SARS-CoV-2 is a virus first reported in Wuhan, China, in December 2019 and later declared a pandemic by the World Health Organization (WHO) on 11 March 20201. Specific comorbidities, such as diabetes, hypertension, asthma, and others associated with COVID-19, have been associated with increased mortality2. The unforeseen eruption of COVID-19, patient overflow, insufficient protective equipment, increased workload, stressful situations, and other factors may contribute to prescription error3. This results in misinformation being the cause of life-threatening situations, particularly for patients with underlying comorbidities suffering from COVID-19.

However, errors in prescriptions can be avoided. It has been reported that medication errors account for 70% of all written prescriptions4. Superscription, inscription, and subscription are the major prescription errors. Drug-drug interaction (DDI), toxicity, adverse drug reactions, and economic waste are the consequences of such prescription errors5. Polypharmacy is the main cause of DDIs and the majority of adverse drug reactions6. A prescription can contain DDI of major, moderate, and minor severity as well as in combination, which can give rise to a life-threatening condition7. According to a report, polypharmacy accounts for 5.33% medication use in Bangladesh8.

SARS-CoV-2 leads to circulation disruption in different organs, forging vulnerability in comorbid patients9. Transmission of SARS-CoV-2 is enabled by prolonged contact time and in connection with an infected individual in an poorly ventilated environment10. Living in a densely populated country like Bangladesh, people are more likely to become infected with COVID-19, as population density has been identified as a societal risk factor for SARS-CoV-2 transmission11. Although polypharmacy and DDIs are major drawbacks in patient care in Bangladesh, it has been a success story to vaccinate people against COVID-19 infections. The country obtained the 5th position in the world in the COVID-19 Recovery Index12.

Earlier studies have indicated that COVID-19 patients with comorbidities should be closely monitored as they are more vulnerable. Patients with comorbidity and those who were older encountered severe forms of COVID-19, such as patients with underlying diabetes who were found to be hospitalized more than non-diabetic patients suffering from COVID-19. Higher morbidity and mortality had also been observed in those comorbid patients13. Likewise, patients with hypertension or any respiratory disease had also sustained severe forms of COVID-1914,15. Elderly patients with underlying comorbidities are classified as vulnerable to COVID-19 as they are at greater risk of suffering adverse outcomes while being administered numerous drugs as part of their clinical management. Prescription errors can lead to further catastrophic outcomes for this group of patients. Such errors can adversely affect patients’ safety and the quality of the healthcare system. To counteract this outcome, priority should be given to ensuring the prescription is written correctly by trained and skilled health professionals, thereby minimizing adverse drug effects, polypharmacy, and, most importantly, DDI.

In December 2020, the development and implementation of the COVID vaccine by the pharmaceutical industry came into use during this time of global emergency. The outcome of which has shown evident success in the prevention and transmission of the disease. Countries with low uptake of vaccination coverage are at a higher risk of transmission, leading to adverse outcomes in patients with comorbidities.

There is no doubt that polypharmacy and prescription errors can damage patients’ safety profiles. There may be an increased risk of higher morbidity and mortality in COVID-19 infected patients. So, it is essential to evaluate the prescriptions with the aim of increasing patient safety through drug use management. Therefore, the present study was designed to evaluate prescription errors by looking at the types of drug-drug interactions comparing comorbid and non-comorbid COVID-19 infected patients.


Study design

This study was carried out at the outpatient departments of different hospitals in Dhaka, Bangladesh, from May to August 2021. Both male and female patients suffering from COVID-19 with and without comorbidities were included in this study. The study’s objectives were explained to the participants, and consent was obtained before collecting the prescription information. Confidentiality was maintained regarding sensitive personal information. There was no direct contact with patients, and information was gathered through the review of prescription scripts. Data were collected from participants who gave informed consent for the purposes of the study.

Data collection

A total of 80 prescriptions were randomly collected from the outpatient departments of different hospitals (Table 1).

