Skip to main content
SpringerLink
Log in

Impact of pharmacists’ interventions on physicians’ decision of a knowledge-based renal dosage adjustment system

  • Research Article
  • Published:
International Journal of Clinical Pharmacy Aims and scope Submit manuscript

Abstract

Background Early interventions with clinical decision support system (CDSS) guidance have ensured appropriate drug dosing for patients with renal impairment. However, the low rates of physician compliance with CDSS alerts have been reported. Objective We investigated whether designated pharmacist interventions were associated with physician’ acceptance of the knowledge-based renal dosage adjustment system (K-RDS) for patients with reduced renal function. Setting A retrospective, single-center study was conducted using a healthcare information system at a tertiary teaching hospital. Methods This study compared physicians’ acceptance of the K-RDS with and without designated pharmacists. The severity of prescription errors and the impact of service provided by the pharmacist were evaluated using the validated method developed by Overhage and Lukes. From April to June 2017, we enrolled patients who were ≥ 20 years of age and admitted with an estimated glomerular filtration rate under 50 ml/min on medications that required dose adjustments. Main outcomes measure The number of dosing alerts of the K-RDS and physicians’ acceptance rates were compared between a control group guided by the central pharmacy only and a group with assigned designated pharmacists. The factors associated with the physicians’ acceptance rate were also analyzed using a multivariate logistic regression method. The impact of service provided by the pharmacist were considered as ‘highly significant’ (categories: 1–2). Severity of prescription errors were defined as ‘serious’ if they corresponded to categories 1–2 of the Overhage and Lukes scale for severity, and interventions were relevant if they corresponded to categories 1–3 in the impact of  service provided by the pharmacist scale. Results Among 1363 prescription interventions, 491 (36.0%) were performed by designated pharmacists. The K-RDS alert acceptance rate by the physicians was 54.4% in the designated pharmacist group and 47.0% in the control group (p = 0.0233). The statistically significant association was found in the designated pharmacists group in ‘highly significant’ service provided by the pharmacist (p < 0.001, OR 1.772; 95% CI 1.362–2.305) and ‘serious’ severity of prescription errors (p = 0.012, OR 1.657; 95% CI 1.116–2.460). The presence of designated pharmacists (OR 1.353, p = 0.0272), patient’s gender (OR 0.758, p = 0.0016), department specialty (OR 0.659, p < 0.0001), eGFR (OR 1.538 if < 10 ml/min; OR 1.519 if 10–40 ml/min, p < 0.0001), and medications (OR 6.058–43.992 depending on the medication category, p < 0.0001) were significant factors affecting physicians’ acceptance. Conclusion Pharmacists’ interventions effectively improved physicians’ acceptance of the K-RDS alerts.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Sittig DF, Krall MA, Dykstra RH, Russell A, Chin HL. A survey of factors affecting clinician acceptance of clinical decision support. BMC Med Inform Decis Mak. 2006;6(1):6.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Chang J, Ronco C, Rosner MH. Computerized decision support systems: improving patient safety in nephrology. Nat Rev Nephrol. 2011;7(6):348.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Hu K-T, Matayoshi A, Stevenson FT. Calculation of the estimated creatinine clearance in avoiding drug dosing errors in the older patient. Am J Med Sci. 2001;322(3):133–6.

    Article  CAS  PubMed  Google Scholar 

  4. Dörks M, Allers K, Schmiemann G, Herget-Rosenthal S, Hoffmann F. Inappropriate medication in non-hospitalized patients with renal insufficiency: a systematic review. J Am Geriatr Soc. 2017;65(4):853–62.

    Article  PubMed  Google Scholar 

  5. Breton G, Froissart M, Janus N, Launay-Vacher V, Berr C, Tzourio C, et al. Inappropriate drug use and mortality in community-dwelling elderly with impaired kidney function—the Three-City population-based study. Nephrol Dial Transplant. 2011;26(9):2852–9.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Seidling HM, Phansalkar S, Seger DL, Paterno MD, Shaykevich S, Haefeli WE, et al. Factors influencing alert acceptance: a novel approach for predicting the success of clinical decision support. J Am Med Inform Assoc. 2011;18(4):479–84.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Drenth-van Maanen AC, Van Marum RJ, Jansen PA, Zwart JE, Van Solinge WW, Egberts TC. Adherence with dosing guideline in patients with impaired renal function at hospital discharge. PLoS ONE. 2015;10(6):e0128237.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Tawadrous D, Shariff SZ, Haynes RB, Iansavichus AV, Jain AK, Garg AX. Use of clinical decision support systems for kidney-related drug prescribing: a systematic review. Am J Kidney Dis. 2011;58(6):903–14.

    Article  PubMed  Google Scholar 

  9. Bennett WM. Drug prescribing in renal failure. Drugs. 1979;17(2):111–23.

    Article  CAS  PubMed  Google Scholar 

  10. Pelayo S, Marcilly R, Bernonville S, Leroy N, Beuscart-Zephir M-C, editors. Human factors based recommendations for the design of medication related clinical decision support systems (CDSS). MIE; 2011.

