Dataset Information

Physician styles of patient management as a potential source of disparities: cluster analysis from a factorial experiment.

ABSTRACT: To identify styles of physician decision making (as opposed to singular clinical actions) and to analyze their association with variations in the management of a vignette presentation of coronary heart disease (CHD).Primary data were collected from primary care physicians in North and South Carolina.In a balanced factorial experimental design, primary care physicians viewed one of 16 (2(4)) video vignette presentations of CHD and provided detailed information about how they would manage the case.256 MD primary care physicians were interviewed face-to-face in North and South Carolina.We identify three clusters depicting unique styles of CHD management that are robust to controls for physician (gender and level of experience) and patient characteristics (age, gender, socioeconomic status, and race) as well as key organizational features of physicians' work settings. Physicians in Cluster 1 "Cardiac" (N = 92) were more likely to focus on cardiac issues compared with their counterparts; physicians in Cluster 2 "Talkers" (N = 93) were more likely to give advice and take additional medical history; whereas physicians in Cluster 3 "Minimalists" (N = 71) were less likely than their counterparts to take action on any of the types of management behavior.Variations in styles of decision making, which encompass multiple outcome variables and extend beyond individual-level demographic predictors, may add to our understanding of disparities in health quality and outcomes.

SUBMITTER: Lutfey KE

PROVIDER: S-EPMC3681246 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Physician styles of patient management as a potential source of disparities: cluster analysis from a factorial experiment.

Lutfey Karen E KE Gerstenberger Eric E McKinlay John B JB

Health services research 20121022 3

<h4>Objective</h4>To identify styles of physician decision making (as opposed to singular clinical actions) and to analyze their association with variations in the management of a vignette presentation of coronary heart disease (CHD).<h4>Data source</h4>Primary data were collected from primary care physicians in North and South Carolina.<h4>Study design</h4>In a balanced factorial experimental design, primary care physicians viewed one of 16 (2(4)) video vignette presentations of CHD and provide ...[more]

PMID: 23088446

Similar Datasets

Project description:BackgroundBecause of internet searches, advice from friends, and pharmaceutical advertising, especially direct-to-consumer advertising, patients are increasingly activated to request medications during a physician encounter.ObjectivesTo estimate the effect of patient requests for medications on physician-prescribing behavior, unconfounded by patient, physician, and practice-setting factors.Research designTwo experiments were conducted among 192 primary care physicians, each using different video-based scenarios: an undiagnosed "patient" with symptoms strongly suggesting sciatica, and a "patient" with already diagnosed chronic knee osteoarthritis. Half of patients with sciatica symptoms requested oxycodone, whereas the other half requested something to help with pain. Similarly, half of knee osteoarthritis patients specifically requested celebrex and half requested something to help with pain.SubjectsTo increase generalizability and ensure sufficient numbers were available, we recruited 192 primary care physicians from 6 US states.MeasuresThe primary outcome was whether physicians would accede to a patient's request for a medication. Alternative pain medications prescribed were secondary outcomes.Results19.8% of sciatica patients requesting oxycodone would receive a prescription for oxycodone, compared with 1% of those making no specific request (P = 0.001). Fifty-three percent of knee osteoarthritis patients requesting celebrex would receive it, compared with 24% of patients making no request (P = 0.001). Patients requesting oxycodone were more likely to receive a strong narcotic (P = 0.001) and less likely to receive a weak narcotic (P = 0.01). Patients requesting celebrex were much less likely to receive a nonselective nonsteroidal anti-inflammatory drugs (P = 0.008). No patient attributes, physician, or organizational factors influenced a physician's willingness to accede to a patient's medication request.ConclusionsIn both scenarios, activated patient requests for a medication substantially affected physician-prescribing decisions, despite the drawbacks of the requested medications.

