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Assessing Quality of Surgical Real-World Data from an Automated Electronic Health Record Pipeline.

Abstract

BACKGROUND

Significant analysis errors can be caused by nonvalidated data quality of electronic health records data. To determine surgical data fitness, a framework of foundational and study-specific data analyses was adapted and assessed using conformance, completeness, and plausibility analyses.

STUDY DESIGN

Electronic health records-derived data from a cohort of 241,695 patients undergoing 412,182 procedures from October 1, 2014 to August 31, 2018 at 3 hospital sites was evaluated. Data quality analyses tested CPT codes, medication administrations, vital signs, provider notes, labs, orders, diagnosis codes, medication lists, and encounters.

RESULTS

Foundational checks showed that all encounters had procedures within the inclusion period, all admission dates occurred before discharge dates, and race was missing for 1% of patients. All procedures had associated CPT codes, 69% had recorded blood pressure, pulse, temperature, respiration rate, and oxygen saturation. After curation, all medication matched RxNorm medication naming standards, 84% of procedures had current outpatient medication lists, and 15% of procedures had missing procedure notes. Study-specific checks temporally validated CPT codes, intraoperative medication doses were in conventional units, and of the 13,500 patients who received blood pressure medication intraoperatively, 93% had a systolic blood pressure >140 mmHg. All procedure notes were completed within less than 30 days of the procedure and 93% of patients after total knee arthroplasty had postoperative physical therapy notes. All patients with postoperative troponin-T lab values ≥0.10 ng/mL had more than 1 ECG with relevant diagnoses. Postoperative opioid prescription decreased by 8.8% and nonopioid use increased by 8.8%.

CONCLUSIONS

High levels of conformance, completeness, and clinical plausability demonstrate higher quality of real-world data fitness and low levels demonstrate less-fit-for-use data.

Authors+Show Affiliations

Duke University School of Medicine, Duke University, Durham, NC; Duke Institute for Health Innovation, Duke University, Durham, NC. Electronic address: corey006@duke.com.Duke University School of Medicine, Duke University, Durham, NC; Duke Institute for Health Innovation, Duke University, Durham, NC.Duke University School of Medicine, Duke University, Durham, NC; Duke Institute for Health Innovation, Duke University, Durham, NC.Duke Clinical Research Institute, Duke University, Durham, NC; Department of Population Health Sciences, Duke University, Durham, NC.Duke Clinical Research Institute, Duke University, Durham, NC.Duke University School of Medicine, Duke University, Durham, NC; Duke Institute for Health Innovation, Duke University, Durham, NC.Duke Institute for Health Innovation, Duke University, Durham, NC.Duke Institute for Health Innovation, Duke University, Durham, NC.Department of Surgery, Duke University, Durham, NC.Department of Surgery, Duke University, Durham, NC.Department of Surgery, Duke University, Durham, NC.Duke Institute for Health Innovation, Duke University, Durham, NC.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

31945461

Citation

Corey, Kristin M., et al. "Assessing Quality of Surgical Real-World Data From an Automated Electronic Health Record Pipeline." Journal of the American College of Surgeons, 2020.
Corey KM, Helmkamp J, Simons M, et al. Assessing Quality of Surgical Real-World Data from an Automated Electronic Health Record Pipeline. J Am Coll Surg. 2020.
Corey, K. M., Helmkamp, J., Simons, M., Curtis, L., Marsolo, K., Balu, S., ... Sendak, M. (2020). Assessing Quality of Surgical Real-World Data from an Automated Electronic Health Record Pipeline. Journal of the American College of Surgeons, doi:10.1016/j.jamcollsurg.2019.12.005.
Corey KM, et al. Assessing Quality of Surgical Real-World Data From an Automated Electronic Health Record Pipeline. J Am Coll Surg. 2020 Jan 13; PubMed PMID: 31945461.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Assessing Quality of Surgical Real-World Data from an Automated Electronic Health Record Pipeline. AU - Corey,Kristin M, AU - Helmkamp,Joshua, AU - Simons,Morgan, AU - Curtis,Lesley, AU - Marsolo,Keith, AU - Balu,Suresh, AU - Gao,Michael, AU - Nichols,Marshall, AU - Watson,Joshua, AU - Mureebe,Leila, AU - Kirk,Allan D, AU - Sendak,Mark, Y1 - 2020/01/13/ PY - 2019/10/02/received PY - 2019/12/19/revised PY - 2019/12/19/accepted PY - 2020/1/17/pubmed PY - 2020/1/17/medline PY - 2020/1/17/entrez JF - Journal of the American College of Surgeons JO - J. Am. Coll. Surg. N2 - BACKGROUND: Significant analysis errors can be caused by nonvalidated data quality of electronic health records data. To determine surgical data fitness, a framework of foundational and study-specific data analyses was adapted and assessed using conformance, completeness, and plausibility analyses. STUDY DESIGN: Electronic health records-derived data from a cohort of 241,695 patients undergoing 412,182 procedures from October 1, 2014 to August 31, 2018 at 3 hospital sites was evaluated. Data quality analyses tested CPT codes, medication administrations, vital signs, provider notes, labs, orders, diagnosis codes, medication lists, and encounters. RESULTS: Foundational checks showed that all encounters had procedures within the inclusion period, all admission dates occurred before discharge dates, and race was missing for 1% of patients. All procedures had associated CPT codes, 69% had recorded blood pressure, pulse, temperature, respiration rate, and oxygen saturation. After curation, all medication matched RxNorm medication naming standards, 84% of procedures had current outpatient medication lists, and 15% of procedures had missing procedure notes. Study-specific checks temporally validated CPT codes, intraoperative medication doses were in conventional units, and of the 13,500 patients who received blood pressure medication intraoperatively, 93% had a systolic blood pressure >140 mmHg. All procedure notes were completed within less than 30 days of the procedure and 93% of patients after total knee arthroplasty had postoperative physical therapy notes. All patients with postoperative troponin-T lab values ≥0.10 ng/mL had more than 1 ECG with relevant diagnoses. Postoperative opioid prescription decreased by 8.8% and nonopioid use increased by 8.8%. CONCLUSIONS: High levels of conformance, completeness, and clinical plausability demonstrate higher quality of real-world data fitness and low levels demonstrate less-fit-for-use data. SN - 1879-1190 UR - https://www.unboundmedicine.com/medline/citation/31945461/Assessing_Quality_of_Surgical_Real-World_Data_From_an_Automated_Electronic_Health_Record_Pipeline L2 - https://linkinghub.elsevier.com/retrieve/pii/S1072-7515(20)30061-2 DB - PRIME DP - Unbound Medicine ER -