United States

Background and Objectives:
Elective surgery cancellations can lead to increased costs, reduced resource utilization, and patient and surgeon dissatisfaction. The reasons for why these cancellations occur remain poorly understood, hindering interventions to prevent their occurrence. Understanding these factors is necessary to implement effective strategies to reduce cancellation rates and improve surgical care delivery. This study aimed to identify the reasons for elective surgery cancellation and how these reasons can be efficiently addressed to reduce cancellation rates.

Methods &amp; Study Design
The study focused on the General Surgery outpatient service at Grady Memorial Hospital, affiliated with Morehouse School of Medicine. We compiled a list of all requested elective surgical cases and documented the number of cases completed versus those canceled and the reasons for cancellations. Data collection occurred from July 1, 2023, to December 29, 2023. Following the appointment of a pre-procedure coordinator, a second set of data was collected from January 1, 2024, to April 22, 2024.

The reasons for cancellations were categorized into patient-related factors (e.g., no-shows, call-in cancellations, non-adherence to NPO status, failure to stop anticoagulation, unexpected illness), surgeon-related factors, missed preoperative anesthesia visits, financial clearance issues, and unknown reasons. We applied a one-sample chi-square goodness-of-fit test to calculate the chi-square statistic for data analysis. Additionally, we conducted a cost analysis to estimate the missed revenue based on average CMS reimbursements for the respective procedures. Using the collected dataset, we extrapolated the potential missed revenue over the course of a year if current trends continued.

Results
During the first five months of the study, 48 elective cases were canceled, representing approximately 30% of the scheduled elective cases. Most of these cancellations (60%) were due to missed pre-anesthesia testing or appointments (PAT) and other patient-related factors.

Following the appointment of a surgery center scheduler to assist with elective cases, there were no missed PAT appointments during the second data collection period in 2024. However, patient-related factors still accounted for most cancellations in 2024, constituting 69.2%.

Cancellations were also categorized as &quot;intervenable&quot; versus &quot;non-intervenable&quot; to evaluate the impact of system-wide deficits. Notably, 66% of the canceled cases were due to &quot;intervenable&quot; reasons, such as patients not showing up for scheduled pre-anesthesia testing because they were unaware of the appointments.

For the first data set, the calculated chi-square value (χ²) was 18.750, greater than the critical value of 15.09 for a degree of freedom (df) of 5, with p = 0.002. The chi-square value for the second data set was 28.462, exceeding the critical value of 11.34 for a degree of freedom (df) of 3, with p &lt; 0.001. 


Conclusions
Since the calculated chi-square values exceed the critical values in both instances, we reject the null hypothesis (H₀), which posits that the observed proportions of surgery cancellations due to different factors are consistent with the expected proportions. This indicates that the observed proportions of surgery cancellations due to multiple dependent factors are inconsistent with the expected proportions, and the findings are statistically significant, not attributable to random chance.

The reasons for surgery cancellations differ significantly from the expected patterns based on the sample data. However, there remains a gap in the system for keeping patients informed about their pre-operative appointments and the overall pre-operative process after scheduling elective surgery. A dedicated outpatient surgery coordinator could help bridge this gap by facilitating more frequent and direct communication between patients and providers, potentially increasing the number of completed scheduled surgeries. Nonetheless, non-intervenable reasons for cancellations, such as unannounced no-shows and new onset medical conditions, will persist as challenges in elective surgery care due to their unpredictable nature and lack of easily identifiable solutions.


AMA Research Challenge 2024 

Analyzing Factors Contributing to Elective Surgery Cancellations: A One-Sample Chi-Square Test Approach

Background and Objectives:
Elective surgery cancellations can lead to increased costs, reduced resource utilization, and patient and surgeon dissatisfaction. The reasons for why these cancellations occur remain poorly understood, hindering interventions to prevent their occurrence. Understanding these factors is necessary to implement effective strategies to reduce cancellation rates and improve surgical care delivery. This study aimed to identify the reasons for elective surgery cancellation and how these reasons can be efficiently addressed to reduce cancellation rates.

