1536. Impact of Type of Provider on Appropriateness of Treatment for Gonorrhea and Chlamydia in Outpatient Clinics

Abstract Background Patients with sexually transmitted infections (STIs) receive care in a variety of outpatient settings with medical providers of different levels of training and expertise, especially regarding STIs. We aimed to determine the impact of type of provider on the appropriateness of treatment for chlamydia and gonorrhea in a large integrated health system. Methods We conducted a retrospective cohort study of adult patients diagnosed with chlamydia and/or gonorrhea at any outpatient clinic within an integrated health system in Des Moines, Iowa. Nucleic-acid amplification tests were used for diagnosis, and all samples were processed at the same laboratory. Adequate treatment was defined as prescription for appropriate antibiotic, dose and duration within 7 days of the positive test. Logistic regression models with robust standard errors and adjusting for clustering by clinic were built. Results We identified 481 unique patients and a total of 515 unique encounters. Considering unique patients only, the median patient age was 23 years (IQR 20-26), 466/481 (96.9%) were female (96.9%), 15/481 (3.1%) were male, and 79/481 (16.4%) were pregnant. Table 1 shows the patient demographic and provider characteristics by appropriateness of treatment for individual visits. A total of 53 patients had inappropriate treatment, some with multiple errors which are described in Table 2. Provider type, age, type of infection, and pregnancy status were significantly associated with appropriateness of treatment. After adjusting for type of infection, pregnancy status and clustering by clinic, compared to physicians, certified nurse midwives (CNMs) had 33% lower odds of prescribing appropriate treatment (95% CI 0.49-0.91; p-value = 0.010), with no difference in appropriateness of prescribing by mid-level providers (OR 1.61, 95% CI 0.82-3.17; p-value = 0.167). Pregnancy was independently associated with lower odds of appropriate treatment (OR 0.35, 95% CI 0.24-0.52; p-value < 0.001), as was infection with gonorrhea (OR 0.29, 95% CI 0.12-0.68; p-value = 0.004). Table 1. Demographic characteristics of adult patients diagnosed with chlamydia and/or gonorrhea in outpatient clinics by appropriateness of treatment. Des Moines, Iowa, January 1, 2019 to December 31, 2019 Table 2. Type of therapeutic errors encountered among patients diagnosed with chlamydia or gonorrhea Conclusion CNMs had lower odds of prescribing appropriate treatment for STIs. Efforts aimed at improving prescribing by healthcare providers should actively engage with this group. Disclosures All Authors: No reported disclosures

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570. Prioritized Access to COVID-19 Vaccines Among Vulnerable Communities Increases Vaccination Rates

Open Forum Infectious Diseases ◽

10.1093/ofid/ofab466.768 ◽

2021 ◽

Vol 8 (Supplement_1) ◽

pp. S386-S387

Author(s):

Leonor Fernandez ◽

Ashley O'Donoghue ◽

Peter Shorett ◽

Jonathan Blair ◽

Lawrence Markson ◽

...

Keyword(s):

Health System ◽

Urban Communities ◽

P Value ◽

Vaccination Rates ◽

Vulnerable Communities ◽

Early Access ◽

Percentage Points ◽

The Difference ◽

National Trends ◽

The Impact

Abstract Background Based on national recommendations,1 Beth Israel Lahey Health (BILH) in Eastern Massachusetts (MA) prioritized vulnerable communities in our distribution of COVID-19 vaccines. We hypothesized that creating prioritized access to appointments for patients in these communities would increase the likelihood vaccination. Methods The BILH health system sent vaccine invitations first to patients of two clinics in vulnerable neighborhoods in Boston (Wave 1), followed by other patients from vulnerable communities (Wave 2) up to 1 day later, and then by all other patients (Wave 3) after up to 1 more day later. To identify whether early access/prioritization increased the likelihood of receipt of vaccine at any site or a vaccine at a BILH clinic, we compared patients in Wave 1 in a single community with high cumulative incidence of COVID-19 (Dorchester) to patients in Wave 2 during a period of limited vaccine access, 1/27/21-2/24/21. Each wave was modeled using logistic regression, adjusted for language and race. By taking the difference between these two differences, we are left with the impact of early vaccination invitation in Wave 1 for a subset of our most vulnerable patients (termed difference-in-differences; Stata SE 16.0). Results In our study of Waves 1 and 2, we offered vaccinations to 24,410 patients. Of those, 6,712 (27.5%) scheduled the vaccine at BILH (Table 1). Patients in Wave 1 were much more likely to be vaccinated at BILH than patients in Wave 2. Patients offered the vaccine in Wave 1 and living in Dorchester were 1.7 percentage points more likely to be vaccinated at all (p=0.445) and 9.4 percentage points more likely to be vaccinated at BILH than another site in MA (p-value = 0.001), relative to patients living outside of Dorchester and offered the vaccine in Wave 2 (Table 2). The coefficient of interest is on Wave1*Dorchester, 0.094. This indicates that residents of Dorchester who were offered the vaccine in Wave 1 were 9.4 percentage points more likely to receive the vaccine at BILH, given that they were vaccinated, relative to patients living outside of Dorchester and offered the vaccine in Wave 2. Conclusion Patients residing in an urban community given prioritized access to vaccination had a higher likelihood of vaccination at our health system, given that they were vaccinated, than patients in other urban communities without prioritized access. We provide an example of a successful effort to move towards equity in access to COVID-19- vaccines, in contrast to larger national trends.2,3 Health systems can use a prioritization approach to improve vaccination equity. Disclosures All Authors: No reported disclosures

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The impact of an integrated health-system specialty pharmacy on HIV antiretroviral therapy adherence, viral suppression and CD4 count in an outpatient ID clinic

Journal of Drug Assessment ◽

10.1080/21556660.2019.1658309 ◽

2019 ◽

Vol 8 (sup1) ◽

pp. 4-4

Author(s):

Elizabeth Barnes ◽

Adam Giumenta ◽

Marc Johnson ◽

Jing Zhao

Keyword(s):

Antiretroviral Therapy ◽

Health System ◽

Viral Suppression ◽

Cd4 Count ◽

Therapy Adherence ◽

Antiretroviral Therapy Adherence ◽

Integrated Health ◽

Specialty Pharmacy ◽

Hiv Antiretroviral Therapy ◽

The Impact

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Prevalence and recognition of obesity and its associated comorbidities: cross-sectional analysis of electronic health record data from a large US integrated health system

BMJ Open ◽

10.1136/bmjopen-2017-017583 ◽

2017 ◽

Vol 7 (11) ◽

pp. e017583 ◽

Cited By ~ 33

Author(s):

Kevin M Pantalone ◽

Todd M Hobbs ◽

Kevin M Chagin ◽

Sheldon X Kong ◽

Brian J Wells ◽

...

Keyword(s):

Electronic Health Record ◽

Health System ◽

Cleveland Clinic ◽

P Value ◽

Health Record ◽

Electronic Health Record Data ◽

Cross Sectional ◽

Academic Medical Centre ◽

Integrated Health ◽

Electronic Health

ObjectiveTo determine the prevalence of obesity and its related comorbidities among patients being actively managed at a US academic medical centre, and to examine the frequency of a formal diagnosis of obesity, via International Classification of Diseases, Ninth Revision (ICD-9) documentation among patients with body mass index (BMI) ≥30 kg/m2.DesignThe electronic health record system at Cleveland Clinic was used to create a cross-sectional summary of actively managed patients meeting minimum primary care physician visit frequency requirements. Eligible patients were stratified by BMI categories, based on most recent weight and median of all recorded heights obtained on or before the index date of 1July 2015. Relationships between patient characteristics and BMI categories were tested.SettingA large US integrated health system.ResultsA total of 324 199 active patients with a recorded BMI were identified. There were 121 287 (37.4%) patients found to be overweight (BMI ≥25 and <29.9), 75 199 (23.2%) had BMI 30–34.9, 34 152 (10.5%) had BMI 35–39.9 and 25 137 (7.8%) had BMI ≥40. There was a higher prevalence of type 2 diabetes, pre-diabetes, hypertension and cardiovascular disease (P value<0.0001) within higher BMI compared with lower BMI categories. In patients with a BMI >30 (n=134 488), only 48% (64 056) had documentation of an obesity ICD-9 code. In those patients with a BMI >40, only 75% had an obesity ICD-9 code.ConclusionsThis cross-sectional summary from a large US integrated health system found that three out of every four patients had overweight or obesity based on BMI. Patients within higher BMI categories had a higher prevalence of comorbidities. Less than half of patients who were identified as having obesity according to BMI received a formal diagnosis via ICD-9 documentation. The disease of obesity is very prevalent yet underdiagnosed in our clinics. The under diagnosing of obesity may serve as an important barrier to treatment initiation.

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Opioid e-prescribing trends at discharge in a large pediatric health system

Journal of Opioid Management ◽

10.5055/jom.2019.0493 ◽

2019 ◽

Vol 15 (2) ◽

pp. 119-127

Author(s):

Christopher M. Horvat, MD, MHA ◽

Brian Martin, DMD ◽

Liwen Wu, MS ◽

Anthony Fabio, PhD ◽

Phil E. Empey, PharmD, PhD ◽

...

Keyword(s):

Health System ◽

Drug Monitoring ◽

Monitoring Program ◽

The United States ◽

Prevalence Odds Ratio ◽

Pediatric Health ◽

Lower Odds ◽

Opioid Prescribing ◽

Prescribing Trends ◽

The Impact

Objective: Legitimate opioid prescriptions have been identified as a risk factor for opioid misuse in pediatric patients. In 2014, Pennsylvania legislation expanded a prescription drug monitoring program (PDMP) to curb inappropriate controlled substance prescriptions. The authors’ objective was to describe recent opioid prescribing trends at a large, pediatric health system situated in a region with one of the highest opioid-related death rates in the United States and examine the impact of the PDMP on prescribing trends.Design: Quasi-experimental assessment of trends of opioid e-prescriptions, from 2012 to 2017. Multivariable Poisson segmented regression examined the effect of the PDMP. Period prevalence comparison of opioid e-prescriptions across the care continuum in 2016.Results: There were 62,661 opioid e-prescriptions identified during the study period. Combination opioid/non-opioid prescriptions decreased, while oxycodone prescriptions increased. Seasonal variation was evident. Of 110,884 inpatient encounters, multivariable regression demonstrated lower odds of an opioid being prescribed at discharge per month of the study period (p 0.001) and a significant interaction between passage of the PDMP legislation and time (p = 0.03). Black patients had lower odds of receiving an opioid at discharge compared to white patients. Inpatients had significantly greater odds of receiving an opioid compared to emergency department (Prevalence Odds Ratio 7.1 [95% confidence interval: 6.9-7.3]; p 0.001) and outpatient (398.9 [355.5-447.5]; p 0.001) encounters.Conclusion: In a large pediatric health system, oxycodone has emerged as the most commonly prescribed opioid in recent years. Early evidence indicates that a state-run drug monitoring program is associated with reduced opioid prescribing. Additional study is necessary to examine the relationship between opioid prescriptions and race.

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Implementing Primary Care Mediated Population Genetic Screening within an Integrated Health System

10.1101/2020.07.16.20140228 ◽

2020 ◽

Author(s):

Sean P David ◽

Henry M Dunnenberger ◽

Raabiah Ali ◽

Adam Matsil ◽

Amy A Lemke ◽

...

Keyword(s):

Primary Care ◽

Health System ◽

Genetic Screening ◽

Screening Program ◽

Median Number ◽

Large Impact ◽

Preventative Care ◽

Number Of Patients ◽

Integrated Health ◽

The Impact

AbstractIntroductionGenetic screenings can have a large impact on enabling personalized preventative care. However, this can be limited by the primary use of medical history-based screenings in determining care. The purpose of this study was to understand the impact of DNA10K, a population-based genetic screening program mediated by primary care physicians (PCPs) within an integrated health system to emphasize its contribution to preventative healthcare.MethodsConstruction of the patient experience as part of DNA10K shaped the context for PCP engagement within the program. A cross-sectional analysis of patient consents, orders, tests, and results of nearly 10,000 patients within the primary care specialties of family medicine, internal medicine or obstetrics/gynecology between April 1, 2019 and January 22, 2020 was conducted.ResultsAcross all specialties, a median number of 7.5 cancer and cardiovascular disease variants per PCP was found. The average age of the study population was 49.6 years. Over 8% of these patients had at least one actionable genetic risk variant and almost 2% of patients had at least one CDC Tier 1 variant. The median number of patients per PCP with either hereditary breast and ovarian cancer, Lynch Syndrome, or Familial Hypercholesterolemia was 1 (Interquartile Range 0-2).DiscussionThe analysis of test results and the engagement of an integrated healthcare system in the implementation of a genetic screening program suggests that it can have a large impact on population health outcomes and minimal referral burden to PCPs if identified risks can lead to preventative care.

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Impact of the COVID-19 Pandemic on Health Care Utilization in a Large Integrated Health Care System (Preprint)

10.2196/preprints.26558 ◽

2020 ◽

Author(s):

Stanley Xu ◽

Sungching Glenn ◽

Lina Sy ◽

Lei Qian ◽

Vennis Hong ◽

...