Table 1

Prescription collection from different hospitals of Dhaka, Bangladesh, May to August 2021

HospitalNumber of prescriptions
Kurmitola General Hospital39
Labaid Specialized Hospital5
Square Hospital1
Holy Family Red Crescent Medical College Hospital1
Popular Medical College Hospital26
Mugda Medical College Hospital1
National Heart Foundation1
TMSS Medical College and Hospital1
Popular Diagnostic Centre2
BGC Trust Medical College2
South Apollo Diagnostic Complex Private Limited1

Data analysis

The information from the prescription scripts was collected by taking explicit images of the scripts. The data retrieved from the prescription scripts were presented in a Microsoft Excel spreadsheet. After a complete list of medicines was compiled, the drug-drug interaction (DDI) was checked using an online drug information system, Drug Interaction Checker ( Drugs from each prescription were categorized by their generic names. Each drug prescribed on the prescription script was checked for DDI. The results obtained were ranked based on mild, moderate, and significant DDIs. Further preference was given to the major DDIs. A list of major generic pairs of drugs that were interacting was identified. Moreover, those interactions were evaluated in terms of their frequency of prescription. Following the subcategories, the prescription error was measured in terms of superscription, inscription, and subscription error. The research method was aligned with the Declaration of Helsinki.


A total of 773 drugs were found in 80 prescriptions. So, the number of medications encountered was 9.66 in each prescription. None of the patients was vaccinated against COVID-19.

Table 2 shows that 67.5% of prescriptions contain 6–10 medications per prescription; 11–15 medications per prescription were found in 23.8% of prescriptions; and 5% of prescriptions contained 16–20 medications per prescription. Only 2.5% of prescriptions had drugs ≤5, and 1.2% of prescriptions contained ≥21 medications.

Table 2

Number of drugs prescribed in prescriptions among COVID-19 patients, May to August 2021 (N=80)

Numbers of drugs per prescriptionNumber of prescriptions%

Table 3 depicts cases of prescription errors, so one prescription may contain multiple cases or multiple prescription errors. From Table 3, superscription error was noticed in 11 cases for comorbid patients and 4 cases for non-comorbid patients. The prescription date was not mentioned in the prescriptions of 10 comorbid cases (12.5%). Overall, inscription errors were found in 76 cases out of 80 prescriptions, 47 cases out of 36 for non-comorbid, and 29 cases out of 44 prescriptions for comorbid. Dosage was not found in 9 prescriptions for comorbid instances (20.46%) and 28 non-comorbid cases (7.77%). The wrong strength of medicine was prescribed in 7.5% of prescriptions for comorbid patients. In 2 (4.54%) and 7 (8.8%) prescriptions for comorbid and non-comorbid cases, the improper dosage form was mentioned, respectively. Subscription errors were found in 35 cases for comorbid patients and 10 instances for non-comorbid patients.

Table 3

Prescription errors in the studied population of COVID-19 patients, Dhaka, Bangladesh, 2021 (N=80)

Prescription errorTypes of errorsComorbid patients (N=44) n (%)Non-comorbid patients (N=36) n (%)Both groups (N=80) n (%)
SuperscriptionAge not mentioned1 (2.28)0 (0)1 (1.25)
Gender not mentioned0 (0)4 (11.11)4 (5.00)
Prescription date not mentioned10 (22.72)0 (0)10 (12.50)
InscriptionDosage not mentioned9 (20.46)28 (77.77)37 (46.25)
Dosage form not mentioned0 (0)0 (0)0 (0)
Wrong strength6 (13.63)0 (0)6 (7.50)
Spelling mistake in drug name2 (4.54)3 (8.33)5 (6.25)
Wrong dosage form2 (4.54)5 (13.88)7 (8.80)
Patient history/symptoms not mentioned10 (22.72)11 (30.55)21 (26.00)
SubscriptionPrescriber date not mentioned28 (63.63)10 (27.77)38 (47.50)
Prescriber signature not mentioned7 (15.90)0 (0)7 (8.80)

Table 4 depicts cases of drug-drug interaction (DDI), so one prescription may contain multiple DDI occurrences. The major DDIs were found in 6 cases out of 44 prescriptions of comorbid patients and in 1 case out of 36 cases of non-comorbid patients (Table 4). Moderate DDIs were found in 39 cases out of 44 prescriptions for comorbid patients and 5 cases out of 36 prescriptions for non-comorbid patients (Table 4).

