Symptom Monitoring Research Articles

Feasibility and usefulness of symptom monitoring with electronic patient-reported outcomes: an experience at single-center outpatient oncology clinic.

The benefit of patient-reported outcomes (PRO) in routine oncology practice is increasingly recognized. This study aimed to develop a team-based monitoring and intervention system using electronic PRO (ePRO) and to evaluate its impact at an outpatient oncology clinic. Patients receiving chemotherapy at our department were eligible for this study. Those who had access to a smartphone or tablet (Bring Your Own Device [BYOD]) and consented participated, and reported 28 symptoms weekly via 3H P-guardian downloaded on their BYOD. E-mail alerts were sent to attending healthcare providers when participants reported at least grade 3 severity for any of nine symptoms (decreased appetite, nausea, vomiting, diarrhea, shortness of breath, pain, insomnia, fatigue, and sadness), which prompted interventions. Comparisons of overall survival (OS), emergency room visits, and hospitalizations were conducted using propensity scores. Among 203 patients who received chemotherapy from September 2021 to August 2023, 77 participated in ePRO monitoring. The overall response rate was 55% (1991 valid responses out of a total of 3597 expected time points), and the median individual response rate was 66% (range, 0-100%). Of 1991 valid responses, 250 (13%) prompted alerts, and most interventions were initiated by making telephone calls. OS and other clinical outcomes were better in ePRO participants compared with non-participants, but these outcomes did not differ significantly between the ePRO and pre-ePRO eras. It was feasible to develop a multi-professional team-based monitoring and intervention system using ePRO at a single-center outpatient oncology clinic. Our results indicate that weekly monitoring of ePRO, along with corresponding interventions, may benefit patients receiving chemotherapy.

Personalized Smartphone-Enabled Assessment of Blood Pressure and Its Treatment During the SARS-CoV-2 COVID-19 Pandemic in Patients From the CURE-19 Study: Longitudinal Observational Study.

The use of digital interventions by patients for remote monitoring and management of health and disease is increasing. This observational study examined the feasibility, use, and safety of a digital smartphone app for routine monitoring of blood pressure (BP), medication, and symptoms of COVID-19 during the COVID-19 pandemic. The objective of this study was to deploy and test electronic data recording using a smartphone app developed for routine monitoring of BP in patients with primary hypertension. We tested the app for ease of data entry in BP management and tracking symptoms of new-onset COVID-19 to determine if participants found this app approach useful and sustainable. This remote, decentralized, 12-week, prospective, observational study was conducted in a community setting within the United States. Participants were approached and recruited from affiliated sites where they were enrolled in an ongoing remote decentralized study (CURE-19) of participants experiencing the COVID-19 pandemic. Potential participants were asked to complete a digital screener to determine eligibility and given informed consent forms to read and consent to using the Curebase digital platform. Following enrollment, participants downloaded the digital app to their smartphones for all data collection. Participants recorded daily BP, associated medication use, and emergent symptoms associated with SARS-CoV-2 infection. In addition, usability (adherence, acceptability, and user experience) was assessed using standard survey questions. Adverse events were collected based on participant self-report. Compliance and engagement were determined from user data entry rates. Feasibility and participant feedback were assessed upon study completion using the User Experience Questionnaire. Of the 389 participants who enrolled in and completed the study, 380 (98%) participants downloaded and entered BP routines in week 1. App engagement remained high; 239 (62.9%) of the 380 participants remained in the study for the full 12-week observation period, and 201 (84.1%) of the 239 participants entered full BP routines into the digital app 80% or more of the time. The smartphone app scored an overall positive evaluation as assessed by the User Experience Questionnaire and was benchmarked as "excellent" for domains of perspicuity, efficiency, and dependability and "above average" for domains of attractiveness and stimulation. Highly adherent participants with hypertension demonstrated well-controlled BP, with no significant changes in average systolic or diastolic BP between week 1 and week 12 (all P>.05). Participants were able to record BP medications and symptoms of SARS-CoV-2 infection. No adverse events attributable to the use of the smartphone app were reported during the observational period. The high retention, engagement and acceptability and positive feedback in this study demonstrates that routine monitoring of BP and medications using a smartphone app is feasible for patients with hypertension in a community setting. Remote monitoring of BP and data collection could be coupled with hypertensive medication in a combination product (drug+digital) for precision management of hypertension.

