Venous thromboembolism performance measurement in the United States: An evolving landscape with many stakeholders.

Venous thromboembolism (VTE), including deep vein thrombosis and pulmonary embolism, is a life-threatening, costly, and common preventable complication associated with hospitalization. Although VTE prevention strategies such as risk assessment and prophylaxis are available, they are not applied uniformly or systematically across US hospitals and healthcare systems. Hospital-level performance measurement has been used nationally to promote standardized approaches for VTE prevention and incentivize the adoption of guideline-based care management. Though most measures reflect care processes rather than outcomes, certain domains including diagnosis, treatment, and continuity of care remain unmeasured. In this article, we describe the development of VTE prevention measures from various stakeholders, measure strengths and limitations, publicly reported rates, the impact of technology and health policy on measure use, and perspectives on future options for surveillance and performance monitoring.

The potential use of artificial intelligence for venous thromboembolism prophylaxis and management: clinician and healthcare informatician perspectives.

Venous thromboembolism (VTE) is the leading cause of preventable death in hospitalized patients. Artificial intelligence (AI) and machine learning (ML) can support guidelines recommending an individualized approach to risk assessment and prophylaxis. We conducted electronic surveys asking clinician and healthcare informaticians about their perspectives on AI/ML for VTE prevention and management. Of 101 respondents to the informatician survey, most were 40 years or older, male, clinicians and data scientists, and had performed research on AI/ML. Of the 607 US-based respondents to the clinician survey, most were 40 years or younger, female, physicians, and had never used AI to inform clinical practice. Most informaticians agreed that AI/ML can be used to manage VTE (56.0%). Over one-third were concerned that clinicians would not use the technology (38.9%), but the majority of clinicians believed that AI/ML probably or definitely can help with VTE prevention (70.1%). The most common concern in both groups was a perceived lack of transparency (informaticians 54.4%; clinicians 25.4%). These two surveys revealed that key stakeholders are interested in AI/ML for VTE prevention and management, and identified potential barriers to address prior to implementation.

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.

Machine learning natural language processing for identifying venous thromboembolism: systematic review and meta-analysis.

ABSTRACT: Venous thromboembolism (VTE) is a leading cause of preventable in-hospital mortality. Monitoring VTE cases is limited by the challenges of manual medical record review and diagnosis code interpretation. Natural language processing (NLP) can automate the process. Rule-based NLP methods are effective but time consuming. Machine learning (ML)-NLP methods present a promising solution. We conducted a systematic review and meta-analysis of studies published before May 2023 that use ML-NLP to identify VTE diagnoses in the electronic health records. Four reviewers screened all manuscripts, excluding studies that only used a rule-based method. A meta-analysis evaluated the pooled performance of each study's best performing model that evaluated for pulmonary embolism and/or deep vein thrombosis. Pooled sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with confidence interval (CI) were calculated by DerSimonian and Laird method using a random-effects model. Study quality was assessed using an adapted TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) tool. Thirteen studies were included in the systematic review and 8 had data available for meta-analysis. Pooled sensitivity was 0.931 (95% CI, 0.881-0.962), specificity 0.984 (95% CI, 0.967-0.992), PPV 0.910 (95% CI, 0.865-0.941) and NPV 0.985 (95% CI, 0.977-0.990). All studies met at least 13 of the 21 NLP-modified TRIPOD items, demonstrating fair quality. The highest performing models used vectorization rather than bag-of-words and deep-learning techniques such as convolutional neural networks. There was significant heterogeneity in the studies, and only 4 validated their model on an external data set. Further standardization of ML studies can help progress this novel technology toward real-world implementation.

Artificial intelligence in the prediction of venous thromboembolism: A systematic review and pooled analysis.

