Background: Hospital stays after major surgery are shorter than ever before. Although enhanced recovery and early discharge have many benefits, some complications will now first manifest themselves in home settings. Remote patient monitoring with wearable sensors in the first days after hospital discharge may capture clinical deterioration earlier but is largely uncharted territory. Objective: This study aimed to assess the technical feasibility of patients, discharged after esophagectomy, being remotely monitored at home with a wireless patch sensor and the experiences of these patients. In addition, we determined whether observing vital signs with a wireless patch sensor influences clinical decision making. Methods: In an observational feasibility study, vital signs of patients were monitored with a wearable patch sensor (VitalPatch, VitalConnect Inc) during the first 7 days at home after esophagectomy and discharge from hospital. Vital signs trends were shared with the surgical team once a day, and they were asked to check the patient’s condition by phone each morning. Patient experiences were evaluated with a questionnaire, and technical feasibility was analyzed on a daily basis as the percentage of data loss and gap durations. In addition, the number of patients for whom a change in clinical decision was made based on the results of remote vital signs monitoring at home was assessed. Results: Patients (N=20) completed 7 days each of home monitoring with the wearable patch sensor. Each of the patients had good recovery at home, and remotely observed vital signs trends did not alter clinical decision making. Patients appreciated that surgeons checked their vital signs daily (mean 4.4/5) and were happy to be called by the surgical team each day (mean 4.5/5). Wearability of the patch was high (mean 4.4/5), and no reports of skin irritation were mentioned. Overall data loss of vital signs measurements at home was 25%; both data loss and gap duration varied considerably among patients. Conclusions: Remote monitoring of vital signs combined with telephone support from the surgical team was feasible and well perceived by all patients. Future studies need to evaluate the impact of home monitoring on patient outcome as well as the cost-effectiveness of this new approach.

Background: Remote monitoring of physical activity in patients with chronic conditions could be useful to offer care professionals real-time assessment of their patient’s daily activity pattern to adjust appropriate treatment. However, the validity of commercially available activity trackers that can be used for telemonitoring purposes is limited. Objective: The purpose of this study was to test usability and determine the validity of 3 consumer-level activity trackers as a measure of free-living activity. Methods: A usability evaluation (study 1) and validation study (study 2) were conducted. In study 1, 10 individuals wore one activity tracker for a period of 30 days and filled in a questionnaire on ease of use and wearability. In study 2, we validated three selected activity trackers (Apple Watch, Misfit Shine, and iHealth Edge) and a fourth pedometer (Yamax Digiwalker) against the reference standard (Actigraph GT3X) in 30 healthy participants for 72 hours. Outcome measures were 95% limits of agreement (LoA) and bias (Bland-Altman analysis). Furthermore, median absolute differences (MAD) were calculated. Correction for bias was estimated and validated using leave-one-out cross validation. Results: Usability evaluation of study 1 showed that iHealth Edge and Apple Watch were more comfortable to wear as compared with the Misfit Flash. Therefore, the Misfit Flash was replaced by Misfit Shine in study 2. During study 2, the total number of steps of the reference standard was 21,527 (interquartile range, IQR 17,475-24,809). Bias and LoA for number of steps from the Apple Watch and iHealth Edge were 968 (IQR −5478 to 7414) and 2021 (IQR −4994 to 9036) steps. For Misfit Shine and Yamax Digiwalker, bias was −1874 and 2004, both with wide LoA of (13,869 to 10,121) and (−10,932 to 14,940) steps, respectively. The Apple Watch noted the smallest MAD of 7.7% with the Actigraph, whereas the Yamax Digiwalker noted the highest MAD (20.3%). After leave-one-out cross validation, accuracy estimates of MAD of the iHealth Edge and Misfit Shine were within acceptable limits with 10.7% and 11.3%, respectively. Conclusions: Overall, the Apple Watch and iHealth Edge were positively evaluated after wearing. Validity varied widely between devices, with the Apple Watch being the most accurate and Yamax Digiwalker the least accurate for step count in free-living conditions. The iHealth Edge underestimates number of steps but can be considered reliable for activity monitoring after correction for bias. Misfit Shine overestimated number of steps and cannot be considered suitable for step count because of the low agreement. Future studies should focus on the added value of remotely monitoring activity patterns over time in chronic patients.

