ArticleBMC medical informatics and decision making2016
Clinician time used for decision making: a best case workflow study using cardiovascular risk assessments and Ask Mayo Expert algorithmic care process models.
Article in BMC medical informatics and decision making, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 14 citations in OpenAlex.
- Cardiogenic Shock Detection Using Electronic Medical Records: A Review and Blueprint for Clinical Implementation and Future Research.Journal of the American Heart Association · 2026Review
- Posthospital Multidisciplinary Care for AKI Survivors: A Feasibility Pilot.Kidney medicine · 2023Article
- Comprehensive Acute Kidney Injury Survivor Care: Protocol for the Randomized Acute Kidney Injury in Care Transitions Pilot Trial.JMIR research protocols · 2023Article
- Workload and workflow implications associated with the use of electronic clinical decision support tools used by health professionals in general practice: a scoping review.BMC primary care · 2023Article
- An Implementation Science Framework to Develop a Clinical Decision Support Tool for Familial Hypercholesterolemia.Journal of personalized medicine · 2020Article
- Physicians Voluntarily Using an EHR-Based CDS Tool Improved Patients' Guideline-Related Statin Prescription Rates: A Retrospective Cohort Study.Applied clinical informatics · 2019Article
- Innovative Informatics Approaches for Peripheral Artery Disease: Current State and Provider Survey of Strategies for Improving Guideline-Based Care.Mayo Clinic proceedings. Innovations, quality & outcomes · 2018Article
- Population health challenges in primary care: What are the unfinished tasks and who should do them?SAGE open medicine · 2018Article
- Optimisation of lipids for prevention of cardiovascular disease in a primary care.BMJ open quality · 2018Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRisk calculation is increasingly used in lipid management, congestive heart failure, and atrial fibrillation. The risk scores are then used for decisions about statin use, anticoagulation, and implantable defibrillator use. Calculating risks for patients and making decisions based on these risks is often done at the point of care and is an additional time burden for clinicians that can be decreased by automating the tasks and using clinical decision-making support.
methodsUsing Morae Recorder software, we timed 30 healthcare providers tasked with calculating the overall risk of cardiovascular events, sudden death in heart failure, and thrombotic event risk in atrial fibrillation. Risk calculators used were the American College of Cardiology Atherosclerotic Cardiovascular Disease risk calculator (AHA-ASCVD risk), Seattle Heart Failure Model (SHFM risk), and CHA2DS2VASc. We also timed the 30 providers using Ask Mayo Expert care process models for lipid management, heart failure management, and atrial fibrillation management based on the calculated risk scores. We used the Mayo Clinic primary care panel to estimate time for calculating an entire panel risk.
resultsMean provider times to complete the CHA2DS2VASc, AHA-ASCVD risk, and SHFM were 36, 45, and 171 s respectively. For decision making about atrial fibrillation, lipids, and heart failure, the mean times (including risk calculations) were 85, 110, and 347 s respectively.
conclusionEven under best case circumstances, providers take a significant amount of time to complete risk assessments. For a complete panel of patients this can lead to hours of time required to make decisions about prescribing statins, use of anticoagulation, and medications for heart failure. Informatics solutions are needed to capture data in the medical record and serve up automatically calculated risk assessments to physicians and other providers at the point of care.
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