INTRODUCTION:

Drug interactions represent an important and widely under recognized source of medication errors¹. It is a vital issue to consider while prescribing drugs, as it alters the therapeutic effectiveness of drugs and also lead to occurrence of adverse drug reactions. Health care providers may not be aware of interactions with drugs they prescribe. Several health care professionals may prescribe medications for one patient. Aging patients have multiple health issues and take many medications. Drug interactions may not be identified as the cause of unexpected treatment results or side effects. Health care providers may not know about all medications and supplements their patients are taking².

Few studies have been done in Bangladesh related to drug interactions. A recent study among indoor cardiac patients in a specialised hospital in Bangladesh found almost 56% of the prescriptions had at least one drug-drug interactions³. Globally, other studies have found rates of potential DDI ranging from approximately 5.4% to 63%^4-8. Drug interactions are important in clinical practice and have been estimated to account for 6%-30% of all adverse drug reactions⁹. Research has shown that both doctors and pharmacists are often unable to recognise potential DDIs^10,11. It is likely that every physician and pharmacist cannot remember and understand all potential DDIs and therefore cannot take corrective actions accordingly. They may be more familiar with drugs used in their specialty but not with drugs used in other specialties¹². Physicians should be able to be aware of and detect drug interactions in order to prevent any adverse effects which may prove harmful for patients.

Knowledge and experience of physicians play an important role in detection of drug interactions. Heavy patient load, various drug promotions, polypharmacy are some factors that result in adverse effects related to drug interactions. In order to avoid drug interactions, physicians must improve rationalism of drug prescription by detecting drug interactions at the point of care, indoor and also in outdoor settings.

In some countries, online software programs are utilized as an additional tool for detecting drug interactions. WebMD interaction checker, RxList, Drug interaction tool (University of Maryland Medical Center), Epocrates, Medscape, Micromedex® Drug-Reax, Drug Interaction Facts®, Lexi-Interact®, and Pharmavista®, Doctors desktop are some of the electronic drug databases utilized in countries like USA, UK and India.

By manual review of drug regimens by pharmacists, without the use of utility (e.g.drug interaction reference and computer program), only 66% of DDIs in a 2‑drug regimen can be correctly identified and the proportion decreases substantially as the number of drugs increases¹³. Efforts to deploy and promote the use of PDA-based drug drug interaction software in a wide range of clinical settings have the potential to improve patient safety¹⁴.

Several countries have implemented the practice of using online interaction checkers and have been benefitted as well. If a similar software application is developed and utilized in Bangladesh, our physicians and researchers will also be able to limit the adverse events related to drug interactions. This will promote the healthcare standards of the nation.

The aim of this study is to determine the opinion of clinicians about using an automated online tool for instant detection of drug interactions.

MATERIAL AND METHODS:

Study design:

This descriptive type of prospective cross-sectional study was carried out among the general physicians and specialists involved in various hospitals in Dhaka from September to November 2017.

Data collection tool and technique:

A pre-designed and pre-tested questionnaire comprising of both closed and open ended questions was used. Participants were informed briefly about the procedure of completing the questionnaire and were assured about the confidentiality of all information. After taking informed consent, they voluntarily participated in the study. The questionnaire included three sections of total 21 questions, related to knowledge of drug interactions, attitude about detection of drug interactions using an online checker and experience of drug interactions in clinical practice. Only completed questionnaires were finally included in the study.

Data analysis:

Data were analysed using Microsoft Excel 2003 and results were expressed using descriptive statistics such as frequency and percentages. Some questions had multiple options, therefore, the sum of percentage is not always 100%.

Ethical considerations:

The study was conducted following the general principles (section 12 and 26) of WMA declaration of Helsinki¹⁵. The human subjects involved in this study did not use any harmful agents, nor any samples were collected from them. As the participants imparted information through a questionnaire, it was not required to take approval from the institutional ethics committee to conduct this survey based research.

RESULTS:

This study was conducted among 50 participants where 24(48%) of them could recall the correct definition of drug interaction. Most of them 26(52%) could not recall the correct definition. Among the total respondents, majority of them 30(60%) know that drug interaction are of two types. But 12(24%) know there is only pharmacodynamic type and 8(16%) know there is only pharmacokinetic type.

