Data collection with iPhone Web apps efficiently collecting patient data using mobile devices

2010 ◽  
Author(s):  
Ali Hamou ◽  
Stacey Guy ◽  
Benoit Lewden ◽  
Adam Bilyea ◽  
Femida Gwadry-Sridhar ◽  
...  
Keyword(s):  
Data Collection ◽  
Mobile Devices ◽  
Patient Data

scholarly journals Passive sensing on mobile devices to improve mental health services with adolescent and young mothers in low-resource settings: the role of families in feasibility and acceptability

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sujen Man Maharjan ◽  
Anubhuti Poudyal ◽  
Alastair van Heerden ◽  
Prabin Byanjankar ◽  
Ada Thapa ◽  
...  
Keyword(s):  
Data Collection ◽  
Health Services ◽  
Mobile Devices ◽  
Family Involvement ◽  
Mobile Phones ◽  
Young Mothers ◽  
Audio Recording ◽  
Low Resource Settings ◽  
Passive Sensing ◽  
Passive Data

Abstract Background Passive sensor data from mobile devices can shed light on daily activities, social behavior, and maternal-child interactions to improve maternal and child health services including mental healthcare. We assessed feasibility and acceptability of the Sensing Technologies for Maternal Depression Treatment in Low Resource Settings (StandStrong) platform. The StandStrong passive data collection platform was piloted with adolescent and young mothers, including mothers experiencing postpartum depression, in Nepal. Methods Mothers (15–25 years old) with infants (< 12 months old) were recruited in person from vaccination clinics in rural Nepal. They were provided with an Android smartphone and a Bluetooth beacon to collect data in four domains: the mother’s location using the Global Positioning System (GPS), physical activity using the phone’s accelerometer, auditory environment using episodic audio recording on the phone, and mother-infant proximity measured with the Bluetooth beacon attached to the infant’s clothing. Feasibility and acceptability were evaluated based on the amount of passive sensing data collected compared to the total amount that could be collected in a 2-week period. Endline qualitative interviews were conducted to understand mothers’ experiences and perceptions of passive data collection. Results Of the 782 women approached, 320 met eligibility criteria and 38 mothers (11 depressed, 27 non-depressed) were enrolled. 38 mothers (11 depressed, 27 non-depressed) were enrolled. Across all participants, 5,579 of the hour-long data collection windows had at least one audio recording [mean (M) = 57.4% of the total possible hour-long recording windows per participant; median (Mdn) = 62.6%], 5,001 activity readings (M = 50.6%; Mdn = 63.2%), 4,168 proximity readings (M = 41.1%; Mdn = 47.6%), and 3,482 GPS readings (M = 35.4%; Mdn = 39.2%). Feasibility challenges were phone battery charging, data usage exceeding prepaid limits, and burden of carrying mobile phones. Acceptability challenges were privacy concerns and lack of family involvement. Overall, families’ understanding of passive sensing and families’ awareness of potential benefits to mothers and infants were the major modifiable factors increasing acceptability and reducing gaps in data collection. Conclusion Per sensor type, approximately half of the hour-long collection windows had at least one reading. Feasibility challenges for passive sensing on mobile devices can be addressed by providing alternative phone charging options, reverse billing for the app, and replacing mobile phones with smartwatches. Enhancing acceptability will require greater family involvement and improved communication regarding benefits of passive sensing for psychological interventions and other health services. Registration International Registered Report Identifier (IRRID): DERR1-10.2196/14734

Usability Evaluation of an Offline Electronic Data Capture App in a Prospective Multicentre Dementia Registry – digiDEM Bayern: a Mixed Method Study (Preprint)