Keyword(s):

Health Care ◽

Health Care Utilization ◽

Early Period ◽

Fold Increase ◽

Integrated Health Care ◽

Care Utilization ◽

P Value ◽

Care Organization ◽

Integrated Health ◽

The Impact

BACKGROUND COVID-19 has caused an abrupt drop in the use of in-person health care, accompanied by a corresponding surge in usage of telehealth services. However, the extent and nature of changes in health care utilization during the pandemic may differ by care setting. Knowledge of the impact of the pandemic on health care utilization is important to health care organizations and policy makers. OBJECTIVE The aims of this study are 1) to describe changes in in-person health care utilization and telehealth visits during the COVID-19 pandemic, and 2) to measure the difference in changes of health care utilization between the pandemic year 2020 and the pre-pandemic year 2019. METHODS We retrospectively assembled a cohort consisting of members of a large integrated health care organization who were enrolled between January 6, 2019-November 2, 2019 (pre-pandemic year) and between January 5, 2020-October 31, 2020 (pandemic year). The rates of visits were calculated weekly for four settings: inpatient, emergency department (ED), outpatient and telehealth. Using Poisson models, we assessed the impact of the pandemic on health care utilization during the early days of the pandemic and conducted difference in deference (DID) analyses to measure the changes in health care utilization adjusting for the trend of health care utilization in the pre-pandemic year. RESULTS In the early days of the pandemic, we observed significant reductions in inpatient, ED, and outpatient utilization (by 30.2%, 51.1%, and 85.5%, respectively). By contrast, there was a 4-fold increase in telehealth visits between week 8 (February 23) and week 13 (March 29) of year 2020. DID analyses showed that after adjusting for pre-pandemic secular trends, the decreases in inpatient, ED, and outpatient visit rates in the early days of the pandemic were 1.6, 12.1, and 415.0 visits per 100 person-years (p-value<0.0001), respectively, while the increase in telehealth visits was 272.9 visits per 100 person-years (p-value<0.0001). Further analyses suggested that the increase in telehealth visits offset the decrease in outpatient visits by week 26 (June 28). CONCLUSIONS Conclusions: In-person health care utilization dropped dramatically during the early period of the pandemic, but there was a corresponding increase in telehealth visits during the same period. By the end of June 2020, the combined outpatient and telehealth visits had recovered to pre-pandemic levels.

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Mudanças na atividade física de lazer, locomoção e tempo de televisão entre homens e mulheres usuários do Sistema Único de Saúde em uma cidade de médio porte: seguimento de 18 meses

Brazilian Journal of Kinanthropometry and Human Performance ◽

10.5007/1980-0037.2018v20n1p20 ◽

2018 ◽

Vol 20 (1) ◽

pp. 20-28

Author(s):

Rafael Orbolato ◽

Rômulo Araújo Fernandes ◽

Bruna Camilo Turi ◽

Monique Yndawe Castanho-Araujo ◽

Carolina Rodrigues Bortolatto ◽

...

Keyword(s):

Physical Activity ◽

Health System ◽

Activity Level ◽

Behavior Patterns ◽

P Value ◽

Unified Health System ◽

Tv Watching ◽

The Impact ◽

Over Time

Given the importance of physical activity for health promotion and for the prevention of chronic non-communicable diseases, the Unified Health System (SUS) has changed its strategy of action in the last decades, trying to adopt preventive activities, seeking better quality of life of the Brazilian population and reduce costs with treatment of diseases. The aim of this study was to investigate changes in physical activity and sedentary behavior patterns in users of the Brazilian National Unified Health System during 18 months and the impact of sex and time on such variables. One hundred and ninety-eight participants (58 men and 140 women) were evaluated. Physical activity level was assessed using the Baecke questionnaire. Men had higher scores in all physical activity variables compared to women: walking (p-value = 0.013), cycling (p-value = 0.001) and commuting (p-value= 0.007), but not for TV watching (p-value = 0.362). After 18 months, in the overall sample, walking score increased 25.9% (95%CI = 10.6 to 41.1), but not cycling (1.5% [95%CI = -2.7 to 5.7]), commuting (14.4% [95%CI = -0.4 to 29.3]) and TV watching (1.6% [95%CI = -5.7 to 9.1]). Men were usually more active than women in active behaviors, but not in TV watching. However, differences over time were similar between sexes.

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