EVIDENCE Publication Checklist for Studies Evaluating Connected Sensor Technologies: Explanation and Elaboration.

The EVIDENCE (EValuatIng connecteD sENsor teChnologiEs) checklist was developed by a multidisciplinary group of content experts convened by the Digital Medicine Society, representing the clinical sciences, data management, technology development, and biostatistics. The aim of EVIDENCE is to promote high quality reporting in studies where the primary objective is an evaluation of a digital measurement product or its constituent parts. Here we use the terms digital measurement product and connected sensor technology interchangeably to refer to tools that process data captured by mobile sensors using algorithms to generate measures of behavioral and/or physiological function. EVIDENCE is applicable to 5 types of evaluations: (1) proof of concept; (2) verification, (3) analytical validation, and (4) clinical validation as defined by the V3 framework; and (5) utility and usability assessments. Using EVIDENCE, those preparing, reading, or reviewing studies evaluating digital measurement products will be better equipped to distinguish necessary reporting requirements to drive high-quality research. With broad adoption, the EVIDENCE checklist will serve as a much-needed guide to raise the bar for quality reporting in published literature evaluating digital measurements products.

From the Patient Perspective, Consent Forms Fall Short of Providing Information to Guide Decision Making.

OBJECTIVE: This study aimed to gather qualitative feedback on patient perceptions of informed consent forms and elicit recommendations to improve readability and utility for enhanced patient safety and engagement in shared decision making. METHODS: Sixty interviews in personal interviews were conducted consisting of a literacy and numeracy assessment, a comprehension quiz to assess retention of key information, and open-ended questions to determine reactions, clarity of information, and suggestions for improvement. RESULTS: Although 68% of the participants had education beyond high school, many still missed comprehension questions and found the forms difficult to read. Recurrent suggestions included specific formatting changes to enhance readability, a need for additional sources of information, mixed attitudes toward inclusion of risk information, and the recognized importance of physician-patient conversations. CONCLUSIONS: This study provides evidence from the patient perspective that consent forms are too complex and fail to achieve comprehension. Future studies should be conducted using patients' suggestions for form redesign and inclusion of supplemental educational tools to optimize communication and safety to achieve more informed health care decision making.

Digital Measures That Matter to Patients: A Framework to Guide the Selection and Development of Digital Measures of Health.

BACKGROUND: With the rise of connected sensor technologies, there are seemingly endless possibilities for new ways to measure health. These technologies offer researchers and clinicians opportunities to go beyond brief snapshots of data captured by traditional in-clinic assessments, to redefine health and disease. Given the myriad opportunities for measurement, how do research or clinical teams know what they should be measuring? Patient engagement, early and often, is paramount to thoughtfully selecting what is most important. Regulators encourage stakeholders to have a patient focus but actionable steps for continuous engagement are not well defined. Without patient-focused measurement, stakeholders risk entrenching digital versions of poor traditional assessments and proliferating low-value tools that are ineffective, burdensome, and reduce both quality and efficiency in clinical care and research. SUMMARY: This article synthesizes and defines a sequential framework of core principles for selecting and developing measurements in research and clinical care that are meaningful for patients. We propose next steps to drive forward the science of high-quality patient engagement in support of measures of health that matter in the era of digital medicine. KEY MESSAGES: All measures of health should be meaningful, regardless of the product's regulatory classification, type of measure, or context of use. To evaluate meaningfulness of signals derived from digital sensors, the following four-level framework is useful: Meaningful Aspect of Health, Concept of Interest, Outcome to be measured, and Endpoint (exclusive to research). Incorporating patient input is a dynamic process that requires more than a single, transactional touch point but rather should be conducted continuously throughout the measurement selection process. We recommend that developers, clinicians, and researchers reevaluate processes for more continuous patient engagement in the development, deployment, and interpretation of digital measures of health.

An Evaluation of Biometric Monitoring Technologies for Vital Signs in the Era of COVID-19.

The novel coronavirus disease 2019 (COVID-19) global pandemic has shifted how many patients receive outpatient care. Telehealth and remote monitoring have become more prevalent, and measurements taken in a patient's home using biometric monitoring technologies (BioMeTs) offer convenient opportunities to collect vital sign data. Healthcare providers may lack prior experience using BioMeTs in remote patient care, and, therefore, may be unfamiliar with the many versions of BioMeTs, novel data collection protocols, and context of the values collected. To make informed patient care decisions based on the biometric data collected remotely, it is important to understand the engineering solutions embedded in the products, data collection protocols, form factors (physical size and shape), data quality considerations, and availability of validation information. This article provides an overview of BioMeTs available for collecting vital signs (temperature, heart rate, blood pressure, oxygen saturation, and respiratory rate) and discusses the strengths and limitations of continuous monitoring. We provide considerations for remote data collection and sources of validation information to guide BioMeT use in the era of COVID-19 and beyond.

Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs).

Digital medicine is an interdisciplinary field, drawing together stakeholders with expertize in engineering, manufacturing, clinical science, data science, biostatistics, regulatory science, ethics, patient advocacy, and healthcare policy, to name a few. Although this diversity is undoubtedly valuable, it can lead to confusion regarding terminology and best practices. There are many instances, as we detail in this paper, where a single term is used by different groups to mean different things, as well as cases where multiple terms are used to describe essentially the same concept. Our intent is to clarify core terminology and best practices for the evaluation of Biometric Monitoring Technologies (BioMeTs), without unnecessarily introducing new terms. We focus on the evaluation of BioMeTs as fit-for-purpose for use in clinical trials. However, our intent is for this framework to be instructional to all users of digital measurement tools, regardless of setting or intended use. We propose and describe a three-component framework intended to provide a foundational evaluation framework for BioMeTs. This framework includes (1) verification, (2) analytical validation, and (3) clinical validation. We aim for this common vocabulary to enable more effective communication and collaboration, generate a common and meaningful evidence base for BioMeTs, and improve the accessibility of the digital medicine field.

Erratum: Publisher Correction: Modernizing and designing evaluation frameworks for connected sensor technologies in medicine.

[This corrects the article DOI: 10.1038/s41746-020-0237-3.].

Modernizing and designing evaluation frameworks for connected sensor technologies in medicine.

This manuscript is focused on the use of connected sensor technologies, including wearables and other biosensors, for a wide range of health services, such as collecting digital endpoints in clinical trials and remotely monitoring patients in clinical care. The adoption of these technologies poses five risks that currently exceed our abilities to evaluate and secure these products: (1) validation, (2) security practices, (3) data rights and governance, (4) utility and usability; and (5) economic feasibility. In this manuscript we conduct a landscape analysis of emerging evaluation frameworks developed to better manage these risks, broadly in digital health. We then propose a framework specifically for connected sensor technologies. We provide a pragmatic guide for how to put this evaluation framework into practice, taking lessons from concepts in drug and nutrition labels to craft a connected sensor technology label.

A systematic review of feasibility studies promoting the use of mobile technologies in clinical research.

Mobile technologies, such as smart phone applications, wearables, ingestibles, and implantables, are increasingly used in clinical research to capture study endpoints. On behalf of the Clinical Trials Transformation Initiative, we aimed to conduct a systematic scoping review and compile a database summarizing pilot studies addressing mobile technology sensor performance, algorithm development, software performance, and/or operational feasibility, in order to provide a resource for guiding decisions about which technology is most suitable for a particular trial. Our systematic search identified 275 publications meeting inclusion criteria. From these papers, we extracted data including the medical condition, concept of interest captured by the mobile technology, outcomes captured by the digital measurement, and details regarding the sensors, algorithms, and study sample. Sixty-seven percent of the technologies identified were wearable sensors, with the remainder including tablets, smartphones, implanted sensors, and cameras. We noted substantial variability in terms of reporting completeness and terminology used. The data have been compiled into an online database maintained by the Clinical Trials Transformation Initiative that can be filtered and searched electronically, enabling a user to find information most relevant to their work. Our long-term goal is to maintain and update the online database, in order to promote standardization of methods and reporting, encourage collaboration, and avoid redundant studies, thereby contributing to the design and implementation of efficient, high-quality trials.

Electronic Cigarette Use Among Counseled Tobacco Users Hospitalized in 2015.

