Development Of Dashboard Research Articles

A Novel Data Analytics Methodology for Discovering Behavioral Risk Profiles: The Case of Diners During a Pandemic

Understanding tourist profiles and behaviors during health pandemics is key to better preparedness for unforeseen future outbreaks, particularly for tourism and hospitality businesses. This study develops and applies a novel data analytics methodology to gain insights into the health risk reduction behavior of restaurant diners/patrons during their dining out experiences in a pandemic. The methodology builds on data relating to four constructs (question categories) and measurements (questions and attributes), with the constructs being worry, health risk prevention behavior, health risk reduction behavior, and demographic characteristics. As a unique contribution, the methodology generates a behavioral typology by identifying risk profiles, which are expressed as one- and two-level decision rules. For example, the results highlighted the significance of restaurants’ adherence to cautionary measures and diners’ perception of seclusion. These and other factors enable a multifaceted analysis, typology, and understanding of diners’ risk profiles, offering valuable guidance for developing managerial strategies and skill development programs to promote safer dining experiences during pandemics. Besides yielding novel types of insights through rules, another practical contribution of the research is the development of a public web-based analytics dashboard for interactive insight discovery and decision support.

ODP-DASHBOARD: Enhancing Marine Species Conservation in the South Atlantic through Linked Open Data Integration

This paper presents the development of a Cloud-based dashboard called ODP-DASHBOARD (Ocean Data Platform), to manage information from the Marine Biodiversity domains and Oceanography. In this context, the Linked Open Data (LOD) paradigm has emerged as a set of best practices for connecting, sharing and exposing data and knowledge. A central part of this paradigm are ontologies, which allow the definition of shared vocabularies and conceptual models that help integrate this information. These considerations provide a strong motivation to formulate a system that takes into account geospatial characteristics that can provide answers to questions such as the following: (i) How can we define spatial regions for our studies? (ii) How are species distributed in a given region? (iii) Given a particular georeference, what geographic region does it belong to? (iv) How to relate species occurrences to environmental variables within a specific region?. This system is composedof (i) Architecture; (ii) Conceptual model and (iii) Linked data set for exploitation through a SPARQL endpoint. The evaluation was carried out from two approaches, the first of which consists of validating the dashboard using real data extracted from Marine Biodiversity and Oceanography repositories and then validating the proposed conceptual model using competency questions. The second approach has to do with validation through case studies defined together with researchers from the Scientific and Technological Center (CENPAT-CONICET).

The OBS UK Dashboard: an interactive tool for representative trial site selection to facilitate equality and diversity in maternity research

BackgroundObstetric Bleeding Study UK (OBS UK) (award ID: 152057) is a National Institute for Health and Care Research (NIHR)-funded stepped wedge cluster randomised controlled trial of a complex intervention for postpartum haemorrhage. This was developed in Wales and evaluated in a feasibility study, with improvements in maternal outcomes observed. Generalisability of the findings is limited by lack of control data and limited ethnic diversity in the Welsh obstetric patient population compared to the United Kingdom (UK): 94% of the Welsh population identifies as White, versus 82% in the UK. Non-White ethnicity and socioeconomic deprivation are linked to increased risk of adverse maternal outcomes. Traditionally, decisions regarding site selection are based on desire to complete trials on target in ‘tried and tested’ research active institutions. To ensure widespread applicability of the results and investigate the impact of ethnicity and social deprivation on trial outcomes, maternity units were recruited that represent the ethnic diversity and social deprivation profiles of the UK.MethodUsing routinely collected, publicly available data, an interactive dashboard was developed that demonstrates the demographics of the population served by each maternity unit in the UK, to inform site recruitment. Data on births per year, ethnic and socioeconomic group of the population for each maternity unit, across the UK, were integrated into the dashboard.ResultsThe dashboard demonstrates that OBS UK trial sites reflect the ethnic and socioeconomic diversity of the UK (study vs UK population ethnicity: White 79.2% vs 81.7%, Asian 10.5% vs 9.3%, Black 4.7% vs 4.0%, Mixed 2.5% vs 2.9%, Other 3.0% vs 2.1%) with variation in site demography, size and location. Missing data varied across sites and nations and is presented.ConclusionThe NIHR equality, diversity and inclusion strategy states studies must widen participation, facilitating individuals from all backgrounds to engage. The development of this novel interactive dashboard demonstrates an innovative way of achieving this. National Health Service (NHS) maternity researchers should consider using this tool to enhance diversity in research, address health disparities and improve generalisability of findings. This approach could be applied to healthcare settings beyond maternity care and across different global populations.Trial registrationISRCTN 17679951. Registered on August 30, 2023.

