Assessing patient information needs for new antidiabetic medications to inform shared decision‐making: A best–worst scaling experiment in China.
Background: Shared decision‐making (SDM) is a patient‐centred approach to improve the quality of care. An essential requirement for the SDM process is to be fully aware of patient information needs. Objectives: Our study aimed to assess patient information needs for new antidiabetic medications usin...
| Publicado en: | Health Expectations Vol. 27; no. 3; pp. 1 - 11 |
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| Autores principales: | , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Jun2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=178131445&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 178131445 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13696513 EVY jtl: Health Expectations issn: 13696513 maglogo: Y pubinfo: dt: Jun2024 vid: 27 iid: 3 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 178131445 178131445 178131445 10.1111/hex.14059 178131445 ppf: 1 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P tig: atl: Assessing patient information needs for new antidiabetic medications to inform shared decision‐making: A best–worst scaling experiment in China. aug: au: Xie, Tongling Meng, Jingyi Feng, Zhe Gao, Yue Chen, Tian Chen, Yalan Geng, Jinsong affil: Center for Evidence‐Based Medicine, Nantong University Medical School, Nantong, China sug: subj: Information Needs Evaluation Patient Education Antibiotics Therapeutic Use Decision Making, Shared Human China Surveys Diabetes Mellitus, Type 2 Questionnaires Regression Data Analysis Software Male Female Middle Age Aged Funding Source Middle Aged: 45-64 years Aged: 65+ years Male Female ab: Background: Shared decision‐making (SDM) is a patient‐centred approach to improve the quality of care. An essential requirement for the SDM process is to be fully aware of patient information needs. Objectives: Our study aimed to assess patient information needs for new antidiabetic medications using the best–worst scaling (BWS) experiment. Methods: BWS tasks were developed according to a literature review and the focus group discussion. We used a balanced incomplete block design and blocking techniques to generate choice sets. The final BWS contains 11 attributes, with 6‐choice scenarios in each block. The one‐to‐one, face‐to‐face BWS survey was conducted among type 2 diabetic patients in Jiangsu Province. Results were analyzed using count‐based analysis and modelling approaches. We also conducted a subgroup analysis to observe preference heterogeneity. Results: Data from 539 patients were available for analysis. The most desired information domain was the comparative effectiveness of new antidiabetic medications. It consists of the incidence of macrovascular complications, the length of extended life years, changes in health‐related quality of life, the incidence of microvascular complications, and the control of glycated haemoglobin. Of all the attributes, the incidence of macrovascular complications was the primary concern. Patients' glycemic control and whether they had diabetes complications exerted a significant influence on their information needs. Conclusions: Information on health benefits is of critical significance for diabetic patients. Patients have different information needs as their disease progresses. Personalized patient decision aids that integrate patient information needs and provide evidence of new antidiabetic medications are worthy of being established. Patient or Public Contribution: Before data collection, a pilot survey was carried out among diabetic patients to provide feedback on the acceptability and intelligibility of the attributes. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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