Background
Shared decision making (SDM) is a process by which a healthcare choice is made by the patient, significant others, or both with one or more healthcare professionals. However, it has not ...yet been widely adopted in practice. This is the second update of this Cochrane review.
Objectives
To determine the effectiveness of interventions for increasing the use of SDM by healthcare professionals. We considered interventions targeting patients, interventions targeting healthcare professionals, and interventions targeting both.
Search methods
We searched CENTRAL, MEDLINE, Embase and five other databases on 15 June 2017. We also searched two clinical trials registries and proceedings of relevant conferences. We checked reference lists and contacted study authors to identify additional studies.
Selection criteria
Randomized and non‐randomized trials, controlled before‐after studies and interrupted time series studies evaluating interventions for increasing the use of SDM in which the primary outcomes were evaluated using observer‐based or patient‐reported measures.
Data collection and analysis
We used standard methodological procedures expected by Cochrane.
We used GRADE to assess the certainty of the evidence.
Main results
We included 87 studies (45,641 patients and 3113 healthcare professionals) conducted mainly in the USA, Germany, Canada and the Netherlands. Risk of bias was high or unclear for protection against contamination, low for differences in the baseline characteristics of patients, and unclear for other domains.
Forty‐four studies evaluated interventions targeting patients. They included decision aids, patient activation, question prompt lists and training for patients among others and were administered alone (single intervention) or in combination (multifaceted intervention). The certainty of the evidence was very low. It is uncertain if interventions targeting patients when compared with usual care increase SDM whether measured by observation (standardized mean difference (SMD) 0.54, 95% confidence interval (CI) ‐0.13 to 1.22; 4 studies; N = 424) or reported by patients (SMD 0.32, 95% CI 0.16 to 0.48; 9 studies; N = 1386; risk difference (RD) ‐0.09, 95% CI ‐0.19 to 0.01; 6 studies; N = 754), reduce decision regret (SMD ‐0.10, 95% CI ‐0.39 to 0.19; 1 study; N = 212), improve physical (SMD 0.00, 95% CI ‐0.36 to 0.36; 1 study; N = 116) or mental health‐related quality of life (QOL) (SMD 0.10, 95% CI ‐0.26 to 0.46; 1 study; N = 116), affect consultation length (SMD 0.10, 95% CI ‐0.39 to 0.58; 2 studies; N = 224) or cost (SMD 0.82, 95% CI 0.42 to 1.22; 1 study; N = 105).
It is uncertain if interventions targeting patients when compared with interventions of the same type increase SDM whether measured by observation (SMD 0.88, 95% CI 0.39 to 1.37; 3 studies; N = 271) or reported by patients (SMD 0.03, 95% CI ‐0.18 to 0.24; 11 studies; N = 1906); (RD 0.03, 95% CI ‐0.02 to 0.08; 10 studies; N = 2272); affect consultation length (SMD ‐0.65, 95% CI ‐1.29 to ‐0.00; 1 study; N = 39) or costs. No data were reported for decision regret, physical or mental health‐related QOL.
Fifteen studies evaluated interventions targeting healthcare professionals. They included educational meetings, educational material, educational outreach visits and reminders among others. The certainty of evidence is very low. It is uncertain if these interventions when compared with usual care increase SDM whether measured by observation (SMD 0.70, 95% CI 0.21 to 1.19; 6 studies; N = 479) or reported by patients (SMD 0.03, 95% CI ‐0.15 to 0.20; 5 studies; N = 5772); (RD 0.01, 95%C: ‐0.03 to 0.06; 2 studies; N = 6303); reduce decision regret (SMD 0.29, 95% CI 0.07 to 0.51; 1 study; N = 326), affect consultation length (SMD 0.51, 95% CI 0.21 to 0.81; 1 study, N = 175), cost (no data available) or physical health‐related QOL (SMD 0.16, 95% CI ‐0.05 to 0.36; 1 study; N = 359). Mental health‐related QOL may slightly improve (SMD 0.28, 95% CI 0.07 to 0.49; 1 study, N = 359; low‐certainty evidence).
It is uncertain if interventions targeting healthcare professionals compared to interventions of the same type increase SDM whether measured by observation (SMD ‐0.30, 95% CI ‐1.19 to 0.59; 1 study; N = 20) or reported by patients (SMD 0.24, 95% CI ‐0.10 to 0.58; 2 studies; N = 1459) as the certainty of the evidence is very low. There was insufficient information to determine the effect on decision regret, physical or mental health‐related QOL, consultation length or costs.
