scholarly journals Understanding the Uptake of Big Data in Health Care: Protocol for a Multinational Mixed-Methods Study (Preprint)

2019 ◽  
Author(s):  
Rik Wehrens ◽  
Vikrant Sihag ◽  
Sandra Sülz ◽  
Hilco van Elten ◽  
Erik van Raaij ◽  
...  
Keyword(s):  
Health Care ◽  
Big Data ◽  
Mixed Methods ◽  
Visual Representations ◽  
European Countries ◽  
Integrated Analysis ◽  
Organizational Routines ◽  
Care Providers ◽  
Big Data Applications ◽  
Societal Dimensions

BACKGROUND Despite the high potential of big data, their applications in health care face many organizational, social, financial, and regulatory challenges. The societal dimensions of big data are underrepresented in much medical research. Little is known about integrating big data applications in the corporate routines of hospitals and other care providers. Equally little is understood about embedding big data applications in daily work practices and how they lead to actual improvements for health care actors, such as patients, care professionals, care providers, information technology companies, payers, and the society. OBJECTIVE This planned study aims to provide an integrated analysis of big data applications, focusing on the interrelations among concrete big data experiments, organizational routines, and relevant systemic and societal dimensions. To understand the similarities and differences between interactions in various contexts, the study covers 12 big data pilot projects in eight European countries, each with its own health care system. Workshops will be held with stakeholders to discuss the findings, our recommendations, and the implementation. Dissemination is supported by visual representations developed to share the knowledge gained. METHODS This study will utilize a mixed-methods approach that combines performance measurements, interviews, document analysis, and cocreation workshops. Analysis will be structured around the following four key dimensions: performance, embedding, legitimation, and value creation. Data and their interrelations across the dimensions will be synthesized per application and per country. RESULTS The study was funded in August 2017. Data collection started in April 2018 and will continue until September 2021. The multidisciplinary focus of this study enables us to combine insights from several social sciences (health policy analysis, business administration, innovation studies, organization studies, ethics, and health services research) to advance a holistic understanding of big data value realization. The multinational character enables comparative analysis across the following eight European countries: Austria, France, Germany, Ireland, the Netherlands, Spain, Sweden, and the United Kingdom. Given that national and organizational contexts change over time, it will not be possible to isolate the factors and actors that explain the implementation of big data applications. The visual representations developed for dissemination purposes will help to reduce complexity and clarify the relations between the various dimensions. CONCLUSIONS This study will develop an integrated approach to big data applications that considers the interrelations among concrete big data experiments, organizational routines, and relevant systemic and societal dimensions. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/16779

scholarly journals Understanding the Uptake of Big Data in Health Care: Protocol for a Multinational Mixed-Methods Study

10.2196/16779 ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. e16779
Author(s):  
Rik Wehrens ◽  
Vikrant Sihag ◽  
Sandra Sülz ◽  
Hilco van Elten ◽  
Erik van Raaij ◽  
...  
Keyword(s):  
Health Care ◽  
Big Data ◽  
Mixed Methods ◽  
Visual Representations ◽  
European Countries ◽  
Integrated Analysis ◽  
Organizational Routines ◽  
Care Providers ◽  
Big Data Applications ◽  
Societal Dimensions

Background Despite the high potential of big data, their applications in health care face many organizational, social, financial, and regulatory challenges. The societal dimensions of big data are underrepresented in much medical research. Little is known about integrating big data applications in the corporate routines of hospitals and other care providers. Equally little is understood about embedding big data applications in daily work practices and how they lead to actual improvements for health care actors, such as patients, care professionals, care providers, information technology companies, payers, and the society. Objective This planned study aims to provide an integrated analysis of big data applications, focusing on the interrelations among concrete big data experiments, organizational routines, and relevant systemic and societal dimensions. To understand the similarities and differences between interactions in various contexts, the study covers 12 big data pilot projects in eight European countries, each with its own health care system. Workshops will be held with stakeholders to discuss the findings, our recommendations, and the implementation. Dissemination is supported by visual representations developed to share the knowledge gained. Methods This study will utilize a mixed-methods approach that combines performance measurements, interviews, document analysis, and cocreation workshops. Analysis will be structured around the following four key dimensions: performance, embedding, legitimation, and value creation. Data and their interrelations across the dimensions will be synthesized per application and per country. Results The study was funded in August 2017. Data collection started in April 2018 and will continue until September 2021. The multidisciplinary focus of this study enables us to combine insights from several social sciences (health policy analysis, business administration, innovation studies, organization studies, ethics, and health services research) to advance a holistic understanding of big data value realization. The multinational character enables comparative analysis across the following eight European countries: Austria, France, Germany, Ireland, the Netherlands, Spain, Sweden, and the United Kingdom. Given that national and organizational contexts change over time, it will not be possible to isolate the factors and actors that explain the implementation of big data applications. The visual representations developed for dissemination purposes will help to reduce complexity and clarify the relations between the various dimensions. Conclusions This study will develop an integrated approach to big data applications that considers the interrelations among concrete big data experiments, organizational routines, and relevant systemic and societal dimensions. International Registered Report Identifier (IRRID) DERR1-10.2196/16779

scholarly journals Big Data in Science and Healthcare: A Review of Recent Literature and Perspectives