Learning from our patients: An exploratory study to inform the development of a case tracking dashboard for internal medicine subspecialty fellows

Background Case tracking (following-up prior patient encounters) can help inform future clinical decisions and supplement experiential learning. Internal medicine subspecialty fellows see a high volume of patients and need to become subject matter experts within a short time frame, yet little is known about their specific needs and motivations around case tracking. Objective The objective of this study was to explore internal medicine subspecialty fellows’ motivations, preferences, and practices around case tracking. Methods We conducted interviews with internal medicine subspecialty fellows at a single academic medical center during the 2022–2023 academic year. Interviews were analyzed using qualitative content analysis. Results 22 fellows were interviewed for our study. We found that most fellows engaged in case tracking with lists in the electronic health record (EHR). Fellows primarily tracked cases of clinical uncertainty and patients with specific diseases or conditions of interest. Fellows sought information on patients’ health outcomes, results, and clinical notes. Motivations for tracking were predominantly related to curiosity, professional growth, and development of practice patterns. Barriers to case tracking included time, challenges maintaining patient lists, losing track of patients, and lack of motivation to develop and maintain an organized system. Conclusions Internal medicine subspecialty fellows engaged in and valued case tracking as a way to supplement their experiential learning. Our study highlighted their current practices, motivations, preferences, and challenges related to case tracking. We plan to use these findings to help develop an EHR-embedded dashboard to facilitate case tracking among subspecialty fellows.

Intensive Care Quality Indicators Dashboard Using Observational Medical Outcomes Partnership Common Data Model.

This paper presents the development of a visualization dashboard for quality indicators in intensive care units (ICUs), using the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). The dashboard enables the user to visualize quality indicator data using histograms, pie charts and tables. Our project uses the OMOP CDM, ensuring a seamless implementation of our dashboard across various hospitals. Future directions for our research include expanding the dashboard to incorporate additional quality indicators and evaluating clinicians' feedback on its effectiveness.

Unit-based Pathways to Reduce InequitieS for familiEs speaking languages other than English (UPRISE).

Health care inequities are common among individuals who speak languages other than English (LOE). Within our PICU, LOE families prefer communication via in-person interpreters (IPI). Spanish-speaking patient families are our largest LOE population; therefore, we sought to increase Spanish IPI utilization for medical updates in the PICU. A quality improvement initiative in a 36-bed PICU included: the addition of a dedicated weekday Spanish-speaking IPI, the creation of communication tools, staff education, optimized identification of LOE families, and development of a language dashboard across multiple Plan, Do, Study, Act cycles. The primary outcome was IPI utilization rates for daily medical updates. Spanish IPI utilization for daily weekday medical updates among 442 Spanish-speaking patient families increased from a median of 39.4% at baseline to a new centerline median of 51.9% during implementation, exhibiting 66.3% (465 of 701) utilization in the final 6 months of implementation. The greatest sustained increases in Spanish IPI utilization occurred after PICU-based IPI implementation, staff education, electronic health record optimization, and a split work week between 2 PICU-based IPIs. This quality improvement initiative increased Spanish IPI utilization for daily weekday medical updates in the PICU across multiple Plan, Do, Study, Act cycles. Future work will adapt these interventions to other languages and other hospital-based units.

