Title |
MyPreventiveCare: implementation and dissemination of an interactive preventive health record in three practice-based research networks serving disadvantaged patients—a randomized cluster trial
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Published in |
Implementation Science, December 2014
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DOI | 10.1186/s13012-014-0181-1 |
Pubmed ID | |
Authors |
Alex H Krist, Rebecca A Aycock, Rebecca S Etz, Jennifer E Devoe, Roy T Sabo, Robert Williams, Karen L Stein, Gary Iwamoto, Jon Puro, Jon Deshazo, Paulette Lail Kashiri, Jill Arkind, Crystal Romney, Miria Kano, Christine Nelson, Daniel R Longo, Susan Wolver, Steven H Woolf |
Abstract |
Evidence-based preventive services for early detection of cancer and other health conditions offer profound health benefits, yet Americans receive only half of indicated services. Policy initiatives promote the adoption of information technologies to engage patients in care. We developed a theory-driven interactive preventive health record (IPHR) to engage patients in health promotion. The model defines five levels of functionality: (1) collecting patient information, (2) integrating with electronic health records (EHRs), (3) translating information into lay language, (4) providing individualized, guideline-based clinical recommendations, and (5) facilitating patient action. It is hypothesized that personal health records (PHRs) with these higher levels of functionality will inform and activate patients in ways that simpler PHRs cannot. However, realizing this vision requires both technological advances and effective implementation based upon clinician and practice engagement. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 2 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Science communicators (journalists, bloggers, editors) | 1 | 50% |
Members of the public | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 3 | 1% |
Argentina | 1 | <1% |
Canada | 1 | <1% |
Switzerland | 1 | <1% |
Unknown | 205 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 34 | 16% |
Student > Ph. D. Student | 31 | 15% |
Researcher | 30 | 14% |
Student > Doctoral Student | 17 | 8% |
Student > Postgraduate | 13 | 6% |
Other | 41 | 19% |
Unknown | 45 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 64 | 30% |
Nursing and Health Professions | 31 | 15% |
Social Sciences | 19 | 9% |
Computer Science | 13 | 6% |
Psychology | 11 | 5% |
Other | 23 | 11% |
Unknown | 50 | 24% |