Health technology assessment for digital health technologies

Health technology assessment (HTA) frameworks used for making public funding decisions on digital health technologies (DHTs) have not been informed by large stakeholder preference studies and rarely cover all nine domains of the widely used EUnetHTA “Core Model”. Our aim was to develop a literature-informed and stakeholder-prioritised checklist of DHT-specific considerations for DHTs that manage chronic disease that extends an internationally established HTA framework. We conducted two systematic reviews to identify: (i) DHT evaluation frameworks and (ii) primary research on DHTs published until 20 March 2020. Stakeholder prioritisation of issues was performed using a best-worst preference study among a broad cross-section of patients, carers, health professionals, and the general population in Australia, Canada, New Zealand, and the UK. Systematic review issues were prioritised and adapted for use as a practical checklist. DHT evaluation content was recommended by 44 identified frameworks for 28 of the 145 issues in the Core Model and for 22 new DHT-specific issues. A coverage assessment of 112 clinical studies of remote treatment and self-management DHTs for patients with cardiovascular disease or diabetes revealed that less than half covered DHT-specific content in all but one domain, or traditional HTA content in clinical effectiveness and ethical analysis. The preference survey of 1,251 stakeholders identified broad agreement on the 12 most important DHT attributes, six of which were related to safety. The most important attribute was “helps health professionals respond quickly when changes in patient care are needed”, which is not a focus of existing DHT HTA frameworks. Using the thesis-developed checklist in conjunction with the Core Model can enable users to perform a DHT-specific and comprehensive HTA on DHTs that manage chronic disease and can assist primary researchers to collect appropriate data to inform this HTA

Stakeholder preferences for attributes of digital health technologies to consider in health service funding

Objectives: Health service providers are currently making decisions on the public funding of digital health technologies (DHTs) for managing chronic diseases with limited understanding of stakeholder preferences for DHT attributes. This study aims to understand the community, patient/carer, and health professionals' preferences to help inform a prioritized list of evaluation criteria. Methods: An online best-worst scaling survey was conducted in Australia, New Zealand, Canada, and the United Kingdom to ascertain the relative importance of twenty-four DHT attributes among stakeholder groups using an efficient incomplete block design. The attributes were identified from a systematic review of DHT evaluation frameworks for consideration in a health technology assessment. Results were analyzed with multinomial models by stakeholder group and latent class. Results: A total of 1,251 participants completed the survey (576 general community members, 543 patients/carers, and 132 health professionals). Twelve attributes achieved a preference score above 50 percent in the stakeholder group model, predominantly related to safety but also covering technical features, effectiveness, ethics, and economics. Results from the latent class model supported this prioritization. Overall, connectedness with the patient's healthcare team seemed the most important; with Helps health professionals respond quickly when changes in patient care are needed as the most highly prioritized of all attributes. Conclusions: It is proposed that these prioritized twelve attributes be considered in all evaluations of DHTs that manage chronic disease, supplemented with a limited number of attributes that reflect the specific perspective of funders, such as equity of access, cost, and system-level implementation considerations

Development and validation of a risk score to predict unplanned hospital readmissions in ICU survivors:A data linkage study

Background: Intensive Care Unit (ICU) follow-up clinics are growing in popularity internationally; however, there is limited evidence as to which patients would benefit most from a referral to this service. Objectives: The objective of this study was to develop and validate a model to predict which ICU survivors are most likely to experience an unplanned hospital readmission or death in the year after hospital discharge and derive a risk score capable of identifying high-risk patients who may benefit from referral to follow-up services. Methods: A multicentre, retrospective observational cohort study using linked administrative data from eight ICUs was conducted in the state of New South Wales, Australia. A logistic regression model was developed for the composite outcome of death or unplanned readmission in the 12 months after discharge from the index hospitalisation. Results: 12,862 ICU survivors were included in the study, of which 5940 (46.2%) patients experienced unplanned readmission or death. Strong predictors of readmission or death included the presence of a pre-existing mental health disorder (odds ratio [OR]: 1.52, 95% confidence interval [CI]: 1.40–1.65), severity of critical illness (OR: 1.57, 95% CI: 1.39–1.76), and two or more physical comorbidities (OR: 2.39, 95% CI: 2.14–2.68). The prediction model demonstrated reasonable discrimination (area under the receiver operating characteristic curve: 0.68, 95% CI: 0.67–0.69) and overall performance (scaled Brier score: 0.10). The risk score was capable of stratifying patients into three distinct risk groups—high (64.05% readmitted or died), medium (45.77% readmitted or died), and low (29.30% readmitted or died). Conclusions: Unplanned readmission or death is common amongst survivors of critical illness. The risk score presented here allows patients to be stratified by risk level, enabling targeted referral to preventative follow-up services.</p

