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Table of Contents
Year : 2022  |  Volume : 8  |  Issue : 2  |  Page : 121-128

Evaluation of prescribing pattern based on World Health Organization indicators in Maharashtra during COVID-19 pandemic

Department of Clinical Pharmacy, Poona College of Pharmacy, Pune, Maharashtra, India

Date of Submission06-Dec-2021
Date of Decision18-Jul-2022
Date of Acceptance19-Jul-2022
Date of Web Publication31-Dec-2022

Correspondence Address:
Dr. Prasanna Deshpande
Poona College of Pharmacy, Bharati Vidyapeeth (Deemed to be University), Pune, Maharashtra
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ijcfm.ijcfm_100_21

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Introduction: Community pharmacy (CP) is one of the health care centers that have a key role to play in the current COVID-19 pandemic period. Prescriptions monitoring studies are essential as this helps in understanding the current prescribing pattern adopted by physicians. Furthermore, only few CP-based research studies were noted. This study was conducted with an aim to study prescribing pattern using World Health Organization (WHO) indicators from few community pharmacies in Maharashtra, India, during COVID-19 Pandemic period.
Material and Methods: An observational study was conducted and sample comprised of prescriptions collected from different parts of Maharashtra (Mumbai, Pune. and Nashik). One thousand and fifty-six prescriptions were collected and data was collected for a period of 6 months (August 2020–January 2021). The variables of interest in this study were: Number of medications in each prescription, number of prescriptions with generic names, number of antibiotics and injectables in each prescription, number of prescribed drugs from essential drug list (EDL), and defined daily dose (DDD).
Results: Out of 3058 drugs prescribed, it was found that average number of drugs per prescription was 2.89 (standard deviation ± 1.37). Only 23 (0.75%) were prescribed by generic name. Antibiotics and injectables were 399 (37.78%) and 29 (2.74%), respectively. Drugs that were prescribed from EDL were only 920 (30.08%). The total class of antimicrobial agents prescribed (Anatomical Therapeutic Chemical group J01) was 13. After calculating DDD, DDD of Azithromycin was found to the highest (81.6 g).
Conclusion: Among five WHO indicators, only the percentage of encounters with an injection was in compliance with the WHO recommended value. Further studies are required for better understanding of this area.

Keywords: Antibiotics, community pharmacy, defined daily dose, India, Maharashtra, prescribing indicators, World Health Organization

How to cite this article:
Jacob S, Malviya R, Sandhan S, Deshpande P. Evaluation of prescribing pattern based on World Health Organization indicators in Maharashtra during COVID-19 pandemic. Indian J Community Fam Med 2022;8:121-8

How to cite this URL:
Jacob S, Malviya R, Sandhan S, Deshpande P. Evaluation of prescribing pattern based on World Health Organization indicators in Maharashtra during COVID-19 pandemic. Indian J Community Fam Med [serial online] 2022 [cited 2023 May 28];8:121-8. Available from: https://www.ijcfm.org/text.asp?2022/8/2/121/366559

  Introduction Top

A community pharmacy (CP), also known as a retail pharmacy, is a place where medicines are stored, dispensed, supplied, or sold.[1] CP is one of the health centers that has a key role to play in the COVID pandemic situation.[1] As part of essential services, CPs play a major role in providing optimal care to patients. Patient-pharmacist interactions have improved as a result of the pandemic, enabling pharmacists to have a greater impact on patient care.[1] COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 had a tremendous impact on the delivery of healthcare worldwide. India crossed 3.03 crore cases of COVID-19, nearly 1 and ½ year after country reported its first case.[2] Global spread of COVID-19 has been placing demands on healthcare services.[2] According to a report from the Ministry of Statistics and Planning and Implementation of the Government of India, during an average 15-day reference period approximately 9% of the rural population and 12% of the urban population go to hospitals or physicians for consultation. This indicates that during the initial 21 initial days caused by COVID19, more than 15 million patients will visit medical institutions for health-related problems (considering that the total population of the country in April 2020 is estimate1.37 thousand million)[3] There has been an increase in the number of people visiting pharmacy with prescriptions.[4] Aiming to evaluate the condition of services offered to population concerning medications, the World Health Organization (WHO) developed, medication use indicators including prescribing indicators were used for assessing current prescribing pattern.[5] Therefore, prescribing practises adopted by physicians and how well those practises adhere to WHO prescribing guidelines can be assessed.[5]

The following are the basic drug use indicators developed by the WHO:

  • Average number of drugs per encounter (to measure degree of polypharmacy)
  • Percentage of drugs prescribed by generic name (adopting practises of prescribing by generic name reduces chances of dispensing errors which may lead to misinterpretation such as sounding brand names and helps reduce chances of error)
  • Percentage of encounters with an antibiotic prescribed (increasing multidrug resistance with limited availability of newer agents to treat emerging multidrug resistant clones emphasized the urgent need for vigilant surveillance, stringent infection control practises as well as rational antibiotic prescription)
  • Percentage of encounters with an injection prescribed (to measure overall level use of commonly overused forms of drug therapy)
  • Percentage of drugs prescribed from essential drug list (EDL) (to measure degree to which practises conform to the drug policy as indicated in the national drug list of India).[5]

The defined daily dose (DDD) is a statistical measure of drug consumption, defined by the WHO Collaborating Center for Drug Statistics Methodology.[6] It is defined in combination with Anatomical Therapeutic Chemical code (ATC code) drug classification system for grouping related drugs. Although knowledge about trends in total drug consumption can be useful, more detailed information about drug use at various levels is required for a fair assessment of current trends.[6] Previous research studies proved that correct interpretation of data on drug utilization requires monitoring at patient level.[6] Prescription monitoring studies have been highlighted as important in bridging areas such as rational prescription use, pharmacovigilance, pharmacoeconomic, and evidence-based medicine.[7] In previous researches, extensive comparisons of drug utilisation data obtained from the different countries were not permissible since the source and form of information differed, therefore researchers devised a new unit of measurement, the DDD, to overcome this challenge (DDD).[7] With ATC/DDD system, it is possible to construct results reflecting the quality of prescribing or drug use. Most studies encompass prescription monitoring of a particular group of drugs such as antiepileptics,[8] antimicrobials,[9] antiasthmatics,[10] and antihypertensive[11] drugs rather than evaluating all the prescribing indicators irrespective of the diagnosis like our study, that would enable capturing a broader picture of the current trends. Use of drugs by International Network of Rational Use of Drugs (INRUD) have devised the standard drug use indicators which help the prescriber to improve quality of the prescriptions.[7] Therefore, drug utilization study and WHO/INRUD guidelines are introspective and one of the critical instruments in providing positive impact on healthcare delivery to the patient.[7]

With this background, the current study was conducted to examine the prescription pattern and drug consumption by using WHO drug use indicators and DDD to assess current prescribing practices adopted by physician and how well they adhere to current standards.

  Material and Methods Top

An observational study was conducted for a period of six months (August 2020–January 2021). One thousand and fifty-six prescriptions were collected by convenience sampling method from three pharmacies (Vishrantwadi-Pune, Vikhroli-Mumbai, Pimpalgaon Baswant-Nashik) Maharashtra, India. Prescriptions from nearby clinics and hospitals were taken. Data were collected through from patients visiting pharmacy. Pediatric and adult population prescriptions, irrespective of age were included in the study. Inpatient cases and medico-legal cases were excluded.

Study protocol was approved by the Institutional Ethics committee (IEC) (Approval number: BVDUMC/IEC/41).

