Clinical Decision Support System with Renal Dose Adjustment Did Not Improve Subsequent Renal and Hepatic Function among Inpatients: The Japan Adverse Drug Event StudyFunding This work was supported by JSPS KAKENHI (grant numbers: JP17689022, JP21659130, JP22390103, JP23659256, JP26293159, and JP18H03032); Ministry of Health, Labor and Welfare of Japan (grant numbers: H26-Iryo-012 and H28-ICT-004); Pfizer Health Research Foundation; and the Uehara Memorial Foundation.
Background Medication dose adjustment is crucial for patients with renal dysfunction (RD). The assessment of renal function is generally mandatory; however, the renal function may change during the hospital stay and the manual assessment is sometimes challenging.
Objective We developed the clinical decision support system (CDSS) that provided a recommended dose based on automated calculated renal function.
Methods We conducted a prospective cohort study in a single teaching hospital in Japan. All hospitalized patients were included except for obstetrics/gynecology and pediatric wards between September 2013 and February 2015. The CDSS was implemented on December 2013. Renal and hepatic dysfunction (HD) were defined as changes in the estimated glomerular filtration rate (eGFR) and alanine aminotransferase or alkaline phosphatase levels based on these measurements during hospital stay. These measurements were obtained before (phase I), after (phase II), and 1 year after (phase III) the CDSS implementation.
Results We included 6,767 patients (phase I: 2,205; phase II: 2,279; phase III: 2,283). The patients' characteristics were similar among phases. Changes in eGFR were similar among phases, but the incidence of RD increased in phase III (phase I: 228 [10.3%]; phase II: 260 [11.4%]; phase III: 296 [13.0%], p = 0.02). However, the differences in incidences of RD were not statistically significant after adjusting for eGFR at baseline and age. The incidences of HD were also similar among phases (phase I: 175 [13.2%]; phase II: 171 [12.9%]; phase III: 167 [12.2%], p = 0.72).
Conclusion The CDSS implementation did not affect the incidence of renal and HD and changes in renal and hepatic function among hospitalized patients. The effectiveness of the CDSS with renal-guided doses should be investigated with respect to other endpoints.
Keywordsclinical decision support system - adverse drug event - renal dysfunction - hepatic dysfunction - renal dose adjustment
Protection of Human and Animal Subjects
This study was approved by the institutional review board at the hospital.
Eingereicht: 08. Juli 2020
Angenommen: 07. Oktober 2020
23. Dezember 2020 (online)
© 2020. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)
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- 1 Morimoto T, Gandhi TK, Seger AC, Hsieh TC, Bates DW. Adverse drug events and medication errors: detection and classification methods. Qual Saf Health Care 2004; 13 (04) 306-314
- 2 Takahashi Y, Sakuma M, Murayama H, Morimoto T. Effect of baseline renal and hepatic function on the incidence of adverse drug events: the Japan Adverse Drug Events study. Drug Metab Pers Ther 2018; 33 (04) 165-173
- 3 Usui J, Yamagata K, Imai E. et al. Clinical practice guideline for drug-induced kidney injury in Japan 2016: digest version. Clin Exp Nephrol 2016; 20 (06) 827-831
- 4 Alkhunaizi AM, Schrier RW. Management of acute renal failure: new perspectives. Am J Kidney Dis 1996; 28 (03) 315-328
- 5 Fujii T, Uchino S, Takinami M, Bellomo R. Subacute kidney injury in hospitalized patients. Clin J Am Soc Nephrol 2014; 9 (03) 457-461
- 6 Morimoto T, Sakuma M, Matsui K. et al. Incidence of adverse drug events and medication errors in Japan: the JADE study. J Gen Intern Med 2011; 26 (02) 148-153
- 7 Rowe JW, Andres R, Tobin JD, Norris AH, Shock NW. The effect of age on creatinine clearance in men: a cross-sectional and longitudinal study. J Gerontol 1976; 31 (02) 155-163
- 8 Verbeeck RK. Pharmacokinetics and dosage adjustment in patients with hepatic dysfunction. Eur J Clin Pharmacol 2008; 64 (12) 1147-1161
- 9 Pichette V, Leblond FA. Drug metabolism in chronic renal failure. Curr Drug Metab 2003; 4 (02) 91-103