Data Visualization Dashboard using Python

This study presents the development of a Data Visualization Dashboard using Python, aimed at providing comprehensive insights into complex datasets. Leveraging Python libraries such as Matplotlib, Seaborn, and Plotly, alongside frameworks like Dash and Streamlit, the dashboard offers an intuitive and interactive interface for data exploration and analysis. The visualization components include various charts, graphs, and maps tailored to depict diverse data types, facilitating the identification of patterns, trends, and outliers. Moreover, advanced features such as dynamic filtering, drill-down capabilities, and real-time updates enhance the dashboard's functionality, enabling users to delve deeper into the data and extract valuable insights efficiently. The dashboard's modular architecture ensures scalability and flexibility, allowing for seamless integration with different data sources and adaptability to evolving analytical requirements. Through case studies and performance evaluations, the effectiveness and usability of the Data Visualization Dashboard are demonstrated, highlighting its potential as a powerful tool for decision- making, reporting, and storytelling in diverse domains

Development and integration of a clinical dashboard within a dental school setting.

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. 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. 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. 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.

APF Charles l. Brewer Award for Distinguished Teaching of Psychology: Viji Sathy.

The APF Gold Medal for Impact in Psychology recognizes Viji Sathy for her dedication to inclusive teaching practices, promoting diversity and equity in classrooms and higher education. Dr. Sathy has continually pushed the boundaries of student learning experiences. Her innovative teaching methods, including flipped classrooms and makerspace courses, have transformed learning environments and ensured that every student feels empowered. Dr. Sathy's advocacy for diversity and inclusion spans globally. Her efforts as a workshop facilitator and keynote speaker at over 100 institutions worldwide have left a mark on the global discourse surrounding inclusive education. Her contributions to initiatives like the Chancellor's Science Scholars program and the development of the MCAD dashboard underscore her commitment to fostering a more inclusive academic landscape. Dr. Sathy's passion will continue to inspire educators to prioritize inclusivity in teaching and learning. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Personalized prediction of intradialytic hypotension in clinical practice: Development and evaluation of a novel AI dashboard incorporating risk factors from previous and current dialysis sessions

BackgroundIntradialytic hypotension (IDH) is one of the most common and critical complications of hemodialysis. Despite many proven factors associated with IDH, accurately predicting it before it occurs for individual patients during dialysis sessions remains a challenge. PurposeTo establish artificial intelligence (AI) predictive models for IDH, which consider risk factors from previous and ongoing dialysis to optimize model performance. We then implement a novel digital dashboard with the best model for continuous monitoring of patients’ status undergoing hemodialysis. The AI dashboard can display the real-time probability of IDH for each patient in the hemodialysis center providing an objective reference for care members for monitoring IDH and treating it in advance. MethodsEight machine learning (ML) algorithms, including Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM), K Nearest Neighbor (KNN), Light Gradient Boosting Machine (LightGBM), Multilayer Perception (MLP), eXtreme Gradient Boosting (XGBoost), and NaiveBayes, were used to establish the predictive model of IDH to determine if the patient will acquire IDH within 60 min. In addition to real-time features, we incorporated several features sourced from previous dialysis sessions to improve the model’s performance. The electronic medical records of patients who had undergone hemodialysis at Chi Mei Medical Center between September 1, 2020 and December 31, 2020 were included in this research. Impact evaluation of AI assistance was conducted by IDH rate. ResultsThe results showed that the XGBoost model had the best performance (accuracy: 0.858, sensitivity: 0.858, specificity: 0.858, area under the curve: 0.936) and was chosen for AI dashboard implementation. The care members were delighted with the dashboard providing real-time scientific probabilities for IDH risk and historic predictive records in a graphic style. Other valuable functions were appended in the dashboard as well. Impact evaluation indicated a significant decrease in IDH rate after the application of AI assistance. ConclusionThis AI dashboard provides high-quality results in IDH risk prediction during hemodialysis. High-risk patients for IDH will be recognized 60 min earlier, promoting individualized preventive interventions as part of the treatment plan. Our approachis believed to promise an excellent way for IDH management.

Development of an electronic health record-integrated patient-reported outcome-based shared decision-making dashboard in oncology.

