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| 6. |
- Andersson, Henrik, et al.
(författare)
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Using optimization to provide decision support for strategic emergency medical service planning - Three case studies
- 2020
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Ingår i: International Journal of Medical Informatics. - : ELSEVIER IRELAND LTD. - 1386-5056 .- 1872-8243. ; 133
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Tidskriftsartikel (refereegranskat)abstract
- To achieve high performing emergency medical services (EMS), planning is of vital importance. EMS planners face several challenges when managing ambulance stations and the fleet of ambulances. In this paper, three strategic cases for EMS planners are presented together with potential solutions. In the first case, the effects of closing down a local emergency room (ER) are analyzed together with how adding an ambulance station and an ambulance to the area affected by the closing of the ER can be used to mitigate the negative consequences from the closing. The second case investigates a change in the organization of EMS. Currently, many non-urgent transport assignments are performed by ambulances which make them unavailable for more urgent calls. The potential for a more effective utilization of the ambulances is explored through transferring these assignments to designated transport vehicles. The third case is more technical and challenges the common practice regarding how time dependent demand is handled. Looking at the busiest hour or the average daily demand, is compared with taking time varying demand into account. The cases and solutions are studied using a recently developed strategic ambulance station location and ambulance allocation model for the Maximum Expected Performance Location Problem with Heterogeneous Regions (MEPLP-HR). The model has been extended to also include multiple time periods. This article demonstrates an innovative use of the model and how it can be applied to find and evaluate solutions to real cases within the field of strategic planning of EMS. The model is found to be a useful decision support tool when analyzing the cases and the expected performance of potential solutions.
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| 7. |
- Belsti, Yitayeh, et al.
(författare)
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Comparison of machine learning and conventional logistic regression-based prediction models for gestational diabetes in an ethnically diverse population : the Monash GDM Machine learning model
- 2023
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Ingår i: International Journal of Medical Informatics. - : Elsevier. - 1386-5056 .- 1872-8243. ; 179
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Tidskriftsartikel (refereegranskat)abstract
- Background: Early identification of pregnant women at high risk of developing gestational diabetes (GDM) is desirable as effective lifestyle interventions are available to prevent GDM and to reduce associated adverse outcomes. Personalised probability of developing GDM during pregnancy can be determined using a risk prediction model. These models extend from traditional statistics to machine learning methods; however, accuracy remains sub-optimal.Objective: We aimed to compare multiple machine learning algorithms to develop GDM risk prediction models, then to determine the optimal model for predicting GDM.Methods: A supervised machine learning predictive analysis was performed on data from routine antenatal care at a large health service network from January 2016 to June 2021. Predictor set 1 were sourced from the existing, internationally validated Monash GDM model: GDM history, body mass index, ethnicity, age, family history of diabetes, and past poor obstetric history. New models with different predictors were developed, considering statistical principles with inclusion of more robust continuous and derivative variables. A randomly selected 80% dataset was used for model development, with 20% for validation. Performance measures, including calibration and discrimination metrics, were assessed. Decision curve analysis was performed.Results: Upon internal validation, the machine learning and logistic regression model's area under the curve (AUC) ranged from 71% to 93% across the different algorithms, with the best being the CatBoost Classifier (CBC). Based on the default cut-off point of 0.32, the performance of CBC on predictor set 4 was: Accuracy (85%), Precision (90%), Recall (78%), F1-score (84%), Sensitivity (81%), Specificity (90%), positive predictive value (92%), negative predictive value (78%), and Brier Score (0.39).Conclusions: In this study, machine learning approaches achieved the best predictive performance over traditional statistical methods, increasing from 75 to 93%. The CatBoost classifier method achieved the best with the model including continuous variables.
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| 10. |
- Chirambo, Griphin Baxter, et al.
