AI-Enhanced Reconstruction of the 12-Lead Electrocardiogram via 3-Leads with Accurate Clinical Assessment.

The 12-lead electrocardiogram (ECG) is an integral component to the diagnosis of a multitude of cardiovascular conditions. It is performed using a complex set of skin surface electrodes, limiting its use outside traditional clinical settings. We developed an artificial intelligence algorithm, trained over 600,000 clinically acquired ECGs, to explore whether fewer leads as input are sufficient to reconstruct a full 12-lead ECG. Two limb leads (I and II) and one precordial lead (V3) were required to generate a reconstructed synthetic 12-lead ECG highly correlated with the original ECG. An automatic algorithm for detection of acute myocardial infarction (MI) performed similarly for original and reconstructed ECGs (AUC=0.94). When interpreted by cardiologists, reconstructed ECGs achieved an accuracy of 81.4±5.0% in identifying ST elevation MI, comparable with the original 12-lead ECGs (accuracy 84.6±4.6%). These results will impact development efforts to innovate ECG acquisition methods with simplified tools in non-specialized settings.

Trends in Prices of Popular Brand-Name Prescription Drugs in the United States.

Importance: High and continually increasing pharmaceutical drug spending is a major health and health policy concern in the United States. Objective: To demonstrate trends in prices among popular brand-name prescription drugs. Design, Setting, and Participants: This economic evaluation of drug prices focuses on 49 top-selling brand-name medications in the United States. Pharmacy claims data from January 1, 2012, through December 31, 2017, were obtained from Blue Cross Blue Shield Axis, a database that includes data from more than 35 million individuals with private pharmaceutical insurance. Drugs that exceeded $500 million in US sales or $1 billion in worldwide sales were examined. Main Outcomes and Measures: The median sum of out-of-pocket and insurance costs paid by patients or insurers for common prescriptions, presented annually and monthly, was the primary outcome. Results: In total, 132 brand-name prescription drugs were identified in 2017 that met the inclusion criteria. Of this total, the study focused on 49 top-selling drugs that exceeded 100 000 pharmacy claims. Substantial cost increases among these drugs was near universal, with a 76% median cost increase from January 2012 through December 2017, and almost all drugs (48 [98%]) displaying regular annual or biannual price increases. Of the 36 drugs that have been available since 2012, 28 (78%) have seen an increase in insurer and out-of-pocket costs by more than 50%, and 16 (44%) have more than doubled in price. Insulins (ie, Novolog, Humalog, and Lantus) and tumor necrosis factor inhibitors (ie, Humira and Enbrel) demonstrated highly correlated price increases, coinciding with some of the largest growth in drug costs. Relative price changes did not differ between drugs that entered the market in the past 3 to 6 years and those that have been on the market longer (number of drugs, 13 vs 36; median, 29% increase from January 2015 through December 2017; P = .81) nor between drugs with or without a Food and Drug Administration-approved therapeutic equivalent (number of drugs, 17 vs 32; median, 79% vs 73%; P = .21). Changes in prices paid were highly correlated with third-party estimates of changes in drug net prices (ρ = 0.55; P = 3.8 × 10-5), suggesting that the current rebate system, which incentivizes high list prices and greater reliance on rebates, increases overall costs. Conclusions and Relevance: The growth of drug spending in the United States associated with government-protected market exclusivity is likely to continue; greater price transparency is warranted.

A decade of digital medicine innovation.

The field of digital medicine has matured over the past decade, but validation will require careful randomized, controlled clinical trials.

Real world usage characteristics of a novel mobile health self-monitoring device: Results from the Scanadu Consumer Health Outcomes (SCOUT) Study.

