APPRAISEMENT OF DRUG UTILIZATION PATTERN OF ANTIMICROBIALS IN THE GENERAL MEDICINE DEPARTMENT OF A TERTIARY CARE TEACHING HOSPITAL – A PROSPECTIVE OBSERVATIONAL ANALYTICAL STUDY

APPRAISEMENT OF DRUG UTILIZATION PATTERN OF ANTIMICROBIALS IN THE GENERAL MEDICINE DEPARTMENT OF A TERTIARY CARE TEACHING HOSPITAL - A PROSPECTIVE OBSERVATIONAL ANALYTICAL STUDY

K. Mahesh Pavan, V. Upajna, G. Kusuma, V. Jaya Lakshmi and Uma Sankar Viriti ^*

Department of Pharmacy Practice, Avanthi Institute of Pharmaceutical Sciences, Cherukupally, Bhogapuram - 500027, Andhra Pradesh, India.

ABSTRACT: AIM: To see the appraisement of drug utilization pattern of antimicrobials in the general medicine department of a tertiary care teaching hospital. Methodology: A prospective observational, analytical study was done on patients admitted in general medicine of Maharaja Institute of Medical Sciences, Vizianagaram, Andhra Pradesh, India information regarding age, gender, diagnosis, patients present/past medical history, treatment, drug interactions were recorded in a standard questionnaire(case report form). The drug utilization process was evaluated using quality indicators of drug use recommendations by WHO. PDD of drugs and maximally used antimicrobials were analyzed. Results: A total of 250 patients were included after excluding missing data. Out of 250 patients, 123 (49.2%) were male, and 127 (50.8%) were female, 183 (65.12%) was bacterial, 74 (26.33%) were viral, 22 (7.82%) were protozoal, 2 (0.7%) were fungal, and the p-value was 0.0213, cephalosporins were most prescribed antimicrobial (27.72%), and anti-helminthics were least (0.33%), and p-value was found to be 0.0016. Out of 18 UTI cases, 3 were male, and 15 were female, and the p-value was found to be 0.0219, and out of 22 cellulitis cases, 15 were male, and 7 were female, and the calculated p-value was 0.0335. Conclusion: Prescription by generic name, antimicrobials from EDL, rationality, and WHO indicators are encouraging findings. Deviation in the therapy of UTI and Cellulitis, polypharmacy, DI are the areas of concern. There is a need for more such studies, including a larger no. of patients and other departments to encourage patient safety.

Drug utilization evaluation, Medication use review, Rationality

INTRODUCTION: Drug use evaluation (DUE) is defined as an ongoing, systematic, criteria-based program of medicine evaluations that will help ensure appropriate medicine use. If therapy is determined to be inappropriate, interventions with physicians or patients will be necessary to optimize pharmaceutical therapy. This terminology is similar to that drug use review (DUR) and medication use review (MUR).

Nowadays, drug utilization studies (DUS) are used as a potential tool in evaluating healthcare systems. Drug utilization studies are powerful tools to ascertain the role of drugs in society. They create a sound socio-medical and health economic basis for the healthcare decision making ¹.

DUE can assess the actual process of medication prescribing, administration, or dispensing. It involves a comprehensive review of prescriptions and medication data before, during, and after dispensing to assure appropriate therapeutic decision-making and positive outcome.

The Need for DUE:

• To find the solution for problems indicated from World Health Organization (WHO) / Management Sciences for Health (MSH) indicator studies.
• To identify and solve a high number of ADRs.
• To evaluate the signs of treatment failures.
• Excessive number of non-formulary medica-tions used. Use of high-cost medicines where less expensive alternatives exist.
• Excessive number of medicines within a therapeutic category.