(författare)
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End-user perspectives of two mHealth decision support tools : Electronic Community Case Management in Northern Malawi
- 2021
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Ingår i: International Journal of Medical Informatics. - : Elsevier BV. - 1386-5056 .- 1872-8243. ; 145
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Tidskriftsartikel (refereegranskat)abstract
- Background: The introduction of a paper-based Community Case Management (CCM) in Malawi has contributed to a reduction of child morbidity and mortality rates. In addition, the introduction of electronic Community Case Management (eCCM) (smartphones with built in CCM apps) may help to reduce the under-five mortality rates even further. Purpose: It is not uncommon for Apps with a similar area of interest to develop different features to assist the end users. Such differences between Apps may have a significant role to play in its overall adoption and integration. The purpose of this research was to explore end users perspectives of two eCCM decision support tools developed and implemented by the Supporting LIFE project (SL eCCM App) and D-Tree International's (Mangologic eCCM App)in Northern Malawi. Methods: A mixed methods approach was applied, involving a survey of 109 users (106 Health Surveillance Assistants (HSAs), and 3 Integrated Management of Childhood Il6lnesses (IMCI) coordinators). This was followed up with semi-structured interviews with 34 respondents (31 HSAs, and 3 IMCI coordinators). Quantitative data was analyzed using SPSS version 20 where descriptive statistics and Chi-Squared tests were generated. Qualitative data were analyzed based on thematic analysis. Results: Participants reported that both Apps could assist the HSAs in the management of childhood illnesses. However, usability differed between the two apps where the Supporting LIFE eCCM App was found to be easier to use (61%) compared to the Mangologic eCCM App (4%). Both Apps were perceived to provide credible and accurate information. Conclusion: It is essential that the quality of the data within Mobile Health (mHealth) Apps is high, however even Apps with excellent levels of data quality may not succeed if the overall usability of the App is low. Therefore it is essential that the Apps has high levels of data quality, usability and credibility. The results of this study will help inform mobile Health (mHealth) App designers in developing future eCCM Apps as well as researchers and policy makers when considering the adoption of mHealth solutions in the future in Malawi and other LMICs.
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| 11. |
- Drissi, Nidal, et al.
(författare)
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An analysis on self-management and treatment-related functionality and characteristics of highly rated anxiety apps.
- 2020
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Ingår i: International Journal of Medical Informatics. - : Elsevier BV. - 1386-5056 .- 1872-8243. ; 141, s. 104243-
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND AND OBJECTIVE: Anxiety is a common emotion that people often feel in certain situations. But when the feeling of anxiety is persistent and interferes with a person's day to day life then this may likely be an anxiety disorder. Anxiety disorders are a common issue worldwide and can fall under general anxiety, panic attacks, and social anxiety among others. They can be disabling and can impact all aspects of an individual's life, including work, education, and personal relationships. It is important that people with anxiety receive appropriate care, which in some cases may prove difficult due to mental health care delivery barriers such as cost, stigma, or distance from mental health services. A potential solution to this could be mobile mental health applications. These can serve as effective and promising tools to assist in the management of anxiety and to overcome some of the aforementioned barriers. The objective of this study is to provide an analysis of treatment and management-related functionality and characteristics of high-rated mobile applications (apps) for anxiety, which are available for Android and iOS systems.METHOD: A broad search was performed in the Google Play Store and App Store following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) protocol to identify existing apps for anxiety. A set of free and highly rated apps for anxiety were identified and the selected apps were then installed and analyzed according to a predefined data extraction strategy.RESULTS: A total of 167 anxiety apps were selected (123 Android apps and 44 iOS apps). Besides anxiety, the selected apps addressed several health issues including stress, depression, sleep issues, and eating disorders. The apps adopted various treatment and management approaches such as meditation, breathing exercises, mindfulness and cognitive behavioral therapy. Results also showed that 51% of the selected apps used various gamification features to motivate users to keep using them, 32% provided social features including chat, communication with others and links to sources of help; 46% offered offline availability; and only 19% reported involvement of mental health professionals in their design.CONCLUSIONS: Anxiety apps incorporate various mental health care management methods and approaches. Apps can serve as promising tools to assist large numbers of people suffering from general anxiety or from anxiety disorders, anytime, anywhere, and particularly in the current COVID-19 pandemic.
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| 12. |
- Ehn, Maria, et al.
