Mikhail A Dziadzko1, Ognjen Gajic2, Brian W Pickering1, Vitaly Herasevich3. 1. Department of Anesthesiology, Mayo Clinic, Rochester, MN, USA. 2. Division of Pulmonology and Critical Care Medicine, Mayo Clinic, Rochester, MN, USA. 3. Department of Anesthesiology, Mayo Clinic, Rochester, MN, USA. Electronic address: herasevich.vitaly@mayo.edu.
Abstract
OBJECTIVE: Clinical calculators are widely used in modern clinical practice, but are not generally applied to electronic health record (EHR) systems. Important barriers to the application of these clinical calculators into existing EHR systems include the need for real-time calculation, human-calculator interaction, and data source requirements. The objective of this study was to identify, classify, and evaluate the use of available clinical calculators for clinicians in the hospital setting. METHODS: Dedicated online resources with medical calculators and providers of aggregated medical information were queried for readily available clinical calculators. Calculators were mapped by clinical categories, mechanism of calculation, and the goal of calculation. Online statistics from selected Internet resources and clinician opinion were used to assess the use of clinical calculators. RESULTS: One hundred seventy-six readily available calculators in 4 categories, 6 primary specialties, and 40 subspecialties were identified. The goals of calculation included prediction, severity, risk estimation, diagnostic, and decision-making aid. A combination of summation logic with cutoffs or rules was the most frequent mechanism of computation. Combined results, online resources, statistics, and clinician opinion identified 13 most utilized calculators. CONCLUSION: Although not an exhaustive list, a total of 176 validated calculators were identified, classified, and evaluated for usefulness. Most of these calculators are used for adult patients in the critical care or internal medicine settings. Thirteen of 176 clinical calculators were determined to be useful in our institution. All of these calculators have an interface for manual input.
OBJECTIVE: Clinical calculators are widely used in modern clinical practice, but are not generally applied to electronic health record (EHR) systems. Important barriers to the application of these clinical calculators into existing EHR systems include the need for real-time calculation, human-calculator interaction, and data source requirements. The objective of this study was to identify, classify, and evaluate the use of available clinical calculators for clinicians in the hospital setting. METHODS: Dedicated online resources with medical calculators and providers of aggregated medical information were queried for readily available clinical calculators. Calculators were mapped by clinical categories, mechanism of calculation, and the goal of calculation. Online statistics from selected Internet resources and clinician opinion were used to assess the use of clinical calculators. RESULTS: One hundred seventy-six readily available calculators in 4 categories, 6 primary specialties, and 40 subspecialties were identified. The goals of calculation included prediction, severity, risk estimation, diagnostic, and decision-making aid. A combination of summation logic with cutoffs or rules was the most frequent mechanism of computation. Combined results, online resources, statistics, and clinician opinion identified 13 most utilized calculators. CONCLUSION: Although not an exhaustive list, a total of 176 validated calculators were identified, classified, and evaluated for usefulness. Most of these calculators are used for adult patients in the critical care or internal medicine settings. Thirteen of 176 clinical calculators were determined to be useful in our institution. All of these calculators have an interface for manual input.
Authors: Matthew Moll; Dandi Qiao; Elizabeth A Regan; Gary M Hunninghake; Barry J Make; Ruth Tal-Singer; Michael J McGeachie; Peter J Castaldi; Raul San Jose Estepar; George R Washko; James M Wells; David LaFon; Matthew Strand; Russell P Bowler; MeiLan K Han; Jorgen Vestbo; Bartolome Celli; Peter Calverley; James Crapo; Edwin K Silverman; Brian D Hobbs; Michael H Cho Journal: Chest Date: 2020-04-27 Impact factor: 9.410
Authors: Anupam B Kharbanda; Gabriela Vazquez-Benitez; Dustin W Ballard; David R Vinson; Uli K Chettipally; Mamata V Kene; Steven P Dehmer; Richard G Bachur; Peter S Dayan; Nathan Kuppermann; Patrick J O'Connor; Elyse O Kharbanda Journal: Pediatrics Date: 2018-03-13 Impact factor: 7.124