Patient-reported outcomes (PROs) describe a patient's unique experiences with disease or treatment, yet effective use of this information during clinical encounters remains challenging. This project sought to build a PRO based dashboard within the electronic health record (EHR), prioritizing interpretability and utility of PROs for clinical decision-making. Codesign principles were used to define the goal, features, and visualization of the data elements on the dashboard. Codesign sessions occurred between February 2019 and May 2020 and involved a diverse group of stakeholders. Pilot evaluation of dashboard usability was performed with patients and clinicians not involved in the codesign process through qualitative interviews and the Systems Usability Scale. The dashboard was placed into a single tab in the EHR and included select PROM scores, clinical data elements, and goals of care questions. Real-time data analytics and enhanced visualization of data was necessary for the dashboard to provide meaningful feedback to clinicians and patients for decision-making during clinic visits. During soft launch, the dashboard demonstrated "good" usability in patients and clinicians at 3 and 6 months (mean total SUS score >70). The current dashboard had good usability and made PRO scores more clinically understandable to patients and clinicians. This paper highlights the development, necessary data elements, and workflow considerations to implement this dashboard at an academic cancer center. As the use of PROs in clinical care is increasing, patient- and clinician-centered tools are needed to ensure that this information is used in meaningful ways.

Optimizing heart failure pathways to enhance patient care: the Program to Optimize Heart Failure Patient Pathways (PRO-HF).

Many European healthcare providers struggle to adopt multidisciplinary, integrated care pathways for people with heart failure (HF) as recommended by the European Society of Cardiology. PRO-HF (Program to Optimize Heart Failure Patient Pathways) was developed to help clinicians identify strengths, gaps, and shortcomings in their HF pathways and support tailored interventions to optimize pathways and enhance patient care. We report initial findings from baseline assessments of HF pathway characteristics and challenges from 10 hospitals in six European countries (France, Ireland, Portugal, Spain, The Netherlands, and United Kingdom). Baseline assessments were holistic appraisals of full HF services to calibrate current status and development needs and assist management teams in prioritizing improvement projects. Assessments were performed using a comprehensive checklist of measures covering the HF patient journey from diagnosis to ongoing follow-up. These included a digital survey sent to full HF care teams and one-to-one interviews. The digital survey focused on four key areas (HF outpatient clinic; remote patient management; efficient device implantation and inpatient pathways; and network maximization) and 16 dimensions of excellence. Priority areas and themes for action identified in baseline assessments were (i) provision of HF specialist care; (ii) data capture and analysis; (iii) institutional care protocols; (iv) hospital-wide strategies; and (v) multidisciplinary teams (MDTs). Suboptimal specialist care of emergency inpatients was an issue at all hospitals and prioritized at 8/10. Availability and accessibility of data on patients, activities, and outcomes was an issue at all hospitals and prioritized by 4/10. A lack of clear protocols, templates, and tools for some HF activities created variability in patient care (e.g., HF specialist consultations, diagnostic testing, follow-up appointments, medications, and device eligibility) and inefficient use of clinician time. This made it difficult to initiate new technologies (e.g., remote patient monitoring) due to the risk of overburdening staff. MDTs were frequently understaffed. Multiple interventions were identified to address gaps and shortcomings that could be tailored to specific needs of individual hospitals (e.g., inpatient pathway optimization, creation/optimization of HF outpatient clinics, development of an HF performance dashboard, enhancement of protocol adherence, streamlining cardiac resynchronisation therapy pathways, and MDT coordination). PRO-HF provides a valuable opportunity to identify gaps and significant shortcomings in HF pathways in European hospitals. Preliminary findings from hospitals that have initiated suggested changes to address these challenges are encouraging, though longer-term follow-up from more hospitals is needed to confirm the impact of PRO-HF on HF pathway optimization and patient care.

Exploring the accessibility of primary health care data in Europe's COVID-19 response: developing key indicators for managing future pandemics (Eurodata study)

