Clinical Decision Support with or without Shared Decision Making to Improve Preventive Cancer Care: A Cluster-Randomized Trial

Impact of personalized risk scores on shared decision making in left ventricular assist device implantation: Findings from a qualitative study

OBJECTIVE

To assess stakeholders' perspectives on integrating personalized risk scores (PRS) into left ventricular assist device (LVAD) implantation decisions and how these perspectives might impact shared decision making (SDM).

METHODS

We conducted 40 in-depth interviews with physicians, nurse coordinators, patients, and caregivers about integrating PRS into LVAD implantation decisions. A codebook was developed to identify thematic patterns, and quotations were consolidated for analysis. We used Thematic Content Analysis in MAXQDA software to identify themes by abstracting relevant quotes.

RESULTS

Clinicians had varying preferences regarding PRS integration into LVAD decision making, while patients and caregivers preferred real-time discussions about PRS with their physicians. Physicians voiced concerns about time constraints and suggested delegating PRS discussions to advanced practice providers or nurse coordinators.

CONCLUSIONS

Integrating PRS information into LVAD decision aids presents both opportunities and challenges for SDM. Given variable preferences among clinicians and patients, clinicians should elicit patients' desired role in the decision-making process. Addressing time constraints and ensuring patient-centered care will be crucial for optimizing SDM. Practice implications Clinicians should elicit patient preferences for PRS information disclosure and address challenges, such as time constraints and delegation of PRS discussions to other team members.

Analysis and mapping the research landscape on patient-centred care in the context of chronic disease management

RATIONALE

Patient-centred care has emerged as a transformative approach in managing chronic diseases, aiming to actively involve patients in their healthcare decisions.

AIMS AND OBJECTIVES

This study was conducted to analyse and map the research landscape on patient-centred care in the context of chronic disease management.

METHODS

This study used Scopus to retrieve the relevant articles. The analysis focused on the growth pattern, highly cited articles, randomised clinical trials, patients and providers perspectives, facilitators and barriers, frequent author keywords, emerging topics, and prolific countries and journals in the field.

RESULTS

In total, 926 research articles met the inclusion criteria. There was a notable increase in the number of publications over time. Cancer had the highest number of articles (n = 379, 40.9%), followed by diabetes mellitus, and mental health and psychiatric conditions. Studies on patient-centred care in diabetic patients received the highest number of citations. The results identified 52 randomised controlled trials that covered four major themes: patient-centred care for diabetes management, shared decision-making in mental health and primary care, shared decision-making in cancer care, and economic evaluation and cost-effectiveness. The study identified 51 studies that examined the impact of tools such as computer-based systems, decision aids, smartphone apps, and online tools to improve patient-centred outcomes. A map of author keywords showed that renal dialysis, HIV, and atrial fibrillation were the most recent topics in the field. Researchers from the United States contributed to more than half of the retrieved publications. The top active journals included "Patient Education and Counselling" and "Health Expectations".

CONCLUSION

This study provides valuable insights into the research landscape of patient-centred care within the context of chronic diseases. The current study provided a comprehensive overview of the research landscape on patient-centred care, which can empower patients by raising their awareness about clinical experiences and outcomes.

Shared decision-making for supporting women's decisions about breast cancer screening

BACKGROUND

In breast cancer screening programmes, women may have discussions with a healthcare provider to help them decide whether or not they wish to join the breast cancer screening programme. This process is called shared decision-making (SDM) and involves discussions and decisions based on the evidence and the person's values and preferences. SDM is becoming a recommended approach in clinical guidelines, extending beyond decision aids. However, the overall effect of SDM in women deciding to participate in breast cancer screening remains uncertain.

OBJECTIVES

To assess the effect of SDM on women's satisfaction, confidence, and knowledge when deciding whether to participate in breast cancer screening.

SEARCH METHODS

We searched the Cochrane Breast Cancer Group's Specialised Register, CENTRAL, MEDLINE, Embase, CINAHL, PsycINFO, ClinicalTrials.gov, and the World Health Organization International Clinical Trials Registry Platform on 8 August 2023. We also screened abstracts from two relevant conferences from 2020 to 2023.

