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Health coaching by medical assistants to improve control of diabetes, hypertension, and hyperlipidemia in low-income patients: a randomized controlled trial.
- Author(s): Willard-Grace, Rachel;
- Chen, Ellen H;
- Hessler, Danielle;
- DeVore, Denise;
- Prado, Camille;
- Bodenheimer, Thomas;
- Thom, David H
- et al.
Published Web Locationhttp://annfammed.org/content/13/2/130.full
No data is associated with this publication.
PurposeHealth coaching by medical assistants could be a financially viable model for providing self-management support in primary care if its effectiveness were demonstrated. We investigated whether in-clinic health coaching by medical assistants improves control of cardiovascular and metabolic risk factors when compared with usual care.
MethodsWe conducted a 12-month randomized controlled trial of 441 patients at 2 safety net primary care clinics in San Francisco, California. The primary outcome was a composite measure of being at or below goal at 12 months for at least 1 of 3 uncontrolled conditions at baseline as defined by hemoglobin A1c, systolic blood pressure, and low-density lipoprotein (LDL) cholesterol. Secondary outcomes were meeting all 3 goals and meeting individual goals. Data were analyzed using χ(2) tests and linear regression models.
ResultsParticipants in the coaching arm were more likely to achieve both the primary composite measure of 1 of the clinical goals (46.4% vs 34.3%, P = .02) and the secondary composite measure of reaching all clinical goals (34.0% vs 24.7%, P = .05). Almost twice as many coached patients achieved the hemoglobin A1c goal (48.6% vs 27.6%, P = .01). At the larger study site, coached patients were more likely to achieve the LDL cholesterol goal (41.8% vs 25.4%, P = .04). The proportion of patients meeting the systolic blood pressure goal did not differ significantly.
ConclusionsMedical assistants serving as in-clinic health coaches improved control of hemoglobin A1c and LDL levels, but not blood pressure, compared with usual care. Our results highlight the need to understand the relationship between patients' clinical conditions, interventions, and the contextual features of implementation.
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