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1.
CA Cancer J Clin ; 70(3): 182-199, 2020 05.
Artículo en Inglés | MEDLINE | ID: mdl-32311776

RESUMEN

Patient-generated health data (PGHD), or health-related data gathered from patients to help address a health concern, are used increasingly in oncology to make regulatory decisions and evaluate quality of care. PGHD include self-reported health and treatment histories, patient-reported outcomes (PROs), and biometric sensor data. Advances in wireless technology, smartphones, and the Internet of Things have facilitated new ways to collect PGHD during clinic visits and in daily life. The goal of the current review was to provide an overview of the current clinical, regulatory, technological, and analytic landscape as it relates to PGHD in oncology research and care. The review begins with a rationale for PGHD as described by the US Food and Drug Administration, the Institute of Medicine, and other regulatory and scientific organizations. The evidence base for clinic-based and remote symptom monitoring using PGHD is described, with an emphasis on PROs. An overview is presented of current approaches to digital phenotyping or device-based, real-time assessment of biometric, behavioral, self-report, and performance data. Analytic opportunities regarding PGHD are envisioned in the context of big data and artificial intelligence in medicine. Finally, challenges and solutions for the integration of PGHD into clinical care are presented. The challenges include electronic medical record integration of PROs and biometric data, analysis of large and complex biometric data sets, and potential clinic workflow redesign. In addition, there is currently more limited evidence for the use of biometric data relative to PROs. Despite these challenges, the potential benefits of PGHD make them increasingly likely to be integrated into oncology research and clinical care.


Asunto(s)
Inteligencia Artificial , Investigación Biomédica/métodos , Atención a la Salud/estadística & datos numéricos , Oncología Médica/métodos , Neoplasias/terapia , Humanos , Morbilidad , Neoplasias/epidemiología , Estados Unidos/epidemiología
2.
J Gen Intern Med ; 2024 Oct 16.
Artículo en Inglés | MEDLINE | ID: mdl-39414734

RESUMEN

BACKGROUND: Technologies, including mobile health applications (apps) and wearables, offer new potential for gathering patient-generated health data (PGHD) from patients; however, little is known about patient preferences for and willingness to collect and share PGHD with their providers and healthcare systems. OBJECTIVE: Describe how patients use their PGHD and factors important to patients when deciding whether to share PGHD with a healthcare system. DESIGN: Cross-sectional mailed longitudinal survey supplemented with administrative data within the Veterans Health Administration (VHA). SUBJECTS: National sample of Veterans who use VHA healthcare. MAIN MEASURES: Survey questions asked about demographics, willingness to use different devices to collect and share PGHD, what Veterans do with their PGHD, and factors important to Veterans when deciding whether to share PGHD with VHA. Administrative data provided information on Veteran health conditions. Multiple logistic regression models assessed factors associated with sharing PGHD with VHA. KEY RESULTS: Overall, 47% of our analytic cohort (n = 383/807) indicated that they share PGHD collected through apps or digital health devices with VHA. In adjusted logistic regression models, Veterans who believed the following factors were Very Important (versus Somewhat/Not At All Important) had higher odds of sharing PGHD with VHA: if their doctor (OR = 1.4; 95%CI, 1.0-2.0) or other healthcare team members (OR = 1.4; 95%CI, 1.0-1.9) recommended they do so; and knowing that their healthcare team would look at the data (OR = 1.4; 95%CI, 1.0-2.0) or use the information to inform their healthcare (OR = 1.5; 95%CI, 1.1-2.1). CONCLUSIONS: Our data suggest that healthcare team members can influence patient sharing of PGHD, as can a patient's knowledge that PGHD will be used in clinical practice. Efforts to increase the number of patients who share PGHD with a healthcare system may benefit from buy-in among healthcare team members, who appear to play an influential role in patient decisions to share data.

3.
Hematol Oncol ; 42(4): e3292, 2024 Jul.
Artículo en Inglés | MEDLINE | ID: mdl-38847317

RESUMEN

Mogamulizumab is a humanized antibody targeting CC chemokine receptor 4 (CCR4). This post-marketing surveillance was conducted in Japan as a regulatory requirement from 2014 to 2020 to ensure the safety and effectiveness of mogamulizumab in patients with relapsed or refractory (r/r) CCR4-positive peripheral T-cell lymphoma (PTCL) or r/r cutaneous T-cell lymphoma (CTCL). Safety and effectiveness data were collected for up to 31 weeks after treatment initiation. A total of 142 patients were registered; safety was evaluated in 136 patients. The median number of doses was 8.0 (range, 1-18). The main reasons for treatment termination were insufficient response (22.1%) and adverse events (13.2%). The frequency of any grade adverse drug reaction was 57.4%, including skin disorders (26.5%), infections and immune system disorders (16.2%), and infusion-related reactions (13.2%). Graft-versus-host disease, grade 2, developed in one of two patients who underwent allogeneic-hematopoietic stem cell transplantation after receiving mogamulizumab. Effectiveness was evaluated in 131 patients (103 with PTCL; 28 with CTCL). The best overall response rate was 45.8% (PTCL, 47.6%; CTCL, 39.3%). At week 31, the survival rate was 69.0% (95% confidence interval, 59.8%-76.5%) [PTCL, 64.4% (54.0%-73.0%); CTCL, 90.5% (67.0%-97.5%)]. Safety and effectiveness were comparable between patients <70 and ≥ 70 years old and between those with relapsed and refractory disease. The safety and effectiveness of mogamulizumab for PTCL and CTCL in the real world were comparable with the data reported in previous clinical trials. Clinical Trial Registration.


Asunto(s)
Anticuerpos Monoclonales Humanizados , Linfoma Cutáneo de Células T , Linfoma de Células T Periférico , Receptores CCR4 , Humanos , Anticuerpos Monoclonales Humanizados/uso terapéutico , Anticuerpos Monoclonales Humanizados/efectos adversos , Anticuerpos Monoclonales Humanizados/administración & dosificación , Masculino , Femenino , Anciano , Persona de Mediana Edad , Receptores CCR4/antagonistas & inhibidores , Adulto , Japón , Linfoma Cutáneo de Células T/tratamiento farmacológico , Linfoma Cutáneo de Células T/patología , Linfoma de Células T Periférico/tratamiento farmacológico , Anciano de 80 o más Años , Vigilancia de Productos Comercializados , Recurrencia Local de Neoplasia/tratamiento farmacológico , Recurrencia Local de Neoplasia/patología , Adulto Joven , Resistencia a Antineoplásicos
4.
J Med Internet Res ; 26: e49320, 2024 May 31.
Artículo en Inglés | MEDLINE | ID: mdl-38820580

RESUMEN

BACKGROUND: Mobile health (mHealth) uses mobile technologies to promote wellness and help disease management. Although mHealth solutions used in the clinical setting have typically been medical-grade devices, passive and active sensing capabilities of consumer-grade devices like smartphones and activity trackers have the potential to bridge information gaps regarding patients' behaviors, environment, lifestyle, and other ubiquitous data. Individuals are increasingly adopting mHealth solutions, which facilitate the collection of patient-generated health data (PGHD). Health care professionals (HCPs) could potentially use these data to support care of chronic conditions. However, there is limited research on real-life experiences of HPCs using PGHD from consumer-grade mHealth solutions in the clinical context. OBJECTIVE: This systematic review aims to analyze existing literature to identify how HCPs have used PGHD from consumer-grade mobile devices in the clinical setting. The objectives are to determine the types of PGHD used by HCPs, in which health conditions they use them, and to understand the motivations behind their willingness to use them. METHODS: A systematic literature review was the main research method to synthesize prior research. Eligible studies were identified through comprehensive searches in health, biomedicine, and computer science databases, and a complementary hand search was performed. The search strategy was constructed iteratively based on key topics related to PGHD, HCPs, and mobile technologies. The screening process involved 2 stages. Data extraction was performed using a predefined form. The extracted data were summarized using a combination of descriptive and narrative syntheses. RESULTS: The review included 16 studies. The studies spanned from 2015 to 2021, with a majority published in 2019 or later. Studies showed that HCPs have been reviewing PGHD through various channels, including solutions portals and patients' devices. PGHD about patients' behavior seem particularly useful for HCPs. Our findings suggest that PGHD are more commonly used by HCPs to treat conditions related to lifestyle, such as diabetes and obesity. Physicians were the most frequently reported users of PGHD, participating in more than 80% of the studies. CONCLUSIONS: PGHD collection through mHealth solutions has proven beneficial for patients and can also support HCPs. PGHD have been particularly useful to treat conditions related to lifestyle, such as diabetes, cardiovascular diseases, and obesity, or in domains with high levels of uncertainty, such as infertility. Integrating PGHD into clinical care poses challenges related to privacy and accessibility. Some HCPs have identified that though PGHD from consumer devices might not be perfect or completely accurate, their perceived clinical value outweighs the alternative of having no data. Despite their perceived value, our findings reveal their use in clinical practice is still scarce. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/39389.


Asunto(s)
Personal de Salud , Datos de Salud Generados por el Paciente , Telemedicina , Humanos , Personal de Salud/psicología , Personal de Salud/estadística & datos numéricos , Teléfono Inteligente
5.
J Med Internet Res ; 26: e53327, 2024 May 16.
Artículo en Inglés | MEDLINE | ID: mdl-38754098

RESUMEN

BACKGROUND: The increased pervasiveness of digital health technology is producing large amounts of person-generated health data (PGHD). These data can empower people to monitor their health to promote prevention and management of disease. Women make up one of the largest groups of consumers of digital self-tracking technology. OBJECTIVE: In this scoping review, we aimed to (1) identify the different areas of women's health monitored using PGHD from connected health devices, (2) explore personal metrics collected through these technologies, and (3) synthesize facilitators of and barriers to women's adoption and use of connected health devices. METHODS: Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for scoping reviews, we searched 5 databases for articles published between January 1, 2015, and February 29, 2020. Papers were included if they targeted women or female individuals and incorporated digital health tools that collected PGHD outside a clinical setting. RESULTS: We included a total of 406 papers in this review. Articles on the use of PGHD for women steadily increased from 2015 to 2020. The health areas that the articles focused on spanned several topics, with pregnancy and the postpartum period being the most prevalent followed by cancer. Types of digital health used to collect PGHD included mobile apps, wearables, websites, the Internet of Things or smart devices, 2-way messaging, interactive voice response, and implantable devices. A thematic analysis of 41.4% (168/406) of the papers revealed 6 themes regarding facilitators of and barriers to women's use of digital health technology for collecting PGHD: (1) accessibility and connectivity, (2) design and functionality, (3) accuracy and credibility, (4) audience and adoption, (5) impact on community and health service, and (6) impact on health and behavior. CONCLUSIONS: Leading up to the COVID-19 pandemic, the adoption of digital health tools to address women's health concerns was on a steady rise. The prominence of tools related to pregnancy and the postpartum period reflects the strong focus on reproductive health in women's health research and highlights opportunities for digital technology development in other women's health topics. Digital health technology was most acceptable when it was relevant to the target audience, was seen as user-friendly, and considered women's personalization preferences while also ensuring accuracy of measurements and credibility of information. The integration of digital technologies into clinical care will continue to evolve, and factors such as liability and health care provider workload need to be considered. While acknowledging the diversity of individual needs, the use of PGHD can positively impact the self-care management of numerous women's health journeys. The COVID-19 pandemic has ushered in increased adoption and acceptance of digital health technology. This study could serve as a baseline comparison for how this field has evolved as a result. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/26110.


Asunto(s)
Salud de la Mujer , Humanos , Femenino , Datos de Salud Generados por el Paciente , COVID-19/epidemiología , Embarazo
6.
J Med Internet Res ; 26: e51059, 2024 May 17.
Artículo en Inglés | MEDLINE | ID: mdl-38758583

RESUMEN

BACKGROUND: Patients with advanced cancer undergoing chemotherapy experience significant symptoms and declines in functional status, which are associated with poor outcomes. Remote monitoring of patient-reported outcomes (PROs; symptoms) and step counts (functional status) may proactively identify patients at risk of hospitalization or death. OBJECTIVE: The aim of this study is to evaluate the association of (1) longitudinal PROs with step counts and (2) PROs and step counts with hospitalization or death. METHODS: The PROStep randomized trial enrolled 108 patients with advanced gastrointestinal or lung cancers undergoing cytotoxic chemotherapy at a large academic cancer center. Patients were randomized to weekly text-based monitoring of 8 PROs plus continuous step count monitoring via Fitbit (Google) versus usual care. This preplanned secondary analysis included 57 of 75 patients randomized to the intervention who had PRO and step count data. We analyzed the associations between PROs and mean daily step counts and the associations of PROs and step counts with the composite outcome of hospitalization or death using bootstrapped generalized linear models to account for longitudinal data. RESULTS: Among 57 patients, the mean age was 57 (SD 10.9) years, 24 (42%) were female, 43 (75%) had advanced gastrointestinal cancer, 14 (25%) had advanced lung cancer, and 25 (44%) were hospitalized or died during follow-up. A 1-point weekly increase (on a 32-point scale) in aggregate PRO score was associated with 247 fewer mean daily steps (95% CI -277 to -213; P<.001). PROs most strongly associated with step count decline were patient-reported activity (daily step change -892), nausea score (-677), and constipation score (524). A 1-point weekly increase in aggregate PRO score was associated with 20% greater odds of hospitalization or death (adjusted odds ratio [aOR] 1.2, 95% CI 1.1-1.4; P=.01). PROs most strongly associated with hospitalization or death were pain (aOR 3.2, 95% CI 1.6-6.5; P<.001), decreased activity (aOR 3.2, 95% CI 1.4-7.1; P=.01), dyspnea (aOR 2.6, 95% CI 1.2-5.5; P=.02), and sadness (aOR 2.1, 95% CI 1.1-4.3; P=.03). A decrease in 1000 steps was associated with 16% greater odds of hospitalization or death (aOR 1.2, 95% CI 1.0-1.3; P=.03). Compared with baseline, mean daily step count decreased 7% (n=274 steps), 9% (n=351 steps), and 16% (n=667 steps) in the 3, 2, and 1 weeks before hospitalization or death, respectively. CONCLUSIONS: In this secondary analysis of a randomized trial among patients with advanced cancer, higher symptom burden and decreased step count were independently associated with and predictably worsened close to hospitalization or death. Future interventions should leverage longitudinal PRO and step count data to target interventions toward patients at risk for poor outcomes. TRIAL REGISTRATION: ClinicalTrials.gov NCT04616768; https://clinicaltrials.gov/study/NCT04616768. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2021-054675.


Asunto(s)
Hospitalización , Medición de Resultados Informados por el Paciente , Humanos , Persona de Mediana Edad , Masculino , Hospitalización/estadística & datos numéricos , Femenino , Anciano , Neoplasias/tratamiento farmacológico , Neoplasias/mortalidad , Neoplasias Pulmonares/tratamiento farmacológico , Neoplasias Pulmonares/mortalidad , Antineoplásicos/uso terapéutico , Antineoplásicos/efectos adversos , Neoplasias Gastrointestinales/tratamiento farmacológico , Neoplasias Gastrointestinales/mortalidad
7.
J Surg Oncol ; 127(1): 192-202, 2023 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-36169200