2021 ◽  
Author(s):  
Michael Reichold ◽  
Miriam Hess ◽  
Peter L. Kolominsky-Rabas ◽  
Elmar Gräßel ◽  
Hans-Ulrich Prokosch
Keyword(s):  
Data Collection ◽  
Technology Acceptance ◽  
Mobile Devices ◽  
Mixed Method ◽  
User Group ◽  
Electronic Data ◽  
Thinking Aloud ◽  
Electronic Data Collection ◽  
Usability Problems ◽  
Dementia Registry

BACKGROUND Digital registries have shown to provide an efficient way better to understand the clinical complexity and long-term progression of diseases. The paperless way of electronic data collection during a patient interview saves both: time and resources. In the prospective multicenter 'Digital Dementia Registry Bavaria - digiDEM Bayern', interviews are also conducted on-site in rural areas with unreliable internet connectivity. It must be ensured that electronic data collection can still be performed there, and it is no need to fall back on paper-based questionnaires. Therefore, the EDC system REDCap offers, in addition to a web-based data collection solution, the option to collect data offline via an app and synchronize it afterward. OBJECTIVE This study evaluates the usability of the REDCap app as an offline electronic data collection option for a lay user group and examines the necessary technology acceptance using mobile devices for data collection. Thereby, the feasibility of the app-based offline data collection in the dementia registry project was evaluated before going live. METHODS The study was conducted with an exploratory mixed-method in the form of an on-site usability test with the 'Thinking Aloud' method combined with a tailored semi-standardized online questionnaire including System Usability Score (SUS). The acceptance of mobile devices for the data collection was surveyed based on the technology acceptance model (TAM) with five categories. RESULTS Using the Thinking Aloud method, usability problems were identified and solutions were derived therefore. The evaluation of the REDCap app resulted in a SUS score of 74, which represents 'good' usability. After evaluating the technology acceptance questionnaire, it can be stated that the lay user group is open to mobile devices as interview tools. CONCLUSIONS The usability evaluation results show that a lay user group like the data collecting partners in the digiDEM project can handle the REDCap app well overall. The usability test provided statements about positive aspects and was able to identify usability problems of the REDCap app. In addition, the current technology acceptance in the sample showed that heterogeneous groups of different ages with different experiences in handling mobile devices are also ready for the use of app-based EDC systems. Based on the results, it can be assumed that the offline use of an app-based EDC system on mobile devices is a viable solution to collect data in a registry-based research project.

Patient-Data Collection System Used During Medical Operations After the 1994 San Fernando Valley-Northridge Earthquake

1995 ◽  
Vol 10 (3) ◽  
pp. 178-183 ◽  
Author(s):  
Ralph B. (Monty) Leonard ◽  
Lew W. Stringer ◽  
Roy Alson
Keyword(s):  
Data Collection ◽  
Patient Flow ◽  
Patient Data ◽  
Northridge Earthquake ◽  
Collection System ◽  
Data Collection System ◽  
Support Unit ◽  
Disaster Assistance ◽  
Major Disaster ◽  
Flow Information

AbstractIntroduction:In large disasters, such as earthquakes and hurricanes, rapid, adequate and documented medical care and distribution of patients are essential.Methods:After a major (magnitude 6.7 Richter scale) earthquake occurred in Southern California, nine disaster medical assistance teams and two Veterans Administration (VA) buses with VA personnel responded to staff four medical stations, 19 disaster-assistance centers, and two mobile vans. All were under the supervision of the medical support unit (MSU) and its supervising officer. This article describes the patient-data collection system used. All facilities used the same patient encounter forms, log sheets, and medical treatment forms. Copies of these records accompanied the patients during every transfer. Centers for Disease Control and Prevention data classifications were used routinely. The MSU collected these forms twice each day so that all facilities had access to updated patient flow information.Results:Through the use of these methods, more than 11,000 victims were treated, transferred, and their cases tracked during a 12-day period.Conclusions:Use of this system by all federal responders to a major disaster area led to organized care for a large number of victims. Factors enhancing this care were the simplicity of the forms, the use of the forms by all federal responders, a central data collection point, and accessibility of the data at a known site available to all agencies every 12 hours.