Co-design of an electronic patient-reported outcome symptom monitoring system for immunotherapy toxicities.

Utilising electronic patient-reported outcomes (ePRO) to monitor symptoms can improve patient outcomes. However, ePRO systems are typically not co-designed with end-users which may limit their utility and long-term sustainability. We aimed to co-design a real-time ePRO symptom monitoring system for immune checkpoint inhibitor (ICI) toxicities. We conducted three co-design workshops at an Australian quaternary cancer centre. Participants were patients who had received/were receiving ICI or their caregivers, managing clinicians, administration staff, and electronic medical record (EMR) analysts. Workshop 1 identified preferences for an ideal ePRO system, informing the development of a prototype and generic workflow. Workshop 2 sought feedback on the prototype and workflow. Workshop 3 reviewed the updated prototype and adapted the generic workflow to create a site-specific workflow. Workshop transcripts were analysed thematically. Twenty-seven participants were included. Themes relating to system content and functionality included the need for customisation according to anticipated ICI toxicities; maximising patient accessibility, comprehension, and usability; providing ICI-specific self-management advice; and maximising clinician interpretability and usability. Themes relating to the model of care included the importance of maintaining the "human element" within the ePRO system, providing 24-hour support, alignment with existing clinical workflows, and automation of symptom monitoring processes using the EMR. Early, broad stakeholder engagement through co-design may improve the relevance, uptake, and sustainability of ePRO systems. Future work will involve usability and acceptance testing of the prototype, followed by implementation into routine care.

Artificial Intelligence Integration in Biochips: Enhancing Diagnostics and Precision Medicine

Abstract: The integration of biochips with AI opened up new possibilities and is expected to revolutionize smart healthcare tools within the next five years. The combination of miniaturized, multi- functional, rapid, high-throughput sample processing and sensing capabilities of biochips, with the computational data processing and predictive power of AI, allows medical professionals to collect and analyze vast amounts of data quickly and efficiently, leading to more accurate and timely diagnoses and prognostic evaluations. Biochips, as smart healthcare devices, offer continuous monitoring of patient symptoms. Integrated virtual assistants have the potential to send predictive feedback to users and healthcare practitioners, paving the way for personalized and predictive medicine. This review explores the current state-of-the-art biochip technologies including gene-chips, organ-on-a-chips, and neural implants, and the diagnostic and therapeutic utility of AI-assisted biochips in medical practices such as cancer, diabetes, infectious diseases and neurological disorders. Choosing the appropriate AI model for a specific biomedical application, and possible solutions to the current challenges are explored. Surveying advances in machine learning models for biochip functionality, this paper offers a review of biochips for the future of biomedicine, an essential guide for keeping up with trends in healthcare, while inspiring cross-disciplinary collaboration among biomedical engineering, medicine, and machine learning fields.

Minimal Clinically Important Differences With the Outcomes of the App-Based Japanese Allergic Conjunctival Diseases Quality of Life Questionnaire: Cross-Sectional Observational Study.

