Background: TEXTMEDS (Text Messages to Improve Medication Adherence and Secondary Prevention After Acute Coronary Syndrome) examined the effects of text message–delivered cardiac education and support on medication adherence after an acute coronary syndrome. Methods: TEXTMEDS was a single-blind, multicenter, randomized controlled trial of patients after acute coronary syndrome. The control group received usual care (secondary prevention as determined by the treating clinician); the intervention group also received multiple motivational and supportive weekly text messages on medications and healthy lifestyle with the opportunity for 2-way communication (text or telephone). The primary end point of self-reported medication adherence was the percentage of patients who were adherent, defined as >80% adherence to each of up to 5 indicated cardioprotective medications, at both 6 and 12 months. Results: A total of 1424 patients (mean age, 58 years [SD, 11]; 79% male) were randomized from 18 Australian public teaching hospitals. There was no significant difference in the primary end point of self-reported medication adherence between the intervention and control groups (relative risk, 0.93 [95% CI, 0.84–1.03]; P =0.15). There was no difference between intervention and control groups at 12 months in adherence to individual medications (aspirin, 96% vs 96%; β-blocker, 84% vs 84%; angiotensin-converting enzyme inhibitor/angiotensin receptor blocker, 77% vs 80%; statin, 95% vs 95%; second antiplatelet, 84% vs 84% [all P >0.05]), systolic blood pressure (130 vs 129 mm Hg; P =0.26), low-density lipoprotein cholesterol (2.0 vs 1.9 mmol/L; P =0.34), smoking ( P =0.59), or exercising regularly (71% vs 68%; P =0.52). There were small differences in lifestyle risk factors in favor of intervention on body mass index <25 kg/m 2 (21% vs 18%; P =0.01), eating ≥5 servings per day of vegetables (9% vs 5%; P =0.03), and eating ≥2 servings per day of fruit (44% vs 39%; P =0.01). Conclusions: A text message–based program had no effect on medical adherence but small effects on lifestyle risk factors. Registration: URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=364448 ; Unique identifier: ANZCTR ACTRN12613000793718.
Objective A growing number of evaluation frameworks have emerged over recent years addressing the unique benefits and risk profiles of new classes of digital health technologies (DHTs). This systematic review aims to identify relevant frameworks and synthesize their recommendations into DHT-specific content to be considered when performing Health Technology Assessments (HTAs) for DHTs that manage chronic noncommunicable disease at home. Methods Searches were undertaken of Medline, Embase, Econlit, CINAHL, and The Cochrane Library (January 2015 to March 2020), and relevant gray literature (January 2015 to August 2020) using keywords related to HTA, evaluation frameworks, and DHTs. Included framework reference lists were searched from 2010 until 2015. The EUNetHTA HTA Core Model version 3.0 was selected as a scaffold for content evaluation. Results Forty-four frameworks were identified, mainly covering clinical effectiveness (n = 30) and safety (n = 23) issues. DHT-specific content recommended by framework authors fell within 28 of the 145 HTA Core Model issues. A further twenty-two DHT-specific issues not currently in the HTA Core Model were recommended. Conclusions Current HTA frameworks are unlikely to be sufficient for assessing DHTs. The development of DHT-specific content for HTA frameworks is hampered by DHTs having varied benefit and risk profiles. By focusing on DHTs that actively monitor/treat chronic noncommunicable diseases at home, we have extended DHT-specific content to all nine HTA Core Model domains. We plan to develop a supplementary evaluation framework for designing research studies, undertaking HTAs, and appraising the completeness of HTAs for DHTs.
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.
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