This study aimed to evaluate the usability (ease of use) and utility (impact on user's decision-making process) of a web-based patient decision aid (PDA) among older-age users. A pragmatic, qualitative research design was used. We recruited patients with type 2 diabetes who were at the point of making a decision about starting insulin from a tertiary teaching hospital in Malaysia in 2014. Computer screen recording software was used to record the website browsing session and in-depth interviews were conducted while playing back the website recording. The interviews were analyzed using the framework approach to identify usability and utility issues. Three cycles of iteration were conducted until no more major issues emerged. Thirteen patients participated: median age 65 years old, 10 men, and nine had secondary education/diploma, four were graduates/had postgraduate degree. Four usability issues were identified (navigation between pages and sections, a layout with open display, simple language, and equipment preferences). For utility, participants commented that the website influenced their decision about insulin in three ways: it had provided information about insulin, it helped them deliberate choices using the option-attribute matrix, and it allowed them to involve others in their decision making by sharing the PDA summary printout.
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http://dx.doi.org/10.1080/17538157.2016.1269108 | DOI Listing |
Front Neurol
December 2024
Sense4Care, Cornellà de Llobregat, Spain.
Parkinson's disease (PD) is a neurodegenerative disorder that significantly impacts patients' quality of life. Managing PD requires accurate assessment of motor and non-motor symptoms, often complicated by the subjectivity in symptom reporting and the limited availability of neurologists. To address these challenges, commercial wearable devices have emerged to continuously monitor PD symptoms outside the clinical setting.
View Article and Find Full Text PDFJ Korean Med Sci
January 2025
Department of Laboratory Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings.
Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals.
BMC Public Health
January 2025
Núcleo de Avaliação de Tecnologias em Saúde, Grupo de Pesquisa Clínica e Políticas Públicas em Doenças Infecciosas e Parasitárias, Instituto René Rachou, Fundação Oswaldo Cruz, Avenue Augusto de lima, 1715, Barro Preto, Belo Horizonte, MG, 30190-009, Brazil.
Background: Open government data (OGD) in the health sector consolidates transparency, access to information, and collaboration between the government and different sectors of society. It is an essential instrument for health systems and researchers to generate initiatives, drive innovations, and qualify decision-making, whether in health emergencies or supporting the creation of more effective public policies. This review aimed to identify OGD initiatives in healthcare and their possible applications.
View Article and Find Full Text PDFBMC Health Serv Res
January 2025
Department of Paediatrics, Maastricht University Medical Center, MosaKids Children's Hospital, Maastricht, the Netherlands.
Background: Chronic respiratory diseases are important causes of disability and mortality globally. Their incidence may be higher in remote locations where healthcare is limited and risk factors, such as smoking and indoor air pollution, are more prevalent. E-health could overcome some healthcare access obstacles in remote locations, but its utilisation has been limited.
View Article and Find Full Text PDFJAMA Netw Open
January 2025
Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
Importance: People with kidney failure have a high risk of death and poor quality of life. Mortality risk prediction models may help them decide which form of treatment they prefer.
Objective: To systematically review the quality of existing mortality prediction models for people with kidney failure and assess whether they can be applied in clinical practice.
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