Assessing changes in quality of life in patients with hay fever-related allergic conjunctivitis requires validated and clinically meaningful metrics. A minimal clinically important difference (MCID) that can be applied to assess Domain II of the Japanese Allergic Conjunctival Disease Quality of Life Questionnaire (JACQLQ) in a smartphone app setting has yet to be determined. This cross-sectional observational study aimed to determine MCIDs for the app-based JACQLQ in assessing hay fever-related allergic conjunctivitis. This study used data from a crowdsourced, cross-sectional, observational study conducted via the smartphone app "AllerSearch" between February 1, 2018, and May 1, 2020. Participants were recruited through digital media and social networking platforms and voluntarily provided electronic informed consent. Participants completed the JACQLQ, which includes items on daily activity and psychological well-being, as well as a visual analog scale to measure stress levels related to hay fever. Data were collected through the app, ensuring comprehensive user input. MCIDs were determined using both anchor- and distribution-based methods. The face scale of the JACQLQ Domain III and stress level scale for hay fever were used as anchors to estimate the MCID; ranges were derived from these MCID estimates. In the distribution-based method, MCIDs were calculated using half the SD and SE of the JACQLQ Domain II scores. SEs were derived from the intraclass correlation coefficient of an app-based JACQLQ test-retest reliability metric. A total of 17,597 individuals were identified, of which 15,749 individuals provided electronic consent. After excluding those with incomplete data, 7590 participants with hay fever were included in the study (mean age 35.3, SD 13.9 years; n=4331, 57.1% of women). MCID ranges calculated using the anchor-based method were 1.0-6.9, 1.2-5.6, and 2.1-12.6 for daily activity, psychological well-being, and total JACQLQ Domain II scores, respectively. Using the distribution-based method, the intraclass correlation coefficients were odds ratio (OR) 0.813 (95% CI 0.769-0.849) for daily activity, OR 0.791 (95% CI 0.743-0.832) for psychological well-being, and OR 0.841 (95% CI 0.791-0.864) for total JACQLQ Domain II scores. In addition, the distribution-based method resulted in 2 MCIDs based on half the SD and SE of measurement for daily activity (4.8 and 4.2), psychological well-being (3.4 and 3.1), and total JACQLQ Domain II (7.8 and 6.4) scores. The final suggested MCID ranges for daily activity, psychological well-being, and total JACQLQ Domain II scores were 4.2-6.0, 3.1-4.7, and 6.4-10.5, respectively. MCID ranges for the JACQLQ estimation could help to standardize the app-based quality of life assessment for patients with hay fever-related allergic conjunctivitis. These MCIDs enhanced the precision of remote symptom monitoring and facilitated timely, data-driven interventions, ultimately improving the overall management and outcomes of allergic conjunctivitis through mobile health platforms.

A mobile app to support self-management and remotely monitor disease impact in rheumatoid arthritis: the randomised controlled AEGORA trial.

We aimed to study if smartphone applications could support the self-management of RA, while investigating engagement and potential negative psychological effects with app-use. App-based Education and GOal-setting in RA (AEGORA) was a multicentre randomised controlled trial with 2:1:1-allocation to usual care or two versions of an app-based self-management intervention for RA. The 16-week programme involved patient education, goal-setting, and remote monitoring of the Rheumatoid Arthritis Impact of Disease (RAID) instrument, either weekly or monthly depending on randomisation. The primary end point was improvement in the Arthritis Self-Efficacy Scale (ASES) after 16 weeks. Secondary endpoints included non-inferiority regarding the Pain Catastrophizing Scale (PCS) and superiority regarding patient-reported physical activity, sleep quality and RAID. App engagement and RAID-scores were analysed descriptively. Overall, 122 patients were included: mean (SD) disease duration 12 (9) years, mean (SD) age 58(11), 68% female, mean (SD) DAS28-CRP 2.4(0.9). The intervention did not improve the ASES-score over usual care (β: 0.44, p= 0.87). Non-inferiority was established for the PCS (β -0.95 [95% CI -3.30 to + 1.40] favouring the intervention). Other predefined outcomes did not differ. App retention steadily declined to 43% by 16 weeks. Although the RAID remained stable over time overall, 35% of app users reported ≥1 episode of clinically relevant worsening over 16 weeks. This app-based self-management intervention was not superior to usual care regarding self-efficacy improvement. However, remote symptom monitoring provided valuable insight and did not increase pain catastrophising, alleviating concerns regarding the psychological impact of remote monitoring with apps. clinicaltrials.gov, NCT05888181.

Nonarteritic anterior ischemic optic neuropathy and the incidence of depression: a nationwide population-based study (2010-2017).

