Determination of potential drug-drug interactions with different interaction software programs in elderly patients over 85 in a community pharmacy setting: a cross-sectional study

Abstract

AimVarious potential drug-drug interaction screening software programs or databases have been developed and implemented as decision support tools to assist clinicians. The risk of adverse drug reactions, hospitalization, compliance problems, and potential drug-drug interactions increases with age. Our research aimed to detect potential drug-drug interactions in elderly patients over 85 and compare the software programs used to detect interactions.MethodsPrescriptions of elderly patients over the age of 85 who received their medications from five different community pharmacies in Konya, Türkiye, in 2022 were retrospectively examined. The software programs Medscape®, Drugs®, Micromedex®, and LexiComp® were used to detect potential drug-drug interactions and reveal common interactions in the patients. The compatibility of the programs was also determined.ResultsA total of 307 patients (43.3% male and 56.7% female) were included in this study. While Micromedex® detected a total of 920 interactions in the total sample, Medscape® detected 1,876, Drugs® detected 1.632, and LexiComp® detected 1.414. However, LexiComp® detected the most contraindications. Regarding the compatibility of the four software programs, Kendall’s W value was calculated as 0.79, and the statistical significance was determined (P < .05).ConclusionMedscape®, Drugs®, Micromedex®, and LexiComp® software programs used to detect potential drug-drug interactions in the elderly exhibit high compatibility with each other. It is recommended that clinicians use more than one software program to determine potential drug-drug interactions for rational drug use.

Keywords

Introduction

Drug-drug interactions (DDIs) are defined as situations in which the pharmacological effect of one drug is altered by another when two drugs are used together. The most important reason why drug interactions are common is the use of multiple drugs at the same time.¹ DDIs are a particularly important type of adverse drug event because they can alter drug effectiveness and safety. While DDIs may not always be preventable, they can often be predicted.^2-3 Actual DDIs are determined from adverse outcomes in patients, whereas potential DDIs (pDDIs) are those identified through analysis of the pharmacokinetic and pharmacodynamic profiles of each drug in use and the identification of potential adverse events resulting from this association. pDDIs may present with adverse outcomes in patients or have no clinical consequence.^3-4-5-6 The prevalence of pDDIs in the community pharmacy setting may vary depending on age and disease.⁷
Various pDDI screening software programs or databases have been developed and implemented as decision support tools to assist clinicians.⁸ These tools frequently report whether pDDIs identified occur due to the pharmacokinetic and/or pharmacodynamic effect, highlight the degree of severity, outline the management of pDDIs and provide reference literature. However, some databases do not include all of these components.⁹
Polypharmacy is the use of multiple medications. Although there is no clear definition for polypharmacy, the simultaneous use of five or more drugs is generally accepted.¹⁰ As drug use increases, drug-drug interactions will also increase and adverse drug reactions (ADRs) may be observed accordingly.¹¹
Old age is defined as age 65 and above. The increase in chronic comorbidities and pharmacokinetic and pharmacodynamic changes with age make elderly patients more sensitive to drug side effects.¹² The risk of ADRs, hospitalization, compliance problems, and pDDIs increases with age.^9,13 The MULTIPAP Study, conducted on elderly patients treated in Spanish primary care centers, indicated that half of the patients had DDIs at least once. Similarly, a cross-sectional study conducted in Brazil reported that the prevalence of DDIs among elderly patients using multiple medications was around 35%. DDIs constitute a part of ADRs. In fact, it is estimated that 6%–30% of all ADRs in the population are caused by DDIs and are therefore largely preventable. Hence, continuous monitoring of inappropriate prescriptions that may lead to DDIs at the patient and/or population level is an important activity for ADRs prevention.^14-15-16-17
Our research aimed to detect pDDIs in elderly patients and compare software programs used to detect interactions.

Materials and Methods

Prescriptions of elderly patients over 85 who received their medications from five different community pharmacies in Konya, Türkiye, from 01.01.2022 to 31.12.2022 were retrospectively examined. Patients’ age, gender, and medication information were recorded, and prescriptions containing medications not covered by the software programs were excluded. The software programs Medscape®, Drugs®, Micromedex®, and LexiComp® were used to detect pDDIs in the patients.
While Medscape® and Drugs® accept free memberships, LexiComp® and Micromedex® accept paid memberships. Interaction classifications of software programs are shown in Figure 1.Ethical ApprovalThis study was approved by the Ethics Committee of Selçuk University Faculty of Medicine Local Ethics Committee (Date: 22.06.2022, Decision No: E.304008).Statistical AnalysesBy analyzing each pDDI using Kendall’s W values, the link between the prospective pDDI software programs was verified based on the outcomes of severity degrees of interaction. Kendall’s W values range from 0–0.2, which denotes a little agreement, to 0.21–0.40 (fair), 0.41–0.60 (considerable), 0.61–0.80 (significant), and 0.81–1.0 (perfect). IBM SPSS 22.0 was used to conduct the statistical analysis. The threshold of statistical significance was set at P < .05.

Results

A total of 307 patients (43.3% male and 56.7% female) were included in this study. While the average age of male patients was 88.38, it was 88.51 for females. While male patients had an average of 6.44 medications in their prescriptions, this number for females was 6.62. Polypharmacy was detected in the prescriptions of 223 (72.63%). Details are given in Table 1. While Micromedex® detected a total of 920 interactions in the total study sample, Medscape® detected 1,876, Drugs® detected 1,632, and LexiComp® detected 1,414 interactions. While Micromedex® detected 1 contraindicated interaction, Medscape® detected 4 and LexiComp® detected 79 contraindicated interactions. The number of interactions per patient in Micromedex®, Medscape®, Drugs®, and LexiComp® were 2.99, 6.11, 5.31, and 4.6, respectively. Details are given in Table 2. When the compatibility of the four software programs was examined, Kendall’s W was calculated as 0.79, and statistical significance was determined (P < .05). The compatibility of the software programs among themselves was also investigated. In the compatibility analysis between Micromedex®, Medscape®, and LexiComp®, Kendall’s W was determined as 0.81 (P < .05). When pairwise comparisons were made between programs, the highest score was between Medscape® and Drugs® (Kendall’s W: 0.9, P < .05). When Kendall’s W values were examined, it was determined that the software programs were highly compatible with each other. LexiComp® detected that 32.9% of contraindicated interactions were caused by combinations of nonsteroidal anti-inflammatory drugs (NSAIDs). Common contraindicated interactions, as well as their potential effect, details are given in Table 3. Metoclopramide/Sertraline was identified as a contraindicated combination in Micromedex® software program. In Medscape®, Clarithromycin/Indapamide, Moxifloxacin/Indapamide, Amisulpride/Olanzapine and Amisulpride/Quetiapine combinations were identified as contraindicated. In the LexiComp® software program, combinations such as Diclofenac/Ketoprofen, Flurbiprofen/Ketoprofen were found to be contraindicated.

Discussion

With age, there is increased physiological changes that may alter the effect of a drug, making the elderly population more prone to ADRs. Therefore, pDDI management is crucial. Clinicians benefit from various software programs for pDDI management. These programs can predict clinically important pDDIs and ADRs. Comparing the differences between such software programs should guide clinicians in predicting critical events.^18-19
In this research, four frequently used interaction software programs were compared. While Medscape® and Drugs® are free to use, LexiComp® and Micromedex® require paid membership. It is thought that the free-to-use option increases the use of Medscape® and Drugs® in the community pharmacy environment. Most pDDIs were detected in Medscape®. The program with the least interaction was Micromedex®. Medscape® explains an interaction with more than one mechanism, and this is thought to be the reason for the difference. The most contraindications were detected in LexiComp®. It is thought that this is because this software program provides an extensive list of contraindications, especially regarding NSAID combinations. There is no contraindication warning for the combined use of NSAIDs in other software programs.
In a study involving patients aged 65 and over, Liu et al. indicated moderate agreement (weighted kappa = 0.473) between LexiComp® and Micromedex®. Furthermore, LexiComp® detected the most contraindicated interactions.²⁰ However, the present study found a high difference between LexiComp® and Micromedex® (Kendall’s W = 0.86). In a study conducted in a community pharmacy environment, Sancar et al. determined that Micromedex®, Medscape®, and Drugs® were highly compatible with each other.²¹ The present study found a similar result between the three programs (Kendall’s W>0.80). In Kheshti et al.’s study, which compared five commonly used drug interaction databases (LexiComp®, Micromedex®, iFacts®, Medscape®, and Epocrates®), LexiComp® and Micromedex® were found to be more suitable than other databases for determining clinically important drug interactions.²² In a study comparing Micromedex®, LexiComp®, and Drugs® for intensive care patients receiving antibiotics, 15% of the interactions detected with Micromedex®, 28.6% of the interactions detected with Medscape®, and 19.8% of the interactions detected with Drugs® were found to be significant.²³
Combinations of NSAIDs are remarkable, especially when contraindicated interactions are examined in LexiComp®. It has been stated that the risk of bleeding increases because of this interaction. Clinicians should be careful when prescribing these combinations in elderly patients. Complications that may develop due to bleeding can turn into life-threatening problems in such patients. Additionally, caution should be exercised when prescribing anticoagulant drugs in the elderly due to the risk of bleeding.²⁴ Drug interactions should always be considered in patients receiving anticoagulant therapy, especially those with multiple comorbidities, to optimize treatment.²⁵

Limitations

Conducting this study retrospectively was the most important limiting factor. Hence, limited data were obtained, and the number of drug interactions detected that were clinically significant could not be determined. Multicenter and larger prospective studies are needed to eliminate these limitations.

Conclusion

Interaction programs used to detect pDDIs in elderly patients in the community pharmacy setting demonstrate high compatibility. However, there are some differences in interaction severity among these programs; therefore, it would be appropriate to use a combination of programs when detecting pDDIs.

References

1. Palleria C, Di Paolo A, Giofrè C, et al. Pharmacokinetic drug-drug interaction and their implication in clinical management. J Res Med Sci. 2013;18(7):601-610.
   PubMed · Google Scholar
2. Juurlink DN, Mamdani M, Kopp A, Laupacis A, Redelmeier DA. Drug-drug interactions among elderly patients hospitalized for drug toxicity. JAMA. 2003;289(13):1652-1658. doi:10.1001/jama.289.13.1652
   Article · PubMed · Google Scholar
3. Montané E, Arellano AL, Sanz Y, Roca J, Farré M. Drug-related deaths in hospital inpatients: a retrospective cohort study. Br J Clin Pharmacol. 2018;84(3):542-552. doi:10.1111/bcp.13471
   Article · PubMed · Google Scholar
4. Alvim MM, Silva LA, Leite IC, Silvério MS. Adverse events caused by potential drug-drug interactions in an intensive care unit of a teaching hospital. Rev Bras Ter Intensiva. 2015;27(4):353-359. doi:10.5935/0103-507x.20150060
   Article · PubMed · Google Scholar
5. Ganeva M, Gancheva T, Troeva J, Kiriyak N, Hristakieva E. Clinical relevance of drug-drug interactions in hospitalized dermatology patients. Adv Clin Exp Med. 2013;22(4):555-563.
   PubMed · Google Scholar
6. Moura CS, Acurcio FA, Belo NO. Drug-drug interactions associated with length of stay and cost of hospitalization. J Pharm Pharm Sci. 2009;12(3):266-272. doi:10.18433/j35c7z
   Article · PubMed · Google Scholar
7. Dirin MM, Mousavi S, Afshari AR, Tabrizian K, Ashrafi MH. Potential drug-drug interactions in prescriptions dispensed in community and hospital pharmacies in east of Iran. J Res Pharm Pract. 2014;3(3):104-107. doi:10.4103/2279-042x.141118
   Article · PubMed · Google Scholar
8. Wang H, Shi H, Wang N, et al. Prevalence of potential drug-drug interactions in the cardiothoracic intensive care unit patients in a Chinese tertiary care teaching hospital. BMC Pharmacol Toxicol. 2022;23(1):39. doi:10.1186/s40360-022-00582-6
   Article · PubMed · Google Scholar
9. Roblek T, Vaupotic T, Mrhar A, Lainscak M. Drug-drug interaction software in clinical practice: a systematic review. Eur J Clin Pharmacol. 2015;71(2):131-142. doi:10.1007/s00228-014-1786-7
   Article · PubMed · Google Scholar
10. Masnoon N, Shakib S, Kalisch-Ellett L, Caughey GE. What is polypharmacy? A systematic review of definitions. BMC Geriatr. 2017;17(1):230. doi:10.1186/s12877-017-0621-2
    Article · PubMed · Google Scholar
11. Dhalwani NN, Fahami R, Sathanapally H, et al. Association between polypharmacy and falls in older adults: a longitudinal study from England. BMJ Open. 2017;7(10). doi:10.1136/bmjopen-2017-016358
    Article · PubMed · Google Scholar
12. Johnell K, Klarin I. The relationship between number of drugs and potential drug-drug interactions in the elderly: a study of over 600000 elderly patients from the Swedish Prescribed Drug Register. Drug Saf. 2007;30(10):911-918. doi:10.2165/00002018-200730100-00009
    Article · PubMed · Google Scholar
13. Livio F, Marzolini C. Prescribing issues in older adults living with HIV: thinking beyond drug-drug interactions with antiretroviral drugs. Ther Adv Drug Saf. 2019;10:2042098619880122. doi:10.1177/2042098619880122
    Article · PubMed · Google Scholar
14. Classen DC, Pestotnik SL, Evans RS, Burke JP. Computerized surveillance of adverse drug events in hospital patients. JAMA. 1991;266(20):2847-2851. doi:10.1001/jama.1991.03470200059035
    Article · PubMed · Google Scholar
15. Rogero-Blanco E, Del-Cura-González I, Aza-Pascual-Salcedo M, et al. Drug interactions detected by a computer-assisted prescription system in primary care patients in Spain: MULTIPAP study. Eur J Gen Pract. 2021;27(1):90-96. doi:10.1080/13814788.2021.1917543
    Article · PubMed · Google Scholar
16. Santos TRA, Silveira EA, Pereira LV, Provin MP, Lima DM, Amaral RG. Potential drug-drug interactions in older adults: a population-based study. Geriatr Gerontol Int. 2017;17(12):2336-2346. doi:10.1111/ggi.13070
    Article · PubMed · Google Scholar
17. Franceschi M, Scarcelli C, Niro V, et al. Prevalence, clinical features, and avoidability of adverse drug reactions as cause of admission to a geriatric unit: a prospective study of 1756 patients. Drug Saf. 2008;31(6):545-556. doi:10.2165/00002018-200831060-00009
    Article · PubMed · Google Scholar
18. Bektay MY, Seker Z, Eke HK, Turk HM, Izzettin FV. Comparison of different decision support software programs in perspective of potential drug-drug interactions in the oncology clinic. J Oncol Pharm Pract. 2023;29(5):1178-1186. doi:10.1177/10781552221104814
    Article · PubMed · Google Scholar
19. Nightingale G, Pizzi LT, Barlow A, et al. The prevalence of major drug-drug interactions in older adults with cancer and the role of clinical decision support software. J Geriatr Oncol. 2018;9(5):526-533. doi:10.1016/j.jgo.2018.02.001
    Article · PubMed · Google Scholar
20. Liu Y, Wang J, Gong H, et al. Prevalence and associated factors of drug-drug interactions in elderly outpatients in a tertiary care hospital: a cross-sectional study based on 3 databases. Ann Transl Med. 2023;11(1):17. doi:10.21037/atm-22-5463
    Article · PubMed · Google Scholar
21. Sancar M, Kaşik A, Okuyan B, Batuhan S, Izzettin FV. Determination of potential drug-drug interactions using various software programs in a community pharmacy setting. Turk J Pharm Sci. 2019;16(1):14-19. doi:10.4274/tjps.30932
    Article · PubMed · Google Scholar
22. Kheshti R, Aalipour M, Namazi S. A comparison of 5 common drug-drug interaction software programs regarding accuracy and comprehensiveness. J Res Pharm Pract. 2016;5(4):257-263. doi:10.4103/2279-042x.192461
    Article · PubMed · Google Scholar
23. Emre K, Tecen-Yücel K, Özdemir N, et al. Yoğun bakım hastalarında antibiyotiklerin diğer ilaçlarla etkileşimlerinin değerlendirilmesi [The evaluation of interactions of antibiotics with other drugs in intensive care patients]. Surekli Tip Egitimi Derg. 2019;28(6):404-409.
    PubMed · Google Scholar
24. Teklay G, Shiferaw N, Legesse B, Bekele ML. Drug-drug interactions and risk of bleeding among inpatients on warfarin therapy: a prospective observational study. Thromb J. 2014;12(1):1-8.
    PubMed · Google Scholar
25. Ceylan C, Umar RM, Çattık BN, Bolel F, Şahna M, Koçberber EK. Potential drug-drug interactions in patients using warfarin, heparin, and enoxaparin. Avicenna J Pharm Res. 2021;2(2):60-65. doi:10.34172/ajpr.2021.12
    Article · PubMed · Google Scholar

Tables

Additional Information

Publisher’s Note
Bayrakol MP remains neutral with regard to jurisdictional and institutional claims.

Rights and Permissions

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). To view a copy of the license, visit https://creativecommons.org/licenses/by-nc/4.0/

View full license details →