Digital Images in Academic Plastic Surgery: A Novel and Secure Methodology for Use in Clinical Practice and Research.

BACKGROUND: Digital photographs have become an integral part in plastic and reconstructive surgery. They are significant in clinical research and outcome evaluation. There is a need for effective and secure methods to store, search, and retrieve those photographs. We developed a Health Insurance Portability and Accountability Act compliant searchable database to archive and index clinical information for clinical and research purposes. METHODS: At our craniofacial clinic, digital media (2-D, 3-D, and 4-D photographs) are obtained on a regular basis to evaluate and document treatment outcomes. In addition, patients are asked to enroll in our institutional review board (IRB)-approved imaging database. Daily, we link all digital photographs to the patient encounter through EPIC's Media Manager. This allows us to automatically identify and extract new digital media, patient demographics, diagnosis codes, relevant providers, and the text of the clinic notes to our digital database. To search our extensive database, we employed the VIEW search engine. RESULTS: To date, our database contains more than 277 000 images of 11 000 patients where more than 1900 patients are enrolled in the IRB study. This search engine allows full-text search with query response time between 2 and 5 seconds. The search engine displays the returned through a web page interface, which includes image thumbnails and the relevant part of the clinic note. In addition, a patient-specific chart allows the user to examine all patient notes and photographs. CONCLUSION: Our solution allows providers and researchers to retrieve all digital media securely and efficiently.

Osteosarcoma Explorer: A Data Commons With Clinical, Genomic, Protein, and Tissue Imaging Data for Osteosarcoma Research.

PURPOSE: Osteosarcoma research advancement requires enhanced data integration across different modalities and sources. Current osteosarcoma research, encompassing clinical, genomic, protein, and tissue imaging data, is hindered by the siloed landscape of data generation and storage. MATERIALS AND METHODS: Clinical, molecular profiling, and tissue imaging data for 573 patients with pediatric osteosarcoma were collected from four public and institutional sources. A common data model incorporating standardized terminology was created to facilitate the transformation, integration, and load of source data into a relational database. On the basis of this database, a data commons accompanied by a user-friendly web portal was developed, enabling various data exploration and analytics functions. RESULTS: The Osteosarcoma Explorer (OSE) was released to the public in 2021. Leveraging a comprehensive and harmonized data set on the backend, the OSE offers a wide range of functions, including Cohort Discovery, Patient Dashboard, Image Visualization, and Online Analysis. Since its initial release, the OSE has experienced an increasing utilization by the osteosarcoma research community and provided solid, continuous user support. To our knowledge, the OSE is the largest (N = 573) and most comprehensive research data commons for pediatric osteosarcoma, a rare disease. This project demonstrates an effective framework for data integration and data commons development that can be readily applied to other projects sharing similar goals. CONCLUSION: The OSE offers an online exploration and analysis platform for integrated clinical, molecular profiling, and tissue imaging data of osteosarcoma. Its underlying data model, database, and web framework support continuous expansion onto new data modalities and sources.

Effects of the electronic health record on job satisfaction of academic pediatric faculty.

OBJECTIVE(S): To evaluate the association of Electronic Health Record (EHR) skills and available support with job satisfaction for pediatric faculty at an academic institution. To identify key opportunities for improvement. STUDY DESIGN: Cross-sectional study of pediatric academic faculty physicians using a REDCap survey to inquire about faculty EHR skills, support services, and associations between EHR workflow and job satisfaction. Results were analyzed using bivariate testing. RESULTS: The majority of respondents (n = 127, response rate 37%), rated the effect of EHR workflow on job satisfaction as neutral (36%) or negative (44%). Users with more EHR skills were more likely to indicate a positive effect of the EHR on overall job satisfaction (p = 0.019). 7% of respondents had none of the EHR skills queried and few felt that initial training (35%) or the Information Technology department (26%) were useful in acquiring skills. Two similar divisions, one with three and one without Physician Builders (providers with specialized training in EHR personalization), had statistically significant different EHR satisfaction ratings (p = 0.0012). CONCLUSIONS: Most faculty indicated a negative/neutral effect of the EHR on their overall job satisfaction. Users who indicated more EHR skills had a higher satisfaction rating. Existing training and support were not helpful to users. The division with the most Physician Builders ranked highest in satisfaction. We speculate that 1) adding EHR skills could increase overall job satisfaction and 2) adding Physician Builder resources could increase skills and satisfaction.

Harnessing the Electronic Health Record and Computerized Provider Order Entry Data for Resource Management During the COVID-19 Pandemic: Development of a Decision Tree.

BACKGROUND: The COVID-19 pandemic has resulted in shortages of diagnostic tests, personal protective equipment, hospital beds, and other critical resources. OBJECTIVE: We sought to improve the management of scarce resources by leveraging electronic health record (EHR) functionality, computerized provider order entry, clinical decision support (CDS), and data analytics. METHODS: Due to the complex eligibility criteria for COVID-19 tests and the EHR implementation-related challenges of ordering these tests, care providers have faced obstacles in selecting the appropriate test modality. As test choice is dependent upon specific patient criteria, we built a decision tree within the EHR to automate the test selection process by using a branching series of questions that linked clinical criteria to the appropriate SARS-CoV-2 test and triggered an EHR flag for patients who met our institutional persons under investigation criteria. RESULTS: The percentage of tests that had to be canceled and reordered due to errors in selecting the correct testing modality was 3.8% (23/608) before CDS implementation and 1% (262/26,643) after CDS implementation (P<.001). Patients for whom multiple tests were ordered during a 24-hour period accounted for 0.8% (5/608) and 0.3% (76/26,643) of pre- and post-CDS implementation orders, respectively (P=.03). Nasopharyngeal molecular assay results were positive in 3.4% (826/24,170) of patients who were classified as asymptomatic and 10.9% (1421/13,074) of symptomatic patients (P<.001). Positive tests were more frequent among asymptomatic patients with a history of exposure to COVID-19 (36/283, 12.7%) than among asymptomatic patients without such a history (790/23,887, 3.3%; P<.001). CONCLUSIONS: The leveraging of EHRs and our CDS algorithm resulted in a decreased incidence of order entry errors and the appropriate flagging of persons under investigation. These interventions optimized reagent and personal protective equipment usage. Data regarding symptoms and COVID-19 exposure status that were collected by using the decision tree correlated with the likelihood of positive test results, suggesting that clinicians appropriately used the questions in the decision tree algorithm.

Determining pediatric hypertension criteria: concordance between observed physician methods and guideline-recommended methods.

OBJECTIVE: To determine and evaluate the accuracy of methods physicians use to detect diagnostic criteria for pediatric hypertension [hypertensive blood pressures (BPs) on three or more occasions] in electronic health records (EHRs). METHODS: Methods used by pediatric-trained physicians (n = 12) to detect diagnostic criteria for hypertension in a simulation using a child's EHR data were directly observed, timed, and evaluated for accuracy. All physicians were given the same information regarding diagnostic criteria to eliminate knowledge gaps. Then, computer modeling and EHR data from 41 654 3-18-year-olds were used to simulate and compare the accuracy of detecting hypertension criteria using an observed-shorthand method vs. the guideline-recommended/gold-standard method. RESULTS: No physician used the guideline-recommended method of determining multiple time-of-care hypertension thresholds for child age/height at the time of each BP measure. One physician estimated the child's BP diagnosis without computing thresholds; 11 of 12 physicians determined the child's hypertension threshold from age/height data at the time of a current visit and applied/imputed this threshold to BP measured at all visits (current-visit threshold used to assess historical-visit BPs) to detect three separate BP elevations. Physicians took 2.3 min (95% confidence interval, 1.5-3.0) to declare a diagnosis. Sensitivity was 83.1% when applying the current-visit threshold to detect the guideline-recommended-BP-threshold diagnosis using EHR data. Specificity and positive-predictive/negative-predictive values ranged from 98.5 to 99.9%. CONCLUSION: Physicians applied a shorthand method to evaluate pediatric BPs. Computer-simulated comparison of the shorthand and guideline methods using clinical data suggest the shorthand method could yield an inaccurate impression of a child's BP history in 17% of pediatric ambulatory visits.