BACKGROUND: Accurate diagnostic and prognostic predictions of venous thromboembolism (VTE) are crucial for VTE management. Artificial intelligence (AI) enables autonomous identification of the most predictive patterns from large complex data. Although evidence regarding its performance in VTE prediction is emerging, a comprehensive analysis of performance is lacking. AIMS: To systematically review the performance of AI in the diagnosis and prediction of VTE and compare it to clinical risk assessment models (RAMs) or logistic regression models. METHODS: A systematic literature search was performed using PubMed, MEDLINE, EMBASE, and Web of Science from inception to April 20, 2021. Search terms included "artificial intelligence" and "venous thromboembolism." Eligible criteria were original studies evaluating AI in the prediction of VTE in adults and reporting one of the following outcomes: sensitivity, specificity, positive predictive value, negative predictive value, or area under receiver operating curve (AUC). Risks of bias were assessed using the PROBAST tool. Unpaired t-test was performed to compare the mean AUC from AI versus conventional methods (RAMs or logistic regression models). RESULTS: A total of 20 studies were included. Number of participants ranged from 31 to 111 888. The AI-based models included artificial neural network (six studies), support vector machines (four studies), Bayesian methods (one study), super learner ensemble (one study), genetic programming (one study), unspecified machine learning models (two studies), and multiple machine learning models (five studies). Twelve studies (60%) had both training and testing cohorts. Among 14 studies (70%) where AUCs were reported, the mean AUC for AI versus conventional methods were 0.79 (95% CI: 0.74-0.85) versus 0.61 (95% CI: 0.54-0.68), respectively (p < .001). However, the good to excellent discriminative performance of AI methods is unlikely to be replicated when used in clinical practice, because most studies had high risk of bias due to missing data handling and outcome determination. CONCLUSION: The use of AI appears to improve the accuracy of diagnostic and prognostic prediction of VTE over conventional risk models; however, there was a high risk of bias observed across studies. Future studies should focus on transparent reporting, external validation, and clinical application of these models.

Venous thromboembolism prophylaxis for hospitalized adult patients: a survey of US health care providers on attitudes and practices.

Background: Venous thromboembolism (VTE) is a leading cause of preventable mortality among hospitalized patients, but appropriate risk assessment and thromboprophylaxis remain underutilized or misapplied. Objectives: We conducted an electronic survey of US health care providers to explore attitudes, practices, and barriers related to thromboprophylaxis in adult hospitalized patients and at discharge. Results: A total of 607 US respondents completed the survey: 63.1% reported working in an academic hospital, 70.7% identified as physicians, and hospital medicine was the most frequent specialty (52.1%). The majority of respondents agreed that VTE prophylaxis is important (98.8%; 95% CI: 97.6%-99.5%) and that current measures are safe (92.6%; 95% CI: 90.2%-94.5%) and effective (93.8%; 95% CI: 91.6%-95.6%), but only half (52.0%; 95% CI: 47.9%-56.0%) believed that hospitalized patients at their institution are on appropriate VTE prophylaxis almost all the time. One-third (35.4%) reported using a risk assessment model (RAM) to determine VTE prophylaxis need; 44.9% reported unfamiliarity with RAMs. The most common recommendation for improving rates of appropriate thromboprophylaxis was to leverage technology. A majority of respondents (84.5%) do not reassess a patient's need for VTE prophylaxis at discharge, and a minority educates patients about the risk (16.2%) or symptoms (18.9%) of VTE at discharge. Conclusion: Despite guideline recommendations to use RAMs, the majority of providers in our survey do not use them. A majority of respondents believed that technology could help improve VTE prophylaxis rates. A majority of respondents do not reassess the risk of VTE at discharge or educate patients about this risk of VTE at discharge.

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.

Cancer-associated venous thromboembolism: Incidence and features in a racially diverse population.

BACKGROUND: Data on the population-based incidence of cancer-associated venous thromboembolism (VTE) from racially diverse populations are limited. OBJECTIVE: To evaluate the incidence and burden of cancer-associated VTE, including demographic and racial subgroups in the general population of Oklahoma County-which closely mirrors the United States. DESIGN: A population-based prospective study. SETTING: We conducted surveillance of VTE at tertiary care facilities and outpatient clinics in Oklahoma County, Oklahoma, from 2012-2014. Surveillance included reviewing all imaging reports used to diagnose VTE and identifying VTE events from hospital discharge data and death certificates. Cancer status was determined by linkage to the Oklahoma Central Cancer Registry. MEASUREMENTS: We used Poisson regression to calculate crude and age-adjusted incidence rates of cancer-associated VTE per 100 000 general population per year, with 95% confidence intervals (95% CI). RESULTS: The age-adjusted incidence (95% CI) of cancer-associated VTE among adults age ≥ 18 was 70.0 (65.1-75.3). The age-adjusted incidence rates (95% CI) were 85.9 (72.7-101.6) for non-Hispanic Blacks, 79.5 (13.2-86.5) for non-Hispanic Whites, 18.8 (8.9-39.4) for Native Americans, 15.6 (7.0-34.8) for Asian/Pacific Islanders, and 15.2 (9.2-25.1) for Hispanics. Recurrent VTE up to 2 years after the initial diagnosis occurred in 38 of 304 patients (12.5%) with active cancer and in 34 of 424 patients (8.0%) with a history of cancer > 6 months previously. CONCLUSION: Age-adjusted incidence rates of cancer-associated VTE vary substantially by race and ethnicity. The relatively high incidence rates of first VTE and of recurrence warrant further assessment of strategies to prevent VTE among cancer patients.

