Dataset Information

Supporting shared decision-making and people's understanding of medicines: An exploration of the acceptability and comprehensibility of patient information.

ABSTRACT: Background:Patient information may assist in promoting shared decision-making, however it is imperative that the information presented is comprehensible and acceptable to the target audience. Objective:This study sought to explore the acceptability and comprehensibility of the ' Medicines in Scotland: What's the right treatment for you?' factsheet to the general public. Methods:Qualitative semi-structured telephone interviews were conducted with members of the public. An interview schedule was developed to explore the acceptability and comprehensibility of the factsheet. Participants were recruited by a researcher who distributed information packs to attendees (n=70) of four community pharmacies. Interviews, (12-24 minutes duration), were audio recorded, transcribed verbatim and analysed using a framework approach. Results:Nineteen participants returned a consent form (27.1%), twelve were interviewed. Six themes were identified: formatting of the factsheet and interpretation; prior health knowledge and the factsheet; information contained in the factsheet; impact of the factsheet on behaviour; uses for the factsheet; and revisions to the factsheet. Conclusions:The factsheet was generally perceived as helpful and comprehensive. It was highlighted that reading the leaflet may generate new knowledge and may have a positive impact on behaviour.

SUBMITTER: Smith KG

PROVIDER: S-EPMC5742002 | biostudies-literature | 2017 Oct-Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Supporting shared decision-making and people's understanding of medicines: An exploration of the acceptability and comprehensibility of patient information.

Smith Katie Gibson KG Booth Jill L JL Stewart Derek D Pfleger Sharon S Mciver Laura L Maclure Kathrine K

Pharmacy practice 20171001 4

<h4>Background</h4>Patient information may assist in promoting shared decision-making, however it is imperative that the information presented is comprehensible and acceptable to the target audience.<h4>Objective</h4>This study sought to explore the acceptability and comprehensibility of the ' Medicines in Scotland: What's the right treatment for you?' factsheet to the general public.<h4>Methods</h4>Qualitative semi-structured telephone interviews were conducted with members of the public. An in ...[more]

PMID: 29317925

Similar Datasets

Project description:This article describes the process undertaken to identify and validate behavioral and normative beliefs and behavioral intent based on the Theory of Reasoned Action (TRA) and applied to men between the ages of 45 and 70 in the context of their participation in shared decision-making (SDM) in medically uncertain situations. This article also discusses the preliminary results of the aforementioned processes and explores potential future uses of this information that may facilitate greater understanding, efficiency and effectiveness of clinician-patient consultations.Twenty-five male subjects from the Philadelphia community participated in this study. Individual semi-structure patient interviews were conducted until data saturation was reached. Based on their review of the patient interview transcripts, researchers conducted a qualitative content analysis to identify prevalent themes and, subsequently, create a category framework. Qualitative indicators were used to evaluate respondents' experiences, beliefs, and behavioral intent relative to participation in shared decision-making during medical uncertainty.Based on the themes uncovered through the content analysis, a category framework was developed to facilitate understanding and increase the accuracy of predictions related to an individual's behavioral intent to participate in shared decision-making in medical uncertainty. The emerged themes included past experience with medical uncertainty, individual personality, and the relationship between the patient and his physician. The resulting three main framework categories include 1) an individual's Foundation for the concept of medical uncertainty, 2) how the individual Copes with medical uncertainty, and 3) the individual's Behavioral Intent to seek information and participate in shared decision-making during times of medically uncertain situations.The theme of Coping (with uncertainty) emerged as a particularly critical behavior/characteristic amongst the subjects. By understanding a subject's disposition with regard to coping, researchers were better able to make connections between a subject's prior experiences, their knowledge seeking activities, and their intent to participate in SDM. Despite having information and social support, the subjects still had to cope with the idea of uncertainty before determining how to proceed with regard to shared decision-making. In addition, the coping category reinforced the importance of information seeking behaviors and preferences for shared decision-making.This study applies and extends the field of behavioral and health informatics to assist medical practice and decision-making in situations of medical uncertainty. More specifically, this study led to the development of a category framework that facilitates the identification of an individual's needs and motivational factors with regard to their intent to participate in shared decision-making in situations of medical uncertainty.

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:INTRODUCTION:Surgical treatments are being offered to more patients than ever before, and increasingly to high-risk patients (typically multimorbid and over 75). Shared decision making is seen as essential practice. However, little is currently known about what 'good' shared decision making involves nor how it applies in the context of surgery for high-risk patients. This new study aims to identify how high-risk patients, their families and clinical teams negotiate decision making for major surgery. METHODS AND ANALYSIS:Focusing on major joint replacement, colorectal and cardiac surgery, we use qualitative methods to explore how patients, their families and clinicians negotiate decision making (including interactional, communicative and informational aspects and the extent to which these are perceived as shared) and reflect back on the decisions they made. Phase 1 involves video recording 15 decision making encounters about major surgery between patients, their carers/families and clinicians; followed by up to 90 interviews (with the same patient, carer and clinician participants) immediately after a decision has been made and again 3-6 months later. Phase 2 involves focus groups with a wider group of (up to 90) patients and (up to 30) clinicians to test out emerging findings and inform development of shared decision making scenarios (3-5 summary descriptions of how decisions are made). ETHICS AND DISSEMINATION:The study forms the first part in a 6-year programme of research, Optimising Shared decision-makIng for high-RIsk major Surgery (OSIRIS). Ethical challenges around involving patients at a challenging time in their lives will be overseen by the programme steering committee, which includes strong patient representation and a lay chair. In addition to academic outputs, we will produce a typology of decision making scenarios for major surgery to feed back to patients, professionals and service providers and inform subsequent work in the OSIRIS programme.

Project description:BackgroundHealth care systems are increasingly moving towards more integrated approaches. Shared decision making (SDM) is central to these models but may be complicated by the need to negotiate and communicate decisions between multiple providers, as well as patients and their family carers; particularly for older people with complex needs. The aim of this review was to provide a context relevant understanding of how interventions to facilitate SDM might work for older people with multiple health and care needs, and how they might be applied in integrated care models.MethodsIterative, stakeholder driven, realist synthesis following RAMESES publication standards. It involved: 1) scoping literature and stakeholder interviews (n = 13) to develop initial programme theory/ies, 2) systematic searches for evidence to test and develop the theories, and 3) validation of programme theory/ies with stakeholders (n = 11). We searched PubMed, The Cochrane Library, Scopus, Google, Google Scholar, and undertook lateral searches. All types of evidence were included.ResultsWe included 88 papers; 29 focused on older people or people with complex needs. We identified four context-mechanism-outcome configurations that together provide an account of what needs to be in place for SDM to work for older people with complex needs. This includes: understanding and assessing patient and carer values and capacity to access and use care, organising systems to support and prioritise SDM, supporting and preparing patients and family carers to engage in SDM and a person-centred culture of which SDM is a part. Programmes likely to be successful in promoting SDM are those that allow older people to feel that they are respected and understood, and that engender confidence to engage in SDM.ConclusionsTo embed SDM in practice requires a radical shift from a biomedical focus to a more person-centred ethos. Service providers will need support to change their professional behaviour and to better organise and deliver services. Face to face interactions, permission and space to discuss options, and continuity of patient-professional relationships are key in supporting older people with complex needs to engage in SDM. Future research needs to focus on inter-professional approaches to SDM and how families and carers are involved.

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.

Dataset Information

Supporting shared decision-making and people's understanding of medicines: An exploration of the acceptability and comprehensibility of patient information.

Publications

Supporting shared decision-making and people's understanding of medicines: An exploration of the acceptability and comprehensibility of patient information.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure