Designing digital patient experiences: The digital health design framework.

BACKGROUND: Digital health (DH) brings considerable benefits, but it comes with potential risks. Human Factors (HF) play a critical role in providing high-quality and acceptable DH solutions. Consultation with designers is crucial for reflecting on and improving current DH design practices. OBJECTIVES: We investigated the general DH design processes, challenges, and corresponding strategies that can improve the digital patient experience (PEx). METHODS: A semi-structured interview study with 24 design professionals. All audio recordings were transcribed, deidentified, grammatically corrected, and imported into ATLAS.ti for data analysis. Three coders participated in data coding following the thematic analysis approach. RESULTS: We identified eight DH design stages and grouped them into four phases: preparation, problem-thinking, problem-solving, and implementation. The analysis presented twelve design challenges associated with contextual, practical, managerial, and commercial aspects that can hinder the design process. We identified eight common strategies used by respondents to tackle these challenges. CONCLUSIONS: We propose a Digital Health Design (DHD) framework to improve the digital PEx. It provides an overview of design deliverables, activities, stakeholders, challenges, and corresponding strategies for each design stage.

Cocreating an Automated mHealth Apps Systematic Review Process With Generative AI: Design Science Research Approach.

BACKGROUND: The use of mobile devices for delivering health-related services (mobile health [mHealth]) has rapidly increased, leading to a demand for summarizing the state of the art and practice through systematic reviews. However, the systematic review process is a resource-intensive and time-consuming process. Generative artificial intelligence (AI) has emerged as a potential solution to automate tedious tasks. OBJECTIVE: This study aimed to explore the feasibility of using generative AI tools to automate time-consuming and resource-intensive tasks in a systematic review process and assess the scope and limitations of using such tools. METHODS: We used the design science research methodology. The solution proposed is to use cocreation with a generative AI, such as ChatGPT, to produce software code that automates the process of conducting systematic reviews. RESULTS: A triggering prompt was generated, and assistance from the generative AI was used to guide the steps toward developing, executing, and debugging a Python script. Errors in code were solved through conversational exchange with ChatGPT, and a tentative script was created. The code pulled the mHealth solutions from the Google Play Store and searched their descriptions for keywords that hinted toward evidence base. The results were exported to a CSV file, which was compared to the initial outputs of other similar systematic review processes. CONCLUSIONS: This study demonstrates the potential of using generative AI to automate the time-consuming process of conducting systematic reviews of mHealth apps. This approach could be particularly useful for researchers with limited coding skills. However, the study has limitations related to the design science research methodology, subjectivity bias, and the quality of the search results used to train the language model.

Timing, Indicators, and Approaches to Digital Patient Experience Evaluation: Umbrella Systematic Review.

BACKGROUND: The increasing prevalence of DH applications has outpaced research and practice in digital health (DH) evaluations. Patient experience (PEx) was reported as one of the challenges facing the health system by the World Health Organization. To generate evidence on DH and promote the appropriate integration and use of technologies, a standard evaluation of PEx in DH is required. OBJECTIVE: This study aims to systematically identify evaluation timing considerations (ie, when to measure), evaluation indicators (ie, what to measure), and evaluation approaches (ie, how to measure) with regard to digital PEx. The overall aim of this study is to generate an evaluation guide for further improving digital PEx evaluation. METHODS: This is a 2-phase study parallel to our previous study. In phase 1, literature reviews related to PEx in DH were systematically searched from Scopus, PubMed, and Web of Science databases. Two independent raters conducted 2 rounds of paper screening, including title and abstract screening and full-text screening, and assessed the interrater reliability for 20% (round 1: 23/115 and round 2: 12/58) random samples using the Fleiss-Cohen coefficient (round 1: k1=0.88 and round 2: k2=0.80). When reaching interrater reliability (k>0.60), TW conducted the rest of the screening process, leaving any uncertainties for group discussions. Overall, 38% (45/119) of the articles were considered eligible for further thematic analysis. In phase 2, to check if there were any meaningful novel insights that would change our conclusions, we performed an updated literature search in which we collected 294 newly published reviews, of which 102 (34.7%) were identified as eligible articles. We considered them to have no important changes to our original results on the research objectives. Therefore, they were not integrated into the synthesis of this review and were used as supplementary materials. RESULTS: Our review highlights 5 typical evaluation objectives that serve 5 stakeholder groups separately. We identified a set of key evaluation timing considerations and classified them into 3 categories: intervention maturity stages, timing of the evaluation, and timing of data collection. Information on evaluation indicators of digital PEx was identified and summarized into 3 categories (intervention outputs, patient outcomes, and health care system impact), 9 themes, and 22 subthemes. A set of evaluation theories, common study designs, data collection methods and instruments, and data analysis approaches was captured, which can be used or adapted to evaluate digital PEx. CONCLUSIONS: Our findings enabled us to generate an evaluation guide to help DH intervention researchers, designers, developers, and program evaluators evaluate digital PEx. Finally, we propose 6 directions for encouraging further digital PEx evaluation research and practice to address the challenge of poor PEx.