A wide range of personal wireless health-related sensor devices are being developed with hope of improving health management. Factors related to effective user engagement, however, are not well-known. We sought to identify factors associated with consistent long-term use of the Scanadu Scout multi-parameter vital sign monitor among individuals who invested in the device through a crowd-funding campaign. Email invitations to join the study were sent to 4525 crowd-funding participants from the US. Those completing a baseline survey were sent a device with follow-up surveys at 3, 12, and 18 months. Of 3872 participants receiving a device, 3473 used it during Week 1, decreasing to 1633 (47 percent) in Week 2. Median time from first use of the device to last use was 17 weeks (IQR: 5-51 weeks) and median uses per week was 1.0 (IQR: 0.6-2.0). Consistent long-term use (defined as remaining in the study at least 26 weeks with at least 3 recordings per week during at least 80% of weeks) was associated with older age, not having children in the household, and frequent use of other medical devices. In the subset of participants answering the 12-month survey (n = 1222), consistent long-term users were more likely to consider the device easy to use and to share results with a healthcare provider. Thirty percent of this subset overall reported improved diet or exercise habits and 25 percent considered medication changes in response to device results. The study shows that even among investors in a device, frequency of device usage fell off rapidly. Understanding how to improve the value of information from personal health-related sensors will be critical to their successful implementation in care.

Characteristics of the modern-day physician house call.

Many barriers to primary healthcare accessibility in the United States exist including an increased opportunity cost associated with seeking primary care. New models of healthcare delivery aimed at addressing these problems are emerging. The potential impact that on-demand primary care physician house calls services can have on healthcare accessibility, patient care, and satisfaction by both patients and physicians is poorly characterized.We performed a retrospective observational analysis on data from 13,849 patients who utilized Heal, Inc, an application (app)-based, on-demand house calls platform between August 2016 and July 2017. We assessed house call wait time and visit duration, diagnoses by International Classification of Diseases, tenth revision, Inc (ICD10) codes, and house call outcomes by post-visit prescription and lab requests, and patient satisfaction survey.Patients who utilized this physician house call service had a bimodal age distribution peaking at age 1 year and 36 years. Same day acute sick exams (93.9% of pediatric (Ped) and 66.9% of adult requests) for fever and/or acute upper respiratory infection represented the most common use. The mean wait time for as soon as possible house calls were 96.1 minutes, with an overall mean house call duration of 27.1 minutes. A house call was primarily chosen over an Urgent Care Clinic or Doctor's office (46.2% and 41.6% of respondents, respectively), due to convenience or fastest appointment available (69.6% and 33.8% of respondents, respectively). Most survey respondents (94.2%) would schedule house calls again.On-demand physician house calls programs can expand access options to primary healthcare, primarily used by younger individuals with acute illness and preference for a smartphone app-based home visit.

Rationale and design of a home-based trial using wearable sensors to detect asymptomatic atrial fibrillation in a targeted population: The mHealth Screening To Prevent Strokes (mSToPS) trial.

Efficient methods for screening populations for undiagnosed atrial fibrillation (AF) are needed to reduce its associated mortality, morbidity, and costs. The use of digital technologies, including wearable sensors and large health record data sets allowing for targeted outreach toward individuals at increased risk for AF, might allow for unprecedented opportunities for effective, economical screening. The trial's primary objective is to determine, in a real-world setting, whether using wearable sensors in a risk-targeted screening population can diagnose asymptomatic AF more effectively than routine care. Additional key objectives include (1) exploring 2 rhythm-monitoring strategies-electrocardiogram-based and exploratory pulse wave-based-for detection of new AF, and (2) comparing long-term clinical and resource outcomes among groups. In all, 2,100 Aetna members will be randomized 1:1 to either immediate or delayed monitoring, in which a wearable patch will capture a single-lead electrocardiogram during the first and last 2 weeks of a 4-month period beginning immediately or 4 months after enrollment, respectively. An observational, risk factor-matched control group (n = 4,000) will be developed from members who did not receive an invitation to participate. The primary end point is the incidence of new AF in the immediate- vs delayed-monitoring arms at the end of the 4-month monitoring period. Additional efficacy and safety end points will be captured at 1 and 3 years. The results of this digital medicine trial might benefit a substantial proportion of the population by helping identify and refine screening methods for undiagnosed AF.

Prognostic value of estimated functional capacity incremental to cardiac biomarkers in stable cardiac patients.

