electronic health record data
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2022 ◽  
Vol 8 ◽  
Author(s):  
Chien-Liang Liu ◽  
You-Lin Tain ◽  
Yun-Chun Lin ◽  
Chien-Ning Hsu

ObjectiveThis study aimed to identify phenotypic clinical features associated with acute kidney injury (AKI) to predict non-recovery from AKI at hospital discharge using electronic health record data.MethodsData for hospitalized patients in the AKI Recovery Evaluation Study were derived from a large healthcare delivery system in Taiwan between January 2011 and December 2017. Living patients with AKI non-recovery were used to derive and validate multiple predictive models. In total, 64 candidates variables, such as demographic characteristics, comorbidities, healthcare services utilization, laboratory values, and nephrotoxic medication use, were measured within 1 year before the index admission and during hospitalization for AKI.ResultsAmong the top 20 important features in the predictive model, 8 features had a positive effect on AKI non-recovery prediction: AKI during hospitalization, serum creatinine (SCr) level at admission, receipt of dialysis during hospitalization, baseline comorbidity of cancer, AKI at admission, baseline lymphocyte count, baseline potassium, and low-density lipoprotein cholesterol levels. The predicted AKI non-recovery risk model using the eXtreme Gradient Boosting (XGBoost) algorithm achieved an area under the receiver operating characteristic (AUROC) curve statistic of 0.807, discrimination with a sensitivity of 0.724, and a specificity of 0.738 in the temporal validation cohort.ConclusionThe machine learning model approach can accurately predict AKI non-recovery using routinely collected health data in clinical practice. These results suggest that multifactorial risk factors are involved in AKI non-recovery, requiring patient-centered risk assessments and promotion of post-discharge AKI care to prevent AKI complications.


PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0262530
Author(s):  
Munerah Almulhem ◽  
Rasiah Thayakaran ◽  
Shahjehan Hanif ◽  
Tiffany Gooden ◽  
Neil Thomas ◽  
...  

Background The effect of fasting on immunity is unclear. Prolonged fasting is thought to increase the risk of infection due to dehydration. This study describes antibiotic prescribing patterns before, during, and after Ramadan in a primary care setting within the Pakistani and Bangladeshi populations in the UK, most of whom are Muslims, compared to those who do not observe Ramadan. Method Retrospective controlled interrupted time series analysis of electronic health record data from primary care practices. The study consists of two groups: Pakistanis/Bangladeshis and white populations. For each group, we constructed a series of aggregated, daily prescription data from 2007 to 2017 for the 30 days preceding, during, and after Ramadan, respectively. Findings Controlling for the rate in the white population, there was no evidence of increased antibiotic prescription in the Pakistani/Bangladeshi population during Ramadan, as compared to before Ramadan (IRR: 0.994; 95% CI: 0.988–1.001, p = 0.082) or after Ramadan (IRR: 1.006; 95% CI: 0.999–1.013, p = 0.082). Interpretation In this large, population-based study, we did not find any evidence to suggest that fasting was associated with an increased susceptibility to infection.


2022 ◽  
pp. 10-19
Author(s):  
Emily Bauman ◽  
Justine Russell ◽  
Angela Morelli

IMPORTANCE: Every year, thousands of emergency department (ED) visits result in patients being discharged with oral antibiotic prescriptions. Published studies that assess the appropriateness of these antibiotic regimens are limited. PURPOSE: The purpose of this study was to examine the appropriateness of antibiotic prescriptions written for patients discharged from a community hospital’s ED. ENDPOINTS: The primary objective was to determine the overall percent of appropriate antibiotic prescriptions for patients discharged from the ED. Secondary objectives included the following: identify reasons for inappropriateness categorized by antibiotic selection, dose, duration, and allergies; identify the most common antibiotics prescribed inappropriately as well as the most common disease states that led to inappropriate prescribing of antibiotics; and analyze prescribing trends based on provider type and time of day the prescription was written. STUDY DESIGN AND METHODS: Patients eligible for inclusion were adults age 18 and older who presented to the ED during four chosen weeks in 2019 and who were discharged with oral antibiotics. Extracted electronic health record data was reviewed to identify the discharge diagnosis for each patient that meets the inclusion criteria. Pertinent information gathered from the patients’ medical records along with a validated antimicrobial assessment tool were utilized to determine the level of appropriateness of the prescribed antibiotic regimens. RESULTS: A total of 76% of the prescribed antibiotics were appropriate, 16% were inappropriate, and the remaining 8% were not assessable. Duration was the most common reason for a regimen to not be optimal. The most frequently inappropriately prescribed antibiotics included cephalexin (but it is noted cephalexin was included in almost half of the antibiotic regimens in this study), clindamycin, and azithromycin. Infections that were most frequently treated inappropriately were skin and soft tissue infections, dental infections, and sinusitis. Overall, medical residents prescribed the highest percent of appropriate regimens, and the time of day that had the highest percent of appropriate prescriptions was third shift (11 p.m. to 7 a.m.). CONCLUSION AND RELEVANCE: Almost half of all the nonoptimal antibiotic regimens had an excessive duration. Targeted local education efforts and future clinical decision support can facilitate appropriate prescribing of discharge antibiotics from the ED, ultimately improving antimicrobial stewardship within the community.


2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Jacqueline M. Ferguson ◽  
Amy C. Justice ◽  
Thomas F. Osborne ◽  
Hoda S. Abdel Magid ◽  
Amanda L. Purnell ◽  
...  