Methods & Study Design
The study focused on the General Surgery outpatient service at Grady Memorial Hospital, affiliated with Morehouse School of Medicine. We compiled a list of all requested elective surgical cases and documented the number of cases completed versus those canceled and the reasons for cancellations. Data collection occurred from July 1, 2023, to December 29, 2023. Following the appointment of a pre-procedure coordinator, a second set of data was collected from January 1, 2024, to April 22, 2024.

The reasons for cancellations were categorized into patient-related factors (e.g., no-shows, call-in cancellations, non-adherence to NPO status, failure to stop anticoagulation, unexpected illness), surgeon-related factors, missed preoperative anesthesia visits, financial clearance issues, and unknown reasons. We applied a one-sample chi-square goodness-of-fit test to calculate the chi-square statistic for data analysis. Additionally, we conducted a cost analysis to estimate the missed revenue based on average CMS reimbursements for the respective procedures. Using the collected dataset, we extrapolated the potential missed revenue over the course of a year if current trends continued.

Results
During the first five months of the study, 48 elective cases were canceled, representing approximately 30% of the scheduled elective cases. Most of these cancellations (60%) were due to missed pre-anesthesia testing or appointments (PAT) and other patient-related factors.

Following the appointment of a surgery center scheduler to assist with elective cases, there were no missed PAT appointments during the second data collection period in 2024. However, patient-related factors still accounted for most cancellations in 2024, constituting 69.2%.

Cancellations were also categorized as "intervenable" versus "non-intervenable" to evaluate the impact of system-wide deficits. Notably, 66% of the canceled cases were due to "intervenable" reasons, such as patients not showing up for scheduled pre-anesthesia testing because they were unaware of the appointments.

For the first data set, the calculated chi-square value (χ²) was 18.750, greater than the critical value of 15.09 for a degree of freedom (df) of 5, with p = 0.002. The chi-square value for the second data set was 28.462, exceeding the critical value of 11.34 for a degree of freedom (df) of 3, with p < 0.001. 


Conclusions
Since the calculated chi-square values exceed the critical values in both instances, we reject the null hypothesis (H₀), which posits that the observed proportions of surgery cancellations due to different factors are consistent with the expected proportions. This indicates that the observed proportions of surgery cancellations due to multiple dependent factors are inconsistent with the expected proportions, and the findings are statistically significant, not attributable to random chance.

The reasons for surgery cancellations differ significantly from the expected patterns based on the sample data. However, there remains a gap in the system for keeping patients informed about their pre-operative appointments and the overall pre-operative process after scheduling elective surgery. A dedicated outpatient surgery coordinator could help bridge this gap by facilitating more frequent and direct communication between patients and providers, potentially increasing the number of completed scheduled surgeries. Nonetheless, non-intervenable reasons for cancellations, such as unannounced no-shows and new onset medical conditions, will persist as challenges in elective surgery care due to their unpredictable nature and lack of easily identifiable solutions.

poster

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Background: 
Recent studies indicate an association between pancreatitis and cardiovascular disease. However, research regarding the association between atrial fibrillation (AF) and acute pancreatitis (AP) is limited. To address this gap and test our hypothesis that AF exacerbates mortality and clinical outcomes in patients with AP, we conducted a retrospective cohort study using the extensive multi-institutional research network, TriNetX.

Methods: 
De-identified patient data from the US Collaborative Network in TriNetX was used to assess the risk of all-cause mortality in AP patients with AF compared to those without AF within 30 days of the index event from January 1, 2010 to July 6, 2024. Secondary outcomes included critical care services, acute kidney injury (AKI), deep vein thrombosis (DVT), acute respiratory distress syndrome (ARDS), hemorrhage, systemic inflammatory response syndrome (SIRS), and severe sepsis within 30 days of the index event. Analyses were performed before and after propensity score matching, with risks expressed as odds ratios (OR) with 95% confidence intervals (95% CI), and Kaplan-Meier curves were generated for outcomes.

