Pier, Jeff

11128 Background: To improve documentation quality in Medical Onc outpatient clinics, a standardized template was created. In this template we embedded: 1. An Epic SmartForm to collect structured data (SD) about patient, disease, and response status at each encounter. Minimal Common Oncology Data Elements (mCODE) compatible SD elements were used to enhance interoperability. 2. Several clinically impactful quality metrics (QM) selected based on the Quality Onc Practice Initiative (QOPI) guidelines. In this analysis, we aim to assess how template use impacted documentation quality. Methods: 113,376 outpatient encounters occurred between 01/2018 – 12/2022 (41 providers: 35 physicians, 6 APPs). The template go live was 3/19/2019. 2,520 randomly selected encounters were manually reviewed. Distinct documentation of 8 items served as QMs (Table). Of note, using the template was voluntary and data entry in the embedded form is not mandated. Documentation of each QM was compared between notes authored with/without template. For each note, a completeness score was calculated based on total number of QMs present/note. Categorical comparisons were made using chi-squared or Fisher’s exact tests. Numerical/continuous values were summarized using means and standard deviations. A template “user” was defined as a provider using the template in >10% of encounters after go live. This QI project was exempted by IRB. Results: 154/2520 encounters were excluded after manual review (visits not for solid tumor malignancy). The template was used in 38.7% (917/2366) of the reviewed notes. Cancer diagnosis was documented in >99.8% of notes regardless of template use. Template use was associated with increased documentation of 7 QMs (Table). Documentation overall completeness improved from 62% to 90% with a very large effect size (Table). Template use positively correlated with female gender and fewer years since last training (p<0.001). In the subgroup of notes written by “users” (21 physicians, 4 APPs), individual QM and overall completeness scores improved with template use (p<0.001). Conclusions: Template use profoundly improved QM documentation (statistically significant and clinically meaningful) by Onc clinic providers. This strategy enhances mCODE compatible structured data collection and semantic interoperability between systems, strengthening the available real-world data (RWD) in EHR. [Table: see text]

PURPOSE Structured data elements within electronic health records are health-related information that can be entered, stored, and extracted in an organized manner at later time points. Tracking outcomes for cancer survivors is also enabled by structured data. We sought to increase structured data capture within oncology practices at multiple sites sharing the same electronic health records. METHODS Applying engineering approaches and the Plan-Do-Study-Act cycle, we launched dual quality improvement initiatives to ensure that a malignant diagnosis and stage were captured as structured data. Intervention: Close Visit Validation (CVV) requires providers to satisfy certain criteria before closing ambulatory encounters. CVV may be used to track open clinical encounters and chart delinquencies to encourage optimal clinical workflows. We added two cancer-specific required criteria at the time of closing encounters in oncology clinics: (1) the presence of at least one malignant diagnosis on the Problem List and (2) staging all the malignant diagnoses on the Problem List when appropriate. RESULTS Six months before the CVV implementation, the percentage of encounters with a malignant diagnosis on the Problem List at the time of the encounter was 65%, whereas the percentage of encounters with a staged diagnosis was 32%. Three months after cancer-specific CVV implementation, the percentages were 85% and 75%, respectively. Rates had increased to 90% and 88% more than 2 years after implementation. CONCLUSION Oncologist performance improved after the implementation of cancer-specific CVV criteria, with persistently high percentages of relevant malignant diagnoses and cancer stage structured data capture 2 years after the intervention.