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2.
Prev Chronic Dis ; 15: E27, 2018 03 01.
Article in English | MEDLINE | ID: mdl-29494332

ABSTRACT

INTRODUCTION: Hypertension is highly prevalent in Florida, but surveillance through the Behavioral Risk Factor Surveillance System (BRFSS) is limited to self-reported hypertension and does not capture data on undiagnosed hypertension or measure blood pressure. We aimed to characterize the hypertensive population in the OneFlorida Clinical Research Consortium by using electronic health records and provide proof-of-concept for using routinely collected clinical data to augment surveillance efforts. METHODS: We identified patients with hypertension, defined as having at least 1 outpatient visit from January 2012 through June 2016 with an ICD-9-CM or ICD-10-CM diagnosis code for hypertension, or in the absence of a diagnosis, an elevated blood pressure (systolic ≥140 mm Hg or diastolic ≥90 mm Hg) recorded in the electronic health record at the most recent visit. The hypertensive population was characterized and mapped by zip code of patient residence to county prevalence. RESULTS: Of 838,469 patients (27.9% prevalence) who met the criteria for hypertension, 68% had received a diagnosis and 61% had elevated blood pressure. The geographic distribution of hypertension differed between diagnosed hypertension (highest prevalence in northern Florida) and undiagnosed hypertension (highest prevalence along eastern coast, in southern Florida, and in some rural western Panhandle counties). Uncontrolled hypertension was concentrated in southern Florida and the western Panhandle. CONCLUSION: Our use of clinical data, representing usual care for Floridians, allows for identifying cases of uncontrolled hypertension and potentially undiagnosed cases, which are not captured by existing surveillance methods. Large-scale pragmatic research networks, like OneFlorida, may be increasingly important for tailoring future health care services, trials, and public health programs.


Subject(s)
Hypertension/epidemiology , Adolescent , Adult , Aged , Ambulatory Care/statistics & numerical data , Cross-Sectional Studies , Databases, Factual , Electronic Health Records/statistics & numerical data , Female , Florida/epidemiology , Humans , Hypertension/prevention & control , Male , Middle Aged , Population Surveillance , Prevalence , Retrospective Studies , Risk Factors , Young Adult
3.
Clin Infect Dis ; 59(3): 390-7, 2014 Aug 01.
Article in English | MEDLINE | ID: mdl-24795331

ABSTRACT

Responding to escalating antimicrobial resistance (AMR), the US Department of Defense implemented an enterprise-wide collaboration, the Antimicrobial Resistance Monitoring and Research Program, to aid in infection prevention and control. It consists of a network of epidemiologists, bioinformaticists, microbiology researchers, policy makers, hospital-based infection preventionists, and healthcare providers who collaborate to collect relevant AMR data, conduct centralized molecular characterization, and use AMR characterization feedback to implement appropriate infection prevention and control measures and influence policy. A particularly concerning type of AMR, carbapenem-resistant Enterobacteriaceae, significantly declined after the program was launched. Similarly, there have been no further reports or outbreaks of another concerning type of AMR, colistin resistance in Acinetobacter, in the Department of Defense since the program was initiated. However, bacteria containing AMR-encoding genes are increasing. To update program stakeholders and other healthcare systems facing such challenges, we describe the processes and impact of the program.


Subject(s)
Anti-Infective Agents/pharmacology , Bacteria/drug effects , Bacterial Infections/prevention & control , Cross Infection/prevention & control , Drug Resistance, Bacterial , Epidemiological Monitoring , Research , United States , United States Department of Defense
4.
J Public Health Manag Pract ; 19(2): 178-86, 2013.
Article in English | MEDLINE | ID: mdl-23358297

ABSTRACT

CONTEXT: In 2008, about 40% of the US population eligible for influenza vaccine was vaccinated, which was below Healthy People 2020 goals. Little emphasis has been put on late-season vaccination efforts by medical providers. OBJECTIVE: Evaluate use of evidence-based practices (EBP) and their association with influenza vaccination for children younger than 5 years and adults aged 50 years and older. DESIGN: Patient surveys and medical clinic information were collected between January and April 2009. Influenza coverage rates and logistic regressions are used to measure associations. SETTING: Nineteen medical clinics serving children, adults, or both in San Diego County participated. PARTICIPANTS: Parents of children aged 6 months to 5 years and adults aged 50 years and over seen by a primary care provider during January through March 2009. MAIN OUTCOME: Influence of clinic EBP use on child and adult influenza vaccination status. MEASURES: Patient-reported influenza vaccination and clinic coverage rates and clinics' use of EBP and patient demographic characteristics. RESULTS: Coverage rates varied by clinic; 50% to 82% (children) and 48% to 85% (adults). Child clinics using the immunization registry, or those that were private practices or medical groups and adult clinics that used influenza vaccination clinics, provider prompts, or electronic medical records had higher coverage. Surveys from 831 children and 1038 adults documented influenza vaccination rates of 64% and 63% respectively. Receiving a reminder or having two or more visits during influenza season was positively associated with child and adult influenza vaccination. Child vaccination was associated with children younger than 2 years. Adult vaccination was associated adults aged 65 years or older, having a high-risk condition, or being female. CONCLUSIONS: Given the low use of EBP, clinics have opportunities to implement EBP appropriate for their settings and patient populations. Along with other strategies, public health departments and medical groups should encourage medical providers to implement EBP to improve influenza vaccination rates.


Subject(s)
Community Health Services , Evidence-Based Practice , Immunization Programs/statistics & numerical data , Influenza Vaccines/administration & dosage , Influenza, Human/prevention & control , Aged , California , Confidence Intervals , Female , Humans , Logistic Models , Male , Middle Aged , Odds Ratio , Primary Health Care
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