Polypharmacy and Drug Interactions in the COVID-19 Pandemic.

The COVID-19 pandemic generated a great impact on health systems. We compared evolution, polypharmacy, and potential drug-drug interactions (P-DDIs) in COVID-19 and non-COVID-19 hospitalizations during first wave of pandemic. Prescriptions for hospitalized patients ≥ 18 years (COVID-19 and non-COVID-19 rooms) between April and September 2020 were included. The computerized medical decision support system SIMDA and the physician order entry system Hdc.DrApp.la were used. Patients in COVID-19 rooms were divided into detectable and non-detectable, according to real-time reverse transcription polymerase chain reaction (RT-PCR). Number of drugs, prescribed on day 1, after day 1, and total; polypharmacy, excessive polypharmacy, and P-DDIs were compared. 1,623 admissions were evaluated: 881 COVID-19, 538 detectable and 343 non-detectable, and 742 non-COVID-19. Mortality was 15% in COVID-19 and 13% in non-COVID-19 (RR [non-COVID-19 vs. COVID-19]: 0.84 [95% CI] [0.66-1.07]). In COVID-19, mortality was 19% in detectable and 9% in non-detectable (RR: 2.07 [1.42-3.00]). Average number of drugs was 4.54/patient (SD ± 3.06) in COVID-19 and 5.92/patient (±3.24) in non-COVID-19 (p<0.001) on day 1 and 5.57/patient (±3.93) in COVID-19 and 9.17/patient (±5.27) in non-COVID-19 (p<0.001) throughout the hospitalization. 45% received polypharmacy in COVID-19 and 62% in non-COVID-19 (RR: 1.38 [1.25-1.51]) and excessive polypharmacy 7% in COVID-19 and 14% in non-COVID-19 (RR: 2.09 [1.54-2.83]). The frequency of total P-DDIs was 0.31/patient (±0.67) in COVID-19 and 0.40/patient (±0.94) in non-COVID-19 (p=0.022). Hospitalizations in the COVID-19 setting are associated with less use of drugs, less polypharmacy and less P-DDIs. Detectable patients had higher mortality.

An Exploratory Study on the Utility of Patient-Generated Health Data as a Tool for Health Care Professionals in Multiple Sclerosis Care.

BACKGROUND: Patient-generated health data (PGHD) are data collected through technologies such as mobile devices and health apps. The integration of PGHD into health care workflows can support the care of chronic conditions such as multiple sclerosis (MS). Patients are often willing to share data with health care professionals (HCPs) in their care team; however, the benefits of PGHD can be limited if HCPs do not find it useful, leading patients to discontinue data tracking and sharing eventually. Therefore, understanding the usefulness of mobile health (mHealth) solutions, which provide PGHD and serve as enablers of the HCPs' involvement in participatory care, could motivate them to continue using these technologies. OBJECTIVE: The objective of this study is to explore the perceived utility of different types of PGHD from mHealth solutions which could serve as tools for HCPs to support participatory care in MS. METHOD: A mixed-methods approach was used, combining qualitative research and participatory design. This study includes three sequential phases: data collection, assessment of PGHD utility, and design of data visualizations. In the first phase, 16 HCPs were interviewed. The second and third phases were carried out through participatory workshops, where PGHD types were conceptualized in terms of utility. RESULTS: The study found that HCPs are optimistic about PGHD in MS care. The most useful types of PGHD for HCPs in MS care are patients' habits, lifestyles, and fatigue-inducing activities. Although these subjective data seem more useful for HCPs, it is more challenging to visualize them in a useful and actionable way. CONCLUSION: HCPs are optimistic about mHealth and PGHD as tools to further understand their patients' needs and support care in MS. HCPs from different disciplines have different perceptions of what types of PGHD are useful; however, subjective types of PGHD seem potentially more useful for MS care.

Perceived Barriers and Facilitators in Using Patient-Reported Outcome Systems for Cancer Care: Systematic Mapping Study.