SELECTION CRITERIA

We included parallel randomised controlled trials (RCTs) and cluster-RCTs assessing interventions targeting various components of SDM. The focus was on supporting women aged 40 to 75 at average or above-average risk of breast cancer in their decision to participate in breast cancer screening.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed studies for inclusion and conducted data extraction, risk of bias assessment, and GRADE assessment of the certainty of the evidence. Review outcomes included satisfaction with the decision-making process, confidence in the decision made, knowledge of all options, adherence to the chosen option, women's involvement in SDM, woman-clinician communication, and mental health.

MAIN RESULTS

We identified 19 studies with 64,215 randomised women, mostly with an average to moderate risk of breast cancer. Two studies covered all aspects of SDM; six examined shortened forms of SDM involving communication on risks and personal values; and 11 focused on enhanced communication of risk without other SDM aspects. SDM involving all components compared to control The two eligible studies did not assess satisfaction with the SDM process or confidence in the decision. Based on a single study, SDM showed uncertain effects on participant knowledge regarding the age to start screening (risk ratio (RR) 1.18, 95% confidence interval (CI) 0.61 to 2.28; 133 women; very low certainty evidence) and frequency of testing (RR 0.84, 95% CI 0.68 to 1.04; 133 women; very low certainty evidence). Other review outcomes were not measured. Abbreviated forms of SDM with clarification of values and preferences compared to control Of the six included studies, none evaluated satisfaction with the SDM process. These interventions may reduce conflict in the decision made, based on two measures, Decisional Conflict Scale scores (mean difference (MD) -1.60, 95% CI -4.21 to 0.87; conflict scale from 0 to 100; 4 studies; 1714 women; very low certainty evidence) and the proportion of women with residual conflict compared to control at one to three months' follow-up (rate of women with a conflicted decision, RR 0.75, 95% CI 0.56 to 0.99; 1 study; 1001 women, very low certainty evidence). Knowledge of all options was assessed through knowledge scores and informed choice. The effect of SDM may enhance knowledge (MDs ranged from 0.47 to 1.44 higher scores on a scale from 0 to 10; 5 studies; 2114 women; low certainty evidence) and may lead to higher rates of informed choice (RR 1.24, 95% CI 0.95 to 1.63; 4 studies; 2449 women; low certainty evidence) compared to control at one to three months' follow-up. These interventions may result in little to no difference in anxiety (MD 0.54, 95% -0.96 to 2.14; scale from 20 to 80; 2 studies; 749 women; low certainty evidence) and the number of women with worries about cancer compared to control at four to six weeks' follow-up (RR 0.88, 95% CI 0.73 to 1.06; 1 study, 639 women; low certainty evidence). Other review outcomes were not measured. Enhanced communication about risks without other SDM aspects compared to control Of 11 studies, three did not report relevant outcomes for this review, and none assessed satisfaction with the SDM process. Confidence in the decision made was measured by decisional conflict and anticipated regret of participating in screening or not. These interventions, without addressing values and preferences, may result in lower confidence in the decision compared to regular communication strategies at two weeks' follow-up (MD 2.89, 95% CI -2.35 to 8.14; Decisional Conflict Scale from 0 to 100; 2 studies; 1191 women; low certainty evidence). They may result in higher anticipated regret if participating in screening (MD 0.28, 95% CI 0.15 to 0.41) and lower anticipated regret if not participating in screening (MD -0.28, 95% CI -0.42 to -0.14). These interventions increase knowledge (MD 1.14, 95% CI 0.61 to 1.62; scale from 0 to 10; 4 studies; 2510 women; high certainty evidence), while it is unclear if there is a higher rate of informed choice compared to regular communication strategies at two to four weeks' follow-up (RR 1.27, 95% CI 0.83 to 1.92; 2 studies; 1805 women; low certainty evidence). These interventions result in little to no difference in anxiety (MD 0.33, 95% CI -1.55 to 0.99; scale from 20 to 80) and depression (MD 0.02, 95% CI -0.41 to 0.45; scale from 0 to 21; 2 studies; 1193 women; high certainty evidence) and lower cancer worry compared to control (MD -0.17, 95% CI -0.26 to -0.08; scale from 1 to 4; 1 study; 838 women; high certainty evidence). Other review outcomes were not measured.