Objectives of a DUE are as Follows:

• To provide assurance that the pharmaceutical. Therapy meets current standards of care.
• For promoting optimal medication therapy.
• To help in preventing medication-related problems.
• It also helps us in identifying specific medicine use problems that require further evaluation.
• DUR will help in creating guidelines (criteria) for appropriate medicine use.
• It is useful in defining thresholds for quality of medicine use.
• It helps us in enhancing accountability in the medicine use process.
• It plays an important role in controlling pharmaceutical costs.

MATERIALS AND METHODOLOGY:

Study Site: The study was conducted in the general medicine department of Maharaja Institute of Medical Sciences, Nellimarla, Vizianagaram, Andhra Pradesh.

Study Period: The study was conducted for a period of 6 months from August 2019 to January 2020.

Study Design: Prospective observational analytical study.

Sample Size: A total of 250 patients were included in the study.

Inclusion Criteria:

• Age between 12 - 85.
• Pregnant women.
• Patients with any kind of infectious diseases.
• Patients of both genders.
• Patient with any kind of comorbidity.

Exclusion Criteria:

• Age less than 12 years.
• Patients with any other chronic complications. Like kidney disease, hepatic diseases,
• Patients who were not willing to give the consent form.

Study Procedure:

Phase I:

• Obtaining consent from hospital authorities.
• Obtaining ethical clearance from institutional research and ethics committee.
• Literature survey.
• Design of data collected form.
• Collection of patient data, treatment chart from patient’s case sheet of inpatients.

Phase Ii:

• After elimination of all the missing data the final sample size 250 (The missing data is due to sudden discharge, sudden death, incomplete data).
• To evaluate the rationality of antimicrobials.
• To check the most commonly used anti-microbials.
• To check the types of drug interactions.
• Data assessment and data evaluation and analysis by using Prism Graphpad software.

RESULTS AND DISCUSSION:

Gender: The data were collected prospectively for 250 patients, and drug utilization evaluation was done.

In this study, demographic characters showed that females (50.8%) were more affected with in-fectious diseases when compared to males (49.2%).

This is similar to a study conducted by Kala et al., who concluded that females were more affected than males ².

TABLE 1: GENDER WISE DISTRIBUTION OF INFECTIOUS PATIENTS

FIG. 1: GENDER WISE DISTRIBUTION OF INFECTIOUS PATIENTS

Age Wise Distribution: Maximum number of patients who were affected with infectious diseases were between the age group of 11-20 years (18.40%) followed by age group 51-60 (18%). This might be due to increased exposure to environ-mental triggers, which may cause infections. This in contrast with Nathiya et al., who concluded that the age group 21-30 years were more affected ³.

TABLE 2: AGE WISE DISTRIBUTION OF PATIENTS

FIG. 2: AGE WISE DISTRIBUTION OF PATIENTS

Infection Wise Distribution: Out of 250 patients, 183 patients were affected with bacterial infections (65.12%), 74 patients (26.33%) were affected with viral infection, 22 patients (7.82%) were affected with protozoal infection, followed by 2 patients (0.71%) who suffered from fungal infection. The bio-statistical analysis was carried out for this data using the student t-test, and it was found to be significant, and the obtained p-value is 0.0213.

TABLE 3: INFECTION WISE DISTRIBUTION OF PATIENTS

P-value: 0.0213. One- or two-tailed P value Two-tailed

FIG. 3: INFECTION WISE DISTRIBUTION OF PATIENTS

Rationality Wise Distribution: Out of 250 pre-scriptions, 206 prescriptions (82.4%) were found to be rational, and 44 prescriptions (17.6%) were found to be irrational. This is similar to the study conducted by M. Praveen Kumar et al., who concluded that rational prescriptions were more in number than irrational ⁴.

TABLE 4: RATIONALITY WISE DISTRIBUTION OF PRESCRIPTIONS

FIG. 4: RATIONALITY WISE DISTRIBUTION OF PRESCRIPTIONS

Prescription Wise Distribution of Anti-Microbials: The majority of antimicrobials were prescribed with generic names (65.64%) followed by brand names (34.36%). Prescribing generic names may lower the cost of treatment, and it becomes easy for the hospital to maintain a proper inventory. This is in contrast with Kala et al., who concluded that antimicrobials were mostly prescribed with brand names than generic names ⁵.

