Background In cancers with a chronic phase, patients and family caregivers face difficult decisions such as whether to start a novel therapy, whether to enroll in a clinical trial, and when to stop treatment. These decisions are complex, require an understanding of uncertainty, and necessitate the consideration of patients’ informed preferences. For some cancers, such as medullary thyroid carcinoma, these decisions may also involve significant out-of-pocket costs and effects on family members. Providers have expressed a need for web-based interventions that can be delivered between consultations to provide education and prepare patients and families to discuss these decisions. To ensure that these tools are effective, usable, and understandable, studies are needed to identify patients’, families’, and providers’ decision-making needs and optimal design strategies for a web-based patient decision aid. Objective Following the international guidelines for the development of a web-based patient decision aid, the objectives of this study are to engage potential users to guide development; review the existing literature and available tools; assess users’ decision-making experiences, needs, and design recommendations; and identify shared decision-making approaches to address each need. Methods This study used the decisional needs assessment approach, which included creating a stakeholder advisory panel, mapping decision pathways, conducting an environmental scan of existing materials, and administering a decisional needs assessment questionnaire. Thematic analyses identified current decision-making pathways, unmet decision-making needs, and decision support strategies for meeting each need. Results The stakeholders reported wide heterogeneity in decision timing and pathways. Relevant existing materials included 2 systematic reviews, 9 additional papers, and multiple educational websites, but none of these met the criteria for a patient decision aid. Patients and family members (n=54) emphasized the need for plain language (46/54, 85%), shared decision making (45/54, 83%), and help with family discussions (39/54, 72%). Additional needs included information about uncertainty, lived experience, and costs. Providers (n=10) reported needing interventions that address misinformation (9/10, 90%), foster realistic expectations (9/10, 90%), and address mistrust in clinical trials (5/10, 50%). Additional needs included provider tools that support shared decision making. Both groups recommended designing a web-based patient decision aid that can be tailored to (64/64, 100%) and delivered on a hospital website (53/64, 83%), focuses on quality of life (45/64, 70%), and provides step-by-step guidance (43/64, 67%). The study team identified best practices to meet each need, which are presented in the proposed decision support design guide. Conclusions Patients, families, and providers report multifaceted decision support needs during the chronic phase of cancer. Web-based patient decision aids that provide tailored support over time and explicitly address uncertainty, quality of life, realistic expectations, and effects on families are needed.
Background and Objective: With the inclusion of Enhanced Recovery Programs (ERPs) into routine clinical practice, scaling programs across an institution is important to drive sustainable change in a patient-centric care delivery paradigm. A review of ERP implementation within a large institution was performed to understand key components that hinder or facilitate success of scaling an ERP. Methods: From January 2018 to March 2018, a needs assessment was completed to review implementation of enhanced recovery across the institution. Implementation progress was categorized into one of 5 phases including Define, Implement, Measure, Analyze, and Optimize. Results: Only 25% of service line ERPs reached the optimization phase within 5 years. One hundred percent of respondents reported more strengths (n = 41) and opportunities (n = 41) than weaknesses or threats (n = 25 and 14, respectively). Commonly identified strengths included established enhanced recovery pathways, functional team databases, and effective provider education. Weaknesses identified were inconsistencies in data quality/collection and a lack of key personnel participation including buy-in and time availability. Respondents perceived the need for data standardization to be an opportunity, while personnel factors were viewed as key threats. Conclusion: Identification of strengths, weaknesses, opportunities, and threats could prove beneficial in helping scale an ERP across an institution. Successful optimization and expansion of ERPs require robust data management for continuous quality improvement efforts among clinicians, administrators, executives, and patients.
Background: With increasing implementation of enhanced recovery programs (ERPs) in clinical practice, standardised data collection and reporting have become critical in addressing the heterogeneity of metrics used for reporting outcomes. Opportunities exist to leverage electronic health record (EHR) systems to collect, analyse, and disseminate ERP data. Objectives: (i) To consolidate relevant ERP variables into a singular data universe; (ii) To create an accessible and intuitive query tool for rapid data retrieval. Method: We reviewed nine established individual team databases to identify common variables to create one standard ERP data dictionary. To address data automation, we used a third-party business intelligence tool to map identified variables within the EHR system, consolidating variables into a single ERP universe. To determine efficacy, we compared times for four experienced research coordinators to use manual, five-universe, and ERP Universe processes to retrieve ERP data for 10 randomly selected surgery patients. Results: The total times to process data variables for all 10 patients for the manual, five universe, and ERP Universe processes were 510, 111, and 76 min, respectively. Shifting from the five-universe or manual process to the ERP Universe resulted in decreases in time of 32% and 85%, respectively. Conclusion: The ERP Universe improves time spent collecting, analysing, and reporting ERP elements without increasing operational costs or interrupting workflow. Implications: Manual data abstraction places significant burden on resources. The creation of a singular instrument dedicated to ERP data abstraction greatly increases the efficiency in which clinicians and supporting staff can query adherence to an ERP protocol.
BACKGROUND In cancers with a chronic phase, patients and family caregivers may face difficult decisions such as whether to start a novel therapy, whether to enroll in a clinical trial, and when to stop treatment. These decisions are complex, require an understanding of uncertainty, and necessitate consideration of patients’ informed preferences. For some cancers, such as medullary thyroid carcinoma, these decisions may also involve significant out-of-pocket costs and effects on family members. Providers expressed a need for web-based interventions that can be delivered between consultations to provide education and prepare patients and families for discussing these decisions. To ensure these tools are effective, usable, and understandable, studies are needed to identify patients’, families’, and providers’ primary decision-making needs and optimal design strategies for a web-based patient decision aid. OBJECTIVE Following international guidelines for development of a web-based patient decision aid, the objectives of this study were to: 1) engage potential users to guide development; 2) review the existing literature and available tools; 3) assess users’ decision-making experiences, needs, and design recommendations; and 4) identify shared decision-making approaches to address each need. METHODS This study used the Decisional Needs Assessment approach, including creating a Stakeholder Advisory Panel, mapping decision pathways, conducting an environmental scan of existing materials, and administering a decisional needs assessment questionnaire. Thematic analyses identified the current decision-making pathways, unmet decision-making needs, and decision support strategies to meet each need. RESULTS Stakeholders reported wide heterogeneity in decision timing and pathways. Relevant existing materials included two systematic reviews, 9 additional papers, and multiple educational websites, but nothing that met the criteria of a patient decision aid. Patients and family members emphasized needing plain language (46 of 54, 85%), shared decision making (45 of 54, 83%), and help with family discussions (39 of 54, 72%). Additional needs included information about uncertainty, lived experience, and costs. Providers (n = 10) reported needing interventions that address misinformation (9 of 10, 90%), foster realistic expectations (9 of 10, 90%), and address mistrust in clinical trials (5 of 10, 50%). Additional needs included provider tools to support shared decision making. Both groups recommended designing a web-based patient decision aid that can be tailored (64 of 64, 100%) and delivered on a hospital website (53 of 64, 83%), and that focuses on quality of life (45 of 64, 70%) and provides step-by-step guidance (43 of 64, 67%). The study team identified best practices to meet each need, which are presented in the proposed Decision Support Design Guide. CONCLUSIONS Patients, families, and providers report multifaceted decision support needs during the chronic phase of cancer. Web-based patient decision aids are needed that provide tailored support over time, and explicitly address uncertainty, quality of life, realistic expectations, and effects on families.
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