Dataset Information

Adoption of shared decision-making and clinical decision support for reducing cardiovascular disease risk in community health centers.

ABSTRACT:

Objective

Electronic health record (EHR)-based shared decision-making (SDM) and clinical decision support (CDS) systems can improve cardiovascular disease (CVD) care quality and risk factor management. Use of the CV Wizard system showed a beneficial effect on high-risk community health center (CHC) patients' CVD risk within an effectiveness trial, but system adoption was low overall. We assessed which multi-level characteristics were associated with system use.

Materials and methods

Analyses included 80 195 encounters with 17 931 patients with high CVD risk and/or uncontrolled risk factors at 42 clinics in September 2018-March 2020. Data came from the CV Wizard repository and EHR data, and a survey of 44 clinic providers. Adjusted, mixed-effects multivariate Poisson regression analyses assessed factors associated with system use. We included clinic- and provider-level clustering as random effects to account for nested data.

Results

Likelihood of system use was significantly higher in encounters with patients with higher CVD risk and at longer encounters, and lower when providers were >10 minutes behind schedule, among other factors. Survey participants reported generally high satisfaction with the system but were less likely to use it when there were time constraints or when rooming staff did not print the system output for the provider.

Discussion

CHC providers prioritize using this system for patients with the greatest CVD risk, when time permits, and when rooming staff make the information readily available. CHCs' financial constraints create substantial challenges to addressing barriers to improved system use, with health equity implications.

Conclusion

Research is needed on improving SDM and CDS adoption in CHCs.

Trial registration

ClinicalTrials.gov, NCT03001713, https://clinicaltrials.gov/.

SUBMITTER: Hauschildt J

PROVIDER: S-EPMC10005607 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Adoption of shared decision-making and clinical decision support for reducing cardiovascular disease risk in community health centers.

Hauschildt Jennifer J Lyon-Scott Kristin K Sheppler Christina R CR Larson Annie E AE McMullen Carmit C Boston David D O'Connor Patrick J PJ Sperl-Hillen JoAnn M JM Gold Rachel R

JAMIA open 20230310 1

<h4>Objective</h4>Electronic health record (EHR)-based shared decision-making (SDM) and clinical decision support (CDS) systems can improve cardiovascular disease (CVD) care quality and risk factor management. Use of the CV Wizard system showed a beneficial effect on high-risk community health center (CHC) patients' CVD risk within an effectiveness trial, but system adoption was low overall. We assessed which multi-level characteristics were associated with system use.<h4>Materials and methods</ ...[more]

PMID: 36909848

Similar Datasets

Project description:ImportanceManagement of cardiovascular disease (CVD) risk in socioeconomically vulnerable patients is suboptimal; better risk factor control could improve CVD outcomes.ObjectiveTo evaluate the impact of a clinical decision support system (CDSS) targeting CVD risk in community health centers (CHCs).Design, setting, and participantsThis cluster randomized clinical trial included 70 CHC clinics randomized to an intervention group (42 clinics; 8 organizations) or a control group that received no intervention (28 clinics; 7 organizations) from September 20, 2018, to March 15, 2020. Randomization was by CHC organization accounting for organization size. Patients aged 40 to 75 years with (1) diabetes or atherosclerotic CVD and at least 1 uncontrolled major risk factor for CVD or (2) total reversible CVD risk of at least 10% were the population targeted by the CDSS intervention.InterventionsA point-of-care CDSS displaying real-time CVD risk factor control data and personalized, prioritized evidence-based care recommendations.Main outcomes and measuresOne-year change in total CVD risk and reversible CVD risk (ie, the reduction in 10-year CVD risk that was considered achievable if 6 key risk factors reached evidence-based levels of control).ResultsAmong the 18 578 eligible patients (9490 [51.1%] women; mean [SD] age, 58.7 [8.8] years), patients seen in control clinics (n = 7419) had higher mean (SD) baseline CVD risk (16.6% [12.8%]) than patients seen in intervention clinics (n = 11 159) (15.6% [12.3%]; P < .001); baseline reversible CVD risk was similarly higher among patients seen in control clinics. The CDSS was used at 19.8% of 91 988 eligible intervention clinic encounters. No population-level reduction in CVD risk was seen in patients in control or intervention clinics; mean reversible risk improved significantly more among patients in control (-0.1% [95% CI, -0.3% to -0.02%]) than intervention clinics (0.4% [95% CI, 0.3% to 0.5%]; P < .001). However, when the CDSS was used, both risk measures decreased more among patients with high baseline risk in intervention than control clinics; notably, mean reversible risk decreased by an absolute 4.4% (95% CI, -5.2% to -3.7%) among patients in intervention clinics compared with 2.7% (95% CI, -3.4% to -1.9%) among patients in control clinics (P = .001).Conclusions and relevanceThe CDSS had low use rates and failed to improve CVD risk in the overall population but appeared to have a benefit on CVD risk when it was consistently used for patients with high baseline risk treated in CHCs. Despite some limitations, these results provide preliminary evidence that this technology has the potential to improve clinical care in socioeconomically vulnerable patients with high CVD risk.Trial registrationClinicalTrials.gov Identifier: NCT03001713.