Modern hospitals are on the brink of a monumental change. They are currently exploring their options to digitally transform their clinical procedures and overall patient engagement. This work thoroughly investigates how hospital departments in the Netherlands can simultaneously leverage their strategic exploration of new IT resources and practices and exploit their current IT practices, i.e., IT ambidexterity, to drive digital transformation. Specifically, we investigate IT ambidexterity’s role in shaping patient agility at the departmental level, i.e., the ability to sense patients’ needs and respond accordingly. In this study, we use the dynamic capability view as our theoretical lens to develop a theoretical model with associated hypotheses and test it using cross-sectional survey data from 90 clinical hospital departments in the Netherlands. We use partial least squares (PLS) structural equation modeling (SEM) and a Fuzzy-set qualitative comparative analysis (fsQCA) approach for our analyses. This study shows that IT ambidexterity positively influences patient agility, providing a foundation for the achievement of high patient service and market performance. Furthermore, this study’s outcomes show that IT ambidexterity is present in each configuration following the fsQCA analyses, showcasing the vital role of a dual strategic approach to IT practices. The study outcomes support the theorized model and the subsequently developed IT-driven patient agility framework and illuminate how to transform clinical practice and drive patient agility.

Background: Telemonitoring can enhance the efficiency of health care delivery by enabling risk stratification, thereby allowing health care professionals to focus on high-risk patients. Additionally, it reduces the need for physical care. In contrast, telemonitoring programs require a significant time investment for implementation and alert processing. A structured method for telemonitoring process optimization is lacking. Objective: We propose a framework for optimizing efficient care delivery in telemonitoring programs based on alert data analysis and scenario analysis of a telemonitoring program for hypertension combined with a narrative literature review on methods to improve efficient telemonitoring care delivery. Methods: We extracted 1-year alert processing data from the telemonitoring platform and electronic health records (June 2022-May 2023) from all users participating in the hypertension telemonitoring program in the outpatient clinic of the Department of Internal Medicine of the Maasstad Hospital. We analyzed the alert burden and alert processing data. Additionally, a scenario analysis with different threshold values was conducted for existing blood pressure alerts to assess the impact of threshold adjustments on the overall alert burden and processing. We searched for English language academic research papers and conference abstracts reporting clinical alert or workflow optimization in telemonitoring programs on May 24, 2024 in Embase, Medline, Cochrane, Web of Science, and Google Scholar. Results: In total, 174 users were included and analyzed. On average, each user was active in the telemonitoring program for 207 days and a total of 30,184 measurements were performed. These triggered a total of 17,293 simple, complex, and inactive or overdue alerts: 13,647 were processed automatically by the telemonitoring platform, and 3646 were processed manually by e-nurses from the telemonitoring center, equivalent to 21 manually processed alerts per user. Additional analysis of the manually processed alerts revealed that 25 (15%) users triggered more than 50% of these specific alerts. Furthermore, scenario analysis of the alert thresholds revealed that a single increase of 5 and 10 mmHg for the diastolic and systolic blood pressure alerts would reduce the number of alerts by about 50%, resulting in a total reduced time investment for the e-nurse of 5973 minutes over 1 year. Literature search yielded 251 articles, of which 7 studies reported methods to improve efficiency in telemonitoring programs, including the introduction of complex alerts and clinical algorithms to triage alerts, scenario analysis with alert threshold adjustments, and a qualitative analysis to create an alert triage algorithm. Conclusions: Based on the data analysis and literature review, a 4-step framework was developed to optimize the efficiency of telemonitoring programs. The 4 steps include ensuring accurate measurements, telemonitoring algorithm and alert optimization, focusing on individual users’ and user groups’ needs, and improving telemonitoring process efficiency. This framework can be an important first step to improve the efficiency of 21st-century telemonitoring programs.

