Int J Pharm Pharm Sci, Vol 16, Issue 5, 72-79Original Article

EVALUATION OF PRESCRIBING PATTERN IN ORTHOPEDICS DEPARTMENT IN A TERTIARY CARE HOSPITAL: A PROSPECTIVE OBSERVATIONAL STUDY

DWIPEN KHANIKAR1, KAMAL OJAH1, LAKHIMI BORAH2, MITRA BHATTACHARYYA2*, PRAN PRATIM SAIKIA1, SIDDHARTHA SHANKAR PATOWARY1, DIPTIMAYEE DEVI1

1Department of Pharmacology, Gauhati Medical College and Hospital, Guwahati, Assam, India. 2Department of Pharmacology, Nalbari Medical College and Hospital, Nalbari, Assam, India
*Corresponding author: Mitra Bhattacharyya; *Email: mitrabhattacharyya06@gmail.com

Received: 10 Feb 2024, Revised and Accepted: 28 Mar 2024


ABSTRAC

Objective: To study the demographic profile and prescription pattern in Orthopedics department in a tertiary care hospital.

Methods: A prospective, observational and cross-sectional study design was adopted for this study. A total of 144 patients were enrolled and their prescriptions were analyzed for three months. The data was analyzed by using a Microsoft Excel Worksheet. The Anatomical Therapeutic Chemical classification system and defined daily dose were used to classify the prescribed drugs.

Results: Out of 144 patients enrolled, 105 (72.92%) were male and 39 (27.08%) were female. Maximum patients were between 21-40 y of age. The mean age of the patients was 35.04±18.53. The average number of drugs per prescription was 4.84. Fracture of limbs (58.33%) was the most common diagnosis. Analgesics were the most commonly prescribed drugs. Diabetes was the most common comorbidity. The percentage of drugs prescribed by generic names was 48.06, and that from the essential drug list was 47.78. The percentage of fixed-dose combinations used was 28.55.

Conclusion: Although we found that a good percentage of drugs were prescribed from essential drug list but, this practice has to be increased in future. It is also seen that average number of drugs per prescription was high and percentage of drugs prescribed by generic names was less than that by brand names. So, there is immense scope of improvement for prescribing in the hospital.

Keywords: Orthopedics, Essential drug list, Generic name, Anatomical therapeutic chemical classification system, Defined daily dose, Fixed dose combinations


INTRODUCTION

Prescription writing is an art. It is the direction the prescriber gives to both pharmacist and patient for the proper use of drugs [1]. Thus, a prescription reflects the physician’s perspective towards the particular disease and the role of the medication in its treatment. It also provides an understanding of the essence of the healthcare delivery system [2].

Monitoring of prescriptions and drug utilization studies help in examining the recent trend of prescription patterns which helps in identifying the problems and providing feedback to prescribers. Thereby, awareness can be created about the irrational use of drugs. It is an inevitable need to investigate thoroughly the factors affecting the prescribing patterns of the doctor to improve the prescription quality and promote rational prescription patterns [3].

World Health Organization (WHO) definition of rational prescription is ‘‘Rational use of medicines requires that patients receive medications appropriate to their clinical needs, in doses that meet their own individual requirements, for an adequate period of time, and at lowest cost to them and their community.’’ [4].

WHO developed a set of core drug-use indicators that include the average number of medications per prescription, percentage of antibiotics, percentage of generics and brands, percentage of injections and percentage of drugs prescribed from an essential medicine list [5].

Drug utilization studies are mainly of two types: quantitative and qualitative [6]. WHO defined drug utilisation as the marketing, distribution, prescribing, dispensing and administration of medication, with consideration of its use economic burden [5]. International agencies such as the WHO and International Network of Rational Utilization of Drugs have deciphered the importance of drug utilization studies in the promotion of rational drug use and their application have helped them to evolve standard drug use indicators and data collection methods [7].

Defined Daily Dose (DDD) is an important tool to compare drug utilization among different clinical setups within a country and between different countries. DDD/100 bed-days provides a rough estimate of drug consumption in hospital inpatients and it is a fixed unit of measurement independent of formulation and price [8, 9].