TABLE 5: PRESCRIPTION WISE DISTRIBUTION OF ANTIMICROBIALS

FIG. 5: PRESCRIPTION WISE DISTRIBUTION OF ANTIMICROBIALS

Route of Administration: Out of 250 pre-scriptions, 123 prescriptions (49.40%) were prescribed with combination of both oral and intravenous antimicrobials followed by 109 prescriptions (43.78%) were prescribed with intravenous and 7 prescriptions (6.82%) were prescribed with oral antimicrobials. This is in contrast with the work done by M. Praveen Kumar et al., who concluded that most of the prescriptions were prescribed with intravenous followed by oral followed by combination of oral and intravenous antimicrobials ⁶.

TABLE 6: DIFFERENT ROUTES OF ADMINIS-TRATION OF ANTIMICROBIALS IN PATIENTS

FIG. 6: DIFFERENT ROUTES OF ADMINISTRATION OF ANTIMICROBIALS IN PATIENTS

Co-Morbidities Wise Distribution: Out of 250 patients, 69 patients (26.95%) were found to be having cardiovascular co-morbidities with the highest incidence, followed by renal co-morbidities with a total of 55 patients (21.48%). This is in contrast with the study conducted by Vimlesh Kumar Meena, Meena Atray, and Apurva Agrawal, department of pharmacology, R. N. T medical college, India, who concluded that respiratory co-morbidities were highest in incidence.

TABLE 7: COMORBIDITIES WISE DISTRIBUTION OF PATIENTS

FIG. 7: GRAPHICAL REPRESENTATION SHOWING PATIENTS SUFFERING WITH DIFFERENT CO-MORBIDITIES

Anti-microbial Wise Distribution: A total of 644 antimicrobials were prescribed among which beta-lactam antibiotics (cephalosporins -27.72%, pe-nicillins -10.39%) were most commonly prescribed followed by anti-malarials (9.24%).

This is because of their broad spectrum activity and convenient dosing regimen. The bio-statistical analysis was carried out for this data using student t test was found to be significant and the obtained p-value is 0.0016.

This result is in similar with Vimlesh Kumar Meena, Meena Atray and Apurva Agrawal, department of pharmacology, R. N. T medical college, India who concluded that beta-lactam antibiotics and anti-malarial drugs were most commonly prescribed.

TABLE 8: ANTIMICROBIAL DISTRIBUTION OF DRUGS

P value (two tailed): 0.0016

FIG. 8: GRAPHICAL REPRESENTATION OF ANTIMICROBIAL DISTRIBUTION OF DRUGS

Frequency of Anti-microbial Drugs Prescribed: More than half of the prescriptions were prescribed with combination therapy of antimicrobials (79.11%) followed by mono-therapy (20.88%).

This is in contrast with the work done by Jubaraj Singha et al., who concluded that prescription with monotherapy was found to be higher than prescription with combination therapy.

TABLE 9: FREQUENCY WISE DISTRIBUTION OF   ANTIMICROBIALS

FIG 9: FREQUENCY WISE DISTRIBUTION OF ANTI-MICROBIALS

Anti-microbial Drug Utilization: Highest number of units were prescribed for beta-lactam antibiotics which include cephalosporins (30.06%), penicillins (11.37%) followed by anti-amoebic (12.19%).

This is in similar to the study conducted by Patel et al., who concluded that beta-lactam antibiotics were prescribed most frequently ⁷.

 TABLE 10: ANTI-MICROBIAL DRUG UTILIZATION

FIG. 10: TOTAL NO. OF UNITS ADMINISTERED FOR DIFFERENT ANTIMICROBIALS

Prevalence o Disease on Gender Basis: Out of 250 patients, 183 patients were found to be suffering from bacterial infection out of which 88 patients were male, and 95 were female, 74 patients were suffering from viral infections out of which 34 patients were male, and 40 were female, 2 patients were found to be suffering from fungal infections out of which 1 patient was male, and 1 was female, and 22 patients were found to be suffering from protozoal infections out of which 14 were male, and 8 were female.

TABLE 11: PREVALENCE OF THE DISEASE ON GENDER BASIS

FIG. 11: PREVALENCE OF THE DISEASE ON GENDER BASIS

Comparison of Infection to Rationality: Out of 183 bacterial cases, 146 were found to be rational, and 37 were irrational; out of 74 viral cases, 58 were found to be rational, and 16 were found to be irrational, out of 2 fungal cases both of them were rational and out of 22 protozoal cases 18 were found to be rational, and 4 were irrational.

TABLE 12: COMPARISON OF TYPE OF INFECTION TO RATIONALITY

FIG. 12: COMPARISON OF TYPE OF INFECTION TO RATIONALITY

Comparison of Disease to Age: Out of 250 patients a highest number of bacterial infections were found between the age group of 51-60 years (19.67%), the highest number of viral infections were found between the age group of 31-40 years (25.67%), the highest number of protozoal infections were found between the age group of 21-30 years (31.81%) and fungal infection were distributed between the age groups of 31-40 years (50%) and 41-50 years (50%). The bio-statistical analysis was carried out for this data using two-way ANOVA was found to be significant.

TABLE 13: COMPARISON OF TYPE OF INFECTION WITH REFERENCE TO AGE

FIG. 13: COMPARISON OF TYPE OF INFECTION WITH REFERENCE TO AGE. Type of test: Two-way ANOVA Row factor: 0.0174 Column factor: <0.0001.

Most Commonly used Anti-microbial: Out of all antimicrobial classes, these five classes were found to be most commonly used.

Gender Wise Distribution of UTI: Out of 18 UTI cases, 15 were found to be female, and 3 cases were found to be male. The bio-statistical analysis was carried out for this data using the student t-test was found to be significant and the obtained p-value is 0.0219.

TABLE 14: MOST COMMONLY USED ANTI-MICROBIAL

FIG. 14: MOST COMMONLY USED ANTI-MICROBIAL

TABLE 15: GENDER WISE DISTRIBUTION OF UTI

P-value: 0.021. One or two-tailed P-value:  Two-tailed

FIG. 15: GENDER WISE DISTRIBUTION OF UTI

Deviation in the Line of Treatment as Per IDSA Guidelines: Out of 13 complicated UTI cases, 6 cases (49.15%) deviated, and out of 5 uncomplicated UTI cases, 4 cases (80%) deviated from therapy as mentioned in IDSA guidelines. This is contrast with the work done by Patil et al., ⁸.

Types of UTI in the Study Population: Out of 250 patients, a total of 18 patients were suffering from UTI among which 13 patients were of complicated UTI and 5 were suffering from uncomplicated UTI.

Uncomplicated UTI occurs in individuals who lack structural or functional abnormalities of the urinary tract that interfere with normal flow of urine, while complicated UTI occurs in patients with functional or structural abnormalities of genito-urinary tract.

This is in contrast with the work done by Patil et al. who concluded that complicated UTI was found in more individuals than uncomplicated UTI ⁹.

TABLE 16: DEVIATION IN THE LINE OF TREATMENT AS PER IDSA GUIDELINES

TABLE 17: TYPES OF UTI IN THE STUDY POPULATION

Gender Wise Distribution of Cellulitis: Out of 22 cellulitis cases, 7 cases were found to be female and 15 cases were male. The bio-statistical analysis was carried out for this data using student t-test, and it was found to be significant, and the obtained p-value is 0.0335.