The risk of depression in patients with non-arteritic anterior ischemic optic neuropathy (NAION) has yet to be thoroughly researched. This study aimed to investigate the association between NAION and the onset of depression using a large-scale nationwide cohort in South Korea. This is a retrospective, nationwide cohort study involving 145,020 subjects without NAION and 29,004 individuals with a previous NAION diagnosis. Follow-up clinical data were collected until December 31, 2017. Multivariable adjustment models were employed to account for potential confounding factors. The incidence of new-onset depression was significantly higher among NAION patients (incidence, 38.09 per 1000 person-years) than among non-NAION individuals (incidence, 29.91 per 1000 person-years). After adjusting for demographic factors, socioeconomic status, and comorbid diseases, the association remained significant (aHR = 1.271; 95% CI = 1.226-1.317). Notably, a subgroup analysis highlighted a particularly pronounced risk of depression in NAION patients aged 40 to 64 compared to those aged 65 or older (aHR = 1.34 vs. 1.207; interaction P = 0.0038). Our findings demonstrate a significant association between NAION and an increased risk of depression, especially in relatively younger patients aged 40 to 64 years. These results highlight the importance of regular monitoring and early intervention for depressive symptoms in patients with NAION.

Hybrid Machine Learning Approach for Early Stroke Prediction in Elderly People

Stroke represents a significant global health challenge, often leading to severe disability and mortality. The timely prediction and intervention of stroke are paramount in enhancing patient outcomes and reducing healthcare burdens. This project proposes a machine learning-based approach to predict stroke risk using multi-modal biosignals, specifically electrocardiogram (ECG) data. By leveraging advanced algorithms, including Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks, the system aims to classify patient health data into critical risk categories such as Normal, Abnormal, Ischemic, and Hemorrhagic. The study utilizes a comprehensive dataset consisting of ECG signals and incorporates techniques for data preprocessing, class balancing, and feature extraction. The predictive model is trained and validated using robust evaluation metrics, including accuracy, precision, recall, and F1-score. The findings underscore the efficacy of the proposed system in providing real-time stroke risk assessments, offering a cost-effective alternative to traditional diagnostic methods. Furthermore, this research explores the integration of wearable technology with machine learning, highlighting its potential for continuous patient monitoring and early detection of stroke symptoms. By creating a user-friendly interface for healthcare professionals and patients, the system aims to facilitate prompt decision-making and intervention, ultimately improving the overall quality of care for individuals at risk of stroke

Healthy at Home for COPD: An Integrated Digital Monitoring, Treatment, and Pulmonary Rehabilitation Intervention.

Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of morbidity and mortality in the United States. Frequent exacerbations result in higher use of emergency services and hospitalizations, leading to poor patient outcomes and high costs. Demonstrate the feasibility of a multimodal, digitally enhanced remote monitoring, treatment, and tele-pulmonary rehabilitation intervention among patients with COPD. In this pilot clinical trial, community-dwelling adults with moderate-severe COPD were enrolled in a multimodal digital monitoring and treatment program including a Fitbit wearable device, study app that tracked COPD-related symptoms, on-demand mobile integrated health (MIH) services for acute home-based treatment, and tele-pulmonary-rehabilitation. Participants were enrolled in the program for six months. COPD severity and health-related quality of life assessments were performed at baseline, 3 months, and 6 months. Primary feasibility outcomes include recruitment and retention rate, and participant protocol fidelity, which were reported descriptively. Exploratory clinical outcomes included patient-reported quality of life, activation, and intervention satisfaction. Over 18 months, 1,333 patients were approached and 100 (7.5%) were enrolled (mean age 66, 52% female). Ninety-six participants (96%) remained in the study for the full enrollment period. Fifty-five (55%) participated in tele-pulmonary-rehabilitation. Participants wore the Fitbit for a median of 114 days (IQR 183.6) and 16.85 hours/day (4.05), resulting in a median of 1133 minutes (243) per day. Completion rates for scheduled instruments ranged from 78-93%. Nearly all participants (85%) performed COPD ecological momentary assessment at least once with a median of 4.85 recordings. On average, a 2.48-point improvement (p=0.03) in COPD Assessment Test Score was observed from baseline to study completion. The adherence and symptom improvement metrics were not associated with baseline patient activation measures. A multimodal intervention combining preventative care, symptom and biometric monitoring, and home treatment was feasible in adults living with COPD. Participants demonstrated high protocol fidelity and engagement and reported improved quality of life.

Prodromal symptoms of a first manic episode: a qualitative study to the perspectives of patients with bipolar disorder and their caregivers’

BackgroundDiagnosing bipolar disorder (BD) is challenging, and adequate treatment is of major importance to minimalize the consequences of the illness. Early recognition is one way to address this. Although in clinical research the prodromal phase of BD is gaining interest, the perspective of patients with BD and their caregivers on prodromal symptoms is still lacking. The aim of this study is to gain insights in prodromal symptoms of patients with BD and their caregivers before the onset of a first manic episode.MethodsA qualitative research method was used to investigate prodromal symptoms one year prior to a first manic episode. In-depth interviews were conducted with patients with BD type I and their caregivers. Only patients with a first manic episode in the previous five years were included.ResultsThe prodromal symptoms from patients’ and caregivers’ perspectives could be clustered into seven themes, with underlying subthemes: behavior (increased activity, destructive behavior, disinhibited behavior, inadequate behavior, changes in appearance), physical changes (changes in sleep, physical signals, differences in facial expression), communication (reciprocity, process, changes in use of social media), thought (process and content), cognition (changes in attention and concentration, forgetfulness), emotions (positive emotions, more intense emotions, mood swings), and personality (more pronounced manifestation of existing personality traits).ConclusionPatients with bipolar I disorder and their caregivers described subsyndromal manic features one year prior to a first manic episode. In addition, they recognized mood lability, physical changes and more pronounced manifestation of existing personality traits. The results of this study confirm the presence of a prodromal phase. In clinical practice, monitoring of prodromal symptoms of BD can be useful in patients with depression, especially those with a familial risk of BD.

Symptom Monitoring With Patient-Reported Outcomes During Pediatric Cancer Care

Symptom Monitoring With Patient-Reported Outcomes During Pediatric Cancer Care

Abstract 4136911: Daily Dyadic Symptom Appraisal Dynamics During Care Transitions in Persons with Heart Failure and Their Care Partners

Background: Symptom monitoring after heart failure (HF) hospitalization is a central aspect of patient education. However, appraising symptoms can be difficult for persons with HF (PWHFs), and studies suggest family care partners (CPs) play a key supportive role. The purpose of this study is to examine dyadic HF symptom appraisal dynamics in PWHF-CP dyads during hospital-to-home transitions. Methods: We conducted a daily diary study of dyadic symptom appraisal in which PWHFs and CPs were enrolled during a HF hospitalization. Over 5 weeks, both completed daily assessments of the PWHF’s symptoms (HF Somatic Perception Scale, PROMIS Fatigue 4a). Each dyad’s appraisal dynamics were quantified using a set of N of 1 dyadic autoregressive time series models examining total symptoms, hallmark symptoms (dyspnea, edema) and nonspecific symptoms (early/subtle cluster, fatigue). Models were examined for within-dyad dynamics (within-dyad associations on the same day or on a 1-day lag). Patterns in significant dynamics across dyads were narratively described. Results: This analysis includes n=14 cohabitating dyads, all partnered. On average, PWHFs and CPs were 69.6±5.4 and 67.4±8.0 years of age. The sample was relatively gender balanced (43% of PWHFs and 64% of CPs identified as female), and primarily identified as non-Hispanic (86% of PWHFs, 93% of CPs) and White (93% of PWHFs, 86% of CPs). Most PWHFs had non-ischemic cardiomyopathy (64%) and were NYHA Class III/IV (86%), with 57% HFrEF (mean EF 37%±17%). Symptom appraisals were highly variable within and across dyads (Fig 1). Most (n=11, 79%) had significant dyadic dynamics, but dynamics across dyads varied by symptom type and time structure (Fig 2). Conclusions: The types of symptoms that HF care dyads are able to appraise together and the time structure of appraisals are variable during care transitions. Precision approaches tailored to individual dyads are needed to optimize inclusion of CPs in symptom monitoring interventions.