Background: During the COVID-19 pandemic, there was limited adoption of contact-tracing apps (CTAs). Adoption was particularly low among vulnerable people (eg, people with a low socioeconomic position or of older age), while this part of the population tends to have lesser access to information and communication technology and is more vulnerable to the COVID-19 virus. Objective: This study aims to understand the cause of this lagged adoption of CTAs in order to facilitate adoption and find indications to make public health apps more accessible and reduce health disparities. Methods: Because several psychosocial variables were found to be predictive of CTA adoption, data from the Dutch CTA CoronaMelder (CM) were analyzed using cluster analysis. We examined whether subgroups could be formed based on 6 psychosocial perceptions (ie, trust in the government, beliefs about personal data, social norms, perceived personal and societal benefits, risk perceptions, and self-efficacy) of (non)users concerning CM in order to examine how these clusters differ from each other and what factors are predictive of the intention to use a CTA and the adoption of a CTA. The intention to use and the adoption of CM were examined based on longitudinal data consisting of 2 time frames in October/November 2020 (N=1900) and December 2020 (N=1594). The clusters were described by demographics, intention, and adoption accordingly. Moreover, we examined whether the clusters and the variables that were found to influence the adoption of CTAs, such as health literacy, were predictive of the intention to use and the adoption of the CM app. Results: The final 5-cluster solution based on the data of wave 1 contained significantly different clusters. In wave 1, respondents in the clusters with positive perceptions (ie, beneficial psychosocial variables for adoption of a CTA) about the CM app were older (P<.001), had a higher education level (P<.001), and had higher intention (P<.001) and adoption (P<.001) rates than those in the clusters with negative perceptions. In wave 2, the intention to use and adoption were predicted by the clusters. The intention to use CM in wave 2 was also predicted using the adoption measured in wave 1 (P<.001, β=–2.904). Adoption in wave 2 was predicted by age (P=.022, exp(B)=1.171), the intention to use in wave 1 (P<.001, exp(B)=1.770), and adoption in wave 1 (P<.001, exp(B)=0.043). Conclusions: The 5 clusters, as well as age and previous behavior, were predictive of the intention to use and the adoption of the CM app. Through the distinguishable clusters, insight was gained into the profiles of CM (non)intenders and (non)adopters. Trial Registration: OSF Registries osf.io/cq742; https://osf.io/cq742

Background: Home blood pressure telemonitoring (HBPT) has been proposed to enhance adherence and optimize health care delivery, yet its prerequisites for cost-effective implementation remain unclear. Objective: This study aims to quantify the potential cost-effectiveness of HBPT and identify prerequisites for cost-effective implementation of HBPT in comparison to standard hypertension management, using an early health economic analysis from a societal perspective. Methods: A decision-analytic Markov model with a lifetime horizon (30 years) and a willingness-to-pay threshold of €20,000 (€1=US $1.09) per quality-adjusted life year (QALY) was developed to assess the cost-effectiveness of HBPT compared to standard of care (SOC). The HBPT intervention was based on an existing HBPT program applied by the Maasstad Hospital, Rotterdam, the Netherlands. The model incorporated 12 health states: 7 blood pressure states, 1 cardiovascular (CV) event, 1 recurrent CV event, 1 postrecurrent CV event, 1 all-cause death, and 1 CV disease–related death. A hypothetical cohort of 1000 patients (average age 65.3 years) was modeled, and results were reported in costs, QALYs, and the incremental cost-effectiveness ratio (ICER). The model assumed 3 in-person outpatient department (OPD) consultations in the SOC group and 1.5 in the HBPT group. Extensive sensitivity analyses were performed to identify important variables for the cost-effective implementation of HBPT. Results: Following the base-case analysis, HBPT was not cost-effective with an ICER of €20,386 per QALY. Sensitivity analyses indicated that reducing the number of in-person OPD consultations resulted in a more favorable ICER. Specifically, reducing the number of in-person OPD consultations to 1.48 annually resulted in an ICER below the willingness-to-pay threshold. Reducing the in-person OPD consultations to an average of 1.18 per year would make HBPT cost-saving. Scenario analyses revealed that extending the duration of HBPT’s clinical effect to 2 or 3 years substantially improved the ICER. Additionally, targeting HBPT toward patients aged 64 years or below further improved the ICER. Conclusions: HBPT could result in cost-effective or cost-saving outcomes with only minor reductions in in-person OPD consultations. These findings highlight the potential of HBPT to transform hypertension management by replacing traditional hypertension management with more efficient care using remote patient monitoring.