Twenty‐eight studies targeted both patients and healthcare professionals. The interventions used a combination of patient‐mediated and healthcare professional directed interventions. Based on low certainty evidence, it is uncertain whether these interventions, when compared with usual care, increase SDM whether measured by observation (SMD 1.10, 95% CI 0.42 to 1.79; 6 studies; N = 1270) or reported by patients (SMD 0.13, 95% CI ‐0.02 to 0.28; 7 studies; N = 1479); (RD ‐0.01, 95% CI ‐0.20 to 0.19; 2 studies; N = 266); improve physical (SMD 0.08, ‐0.37 to 0.54; 1 study; N = 75) or mental health‐related QOL (SMD 0.01, ‐0.44 to 0.46; 1 study; N = 75), affect consultation length (SMD 3.72, 95% CI 3.44 to 4.01; 1 study; N = 36) or costs (no data available) and may make little or no difference to decision regret (SMD 0.13, 95% CI ‐0.08 to 0.33; 1 study; low‐certainty evidence).
It is uncertain whether interventions targeting both patients and healthcare professionals compared to interventions of the same type increase SDM whether measured by observation (SMD ‐0.29, 95% CI ‐1.17 to 0.60; 1 study; N = 20); (RD ‐0.04, 95% CI ‐0.13 to 0.04; 1 study; N = 134) or reported by patients (SMD 0.00, 95% CI ‐0.32 to 0.32; 1 study; N = 150 ) as the certainty of the evidence was very low. There was insuffient information to determine the effects on decision regret, physical or mental health‐related quality of life, or consultation length or costs.
Authors' conclusions
It is uncertain whether any interventions for increasing the use of SDM by healthcare professionals are effective because the certainty of the evidence is low or very low.
Objective Contraceptive methods have differing attributes. Women’s preferences for these attributes may influence contraceptive decision making. Our objective was to identify women’s contraceptive ...preferences among women initiating a new contraceptive method. Study Design We conducted a cross-sectional, self-administered survey of women’s contraceptive preferences at the time of enrollment into the Contraceptive CHOICE Project. Participants were asked to rank the importance of 15 contraceptive attributes on a 3-point scale (1 = not at all important, 2 = somewhat important, and 3 = very important) and then to rank the 3 attributes that were the most important when choosing a contraceptive method. The survey also contained questions about prior contraceptive experience and barriers to contraceptive use. Information about demographic and reproductive characteristics was collected through the CHOICE Project baseline survey. Results There were 2590 women who completed the survey. Our sample was racially and socioeconomically diverse. Method attributes with the highest importance score (mean score SD) were effectiveness (2.97 0.18), safety (2.96 0.22), affordability (2.61 0.61), whether the method is long lasting (2.58 0.61), and whether the method is “forgettable” (2.54 0.66). The attributes most likely to be ranked by respondents among the top 3 attributes included effectiveness (84.2%), safety (67.8%), and side effects of the method (44.6%). Conclusion Multiple contraceptive attributes influence decision making and no single attribute drives most women’s decisions. Tailoring communication and helping women make complex tradeoffs between attributes can better support their contraceptive decisions and may assist them in making value-consistent choices. This process could improve continuation and satisfaction.
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Decision aids help patients consider the benefits and drawbacks of care options but rarely include cost information. We assessed the impact of a conversation-based decision aid containing information ...about low-risk prostate cancer management options and their relative costs.
We conducted a stepped-wedge cluster randomised trial in outpatient urology practices within a US-based academic medical center. We randomised five clinicians to four intervention sequences and enroled patients newly diagnosed with low-risk prostate cancer. Primary patient-reported outcomes collected postvisit included the frequency of cost conversations and referrals to address costs. Other patient-reported outcomes included: decisional conflict postvisit and at 3 months, decision regret at 3 months, shared decision-making postvisit, financial toxicity postvisit and at 3 months. Clinicians reported their attitudes about shared decision-making pre- and poststudy, and the intervention's feasibility and acceptability. We used hierarchical regression analysis to assess patient outcomes. The clinician was included as a random effect; fixed effects included education, employment, telehealth versus in-person visit, visit date, and enrolment period.
Between April 2020 and March 2022, we screened 513 patients, contacted 217 eligible patients, and enroled 117/217 (54%) (51 in usual care, 66 in the intervention group). In adjusted analyses, the intervention was not associated with cost conversations (β = .82, p = .27), referrals to cost-related resources (β = -0.36, p = .81), shared decision-making (β = -0.79, p = .32), decisional conflict postvisit (β = -0.34, p= .70), or at follow-up (β = -2.19, p = .16), decision regret at follow-up (β = -9.76, p = .11), or financial toxicity postvisit (β = -1.32, p = .63) or at follow-up (β = -2.41, p = .23). Most clinicians and patients had positive attitudes about the intervention and shared decision-making. In exploratory unadjusted analyses, patients in the intervention group experienced more transient indecision (p < .02) suggesting increased deliberation between visit and follow-up.