Majority of them 28(56%) were not sure whether drug interaction can produce adverse effects. Only 18(36%) know that it can produce adverse effects and the rest 4(8%) know it does not produce any adverse effects. Regarding the knowledge about common drug interactions in all specialities, most of them 23(46%) were not sure about the common drug interactions, followed by 17(34%) who stated that they know all of them and 10(20%) do not have knowledge about all (Table 1).

Table 1: Knowledge of participants about drug interaction (n=50)

Attributes

Frequency (%)

Types of drug interaction

Pharmacokinetic interaction

Pharmacodynamic interaction

Both

Total

8(16)

12(24)

30(60)

50(100)

Drug interactions can produce adverse effects

Yes

Not sure

Total

18(36)

4(8)

28(56)

50(100)

Know common drug interactions in all specialities

Yes

Not sure

Total

17(34)

10(20)

23(46)

50(100)

Figure 1 shows the response of participants’ knowledge about the patient category who are more prone to suffer from drug interactions. More than half of the respondents 28(56%), report that patients with polypharmacy suffer the most, followed by elderly and children, as revealed by 14(28%) and 12(24%), respectively. Others 4(8%) and 2(4%) state, patients taking less safe drugs and smokers suffer, respectively. As shown in figure 2, 30(60%) of the participants reported that steroids produce maximum drug interactions among all drug groups, followed by 24(48%) and 9(18%) who revealed antibiotics and beta blockers are also responsible. Some of them, 4(8%) and 3(6%) revealed that ACE inhibitors/ARBs and antiplatelet agents produce drug interactions, respectively. Only a few 1(2%) stated, other drugs include sedatives/antidepressants.

Fig. 1: Knowledge of participants regarding patient category prone to drug interactions

Fig. 2: Knowledge of participants related to drug groups causing drug interactions

We observed the knowledge of participants regarding various disease conditions where drug interactions are common and found half of them 25(50%) reported hypertension comprised of maximum drug interactions, 18(36%) said diabetes mellitus, followed by 15(30%), 10(20%) and 2(4%) who stated bronchial asthma, ischaemic heart disease and others (depression), respectively (Figure 3).

Fig. 3: Knowledge of participants about diseases with common drug interactions

Moreover, a maximum portion 37(74%) find searching information on drug interaction while prescribing is time consuming from various sources and 13(26%) do not think so. Figure 4 displays the opinion of participants about an online drug interaction checker where a majority of them 27(54%) think it will be a quick and easy access for drug interaction information. Only 23(46%) disagreed with the option. In addition, opinion regarding whether such a software application could help to prevent drug interactions revealed that 25(50%) of them think it can prevent so. Another 22(44%) were not sure whether it can help to prevent or not and a few 3(6%) stated it cannot prevent.

Fig. 4: Opinion about online drug interaction checker

Figure 5 and table 2 depict the respondents’ opinion related to drug information which is to be included in the online drug interaction checker. Most of them 29(58%) stated that generic name of drugs can be included. 19(38%) stated both trade name and generic name can be included and 2(4%) opted for trade name only. Common adverse effects, dose of drugs and type of drug interaction are suggested to be included in the online checker by 31(62%), 20(40%) and 19(38%), respectively. Furthermore, 16(32%), 13(26%) and 2(4%) opted for intensity of drug interaction, drug formulation and interaction with food/tobacco/other diseases, respectively.

Fig. 5: Type of drug name to be included in drug interaction checker

Table 2: Drug information to be included in drug interaction checker

Items	Frequency (%)
Type of drug interaction	19(38)
Dose of drug	20(40)
Drug formulations	13(26)
Intensity of drug interaction	16(32)
Common adverse effects	31(62)
Interactions with food/tobacco/disease conditions	2(4)

Moreover, outdoor patients will be benefitted most by the online checker as 29(58%) of the respondents stated, while 16(32%) of them think indoor patients will be benefitted and emergency cases were selected as the least choice by 5(10%) of them (Figure 6). Majority of the participants 27(54%) prefer the online checker to be presented in both English and Bangla language. Some of them 15(30%) prefer in English only and a few 8(16%) opted for Bangla only.