TABLE 18: GENDER WISE DISTRIBUTION OF CELLULITIS

P-value: 0.0335. One or two-tailed P-value: Two-tailed

FIG. 18: GENDER WISE DISTRIBUTION OF CELLULITIS

Deviation in the Line of Treatment as Per Crest Guidelines: Out of 22 cellulitis cases, no patients were found in class-I, 8 patients were suffering with class-II cellulitis, out of which 2 patients deviated from the therapy, 2 out of 6 patients in class-III cellulitis deviated from therapy, 6 out of 8 patients deviated from the therapy mentioned as per CREST guidelines. This is similar to the study conducted by Patil, et al., who concluded that most of the cellulitis patients were found in class-III and IV ¹⁰.

TABLE 19: DEVIATION IN THE LINE OF TREATMENT AS PER CREST GUIDELINES

FIG. 19: DEVIATION IN THE LINE OF TREATMENT AS PER CREST GUIDELINES

Distribution of Drugs as Per EDL: A total of 644 antimicrobials were prescribed in 250 cases, out of which 595 antimicrobials (92.39%) were from the essential drug list, which is similar to the study conducted by Kala et al., who concluded that most of the prescribed antibiotics were from essential drug list. Drugs from EDL should be promoted for optimal use of resources and safety ¹¹.

Drug Interactions with Antimicrobials in Total Cases: Out of 250 prescriptions, 98 prescriptions showed drug-drug interactions. The reason for the incidence of drug-drug interaction may be due to polypharmacy used in the treatment of infection and also comorbid conditions.

TABLE 20: DISTRIBUTION OF DRUGS AS PER EDL

TABLE 21: COMPARISON OF PDD AND DDD VALUES

While comparing PDD and DDD values Cephalosporin’s were found to be higher in all the three categories with respect to antimicrobials

TABLE 22: COMPARISON OF PDD AND DDD VALUES

FIG. 22: DRUG INTERACTIONS IN TOTAL CASES

Drug Interactions with Anti-microbials in Total Cases: The drug interactions are categorized as mild, moderate, and severe.

Among 98 prescriptions, a total of 166 interactions were found, out of which 97 were mild (58.43%), 54 were moderate (32.53%), and 15 were severe (9.03%).

TABLE 23: DRUG INTERACTIONS IN TOTAL CASES

FIG. 23: DRUG INTERACTIONS WITH ANTI-MICROBIALS IN TOTAL CASES

Drug Interactions in between Different Anti-microbials: While considering the drug intera-ctions between antimicrobials and antimicrobials 20were found to be mild (46.66%), 17 were moderate (50%), and 2 were severe (3.34%).

TABLE 24: DRUG INTERACTIONS WITH ANTI-MICROBIALS IN TOTAL CASES

FIG. 24: DRUG INTERACTIONS BETWEEN ANTI-MICROBIALS

Drug Interactions between Anti-microbials and Other Drugs: While considering interactions between antimicrobials and other concomitant drugs 77 were mild (47.09%), 37 were moderate (30.1%), and 13 were severe (22.81%).

TABLE 25: DRUG INTERACTIONS BETWEEN DIFFERENT ANTI-MICROBIALS

FIG. 25: DRUG INTERACTIONS BETWEEN ANTI-MICROBIALS AND OTHER DRUGS

WHO Indicators: Average number of drugs per prescription was 0.3%, average number of anti-microbials per prescription was 0.4%, percentage of antimicrobials encountered with generic name was 66.4%, percentage of prescriptions en-countered with antimicrobials was 99.6%, percentage of antimicrobials prescribed intra-venously was 56.8% and percentage of antimicrobials from essential drug list was 92.3%. while comparing our work with Jubaraj Singha et al, the following parameters have lesser percentage, which include average no. of drugs per pre-scription, average no. of antimicrobials per pre-scription, percentage of antimicrobials encountered with generic name, percentage of antimicrobials prescribed intravenously and remaining parameters were found to be having higher percentage which include percentage of prescriptions encountered with antimicrobials and percentage of anti-microbials from EDL.

