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  • 1
    Online Resource
    Online Resource
    Impact of Phlebotomist-Only Venipuncture and Central Line Avoidance for Blood Culture in a Large Tertiary Care University Hospital
    Ovid Technologies (Wolters Kluwer Health) ; 2018
    In:  Infectious Diseases in Clinical Practice Vol. 26, No. 2 ( 2018-3), p. 91-96
    Details
    In: Infectious Diseases in Clinical Practice, Ovid Technologies (Wolters Kluwer Health), Vol. 26, No. 2 ( 2018-3), p. 91-96
    Abstract: Drawing blood for culture from central vascular access sites may increase rates of blood culture contamination and central line–associated bloodstream infection. Methods We examined the impact of phlebotomist-only blood draws and central line avoidance for blood culture in a large university hospital that also cares for patients with cancer, stem cell transplants, and solid-organ transplants. Policy enforcement began in September 2013. The preimplementation era was defined from January 2012 to June 2013, and the postimplementation era was defined from January 2014 to September 2015. Outcomes in preimplementation and postimplementation eras were compared using time-series analyses, t tests, and Wilcoxon rank sum tests. Results Policy implementation led to 29%, 31%, and 38% decreases in blood culture performance, positivity, and contamination, respectively; an 86% decrease in blood cultures drawn from central lines; and a 66% decrease in central line–associated bloodstream infections. Our policy coincided with an 11% decrease in intravenous vancomycin, daptomycin, or linezolid use, whereas there was no change in piperacillin-tazobactam, cefepime/ceftazidime, or carbapenem use. Hospital lengths of stay and mortality rates were unchanged in the general hospital population and were stable or improved in patients with kidney disease, liver disease, cancer, and abdominal solid-organ transplants. Conclusions Our findings suggest that having phlebotomists draw blood for culture almost exclusively by venipuncture resulted in decreased blood culture positivity that did not translate into harm as measured by length of stay or inpatient death even among immunocompromised hosts.
    Type of Medium: Online Resource
    ISSN: 1536-9943 , 1056-9103
    URL: Article
    DOI: 10.1097/IPC.0000000000000584
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2018
    detail.hit.zdb_id: 2062211-9
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  • 2
    Online Resource
    Online Resource
    Effect of an obesity best practice alert on physician documentation and referral practices
    Oxford University Press (OUP) ; 2017
    In:  Translational Behavioral Medicine Vol. 7, No. 4 ( 2017-12), p. 881-890
    Details
    In: Translational Behavioral Medicine, Oxford University Press (OUP), Vol. 7, No. 4 ( 2017-12), p. 881-890
    Type of Medium: Online Resource
    ISSN: 1869-6716 , 1613-9860
    URL: Article
    DOI: 10.1007/s13142-017-0514-0
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2017
    detail.hit.zdb_id: 2586893-7
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  • 3
    Online Resource
    Online Resource
    Impact of Avoiding Central Vascular Catheter-Drawn Blood Samples for Culture in a Large Tertiary Care University Hospital
    Oxford University Press (OUP) ; 2016
    In:  Open Forum Infectious Diseases Vol. 3, No. suppl_1 ( 2016-12-01)
    Details
    In: Open Forum Infectious Diseases, Oxford University Press (OUP), Vol. 3, No. suppl_1 ( 2016-12-01)
    Type of Medium: Online Resource
    ISSN: 2328-8957
    URL: Article
    DOI: 10.1093/ofid/ofw172.1182
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2016
    detail.hit.zdb_id: 2757767-3
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  • 4
    Online Resource
    Online Resource
    A computable phenotype for influenza vaccination status in patients with asthma
    Elsevier BV ; 2020
    In:  Journal of Allergy and Clinical Immunology Vol. 145, No. 2 ( 2020-02), p. AB59-
    Details
    In: Journal of Allergy and Clinical Immunology, Elsevier BV, Vol. 145, No. 2 ( 2020-02), p. AB59-
    Type of Medium: Online Resource
    ISSN: 0091-6749
    URL: Article
    DOI: 10.1016/j.jaci.2019.12.710
    RVK:
    XA 52000
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2020
    detail.hit.zdb_id: 2006613-2
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  • 5
    Online Resource
    Online Resource
    External validation of an opioid misuse machine learning classifier in hospitalized adult patients
    Springer Science and Business Media LLC ; 2021
    In:  Addiction Science & Clinical Practice Vol. 16, No. 1 ( 2021-12)
    Details
    In: Addiction Science & Clinical Practice, Springer Science and Business Media LLC, Vol. 16, No. 1 ( 2021-12)
    Abstract: Opioid misuse screening in hospitals is resource-intensive and rarely done. Many hospitalized patients are never offered opioid treatment. An automated approach leveraging routinely captured electronic health record (EHR) data may be easier for hospitals to institute. We previously derived and internally validated an opioid classifier in a separate hospital setting. The aim is to externally validate our previously published and open-source machine-learning classifier at a different hospital for identifying cases of opioid misuse. Methods An observational cohort of 56,227 adult hospitalizations was examined between October 2017 and December 2019 during a hospital-wide substance use screening program with manual screening. Manually completed Drug Abuse Screening Test served as the reference standard to validate a convolutional neural network (CNN) classifier with coded word embedding features from the clinical notes of the EHR. The opioid classifier utilized all notes in the EHR and sensitivity analysis was also performed on the first 24 h of notes. Calibration was performed to account for the lower prevalence than in the original cohort. Results Manual screening for substance misuse was completed in 67.8% (n = 56,227) with 1.1% (n = 628) identified with opioid misuse. The data for external validation included 2,482,900 notes with 67,969 unique clinical concept features. The opioid classifier had an AUC of 0.99 (95% CI 0.99–0.99) across the encounter and 0.98 (95% CI 0.98–0.99) using only the first 24 h of notes. In the calibrated classifier, the sensitivity and positive predictive value were 0.81 (95% CI 0.77–0.84) and 0.72 (95% CI 0.68–0.75). For the first 24 h, they were 0.75 (95% CI 0.71–0.78) and 0.61 (95% CI 0.57–0.64). Conclusions Our opioid misuse classifier had good discrimination during external validation. Our model may provide a comprehensive and automated approach to opioid misuse identification that augments current workflows and overcomes manual screening barriers.
    Type of Medium: Online Resource
    ISSN: 1940-0640
    URL: Article
    DOI: 10.1186/s13722-021-00229-7
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
    detail.hit.zdb_id: 2492632-2
    SSG: 15,3
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  • 6
    Online Resource
    Online Resource
    Development of a predictive model for identifying women vulnerable to HIV in Chicago
    Springer Science and Business Media LLC ; 2023
    In:  BMC Women's Health Vol. 23, No. 1 ( 2023-06-16)
    Details
    In: BMC Women's Health, Springer Science and Business Media LLC, Vol. 23, No. 1 ( 2023-06-16)
    Abstract: Researchers in the United States have created several models to predict persons most at risk for HIV. Many of these predictive models use data from all persons newly diagnosed with HIV, the majority of whom are men, and specifically men who have sex with men (MSM). Consequently, risk factors identified by these models are biased toward features that apply only to men or capture sexual behaviours of MSM. We sought to create a predictive model for women using cohort data from two major hospitals in Chicago with large opt-out HIV screening programs. Methods We matched 48 newly diagnosed women to 192 HIV-negative women based on number of previous encounters at University of Chicago or Rush University hospitals. We examined data for each woman for the two years prior to either their HIV diagnosis or their last encounter. We assessed risk factors including demographic characteristics and clinical diagnoses taken from patient electronic medical records (EMR) using odds ratios and 95% confidence intervals. We created a multivariable logistic regression model and measured predictive power with the area under the curve (AUC). In the multivariable model, age group, race, and ethnicity were included a priori due to increased risk for HIV among specific demographic groups. Results The following clinical diagnoses were significant at the bivariate level and were included in the model: pregnancy (OR 1.96 (1.00, 3.84)), hepatitis C (OR 5.73 (1.24, 26.51)), substance use (OR 3.12 (1.12, 8.65)) and sexually transmitted infections (STIs) chlamydia, gonorrhoea, or syphilis. We also a priori included demographic factors that are associated with HIV. Our final model had an AUC of 0.74 and included healthcare site, age group, race, ethnicity, pregnancy, hepatitis C, substance use, and STI diagnosis. Conclusions Our predictive model showed acceptable discrimination between those who were and were not newly diagnosed with HIV. We identified risk factors such as recent pregnancy, recent hepatitis C diagnosis, and substance use in addition to the traditionally used recent STI diagnosis that can be incorporated by health systems to detect women who are vulnerable to HIV and would benefit from preexposure prophylaxis (PrEP).
    Type of Medium: Online Resource
    ISSN: 1472-6874
    URL: Article
    DOI: 10.1186/s12905-023-02460-7
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2050444-5
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  • 7
    Online Resource
    Online Resource
    Evolution of an Electronic Health Record Based–Human Immunodeficiency Virus (HIV) Screening Program in an Urban Emergency Department for Diagnosing Acute and Chronic HIV Infection
    Elsevier BV ; 2019
    In:  The Journal of Emergency Medicine Vol. 57, No. 5 ( 2019-11), p. 732-739
    Details
    In: The Journal of Emergency Medicine, Elsevier BV, Vol. 57, No. 5 ( 2019-11), p. 732-739
    Type of Medium: Online Resource
    ISSN: 0736-4679
    URL: Article
    DOI: 10.1016/j.jemermed.2019.08.008
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2019
    detail.hit.zdb_id: 2006769-0
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  • 8
    Online Resource
    Online Resource
    COVID-19 Outcomes in Hospitalized Patients With Neurodegenerative Disease: A Retrospective Cohort Study
    Ovid Technologies (Wolters Kluwer Health) ; 2021
    In:  Neurology: Clinical Practice
    Details
    In: Neurology: Clinical Practice, Ovid Technologies (Wolters Kluwer Health)
    Abstract: COVID-19 outcomes in patients with neurodegenerative disorders are not well understood, and we hypothesize there may be increased morbidity and mortality in this group. Methods: This is a retrospective cohort study performed at three hospitals in the Chicagoland area. All patients hospitalized with COVID-19 infection with neurodegenerative disorder (ND) during a 3-month period (March 15-June 15, 2020) were included and compared with age-matched controls (CL) at 1:1 ratio. Primary outcomes were death, ICU admission and invasive ventilation. Secondary outcomes included presenting COVID-19 symptoms, development of encephalopathy, supplementary oxygen use, discharge disposition, and risk factors for mortality. Results: The study included 132 neurodegenerative patients and 132 age-matched controls. 90-day mortality (ND 19.7% vs CL 23.5%, p=0.45) and ICU admission (ND 31.5% vs CL 35.9%, p=0.43) rates were not significantly different between the two groups. ND patients had lower rate of invasive ventilation (ND 11.4% vs CL 23.2%, p=0.0075) and supplementary oxygen use (ND 83.2% vs CL 95.1%, p=0.0012). ND patients were also more likely to have “altered mental status or confusion” as their presenting COVID-19 symptom, and less likely to present with respiratory symptoms. ND patients were discharged to nursing home or hospice at higher rates compared to CL. Conclusion: We found there was no difference in short-term mortality of ND patients hospitalized for COVID-19 compared to controls, but they may have higher rates of neurologic complications and disability. Future studies should address long-term outcomes.
    Type of Medium: Online Resource
    ISSN: 2163-0402 , 2163-0933
    URL: Article
    DOI: 10.1212/CPJ.0000000000001117
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2021
    detail.hit.zdb_id: 2645818-4
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  • 9
    Online Resource
    Online Resource
    Data_Sheet_1.docx
    Frontiers Media SA ; 2022
    In:  Frontiers in Medicine Vol. 8 ( 2022-1-4)
    Details
    In: Frontiers in Medicine, Frontiers Media SA, Vol. 8 ( 2022-1-4)
    Abstract: There is a need for treatments to reduce coronavirus disease 2019 (COVID-19) mortality. Alpha-2 adrenergic receptor (α 2 AR) agonists can dampen immune cell and inflammatory responses as well as improve oxygenation through physiologic respiratory parameters. Therefore, α 2 AR agonists may be effective in reducing mortality related to hyperinflammation and acute respiratory failure in COVID-19. Dexmedetomidine (DEX) is an α 2 AR agonist used for sedation. We performed a retrospective analysis of adults at Rush University System for Health hospitals between March 1, 2020 and July 30, 2020 with COVID-19 requiring invasive mechanical ventilation and sedation ( n = 214). We evaluated the association of DEX use and 28-day mortality from time of intubation. Overall, 28-day mortality in the cohort receiving DEX was 27.0% as compared to 64.5% in the cohort that did not receive DEX (relative risk reduction 58.2%; 95% CI 42.4–69.6). Use of DEX was associated with reduced 28-day mortality on multivariable Cox regression analysis (aHR 0.19; 95% CI 0.10–0.33; p & lt; 0.001). Adjusting for time-varying exposure to DEX also demonstrated that DEX was associated with reduced 28-day mortality (aHR 0.51; 95% CI 0.28–0.95; p = 0.03). Earlier DEX use, initiated & lt;3.4 days from intubation, was associated with reduced 28-day mortality (aHR 0.25; 95% CI 0.13–0.50; p & lt; 0.001) while later DEX use was not (aHR 0.64; 95% CI 0.27–1.50; p = 0.30). These results suggest an α 2 AR agonist might reduce mortality in patients with COVID-19. Randomized controlled trials are needed to confirm this observation.
    Type of Medium: Online Resource
    ISSN: 2296-858X
    URL: Article
    URL: Article
    DOI: 10.3389/fmed.2021.797647
    DOI: 10.3389/fmed.2021.797647.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2775999-4
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