AbstractThe coronavirus pandemic has disproportionally impacted racial and ethnic minority communities in the United States. Patterns of these disparities may be changing over time as outbreaks occur in different communities. Utilizing electronic health record data from the US Department of Veterans Affairs (VA), we estimated odds ratios, stratified by time period and region, for testing positive among 1,313,402 individuals tested for SARS-CoV-2 between February 12, 2020 and August 16, 2021 at VA medical facilities. We adjusted for personal characteristics (sex, age, rural/urban residence, VA facility) and a wide range of clinical characteristics that have been evaluated in prior SARS-CoV-2 reports and could potentially explain racial/ethnic disparities in SARS-CoV-2. Our study found racial and ethnic disparities for testing positive were most pronounced at the beginning of the pandemic and decreased over time. A key finding was that the disparity among Hispanic individuals attenuated but remained elevated, while disparities among Asian individuals reversed by March 1, 2021. The variation in racial and ethnic disparities in SARS-CoV-2 positivity by time and region, independent of underlying health status and other demographic characteristics in a nationwide cohort, provides important insight for strategies to prevent further outbreaks.


Author(s):  
Anna E. Schorer ◽  
Richard Moldwin ◽  
Jacob Koskimaki ◽  
Elmer V. Bernstam ◽  
Neeta K. Venepalli ◽  
...  

PURPOSE The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) requires eligible clinicians to report clinical quality measures (CQMs) in the Merit-Based Incentive Payment System (MIPS) to maximize reimbursement. To determine whether structured data in electronic health records (EHRs) were adequate to report MIPS CQMs, EHR data aggregated by ASCO's CancerLinQ platform were analyzed. MATERIALS AND METHODS Using the CancerLinQ health technology platform, 19 Oncology MIPS (oMIPS) CQMs were evaluated to determine the presence of data elements (DEs) necessary to satisfy each CQM and the DE percent population with patient data (fill rates). At the time of this analysis, the CancerLinQ network comprised 63 active practices, representing eight different EHR vendors and containing records for more than 1.63 million unique patients with one or more malignant neoplasms (1.73 million cancer cases). RESULTS Fill rates for the 63 oMIPS-associated DEs varied widely among the practices. The average site had at least one filled DE for 52% of the DEs. Only 35% of the DEs were populated for at least one patient record in 95% of the practices. However, the average DE fill rate of all practices was 23%. No data were found at any practice for 22% of the DEs. Since any oMIPS CQM with an unpopulated DE component resulted in an inability to compute the measure, only two (10.5%) of the 19 oMIPS CQMs were computable for more than 1% of the patients. CONCLUSION Although EHR systems had relatively high DE fill rates for some DEs, underfilling and inconsistency of DEs in EHRs render automated oncology MIPS CQM calculations impractical.


2021 ◽  
Author(s):  
Tracey Pérez Koehlmoos ◽  
Jessica Korona-Bailey ◽  
Miranda Lynn Janvrin ◽  
Cathaleen Madsen

ABSTRACT Introduction Racial disparities in health care are a well-documented phenomenon in the USA. Universal insurance has been suggested as a solution to mitigate these disparities. We examined race-based disparities in the Military Health System (MHS) by constructing and analyzing a framework of existing studies that measured disparities between direct care (care provided by military treatment facilities) and private sector care (care provided by civilian health care facilities). Materials and Methods We conducted a framework synthesis on 77 manuscripts published in partnership with the Comparative Effectiveness and Provider-Induced Demand Collaboration Project that use MHS electronic health record data to present an overview of racial disparities assessed for multiple treatment interventions in a nationally representative, universally insured population. Results We identified 32 studies assessing racial disparities in areas of surgery, trauma, opioid prescription and usage, women’s health, and others. Racial disparities were mitigated in postoperative complications, trauma care, and cancer screenings but persisted in diabetes readmissions, opioid usage, and minimally invasive women’s health procedures. Conclusion Universal coverage mitigates many, but not all, racial disparities in health care. An examination of a broader range of interventions, a closer look at variation in care provided by civilian facilities, and a look at the quality of care by race provide further opportunities for research.


2021 ◽  
pp. 089801012110655
Author(s):  
Emily Marsh ◽  
Donna Millette ◽  
Alison Wolfe

Purpose: This study analyzed the efficacy of Post-Ease, a custom essential oil aromatherapy blend, in decreasing postoperative nausea and vomiting (PONV) and the need for antiemetic drugs in an orthopaedic surgical population. Study Design: This is retrospective cohort study, utilizing electronic health record data pre- and post-implementation of a nurse-driven quality improvement intervention. Methods: The study examined the impact of an inhaled custom blend of essential oils containing lavender, peppermint, ginger and lemon to assist in decreasing PONV and reduce the use of antiemetic medications. Data on the use of antiemetic drugs in pre- and post-intervention periods were analyzed. Findings: Nurses provided the Post-Ease blend 384 times in 2020 to patients as an option before proceeding, if necessary, to antiemetic drugs. The intervention group demonstrated a statistically significant reduction in the number of unique surgical patients’ need for antiemetics as treatment (22%; p = .05). Similarly, the total doses of antiemetics administered was significantly reduced (21%; p ≤ .05) during the study period. Conclusion: This study supports the use of aromatherapy to reduce PONV and minimize antiemetic use in an orthopaedic population.


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