AUTHORS' CONCLUSIONS

Studies using abbreviated forms of SDM and other forms of enhanced communications indicated improvements in knowledge and reduced decisional conflict. However, uncertainty remains about the effect of SDM on supporting women's decisions. Most studies did not evaluate outcomes considered important for this review topic, and those that did measured different concepts. High-quality randomised trials are needed to evaluate SDM in diverse cultural settings with a focus on outcomes such as women's satisfaction with choices aligned to their values.

Decision aids for people facing health treatment or screening decisions

BACKGROUND

Patient decision aids are interventions designed to support people making health decisions. At a minimum, patient decision aids make the decision explicit, provide evidence-based information about the options and associated benefits/harms, and help clarify personal values for features of options. This is an update of a Cochrane review that was first published in 2003 and last updated in 2017.

OBJECTIVES

To assess the effects of patient decision aids in adults considering treatment or screening decisions using an integrated knowledge translation approach.

SEARCH METHODS

We conducted the updated search for the period of 2015 (last search date) to March 2022 in CENTRAL, MEDLINE, Embase, PsycINFO, EBSCO, and grey literature. The cumulative search covers database origins to March 2022.

SELECTION CRITERIA

We included published randomized controlled trials comparing patient decision aids to usual care. Usual care was defined as general information, risk assessment, clinical practice guideline summaries for health consumers, placebo intervention (e.g. information on another topic), or no intervention.

DATA COLLECTION AND ANALYSIS

Two authors independently screened citations for inclusion, extracted intervention and outcome data, and assessed risk of bias using the Cochrane risk of bias tool. Primary outcomes, based on the International Patient Decision Aid Standards (IPDAS), were attributes related to the choice made (informed values-based choice congruence) and the decision-making process, such as knowledge, accurate risk perceptions, feeling informed, clear values, participation in decision-making, and adverse events. Secondary outcomes were choice, confidence in decision-making, adherence to the chosen option, preference-linked health outcomes, and impact on the healthcare system (e.g. consultation length). We pooled results using mean differences (MDs) and risk ratios (RRs) with 95% confidence intervals (CIs), applying a random-effects model. We conducted a subgroup analysis of 105 studies that were included in the previous review version compared to those published since that update (n = 104 studies). We used Grading of Recommendations Assessment, Development, and Evaluation (GRADE) to assess the certainty of the evidence.

MAIN RESULTS

This update added 104 new studies for a total of 209 studies involving 107,698 participants. The patient decision aids focused on 71 different decisions. The most common decisions were about cardiovascular treatments (n = 22 studies), cancer screening (n = 17 studies colorectal, 15 prostate, 12 breast), cancer treatments (e.g. 15 breast, 11 prostate), mental health treatments (n = 10 studies), and joint replacement surgery (n = 9 studies). When assessing risk of bias in the included studies, we rated two items as mostly unclear (selective reporting: 100 studies; blinding of participants/personnel: 161 studies), due to inadequate reporting. Of the 209 included studies, 34 had at least one item rated as high risk of bias. There was moderate-certainty evidence that patient decision aids probably increase the congruence between informed values and care choices compared to usual care (RR 1.75, 95% CI 1.44 to 2.13; 21 studies, 9377 participants). Regarding attributes related to the decision-making process and compared to usual care, there was high-certainty evidence that patient decision aids result in improved participants' knowledge (MD 11.90/100, 95% CI 10.60 to 13.19; 107 studies, 25,492 participants), accuracy of risk perceptions (RR 1.94, 95% CI 1.61 to 2.34; 25 studies, 7796 participants), and decreased decisional conflict related to feeling uninformed (MD -10.02, 95% CI -12.31 to -7.74; 58 studies, 12,104 participants), indecision about personal values (MD -7.86, 95% CI -9.69 to -6.02; 55 studies, 11,880 participants), and proportion of people who were passive in decision-making (clinician-controlled) (RR 0.72, 95% CI 0.59 to 0.88; 21 studies, 4348 participants). For adverse outcomes, there was high-certainty evidence that there was no difference in decision regret between the patient decision aid and usual care groups (MD -1.23, 95% CI -3.05 to 0.59; 22 studies, 3707 participants). Of note, there was no difference in the length of consultation when patient decision aids were used in preparation for the consultation (MD -2.97 minutes, 95% CI -7.84 to 1.90; 5 studies, 420 participants). When patient decision aids were used during the consultation with the clinician, the length of consultation was 1.5 minutes longer (MD 1.50 minutes, 95% CI 0.79 to 2.20; 8 studies, 2702 participants). We found the same direction of effect when we compared results for patient decision aid studies reported in the previous update compared to studies conducted since 2015.

