Practice guidelines and clinical risk assessment models: is it time to reform?

Sepehrvand, Nariman; Pakdel, Firouz Ghaderi; Rahimi-Rad, Mohammad Hossein; Moosavi-Toomatari, Babak; Bazargan‐Hejazi, Shahrzad

doi:10.1186/1472-6947-11-63

Cited by 6 publications

(4 citation statements)

References 21 publications

(31 reference statements)

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“…With the growing volume of evidence and expanding number of risk prediction models in clinical practice each day, it becomes paramount to find and incorporate innovative approaches to keep clinicians up to speed in using the evidence and facilitating decision-making for them. Clinical decision support tools, 21,22 electronic alerts, 23,24 mobile apps, 25 and real-time automatic calculators connected to electronic medical records have evolved significantly with the goal of using the best evidence and improving the clinical practice for our patients and healthcare professionals, and have the potential to become an inseparable part of the future's clinical practice.…”

Section: Discussionmentioning

confidence: 99%

External Validation and Refinement of Emergency Heart Failure Mortality Risk Grade Risk Model in Patients With Heart Failure in the Emergency Department

et al. 2019

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Background: Emergency Heart Failure Mortality Risk Grade (EHMRG) assesses the risk of death within 7 days of emergency department (ED) presentation for patients with acute heart failure (AHF). We aimed to externally validate and refine the EHMRG model in patients who presented to the ED with AHF. Methods: We performed a cohort study using administrative data for all ambulance-transported patients from Alberta (2012)(2013)(2014)(2015)(2016) presenting to the ED with a primary diagnosis of AHF. Results: Among 6708 patients with AHF, the 7-day mortality was 0.0%, 0.8%, 1.6%, 4.0%, 4.2%, and 12.0% across EHMRG risk categories (1-4, 5A and 5B). The EHMRG score had a c-index of 0.73 (95% confidence interval [CI], 0.71-0.76) for 7-day mortality and 0.71 (95% CI, 0.70-0.73) for 30-day mortality, but lower c-statistics for other outcomes (0.61-0.67). The inclusion of natriuretic peptides to the EHMRG model improved prediction (Net Reclassification Improvement, 0.268; 95% CI, 0.173-0.363; P < 0.01) for 7-day mortality, as did the R ESUM E

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Section: Discussionmentioning

confidence: 99%

External Validation and Refinement of Emergency Heart Failure Mortality Risk Grade Risk Model in Patients With Heart Failure in the Emergency Department

et al. 2019

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“…Strategies for improvement of adherence to VTE prophylaxis such as laminated cards and educational training were not adequate to improve outcomes and reduce rates of VTE [4] . Risk stratifi cation in the absence of a RAM tool can be challenging [27] . Clinical decision support system is an appropriate and easily accessible method for improving qualitative health care.…”

Section: Venous Thromboembolism Prevalence Risk Factors and Risk Assessment Models Vary Between Obstetrics And Gynecology Patientsmentioning

confidence: 99%

Validation of a Smartphone Application for Assessment of Risk of Venous Thromboembolism in Obstetrics and Gynecology

Zaher

Adam

2017

JKAU Med Sci

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Venous thromboembolism is a serious but potentially preventable condition. However, morbidity and mortality occur due to lack of thrombo-prophylaxis. Obstetrics and gynecology patients are at risk for developing venous thromboembolism. To improve adherence to thromboprophylaxis in this patient population, we developed a smart phone clinical decision support system designed to assess risk score and recommend thromboprophylaxis. Clinical data were collected by review of electronic medical charts. The risk score and thromboprophylaxis recommendations were calculated for each patient by clinical decision support system and by an expert hematologist and results were compared for correlation. We hypothesize that the system is a valid tool for risk assessment in obstetrics and gynecology patients. A total of 188 female patients admitted at King Abdulaziz University Hospital between December 2015 and March 2016 were included. One hundred and sixteen were gynecology, and 72 were obstetric patients with a mean age of 40.7 (± 12.8). The risk score obtained by the system showed a strong correlation with that of the expert hematologist’s opinion (r = 83%). The clinical decision support system showed a good correlation for thromboprophylaxis decision as well. Accessibility and ease of use of clinical decision support system can improve the clinical outcome of hospitalized patients.

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“…113,114 This approach is being applied to preventing a complication of stroke, venous thromboembolism. 115 Alternatives to Clinical Practice Guidelines Some ventures that might eventually evolve into guidelines begin slowly as a structured approach to evaluating a child with a symptom or set of symptoms. 116 These lack the imprimatur of any organization and are not expected to be viewed as preferred to any other set of recommendations.…”

Section: Risk Assessmentmentioning

confidence: 99%

Clinical Practice Guidelines and Practice Parameters for the Child Neurologist

2013

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Guidance about how to practice child neurology has been around for decades. Recently, however, clinical practice guidelines, practice parameters, and standardized clinical assessment and management plans are gaining increasing attention. This overview, written for child neurologists, addresses such issues as the following: what are clinical practice guidelines, why are they needed, how are they created, how should they be created, how well are they accepted and adhered to, what influences acceptance and adherence, do guidelines improve care, do they reduce costs, will they be viewed by courts as the standard of care, how can they be updated and improved, and are there better alternatives?

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Practice guidelines and clinical risk assessment models: is it time to reform?

Cited by 6 publications

References 21 publications

External Validation and Refinement of Emergency Heart Failure Mortality Risk Grade Risk Model in Patients With Heart Failure in the Emergency Department

External Validation and Refinement of Emergency Heart Failure Mortality Risk Grade Risk Model in Patients With Heart Failure in the Emergency Department

Validation of a Smartphone Application for Assessment of Risk of Venous Thromboembolism in Obstetrics and Gynecology

Clinical Practice Guidelines and Practice Parameters for the Child Neurologist

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