BACKGROUND: Cancer is a major global health problem. Patient-reported outcome (PRO) systems have been developed to support the treatment of patients with cancer. Although clear evidence of the benefits of the routine use of electronic patient-reported outcomes (ePROs) exists, engaging physicians in using these systems has been challenging. OBJECTIVE: This study aims to identify and analyze what is currently known about health care professionals' (HCPs) perceived barriers and facilitators that exist and influence the use of ePRO systems for cancer care. METHODS: We carried out a systematic mapping study by conducting searches of 3 databases (Association for Computing Machinery, PubMed, and Scopus). Eligible papers were published between 2010 and 2021, and they described HCPs' perspectives on using ePROs. The data on the included papers were extracted, a thematic meta-synthesis was performed, and 7 themes were summarized into 3 categories. RESULTS: A total of 17 papers were included in the study. The HCPs' perceived barriers and facilitators of using ePROs can be summarized into 7 themes: clinical workflow, organization and infrastructure, value to patients, value to HCPs, digital health literacy, usability, and data visualization and perceived features. These themes can be further summarized into 3 categories: work environment, value to users, and suggested features. According to the study, ePROs should be interoperable with hospital electronic health records and adapted to the hospital workflow. HCPs should get appropriate support for their use. Additional features are needed for ePROs, and special attention should be paid to data visualization. Patients should have the option to use web-based ePROs at home and complete it at the time most valuable to the treatment. Patients' ePRO notes need attention during clinical visits, but ePRO use should not limit patient-clinician face-to-face communication. CONCLUSIONS: The study revealed that several aspects need improvement in ePROs and their operating environments. By improving these aspects, HCPs' experience with ePROs will enhance, and thus, there will be more facilitating factors for HCPs to use ePROs than those available today. More national and international knowledge about using ePROs is still needed to cover the need for information to develop them and their operating environments to meet the needs of HCPs.

Development and Implementation of the Hdc.DrApp.la and SIMDA Programs to Reduce Polypharmacy and Drug-drug Interactions in Patients Hospitalized in Internal Medicine.

OBJECTIVES: We evaluated polypharmacy and possible drug-drug interactions (p-DDIs) in hospitalized patients before and after using the SIMDA Computerized Medical Decision Support System (CMDSS). MATERIALS AND METHODS: We included the prescriptions of ≥ 18 years hospitalized patients in the internal medicine department. We developed and implemented the Hdc.DrApp Physician Order Entry System and the CMDSS SIMDA, which detects p-DDIs and signals dosage adjustment based on renal function. To evaluate the impact of the CMDSS, we made a comparison Before (Survey) / After (Intervention): Survey between Oct/22/2019, and Mar/21/2020, and Intervention between Apr/4/2020 and Sep/3/2020. We analyze prescriptions from the first day and after the first day. We compared the number of drugs, polypharmacy (≥ 5 drugs), excessive polypharmacy (≥ 10 drugs), and p-DDIs. We evaluated differences with the X2 test, Yates correction, Fisher's exact test, ANOVA, and post hoc tests according to their characteristics. RESULTS: We evaluated 2,834 admissions: Survey 1,211 and Intervention 1,623. The number of drugs per patient was 6.02 (± 3.20) in Survey and 5.17 (± 3.22) in Intervention (p < 0.001) on the first day and 9.68 (± 5.60) in Survey and 7.22 (± 4.93) in Intervention (p < 0.001) throughout the hospitalization. Polypharmacy was present in 64% of the Survey and 53% of Interventions (RR: 0.83 (0.78-0.88); and excessive polypharmacy in 14% of the Survey and 10% of Intervention (RR: 0.73, 0.60-0.90). The frequency of total p-DDIs was 1.91/patient (± 4.11) in Survey and 0.35 (± 0.81) in the Intervention (p < 0.001). CONCLUSIONS: We developed and implemented the Hdc.DrApp and SIMDA systems that were easy to use and allowed us to quantify and reduce polypharmacy and p-DDIs.

Digital Patient Experience: Umbrella Systematic Review.