Results: 
A total of 267,429 patients with AP were identified, of whom 44,621 had a diagnosis of AF. Patients in the AP with AF cohort, predominantly older males of White and Native Hawaiian or Other Pacific Islander ethnicity, presented with higher comorbidity burdens compared to the non-AF cohort before propensity score matching. After matching, the AF cohort exhibited increased risks of all-cause mortality (OR, 1.24; 95% CI 1.18-1.3), AKI (OR, 1.17; 95% CI 1.14-1.2), DVT (OR, 1.33; 95% CI 1.27-1.39), hemorrhage (OR, 1.06; 95% CI 1.01-1.11), ARDS (OR, 1.4; 95% CI 1.27-1.54), SIRS (OR, 1.12; 95% CI 1.03-1.22), severe sepsis (OR, 1.3; 95% CI 1.25-1.35,), and requiring critical care services (OR, 1.19; 95% CI 1.16-1.23) compared to the non-AF cohort. Kaplan-Meier survival analysis demonstrated significantly lower 30-day survival probabilities for all-cause mortality, ICU level of care, AKI, DVT, and hemmorrhage in the AF cohort compared to patients without AF, while similar survival probabilities were observed for ARDS and SIRS between the two cohorts.

Conclusion: 
Our results suggest that AF significantly increases the risk of mortality in patients with AP, even after accounting for confounding etiological, comorbid, and pharmacological factors. Patients with AP and AF are also at greater risk of worse clinical outcomes.

Atrial Fibrillation and the Risk of Adverse Events and Mortality in Adults with Acute Pancreatitis: A Propensity-Score Matched Analysis

Introduction: Obesity is associated with a number of comorbidities which deteriorate health status and are costly to manage. We are interested in assessing the cost-effectiveness of the two most common bariatric procedures, the sleeve gastrectomy, and roux-en-y gastric bypass (RYGB) for reducing comorbidity rates and costs. With the entry of new weight-loss medications to market, this long-term data will serve as a benchmark to compare therapies as outcome data become available.

Methods: A meta-analysis was submitted to PROSPERO and performed utilizing Ovid Medline. A total of 53 articles were identified which met quality and inclusion criteria. Data were extracted for a total of 113,762 patients. Utility values, procedural and annual comorbidity cost data were extracted from literature and adjusted for inflation. A cost-utility analysis model was constructed for each of these data trends, to a maximal of 20-years post-operatively.

Results: At 10 years post-RYGB or sleeve, patients had significant and sustained BMI decreases of 15.9 and 11.1 points respectively as compared to 1.3 points for mixed medical/diet control. RYGB data at 20 years, demonstrated a sustained decrease of 17.8 points, compared to control at 1.9. At 10 years RYGB patients had a 12.3% reduction in DM, sleeve a 10.5% reduction, compared to a 12.8% increase in the control group. At 12 years, DM prevalence in RYGB was decreased by 14.9% whereas the control group had increased by 16.1%. At 10 years there was a net-positive cost of $946 for RYGB and $7,623 for sleeve, with QALY gain of 1.04 and 0.74 and ICER of $909/QALY and $10,262/QALY respectively. BMI and DM data were available for RYGB at 12 years, where a net cost-savings for RYGB of $6,129 per patient and 1.28 utility gain was observed.

Conclusion: While bariatric surgery may be viewed as having a high initial cost, this study demonstrates that these procedures are not only cost-effective, they are cost sparing. At 10 years this study demonstrates ICER at $909/QALY for RYGB and $10,262/QALY for sleeve gastrectomy, qualifying them as extremely cost-effective procedures. At the 12-year mark, RYGB was cost negative with a net savings of $6,129 per patient. In addition to these cost-savings, both procedures demonstrate a major reduction in type 2 diabetes and BMI, which cannot be overstated for the unquantified subjective impact on quality of life. Future work will include addition of other comorbidities and the impact of complications of both medical and surgical therapy.


