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Shared decision making and antibiotic benefit-harm conversations: an observational study of consultations between general practitioners and patients with acute respiratory infections.

ABSTRACT: BACKGROUND:Little research has examined whether shared decision making (SDM) occurs in consultations for acute respiratory infections (ARIs), including what, and how, antibiotic benefits and harms are discussed. We aimed to analyse the extent and nature of SDM in consultations between GPs and patients with ARIs, and explore communication with and without the use of patient decision aids. METHODS:This was an observational study in Australian general practices, nested within a cluster randomised trial of decision aids (for acute otitis media [AOM], sore throat, acute bronchitis) designed for general practitioners (GPs) to use with patients, compared with usual care (no decision aids). Audio-recordings of consultations of a convenience sample of consenting patients seeing a GP for an ARI were independently analysed by two raters using the OPTION-12 (observing patient involvement in decision making) scale (maximum score of 100) and 5 items (about communicating evidence) from the Assessing Communication about Evidence and Patient Preferences (ACEPP) tool (maximum score of 5). Patients also self-completed a questionnaire post-consultation that contained items from CollaboRATE-5 (perceptions of involvement in the decision-making process), a decisional conflict scale, and a decision self-efficacy scale. Descriptive statistics were calculated for each measure. RESULTS:Thirty-six consultations, involving 13 GPs, were recorded (20 for bronchitis, 10 sore throat, 6 AOM). The mean (SD) total OPTION-12 score was 29.4 (12.5; range 4-54), with item 12 (need to review decision) the highest (mean?=?3) and item 10 (eliciting patients' preferred level of decision-making involvement) the lowest (mean?=?0.1). The mean (SD) total ACEPP score was 2 (1.6), with the item about discussing benefits scoring highest. In consultations where a decision aid was used (15, 42%), compared to the 21 usual care consultations, mean observer-assessed SDM scores (OPTION-12, ACEPP scores) were higher and antibiotic harms mentioned in all (compared to only 1) consultations. Patients generally reported high decision involvement and self-efficacy, and low decisional conflict. CONCLUSIONS:The extent of observer-assessed SDM between GPs and patients with ARIs was generally low. Balanced discussion of antibiotic benefits and harms occurred more often when decision aids were used.

SUBMITTER: Bakhit M

PROVIDER: S-EPMC6173855 | biostudies-other | 2018 Oct

REPOSITORIES: biostudies-other

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Shared decision making and antibiotic benefit-harm conversations: an observational study of consultations between general practitioners and patients with acute respiratory infections.

Bakhit Mina M Del Mar Chris C Gibson Elizabeth E Hoffmann Tammy T

BMC family practice 20181006 1

<h4>Background</h4>Little research has examined whether shared decision making (SDM) occurs in consultations for acute respiratory infections (ARIs), including what, and how, antibiotic benefits and harms are discussed. We aimed to analyse the extent and nature of SDM in consultations between GPs and patients with ARIs, and explore communication with and without the use of patient decision aids.<h4>Methods</h4>This was an observational study in Australian general practices, nested within a clust ...[more]

PMID: 30292242

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Project description:ObjectiveTo investigate the impact of cost conversations occurring with or without the use of encounter shared decision-making (SDM) tools in medication adherence.Patients and methodsUsing a coding scheme that included the occurrence and characteristics of cost conversation, we analyzed a randomly selected sample of 169 video recordings of clinical encounters. These videos were obtained during the conduct of practice-based randomized clinical trials comparing care with and without SDM tools for patients with diabetes, osteoporosis, and depression. Medication adherence was described in 2 ways: as a binary (yes/no) outcome, in which the patient met at least 80% adherence, or as a continuous variable, which was the percent of days that the patient adhered to their medication. The secondary analysis took place in 2018 from trials that ran between 2007 and 2015.ResultsMost patients were White (155, 93.4%), educated (104, 63.4% completed college), middle-aged (mean age, 58 years), female (104, 61.5%), and from diabetes (86, 50.9%), depression (43, 25.4%), and osteoporosis (40, 23.7%) trials. Cost conversations occurred in 119 clinical encounters (70%) and were more frequent in those encounters in which SDM tools were used (P=.03). Furthermore, 97 (57.4%) of the participants reported more than 80% medication adherence and 70.3±29.34 percentage of days with adherent medication of 70 days. In the multiple regression model, the only factor associated with adherence (binary or continuous) was the condition of the trial in which people participated. For the participants who had cost conversations, the use of an SDM tool, their sex, the nature of cost conversation (direct or indirect), the nature of cost concerns (treatment or patient issue), and the clinician-offered strategies (yes or no) were not associated with adherence.ConclusionIn this videographic analysis of SDM practice-based clinical trials, cost conversations were not associated with the general measures of medication adherence. Future studies should assess whether a tailored cost conversation intervention would impact the cost-related nonadherence among patients.