AUTHORS' CONCLUSIONS

Compared to usual care, across a wide variety of decisions, patient decision aids probably helped more adults reach informed values-congruent choices. They led to large increases in knowledge, accurate risk perceptions, and an active role in decision-making. Our updated review also found that patient decision aids increased patients' feeling informed and clear about their personal values. There was no difference in decision regret between people using decision aids versus those receiving usual care. Further studies are needed to assess the impact of patient decision aids on adherence and downstream effects on cost and resource use.

A few-shot disease diagnosis decision making model based on meta-learning for general practice

BACKGROUND

Diagnostic errors have become the biggest threat to the safety of patients in primary health care. General practitioners, as the "gatekeepers" of primary health care, have a responsibility to accurately diagnose patients. However, many general practitioners have insufficient knowledge and clinical experience in some diseases. Clinical decision making tools need to be developed to effectively improve the diagnostic process in primary health care. The long-tailed class distributions of medical datasets are challenging for many popular decision making models based on deep learning, which have difficulty predicting few-shot diseases. Meta-learning is a new strategy for solving few-shot problems.

METHODS AND MATERIALS

In this study, a few-shot disease diagnosis decision making model based on a model-agnostic meta-learning algorithm (FSDD-MAML) is proposed. The MAML algorithm is applied in a knowledge graph-based disease diagnosis model to find the optimal model parameters. Moreover, FSDD-MAML can learn learning rates for all modules of the knowledge graph-based disease diagnosis model. For n-way, k-shot learning tasks, the inner loop of FSDD-MAML performs multiple gradient update steps to learn internal features in disease classification tasks using n×k examples, and the outer loop of FSDD-MAML optimizes the meta-objective to find the associated optimal parameters and learning rates. FSDD-MAML is compared with the original knowledge graph-based disease diagnosis model and other meta-learning algorithms based on an abdominal disease dataset.

RESULT

Meta-learning algorithms can greatly improve the performance of models in top-1 evaluation compared with top-3, top-5, and top-10 evaluations. The proposed decision making model FSDD-MAML outperforms all the other models, with a precision@1 of 90.02 %. We achieve state-of-the-art performance in the diagnosis of all diseases, and the prediction performance for few-shot diseases is greatly improved. For the two groups with the fewest examples of diseases, FSDD-MAML achieves relative increases in precision@1 of 29.13 % and 21.63 % compared with the original knowledge graph-based disease diagnosis model. In addition, we analyze the reasoning process of several few-shot disease predictions and provide an explanation for the results.

CONCLUSION

The decision making model based on meta-learning proposed in this paper can support the rapid diagnosis of diseases in general practice and is especially capable of helping general practitioners diagnose few-shot diseases. This study is of profound significance for the exploration and application of meta-learning to few-shot disease assessment in general practice.

Evaluation of clinical decision support systems in oncology: An updated systematic review

With increasing reliance on technology in oncology, the impact of digital clinical decision support (CDS) tools needs to be examined. A systematic review update was conducted and peer-reviewed literature from 2016 to 2022 were included if CDS tools were used for live decision making and comparatively assessed quantitative outcomes. 3369 studies were screened and 19 were included in this updated review. Combined with a previous review of 24 studies, a total of 43 studies were analyzed. Improvements in outcomes were observed in 42 studies, and 34 of these were of statistical significance. Computerized physician order entry and clinical practice guideline systems comprise the greatest number of evaluated CDS tools (13 and 10 respectively), followed by those that utilize patient-reported outcomes (8), clinical pathway systems (8) and prescriber alerts for best-practice advisories (4). Our review indicates that CDS can improve guideline adherence, patient-centered care, and care delivery processes in oncology.