Table 4

Major, minor, and moderate drug-drug interaction cases among the comorbid patients and non-comorbid patients with COVID-19, Dhaka, Bangladesh, 2021 (N=80)

Responsible drug-pair for drug-drug interactionSeverity of interactionComorbid patients (N=44) n (%)Non-comorbid patients (N=36) n (%)
Palonosetron – HaloperidolMajor1 (2.72)0 (0)
Moxifloxacin – DexamethasoneMajor2 (4.54)1 (2.78)
Insulin Human – MoxifloxacinMajor1 (2.72)0 (0)
Ciprofloxacin – Methyl PrednisoloneMajor1 (2.72)0 (0)
Voriconazole – MoxifloxacinMajor1 (2.72)0 (0)
Amlodipine – RosuvastatinMinor1 (2.72)0 (0)
Rosuvastatin – MoxifloxacinMinor1 (2.72)0 (0)
Salbutamol – BudesonideMinor2 (4.54)0 (0)
Bisoprolol Hemifumerate – Levothyroxine sodiumMinor1 (2.72)0 (0)
Dexamethasone – DiazepamMinor1 (2.72)0 (0)
Clarithromycin – LinagliptinModerate1 (2.72)0 (0)
Insulin Human – LinagliptinModerate1 (2.72)0 (0)
Losartan potassium – Cefixime TrihydrateModerate1 (2.72)0 (0)
Haloperidol – Procyclidine HClModerate1 (2.72)0 (0)
Ivabradine – DexamethasoneModerate1 (2.72)0 (0)
Moxifloxacin - RemdesivirModerate7 (15.90)3 (8.33)
Clarithromycin – RivaroxabanModerate1 (2.72)0 (0)
Dexamethasone – Prazosin HClModerate1 (2.72)0 (0)
Clopidogrel – Atorvastatin CalciumModerate3 (6.81)0 (0)
Atorvastatin – EsomeprazoleModerate1 (2.72)0 (0)
Solifenacin – NystatinModerate1 (2.72)0 (0)
Ceftriaxone – MoxifloxacinModerate1 (2.72)2 (5.56)
Paracetamol – RemdesivirModerate1 (2.72)0 (0)
Insulin Human – Dexamethasone sodium phosphateModerate4 (9.09)0 (0)
Dexamethasone sodium phosphate – GlycerinModerate2 (4.54)0 (0)
Clarithromycin – Insulin GlargineModerate1 (2.72)0 (0)
Nebivolol HCl – InsulinModerate1 (2.72)0 (0)
Insulin NPH – Clopidogrel bisulphateModerate1 (2.72)0 (0)
Amlodipine – AtenololModerate1 (2.72)0 (0)
Bisoprolol Hemifumarate –RisperidoneModerate1 (2.72)0 (0)
Piperacillin – AmikacinModerate1 (2.72)0 (0)
Mirtazapine – ClonazepamModerate1 (2.72)0 (0)
Formoterol – SalbutamolModerate1 (2.72)0 (0)
Ondansetron – PalonosetronModerate1 (2.72)0 (0)
Oxcarbazepine – Quetiapine FumarateModerate1 (2.72)0 (0)
Gabapentin – OxcarbazepineModerate1 (2.72)0 (0)
Bisoprolol Hemifumarate – FurosemideModerate1 (2.72)0 (0)


In this study, moderate drug-drug interaction (DDI) was observed in 44 cases among the 80 prescriptions collected, indicating a higher risk of developing adverse outcomes as a result of prescription error in the studied population. This study showed a high incidence of drug-drug interactions (of any type), with 71.25% of cases affected. The study found a high frequency of moderate DDI in Moxifloxacin and Remdesivir when used in combination. There were 7 cases for comorbid patients and 3 cases for non-comorbid patients. Among the major DDIs, high numbers were seen with the Moxifloxacin and Dexamethasone combination, with 2 cases for comorbid patients and 1 case for non-comorbid patients. Polypharmacy was observed in 78 prescriptions (97.50% cases), which contained a total drug number of more than 6 per prescription. A total of 136 cases of prescription errors were found among 80 prescriptions, of which 15 were superscription errors, 45 were subscription errors, and the remaining 76 were inscription errors.

