S vs People Heart Study

SSMART (Stanford Surgical Mobile Assessing Risk Tracker) is a smartphone-based health app for a research study by the VA Palo Alto and Stanford University. SSMART acts as a platform to track surgical patients across a highly structured episode of care, their relationship between opioid use and pain, and self-reporting health-related symptoms. This app integrates with HealthKit, ResearchKit and CareKit, as well as the Apple Health App to collect data related to your medical condition, activity and general health.   Since SSMART is a research study based health app, the first step is for users to go through a consent process to participate in the research study; users may also withdraw from the study at any time as they please. Once user consent is given, SSMART will use the mobile health capabilities of a smartphone to access daily activity measures of patients with differing degrees of surgical procedures, once . Users that participate in the study will be asked to complete short assessments on their biopsychosocial behavioral patterns, medication and prescription details, and metrics related to pain, sleep, quality of life, daily functioning. These surveys will be staged pre- and post-surgery in different frequency patterns, as well as are presented to the user optionally. By using CareKit, users are given an easy way to track their health over time as well. Altogether, SSMART is a platform that allow physicians to better help their patients, but it is important to note SSMART does not give health advice. If health advice is needed, it is advised to visit VA Palo Alto Healthcare’s site: paloalto.va.gov.   Survey responses are saved in a secure and HIPAA compliant database. Medical professionals from Stanford Medicine and the VA Palo Alto that have approval for this study through the IRB will be the only ones to receive access to this data .All the information the patient provides will be used by the physician to monitor the patient’s overall health through the backend analytic web app.

We are interested in understanding how data can empower individuals to evaluate their health. In particular, we are studying how individuals can use their personal health data to assess their heart health. Why heart health? Because heart disease remains the leading cause of death in the United States, and evidence suggests that appropriate lifestyle and medical management can prevent it. Our study will help us understand whether individuals gaining digital access to their lab tests and medical history from their care providers results in enough data to produce heart health recommendations like this that adhere to current American College of Cardiology / American Heart Association guidelines for primary prevention of heart disease. Who can participate? -------------------- Individuals meeting the following criteria are eligible to enroll in this study - Age 40–75 years - Residents of the United States - Willing to link and share health record from iPhone’s Health app - Have NO history of heart attack, stroke or other heart-related illness What to expect --------------- Once all steps are completed, the app will create a heart disease risk report, including in the form of a downloadable PDF file, that can be shared with your doctor. This report will include information on your heart disease risk scores, major and minor risk factors, and suggested lifestyle changes. It may also include a recommended medication as appropriate. Discuss with your doctor ------------------------- The PDF report will contain guideline-based recommendations, including whether or not you may require interventions. Discussing this with your doctor can help you make better decisions. Please note ----------- While the recommendations may be based on a mix of your health data from your Electronic Health Records (EHR) and your self-reported medical history, they do not replace clinical judgment and are thus for research purposes only. Consulting your doctor with the report provided by the study may lead to a more informed, shared decision making process.