BackgroundPrimary Health Care (PHC) plays a crucial role in managing the COVID-19 pandemic, with only 8% of cases requiring hospitalization. However, PHC COVID-19 data often goes unnoticed on European government dashboards and in media discussions. This project aims to examine official information on PHC patient care during the COVID-19 pandemic in Europe, with specific objectives: (1) Describe PHC’s clinical pathways for acute COVID-19 cases, including long-term care facilities, (2) Describe PHC COVID-19 pandemic indicators, (3) Develop COVID-19 PHC activity indicators, (4) Explain PHC’s role in vaccination strategies, and (5) Create a PHC contingency plan for future pandemics.MethodsA mixed-method study will employ two online questionnaires to gather retrospective PHC data on COVID-19 management and PHC involvement in vaccination strategies. Validation will occur through focus group discussions with medical and public health (PH) experts. A two-wave Delphi survey will establish a European PHC indicators dashboard for future pandemics. Additionally, a coordinated health system action plan involving PHC, secondary care, and PH will be devised to address future pandemic scenarios. Analysis: Quantitative data will be analysed using STATA v16.0 for descriptive and multivariate analyses. Qualitative data will be collected through peer-reviewed questionnaires and content analysis of focus group discussions. A Delphi survey and multiple focus groups will be employed to achieve consensus on PHC indicators and a common European health system response plan for future pandemics. The Eurodata research group involving researchers from 28 European countries support the development.DiscussionWhile PHC manages most COVID-19 acute cases, data remains limited in many European countries. This study collects data from numerous countries, offering a comprehensive perspective on PHC’s role during the pandemic in Europe. It pioneers the development of a PHC dashboard and health system plan for pandemics in Europe. These results may prove invaluable in future pandemics. However, data may have biases due to key informants’ involvement and may not fully represent all European GP practices. PHC has a significant role in the management of the COVID-19 pandemic, as most of the cases are mild or moderate and only 8% needed hospitalization. However, PHC COVID-19 activity data is invisible on governments’ daily dashboards in Europe, often overlooked in media and public debates.

CLIMAEXTREMO: A New Risk Indicator for the Health Risk to Building Occupants during Extreme Weather Events in Portugal

Portugal is the country in Europe where the death rate in winter and summer has the highest correlation with outdoor temperatures. The Portuguese National Institute of Public Health Ricardo Jorge has developed a national warning system for heat waves called ICARO, which has been in place since 1999 (and is the oldest in Europe). However, it presents some limitations, namely, the low spatial resolution (five regions in Portugal’s mainland), the low temporal forecasting period (one day), and the fact that it was only accessible to health authorities until very recently. This work describes the development of a new public dashboard that uses a new early warning index for extreme weather events, the CLIMAEXTREMO index, which extends the current warning system by improving the current forecasting models for risk by integrating new sources of public data and increasing the spatial and time resolution of the warnings to the municipality or the parish level. The new index is a combination of a new model to estimate the relative mortality increase (updating the model used in ICARO) together with a model of the indoor temperature of building archetypes for all municipalities and a vulnerability index that considers socio-demographic economic indicators. This work discusses the results of the new risk indicator for the heat waves that occurred in Portugal at the end of June and mid-August 2023, and it shows that the index was able to indicate a high risk for the municipalities that had an increase in the number of deaths during that period.

Development and Utility of an Interactive Online Dashboard for Monitoring Data Collection and Data Processing During a School-Based Health Survey.

We built an interactive online dashboard using Google Looker Studio to monitor data collection and data processing activities during the Adolescent Health Survey (AHS) 2022, a large-scale nationwide survey conducted among school-going adolescents in Malaysia. Through user testing and training, refinements were made to the initial dashboard, resulting in a more streamlined and concise dashboard design. The dashboard comprised 2 pages that provided key metrics on the progress of data collection and data processing, respectively. The introduction of the dashboard enhanced the quality and ease of weekly progress reporting during meetings of the survey's central coordinating team, while its drill-down and filtering functionalities helped us detect arising issues early and supported collaborative problem-solving. Research teams coordinating comparable school-based health surveys are invited to duplicate the dashboard using Looker Studio's built-in "Make a copy" function and customize it further based on their country- or survey-specific requirements.

Development of a Real-Time Dashboard for Overdose Touchpoints: User-Centered Design Approach.