According to the prescribing indicator of the WHO, the leading health organization throughout the globe, the optimum number of drugs per encounter was directed at 1.6–1.8. In contrast, in this study, only 2 prescriptions (2.5%) were found to have the number of drugs prescribed below 5; the remaining 78 prescriptions (97.5%) were found to have a drug number greater than 5, indicating a substantial deviation from the standard guideline16. Earlier studies reported that inflated drug numbers prompted outpatient visits, elevated hospitalization rates, and an increase in medical costs17. A previous study on outpatients outlined that patients administering more than five medications concurrently had a 50% higher probability of an adverse drug reaction18. Moreover, patients taking more than five medications reported a diminishing ability to implement instrumental activities of daily living19. In 54% of patients prescribed more than 10 medications, cognitive impairment was observed20. A study on the eastern Indian population revealed that 87.5% of COVID-19 prescriptions contain drug-drug interactions, of which 20% are major drug-drug interactions and 77.14% are moderate drug-drug interactions21. We have also found different categories of DDIs in our study.

The drug-drug interaction may influence pharmacodynamic and pharmacokinetic effects. Simultaneous administration of medications can have a synergistic effect, which has a more significant impact than a summation of the administered drugs, and an additive effect, which is the sum of the co-administered drugs’ influence. Pharmacokinetic interaction can alter the concentration of the co-administered drugs by interfering with pharmacokinetic parameters such as absorption, distribution, metabolism, and elimination. Several drugs commonly prescribed for COVID-19 patients, such as antiplatelet and anticoagulant combinations, were reported earlier to have toxicological consequences by increasing the risk of bleeding22. Patients’ prescription errors can lead to fatal situations, especially for the comorbid population. A previous study conducted in the emergency outpatient department indicated that 54% of all medication errors were associated with prescription errors23.

The communication gap between the prescribers and the patients and unethical medical product promotion were responsible for prescription error24. The prescription error was reported to be the reason for the economic burden for the patients; being a lower middle-income country, this incidence is much more fierce for the Bangladeshi population25. Polypharmacy; patients with comorbidity, primarily older people, requiring new medications for treatment of COVID-19 will have increased issues that will arise from this situation. This group of the population is at high risk of suffering from adverse effects due to prescription errors26. In our study, we found many medications in one prescription, which may lead to DDIs, thereby increasing the risk of vulnerability among COVID-19 patients. It has been reported that more than 250 million doses of COVID-19 vaccines have been administered in Bangladesh until May 202227. That can have a positive impact on future episodes of COVID-19 infections in terms of DDIs.

Prescription error is an avoidable occurrence and may be eradicated by awareness, aiding tools, and some preventive measures. A study reported that more than 60% of prescription-related mistakes could be avoided by employing computer software28. Moreover, clinical pharmacists and hospital pharmacists may play a crucial role in reducing prescription error-related adverse effects. This is lacking in Bangladesh, as graduate pharmacists have little scope to work in clinical or hospital settings.


The limitations of this study include a small sample size due to the urgency of the situation and certain restrictions during sample collection.


Prescription error is a global problem, but its consequences may have led to fatalities during the pandemic. Compliance with prescribed medications ensures a successful treatment outcome, provided the prescription is free of error. Policymakers in the health sector and experts need to emphasize the issue of prescription errors to secure adequate health safety for patients. Strict rules and regulations should be implemented by policymakers and those in power to reduce prescription error.