Fig. 6: Patient category to be benefitted by drug interaction checker

Table 3 displays the response of respondents related to practice with drug interaction. Half of them 25(50%) encounter drug interaction every six months, 23(46%) encounter once yearly and a few 2(4%) find monthly. Intensity of drug interaction found by maximum 31(62%) was moderate followed by 16(32%) stated severe intensity and 3(6%) stated mild. Most of the respondents 24(48%) sometimes give priority to drug interaction while prescribing, many of them 20(40%) give priority always but 6(12%) do not give priority at all. Regarding retrieval of drug interaction information while prescribing, majority of them 30(60%) depend on drug leaflets, followed by 22(44%) depend on drug reference books, some 17(34%) recall from previous knowledge and few 5(10%) obtain information from internet.

Furthermore, most of them 33(66%) sometimes check drug interaction information while prescribing, some 12(24%) always check and 5(10%) never check. Among the respondents, 27(54%) of them find the available information inadequate to avoid drug interaction, 21(42%) sometimes find it adequate and few 2(4%) find it adequate enough. Maximum respondents 42(84%) did not use any online drug interaction checker previously but a few 8(16%) have used a national online drug index named DIMS (Drug Information Management System) before.

Table 3: Response of participants related to practice with drug interaction

Items

Frequency (%)

Frequency of drug interaction related adverse effects

Monthly

Six monthly

Yearly

2(4)

25(50)

23(46)

Intensity of drug interaction

Mild

Moderate

Severe

3(6)

31(62)

16(32)

Priority given to drug interaction while prescribing

Yes

Sometimes

20(40)

6(12)

24(48)

Information source of drug interaction while prescribing

Previous knowledge

Drug reference books

Drug leaflets

Internet

17(34)

22(44)

30(60)

5(10)

Frequency of checking drug interaction information while prescribing

Always

Sometimes

Never

12(24)

33(66)

5(10)

Available information adequate to avoid drug interactions

Yes

Sometimes

2(4)

27(54)

21(42)

Used mobile application on drug interaction previously

Yes

8(16)

42(84)

DISCUSSION:

In this study, 52% of participants could not recall the correct definition and a majority of 60% had correct knowledge about the types of drug interaction. Many could not recall precisely maybe due to lack of recapitulation of previous knowledge spontaneously. Comparatively, Barot PA et al.¹⁶ evaluated the occurrence of drug interactions by using online Medscape drug interaction checker software where more than 95% patients encountered with drug interactions, of which 73% were of pharmacodynamic type and 24% were of pharmacokinetic type. Only 36% know drug interactions can produce adverse effects while maximum of 56% were not sure. Moreover, 66% were either unaware or not sure about the common interactions in all specialities. Lack of awareness about vital issues related to drug interactions may pose a threat to patient safety consequently. Among them 56% know patients with polypharmacy and 28% know elderly patients experience drug interactions more commonly. This is analogous to the study of Radosevic N. et al¹⁷, where age and number of drugs were significantly associated with potential drug interactions proving elderly patients and polypharmacy are risk factors for drug interactions. Besides, 60% participants stated steroids and 48% stated antibiotics as the most common drug groups which produce drug interactions. In addition, 50% reported hypertension and 36% reported diabetes mellitus as common diseases that comprised of drug interactions.

Most of the participants, 54% think it will be quick and easy to derive information about drug interactions from an online checker rather than from various other time consuming sources as thought by 74% of the participants. Research by Robert Barrons¹⁸ is in accordance with this study where several software applications were compared and found iFacts and Lexi-Interact software are user friendly for drug interaction queries. Fifty percent stated that a software application would be a feasible way to prevent drug interactions. Detecting drug interactions instantly while prescribing using an online checker, especially in multiple disease conditions, will be an accurate option to prescribe rationally. A research by Missiakos O et al.¹⁹ found all their participants suggested a reference look up tool to be included in the hospital electronic drug database as a strategy to identify and prevent drug-drug interactions. Robert L. Robinson and Martha S. Burk¹⁴ studied six databases and found them to be sensitive from 84% to 100% and specific from 68% to 95%. Furthermore, a maximum of 58% suggest generic names of drugs to be included in the application. Moreover, 62%, 40%, 38% propose common adverse effects, dose of drugs and type of drug interaction to be included respectively. This elaborate information maybe useful for all clinicians at the time of prescribing, especially for junior doctors. Roblek T. et al²⁰ found that by using electronic databases the detection of mechanism of action and onset of adverse effects alongwith its intensity is possible. Majority of the respondents 58% think outdoor patients will be benefitted the most from this application. 54% of participants suggest the online checker will be best if produced in both English and native Bangla language.

In this study, 50% of respondents find patients presenting with drug interaction related adverse effects every six months which is quite similar to the work of Getachew Moges²¹ where 70.7% of participants encountered cases with drug-drug interactions that caused adverse outcomes and 49.3% mostly encountered several times. A recent Bangladeshi study³ revealed a majority of 56% prescriptions comprised of atleast one drug-drug interactions. It maybe possible that manual evaluation of prescriptions may miss out any significant information. Comparatively, a software based Croatian research²² revealed 90.6% of elderly patients with arterial hypertension have atleast one potential, clinically significant drug-drug interaction. Our study found 62% of drug interactions were of moderate intensity. The respondents reported that 48% sometimes give priority to drug interactions while prescribing drugs. Patients will not receive effective therapeutic regimen if drug interaction is not given enough priority by healthcare providers. Missiakos O et al.¹⁹showed less than half of their participants thought of drug interactions before prescribing. In addition, 60% obtain information from drug leaflets, 44% from drug reference books and 34% from previous knowledge. These various sources may not comprise of adequate relevant information which can be time consuming to search for. Similar are the findings of Getachew Moges²¹ where the most common source of information was drug reference books being 44.3%. A Bangladeshi study²³ found more than half out of 150 package inserts did not comprise any information about drug interactions mainly including common drugs. 24% participants always need to check information of drug interactions when prescribing similar to Missiakos O et al.¹⁹ where less than half of the participants had moderate level of confidence regarding recognition of dangerous drug interactions. But most of them state the available information is not adequate, likewise in this work where 54% admit the same. This study also found that maximum participants 84% did not use a drug interaction checker application previously except a few who named DIMS (Drug Information Management System)_ a drug reference index was used, which is available as a mobile application.

CONCLUSION:

Online drug databases can reduce the time for information procurement, ease decision making while prescribing, improve prescribing potential and prevent drug related adverse events. Lack of confidence among doctors related to drug interactions in prescribing drugs may be outweighed, if computer based drug interaction checker can be implemented. Regularly updated drug databases can further enrich the knowledge of practising physicians and ensure patient safety.

Further research is required to be carried out among a large number of respondents nationwide to improvise the work.

ACKNOWLEDGEMENT:

The authors would like to thank all physicians and specialists who showed keen interest to participate in this survey despite of their busy schedule.

REFERENCES:

1 Sandson N. Drug-drug interaction: the silent epidemic. Psychiatric Services 2005; 56(1): 22-4.

2 Drugs interactions Fact Sheet 407 (2014). Available from: http://www.aidsinfonet.org/fact_sheets/view/407. (Accessed on 7/3/2017).

3 Uddin MB, Nipa N, Ahmed S, Haider B, Hasan SB, Yousuf A. Possibility of Drug-Drug Interaction through Prescription Analysis at the National Institute of Cardiovascular Disease (NICVD), Bangladesh. Peertechz J Clin Pharmacol Clin Pharmacokinet 2016; 2(1): 007-010.

4 Heininger-Rothbucher D, Bischinger S, Ulmer H, Pechlaner C, Speer G, Wiedermann CJ. Incidence and risk of potential adverse drug interactions in the emergency room. Resuscitation 2001; 49(3):283-8.

5 Janchawee B, Wongpoowarak W, Owatranporn T, Chongsuvivatwong V. Pharmacoepidemiologic study of potential drug interactions in outpatients of a university hospital in Thailand. J Clin Pharm Ther 2005; 30:13-20.

6 Cruciol-Souza JM, Thomson, JC. Prevalence of potential drug-drug interactions and its associated factors in a Brazilian teaching hospital. J Pharm Sci 2006; 9:427-33.

7 Glintborg B, Andersen SE, Dalhoff, K. Drug-drug interactions among recently hospitalised patients- frequent but mostly clinically insignificant. Eur J Clin Pharmacol 2005; 61:675-81.