Project description:BackgroundShared decision-making (SDM) is widely recommended and required by the Centers for Medicare and Medicaid for patients considering lung cancer screening (LCS).ObjectiveWe examined clinicians' communication practices and perceived barriers of SDM for LCS at three medical centers with established screening programs.DesignMulticenter qualitative study of clinicians participating in LCS.ApproachWe performed semi-structured interviews, which were transcribed and analyzed using directed content analysis, guided by a theoretical model of patient-clinician communication.ParticipantsWe interviewed 24 clinicians including LCS coordinators (2), pulmonologists (3), and primary care providers (17), 4 of whom worked for the LCS program, a thoracic surgeon, and a radiologist.ResultsAll clinicians agreed with the goal of SDM, to ensure the screening decision was congruent with the patient's values. The depth and type of information presented by each clinician role varied considerably. LCS coordinators presented detailed information including numeric estimates of benefit and harm. Most PCPs explained the process more generally, focusing on logistics and the high rate of nodule detection. No clinician explicitly elicited values or communication preferences. Many PCPs tailored the conversation based on their implicit understanding of patients' values and preferences, gained from past experiences. PCPs reported that time, lack of detailed personal knowledge of LCS, and patient preferences were barriers to SDM. Many clinicians perceived that a significant proportion of patients were not interested in specific percentages and preferred to receive a clinician recommendation.ConclusionsOur results suggest that clinicians support the goal of SDM for LCS decisions but PCPs may not perform some of its elements. The lack of completion of some elements, such as PCPs' lack of in-depth information exchange, may reflect perceived patient preferences for communication. As LCS is implemented, further research is needed to support a personalized, patient-centered approach to produce better outcomes.

Project description:Background. Accurate diagnosis of patients' preferences is central to shared decision making. Missing from clinical practice is an approach that links pretreatment preferences and patient-reported outcomes. Objective. We propose a Bayesian collaborative filtering (CF) algorithm that combines pretreatment preferences and patient-reported outcomes to provide treatment recommendations. Design. We present the methodological details of a Bayesian CF algorithm designed to accomplish 3 tasks: 1) eliciting patient preferences using conjoint analysis surveys, 2) clustering patients into preference phenotypes, and 3) making treatment recommendations based on the posttreatment satisfaction of like-minded patients. We conduct a series of simulation studies to test the algorithm and to compare it to a 2-stage approach. Results. The Bayesian CF algorithm and 2-stage approaches performed similarly when there was extensive overlap between preference phenotypes. When the treatment was moderately associated with satisfaction, both methods made accurate recommendations. The kappa estimates measuring agreement between the true and predicted recommendations were 0.70 (95% confidence interval = 0.052-0.88) and 0.73 (0.56-0.90) under the Bayesian CF and 2-stage approaches, respectively. The 2-stage approach failed to converge in settings in which clusters were well separated, whereas the Bayesian CF algorithm produced acceptable results, with kappas of 0.73 (0.56-0.90) and 0.83 (0.69-0.97) for scenarios with moderate and large treatment effects, respectively. Limitations. Our approach assumes that the patient population is composed of distinct preference phenotypes, there is association between treatment and outcomes, and treatment effects vary across phenotypes. Findings are also limited to simulated data. Conclusion. The Bayesian CF algorithm is feasible, provides accurate cluster treatment recommendations, and outperforms 2-stage estimation when clusters are well separated. As such, the approach serves as a roadmap for incorporating predictive analytics into shared decision making.

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Shared decision making and antibiotic benefit-harm conversations: an observational study of consultations between general practitioners and patients with acute respiratory infections.

Publications

Shared decision making and antibiotic benefit-harm conversations: an observational study of consultations between general practitioners and patients with acute respiratory infections.

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