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  • 1.
    Berglund, Erik
    et al.
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för folkhälso- och vårdvetenskap, Socialmedicinsk epidemiologi.
    Westerling, Ragnar
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för folkhälso- och vårdvetenskap, Socialmedicinsk epidemiologi.
    Sundström, Johan
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Klinisk epidemiologi. Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska och farmaceutiska vetenskapsområdet, centrumbildningar mm, Uppsala kliniska forskningscentrum (UCR).
    Lytsy, Per
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för folkhälso- och vårdvetenskap, Socialmedicinsk epidemiologi.
    Length of time periods in treatment effect descriptions and willingness to initiate preventive therapy: a randomised survey experiment2018Inngår i: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 18, artikkel-id 106Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background Common measures used to describe preventive treatment effects today are proportional, i.e. they compare the proportions of events in relative or absolute terms, however they are not easily interpreted from the patient's perspective and different magnitudes do not seem to clearly discriminate between levels of effect presented to people. Methods In this randomised cross-sectional survey experiment, performed in a Swedish population-based sample (n=1041, response rate 58.6%), the respondents, aged between 40 and 75years were given information on a hypothetical preventive cardiovascular treatment. Respondents were randomised into groups in which the treatment was described as having the effect of delaying a heart attack for different periods of time (Delay of Event,DoE): 1month, 6months or 18months. Respondents were thereafter asked about their willingness to initiate such therapy, as well as questions about how they valued the proposed therapy. ResultsLonger DoE:s were associated with comparatively greater willingness to initiate treatment. The proportions accepting treatment were 81, 71 and 46% when postponement was 18months, 6months and 1month respectively. In adjusted binary logistic regression models the odds ratio for being willing to take therapy was 4.45 (95% CI 2.72-7.30) for a DoE of 6months, and 6.08 (95% CI 3.61-10.23) for a DoE of 18months compared with a DoE of 1month. Greater belief in the necessity of medical treatment increased the odds of being willing to initiate therapy. ConclusionsLay people's willingness to initiate preventive therapy was sensitive to the magnitude of the effect presented as DoE. The results indicate that DoE is a comprehensible effect measure, of potential value in shared clinical decision-making.

  • 2. Davoody, Nadia
    et al.
    Koch, Sabine
    Krakau, Ingvar
    Hägglund, Maria
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för kvinnors och barns hälsa, Forskargrupper (Inst. för kvinnor och barns hälsa), Klinisk psykologi i hälso- och sjukvård.
    Accessing and sharing health information for post-discharge stroke care through a national health information exchange platform: a case study2019Inngår i: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 19, nr 1, artikkel-id 95Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    BACKGROUND:

    Patients and citizens need access to their health information to get a retrospective as well as a prospective view on their care and rehabilitation processes. However, patients' health information is stored in several health information systems and interoperability problems often hamper accessibility. In Sweden a national health information exchange (HIE) platform has been developed that enables information exchange between different health information systems. The aim of this study is to explore the opportunities and limitations of accessing and interacting with important health information through the Swedish national HIE platform.

    METHODS:

    A single case study approach was used for this study as an in-depth understanding of the subject was needed. A fictive patient case with a pseudo-name was created based on an interview with a stroke coordinator in Stockholm County. Information access through the national health information exchange platform and available service contracts and application programming interfaces were studied using different scenarios.

    RESULTS:

    Based on the scenarios created in this study, patients would be able to access some health related information from their electronic health records using the national health information exchange platform. However, there is necessary information which is not retrievable as it is either stored in electronic health records and eHealth services which are not connected to the national health information exchange platform or there is no service contract developed for these types of information. In addition, patients are not able to share information with healthcare professionals.

    CONCLUSION:

    The national Swedish HIE platform provides the building blocks needed to allow patients online access to their health information in a fragmented and distributed health system. However, more complex interaction scenarios allowing patients to communicate with their health care providers or to update their health related information are not yet supported. Therefore it is of great importance to involve patients throughout the design and evaluation of eHealth services on both national and local levels to ensure that their needs for interoperability and information exchange are met.