Investigating the Factors Influencing Pre-Service Teachers' Acceptance to Use Mobile Devices for Learning

2020 ◽  
pp. 183-208
Author(s):  
Georgios K. Zacharis
Keyword(s):  
Data Collection ◽  
University Students ◽  
Social Influence ◽  
Mobile Devices ◽  
Behavioral Intention ◽  
Study Results ◽  
Data Collection Instrument ◽  
Faculty Of Education ◽  
Facilitating Conditions ◽  
Behavioral Intention To Use

This chapter determines the factors that significantly influence pre-service teachers' acceptance to use mobile devices as resources for learning in a university context. Based on the methodological framework of the UTAUT, a modified contextualized model of evaluation was created. A data collection instrument was designed, validated contextually, and optimized for mobile learning in higher education. A total of 320 Greek university students from a Faculty of Education participated in the study. Results demonstrated that the instrument constructed showed a notable internal consistency, with a high validity for data collection in 8 of its 9 factors. Results indicated Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Hedonic Motivation, and Empowerment in Learning as factors which affected participants' Behavioral Intention to use mobile technology for learning. Behavioral Intention, Social Influence and Empowerment in Learning affected university students' behavior to use mobile devices for learning.

scholarly journals P155: Utilization of personal mobile devices to record patient data by emergency physicians and residents

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S112-S112
Author(s):  
K. E. Walker ◽  
D. Migneault ◽  
H. C. Lindsay ◽  
R. B. Abu-Laban
Keyword(s):  
Patient Care ◽  
Mobile Devices ◽  
Demographic Data ◽  
Patient Data ◽  
Physician Education ◽  
Emergency Physicians ◽  
Healthcare Settings ◽  
Canadian Association ◽  
Personal Mobile Devices ◽  
Privacy And Confidentiality

Introduction: The use of personal mobile devices to record patient data appears to be increasing, but remains poorly studied. We sought to determine the magnitude and purposes for which Canadian emergency physicians (EPs) and residents use their personal mobile devices (PMDs) to record patient data in the emergency department (ED). Methods: An anonymous survey was distributed to EPs and residents in the Canadian Association of Emergency Physicians (CAEP) database between 27/02/17 and 23/03/17. The survey captured demographic information and information on frequency and purpose of PMD use in the ED, whether consent was obtained, how the information was secured, and any possible implications for patient care. Participants were also asked about knowledge of, and any perceived restrictions from, current regulations regarding the use of PMDs healthcare settings. Results: The survey response rate was 23.1%. Of 415 respondents, 9 surveys were rejected for incomplete demographic data, resulting in 406 participants. A third (31.5%, 128/406, 95% CI 27.0-36.3) reported using PMDs to record patient data. Most (78.1%) reported doing so more than once a month and 7.0% reported doing so once every shift. 10.9% of participants indicated they did not obtain written or verbal consent. Reasons cited by participants for using PMDs to record patient data included a belief that doing so improves care provided by consultants (36.7%), expedites patient care (31.3%), and improves medical education (32.8%). 53.2% of participants were unaware of current regulations and 19.7% reported feeling restricted by them. Subgroup analysis suggested an increased frequency of PMD use to record patient data among younger physicians and physicians in rural settings. Conclusion: This is the first known Canadian study on the use of PMDs to record patient data in the ED. Our results suggest that this practice is common, and arises from a belief that doing so enhances patient care through better communication, efficiency, and education. Our findings also suggest current practices result in risk of both privacy and confidentiality breaches, and thus support arguments for both physician education and regulation reform.

