Int J Pharm Pharm Sci, Vol 8, Issue 5, 58-61Original Article
DRUG UTILIZATION STUDY OF ANTIHYPERGLYCEMIC AGENTS IN OUTPATIENTS AT OPD CLINICS IN SOUTH INDIAN METROPOLITAN CITY
KAYAMKANI ABEDULLA KHAN1
1Department of Pharmacy Practice, Sultan-ul–uloom College of Pharmacy, Banjara Hills, Hyderabad-34, Telangana State, India
Email: abidulla.k@gmail.com
Received: 09 Dec 2015 Revised and Accepted: 15 Mar 2016
ABSTRACT
Objective: To determine the drug utilization pattern of anti-diabetic medications in diabetic patients at diabetic outpatient clinics.
Methods: A prospective observational study was conducted to find out the drugs utilization and prescriptions pattern of antihyperglycemic agents in diabetic outpatients in urban Telangana. This study was conducted for a period of six months, known cases of Diabetic Mellitus who were receiving antihyperglycemic medicines as outpatients of either sex of all age groups were included and Patients with gestational diabetes were excluded from the study.
Results: In this study a total number of 250 prescriptions were collected which contained 1674 drugs. Among the prescriptions as an average each prescription contained more than 6.7drugs, this indicates polypharmacy. Among the antidiabetic drugs, metformin was found in a maximum number of prescription i.e. 109 (43.60%) and sitagliptin was found in a minimum number of prescriptions i.e.28 (11.20%) and most of the prescriptions contained antihypertensive agents, analgesics, vitamins and minerals preparations as supplements.
Conclusion: This report alarm all the physicians and health care professionals about various drug interactions and adverse drug reactions which occur due to polypharmacy and also causing a more financial burden to chronic disease patients.
Keywords: Drug utilization, Diabetes, Drug-drug interactions, Adverse drug reactions, DDD-defined daily dosage, ATC-Anatomical Therapeutic Chemical Classification and OPD-outpatient department
© 2016 The Authors. Published by Innovare Academic Sciences Pvt Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
INTRODUCTION
Diabetes mellitus (DM) is a group of metabolic diseases in which there is the elevation of blood sugar levels over a prolonged period [1]. High blood sugar cause frequent urination, increased thirst and increased hunger. If left untreated, diabetes can cause many complications [2]. Acute complications include diabetic ketoacidosis and hyperosmolar nonketotic coma [3]. Serious long-term complications include cardiovascular disease, stroke, chronic kidney failure, foot ulcers, and damage to the eyes [2].
As of 2013, 382 million people have diabetes worldwide [4]. Type 2 makes up about 90% of the cases [5, 6]. This is equal to 8.3% of the adult population [4] with equal rates in both women and men [6]. As of 2014, an estimated 387 million people have diabetes all over the world [7] with type 2 DM making up about 90% of the cases [4, 5]. From 2012 to 2014, diabetes is estimated to have resulted in 1.5 to 4.9 million deaths each year [7]. Diabetes, at least, doubles a person's risk of death [3]. The number of people with diabetes is expected to rise to 592 million by 2035[7]. The global economic cost of diabetes in 2014 was estimated to be $612 billion USD [4].
The greatest increase in diabetes rates was expected to occur in Asia and Africa, where most people with diabetes will probably live in 2030 [8]. The increase in rates in developing countries follows the trend of urbanization and lifestyle changes, including a "Western-style" diet.
Drug utilization study is a vital segment of pharmacoepidemiology, which describes the amount, quality, and determinants of drug exposure with the ultimate goal to facilitate rational use of drugs in the population [9–12]. Drug therapy is a major component of patient care management in health care settings. Prescribers and consumers are flooded with a vast array of pharmaceutical products with numerous brand names, available often at an unaffordable cost [13]. Irrational and inappropriate use of drugs in health care system notice globally is a major concern [9, 14, 15]. In this regard drug utilization study was undertaken in the diabetic outpatient clinics in urban Telangana state using ATC/defined daily dosage (DDD) system.
MATERIALS AND METHODS
A prospective observational study was carried out a period of six months from various outpatient clinics, hospitals, and pharmacies once the consultation by the physician was over, the prescriptions were copied, and the patients were interviewed as per the WHO guidelines and the following indicators were determined. DDD was calculated as per guidelines for ATC classification and DDD assignment as given by WHO collaborating center for drug statistics methodology, Oslo, Norway.
- Collect information on the diagnosis, drugs prescribed and calculate the mean number of drugs per prescription.