Despite enthusiasm from clinicians, the intervention was not significantly associated with hypothesised outcomes, though we were unable to robustly test outcomes due to recruitment challenges. Recruitment at the start of the COVID-19 pandemic impacted eligibility, sample size/power, study procedures, and increased telehealth visits and financial worry, independent of the intervention. Future work should explore ways to support shared decision-making, cost conversations, and choice deliberation with a larger sample. Such work could involve additional members of the care team, and consider the detail, quality, and timing of addressing these issues.
Patients and clinicians were engaged as stakeholder advisors meeting monthly throughout the duration of the project to advise on the study design, measures selected, data interpretation, and dissemination of study findings.
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Background
Several interventions have been developed to promote informed consent for participants in clinical trials. However, many of these interventions focus on the content and structure of ...information (e.g. enhanced information or changes to the presentation format) rather than the process of decision making. Patient decision aids support a decision making process about medical options. Decision aids support the decision process by providing information about available options and their associated outcomes, alongside information that enables patients to consider what value they place on particular outcomes, and provide structured guidance on steps of decision making. They have been shown to be effective for treatment and screening decisions but evidence on their effectiveness in the context of informed consent for clinical trials has not been synthesised.
Objectives
To assess the effectiveness of decision aids for clinical trial informed consent compared to no intervention, standard information (i.e. usual practice) or an alternative intervention on the decision making process.
Search methods
We searched the following databases and to March 2015: Cochrane Central Register of Controlled Trials (CENTRAL), The Cochrane Library; MEDLINE (OvidSP) (from 1950); EMBASE (OvidSP) (from 1980); PsycINFO (OvidSP) (from 1806); ASSIA (ProQuest) (from 1987); WHO International Clinical Trials Registry Platform (ICTRP) (http://apps.who.int/trialsearch/); ClinicalTrials.gov; ISRCTN Register (http://www.controlled‐trials.com/isrctn/). We also searched reference lists of included studies and relevant reviews. We contacted study authors and other experts. There were no language restrictions.
Selection criteria
We included randomised and quasi‐randomised controlled trials comparing decision aids in the informed consent process for clinical trials alone, or in conjunction with standard information (such as written or verbal) or alongside alternative interventions (e.g. paper‐based versus web‐based decision aids). Included trials involved potential trial participants, or their guardians, being asked to consider participating in a real or hypothetical clinical trial.
Data collection and analysis
At least two authors independently assessed studies for inclusion, extracted reported data and assessed risk of bias. Findings were pooled where appropriate. We used GRADE to assess the quality of the evidence for each outcome.
Main results
We identified one study (290 randomised participants) that investigated the effectiveness of decision aids compared to standard information in the informed consent process for clinical trials. This study reported two separate decision aid randomised controlled trials (RCTs). The decision aid trials were nested within two different parent trials focusing on breast cancer in postmenopausal women. One trial focused on informed consent for treatment in women who had previously had surgery for ductal carcinoma in situ (DCIS), the other on informed consent for prevention in women at high risk for breast cancer. Two different decision aids were used in these RCTs, and were compared with standard information.
The pooled findings highlight the uncertainty surrounding most reported outcomes, including knowledge, decisional conflict, anxiety, trial participation and attrition. There was very low quality evidence that decision aids lower levels of decisional regret to a small degree (MD ‐5.53, 95% CI ‐10.29 to ‐0.76). No data were identified on several prespecified primary outcomes, including accurate risk perception, values‐based decision, or whether potential participants recognised that a decision needed to be made, were able to identify features of options that matter most to individuals, or were involved in the decision.
Authors' conclusions
There was insufficient evidence to determine whether decision aids to support the informed consent process for clinical trials are more effective than standard information. Additional well designed, adequately powered clinical trials in more diverse clinical and social populations are needed to strengthen the results of this review. More generally, future research on which outcomes are most relevant for assessment in this context would be helpful.
Shared decision making (SDM) can reduce overuse of options not associated with benefits for all and respects patient rights, but has not yet been widely adopted in practice.
To determine the ...effectiveness of interventions to improve healthcare professionals' adoption of SDM.