8 Riechelmann RP, Zimmermann C, Chin SN, Wang L, Carroll AO, Zarinehbaf S, Krzyzanowska MK. Potential drug interactions in cancer patients receiving supportive care exclusively. J Pain Symptom Manage, 2008; 35:535-43.

9 Classen DC, Pestotnick SL, Evans RS, Burke JP. Computer surveillance of adverse drug events in hospital patients. JAMA 1991; 266:2847-51.

10 Glassman P, Simon B, Belperio P, Lanto A. Improving Recognition of Drug Interactions: Benefits and Barriers to Using Automated Drug Alerts. Medical Care 2002; 40(12):1161-71.

11 Ko Y, Malone D, Skrepnek G. Prescribers' knowledge of and sources of information for potential drug-drug interactions; a postal survey of US prescribers. Drug Safety 2008; 31:525-36.

12 Kheshti R, Aalipour M, Namazi S. A comparison of five common drug–drug interaction software programs regarding accuracy and comprehensiveness. J Res Pharm Pract 2016; 5:257-63.

13 Weideman RA, Bernstein IH, McKinney WP. Pharmacist recognition of potential drug interactions. Am J Health Syst Pharm 1999; 56:1524‑9.

14 Robert L. Robinson, Martha S. Burk. Southern Illinois University School of Medicine Springfield, Illinois. Letter to the editor. March 1, 2004. The American Journal of Medicine; Volume 116:357.

15 World Medical Association Declaration of Helsinki- Ethical Principles for Medical Research Involving Human Subject. Adopted by 18^th WMA General Assembly Helsinki, Finland, June 1964 and Amended by the 52nd WMA General Assembly, Edinburgh, Scotland, October 7; 2000. Available from: http://www.wma.net/e/ policy/b3.html. [Last cited on 2017 Aug 30].

16 Barot PA, Malhotra SD, Patel VJ. Evaluation of Potential Drug-Drug Interactions in Patients of Emergency Medicine Department at a Tertiary Care Teaching Hospital: A Prospective Study. Int J Sci Stud 2015; 3(5):48-53.

17 Radosević N, Gantumur M, Vlahović-Palcevski V. Potentially inappropriate prescribing to hospitalised patients. Pharmacoepidemiol Drug Saf. 2008 Jul; 17(7):733-7.

18 Robert Barrens. Evaluation of personal digital assistant software for drug interactions. Am J Health-Syst Pharm 2004; 61:380-5.

19 Missiakos O, Baysari MT, Day RO. Identifying effective computerized strategies to prevent drug-drug interactions in hospital: A user-centered approach. Int J Med Inform. 2015 Aug; 84(8):595-600. doi:10.1016/ j.ijmedinf.2015.04.001. Epub 2015 Apr 13.

20 Roblek T, Vaupotic T, Mrhar A, Lainscak M. Drug-drug interaction software in clinical practice: a systematic review. Eur J Clin Pharmacol. 2015 Feb; 71(2):131-42. doi:10.1007/s00228-014-1786-7. Epub 2014 Dec 23.

21 Getachew Moges. Assessment of physicians’ awareness on drug-drug interactions and common sources of information in general hospitals of Addis Ababa, Masters thesis 2013.Addis Ababa University. Available from etd.aau.edu.et/bitstream/123456789/6077/1/get final.pdf [Last cited on 2017 Aug 25].

22 Bacic-Vrca V, Marusic S, Erdeljic V, Falamic S, Gojo-Tomic N, Rahelic D. The incidence of potential drug-drug interactions in elderly patients with arterial hypertension. Pharm World Sci 2010; 32:815–821. DOI 10.1007/s11096-010-9442-5.

23 M Saidul Islam, S Farah. Availability and characteristics of information on Drug-Durg Interactions in the drug package inserts: An experience from Bangladesh. The Internet Journal of Health. 2006; 6(1). Available from https://print.ispub.com/api/0/ispub-article/8539 [Last cited on 2017 Aug 25].

Received on 12.12.2017 Modified on 27.01.2018

Research J. Pharm. and Tech 2018; 11(6): 2345-2350.

DOI: 10.5958/0974-360X.2018.00435.3