Diagnostic accuracy of handheld electrocardiogram devices in detecting atrial fibrillation in adults in community versus hospital settings : a systematic review and meta-analysis

With increasing use of handheld ECG devices for atrial fibrillation (AF) screening, it is important to understand their accuracy in community and hospital settings and how it differs among settings and other factors. A systematic review of eligible studies from community or hospital settings reporting the diagnostic accuracy of handheld ECG devices (ie, devices producing a rhythm strip) in detecting AF in adults, compared with a gold standard 12-lead ECG or Holter monitor, was performed. Bivariate hierarchical random-effects meta-analysis and meta-regression were performed using R V.3.6.0. The search identified 858 articles, of which 14 were included. Six studies recruited from community (n=6064 ECGs) and eight studies from hospital (n=2116 ECGs) settings. The pooled sensitivity was 89% (95% CI 81% to 94%) in the community and 92% (95% CI 83% to 97%) in the hospital. The pooled specificity was 99% (95% CI 98% to 99%) in the community and 95% (95% CI 90% to 98%) in the hospital. Accuracy of ECG devices varied: sensitivity ranged from 54.5% to 100% and specificity ranged from 61.9% to 100%. Meta-regression showed that setting (p=0.032) and ECG device type (p=0.022) significantly contributed to variations in sensitivity and specificity. The pooled sensitivity and specificity of single-lead handheld ECG devices were high. Setting and handheld ECG device type were significant factors of variation in sensitivity and specificity. These findings suggest that the setting including user training and handheld ECG device type should be carefully reviewed

Trends in modifiable risk factors amongst first presentation ST elevation myocardial infarction patients in a large longitudinal registry

Background: Recent studies suggest that the risk factor profile of patients presenting with ST elevation myocardial infarction (STEMI) is changing. Aim: The aim is to determine if there has been a shift of cardiovascular risk factors to cardiometabolic causes in the first presentation STEMI population. Method: We analysed data from a STEMI registry from a large tertiary referral percutaneous coronary intervention centre to determine the prevalence and trends of the modifiable risk factors of hypertension, diabetes, smoking and hypercholesterolaemia. Participants: Consecutive first presentation STEMI patients between January 2006 to December 2018. Results: Among the 2,366 patients included (mean age 59, SD 12.66, 80% male) the common risk factors were hypertension (47%), hypercholesterolaemia (47%) current smoking (42%) and diabetes (27%). Over the 13 years, patients with diabetes (20% to 26%, OR 1.09 per year, CI 1.06–1.11, p<0.001) and patients with no modifiable risk factors increased (9% to 17%, OR 1.08, CI 1.04–1.11, p<0.001). Concurrently there was a fall in prevalence of hypercholesterolaemia, (47% to 37%, OR 0.94 per year, CI 0.92–0.96, p<0.001) and smoking (44% to 41%, OR 0.94, CI 0.92–0.96, p<0.001) but no significant change in rates of hypertension (53% to 49%, OR 0.99, CI 0.97–1.01, p=0.25). Conclusion: The risk factor profile of first presentation STEMI has changed over time with a reduction in smoking and a concurrent rise in patients with no traditional risk factors. This suggests the mechanism of STEMI may be changing and further investigation of potential causal factors is warranted for the prevention and management of cardiovascular disease