RESUMEN
ABSTRACT Objective To analyze the most common ophthalmologic disorders in pregnant women seen in a hospital in Munich in Germany using a big data analysis system, as well as to compare the results obtained with those from other epidemiological studies that used different data acquisition methods. Methods We retrospectively analyzed electronic health records of pregnant women who were seen at the ophthalmology department from 2003 to 2019 at the Ludwig-Maximilians-Universität München hospital. The main complaints that led to ophthalmic consultations during this period were evaluated, and also the variation in intraocular pressure of patients throughout gestational trimesters by analyzing data from the data warehouse system. Results A total of 27,326 electronic health records were analyzed. Of participants, 149 (0.54%) required eye care during pregnancy. Their mean intraocular pressure was 17mmHg in the first trimester, 12mmHg in the second trimester, and 14mmHg in the third trimester. The most prevalent findings were dry eye (29.3%) and conjunctivitis (16%), and ametropia (16%). The most common posterior segment problem was diabetic retinopathy (4.6%). The lower mean intraocular pressure in the second and third trimester found in our study is in accordance with other studies that used other method for data acquisition. Conclusion The most common ophthalmic conditions found in this study population were dry eye, conjunctivitis, and ametropia. The use of data warehouse proved to be useful for acquiring and analyzing data from many patients. This study results are comparable with other studies in published literature that adopted different methodology.
RESUMEN
OBJECTIVES: A clinical data warehouse (CDW) is part of our hospital information system, and it provides user-friendly ‘data search and extraction’ interfaces for query composition. We carried out a risk factor analysis for the extended use of opioids after coronary artery bypass grafting (CABG), taking advantage of the CDW system. METHODS: From 2015 to 2017, clinical data from 461 patients who had undergone either isolated or concomitant CABG were extracted using the CDW; the extracted data included baseline patient characteristics, various examination results, and opioid prescription information. Supplementary data that could not be extracted with the CDW were collected via manual review of the electronic medical records. RESULTS: Data from a total of 447 patients were analyzed finally. The mean patient age was 66.8 ± 10.9 years, 332 patients (74%) were male, and 235 patients (53%) had diabetes. Among the 447 patients, 90 patients (20.1%) took some type of opioid at the 15th postoperative day. An oral rapid-acting agent was the most frequently used opioid (83%). In the risk factor analysis for extended opioid use, duration of operation was the only significant risk factor (odds ratio = 1.004; 95% confidence interval, 1.001–1.007; p = 0.008). CONCLUSIONS: Longer operation time was associated with the risk of extended opioid use after CABG. CDW was a helpful tool for extracting mass clinical data rapidly, but to maximize its utility, the data should be checked carefully as they are entered in the system so that post-processing can be minimized. Further refinement of the clinical data input and output interface is warranted.