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Quantitative examination of video-recorded NHS Health Checks: comparison of the use of QRISK2 versus JBS3 cardiovascular risk calculators.

ABSTRACT: OBJECTIVES:Quantitatively examine the content of National Health Service Health Check (NHSHC), patient-practitioner communication balance and differences when using QRISK2 versus JBS3 cardiovascular disease (CVD) risk calculators. DESIGN:RIsk COmmunication in NHSHC was a qualitative study with quantitative process evaluation, comparing NHSHC using QRISK2 or JBS3. We present data from the quantitative process evaluation. SETTING AND PARTICIPANTS:Twelve general practices in the West Midlands (England) conducted NHSHC using JBS3 or QRISK2 (6/group). Patients were eligible for NHSHC based on national criteria (aged 40-74, no existing cardiovascular-related diagnoses, not taking statins). Recruitment was stratified by patients' age, gender and ethnicity. METHODS:Video recordings of NHSHC were coded, second-by-second, to quantify who was speaking and what was being discussed. Outcomes included consultation duration, practitioner verbal dominance (ratio of practitioner:patient speaking time (pr:pt ratio)) and proportion of time discussing CVD risk, risk factors and risk management. RESULTS:173 video-recorded NHSHC were analysed (73 QRISK, 100 JBS3). The sample was 51% women, 83% white British, with approximately equal proportions across age groups. NHSHC duration varied greatly (6.8-38.0?min). Most (60%) lasted less than 20?min. On average, CVD risk was discussed for less than 2?min (9.06%±4.30% of consultation time). There were indications that, compared with NHSHC using JBS3, those with QRISK2 involved less CVD risk discussion (JBS3 M=10.24%, CI: 8.01-12.48 vs QRISK2 M=7.44%, CI: 5.29-9.58) and were more verbally dominated by practitioners (pr:pt ratio JBS3 M=3.21%, CI: 2.44-3.97 vs QRISK2=2.35%, CI: 1.89-2.81). The largest proportion of NHSHC time was spent discussing causal risk factors (M=37.54%, CI: 32.92-42.17). CONCLUSIONS:There was wide variation in NHSHC duration. Many were short and practitioner-dominated, with little time discussing CVD risk. JBS3 appears to extend CVD risk discussion and patient contribution. Qualitative examination of how it is used is necessary to fully understand the potential benefits of these differences. TRIAL REGISTRATION NUMBER:ISRCTN10443908.

SUBMITTER: Gidlow CJ

PROVIDER: S-EPMC7520846 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Quantitative examination of video-recorded NHS Health Checks: comparison of the use of QRISK2 versus JBS3 cardiovascular risk calculators.

Gidlow Christopher J CJ Ellis Naomi J NJ Cowap Lisa L Riley Victoria A VA Crone Diane D Cottrell Elizabeth E Grogan Sarah S Chambers Ruth R Clark-Carter David D

BMJ open 20200925 9

<h4>Objectives</h4>Quantitatively examine the content of National Health Service Health Check (NHSHC), patient-practitioner communication balance and differences when using QRISK2 versus JBS3 cardiovascular disease (CVD) risk calculators.<h4>Design</h4>RIsk COmmunication in NHSHC was a qualitative study with quantitative process evaluation, comparing NHSHC using QRISK2 or JBS3. We present data from the quantitative process evaluation.<h4>Setting and participants</h4>Twelve general practices in t ...[more]

PMID: 32978197

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Project description:Background:Statistically derived cardiovascular risk calculators (CVRC) that use conventional risk factors, generally underestimate or overestimate the risk of cardiovascular disease (CVD) or stroke events primarily due to lack of integration of plaque burden. This study investigates the role of machine learning (ML)-based CVD/stroke risk calculators (CVRCML) and compares against statistically derived CVRC (CVRCStat) based on (I) conventional factors or (II) combined conventional with plaque burden (integrated factors). Methods:The proposed study is divided into 3 parts: (I) statistical calculator: initially, the 10-year CVD/stroke risk was computed using 13 types of CVRCStat (without and with plaque burden) and binary risk stratification of the patients was performed using the predefined thresholds and risk classes; (II) ML calculator: using the same risk factors (without and with plaque burden), as adopted in 13 different CVRCStat, the patients were again risk-stratified using CVRCML based on support vector machine (SVM) and finally; (III) both types of calculators were evaluated using AUC based on ROC analysis, which was computed using combination of predicted class and endpoint equivalent to CVD/stroke events. Results:An Institutional Review Board approved 202 patients (156 males and 46 females) of Japanese ethnicity were recruited for this study with a mean age of 69±11 years. The AUC for 13 different types of CVRCStat calculators were: AECRS2.0 (AUC 0.83, P<0.001), QRISK3 (AUC 0.72, P<0.001), WHO (AUC 0.70, P<0.001), ASCVD (AUC 0.67, P<0.001), FRScardio (AUC 0.67, P<0.01), FRSstroke (AUC 0.64, P<0.001), MSRC (AUC 0.63, P=0.03), UKPDS56 (AUC 0.63, P<0.001), NIPPON (AUC 0.63, P<0.001), PROCAM (AUC 0.59, P<0.001), RRS (AUC 0.57, P<0.001), UKPDS60 (AUC 0.53, P<0.001), and SCORE (AUC 0.45, P<0.001), while the AUC for the CVRCML with integrated risk factors (AUC 0.88, P<0.001), a 42% increase in performance. The overall risk-stratification accuracy for the CVRCML with integrated risk factors was 92.52% which was higher compared all the other CVRCStat. Conclusions:ML-based CVD/stroke risk calculator provided a higher predictive ability of 10-year CVD/stroke compared to the 13 different types of statistically derived risk calculators including integrated model AECRS 2.0.

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Quantitative examination of video-recorded NHS Health Checks: comparison of the use of QRISK2 versus JBS3 cardiovascular risk calculators.

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Quantitative examination of video-recorded NHS Health Checks: comparison of the use of QRISK2 versus JBS3 cardiovascular risk calculators.

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