Structured and validated logbook was used to collect the data. Consent was taken from the patient before the collection of data. Name of the prescriber, age and gender of the patient, suspected diagnosis, medicines prescribed, duration of the prescribed medicines, dose, class of drugs, route of administration, frequency and duration of treatment were recorded in logbook. Based on this collected data, average number of drugs prescribed per patient encounter, percentage of encounters with an antibiotic prescribed, percentage of drugs prescribed by generic name, and percentage of drugs prescribed from essential drugs list from National List of Essential Medicines or formulary were calculated.

Statistical analysis

Descriptive statistics mean and standard deviation (SD) was calculated using GraphPad Prism version 9.1.2 (Windows and Mac),[12]

SocSci statistics (an online statistics calculator) was used to calculate P value (5 indicators)[13] Chi-square calculator (an online Chi-square calculator) was used to calculate Chi-square tests (Prescriber vs. WHO Indicators and Site vs. WHO indicators).[14]

Calculation of DDD was also conducted to understand the DDD of each antibiotic consumption, and therefore, it was calculated as below:

If prescribed daily dose by physician for Amoxicillin Clavulanic acid is 625 mg and frequency/number of times amoxicillin clavulanic acid was prescribed is 24. Then, DDD = 625 × 24 = 53126 mg = 53.12 g DDD prescribed by WHO for Amoxicillin Clavulanic acid = 1.5 g. Therefore, DDD of Amoxicillin Clavulanic acid is 53.12 g/1.5 g = 35 g.

  Results Top

A total of 1056 patients were enrolled in this study. Out of 1056, male predominance was noted 560 (53.03%) [Table 1]. Age groups between 0 and 20 were more in count as 1/3rd of the prescriptions collected were under this category. Most people visiting pharmacies were with prescriptions for age group between 21 and 60. Geriatric prescriptions were comparatively low. During this study, 19 physicians were encountered. Prescribers information [Table 1] represents prescriptions that were collected of each physician that was encountered during the study.
Table 1: Demographic details of current population

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Infectious diseases were noted to be higher in our study (28.9%) [Figure 1] The current study shows that, most common suspected diagnosis include infectious diseases (28.9%) with common symptoms of fever, cough, and dengue followed by endocrine problems (11.8%) with more prevalence of diabetes, gastrointestinal related (9.6%) which included common symptoms such as nausea, vomiting, diarrhea, constipation, cardiac related (9.2%) include hypertension, respiratory disorders (9.20%) with more prevalence of asthma and few others. A few skin-related disorders have also been noted (6.70%) and other suspected diagnosis during this study period include musculoskeletal, nephrorelated, autoimmune, hematological, ear, and eye related and oncology. [Table 2].
Figure 1: Suspected diagnoses

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Table 2: World Health Organization prescribing indicators obtained value and optimal value

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Route of administration

Most of the prescription comprises of oral route (96.3%). The most common prescribed dosage form were tablets (59.3%), followed by capsules (4.3%), syrups (13.2%), suspensions (5.5%), drops (4.2%), dry syrups (2.3%), creams (1.8%), powders (1.8%), ointment (1.5%), injections (1.5%), lotions (1.4%), sprays (1.1%), and inhalers (1.1%). Common frequency noted was, BID-1360 (55.40%), once daily (OD)-770 (31.30%), three times a day (TID) – 251 (10.20%), SOS-45 (1.80%), once a week-27 (1.10%), QID–4 (0.20%).

A total of 3058 drugs were prescribed in 1056 prescriptions. The number of drugs per encounter ranged from one to seven [Figure 2].
Figure 2: Number of drugs per prescription

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For World Health Organization indicators

Among the prescribing indicators, we found that the average number of drugs per prescription was 2.89 (SD ± 1.37). Only 23 (0.75%) were prescribed by generic name. Antibiotics and injections were prescribed with 399 (37.78%) and 29 (2.74%), respectively. Drugs that were prescribed from EDL were only 920 (30.08) [Table 3].
Table 3: Statistical analysis of World Health Organization indicators

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Statistical analysis was performed. Spearman's rank correlation test was used to assess age versus all five prescribing indicators [Table 3]. Mann–Whitney U test was performed to find correlation between gender and five prescribing indicators [Table 3]. Chi-square test was performed to find association between WHO indicators versus prescriber and WHO indicators versus site distribution [Table 4].
Table 4: Relationship between World Health Organization indicators versus prescriber and site distribution

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Defined daily dose

For DDD calculation, 678 prescriptions were only included in our study as 378 prescriptions were paediatric. From class of drugs, the antimicrobials (20.40%) was the highest, followed by the class vitamin and minerals (18.00%), antacids and PPI (10.20%), antipyretic (9.10%), antihistamine (8.40%), cardiovascular and hypertension (7.70%), mucolytic and expectorants (6.30%), antidiabetic (5.60%), others (3.90%), nonsteroidal anti-inflammatory drugs (3.20%), topical preparations (2.20%), corticosteroids (2.20%), analgesic (1.50%), and benzodiazepines (1.10%). Most prescriptions had antimicrobials and antibiotics were more frequently prescribed. Furthermore, DDD is calculated only for antibiotics, and therefore, DDD calculation of antibiotics was conducted [Table 5]. After calculating for DDD, azithromycin was noted to be high when compared with the WHO prescribed values.
Table 5: Define daily dose calculation of drugs

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  Discussion Top


Mean age of the patients was 21.85 (in years) and had both paediatric and adult population, whereas different studies conducted by Aravamuthan et al. 28.37 (in years)[15] and Parveen et al. 39.84 (in years)[16] showed almost near similarity, and others like, Mittal et al.,[17] Hussain et al.,[18] Ferreira et al.,[19] had comparatively more differences of 40.5, 41.12, 50.8 respectively. None of these were published during this pandemic period. Our study showed predominance of male patients (53.03%) and was similar to studies conducted by Mittal. et al. (50.2%)[17] Aravamuthan et al. (57.5%),[15] Hussain et al., (54.70%),[18] Pathak et al. (63.01%),[20] wherein female predominance was noted in Demoz et al. (60.6%),[21] and Parveen et al. (68.75%).[16] Most prescriptions consisted of oral route-1562, (96.70%), followed by topical-24, (1.50%) and parenteral routes-22, (1.40%), which is similar to the study conducted by Pathak et al.,[20] Hussain et al.[18] Most common prescribed dosage form was tablet (59.3%) followed by syrups (13.2%) and suspensions (5.5%). Common frequency was BID (Twice a day)-1360 (55.40%) followed by OD-770 (31.30%) and TID-251 (10.20%). When compared, OD was more commonly noted Mule et al.[22] It was observed that infectious diseases were most common (28.90%), followed by endocrine disorders (11.80%), gastrointestinal problems (9.60%), and cardiac problems (9.20%).

This is because of the possibility that infectious diseases are more prevalent in developing countries.[23] Others included respiratory diseases, skin-related problems, neurological disorders, musculoskeletal, nephro-related, and autoimmune diseases, hematological, ear and eye related, and oncology.

Prescribing indicators

No of drugs per encounter

The number of drugs per encounter was 2.89, higher than the WHO-recommended ideal value (<2). Average number of drugs prescribed was considered as an index for polypharmacy, and thus, our study showed clearly that prescribing practises adopted need to be changed in order to reduce the degree of polypharmacy, as such prescribing behaviour could lead to various negative consequences on patients. Aravamuthan et al. (3.7),[15] Mittal et al. (3.6),[17] Hussain et al. (2.91),[18] Ferreira et al. (2.2),[19] Chijoke-Nwauche et al. (3.4),[24] Ragam et al. (3.3),[25] Shrestha and Prajapati (3.2),[26] Vooss and Diefenthaeler (2.03),[27] all observed increased values than the recommended range. In comparison to other studies, Amaha et al. (1.76)[28] showed only a subtle difference. This variation in number of medicines prescribed per patient may be due to the differences in the study setting and prescribing practices among various medical specialist.[25] Polypharmacy also might be due need for patients requiring more than one medication to control multiple medical problems resulting in polypharmacy prescribing behavior.