(författare)
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User-centered requirements engineering to manage the fuzzy front-end of open innovation in e-health : A study on support systems for seniors’ physical activity
- 2021
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Ingår i: International Journal of Medical Informatics. - : Elsevier Ireland Ltd. - 1386-5056 .- 1872-8243. ; 154
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Tidskriftsartikel (refereegranskat)abstract
- Background: Although e-health potentials for improving health systems in their safety, quality and efficiency has been acknowledged, a large gap between the postulated and empirically demonstrated benefits of e-health technologies has been ascertained. E-health development has classically been technology-driven, often resulting in the design of devices and applications that ignore the complexity of the real-world setting, thus leading to slow diffusion of innovations to care. Therefore, e-health innovation needs to consider the mentioned complexity already from the start. The early phases of innovation, fuzzy front-end (FFE) defined as “the period between when an opportunity is first considered and when an idea is judged ready for development” has been identified to have the highest impact on the innovation process and its outcome. The FFE has been recognized as the most difficult stage to manage in the innovation process as it involves a high degree of uncertainty. Such a phase becomes even more difficult when different sectors and organizations are involved. Therefore, effective methods for involving different organizations and user groups in the FFE of innovation are needed. Objective: The aim of this study was to manage the FFE of a collaborative, open innovation (OI) process, to define a software system supporting seniors’ physical activity (PA) by applying a framework of methods from software requirements engineering (RE) to elicit and analyze needs and requirements of users and stakeholders, as well as the context in which the system should be used. Methods: Needs and requirements of three future user groups were explored through individual- and focus group interviews. Requirements were categorized and analyzed in a workshop with a multidisciplinary team: a system overview was produced by conceptual modelling using elicited functional requirements; high-level non-functional requirements were negotiated and prioritized. Scenario descriptions of system's supportive roles in different phases of a behavioral change process were developed. Results: User-centered RE methods were successfully used to define a system and a high-level requirements description was developed based on needs and requirements from three identified user groups. The system aimed to support seniors’ motivation for PA and contained four complementary sub-systems. The outcome of the study was a Concept of Operations (ConOps) document that specified the high-level system requirements in a way that was understandable for stakeholders. This document was used both to identify and recruit suitable industrial partners for the following open innovation development and to facilitate communication and collaboration in the innovation process. Conclusions: Applying software RE methods and involving user groups in the early phases of OI can contribute to the development of new concepts that meet complex real-world requirements. Different user groups can complement each other in conveying needs and requirements from which systems can be designed. Empirical studies applying and exploring different methods used to define new e-health solutions can contribute with valuable knowledge about handling innovation FFE.
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| 13. |
- Florin, Jan, et al.
(författare)
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A comparison between the ICNP and the ICF for expressing nursing content in the electronic health record
- 2021
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Ingår i: International Journal of Medical Informatics. - : Elsevier BV. - 1386-5056 .- 1872-8243. ; 154
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Tidskriftsartikel (refereegranskat)abstract
- Background: The use of standardised terminologies for electronic health records (EHRs) is important and a sufficient coverage of all aspects of health care is increasingly being developed worldwide. The International Classification of Functioning, Disabilities and Health (ICF) is suggested as a unifying terminology suitable in a multi-professional EHR, but the level of representation of nursing content is unclear. Objectives: The aim was to describe lexical and semantic accordance in relation to comprehensiveness and granularity of concepts between the International Classification of Nursing Practise (ICNP) and the ICF. Methods: 806 pre-coordinated concepts for diagnoses and outcomes in the ICNP terminology were manually mapped to 1516 concepts on level 4-6 in the ICF. Results: Several dimensions of nursing diagnoses and outcomes in the ICNP were missing in the ICF. 60% of the concepts for diagnosis and outcome in the ICNP could not be stated using the ICF while another 31% could only be matched either as a subordinate or as a superordinate concept. Conclusions: The lexical and semantic accordance in relation to comprehensiveness and granularity between concepts in the ICNP and ICF was rather low. A large proportion of concepts for diagnoses and outcomes in the ICNP could not be satisfactorily stated using the ICF. Standardised terminologies rooted in a nursing tradition (e. g., the ICNP) is needed for communication and documentation in health care to represent the patient's health situation as well as professional diagnostic decisions and evaluations in nursing.
