scholarly journals Novel screening metric for the identification of at-risk peripheral artery disease patients using administrative claims data

2015 ◽  
Vol 21 (1) ◽  
pp. 33-40 ◽  
Author(s):  
Vishal Bali ◽  
Irina Yermilov ◽  
Kayla Coutts ◽  
Antonio P Legorreta
Keyword(s):  
At Risk ◽  
Peripheral Artery Disease ◽  
Claims Data ◽  
Administrative Claims ◽  
Peripheral Artery ◽  
Administrative Claims Data ◽  
Artery Disease

Abstract 91: Are At Risk Outpatient Cardiology Patients being Appropriately Evaluated for Lower Extremity PAD as Recommended by ACC/AHA Guidelines?

2012 ◽  
Vol 5 (suppl_1) ◽  
Author(s):  
Rajesh M Kabadi ◽  
Ankitkumar Patel ◽  
Rajani Sharma ◽  
Rita Schmidt ◽  
Elias Iliadis
Keyword(s):  
Risk Factors ◽  
At Risk ◽  
High Risk ◽  
Lower Extremity ◽  
Peripheral Artery Disease ◽  
Ankle Brachial Index ◽  
Heart Association ◽  
Low Risk ◽  
Peripheral Artery ◽  
Artery Disease

Background: Lower extremity peripheral artery disease (PAD) is a common syndrome that afflicts many individuals and leads to significant morbidity. Once appropriate at risk patients are identified, ankle-brachial index (ABI) testing is a relatively quick and inexpensive test that is recommended for proper assessment of PAD, per the recommendations outlined in the American College of Cardiology (ACC)/American Heart Association (AHA) Guidelines for the Management of Peripheral Artery Disease (PAD) (JACC, 2006). Outpatient cardiology practices often take care of individuals at risk for PAD and have the opportunity to test and appropriately treat this condition. Methods: A randomly selected group of 367 outpatients seen in a large academic cardiology practice from September 2011 underwent retrospective chart review. Risk factors for PAD that were assessed include history of smoking, hypertension, diabetes, hyperlipidemia, homocysteine levels, and CRP. Those that had three or more risk factors were classified as high risk and those with less than that were classified as low risk and frequency of ABI testing was evaluated. Fishers exact test was utilized for statistical analysis. Results: Fifty-one percent (N=187) of our population were classified as high risk for PAD, forty-three percent (N=158) were low risk, and six percent (N=22) were known to already have PAD. Amongst the high risk individuals, only six percent (N=12) had ABI testing performed while there were three percent (N=6) of low risk individuals that had this test (p=-0.34). Conclusions: There was no difference in ABI testing between high and low risk populations. Limitations of this study include lack of information regarding other diagnostic modalities that may have been used in place of ABI testing. Quality improvement may be achieved by increased use of such testing as this would allow for quicker identification of the disease, prompter treatment, and better outcomes, at a minimal cost.

Abstract 266: Are Outpatient Cardiologists Asking about Peripheral Artery Disease Clinical Symptoms in Low and High Risk Patients in accordance with ACC/AHA Guidelines?

2012 ◽  
Vol 5 (suppl_1) ◽  
Author(s):  
Ankitkumar K Patel ◽  
Rajesh M Kabadi ◽  
Rajani Sharma ◽  
Rita Schmidt ◽  
Elias Iliadis
Keyword(s):  
Risk Factors ◽  
At Risk ◽  
High Risk ◽  
Peripheral Artery Disease ◽  
Clinical Symptoms ◽  
Low Risk ◽  
Peripheral Artery ◽  
Symptom Screening ◽  
Risk Patients ◽  
Artery Disease

Background: Lower extremity peripheral artery disease (PAD) is a common syndrome that afflicts many individuals and leads to significant morbidity. The American College of Cardiology (ACC)/American Heart Association (AHA) Guidelines for the Management of Peripheral Artery Disease (PAD) (JACC, 2006) outlines four clinical symptoms (claudication, walking impairment, exertional leg complaints and poorly healing wounds) that should be asked to at risk patients. Outpatient cardiology practices often take care of individuals at risk for PAD and have the opportunity to screen and improve quality of medical care in accordance with professional guidelines. Methods: A group of 367 outpatients seen in a large academic cardiology practice from September 2011 underwent chart review. Risk factors for PAD that were assessed include history of smoking, hypertension, diabetes, hyperlipidemia, homocysteine levels, and CRP. Those that had three or more risk factors or a previous diagnosis of known PAD were classified as high risk and those with less than 2 risk factors were classified as low risk. Documentation of whether clinical symptoms were asked was obtained from outpatient chart. Fisher exact test was utilized for statistical analysis. Results: Fifty-seven percent (N=208) of our population were classified as high risk for PAD and forty-three percent (N=158) were low risk. Table 1 below shows assessment of clinical symptoms in high and low risk patients. Conclusions: Though both high risk and low risk PAD patients are assessed at equivalent rates for clinical symptoms, the vast majority of patients overall are underassessed. Lack of knowledge of clinical symptoms can lead to underscreening of PAD and thus undertreatment. Increasing clinical symptom screening in the outpatient cardiology setting can lead to quality improvement and adherence to ACC/AHA Guidelines.

Abstract 514: Development and Validation of Risk Model for Predicting Prevalence of Peripheral Artery Disease in a Low to Intermediate Risk Population

2016 ◽  
Vol 36 (suppl_1) ◽  
Author(s):  
Waqas A Malick ◽  
Caron B Rockman ◽  
Yu Guo ◽  
Jinfeng Xu ◽  
Mark A Adelman ◽  
...  
Keyword(s):  
At Risk ◽  
Variable Selection ◽  
Peripheral Artery Disease ◽  
Risk Model ◽  
Validation Cohort ◽  
The United States ◽  
Peripheral Artery ◽  
Derivation Cohort ◽  
Best Fitting ◽  
Artery Disease

Background: Peripheral artery disease (PAD) is associated with impaired quality of life and significant cardiovascular morbidity and mortality, yet remains under recognized and under diagnosed. Objectives: This study sought to develop and validate a risk model for the identification of individuals at risk for PAD that could be useful in the clinical setting. Methods: Twenty three variables assessed in ≈3.2 million self-referred participants without established cardiovascular disease from 2003 to 2008 who completed a medical and lifestyle questionnaire in the United States were evaluated by screening ankle brachial indices <0.90 for PAD. Subjects were divided into a derivation cohort (1.57 million) and a validation cohort (1.57 million). Lasso variable selection was used in the derivation cohort to develop the best-fitting parsimonious prediction models. Discrimination and calibrations was evaluated using the C statistic and the Hosmer-Lemeshow calibration statistic. Results: The overall prevalence of PAD was 3.96%. Using lasso variable selection, 11 variables were included in complex best-fitting model: age, sex, race, marital status, BMI group, smoking status, hypertension, diabetes, family history of PAD, physical activity, and inter-arm systolic blood pressure difference. In the validation cohort, the C-statistics for this model was .746 and the calibration was excellent (P=0.38; no significant deviation between predicted and observed outcomes). The current risk score has improved discrimination and calibration compared with other existing risk scores for PAD. Conclusion: This robust PAD risk calculator derived from a diverse population across the US provides a good risk estimate of PAD and is anticipated to assist in identifying subjects at risk for PAD.

Abstract 14374: Peripheral Artery Disease and Gait Speed in Women With and at Risk for HIV

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Emily R Cedarbaum ◽  
Yifei Ma ◽  
Rebecca Scherzer ◽  
Adaora A Adimora ◽  
Marcas Bamman ◽  
...  
Keyword(s):  
Risk Factors ◽  
At Risk ◽  
Peripheral Artery Disease ◽  
Gait Speed ◽  
Disease Risk ◽  
Univariate Analysis ◽  
Ankle Brachial Index ◽  
Peripheral Artery ◽  
Early Assessment ◽  
Artery Disease

Introduction: Peripheral artery disease (PAD) is associated with decreased physical function and increased mortality in the general population. PAD is common in women with and at risk for HIV infection, but its association with functional decline is unclear. We examined the contribution of PAD to gait speed in the Women’s Interagency HIV Study, controlling for traditional cardiovascular risk factors and HIV-related factors. Methods: 1,839 participants (72% HIV+) with measured ankle-brachial index (ABI) and 4-meter gait speed were included in analysis. ABI scores were categorized as: <0.7, moderate-severe PAD; 0.7-<0.9, mild PAD; 0.9-<1.0, borderline PAD; 1.0-<1.1, low-normal; 1.1-1.4, normal. Longitudinal regression models with repeated measures were used to examine the association of PAD category with log-transformed gait speed after controlling for demographic, behavioral, and cardiovascular disease risk factors, and HIV and HCV status. Coefficients represented percentage differences. Results: Median age was 50 years, >70% were Black. Figure 1 shows median gait speed by PAD group. In univariate analysis, compared to normal ABI, each category of PAD severity was associated with slower gait speed: 6% slower for low-normal (95% confidence interval [CI]:4%, 9%), 10% for borderline (95% CI:6%, 13%), 14% for mild (95% CI:9%, 18%), and 16% for moderate-severe (95% CI:5%, 25%). In multivariate analysis, PAD severity remained associated with 6% (95% CI:4%, 9%), 10% (95%CI:7%, 14%), 12% (95%CI:8%, 17%), and 11% (95%CI: -1%, 22%) slower gait speed, respectively. HIV/HCV coinfection reduced gait speed by 9% (95%CI:4%, 14%). Among HIV+ women, neither CD4 count nor HIV viral load was associated with gait speed. Conclusions: In middle-aged women with and at risk for HIV, greater PAD severity is associated with progressively slower gait speed. ABI measurement may be a simple and clinically useful tool for early assessment of functional declines.

Abstract 150: Machine Learning Methodology Predicts Comorbidities are Associated With Increased Total Healthcare Costs Among Patients With Severe Peripheral Artery Disease

2017 ◽  
Vol 10 (suppl_3) ◽  
Author(s):  
Jeffrey S Berger ◽  
Lloyd Haskell ◽  
Windsor Ting ◽  
Fedor Lurie ◽  
Zubin Eapen ◽  
...  
Keyword(s):  
Peripheral Artery Disease ◽  
Healthcare Costs ◽  
Index Date ◽  
Kidney Diseases ◽  
Clinical Activity ◽  
Administrative Claims ◽  
Peripheral Artery ◽  
Annual Total ◽  
The Mean ◽  
Artery Disease

Introduction: Peripheral artery disease (PAD) is manifested over a continuum of severity with comorbidities that may significantly increase healthcare costs (HC). Little research has been completed to understand the healthcare resource use (HRU) and HC in this population, specifically among severe PAD patients. We sought to understand the economic burden in this population. Methods: We identified severe PAD patients (rest pain, gangrene or ulceration) from an integrated administrative claims and electronic medical records database (Optum + Humedica 2007-15) with over 7 million patients. The first PAD diagnosis was the index date. Patients were required to be age ≥50 at index date, have clinical activity and continuous enrollment in the 6-month pre-index and 12-month or until death post-index periods. Patients with history of intracranial hemorrhage, stroke and transient ischemic attack were removed. We assessed HRU and all-cause annual total HC in the post-index period or until death, and descriptive analyses, means and SDs. Reverse Engineering and Forward Simulation (REFS TM ) models, an ensemble of Bayesian networks, were machine learned to examine baseline demographic and clinical characteristics and their association with post-index natural log all-cause annual total HC among living patients. We assessed effect estimates across the ensemble using Mean Percentage Change in Costs (MPCC) with SD. Results: The final study sample included 3,189 severe PAD patients. Mean number of all-cause hospitalizations was 1.3 (SD 1.8) and the mean length of stay was 8.0 days (SD 18.2). The mean all-cause annual total HC per patient was $56,973 (SD $91,523). Highly predictive factors associated with increased costs were (MPCC, SD): chronic ulcer of leg or foot (1.9, 0.1), chronic kidney diseases (CKD; 1.9, 0.2), cellulitis and abscess (1.8, 0.2), hypertension (1.6, 0.1), and carditis and cardiomyopathy (1.2, 0.1). Conclusion: In this study, the presence of chronic ulcers in the lower extremities and CKD were two factors most predictive of increased all-cause total HC in a geographically diverse population of severe PAD patients.

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