  • 3. Davoody, Nadia
    et al.
    Koch, Sabine
    Krakau, Ingvar
    Hägglund, Maria
    Post-discharge stroke patients' information needs as input to proposing patient-centred eHealth services.2016Inngår i: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 16, artikkel-id 66Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    BACKGROUND: Despite the potential of eHealth services to revolutionize the way healthcare and prevention is provided many applications developed for patients fail to deliver their promise. Therefore, the aim of this study is to use patient journey mapping to explore post-discharge stroke patients' information needs to propose eHealth services that meet their needs throughout their care and rehabilitation processes.

    METHODS: Three focus groups with younger (<65 years) and older (> = 65 years) stroke patients were performed. Content analysis was used to analyse the data. Stroke patients' information needs was explored using patient journey model.

    RESULTS: Four main events (discharge from hospital, discharge from rehab clinic, coming home, and clinical encounters) and two phases (at rehab clinic, at home) have been identified in patients' post-discharge journey. The main categories identified in this study indicate that patients not only need to have access to health related information about their care and rehabilitation processes but also practical guidance through healthcare and community services. Patients also have different information needs at different events and during different phases. Potential supportive eHealth services were suggested by the researchers considering different parts of the patients' journeys.

    CONCLUSIONS: Patient journey models and qualitative analysis of patients' information needs are powerful tools that can be used to improve healthcare from a patient perspective. As patients' understanding of their illness changes over time, their need of more flexible support throughout the care and rehabilitation processes increases. To design appropriate eHealth services that meet patients' information needs, it is imperative to understand the current care and rehabilitation processes and identify patients' information needs throughout their journey.

  • 4.
    Fors, Uno
    et al.
    Stockholm Univ, Dept Comp & Syst Sci DSV, Stockholm, Sweden.
    Kamwesiga, Julius T.
    Uganda Allied Hlth Examinat Board, Kampala, Uganda;Karolinska Inst, Div Occupat Therapy, Dept Neurobiol Care Sci & Soc, Stockholm, Sweden.
    Eriksson, Gunilla
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för folkhälso- och vårdvetenskap, Forskning om funktionshinder och habilitering. Karolinska Inst, Div Occupat Therapy, Dept Neurobiol Care Sci & Soc, Stockholm, Sweden.
    von Koch, Lena
    Karolinska Inst, Div Occupat Therapy, Dept Neurobiol Care Sci & Soc, Stockholm, Sweden;Karolinska Univ Hosp, Theme Neuro, Stockholm, Sweden.
    Guidetti, Susanne
    Karolinska Inst, Div Occupat Therapy, Dept Neurobiol Care Sci & Soc, Stockholm, Sweden.
    User evaluation of a novel SMS-based reminder system for supporting post-stroke rehabilitation2019Inngår i: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 19, artikkel-id 122Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background: According to WHO stroke is a growing societal challenge and the third leading cause of global disease-burden estimated using disability-adjusted life years. Rehabilitation after stroke is an area of mutual interest for health care in many countries. Within the health care sector there is a growing emphasis on ICT services to provide clients with easier access to information, self-evaluation, and self-management. ICT-supported care programs possible to use in clients' home environments are also recommended when there are long distances to the health care specialists. The aim of this study was to evaluate the technical usability of a SMS-based reminder system as well as user opinions when using such a system to assist clients to remember to perform daily rehabilitation activities, to rate their performance and to allow Occupational therapists (OT's) to track and follow-up clients' results over time.

    Methods: Fifteen persons with stroke were invited to participate in the study and volunteered to receive daily SMS-based reminders regarding three activities to perform on a daily basis as well as answer daily SMS-based questions about their success rate during eight weeks. Clients, a number of family members, as well as OTs were interviewed to evaluate their opinions of using the reminder system.

    Results: All clients were positive to the reminder system and felt that it helped them to regain their abilities. Their OTs agreed that the reminder and follow-up system was of benefit in the rehabilitation process. However, some technical and other issues were limiting the use of the system for some clients. The issues were mostly linked to the fact that the SMS system was based on a Swedish phone number, so that all messages needed to be sent internationally.

    Conclusion: In conclusion, it seems that this type of SMS-based reminder systems could be of good use in the rehabilitation process after stroke, even in low income counties where few clients have access to Internet or smart phones, and where access to healthcare services is limited. However, since the results are based on clients', OTs' and family members' expressed beliefs, we suggest that future research objectively investigate the intervention's beneficial effects on the clients' physical and cognitive health.

  • 5.
    Hamberg, Anna-Karin
    et al.
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Klinisk farmakogenomik och osteoporos.
    Hellman, Jacob
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Tekniska sektionen, Institutionen för teknikvetenskaper, Nanoteknologi och funktionella material.
    Dahlberg, Jonny
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Tekniska sektionen, Institutionen för teknikvetenskaper, Nanoteknologi och funktionella material.
    Jonsson, E Niclas
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap.
    Wadelius, Mia
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Klinisk farmakogenomik och osteoporos.
    A Bayesian decision support tool for efficient dose individualization of warfarin in adults and children2015Inngår i: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 15, nr 7Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Warfarin is the most widely prescribed anticoagulant for prevention and treatment of thromboembolic events. Although highly effective, the use of warfarin is limited by a narrow therapeutic range combined with a more than ten-fold difference in the dose required for adequate anticoagulation in adults. For each patient, an optimal dose that leads to a favourable balance between the wanted antithrombotic effect and the risk of bleeding, measured as the prothrombin time International Normalised Ratio (INR), must be found. A model capable of describing the time-course of the INR response to warfarin therapy can be used to aid dose selection, both before starting therapy (a priori dose prediction) and after therapy has been initiated (a posteriori dose revision). In this paper we describe the transfer of a population PKPD-model for warfarin developed in NONMEM to a platform independent decision support tool written in Java. The tool proved capable of solving a system of differential equations representing the pharmacokinetics and pharmacodynamics of warfarin, with a performance comparable to NONMEM. To estimate an a priori dose the user provides information on body weight, age, CYP2C9 and VKORC1 genotype, baseline and target INR. With addition of information about previous doses and INR observations, the tool will use a Bayesian forecasting method to suggest an a posteriori dose, i.e. the dose with the highest probability to result in the desired INR. Results are displayed as the predicted dose per day and per week, and graphically as the predicted INR curve. The tool can also be used to predict INR following any given dose regimen, e.g. a loading-dose regimen. We believe it will provide a clinically useful tool for initiating and maintaining warfarin therapy in the clinic. It will ensure consistent dose adjustment practices between prescribers, and provide more efficient individualization of warfarin dosing in both children and adults.

  • 6.
    Janssens, Rosanne
    et al.
    Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Herestraat 49, Box 521, 3000, Leuven, Belgium.
    Huys, Isabelle
    Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Herestraat 49, Box 521, 3000, Leuven, Belgium.
    van Overbeeke, Eline
    Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Herestraat 49, Box 521, 3000, Leuven, Belgium.
    Whichello, Chiara
    Erasmus School of Health Policy & Management (ESHPM) and Erasmus Choice Modelling Centre (ECMC), Erasmus University Rotterdam, P.O. Box 1738, 3000, DR, Rotterdam, The Netherlands.
    Harding, Sarah
    Takeda International, UK Branch, 61 Aldwych, London, WC2B 4AE, UK.
    Kübler, Jürgen
    QSciCon, Europabadstr. 8, 35041, Marburg, Germany.
    Juhaeri, Juhaeri
    Sanofi, 55 Corporate Drive, Bridgewater Township, NJ, 08807, USA.
    Ciaglia, Antonio
    International Alliance of Patients’ Organizations, 49-51 East Rd, Hoxton, London, N1 6AH, UK.
    Simoens, Steven
    Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Herestraat 49, Box 521, 3000, Leuven, Belgium.
    Stevens, Hilde
    Institute for Interdisciplinary Innovation in healthcare (I3h), Université libre de Bruxelles (ULB), Route de Lennik 808, 1070, Brussels, Belgium.
    Smith, Meredith
    Amgen, Inc., Thousand Oaks, California, USA.
    Levitan, Bennet
    Global R&D Epidemiology, Janssen Research & Development, 1125 Trenton-Harbourton Road, PO Box 200, Titusville, NJ, 08560, USA.
    Cleemput, Irina
    Belgian Health Care Knowledge Centre (KCE), Kruidtuinlaan 55, 1000, Brussels, Belgium.
    de Bekker-Grob, Esther
    Erasmus School of Health Policy & Management (ESHPM) and Erasmus Choice Modelling Centre (ECMC), Erasmus University Rotterdam, P.O. Box 1738, 3000, DR, Rotterdam, The Netherlands.
    Veldwijk, Jorien
    Erasmus School of Health Policy & Management (ESHPM) and Erasmus Choice Modelling Centre (ECMC), Erasmus University Rotterdam, P.O. Box 1738, 3000, DR, Rotterdam, The Netherlands.
    Opportunities and challenges for the inclusion of patient preferences in the medical product life cycle: a systematic review2019Inngår i: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background: The inclusion of patient preferences (PP) in the medical product life cycle is a topic of growing interest to stakeholders such as academics, Health Technology Assessment (HTA) bodies, reimbursement agencies, industry, patients, physicians and regulators. This review aimed to understand the potential roles, reasons for using PP and the expectations, concerns and requirements associated with PP in industry processes, regulatory benefitrisk assessment (BRA) and marketing authorization (MA), and HTA and reimbursement decision-making. Methods: A systematic review of peer-reviewed and grey literature published between January 2011 and March 2018 was performed. Consulted databases were EconLit, Embase, Guidelines International Network, PsycINFO and PubMed. A two-step strategy was used to select literature. Literature was analyzed using NVivo (QSR international). Results: From 1015 initially identified documents, 72 were included. Most were written from an academic perspective (61%) and focused on PP in BRA/MA and/or HTA/reimbursement (73%). Using PP to improve understanding of patients’ valuations of treatment outcomes, patients’ benefit-risk trade-offs and preference heterogeneity were roles identified in all three decision-making contexts. Reasons for using PP relate to the unique insights and position of patients and the positive effect of including PP on the quality of the decision-making process. Concerns shared across decision-making contexts included methodological questions concerning the validity, reliability and cognitive burden of preference methods. In order to use PP, general, operational and quality requirements were identified, including recognition of the importance of PP and ensuring patient understanding in PP studies. Conclusions: Despite the array of opportunities and added value of using PP throughout the different steps of the MPLC identified in this review, their inclusion in decision-making is hampered by methodological challenges and lack of specific guidance on how to tackle these challenges when undertaking PP studies. To support the development of such guidance, more best practice PP studies and PP studies investigating the methodological issues identified in this review are critically needed.

  • 7. Lamarche-Vadel, Agathe
    et al.
    Pavillon, Gérard
    Aouba, Albertine
    Johansson, Lars Age
    Swedish National Board of Health and Welfare, Center for Epidemiology, Stockholm, Sweden .
    Meyer, Laurence
    Jougla, Eric
    Rey, Grégoire
    Automated comparison of last hospital main diagnosis and underlying cause of death ICD10 codes, France, 2008-20092014Inngår i: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 14, s. 44-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    BACKGROUND: In the age of big data in healthcare, automated comparison of medical diagnoses in large scale databases is a key issue. Our objectives were: 1) to formally define and identify cases of independence between last hospitalization main diagnosis (MD) and death registry underlying cause of death (UCD) for deceased subjects hospitalized in their last year of life; 2) to study their distribution according to socio-demographic and medico-administrative variables; 3) to discuss the interest of this method in the specific context of hospital quality of care assessment.

    METHODS: 1) Elaboration of an algorithm comparing MD and UCD, relying on Iris, a coding system based on international standards. 2) Application to 421,460 beneficiaries of the general health insurance regime (which covers 70% of French population) hospitalized and deceased in 2008-2009.