Cost Utility Analysis of Long-Term Outcomes of Bariatric Surgery as Compared to Medical Therapy for Obesity Management

Abstract Title:
Enhancing Continuity of Care in Outpatient Setting: A Quality Improvement Initiative

Background:
Continuity of care is the process of ensuring high-quality care over time through a continuous, long-term relationship between patients and physicians. When patients receive consistent care from the same healthcare provider, it enhances the provider’s understanding of the patient’s medical history and preferences, leading to better communication, enhanced trust, thus fostering strong doctor-patient relationships. This continuity was documented to reduce healthcare costs, improve medication adherence and patient satisfaction. Residency programs in internal medicine are required to create a continuous relationship between residents and a panel of patients. However, maintaining continuity can be challenging due to limited time and availability of residents, as well as scheduling issues. 

Methods:
We aimed to improve continuity of care by at least 50% at Federally Qualified Health Center (FQHC) of our hospital during the period of September to December 2023. Interventions include: 1. Educating residents on the importance of continuity of care through presentations and posters. 2. Preparing the annual resident schedule in advance to facilitate appropriate follow-up scheduling. 3. Confirming patient availability to ensure clinic visits on agreed dates. 4. Coordinating with support staff involved in setting up appointments by providing them access to the annual resident schedule. 

Results:
During the specified period, a total of 313 patients were seen in the clinic who met the inclusion criteria, with 184 (58.8%) of them being females. The mean age of the group was 48.9 (14.8) years. Out of 151 patients in the pre-intervention group, 13.9% (21) were followed by the same physician during their visits. This figure increased to 26.5% (43 among the 162 patients) in the post-intervention group. This disparity was statistically significant, with a p-value of 0.006. There were no notable differences in gender or age between the two groups (p-value > 0.05). Resident survey: All the residents (100%) emphasized the extreme importance of continuity of care. 68% of the residents have observed patients requesting to be seen by the same physician during their clinic visits. When asked how they would perceive patient satisfaction levels post-intervention, 75% of them found that patients were more satisfied.

Conclusion:
Our project resulted in increasing in the continuity of care from 13.9% to 26.5%, which was statistically significant. A physician-led, team-based approach to healthcare along with targeted interventions can facilitate continuity of care, reducing fragmentation of care and improving patient health care quality and patients’ satisfaction.


Enhancing Continuity of Care in Outpatient Setting: A Quality Improvement Initiative

Background
The extreme scarcity of donor hearts limits the availability of heart transplantation. Patients from vulnerable communities are disproportionately impacted. Social determinants of health (SDoH) are often quantified using place-based disadvantage indices. In this study, we apply place-based disadvantage indices and evaluate their relationship with heart transplant waitlist outcomes. 
Methods
We studied all adult heart-only transplant candidates initially listed between January 1, 2019 and December 31, 2022. Four indicies were compared: SVM, SVI, ADI, and DCI. Covariates included demographic characteristics, VADs, total artificial heart, and initial status (1-6).
The primary event of interest was heart transplantation. Candidate death or removal from the waitlist due to deterioration served as a competing event. For each index, we performed a competing risk regression with indices split by decile (categorical variable) and all covariates. We also performed competing risk regressions stratified by the transplant center where each candidate was waitlisted.
Results
Our final study cohort included 16,639 adult heart transplant candidates. Candidates in the 10th SVM decile were significantly less likely to receive transplantation than candidates in the 1st decile (sub-HR=0.84, p<0.001). Candidates in the 4th, 7th, and 9th SVI decile were significantly less likely to be transplanted (9th: sub-HR=0.82, p=0.034). Candidates in the 4th through 10th ADI decile were significantly less likely to be transplanted (10th: sub-HR=0.73, p<0.001). Candidates in the 3rd and 10th DCI decile were less likely to receive a transplant (10th: sub-HR=0.87, p=0.006).
When stratifying by transplant center, we found that SVM decile did not significantly predict a candidate’s likelihood of receiving a transplant. For SVI, candidates in every SVI decile (2nd – 10th) were significantly less likely to receive a transplant than candidates in the 1st SVI decile (10th decile: sub-HR = 0.79, p=0.035). For ADI, candidates in the 9th decile were significantly less likely to receive a transplant than patients in the 1st ADI decile (sub-HR = 0.86, p=0.025). For DCI, candidates in the 3rd decile were significantly less likely to receive a transplant than patients in the 1st DCI decile (sub-HR = 0.91, p=0.048).
Conclusion
All four indices showed an association with a candidate’s likelihood of transplantation, with significant variability between the indices. These findings highlight the relationship between neighborhood vulnerability and access to transplant, and the importance of investigating more deeply how best to correct for this obstacle to equitable distribution in the forthcoming continuous distribution heart allocation framework.

