Assessing Shared Decision-Making in Cystic Fibrosis Care Using collaboRATE: A Cross-Sectional Study of 159 Programs.
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ABSTRACT:
SUBMITTER: Homa K
PROVIDER: S-EPMC8381423 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Objective: Patients with cystic fibrosis (CF) undertake time-consuming programs of home therapies. Our objective was to develop a tool to help CF patients prioritize personal goals for some of these treatments. We describe the development and results of initial evaluation of this shared decision-making tool. Methods: Multicriteria decision-making method to develop a shared decision-making tool that integrates patient's values and perceptions of treatment impact on functionality/sense of well-being. Treatment efficacy data obtained through comprehensive review of English language literature and Cochrane reviews. Field study of 21 patients was performed to assess acceptability of the approach, understandability of the tool, and to determine whether there was sufficient patient-to-patient variability in treatment goals and patient preferences to make use of a personalized tool worthwhile. Results: Patients found the tool easy to understand and felt engaged as active participants in their care. The tool was responsive to variations in patient preferences. Priority scores were calculated (0-1.0 ± SD). Patients' most important treatment goals for improving lung health included improving breathing function (0.27 ± 0.11), improving functionality/sense of well-being (0.24 ± 0.13), preventing lung infection (0.21 ± 0.08), minimizing time to complete treatments (0.16 ± 0.12), and minimizing cost (0.11 ± 0.09). Conclusions: A shared decision-making tool that integrates patients' values and best evidence is feasible and could result in improved patient engagement in their own care.
| S-EPMC6136161 | biostudies-literature
Project description:PURPOSE OF REVIEW:Almost 15 years have now passed since bacterial community profiling techniques were first used to analyse respiratory samples from people with cystic fibrosis. Since then, many different analytical approaches have been used to try to better understand the contribution of the cystic fibrosis lung microbiota to disease, with varying degrees of success. We examine the extent to which cystic fibrosis respiratory microbiome research has been successful in informing clinical decision-making, and highlight areas that we believe have the potential to yield important insight. RECENT FINDINGS:Recent research on the cystic fibrosis lung microbiome can be broadly divided into efforts to better characterize microbiota composition, particularly relative to key clinical events, and attempts to understand the cystic fibrosis lung microbiology as an interactive microbial system. The latter, in particular, has led to the development of a number of models in which microbiome-mediated processes precipitate clinical events. SUMMARY:Growing technological sophistication is enabling increasingly detailed microbiological data to be generated from cystic fibrosis respiratory samples. However, translating these data into clinically useful measures that accurately predict outcomes and guide treatments remains a formidable challenge. The development of systems biology approaches that enable the integration of complex microbiome and host-derived data provide an exciting opportunity to address this goal.
| S-EPMC5639941 | biostudies-other
Project description:BackgroundClinical guidelines recommend engaging patients in shared decision making for common orthopedic procedures; however, limited work has assessed what is occurring in practice. This study assessed the quality of shared decision making for elective hip and knee replacement and spine surgery at four network-affiliated hospitals.MethodsA cross-sectional sample of 875 adult patients undergoing total hip or knee joint replacement (TJR) for osteoarthritis or spine surgery for lumbar herniated disc or lumbar spinal stenosis was selected. Patients were mailed a survey including measures of Shared Decision Making (SDMP scale) and Informed, Patient-Centered (IPC) decisions. We examined decision-making across sites, surgeons, and conditions, and whether the decision-making measures were associated with better health outcomes. Analyses were adjusted for clustering of patients within surgeons.ResultsSix hundred forty-six surveys (74% response rate) were returned with sufficient responses for analysis. Patients who had TJR reported lower SDMP scores than patients who had spine surgery (2.2 vs. 2.8; p < 0.001). Patients who had TJR were more likely to make IPC decisions (OA = 70%, Spine = 41%; p < 0.001). SDMP and IPC scores varied widely across surgeons, but the site was not predictive of SDMP scores or IPC decisions (all p > 0.09). Higher SDMP scores and IPC decisions were associated with larger improvements in global health outcomes for patients who had TJR, but not patients who had spine surgery.ConclusionsMeasures of shared decision making and decision quality varied among patients undergoing common elective orthopedic procedures. Routine measurement of shared decision making provides insight into areas of strength across these different orthopedic conditions as well as areas in need of improvement.
| S-EPMC8605511 | biostudies-literature
Project description:BackgroundWe assessed inpatient perceived shared decision making (SDM) and tested the association of SDM with inpatient satisfaction in public tertiary hospitals in Shanghai, China.MethodsA cross-sectional survey of 2585 inpatients in 47 public tertiary hospitals in Shanghai in July and August 2018 was conducted. We assessed overall SDM and 4 aspects of SDM and tested the factors influencing SDM and the association of SDM with patient satisfaction (patient satisfaction with physician services, medical expenses, outcomes and overall inpatient care), by adopting linear or two-level regression models.ResultsThe positive response rate (PRR) and high positive response rate (HPRR) to overall SDM among the inpatients of public tertiary hospitals in Shanghai were relatively high (95.30% and 87.86%, respectively), while the HPRR to "My physician informed me of different treatment alternatives" was relatively low (80.09%). In addition, the inpatients who underwent surgery during admission had higher HPRRs and adjusted HPRRs to overall SDM than those who did not undergo surgery. The study showed that the adjusted high satisfaction rates (HSRs) with physician services, medical expenses, outcomes and overall inpatient care among the inpatients with high level of overall SDM were higher (96.50%, 68.44%, 89.50% and 92.60%) than those among the inpatients without a high level of overall SDM (71.77%, 35.19%, 57.30% and 67.49%). The greatest differences in the adjusted HSRs between the inpatients with and without a high level of SDM were found in inpatient satisfaction with medical expenses and informed consent in SDM. Moreover, 46.22% of the variances in the HSRs with overall inpatient care across the hospitals were attributed to the hospital type (general hospitals vs. specialty hospitals).ConclusionsInpatient PRRs and HPRRs to SDM in public tertiary hospitals in Shanghai are relatively high overall but lower to information regarding alternatives. SDM can be affected by the SDM preference of both the patients and physicians and medical condition. Patient satisfaction can be improved through better SDM and should be committed at the hospital level.
