Dataset Information

Creating Consumer-Generated Health Data: Interviews and a Pilot Trial Exploring How and Why Patients Engage.

ABSTRACT:

Background

Consumer-generated health data (CGHD) are any clinically relevant data collected by patients or their carers (consumers) that may improve health care outcomes. Like patient experience measures, these data reflect the consumer perspective and is part of a patient-centric agenda. The use of CGHD is believed to enhance diagnosis, patient engagement, and thus foster an improved therapeutic partnership with health care providers.

Objective

The aim of this study was to further identify how these data were used by consumers and how it influences engagement via a validated framework. In addition, carer data has not been explored for the purpose of engagement.

Methods

Study 1 used interviews with CGHD-experienced patients, carers, and doctors to understand attitudes about data collection and use, developing an ontological framework. Study 2 was a pilot trial with carers (parents) of children undergoing laparoscopic appendectomy. For 10 days carers generated and emailed surgical site photographs to a tertiary children's hospital. Subsequently, carers were interviewed about the engagement framework. In total, 60 interviews were analyzed using theme and content analysis.

Results

This study validates a framework anchored in engagement literature, which categorizes CGHD engagement outcomes into 4 domains: physiological, cognitive, emotional, and behavioral. CGHD use is complex, interconnected, and can be organized into 10 themes within these 4 domains.

Conclusions

CGHD can instigate an ecosystem of engagement and provide clinicians with an enhanced therapeutic relationship through an extended view into the patient's world. In addition to clinical diagnosis and efficient use of health care resources, data offer another tool to manage consumers service experience, especially the emotions associated with the health care journey. Collection and use of data increases consumers sense of reassurance, improves communication with providers, and promotes greater personal responsibility, indicating an empowering consumer process. Finally, it can also improve confidence and satisfaction in the service.

SUBMITTER: Burns K

PROVIDER: S-EPMC6598415 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Creating Consumer-Generated Health Data: Interviews and a Pilot Trial Exploring How and Why Patients Engage.

Burns Kara K McBride Craig A CA Patel Bhaveshkumar B FitzGerald Gerard G Mathews Shane S Drennan Judy J

Journal of medical Internet research 20190613 6

<h4>Background</h4>Consumer-generated health data (CGHD) are any clinically relevant data collected by patients or their carers (consumers) that may improve health care outcomes. Like patient experience measures, these data reflect the consumer perspective and is part of a patient-centric agenda. The use of CGHD is believed to enhance diagnosis, patient engagement, and thus foster an improved therapeutic partnership with health care providers.<h4>Objective</h4>The aim of this study was to furthe ...[more]

PMID: 31199312

Similar Datasets

Project description:BackgroundIn 2020, the number of internet users surpassed 4.6 billion. Individuals who create and share digital data can leave a trail of information about their habits and preferences that collectively generate a digital footprint. Studies have shown that digital footprints can reveal important information regarding an individual's health status, ranging from diet and exercise to depression. Uses of digital applications have accelerated during the COVID-19 pandemic where public health organizations have utilized technology to reduce the burden of transmission, ultimately leading to policy discussions about digital health privacy. Though US consumers report feeling concerned about the way their personal data is used, they continue to use digital technologies.ObjectiveThis study aimed to understand the extent to which consumers recognize possible health applications of their digital data and identify their most salient concerns around digital health privacy.MethodsWe conducted semistructured interviews with a diverse national sample of US adults from November 2018 to January 2019. Participants were recruited from the Ipsos KnowledgePanel, a nationally representative panel. Participants were asked to reflect on their own use of digital technology, rate various sources of digital information, and consider several hypothetical scenarios with varying sources and health-related applications of personal digital information.ResultsThe final cohort included a diverse national sample of 45 US consumers. Participants were generally unaware what consumer digital data might reveal about their health. They also revealed limited knowledge of current data collection and aggregation practices. When responding to specific scenarios with health-related applications of data, they had difficulty weighing the benefits and harms but expressed a desire for privacy protection. They saw benefits in using digital data to improve health, but wanted limits to health programs' use of consumer digital data.ConclusionsCurrent privacy restrictions on health-related data are premised on the notion that these data are derived only from medical encounters. Given that an increasing amount of health-related data is derived from digital footprints in consumer settings, our findings suggest the need for greater transparency of data collection and uses, and broader health privacy protections.

Project description:BackgroundEngagement frameworks provide the conceptual structure for consumer engagement in healthcare decision making, but the level to which these frameworks support culturally and linguistically diverse (CALD) consumer engagement is not known.ObjectiveThis study aimed to investigate how consumer engagement is conceptualised and operationalized and to determine the implications of current consumer engagement frameworks for engagement with CALD consumers.MethodAltheide's document analysis approach was used to guide a systematic search, selection and analytic process. Australian Government health department websites were searched for eligible publicly available engagement frameworks. A narrative synthesis was conducted.ResultsEleven engagement frameworks published between 2007 and 2019 were identified and analysed. Only four frameworks discussed engagement with CALD consumers distinctly. Organisational prerequisites to enhance engagement opportunities and approaches to enable activities of engagement were highlighted to improve CALD consumers' active participation in decision making; however, these largely focused on language, with limited exploration of culturally sensitive services.ConclusionThere is limited discussion of what culturally sensitive services look like and what resources are needed to enhance CALD consumer engagement in high-level decision making. Health services and policy makers can enhance opportunities for engagement with CALD consumers by being flexible in their approach, implementing policies for reimbursement for participation and evaluating and adapting the activities of engagement in collaboration with CALD consumers.Patient/public contributionThis study is part of a wider 'CanEngage' project, which includes a consumer investigator, and is supported by a consumer advisory group. The study was conceived with inputs from the consumer advisory group, which continued to meet regularly with the project team to discuss the methodology and emerging findings.

Project description:BackgroundFailure to find and attract clinical trial participants remains a persistent barrier to clinical research. Researchers increasingly complement recruitment methods with social media-based methods. We hypothesized that user-generated data from cancer survivors and their family members and friends on the social network Twitter could be used to identify, engage, and recruit cancer survivors for cancer trials.ObjectiveThis pilot study aims to examine the feasibility of using user-reported health data from cancer survivors and family members and friends on Twitter in Los Angeles (LA) County to enhance clinical trial recruitment. We focus on 6 cancer conditions (breast cancer, colon cancer, kidney cancer, lymphoma, lung cancer, and prostate cancer).MethodsThe social media intervention involved monitoring cancer-specific posts about the 6 cancer conditions by Twitter users in LA County to identify cancer survivors and their family members and friends and contacting eligible Twitter users with information about open cancer trials at the University of Southern California (USC) Norris Comprehensive Cancer Center. We reviewed both retrospective and prospective data published by Twitter users in LA County between July 28, 2017, and November 29, 2018. The study enrolled 124 open clinical trials at USC Norris. We used descriptive statistics to report the proportion of Twitter users who were identified, engaged, and enrolled.ResultsWe analyzed 107,424 Twitter posts in English by 25,032 unique Twitter users in LA County for the 6 cancer conditions. We identified and contacted 1.73% (434/25,032) of eligible Twitter users (127/434, 29.3% cancer survivors; 305/434, 70.3% family members and friends; and 2/434, 0.5% Twitter users were excluded). Of them, 51.4% (223/434) were female and approximately one-third were male. About one-fifth were people of color, whereas most of them were White. Approximately one-fifth (85/434, 19.6%) engaged with the outreach messages (cancer survivors: 33/85, 38% and family members and friends: 52/85, 61%). Of those who engaged with the messages, one-fourth were male, the majority were female, and approximately one-fifth were people of color, whereas the majority were White. Approximately 12% (10/85) of the contacted users requested more information and 40% (4/10) set up a prescreening. Two eligible candidates were transferred to USC Norris for further screening, but neither was enrolled.ConclusionsOur findings demonstrate the potential of identifying and engaging cancer survivors and their family members and friends on Twitter. Optimization of downstream recruitment efforts such as screening for digital populations on social media may be required. Future research could test the feasibility of the approach for other diseases, locations, languages, social media platforms, and types of research involvement (eg, survey research). Computer science methods could help to scale up the analysis of larger data sets to support more rigorous testing of the intervention.Trial registrationClinicalTrials.gov NCT03408561; https://clinicaltrials.gov/ct2/show/NCT03408561.

Project description:BACKGROUND:Non-medical data, such as the amount of time that patients and caregivers spend managing their condition, may be relevant when assessing therapeutic strategies. For chronic pediatric conditions, the time that patients and caregivers spend in seeking and providing care (which are the indirect costs in an economic evaluation) can be significantly different depending on the treatment arm. To explore methods for collecting information on the care burden for caregivers and patients, we investigated whether a patient diary provided additional information compared to retrospective investigator-led interviews and whether a diary that was completed intermittently produced more or less information than a diary completed continually. The main objective of this study was to identify which type of data collection was most effective for measuring the time spent by caregivers and for estimating indirect treatment costs over 9 months. METHODS:Start-In! is a randomized controlled trial comparing the efficacy of three strategies of real-time continuous glucose monitoring for 12?months in children and adolescents with type 1 diabetes. We designed an ancillary study to assess methods of collecting information on the time spent by patients and caregivers in managing their condition (indirect costs). Data were entered retrospectively in case report forms (CRFs) by investigators during quarterly follow-up visits, which were supplemented with diaries completed prospectively by children or caregivers either continuously or intermittently. Data about absences from school and work as well as the time that caregivers spent on diabetes care were collected and the three collection methods were compared. RESULTS:At the end of the 9-month study, 42% of the study participants failed to return their diary. For the diaries that were received, less than 10% of expected data were collected versus 82% during investigators'interviews. Based on all the information collected, we calculated that over 9?months, caregivers lost on average 3.9?days of working time (€786) and 4?days of personal time, i.e. the equivalent of €526, and spent around 15?min of time on care per day, i.e. the equivalent of €1700. CONCLUSIONS:The CRFs completed by investigators during quarterly visits cannot be replaced by a diary. Completing the diaries appeared to represent an important additional burden to children and their caregivers, and the diaries provided little additional information compared to investigators' entries in the CRF. TRIAL REGISTRATION:ClinicalTrials.gov, NCT00949221. Registered on 30 July 2009. Registry name: Study of Insulin Therapy Augmented by Real Time Sensor in Type 1 Children and Adolescents (START-IN!).

Dataset Information

Creating Consumer-Generated Health Data: Interviews and a Pilot Trial Exploring How and Why Patients Engage.

Background

Objective

Methods

Results

Conclusions

Publications

Creating Consumer-Generated Health Data: Interviews and a Pilot Trial Exploring How and Why Patients Engage.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure