29 Oct Community Interventions Improved Blood Pressure Control In Diverse Populations
Medical Research: What are the main findings of the study?
Dr. Thomas: The number of participants with controlled blood pressure (readings of less than 140/90) increased by 12 percent in the six months between the first and last readings. Mean systolic blood pressure for the population decrease by 4.7mmHg. The number of participants who had high blood pressure in the range of 140-149/90-99 decreased systolic blood pressure by a mean of 8.8mmHg and those with readings in the higher range of 150/100 or above decreased systolic blood pressure by 23.7percent. The study concluded that a program that followed this type of approach was associated with improved blood pressures across a diverse high-risk community.”
Medical Research: What was most surprising about the results?
The magnitude of the benefit provided to special populations including the uninsured/underinsured, racial and ethnic minorities.
The enthusiasm in which the majority of patients embraced this initiative.
Medical Research: What should clinicians and patients take away from your report?
Dr. Thomas: There are a myriad of reasons why blood pressure goals are not obtained thus there is no magic bullet that will fix the problem; it requires multiple levels of intervention. Utilizing advanced practice providers (PA’s), community health coaches and physicians allows for a balanced more cost effective approach that capitalizes on the individual strengths of these providers to meet the needs of patients. Don’t underestimate the effect of self-motivation/self empowerment in the lowering of blood pressure.
Medical Research: What recommendations do you have for future research as a result of this study?
Dr. Thomas: We need to implement and focus on sustainability for these type of community based programs to ensure the benefits can be maintained over a longer period of evaluation. The core premise and structure of our program is transferrable to other chronic conditions such as diabetes, asthma, hyperlipidemia etc. We need to evaluate this model in those diseases and in different communities.