BACKGROUND: The adoption and use of technology have significantly changed health care delivery. Patient experience has become a significant factor in the entire spectrum of patient-centered health care delivery. Digital health facilitates further improvement and empowerment of patient experiences. Therefore, the design of digital health is served by insights into the barriers to and facilitators of digital patient experience (PEx). OBJECTIVE: This study aimed to systematically review the influencing factors and design considerations of PEx in digital health from the literature and generate design guidelines for further improvement of PEx in digital health. METHODS: We performed an umbrella systematic review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology. We searched Scopus, PubMed, and Web of Science databases. Two rounds of small random sampling (20%) were independently reviewed by 2 reviewers who evaluated the eligibility of the articles against the selection criteria. Two-round interrater reliability was assessed using the Fleiss-Cohen coefficient (k1=0.88 and k2=0.80). Thematic analysis was applied to analyze the extracted data based on a small set of a priori categories. RESULTS: The search yielded 173 records, of which 45 (26%) were selected for data analysis. Findings and conclusions showed a great diversity; most studies presented a set of themes (19/45, 42%) or descriptive information only (16/45, 36%). The digital PEx-related influencing factors were classified into 9 categories: patient capability, patient opportunity, patient motivation, intervention technology, intervention functionality, intervention interaction design, organizational environment, physical environment, and social environment. These can have three types of impacts: positive, negative, or double edged. We captured 4 design constructs (personalization, information, navigation, and visualization) and 3 design methods (human-centered or user-centered design, co-design or participatory design, and inclusive design) as design considerations. CONCLUSIONS: We propose the following definition for digital PEx: "Digital patient experience is the sum of all interactions affected by a patient's behavioral determinants, framed by digital technologies, and shaped by organizational culture, that influence patient perceptions across the continuum of care channeling digital health." In this study, we constructed a design and evaluation framework that contains 4 phases-define design, define evaluation, design ideation, and design evaluation-and 9 design guidelines to help digital health designers and developers address digital PEx throughout the entire design process. Finally, our review suggests 6 directions for future digital PEx-related research.

Design-Relevant Factors Affecting the Patient Experience in Digital Health: Preliminary Results of an Umbrella Systematic Review.

Since Covid-19, digital health interventions (DHIs) have been embraced as never before. The pandemic led to many new challenges, including the patient experience in digital health care delivery. In this literature study, we identified and synthesized factors that impact patient experience in digital health (dPEx), and reviewed the methods and strategies relevant to its design and implementation. We conducted an umbrella review including 15 reviews representing 543 studies. Four themes were identified that describe design-relevant factors that impact dPEx: individual context, content, technical issues, and design features. We propose a preliminary framework to explain the relationship between each factor and support user-centered design efforts. Further research is needed to identify which factors have the most impact.

Informing the Product Development of an mHealth Solution for People with Multiple Sclerosis Through Early Health Technology Assessment.

The potential of mHealth is enormous for chronic conditions, yet the integration of these technologies into the clinical infrastructures and healthcare pathways remains an ongoing challenge. Digi-HTA has been developed to support health technology assessment activities for novel digital healthcare technologies. The use of Early Health Technology Assessment (EHTA) can help product development. The present study describes the way in which EHTA can guide the development of a product to anticipate future needs and market access.

Experiences Using Patient and Public Involvement in Digital Health Research for Multiple Sclerosis.

Patient and public involvement (PPI) is increasingly used for improving quality of the research. There are many barriers in translating PPI into practice, including lacking examples of good practices. Frameworks that have been developed in one setting do not readily transfer to other settings. In this paper, we examine the implementation of PPI in the context of a digital health research project that explores the design, development and use of mHealth for persons with Multiple Sclerosis taking an iterative user-centered design approach. Methods: Instrumental case study to describe the PPI process on a digital health research project. Results: Overall experience was positive. We found 3 roles for PPI involvement: strategic members; design and development partners; and expert members. Challenges lay on unclear PPI terminology; managing roles and expectations; and ensuring accessibility.

Health Care Professionals' Perspectives on the Uses of Patient-Generated Health Data.

Integration of digital self-management solutions into health care processes requires the involvement of health care professionals in the adoption and use of the solutions as part of the care pathway. We conducted 23 interviews with diverse profiles of health care professionals participating in the treatment of chronic patients in three different countries. Our results indicate that health care professionals appeared relatively motivated at the prospect of having access to patient-generated data. Nevertheless, they appeared less confident in weighing what types of data could be collected efficiently through mobile devices and how it could be presented in ways that would provide value to the care process. Our results identify four broad categories for how patient-generated health data could be useful: monitoring, prevention, research, and transparency of condition parameters.

Usability assessment of an interactive health technology for kidney living donors: protocol for a prospective cross-sectional survey.

INTRODUCTION: Several web portals for kidney patients are available, but assessments of their performance are scarce. A crucial aspect of living donation is to provide standardised information about the risks of the procedure. This is of particular interest among candidates for kidney living donation. In 2019, the Digital Care Path for Living Kidney Donor Candidates was launched in Finland as part of the Health Village portal, containing information about the donation process and facilitating communication between clinicians, transplant coordinators and patients. The performance of this eHealth service has not yet been studied. The present study will investigate living donor candidates' experience with the Health Village and Digital Care Path for Living Kidney Donor Candidates. Participants' general attitudes towards the use of eHealth services will also be explored as a secondary objective. METHODS AND ANALYSIS: A prospective cross-sectional survey study will take place. Participants will be kidney donor candidates who have used the digital care path since its implementation in January 2019 up to 1 March 2021 (N=122). The surveys will include demographic data, electronic device ownership and digital health literacy. Platform's ease of use will be assessed with the System Usability Scale. Open-ended questions will be used to gather suggestions. ETHICS AND DISSEMINATION: The research protocol has been approved by the Helsinki University Hospital ethical committee (HUS/501/2021) to ensure that the work is done in accordance with the declaration of Helsinki and Declaration of Istanbul. Recruitment will start during the first semester of 2021. Initial results are expected during the second semester of 2021. TRIAL REGISTRATION NUMBER: NCT04791670; Pre-results.

Impact of COVID-19 on Multiple Sclerosis Topic Discussion on Twitter.

INTRODUCTION: Multiple sclerosis (MS) is one of the world's most common neurologic disorders. Social media have been proposed as a way to maintain and even increase social interaction for people with MS. The objective of this work is to identify and compare the topics on Twitter during the first wave of COVID-19 pandemic. METHODS: Data was collected using the Twitter API between 9/2/2019 and 13/5/2020. SentiStrength was used to analyze data with the day that the pandemic was declared used as a turning point. Frequency-inverse document frequency (tf-idf) was used for each unigram and calculated the gains in tf-idf value. A comparative analysis of the relevance of words and categories among the datasets was performed. RESULTS: The original dataset contained over 610k tweets, our final dataset had 147,963 tweets. After the 10th of march some categories gained relevance in positive tweets ("Healthcare professional", "Chronic conditions", "Condition burden"), while in negative tweets "Emotional aspects" became more relevant and "COVID-19" emerged as a new topic. CONCLUSIONS: Our work provides insight on how COVID-19 has changed the online discourse of people with MS.

The impact of COVID-19 on abortion access: Insights from the European Union and the United Kingdom.

Government policies on abortion are a longstanding topic of heated political debates. The COVID-19 pandemic shook health systems to the core adding further to the complexity of this topic, as imposed national lockdowns and movement restrictions affected access to timely abortion for millions of women across the globe. In this paper, we examine how countries within the European Union and the United Kingdom responded to challenges brought by the COVID-19 crisis in terms of access to abortion. By combining information from various sources, we have explored different responses according to two dimensions: changes in policy and protocols, and reported difficulties in access. Our analysis shows significant differences across the observed regions and salient debates around abortion. While some countries made efforts to maintain and facilitate abortion care during the pandemic through the introduction or expansion of use of telemedicine and early medical abortion, others attempted to restrict it further. The situation was also diverse in the countries where governments did not change policies or protocols. Based on our data analysis, we provide a framework that can help policy makers improve abortion access.

The Need for Sustainable Teleconsultation Systems in the Aftermath of the First COVID-19 Wave.

The physical and social distancing measures that have been adopted worldwide because of COVID-19 will probably remain in place for a long time, especially for senior adults, people with chronic conditions, and other at-risk populations. Teleconsultations can be useful in ensuring that patients continue to receive clinical care while reducing physical crowding and avoiding unnecessary exposure of health care staff. Implementation processes that typically take months of planning, budgeting, pilot testing, and education were compressed into days. However, in the urgency to deal with the present crisis, we may be forgetting that the introduction of digital health is not exclusively a technological issue, but part of a complex organizational change problem. This viewpoint offers insight regarding issues that rapidly adopted teleconsultation systems may face in a post-COVID-19 world.

Data-Driven Personalization of a Physiotherapy Care Pathway: Case Study of Posture Scanning.

