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Objectives: To assess the use of a co-designed patient-reported outcome (PRO) clinical dashboard and estimate its impact on shared decision-making (SDM) and symptomatology in adults with advanced cancer or chronic kidney disease (CKD)., Materials and Methods: We developed a clinical PRO dashboard within the Northwestern Medicine Patient-Reported Outcomes system, enhanced through co-design involving 20 diverse constituents. Using a single-group, pretest-posttest design, we evaluated the dashboard's use among patients with advanced cancer or CKD between June 2020 and January 2022. Eligible patients had a visit with a participating clinician, completed at least two dashboard-eligible visits, and consented to follow-up surveys. PROs were collected 72 h prior to visits, including measures for chronic condition management self-efficacy, health-related quality of life (PROMIS measures), and SDM (collaboRATE). Responses were integrated into the EHR dashboard and accessible to clinicians and patients., Results: We recruited 157 participants: 66 with advanced cancer and 91 with CKD. There were significant improvements in SDM from baseline, as assessed by collaboRATE scores. The proportion of participants reporting the highest level of SDM on every collaboRATE item increased by 15 percentage points from baseline to 3 months, and 17 points between baseline and 6-month follow-up. Additionally, there was a clinically meaningful decrease in anxiety levels over study period (T-score baseline: 53; 3-month: 52; 6-month: 50; P < .001), with a standardized response mean (SRM) of -0.38 at 6 months., Discussion: PRO clinical dashboards, developed and shared with patients, may enhance SDM and reduce anxiety among patients with advanced cancer and CKD., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Objectives: Patient-reported outcomes (PROs) describe a patient's unique experiences with disease or treatment, yet effective use of this information during clinical encounters remains challenging. This project sought to build a PRO based dashboard within the electronic health record (EHR), prioritizing interpretability and utility of PROs for clinical decision-making., Materials and Methods: Codesign principles were used to define the goal, features, and visualization of the data elements on the dashboard. Codesign sessions occurred between February 2019 and May 2020 and involved a diverse group of stakeholders. Pilot evaluation of dashboard usability was performed with patients and clinicians not involved in the codesign process through qualitative interviews and the Systems Usability Scale., Results: The dashboard was placed into a single tab in the EHR and included select PROM scores, clinical data elements, and goals of care questions. Real-time data analytics and enhanced visualization of data was necessary for the dashboard to provide meaningful feedback to clinicians and patients for decision-making during clinic visits. During soft launch, the dashboard demonstrated "good" usability in patients and clinicians at 3 and 6 months (mean total SUS score >70)., Discussion: The current dashboard had good usability and made PRO scores more clinically understandable to patients and clinicians. This paper highlights the development, necessary data elements, and workflow considerations to implement this dashboard at an academic cancer center., Conclusion: As the use of PROs in clinical care is increasing, patient- and clinician-centered tools are needed to ensure that this information is used in meaningful ways., Competing Interests: None declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Background: Shared decision making (SDM) is the process by which patients and clinicians exchange information and preferences to come to joint healthcare decisions. Clinical dashboards can support SDM by collecting, distilling, and presenting critical information, such as patient-reported outcomes (PROs), to be shared at points of care and in between appointments. We describe the implementation strategies and outcomes of a multistakeholder collaborative process known as "co-design" to develop a PRO-informed clinical dashboard to support SDM for patients with advanced cancer or chronic kidney disease (CKD). Methods: Across 14 sessions, two multidisciplinary teams comprising patients, care partners, clinicians, and other stakeholders iteratively co-designed an SDM dashboard for either advanced cancer (N = 25) or CKD (N = 24). Eligible patients, care partners, and frontline clinicians were identified by six physician champions. The co-design process included four key steps: (1) define "the problem", (2) establish context of use, (3) build a consensus on design, and (4) define and test specifications. We also evaluated our success in implementing the co-design strategy using measures of fidelity, acceptability, adoption, feasibility, and effectiveness which were collected throughout the process. Results: Mean ( M ) scores across implementation measures of the co-design process were high, including observer-rated fidelity and adoption of co-design practices ( M = 19.1 on a 7-21 scale, N = 36 ratings across 9 sessions), as well as acceptability based on the perceived degree of SDM that occurred during the co-design process ( M = 10.4 on a 0 to 12 adapted collaboRATE scale). Capturing the feasibility and adoption of convening multistakeholder co-design teams, min-max normalized scores (ranging from 0 to 1) of stakeholder representation demonstrated that, on average, 95% of stakeholder types were represented for cancer sessions ( M = 0.95) and 85% for CKD sessions ( M = 0.85). The co-design process was rated as either "fully" or "partially" effective by 100% of respondents, in creating a dashboard that met its intended objective. Conclusions: A co-design process was successfully implemented to develop SDM clinical dashboards for advanced cancer and CKD care. We discuss key strategies and learnings from this process that may aid others in the development and uptake of patient-centered healthcare innovations.