Drugs prescribed with generics

Prescribing by generic name permits dispensers to dispense substitute therapeutic equivalence when one particular brand is not available. In our study, the percentage of drugs prescribed by generic name was 0.75%, which is very low in comparison to the expected value (100%). Other areas with low generic prescribing would Aravamuthan et al. (8%)[15] Mittal et al. (21.5%),[17] Hussain et al. (10.05%),[18] and Chijoke-Nwauche et al. (35.5%),[24] Ragam et al. (1.53%),[25] Shrestha and Prajapati (2.9%)[26] conversely, Ferreira et al. (86.1%),[19] Vooss and Diefenthaeler (72.8%),[27] Pathak et al. (89.99%),[20] Amaha et al. (83.14%)[28] showed a high percentage. Possible reasons for low presentation by generic names could be due to continuous communication with the physicians by pharmaceutical companies which increased the likelihood of using nongeneric (brand) names rather than generic names. Prescription of drugs by generic name is beneficial to decrease cost of drug therapy.[29]

Drugs prescribed with antibiotics

Antibiotic prescription was found to be 37.7% in our study which was almost similar to Chijoke-Nwauche et al. (32.7%)[24] and Shrestha and Prajapati (37.9%).[27] This is due to increased prevalence of infectious diseases. Few other areas that reported higher antibiotic use include Aravamuthan et al. (58.8%),[15] Mittal et al., (66.7%)[17] and Amaha et al. (53.0%)[28] than the optimal range (<30%). Other areas had less antibiotics prescribed which include Hussain et al. (19.70%,)[18] Ferreira et al. (13.1%),[19] Vooss and Diefenthaeler (21.7%),[27] Pathak et al. (24.27%),[20] and Ragam et al. (19.44%).[25] Increased prevalence of infectious diseases in developing countries results in an increased amount of antibiotics being prescribed. Second, it may be due to the high level of routine empirical treatments seen in resource-poor countries. Third, could be patient pressure on prescribers.[28] Therefore, this reflects that higher use of antibiotics may be due to increase in infectious diseases with maximum antibiotics prescribed.

Drugs prescribed with injectables

The percentage of injectables prescribed in this study was 2.74% and is below the WHO standard of 20%, It is nearly equivalent to other studies in Chijoke-Nwauche et al. (1.4%),[24] Ferreira et al. (2.5%),[19] Hussain et al. (2.20%),[18] Vooss and Diefenthaeler (2.4%),[27] Ragam et al. (8.33%),[25] Amaha et al. (7.80),[28] Shrestha and Prajapati (0.7%).[26] Many studies reported higher percentage of injectables per encounter than expected like Aravamuthan et al. (26.8%),[15] Mittal et al. (80.1%),[17] Pathak et al. (24.05%).[20] These differences may be due to comparisons with hospital-based studies rather than CP which could account for the increased percentage of injections being prescribed.

Drugs prescribed from essential drugs list

Low levels of drugs were prescribed from the formulary (30.8%). Similar low prescribing was noted in Shrestha and Prajapati (21.3%).[26] Surprisingly, high levels were noted in as mentioned in Aravamuthan et al.[15] and the reason why this was addressed is the community pharmacist there, ensured that generic equivalence, whether it is bio-equivalent or not, is substituted for what is prescribed by the physician. Therefore, availability of drugs from their formulary was 100%. Few others that had high values include Vooss and Diefenthaeler (80.3%)[27] Pathak et al. (76.06%),[20] Amaha et al. (98.39%).[28] Other regions with a relatively higher rate include Mittal et al. (78.4%),[17] Chijoke-Nwauche et al. (61.3%),[24] and Ferreira et al. (73.7%).[19] Prescribing drugs from EDL issued by WHO provides a framework for rational prescribing, drugs on the list are well-established drugs, already tested in practice, with established clinical use and lower cost than newer drugs.[30] In general, no subtle differences were observed in values on WHO prescribing indicators before and during the COVID pandemic period.

According to Imtiaz and Hafeez's study[31] conducted in Pakistan, age versus antibiotic dispensing and gender versus antibiotic dispensing had shown statistically significant association, whereas in our study, gender had shown significant association with all the WHO indicators. Furthermore, significant association was observed between prescriber versus drugs per encounter, prescriber versus injections prescribed, prescriber versus antibiotics prescribed and prescriber versus drugs prescribed from EDL, while significant association was observed between site versus drugs per encounter, site versus antibiotics prescribed and site versus drugs prescribed from EDL which was similar to the article by Mule et al.[22]

Defined daily dose

Out of 1056 prescriptions collected from three pharmacies, 378 prescriptions were excluded as those were paediatric patients. 678 prescriptions were analyzed and study showed that DDD did not correspond to the WHO-defined DDD for many drugs. In general, DDDs are based on use in adults. From, the class of drugs, antimicrobials (20.40%) were highest, followed by vitamin and minerals (18.00%), antacids and PPI (10.20%) which was similar to the study by Mittal et al.[17] Usually, DDDs are assigned only to antibiotic class and therefore antimicrobials were taken to calculate drug consumption. The reason for antibiotic usage in our study was respiratory tract infections (upper and lower respiratory tract infections). Such reasons could be the cause of rising incidences of antibiotic resistance in our country. Hence, the diagnosis of the patients was the core factor which influences the prescribing pattern of drugs. The total class of antimicrobial agents prescribed (ATC group J01) was 13. Cefpodoxime was most frequently prescribed and highest DDD noted was of Azithromycin. Infectious diseases are more prevalent in developing countries even during the COVID-19 pandemic period.[32] Therefore, more antibiotic use is justifiable. Antibiotic use is being increasingly recognized as the main pressure driving resistance to antibiotics. Validated antibiotic use data are needed to identify heavy use areas and provide feedback to prescribers, to study the relationship between antibiotic use and resistance and to design and evaluate interventions and decide which intervention is likely to prove successful in a particular setting. There are existing prescribing standards at national level. Medical Council of India (MCI) provides little guidance on prescribing pattern in India.[33] As per clause 1.5 of MCI professional regulation 2002 “Use of generic names of drugs: Every physician should as far as possibly prescribe drugs with generic names and shall ensure that there is rational use of drugs.”[29]

Our study had strengths as well as limitations. Less number of studies are published on CP-based assessment of prescribing patterns and therefore is one of the main strengths in our study. 19 prescribers were included from 3 pharmacies. Our study limitations are data were gathered only for 6 months, which might exclude prescriptions for specific seasonal diseases. Furthermore, it was a CP-based study and confirmed diagnoses were not mentioned in many prescriptions. Usually, DDD is calculated using 3 methods, DDDs per 1000 inhabitants per day/DDDs per 100 bed-days/DDDs per inhabitant per year. Calculation of DDD was not in accordance with the formula described by the WHO as the data were collected based on OPD prescriptions from pharmacies. Out of 1056 prescriptions, DDD is calculated only for adult population.

  Conclusions Top

Among five WHO indicators, only the percentage of encounters with an injection was in compliance with the WHO recommended value. Further measures are required for prescriptions to be better adhered to the guidelines. Adoption of better strategy would improve prescribing practises by physicians and there should be more regulations implemented, to change the prescribing attitudes by physicians through requesting them to prescribe generic than brand names. Furthermore, physicians should be urged not to prescribe medications that might raise the incidence of polypharmacy without offering extra benefits to patient condition. Overall, this study highlights the equal importance of CP-based studies along with hospital-based studies. Further research may help community pharmacists to expand their roles in drug utilization studies.

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Conflicts of interest

There are no conflicts of interest.

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  [Figure 1], [Figure 2]

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]


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