Main Article Content
Drug dispensing, Pharmacist, Perception, Patient safety, Factor analysis
Objectives: Automated drug dispensing system (ADDs) is an emerging technology positively impacts drug dispensing efficiency by minimizing medication errors. However, the pharmacist perception of the impact of ADDs on patient safety is not well-established. This cross-sectional observational study aimed to evaluate the dispensing practice and pharmacist perception of ADDs towards patient safety through a validated questionnaire. Methods: A selfdesigned questionnaire was validated and the pharmacist perception of dispensing practice was compared between two hospitals adopting ADDs and traditional drug dispensing system (TDDs). Results: The developed questionnaire had an excellent internal consistency (both Cronbach’s α and McDonald’s ω coefficients were >0.9). Factor analysis retained three significant factors (subscales) that explained pharmacist perception of dispensing system, dispensing practice, and patient counseling (p<0.001 for each factor). The average number of prescriptions dispensed per day, drugs contained in each prescription, average time for labeling each prescription and inventory management were significantly varied between ADDs and TDDs (p=0.027, 0.013 0.044 and 0.004, respectively). The perception of pharmacists using ADDs on three domains were higher than the TDDs. The pharmacists in ADDs agreed that they had enough time to review the medications before dispensing than TDDs and this difference was found to be statistically significant (p=0.028). Conclusions: ADDs was highly effective in improving dispensing practice and medication review; however, the pharmacists need to emphasize the importance of ADDs to translate the pharmacists’ freed-time towards patient care.
2. Einarson TR. Drug-related hospital admissions. Ann Pharmacother. 1993;27(7-8):832-840. https://doi.org/10.1177/106002809302700702
3. Alshammari TM, Alenzi KA, Alatawi Y, et al. Current Situation of Medication Errors in Saudi Arabia: A Nationwide ObservationalStudy. J Patient Saf. 2022;18(2):e448-e453. https://doi.org/10.1097/PTS.0000000000000839
4. Weant KA, Bailey AM, Baker SN. Strategies for reducing medication errors in the emergency department. Open Access EmergMed. 2014;6:45-55. https://doi.org/10.2147/OAEM.S64174
5. ASHP Guidelines on the safe use of automated dispensing devices. Am J Health Syst Pharm. 2010;67(6):483-490.
6. de-Carvalho D, Alvim-Borges JL, Toscano CM. Impact assessment of an automated drug-dispensing system in a tertiary hospital.Clinics (Sao Paulo). 2017;72(10):629-636. https://doi.org/10.6061/clinics/2017(10)07
7. Berdot S, Korb-Savoldelli V, Jaccoulet E, et al. A centralized automated-dispensing system in a French teaching hospital: return on investment and quality improvement. Int J Qual Health Care. 2019;31(3):219-224. https://doi.org/10.1093/intqhc/mzy152
8. Fanning L, Jones N, Manias E. Impact of automated dispensing cabinets on medication selection and preparation error rates in an emergency department: a prospective and direct observational before-and-after study. J Eval Clin Pract. 2016;22(2):156-163. https://doi.org/10.1111/jep.12445
9. Agrawal A. Medication errors: prevention using information technology systems. Br J Clin Pharmacol. 2009;67(6):681-686. https://doi.org/10.1111/j.1365-2125.2009.03427.x
10. Tsao NW, Lo C, Babich M, et al. Decentralized automated dispensing devices: systematic review of clinical and economic impacts in hospitals. Can J Hosp Pharm. 2014;67(2):138-148. https://doi.org/10.4212/cjhp.v67i2.1343
11. Keers RN, Williams SD, Cooke J, et al. Impact of interventions designed to reduce medication administration errors in hospitals:a systematic review. Drug Saf. 2014;37(5):317-332. https://doi.org/10.1007/s40264-014-0152-0
12. Chapuis C, Roustit M, Bal G, et al. Automated drug dispensing system reduces medication errors in an intensive care setting.Crit Care Med. 2010;38(12):2275-2281. https://doi.org/10.1097/CCM.0b013e3181f8569b
