Medical calculators: Prevalence, and barriers to use

Medical calculators derived synthetic cohorts: a novel method for generating synthetic patient data

This study shows that we can use synthetic cohorts created from medical risk calculators to gain insights into how risk estimations, clinical reasoning, data-driven subgrouping, and the confidence in risk calculator scores are connected. When prediction variables aren't evenly distributed in these synthetic cohorts, they can be used to group similar cases together, revealing new insights about how cohorts behave. We also found that the confidence in predictions made by these calculators can vary depending on patient characteristics. This suggests that it might be beneficial to include a "normalized confidence" score in future versions of these calculators for healthcare professionals. We plan to explore this idea further in our upcoming research.

Digital Response to Physical Crises: The Role of an E-Health Platform in the 2023 Southern Turkey Earthquakes

The catastrophic earthquakes that struck Southern Turkey in 2023 highlighted the pressing need for effective disaster management strategies. The unprecedented scale of the crisis tested the robustness of traditional healthcare responses and highlighted the potential of e-health solutions. Despite the deployment of Emergency Medical Teams, initial responders - primarily survivors of the earthquakes - faced an enormous challenge due to their lack of training in mass-casualty situations. An e-health platform was introduced to support these first responders, offering tools for drug calculations, case management guidelines, and a deep learning model for pediatric X-ray analysis. This commentary presents an analysis of the platform's use and contributes to the growing discourse on integrating digital health technologies in disaster response and management.

Identifying barriers and facilitators to successful implementation of computerized clinical decision support systems in hospitals: a NASSS framework-informed scoping review

BACKGROUND

Successful implementation and utilization of Computerized Clinical Decision Support Systems (CDSS) in hospitals is complex and challenging. Implementation science, and in particular the Nonadoption, Abandonment, Scale-up, Spread and Sustainability (NASSS) framework, may offer a systematic approach for identifying and addressing these challenges. This review aimed to identify, categorize, and describe barriers and facilitators to CDSS implementation in hospital settings and map them to the NASSS framework. Exploring the applicability of the NASSS framework to CDSS implementation was a secondary aim.

METHODS

Electronic database searches were conducted (21 July 2020; updated 5 April 2022) in Ovid MEDLINE, Embase, Scopus, PyscInfo, and CINAHL. Original research studies reporting on measured or perceived barriers and/or facilitators to implementation and adoption of CDSS in hospital settings, or attitudes of healthcare professionals towards CDSS were included. Articles with a primary focus on CDSS development were excluded. No language or date restrictions were applied. We used qualitative content analysis to identify determinants and organize them into higher-order themes, which were then reflexively mapped to the NASSS framework.

RESULTS

Forty-four publications were included. These comprised a range of study designs, geographic locations, participants, technology types, CDSS functions, and clinical contexts of implementation. A total of 227 individual barriers and 130 individual facilitators were identified across the included studies. The most commonly reported influences on implementation were fit of CDSS with workflows (19 studies), the usefulness of the CDSS output in practice (17 studies), CDSS technical dependencies and design (16 studies), trust of users in the CDSS input data and evidence base (15 studies), and the contextual fit of the CDSS with the user's role or clinical setting (14 studies). Most determinants could be appropriately categorized into domains of the NASSS framework with barriers and facilitators in the "Technology," "Organization," and "Adopters" domains most frequently reported. No determinants were assigned to the "Embedding and Adaptation Over Time" domain.

CONCLUSIONS

This review identified the most common determinants which could be targeted for modification to either remove barriers or facilitate the adoption and use of CDSS within hospitals. Greater adoption of implementation theory should be encouraged to support CDSS implementation.

Clinical Algorithms with Race: An Online Database

Some clinical algorithms incorporate a person's race, ethnicity, or both as an input variable or predictor in determining diagnoses, prognoses, treatment plans, or risk assessments. Inappropriate use of race and ethnicity in clinical algorithms at the point of care may exacerbate health disparities and promote harmful practices of race-based medicine. This article describes a comprehensive search of online resources, the scientific literature, and the FDA Drug Label Information that uncovered 39 race-based risk calculators, six laboratory test results with race-based reference ranges, one race-based therapy recommendation, and 15 medications with race-based recommendations. These clinical algorithms based on race are freely accessible through an online database. This resource aims to raise awareness about the use of race-based clinical algorithms and track the progress made toward eradicating the inappropriate use of race. The database will be actively updated to include clinical algorithms based on race that were previously omitted, along with additional characteristics of these algorithms.

Usage Patterns of Web-Based Stroke Calculators in Clinical Decision Support: Retrospective Analysis

Background

Clinical scores are frequently used in the diagnosis and management of stroke. While medical calculators are increasingly important support tools for clinical decisions, the uptake and use of common medical calculators for stroke remain poorly characterized.