PRO-P: evaluating the effect of electronic patient-reported outcome measures monitoring compared with standard care in prostate cancer patients undergoing surgery—study protocol for a randomized controlled trial

BackgroundWith over 65,000 new cases per year in Germany, prostate cancer (PC) is the most common cancer in men in Germany. Localized PC is often treated by radical prostatectomy and has a very good prognosis. Postoperative quality of life (QoL) is significantly influenced by the side effects of surgery. One possible approach to improve QoL is postoperative symptom monitoring using ePROMs (electronic patient-reported outcome measures) to accurately identify any need for support.MethodsThe PRO-P (“Influence of ePROMS in surgical therapy of PC on the postoperative course”) study is a randomized controlled trial employing 1:1 randomization at 6 weeks postoperatively, involving 260 patients with incontinence (≥ 1 pad/day) at six participating centers. Recruitment is planned for 1 year with subsequent 1-year follow-up. PRO-monitoring using domains of EPIC-26, psychological burden, and QoL are assessed 6, 12, 18, 24, 36, and 52 weeks postoperatively. Exceeding predefined PRO-score cutoffs triggers an alert at the center, prompting patient contact, medical consultation, and potential interventions. The primary endpoint is urinary continence. Secondary endpoints refer to EPIC-26 domains, psychological distress, and QoL. Aspects of feasibility, effect, and implementation of the intervention will be investigated within the framework of a qualitative process evaluation.DiscussionPRO-P investigates the effect on postoperative symptom monitoring of a structured follow-up using ePROMs in the first year after prostatectomy. It is one of the first studies in cancer surgery investigating PRO-monitoring and its putative applicability to routine care. Patient experiences with intensified monitoring of postoperative symptoms and reflective counseling will be examined in order to improve primarily urinary continence, and secondly other burdens of physical and psychological symptoms, quality-of-life, and patient competence. The potential applicability of the intervention in clinical practice is facilitated by IT adaption to the certification standards of the German Cancer Society and the integration of the ePROMs survey via a joint patient portal. Positive outcomes could readily translate this complex intervention into routine clinical care. PRO-P might improve urinary incontinence and QoL in patients with radical prostatectomy through the structured use of ePROMs.Trial registrationClinicalTrials.gov NCT05644821. Registered on 09 December 2022.

Abstract 4141453: The Pandemic influenced the Self-care of African Immigrants with Diabetes and Hypertension

Background: Self-Care is essential for chronic illness management. Self-Care comprises three domains: Self-Care maintenance (daily behaviors to maintain health [e.g., medication adherence]), Self-Care monitoring (surveillance for changes), and (3) Self-Care management (prompt response to symptoms). The COVID-19 pandemic challenged self-care in some populations, but little is known about how it influenced the self-care of African immigrants living in the US with chronic illnesses such as hypertension and diabetes. Methods: Using a qualitative descriptive design, we enrolled a purposeful sample of 24 sub-Saharan African immigrant adults with self-reported symptomatic hypertension or diabetes. Participants who spoke English were enrolled between March 2020 and September 2021. Individual audio-taped interviews were transcribed and analyzed. Inductive and deductive thematic analysis was guided by the Theory of Self-Care of Chronic Illness. Results: Participants were mean=59 years (range 40-72). Most were Nigerian (n=16), male (n=16), married (n=17), living with family (n=21), highly educated (n=21), and reporting enough income to meet their needs (n=21). Five major themes were identified: (1) Being especially careful in following COVID-19 precautions (e.g., use of facemasks). (2) A focus on self-care maintenance (e.g., healthy diet, staying active while at home). Fear of COVID-19 increased medication adherence. Participants were diligent in taking medications as prescribed due to fear of COVID-19. (3) Close monitoring for symptoms. (4) Trouble reaching providers to discuss symptoms. (5) Access to resources. Participants reported loss of health insurance/jobs and lack of provider access, which impacted their ability to perform self-care. Conclusions: COVID-19 increased focused attention on self-care but also created barriers for sub-Saharan African Immigrants. Most impacted was self-care maintenance. Interventions to promote self-care in this population should leverage heightened vigilance to self-care and address challenges around access to resources.

