Background Due to the increasing use of shared decision-making, patients with esophagogastric cancer play an increasingly important role in the decision-making process. To be able to make well-informed decisions, patients need to be adequately informed about treatment options and their outcomes, namely survival, side effects or complications, and health-related quality of life. Web-based tools and training programs can aid physicians in this complex task. However, to date, none of these instruments are available for use in informing patients with esophagogastric cancer about treatment outcomes. Objective This study aims to develop and evaluate the feasibility of using a web-based prediction tool and supporting communication skills training to improve how physicians inform patients with esophagogastric cancer about treatment outcomes. By improving the provision of treatment outcome information, we aim to stimulate the use of information that is evidence-based, precise, and personalized to patient and tumor characteristics and is communicated in a way that is tailored to individual information needs. Methods We designed a web-based, physician-assisted prediction tool—Source—to be used during consultations by using an iterative, user-centered approach. The accompanying communication skills training was developed based on specific learning objectives, literature, and expert opinions. The Source tool was tested in several rounds—a face-to-face focus group with 6 patients and survivors, semistructured interviews with 5 patients, think-aloud sessions with 3 medical oncologists, and interviews with 6 field experts. In a final pilot study, the Source tool and training were tested as a combined intervention by 5 medical oncology fellows and 3 esophagogastric outpatients. Results The Source tool contains personalized prediction models and data from meta-analyses regarding survival, treatment side effects and complications, and health-related quality of life. The treatment outcomes were visualized in a patient-friendly manner by using pictographs and bar and line graphs. The communication skills training consisted of blended learning for clinicians comprising e-learning and 2 face-to-face sessions. Adjustments to improve both training and the Source tool were made according to feedback from all testing rounds. Conclusions The Source tool and training could play an important role in informing patients with esophagogastric cancer about treatment outcomes in an evidence-based, precise, personalized, and tailored manner. The preliminary evaluation results are promising and provide valuable input for the further development and testing of both elements. However, the remaining uncertainty about treatment outcomes in patients and established habits in doctors, in addition to the varying trust in the prediction models, might influence the effectiveness of the tool and training in daily practice. We are currently conducting a multicenter clinical trial to investigate the impact that the combined tool and training have on the provision of information in the context of treatment decision-making.

Background Electronic health record (EHR) system users devise workarounds to cope with mismatches between workflows designed in the EHR and preferred workflows in practice. Although workarounds appear beneficial at first sight, they frequently jeopardize patient safety, the quality of care, and the efficiency of care. Objective This review aims to aid in identifying, analyzing, and resolving EHR workarounds; the Sociotechnical EHR Workaround Analysis (SEWA) framework was published in 2019. Although the framework was based on a large case study, the framework still required theoretical validation, refinement, and enrichment. Methods A scoping literature review was performed on studies related to EHR workarounds published between 2010 and 2021 in the MEDLINE, Embase, CINAHL, Cochrane, or IEEE databases. A total of 737 studies were retrieved, of which 62 (8.4%) were included in the final analysis. Using an analytic framework, the included studies were investigated to uncover the rationales that EHR users have for workarounds, attributes characterizing workarounds, possible scopes, and types of perceived impacts of workarounds. Results The SEWA framework was theoretically validated and extended based on the scoping review. Extensive support for the pre-existing rationales, attributes, possible scopes, and types of impact was found in the included studies. Moreover, 7 new rationales, 4 new attributes, and 3 new types of impact were incorporated. Similarly, the descriptions of multiple pre-existing rationales for workarounds were refined to describe each rationale more accurately. Conclusions SEWA is now grounded in the existing body of peer-reviewed empirical evidence on EHR workarounds and, as such, provides a theoretically validated and more complete synthesis of EHR workaround rationales, attributes, possible scopes, and types of impact. The revised SEWA framework can aid researchers and practitioners in a wider range of health care settings to identify, analyze, and resolve workarounds. This will improve user-centered EHR design and redesign, ultimately leading to improved patient safety, quality of care, and efficiency of care.

