scholarly journals Investigating the possibilities of using patient-generated health data in emergency care: an explorative study

2021 ◽  
Vol 4 (1) ◽  
pp. 10-16
Author(s):  
Fie Brosbøl Kobberup ◽  
Brit-Silje Sode ◽  
Gitte Boier Tygesen ◽  
Malik Kalmriz
Keyword(s):  
Emergency Care ◽  
Information Technologies ◽  
Participant Observation ◽  
Patient Flow ◽  
Health Data ◽  
Urgent Care ◽  
Patient Questionnaire ◽  
Health Information Technologies ◽  
Large Patient ◽  
Patient Pathways

AbstractIt is well known that emergency departments (EDs) are exposed to human errors and unintended events due to large patient flow, high work pressure and overload of information. Strategies for providing efficient and effective health care are therefore imperative, and health information technologies are suggested to be one of the solutions. This study sought to investigate if the use of patient-generated health data gathered through a digital patient questionnaire and visualised as a patient-generated journal (PGJ v.1.0) has the potential to improve the care delivered in EDs.MethodsUsing a mixed-method approach, the PGJ (v.1.0) was investigatedfrom key stakeholders’ perspectives. First, we examined the PGJ from a patient perspective via participant observation (n = 18) and interviews (n = 18), supported by statistical data from the PGJ (n = 56). Second, we used questionnaires to explore the physicians’ perspectives (n = 9). Lastly, two interviews were conducted with healthcare leaders from the ED. The data were compared and analysed using descriptive statistics and hermeneutic analysis.Results From the findings, it appears that patients in need of urgent care accept the use of patient-generated data, and patients highly favoured being active in their patient pathway. However, the system needed some adjustments to fit the patients’abilities in urgent situations.The physicians expressed mixed attitudes towards the PGJ: the majority agreed that the system needed some adjustments in order for the full benefits to be gained, but thought that it had potential to improve their work processes when fully developed.Conclusions This study concludes that the use of patient-generated data is well accepted by patients in an urgent setting, and that the PGJ has the potential to improve quality of care in patient pathways by adding value to patient flows as well as clinical workflows. The concept of utilising patient-generated health data in emergency care should therefore be further developed and investigated.

scholarly journals Enabling Better Use of Person-Generated Health Data in Stroke Rehabilitation Systems: Systematic Development of Design Heuristics

10.2196/17132 ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. e17132
Author(s):  
Gerardo Luis Dimaguila ◽  
Kathleen Gray ◽  
Mark Merolli
Keyword(s):  
Stroke Rehabilitation ◽  
Information Technologies ◽  
Best Practice ◽  
Health Data ◽  
Health Information Technologies ◽  
Positive Effects ◽  
Credible Set ◽  
Remote Patient ◽  
Patient Use

Background An established and well-known method for usability assessment of various human-computer interaction technologies is called heuristic evaluation (HE). HE has been adopted for evaluations in a wide variety of specialized contexts and with objectives that go beyond usability. A set of heuristics to evaluate how health information technologies (HITs) incorporate features that enable effective patient use of person-generated health data (PGHD) is needed in an era where there is a growing demand and variety of PGHD-enabled technologies in health care and where a number of remote patient-monitoring technologies do not yet enable patient use of PGHD. Such a set of heuristics would improve the likelihood of positive effects from patients’ use of PGHD and lower the risk of negative effects. Objective This study aims to describe the development of a set of heuristics for the design and evaluation of how well remote patient therapeutic technologies enable patients to use PGHD (PGHD enablement). We used the case of Kinect-based stroke rehabilitation systems (K-SRS) in this study. Methods The development of a set of heuristics to enable better use of PGHD was primarily guided by the R3C methodology. Closer inspection of the methodology reveals that neither its development nor its application to a case study were described in detail. Thus, where relevant, each step was grounded through best practice activities in the literature and by using Nielsen’s heuristics as a basis for determining the new set of heuristics. As such, this study builds on the R3C methodology, and the implementation of a mixed process is intended to result in a robust and credible set of heuristics. Results A total of 8 new heuristics for PGHD enablement in K-SRS were created. A systematic and detailed process was applied in each step of heuristic development, which bridged the gaps described earlier. It is hoped that this would aid future developers of specialized heuristics, who could apply the detailed process of heuristic development for other domains of technology, and additionally for the case of PGHD enablement for other health conditions. The R3C methodology was also augmented through the use of qualitative studies with target users and domain experts, and it is intended to result in a robust and credible set of heuristics, before validation and refinement. Conclusions This study is the first to develop a new set of specialized heuristics to evaluate how HITs incorporate features that enable effective patient use of PGHD, with K-SRS as a key case study. In addition, it is the first to describe how the identification of initial HIT features and concepts to enable PGHD could lead to the development of a specialized set of heuristics.

scholarly journals Enabling Better Use of Person-Generated Health Data in Stroke Rehabilitation Systems: Systematic Development of Design Heuristics (Preprint)

2019 ◽  
Author(s):  
Gerardo Luis Dimaguila ◽  
Kathleen Gray ◽  
Mark Merolli
Keyword(s):  
Stroke Rehabilitation ◽  
Information Technologies ◽  
Best Practice ◽  
Health Data ◽  
Health Information Technologies ◽  
Positive Effects ◽  
Credible Set ◽  
Remote Patient ◽  
Patient Use