| S-EPMC7831242 | biostudies-literature
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.
| S-EPMC7018920 | biostudies-literature
Project description:ObjectiveThe objective of this study is to determine the factors influencing pancreatic surgery patients' perceptions of the shared decision-making process (SDM).BackgroundDecision-making in pancreatic surgery is complicated by the risk of morbidity and mortality and risk of early recurrence of disease. Improvement in SDM has the potential to improve the receipt of goal- and value-concordant care.MethodsThis cross-sectional survey included patients who underwent pancreatic surgery. The following components were studied in relation to SDM: modified satisfaction with decision scale (SWD), modified decisional regret scale (DRS), quality of physician and patient interaction, and the impact of quality of life (FACT-Hep). Correlations were computed using Pearson's correlation score and a regression model.ResultsThe survey completion rate was 72.2% (of 40/55) and the majority (72.5%) of patients underwent pancreaticoduodenectomy. There were significant positive relationships between the SDM measure and (DRS, SWD; r = 0.70, P < 0.001) and responses to questions regarding how well the patient's actual recovery matched their expectations before treatment (r = 0.62, P < 0.001). The quality of the physician-patient relationship correlated with how well recovery matched expectations (r = 0.53, P = 0.002). SDM measure scores were significant predictors of the decision evaluation measure (R2(adj) = 0.48, P < 0.001), FACT-Hep (R2(adj) = 0.15, P < 0.001), and recovery expectations measure (R2(adj) = 0.37, P < 0.001).ConclusionsImproved SDM in pancreatic surgery is associated with more realistic recovery expectations, decreased decisional regret, and improved quality of life.
| S-EPMC10431427 | biostudies-literature
Project description:Potentially inappropriate medications are associated with polypharmacy and polypathology. Some interventions such as pharmacotherapy reviews have been designed to reduce the prescribing of inappropriate medications. The objective of this study is to evaluate how effective a decision-making support tool is for determining medication appropriateness in patients with one or more chronic diseases (hypertension, dyslipidaemia, and/or diabetes) and polypharmacy in the primary care setting. For this, a quasi-experimental study (randomised, controlled and multicentre) has been developed. The study compares an intervention group, which assesses medication appropriateness by applying a decision support tool, with a control group that follows the usual clinical practice. The intervention included a decision support tool in paper format, where participants were informed about polypharmacy, inappropriate medications, associated problems and available alternatives, as well as shared decision-making. This is an informative guide aimed at helping patients with decision-making by providing them with information about the secondary risks associated with inappropriate medications in their treatment, according to the Beers and START/STOPP criteria. The outcome measure was the proportion of medication appropriateness. The proportion of patients who confirmed medication appropriateness after six months of follow-up is greater in the intervention group (32.5%) than in the control group (27.9%) p = 0.008. The probability of medication appropriateness, which was calculated by the proportion of drugs withdrawn or replaced according to the STOPP/Beers criteria and those initiated according to the START criteria, was 2.8 times higher in the intervention group than in the control group (OR = 2.8; 95% CI 1.3-6.1) p = 0.008. In patients with good adherence to the treatment, the percentage of appropriateness was 62.1% in the shared decision-making group versus 37.9% in the control group (p = 0.005). The use of a decision-making support tool in patients with potentially inappropriate medications increases the percentage of medication appropriateness when compared to the usual clinical practice.
| S-EPMC6616406 | biostudies-literature
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.
| S-EPMC7676870 | biostudies-literature
Project description:Policymakers and researchers are strongly encouraging clinicians to support patient autonomy through shared decision-making (SDM). In setting policies for clinical care, decision-makers need to understand that current models of SDM have tended to focus on major decisions (e.g., surgeries and chemotherapy) and focused less on everyday primary care decisions. Most decisions in primary care are substantive everyday decisions: intermediate-stakes decisions that occur dozens of times every day, yet are non-trivial for patients, such as whether routine mammography should start at age 40, 45, or 50. Expectations that busy clinicians use current models of SDM (here referred to as "detailed" SDM) for these decisions can feel overwhelming to clinicians. Evidence indicates that detailed SDM is simply not realistic for most of these decisions and without a feasible alternative, clinicians usually default to a decision-making approach with little to no personalization. We propose, for discussion and refinement, a compromise approach to personalizing these decisions (everyday SDM). Everyday SDM is based on a feasible process for supporting patient autonomy that also allows clinicians to continue being respectful health advocates for their patients. We propose that alternatives to detailed SDM are needed to make progress toward more patient-centered care.
| S-EPMC7572954 | biostudies-literature
Project description: Not available
| S-EPMC6485676 | biostudies-literature