scholarly journals Improving Chinese primary care providers’ recruitment and retention: a discrete choice experiment

2013 ◽  
Vol 30 (1) ◽  
pp. 68-77 ◽  
Author(s):  
Kuimeng Song ◽  
Anthony Scott ◽  
Peter Sivey ◽  
Qingyue Meng
Keyword(s):  
Primary Care ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Primary Care Providers ◽  
Care Providers ◽  
Recruitment And Retention

scholarly journals Eliciting Preferences of Providers in Primary Care Settings for Post Hospital Discharge Patient Follow-Up

2021 ◽  
Vol 18 (16) ◽  
pp. 8317
Author(s):  
Xin Wang ◽  
Kuimeng Song ◽  
Lijin Chen ◽  
Yixiang Huang ◽  
Stephen Birch
Keyword(s):  
Primary Care ◽  
Hospital Discharge ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Primary Care Providers ◽  
Care Providers ◽  
Post Discharge ◽  
Primary Care Settings ◽  
Follow Up Care

Background: Post-hospital discharge follow-up has been a principal intervention in addressing gaps in care pathways. However, evidence about the willingness of primary care providers to deliver post-discharge follow-up care is lacking. This study aims to assess primary care providers’ preferences for delivering post-discharge follow-up care for patients with chronic diseases. Methods: An online questionnaire survey of 623 primary care providers who work in a hospital group of southeast China. Face-to-face interviews with 16 of the participants. A discrete choice experiment was developed to elicit preferences of primary care providers for post-hospital discharge patient follow-up based on six attributes: team composition, workload, visit pattern, adherence of patients, incentive mechanism, and payment. A conditional logit model was used to estimate preferences, willingness-to-pay was modelled, a covariate-adjusted analysis was conducted to identify characteristics related to preferences, 16 interviews were conducted to explore reasons for participants’ choices. Results: 623 participants completed the discrete choice experiment (response rate 86.4%, aged 33 years on average, 69.5% female). Composition of the follow-up team and adherence of patients were the attributes of greatest relative importance with workload and incentives being less important. Participants were indifferent to follow-up provided by home visit or as an outpatient visit. Conclusion: Primary care providers placed the most importance on the multidisciplinary composition of the follow-up team. The preference heterogeneity observed among primary care providers suggests personalized management is important in the multidisciplinary teams, especially for those providers with relatively low educational attainment and less work experience. Future research and policies should work towards innovations to improve patients’ engagement in primary care settings.

Provider preferences for attributes of artificial intelligence in breast cancer screening: A discrete choice experiment.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e14118-e14118
Author(s):  
Nathaniel Hendrix ◽  
A. Brett Hauber ◽  
Christoph I. Lee ◽  
Aasthaa Bansal ◽  
David Leroy Veenstra
Keyword(s):  
Breast Cancer ◽  
Artificial Intelligence ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Qualitative Interviews ◽  
Primary Care Providers ◽  
Care Providers

e14118 Background: One of the emerging medical applications of artificial intelligence (AI) is the interpretation of mammograms for breast cancer screening. It is uncertain what attributes would result in acceptance of AI for breast cancer screening (AI BCS) among ordering clinicians. Methods: We performed qualitative interviews to identify the most important attributes of AI BCS for ordering clinicians. We then invited US-based primary care providers (PCPs) to participate in a discrete choice experiment (DCE). The experiment featured 15 choices between radiologist alone and two AI BCS alternatives where respondents traded better metrics on some attributes for worse metrics on others. Responses were analyzed using a mixed logit model adjusting for preference heterogeneity to determine the probability of recommending AI BCS. Results: In qualitative interviews, the six most important attributes to PCPs were AI sensitivity, specificity, radiologist involvement, understandability of AI decision-making, supporting evidence, and diversity of training data. Forty PCPs completed the DCE. Sensitivity was the most important attribute: a 4 percentage point improvement in sensitivity over the average radiologist increased the probability of recommending AI by 0.41 (95% confidence interval (CI), 0.38-0.42). Specificity was approximately half as important. Respondents were indifferent to whether radiologists confirmed all or only screens likely to be abnormal. However, no radiologist involvement reduced the probability of recommendation by 0.31 (95% CI, 0.29-0.31). An AI developed using data from diverse populations increased the probability of recommendation by 0.38 (95% CI, 0.36-0.39). Lastly, an AI that is transparent in the rationale for its decisions increased the probability of recommendation by 0.41 (95% CI, 0.39-0.41). Conclusions: PCPs prefer AI BCS that improves sensitivity versus specificity, and involves radiologists in the confirmation of abnormal screens. Improving sensitivity alone, however, will likely not be sufficient to support widespread PCP acceptance – algorithms will need to be developed with diverse data and more transparent explanations of their decisions.

scholarly journals How Do Type 2 Diabetes Patients Value Urban Integrated Primary Care in China? Results of a Discrete Choice Experiment

2019 ◽  
Vol 17 (1) ◽  
pp. 117
Author(s):  
Xin Wang ◽  
Kuimeng Song ◽  
Paiyi Zhu ◽  
Pim Valentijn ◽  
Yixiang Huang ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Primary Care ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Integrated Primary Care ◽  
World Health ◽  
Care Providers ◽  
Diabetes Patients