Physicians in their day-to-day practice, prescribe a greater number of fixed-dose combinations (FDCs) [10]. Unfortunately, most of them are irrational and harmful. It is crucial that principles of rational prescription are adhered to and an important step toward this is by prescribing drugs only published in the WHO Essential Medicines List (EML) or National List of Essential Medicines (NLEM).

The prescribing pattern of drugs in the orthopedics field has to be regularly observed as many of the drugs prescribed have unwanted adverse effects. The objective of conducting a prescribing pattern study is to monitor, evaluate, and if necessary, suggest modifications in the prescribing behavior of medical practitioners to make medical care cost-effective and rational [11].

This study was undertaken as an attempt to know the disease pattern and also prescribing practices in the orthopedics in-patient department of the tertiary care hospital of Guwahati, Assam. Moreover, this study was also performed to evaluate whether the prescribed drugs were enlisted under the WHO Model List of Essential Medicines 2021 (22nd list) and prescribed by generic name.

MATERIALS AND METHODS

A prospective, observational and cross-sectional study design was adopted for this study. The data was collected from October to December 2022 at Orthopedics in-patient department of a tertiary care teaching hospital in Guwahati, Assam. Patients of all age groups, both male and female patients from the Orthopedics in-patient department with other comorbidities were included in the study. The patients were enrolled only after their prior consent. Patients from the outpatient department, those admitted to other in-patient department, patients who absconded or discharged against medical advice and pregnant women were excluded from the study. The Institutional Ethics Committee permission was taken to conduct this study (IEC approval no. MC/190/2007/Pt-II/JUN-2022/17).

The sample size of this study was 144 and the data from the prescription of the patient was noted in profile forms and entered in a Microsoft Excel Worksheet and descriptive statistics such as mean, frequency and percentage were calculated.

The Anatomical Therapeutic Chemical (ATC) classification system and defined daily dose (DDD) were used to classify the prescribed drugs. The ATC system divides the active substances into groups and subgroups, and the DDD is the assumed average maintenance dose per day for a drug when used for its main indication in adults. The DDD provides a fixed unit of measurement, independent from, e. g., strength and price, which enables research on patterns in the prescription of drugs [12].

RESULTS

In the present study, 144 patients were enrolled and their prescriptions were analyzed during 3 mo. We observed that there were 697 drugs prescribed and the average number of drugs per prescription was 4.84. Out of 144 patients enrolled, 105 (72.92%) were male and 39 (27.08%) were female (fig. 1). Demographic details revealed that the patients of age between 21-40 y were more (56 patients) followed by 41-60 y (41 patients), then 0-20 y (36 patients) and 61-80 y (11 patients) (table 1). This described the effect of age factor on disease distribution. The mean age of the patients was 35.04±18.53. The majority of the patients who were admitted in-patient ward of the Orthopedics Department had suffered from a fracture of limbs i.e. 84(58.33%), followed by 38(26.39%) patients with other orthopedic ailments,15(10.42%) patients with soft tissue injury, 4(2.78%) patients with osteomyelitis and 3(2.08%) patients with congenital anomalies (fig. 2). Analgesics were the most commonly prescribed drugs in the Orthopedics Department. There were 190 analgesics (27.26%), followed by 169 antibiotics (24.25%), 119 gastroprotective drugs (17.07%), 80 miscellaneous drugs (11.48%), 57 Calcium and Vitamin D (8.18%), 51vitamins (7.32%) and 31 antiemetics (4.45) (fig. 3).

Fig. 1: Gender distribution

Fig. 2: Major diagnosis

Fig. 3: Therapeutic categories of the prescribed drugs

Table 1: Age distribution

Age range (Years) Number of patients Percentage (%)
0-20 36 25
21-40 56 38.89
41-60 41 28.47
61-80 11 7.64

In table 2: ATC classification of 190 analgesics along with their individual WHO-assigned DDD (in mg), routes of administration and number of individual analgesics have been mentioned.

Table 2: Analgesics with ATC code, DDD (mg) and route of administration

Name ATC code DDD (mg) Adm. R Total (%)
Paracetamol N02BE01 3000

Oral

Parenteral

Rectal

55(28.95)
Diclofenac M01AB05 100

Oral

Parenteral

Rectal

30(15.79)
Aceclofenac M01AB16 200 Oral 6(3.16)
Ibuprofen M01AE01 1200

Oral

Parenteral

Rectal

13(6.84)
Ketorolac M01AB15 30

Oral

Parenteral

8(4.21)
Indomethacin M01AB01 100

Oral

Parenteral

Rectal

3(1.58)
Etoricoxib M01AH05 60 Oral 2(1.05)
Aceclofenac+Paracetamol M01AX

200

3000

Oral 59(31.05)
Aceclofenac+Serratiopeptidase+Paracetamol M01AX

200

0.9

3000

Oral 2(1.05)
Aceclofenac+Serratiopeptidase M01AX

200

0.9

Oral 1(0.53)
Paracetamol+Diclofenac N02BE51

3000

100

Oral 1(0.53)
Paracetamol+Etoricoxib N02BE51

3000

60

Oral 1(0.53)
Paracetamol+Ibuprofen N02BE51

3000

1200

Oral 5(2.63)
Tramadol+Acetaminophen N02AJ15

300

6000

Oral 3(1.58)
Etodolac+Thiocolchicoside M03BX 400, Not assigned Oral 1(0.53)

In table 3, ATC classification of 169 antibiotics along with their individual WHO-assigned DDD (in mg), routes of administration and number of individual antibiotics have been mentioned.

Table 3: Antibiotics with ATC code, DDD (mg) and route of administration

Name ATC code DDD (mg) Adm. R Total (%)
Cefuroxime J01DC02

500

3000

Oral

Parenteral

8(4.73)
Amikacin J01GB06

1000

590

Parenteral

Inhale. Solution

49(28.99)
Ceftriaxone J01DD04 2000 Parenteral 64(37.87)
Metronidazole J01XD01 1500 Parenteral 14(8.28)
Linezolid J01XX08

1200

1200

Oral

Parenteral

3(1.78)
Vancomycin J01XA01 2000 Parenteral 1(0.59)
Meropenem J01DH02 3000 Parenteral 3(1.78)
Teicoplanin J01XA02 400 Parenteral 1(0.59)
Tigecycline J01AA12 100 Parenteral 1(0.59)
Fluconazole J02AC01

200

200

Oral

Parenteral

1(0.59)
Cefixime J01DD08 400 Oral 1(0.59)
Cefuroxime+Clavulanic acid J01DC50

500

3000

Oral

Parenteral

5(2.96)
Piperacillin+Tazobactum J01CR05 14000 Parenteral 15(8.88)
Ceftriaxone+Sulbactum J01DD63 2000 Parenteral 2(1.18)
Amoxicillin+Clavulanic acid J01CR02

1500

3000

Oral

Parenteral

1(0.59)

In table 4: ATC classification of 119 gastroprotective drugs along with their individual WHO-assigned DDD-Defined Daily Dose (in mg), routes of administration and number of individual gastroprotective drugs have been mentioned.

Table 4: Gastroprotective drugs with ATC code, DDD (mg) and route of administration

Name ATC code DDD (mg) Adm. R Total (%)
Pantoprazole A02BC02

40

40

Oral

Parenteral

100(84.03)
Esomeprazole A02BC05

30

30

Oral

Parenteral

1(0.84)
Rabeprazole A02BC04 20 Oral 12(10.08)
Lansoprazole A02BC03 30 Oral 1(0.84)
Rabeprazole+Domperidone A02BC54

20

30

Oral 2(1.68)
Pantoprazole+Domperidone A02BC54

40

30

Oral 1(0.84)
Esomeprazole+Domperidone A02BC54

30

30

Oral 2(1.68)

In table 5, ATC classification of 80 miscellaneous drugs along with their individual WHO-assigned DDD-Defined Daily Dose (in mg), routes of administration and number of individual miscellaneous drugs have been mentioned.

Table 5: Miscellaneous drugs with ATC code, DDD (mg) and route of administration

Name ATC code DDD (mg) Adm. R Total (%)
Tab Collagen Peptides type I, Sodium Hyaluronate, Chondroitin Sulfateand Vitamin C D11AX57 Not assigned Oral 1(1.25)
InjAminoacid B05BA01 Not assigned Parenteral 2(2.5)
Tab Trypsin and Bromelain M09AB52 Not assigned Oral 2(2.5)
Tab Trypsin, Bromelain andRutoside Trihydrate M09AB52 Not assigned Oral 38(47.5)
Tab Trypsin, Bromelain, Rutoside Trihydrate and Papain M09AB52 Not assigned Oral 10(12.5)
Tab Trypsin, Bromelain, Rutoside Trihydrate and Diclofenac M09AB52 Not assigned Oral 2(2.5)
Tab Trypsin D03BA01 Not assigned Oral 9(11.25)
Tab Trypsin-chymotrypsin M09AB52 Not assigned Oral 1(1.25)
Tab Anastrozole L02BG03 1 Oral 1(1.25)
Inj Adalimumab L04AB04 2.9 Parenteral 1(1.25)
Cap Thiocolchicoside M03BX05 Not assigned Oral 1(1.25)
Cap Calcitriol, Calcium carbonate, Vitamin K2-7, Methylcobalamin, L-Methyl Folate, Zinc Oxide and Magnesium A11CC20 Not assigned Oral 1(1.25)
Intravenous fat emulsion B05BA02 Not assigned Parenteral 1(1.25)
Tab Glutathione V03AB32 Not assigned Oral 1(1.25)
Fortified micronutrients A11AA01 Not assigned Oral 1(1.25)
Inj Tranexamic acid B02AA02 2000

Oral

Parenteral

1(1.25)
Inj Tetanus Toxoid J07AM01 Not assigned Parenteral 1(1.25)
Tab Isoxsuprine C04AA01 60

Oral

Parenteral

1(1.25)
Tab Clopidogrel B01AC04 75 Oral 1(1.25)
Tab Rifaximin A07AA11 600 Oral 1(1.25)
Syrup Di-sodium Hydrogen Citrate B05CB02 Not assigned Oral 1(1.25)
Inj Mannitol B05BC01 Not assigned Oral 1(1.25)
Tab Alprazolam N05BA12 1 Oral 1(1.25)

In table 6: ATC classification of 57 Vitamin D and Calcium drugs along with their individual WHO assigned DDD-Defined Daily Dose (in mg), routes of administration and number of individual Vitamin D and Calcium drugs have been mentioned.

Table 6: Vitamin D+Calcium with ATC code, DDD (mg) and route of administration

Name ATC code DDD (mg) Adm. R Total (%)
Calcitriol A11CC04 0.001

Oral

Parenteral

1(1.75)
Vit D3 A11CC05 0.02 Oral 3(5.26)
Calcium A12AA20 500 Oral 13(22.81)
Calcium+Vit D3 A12AX 500, 0.02 Oral 39(68.42)
Calcium+Calcitriol A12AX 500, 0.001 Oral 1(1.75)

In table 7, ATC classification of 51 Vitamins along with their individual WHO-assigned DDD (in mg), routes of administration and number of individual Vitamins have been mentioned.

Table 7: Vitamins ATC code, DDD (mg) and route of administration

Name ATC code DDD (mg) Adm. R Total (%)
Thiamine A11DA01 50 Oral, Parenteral 2(3.92)
Thiamine+Bentonite forte Not assigned Not assigned 1(1.96)
Methylcobalamin B03BA05

1.5

0.2

Oral

Parenteral

4(7.84)
Vitamin C A11GA01 200 Oral, Parenteral 41(80.39)
Multivitamin A11AB Not assigned 3(5.88)

In table 8, ATC classification of 31 antiemetics along with their individual WHO-assigned DDD-Defined Daily Dose (in mg), routes of administration and number of individual antiemetic drugs have been mentioned.

Table 8: Antiemetics with ATC code, DDD (mg) and route of administration

Name ATC code DDD (mg) Adm. R Total (%)
Ondansetron A04AA01 16

Oral

Parenteral

Rectal

31(100)

Out of 144 patients, along with the main diagnosis, comorbid conditions were also observed in 26 patients. To treat these comorbidities some other classes of drugs were prescribed. Of these 7 patients (26.92%) were prescribed with anti-diabetics, 4 patients (15.38%) with antianxiety, 4 patients (15.38%) with antiepileptics, 3 patients (11.54%) with antihypertensive, 3 patients (11.54%) with thyroid hormone, 2 patients (7.69%) with antipsychotic and 1 patient (3.85%) with central anticholinergic, 1 patient (3.85%) with aromatase inhibitor and 1 (3.85%) patient with gallstone dissolving drugs respectively (table 9).

Table 9: Distribution of drugs prescribed for associated comorbid conditions (N=26)

Other drugs Number of patients (%)
Antidiabetic 7(26.92%)
Antianxiety 4(15.38%)
Antiepileptic 4(15.38%)
Antihypertensive 3(11.54%)
Thyroid hormone 3(11.54%)
Antipsychotic 2(7.69%)
Central anticholinergic 1(3.85%)
Aromatase inhibitor 1(3.85%)
Gallstone dissolving drugs 1(3.85%)

The rationality of a prescription can be evaluated by the total number of drugs prescribed for a patient. The more the number of drugs prescribed, the more the development of resistance, adverse drug reactions and other drug-related problems. Indirectly it may affect the patient’s adherence towards treatment. However, according to the severity of the disease, multiple drugs are prescribed for the treatment [13]. In the present study, 45 patients (31.25%) were prescribed with 3-4number of drugs, followed by 31 patients (21.53%) with 1-2 drugs,30 patients (20.83%) with 5-6 drugs, 23 patients (15.97%) with 7-8 drugs and 15 patients (10.41%) with equal or more than 9 drugs (fig. 4).

Rationality of prescriptions was assessed using WHO core prescribing indicators, values of which are presented in table 10.

Fig. 4: Number of drugs per prescription with number of patients

Table 10: The WHO core prescribing indicators assessed for drug prescription

Prescribing indicators assessed Average/Percentage
Average number of drugs per encounter 4.84
Percentage of drugs prescribed by generic names 48.06
Percentage of encounters with antibiotics 24.25
Percentage of encounters with injections 43.90
Percentage of drugs from essential drug list 47.78

In this study out of 697 prescribed drugs, 391 drugs were given orally and 306 drugs were given parenterally as shown in fig. 5.

Fig. 5: Routes of administration

In this study, out of 697 prescribed drugs, 335 drugs were prescribed by their generic names and 362 drugs were prescribed by their brand names as shown in fig. 6.

The following table shows the number of fixed-dose combinations used in each category of drugs, along with their percentages (table 11). In our study, a total of 199 (28.55%) FDCs were used.

Fig. 6: Generic and brand drugs

Table 11: Fixed dose combination

Therapeutic categories of drugs Number of FDCs used Percentage
Analgesics 73 10.47
Antibiotics 23 3.30
Gastroprotective drugs 5 0.72
Calcium and vitamin D 40 5.74
Vitamins 4 0.57
Antiemetics and Miscellaneous drugs 54 7.75
Total 199 28.55

DISCUSSION

This study was carried out to know the prescribing pattern of drugs used in the Orthopedics In-patient Department of Gauhati Medical College and Hospital, Guwahati. During the period of study, sex-wise distribution of patients shows that male patients (105 out of 144) were found to be more than that of female patients (39). Male dominance was also found in Gupta et al. [14] study, where 315 male and 185 female patients were enrolled based on only non-steroidal anti-inflammatory drugs (NSAIDs) use. Again in our study, the number of patients was higher in the age group of 21-40 y i.e. 56, which is similar to Ingle et al. [15] study where the number of patients was also more i.e. 91 in the age group of 18-40 y. When we compared the average number of drugs (4.84) prescribed in our study was found to be more than several other studies i.e. 3.5 in Alshakka et al. [16], 1.33 in Das et al. [17] and 1.9 in Shankar et al. [18] study, at par (4.72) with Mishra R et al. [19] and less than (8.86) that of Baghel R et al. [20] study.

Analogous to our study, Choudhury et al. [21] study had also reported fracture as the most common diagnosis encountered in Orthopedics In-patient. NSAIDs were the most commonly prescribed drugs in our study, similar to Shehnaz et al. [22] study. Among the NSAIDs, paracetamol was the most prescribed NSAID, similar to that of Patil LV et al. [23] study. In the present study, we observed that gastroprotective agents Proton-pump inhibitors (PPIs) were co-administered with NSAIDs. The most commonly prescribed PPI was pantoprazole (84.03%) (table 4). The main reason for their use was NSAID-associated peptic ulcer and gastrointestinal bleeding [24]. In Rahman MS et al. study revealed that the proton pump inhibitors were used as the anti-ulcer agents of choice [25].

In our study, out of 144 patients, 26 of them also had other comorbidities and it was seen that Diabetes was the most common comorbidity just as Narne et al. [13] study. Again, when we compared the number of drugs per prescription given to patients, it was seen that in our study, a maximum of 45 patients were prescribed 3-4 drugs in contrast to Narne et al. [13] study, where 69 patients had 4-6 drugs.

The use of Fixed Dose Combinations (28.55%) was found to be much higher than that reported in the Shankar PR et al. (13.1%) study [18] but lower than that reported by Das et al. (36.25%) study [17]. Moreover, the use of parenteral preparations (43.90%) was found to be much higher than that reported in the Shankar PR et al. (8.6%) study [18] and Das et al. (17.4 %) study [17].

Most of the drug utilization studies have reported that the majority of the drugs were prescribed by brand names. Shankar PR et al. [18] study and Shankar PR et al. [26] study found 80.7% and 67.4% prescriptions in brand names, respectively, similar to our study (51.94%). Analogous to our study (48.06%), in Alam K et al. study (44%) too drugs were prescribed by generic names [27]. Generic drugs are usually inexpensive than brand drugs [22]. The percentage of drugs prescribed from the WHO essential drug list was 47.78% in contrast to Ingle et al. (51.05%) study [15].

LIMITATIONS

The limitations of our study were that the period of our study should have been longer so that we could have included more number of patients and analyzed their prescriptions to get better results and observations. We should have also included OPD patients to get the statistics about the average consultation and dispensing time of the drugs.

CONCLUSION

The study shows that a good percentage of drugs were prescribed from the essential drug list, but this practice has to be increased in future. Again, the average number of drugs per prescription was high, so the physicians must make the habit of reducing the number of drugs per prescription to avoid adverse drug reactions. Although a good number of drugs were prescribed by their generic names, it was less in comparison to that of brand drugs. Regular educational interventions at different levels further promote rational prescribing.

ACKNOWLEDGEMENT

We are thankful to authorities of Gauhati Medical College (GMC), Guwahati, for allowing us to carry out the study. We are also thankful to participants for their support to accomplish this study.

FUNDING

Nil

AUTHORS CONTRIBUTIONS

Conception/design-Dr Dwipen Khanikar, Dr Kamal Ojah, Dr Lakhimi Borah, Dr Mitra Bhattacharyya, Dr Pran Pratim Saikia, Dr Siddhartha Shankar Patowary, Dr Diptimayee Devi

Provision of study material-Dr Dwipen Khanikar, Dr Kamal Ojah, Dr Lakhimi Borah, Dr Mitra Bhattacharyya, Dr Pran Pratim Saikia, Dr Siddhartha Shankar Patowary, Dr Diptimayee Devi

Collection of data-Dr Dwipen Khanikar, Dr Kamal Ojah, Dr Lakhimi Borah, Dr Mitra Bhattacharyya, Dr Pran Pratim Saikia, Dr Siddhartha Shankar Patowary, Dr Diptimayee Devi

Data analysis and interpretation-Dr Dwipen Khanikar, Dr Kamal Ojah, Dr Lakhimi Borah, Dr Mitra Bhattacharyya, Dr Pran Pratim Saikia, Dr Siddhartha Shankar Patowary, Dr Diptimayee Devi

Manuscript writing-Dr Dwipen Khanikar, Dr Kamal Ojah, Dr Lakhimi Borah, Dr Mitra Bhattacharyya, Dr Pran Pratim Saikia, Dr Siddhartha Shankar Patowary, Dr Diptimayee Devi

Final approval of manuscript-Dr Dwipen Khanikar, Dr Kamal Ojah, Dr Lakhimi Borah, Dr Mitra Bhattacharyya, Dr Pran Pratim Saikia, Dr Siddhartha Shankar Patowary, Dr Diptimayee Devi

CONFLICT OF INTERESTS

Declared none

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