Project description:BackgroundNoncommunicable diseases (NCDs) constitute a burden on public health. These are best controlled through self-management practices, such as self-information. Fostering patients' access to health-related information through efficient and accessible channels, such as commercial voice assistants (VAs), may support the patients' ability to make health-related decisions and manage their chronic conditions.ObjectiveThis study aims to evaluate the reliability of the most common VAs (ie, Amazon Alexa, Apple Siri, and Google Assistant) in responding to questions about management of the main NCD.MethodsWe generated health-related questions based on frequently asked questions from health organization, government, medical nonprofit, and other recognized health-related websites about conditions associated with Alzheimer's disease (AD), lung cancer (LCA), chronic obstructive pulmonary disease, diabetes mellitus (DM), cardiovascular disease, chronic kidney disease (CKD), and cerebrovascular accident (CVA). We then validated them with practicing medical specialists, selecting the 10 most frequent ones. Given the low average frequency of the AD-related questions, we excluded such questions. This resulted in a pool of 60 questions. We submitted the selected questions to VAs in a 3×3×6 fractional factorial design experiment with 3 developers (ie, Amazon, Apple, and Google), 3 modalities (ie, voice only, voice and display, display only), and 6 diseases. We assessed the rate of error-free voice responses and classified the web sources based on previous research (ie, expert, commercial, crowdsourced, or not stated).ResultsGoogle showed the highest total response rate, followed by Amazon and Apple. Moreover, although Amazon and Apple showed a comparable response rate in both voice-and-display and voice-only modalities, Google showed a slightly higher response rate in voice only. The same pattern was observed for the rate of expert sources. When considering the response and expert source rate across diseases, we observed that although Google remained comparable, with a slight advantage for LCA and CKD, both Amazon and Apple showed the highest response rate for LCA. However, both Google and Apple showed most often expert sources for CVA, while Amazon did so for DM.ConclusionsGoogle showed the highest response rate and the highest rate of expert sources, leading to the conclusion that Google Assistant would be the most reliable tool in responding to questions about NCD management. However, the rate of expert sources differed across diseases. We urge health organizations to collaborate with Google, Amazon, and Apple to allow their VAs to consistently provide reliable answers to health-related questions on NCD management across the different diseases.

Project description:BackgroundThe emergence of proprotein convertase subtilisin/kexin type 9 inhibitors offered dyslipidemia patients an alternative to statins for lipid-lowering treatment. Understanding patient and physician preferences for lipid-lowering drugs may promote shared decision-making and improve treatment outcomes.MethodsThis study utilized an online discrete choice experiment (DCE) to assess the relative importance (RI) of six attributes related to lipid-lowering drugs, including frequency of administration, mode of administration, reduction of low-density lipoprotein cholesterol (LDL-C) level, risk of myopathy, risk of liver damage, and out-of-pocket monthly cost. Respondents were recruited from dyslipidemia patients and cardiovascular physicians in China. A mixed logit model and latent class analysis were employed to estimate the preference coefficient, marginal willingness to pay (mWTP), and RI of attributes. Ethical approval has been obtained for this study.ResultsA total of 708 patients and 507 physicians participated in the survey. Patients prioritized the 'risk of liver damage' (RI = 23.6%) with 'mode of administration' (RI = 19.2%) and 'frequency of administration' (RI = 18.8%) following closely. Contrarily, physicians prioritized the 'reduction of LDL-C level' (RI = 33.5%), followed by 'risk of liver damage' (RI = 26.0%) and 'risk of myopathy' (RI = 16.1%). Patients placed a higher value on 'frequency of administration' (p < .001) and 'mode of administration' (p < .001) compared to physicians, while physicians valued 'reduction of LDL-C level' (p < .001) and 'risk of myopathy' (p = .012) more than patients. Physicians exhibited higher mWTP than patients for all attributes except frequency and mode of administration. The LCA revealed three distinct patient classes: focus on oral administration, focus on hepatic safety and frequency and focus on hepatic safety and cost. Likewise, three physician classes were identified: frequency-insensitive, efficacy-focused and safety-focused.ConclusionsThe preferences for lipid-lowering drug therapy differed between patients and physicians in China. Physicians should take into account patients' preferences and provide personalized treatment when they formulate lipid-lowering treatment plans.Patient or public contributionPatients participated in the questionnaire design process. They engaged in a focus group discussion to determine attributes and levels and also participated in a pilot survey to assess the comprehensibility of the questionnaires. Additionally, patients were involved in the DCE survey to express their preferences. The findings of patient preference for lipid-lowering drug therapy will promote shared decision-making and optimize the treatment regimen.

Dataset Information

Physician styles of patient management as a potential source of disparities: cluster analysis from a factorial experiment.

Publications

Physician styles of patient management as a potential source of disparities: cluster analysis from a factorial experiment.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets