%0 Journal Article %1 Lingren2018 %A Lingren, Todd %A Sadhasivam, Senthilkumar %A Zhang, Xue %A Marsolo, Keith %D 2018 %I Elsevier %J International journal of medical informatics %K Dataquality Dimensionalmeasurementaccuracy Electronicmedicalrecords Opioidanalgesics Postoperativepain Respiratorydepression %N March 2017 %P 45-50 %R 10.1016/j.ijmedinf.2017.12.014 %T Electronic medical records as a replacement for prospective research data collection in postoperative pain and opioid response studies. %U https://doi.org/10.1016/j.ijmedinf.2017.12.014 http://www.ncbi.nlm.nih.gov/pubmed/29425633 http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC5808990 %V 111 %X BACKGROUND AND AIM Many clinical research studies claim to collect data that are also captured in the electronic medical record (EMR). We evaluate the potential for EMR data to replace prospective research data collection. METHODS Using a dataset of 358 surgical patients enrolled in a prospective study, we examined the completeness and agreement of EMR and study entries for several variables, including the patient's stay in the post-operative care unit (PACU), surgical pain relief and pain medication side effects. RESULTS For all variables with a completeness percentage, values were greater than 96%. For the adverse event variables, we found slight to substantial agreement (Cohen's kappa), ranging from 0.19 (nausea) to 0.48 (respiratory depression) to 0.73 (emesis). CONCLUSION The potential to use EMR data as a replacement for prospective research data collection shows promise, but for now, should be evaluated on a variable-by-variable basis.

@article{Lingren2018, abstract = {BACKGROUND AND AIM Many clinical research studies claim to collect data that are also captured in the electronic medical record (EMR). We evaluate the potential for EMR data to replace prospective research data collection. METHODS Using a dataset of 358 surgical patients enrolled in a prospective study, we examined the completeness and agreement of EMR and study entries for several variables, including the patient's stay in the post-operative care unit (PACU), surgical pain relief and pain medication side effects. RESULTS For all variables with a completeness percentage, values were greater than 96%. For the adverse event variables, we found slight to substantial agreement (Cohen's kappa), ranging from 0.19 (nausea) to 0.48 (respiratory depression) to 0.73 (emesis). CONCLUSION The potential to use EMR data as a replacement for prospective research data collection shows promise, but for now, should be evaluated on a variable-by-variable basis.}, added-at = {2023-02-03T11:44:35.000+0100}, author = {Lingren, Todd and Sadhasivam, Senthilkumar and Zhang, Xue and Marsolo, Keith}, biburl = {https://www.bibsonomy.org/bibtex/29a441580ec79a1eff38c020df227831c/jepcastel}, doi = {10.1016/j.ijmedinf.2017.12.014}, interhash = {938ed2c23233abf515cfbd1924608e0c}, intrahash = {9a441580ec79a1eff38c020df227831c}, issn = {1872-8243}, journal = {International journal of medical informatics}, keywords = {Dataquality Dimensionalmeasurementaccuracy Electronicmedicalrecords Opioidanalgesics Postoperativepain Respiratorydepression}, month = {3}, note = {Databases; Dolor}, number = {March 2017}, pages = {45-50}, pmid = {29425633}, publisher = {Elsevier}, timestamp = {2023-02-03T11:44:35.000+0100}, title = {Electronic medical records as a replacement for prospective research data collection in postoperative pain and opioid response studies.}, url = {https://doi.org/10.1016/j.ijmedinf.2017.12.014 http://www.ncbi.nlm.nih.gov/pubmed/29425633 http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC5808990}, volume = 111, year = 2018 }