Project description:BackgroundChildren with medical complexity is an increasing population whose parents and healthcare providers face multiple decisions. Shared decision-making is a process where patients, their families and healthcare providers collaborate to make decisions based on clinical evidence and informed preferences of the family. Shared decision-making has benefits for the child, family and healthcare providers, including improved parental understanding of the child's difficulties, increased participation, improved coping skills and more efficient healthcare use. It is, however, poorly implemented.Aims and methodsA scoping review was conducted to explore shared decision-making for children with medical complexity in community health services, including how shared decision-making is defined in research, how it is implemented, including barriers and facilitators and recommendations for research. Six databases were systematically searched for papers published in English up to May 2022: Medline, CINAHL, EMBASE, PsycINFO, PubMed, Cochrane Database of Systematic Reviews and sources of grey literature. The review is reported according to the Preferred Reporting Items for Scoping Reviews.ResultsThirty sources met the inclusion criteria. Most factors can either be a facilitator or barrier to shared decision-making depending on the context. Two significant barriers to shared decision-making in this population include uncertainty about the child's diagnosis, prognosis, and treatment options and the presence of hierarchy and power imbalance during clinical encounters with healthcare providers. Further influencing factors include continuity of care, the availability of accurate, accessible, adequate, and balanced information and the interpersonal and communication skills of parents and healthcare providers.ConclusionUncertainty about diagnosis, prognosis and treatment outcomes for children with medical complexity are additional challenges to the known barriers and facilitators to shared decision-making in community health services. Effective implementation of shared decision-making requires advancement of the evidence base for children with medical complexity, reducing power imbalance in clinical encounters, improving continuity of care, and improving the availability and accessibility of information resources.

Project description:ImportanceShared decision-making (SDM) is a key component of the provision of ethical care, but prior reviews have indicated that clinical practice guidelines seldom promote or facilitate SDM. It is currently unknown whether these findings extend to contemporary cardiovascular guidelines.ObjectiveTo identify and characterize integration of SDM in contemporary cardiovascular guideline recommendations using a systematic classification system.Design, setting, and participantsThis cross-sectional study assessed the latest guidelines or subsequent updates that included pharmacotherapy recommendations and were published between January 2012 and December 2022 by the American College of Cardiology (ACC), Canadian Cardiovascular Society (CCS), and European Society of Cardiology (ESC). Data were analyzed from February 21 to July 21, 2023.Main outcomes and measuresAll pharmacotherapy recommendations were identified within each guideline. Recommendations that incorporated SDM were rated according to a systematic rating framework to evaluate the quality of SDM incorporation based on directness (range, 1-3; assessing whether SDM was incorporated directly and impartially into the recommendation's text, with 1 indicating direct and impartial incorporation of SDM into the recommendation's text) and facilitation (range, A-D; assessing whether decision aids or quantified benefits and harms were provided, with A indicating that a decision aid quantifying benefits and harms was provided). The proportion of recommendations incorporating SDM was also analyzed according to guideline society and category (eg, general cardiology, heart failure).ResultsAnalyses included 65 guideline documents, and 33 documents (51%) incorporated SDM either in a general statement or within specific recommendations. Of 7499 recommendations, 2655 (35%) recommendations addressed pharmacotherapy, and of these, 170 (6%) incorporated SDM. By category, general cardiology guidelines contained the highest proportion of pharmacotherapy recommendations incorporating SDM (86 of 865 recommendations [10%]), whereas heart failure and myocardial disease contained the least (9 of 315 recommendations [3%]). The proportion of pharmacotherapy recommendations incorporating SDM was comparable across societies (ACC: 75 of 978 recommendations [8%]; CCS: 29 of 333 recommendations [9%]; ESC: 67 of 1344 recommendations [5%]), with no trend for change over time. Only 5 of 170 SDM recommendations (3%) were classified as grade 1A (impartial recommendations for SDM supported by a decision aid), whereas 114 of 170 recommendations (67%) were grade 3D (SDM mentioned only in supporting text and without any tools or information to facilitate SDM).Conclusions and relevanceIn this cross-sectional study across guidelines published by 3 major cardiovascular societies over the last decade, 51% of guidelines mentioned the importance of SDM, yet only 6% of recommendations incorporated SDM in any form, and fewer adequately facilitated SDM.