2014 ◽  
Vol 23 (01) ◽  
pp. 21-26 ◽  
Author(s):  
T. Miron-Shatz ◽  
A. Y. S. Lau ◽  
C. Paton ◽  
M. M. Hansen
Keyword(s):  
Health Care ◽  
Big Data ◽  
Health Care Providers ◽  
Data Privacy ◽  
Recent Literature ◽  
Unstructured Data ◽  
Small Scale ◽  
Small Data ◽  
Quantified Self ◽  
Care Providers

Summary Objectives: As technology continues to evolve and rise in various industries, such as healthcare, science, education, and gaming, a sophisticated concept known as Big Data is surfacing. The concept of analytics aims to understand data. We set out to portray and discuss perspectives of the evolving use of Big Data in science and healthcare and, to examine some of the opportunities and challenges. Methods: A literature review was conducted to highlight the implications associated with the use of Big Data in scientific research and healthcare innovations, both on a large and small scale. Results: Scientists and health-care providers may learn from one another when it comes to understanding the value of Big Data and analytics. Small data, derived by patients and consumers, also requires analytics to become actionable. Connectivism provides a framework for the use of Big Data and analytics in the areas of science and healthcare. This theory assists individuals to recognize and synthesize how human connections are driving the increase in data. Despite the volume and velocity of Big Data, it is truly about technology connecting humans and assisting them to construct knowledge in new ways. Concluding Thoughts: The concept of Big Data and associated analytics are to be taken seriously when approaching the use of vast volumes of both structured and unstructured data in science and health-care. Future exploration of issues surrounding data privacy, confidentiality, and education are needed. A greater focus on data from social media, the quantified self-movement, and the application of analytics to “small data” would also be useful.

scholarly journals Health Care Providers’ Knowledge of HPV Vaccination, Barriers, and Strategies in a State With Low HPV Vaccine Receipt: Mixed-Methods Study

JMIR Cancer ◽  
2017 ◽  
Vol 3 (2) ◽  
pp. e12 ◽  
Author(s):  
Echo L Warner ◽  
Qian Ding ◽  
Lisa Pappas ◽  
Julia Bodson ◽  
Brynn Fowler ◽  
...  
Keyword(s):  
Health Care ◽  
Mixed Methods ◽  
Health Care Providers ◽  
Hpv Vaccine ◽  
Hpv Vaccination ◽  
Mixed Methods Study ◽  
Care Providers ◽  
Vaccination Barriers

Violence Against Health Care Providers: A Mixed-Methods Study from Karachi, Pakistan

2018 ◽  
Vol 54 (4) ◽  
pp. 558-566.e2 ◽  
Author(s):  
Lubna Ansari Baig ◽  
Shiraz Shaikh ◽  
Maciej Polkowski ◽  
Syeda Kausar Ali ◽  
Seemin Jamali ◽  
...  
Keyword(s):  
Health Care ◽  
Mixed Methods ◽  
Health Care Providers ◽  
Mixed Methods Study ◽  
Care Providers

Modularising outpatient care delivery: A mixed methods case study at a Finnish University Hospital

2018 ◽  
Vol 31 (4) ◽  
pp. 195-204 ◽  
Author(s):  
Katariina Silander ◽  
Paulus Torkki ◽  
Antti Peltokorpi ◽  
Aino Lepäntalo ◽  
Maija Tarkkanen ◽  
...  
Keyword(s):  
Health Care ◽  
Mixed Methods ◽  
Health Care Delivery ◽  
Outpatient Care ◽  
Hospital Care ◽  
Care Delivery ◽  
University Hospital ◽  
Care Providers ◽  
Mixed Methods Case Study

