Prescription Audit and Drug Interactions of Anti-diabetic Drugs at Outpatient Department at a Tertiary Care Teaching Hospital in Eastern Nepal

Type 2 diabetes mellitus (T2DM) is the third major non-communicable disease in Nepal. Drug utilization studies help in reducing the patient’s expenditure, adverse drug reactions and drug-drug interactions. It would help in understanding of consumption of drugs including newer ones. Objective was to analyze the prescribing pattern and drug interactions of anti-diabetic drugs. A prospective cross-sectional study was conducted among patients having T2DM at Birat Medical College and Teaching Hospital (BMCTH), Biratnagar, Nepal from May 2019-August 2019. WHO core drug use indicators were used to analyze the obtained data. Descriptive statistics like mean, standard deviation, frequency and percentage were calculated using Microsoft Excel 2013. Out of 200 patients, 104 (52.0%) were females and 49.5% were from the age group of 41-60 years. Average number of drugs per patient was 5.74. Biguanides (40.7%) were the most common prescribed oral antidiabetic drugs followed by Sulfonylureas (23.3%). The percentage of drugs prescribed by generic name and from WHO essential drug list was 0.6% and 15.4% respectively. A total of 95 (47.5%) patients has potential drug-drug interaction (DDI) and it was most common in the age group of 41-60 years (43.2%). Among 95 DDI, Metformin+Amlodipine ranked in 1st position (16 encounters). Polypharmacy was prevalent in the present study. Metformin was the most commonly prescribed anti-diabetic drug. The percentage of drugs from the WHO essential medicine list and prescribed by generic names was low. Prevalence of potential DDI was high.


INTRODUCTION
Diabetes mellitus is a chronic metabolic disease characterized by elevated levels of blood glucose which leads over time to serious damage to the heart, blood vessels, eyes, kidneys and nerves.The global diabetes prevalence was estimated to be 9.3% in 2019 which is expected to rise to 10.2% by 2030 and 10.9% by 2045. 1 About 1 in 11 adults worldwide now have diabetes mellitus, 90% of whom have type 2 diabetes mellitus (T2DM). 2 Its prevalence is 8.5% in Nepal. 3T2DM is the third major non-communicable disease in Nepal and is approaching pandemic levels due to rapid change in socioeconomic status and life-style of the people. 4ug Utilization Research (DUR) is the marketing, distribution, prescription and use of drugs in the community with special emphasis on the resulting medical, social and economic consequences.It creates a rigorous socio-medical and health economic basis for healthcare decision making.It also helps to determine the role of drugs in society. 5It provides valuable evidence to the researchers, policymaker and drug and therapeutics committee members.Its ultimate importance is the rational use of drugs that helps in reducing the patient's expenditure, adverse drug reactions and drug-drug interactions. 5The associated complications and comorbidities results in prescription of several drugs that ultimately leads to polypharmacy. 6escription studies help to expand the importance of rational use of drugs.It would help in understanding of consumption of drugs including newer ones. 7Studies on drug utilization in diabetes is scarce in our context where the available resources are limited.Objective of the study was to analyze the prescribing pattern and drug interactions of anti-diabetic drugs at medicine OPD department in tertiary care teaching hospital, Eastern Nepal.

Materials and Methods
It was a prospective and quantitative hospitalbased study and was conducted in Birat Medical College and Teaching Hospital (BMCTH), Biratnagar, Nepal.The hospital is providing the tertiary level of health services.The data were collected from the patients having T2DM and visiting Medicine Outpatient Department at BMCTH, Biratnagar, Nepal from May 2019-August 2019.Using the formula, n= Z 2 *P*(1-P)/ d 2 , sample size was calculated to be 145 at 95% confidence level and prevalence of 56.4% 8 and the convenience sampling was used as sampling technique.

Data collection technique:
The study objectives were explained to the patients and written informed consent was taken.The OPD card of the patients were reviewed to collect the relevant data directly into the proforma.Medscape online app was used as drug-drug interaction checker and the pattern of potential DDI were analyzed and identified.Medscape drug-drug interaction checker is an electronic database that contains a separate section on DDI known as Medscape drug reference on entering the list of prescribed medication it enlisted all possible hazardous drug therapy and interactions on the basis of severity and documentation status. 9The following WHO core drug use indicators were used to analyze the obtained data: 10 (i).Percentage of drugs prescribed by generic name was calculated to measure the tendency of prescribing by generic name.It will be calculated by dividing the number of drugs prescribed by generic name by total number of drugs prescribed, multiplied by 100.
(ii).Average number of drugs per prescription was calculated by dividing the number of drugs prescribed by total number of patients.
(iii).Percentage of drugs prescribed from an essential drug list (EDL) was calculated to measure the degree to which practices conform to a national drug policy as indicated in the national drug list of Nepal. 11Percentage was calculated by dividing number of products prescribed which were in essential drug list by the total number of drugs prescribed, multiplied by 100.
(iv).Percentage of fixed-dose combination (FDC) prescribed= Number of FDC/Total drugs*100 Data analysis: The data were entered in Microsoft Excel 2013 and descriptive statistics like mean, standard deviation, frequency and percentage were calculated using SPSS-11.5.The findings were presented as tables and graphs.