    RESULTS: 1) Independence, was defined as MD and UCD belonging to different trains of events leading to death 2) Among the deaths analyzed automatically (91.7%), 8.5% of in-hospital deaths and 19.5% of out-of-hospital deaths were classified as independent. Independence was more frequent in elder patients, as well as when the discharge-death time interval grew (14.3% when death occurred within 30 days after discharge and 27.7% within 6 to 12 months) and for UCDs other than neoplasms.

    CONCLUSION: Our algorithm can identify cases where death can be considered independent from the pathology treated in hospital. Excluding these deaths from the ones allocated to the hospitalization process could contribute to improve post-hospital mortality indicators. More generally, this method has the potential of being developed and used for other diagnoses comparisons across time periods or databases.

  • 8.
    Lindhagen, Lars
    et al.
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska och farmaceutiska vetenskapsområdet, centrumbildningar mm, Uppsala kliniska forskningscentrum (UCR).
    Van Hemelrijck, Mieke
    Kings Coll London, Sch Med, Canc Epidemiol Grp, Div Canc Studies,Res Oncol,Guys Hosp, London SE1 9RT, England.;Karolinska Inst, Inst Environm Med, S-10401 Stockholm, Sweden..
    Robinson, David
    Ryhov Cty Hosp, Dept Urol, Jonkoping, Sweden..
    Stattin, Pär
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för kirurgiska vetenskaper, Urologkirurgi. Umea Univ, Dept Surg & Perioperat Sci Urol & Androl, Umea, Sweden..
    Garmo, Hans
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska och farmaceutiska vetenskapsområdet, centrumbildningar mm, Uppsala kliniska forskningscentrum (UCR). Kings Coll London, Sch Med, Canc Epidemiol Grp, Div Canc Studies,Res Oncol,Guys Hosp, London SE1 9RT, England.
    How to model temporal changes in comorbidity for cancer patients using prospective cohort data2015Inngår i: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 15, artikkel-id 96Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background: The presence of comorbid conditions is strongly related to survival and also affects treatment choices in cancer patients. This comorbidity is often quantified by the Charlson Comorbidity Index (CCI) using specific weights (1, 2, 3, or 6) for different comorbidities. It has been shown that the CCI increases at different times and with different sizes, so that traditional time to event analysis is not adequate to assess these temporal changes. Here, we present a method to model temporal changes in CCI in cancer patients using data from PCBaSe Sweden, a nation-wide population-based prospective cohort of men diagnosed with prostate cancer. Our proposed model is based on the assumption that a change in comorbidity, as quantified by the CCI, is an irreversible one-way process, i.e., CCI accumulates over time and cannot decrease. Methods: CCI was calculated based on 17 disease categories, which were defined using ICD-codes for discharge diagnoses in the National Patient Register. A state transition model in discrete time steps (i.e., four weeks) was applied to capture all changes in CCI. The transition probabilities were estimated from three modelling steps: 1) Logistic regression model for vital status, 2) Logistic regression model to define any changes in CCI, and 3) Poisson regression model to determine the size of CCI change, with an additional logistic regression model for CCI changes >= 6. The four models combined yielded parameter estimates to calculate changes in CCI with their confidence intervals. Results: These methods were applied to men with low-risk prostate cancer who received active surveillance (AS), radical prostatectomy (RP), or curative radiotherapy (RT) as primary treatment. There were large differences in CCI changes according to treatment. Conclusions: Our method to model temporal changes in CCI efficiently captures changes in comorbidity over time with a small number of regression analyses to perform - which would be impossible with tradition time to event analyses. However, our approach involves a simulation step that is not yet included in standard statistical software packages. In our prostate cancer example we showed that there are large differences in development of comorbidities among men receiving different treatments for prostate cancer.

