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1.
J Med Internet Res ; 25: e44030, 2023 05 04.
Article in English | MEDLINE | ID: mdl-37140973

ABSTRACT

The use of artificial intelligence (AI) and big data in medicine has increased in recent years. Indeed, the use of AI in mobile health (mHealth) apps could considerably assist both individuals and health care professionals in the prevention and management of chronic diseases, in a person-centered manner. Nonetheless, there are several challenges that must be overcome to provide high-quality, usable, and effective mHealth apps. Here, we review the rationale and guidelines for the implementation of mHealth apps and the challenges regarding quality, usability, and user engagement and behavior change, with a special focus on the prevention and management of noncommunicable diseases. We suggest that a cocreation-based framework is the best method to address these challenges. Finally, we describe the current and future roles of AI in improving personalized medicine and provide recommendations for developing AI-based mHealth apps. We conclude that the implementation of AI and mHealth apps for routine clinical practice and remote health care will not be feasible until we overcome the main challenges regarding data privacy and security, quality assessment, and the reproducibility and uncertainty of AI results. Moreover, there is a lack of both standardized methods to measure the clinical outcomes of mHealth apps and techniques to encourage user engagement and behavior changes in the long term. We expect that in the near future, these obstacles will be overcome and that the ongoing European project, Watching the risk factors (WARIFA), will provide considerable advances in the implementation of AI-based mHealth apps for disease prevention and health promotion.


Subject(s)
Mobile Applications , Telemedicine , Humans , Artificial Intelligence , Reproducibility of Results , Telemedicine/methods , Risk Factors
2.
J Med Internet Res ; 24(1): e32220, 2022 01 10.
Article in English | MEDLINE | ID: mdl-35006087

ABSTRACT

BACKGROUND: Flexible Assertive Community Treatment (FACT) is a model for treatment of long-term severe mental disorders. This method has become more widespread in Norway. OBJECTIVE: The objective of our study was to examine how the implementation of FACT teams in Norway has been affected by eHealth policy, infrastructure, and regulations. Another objective was to examine existing literature on eHealth interventions and challenges within FACT teams. METHODS: We have examined Norwegian policy regulating mental health services, laws and regulations, eHealth infrastructure, relevant literature on FACT teams, and current implementation of FACT in Norway. RESULTS: FACT teams are a wanted part of the Norwegian service system, but the current eHealth infrastructure makes sharing of data within teams and levels of health care challenging, even if eHealth regulations allow such sharing. This has been shown to be an issue in the current implementation of FACT teams in Norway. There is little or no existing research on the eHealth challenges facing FACT teams. CONCLUSIONS: Weaknesses in the Norwegian eHealth infrastructure have been a barrier for an easy implementation of FACT teams in Norway. It is difficult to share information between the different levels of health care. We need systems that allow for easy, secure sharing of health information to and between the FACT team members and other involved health care workers.


Subject(s)
Community Mental Health Services , Mental Disorders , Mental Health Services , Telemedicine , Delivery of Health Care , Humans , Norway
3.
J Med Internet Res ; 20(5): e10235, 2018 05 01.
Article in English | MEDLINE | ID: mdl-29716883

ABSTRACT

BACKGROUND: eHealth has an enormous potential to improve healthcare cost, effectiveness, and quality of care. However, there seems to be a gap between the foreseen benefits of research and clinical reality. OBJECTIVE: Our objective was to systematically review the factors influencing the outcome of eHealth interventions in terms of success and failure. METHODS: We searched the PubMed database for original peer-reviewed studies on implemented eHealth tools that reported on the factors for the success or failure, or both, of the intervention. We conducted the systematic review by following the patient, intervention, comparison, and outcome framework, with 2 of the authors independently reviewing the abstract and full text of the articles. We collected data using standardized forms that reflected the categorization model used in the qualitative analysis of the outcomes reported in the included articles. RESULTS: Among the 903 identified articles, a total of 221 studies complied with the inclusion criteria. The studies were heterogeneous by country, type of eHealth intervention, method of implementation, and reporting perspectives. The article frequency analysis did not show a significant discrepancy between the number of reports on failure (392/844, 46.5%) and on success (452/844, 53.6%). The qualitative analysis identified 27 categories that represented the factors for success or failure of eHealth interventions. A quantitative analysis of the results revealed the category quality of healthcare (n=55) as the most mentioned as contributing to the success of eHealth interventions, and the category costs (n=42) as the most mentioned as contributing to failure. For the category with the highest unique article frequency, workflow (n=51), we conducted a full-text review. The analysis of the 23 articles that met the inclusion criteria identified 6 barriers related to workflow: workload (n=12), role definition (n=7), undermining of face-to-face communication (n=6), workflow disruption (n=6), alignment with clinical processes (n=2), and staff turnover (n=1). CONCLUSIONS: The reviewed literature suggested that, to increase the likelihood of success of eHealth interventions, future research must ensure a positive impact in the quality of care, with particular attention given to improved diagnosis, clinical management, and patient-centered care. There is a critical need to perform in-depth studies of the workflow(s) that the intervention will support and to perceive the clinical processes involved.


