Customer Relationship Management Intervention Application (CRM) on Drug Interaction and Quality Improvement of Life Patients with Hypertension

Customer Relationship Management Intervention Application (CRM) on Drug Interaction and Quality Improvement of Life Patients with Hypertension

Authors

  • Ari Usman , Eva SartikaDasopang , and NilsyaFebrikaZebua

Keywords:

CRM, hypertension, drug interactions.

Abstract

Customer Relationship Management (CRM) applications are one way to improve
services forpatients. This application can be used to overcome the problem of patient noncompliance in the consumption of antihypertensive drugs that must be consumed
continuously to control blood pressure levels. Hypertension is a metabolic disease that is often
accompanied by other diseases, so that it is handled using polypharmacy drug therapy and
the possibility of drug interactions can occur. This study aims to see the intervention of
Customer Relationship Management (CRM) applications in reducing blood pressure so as to
improve the quality of life in patients with Diabetes Mellitus and drug interactions that occur
due to the use of polypharmacy drugs. This research method was carried out using a CRM
application with a research design conducted in a cross sectional perspective. This research
was conducted in one of the health centers in the city of Medan against patients with
hypertension. Data analysis was carried out descriptively using the Chi-Square test of the
SPSS Advanced statistic 16.0.
The results of this study note that the highest gender category in hypertensive patients is
52.5%, the age category with the most hypertension is> 60 years age group as much as 70%,
the most use of single antihypertensive drugs is a calcium channel blockers (amlodipine) 75%,
and the most widely used combination is the calcium channel blockers with angiotensin
receptor blockers (amlodipin + Valsartan) 15%. This study showed a significant correlation
between blood sugar levels before and after using the CRM application intervention using test
analysis. Chi-square can get p value 0.034 (p <0.05)

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Published

30-10-2018

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Section

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