The Role of Nursing in Managing Chronic Illness: A Review of Patient Outcomes and Quality of Life

The management of chronic illness is a growing priority in healthcare, with nursing playing a critical role in improving patient outcomes and quality of life. This review explores the various nursing interventions that support chronic illness management, including patient education, symptom monitoring, and emotional support. By providing personalized care and fostering self-management skills, nurses contribute to reduced hospital readmissions, improved medication adherence, and enhanced physical and mental health outcomes. Additionally, nursing care significantly influences patients' quality of life, offering emotional support that positively impacts their mental well-being and overall satisfaction. Despite the benefits, challenges such as limited resources, time constraints, and nursing burnout remain barriers to effective care. This review emphasizes the need for continued support for nursing roles in chronic illness management, policy adjustments to address resource limitations, and integration of technology to enhance care delivery. Overall, a strengthened nursing role in chronic illness management not only benefits patient outcomes but also enhances patients' quality of life, underscoring the importance of investment in nursing care to meet the demands of chronic illness in healthcare.

A brief report: Lessons learned using wearable technology to collect data from adults receiving medications for opioid use disorder

ABSTRACT Background Incorporating wearable technology into substance use disorder research enables continuous, objective, and remote data collection, facilitating symptom monitoring to prevent relapse. However, implementation challenges may hinder data collection. This paper aims to assess adherence patterns to a wrist-worn wearable device, and to share lessons learned from incorporating wearable technology to collect physiological data from adults with opioid use disorder. Methods Employing a prospective observational design, we used convenience sampling to recruit adults receiving medications for opioid use disorder in outpatient settings. Wearable adherence was measured by days and nights worn over eight weeks, acceptability by a visual analog scale, and anecdotal notes tracked study activities and challenges. Results Twenty-three participants completed baseline, and 16 (70.0%) completed the study. Daytime and nighttime wearable adherence averaged 60.1% and 47.7%, respectively. Wearable adherence was highest at the earlier phase of the study (67.7%) and plateaued after overtime. User-related and technical challenges included digital illiteracy, protocol nonadherence, low motivation, measurement errors, and short battery life. Unique challenges included wearable design concerns and sleep problems. Conclusions This study demonstrates the feasibility of wearable use and highlights the potential to overcome challenges. Proactively sharing insights can facilitate wearable technology adoption for both participants and researchers.

Examining the clinical role and educational preparation of heart failure nurses across Europe. A survey of the Heart Failure Association (HFA) of the European Society of Cardiology (ESC) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP) of the ESC.

To describe the clinical practice and educational preparation of heart failure (HF) nurses across Europe and determine the key differences between countries. A survey tool was developed, in English, by the Heart Failure Association Patient Care committee of the European Society of Cardiology (ESC). It was translated into eight languages, before electronically disseminated by nurse ambassadors, presidents of HF national societies and through social media. A total of 837 nurses involved in the daily care of patients with HF from 15 countries completed the survey. Most nurses, 78% (n = 395) worked within a hospital outpatient setting, and 51% (n = 431) had access to a specialized HF multidisciplinary team. Nurses performed a range of activities including patient education to promote self-care, virtual and in-person symptom monitoring. A third had more than 5-year experience in cardiac care and 22% (n = 182) prescribed HF medications. There was a significant correlation between HF nurses that prescribed HF medications and access to a specialist multidisciplinary team (p = 0.04). A small number of nurses, mainly from Belgium, supported invasive monitoring (n = 68, 8%) with 14% (n = 120) of mostly Danish nurses supporting exercise programmes. The majority of nurses surveyed were committed to further academic professional development, with 41% (n = 343) having completed a HF course. The role of the HF nurse varies across Europe, however involvement in patient education, symptom monitoring and follow-up remain core to their practice. In specific activities including the prescribing of HF medications and involvement in invasive monitoring, practice has advanced with collaboration in the multidisciplinary team. Consequently, harmonization of education, training and career pathways are required to standardize HF care aligned with expert guidelines across Europe.

