@article{paramita_agor_mayorga_ivy_miller_ozaltin_2023, title={Quantifying association and disparities between diabetes complications and COVID-19 outcomes: A retrospective study using electronic health records}, volume={18}, ISSN={["1932-6203"]}, DOI={10.1371/journal.pone.0286815}, abstractNote={
Background
Despite established relationships between diabetic status and an increased risk for COVID-19 severe outcomes, there is a limited number of studies examining the relationships between diabetes complications and COVID-19-related risks. We use the Adapted Diabetes Complications Severity Index to define seven diabetes complications. We aim to understand the risk for COVID-19 infection, hospitalization, mortality, and longer length of stay of diabetes patients with complications.


Methods
We perform a retrospective case-control study using Electronic Health Records (EHRs) to measure differences in the risks for COVID-19 severe outcomes amongst those with diabetes complications. Using multiple logistic regression, we calculate adjusted odds ratios (OR) for COVID-19 infection, hospitalization, and in-hospital mortality of the case group (patients with diabetes complications) compared to a control group (patients without diabetes). We also calculate adjusted mean difference in length of stay between the case and control groups using multiple linear regression.


Results
Adjusting demographics and comorbidities, diabetes patients with renal complications have the highest odds for COVID-19 infection (OR = 1.85, 95% CI = [1.71, 1.99]) while those with metabolic complications have the highest odds for COVID-19 hospitalization (OR = 5.58, 95% CI = [3.54, 8.77]) and in-hospital mortality (OR = 2.41, 95% CI = [1.35, 4.31]). The adjusted mean difference (MD) of hospital length-of-stay for diabetes patients, especially those with cardiovascular (MD = 0.94, 95% CI = [0.17, 1.71]) or peripheral vascular (MD = 1.72, 95% CI = [0.84, 2.60]) complications, is significantly higher than non-diabetes patients. African American patients have higher odds for COVID-19 infection (OR = 1.79, 95% CI = [1.66, 1.92]) and hospitalization (OR = 1.62, 95% CI = [1.39, 1.90]) than White patients in the general diabetes population. However, White diabetes patients have higher odds for COVID-19 in-hospital mortality. Hispanic patients have higher odds for COVID-19 infection (OR = 2.86, 95% CI = [2.42, 3.38]) and shorter mean length of hospital stay than non-Hispanic patients in the general diabetes population. Although there is no significant difference in the odds for COVID-19 hospitalization and in-hospital mortality between Hispanic and non-Hispanic patients in the general diabetes population, Hispanic patients have higher odds for COVID-19 hospitalization (OR = 1.83, 95% CI = [1.16, 2.89]) and in-hospital mortality (OR = 3.69, 95% CI = [1.18, 11.50]) in the diabetes population with no complications.


Conclusions
The presence of diabetes complications increases the risks of COVID-19 infection, hospitalization, and worse health outcomes with respect to in-hospital mortality and longer hospital length of stay. We show the presence of health disparities in COVID-19 outcomes across demographic groups in our diabetes population. One such disparity is that African American and Hispanic diabetes patients have higher odds of COVID-19 infection than White and Non-Hispanic diabetes patients, respectively. Furthermore, Hispanic patients might have less access to the hospital care compared to non-Hispanic patients when longer hospitalizations are needed due to their diabetes complications. Finally, diabetes complications, which are generally associated with worse COVID-19 outcomes, might be predominantly determining the COVID-19 severity in those infected patients resulting in less demographic differences in COVID-19 hospitalization and in-hospital mortality.
}, number={9}, journal={PLOS ONE}, author={Paramita, Ni Luh Putu S. P. and Agor, Joseph K. and Mayorga, Maria E. and Ivy, Julie S. and Miller, Kristen E. and Ozaltin, Osman Y.}, year={2023}, month={Sep} }
 @article{agor_paramita_ozaltn_2021, title={Prediction of Sepsis Related Mortality: An Optimization Approach}, volume={25}, ISSN={["2168-2208"]}, url={https://doi.org/10.1109/JBHI.2021.3096470}, DOI={10.1109/JBHI.2021.3096470}, abstractNote={Sepsis is a condition that progresses quickly and is a major cause of mortality in hospitalized patients. Data-driven diagnostic and therapeutic interventions are essential to ensure early diagnosis and appropriate care. The Sequential Organ Failure Assessment (SOFA) score is widely utilized in clinical practice to assess septic patients for organ dysfunction. The SOFA score uses points between 0 and 4 to quantify the level of dysfunction in six organ systems. These points are determined based on expert opinion and not informed by data, thus their usefulness can vary among different medical institutions depending on the targeted use. In this study, we propose multiple strategies to adjust the SOFA score using mixed-integer programming to improve the in-hospital mortality prediction of septic patients based on Electronic Health Records (EHRs). We use the same variables and threshold values of the original SOFA score in each strategy. Thus, the proposed approach takes advantage of optimization and data analysis while taking into account the medical expertise. Our results demonstrate a statistically significant improvement ($p< 0.001$) in the prediction of in-hospital mortality among patients susceptible to sepsis when implementing our proposed strategies. Area under the receiver operator curve (AUC) and accuracy values of 0.8928 and 0.8904 are achieved by optimizing the point values of the SOFA score.}, number={11}, journal={IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Agor, Joseph K. and Paramita, Ni Luh Putu S. P. and Ozaltn, Osman Y.}, year={2021}, month={Nov}, pages={4207–4216} }
 @article{wijaya_paramita_uluwiyah_rheza_zahara_puspita_2022, title={Estimating city-level poverty rate based on e-commerce data with machine learning}, volume={22}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85086656634&partnerID=MN8TOARS}, DOI={10.1007/s10660-020-09424-1}, number={1}, journal={Electronic Commerce Research}, author={Wijaya, D.R. and Paramita, N.L.P.S.P. and Uluwiyah, A. and Rheza, M. and Zahara, A. and Puspita, D.R.}, year={2022}, pages={195–221} }
 @inproceedings{suciptawati_paramita_aristayasa_2019, title={Customer satisfaction analysis based on service quality: Case of local credit provider in Bali}, volume={1321}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85075333457&partnerID=MN8TOARS}, DOI={10.1088/1742-6596/1321/2/022055}, abstractNote={Abstract
               
                  Lembaga Perkreditan Desa (LPD) or village credit institution is a financial institution that is only exists in Bali. LPDs had been developed to promote the local people economies by providing micro credits as well as to deposit their money. This paper is aimed to study the satisfaction of customers toward LPD’s services. A hundred and fifty customers of LPD Sidakarya that is located at Denpasar were purposive sampling selected as the respondents of the study on July 2017. The data were collected by applying self-organized questionnairé which its items were developed using 7 scale on Likerts’ measurement. The respondents were asked to value their expectation as well as their perception on five dimension of service quality i.e. tangible factor, reliability, responsiveness, assurance, and empathy. The study reveals tangible factor was perceived positively whilest the other determinants need to be improved.}, number={2}, booktitle={Journal of Physics: Conference Series}, author={Suciptawati, N.L.P. and Paramita, N.L.P.S.P. and Aristayasa, I.P.}, year={2019} }