Evaluating Place-Based Disadvantage Indices in Heart Transplantation

Background: Although safety net coverage programs like Medicaid exist to fund health care for low-income patients, the administrative burden of the lengthy application limits uptake by eligible individuals. Therefore, many patients do not attempt to enroll until they become ill, which is common among uninsured adults diagnosed with cancer. Further, key groups, including many non-citizen immigrants (~8% of the US population), are not eligible for Medicaid, and must be covered by local charity care programs. The literature reports worse cancer outcomes for those with Medicaid, but reasons for this are unclear. The delays in enrollment for patients with uncertain coverage at the time of diagnosis – those in limbo – are understudied and may explain some of this persisting disparity. 

Objective: We estimated the patient and health system burdens for those with uncertain coverage status at the time of cancer diagnosis at Parkland Health, the main provider of cancer treatment for the uninsured in Dallas, Texas. 

Methods: We assembled the electronic health record financial encounter data of patients with an incident cancer diagnosis in the Parkland tumor registry, diagnosed from 2010 – 2022. We defined patients as being “in limbo” if they had self-pay, pending, or missing insurance plans at the date of diagnosis. We also included patients whose coverage verification date occurred after diagnosis date, since coverage programs can apply retroactively for 90 days. We used plan verification dates to identify when limbo status resolved. We used coarsened exact matching to balance across age, race, Spanish-language preference, Charlson, and screenable cancer type, then multivariate regression to compare patients that were in limbo to those that had established coverage before cancer diagnosis. 

Results: We identified 17,468 adults newly diagnosed with cancer, 80% of whom were < age 65, 55% female, 73% Hispanic and/or Black, and 30% were Spanish-language preferring. The most common cancer types were GI/colorectal (19%), breast (17%), and lung (9%); 23% were advanced stage at diagnosis and 13% died within 180 days of diagnosis. 52.1% were already enrolled in Medicaid/charity care, but one-third (35%) were in limbo at diagnosis, which lasted for a median 31 days (IQR 13 – 126). Over half (55%) of patients in limbo resolved to Medicaid or charity care. Patients who experienced limbo had a median of 596 financial account notes in the first year after diagnosis, 121 more than the comparison group (95% CI 86.7 - 156.1) and began treatment 10 days later (95% CI 7.7 - 12.7). They also had a median of 1 ED visit in the year after diagnosis, 0.2 more than patients never in limbo (95% CI 0.11 - 0.26). 

Conclusions: The administrative burden of enrolling into coverage programs for the uninsured may impose direct and indirect costs on patients and safety-net health systems and may contribute to worse cancer care outcomes. A more comprehensive accounting of the effects of administrative burdens might suggest ways to redesign coverage enrollment for the uninsured to improve care and reduce costs.