- Calculate the percentage of drugs prescribed the percentage of drugs prescribed by generic name, an average number of prescriptions (mean).
- Analyze the prescriptions for completeness of information as the presence of OPD number, name, age, and sex of the patient, diagnosis, name, dose, and duration of prescribed drugs.
- Percentage of drug prescribed from essential drug list or formulary.
Inclusion criteria
Diabetic patients treating as an outpatient, patients with diabetic & other co-morbid diseases with the various age group.
Exclusion criteria
Patients are unable to communicate, i.e., patients on ventilators or seriously ill patients requiring ICU admissions as well as those unwilling to participate were excluded from the study.
The DDD/1000/day was calculated as follows:
RESULTS
A total of 250 prescriptions were collected, which contained 1674 different drugs as included according to the inclusion criteria as mentioned above, out of 250 patients 95.2 % patients were type-2 diabetes and 4.8 % patients were type-1 diabetes. Among the prescriptions on an average each prescription contained 6.7 drugs which indicate polypharmacy. There were males (55%) than females (45%). Most of the prescriptions contained vitamins and minerals preparations as supplements. Among the subcategories of anti-diabetic drugs, Metformin was found in a maximum number of prescription i.e. 109 (43.60%) and sitagliptin was found in a minimum number of prescriptions, i.e.,.28 (11.20%). There were 32.1% patients with diabetics are 61 y and above age projected in fig.1. The DDD/1000/day and the percentage of drugs prescribed were described in the table.1, and the DDD/1000/day maximum value was found to be gliclazide. DDD was calculated as per guidelines for ATC classification and DDD assignment as given by WHO collaborating center for drug statistics methodology, Oslo, Norway.
The prescription pattern of Antidiabetics drugs in a number of Prescriptions is shown in fig.2. The types of antidiabetic drugs prescribed according to age exhibit in table 2. metformin prescribed concomitantly along with other antidiabetic drugs was found more often 27.2% of prescriptions(table.5). 36.8 % of prescriptions were observed to be prescribed with highest in a number of drugs (8 in each) which was reveal in table 6. Only 4.8% of Percent of drugs prescribed by generic Name. Whereas the Percentage of drugs prescribed from National Essential drug list (NEDL)/National Formulary of India (NFI) was 34.18%.
Fig. 1: Patients according to the age groups
Fig. 2: Types of Antidiabetic drugs prescribed in number of prescriptions
Table 1: The DDD/1000/day and the percentage of drugs prescribed at the diabetic OPD clinics
S. No. |
Types of anti-diabetics |
No. of prescriptions |
Percentage of usage |
DDD/1000/day |
1 |
Metformin (Biguanide) |
109 |
43.60 |
0.33 |
2 |
Glibenclamide (Sulfonylurea) |
34 |
13.60 |
0.66 |
3 |
Glipizide (Sulfonylurea) |
42 |
16.80 |
1.33 |
4 |
Gliclazide (Sulfonylurea) |
54 |
21.60 |
1.78 |
5 |
Repaglinide (Meglitinide) |
32 |
12.80 |
0.67 |
6 |
Rosiglitazone (Thiazolidinedione) |
51 |
20.40 |
0.89 |
7 |
Sitagliptin (Dipeptidyl Peptidase-4 Inhibitors) |
28 |
11.2 |
0.533 |
8 |
Insulin |
45 |
18.00 |
0.625 |
Total: 6.818 |
||||
Table 2: Age distribution of prescriptions according to antidiabetic drugs
Anti-diabetic drugs |
Age in years |
|||||
Drug names |
ATC codes |
No. of prescriptions |
1-20 y |
21-40 y |
41-60 y |
Above 61 y |
Metformin |
A10BA02 |
109 |
12 |
22 |
40 |
35 |
Glibenclamide |
A10BB01 |
34 |
02 |
08 |
10 |
14 |
Glipizide |
A10BB07 |
42 |
00 |
05 |
27 |
10 |
Gliclazide |
A10BB09 |
54 |
05 |
10 |
22 |
17 |
Repaglinide |
A10BX02 |
32 |
00 |
08 |
14 |
10 |
Rosiglitazone |
A10BG02 |
51 |
00 |
11 |
18 |
22 |
Sitagliptin |
A10BH01 |
28 |
00 |
08 |
14 |
06 |
Insulin |
A10AB01 |
45 |
00 |
06 |
12 |
27 |
Table 3: Gender distribution of prescriptions according to antidiabetics
Anti-diabetics |
No. of prescriptions |
Gender |
||
Drugs |
ATC codes |
Prescriptions (%) |
Male |
Female |
Metformin |
A10BA02 |
43.60 (109) |
47 |
62 |
Glibenclamide |
A10BB01 |
13.60 (34) |
14 |
20 |
Glipizide |
A10BB07 |
16.80 (42) |
23 |
19 |
Gliclazide |
A10BB09 |
21.60 (54) |
28 |
26 |
Repaglinide |
A10BX02 |
12.80 (32) |
15 |
17 |
Rosiglitazone |
A10BG02 |
20.40 (51) |
23 |
28 |
Sitagliptin |
A10BH01 |
11.2 (28) |
13 |
15 |
Insulin |
A10AB01 |
18.00 (45) |
28 |
17 |
Table 4: Diagnosis of patients receiving antidiabetic
Diagnosis |
No. of patients |
% of patients |
No. of prescriptions |
TYPE-1 |
12 |
4.8 |
12 |
TYPE-2 |
238 |
95.2 |
238 |
Table 5: Number of occasion’s concomitant antidiabetic prescribed in the prescriptions
Drugs |
No. of occasions |
% occasions (out of total prescriptions) |
Metformin |
68 |
27.2 |
Glibenclamide |
23 |
9.2 |
Glipizide |
18 |
7.2 |
Gliclazide |
16 |
6.4 |
Repaglinide |
19 |
7.6 |
Rosiglitazone |
12 |
4.8 |
Sitagliptin |
20 |
8.0 |
Insulin |
54 |
21.6 |
Table 6: Number of drugs per prescription
No. of drugs per prescription |
No. of prescriptions |
No. of drugs |
% of prescriptions |
1 |
03 |
03 |
1.2 |
2 |
06 |
12 |
2.4 |
3 |
08 |
24 |
3.2 |
4 |
08 |
32 |
3.2 |
5 |
12 |
60 |
4.8 |
6 |
40 |
240 |
16 |
7 |
81 |
567 |
32.4 |
8 |
92 |
736 |
36.8 |
Total number of drugs = 1674
Total number of Prescriptions = 250
Average drugs per Prescription = 6.696 drugs
DISCUSSION
Drug utilization studies are important for obtaining data about the patterns and quality of use, the determinants of drug use, and the outcomes of use. The WHO drug use indicators are highly standardized and are recommended for inclusion in drug utilization studies [17–19]. The present study attempts mainly to describe the current prescribing pattern and drug utilization with the WHO core prescribing indicators in Outpatient diabetic clinics. For outpatients, DDD/1000/day provides a rough estimate of drug consumptions [22]. The utilization of Gliclazide was 1.78 DDD/1000/day. Total antidiabetic drug consumption in diabetic OPD clinics was 6.818 DDD/1000/day.
Most common antidiabetic prescribed were biguanide (metformin). The newer antidiabetic–Repaglinide and Sitagliptin accounted for the bulk of prescriptions, which followed the global trend towards antidiabetic prescribing. Percentages of prescriptions prescribed by generic name are very less 4.8% (20).
However, prescribing drugs by generic name makes the therapeutic management economic and rational as it evades prescription writing errors and confusion of dispensing of different brand names which sound alike and spell similar [21]. The doses of antidiabetic were decided upon according to the severity of the disease/disorder, starting with low doses and titrating upwards or downwards according to the clinical response and the patients were kept on regular follow-up. In our study, we found that the average drugs per Prescription are 6.696, which is polypharmacy.
Most of the prescriptions contained multivitamins and minerals, analgesics and antiulcer drug preparations as supplements. This report alarm all the physicians and health care professionals about various drug interactions and adverse drug reactions which are occurring due to polypharmacy and also causing a more financial burden to chronic disease patients.
It is advice to prescribe the only optimal drug for the respective disease conditions. There is need of various drug utilization studies should be conducted to rationalize the prescription patron in India, and there should be a vigilance who should monitor the prescriptions before dispensing and to minimize the ADR, drug interactions and decrease the economic burden and also other complications in patients.
Which can be possible only with Clinical pharmacists, so Indian ministry of health should avail the service of a clinical pharmacist in Indian? Which will save the economy of the country and also prevent the morbidity and mortality occur due to irrational drug prescriptions?
CONCLUSION
Our study in Hyderabad has shown that pharmacists can contribute substantially to promote the rational use of medicines, even in resource-limited settings. This, of course, requires strong collaboration between different institutions and commitments of the pharmacists to the cause. Pharmacist medication review, patient counseling and telephone follow-up can minimize the Adverse Drug Reactions. Medication discrepancies before and after discharge were common targets of intervention.