RESULTS
A total of 200 patients were enrolled in the study and 104 (52.0%) were males.About one-half of the patients (49.5%) were from the age group of 41-60 years followed by 61-80 years (29.0%).One hundred and eleven patients (55.5%) were found to be illiterate and 126 (62.0%) were unemployed (Table 1).
A total of 1148 drugs were prescribed to 200 patients and average number of drugs per patient was 5.74.Anti-diabetic drugs (41.5%) were the most common prescribed drugs followed by cardiovascular drugs (21.16%) (Table 2).3).
WHO prescribing indicators are shown in Table 4.The percentage of drugs prescribed by generic name was 0.6%.The percentage of encounters with an injection preparation was 4.6%.The percentage of drugs prescribed from WHO essential drug list was 15.4%.The number of fixed dose combination prescribed was 12.2%.
In this present study, metformin (29.5%) was the most common drug associated with potential DDI followed by glimepiride (24.0%) (Table 5).

DISCUSSIONS
The present study revealed that half of the patients (49.5%) with DM were in the middleaged group (41-60 years) and this was similar to an Indian study (48.57%). 12It might be due to the unhealthy lifestyle and a high stress level in this age group.These age groups have a high chance of developing diabetes in their productive age because of their lifestyle modification, physical changes and stress.Most of the patients were female in the present study and this was in consistent with other study. 13ajority of the patients were illiterate and unemployed in the present study and similar findings were also reported by other reports. 14,15hese findings suggest that individuals with unemployement and less education are two to four times more likely to develop diabetes mellitus and more likely to be affected by the diabetes complications. 16er one-half of the patients (58.5%) had DM for 1-10 years.Besides, a family history of diabetes was observed in 25.0% of diabetic patients and was similar to an Indian study (83.4%). 17A family history of DM was observed in one-fourth of the patients in our study and was lower than a study conducted in India (32.0%). 17In our study, majority (76.0%) of the patients had one or more co-morbidities and hypertension was the commonest comorbidity.These findings were in consistent with other studies. 18,19Person with diabetes having more comorbidities are prescribed more drugs that can lead to polypharmacy and harmful drugdrug interactions. 20thin prescribed drugs, the percentage of antidiabetic drugs was found to be 41.4% in our study.In contrast to this, Jimoh et al. reported that 53.9% drugs were antidiabetics prescribed to the study participants. 213][24] About half of patients (48.5%) were prescribed three antidiabetic drugs in the present study and it was not consistent with Sharma et al 22 in which majority (50.6%) patients were prescribed two antidiabetic drugs.The study findings supported trend of combined antidiabetic therapy to achieve better glycemic control and to prevent progression of disease. 25n our study, average number of drugs per prescription was 5.7 that was higher than study by Eze Uchenna et al 14 (4.7) and Sharma et al 22 (4.2) and these findings unfortunately deviate from the WHO standard (1.6-1.8). 26,27It might be due to fact that the diabetic patients might have multiple comorbidities along with the various complications that lead to polypharmacy.
Considering, the prescribing indicators the percentage of drugs prescribed by generic names was 0.7% which is too low compared with the WHO standard. 27Abidi et al 28 found 4.5% of drugs were written in a generic name and Ramachandran et al 29 found 25.3% of generic drugs was prescribed.It is obvious that the trends of prescribing in the brand name imply to the promotion of the propriety products by pharmaceutical companies and pressure from the medical representatives of the branded products to prescribe their brand.
We found that 3.2% injectable drugs were prescribed that does not fall in the recommended range given by WHO. 27These findings closely matched to Acharya et al 30 (4.3%).Patients who have diabetes along with hypertension are mostly managed with oral hypoglycemic agents.This could be the reason behind the findings which does not meet the standard value.
In the current study, only 15.4% the drugs prescribed were from the National List of Essential Medicines, Nepal and this was lower than that found in western Nepal (88.0%) and India (90.6%). 19,31This could be the lack of advocacy on the importance of essential drugs list in our settings.Enforcement of rules to instruct the prescribers to prescribe from the essential drug lists to patients in private and public hospitals should be advocated.
Nearly half of the patients (47.5%) were exposed to drug-drug interaction (DDI).Similar result was also reported by Londhe et al 32 (63.3%).The most common drug pair with DDI was metformin-amlodipine.In contrast to this, insulin-metformin was the most common drug pair with DDI in a study by Londhe et al. 32 Furthermore, Upadhaya et al 33 found metformin-enalapril as the most common interacting drug pair.These variations might be due to varied prescription in other hospitals.Diabetes Mellitus is associated with multiple comorbidities and multiple drug therapy leading to increased risk of DDIs.Hence, to prevent these DDIs health care providers should have adequate information about DDIs not only via drug information center which can provide evidence-based information to healthcare professionals but also through encouraging the empowerment of clinical pharmacists that can provide the evidence-based approach to drugs and thereby prevent drug therapy problems.The present study had some limitations.Sample size of our study was small.The duration of the study was brief.Being a single center study, the findings cannot be generalized.
The present study revealed that polypharmacy was prevalent among persons with diabetes.
The percentage of drugs from the WHO essential medicine list and prescribed by generic names was low.Metformin was the most commonly prescribed anti-diabetic drug followed by fixed dose combination of metformin with sitagliptin.Prevalence of potential DDI was high and the topmost drug-drug interaction pair was metformin-amlodipine.Further research on a larger population is needed to sustain our study findings.

Fig.
Fig. Numbers of anti-diabetic drugs prescribed to the patients (n=200)