Abstract
Background/Purpose Although prohibitively labor intensive, manual data extraction (MDE) is the prevailing method used to obtain clinical research and quality improvement (QI) data. Automated data extraction (ADE) offers a powerful alternative. The purposes of this study were to 1) assess the feasibility of ADE from provider-authored outpatient documentation, and 2) evaluate the effectiveness of ADE compared to MDE. Methods A prospective collection of data was performed on 90 ADE-templated notes (N = 71 patients) evaluated in our bowel management clinic. ADE captured data were compared to 59 MDE notes (N = 51) collected under an IRB-exempt review. Sixteen variables were directly comparable between ADE and MDE. Results MDE for 59 clinic notes (27 unique variables) took 6 months to complete. ADE-templated notes for 90 clinic notes (154 unique variables) took 5 min to run a research/QI report. Implementation of ADE included eight weeks of development and testing. Pre-implementation clinical documentation was similar to post-implementation documentation (5–10 min). Conclusions ADE-templated notes allow for a 5-fold increase in clinically relevant data that can be captured with each encounter. ADE also results in real-time data extraction to a research/QI database that is easily queried. The immediate availability of these data, in a research-formatted spreadsheet, allows for rapid collection, analyses, and interpretation of the data. Level of evidence IV. Type of study Retrospective Study.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 149-152 |
| Number of pages | 4 |
| Journal | Journal of pediatric surgery |
| Volume | 52 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 1 2017 |
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Keywords
- Automated data extraction
- Clinical documentation
- Electronic data capture
- Electronic documentation
- Templated notes
ASJC Scopus subject areas
- Surgery
- Pediatrics, Perinatology, and Child Health
Cite this
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Automated data extraction : merging clinical care with real-time cohort-specific research and quality improvement data. / Hebal, Ferdynand; Nanney, Elizabeth; Stake, Christine; Miller, M. L.; Lales, George; Barsness, Katherine A.
In: Journal of pediatric surgery, Vol. 52, No. 1, 01.01.2017, p. 149-152.Research output: Contribution to journal › Article
TY - JOUR
T1 - Automated data extraction
T2 - merging clinical care with real-time cohort-specific research and quality improvement data
AU - Hebal, Ferdynand
AU - Nanney, Elizabeth
AU - Stake, Christine
AU - Miller, M. L.
AU - Lales, George
AU - Barsness, Katherine A.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - Background/Purpose Although prohibitively labor intensive, manual data extraction (MDE) is the prevailing method used to obtain clinical research and quality improvement (QI) data. Automated data extraction (ADE) offers a powerful alternative. The purposes of this study were to 1) assess the feasibility of ADE from provider-authored outpatient documentation, and 2) evaluate the effectiveness of ADE compared to MDE. Methods A prospective collection of data was performed on 90 ADE-templated notes (N = 71 patients) evaluated in our bowel management clinic. ADE captured data were compared to 59 MDE notes (N = 51) collected under an IRB-exempt review. Sixteen variables were directly comparable between ADE and MDE. Results MDE for 59 clinic notes (27 unique variables) took 6 months to complete. ADE-templated notes for 90 clinic notes (154 unique variables) took 5 min to run a research/QI report. Implementation of ADE included eight weeks of development and testing. Pre-implementation clinical documentation was similar to post-implementation documentation (5–10 min). Conclusions ADE-templated notes allow for a 5-fold increase in clinically relevant data that can be captured with each encounter. ADE also results in real-time data extraction to a research/QI database that is easily queried. The immediate availability of these data, in a research-formatted spreadsheet, allows for rapid collection, analyses, and interpretation of the data. Level of evidence IV. Type of study Retrospective Study.
AB - Background/Purpose Although prohibitively labor intensive, manual data extraction (MDE) is the prevailing method used to obtain clinical research and quality improvement (QI) data. Automated data extraction (ADE) offers a powerful alternative. The purposes of this study were to 1) assess the feasibility of ADE from provider-authored outpatient documentation, and 2) evaluate the effectiveness of ADE compared to MDE. Methods A prospective collection of data was performed on 90 ADE-templated notes (N = 71 patients) evaluated in our bowel management clinic. ADE captured data were compared to 59 MDE notes (N = 51) collected under an IRB-exempt review. Sixteen variables were directly comparable between ADE and MDE. Results MDE for 59 clinic notes (27 unique variables) took 6 months to complete. ADE-templated notes for 90 clinic notes (154 unique variables) took 5 min to run a research/QI report. Implementation of ADE included eight weeks of development and testing. Pre-implementation clinical documentation was similar to post-implementation documentation (5–10 min). Conclusions ADE-templated notes allow for a 5-fold increase in clinically relevant data that can be captured with each encounter. ADE also results in real-time data extraction to a research/QI database that is easily queried. The immediate availability of these data, in a research-formatted spreadsheet, allows for rapid collection, analyses, and interpretation of the data. Level of evidence IV. Type of study Retrospective Study.
KW - Automated data extraction
KW - Clinical documentation
KW - Electronic data capture
KW - Electronic documentation
KW - Templated notes
UR - http://www.scopus.com/inward/record.url?scp=85006809838&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85006809838&partnerID=8YFLogxK
U2 - 10.1016/j.jpedsurg.2016.10.040
DO - 10.1016/j.jpedsurg.2016.10.040
M3 - Article
VL - 52
SP - 149
EP - 152
JO - Journal of Pediatric Surgery
JF - Journal of Pediatric Surgery
SN - 0022-3468
IS - 1
ER -