Overdose Fatality Review (OFR) is an important public health tool for shaping overdose prevention strategies in communities. However, OFR teams review only a few cases at a time, which typically represent a small fraction of the total fatalities in their jurisdiction. Such limited review could result in a partial understanding of local overdose patterns, leading to policy recommendations that do not fully address the broader community needs. This study explored the potential to enhance conventional OFRs with a data dashboard, incorporating visualizations of touchpoints-events that precede overdoses-to highlight prevention opportunities. We conducted 2 focus groups and a survey of OFR experts to characterize their information needs and design a real-time dashboard that tracks and measures decedents' past interactions with services in Indiana. Experts (N=27) were engaged, yielding insights on essential data features to incorporate and providing feedback to guide the development of visualizations. The findings highlighted the importance of showing decedents' interactions with health services (emergency medical services) and the justice system (incarcerations). Emphasis was also placed on maintaining decedent anonymity, particularly in small communities, and the need for training OFR members in data interpretation. The developed dashboard summarizes key touchpoint metrics, including prevalence, interaction frequency, and time intervals between touchpoints and overdoses, with data viewable at the county and state levels. In an initial evaluation, the dashboard was well received for its comprehensive data coverage and its potential for enhancing OFR recommendations and case selection. The Indiana touchpoints dashboard is the first to display real-time visualizations that link administrative and overdose mortality data across the state. This resource equips local health officials and OFRs with timely, quantitative, and spatiotemporal insights into overdose risk factors in their communities, facilitating data-driven interventions and policy changes. However, fully integrating the dashboard into OFR practices will likely require training teams in data interpretation and decision-making.

Development and usability of an EHR-driven hypertension disparities dashboard in primary care: A qualitative study.

Hypertension disparities persist and remain high among racial and ethnic minority populations in the United States (US). Data-driven approaches based on electronic health records (EHRs) in primary care are seen as a strong opportunity to address this situation. This qualitative study evaluated the development, sustainability, and usability of an EHR-integrated hypertension disparities dashboard for health care professionals in primary care. Ten semi-structured interviews, exploring the approach and sustainability, as well as eight usability interviews, using the think aloud protocol were conducted with quality improvement managers, data analysts, program managers, evaluators, and primary care providers. For the results, dashboard development steps include having clear goals, defining a target audience, compiling data, and building multidisciplinary teams. For sustainability, the dashboard can enhance understanding of the social determinants of health or to inform QI projects. In terms of dashboard usability, positive aspects consisted of the inclusion of summary pages, patient's detail pages, and hover-over interface. Important design considerations were refining sorting functions, gender inclusivity, and increasing dashboard visibility. In sum, an EHR-driven dashboard can be a novel tool for addressing hypertension disparities in primary care. It offers a platform where clinicians can identify patients for culturally tailored interventions. Factors such as physician time constraints, data definitions, comprehensive patient demographic information, end-users, and future sustenance, should be considered before implementing a dashboard. Additional research is needed to identify practices for integrating a dashboard into clinical workflow for hypertension.

Integration of patient navigation into clinical operations of an outpatient cancer center.

e23091 Background: Recognizing the critical importance of expanding access to high-quality, integrated cancer care, Dana-Farber Cancer Institute’s (DFCI) Cancer Care Equity Program developed a multi-year plan to integrate a centralized, systems-based patient navigation (PN) program focused on supporting adult medical oncology patients from historically marginalized groups. The goal was to proactively address patients’ socio-economic, emotional, and structural barriers to attending medical appointments and adhering to cancer treatment plans through care coordination, physical accompaniment, and resource provision. Methods: Inclusion of the new program in DFCI’s operating goals supported prioritization of the work across the cancer center. A multidisciplinary workgroup developed standard operating procedures grounded in evidence-based approaches while leveraging existing clinical operations. The Freeman Navigation Model informed PN scope of work with a focus on historically marginalized communities. DFCI’s Community Health Needs Assessment guided the decision to prioritize patients from zip codes with significant disparities related to social determinants of health. Utilization of electronic health records for PN documentation ensured effective communication with care teams and enabled accurate and consistent data collection and reporting. Alignment of the program’s measurement strategy with national PN metrics and development of a data dashboard allowed for ongoing monitoring and evaluation. Results: The program was implemented sequentially in five cancer treatment centers: gastrointestinal, breast, thoracic, and gynecologic oncology as well as hematologic malignancies. 517 patients were contacted and 1,736 barriers to cancer care were addressed at time of analysis. Preliminary findings from the first cancer treatment center suggest a decreased no show rate in the second year of the program. Conclusions: The multidisciplinary approach to integrating an evidence-based PN program into clinical operations supported general adoption among care teams and timely replication across cancer types. The infrastructure developed for the program could potentially support implementation of Centers for Medicare and Medicaid Services reimbursement for PN services. Next steps include confirming preliminary findings in a larger sample, conducting a cost-benefit analysis, and expanding the program across the clinical enterprise. [Table: see text]

