This commentary introduces the Patient-Centered Clinical Decision Support (PCCDS) Learning Network, which is collaborating with AcademyHealth to publish “Better Decisions Together” as part of eGEMs. Patient-centered clinical decision support (CDS) is an important vehicle to address broad issues in the U.S. health care system regarding quality and safety while also achieving better outcomes and better patient and provider satisfaction. Defined as CDS that supports individual patients and their care givers and/or care teams in health-related decisions and actions, PCCDS is an important step forward in advancing endeavors to move patient-centered care forward. The PCCDS Learning Network has developed a framework, referred to as the Analytic Framework for Action (AFA), to organize thinking and activities around PCCDS. A wide array of activities the PCCDS Learning Network is engaging in to inform and connect stakeholders is discussed.

The Medipix3 x-ray imaging detector has been characterized using the MARS camera. This x-ray camera comprises custom built readout electronics and software libraries designed for the Medipix family of detectors. The performance of the Medipix3 and MARS camera system is being studied prior to use in real-world applications such as the recently developed MARS-CT3 spectroscopic micro-CT scanner. We present the results of characterization measurements, describe methods for optimizing performance and give examples of spectroscopic images acquired with Medipix3 and the MARS camera system.A limited number of operating modes of the Medipix3 chip have been characterized and singlepixel mode has been found to give acceptable performance in terms of energy response, image quality and stability over time. Spectroscopic performance is significantly better in charge-summing mode than single-pixel mode however image quality and stability over time are compromised. There are more modes of operation to be tested and further work is required to optimize the performance of the chip.

Background Partnerships among patients, families, caregivers, and clinicians are critical to helping patients lead their best lives given their specific genetics, conditions, circumstances, and the environments in which they live, work, and play. These partnerships extend to the development of health information technology, including clinical decision support (CDS). Design of these technologies, however, often occurs without a profound understanding of the true needs, wants, and concerns of patients and family members. Patient perspective is important not only for patient-facing applications but for provider-facing applications, especially those intended to support shared decision-making. Objectives Our objective is to describe models for effectively engaging patients and caregivers during CDS development and implementation and to inspire CDS developers to partner with patients and caregivers to improve the potential impact of CDS. Methods This article serves as a case study of how two patient activists successfully implemented models for engaging patients and caregivers in a federal program designed to increase the uptake of research evidence into clinical practice through CDS. Models included virtual focus groups, social media, agile software development, and attention to privacy and cybersecurity. Results Impact on the federal program has been substantial and has resulted in improved CDS training materials, new prototype CDS applications, prioritization of new functionality and features, and increased engagement of patient and caregiver communities in ongoing projects. Among these opportunities is a group of developers and patient activists dedicated and committed to exploring strategic and operational opportunities to codesign CDS applications. Conclusion Codesign and implementation of CDS can occur as a partnership among developers, implementers, patients, cybersecurity and privacy activists, and caregivers. Several approaches are viable, and an iterative process is most promising. Additional work is needed to investigate scalability of the approaches explored by this case study and to identify measures of meaningful inclusion of patients/caregivers in CDS projects.

Background. Most people with multiple sclerosis (MS) want to be involved in medical decision making about disease-modifying therapies (DMTs), but new approaches are needed to overcome barriers to participation. Objectives. We sought to develop a shared decision-making (SDM) tool for MS DMTs, evaluate patient and provider responses to the tool, and address challenges encountered during development to guide a future trial. Methods. We created a patient-centered design process informed by image theory to develop the MS-SUPPORT SDM tool. Development included semistructured interviews and alpha and beta testing with MS patients and providers. Beta testing assessed dissemination and clinical integration strategies, decision-making processes, communication, and adherence. Patients evaluated the tool before and after a clinic visit. Results. MS-SUPPORT combines self-assessment with tailored feedback to help patients identify their treatment goals and preferences, correct misperceptions, frame decisions, and promote adherence. MS-SUPPORT generates a personal summary of their responses that patients can share with their provider to facilitate communication. Alpha testing (14 patients) identified areas needing improvement, resulting in reorganization and shortening of the tool. MS-SUPPORT was highly rated in beta testing (15 patients, 4 providers) on patient-provider communication, patient preparation, adherence, and other endpoints. Dissemination through both patient and provider networks appeared feasible. All patient testers wanted to share the summary report with their provider, but only 60% did. Limitations. Small sample size, no comparison group. Conclusions. The development process resulted in a patient-centered SDM tool for MS that may facilitate patient involvement in decision making, help providers understand their patients’ preferences, and improve adherence, though further testing is needed. Beta testing in real-world conditions was critical to prepare the tool for future testing and inform the design of future studies.

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