13. Rochais E, Atkinson S, Guilbeault M, et al. Nursing perception of the impact of automated dispensing cabinets on patient safety and ergonomics in a teaching health care center. J Pharm Pract. 2014;27(2):150-157. https://doi.org/10.1177/0897190013507082
14. Zheng WY, Lichtner V, Van Dort BA, et al. The impact of introducing automated dispensing cabinets, barcode medication administration, and closed-loop electronic medication management systems on work processes and safety of controlled
medications in hospitals: A systematic review. Res Social Adm Pharm. 2021;17(5):832-841. https://doi.org/10.1016/j.sapharm.2020.08.001
15. Roman C, Poole S, Walker C, et al. A ‘time and motion’ evaluation of automated dispensing machines in the emergency department. Australas Emerg Nurs J. 2016;19(2):112-117. https://doi.org/10.1016/j.aenj.2016.01.004
16. Gray JP, Ludwig B, Temple J, et al. Comparison of a hybrid medication distribution system to simulated decentralized distribution nmodels. Am J Health Syst Pharm. 2013;70(15):1322-1335. https://doi.org/10.2146/ajhp120512
17. Zaidan M, Rustom F, Kassem N, et al. Nurses’ perceptions of and satisfaction with the use of automated dispensing cabinets at the Heart and Cancer Centers in Qatar: a cross-sectional study. BMC Nurs. 2016;15:4. https://doi.org/10.1186/s12912-015-0121-7
18. Pedersen CA, Schneider PJ, Scheckelhoff DJ. ASHP national survey of pharmacy practice in hospital settings: Prescribing and transcribing- 2013. Am J Heal Pharm. 2014;71(11):924-942. https://doi.org/10.2146/ajhp140032
19. Darwesh BM, Machudo SB, John S. The Experience of Using an Automated Dispensing System to Improve Medication Safety and Management at King Abdul aziz. University Hospital. J Pharm Pract Community Med. 2017;3(3):114-119.
20. Al Muallem Y, Al Dogether M, Al Assaf R, et al. The implementation experiences of a pharmacy automation drug dispensing system in saudi arabia. Stud Health Technol Inform. 2015;208:22-26.
21. Alsultan MS, Khurshid F, Mayet AY, et al. Hospital pharmacy practice in Saudi Arabia: Dispensing and administration in the Riyadh region. Saudi Pharm J. 2012;20(4):307-315. https://doi.org/10.1016/j.jsps.2012.05.003
22. Charan J, Biswas T. How to calculate sample size for different study designs in medical research? Indian J Psychol Med.2013;35(2):121-126. https://doi.org/10.4103/0253-7176.116232
23. Muflih SM, Al-Azzam S, Abuhammad S, et al. Pharmacists’ experience, competence and perception of telepharmacy technology in response to COVID-19. Int J Clin Pract. 2021;75(7):e14209. https://doi.org/10.1111/ijcp.14209
24. Sng Y, Ong CK, Lai YF. Approaches to outpatient pharmacy automation: a systematic review. Eur J Hosp Pharm. 2019;26(3):157- 162. https://doi.org/10.1136/ejhpharm-2017-001424
25. Jain S, Dubey S, Jain S. Designing and validation of questionnaire. Int Dent Med J Adv Res. 2016;2(1):1-3.
26. Viladrich C, Angulo-Brunet A, Doval E. A Journey around alpha and omega to stimate internal consistency reliability. Anales de Psicología. 2017;33(3):755-782.
27. Liou CY, Musicus R. Cross Entropy Approximation of Structured Gaussian Covariance Matrices. IEEE Transactions on Signal Processing. 2008;56 (7), 3362-3367.
28. Watkins MW. Exploratory Factor Analysis: A Guide to Best Practice. Journal of Black Psychology. 2018;44(3):219-246.
29. Peterson RA. A Meta-Analysis of Variance Accounted for and Factor Loadings in Exploratory Factor Analysis. Marketing Letters.2000;11:261-275.
30. Kaiser HF. An index of factorial simplicity. Psychometrika. 1974;39:31-36.
31. Bartlett MS. A further note on the multiplying factors for various chi-square approximations in factor analysis. Journal of the Royal Statistical Society, Series B, 1954;16:296-298.
32. Alavi M, Visentin DC, Thapa DK, et al. Chi-square for model fit in confirmatory factor analysis. J Adv Nurs. 2020;76(9):2209- 2211. https://doi.org/10.1111/jan.14399
33. Hu LT, Bentler PM. Fit indices in covariance structure modeling: sensitivity to under-parameterized model misspecification.Psychological Methods. 1998;3:424-453.
34. Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Structural Equation Modeling. 1999;6:1-55.