Design and development of the clinical pharmacy key performance indicators dashboard for equity of service provision at regional and rural hospitals in North Queensland, Australia

AbstractBackgroundProvision of a Medication Action Plan (MAP) on admission and a Discharge Medication Record (DMR) are associated with reduced medication‐related harm.AimTo report factors associated with the provision of MAPs and DMRs in rural and regional hospitals in Queensland, Australia.MethodA literature search, environmental scan and department consultations were conducted to develop Clinical Pharmacy Key Performance Indicators (cpKPIs) and design a cpKPI dashboard. Two of the five KPIs included in the dashboard, relating to medication action plans on admission and medication records on discharge, were reported for all the hospitals and were included in the study. A retrospective, period‐prevalence study was conducted to evaluate the coverage and equity of clinical pharmacy service provision for patients admitted for longer than 24 h. The proportions of patients who received MAPs and DMRs were stratified by age, gender, Indigeneity and hospital type. Statistical analysis used chi‐squared tests and logistic regression in R. This project was exempt due to the local policy requirements that constitute research by the Far North Queensland Human Research Ethics Committee (Reference no: EX/2023/QCH/94383‐1684QA). The justification for this exemption is as follows: the project was determined to be negligible risk research and involved the use of existing collection of data or records that contain only non‐identifiable data about human beings.ResultsIn total, 13 818 patients (37.9% of admissions) received a MAP and 11 631 patients (32.7% of discharges) received a DMR. The proportion of MAPs and DMRs was significantly higher in rural hospitals than in regional hospitals (MAP 50.6% vs 34.6%, DMR 33.1% vs 31.3%) and for male patients than female patients (MAP 42.2% vs 33.7%, DMR 36.4% vs 29.2%). When stratified by age, First Nations patients received a higher proportion of MAPs and DMRs in each age group, except for age 85 years and over. The proportion of First Nations patients aged 50 years and over who received MAP was lower compared to that for non‐Indigenous patients aged 65 years and over (56.3% vs 59.8%), whilst the proportion for DMRs was similar (50.4% vs 49.3%).ConclusionThe study defined the clinical pharmacy key performance indicators for measuring equity of clinical pharmacy service provision in Australia. When adjusted for a difference in life expectancy, the proportion of MAPs for First Nations patients was lower compared to the proportion of MAPs for non‐Indigenous patients. Further improvements are required to achieve equity of service provision for First Nations patients and female patients.

Enhancing online learning environments through real-time social presence dashboards

Online learning is promoted to play a pivotal role in the future of education, necessitating a focus on student engagement and interactivity as essential components for successful online educational environments. Social presence, as a construct capturing these social aspects, is extensively recognized, and investigated within the realm of education and widely shaping the online learning experience. However, a crucial gap remains in the absence of a real-time measurement of social presence.Drawing from prior research, this study identifies indicators derived from social network analysis as promising metrics for assessing social presence in online learning environments. What remains unclear is the means to effectively convey this information to instructors, enabling them to enhance the educational online experience. To address this gap, we conducted focus groups involving seven experts in online education and pedagogical expertise.Our findings reveal that the development of a social presence dashboard holds immense potential for enriching the online teaching experiences through the utilization of these identified indicators. Furthermore, incorporating additional visualizations and graphical representations with such dashboards can equip online instructors with the necessary insights to foster social interactions and capture real-time social dynamics within online courses.However, the implementation of such dashboards necessitates a careful consideration of important ethical and practical considerations, including informed consent procedures, student monitoring practices, and adherence to ethical standards. This research contributes valuable insights into the ongoing discourse on improving online education by leveraging technology to enhance social presence and pedagogical effectiveness.