BACKGROUND: Few studies have investigated functional capacity self-assessment tools in either prediction of future major adverse cardiac outcomes beyond all-cause mortality or direct comparisons with clinically available biomarkers. METHODS AND RESULTS: We estimated functional capacity using the Duke Activity Status Index (DASI) questionnaire in 8987 sequential stable patients without acute coronary syndrome who were undergoing elective diagnostic coronary angiography with 3-year follow-up of major adverse cardiac events (death, nonfatal myocardial infarction, or stroke). A low DASI score provided independent prediction of a 4.8-fold increase in future risk of incident major adverse cardiac events at 3 years (quartiles 1 versus 4 hazard ratio [95% CI] 4.76 [4.03 to 5.61], P<0.001), and a 3.8-fold increased risk after adjusting for traditional risk factors (3.77 [3.15 to 4.51], P<0.001). The prognostic value of the DASI score was evident in both primary and secondary prevention cohorts, with and without heart failure, as well as high and low C-reactive protein and B-type natriuretic peptide levels. The DASI score reclassified 15% of patients (P<0.001) beyond traditional risk factors in predicting future MACE. CONCLUSION: A simple self-assessment tool of functional capacity in stable patients undergoing elective diagnostic cardiac evaluation provides independent and incremental prognostic value for prediction of both significant coronary angiographic disease and long-term adverse clinical events.

Characteristics of genomic test consumers who spontaneously share results with their health care provider.

The purpose of this study was to evaluate the characteristics of direct-to-consumer (DTC) genomic test consumers who spontaneously shared their test results with their health care provider. Utilizing data from the Scripps Genomic Health Initiative, we compared demographic, behavioral, and attitudinal characteristics of DTC genomic test consumers who shared their results with their physician or health care provider versus those who did not share. We also compared genomic risk estimates between the two groups. Of 2,024 individuals assessed at approximately 6 months post testing, 540 individuals (26.5%) reported sharing their results with their physician or health care provider. Those who shared were older (p < .001), had a higher income (p = .01), were more likely to be married (p = .005), and were more likely to identify with a religion (p = .004). As assessed prior to undergoing testing, sharers also reported higher levels of exercise (p = .003), lower fat intake (p = .02), fewer overall concerns about testing (p = .001), and fewer concerns related to the privacy of their genomic information (p = .03). The genomic disease risk estimates disclosed were not associated with sharing. Thus, in a DTC genomic testing context, physicians and other health care providers may be more likely to encounter patients who are more health conscious and have fewer concerns about the privacy of their genomic information. Genomic risk itself does not appear to be a primary determinant of sharing behavior among consumers.

Impact of direct-to-consumer genomic testing at long term follow-up.

BACKGROUND: There are few empirical data to inform the debate surrounding the use and regulation of direct-to-consumer (DTC) genome-wide disease risk tests. This study aimed to determine the long term psychological, behavioural, and clinical impacts of genomic risk testing for common disease. METHODS: The Scripps Genomic Health Initiative is a prospective longitudinal cohort study of adults who purchased the Navigenics Health Compass, a commercially available genomic test. Web based assessments were administered at baseline, short (3 months), and long term (1 year) follow-up. RESULTS: 2240 participants completed either or both follow-ups and a subset of 1325 completed long term follow-up. There were no significant differences from baseline in anxiety (p=0.50), fat intake (p=0.34), or exercise (p=0.39) at long term follow-up, and 96.8% of the sample had no test related distress. Longitudinal linear mixed model analyses were consistent with results of cross-sectional analyses. Screening test completion was associated with sharing genomic test results with a physician (36.0% shared; p<0.001) and perceived utility of the test (61.5% high perceived utility; p=0.002), but was not associated with the genomic risk estimate values themselves. CONCLUSIONS: Over a third of DTC genomic test recipients shared their results with their own physician during an approximate 1 year follow-up period, and this sharing was associated with higher screening test completion. Genomic testing was not associated with long term psychological risks, and most participants reportedly perceived the test to be of high personal utility.