For this update we searched for primary studies in The Cochrane Library, MEDLINE, EMBASE, CINAHL, the Cochrane Effective Practice and Organisation of Care (EPOC) Specialsied Register and PsycINFO for the period March 2009 to August 2012. We searched the Clinical Trials.gov registry and the proceedings of the International Shared Decision Making Conference. We scanned the bibliographies of relevant papers and studies. We contacted experts in the field to identify papers published after August 2012.
Randomised and non-randomised controlled trials, controlled before-and-after studies and interrupted time series studies evaluating interventions to improve healthcare professionals' adoption of SDM where the primary outcomes were evaluated using observer-based outcome measures (OBOM) or patient-reported outcome measures (PROM).
The three overall categories of intervention were: interventions targeting patients, interventions targeting healthcare professionals, and interventions targeting both. Studies in each category were compared to studies in the same category, to studies in the other two categories, and to usual care, resulting in nine comparison groups. Statistical analysis considered categorical and continuous primary outcomes separately. We calculated the median of the standardized mean difference (SMD), or risk difference, and range of effect across studies and categories of intervention. We assessed risk of bias.
Thirty-nine studies were included, 38 randomised and one non-randomised controlled trial. Categorical measures did not show any effect for any of the interventions. In OBOM studies, interventions targeting both patients and healthcare professionals had a positive effect compared to usual care (SMD of 2.83) and compared to interventions targeting patients alone (SMD of 1.42). Studies comparing interventions targeting patients with other interventions targeting patients had a positive effect, as did studies comparing interventions targeting healthcare professionals with usual care (SDM of 1.13 and 1.08 respectively). In PROM studies, only three comparisons showed any effect, patient compared to usual care (SMD of 0.21), patient compared to another patient (SDM of 0.29) and healthcare professional compared to another healthcare professional (SDM of 0.20). For all comparisons, interpretation of the results needs to consider the small number of studies, the heterogeneity, and some methodological issues. Overall quality of the evidence for the outcomes, assessed with the GRADE tool, ranged from low to very low.
It is uncertain whether interventions to improve adoption of SDM are effective given the low quality of the evidence. However, any intervention that actively targets patients, healthcare professionals, or both, is better than none. Also, interventions targeting patients and healthcare professionals together show more promise than those targeting only one or the other.
Background
Treatment decisions about menopause are predicated on a transient duration of vasomotor symptoms. However, evidence supporting a specific duration is weak.
Objective
To estimate the ...natural progression of vasomotor symptoms during the menopause transition by systematically compiling available evidence using meta-analytic techniques.
Data Sources
We searched MEDLINE, hand searched secondary references in relevant studies, book chapters, and review papers, and contacted investigators about relevant published research.
Review Methods
English language, population-based studies reporting vasomotor symptom prevalence among women in menopausal transition in time intervals based on years to or from final menstrual period were included. Two reviewers independently assessed eligibility and quality of studies and extracted data for vasomotor symptom prevalence.
Results
The analyses included 10 studies (2 longitudinal, 8 cross sectional) with 35,445 participants. The percentage of women experiencing symptoms increased sharply in the 2 years before final menstrual period, peaked 1 year after final menstrual period, and did not return to premenopausal levels until about 8 years after final menstrual period. Nearly 50% of all women reported vasomotor symptoms 4 years after final menstrual period, and 10% of all women reported symptoms as far as 12 years after final menstrual period. When data were examined according to symptom severity (‘any’ vs. ‘bothersome’), bothersome symptoms peaked about 1 year earlier and declined more rapidly than symptoms of any severity level.
Conclusions
Our findings suggest a median symptom duration of about 4 years among symptomatic women. A longer symptom duration may affect treatment decisions and clinical guidelines. Further prospective, longitudinal studies of menopausal symptoms should be conducted to confirm these results.
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Navigating health insurance and health care choices requires considerable health insurance literacy. Although recommended preventive services are exempt from out-of-pocket costs under the Affordable ...Care Act, many people may remain unaware of this provision and its effect on their required payment. Little is known about the association between individuals' health insurance literacy and their use of preventive or nonpreventive health care services.
To assess the association between health insurance literacy and self-reported avoidance of health care services owing to cost.
In this survey study, a US national, geographically diverse, nonprobability sample of 506 US residents aged 18 years or older with current health insurance coverage was recruited to participate in an online survey between February 22 and 23, 2016.