Epidemiology of cerebral venous sinus thrombosis and cerebral venous sinus thrombosis with thrombocytopenia in the United States, 2018 and 2019.

Background: Population-based data about cerebral venous sinus thrombosis (CVST) are limited. Objectives: To investigate the epidemiology of CVST in the United States. Patients/Methods: Three administrative data systems were analyzed: the 2018 Healthcare Cost and Utilization Project National Inpatient Sample (NIS) the 2019 IBM MarketScan Commercial and Medicare Supplemental Claims Database, and the 2019 IBM MarketScan Multi-state Medicaid Database. CVST, thrombocytopenia, and numerous comorbidities were identified using the International Classification of Diseases, Tenth Revision, Clinical Modification codes. Incidence rates of CVST and CVST with thrombocytopenia were estimated (per 100,000 total US population [NIS] and per 100,000 population aged 0 to 64 years covered by relevant contributing health plans [MarketScan samples]). Comorbidity prevalence was estimated among CVST cases versus total inpatients in the NIS sample. Recent pregnancy prevalence was estimated for the Commercial sample. Results: Incidence rates of CVST in NIS, Commercial, and Medicaid samples were 2.85, 2.45, and 3.16, respectively. Incidence rates of CVST with thrombocytopenia were 0.21, 0.22, and 0.16, respectively. In all samples, CVST incidence increased with age; however, peak incidence was reached at younger ages in females than males. Compared with the general inpatient population, persons with CVST had higher prevalences of hemorrhagic stroke, ischemic stroke, other venous thromboembolism (VTE), central nervous system infection, head or neck infection, prior VTE, thrombophilia, malignancy, head injury, hemorrhagic disorder, and connective tissue disorders. Women aged 18 to 49 years with CVST had a higher pregnancy prevalence than the same-aged general population. Conclusions: Our findings provide recent and comprehensive data on the epidemiology of CVST and CVST with thrombocytopenia.

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.

Incidence of Venous Thromboembolism in a Racially Diverse Population of Oklahoma County, Oklahoma.

BACKGROUND: Contemporary incidence data for venous thromboembolism (VTE) from racially diverse populations are limited. The racial distribution of Oklahoma County closely mirrors that of the United States. OBJECTIVE: To evaluate VTE incidence and mortality, including demographic and racial subgroups. DESIGN: Population-based prospective study. SETTING: We conducted VTE surveillance at all relevant tertiary care facilities and outpatient clinics in Oklahoma County, Oklahoma during 2012 to 2014, using both active and passive methods. Active surveillance involved reviewing all imaging reports used to diagnose VTE. Passive surveillance entailed identifying VTE events from hospital discharge data and death certificate records. MEASUREMENTS: We used Poisson regression to calculate crude, age-stratified, and age-adjusted incidence and mortality rates per 1,000 population per year and 95% confidence intervals (CIs). RESULTS: The incidence rate of all VTE was 3.02 (2.92-3.12) for those age ≥18 years and 0.05 (0.04-0.08) for those <18 years. The age-adjusted incidence rates of all VTE, deep vein thrombosis, and pulmonary embolism were 2.47 (95% CI: 2.39-2.55), 1.47 (1.41-1.54), and 0.99 (0.93-1.04), respectively. The age-adjusted VTE incidence and the 30-day mortality rates, respectively, were 0.63 and 0.121 for Asians/Pacific Islanders, 3.25 and 0.355 for blacks, 0.67 and 0.111 for Hispanics, 1.25 and 0.195 for Native Americans, and 2.71 and 0.396 for whites. CONCLUSION: The age-adjusted VTE incidence and mortality rates vary substantially by race. The incidence of three per 1,000 adults per year indicates an important disease burden, and is informative of the burden in the U.S.

