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  1. Article ; Online: Improved Documentation of Electronic Cigarette Use in an Electronic Health Record

    Thulasee Jose / J Taylor Hays / David O. Warner

    International Journal of Environmental Research and Public Health, Vol 17, Iss 5908, p

    2020  Volume 5908

    Abstract: The use of electronic cigarettes (e-cigarettes) can affect patient health and clinical care. However, the current documentation of e-cigarette use in the electronic health records (EHR) is inconsistent. This report outlines how the ambulatory clinical ... ...

    Abstract The use of electronic cigarettes (e-cigarettes) can affect patient health and clinical care. However, the current documentation of e-cigarette use in the electronic health records (EHR) is inconsistent. This report outlines how the ambulatory clinical practices of a large U.S. hospital system optimized its electronic health records (EHR) framework to better record e-cigarettes used by patients. The new EHR section for e-cigarette information was implemented for outpatient appointments. During a 30-week evaluation period post-implementation, 638,804 patients (12 yrs and older) completed ambulatory appointments within the health system; of these, the new section contained e-cigarette use information for 37,906 (6%) patients. Among these patients, 1005 (2.7%) were identified as current e-cigarette users (current every day or current some day e-cigarette use), 941 (2.5%) were reported as former e-cigarette users, and 35,960 (94%) had never used e-cigarettes. A separate EHR section to document e-cigarette use is feasible within existing clinical practice models. Utilization of the new section was modest in routine clinical practice, indicating the need for more intensive implementation strategies that emphasize the health effects of e-cigarette use, and how consistent ascertainment could improve clinical practice.
    Keywords e-cigarettes ; vaping ; electronic nicotine delivery device ; electronic cigarettes ; Medicine ; R
    Subject code 027
    Language English
    Publishing date 2020-08-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Electronic Cigarette Use Is Not Associated with COVID-19 Diagnosis

    Thulasee Jose / Ivana T. Croghan / J. Taylor Hays / Darrell R. Schroeder / David O. Warner

    Journal of Primary Care & Community Health, Vol

    2021  Volume 12

    Abstract: This analysis tested the hypothesis that current e-cigarette use was associated with an increased risk of SARS-CoV-2 infection in patients seeking medical care. E-cigarette and conventional cigarette use were ascertained using a novel electronic health ... ...

    Abstract This analysis tested the hypothesis that current e-cigarette use was associated with an increased risk of SARS-CoV-2 infection in patients seeking medical care. E-cigarette and conventional cigarette use were ascertained using a novel electronic health record tool, and COVID-19 diagnosis was ascertained by a validated institutional registry. Logistic regression models were fit to assess whether current e-cigarette use was associated with an increased risk of COVID-19 diagnosis. A total of 69,264 patients who were over the age of 12 years, smoked cigarettes or vaped, and were sought medical care at Mayo Clinic between September 15, 2019 and November 30, 2020 were included. The average age was 51.5 years, 62.1% were females and 86.3% were white; 11.1% were currently smoking cigarettes or using e-cigarettes and 5.1% tested positive for SARS-CoV-2. Patients who used only e-cigarettes were not more likely to have a COVID-19 diagnosis (OR 0.93 [0.69-1.25], P = .628), whereas those who used only cigarettes had a decreased risk (OR 0.43 [0.35-0.53], P < .001). The OR for dual users fell between these 2 values (OR 0.67 [0.49-0.92], P = .013). Although e-cigarettes have the well-documented potential for harm, they do not appear to increase susceptibility to SARS-CoV-2 infection. This result suggests the hypothesis that any beneficial effects of conventional cigarette smoking on susceptibility are not mediated by nicotine.
    Keywords Computer applications to medicine. Medical informatics ; R858-859.7 ; Public aspects of medicine ; RA1-1270
    Subject code 610
    Language English
    Publishing date 2021-06-01T00:00:00Z
    Publisher SAGE Publishing
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Inter-library loan at ZB MED

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  3. Article ; Online: Design and Pilot Implementation of an Electronic Health Record-Based System to Automatically Refer Cancer Patients to Tobacco Use Treatment

    Thulasee Jose / Joshua W. Ohde / J. Taylor Hays / Michael V. Burke / David O. Warner

    International Journal of Environmental Research and Public Health, Vol 17, Iss 4054, p

    2020  Volume 4054

    Abstract: Continued tobacco use after cancer diagnosis is detrimental to treatment and survivorship. The current reach of evidence-based tobacco treatments in cancer patients is low. As a part of the National Cancer Institute Cancer Center Cessation Initiative, ... ...

    Abstract Continued tobacco use after cancer diagnosis is detrimental to treatment and survivorship. The current reach of evidence-based tobacco treatments in cancer patients is low. As a part of the National Cancer Institute Cancer Center Cessation Initiative, the Mayo Clinic Cancer Center designed an electronic health record (EHR, Epic © )-based process to automatically refer ambulatory oncology patients to tobacco use treatment, regardless of intent to cease tobacco use(“opt out”). The referral and patient scheduling, accomplished through a best practice advisory (BPA) directed to staff who room patients, does not require a co-signature from clinicians. This process was piloted for a six-week period starting in July of 2019 at the Division of Medical Oncology, Mayo Clinic, Rochester, MN. All oncology patients who were tobacco users were referred for tobacco treatment by the rooming staff ( n = 210). Of these, 150 (71%) had a tobacco treatment appointment scheduled, and 25 (17%) completed their appointment. We conclude that an EHR-based “opt-out” approach to refer patients to tobacco dependence treatment that does not require active involvement by clinicians is feasible within the oncology clinical practice. Further work is needed to increase the proportion of scheduled patients who attend their appointments.
    Keywords electronic health record ; tobacco ; smoking ; cancer ; opt-out ; Medicine ; R
    Language English
    Publishing date 2020-06-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Inter-library loan at ZB MED

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  4. Article ; Online: Utilization of an Electronic Health Record Integrated Risk Score to Predict Hospitalization Among COVID-19 Patients

    Mark A. Nyman / Thulasee Jose / Ivana T. Croghan / Mark A. Parkulo / Charles D. Burger / Darrell R. Schroeder / Ryan T. Hurt / John C. O’Horo

    Journal of Primary Care & Community Health, Vol

    2022  Volume 13

    Abstract: Objective: To evaluate the performance of an Electronic Health Record (EHR) integrated risk score for COVID-19 positive outpatients to predict 30-day risk of hospitalization. Patients and Methods: A retrospective observational study of 67 470 patients ... ...

    Abstract Objective: To evaluate the performance of an Electronic Health Record (EHR) integrated risk score for COVID-19 positive outpatients to predict 30-day risk of hospitalization. Patients and Methods: A retrospective observational study of 67 470 patients with COVID-19 confirmed by polymerase chain reaction (PCR) test between March 12, 2020 and February 8, 2021. Risk scores were calculated based on data in the chart at the time of the incident infection. Results: The Mayo Clinic COVID-19 risk score consisted of 13 components included age, sex, chronic lung disease, congenital heart disease, congestive heart failure, coronary artery disease, diabetes mellitus, end stage liver disease, end stage renal disease, hypertension, immune compromised, nursing home resident, and pregnant. Univariate analysis showed all components, except pregnancy, have significant ( P < .001) association with admission. The Mayo Clinic COVID-19 risk score showed a Receiver Operating Characteristic Area Under Curve (AUC) of 0.837 for the prediction of admission for this large cohort of COVID-19 positive patients. Conclusion: The Mayo Clinic COVID-19 risk score is a simple score that is easily integrated into the EHR with excellent predictive performance for severe COVID-19. It can be leveraged to stratify risk for severe COVID-19 at initial contact, when considering therapeutics or in the allocation of vaccine supply.
    Keywords Computer applications to medicine. Medical informatics ; R858-859.7 ; Public aspects of medicine ; RA1-1270
    Subject code 610
    Language English
    Publishing date 2022-01-01T00:00:00Z
    Publisher SAGE Publishing
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  5. Article ; Online: Digital Health Surveillance Strategies for Management of Coronavirus Disease 2019

    Thulasee Jose, MD / David O. Warner, MD / John C. O’Horo, MD, MPH / Steve G. Peters, MD / Rajeev Chaudhry, MBBS, MPH / Matthew J. Binnicker, PhD / Charles D. Burger, MD

    Mayo Clinic Proceedings: Innovations, Quality & Outcomes, Vol 5, Iss 1, Pp 109-

    2021  Volume 117

    Abstract: Objective: To describe the design, implementation, and utilization of electronic health record (EHR)–based digital health surveillance strategies used to manage the coronavirus disease 2019 (COVID-19) pandemic and to ensure delivery of high-quality ... ...

    Abstract Objective: To describe the design, implementation, and utilization of electronic health record (EHR)–based digital health surveillance strategies used to manage the coronavirus disease 2019 (COVID-19) pandemic and to ensure delivery of high-quality clinical care, such as case identification, remote monitoring, telemedicine services, and recruitment to clinical trials at Mayo Clinic. Methods: The design and implementation work described in this report was performed at Mayo Clinic, a large multistate integrated health care system with more than 1.5 million annual patient visits that uses the Epic EHR system. Rule-based live registries were designed in the EHR system to classify patients who currently test positive for COVID-19, patients who test positive but have recovered from COVID-19, patients who are thought to have COVID-19 but do not yet meet clinical diagnostic criteria, patients who test negative for COVID-19, and patients who exceed a risk score for serious complications from COVID-19. Results: By use of registries, custom dashboards and operational reports were developed to provide a daily high-level summary for clinical practice use and up-to-date information to manage individual patients affected by COVID-19, including support of case identification, contact isolation, and other care management tasks. Conclusion: We developed and implemented a systematic approach to the use of EHR patient registries to manage the COVID-19 pandemic that proved feasible and useful in a large multistate group clinical practice. The key to harnessing the potential of digital surveillance tools to promote patient-centered care during the COVID-19 pandemic was to use the registry data, reports, and dashboards as informatics tools to inform decision-making.
    Keywords Medicine (General) ; R5-920
    Subject code 610
    Language English
    Publishing date 2021-02-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Inter-library loan at ZB MED

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