Background: Patient-reported outcomes-symptoms, treatment side effects, and health-related quality of life-are important to consider in chronic illness care. The increasing availability of health IT to collect patient-reported outcomes and integrate results within the electronic health record provides an unprecedented opportunity to support patients' symptom monitoring, shared decision-making, and effective use of the health care system., Objective: The objectives of this study are to co-design a dashboard that displays patient-reported outcomes along with other clinical data (eg, laboratory tests, medications, and appointments) within an electronic health record and conduct a longitudinal demonstration trial to evaluate whether the dashboard is associated with improved shared decision-making and disease management outcomes., Methods: Co-design teams comprising study investigators, patients with advanced cancer or chronic kidney disease, their care partners, and their clinicians will collaborate to develop the dashboard. Investigators will work with clinic staff to implement the co-designed dashboard for clinical testing during a demonstration trial. The primary outcome of the demonstration trial is whether the quality of shared decision-making increases from baseline to the 3-month follow-up. Secondary outcomes include longitudinal changes in satisfaction with care, self-efficacy in managing treatments and symptoms, health-related quality of life, and use of costly and potentially avoidable health care services. Implementation outcomes (ie, fidelity, appropriateness, acceptability, feasibility, reach, adoption, and sustainability) during the co-design process and demonstration trial will also be collected and summarized., Results: The dashboard co-design process was completed in May 2020, and data collection for the demonstration trial is anticipated to be completed by the end of July 2022. The results will be disseminated in at least one manuscript per study objective., Conclusions: This protocol combines stakeholder engagement, health care coproduction frameworks, and health IT to develop a clinically feasible model of person-centered care delivery. The results will inform our current understanding of how best to integrate patient-reported outcome measures into clinical workflows to improve outcomes and reduce the burden of chronic disease on patients and health care systems., International Registered Report Identifier (irrid): DERR1-10.2196/38461., (©Laura M Perry, Victoria Morken, John D Peipert, Betina Yanez, Sofia F Garcia, Cynthia Barnard, Lisa R Hirschhorn, Jeffrey A Linder, Neil Jordan, Ronald T Ackermann, Alexandra Harris, Sheetal Kircher, Nisha Mohindra, Vikram Aggarwal, Rebecca Frazier, Ava Coughlin, Katy Bedjeti, Melissa Weitzel, Eugene C Nelson, Glyn Elwyn, Aricca D Van Citters, Mary O'Connor, David Cella. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 21.09.2022.)

Background: Commercially available pedometers have been used as tools to measure endpoints in studies evaluating physical activity promotion programs. However, their accuracy in patients recovering from COPD exacerbations is unknown. The objectives of this study were to 1) assess the relative accuracy of different commercially available pedometers in healthy volunteers and 2) evaluate the accuracy of the top-performing commercially available pedometer in patients recovering from COPD exacerbations following hospital discharge., Methods: Twelve healthy volunteers wore 2 pedometers, 2 smartphones with pedometer apps and an accelerometer for 15 minutes of indoor activity. The top-performing device in healthy volunteers was evaluated in 4 patients recovering from COPD exacerbations following hospital discharge during 6 minutes of walking performed at home. Bland-Altman plots were employed to evaluate accuracy of each device compared with direct observation (the reference standard)., Results: In healthy volunteers, the mean percent error compared to direct observation of the various devices ranged from -49% to +1%. The mean percent error [95% confidence interval (CI)] of the top-performing device in healthy volunteers, the Fitbit Zip ® , was +1% [-33 to +35%], significantly lower than that of the accelerometer (-13% [-56 to +29%], p =0.01). The mean percent error [95% CI] for the Fitbit Zip ® in patients recovering from COPD exacerbations was -3% [-7 to +12%]., Conclusions: The accuracy of commercially available pedometers in healthy volunteers is highly variable. The top-performing pedometer in our study, the Fitbit Zip, ® accurately measures step counts in both healthy volunteers and patients recovering from COPD exacerbations.