  11. Terrell KM, Perkins AJ, Hui SL, Callahan CM, Dexter PR, Miller DK. Computerized decision support for medication dosing in renal insufficiency: a randomized, controlled trial. Ann Emerg Med. 2010;56(6):623–9.

    Article  PubMed  Google Scholar 

  12. Payne TH, Nichol WP, Hoey P, Savarino J, editors. Characteristics and override rates of order checks in a practitioner order entry system. In: Proceedings of the AMIA symposium. American Medical Informatics Association; 2002.

  13. Shah NR, Seger AC, Seger DL, Fiskio JM, Kuperman GJ, Blumenfeld B, et al. Improving acceptance of computerized prescribing alerts in ambulatory care. J Am Med Inform Assoc. 2006;13(1):5–11.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Hassan Y, Al-Ramahi RJ, Aziz NA, Ghazali R. Impact of a renal drug dosing service on dose adjustment in hospitalized patients with chronic kidney disease. Ann Pharmacother. 2009;43(10):1598–605.

    Article  PubMed  Google Scholar 

  15. Salgado TM, Moles R, Benrimoj SI, Fernandez-Llimos F. Pharmacists’ interventions in the management of patients with chronic kidney disease: a systematic review. Nephrol Dial Transplant. 2011;27(1):276–92.

    Article  CAS  PubMed  Google Scholar 

  16. Golightly L, O’fallon C, Moran W, Sorocki A. Pharmacist monitoring of drug therapy in patients with abnormal serum creatinine levels. Hosp Pharm. 1993;28(8):725–7, 30–2.

  17. Long CL, Raebel MA, Price DW, Magid DJ. Compliance with dosing guidelines in patients with chronic kidney disease. Ann Pharmacother. 2004;38(5):853–8.

    Article  PubMed  Google Scholar 

  18. McMullin ST, Reichley RM, Kahn MG, Dunagan WC, Bailey TC. Automated system for identifying potential dosage problems at a large university hospital. Am J Health Syst Pharm. 1997;54(5):545–9.

    Article  CAS  PubMed  Google Scholar 

  19. Berbatis C, Eckert G, Neale F, Rothwell J. Quality assurance of drug therapy in hospitals: patient serum creatinine values used by ward pharmacists in checking dosage regimens. Med J Aust. 1979;1(2):46–7.

    CAS  PubMed  Google Scholar 

  20. Zaal RJ, Jansen MM, Duisenberg-van Essenberg M, Tijssen CC, Roukema JA, van den Bemt PM. Identification of drug-related problems by a clinical pharmacist in addition to computerized alerts. Int J Clin Pharm. 2013;35(5):753–62.

    Article  CAS  PubMed  Google Scholar 

  21. Calloway S, Akilo HA, Bierman K. Impact of a clinical decision support system on pharmacy clinical interventions, documentation efforts, and costs. Hosp Pharm. 2013;48(9):744–52.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Robertson J, Walkom E, Pearson SA, Hains I, Williamson M, Newby D. The impact of pharmacy computerised clinical decision support on prescribing, clinical and patient outcomes: a systematic review of the literature. Int J Pharm Pract. 2010;18(2):69–87.

    PubMed  Google Scholar 

  23. Yoo S, Hwang H, Jheon S. Hospital information systems: experience at the fully digitized Seoul National University Bundang Hospital. J Thorac Dis. 2016;8(Suppl 8):S637.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Overhage JM, Lukes A. Practical, reliable, comprehensive method for characterizing pharmacists’ clinical activities. Am J Health Syst Pharm. 1999;56:2444–50.

    Article  CAS  PubMed  Google Scholar 

  25. Pérez-Moreno MA, Rodríguez-Camacho JM, Calderón-Hernanz B, Comas-Díaz B, Tarradas-Torras J. Clinical relevance of pharmacist intervention in an emergency department. Emerg Med J. 2017;34(8):495–501.

    Article  PubMed  Google Scholar 

Download references

Funding

None.

Conflicts of interest

The authors have no conflicts of interest to disclose.

Author information

Authors and Affiliations

  1. Division of Life and Pharmaceutical Sciences, Ewha Womans University, Seoul, Republic of Korea

    Kyung Suk Choi & Sandy Jeong Rhie

  2. Department of Pharmacy, Seoul National University Bundang Hospital, Seoungnam-si, Republic of Korea

    Kyung Suk Choi & Eunsook Lee

  3. College of Pharmacy, Ewha Womans University, Seoul, Republic of Korea

    Sandy Jeong Rhie

Authors
  1. Kyung Suk Choi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eunsook Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sandy Jeong Rhie
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sandy Jeong Rhie.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

See Table 5.

Table 5 Classification of the different categories of the validated method proposed by Overhage and Lukes regarding ‘severity of prescription error’ and ‘impact of service provided by the pharmacist’
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Choi, K.S., Lee, E. & Rhie, S.J. Impact of pharmacists’ interventions on physicians’ decision of a knowledge-based renal dosage adjustment system. Int J Clin Pharm 41, 424–433 (2019). https://doi.org/10.1007/s11096-019-00796-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11096-019-00796-5

Keywords

Search

Navigation