Objectives: Fragmented healthcare in China cannot meet the needs of the growing number of type 2 diabetes patients. The World Health Organization proposed an integrated primary care approach to address the needs of patients with chronic conditions. This study aims to measure type 2 diabetes patients’ preferences for urban integrated primary care in China. Methods: A discrete choice experiment was designed to measure type 2 diabetes patient preferences for seven priority attributes of integrated care. A two-stage sampling survey of 307 type 2 diabetes mellitus (T2DM) patients in 16 community health stations was carried out. Interviews were conducted to explore the reasons underpinning the preferences. A logit regression model was used to estimate patients’ willingness to pay and to analyze the expected impact of potential policy changes. Results: Travel time to care providers and experience of care providers are the most valued attributes for respondents rather than out-of-pocket cost. Attention to personal situation, the attentiveness of care providers, and the friendliness and helpfulness of staff were all related to interpersonal communication between patients and health care providers. Accurate health information and multidisciplinary care were less important attributes. Conclusions: The study provides an insight into type 2 diabetes patients’ needs and preferences of integrated primary care. People-centered interventions, such as increasing coverage by family doctor and cultivating mutual continuous relationships appear to be key priorities of policy and practice in China.

Parent and Primary Care Provider Priorities for Wellness in Early Childhood: A Discrete Choice Experiment

2021 ◽  
Author(s):  
Stephanie L. Mayne ◽  
Chloe Hannan ◽  
Jennifer Faerber ◽  
Rupreet Anand ◽  
Ella Labrusciano-Carris ◽  
...  
Keyword(s):  
Primary Care ◽  
Early Childhood ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Care Provider ◽  
Primary Care Provider ◽  
Choice Experiment

scholarly journals Public preferences for primary care provision in Germany – a discrete choice experiment

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Kim-Sarah Krinke ◽  
Ulla Tangermann ◽  
Volker Eric Amelung ◽  
Christian Krauth
Keyword(s):  
Primary Care ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Care Provision ◽  
Public Preferences

scholarly journals Patients’ preferences for GP consultation for perceived cancer risk in primary care: a discrete choice experiment

2017 ◽  
Vol 67 (659) ◽  
pp. e388-e395 ◽  
Author(s):  
Katriina L Whitaker ◽  
Alex Ghanouni ◽  
Yin Zhou ◽  
Georgios Lyratzopoulos ◽  
Stephen Morris
Keyword(s):  
Primary Care ◽  
Cancer Risk ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Online Survey ◽  
Population Characteristics ◽  
Risk Level ◽  
Listening Skills ◽  
Potential Cancer

BackgroundContacting a doctor for advice when experiencing a potential cancer symptom is an important step in early diagnosis, but barriers to consultation are commonly reported. Understanding barriers to consulting in primary care within the cancer context provides opportunities to improve earlier diagnosis of cancerAimTo investigate patients’ GP consultation preferences when presented with a potential cancer symptom, and to describe whether these preferences are mediated by variable levels of cancer risk.Design and settingA UK-wide online survey of adults ≥50 years old, using quota sampling to reflect general population characteristics.MethodA discrete choice experiment examined participants’ preferences for primary care consultation for three cancer symptom scenarios: risk level not mentioned, risk designated as ‘low’, or risk designated as ‘high’. Scenarios based on length of consultation, time to getting an appointment, convenience, choice of GP, and GP listening skills were presented in a self-completed online questionnaire.ResultsA total of 9616 observations were obtained from 601 participants. Participants expressed preferences for doctors with better listening skills, the ability to see a GP of their choice, and shorter waiting times. These findings were the same across risk conditions and demographic groups. Participants were willing to wait an extra 3.5 weeks for an appointment with a doctor with good/very good listening skills (versus very poor listening skills) and an extra week for an appointment with a GP of their choice (versus any GP).ConclusionPatient decisions about help seeking seem to be particularly influenced by the anticipated listening skills of doctors. Improving doctors’ communication skills may in the longer term encourage people to seek prompt medical help when they experience a cancer symptom.

scholarly journals Personal health records in the Netherlands: potential user preferences quantified by a discrete choice experiment

2016 ◽  
Vol 24 (3) ◽  
pp. 529-536 ◽  
Author(s):  
Domino Determann ◽  
Mattijs S Lambooij ◽  
Dorte Gyrd-Hansen ◽  
Esther W de Bekker-Grob ◽  
Ewout W Steyerberg ◽  
...  
Keyword(s):  
Health Care ◽  
Data Storage ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Health Care Providers ◽  
Choice Experiment ◽  
Personal Health Records ◽  
Personal Health ◽  
Care Providers ◽  
Health Records

Objective: To identify groups of potential users based on their preferences for characteristics of personal health records (PHRs) and to estimate potential PHR uptake. Methods: We performed a discrete choice experiment, which consisted of 12 choice scenarios, each comprising 2 hypothetical PHR alternatives and an opt-out. The alternatives differed based on 5 characteristics. The survey was administered to Internet panel members of the Dutch Federation of Patients and Consumer Organizations. We used latent class models to analyze the data. Results: A total of 1,443 potential PHR users completed the discrete choice experiment. We identified 3 latent classes: “refusers” (class probability 43%), “eager adopters” (37%), and “reluctant adopters” (20%). The predicted uptake for the reluctant adopters ranged from 4% in the case of a PHR with the worst attribute levels to 68% in the best case. Those with 1 or more chronic diseases were significantly more likely to belong to the eager adopter class. The data storage provider was the most decisive aspect for the eager and reluctant adopters, while cost was most decisive for the refusers. Across all classes, health care providers and independent organizations were the most preferred data storage providers. Conclusion: We identified 3 groups, of which 1 group (more than one-third of potential PHR users) indicated great interest in a PHR irrespective of PHR characteristics. Policymakers who aim to expand the use of PHRs will be most successful when health care providers and health facilities or independent organizations store PHR data while refraining from including market parties.

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