Developing a clinical decision support framework for integrating predictive models into routine nursing practices in home health care for patients with heart failure.

The healthcare industry increasingly values high-quality and personalized care. Patients with heart failure (HF) receiving home health care (HHC) often experience hospitalizations due to worsening symptoms and comorbidities. Therefore, close symptom monitoring and timely intervention based on risk prediction could help HHC clinicians prevent emergency department (ED) visits and hospitalizations. This study aims to (1) describe important variables associated with a higher risk of ED visits and hospitalizations in HF patients receiving HHC; (2) map data requirements of a clinical decision support (CDS) tool to the exchangeable data standard for integrating a CDS tool into the care of patients with HF; (3) outline a pipeline for developing a real-time artificial intelligence (AI)-based CDS tool. We used patient data from a large HHC organization in the Northeastern US to determine the factors that can predict ED visits and hospitalizations among patients with HF in HHC (9362 patients in 12,223 care episodes). We examined vital signs, HHC visit details (e.g., the purpose of the visit), and clinical note-derived variables. The study identified critical factors that can predict ED visits and hospitalizations and used these findings to suggest a practical CDS tool for nurses. The tool's proposed design includes a system that can analyze data quickly to offer timely advice to healthcare clinicians. Our research showed that the length of time since a patient was admitted to HHC and how recently they have shown symptoms of HF were significant factors predicting an adverse event. Additionally, we found this information from the last few HHC visits before the occurrence of an ED visit or hospitalization were particularly important in the prediction. One hundred percent of clinical demographic profiles from the Outcome and Assessment Information Set variables were mapped to the exchangeable data standard, while natural language processing-driven variables couldn't be mapped due to their nature, as they are generated from unstructured data. The suggested CDS tool alerts nurses about newly emerging or rising risks, helping them make informed decisions. This study discusses the creation of a time-series risk prediction model and its potential CDS applications within HHC, aiming to enhance patient outcomes, streamline resource utilization, and improve the quality of care for individuals with HF. This study provides a detailed plan for a CDS tool that uses the latest AI technology designed to aid nurses in their day-to-day HHC service. Our proposed CDS tool includes an alert system that serves as a guard rail to prevent ED visits and hospitalizations. This tool can potentially improve how nurses make decisions and improve patient outcomes by providing early warnings about ED visits and hospitalizations.

Trajectories of depressive symptoms in Korean adults with diabetes: Individual differences and associations with life satisfaction and mortality.

We examined trajectories of depressive symptoms and their predictors in adults with diabetes. We assessed whether these trajectories were related to life satisfaction and mortality. Longitudinal, prospective observational study. We analysed data from 1217 adults with diabetes (aged ≥45 years) in the Korean Longitudinal Study of Aging (2006-2018). Three trajectories of depressive symptomology were identified in growth mixture models: low/stable (i.e., low and stable levels of symptoms; 85.56%), high/decreasing (i.e., high levels of symptoms with a decreasing trajectory; 7.47%), and moderate/increasing (i.e., moderate levels of symptoms with an increasing trajectory; 6.98%). Participants with poor perceived health status at baseline were more likely to be in the moderate/increasing or high/decreasing classes than in the low/stable class. The moderate/increasing class had the lowest satisfaction with quality of life, followed by the high/decreasing and low/stable classes. The moderate/increasing and the high/decreasing classes had lower satisfaction with relationships with spouse and children than the low/stable class. The high/decreasing class had a higher mortality risk than the low/stable class. Long-term monitoring of depressive symptoms in adults with diabetes is warranted given their potential adverse impact on life satisfaction and mortality.

Patient and clinician perspectives of an eHealth intervention for supporting cancer treatment in the UK: mixed methods evaluation of the eRAPID randomised controlled trial

ObjectivesDuring 2015–2018, a randomised controlled trial (RCT) evaluated eRAPID, an eHealth intervention designed to capture patient-reported symptoms online during cancer treatment. eRAPID provides patients with advice on when to self-manage...