Using electronic health record system triggers to target delivery of a patient-centered intervention to improve venous thromboembolism prevention for hospitalized patients: Is there a differential effect by race?

Owodunni, Oluwafemi P.; Haut, Elliott R.; Shaffer, Dauryne L.; Hobson, Deborah B.; Wang, Jiangxia; Yenokyan, Gayane; Kraus, Peggy S.; Aboagye, Jonathan; Florecki, Katherine L.; Webster, Kristen L. W.; Holzmueller, Christine G.; Streiff, Michael B.; Lau, Brandyn

doi:10.1371/journal.pone.0227339

Cited by 12 publications

(12 citation statements)

References 41 publications

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“…Other studies have reached similar conclusions [31][32][33]. Though, many embedded VTE warning software has been developed and integrated with electronic medical record system but this software is mostly based on Caprini Risk Assessment Scale, or Padua Assessment Scale, etc [34][35][36][37]. Vyas et al [38] adopted the analysis way of Ishikawa Fishbone Diagram, and found that main reason for the improper prevention of DVT were the lacks of unified standard specifications, the computerized input system for doctors' orders and effective risk assessment methods [39].…”

Section: Clinical Status Of Early Warning Mechanism Of Venous Thrombomentioning

confidence: 67%

“…The VTE prediction model are established with the purpose of making accurate assessment and diagnosis of VTE in the first time and avoiding adulterating human factors as much as possible. We know that there is a lot of VTE-related information in the electronic medical record system [27,[33][34][35][40][41][42], and this information needs to be further explored and fully utilized in the clinical warning of VTE. The VTE risk warning model makes full use of the Caprini risk assessment scale, which is widely used in clinical medicine and surgery, with the important clinical symptoms and signs of VTE patients and laboratory examination indicators, to carry out comprehensive and multidimensional comprehensive warning and achieve higher prediction efficiency.…”

Section: Clinical Significance Of Early Warning Model For Venous Thromentioning

confidence: 99%

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Predicting the occurrence of venous thromboembolism: construction and verification of Risk Warning Model

Shen

Liu

et al. 2020

Preprint

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Background: The onset of venous thromboembolism is insidious and the prognosis is poor. In this study, we aimed to construct a VTE risk early warning model and explore the clinical application value of the VTE risk early warning model. 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 in previous studies. The truncated value of screening VTE was obtained and the model was evaluated. ROC curve analysis was used to compare the test performance of Caprini risk assessment scale and VTE risk warning model on VTE. The validation data set was established, and 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 = ex / ( 1+ ex ) , 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 (95%CI), accuracy, Youden index (95%), sensitivity, specificity and other evaluation indexes, Caprini risk assessment scale is 0.596 (0.552, 0.638), > 5 (> 4, > 5), 61.3%, 0.226 (0.167, 0.290), 26.07%, 96.50%, VTE risk warning model is 0.960 (0.940, 0.976), > 0.438 (> 0.263), respectively. >, 0.504), 92.2%, 0.844 (0.789, 0.879), 92.61%, 91.83%, 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 has high accuracy in predicting the occurrence of VTE in hospitalized patients, and its test performance is higher than Caprini risk assessment scale. It also has high test performance for VTE in external population.

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Section: Clinical Status Of Early Warning Mechanism Of Venous Thrombomentioning

confidence: 67%

Section: Clinical Significance Of Early Warning Model For Venous Thromentioning

confidence: 99%

Predicting the occurrence of venous thromboembolism: construction and verification of Risk Warning Model

Shen

Liu

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Though, many embedded VTE warning software has been developed and integrated with electronic medical record system but such software was mostly based on Caprini Risk Assessment Scale, or Padua Assessment Scale, etc. [33][34][35][36]. Vyas et al [37] adopted the analysis way of Ishikawa Fishbone Diagram, and found that main reason for the improper prevention of DVT were the lacks of unified standard specifications, the computerized input system for doctors' orders and effective risk assessment methods [38].…”

Section: Clinical Status Of Vte Early Warning Mechanismmentioning

confidence: 99%

“…The VTE prediction model were established with purpose of making accurate assessment and diagnosis of VTE in the first time and avoiding adulterating human factors as much as possible. We know that there is a lot of VTE-related information in the electronic medical record system [27,[33][34][35][39][40][41], and such information needs to be further explored and fully utilized in the clinical VTE warning. The VTE risk warning model made full use of Caprini risk assessment scale, which was widely used in clinical medicine and surgery, with the important clinical symptoms and signs of VTE patients and laboratory examination indicators, to carry out comprehensive and multi-dimensional warning and achieve higher prediction efficiency.…”

Section: Clinical Significance Of Vte Early Warning Modelmentioning

confidence: 99%

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

Shen

Liu

et al. 2020

BMC Cardiovasc Disord

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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 cutoff 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 • X 10(1) + 1.432 • X 14(1) + 2.977 • X 15(1) + 3.445 • X 18(1) + 1.086 • X 25(1) + 0.249 • X 34 + 0.282 • X 41. 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.

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“…10,15 For patient refusal of prophylaxis doses, 14 we conducted a second trial and found that a real-time, alert-triggered patient-centered education bundle significantly reduced any missed dose of VTE prophylaxis by 43% and patient refusal by 47%, 16 with no difference by race. 17…”

Section: Introductionmentioning

confidence: 99%

Disseminating a patient-centered education bundle to reduce missed doses of pharmacologic venous thromboembolism (VTE) prophylaxis to a community hospital

Owodunni

Lau

Shaffer

et al. 2020

Journal of Patient Safety and Risk Management

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Background Venous thromboembolism (VTE) is a leading cause of preventable harm in hospitalized patients. However, many doses of prescribed pharmacologic VTE prophylaxis are frequently missed. We investigated the effect of a patient-centered education bundle on missed doses of VTE prophylaxis in a community hospital. Methods We performed a pre-post analysis examining missed doses of VTE prophylaxis in a community hospital. A real-time alert from the electronic health record system facilitated the delivery of a patient education bundle intervention. We included all patient visits on a single floor where at least 1 dose of VTE prophylaxis was prescribed during pre- (January 1, 2018, - November 31, 2018) and post- (January 1 - June 31, 2019) intervention periods. Outcomes included any missed dose (primary) and reasons for missed doses (refusal, other [secondary]) and were compared between both periods. Results 1,614 patient visits were included. The proportion of any missed dose significantly decreased (13.8% vs. 8.2% [OR, 0.56; 95% CI, 0.48, 0.64]) between the pre-post intervention periods. Patient refusal was the most frequent reason for missed doses. In the post-intervention period, patient refusal significantly decreased from 8.8% to 5.0% (OR, 0.54; 95% CI, 0.46, 0.64). Similarly, other reasons for missed doses significantly decreased from 5.0% to 3.2% (OR, 0.62; 95% CI, 0.51, 0.77). Conclusions A real-time alert-triggered patient-centered education bundle developed and tested in an academic hospital, significantly reduced missed doses of prescribed pharmacologic VTE prophylaxis when disseminated to a community hospital.

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Using electronic health record system triggers to target delivery of a patient-centered intervention to improve venous thromboembolism prevention for hospitalized patients: Is there a differential effect by race?

Cited by 12 publications

References 41 publications

Predicting the occurrence of venous thromboembolism: construction and verification of Risk Warning Model

Predicting the occurrence of venous thromboembolism: construction and verification of Risk Warning Model

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

Disseminating a patient-centered education bundle to reduce missed doses of pharmacologic venous thromboembolism (VTE) prophylaxis to a community hospital

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