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

BACKGROUND: Systematic surveillance for venous thromboembolism (VTE) in the United States has been recommended by several organizations. Despite adoption of electronic medical records (EMRs) by most health care providers and facilities, however, systematic surveillance for VTE is not available. OBJECTIVES: This article develops a comprehensive, population-based surveillance strategy for VTE in a defined geographical region. METHODS: The primary surveillance strategy combined computerized searches of the EMR with a manual review of imaging data at the Duke University Health System in Durham County, North Carolina, United States. Different strategies of searching the EMR were explored. Consolidation of results with autopsy reports (nonsearchable in the EMR) and with results from the Durham Veterans' Administration Medical Center was performed to provide a comprehensive report of new VTE from the defined region over a 2-year timeframe. RESULTS: Monthly searches of the primary EMR missed a significant number of patients with new VTE who were identified by a separate manual search of radiology records, apparently related to delays in data entry and coding into the EMR. Comprehensive searches incorporating a location-restricted strategy were incomplete due to the assigned residence reflecting the current address and not the address at the time of event. The most comprehensive strategy omitted the geographic restriction step and identified all patients with VTE followed by manual review of individual records to remove incorrect entries (e.g., outside the surveillance time period or geographic location; no evidence for VTE). Consolidation of results from the EMR searches with results from autopsy reports and the separate facility identified additional patients not diagnosed within the Duke system. CONCLUSION: We identified several challenges with implementing a comprehensive VTE surveillance program that could limit accuracy of the results. Improved electronic strategies are needed to cross-reference patients across multiple health systems and to minimize the need for manual review and confirmation of results.

Incidence and Outcome of Severe and Nonsevere Thrombocytopenia Associated With Zika Virus Infection-Puerto Rico, 2016.

BACKGROUND: Zika virus (ZIKV) infection has been associated with severe thrombocytopenia. We describe the incidence, clinical manifestations, and outcomes of patients with ZIKV infection and thrombocytopenia. METHODS: We reviewed medical records of patients with ZIKV infection and thrombocytopenia (platelet count <100 ×109 cells/L) in Puerto Rico during 2016. Severe thrombocytopenia was defined by platelet count <20 ×109/L or a platelet count <50 ×109/L and treatment for immune thrombocytopenia (ITP). RESULTS: Of 37 878 patients with ZIKV infection, 47 (0.1%) had thrombocytopenia in the absence of an alternative etiology (1.4 cases/100 000 population), including 12 with severe thrombocytopenia. Most patients with thrombocytopenia were adult (77%) and male (53%). Platelet nadir occurred a median (range) of 6 (1-16) and 5 (0-34) days after symptom onset for patients with severe and nonsevere thrombocytopenia, respectively. Among patients with severe thrombocytopenia, all had bleeding, 33% were admitted to the intensive care unit, and 8% died; 50% were treated for ITP. Among 5 patients with severe thrombocytopenia who received intravenous immunoglobulin, the median platelet count increase (range) was 112 (65-202) ×109/L. In contrast, among 4 patients who received platelet transfusion, the median increase in platelet count (range) was 8.5 (-6 to 52) ×109/L. CONCLUSIONS: Patients with severe thrombocytopenia and ZIKV infection experienced prominent acute morbidity. Consistent with recommended management, administration of ITP treatments to such patients may be more efficacious than platelet transfusion in resolving thrombocytopenia. Severe thrombocytopenia should be considered a rare outcome of ZIKV infection.

The design and implementation of a new surveillance system for venous thromboembolism using combined active and passive methods.

Estimates of venous thromboembolism (VTE) incidence in the United States are limited by lack of a national surveillance system. We implemented a population-based surveillance system in Oklahoma County, OK, for April 1, 2012 to March 31, 2014, to estimate the incidences of first-time and recurrent VTE events, VTE-related mortality, and the proportion of case patients with provoked versus unprovoked VTE. The Commissioner of Health made VTE a reportable condition and delegated surveillance-related responsibilities to the University of Oklahoma, College of Public Health. The surveillance system included active and passive methods. Active surveillance involved reviewing imaging studies (such as chest computed tomography and compression ultrasounds) from all inpatient and outpatient facilities. Interrater agreement between surveillance officers collecting data was assessed using κ. Passive surveillance used International Classification of Disease, Ninth Revision (ICD-9) codes from hospital discharge data to identify cases. The sensitivity and specificity of various ICD-9-based case definitions will be assessed by comparison with cases identified through active surveillance. As of February 1, 2015, we screened 54,494 (99.5%) of the imaging studies and identified 2,725 case patients, of which 91.6% were from inpatient facilities, and 8.4% were from outpatient facilities. Agreement between surveillance officers was high (κ ≥0.61 for 93.2% of variables). Agreement for the diagnosis of pulmonary embolism and diagnosis of deep vein thrombosis was κ = 0.92 (95% CI 0.74-1.00) and κ = 0.89 (95% CI 0.71-1.00), respectively. This surveillance system will provide data on the accuracy of ICD-9-based case definitions for surveillance of VTE events and help the Centers for Disease Control and Prevention develop a national VTE surveillance system.

Using multiple sources of data for surveillance of postoperative venous thromboembolism among surgical patients treated in Department of Veterans Affairs hospitals, 2005-2010.

BACKGROUND: There are limitations to using administrative data to identify postoperative venous thromboembolism (VTE). We used a novel approach to quantify postoperative VTE events among Department of Veterans Affairs (VA) surgical patients during 2005-2010. METHODS: We used VA administrative data to exclude patients with VTE during 12 months prior to surgery. We identified probable postoperative VTE events within 30 and 90 days post-surgery in three settings: 1) pre-discharge inpatient, using a VTE diagnosis code and a pharmacy record for anticoagulation; 2) post-discharge inpatient, using a VTE diagnosis code followed by a pharmacy record for anticoagulation within 7 days; and 3) outpatient, using a VTE diagnosis code and either anticoagulation or a therapeutic procedure code with natural language processing (NLP) to confirm acute VTE in clinical notes. RESULTS: Among 468,515 surgeries without prior VTE, probable VTEs were documented within 30 and 90 days in 3,931 (0.8%) and 5,904 (1.3%), respectively. Of probable VTEs within 30 or 90 days post-surgery, 47.8% and 62.9%, respectively, were diagnosed post-discharge. Among post-discharge VTE diagnoses, 86% resulted in a VA hospital readmission. Fewer than 25% of outpatient records with both VTE diagnoses and anticoagulation prescriptions were confirmed by NLP as acute VTE events. CONCLUSION: More than half of postoperative VTE events were diagnosed post-discharge; analyses of surgical discharge records are inadequate to identify postoperative VTE. The NLP results demonstrate that the combination of VTE diagnoses and anticoagulation prescriptions in outpatient administrative records cannot be used to validly identify postoperative VTE events.

Public health surveillance of nonmalignant blood disorders.

Nonmalignant blood disorders currently affect millions of Americans, and their prevalence is expected to grow over the next several decades. This is owing to improvements in treatment leading to increased life expectancy of people with hereditary conditions, like sickle cell disease and hemophilia, but also the rising occurrence of risk factors for venous thromboembolism. The lack of adequate surveillance systems to monitor these conditions and their associated health indicators is a significant barrier to successfully assess, inform, and measure prevention efforts and progress toward national health goals. CDC is strengthening surveillance activities for blood disorders by improving and developing new methods that are tailored to best capture and monitor the epidemiologic characteristics unique to each disorder. These activities will provide a robust evidence base for public health action to improve the health of patients affected by or at risk for these disorders.

Hospitalizations of adults ≥60 years of age with venous thromboembolism.

We assessed the rates, trends, and factors associated with venous thromboembolism (VTE) diagnosis among hospitalizations of adults ≥60 years of age during the period 2001 to 2010. Data from the National Hospital Discharge Survey were used for this study. During the period 2001 to 2010, the estimated annual number of hospitalizations in which a VTE diagnosis was recorded, among adults ≥ 60 years of age, ranged from approximately 2 70 000 in 2001 to 4 23 000 in 2010. The rate of such hospitalizations per 1 00 000 US population ≥60 years of age ranged from 581 in 2001 to 739 in 2010. During the period 2001 to 2004, there was a significant increasing trend in the rate of hospitalizations with VTE among women ≥60 years of age. The factors positively associated with an increased risk of VTE diagnosis were female sex, summer and autumn seasons (compared with spring), venous catheterization, cancer, and greater length of hospital stay.

