UNASSIGNED: Patient-monitoring software generates a large amount of data that can be reused for clinical audits and scientific research. The Observational Health Data Sciences and Informatics (OHDSI) consortium developed the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to standardize electronic health record data and promote large-scale observational and longitudinal research.
UNASSIGNED: This study aimed to transform primary care data into the OMOP CDM format.
UNASSIGNED: We extracted primary care data from electronic health records at a multidisciplinary health center in Wattrelos, France. We performed structural mapping between the design of our local primary care database and the OMOP CDM tables and fields. Local French vocabularies concepts were mapped to OHDSI standard vocabularies. To validate the implementation of primary care data into the OMOP CDM format, we applied a set of queries. A practical application was achieved through the development of a dashboard.
UNASSIGNED: Data from 18,395 patients were implemented into the OMOP CDM, corresponding to 592,226 consultations over a period of 20 years. A total of 18 OMOP CDM tables were implemented. A total of 17 local vocabularies were identified as being related to primary care and corresponded to patient characteristics (sex, location, year of birth, and race), units of measurement, biometric measures, laboratory test results, medical histories, and drug prescriptions. During semantic mapping, 10,221 primary care concepts were mapped to standard OHDSI concepts. Five queries were used to validate the OMOP CDM by comparing the results obtained after the completion of the transformations with the results obtained in the source software. Lastly, a prototype dashboard was developed to visualize the activity of the health center, the laboratory test results, and the drug prescription data.
UNASSIGNED: Primary care data from a French health care facility have been implemented into the OMOP CDM format. Data concerning demographics, units, measurements, and primary care consultation steps were already available in OHDSI vocabularies. Laboratory test results and drug prescription data were mapped to available vocabularies and structured in the final model. A dashboard application provided health care professionals with feedback on their practice.

BACKGROUND: Online food delivery services (OFDS) enable individuals to conveniently access foods from any deliverable location. The increased accessibility to foods may have implications on the consumption of healthful or unhealthful foods. Concerningly, previous research suggests that OFDS offer an abundance of energy-dense and nutrient-poor foods, which are heavily promoted through deals or discounts.
OBJECTIVE: In this paper, we describe the development of the DIGIFOOD dashboard to monitor the digitalization of local food environments in New South Wales, Australia, resulting from the proliferation of OFDS.
METHODS: Together with a team of data scientists, we designed a purpose-built dashboard using Microsoft Power BI. The development process involved three main stages: (1) data acquisition of food outlets via web scraping, (2) data cleaning and processing, and (3) visualization of food outlets on the dashboard. We also describe the categorization process of food outlets to characterize the healthfulness of local, online, and hybrid food environments. These categories included takeaway franchises, independent takeaways, independent restaurants and cafes, supermarkets or groceries, bakeries, alcohol retailers, convenience stores, and sandwich or salad shops.
RESULTS: To date, the DIGIFOOD dashboard has mapped 36,967 unique local food outlets (locally accessible and scraped from Google Maps) and 16,158 unique online food outlets (accessible online and scraped from Uber Eats) across New South Wales, Australia. In 2023, the market-leading OFDS operated in 1061 unique suburbs or localities in New South Wales. The Sydney-Parramatta region, a major urban area in New South Wales accounting for 28 postcodes, recorded the highest number of online food outlets (n=4221). In contrast, the Far West and Orana region, a rural area in New South Wales with only 2 postcodes, recorded the lowest number of food outlets accessible online (n=7). Urban areas appeared to have the greatest increase in total food outlets accessible via online food delivery. In both local and online food environments, it was evident that independent restaurants and cafes comprised the largest proportion of food outlets at 47.2% (17,437/36,967) and 51.8% (8369/16,158), respectively. However, compared to local food environments, the online food environment has relatively more takeaway franchises (2734/16,158, 16.9% compared to 3273/36,967, 8.9%) and independent takeaway outlets (2416/16,158, 14.9% compared to 4026/36,967, 10.9%).
CONCLUSIONS: The DIGIFOOD dashboard leverages the current rich data landscape to display and contrast the availability and healthfulness of food outlets that are locally accessible versus accessible online. The DIGIFOOD dashboard can be a useful monitoring tool for the evolving digital food environment at a regional scale and has the potential to be scaled up at a national level. Future iterations of the dashboard, including data from additional prominent OFDS, can be used by policy makers to identify high-priority areas with limited access to healthful foods both online and locally.