Subject(s)
Medical Informatics/methods , Telemedicine/methods , Humans
4.
J Digit Imaging ; 27(1): 33-40, 2014 Feb.
Article in English | MEDLINE | ID: mdl-23917864

ABSTRACT

The growing influx of patients in healthcare providers is the result of an aging population and emerging self-consciousness about health. In order to guarantee the welfare of all the healthcare stakeholders, it is mandatory to implement methodologies that optimize the healthcare providers' efficiency while increasing patient throughput and reducing patient's total waiting time. This paper presents a case study of a conventional radiology workflow analysis in a Portuguese healthcare provider. Modeling tools were applied to define the existing workflow. Re-engineered workflows were analyzed using the developed simulation tool. The integration of modeling and simulation tools allowed the identification of system bottlenecks. The new workflow of an imaging department entails a reduction of 41 % of the total completion time.


Subject(s)
Appointments and Schedules , Computer Simulation/statistics & numerical data , Diagnostic Imaging/statistics & numerical data , Efficiency, Organizational/statistics & numerical data , Patient Admission/statistics & numerical data , Radiology/organization & administration , Humans , Models, Organizational , Portugal , Workflow
5.
Int J Med Inform ; 192: 105623, 2024 Dec.
Article in English | MEDLINE | ID: mdl-39317033

ABSTRACT

BACKGROUND: Despite the recognized benefits of integrating patient perspectives into healthcare design and clinical decision support, theoretical approaches and standardized methods are lacking. Various strategies, such as developing pathways, have evolved to address these challenges. Previous research emphasized the need for a framework for care pathways that includes theoretical principles, extensive user involvement, and data from electronic health records to bridge the gap between different fields and disciplines. Standardizing the representation of the patient perspective could facilitate its sharing across healthcare organizations and domains and its integration into journal systems, shifting the balance of power from the provider to the patient. OBJECTIVES: This study aims to 1) Identify research approaches taken to develop patient-centred, integrated, care pathways supported by electronic health records 2) Propose a socio-technical framework for designing patient-centred care pathways across multiple healthcare levels that integrates the voice of the patient with the knowledge of the care provider and technological perspectives. METHODS: This study conducted a scoping review following the Joanna Briggs Institute guidelines and PRISMA-ScR protocol. The databases PubMed, Scopus, Web of Science, ProQuest, IEEE, and Google Scholar were searched using a key term search strategy including variations of patient-centred, integrated care, pathway, framework and model to identify relevant studies. Eligible articles included peer-reviewed literature documenting methodologies for mapping patient-centred, integrated care pathways in healthcare service design. RESULTS: This review summarizes the application of care pathway modelling practices across various areas of healthcare innovation. The search resulted in 410 studies, with 16 articles included after the full review and grey literature search. CONCLUSIONS: Our research illustrated incorporating patient perspectives into modelling care pathways and healthcare service design. Regardless of the medical domain, our methodology proposes an approach for modelling patient-centred, integrated care pathways across the care continuum, including using electronic health records to support the pathways.


Subject(s)
Critical Pathways , Delivery of Health Care, Integrated , Electronic Health Records , Patient-Centered Care , Humans , Patient Participation , Decision Support Systems, Clinical
6.
BioData Min ; 17(1): 46, 2024 Oct 30.
Article in English | MEDLINE | ID: mdl-39478549

