Assessment of Life's Simple 7 in the primary care setting: the Stroke Prevention in Healthcare Delivery EnviRonmEnts (SPHERE) study.
BACKGROUND
Adverse health behaviors and factors predict increased coronary heart disease and stroke risk, and effective use of health information technology (HIT) to automate assessment of and intervention on these factors is needed. A comprehensive, automated cardiovascular health (CVH) assessment deployed in the primary care setting offers the potential to enhance prevention, facilitate patient-provider communication, and ultimately reduce cardiovascular (CV) disease risk. We describe the methods for a study to develop and test an automated CVH application for stroke prevention in older women.


RESULTS
The eligible study population for the Stroke Prevention in Healthcare Delivery EnviRonmEnts (SPHERE) study is approximately 1600 female patients aged 65 years and older and their primary care providers at The Ohio State University Wexner Medical Center. We will use an intervention design that will allow for a run-in period, comparison group data collection, a provider education period, and implementation of a best practice alert to prompt provider-patient interactions regarding CVH. Our primary outcome is a CVH score, comprising Life's Simple 7: smoking status, body mass index, blood pressure, cholesterol, fasting glucose, physical activity, and diet. The SPHERE application will generate visualizations of the CVH score within the electronic health record (EHR) during the patient-provider encounter. A key outcome of the study will be change in mean CVH score pre- and post-intervention.


CONCLUSIONS
The SPHERE application leverages the EHR and may improve health outcomes through HIT designed to empower clinicians to discuss CVH with their patients and enhance primary prevention efforts.
Division of Epidemiology, The Ohio State University College of Public Health, Columbus, OH, USA. Electronic address: rforaker@cph.osu.edu.
Randi E
RE
Foraker
Division of Biostatistics, The Ohio State University College of Public Health, Columbus, OH, USA.
Abigail B
AB
Shoben
Department of Biomedical Informatics, The Ohio State University College of Medicine, Columbus, OH, USA.
Marcelo A
MA
Lopetegui
Department of Biomedical Informatics, The Ohio State University College of Medicine, Columbus, OH, USA.
Albert M
AM
Lai
Department of Biomedical Informatics, The Ohio State University College of Medicine, Columbus, OH, USA.
Philip R O
PR
Payne
Department of Biomedical Informatics, The Ohio State University College of Medicine, Columbus, OH, USA.
Marjorie
M
Kelley
Department of Biomedical Informatics, The Ohio State University College of Medicine, Columbus, OH, USA.
Caryn
C
Roth
Division of General Internal Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Hilary
H
Tindle
Department of Internal Medicine, The Ohio State University College of Medicine, Columbus, OH, USA.
Andrew
A
Schreiner
Department of Endocrinology, The Ohio State University College of Medicine, Columbus, OH, USA.
Rebecca D
RD
Jackson
D000368:Aged; D001786:Blood Glucose; D001794:Blood Pressure; D015992:Body Mass Index; D002318:Cardiovascular Diseases / Q000175:diagnosis / Q000517:prevention & control*; D002784:Cholesterol / Q000097:blood; D020000:Decision Support Systems, Clinical / Q000458:organization & administration; D004032:Diet; D057286:Electronic Health Records / Q000458:organization & administration*; D015444:Exercise; D005260:Female; D015438:Health Behavior; D006801:Humans; D009820:Ohio; D011320:Primary Health Care / Q000458:organization & administration*; D011322:Primary Prevention / Q000458:organization & administration*; D012107:Research Design; D012307:Risk Factors; D000074606:Smoking Prevention; D020521:Stroke / Q000517:prevention & control
D001786:Blood Glucose; D002784:Cholesterol
Aging; Biomedical informatics; Lifestyle; Risk factor; Women