OBJECTIVES: Few studies have examined the prevalence of electronic cigarette use among the inpatient population regardless of the patients' cessation goals. The objectives of this study were to examine the prevalence of electronic cigarette use among counseled tobacco users admitted to 2 academic hospitals. METHODS: Cross-sectional data of hospitalized adult tobacco users who were admitted between January 1, 2015 and December 31, 2015 and who received bedside tobacco cessation counseling from a tobacco treatment service counselor were examined. Demographic and smoking history items were compared as a function of electronic cigarette use using chi-square and independent t tests. Logistic regression was used to test independent associations with electronic cigarette use. RESULTS: Of 2194 hospitalized tobacco users counseled, 22% had used an electronic cigarette. Most of these patients used electronic cigarettes to quit or reduce use of combustible cigarettes. Adjusted odds of electronic cigarette use were higher for females (adjusted odds ratio [AOR] 0.60 for male patients, 95% confidence interval [CI] 0.47-0.76), younger patients (AOR 0.98 for older patients, 95% CI 0.97-0.99), and individuals who initiated tobacco use earlier in life (AOR 0.97 for later smoking initiation, 95% CI 0.95-0.99). CONCLUSIONS: Screening hospitalized cigarette smokers for electronic cigarette use offers an opportunity to counsel all patients on evidence-based quit aids. Young, female patients are most likely to use electronic cigarettes and may benefit most from directed discussions about electronic cigarette use and Federal Drug Administration-approved cessation methods during smoking cessation counseling.

Embedding a trauma hospitalist in the trauma service reduces mortality and 30-day trauma-related readmissions.

BACKGROUND: Recognizing the increasing age and comorbid conditions of patients admitted to our trauma service, we embedded a hospitalist on the trauma service at our Level I trauma center.This program was initiated in January 2013. This study was designed to investigate differences in outcomes between trauma patients who received care from the trauma hospitalist (THOSP) program and similarly medically complex trauma patients who did not receive THOSP care. METHODS: There were 566 patients comanaged with THOSP between December 2013 and November 2014. These patients were matched (1:2) with propensity scores to a contemporaneous control group based on age, Injury Severity Score (ISS), and comorbid conditions. Outcomes examined included mortality, trauma-related readmissions, upgrades to the intensive care unit, hospital length of stay, the development of in-hospital complications, and the frequency of obtaining medical subspecialist consultation. Differences in outcomes were compared with Mann-Whitney U-test or χ test as appropriate. RESULTS: High-quality matching resulted in the loss of 97 THOSP patients for the final analysis. Table 1 shows the balance between the two groups after matching. While there was a 1-day increase in hospital length of stay and an increase in upgrades to the intensive care unit, there was a reduction in mortality, trauma-related readmissions, and the development of renal failure after implementation of the THOSP program (Table 2). Implementation of this program made no significant difference in the frequency of cardiology, nephrology, neurology, or endocrinology consultations. There was also no difference in the development of the complications of venous thromboembolism, pneumonia, stroke, urinary tract infection, bacteremia, or alcohol withdrawal. CONCLUSION: Our study provides evidence that embedding a hospitalist on the trauma service reduces mortality and trauma-related readmissions. A reason for these improved outcomes may be related to THOSP "vigilance." LEVEL OF EVIDENCE: Therapeutic/care management study, level IV.

Increasing the efficiency of a targeted methicillin-resistant Staphylococcus aureus screening program.

An interdisciplinary team implemented a screening program targeting patients with a history of methicillin-resistant Staphylococcus aureus (MRSA), to reduce unnecessary contact isolation. After converting from a 2-step culture-based protocol to single polymerase chain reaction (PCR) testing, we increased the efficiency of the screening program from 77% to 100%. Despite the higher cost of PCR-based testing, this program remained cost-saving.

Using a Lean Six Sigma Approach to Yield Sustained Pressure Ulcer Prevention for Complex Critical Care Patients.

BACKGROUND: Under value-based purchasing, Medicare withholds reimbursements for hospital-acquired pressure ulcer occurrence and rewards hospitals that meet performance standards. With little evidence of a validated prevention process, nurse managers are challenged to find evidence-based interventions. OBJECTIVE: The aim of this study was to reduce the unit-acquired pressure ulcer (UAPU) rate on targeted intensive care and step-down units by 15% using Lean Six Sigma (LSS) methodology. METHODS: An interdisciplinary team designed a pilot program using LSS methodology to test 4 interventions: standardized documentation, equipment monitoring, patient out-of-bed-to-chair monitoring, and a rounding checklist. RESULTS: During the pilot, the UAPU rate decreased from 4.4% to 2.8%, exceeding the goal of a 15% reduction. The rate remained below the goal through the program control phase at 2.9%, demonstrating a statistically significant reduction after intervention implementation. CONCLUSIONS: The program significantly reduced UAPU rates in high-risk populations. LSS methodologies are a sustainable approach to reducing hospital-acquired conditions that should be broadly tested and implemented.