BACKGROUND Electronic health record system (EHR) users devise workarounds to cope with mismatches between workflows designed in the EHR and preferred workflows in practice. Although workarounds appear beneficial at first sight, they frequently jeopardize patient safety, quality of care, and efficiency of care. OBJECTIVE To aid in identifying, analyzing, and resolving EHR workarounds, a sociotechnical EHR workaround analysis framework (SEWA) was published in 2019. Although the framework was based on a large case study, the framework still required theoretical validation, refinement, and enrichment. METHODS A scoping literature review was performed on studies related to EHR workarounds published between 2010-2021 in MEDLINE, EMBASE, CINAHL, Cochrane or IEEE databases. 737 studies were retrieved, of which 62 were included in the final analysis. Using an analytic frame, the included studies were investigated to uncover rationales EHR users have for workarounds, attributes characterizing workarounds, possible scopes, and types of perceived impact of workarounds. RESULTS The SEWA framework was validated and refined based on the scoping review. Extensive support for the preexisting rationales, attributes, possible scopes, and types of impact was found in the included studies. Moreover, 7 new rationales, 4 new attributes, and 3 new types of impact were incorporated. Similarly, the descriptions of multiple preexisting rationales for workarounds were refined to describe each rationale more accurately. CONCLUSIONS SEWA is now grounded in the existing body of peer-reviewed empirical evidence on EHR workarounds and as such provides a validated and more complete synthesis on EHR workaround rationales, attributes, possible scopes, and types of impact. Moreover, SEWA is likely now also applicable in settings other than academic hospitals. The revised SEWA framework can aid researchers and practitioners in a wider range of healthcare settings to identify, analyze, and resolve workarounds. This to improve user centered EHR (re)design, ultimately leading to improved patient safety, quality of care, and efficiency of care.

BACKGROUND With the increasing use of shared decision making (SDM), esophagogastric cancer patients play a larger and more important role in the decision-making process. To be able to make well-informed decisions, patients need to be adequately informed about treatment options and their outcomes, namely survival, side effects or complications, and health related quality of life (HRQoL). Online tools and training programs can aid physicians in this complex task, however to date none of these are available for use in informing esophagogastric cancer patients about treatment outcomes. OBJECTIVE This study aims to develop and evaluate the feasibility of an online prediction tool and a supporting communication skills training to improve the manner in which physicians inform esophagogastric cancer patients on treatment outcomes. With improving the provision of treatment outcome information, we aim for information that is evidence-based, precise, and personalized to patient and tumor characteristics which is communicated in a way tailored to the individual information needs. METHODS An online prediction tool to be used during the consultation, named the Source tool, was designed using an iterative, user-centered approach. An accompanying communication skills training was developed based on specified learning objectives, literature and expert opinions. The Source tool was tested in several rounds: 1) a focus group (6 patients and survivors), 2) semi-structured patient interviews (5 patients), 3) think-aloud sessions (3 medical oncologists) and 4) expert interviews (6 field experts). In a final pilot study, the Source tool and training were tested as a combined intervention using 5 medical oncology fellows and 3 esophagogastric outpatients. RESULTS The Source tool contained personalized prediction models and data from meta-analyses concerning survival, treatment side effects/complications and quality of life. The treatment outcomes were visualized in a patient-friendly manner using pictographs, and bar and line graphs. The communication skills training consisted of a blended learning for clinicians comprised of an e-learning and two face-to-face sessions. Adjustments to improve both training and tool were made according to feedback from all testing rounds. CONCLUSIONS The Source tool and training could play an important role in informing esophagogastric patients in an evidence-based, precise, personalized and tailored manner about treatment outcomes. Preliminary evaluation results are promising and provide valuable input for further development and testing of both elements. However, patient’s remaining uncertainties and doctors’ old habits and variating trust in the prediction models might influence the effect of the tool and training on daily practice. To investigate the impact of the combined tool and training on information provision in the context of treatment decision-making, we are currently conducting a multicenter clinical trial (SOURCE, NCT04232735).