Background Modularisation is a potential means to develop health care delivery by combining standardisation and customisation. However, little is known about the effects of modularisation on hospital care. The objective was to analyse how modularisation may change and support health care delivery in specialised hospital care. Methods A mixed methods case study methodology was applied using both qualitative and quantitative data, including interviews, field notes, documents, service usage data, bed count and personnel resource data. Data from a reference hospital’s unit were used to understand the context and development of care delivery in general. Results The following outcome themes were identified from the interviews: balance between demand and supply; support in shift from inpatient to outpatient care; shorter treatment times and improved management of service production. Modularisation supported the shift from inpatient towards outpatient care. Changes in resource efficiency measures were both positive and negative; the number of patients per personnel decreased, while the number of visits per personnel and the bed utilisation rate increased. Conclusions Modularisation may support health care providers in classifying patients and delivering services according to patients’ needs. However, as the findings are based on a single university hospital case study, more research is needed.

scholarly journals Medical Students’ Experiences and Outcomes Using a Virtual Human Simulation to Improve Communication Skills: Mixed Methods Study (Preprint)

2019 ◽  
Author(s):  
Timothy C Guetterman ◽  
Rae Sakakibara ◽  
Srikar Baireddy ◽  
Frederick W Kron ◽  
Mark W Scerbo ◽  
...  
Keyword(s):  
Health Care ◽  
Mixed Methods ◽  
Medical Students ◽  
Communication Skills ◽  
Health Care Providers ◽  
Mixed Methods Study ◽  
Virtual Human ◽  
Care Providers ◽  
Empathic Communication ◽  
Nonverbal Skills

BACKGROUND Attending to the wide range of communication behaviors that convey empathy is an important but often underemphasized concept to reduce errors in care, improve patient satisfaction, and improve cancer patient outcomes. A virtual human (VH)–based simulation, MPathic-VR, was developed to train health care providers in empathic communication with patients and in interprofessional settings and evaluated through a randomized controlled trial. OBJECTIVE This mixed methods study aimed to investigate the differential effects of a VH-based simulation developed to train health care providers in empathic patient-provider and interprofessional communication. METHODS We employed a mixed methods intervention design, involving a comparison of 2 quantitative measures—MPathic-VR–calculated scores and the objective structured clinical exam (OSCE) scores—with qualitative reflections by medical students about their experiences. This paper is a secondary, focused analysis of intervention arm data from the larger trial. Students at 3 medical schools in the United States (n=206) received simulation to improve empathic communication skills. We conducted analysis of variance, thematic text analysis, and merging mixed methods analysis. RESULTS OSCE scores were significantly improved for learners in the intervention group (mean 0.806, SD 0.201) compared with the control group (mean 0.752, SD 0.198; <italic>F</italic><sub>1,414</sub>=6.09; <italic>P</italic>=.01). Qualitative analysis revealed 3 major positive themes for the MPathic-VR group learners: gaining useful communication skills, learning awareness of nonverbal skills in addition to verbal skills, and feeling motivated to learn more about communication. Finally, the results of the mixed methods analysis indicated that most of the variation between high, middle, and lower performers was noted about nonverbal behaviors. Medium and high OSCE scorers most often commented on the importance of nonverbal communication. Themes of motivation to learn about communication were only present in middle and high scorers. CONCLUSIONS VHs are a promising strategy for improving empathic communication in health care. Higher performers seemed most engaged to learn, particularly nonverbal skills.

scholarly journals Exploring the Specific Needs of Persons with Multiple Sclerosis for mHealth Solutions for Physical Activity: Mixed-Methods Study (Preprint)

2017 ◽  
Author(s):  
Guido Giunti ◽  
Jan Kool ◽  
Octavio Rivera Romero ◽  
Enrique Dorronzoro Zubiete
Keyword(s):  
Physical Activity ◽  
Multiple Sclerosis ◽  
Health Care ◽  
Mixed Methods ◽  
Goal Setting ◽  
Health Care Professionals ◽  
Mobile Technologies ◽  
Satisfaction With Life Scale ◽  
Care Providers ◽  
Mhealth Apps