Project description:BackgroundIncreasing patient engagement in healthcare has become a health policy priority. However, there has been concern that promoting supported shared decision-making could increase health inequalities.ObjectiveTo evaluate the impact of SDM interventions on disadvantaged groups and health inequalities.DesignSystematic review and meta-analysis of randomised controlled trials and observational studies.Data sourcesCINAHL, the Cochrane Register of Controlled Trials, the Cochrane Database of Systematic Reviews, EMBASE, HMIC, MEDLINE, the NHS Economic Evaluation Database, Open SIGLE, PsycINFO and Web of Knowledge were searched from inception until June 2012.Study eligibility criteriaWe included all studies, without language restriction, that met the following two criteria: (1) assess the effect of shared decision-making interventions on disadvantaged groups and/or health inequalities, (2) include at least 50% of people from disadvantaged groups, except if a separate analysis was conducted for this group.ResultsWe included 19 studies and pooled 10 in a meta-analysis. The meta-analyses showed a moderate positive effect of shared decision-making interventions on disadvantaged patients. The narrative synthesis suggested that, overall, SDM interventions increased knowledge, informed choice, participation in decision-making, decision self-efficacy, preference for collaborative decision making and reduced decisional conflict among disadvantaged patients. Further, 7 out of 19 studies compared the intervention's effect between high and low literacy groups. Overall, SDM interventions seemed to benefit disadvantaged groups (e.g. lower literacy) more than those with higher literacy, education and socioeconomic status. Interventions that were tailored to disadvantaged groups' needs appeared most effective.ConclusionResults indicate that shared decision-making interventions significantly improve outcomes for disadvantaged patients. According to the narrative synthesis, SDM interventions may be more beneficial to disadvantaged groups than higher literacy/socioeconomic status patients. However, given the small sample sizes and variety in the intervention types, study design and quality, those findings should be interpreted with caution.

Project description:BACKGROUND:Shared decision-making (SDM) can advance patient satisfaction, understanding, goal fulfilment, and patient-reported outcomes. We lack clarity on whether this physician-focused literature applies to community rehabilitation, and on the integration of SDM policies in healthcare settings. We aimed to understand patient and provider perceptions of shared decision-making (SDM) in community rehabilitation, particularly the barriers and facilitators to SDM. METHODS:We used a focused ethnography involving 14 community rehabilitation sites across Alberta, including rural, regional-urban and metropolitan-urban sites. We conducted semi-structured interviews that asked participants about their positive and negative communication experiences (n = 23 patients; n = 26 providers). RESULTS:We found SDM experiences fluctuated between extremes: Getting Patient Buy-In and Aligning Expectations. The former is provider-driven, prescriptive and less flexible; the latter is collaborative, inquisitive and empowering. In Aligning Expectations, patients and providers express humility and openness, communicate in the language of ask and listen, and view education as empowering. Patients and providers described barriers and facilitators to SDM in community rehabilitation. Facilitators included geography influencing context and connections; consistent, patient-specific messaging; patient lifestyle, capacity and perceived outlook; provider confidence, experience and perceived independence; provider training; and perceptions of more time (and control over time) for appointments. SDM barriers included lack of privacy; waitlists and financial barriers to access; provider approach; how choices are framed; and, patient's perceived assertiveness, lack of capacity, and level of deference. CONCLUSIONS:We have found both excellent experiences and areas for improvement for applying SDM in community rehabilitation. We proffer recommendations to advance high-quality SDM in community rehabilitation based on promoting facilitators and overcoming barriers. This research will support the spread, scale and evaluation of a new Model of Care in rehabilitation by the provincial health system, which aimed to promote patient-centred care.

Project description:BackgroundLung cancer treatment decisions are typically made among clinical experts in a multidisciplinary tumour board (MTB) based on clinical data and guidelines. The rise of artificial intelligence and cultural shifts towards patient autonomy are changing the nature of clinical decision-making towards personalized treatments. This can be supported by clinical decision support systems (CDSSs) that generate personalized treatment information as a basis for shared decision-making (SDM). Little is known about lung cancer patients' treatment decisions and the potential for SDM supported by CDSSs. The aim of this study is to understand to what extent SDM is done in current practice and what clinicians need to improve it.ObjectiveTo explore (1) the extent to which patient preferences are taken into consideration in non-small-cell lung cancer (NSCLC) treatment decisions; (2) clinician perspectives on using CDSSs to support SDM.DesignMixed methods study consisting of a retrospective cohort study on patient deviation from MTB advice and reasons for deviation, qualitative interviews with lung cancer specialists and observations of MTB discussions and patient consultations.Setting and participantsNSCLC patients (N = 257) treated at a single radiotherapy clinic and nine lung cancer specialists from six Dutch clinics.ResultsWe found a 10.9% (n = 28) deviation rate from MTB advice; 50% (n = 14) were due to patient preference, of which 85.7% (n = 12) chose a less intensive treatment than MTB advice. Current MTB recommendations are based on clinician experience, guidelines and patients' performance status. Most specialists (n = 7) were receptive towards CDSSs but cited barriers, such as lack of trust, lack of validation studies and time. CDSSs were considered valuable during MTB discussions rather than in consultations.ConclusionLung cancer decisions are heavily influenced by clinical guidelines and experience, yet many patients prefer less intensive treatments. CDSSs can support SDM by presenting the harms and benefits of different treatment options rather than giving single treatment advice. External validation of CDSSs should be prioritized.Patient or public contributionThis study did not involve patients or the public explicitly; however, the study design was informed by prior interviews with volunteers of a cancer patient advocacy group. The study objectives and data collection were supported by Dutch health care insurer CZ for a project titled 'My Best Treatment' that improves patient-centeredness and the lung cancer patient pathway in the Netherlands.