These efforts must include both studies to understand the best methods to reinforce more successfully the appropriate use of medications according to accepted guidelines and innovative tools to support physician decision making and patient compliance.
ABBREVIATION
DM-Diabetes Mellitus, ADR-Adverse Drug Reaction; USD-US Dollar; DDD-defined daily dosage; ATC-Anatomical Therapeutic Chemical Classification; OPD-outpatient department.
WHO–world health organization; ICU–intensive care unit; NEDL-National Essential drug list and NFI-National Formulary of India
ACKNOWLEDGEMENT
Authors thank all the patients for their participation and cooperation in the study.
CONFLICT OF INTERESTS
Conflict of interest declared none.
REFERENCES
- World Health Organization and International Diabetes Federation (IDF) Technical Advisory Group, review and update the current WHO guidelines on diabetes. WHO, Geneva; 2005.
- World Health Organization. Global Health Estimates: Deaths by Cause, Age, Sex and Country from 2000 to 2012. Geneva, WHO; 2014.
- Kitabchi AE, Umpierrez GE, Miles JM, Fisher JN. Hyperglycemic crises in adult patients with diabetes. Diabetes Care 2009;32:1335–43.
- IDF Diabetes atlas. 6th edition. International Diabetes Federation; 2013. p. 7.
- Vos T, Flaxman AD, Naghavi M, Lozano R, Michaud C, Ezzati M, Shibuya K, et al. Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries in 1990–2010 a systematic analysis for the global burden of disease study 2010.Lancet 2015;9859:2163–96.
- Cooke DW, Plotnick L. Type 1 diabetes mellitus in pediatrics.Pediatr Rev2008;29:374–84.
- The online version of International Diabetes Federation (IDF) Diabetes Atlas. Sixth edition; 2013. p. 71-82.
- Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes: Estimates for the year 2000 and projections for 2030.Diabetes Care 2004;27:1047–53.
- World Health Organization (WHO) and International Network for Rational Use of Drugs, How to Investigate Drug Use in Health Facilities: Selected Drug Use indicators, WHO/ DAP/93.1, WHO, Geneva, Switzerland; 1993.
- World Health Organization (WHO) International Working Group for Drug Statistics Methodology, WHO Collaborating Centre for Drug Statistics Methodology, WHO Collaborating Centre for Drug Utilization Research and Clinical Pharmacological Services, Introduction to Drug Utilization Research, WHO, Oslo, Norway; 2003.
- World Health Organization, Introduction to Drug Utilization Research, WHO, Oslo, Norway; 2003.
- D Lee, U Bergman, LB Storm. Ed John Wiley and Sons, Chichester, UK. Studies of drug utilization in Pharmacoepidemiology; 2005. p. 401–17.
- NY Mirza, S Desai, B Ganguly. Prescribing pattern in a pediatric out-patient department in Gujarat. Bangladesh J Pharmacol 2009;4:39–42.
- HV Hogerzeil. Promoting rational prescribing: an international perspective. Br J Clin Pharmacol 1995;39:1–6.
- B Dinesh Kumar, TC Raghuram, G Radhaiah, K Krishnaswamy. Profile of drug users in urban and rural India. PharmacoEconomics 1995;7:332–46.
- R Like, I Francetic, M Bilusic. Benefits of optimization in antibiotic use. Coll Antropol 2007;31:241-6.
- World Health Organization (WHO) and International Network for Rational Use of Drugs, How to Investigate Drug Use in Health Facilities: Selected Drug Use indicators, WHO/DAP/93.1. WHO, Geneva, Switzerland; 1993.
- World health organization (WHO) international working group for drug statistics methodology, who is collaborating center for drug statistics methodology, who is collaborating center for drug utilization research and clinical pharmacological services, introduction to drug utilization research, WHO, Oslo, Norway; 2003.
- World Health Organization, Introduction to Drug Utilization Research, WHO, Oslo, Norway; 2003.
- Ruckmani A. Rational drug use: a remote possibility? Bull Drug Health Information 1995;2:20.
- M Nehru, K Kohli, B Kapoor, P Sadhotra, V Chopra, R Sharma. Drug utilization study in ophthalmology outpatient department of government medical college jammu. JK Science 2005;7:149–51.
- WHO Collaborating Centre for Drug Statistics Methodology. ATC index with DDDs. Oslo: WHO Collaborating Centre for Drug Statistics Methodology; 2002.