The implementation of a multidisciplinary, electronic health record embedded care pathway to improve structured data recording and decrease electronic health record burden.

INTRODUCTION: Theoretically, the added value of electronic health records (EHRs) is extensive. Reusable data capture in EHRs could lead to major improvements in quality measurement, scientific research, and decision support. To achieve these goals, structured and standardized recording of healthcare data is a prerequisite. However, time spent on EHRs by physicians is already high. This study evaluated the effect of implementing an EHR embedded care pathway with structured data recording on the EHR burden of physicians. MATERIALS AND METHODS: Before and six months after implementation, consultations were recorded and analyzed with video-analytic software. Main outcome measures were time spent on specific tasks within the EHR, total consultation duration, and usability indicators such as required mouse clicks and keystrokes. Additionally, a validated questionnaire was completed twice to evaluate changes in physician perception of EHR system factors and documentation process factors. RESULTS: Total EHR time in initial oncology consultations was significantly reduced by 3.7 min, a 27 % decrease. In contrast, although a decrease of 13 % in consultation duration was observed, no significant effect on EHR time was found in follow-up consultations. Additionally, perceptions of physicians regarding the EHR and documentation improved significantly. DISCUSSION: Our results have shown that it is possible to achieve structured data capture while simultaneously reducing the EHR burden, which is a decisive factor in end-user acceptance of documentation systems. Proper alignment of structured documentation with workflows is critical for success. CONCLUSION: Implementing an EHR embedded care pathway with structured documentation led to decreased EHR burden.

Development and validation of automated electronic health record data reuse for a multidisciplinary quality dashboard.

Objective: To describe the development and validation of automated electronic health record data reuse for a multidisciplinary quality dashboard. Materials and methods: Comparative study analyzing a manually extracted and an automatically extracted dataset with 262 patients treated for HNC cancer in a tertiary oncology center in the Netherlands in 2020. The primary outcome measures were the percentage of agreement on data elements required for calculating quality indicators and the difference between indicators results calculated using manually collected and indicators that used automatically extracted data. Results: The results of this study demonstrate high agreement between manual and automatically collected variables, reaching up to 99.0% agreement. However, some variables demonstrate lower levels of agreement, with one variable showing only a 20.0% agreement rate. The indicator results obtained through manual collection and automatic extraction show high agreement in most cases, with discrepancy rates ranging from 0.3% to 3.5%. One indicator is identified as a negative outlier, with a discrepancy rate of nearly 25%. Conclusions: This study shows that it is possible to use routinely collected structured data to reliably measure the quality of care in real-time, which could render manual data collection for quality measurement obsolete. To achieve reliable data reuse, it is important that relevant data is recorded as structured data during the care process. Furthermore, the results also imply that data validation is conditional to development of a reliable dashboard.

Evaluation of a remote monitoring app in head and neck cancer follow-up care.

BACKGROUND: A remote monitoring app was developed for head and neck cancer (HNC) follow-up during the SARS-CoV-2 pandemic. This mixed-methods study provides insight in the usability and patients' experiences with the app to develop recommendations for future use. METHODS: Patients were invited to participate if they were treated for HNC, used the app at least once and were in clinical follow-up. A subset was selected for semi-structured interviews through purposive sampling considering gender and age. This study was conducted between September 2021-May 2022 at a Dutch university medical center. RESULTS: 135 of the 216 invited patients completed the questionnaire, resulting in a total mHealth usability score of 4.72 (± 1.13) out of 7. Thirteen semi-structured interviews revealed 12 barriers and 11 facilitators. Most of them occurred at the level of the app itself. For example, patients received no feedback when all their answers were normal. The app made patients feel more responsible over their follow-up, but could not fulfill the need for personal contact with the attending physician. Patients felt that the app could replace some of the outpatient follow-up visits. CONCLUSIONS: Our app is user-friendly, makes patients feel more in control and remote monitoring can reduce the frequency of outpatient follow-up visits. The barriers that emerged must be resolved before the app can be used in regular HNC follow-up. Future studies should investigate the appropriate ratio of remote monitoring to outpatient follow-up visits and the cost-effectiveness of remote monitoring in oncology care on a larger scale.

Quantifying the Electronic Health Record Burden in Head and Neck Cancer Care.

BACKGROUND: Although the main task of health care providers is to provide patient care, studies show that increasing amounts of time are spent on documentation. OBJECTIVE: To quantify the time and effort spent on the electronic health record (EHR) in head and neck cancer care. METHODS: Cross-sectional time-motion study. Primary outcomes were the percentages of time spent on the EHR and the three main tasks (chart review, input, placing orders), number of mouse events, and keystrokes per consultation. Secondary outcome measures were perceptions of health care providers regarding EHR documentation and satisfaction. RESULTS: In total, 44.0% of initial oncological consultation (IOC) duration and 30.7% of follow-up consultation (FUC) duration are spent on EHR tasks. During 80.0% of an IOC and 67.9% of a FUC, the patient and provider were actively communicating. Providers required 593 mouse events and 1,664 keystrokes per IOC and 140 mouse events and 597 keystrokes per FUC, indicating almost 13 mouse clicks and close to 40 keystrokes for every minute of consultation time. Less than a quarter of providers indicated that there is enough time for documentation. CONCLUSION: This study quantifies the widespread concern of high documentation burden for health care providers in oncology, which has been related to burnout and a decrease of patient-clinician interaction. Despite excessive time and effort spent on the EHR, health care providers still felt this was insufficient for proper documentation. However, the need for accurate and complete documentation is high, as reuse of information becomes increasingly important. The challenge is to decrease the documentation burden while increasing the quality of EHR data.

The Impact of Structured and Standardized Documentation on Documentation Quality; a Multicenter, Retrospective Study.

The reuse of healthcare data for various purposes will become increasingly important in the future. To enable the reuse of clinical data, structured and standardized documentation is conditional. However, the primary purpose of clinical documentation is to support high-quality patient care. Therefore, this study investigated the effect of increased structured and standardized documentation on the quality of notes in the Electronic Health Record. A multicenter, retrospective design was used to assess the difference in note quality between 144 unstructured and 144 structured notes. Independent reviewers measured note quality by scoring the notes with the Qnote instrument. This instrument rates all note elements independently using and results in a grand mean score on a 0-100 scale. The mean quality score for unstructured notes was 64.35 (95% CI 61.30-67.35). Structured and standardized documentation improved the Qnote quality score to 77.2 (95% CI 74.18-80.21), a 12.8 point difference (p < 0.001). Furthermore, results showed that structured notes were significantly longer than unstructured notes. Nevertheless, structured notes were more clear and concise. Structured documentation led to a significant increase in note quality. Moreover, considering the benefits of structured data recording in terms of data reuse, implementing structured and standardized documentation into the EHR is recommended.