  • 9. Revenas, Asa
    et al.
    Opava, Christina H.
    Åsenlöf, Pernilla
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för neurovetenskap, Fysioterapi.
    Lead users' ideas on core features to support physical activity in rheumatoid arthritis: a first step in the development of an internet service using participatory design2014Inngår i: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 14, s. 21-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background: Despite the growing evidence of the benefits of physical activity (PA) in individuals with rheumatoid arthritis (RA), the majority is not physically active enough. An innovative strategy is to engage lead users in the development of PA interventions provided over the internet. The aim was to explore lead users' ideas and prioritization of core features in a future internet service targeting adoption and maintenance of healthy PA in people with RA. Methods: Six focus group interviews were performed with a purposively selected sample of 26 individuals with RA. Data were analyzed with qualitative content analysis and quantification of participants' prioritization of most important content. Results: Six categories were identified as core features for a future internet service: up-to-date and evidence-based information and instructions, self-regulation tools, social interaction, personalized set-up, attractive design and content, and access to the internet service. The categories represented four themes, or core aspects, important to consider in the design of the future service: (1) content, (2) customized options, (3) user interface and (4) access and implementation. Conclusions: This is, to the best of our knowledge, the first study involving people with RA in the development of an internet service to support the adoption and maintenance of PA. Participants helped identifying core features and aspects important to consider and further explore during the next phase of development. We hypothesize that involvement of lead users will make transfer from theory to service more adequate and user-friendly and therefore will be an effective mean to facilitate PA behavior change.

  • 10. Riggare, Sara
    et al.
    Scott Duncan, Therese
    Hvitfeldt, Helena
    Hägglund, Maria
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för kvinnors och barns hälsa, Forskargrupper (Inst. för kvinnor och barns hälsa), Klinisk psykologi i hälso- och sjukvård. Karolinska Inst.
    “You have to know why you're doing this”: a mixed methods study of the benefits and burdens of self-tracking in Parkinson's disease2019Inngår i: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 19, nr 1, artikkel-id 175Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background: This study explores opinions and experiences of people with Parkinson's disease (PwP) in Sweden of using self-tracking. Parkinson's disease (PD) is a neurodegenerative condition entailing varied and changing symptoms and side effects that can be a challenge to manage optimally. Patients' self-tracking has demonstrated potential in other diseases, but we know little about PD self-tracking. The aim of this study was therefore to explore the opinions and experiences of PwP in Sweden of using self-tracking for PD.

    Method: A mixed methods approach was used, combining qualitative data from seven interviews with quantitative data from a survey to formulate a model for self-tracking in PD. In total 280 PwP responded to the survey, 64% (n = 180) of which had experience from self-tracking.

    Result: We propose a model for self-tracking in PD which share distinctive characteristics with the Plan-Do-Study-Act (PDSA) cycle for healthcare improvement. PwP think that tracking takes a lot of work and the right individual balance between burdens and benefits needs to be found. Some strategies have here been identified; to focus on positive aspects rather than negative, to find better solutions for their selfcare, and to increase the benefits through improved tools and increased use of self-tracking results in the dialogue with healthcare.

    Conclusion: The main identified benefits are that self-tracking gives PwP a deeper understanding of their own specific manifestations of PD and contributes to a more effective decision making regarding their own selfcare. The process of self-tracking also enables PwP to be more active in communicating with healthcare. Tracking takes a lot of work and there is a need to find the right balance between burdens and benefits.