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| 14. |
- Galozy, Alexander, 1991-, et al.
(författare)
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Pitfalls of medication adherence approximation through EHR and pharmacy records: Definitions, data and computation
- 2020
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Ingår i: International Journal of Medical Informatics. - Shannon : Elsevier BV. - 1386-5056 .- 1872-8243. ; 136
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Tidskriftsartikel (refereegranskat)abstract
- Background and purpose: Patients' adherence to medication is a complex, multidimensional phenomenon. Dispensation data and electronic health records are used to approximate medication-taking through refill adherence. In-depth discussions on the adverse effects of data quality and computational differences are rare. The purpose of this article is to evaluate the impact of common pitfalls when computing medication adherence using electronic health records. Procedures: We point out common pitfalls associated with the data and operationalization of adherence measures. We provide operational definitions of refill adherence and conduct experiments to determine the effect of the pitfalls on adherence estimations. We performed statistical significance testing on the impact of common pitfalls using a baseline scenario as reference. Findings: Slight changes in definition can significantly skew refill adherence estimates. Pickup patterns cause significant disagreement between measures and the commonly used proportion of days covered. Common data related issues had a small but statistically significant (p < 0.05) impact on population-level and significant effect on individual cases. Conclusion: Data-related issues encountered in real-world administrative databases, which affect various operational definitions of refill adherence differently, can significantly skew refill adherence values, leading to false conclusions about adherence, particularly when estimating adherence for individuals.
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| 15. |
- Hagström, Josefin, et al.
(författare)
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Minors' and guardian access to and use of a national patient portal : A retrospective comparative case study of Sweden and Finland.
- 2024
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Ingår i: International Journal of Medical Informatics. - 1386-5056 .- 1872-8243. ; 187
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Approaches to implementing online record access (ORA) via patient portals for minors and guardians vary internationally, as more countries continue to develop patient-accessible electronic health records (PAEHR) systems. Evidence of ORA usage and country-specific practices to allow or block minors' and guardians' access to minors' records during adolescence (i.e. access control practices) may provide a broader understanding of possible approaches and their implications for minors' confidentiality and guardian support.AIM: To describe and compare minors' and guardian proxy users' PAEHR usage in Sweden and Finland. Furthermore, to investigate the use of country-specific access control practices.METHODS: A retrospective, observational case study was conducted. Data were collected from PAEHR administration services in Sweden and Finland and proportional use was calculated based on population statistics. Descriptive statistics were used to analyze the results.RESULTS: In both Sweden and Finland, the proportion of adolescents accessing their PAEHR increased from younger to older age-groups reaching the proportion of 59.9 % in Sweden and 84.8 % in Finland in the age-group of 17-year-olds. The PAEHR access gap during early adolescence in Sweden may explain the lower proportion of users among those who enter adulthood. Around half of guardians in Finland accessed their minor children's records in 2022 (46.1 %), while Swedish guardian use was the highest in 2022 for newborn children (41.8 %), and decreased thereafter. Few, mainly guardians, applied for extended access in Sweden. In Finland, where a case-by-case approach to access control relies on healthcare professionals' (HCPs) consideration of a minor's maturity, 95.8 % of minors chose to disclose prescription information to their guardians.CONCLUSION: While age-based access control practices can hamper ORA for minors and guardians, case-by-case approach requires HCP resources and careful guidance to ensure equality between patients. Guardians primarily access minors' records during early childhood and adolescents show willingness to share their PAEHR with parents.
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| 16. |
- Hertzum, Morten, et al.
(författare)
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Implementing Large-Scale Electronic Health Records : Experiences from Implementations of Epic in Denmark and Finland
- 2022
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Ingår i: International Journal of Medical Informatics. - : Elsevier. - 1386-5056 .- 1872-8243. ; 167
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Tidskriftsartikel (refereegranskat)abstract
- Background: With the still larger scale of electronic health records (EHRs), their implementation has become increasingly complex. In this study, we focus on one large-scale EHR – Epic.Purpose: We analyze the Epic implementations in Denmark and Finland to understand how healthcare professionals experience this large-scale EHR.Method: The study is based on documentary analysis. The analyzed documents include user surveys, assessment reports, material from project partners, and research papers.Results: The Danish and Finnish Epic implementations are still troubled five and three years, respectively, after the first go-live. In Denmark, the business case and implementation process have been sharply criticized. The correction of usability problems and unstable system integrations have been slow, the time required to perform common clinical tasks has increased, and 32% of the users remain dissatisfied or very dissatisfied with the system. In Finland, the physicians and nurses experience improved technical performance but inferior usability and reduced work support compared to the EHR they used before Epic; only 4.7% (physicians) and 7.3% (nurses) agree that patient information is easy to access, and only 9.3% (physicians) and 26.2% (nurses) agree that Epic helps improve the quality of care.Conclusion: The post-implementation experiences from the two implementations contradict pre-implementation expectations. Specifically, the consequences of using Epic have become salient only after go-live. As a result, the implementing organizations and their users have predominantly found themselves in a reactive mode of fending off problems rather than a proactive mode of realizing benefits.
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| 18. |
- Iwaya, Leonardo H, et al.
(författare)
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Early Labour App: Developing a practice-based mobile health application for digital early labour support
- 2023
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Ingår i: International Journal of Medical Informatics. - : Elsevier. - 1386-5056 .- 1872-8243. ; 177
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Tidskriftsartikel (refereegranskat)abstract
- Background: Pregnant women in early labour have felt excluded from professional care, and their partners have been restricted from being involved in the birthing process. Expectant parents must be better prepared to deal with fear and stress during early labour. There is a need for evidence-based information and digital applications that can empower couples during childbirth.Objective: To develop and identify requirements for a practice-based mobile health (mHealth) application for Digital Early Labour Support.Methods: This research started with creating an expert group composed of a multidisciplinary team capable of informing the app development process on evidence-based practices. In consultation with the expert group, the app was built using an agile development approach (i.e., Scrum) within a continuous software engineering setting (i.e., CI/CD, DevOps), also including user and security tests.Results: During the development of the Early Labour App, two main types of challenges emerged: (1) user challenges, related to understanding the users’ needs and experience with the app, and (2) team challenges, related to the software development team in particular, and the necessary skills for translating an early labour intervention into a digital solution. This study reaffirms the importance of midwife support via blended care and the opportunity of complementing it with an app. The Early Labour App was easy to use, the women needed little to no help, and the partner's preparation was facilitated. The combination of the app together with blended care opens up awareness, thoughts and feelings about the method and provides good preparation for the birth.Conclusion: We propose the creation of the Early Labour App, a mHealth app for early labour support. The preliminary tests conducted for the Early Labour App show that the app is mature, allowing it to be used in the project's Randomised Control Trial, which is already ongoing.
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| 19. |
- Jarva, E., et al.
(författare)
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Healthcare professionals' digital health competence and its core factors; development and psychometric testing of two instruments
- 2023
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Ingår i: International Journal of Medical Informatics. - Shannon : Elsevier. - 1386-5056 .- 1872-8243. ; 171
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Healthcare professionals' digital health competence is an important phenomenon to study as healthcare practices are changing globally. Recent research aimed to define this complex phenomenon and identify the current state of healthcare professionals' competence in digitalisation but did not include an overarching outlook when measuring digital health competence of healthcare professionals. OBJECTIVES: The purpose of this study was to develop and psychometrically validate two self-assessed instruments measuring digital health competence and factors associating with it. METHODS: The study followed three phases of instrument development and validation: 1) conceptualisation and item pool generation; 2) content validity testing and pilot study; and 3) construct validity and reliability testing. The conceptual background of the instruments was based on individual interviews conducted with healthcare professionals (n = 20) and previous systematic reviews. A total of 17 experts assessed the instrument's content validity. Face validity was evaluated by a group of healthcare professionals (n = 20). Data collection from 817 professionals took place in spring-summer 2022 in nine organisations. Construct validity was confirmed with exploratory factor analysis. Cronbach's alpha was used to assess the internal consistency of the instruments. RESULTS: The instrument development and validation process resulted in two instruments: DigiHealthCom and DigiComInf. DigiHealthCom included 42 items in 5 factors related to digital health competence, and DigiComInf included 15 items in 3 factors related to educational and organisational factors associated with digital health competence. The DigiHealthCom instrument explained 68.9 % of the total variance and the factors' Cronbach alpha values varied between 0.91 and 0.97. The DigiComInf instrument explained 59.6 % of the total variance and the factors' Cronbach alpha values varied between 0.76 and 0.88. CONCLUSIONS: The two instruments gave valid and reliable results in psychometric testing. The instruments could be used to evaluate healthcare professionals' digital health competence and associated factors. Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.