For time-sensitive treatment of a patient with malignant melanoma, physicians must obtain a rapid overview of the patient\'s status. This study aimed to analyze context-specific features and processes at the point of care to derive requirements for a dashboard granting more straightforward access to information. The Think-Aloud method, contextual inquiries, and interviews were performed with physicians from the Department of Dermatology at the University Hospital Essen in Germany. The user statements and observations that were obtained were grouped and categorized using an affinity diagram. Based on the derived subjects, requirements were defined, confirmed, and prioritized. The resulting affinity diagram revealed four topics of importance at the point of care. These topics are \"Identifying and Processing the Important\", a comprehensive \"Patient Record\", tasks and challenges in the \"Clinical Routine\", and interactions and experiences with the available \"Systems\". All aspects have been reflected in 135 requirements for developing context- and indication-specific patient dashboards. Our work has elucidated the most important aspects to consider when designing a dashboard that improves patient care by enabling physicians to focus on the relevant information. Furthermore, it has been demonstrated that the aspects most often mentioned are not context-specific and can be generalized to other medical contexts.

BACKGROUND: The enormous consequences of drugs include suicides, traffic accidents, and violence, affecting the individual, family, society, and country. Therefore, it is necessary to constantly identify and monitor the drug abuse rate among school-going youth. A geospatial dashboard is vital for the monitoring of drug abuse and related crime incidence in a decision support system.
OBJECTIVE: This paper mainly focuses on developing MyAsriGeo, a geospatial drug abuse risk assessment and monitoring dashboard tailored for school students. It introduces innovative functionality, seamlessly orchestrating the assessment of drug abuse usage patterns and risks using multivariate student data.
METHODS: A geospatial drug abuse dashboard for monitoring and analysis was designed and developed in this study based on agile methodology and prototyping. Using focus group and interviews, we first examined and gathered the requirements, feedback, and user approval of the MyAsriGeo dashboard. Experts and stakeholders such as the National Anti-Drugs Agency, police, the Federal Department of Town and Country Planning, school instructors, students, and researchers were among those who responded. A total of 20 specialists were involved in the requirement analysis and acceptance evaluation of the pilot and final version of the dashboard. The evaluation sought to identify various user acceptance aspects, such as ease of use and usefulness, for both the pilot and final versions, and 2 additional factors based on the Post-Study System Usability Questionnaire and Task-Technology Fit models were enlisted to assess the interface quality and dashboard sufficiency for the final version.
RESULTS: The MyAsriGeo geospatial dashboard was designed to meet the needs of all user types, as identified through a requirement gathering process. It includes several key functions, such as a geospatial map that shows the locations of high-risk areas for drug abuse, data on drug abuse among students, tools for assessing the risk of drug abuse in different areas, demographic information, and a self-problem test. It also includes the Alcohol, Smoking, and Substance Involvement Screening Test and its risk assessment to help users understand and interpret the results of student risk. The initial prototype and final version of the dashboard were evaluated by 20 experts, which revealed a significant improvement in the ease of use (P=.047) and usefulness (P=.02) factors and showed a high acceptance mean scores for ease of use (4.2), usefulness (4.46), interface quality (4.29), and sufficiency (4.13).
CONCLUSIONS: The MyAsriGeo geospatial dashboard is useful for monitoring and analyzing drug abuse among school-going youth in Malaysia. It was developed based on the needs of various stakeholders and includes a range of functions. The dashboard was evaluated by a group of experts. Overall, the MyAsriGeo geospatial dashboard is a valuable resource for helping stakeholders understand and respond to the issue of drug abuse among youth.

Objective: This article aims to describe the implementation of a new health information technology system called Health Connect that is harmonizing cancer data in the Canadian province of Newfoundland and Labrador; explain high-level technical details of this technology; provide concrete examples of how this technology is helping to improve cancer care in the province, and to discuss its future expansion and implications. Methods: We give a technical description of the Health Connect architecture, how it integrated numerous data sources into a single, scalable health information system for cancer data and highlight its artificial intelligence and analytics capacity. Results: We illustrated two practical achievements of Health Connect. First, an analytical dashboard that was used to pinpoint variations in colon cancer screening uptake in small defined geographic regions of the province; and second, a natural language processing algorithm that provided AI-assisted decision support in interpreting appropriate follow-up action based on assessments of breast mammography reports. Conclusion: Health Connect is a cutting-edge, health systems solution for harmonizing cancer screening data for practical decision-making. The long term goal is to integrate all cancer care data holdings into Health Connect to build a comprehensive health information system for cancer care in the province.

The existing surgery timetable is very simple, not user-friendly, and has very limited information. This article outlines the creation of a surgical dynamic dashboard for users, using Microsoft Power BI. The dashboard was developed based on in-depth interviews with the surgical team members to determine their requirements. The outcome of dashboard was evaluated by 5-likert scale questionnaire to measure satisfaction of all surgical team members. All team members were very satisfied with the dashboard compared to the existing surgery timetable. In addition, with the function of auto-generated analytic reports through data criteria selection on the dashboard saved time on manually generating reports. This study supports to replace the existing surgery timetable by the user-centric and real time surgical dashboard.

