Design and Implementation of a Comprehensive Surveillance System for Venous Thromboembolism in a Defined Region Using Electronic and Manual Approaches

An epidemiologic study comparing cancer- and noncancer-associated venous thromboembolism in a racially diverse Southeastern United States county

Background

Cancer-associated venous thromboembolism (CA-VTE) represents a major cause of morbidity and mortality in patients with cancer. Despite poor outcomes, there is an ongoing knowledge gap in epidemiologic data related to this association.

Objectives

To compare venous thromboembolism (VTE) characteristics, risk factors, and outcomes between patients with and without active cancer in a racially diverse population.

Methods

Our surveillance project occurred at the 3 hospitals in Durham County, North Carolina, from April 2012 through March 2014. Electronic and manual methods were used to identify unique Durham County residents with VTE.

Results

We identified 987 patients with VTE during the surveillance period. Of these, 189 patients had active cancer at the time of their VTE event. Patients with CA-VTE were older (median age: 69 years vs 60 years, P < .0001) and had a lower body mass index (median body mass index: 26.0 kg/m2 vs 28.4 kg/m2, P = .0001) than noncancer patients. The most common cancers in our cohort were gastrointestinal, breast, genitourinary, and lung. The proportion of VTE cases with pulmonary embolism (PE) was greater in the cancer cohort compared with that in the noncancer cohort (58.2% vs 44.0%, P = .0004). Overall survival was lower in the CA-VTE group than in patients without cancer (P < .0001). Black patients with CA-VTE had lower proportion of PE (52.3% vs 67.1%, P = .05) but had decreased survival (P < .0003) in comparison with White patients.

Conclusion

Future studies may be needed to continue to evaluate local and national VTE data to improve VTE prevention strategies and CA-VTE outcomes.

Provider Response to a Venous Thromboembolism Risk Assessment and Prophylaxis Ordering Tool: Observational Study

OBJECTIVES

Our health system launched an initiative to regulate venous thromboembolism (VTE) risk assessment and prophylaxis with electronically embedded risk assessment models based on validated clinical prediction rules. Prior to system-wide implementation, usability testing was conducted on the VTE clinical decision support system (CDSS) to assess provider perceptions, facilitate adoption, and usage of the tool. The objective of this study was to conduct usability testing with end users on the CDSS' risk assessment model and prophylaxis ordering components.

METHODS

This laboratory usability testing study was conducted with 24 health care providers. Participants were given two case scenarios that mirrored real-world scenarios to assess likelihood of use and adoption. During each case scenario, participants engaged in a think-aloud session, verbalizing their decision-making process while interacting with the tool. Following each case scenario, participants completed the System Usability Scale (SUS) and a posttask interview. Participants' comments and interactions with the VTE CDSS were placed into coding categories and analyzed for generalizable themes by three independent coders.

RESULTS

Of the 24 participants, 50% were female and the mean age of all participants was 32.76 years. The average SUS across the different services lines was 72.39 (C grade). Each participant's comments were grouped into three overarching themes: functionality, visibility/navigation, and content. Comments included personalizing workflow for each service line, minimizing the number of clicks, clearly defining risk models, including background on risk scores, and providing treatment guidelines for order sets.

CONCLUSION

An important step toward providing quality health care to patients at risk of developing a VTE event is providing user-friendly tools to providers. Following usability testing, our study revealed opportunities to positively impact provider behavior and acceptance. The rigor and breadth of this usability testing study and adoption of the optimizations should increase provider adoption and retention of the VTE CDSS.

Racial differences in venous thromboembolism: A surveillance program in Durham County, North Carolina

Background

Venous thromboembolism (VTE) affects approximately 1-2 individuals per 1000 annually and is associated with an increased risk for pulmonary hypertension, postthrombotic syndrome, and recurrent VTE.

Objective

To determine risk factors, incidence, treatments, and outcomes of VTE through a 2-year surveillance program initiated in Durham County, North Carolina (population approximately 280,000 at time of study).

Patients/Methods

We performed a retrospective analysis of data actively collected from three hospitals in Durham County during the surveillance period.

Results

A total of 987 patients were diagnosed with VTE, for an annual rate of 1.76 per 1000 individuals. Hospital-associated VTE occurred in 167 hospitalized patients (16.9%) and 271 outpatients who were hospitalized within 90 days of diagnosis (27.5%). Annual incidence was 1.98 per 1000 Black individuals compared to 1.25 per 1000 White individuals (p < 0.0001), and Black individuals with VTE were younger than White individuals (p < 0.0001). Common risk factors included active cancer, prolonged immobility, and obesity, and approximately half were still taking anticoagulant therapy 1 year later. A total of 224 patients died by 1 year (28.5% of patients for whom outcomes could be confirmed), and Black patients were more likely to have recurrent VTE than White patients during the first 6 months following initial presentation (9.4% vs. 4.1%, p = 0.01).

Conclusions

Ongoing surveillance provides an effective strategy to identify patients with VTE and monitor treatment and outcomes. We demonstrated that hospital-associated VTE continues to be a major contributor to the burden of VTE and confirmed the higher incidence of VTE in Black compared to White individuals.

Exploring the Applicability of Using Natural Language Processing to Support Nationwide Venous Thromboembolism Surveillance: Model Evaluation Study

Background

Venous thromboembolism (VTE) is a preventable, common vascular disease that has been estimated to affect up to 900,000 people per year. It has been associated with risk factors such as recent surgery, cancer, and hospitalization. VTE surveillance for patient management and safety can be improved via natural language processing (NLP). NLP tools have the ability to access electronic medical records, identify patients that meet the VTE case definition, and subsequently enter the relevant information into a database for hospital review.

Objective

We aimed to evaluate the performance of a VTE identification model of IDEAL-X (Information and Data Extraction Using Adaptive Learning; Emory University)-an NLP tool-in automatically classifying cases of VTE by "reading" unstructured text from diagnostic imaging records collected from 2012 to 2014.

Methods

After accessing imaging records from pilot surveillance systems for VTE from Duke University and the University of Oklahoma Health Sciences Center (OUHSC), we used a VTE identification model of IDEAL-X to classify cases of VTE that had previously been manually classified. Experts reviewed the technicians' comments in each record to determine if a VTE event occurred. The performance measures calculated (with 95% CIs) were accuracy, sensitivity, specificity, and positive and negative predictive values. Chi-square tests of homogeneity were conducted to evaluate differences in performance measures by site, using a significance level of .05.

Results

The VTE model of IDEAL-X "read" 1591 records from Duke University and 1487 records from the OUHSC, for a total of 3078 records. The combined performance measures were 93.7% accuracy (95% CI 93.7%-93.8%), 96.3% sensitivity (95% CI 96.2%-96.4%), 92% specificity (95% CI 91.9%-92%), an 89.1% positive predictive value (95% CI 89%-89.2%), and a 97.3% negative predictive value (95% CI 97.3%-97.4%). The sensitivity was higher at Duke University (97.9%, 95% CI 97.8%-98%) than at the OUHSC (93.3%, 95% CI 93.1%-93.4%; P<.001), but the specificity was higher at the OUHSC (95.9%, 95% CI 95.8%-96%) than at Duke University (86.5%, 95% CI 86.4%-86.7%; P<.001).

Conclusions

The VTE model of IDEAL-X accurately classified cases of VTE from the pilot surveillance systems of two separate health systems in Durham, North Carolina, and Oklahoma City, Oklahoma. NLP is a promising tool for the design and implementation of an automated, cost-effective national surveillance system for VTE. Conducting public health surveillance at a national scale is important for measuring disease burden and the impact of prevention measures. We recommend additional studies to identify how integrating IDEAL-X in a medical record system could further automate the surveillance process.

Predicting the occurrence of venous thromboembolism: construction and verification of risk warning model

Background

The onset of venous thromboembolism is insidious and the prognosis is poor. In this study, we aimed to construct a VTE risk warning model and testified its clinical application value.

Methods

Preliminary construction of the VTE risk warning model was carried out according to the independent risk warning indicators of VTE screened by Logistic regression analysis. The truncated value of screening VTE was obtained and the model was evaluated. ROC curve analysis was used to compare the test of Caprini risk assessment scale and VTE risk warning model. The cut-off value of the VTE risk warning model was used to evaluate the test effectiveness of the model for VTE patients with validation data set.

Results

The VTE risk warning model is p = e^x / (1+ e^x), x = − 4.840 + 2.557 • X₁₀₍₁₎ + 1.432 • X₁₄₍₁₎ + 2.977 • X₁₅₍₁₎ + 3.445 • X₁₈₍₁₎ + 1.086 • X₂₅₍₁₎ + 0.249 • X₃₄ + 0.282 • X₄₁. ROC curve results show that: AUC (95%CI), cutoff value, sensitivity, specificity, accuracy, Youden index, Caprini risk assessment scale is 0.596 (0.552, 0.638), 5, 26.07, 96.50, 61.3%, 0.226, VTE risk warning model is 0.960 (0.940, 0.976), 0.438, 92.61, 91.83, 92.2%, 0.844, respectively, with statistically significant differences (Z = 14.521, P < 0.0001). The accuracy and Youden index of VTE screening using VTE risk warning model were 81.8 and 62.5%, respectively.

Conclusions

VTE risk warning model had high accuracy in predicting VTE occurrence in hospitalized patients. Its test performance was better than Caprini risk assessment scale. It also had high test performance in external population.

Preventing Diagnostic Errors in Ambulatory Care: An Electronic Notification Tool for Incomplete Radiology Tests

BACKGROUND

Failure to complete recommended diagnostic tests may increase the risk of diagnostic errors.

OBJECTIVES

The aim of this study is to develop and evaluate an electronic monitoring tool that notifies the responsible clinician of incomplete imaging tests for their ambulatory patients.

METHODS

A results notification workflow engine was created at an academic medical center. It identified future appointments for imaging studies and notified the ordering physician of incomplete tests by secure email. To assess the impact of the intervention, the project team surveyed participating physicians and measured test completion rates within 90 days of the scheduled appointment. Analyses compared test completion rates among patients of intervention and usual care clinicians at baseline and follow-up. A multivariate logistic regression model was used to control for secular trends and differences between cohorts.

RESULTS

A total of 725 patients of 16 intervention physicians had 1,016 delayed imaging studies; 2,023 patients of 42 usual care clinicians had 2,697 delayed studies. In the first month, physicians indicated in 23/30 cases that they were unaware of the missed test prior to notification. The 90-day test completion rate was lower in the usual care than intervention group in the 6-month baseline period (18.8 vs. 22.1%, p = 0.119). During the 12-month follow-up period, there was a significant improvement favoring the intervention group (20.9 vs. 25.5%, p = 0.027). The change was driven by improved completion rates among patients referred for mammography (21.0 vs. 30.1%, p = 0.003). Multivariate analyses showed no significant impact of the intervention.

CONCLUSION

There was a temporal association between email alerts to physicians about missed imaging tests and improved test completion at 90 days, although baseline differences in intervention and usual care groups limited the ability to draw definitive conclusions. Research is needed to understand the potential benefits and limitations of missed test notifications to reduce the risk of delayed diagnoses, particularly in vulnerable patient populations.