BACKGROUND: Advanced sensor, measurement, and analytics technologies are enabling entirely new ways to deliver health care. The increased availability of digital data can be used for data-driven personalization of care. Data-driven personalization can complement expert-driven personalization by providing support for decision making or even by automating some parts of decision making in relation to the care process. OBJECTIVE: The aim of this study was to analyze how digital data acquired from posture scanning can enhance physiotherapy services and enable more personalized delivery of physiotherapy. METHODS: A case study was conducted with a company that designed a posture scan recording system (PSRS), which is an information system that can digitally record, measure, and report human movement for use in physiotherapy. Data were collected through interviews with different stakeholders, such as health care professionals, health care users, and the information system provider, and were analyzed thematically. RESULTS: Based on the results of our thematic analysis, we propose three different types of support that posture scanning data can provide to enhance and enable more personalized delivery of physiotherapy: 1) modeling the condition, in which the posture scanning data are used to detect and understand the health care user's condition and the root cause of the possible pain; 2) visualization for shared understanding, in which the posture scanning data are used to provide information to the health care user and involve them in more collaborative decision-making regarding their care; and 3) evaluating the impact of the intervention, in which the posture scanning data are used to evaluate the care progress and impact of the intervention. CONCLUSIONS: The adoption of digital tools in physiotherapy has remained low. Physiotherapy has also lacked digital tools and means to inform and involve the health care user in their care in a person-centered manner. In this study, we gathered insights from different stakeholders to provide understanding of how the availability of digital posture scanning data can enhance and enable personalized physiotherapy services.

Evaluation of More Stamina, a Mobile App for Fatigue Management in Persons with Multiple Sclerosis: Protocol for a Feasibility, Acceptability, and Usability Study.

BACKGROUND: Multiple sclerosis (MS) is one of the world's most common neurologic disorders leading to severe disability in young adults. MS-related fatigue directly impacts on the quality of life and activity levels of people with MS. Self-management strategies are used to support them in the care of their health. Mobile health (mHealth) solutions can offer tools to help symptom management. Following a user-centered design and evidence-based process, an mHealth solution called More Stamina was created to help persons with MS manage their fatigue. OBJECTIVE: The overall study aims are to explore the feasibility, acceptability, and usability of More Stamina, a mobile app for fatigue self-management for persons with MS. METHODS: A mixed-methods, multicenter study will be used to assess the feasibility, acceptability, and usability of More Stamina. The study will take place during the third and fourth quarters of 2020 (Q3-Q4 2020) in 3 locations: Argentina, Spain, and Switzerland. A longitudinal cohort study will take place, and think-aloud protocols, open-ended interviews, and short answer questionnaires will be used. Persons with MS will be recruited from the different locations. This study seeks to enroll at least 20 patients that meet the criteria from each site for the longitudinal cohort study (total n=60). RESULTS: Ethical approval has been granted in Argentina and is pending in Spain and Switzerland. Outcomes will be published in peer-reviewed medical journals and presented at international conferences. CONCLUSIONS: Findings from this study will be used to help understand the role that mHealth can play in fatigue management in MS. TRIAL REGISTRATION: ClinicalTrials.gov NCT04244214; https://clinicaltrials.gov/ct2/show/NCT04244214. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/18196.

Analysing Sentiment and Topics Related to Multiple Sclerosis on Twitter.

BACKGROUND AND OBJECTIVE: Social media could be valuable tools to support people with multiple sclerosis (MS). There is little evidence on the MS-related topics that are discussed on social media, and the sentiment linked to these topics. The objective of this work is to identify the MS-related main topics discussed on Twitter, and the sentiment linked to them. METHODS: Tweets dealing with MS in the English language were extracted. Latent-Dirilecht Allocation (LDA) was used to identify the main topics discussed in these tweets. Iterative inductive process was used to group the tweets into recurrent topics. The sentiment analysis of these tweets was performed using SentiStrength. RESULTS: LDA' identified topics were grouped into 4 categories, tweets dealing with: related chronic conditions; condition burden; disease-modifying drugs; and awareness-raising. Tweets on condition burden and related chronic conditions were the most negative (p<0.001). A significant lower positive sentiment was found for both tweets dealing with disease-modifying drugs, condition burden, and related chronic conditions (p<0.001). Only tweets on awareness-raising were most positive than the average (p<0.001). DISCUSSION: The use of both tools to identify the main discussed topics on social media and to analyse the sentiment of these topics, increases the knowledge of the themes that could represent the bigger burden for persons affected with MS. This knowledge can help to improve support and therapeutic approaches addressed to them.

Service Personalization in IT-Supported Finnish Healthcare.

This paper reports a case study on the spontaneous personalization discussions emerged from interviews with healthcare professionals when asked about their work practices and the role of information technology (IT) during consultations. We thematically analyzed the personalization elements using an existing personalization framework to provide insights on the service personalization. Our results contribute to the better design of IT solutions that can support health services' personalization.