This paper examines the use of quality control indicator audits in healthcare services to identify potential risk issues and improve the quality of medical care. A multi-stage approach was adopted to establish audit tools. This involved creating a cloud-based assessment form using Microsoft Form, developing Power BI dashboards connected to databases, and creating a mobile application for on-the-go auditing and result retrieval. Mobile application has replaced the need to search for and print audit forms, reducing paper usage. Automated audit results are linked to Power BI dashboards, significantly reducing the time spent on manual documentation and chart analysis, saving an average of 40 minutes per audit indicator. The paper proposes that the dashboard\'s real-time and automated features assist managers in promptly identifying potential issues and taking necessary intervention and guidance measures. These findings emphasise the significance of quality control indicator audits in enhancing the quality and safety of healthcare services.

Like most organizations, The Children\'s Hospital of Philadelphia (CHOP) generates a lot of data of varying types, from clinical to staffing and operations. However, these datasets are separated, preventing effective analytics. To improve workforce management and care delivery, CHOP\'s Nursing department collaborated with the Data & Analytics team to create a dashboard-based platform for analyzing workforce metrics and patient outcomes, aiding nursing leaders in decision-making. This project involved multiple phases with contributions from Nursing, Data & Analytics, CHOP\'s Data Trust Office, and Human Resources. Key performance indicators were identified, and a variety of data sources were aggregated to provide a comprehensive view of the nursing enterprise. The resulting platform offers automated, current, and reliable analytics on various aspects, including nursing demographics, education, survey results, staffing actuals by job group, and patient and family experience data. The platform\'s usability was assessed using a modified Health Information Technology Usability Evaluation Scale survey, with a 29% response rate primarily from senior directors and managers. The findings showed high usability and satisfaction, indicating the dashboard is a valuable decision-support tool. Lessons learned include the need for analytics education for nurses and mid-managers, the inclusion of critical nursing-specific metrics (and development of the data pipelines making them possible), and the integration of multidisciplinary team metrics for comprehensive nursing analytics.

UNASSIGNED: Public sharing of de-identified biomedical data promotes collaboration between researchers and accelerates the development of disease prevention and treatment strategies. However, open-access data sharing presents challenges to researchers who need to protect the privacy of study participants, ensure that data are used appropriately, and acknowledge the inputs of all involved researchers. This article presents an approach to data sharing which addresses the above challenges by using a publicly available dashboard with de-identified, aggregated participant data from a large HIV surveillance cohort.
UNASSIGNED: Data in this study originated from the Rakai Community Cohort Study (RCCS), which was integrated into a centralized data mart as part of a larger data management strategy for the Rakai Health Sciences Program in Uganda. These data were used to build a publicly available, protected health information (PHI)-secured visualization dashboard for general research use.
UNASSIGNED: Using two unique case studies, we demonstrate the capability of the dashboard to generate the following hypotheses: firstly, that HIV prevention strategies ART and circumcision have differing levels of impact depending on the marital status of investigated communities; secondly, that ART is very successful in comparison to circumcision as an interventional strategy in certain communities.
UNASSIGNED: The democratization of large-scale anonymized epidemiological data using public-facing dashboards has multiple benefits, including facilitated exploration of research data and increased reproducibility of research findings.
UNASSIGNED: By allowing the public to explore data in depth and form new hypotheses, public-facing dashboard platforms have significant potential to generate new relationships and collaborations and further scientific discovery and reproducibility.

OBJECTIVE: To describe the development and integration of an electronic health record-driven, student dashboard that displays real-time data relative to the students\' patient management and clinic experiences at the University of Illinois Chicago, College of Dentistry.
METHODS: Following development and implementation of the student dashboard, various objective metrics were evaluated to identify any improvements in the clinical patient management. A cross-sectional retrospective chart review was completed of the electronic health record (axiUm, Exan, Coquitlam, BC, Canada) from January 2019 to April 2022 evaluating four performance metrics: student lockouts, note/code violations, overdue active patients, and overdue recall patients. Descriptive statistics were analyzed. The Kolmogorov-Smirnov test was applied to assess the normal distribution of data. Data were analyzed by the Kruskal-Wallis tests for potential differences between pre-dashboard and post-dashboard implementation years with the mean overdue active/recall patient to student ratio variables. Mann-Whitney U-tests for between-groups comparisons with Bonferroni correction for multiple comparisons were performed (α = 0.05). Descriptive statistics were performed to analyze the student utilization frequency of the dashboard.
RESULTS: Post-implementation analysis indicated a slight decrease in the number of lockouts and note/code violation; and a statistically significant decrease in overdue active patients post-dashboard (P < 0.001). On average, students accessed their dashboards 3.3 times a week.
CONCLUSIONS: Implementation of a student dashboard through the electronic health record platform within an academic dental practice has the potential to assist students with patient management and is utilized regularly by the students.