The Palm Computer Is Fast, Accurate and Portable for Burn Patient Data Collection

2000 ◽  
Vol 21 ◽  
pp. S247
Author(s):  
S. Lal ◽  
D. Chinkes ◽  
F. Smith ◽  
R. E. Barrow ◽  
D. N. Herndon
Keyword(s):  
Data Collection ◽  
Patient Data ◽  
Burn Patient

scholarly journals Landscape of MS patient cohorts and registries: Recommendations for maximizing impact

2017 ◽  
Vol 24 (5) ◽  
pp. 579-586 ◽  
Author(s):  
Bruce F Bebo ◽  
Robert J Fox ◽  
Karen Lee ◽  
Ursula Utz ◽  
Alan J Thompson
Keyword(s):  
Multiple Sclerosis ◽  
Data Collection ◽  
Patient Data ◽  
Landscape Analysis ◽  
Multiple Sclerosis Patients

Background: There is a growing number of cohorts and registries collecting phenotypic and genotypic data from groups of multiple sclerosis patients. Improved awareness and better coordination of these efforts is needed. Objective: The purpose of this report is to provide a global landscape of the major longitudinal MS patient data collection efforts and share recommendations for increasing their impact. Methods: A workshop that included over 50 MS research and clinical experts from both academia and industry was convened to evaluate how current and future MS cohorts could be better used to provide answers to urgent questions about progressive MS. Results: The landscape analysis revealed a significant number of largely uncoordinated parallel studies. Strategic oversight and direction is needed to streamline and leverage existing and future efforts. A number of recommendations for enhancing these efforts were developed. Conclusions: Better coordination, increased leverage of evolving technology, cohort designs that focus on the most important unanswered questions, improved access, and more sustained funding will be needed to close the gaps in our understanding of progressive MS and accelerate the development of effective therapies.

A multidisciplinary-guided digital solution to data capture in early-phase clinical trials.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e18063-e18063
Author(s):  
Donna M. Graham ◽  
Joanna Clarke ◽  
Gemma Wickert ◽  
Leanna Goodwin ◽  
Carla Timmins ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Focus Group ◽  
Data Collection ◽  
Early Phase ◽  
Patient Data ◽  
Simulated Patient ◽  
Data Capture ◽  
Health Staff ◽  
Case Report Form ◽  
Acceptance Test

e18063 Background: Data capture in early phase cancer clinical trials (EPCCT) is usually via paper records with manual transcription to the sponsor’s case report form. Capturing real time trial data directly to computer (eSource) may reduce errors and increase completeness and timeliness of data entry. A simulated system pilot took place between Oct 2018 and Jan 2019 at an EPCCT facility to appraise Foundry Health’s eSource system “ClinSpark”. Aims were to assess consistency and effectiveness of creating electronic templates for source data capture and live data collection compliance. Methods: A multidisciplinary focus group (2 research nurses, 1 doctor, 3 data managers) was created to collaborate with Foundry Health staff. The focus group agreed on a 52 item user acceptance test listing ideal features for a data collection tool, classifying items as high, medium or low priority. Specialised features of the eSource system were adapted to handle the complex needs of EPCCT. The pilot incorporated a 5 day boot camp for familiarisation to the digital platform; a conference room test using simulated patient data; construction of a trial template including contingency planning; and a clinic floor test with live simulated patient data collection using digital tablets. Results: During the 3 month pilot, templates for 2 EPCCT were planned and created. Using eSource, 43 items (83%) of the acceptance test were passed compared with 27 items (52%) for the current (paper-based) system. The paper system did not pass any of the 9 items for which eSource failed. For the 30 high priority items, eSource passed 30 (100%) compared with 22 for the paper system (73%). Time saving and potential error reduction were noted as additional benefits. Conclusions: This process demonstrates that a multidisciplinary approach can be used to successfully integrate a customised eSource system working with previously untrained staff. Improved performance across pre-specified domains and potential additional benefits were noted. As FDA encourages the use of digital solutions in clinical trials, using eSource provides a potential solution for compliant and efficient capture of data from protocol assessments at investigator sites and rapid data transfer to sponsors.

Sign in / Sign up

Export Citation Format

Share Document