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A universal decision support system. Addressing the decision-making needs of patients, families, and clinicians in the setting of critical illness.

ABSTRACT: In the setting of a complex critical illness, preference-sensitive decision making-choosing between two or more reasonable treatment options-can be difficult for patients, families, and clinicians alike. A common challenge to making high-quality decisions in this setting is a lack of critical information access and sharing among participants. Decision aids-brochures, web applications, and videos-are a major focus of current research because mounting evidence suggests they can improve decision-making quality and enhance collaborative shared decision making. However, many decision aids have important limitations, including a relatively narrow capacity for personalization, an inability to gather and generate clinical data, a focus on only a single disease or treatment, and high developmental costs. To address these issues and to help guide future research, we propose a model of "universal" electronic decision support that can be easily adapted by clinicians and patients/families for whatever decision is at hand. In this scalable web-based platform, a general shared decision-making core structure would accommodate simple, interchangeable disease and treatment information modules. The format and content of the system could be adapted to decisional participants' unique characteristics, abilities, and needs. Universal decision support can better standardize a decisional approach and also allow a unique degree of personalization within a framework of shared decision making. We also discuss potential criticisms of this approach as well as strategies that can overcome them in a critical illness setting.

SUBMITTER: Cox CE

PROVIDER: S-EPMC4214132 | biostudies-other | 2014 Aug

REPOSITORIES: biostudies-other

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A universal decision support system. Addressing the decision-making needs of patients, families, and clinicians in the setting of critical illness.

Cox Christopher E CE White Douglas B DB Abernethy Amy P AP

American journal of respiratory and critical care medicine 20140801 4

In the setting of a complex critical illness, preference-sensitive decision making-choosing between two or more reasonable treatment options-can be difficult for patients, families, and clinicians alike. A common challenge to making high-quality decisions in this setting is a lack of critical information access and sharing among participants. Decision aids-brochures, web applications, and videos-are a major focus of current research because mounting evidence suggests they can improve decision-ma ...[more]

PMID: 25019639

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Project description:BackgroundAppropriate tools are essential to support a clinician's decision to refer very preterm infants to developmental resources. Streamlining the use of developmental assessment or screening tools to make clinical decisions offers an alternative methodology to help to choose the most effective way to assess this very high-risk population.ObjectiveTo examine the influence of the Ages and Stages Questionnaire-3rd edition (ASQ3) and the Bayley Scales of Infant Development-3rd edition (Bayley-III) scores within a clinically-based decision-making process.MethodsThis retrospective cohort study includes children born at less than 29 weeks gestation who had completed both psychologist-administered Bayley-III and physician-observed ASQ3 assessments at 18 months corrected age. Theoretical referral decisions (TRDs) based on each assessment results were formulated, using cut-off scores between the lower first and second standard deviation values and below the lower second standard deviation values. TRDs to refer to developmental resources were evaluated in light of the multidisciplinary team's actual final integrated decisions (FID).ResultsComplete data was available for 67 children. The ASQ3 and the Bayley-III had similar predictive value for the FID, with comparable kappa values. Comparisons of the physicians' and psychologists' TRDs with the FIDs demonstrated that the ASQ3 in conjunction with the medical and socio-familial findings predicted 93% of referral decisions.ConclusionTaking into consideration potential methodological biases, the results suggest that either ASQ3 or Bayley-III, along with socio-environmental, medical and neurological assessment, are sufficient to guide the majority of clinicians' decisions regarding referral for specialty services. This retrospective study suggests that the physician-supervised ASQ3 may be sufficient to assess children who had been extremely preterm infants for referral purposes. The findings need to be confirmed in a larger, well-designed prospective study to minimize and account for potential sources of bias.

Project description:Importance: Early mobilization, out-of-bed activity, is a component of acute stroke unit care; however, stroke patient heterogeneity requires complex decision-making. Clinically credible and applicable CPGs are needed to support and optimize the delivery of care. In this study, we are specifically exploring the role of clinical practice guidelines to support individual patient-level decision-making by stroke clinicians about early mobilization post-stroke. Methods: Our study uses a novel, two-pronged approach. (1) A review of CPGs containing recommendations for early mobilization practices published after 2015 was appraised using purposely selected items from the Appraisal of Guidelines Research and Evaluation-Recommendations Excellence (AGREE-REX) tool relevant to decision-making for clinicians. (2) A cross-sectional study involving semi-structured interviews with Australian expert stroke clinicians representing content experts and CPG target users. Every CPG was independently assessed against the AGREE-REX standard by two reviewers. Expert stroke clinicians, invited via email, were recruited between June 2019 to March 2020.The main outcomes from the review was the proportion of criteria addressed for each AGREE-REX item by individual and all CPG(s). The main cross-sectional outcomes were the distributions of stroke clinicians' responses about the utility of CPGs, specific areas of uncertainty in early mobilization decision-making, and suggested parameters for inclusion in future early mobilization CPGs. Results: In 18 identified CPGs, many did not adequately address the "Evidence" and "Applicability to Patients" AGREE-REX items. Out of 30 expert stroke clinicians (11 physicians [37%], 11 physiotherapists [37%], 8 nurses [26%]; median [IQR] years of experience, 14 [10-25]), 47% found current CPGs "too broad or vague," while 40% rely on individual clinical judgement and interpretation of the evidence to select an evidence-based choice of action. The areas of uncertainty in decision-making revealed four key suggestions: (1) more granular descriptions of patient and stroke characteristics for appropriate tailoring of decisions, (2) clear statements about when clinical flexibility is appropriate, (3) detailed description of the intervention dose, and (4) physical assessment criteria including safety parameters. Conclusions: The lack of specificity, clinical applicability, and adaptability of current CPGs to effectively respond to the heterogeneous clinical stroke context has provided a clear direction for improvement.

Project description:BackgroundThis project engages patients and physicians in the development of Decision Boxes, short clinical topic summaries covering medical questions that have no single best answer. Decision Boxes aim to prepare the clinician to communicate the risks and benefits of the available options to the patient so they can make an informed decision together.MethodsSeven researchers (including four practicing family physicians) selected 10 clinical topics relevant to primary care practice through a Delphi survey. We then developed two one-page prototypes on two of these topics: prostate cancer screening with the prostate-specific antigen test, and prenatal screening for trisomy 21 with the serum integrated test. We presented the prototypes to purposeful samples of family physicians distributed in two focus groups, and patients distributed in four focus groups. We used the User Experience Honeycomb to explore barriers and facilitators to the communication design used in Decision Boxes. All discussions were transcribed, and three researchers proceeded to thematic content analysis of the transcriptions. The coding scheme was first developed from the Honeycomb's seven themes (valuable, usable, credible, useful, desirable, accessible, and findable), and included new themes suggested by the data. Prototypes were modified in light of our findings.ResultsThree rounds were necessary for a majority of researchers to select 10 clinical topics. Fifteen physicians and 33 patients participated in the focus groups. Following analyses, three sections were added to the Decision Boxes: introduction, patient counseling, and references. The information was spread to two pages to try to make the Decision Boxes less busy and improve users' first impression. To try to improve credibility, we gave more visibility to the research institutions involved in development. A statement on the boxes' purpose and a flow chart representing the shared decision-making process were added with the intent of clarifying the tool's purpose. Information about the risks and benefits according to risk levels was added to the Decision Boxes, to try to ease the adaptation of the information to individual patients.ConclusionResults will guide the development of the eight remaining Decision Boxes. A future study will evaluate the effect of Decision Boxes on the integration of evidence-based and shared decision making principles in clinical practice.

Project description:Background and aimSelf-management support is an integral part of current chronic care guidelines. The success of self-management interventions varies between individual patients, suggesting a need for tailored self-management support. Understanding the role of patient factors in the current decision making of health professionals can support future tailoring of self-management interventions. The aim of this study is to identify the relative importance of patient factors in health professionals' decision making regarding self-management support.MethodA factorial survey was presented to primary care physicians and nurses. The survey consisted of clinical vignettes (case descriptions), in which 11 patient factors were systematically varied. Each care provider received a set of 12 vignettes. For each vignette, they decided whether they would give this patient self-management support and whether they expected this support to be successful. The associations between respondent decisions and patient factors were explored using ordered logit regression.ResultsThe survey was completed by 60 general practitioners and 80 nurses. Self-management support was unlikely to be provided in a third of the vignettes. The most important patient factor in the decision to provide self-management support as well as in the expectation that self-management support would be successful was motivation, followed by patient-provider relationship and illness perception. Other factors, such as depression or anxiety, education level, self-efficacy and social support, had a small impact on decisions. Disease, disease severity, knowledge of disease, and age were relatively unimportant factors.ConclusionThis is the first study to explore the relative importance of patient factors in decision making and the expectations regarding the provision of self-management support to chronic disease patients. By far, the most important factor considered was patient's motivation; unmotivated patients were less likely to receive self-management support. Future tailored interventions should incorporate strategies to enhance motivation in unmotivated patients. Furthermore, care providers should be better equipped to promote motivational change in their patients.

Project description:ObjectivesTo analyze current practices in shared decision-making (SDM) in primary care and perform a needs assessment for the role of information technology (IT) interventions.Materials and methodsA mixed-methods study was conducted in three phases: (1) ethnographic observation of clinical encounters, (2) patient interviews, and (3) physician interviews. SDM was measured using the validated OPTION scale. Semistructured interviews followed an interview guide (developed by our multidisciplinary team) informed by the Traditional Decision Conflict Scale and Shared Decision Making Questionnaire. Field notes were independently coded and analyzed by two reviewers in Dedoose.ResultsTwenty-four patient encounters were observed in 3 diverse practices with an average OPTION score of 57.2 (0-100 scale; 95% confidence interval [CI], 51.8-62.6). Twenty-two patient and 8 physician interviews were conducted until thematic saturation was achieved. Cohen's kappa, measuring coder agreement, was 0.42. Patient domains were: establishing trust, influence of others, flexibility, frustrations, values, and preferences. Physician domains included frustrations, technology (concerns, existing use, and desires), and decision making (current methods used, challenges, and patients' understanding).DiscussionGiven low SDM observed, multiple opportunities for technology to enhance SDM exist based on specific OPTION items that received lower scores, including: (1) checking the patient's preferred information format, (2) asking the patient's preferred level of involvement in decision making, and (3) providing an opportunity for deferring a decision. Based on data from interviews, patients and physicians value information exchange and are open to technologies that enhance communication of care options.ConclusionFuture primary care IT platforms should prioritize the 3 quantitative gaps identified to improve physician-patient communication and relationships. Additionally, SDM tools should seek to standardize common workflow steps across decisions and focus on barriers to increasing adoption of effective SDM tools into routine primary care.

Dataset Information

A universal decision support system. Addressing the decision-making needs of patients, families, and clinicians in the setting of critical illness.

Publications

A universal decision support system. Addressing the decision-making needs of patients, families, and clinicians in the setting of critical illness.

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