Clustering patterns of comorbidities associated with in-hospital death in hospitalizations of US adults with venous thromboembolism.

BACKGROUND: Venous thromboembolism (VTE) is a significant source of mortality, morbidity, disability, and impaired health-related quality of life in the world. OBJECTIVE: We aimed to evaluate the clustering patterns and associations of 29 comorbidities with in-hospital death among adult hospitalizations with a diagnosis of VTE in the United States by analyzing data from the 2009 Nationwide Inpatient Sample. METHODS: This cross-sectional study included 153,124 adult hospitalizations with a diagnosis of VTE. Adjusted rate ratios and 95% confidence intervals (CI) for in-hospital death were generated by using multivariable log-linear regression models to measure independent associations between comorbidities and in-hospital death. RESULTS: We estimated that 44,200 in-hospital deaths occurred in 2009 among 773,273 US adult hospitalizations with a diagnosis of VTE. Subgroups of hospitalizations with comorbidities of "congestive heart failure," "chronic pulmonary disease," "coagulopathy," "liver disease," "lymphoma," "fluid and electrolyte disorders," "metastatic cancer," "peripheral vascular disorders," "pulmonary circulation disorders," "renal failure," "solid tumor without metastasis," or "weight loss" were positively and independently associated with 1.07 (95% CI: 1.02-1.12 ) to 2.06 (95% CI: 1.97-2.16) times increased likelihoods of in-hospital death, when compared to those without the corresponding comorbidities. The clustering patterns of these comorbidities by 4 disease categories (i.e., "cancer," "cardiovascular/respiratory/blood," "gastrointestinal/urologic," and "nutritional/bodyweight") were associated with 2.74 to 10.28 times increased likelihoods of in-hospital death, as compared to hospitalizations without any of these comorbidities. The overall increase in the cumulative number of comorbidities corresponded to significantly elevated risks (P-trend<0.01) for in-hospital death among hospitalizations with a diagnosis of VTE. CONCLUSION: The presence of multiple comorbidities is ubiquitous among hospitalizations of adults with VTE and among in-hospital deaths with VTE in the United States. The findings of our study further suggest that, among hospitalizations of adults with VTE, the presence of certain comorbidities or clustering of these comorbidities significantly elevates the risk of in-hospital death.

Correlates of in-hospital deaths among hospitalizations with pulmonary embolism: findings from the 2001-2008 National Hospital Discharge Survey.

BACKGROUND: Deep vein thrombosis and pulmonary embolism (PE) are responsible for substantial mortality, morbidity, and impaired health-related quality of life. The aim of this study was to evaluate the correlates of in-hospital deaths among hospitalizations with a diagnosis of PE in the United States. METHODS: By using data from the 2001-2008 National Hospital Discharge Survey, we assessed the correlates of in-hospital deaths among 14,721 hospitalizations with a diagnosis of PE and among subgroups stratified by age, sex, race, days of hospital stay, type of admission, cancer, pneumonia, and fractures. We produced adjusted rate ratios (aRR) and 95% confidence intervals using log-linear multivariate regression models. RESULTS: Regardless of the listing position of diagnostic codes, we observed an increased likelihood of in-hospital death in subgroups of hospitalizations with ages 50 years and older (aRR = 1.82-8.48), less than 7 days of hospital stay (aRR = 1.43-1.57), cancer (aRR = 2.10-2.28), pneumonia (aRR = 1.79-2.20), or fractures (aRR = 2.18) (except for first-listed PE), when compared to the reference groups with ages 1-49 years, 7 days or more of hospital stay, without cancer, pneumonia, or fractures while adjusting for covariates. In addition, we observed an increased likelihood of in-hospital death for first-listed PE in hospitalizations of women, when compared to those of men (aRR = 1.45). CONCLUSIONS: The results of this study provide support for identifying, developing, and implementing effective, evidence-based clinical assessment and management strategies to reduce PE-related morbidity and mortality among hospitalized PE patients who may have concurrent health conditions including cancer, pneumonia, and fractures.