35. Ahtiainen HK, Kallio MM, Airaksinen M, et al. Safety, time and cost evaluation of automated and semi-automated drug distribution systems in hospitals: a systematic review. Eur J Hosp Pharm. 2020;27(5):253-262. https://doi.org/10.1136/ejhpharm-2018-001791
36. Schneider P. The Impact of Technology on Safe Medicines Use and Pharmacy Practice in the US. Front. Pharmacol. 2018;9:1361.https://doi.org/10.3389/fphar.2018.01361
37. Rodriguez-Gonzalez CG, Herranz-Alonso A, Escudero-Vilaplana V, et al. Robotic dispensing improves patient safety, inventory management, and staff satisfaction in an outpatient hospital pharmacy. J Eval Clin Pract. 2019;25(1):28-35. https://doi. org/10.1111/jep.13014
38. Almalki ZS, Alqahtani N, Salway NT, et al. Evaluation of medication error rates in Saudi Arabia: A protocol for systematic review and meta-analysis. Medicine (Baltimore). 2021;100(9):e24956. https://doi.org/10.1097/MD.0000000000024956
39. Pratt N, Roughead E. Assessment of Medication Safety Using Only Dispensing Data. Curr Epidemiol Rep. 2018;5(4):357-369. https://doi.org/10.1007/s40471-018-0176-6
40. Aldhwaihi K, Schifano F, Pezzolesi C, et al. A systematic review of the nature of dispensing errors in hospital pharmacies. Integr Pharm Res Pract. 2016;5:1-10. https://doi.org/10.2147/IPRP.S95733
41. Keers RN, Williams SD, Cooke J, et al. Impact of interventions designed to reduce medication administration errors in hospitals: a systematic review. Drug Saf. 2014;37(5):317-332. https://doi.org/10.1007/s40264-014-0152-0
42. Berdot S, Roudot M, Schramm C, et al. Interventions to reduce nurses’ medication administration errors in inpatient settings: A systematic review and meta-analysis. Int J Nurs Stud. 2016;53:342-350. https://doi.org/10.1016/j.ijnurstu.2015.08.012
43. Al-Jazairi AS, Horanieh BK, Alswailem OA. The usefulness of an ambulatory care pharmacy performance dashboard during the COVID-19 pandemic in a complex tertiary care system. Am J Health Syst Pharm. 2021;78(9):813-817. https://doi.org/10.1093/ajhp/zxab049
44. Alam S, Osama M, Iqbal F, et al. Reducing pharmacy patient waiting time. Int J Health Care Qual Assur. 2018;31(7):834-844.
45. Loh BC, Wah KF, Teo CA, et al. Impact of value added services on patient waiting time at the ambulatory pharmacy Queen Elizabeth Hospital. Pharm Pract (Granada). 2017;15(1):846. https://doi.org/10.18549/PharmPract.2017.01.846
46. Risør BW, Lisby M, Sørensen J. Comparative Cost-Effectiveness Analysis of Three Different Automated Medication Systems Implemented in a Danish Hospital Setting. Appl Health Econ Health Policy. 2018;16(1):91-106. https://doi.org/10.1007/s40258-017-0360-8
47. Risør BW, Lisby M, Sørensen J. Cost-Effectiveness Analysis of an Automated Medication System Implemented in a Danish Hospital Setting. Value Health. 2017;20(7):886-893. https://doi.org/10.1016/j.jval.2017.03.001
48. Bohand X, Simon L, Perrier E, et al. Frequency, types, and potential clinical significance of medication-dispensing errors. Clinics. 2009;64(1):11-16. https://doi.org/10.1590/s1807-59322009000100003
49. Ali S, Shimels T, Bilal AI. Assessment of Patient Counseling on Dispensing of Medicines in Outpatient Pharmacy of Tikur-Anbessa Specialized Hospital, Ethiopia. Ethiop J Health Sci. 2019;29(6):727-736. https://doi.org/0.4314/ejhs.v29i6.9
50. Alshahrani F, Marriott JF, Cox AR. A qualitative study of prescribing errors among multi-professional prescribers within an e-prescribing system. Int J Clin Pharm. 2021;43(4):884-892. https://doi.org/10.1007/s11096-020-01192-0
51. Tariq RA, Vashisht R, Sinha A, et al. Medication Dispensing Errors and Prevention. [Updated 2021 Nov 14]. In: StatPearls.Treasure Island (FL): StatPearls Publishing; 2022 Jan. Available from: https://www.ncbi.nlm.nih.gov/books/NBK519065/
52. Momattin H, Arafa S, Momattin S, et al. Robotic Pharmacy Implementation and Outcomes in Saudi Arabia: A 21-Month Usability Study. JMIR Hum Factors. 2021;8(3):e28381. https://doi.org/10.2196/28381