The validated 21-item Health Insurance Literacy Measure (HILM) assessed individuals' self-rated confidence in selecting and using health insurance (score range, 0-84, with higher scores indicating greater levels of health insurance literacy). Dependent variables included delayed or foregone preventive and nonpreventive services in the past 12 months owing to perceived costs, and preventive and nonpreventive use of services. Covariates included age, sex, race/ethnicity, income, educational level, high-deductible health insurance plan, health literacy, numeracy, and chronic health conditions. Analyses included descriptive statistics and bivariate and multivariable logistic regression.
A total of 506 of 511 participants who began the survey completed it (participation rate, 99.0%). Of the 506 participants, 339 (67.0%) were younger than 35 years (mean SD age, 34 10.4 years), 228 (45.1%) were women, 406 of 504 who reported race (80.6%) were white, and 245 (48.4%) attended college for 4 or more years. A total of 228 participants (45.1%) had 1 or more chronic health condition, 361 of 500 (72.2%) who responded to the survey item had seen a physician in the outpatient setting in the past 12 months, and 446 of the 501 (89.0%) who responded to the survey item had their health insurance plan for 12 or more months. One hundred fifty respondents (29.6%) reported having delayed or foregone care because of cost. The mean (SD) HILM score was 63.5 (12.3). In multivariable logistic regression, each 12-point increase in HILM score was associated with a lower likelihood of both delayed or foregone preventive care (adjusted odds ratio aOR, 0.61; 95% CI, 0.48-0.78) and delayed or foregone nonpreventive care (aOR, 0.71; 95% CI, 0.55-0.91).
This study's findings suggest that lower health insurance literacy may be associated with greater avoidance of both preventive and nonpreventive services. It appears that to improve appropriate use of recommended health care services, including preventive health services, clinicians, health plans, and policymakers may need to communicate health insurance concepts in accessible ways regardless of individuals' health insurance literacy. Plain language communication may be able to improve patients' understanding of services exempt from out-of-pocket costs.
Abstract Objective To identify and analyze training programs in shared decision-making (SDM) for health professionals. Methods We conducted an environmental scan looking for programs that train ...health professionals in SDM. Pairs of reviewers independently analyzed the programs identified using a standardized data extraction sheet. The developers of the programs validated the data extracted. Results We identified 54 programs conducted between 1996 and 2011 in 14 countries and 10 languages. Thirty-four programs targeted licensed health professionals, 10 targeted pre-licensure health professionals, and 10 targeted both. Most targeted only the medical profession ( n = 32); six targeted more than one health profession. The five most frequently mentioned teaching methods were case-based discussion, small group educational session, role play, printed educational material, and audit and feedback. Thirty-six programs reported having evaluated their impacts but evaluation data was available only for 17. Conclusions Health professional training programs in SDM vary widely in how and what they deliver, and evidence of their effectiveness is sparse. Practice implications This study suggests there is a need for international consensus on ways to address the variability in SDM training programs. We need agreed criteria for certifying the programs and for determining the most effective types of training.
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ABSTRACT
Clinical practice guidelines aim to improve the health of patients by guiding individual care in clinical settings. Many guidelines specifically about health promotion or primary disease ...prevention are beginning to support informed patient choice, and suggest that clinicians and patients engage in shared discussions to determine how best to tailor guidelines to individuals. However, guidelines generally do not address how to translate evidence from the population to the individual in clinical practice, or how to engage patients in these discussions. In addition, they often fail to reconcile patients’ preferences and social norms with best evidence. Shared decision making (SDM) is one solution to bridge guidelines about health promotion and disease prevention with clinical practice. SDM describes a collaborative process between patients and their clinicians to reach agreement about a health decision involving multiple medically appropriate treatment options. This paper discusses: 1) a brief overview of SDM; 2) the potential role of SDM in facilitating the implementation of prevention-focused practice guidelines for both preference-sensitive and effective care decisions; and 3) avenues for future empirical research to test how best to engage individual patients and clinicians in these complex discussions about prevention guidelines. We suggest that SDM can provide a structure for clinicians to discuss clinical practice guidelines with patients in a way that is evidence-based, patient-centered, and incorporates patients’ preferences. In addition to providing a model for communicating about uncertainty at the individual level, SDM can provide a platform for engaging patients in a conversation. This process can help manage patients’ and clinicians’ expectations about health behaviors. SDM can be used even in situations with strong evidence for benefits at the level of the population, by helping patients and clinicians prioritize behaviors during time-pressured medical encounters. Involving patients in discussions could lead to improved health through better adherence to chosen options, reduced practice variation about preference-sensitive options, and improved care more broadly. However, more research is needed to determine the impact of this approach on outcomes such as morbidity and mortality.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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