BACKGROUND Multiple sclerosis (MS) is one of the world’s most common neurologic disorders, with symptoms such as fatigue, cognitive problems, and issues with mobility. Evidence suggests that physical activity (PA) helps people with MS reduce fatigue and improve quality of life. The use of mobile technologies for health has grown in recent years with little involvement from relevant stakeholders. User-centered design (UCD) is a design philosophy with the goal of creating solutions specific to the needs and tasks of the intended users. UCD involves stakeholders early and often in the design process. In a preliminary study, we assessed the landscape of commercially available MS mobile health (mHealth) apps; to our knowledge, no study has explored what persons with MS and their formal care providers think of mHealth solutions for PA. OBJECTIVE The aim of this study was to (1) explore MS-specific needs for MS mHealth solutions for PA, (2) detect perceived obstacles and facilitators for mHealth solutions from persons with MS and health care professionals, and (3) understand the motivational aspects behind adoption of mHealth solutions for MS. METHODS A mixed-methods design study was conducted in Kliniken Valens, Switzerland, a clinic specializing in neurological rehabilitation. We explored persons with MS and health care professionals who work with them separately. The study had a qualitative part comprising focus groups and interviews, and a quantitative part with standardized tools such as satisfaction with life scale and electronic health (eHealth) literacy. RESULTS A total of 12 persons with relapsing-remitting MS and 12 health care professionals from different backgrounds participated in the study. Participants were well-educated with an even distribution between genders. Themes identified during analysis were MS-related barriers and facilitators, mHealth design considerations, and general motivational aspects. The insights generated were used to create MS personas for design purposes. Desired mHealth features were as follows: (1) activity tracking, (2) incentives for completing tasks and objectives, (3) customizable goal setting, (4) optional sociability, and (5) game-like attitude among others. Potential barriers to mHealth apps adoption were as follows: (1) rough on-boarding experiences, (2) lack of clear use benefits, and (3) disruption of the health care provider-patient relationship. Potential facilitators were identified: (1) endorsements from experts, (2) playfulness, and (3) tailored to specific persons with MS needs. A total of 4 MS personas were developed to provide designers and computer scientists means to help in the creation of future mHealth solutions for MS. CONCLUSIONS mHealth solutions for increasing PA in persons with MS hold promise. Allowing for realistic goal setting and positive feedback, while minimizing usability burdens, seems to be critical for the adoption of such apps. Fatigue management is especially important in this population; more attention should be brought to this area.

Challenges for developing health-care knowledge in the digital age

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dana Abdullah Alrahbi ◽  
Mehmood Khan ◽  
Shivam Gupta ◽  
Sachin Modgil ◽  
Charbel Jose Chiappetta Jabbour
Keyword(s):  
Health Care ◽  
Big Data ◽  
United Arab Emirates ◽  
Health Care Providers ◽  
Health Care Sector ◽  
Primary Data ◽  
Care Organization ◽  
Strongly Correlated ◽  
Care Providers ◽  
Content Type

Purpose Health-care knowledge is dispersed among different departments in a health care organization, which makes it difficult at times to provide quality care services to patients. Therefore, this study aims to identify the main challenges in adopting health information technology (HIT). Design/methodology/approach This study surveyed 148 stakeholders in 4 key categories [patients, health-care providers, United Arab Emirates (UAE) citizens and foresight experts] to identify the challenges they face in adopting health care technologies. Responses were analyzed using exploratory (EFA) and confirmatory factor analysis (CFA). Findings EFA revealed four key latent factors predicting resistance to HIT adoption, namely, organizational strategy (ORGS); technical barriers; readiness for big data and the internet of things (IoT); and orientation (ORI). ORGS accounted for the greatest amount of variance. CFA indicated that readiness for big data and the IoT was only moderately correlated with HIT adoption, but the other three factors were strongly correlated. Specific items relating to cost, the effectiveness and usability of the technology and the organization were strongly correlated with HIT adoption. These results indicate that, in addition to financial considerations, effective HIT adoption requires ensuring that technologies will be easy to implement to ensure their long-term use. Research limitations/implications The results indicate that readiness for big data and the IoT-related infrastructure poses a challenge to HIT adoption in the UAE context. Respondents believed that the infrastructure of big data can be helpful in more efficiently storing and sharing health-care information. On the technological side, respondents felt that they may experience a steep learning curve. Regarding ORI, stakeholders expected many more such initiatives from health-care providers to make it more knowledge-specific and proactive. Practical implications This study has implications for knowledge management in the health -care sector for information technologies. The HIT can help firms in creating a knowledge eco-system, which is not possible in a dispersed knowledge environment. The utilization of the knowledge base that emerged from the practices and data can help the health care sector to set new standards of information flow and other clinical services such as monitoring the self-health condition. The HIT can further influence the actions of the pharmaceutical and medical device industry. Originality/value This paper highlights the challenges in HIT adoption and the most prominent factors. The conceptual model was empirically tested after the collection of primary data from the UAE using stakeholder theory.

Management of antithrombotic therapy after gastrointestinal bleeding: A mixed methods study of health‐care providers

2020 ◽  
Vol 19 (1) ◽  
pp. 153-160
Author(s):  
Derek H. W. Little ◽  
Tara Robertson ◽  
James Douketis ◽  
Joanna C. Dionne ◽  
Anne Holbrook ◽  
...  
Keyword(s):  
Health Care ◽  
Mixed Methods ◽  
Gastrointestinal Bleeding ◽  
Health Care Providers ◽  
Antithrombotic Therapy ◽  
Mixed Methods Study ◽  
Care Providers
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