RESUMEN

BACKGROUND: The feasibility of remote perioperative telemonitoring of patient-generated physiologic health data and patient-reported outcomes in a high risk complex general and urologic oncology surgery population is evaluated. METHODS: Complex general surgical/urologic oncology patients wore a pedometer, completed ePROs (electronic patient-reported outcome surveys) and record their vitals (weight, pulse, pulse oximetry, blood pressure, and temperature) via a telehealth app platform. Feasibility (% adherence) was assessed as the primary outcome measure. RESULTS: Twenty-one patients with a median age 58 (32-82) years were included. The readmission rate was 33% and the incidence of ≥Grade 3a morbidity was 24%. Adherence to vital sign and ePRO measurements was 95% before surgery, 91% at discharge, and 82%, 68%, and 64% at postdischarge d2, 7, 14, and 30, respectively. There was significant worsening of mobility, self-care and usual daily activity at postdischarge d2 compared to preoperative baseline (p < 0.05). Median daily preoperative steps taken by patients with

Asunto(s)
Oncología Quirúrgica , Telemedicina , Humanos , Persona de Mediana Edad , Alta del Paciente , Estudios de Factibilidad , Cuidados Posteriores
8.
J Med Internet Res ; 25: e42743, 2023 02 27.
Artículo en Inglés | MEDLINE | ID: mdl-36848185

RESUMEN

BACKGROUND: Wearable devices have limited ability to store and process such data. Currently, individual users or data aggregators are unable to monetize or contribute such data to wider analytics use cases. When combined with clinical health data, such data can improve the predictive power of data-driven analytics and can proffer many benefits to improve the quality of care. We propose and provide a marketplace mechanism to make these data available while benefiting data providers. OBJECTIVE: We aimed to propose the concept of a decentralized marketplace for patient-generated health data that can improve provenance, data accuracy, security, and privacy. Using a proof-of-concept prototype with an interplanetary file system (IPFS) and Ethereum smart contracts, we aimed to demonstrate decentralized marketplace functionality with the blockchain. We also aimed to illustrate and demonstrate the benefits of such a marketplace. METHODS: We used a design science research methodology to define and prototype our decentralized marketplace and used the Ethereum blockchain, solidity smart-contract programming language, the web3.js library, and node.js with the MetaMask application to prototype our system. RESULTS: We designed and implemented a prototype of a decentralized health care marketplace catering to health data. We used an IPFS to store data, provide an encryption scheme for the data, and provide smart contracts to communicate with users on the Ethereum blockchain. We met the design goals we set out to accomplish in this study. CONCLUSIONS: A decentralized marketplace for trading patient-generated health data can be created using smart-contract technology and IPFS-based data storage. Such a marketplace can improve quality, availability, and provenance and satisfy data privacy, access, auditability, and security needs for such data when compared with centralized systems.


Asunto(s)
Cadena de Bloques , Humanos , Exactitud de los Datos , Pacientes , Privacidad , Lenguajes de Programación
9.
J Med Internet Res ; 25: e47006, 2023 12 29.
Artículo en Inglés | MEDLINE | ID: mdl-38157233

RESUMEN

BACKGROUND: In the burgeoning area of clinical digital phenotyping research, there is a dearth of literature that details methodology, including the key challenges and dilemmas in developing and implementing a successful architecture for technological infrastructure, patient engagement, longitudinal study participation, and successful reporting and analysis of diverse passive and active digital data streams. OBJECTIVE: This article provides a narrative rationale for our study design in the context of the current evidence base and best practices, with an emphasis on our initial lessons learned from the implementation challenges and successes of this digital phenotyping study. METHODS: We describe the design and implementation approach for a digital phenotyping pilot feasibility study with attention to synthesizing key literature and the reasoning for pragmatic adaptations in implementing a multisite study encompassing distinct geographic and population settings. This methodology was used to recruit patients as study participants with a clinician-validated diagnostic history of unipolar depression, bipolar I disorder, or bipolar II disorder, or healthy controls in 2 geographically distinct health care systems for a longitudinal digital phenotyping study of mood disorders. RESULTS: We describe the feasibility of a multisite digital phenotyping pilot study for patients with mood disorders in terms of passively and actively collected phenotyping data quality and enrollment of patients. Overall data quality (assessed as the amount of sensor data obtained vs expected) was high compared to that in related studies. Results were reported on the relevant demographic features of study participants, revealing recruitment properties of age (mean subgroup age ranged from 31 years in the healthy control subgroup to 38 years in the bipolar I disorder subgroup), sex (predominance of female participants, with 7/11, 64% females in the bipolar II disorder subgroup), and smartphone operating system (iOS vs Android; iOS ranged from 7/11, 64% in the bipolar II disorder subgroup to 29/32, 91% in the healthy control subgroup). We also described implementation considerations around digital phenotyping research for mood disorders and other psychiatric conditions. CONCLUSIONS: Digital phenotyping in affective disorders is feasible on both Android and iOS smartphones, and the resulting data quality using an open-source platform is higher than that in comparable studies. While the digital phenotyping data quality was independent of gender and race, the reported demographic features of study participants revealed important information on possible selection biases that may result from naturalistic research in this domain. We believe that the methodology described will be readily reproducible and generalizable to other study settings and patient populations given our data on deployment at 2 unique sites.


Asunto(s)
Trastorno Bipolar , Trastornos del Humor , Humanos , Femenino , Adulto , Masculino , Trastornos del Humor/diagnóstico , Estudios de Factibilidad , Proyectos Piloto , Estudios Longitudinales , Trastorno Bipolar/diagnóstico
10.
J Med Internet Res ; 25: e46992, 2023 10 11.
Artículo en Inglés | MEDLINE | ID: mdl-37819698

RESUMEN

BACKGROUND: Digital health technologies (DHTs) play an ever-expanding role in health care management and delivery. Beyond their use as interventions, DHTs also serve as a vehicle for real-world data collection to characterize patients, their care journeys, and their responses to other clinical interventions. There is a need to comprehensively map the evidence-across all conditions and technology types-on DHT measurement of patient outcomes in the real world. OBJECTIVE: We aimed to investigate the use of DHTs to measure real-world clinical outcomes using patient-generated data. METHODS: We conducted this systematic scoping review in accordance with the Joanna Briggs Institute methodology. Detailed eligibility criteria documented in a preregistered protocol informed a search strategy for the following databases: MEDLINE (Ovid), CINAHL, Cochrane (CENTRAL), Embase, PsycINFO, ClinicalTrials.gov, and the EU Clinical Trials Register. We considered studies published between 2000 and 2022 wherein digital health data were collected, passively or actively, from patients with any specified health condition outside of clinical visits. Categories for key concepts, such as DHT type and analytical applications, were established where needed. Following screening and full-text review, data were extracted and analyzed using predefined fields, and findings were reported in accordance with established guidelines. RESULTS: The search strategy identified 11,015 publications, with 7308 records after duplicates and reviews were removed. After screening and full-text review, 510 studies were included for extraction. These studies encompassed 169 different conditions in over 20 therapeutic areas and 44 countries. The DHTs used for mental health and addictions research (111/510, 21.8%) were the most prevalent. The most common type of DHT, mobile apps, was observed in approximately half of the studies (250/510, 49%). Most studies used only 1 DHT (346/510, 67.8%); however, the majority of technologies used were able to collect more than 1 type of data, with the most common being physiological data (189/510, 37.1%), clinical symptoms data (188/510, 36.9%), and behavioral data (171/510, 33.5%). Overall, there has been real growth in the depth and breadth of evidence, number of DHT types, and use of artificial intelligence and advanced analytics over time. CONCLUSIONS: This scoping review offers a comprehensive view of the variety of types of technology, data, collection methods, analytical approaches, and therapeutic applications within this growing body of evidence. To unlock the full potential of DHT for measuring health outcomes and capturing digital biomarkers, there is a need for more rigorous research that goes beyond technology validation to demonstrate whether robust real-world data can be reliably captured from patients in their daily life and whether its capture improves patient outcomes. This study provides a valuable repository of DHT studies to inform subsequent research by health care providers, policy makers, and the life sciences industry. TRIAL REGISTRATION: Open Science Framework 5TMKY; https://osf.io/5tmky/.


Asunto(s)
Salud Digital , Aplicaciones Móviles , Humanos , Inteligencia Artificial , Tecnología Digital , Autocuidado/métodos
11.
Sensors (Basel) ; 23(5)2023 Feb 24.
Artículo en Inglés | MEDLINE | ID: mdl-36904750

RESUMEN

People with diabetes-related foot ulcers (DFUs) need to perform self-care consistently over many months to promote healing and to mitigate risks of hospitalisation and amputation. However, during that time, improvement in their DFU can be hard to detect. Hence, there is a need for an accessible method to self-monitor DFUs at home. We developed a new mobile phone app, "MyFootCare", to self-monitor DFU healing progression from photos of the foot. The aim of this study is to evaluate the engagement and perceived value of MyFootCare for people with a plantar DFU over 3 months' duration. Data are collected through app log data and semi-structured interviews (weeks 0, 3, and 12) and analysed through descriptive statistics and thematic analysis. Ten out of 12 participants perceive MyFootCare as valuable to monitor progress and to reflect on events that affected self-care, and seven participants see it as potentially valuable to enhance consultations. Three app engagement patterns emerge: continuous, temporary, and failed engagement. These patterns highlight enablers for self-monitoring (such as having MyFootCare installed on the participant's phone) and barriers (such as usability issues and lack of healing progress). We conclude that while many people with DFUs perceive app-based self-monitoring as valuable, actual engagement can be achieved for some but not for all people because of various facilitators and barriers. Further research should target improving usability, accuracy and sharing with healthcare professionals and test clinical outcomes when using the app.


Asunto(s)
Teléfono Celular , Diabetes Mellitus , Pie Diabético , Aplicaciones Móviles , Humanos , Pie Diabético/diagnóstico , Pie , Amputación Quirúrgica
12.
J Pediatr Nurs ; 69: 10-17, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-36592607

RESUMEN

BACKGROUND: The increase in telehealth usage has sustained since the beginning of the COVID-19 pandemic. While Remote Patient Monitoring (RPM) programs are abundantly used in the management of adults, pediatric RPM programs remain rare. METHODS: An RPM department was developed to serve several, multi-specialty pediatric programs. This department uses a centralized nursing team that manages all patients enrolled in RPM programs. Each program is unique and created in partnership with the centralized nurses and the ambulatory care teams. The various programs allow for transmission of patient- and caregiver-generated health data and consistent communication between the patient or caregiver and the managing providers, allowing for real-time plan adaptation. FINDINGS: Over 1200 patients have been managed through the 18 various RPM programs. Approximately 300 patients are monitored each month by the centralized nursing team. Patient and caregiver experience has been high due to resources offered including on-demand video visits and text messaging with the nursing team. DISCUSSION: Multi-specialty RPM departments help to expand the reach of an institution and provide care to more patients. Quality improvement must be ongoing to ensure equity of participation and perceived benefit of the programs for both providers and patients and caregivers. APPLICATION TO PRACTICE: Pediatric RPM programs can improve patient care delivery by decreasing days away from home while improving access to care. Ensuring equitable opportunity for patient participation is imperative in achieving success for an RPM department.


Asunto(s)
COVID-19 , Telemedicina , Adulto , Humanos , Niño , Pandemias , Monitoreo Fisiológico , Atención Ambulatoria
13.
Ann Fam Med ; 20(4): 305-311, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-35879086

RESUMEN

PURPOSE: Evidence shows the value of home blood pressure (BP) monitoring in hypertension management. Questions exist about how to effectively incorporate these readings into BP follow-up visits. We developed and implemented a tool that combines clinical and home BP readings into an electronic health record (EHR)-integrated visualization tool. We examined how this tool was used during primary care visits and its effect on physician-patient communication and decision making about hypertension management, comparing it with home BP readings on paper. METHODS: We video recorded the hypertension follow-up visits of 73 patients with 15 primary care physicians between July 2018 and April 2019. During visits, physicians reviewed home BP readings with patients, either directly from paper or as entered into the EHR visualization tool. We used conversation analysis to analyze the recordings. RESULTS: Home BP readings were viewed on paper for 26 patients and in the visualization tool for 47 patients. Access to home BP readings during hypertension management visits, regardless of viewing mode, positioned the physician and patient to assess BP management and make decisions about treatment modification, if needed. Length of BP discussion with the visualization tool was similar to or shorter than that with paper. Advantages of the visualization tool included ease of use, and enhanced and faster sense making and decision making. Successful use of the tool required patients' ability to obtain their BP readings and enter them into the EHR via a portal, and an examination room configuration that allowed for screen sharing. CONCLUSIONS: Reviewing home BP readings using a visualization tool is feasible and enhances sense making and patient engagement in decision making. Practices and their patients need appropriate infrastructure to realize these benefits.


Asunto(s)
Visualización de Datos , Hipertensión , Presión Sanguínea , Determinación de la Presión Sanguínea , Monitoreo Ambulatorio de la Presión Arterial , Toma de Decisiones Clínicas , Humanos , Hipertensión/tratamiento farmacológico , Atención Primaria de Salud
14.
J Med Internet Res ; 24(4): e28867, 2022 04 12.
Artículo en Inglés | MEDLINE | ID: mdl-35412458

RESUMEN

BACKGROUND: Patient-generated health data are increasingly used to record health and well-being concerns and engage patients in clinical care. Patient-generated photographs and videos are accessible and meaningful to patients, making them especially relevant during the current COVID-19 pandemic. However, a systematic review of photos and videos used by patients across different areas of health and well-being is lacking. OBJECTIVE: This review aims to synthesize the existing literature on the health and well-being contexts in which patient-generated photos and videos are used, the value gained by patients and health professionals, and the challenges experienced. METHODS: Guided by a framework for scoping reviews, we searched eight health databases (CINAHL, Cochrane Library, Embase, PsycINFO, PubMed, MEDLINE, Scopus, and Web of Science) and one computing database (ACM), returning a total of 28,567 studies. After removing duplicates and screening based on the predefined inclusion criteria, we identified 110 relevant articles. Data were charted and articles were analyzed following an iterative thematic approach with the assistance of NVivo software (version 12; QSR International). RESULTS: Patient-generated photos and videos are used across a wide range of health care services (39/110, 35.5% articles), for example, to diagnose skin lesions, assess dietary intake, and reflect on personal experiences during therapy. In addition, patients use them to self-manage health and well-being concerns (33/110, 30%) and to share personal health experiences via social media (36/110, 32.7%). Photos and videos create significant value for health care (59/110, 53.6%), where images support diagnosis, explanation, and treatment (functional value). They also provide value directly to patients through enhanced self-determination (39/110, 35.4%), social (33/110, 30%), and emotional support (21/110, 19.1%). However, several challenges emerge when patients create, share, and examine photos and videos, such as limited accessibility (16/110, 14.5%), incomplete image sets (23/110, 20.9%), and misinformation through photos and videos shared on social media (17/110, 15.5%). CONCLUSIONS: This review shows that photos and videos engage patients in meaningful ways across different health care activities (eg, diagnosis, treatment, and self-care) for various health conditions. Although photos and videos require effort to capture and involve challenges when patients want to use them in health care, they also engage and empower patients, generating unique value. This review highlights areas for future research and strategies for addressing these challenges.


Asunto(s)
COVID-19 , Pandemias , Comunicación , Personal de Salud , Humanos , Grabación de Cinta de Video
15.
J Med Internet Res ; 24(4): e30898, 2022 04 29.
Artículo en Inglés | MEDLINE | ID: mdl-35486428

RESUMEN

BACKGROUND: The emerging health technologies and digital services provide effective ways of collecting health information and gathering patient-generated health data (PGHD), which provide a more holistic view of a patient's health and quality of life over time, increase visibility into a patient's adherence to a treatment plan or study protocol, and enable timely intervention before a costly care episode. OBJECTIVE: Through a national cross-sectional survey in the United States, we aimed to describe and compare the characteristics of populations with and without mental health issues (depression or anxiety disorders), including physical health, sleep, and alcohol use. We also examined the patterns of social networking service use, PGHD, and attitudes toward health information sharing and activities among the participants, which provided nationally representative estimates. METHODS: We drew data from the 2019 Health Information National Trends Survey of the National Cancer Institute. The participants were divided into 2 groups according to mental health status. Then, we described and compared the characteristics of the social determinants of health, health status, sleeping and drinking behaviors, and patterns of social networking service use and health information data sharing between the 2 groups. Multivariable logistic regression models were applied to assess the predictors of mental health. All the analyses were weighted to provide nationally representative estimates. RESULTS: Participants with mental health issues were significantly more likely to be younger, White, female, and lower-income; have a history of chronic diseases; and be less capable of taking care of their own health. Regarding behavioral health, they slept <6 hours on average, had worse sleep quality, and consumed more alcohol. In addition, they were more likely to visit and share health information on social networking sites, write online diary blogs, participate in online forums or support groups, and watch health-related videos. CONCLUSIONS: This study illustrates that individuals with mental health issues have inequitable social determinants of health, poor physical health, and poor behavioral health. However, they are more likely to use social networking platforms and services, share their health information, and actively engage with PGHD. Leveraging these digital technologies and services could be beneficial for developing tailored and effective strategies for self-monitoring and self-management.


Asunto(s)
Informática Médica , Salud Mental , Estudios Transversales , Tecnología Digital , Femenino , Humanos , Calidad de Vida , Red Social , Estados Unidos
16.
Malays J Med Sci ; 29(3): 99-109, 2022 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-35846490

RESUMEN

Background: Patient-generated health data (PGHD) is health-related data captured and recorded by patients which informs healthcare practitioners (HCP) about the patients' health status between clinic visits. PGHD could be attributed as part of digital health and technological advancement. Methods: This is an exploratory qualitative study to explore the current PGHD usage and the views and experience of HCP towards PGHD. Semi-structured in-depth online interviews based on the modified Unified Theory of Acceptance and Use of Technology (UTAUT) were conducted with seven Hospital Kuala Lumpur medical- and surgical-based HCP specialists between October 2019 and February 2020. Purposive sampling method was applied to ensure speciality diversity among study respondents. Thematic analysis was performed on the interview transcripts. Results: Four main themes were identified namely the PGHD usage among the study respondents, the benefits of PGHD, the challenges of PGHD usage and the effort needed to use the PGHD. The main finding of this study includes the exploration of the benefits of PGHD usage such as efficient data management in aiding clinical consultation. Nonetheless, the clinical decision making based on PGHD is limited due to poor adoption of PGHD and unavailability of electronic data. This could be due to the lack of awareness, ICT infrastructure, funding, poor health literacy and language and cultural problems. Conclusion: PGHD has huge potential to be adopted in the clinical setting and subsequently benefiting the patients. However, parallel supportive environment is essential in supporting the usage of PGHD in the clinical setting.

17.
Rheumatology (Oxford) ; 60(SI): SI77-SI84, 2021 10 09.
Artículo en Inglés | MEDLINE | ID: mdl-33629107

RESUMEN

OBJECTIVES: During the COVID-19 pandemic, much communication occurred online, through social media. This study aimed to provide patient perspective data on how the COVID-19 pandemic impacted people with rheumatic and musculoskeletal diseases (RMDs), using Twitter-based patient-generated health data (PGHD). METHODS: A convenience sample of Twitter messages in English posted by people with RMDs was extracted between 1 March and 12 July 2020 and examined using thematic analysis. Included were Twitter messages that mentioned keywords and hashtags related to both COVID-19 (or SARS-CoV-2) and select RMDs. The RMDs monitored included inflammatory-driven (joint) conditions (ankylosing spondylitis, RA, PsA, lupus/SLE and gout). RESULTS: The analysis included 569 tweets by 375 Twitter users with RMDs across several countries. Eight themes emerged regarding the impact of the COVID-19 pandemic on people with RMDs: (i) lack of understanding of SARS-CoV-2/COVID-19; (ii) critical changes in health behaviour; (iii) challenges in healthcare practice and communication with healthcare professionals; (iv) difficulties with access to medical care; (v) negative impact on physical and mental health, coping strategies; (vi) issues around work participation; (vii) negative effects of the media; and (viii) awareness-raising. CONCLUSION: The findings show that Twitter serves as a real-time data source to understand the impact of the COVID-19 pandemic on people with RMDs. The platform provided 'early signals' of potentially critical health behaviour changes. Future epidemics might benefit from the real-time use of Twitter-based PGHD to identify emerging health needs, facilitate communication and inform clinical practice decisions.


Asunto(s)
COVID-19/prevención & control , Enfermedades Musculoesqueléticas/psicología , Cuarentena/psicología , Enfermedades Reumáticas/psicología , Medios de Comunicación Sociales , Adaptación Psicológica , Comunicación , Conductas Relacionadas con la Salud , Accesibilidad a los Servicios de Salud , Humanos , SARS-CoV-2
18.
J Surg Oncol ; 123(5): 1345-1352, 2021 Apr.
Artículo en Inglés | MEDLINE | ID: mdl-33621378

RESUMEN

BACKGROUND AND OBJECTIVES: Post-discharge oncologic surgical complications are costly for patients, families, and healthcare systems. The capacity to predict complications and early intervention can improve postoperative outcomes. In this proof-of-concept study, we used a machine learning approach to explore the potential added value of patient-reported outcomes (PROs) and patient-generated health data (PGHD) in predicting post-discharge complications for gastrointestinal (GI) and lung cancer surgery patients. METHODS: We formulated post-discharge complication prediction as a binary classification task. Features were extracted from clinical variables, PROs (MD Anderson Symptom Inventory [MDASI]), and PGHD (VivoFit) from a cohort of 52 patients with 134 temporal observation points pre- and post-discharge that were collected from two pilot studies. We trained and evaluated supervised learning classifiers via nested cross-validation. RESULTS: A logistic regression model with L2 regularization trained with clinical data, PROs and PGHD from wearable pedometers achieved an area under the receiver operating characteristic of 0.74. CONCLUSIONS: PROs and PGHDs captured through remote patient telemonitoring approaches have the potential to improve prediction performance for postoperative complications.