ABSTRACT

BACKGROUND: Cutaneous melanoma is the most aggressive form of skin cancer, responsible for most skin cancer-related deaths. Recent advances in artificial intelligence, jointly with the availability of public dermoscopy image datasets, have allowed to assist dermatologists in melanoma identification. While image feature extraction holds potential for melanoma detection, it often leads to high-dimensional data. Furthermore, most image datasets present the class imbalance problem, where a few classes have numerous samples, whereas others are under-represented. METHODS: In this paper, we propose to combine ensemble feature selection (FS) methods and data augmentation with the conditional tabular generative adversarial networks (CTGAN) to enhance melanoma identification in imbalanced datasets. We employed dermoscopy images from two public datasets, PH2 and Derm7pt, which contain melanoma and not-melanoma lesions. To capture intrinsic information from skin lesions, we conduct two feature extraction (FE) approaches, including handcrafted and embedding features. For the former, color, geometric and first-, second-, and higher-order texture features were extracted, whereas for the latter, embeddings were obtained using ResNet-based models. To alleviate the high-dimensionality in the FE, ensemble FS with filter methods were used and evaluated. For data augmentation, we conducted a progressive analysis of the imbalance ratio (IR), related to the amount of synthetic samples created, and evaluated the impact on the predictive results. To gain interpretability on predictive models, we used SHAP, bootstrap resampling statistical tests and UMAP visualizations. RESULTS: The combination of ensemble FS, CTGAN, and linear models achieved the best predictive results, achieving AUCROC values of 87% (with support vector machine and IR=0.9) and 76% (with LASSO and IR=1.0) for the PH2 and Derm7pt, respectively. We also identified that melanoma lesions were mainly characterized by features related to color, while not-melanoma lesions were characterized by texture features. CONCLUSIONS: Our results demonstrate the effectiveness of ensemble FS and synthetic data in the development of models that accurately identify melanoma. This research advances skin lesion analysis, contributing to both melanoma detection and the interpretation of main features for its identification.

7.
Stud Health Technol Inform ; 316: 1219-1223, 2024 Aug 22.
Article in English | MEDLINE | ID: mdl-39176600

ABSTRACT

The Valkyrie project aims to develop a demonstration Federated Electronic Health Record for the use of mental health practitioners in Norway. Information for the record is drawn from existing records in Source Systems operating across primary and secondary care. Recording of information in any such system, in response to a healthcare event, triggers the generation of an Encrypted Token, containing summary metadata about the event, clinical coding indicating its clinical context and a locator that can be used to retrieve the full record of the event from the original Source System. The Valkyrie architecture consists of a number of interlinked Security Domains, each with its own private and public keys, through which the Encrypted Tokens are passed. Each Security Domain performs a specific function on a set of Tokens and only has access to the information within each Token that is necessary to perform that function. This paper describes the structure of the Encrypted Token, the function of each Security Domain and the orchestration of the flow of Tokens through the Domains. Together this allows a user to run a Valkyrie Session, in which they can view the content of a patient record, where all content has been drawn in real-time from heterogenous Source Systems (ISO13606- and openEHR-based) and is destroyed when the session terminates.


Subject(s)
Blockchain , Computer Security , Electronic Health Records , Norway , Humans , Medical Record Linkage/methods
8.
Stud Health Technol Inform ; 316: 247-251, 2024 Aug 22.
Article in English | MEDLINE | ID: mdl-39176720

ABSTRACT

This paper presents the design, implementation and early tests of an app that collects a comprehensive set of health-related data, as part of the EU-project WARIFA. To achieve the main aim of the project - using AI to prevent chronic conditions - a wide range of data needs to be collected and stored at a backend server for processing. The methods and elements for creating this system are presented, as well as results from the co-creation process and early user-tests. Challenges regarding complexity, security, and privacy are discussed, as well as the needs and prospectives for easier ways of collecting health-related data.


Subject(s)
Mobile Applications , Chronic Disease/prevention & control , Humans , Artificial Intelligence , Computer Security , Data Collection
9.
JMIR Form Res ; 7: e42796, 2023 Feb 09.
Article in English | MEDLINE | ID: mdl-36730062

ABSTRACT

BACKGROUND: Flexible Assertive Community Treatment (FACT) is a model of integrated care for patients with long-term serious mental illness. FACT teams deliver services using assertive outreach to treat patients who can be hard to reach by the health care service, and focus on both the patient's health and their social situation. However, in Norway, FACT team members have challenges with their information and communication (ICT) solutions. OBJECTIVE: The aim of this study was to explore Norwegian FACT teams' experiences and expectations of their ICT solutions, including electronic health records, electronic whiteboards, and calendars. METHODS: We gathered data in two phases. In the first phase, we conducted semistructured interviews with team leaders and team coordinators, and made observations in FACT teams targeting adults. In the second phase, we conducted semistructured group interviews in FACT teams targeting youth. We performed a thematic analysis of the data in a theoretical manner to address the specific objectives of the study. RESULTS: A total of 8 teams were included, with 5 targeting adults and 3 targeting youth. Due to the COVID-19 pandemic, we were not able to perform observations in 2 of the teams targeting adults. Team leaders and coordinators in all 5 teams targeting adults were interviewed, with a total of 7 team members participating in the teams targeting youth. We found various challenges with communication, documentation, and organization for FACT teams. The COVID-19 pandemic was challenging for the teams and changed the way they used ICT solutions. There were issues with some technical solutions used in the teams, including electronic health records, electronic whiteboards, and calendars. Lack of integration and access to data were some of the main issues identified. CONCLUSIONS: Despite the FACT model being successfully implemented in Norway, there are several issues regarding the ICT solutions they use, mainly related to access to data and integration. Further research is required to detail how improved ICT solutions should be designed. While FACT teams targeting adults and youth differ in some ways, their needs for ICT solutions are largely similar.