Impacts of the administrative burden of establishing healthcare coverage for the uninsured​

Background: The catastrophic Crowdstrike patch failure of July 19, 2024, exposed criticalvulnerabilities in global healthcare systems, stemming from a memory safety issue in C++ code. This null pointer error, a common pitfall in languages without automatic memorymanagement, led to system-wide failures in Microsoft-based environments while GNU/Linux and Apple systems remained unaffected. This event underscores the urgent need for robust,quantum-resistant cryptographic solutions in healthcare IT infrastructure.

Methods: We developed a protocol for building and benchmarking National Institute of Standards and Technology (NIST)-endorsed classical and post-quantum encryption algorithmson-premesis, using consumer grade Linux computers to prioritize viability for underservedregions & underfunded institutions. We compiled OpenSSL with Open Quantum Safe (OQS) Clibrary to enable post-quantum encryption development that allowed the same level of accessas Crowdstrike's faulty driver code while allowing for bindings with numerous memory safeprogramming languages. Our focus on post-quantum Key Encapsulation Mechanism (KEM) encryption reflects the ubiqutious protection that these protocols provide to securecommunication and knowledge-work as well as the relative ease of hybridization with classicalencryption protocols like Elliptical Curve Diffie-Hellman (ECDH). Following on-devicecompilation and installation of the encryption binaries, we built and executed an evaluationscript with OpenSSL's native toolkit for twenty-four NIST-endorsed KEM protocols consisting ofclassical, quantum, and hybrid KEM implementations. We evaluated the KEMs on the numberand rate of key generations (keygen), key encapsulation (encap) rate, and key decapsulations(decap) and rated their NIST post-quantum security level according to NIST advancedencryption standard (AES) exaustic key search levels.

Results: We successfully benchmarked all 24 KEM protocols, producing an examplepublic/private key pair following the evaluation. The 24 KEM protocols are evenly split acrossNIST security levels 1, 3, and 5, with 8 protocols at each.We made all relevant code, regulatoryinformation, and the example cryptographic key pairs available on the Qompass AI Github page.We released them under the GNU Affero General Public License (AGPL) to maintain the freeavailability of these encryption tools to benefit communities.Conclusion: Out of the evaluated KEMs, we propose hybrid combinations of ECDH and Kyber for most acute adoption of enhanced encryption protocols due to the layered security of nascentpost-quantum encryption with established efficient classical protocols. Currently, Google Chrome implements Kyber768/X25519 hybrid encryption as part of its Transport Layer Security (TLS), offering a familiar and accessible platform to perform institutional assessements.

Kyber Odyssey: Charting a course for secure innovation in a post-Crowdstrike world

Unhoused trauma patients present with unique injury patterns and comorbidities. While this population has a higher prevalence of substance use, the existing literature does not characterize rates of polysubstance use. This study aims to evaluate differences in substance use in housed and unhoused trauma patients at a national scale, particularly for rates of polysubstance use. 

Methods
All patients included from 1/1/2021 to 12/31/2021 in the National Trauma Database (NTDB) were retrospectively sorted into housed and unhoused groups, and their drug and alcohol screening results were collected. The NTDB reports the screening of alcohol and 13 types of drugs, of which tricyclic antidepressants were excluded. A BAC greater than or equal to 0.08% was considered alcohol positive. Polysubstance use was defined as positive screening results of 2 or more substances (drugs and/or alcohol). All statistical analyses were performed in R4.4.0.

The NTDB 2021 dataset contains a total of 1,209,097 patients, of which 9537 (0.79%) identified as unhoused. 82.64% of unhoused patients were male compared to 57.98% of housed patients. 

Unhoused patients underwent alcohol testing more frequently than housed patients (RR=1.80, 95% CI [1.78, 1.82]). Of those screened for alcohol, the unhoused had a higher likelihood of positive test results (RR=1.36, 95% CI [1.31,1.41]). Unhoused patients were also more likely to be drug tested than housed patients (RR=2.12, 95% CI [2.08, 2.15]). Of those screened for drugs, unhoused patients were more than twice as likely to test positive (RR=1.73, 95% CI [1.70,1.76]).