  • 11.
    Ventimiglia, Eugenio
    et al.
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för kirurgiska vetenskaper, Urologkirurgi. IRCCS, Osped San Raffaele, Div Expt Oncol, Unit Urol, Milan, Italy.
    Van Hemelrijck, Mieke
    Kings Coll London, Sch Canc & Pharmaceut Sci, Translat Oncol & Urol Res Tour, Guys Hosp, 3rd Floor, London SE1 9RT, England.
    Lindhagen, Lars
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska och farmaceutiska vetenskapsområdet, centrumbildningar mm, Uppsala kliniska forskningscentrum (UCR).
    Stattin, Pär
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för kirurgiska vetenskaper, Urologkirurgi.
    Garmo, Hans
    Kings Coll London, Sch Canc & Pharmaceut Sci, Translat Oncol & Urol Res Tour, Guys Hosp, 3rd Floor, London SE1 9RT, England;Uppsala Orebro, Reg Canc Ctr, Uppsala, Sweden.
    How to measure temporal changes in care pathways for chronic diseases using health care registry data2019Inngår i: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 19, artikkel-id 103Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background: Disease trajectories for chronic diseases can span over several decades, with several time-dependent factors affecting treatment decisions. Thus, there is a need for long-term predictions of disease trajectories to inform patients and healthcare professionals on the long-term outcomes and provide information on the need of future health care. Here, we propose a state transition model to describe and predict disease trajectories up to 25 years after diagnosis in men with prostate cancer (PCa), as a proof of principle. Methods: States, state transitions, and transition probabilities were identified and estimated in Prostate Cancer data Base of Sweden (PCBaSeTraject), using nationwide population-based data from 118,743 men diagnosed with PCa. A state transition model in discrete time steps (i.e., 4 weeks) was developed and applied to capture all possible transitions (PCBaSeSim). Transition probabilities were estimated for changes in both treatment and comorbidity. These models combined yielded parameter estimates to run an individual-level simulation based on the state-transition model to obtain prediction estimates. Predicted estimates were then compared to real world data in PCBaSeTraject. Results: PCBaSeSim estimates for the cumulative incidence of first and second transitions, death from PCa and death from other causes were compared to observed transitions in PCBaSeTraject. A good agreement was found between simulated and observed estimates. Conclusions: We developed a reliable and accurate simulation tool, PCBaSeSim that provides information on disease trajectories for subjects with a chronic disease on an individual and population-based level.

  • 12.
    Wallert, John
    et al.
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för kvinnors och barns hälsa, Klinisk psykologi i hälso- och sjukvård. Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för folkhälso- och vårdvetenskap.
    Tomasoni, Mattia
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för folkhälso- och vårdvetenskap.
    Madison, Guy
    Department of Psychology, Umeå University.
    Held, Claes
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska och farmaceutiska vetenskapsområdet, centrumbildningar mm, Uppsala kliniska forskningscentrum (UCR). Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper.
    Predicting two-year survival versus non-survival after first myocardial infarction using machine learning and Swedish national register data2017Inngår i: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 17, s. 1-11, artikkel-id 99Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background: Machine learning algorithms hold potential for improved prediction of all-cause mortality in cardiovascular patients, yet have not previously been developed with high-quality population data. This study compared four popular machine learning algorithms trained on unselected, nation-wide population data from Sweden to solve the binary classification problem of predicting survival versus non-survival 2 years after first myocardial infarction (MI).

    Methods: This prospective national registry study for prognostic accuracy validation of predictive models used data from 51,943 complete first MI cases as registered during 6 years (2006–2011) in the national quality register SWEDEHEART/RIKS-HIA (90% coverage of all MIs in Sweden) with follow-up in the Cause of Death register (> 99% coverage). Primary outcome was AUROC (C-statistic) performance of each model on the untouched test set (40% of cases) after model development on the training set (60% of cases) with the full (39) predictor set. Model AUROCs were bootstrapped and compared, correcting the P-values for multiple comparisons with the Bonferroni method. Secondary outcomes were derived when varying sample size (1–100% of total) and predictor sets (39, 10, and 5) for each model. Analyses were repeated on 79,869 completed cases after multivariable imputation of predictors.

    Results: A Support Vector Machine with a radial basis kernel developed on 39 predictors had the highest complete cases performance on the test set (AUROC = 0.845, PPV = 0.280, NPV = 0.966) outperforming Boosted C5.0 (0.845 vs. 0. 841, P = 0.028) but not significantly higher than Logistic Regression or Random Forest. Models converged to the point of algorithm indifference with increased sample size and predictors. Using the top five predictors also produced good classifiers. Imputed analyses had slightly higher performance.

    Conclusions: Improved mortality prediction at hospital discharge after first MI is important for identifying high-risk individuals eligible for intensified treatment and care. All models performed accurately and similarly and because of the superior national coverage, the best model can potentially be used to better differentiate new patients, allowing for improved targeting of limited resources. Future research should focus on further model development and investigate possibilities for implementation. 

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