10.
Stud Health Technol Inform ; 294: 259-263, 2022 May 25.
Article in English | MEDLINE | ID: mdl-35612068

ABSTRACT

Flexible assertive community treatment (FACT) is a model for delivering long-term, integrated and comprehensive treatment and follow-up for patients with severe mental illness. The objective of this study was to examine ICT challenges of Norwegian FACT teams. Doing observations in 3 teams and interviews with 5 teams we examined use of ICT systems, identifying challenges with the use of the electronic whiteboards, electronic health records, and team calendars. Better ICT systems and infrastructure are needed to support Norwegian FACT teams.


Subject(s)
Community Mental Health Services , Mental Disorders , Telemedicine , Humans , Mental Disorders/epidemiology , Mental Disorders/therapy , Norway , Patient Care Team
11.
JMIR Diabetes ; 4(3): e14002, 2019 Jul 09.
Article in English | MEDLINE | ID: mdl-31290396

ABSTRACT

BACKGROUND: Introducing self-collected health data from patients with diabetes into consultation can be beneficial for both patients and clinicians. Such an initiative can allow patients to be more proactive in their disease management and clinicians to provide more tailored medical services. Optimally, electronic health record systems (EHRs) should be able to receive self-collected health data in a standard representation of medical data such as Fast Healthcare Interoperability Resources (FHIR), from patients systems like mobile health apps and display the data directly to their users-the clinicians. However, although Norwegian EHRs are working on implementing FHIR, no solution or graphical interface is available today to display self-collected health data. OBJECTIVE: The objective of this study was to design and assess a dashboard for displaying relevant self-collected health data from patients with diabetes to clinicians. METHODS: The design relied on an iterative participatory process involving workshops with patients, clinicians, and researchers to define which information should be available and how it should be displayed. The assessment is based on a case study, presenting an instance of the dashboard populated with data collected from one patient with diabetes type 1 (in-house researcher) face-to-face by 14 clinicians. We performed a qualitative analysis based on usability, functionality, and expectation by using responses to questionnaires that were distributed to the 14 clinicians at the end of the workshops and collected before the participants left. The qualitative assessment was guided by the Standards for Reporting Qualitative Research. RESULTS: We created a dashboard permitting clinicians to assess the reliability of self-collected health data, list all collected data including medical calculations, and highlight medical situations that need to be investigated to improve the situation of the patients. The dashboard uses a combination of tables, graphs, and other visual representations to display the relevant information. Clinicians think that this type of solution will be useful during consultations every day, especially for patients living in remote areas or those who are technologically interested. CONCLUSIONS: Displaying self-collected health data during consultations is not enough for clinicians; the data reliability has to be assured and the relevant information needs to be extracted and displayed along with the data to ease the introduction during a medical encounter. The prestudy assessment showed that the system provides relevant information to meet clinicians' need and that clinicians were eager to start using it during consultations. The system has been under testing in a medical trial since November 2018, and the first results of its assessment in a real-life situation are expected in the beginning of next year (2020).

12.
Stud Health Technol Inform ; 216: 438-42, 2015.
Article in English | MEDLINE | ID: mdl-26262088

ABSTRACT

Surgery cancellations are undesirable in hospital settings as they increase costs, reduce productivity and efficiency, and directly affect the patient. The problem of elective surgery cancellations in a North Norwegian University Hospital is addressed. Based on a three-step methodology conducted at the hospital, the preoperative planning process was modeled taking into consideration the narratives from different health professions. From the analysis of the generated process models, it is concluded that in order to develop a useful patient centered web-based communication tool, it is necessary to fully understand how hospitals plan and organize surgeries today. Moreover, process reengineering is required to generate a standard process that can serve as a tool for health ICT designers to define the requirements for a robust and useful system.


Subject(s)
Appointments and Schedules , General Surgery/organization & administration , Hospital Communication Systems/organization & administration , Internet/organization & administration , Patient Participation/methods , Software , Humans , No-Show Patients , Norway , Organizational Case Studies , Preoperative Care/methods , Remote Consultation/organization & administration
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