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| 21. |
- Khumalo, A., et al.
(författare)
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Perspectives on record-keeping practices in MDT meetings and meeting record utility
- 2022
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Ingår i: International Journal of Medical Informatics. - : Elsevier. - 1386-5056 .- 1872-8243. ; 161
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Tidskriftsartikel (refereegranskat)abstract
- Background and purpose: Working collaboratively as a multidisciplinary team in the treatment and care of cancer patients is proven effective in increasing the quality of patient care. A multidisciplinary team (MDT) meeting (MDTM) is the main vehicle that facilitates this collaborative work between different healthcare specialities, and an appropriate meeting record is essential to communicate the meeting's outcomes. There is limited research to date regarding MDTM documentation, and here we report on a sample of healthcare professional's perspectives on current practices. Methodology: A survey, distributed to a purposive snowball sample, is used to collect the perceptions on record-keeping at MDTMs from involved healthcare workers. The survey is descriptive and exploratory in nature and uses closed and open-ended questions offered in both English and Swedish. Results: With a response of 37 healthcare workers, several commonly understood practices of MDTMs are confirmed, documentation is mostly electronic, encompasses suggested information, and the record is mostly acceptable in quality. The issues of responsibility, registering attendance, and verification of documentation can be improved. Conclusion: Electronic documentation is a laudable step that shows advancement in MDTM record-keeping. The highlighted quality of the records suggests that MDTM proceedings are reasonably well documented. There remain some important questions, with regard to standardization, centralization, and the responsibility for record-keeping at MDTMs.
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| 22. |
- Kujala, Sari, et al.
(författare)
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Benchmarking usability of patient portals in Estonia, Finland, Norway, and Sweden
- 2024
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Ingår i: International Journal of Medical Informatics. - : Elsevier. - 1386-5056 .- 1872-8243. ; 181
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: Poor usability is a barrier to widespread adoption of electronic health records (EHR). Providing good usability is especially challenging in the health care context, as there is a wide variety of patient users. Usability benchmarking is an approach for improving usability by evaluating and comparing the strength and weaknesses of systems. The main purpose of this study is to benchmark usability of patient portals across countries. METHODS: A mixed-methods survey approach was applied to benchmark the national patient portals offering patient access to EHR in Estonia, Finland, Norway, and Sweden. These Nordic countries have similar public healthcare systems, and they are pioneers in offering patients access to EHR for several years. In a survey of 29,334 patients, both patients' quantitative ratings of usability and their qualitative descriptions of very positive and very negative peak experiences of portal use were collected. RESULTS: The usability scores ranged from good to fair level of usability. The narratives of very positive and very negative experiences included the benefits of the patient portals and experienced usability issues. The regression analysis of results showed that very positive and negative experiences of patient portal use explain 19-35% of the variation of usability scores in the four countries. The percentage of patients who reported very positive or very negative experiences in each country was unrelated to the usability scores across countries. CONCLUSIONS: The survey approach could be used to evaluate usability with a wide variety of users and it supported learning from comparison across the countries. The combination of quantitative and qualitative data provided an approximation of the level of the perceived usability, and identified usability issues to be improved and useful features that patients appreciate. Further work is needed to improve the comparability of the varied samples across countries.
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| 23. |
- Kurbalija, Vladimir, et al.
(författare)
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Analysis of neuropsychological and neuroradiological features for diagnosis of Alzheimer's disease and mild cognitive impairment
- 2023
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Ingår i: International Journal of Medical Informatics. - : Elsevier BV. - 1386-5056 .- 1872-8243. ; 178
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Tidskriftsartikel (refereegranskat)abstract
- Background: Age-related neurodegenerative diseases are constantly increasing with prediction that in 2050 over 60 % of population will suffer from some level of cognitive impairment. A cure for the Alzheimer's disease (AD) does not exist, so early diagnosis is of a great importance. Machine learning techniques can help in early diagnosis with deep medical data processing, disease understanding, intervention analysis and knowledge dis-covery for achieving better medical decision making.Methods: In this paper, we analyze the dataset consisting of 90 individuals and 482 input features. We investigate the achieved AD prediction performances using seven classifiers and five feature selection algorithms. We pay special focus on analyzing performance by utilizing only a subset of best ranked attributes to establish the minimum amount of input features that ensure acceptable performance. We also investigate the significance of neuropsychological (NP) and neuroradiological (NR) attributes for the AD diagnosis.Results: The accuracy for the whole set of attributes ranged between 66.22 % and 81.00 %, and the weighted average AUROC was between 76.3 % and 95.0 %. The best results were achieved by the naive Bayes classifier and the Relief feature selection algorithm. Additionally, Support Vector Machines classifier shows the most stable results since it depends the least on the feature selection algorithm which is used. As the main result of this paper, we compare the performance of models trained with automatically selected features to models trained with hand-selected features performed by medical experts (NP and NR features).Conclusions: The results reveal that unlike the NR attributes, the NP attributes achieve a good performance that is comparable to the full set of attributes, which suggests that they possess a high predictive power for AD diagnosis.
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| 25. |
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| 26. |
- Pasarelu, Costina Ruxandra, et al.
(författare)
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Attention-deficit/ hyperactivity disorder mobile apps : A systematic review
- 2020
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Ingår i: International Journal of Medical Informatics. - : Elsevier. - 1386-5056 .- 1872-8243. ; 138
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Forskningsöversikt (refereegranskat)abstract
- Background: Attention-Deficit/ Hyperactivity Disorder (ADHD) is a prevalent condition in children and adolescents. Although there are pharmacological and non-pharmacological treatments for this disorder, barriers in accessing evidence-based treatments are still a major problem. Digital health interventions are promising for multiple mental health problems. Recent years have brought an increase in the number of existing mobile apps designed for the management of ADHD. The aim of this study was to systematically review the existing mobile apps designed for ADHD in terms of general characteristics, empirical support for their development and efficacy/ effectiveness, and to describe the content and design of the four most downloaded ADHD apps. Method: We conducted systematic searches on iTunes/iOS (Apple App Store), Google Play and the National Health Service Health Apps Library up to May 2017 and checked for changes in March and September 2019. We included those apps that were designed for ADHD, target assessment, treatment, or both, were in English and were functional. We identified 355 apps in the virtual stores, out of which we included 109 apps in the present systematic review. For each app we extracted the following information: target population, developer, price, number of downloads, ratings, privacy, available language other than English, category, purpose and empirical support. A second search was conducted in literature databases up to September 2019: PsycINFO, Pubmed, Scopus, Web of Science, Cochrane database. Results: We found 109 ADHD apps in the virtual stores available to both young and adult populations, developed for children, adolescents, parents, teachers, and professionals. Most of the apps included are designed for treatment, or ADHD symptoms assessment, however, we found several apps designed for both assessment and treatment purposes. Very few apps contained information regarding their development and none contained information regarding evidence for its efficacy/ effectiveness. Four apps were the most downloaded, with 10,000 (three apps) to 100,000-500,000 (one app) downloads. Out of 51 papers identified through systematic searches in the literature, we identified only one study that met our inclusion criteria, however, this study was published in 2018, outside of the 2017 app store search, therefore, there is no overlap between evidence in the literature and apps on the market. Conclusions: Given the large proliferation of mental health apps and their potential benefits in terms of dissemination and costs, future research needs to be conducted in order to establish the safety and efficacy of ADHD apps available on the commercial market.
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| 27. |
- Rafiq, Muhammad, et al.