Compared to housed patients, unhoused patients were more likely to be screened for both drugs and alcohol (RR=2.21, 95% CI [2.17, 2.26]). In patients screened for both drugs and alcohol, a positive drug and alcohol screening was use more likely in the unhoused (RR=2.83, 95% CI [2.65, 3.01]), and negative testing for all substances was 30% less likely in the unhoused (RR=0.70, 95% CI [0.70, 0.71]). When accounting for all polysubstance combinations, the unhoused had a significantly higher risk of preinjury polysubstance use. (RR=2.59, 95% CI [2.51, 2.66]). 


Conclusion
Unhoused trauma patients have higher rates of positive tests for alcohol, drug, and polysubstance use than housed patients; however, there is a discrepancy in substance screening based on housing status.

Polysubstance Use in Unhoused Trauma Patients: Results from Drug
and Alcohol Screening in the National Trauma Data Bank

Background:
The incidence of endometrial cancer in the United States has increased, disproportionately affecting medically underserved women of lower socioeconomic backgrounds and minority ethnicities. Previous studies have shown that women with endometrial cancer residing in rural communities have a worse prognosis and lower survival rate than those of urban settings, but few have evaluated the relationship between location of residence and stage at diagnosis. We aim to determine whether rural versus urban residence influences stage of endometrial cancer at diagnosis.

Methods:
Data from the National Cancer Institute’s Surveillance Epidemiology and End Results (SEER) database from 2000-2019 was included. Eligible participants were women ages 18 and older with a diagnosis of endometrial cancer (ICD-0-3 C54.1). Rural versus urban population was the exposure variable, with stage of the endometrial cancer at diagnosis (localized vs regional / distant) as the outcome. Statistical analysis methods included exploratory and descriptive to characterize the population, Chi-Square test to determine the unadjusted association of the exposure and outcome, and logistic regression to calculate the unadjusted and adjusted odds ratio (OR) and 95% confidence intervals (CI).

Results:
192,973 women were included (59.1% aged 60+, 70.0% of white race, 88.5% residing in urban areas). Advanced stage of diagnosis of endometrial cancer was seen in 28.1% of women and was more frequent among those residing in urban areas, aged 80+, of Non-Hispanic Black ethnicity, or with Type 2 histology (p<0.001). The unadjusted odds of being diagnosed at regional/distant stage decreased by 6% in individuals of rural areas compared to those in urban areas (OR 0.94, (95% CI 0.91-0.97, p<0.001)). When adjusting for confounders, this risk became nonsignificant (OR 0.99, 95% CI, 0.95-1.02,) p=0.41)). Women aged 80+, of Non-Hispanic Black ethnicity, or with Type 2 histology had an increased odds of advanced stage at diagnosis of 41%, 45%, and nearly 400% respectively.

Conclusion:
Residential status (urban vs rural) was not associated with the stage of endometrial cancer at diagnosis. However, our study found significant associations between advanced stage and age, race, and histology type, therefore suggesting the presence of additional health disparities affecting the diagnosis of endometrial cancer.

The Effect of Rural versus Urban Residence on Stage of Endometrial Cancer at Diagnosis

With limited healthcare resources, clinics and physicians face productivity challenges. Currently, minimal workflow standardization exists. As electronic health record systems (EHR) offer more capabilities to track times for which clinic stakeholders – physicians, patient flow coordinators, nurses, technicians, trainees, and other staff – interact with the system, such secondary data can reflect clinic activities. Despite the large data repository, little is known about its accuracy and applications. Therefore, this study aimed to understand the accuracy of time-motion metrics within EHR data and demonstrate preliminary trends in the clinic workflow.

Methods
This study was conducted at the Ambulatory Cardiac Clinics at Peter Munk Cardiac Center, University Health Network in Toronto, Canada. Two trained observers collected a convenient sample of over 60 hours of observational data using a time-motion approach during 7 clinic days. Automated data captured by this clinic’s EHR, EPIC, of all in-person outpatient visits during regular hours between January to December 2023 were used. Time-related and descriptive variables with >10% missingness were excluded. The acceptable error for accurate timestamp and interval variables was ±5 minutes and ±5% of the total interval time, respectively, for ≥ 90% of EPIC data compared to observational data. Using acceptable variables as metrics, EPIC data was analyzed using summary statistics and multivariable regressions to capture preliminary clinic workflow trends.

Results
Across 9 cardiologists, 158 observational data records were compared with EPIC data. Of 49 time- and date-related variables, only 6 had less than 10% missingness (appointment date, appointment weekday, appointment time, appointment length, patient check-in time, and department-recorded check-in time), all of which were accurate. 15 descriptive variables also had less than 10% missingness. During the study period, 51,887 records from EPIC during weekdays 7 am - 5 pm were analyzed. The median patient appointment lasted 20 minutes [interquartile range 15, 60]. Furthermore, morning and afternoon clinic transitioned from 12 – 1pm and the 30-minute appointment load peaked during the middle of each morning and afternoon clinic. 

Conclusion
Secondary data automatically collected as part of the EPIC system is accurate and can be used to measure, manage, and improve clinic efficiency. However, further standardization of when stakeholders engage with the EHR is necessary to reduce missingness and increase the number of variables as clinic efficiency metrics. Additionally, more variables allow for regionalization, physician workload, and patient satisfaction to be determined for clinic function and management in addition to appointment-related metrics.

Standardizing Secondary Data from Electronic Health Record System to Assess Clinic Workflow – A Time-Motion Approach

Background
Developments in artificial intelligence (AI) have enabled programs to mimic human behaviors, including thought and speech. Capabilities of AI (e.g. ChatGPT) include summarizing findings of previous research, generating and analyzing data, and assisting in writing and editing. However, these capabilities also raise concerns surrounding copyright, attribution, plagiarism, authorship, accuracy. This cross-sectional study aims to assess how dermatology journals address the use of AI for authors and reviewers and determine if there is a difference in impact factor (IF) between journals with and without AI statements.

Methods
Dermatology journals, ranks, and IFs were identified from The Observatory of International Research in July 2024. Journals’ statements on AI were collected from their guidelines pages. When the journal deferred to the publisher for AI guidance, statements were also collected from the publishers’ guidelines pages. The Shapiro-Wilk test assessed the distribution of the data. The Mann-Whitney-Wilcoxon test examined differences in IFs between journals with and without AI statements. Significance was set at p<0.05.

Results
A total of 59 journals were included in the study, 29 (49.2%) and 41 (69.5%) of which did not have AI statements for authors and reviewers, respectively. The most common author guidelines included: requiring disclosure of AI use (n=29, 49.2%), prohibiting listing AI as author (n=27, 45.8%), and allowing AI to enhance readability and language (n=12, 20.3%). For reviewers, the most common guidelines included: cautioning against AI use due to confidentiality concerns (n=16, 27.1%), requiring declaration of AI use in peer review reports (n=5, 8.5%), and prohibiting AI use in peer review (n=3, 5.1%). No significant difference in IF was found between journals with and without AI statements for authors (p=0.26); however, journals with higher IF were more likely to have AI statements for reviewers (p=0.03).

Conclusion
We found that nearly half of the dermatology journals included in our study lacked AI guidelines for authors, and even more did not have guidelines for reviewers. Journals of all impacts have begun to release AI statements for authors, but higher impact journals are more likely to provide guidance to reviewers. As AI technology continues to evolve, it is crucial for journals to establish comprehensive and clear guidelines to ensure ethical and accurate use of AI in research. In the meantime, dermatology researchers should adhere to these guidelines to ensure transparency in their work, and readers should be aware of these standards when interpreting research findings.

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