable, the device should be intended for level 1 healthcare settings or lower, used by minimally trained healthcare workers and allow testing using self-contained cartridges or strips without the need for additional reagents. Throughput should be one sample at a time in a single or multi-analyte cartridge, or optimally enable testing of several samples and analytes in parallel with random access. Conclusion This TPP will inform developers of cardiometabolic multi-parameter devices for LMIC settings, and will support decision makers in the evaluation of existing and future devices.

scholarly journals LO73: A randomized controlled trial of electronic clinical decision support to reduce unnecessary CT imaging for patients with suspected pulmonary embolism

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S32-S33
Author(s):  
J.E. Andruchow ◽  
D. Grigat ◽  
A.D. McRae ◽  
T. Abedin ◽  
D. Wang ◽  
...  
Keyword(s):  
Pulmonary Embolism ◽  
Randomized Controlled Trial ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Controlled Trial ◽  
Clinical Decision ◽  
Evidence Based ◽  
Index Visit ◽  
Randomized Controlled ◽  
Electronic Clinical Decision Support

Introduction: Utilization of CT pulmonary angiography (CTPA) to rule out pulmonary embolism (PE) has risen dramatically but diagnostic yield has fallen over the past several decades, suggesting that lower risk patients are being tested. Given little evidence to suggest improved patient outcomes with higher CTPA utilization, and increasing evidence of harm, evidence-based guidelines have been developed to reduce unnecessary CTPA use. The objective of this study was to assess the impact of an electronic clinical decision support (CDS) intervention to reduce unnecessary CTPA utilization for emergency department (ED) patients with suspected PE. Methods: This was a cluster-randomized, controlled trial with physicians as the unit of randomization. All emergency physicians (EPs) at 4 urban adult EDs and 1 urgent care center were randomly assigned to receive either evidence-based imaging CDS for patients with suspected PE (intervention) or no CDS (control) over a 1-year study period. CDS was launched in an external web browser whenever an intervention EP ordered a CTPA from the computerized physician order entry software for ED patients CTAS 2-5; however, physician interaction with CDS was voluntary. The CDS tool enabled calculation of patient-specific information, including the patients Wells score, PERC score, and age-adjusted D-dimer, as well as prediction of each patients pre-test risk of PE along with an imaging/no imaging recommendation. CDS recommendations could be printed for the medical record as could educational patient handouts to support physician decision-making. The primary outcome was CTPA utilization for patients with CEDIS chief complaints of shortness of breath or chest pain on the index visit. Secondary outcomes included index visit length of stay (LOS), and CTPA use or VTE diagnosis within 90-days. This study was REB approved. Results: Demographics were similar among intervention and control EPs; however, during a 2-year pre-intervention period control EPs had a higher baseline CTPA rate (8.5% vs 7.7%, p<0.001). In the first 8-months following CDS implementation, 94 intervention EPs saw 9,609 patients and voluntarily interacted with the CDS tool on 43.2% of eligible encounters while 91 control EPs saw 9,498 patients. CTPA utilization was higher among intervention EPs than control (9.6% vs 8.3%, p<0.001) as was ED LOS (302 vs 287 minutes, p<0.001). There was no difference in 90-day CTPA use or VTE diagnoses. Conclusion: In one of the largest RCTs of CDS to date, exposure to CDS was associated with higher rates of CTPA utilization and longer ED LOS on the index visit, and no difference in 90-day CT use or VTE diagnoses. These results differ from a concurrent study of CDS for patients with mild traumatic brain injury in the same physician population and may relate to the implementation of the CDS intervention and/or complexity of the underlying evidence-based algorithms.

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