Abstract 095: Digital Solution Assisted Retail Pharmacists in Community Hypertension Control in China: A Real World Study of Large Samples

Abstract

Objective: To identify the effects of a digital healthcare solution for hypertension management at retail pharmacies by pharmacists. Methods: We developed a digital healthcare solution that includes BP telemonitor, an App, and a cloud database with algorithms to assist: 1) CVD risk screening, 2) personalized meal planning, 3) personalized health coaching, and 4) medication guidance and compliance during the pharmacy consultation service. This solution has been implemented in 5,067 retail pharmacies in 141 cities in China as a decision support system to help pharmacists manage their hypertensive members. During Jan 1 st 2015 to Dec 31 st 2016, a total of 1,817,594 patients received in-store hypertension care and 23,024 of them were selected in this analysis following 4 inclusion criteria: 1) baseline BP was hypertensive (≥ 140/90 mm Hg), 2) the frequency of in-store hypertensive care was ≥ 1 time per month, 3) the intervention duration between the first- and last-time hypertensive care was ≥ 1 month, and 4) baseline characteristics were complete. Dynamic changes of SBP, DBP, disease staging, and population distribution over time were the major end points in this real-world, retrospective analysis. Results: SBP and DBP of the study population (n=23,024) were reduced on average by 11.2 mm Hg (baseline: 151.7 ± 14.8 mm Hg, last time: 140.5 ± 18.8 mm Hg, P< 0.001) and 6.3 mm Hg (baseline: 91.2 ± 11.9 mm Hg, last time: 84.9 ± 12.7 mm Hg, P<0.001), respectively. A total of 13,001 (56.5%) patients demonstrated improved hypertension stages by the last time BP measures with 9,625 (41.8%) of them returning to the normal range. The principal BP control effect took place after the first-time intervention, followed by gradual BP reduction over time. Simulation analysis revealed linear descending relationship of both SBP and DBP to time, and the concentration distributions were moving towards the normal BP level. The linear fitting functions were: SBP, Y = -0.103x + 140.278; DBP, Y = -0.060x + 84.799. Conclusion: Digital healthcare solution is effective in assisting retail pharmacists to deliver community hypertension care in real world.