TABLE 26: DRUG INTERACTIONS BETWEEN ANTI-MICROBIALS AND OTHER DRUGS

FIG. 26: CONCOMITANT DRUGS PRESCRIBED IN THE TREATMENT

Concomitant Drugs Prescribed in the Treat-ment: Among the concomitant medications, anti-ulcer drugs were prescribed in 25.65% of the cases followed by NSAID’s in 21.22% of the cases.

Antiulcer drugs were prescribed in highest percentage to relieve the symptoms of GI irritation caused due to antibiotics, and NSAID’s are prescribed to relieve inflammatory reactions due to infections.

TABLE 27: WHO INDICATORS

This is similar to the study conducted by Farhan Ahmed Khan, Vinod Kumar Singh and Preeti Singh who concluded that anti-ulcer drugs and NSAID’s were the most frequently used concomitant drugs ¹².

TABLE 28: CONCOMITANT DRUGS PRESCRIBED IN THE TREATMENT

Some Encouraging Findings in Present Study: In our study we found that rationality of prescriptions was more than that of irrationality. Drugs are mostly prescribed with generic names that that of brand names. Most of the prescribed antimicrobials are from Essential Drug List (EDL).

Areas of Concern in Present Study: Deviation in the treatment of UTI was observed while comparing with the treatment prescribed in IDSA guidelines. Deviation in the treatment of cellulitis was observed while comparing with the treatment prescribed in CREST guidelines. A significant number of drug interactions was observed with antimicrobials.

Limitations of Present Study: The sample size which we considered in the evaluation was less, and it should be further expanded. Our Evaluation work was confined to only the general medicine department, and it should be further expanded to other departments. The total study was done in a single tertiary care hospital, and it can be expanded to more tertiary care hospitals, which will give the scope to include more patients.

CONCLUSION: Out of all the infectious diseases, bacterial infections were found to be dominant. Rationality is high when compared to irrationality, which is a good indication and helps in the improvement of patient quality of life. A significant percentage (34.36%) was prescribed with brand names. The physician should be aware while prescribing drugs with brand names as there is a chance of occurrence of dispensing errors and sometimes which may lead to an economic burden. Beta lactam antibiotics were most commonly prescribed cephalosporins particularly.

Patients were counselled regarding the side effects of beta lactam antibiotics for the safety and efficacy of drug usage. Cardiovascular comorbidities were more commonly seen in patients, followed by renal complications. We have advised the patient regarding the etiology, lifestyle modifications, and precautions to be taken. Most of the prescriptions were prescribed with drugs according to EDL, which indicates that the quality of prescription is very much appreciated. Cephalosporin prescribing pattern was found to be complicated in accordance with PDD and DDD values.

In some prescriptions, PDD of Cephalosporin’s was much higher than DDD, and in some prescriptions, it was less. Deviation in the line of treatment was clearly observed in cellulitis therapy in accordance with CREST guidelines which is to be concentrated by the physician so that deviations are to be avoided. Much more deviations were observed in UTI therapy in accordance with IDSA guidelines which is to be concentrated by the physician so that deviations are to be avoided. A significant percentage of drug interactions were observed with antimicrobials and discussed with physician regarding serious drug interactions and physician acceptance ratio was also appreciated. Further, research is to be carried out by using large sample size with more number of departments.

ACKNOWLEDGEMENT: We acknowledge the continuous support of Dr. M.B.V Raju (principal) for successfully completing the research.

CONFLICTS OF INTEREST: There were no conflicts of interest.

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    How to cite this article:

    Pavan KM, Upajna V, Kusuma G, Lakshmi VJ and Viriti US: Appraisement of drug utilization pattern of antimicrobials in the general medicine department of a tertiary care teaching hospital - a prospective observational analytical study. Int J Pharm Sci & Res 2021; 12(4): 2310-22. doi: 10.13040/IJPSR.0975-8232.12(4).2310-22.

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