(författare)
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Predictive analytics support for complex chronic medical conditions : An experience-based co-design study of physician managers’ needs and preferences
- 2024
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Ingår i: International Journal of Medical Informatics. - Shannon : Elsevier. - 1386-5056 .- 1872-8243. ; 187, s. 1-9
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: The literature suggests predictive technology applications in health care would benefit from physician and manager input during design and development. The aim was to explore the needs and preferences of physician managers regarding the role of predictive analytics in decision support for patients with the highly complex yet common combination of multiple chronic conditions of cardiovascular (Heart) and kidney (Nephrology) diseases and diabetes (HND). Methods: This qualitative study employed an experience-based co-design model comprised of three data gathering phases: 1. Patient mapping through non-participant observations informed by process mining of electronic health records data, 2. Semi-structured experience-based interviews, and 3. A co-design workshop. Data collection was conducted with physician managers working at or collaborating with the HND center, Danderyd University Hospital (DSAB), in Stockholm, Sweden. HND center is an integrated practice unit offering comprehensive person-centered multidisciplinary care to stabilize disease progression, reduce visits, and develop treatment strategies that enables a transition to primary care. Results: Interview and workshop data described a complex challenge due to the interaction of underlying pathophysiologies and the subsequent need for multiple care givers that hindered care continuity. The HND center partly met this challenge by coordinating care through multiple interprofessional and interdisciplinary shared decision-making interfaces. The large patient datasets were difficult to operationalize in daily practice due to data entry and retrieval issues. Predictive analytics was seen as a potentially effective approach to support decision-making, calculate risks, and improve resource utilization, especially in the context of complex chronic care, and the HND center a good place for pilot testing and development. Simplicity of visual interfaces, a better understanding of the algorithms by the health care professionals, and the need to address professional concerns, were identified as key factors to increase adoption and facilitate implementation. Conclusions: The HND center serves as a comprehensive integrated practice unit that integrates different medical disciplinary perspectives in a person-centered care process to address the needs of patients with multiple complex comorbidities. Therefore, piloting predictive technologies at the same time with a high potential for improving care represents an extreme, demanding, and complex case. The study findings show that health care professionals’ involvement in the design of predictive technologies right from the outset can facilitate the implementation and adoption of such technologies, as well as enhance their predictive effectiveness and performance. Simplicity in the design of predictive technologies and better understanding of the concept and interpretation of the algorithms may result in implementation of predictive technologies in health care. Institutional efforts are needed to enhance collaboration among the health care professionals and IT professionals for effective development, implementation, and adoption of predictive analytics in health care. © 2024 The Author(s)
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- Shah, N., et al.
(författare)
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Governing health data across changing contexts : A focus group study of citizen’s views in England, Iceland, and Sweden
- 2021
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Ingår i: International Journal of Medical Informatics. - : Elsevier. - 1386-5056 .- 1872-8243. ; 156
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundThe governance structures associated with health data are evolving in response to advances in digital technologies that enable new ways of capturing, using, and sharing different types of data. Increasingly, health data moves between different contexts such as from healthcare to research, or to commerce and marketing. Crossing these contextual boundaries has the potential to violate societal expectations about the appropriate use of health data and diminish public trust. Understanding citizens’ views on the acceptability of and preferences for data use in different contexts is essential for developing information governance policies in these new contexts.MethodsFocus group design presenting data sharing scenarios in England, Iceland, and Sweden.ResultsSeventy-one participants were recruited. Participants supported the need for data to help understand the observable world, improve medical research, the quality of public services, and to benefit society. However, participants consistently identified the lack of information, transparency and control as barriers to trusting organisations to use data in a way that they considered appropriate. There was considerable support for fair and transparent data sharing practices where all parties benefitted.ConclusionData governance policy should involve all stakeholders’ perspectives on an ongoing basis, to inform and implement changes to health data sharing practices that accord with stakeholder views. The Findings showed that (1) data should be used for ethical purposes even when there was commercial interest; (2) data subjects and/or public institutions that provide and share data should also receive benefits from the sharing of data; (3) third parties use of data requires greater transparency and accountability than currently exists, (4) there should be greater information provided to empower data subjects.
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