Project description:ObjectivePatient values and preferences are an important component to decision making when tradeoffs exist that impact quality of life, such as tradeoffs between stroke prevention and hemorrhage in patients with atrial fibrillation (AF) contemplating anticoagulant therapy. Our objective is to describe the development of an Atrial Fibrillation Guideline Support Tool (AFGuST) to assist the process of integrating patients' preferences into this decision.Materials and methodsCHA2DS2VASc and HAS-BLED were used to calculate risks for stroke and hemorrhage. We developed a Markov decision analytic model as a computational engine to integrate patient-specific risk for stroke and hemorrhage and individual patient values for relevant outcomes in decisions about anticoagulant therapy.ResultsIndividual patient preferences for health-related outcomes may have greater or lesser impact on the choice of optimal antithrombotic therapy, depending upon the balance of patient-specific risks for ischemic stroke and major bleeding. These factors have been incorporated into patient-tailored booklets which, along with an informational video, were developed through an iterative process with clinicians and patient focus groups.Key limitationsCurrent risk prediction models for hemorrhage, such as the HAS-BLED, used in the AFGuST, do not incorporate all potentially significant risk factors. Novel oral anticoagulant agents recently approved for use in the United States, Canada, and Europe have not been included in the AFGuST. Rather, warfarin has been used as a conservative proxy for all oral anticoagulant therapy.ConclusionsWe present a proof of concept that a patient-tailored decision-support tool could bridge the gap between guidelines and practice by incorporating individual patient's stroke and bleeding risks and their values for major bleeding events and stroke to facilitate a shared decision making process. If effective, the AFGuST could be used as an adjunct to published guidelines to enhance patient-centered conversations about the anticoagulation management.

Project description:BackgroundThere is a critical need to improve support for families making difficult shared decisions about patient care with clinicians in the neuroscience ICU (neuro-ICU). The aim of this study is to identify patient- and family-related factors associated with dissatisfaction with shared decision-making support among families of neuro-critically ill patients.MethodsWe conducted a retrospective observational cohort study using survey data that had been collected from a consecutive sample of family members of patients in the neuro-ICU (one family member per patient) at two US academic centers. Satisfaction with shared decision-making support on ICU discharge had been measured among family members using one specific Likert scale item on the Family Satisfaction in the ICU 24 survey, a validated survey instrument for families of patients in the ICU. We dichotomized top-box responses for this particular item as an outcome variable and identified available patient- and family-related covariates associated with dissatisfaction (i.e., less than complete satisfaction) via univariate and multivariate analyses.ResultsAmong 355 surveys, 180 (49.5%) of the surveys indicated dissatisfaction with support during decision-making. In a multivariate model, no preexisting characteristics of families or patients ascertainable on ICU admission were predictive of dissatisfaction. However, among family factors determined during the ICU course, experiencing three or fewer formal family meetings (odds ratio 1.93 [confidence interval 1.13-3.31]; p = 0.01) was significantly predictive of dissatisfaction with decisional support in this cohort with an average patient length of stay of 8.6 days (SD 8.4). There was also a trend toward a family's decision to keep a patient as full code, without treatment limitations, being predictive of dissatisfaction (odds ratio 1.80 [confidence interval 0.93-3.51]; p = 0.08).ConclusionsFamily dissatisfaction with neuro-ICU shared decision-making support is not necessarily predicted by any preexisting family or patient variables but appears to correlate with participating in fewer formal family meetings during ICU admission. Future studies to improve family satisfaction with neurocritical care decision-making support should have broad inclusion criteria for participants and should consider promoting frequency of family meetings as a core strategy.

Dataset Information

Adoption of shared decision-making and clinical decision support for reducing cardiovascular disease risk in community health centers.

Objective

Materials and methods

Results

Discussion

Conclusion

Trial registration

Publications

Adoption of shared decision-making and clinical decision support for reducing cardiovascular disease risk in community health centers.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets