Implementation of automatic data extraction from an enterprise database warehouse (EDW) for validating pediatric VTE decision rule: a prospective observational study in a critical care population

Abstract

Multiple clinical risk prediction tools for hospital acquired venous thromboembolism (HA-VTE) have been developed. The objectives of this study were to develop and assess the feasibility of data extraction from Electronic Medical Records (EMR) from an enterprise database warehouse (EDW) and to test the validity of a previously developed Pediatric Clot Decision Rule (PCDR). This single-center prospective observational cohort study was conducted between March 2016 and March 2017 and included eligible patients admitted to the intensive care units. Risk score was calculated using the PCDR tool. Sensitivity, specificity, positive and negative predicted value (PPV and NPV) were calculated based on a cut‐point of 3. A total of 2822 children were eligible for analysis and 5.1% (95% CI 4.2–6.2) children had a PCDR score of 3. Children with PCDR score of ≥ 3 had a 3 times higher odd of developing VTE compared to those with scores < 3 (OR 3.1; 95% CI 1.93–4.80; p < 0.001). The model performance showed that at the cutoff point of ≥ 3, both the specificity and sensitivity of the PCDR in predicting VTE was 69% and NPV of 98%. We successfully demonstrated using our EDW to populate a research database using an automatic data import. A PCDR score of ≥ 3 was associated with VTE. Collaboration through large registries will be useful in informing practices and guidelines for rare disorders such as pediatric VTE.

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Abbreviations

HA-VTE:

Hospital acquired venous thromboembolism

EMR:

Electronic Medical Records

EDW:

Enterprise database warehouse

PCDR:

Pediatric Clot Decision rule

PPV:

Positive predictive values

NPV:

Negative predictive values

CVC:

Central venous catheters

SPS:

Children’s Hospitals Solutions for Patient Safety

ICU:

Intensive care unit

AUC:

Area under the curve

IT:

Information technology

CCPMS:

Computerized care process management system

PICU:

Pediatric intensive care unit

CICU:

Cardiac intensive care unit

NICU:

Neonatal Intensive care unit

SQL:

Structured Query Language

BMI:

Body mass index

CVC:

Central venous catheter

OCP:

Estrogen containing contraceptive pills

MV:

Mechanical ventilation

AUC:

Area under the receiver operating characteristics curve

ISTH:

International society of thrombosis and Haemostasis

CER:

Comparative effectiveness research

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Authors

Contributions

RS: Collected data for Phase III part of the study, data analysis, drafted and revised manuscript. AS: Conceived the research design and developed the research database, drafted and revised the manuscript. SKW: Performed data-analyses, drafted and revised the manuscript. KD: Developed the code for data export code, developed research database and revised manuscript. GL: Built research database and approved manuscript. RB: Supervised data quality, conduct of research, data analysis and drafted and revised manuscript. All authors made contributions to the study conception and design, drafted or revised it critically for important intellectual content and approved final version of the manuscript.

Corresponding author

Correspondence to Rukhmi Bhat.

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The paper has been published as a meeting abstract in the following meetings listed below: (1) Prospective Validation of the Peds Clot Clinical Decision Rule [Pcdr] in Hospital-Acquired Venous Thromboembolism: An Interim Analysis. American Society of Hematology 2016. Schultz RF, Kwon K, Sharathkumar A, Bhat R. Blood. 2016; 128. (2) Validation of the Peds Clot Clinical Decision Rule [PCDR] in Hospital-Acquired Venous Thromboembolism. American Society of Hematology 2017. Schultz R, Kwon S, Sharathkumar A, Bhat R. Blood. 2017; 130.

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Schultz, R.F., Sharathkumar, A., Kwon, S. et al. Implementation of automatic data extraction from an enterprise database warehouse (EDW) for validating pediatric VTE decision rule: a prospective observational study in a critical care population. J Thromb Thrombolysis (2020). https://doi.org/10.1007/s11239-020-02158-9

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Keywords

  • Pediatrics
  • Venous thromboembolism
  • Enterprise database warehouse
  • Medical record linkage
  • Critical care
  • Information technology