Asunto(s)
Cuidados Posteriores/normas , Neoplasias/cirugía , Alta del Paciente , Evaluación del Resultado de la Atención al Paciente , Medición de Resultados Informados por el Paciente , Complicaciones Posoperatorias/fisiopatología , Tecnología Inalámbrica/instrumentación , Adulto , Anciano , Anciano de 80 o más Años , Estudios de Cohortes , Femenino , Estudios de Seguimiento , Humanos , Aprendizaje Automático , Masculino , Persona de Mediana Edad , Neoplasias/patología , Valor Predictivo de las Pruebas , Recuperación de la Función , Adulto Joven
19.
J Biomed Inform ; 113: 103639, 2021 01.
Artículo en Inglés | MEDLINE | ID: mdl-33316422

RESUMEN

Decision-making related to health is complex. Machine learning (ML) and patient generated data can identify patterns and insights at the individual level, where human cognition falls short, but not all ML-generated information is of equal utility for making health-related decisions. We develop and apply attributable components analysis (ACA), a method inspired by optimal transport theory, to type 2 diabetes self-monitoring data to identify patterns of association between nutrition and blood glucose control. In comparison with linear regression, we found that ACA offers a number of characteristics that make it promising for use in decision support applications. For example, ACA was able to identify non-linear relationships, was more robust to outliers, and offered broader and more expressive uncertainty estimates. In addition, our results highlight a tradeoff between model accuracy and interpretability, and we discuss implications for ML-driven decision support systems.


Asunto(s)
Diabetes Mellitus Tipo 2 , Diabetes Mellitus Tipo 2/diagnóstico , Diabetes Mellitus Tipo 2/terapia , Humanos , Aprendizaje Automático
20.
J Med Internet Res ; 23(2): e23493, 2021 02 25.
Artículo en Inglés | MEDLINE | ID: mdl-33629962

RESUMEN

BACKGROUND: Use of patient portals has been associated with positive outcomes in patient engagement and satisfaction. Portal studies have also connected portal use, as well as the nature of users' interactions with portals, and the contents of their generated data to meaningful cost and quality outcomes. Incentive programs in the United States have encouraged uptake of health information technology, including patient portals, by setting standards for meaningful use of such technology. However, despite widespread interest in patient portal use and adoption, studies on patient portals differ in actual metrics used to operationalize and track utilization, leading to unsystematic and incommensurable characterizations of use. No known review has systematically assessed the measurements used to investigate patient portal utilization. OBJECTIVE: The objective of this study was to apply systematic review criteria to identify and compare methods for quantifying and reporting patient portal use. METHODS: Original studies with quantifiable metrics of portal use published in English between 2014 and the search date of October 17, 2018, were obtained from PubMed using the Medical Subject Heading term "Patient Portals" and related keyword searches. The first search round included full text review of all results to confirm a priori data charting elements of interest and suggest additional categories inductively; this round was supplemented by the retrieval of works cited in systematic reviews (based on title screening of all citations). An additional search round included broader keywords identified during the full-text review of the first round. Second round results were screened at abstract level for inclusion and confirmed by at least two raters. Included studies were analyzed for metrics related to basic use/adoption, frequency of use, duration metrics, intensity of use, and stratification of users into "super user" or high utilizers. Additional categories related to provider (including care team/administrative) use of the portal were identified inductively. Additional analyses included metrics aligned with meaningful use stage 2 (MU-2) categories employed by the US Centers for Medicare and Medicaid Services and the association between the number of portal metrics examined and the number of citations and the journal impact factor. RESULTS: Of 315 distinct search results, 87 met the inclusion criteria. Of the a priori metrics, plus provider use, most studies included either three (26 studies, 30%) or four (23 studies, 26%) metrics. Nine studies (10%) only reported the patient use/adoption metric and only one study (1%) reported all six metrics. Of the US-based studies (n=76), 18 (24%) were explicitly motivated by MU-2 compliance; 40 studies (53%) at least mentioned these incentives, but only 6 studies (8%) presented metrics from which compliance rates could be inferred. Finally, the number of metrics examined was not associated with either the number of citations or the publishing journal's impact factor. CONCLUSIONS: Portal utilization measures in the research literature can fall below established standards for "meaningful" or they can substantively exceed those standards in the type and number of utilization properties measured. Understanding how patient portal use has been defined and operationalized may encourage more consistent, well-defined, and perhaps more meaningful standards for utilization, informing future portal development.


Asunto(s)
Participación del Paciente/métodos , Portales del Paciente/normas , Revisión de Utilización de Recursos/métodos , Humanos
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