BACKGROUND An established and well-known method for usability assessment of various human-computer interaction technologies is called heuristic evaluation (HE). HE has been adopted for evaluations in a wide variety of specialized contexts and with objectives that go beyond usability. A set of heuristics to evaluate how health information technologies (HITs) incorporate features that enable effective patient use of person-generated health data (PGHD) is needed in an era where there is a growing demand and variety of PGHD-enabled technologies in health care and where a number of remote patient-monitoring technologies do not yet enable patient use of PGHD. Such a set of heuristics would improve the likelihood of positive effects from patients’ use of PGHD and lower the risk of negative effects. OBJECTIVE This study aims to describe the development of a set of heuristics for the design and evaluation of how well remote patient therapeutic technologies enable patients to use PGHD (PGHD enablement). We used the case of Kinect-based stroke rehabilitation systems (K-SRS) in this study. METHODS The development of a set of heuristics to enable better use of PGHD was primarily guided by the R3C methodology. Closer inspection of the methodology reveals that neither its development nor its application to a case study were described in detail. Thus, where relevant, each step was grounded through best practice activities in the literature and by using Nielsen’s heuristics as a basis for determining the new set of heuristics. As such, this study builds on the R3C methodology, and the implementation of a mixed process is intended to result in a robust and credible set of heuristics. RESULTS A total of 8 new heuristics for PGHD enablement in K-SRS were created. A systematic and detailed process was applied in each step of heuristic development, which bridged the gaps described earlier. It is hoped that this would aid future developers of specialized heuristics, who could apply the detailed process of heuristic development for other domains of technology, and additionally for the case of PGHD enablement for other health conditions. The R3C methodology was also augmented through the use of qualitative studies with target users and domain experts, and it is intended to result in a robust and credible set of heuristics, before validation and refinement. CONCLUSIONS This study is the first to develop a new set of specialized heuristics to evaluate how HITs incorporate features that enable effective patient use of PGHD, with K-SRS as a key case study. In addition, it is the first to describe how the identification of initial HIT features and concepts to enable PGHD could lead to the development of a specialized set of heuristics.

scholarly journals Computerized Clinical Decision Support: Contributions from 2014

2015 ◽  
Vol 24 (01) ◽  
pp. 119-124 ◽  
Author(s):  
V. Koutkias ◽  
J. Bouaud ◽  
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Information Technologies ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Editorial Team ◽  
Bibliographic Databases ◽  
Health Information Technologies ◽  
Selection Of

Summary Objective: To summarize recent research and propose a selection of best papers published in 2014 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook.Method: A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry systems in order to select a list of candidate best papers to be then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the editorial team was finally organized to conclude on the selection of best papers. Results: Among the 1,254 returned papers published in 2014, the full review process selected four best papers. The first one is an experimental contribution to a better understanding of unintended uses of CDSSs. The second paper describes the effective use of previously collected data to tailor and adapt a CDSS. The third paper presents an innovative application that uses pharmacogenomic information to support personalized medicine. The fourth paper reports on the long-term effect of the routine use of a CDSS for antibiotic therapy. Conclusions: As health information technologies spread more and more meaningfully, CDSSs are improving to answer users’ needs more accurately. The exploitation of previously collected data and the use of genomic data for decision support has started to materialize. However, more work is still needed to address issues related to the correct usage of such technologies, and to assess their effective impact in the long term.

Health Information Technologies: Which Nursing Homes Adopted Them?

2016 ◽  
Author(s):  
Ning Zhang ◽  
Susan Feng Lu ◽  
Biao Xu ◽  
Bingxiao Wu ◽  
Rosa Rodriguez-Monguio ◽  
...  
Keyword(s):  
Nursing Homes ◽  
Health Information ◽  
Information Technologies ◽  
Health Information Technologies

scholarly journals COMPREHENSIVE MEDICATION MANAGEMENT SERVICES IN A BRAZILIAN SPECIALITY PHARMACY: A QUALITATIVE ASSESSMENT

2017 ◽  
Vol 9 (3) ◽  
pp. 227 ◽  
Author(s):  
Kirla Barbosa Detoni ◽  
Mariana Martins Gonzaga Do Nascimento ◽  
Isabela Viana Oliveira ◽  
Mateus Rodrigues Alves ◽  
Manoel Machuca GonzÁles ◽  
...  
Keyword(s):  
Participant Observation ◽  
Patient Flow ◽  
Medication Management ◽  
Implementation Process ◽  
Ethnographic Study ◽  
Qualitative Assessment ◽  
Healthcare Team ◽  
Structured Interviews ◽  
Eligibility Criteria ◽  
Manager Support

Objective: To understand and describe the implementation process of a comprehensive medication management (CMM) service in a public speciality pharmacy in Brazil.Methods: Ethnographic study conducted over 17 mo (September 2014 to February 2016) in a public speciality pharmacy. Semi-structured interviews were conducted with twelve participants. Notes on field journals, resulting from participant observation conducted by the two pharmacists directly responsible for the service implementation, were also used as a source of data.Results: Ten important conditions to improve the success of CMM service implementation were identified: manager support; evaluation of physical and material resources; evaluation of human resources practitioners’ characteristics and knowledge about the theoretical framework of CMM services; time dedicated to CMM services; redefining the work process; defining patient eligibility criteria to CMM service; defining patient flow to CMM service; communication with healthcare team; integration with the staff; and marketing the service internally.Conclusion: The results unveiled by this article can be used by pharmacists and managers as a tool to optimize the implementation of CMM services in different healthcare settings. These conditions do not consist the only aspects necessary to ensure the success of the service; however, they can contribute to optimize the implementation process of the practice

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