Objective

We aimed to describe use patterns in frequently used stroke-related medical calculators for clinical decisions from a web-based support system.

Methods

We conducted a retrospective study of calculators from MDCalc, a web-based and mobile app–based medical calculator platform based in the United States. We analyzed metadata tags from MDCalc’s calculator use data to identify all calculators related to stroke. Using relative page views as a measure of calculator use, we determined the 5 most frequently used stroke-related calculators between January 2016 and December 2018. For all 5 calculators, we determined cumulative and quarterly use, mode of access (eg, app or web browser), and both US and international distributions of use. We compared cumulative use in the 2016-2018 period with use from January 2011 to December 2015.

Results

Over the study period, we identified 454 MDCalc calculators, of which 48 (10.6%) were related to stroke. Of these, the 5 most frequently used calculators were the CHA₂DS₂-VASc score for atrial fibrillation stroke risk calculator (5.5% of total and 32% of stroke-related page views), the Mean Arterial Pressure calculator (2.4% of total and 14.0% of stroke-related page views), the HAS-BLED score for major bleeding risk (1.9% of total and 11.4% of stroke-related page views), the National Institutes of Health Stroke Scale (NIHSS) score calculator (1.7% of total and 10.1% of stroke-related page views), and the CHADS₂ score for atrial fibrillation stroke risk calculator (1.4% of total and 8.1% of stroke-related page views). Web browser was the most common mode of access, accounting for 82.7%-91.2% of individual stroke calculator page views. Access originated most frequently from the most populated regions within the United States. Internationally, use originated mostly from English-language countries. The NIHSS score calculator demonstrated the greatest increase in page views (238.1% increase) between the first and last quarters of the study period.

Conclusions

The most frequently used stroke calculators were the CHA₂DS₂-VASc, Mean Arterial Pressure, HAS-BLED, NIHSS, and CHADS₂. These were mainly accessed by web browser, from English-speaking countries, and from highly populated areas. Further studies should investigate barriers to stroke calculator adoption and the effect of calculator use on the application of best practices in cerebrovascular disease.

Accuracy of freely available online GFR calculators using the CKD-EPI equation

Purpose

Estimated glomerular filtration rate (eGFR) as calculated by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation is used for detection of chronic kidney disease and drug dose adjustment. The purpose of the present study was to investigate the accuracy of freely available eGFR online calculators.

Methods

All identified CKD-EPI online calculators were run with five reference cases differing in age, sex, serum creatinine, and ethnicity. Conversion from eGFR_indexed (unit ml/min per 1.73 m²) to eGFR_non-indexed (unit ml/min) and creatinine unit from milligramme/decilitre to micromole/litre was checked, if available.

Results

Only 36 of 47 calculators (76.6%) produced accurate eGFR results for all reference cases. Eight of 47 (17.0%) calculators were considered as faulty because of errors relating to ethnicity (4 calculators), to conversion of the eGFR unit (2 calculators), to erroneous eGFR values without obvious explanation (2 calculators), to conversion of the creatinine unit (1 calculator), and to an error in the eGFR unit displayed (1 calculator). Overall, 28 errors were found (range 59 to 147% of the correct eGFR value), the majority concerning calculation of eGFR_indexed and the conversion to eGFR_non-indexed. Only 7 of 47 (14.9%) calculators offered conversion of the eGFR unit.

Conclusions

Erroneous calculations that might lead to inappropriate clinical decision-making were found in 8 of 47 calculators. Thus, online calculators should be evaluated more thoroughly after implementation. Conversion of eGFR units that might be needed for drug dose adjustments should be implemented more often.

Electronic supplementary material

The online version of this article (10.1007/s00228-020-02932-x) contains supplementary material, which is available to authorized users.

Novel Calculators for Risk Stratification in Hepatocellular Carcinoma: A Concise Review

Among clinicians, the users of medical calculators have expanded in recent years to an unprecedented number. The usefulness of some of these calculators is sometimes debatable, and experienced professionals may at times be right in avoiding their use; however, many may simply be unaware of the very existence of medical calculators applicable to their field of interest. The authors felt that this latter scenario might possibly apply to hepatocellular carcinoma (HCC). Hence, the authors concisely reviewed 10 free online medical calculators proposed in the last 8 years, categorizing them on the basis of the purpose for which they were developed (risk of harboring or developing HCC, N=4; prognostication in established HCC, N=6). In addition, the authors tried to establish the success each calculator has had so far in the medical community, by 2 criteria: having been included in the more popular app of medical calculators and being highly cited in the scientific literature.