- 10 Verbeeck RK, Musuamba FT. Pharmacokinetics and dosage adjustment in patients with renal dysfunction. Eur J Clin Pharmacol 2009; 65 (08) 757-773
- 11 Spruill WJ, Wade WE, Cobb III HH. Comparison of estimated glomerular filtration rate with estimated creatinine clearance in the dosing of drugs requiring adjustments in elderly patients with declining renal function. Am J Geriatr Pharmacother 2008; 6 (03) 153-160
- 12 Ibáñez-Garcia S, Rodriguez-Gonzalez C, Escudero-Vilaplana V. et al. Development and evaluation of a clinical decision support system to improve medication safety. Appl Clin Inform 2019; 10 (03) 513-520
- 13 Kirkendall ES, Spires WL, Mottes TA, Schaffzin JK, Barclay C, Goldstein SL. Development and performance of electronic acute kidney injury triggers to identify pediatric patients at risk for nephrotoxic medication-associated harm. Appl Clin Inform 2014; 5 (02) 313-333
- 14 Wong A, Wright A, Seger DL, Amato MG, Fiskio JM, Bates D. Comparison of overridden medication-related clinical decision support in the intensive care unit between a commercial system and a legacy system. Appl Clin Inform 2017; 8 (03) 866-879
- 15 Chertow GM, Lee J, Kuperman GJ. et al. Guided medication dosing for inpatients with renal insufficiency. JAMA 2001; 286 (22) 2839-2844
- 16 Awdishu L, Coates CR, Lyddane A. et al. The impact of real-time alerting on appropriate prescribing in kidney disease: a cluster randomized controlled trial. J Am Med Inform Assoc 2016; 23 (03) 609-616
- 17 Sonoyama T, Niiyama T, Ajiki K. et al. Appropriate drug dosing based on renal function using a decision support system of prescription order entry - display of the proper dosage and dose check -. J Jpn Soc Hosp Pharm 2016; 52 (08) 1013-1017
- 18 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 (06) 903-914
- 19 Garg AX, Adhikari NK, McDonald H. et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA 2005; 293 (10) 1223-1238
- 20 Hunt DL, Haynes RB, Hanna SE, Smith K. Effects of computer-based clinical decision support systems on physician performance and patient outcomes: a systematic review. JAMA 1998; 280 (15) 1339-1346
- 21 Schedlbauer A, Prasad V, Mulvaney C. et al. What evidence supports the use of computerized alerts and prompts to improve clinicians' prescribing behavior?. J Am Med Inform Assoc 2009; 16 (04) 531-538
- 22 Walton R, Dovey S, Harvey E, Freemantle N. Computer support for determining drug dose: systematic review and meta-analysis. BMJ 1999; 318 (7189): 984-990
- 23 Sakuma M, Ida H, Nakamura T. et al. Adverse drug events and medication errors in Japanese paediatric inpatients: a retrospective cohort study. BMJ Qual Saf 2014; 23 (10) 830-837
- 24 Ohta Y, Sakuma M, Koike K, Bates DW, Morimoto T. Influence of adverse drug events on morbidity and mortality in intensive care units: the JADE study. Int J Qual Health Care 2014; 26 (06) 573-578
- 25 Ayani N, Sakuma M, Morimoto T. et al. The epidemiology of adverse drug events and medication errors among psychiatric inpatients in Japan: the JADE study. BMC Psychiatry 2016; 16: 303
- 26 Japan nephrology society. [Special issue: Clinical practice guidebook for diagnosis and treatment of chronic kidney disease 2012] Nippon Jinzo Gakkai Shi 2012; 54 (08) 1034-1191
- 27 Niiyama T, Yokote K, Moriyama F. et al. Approaches to appropriate use of injectable antimicrobial agents and changes in antimicrobial susceptibility of pseudomonαs aeruginosa. J Jpn Soc Hosp Pharm 2014; 50 (07) 877-881
- 28 Matsuo S, Imai E, Horio M. et al; Collaborators developing the Japanese equation for estimated GFR. Revised equations for estimated GFR from serum creatinine in Japan. Am J Kidney Dis 2009; 53 (06) 982-992
- 29 Takikawa H, Onji M, Takamori Y. et al. Proposal of diagnostic criteria of drug induced hepatic injury in DDW-J2004. Kanzo 2005; 46 (02) 85-90
- 30 Kwo PY, Cohen SM, Lim JK. ACG clinical guideline: evaluation of abnormal liver chemistries. Am J Gastroenterol 2017; 112 (01) 18-35
- 31 Kidney Disease: Improving Global Outcomes. Chapter 1: Definition and classification of CKD. Kidney Int Suppl (2011) 2013; 3 (01) 19-62
- 32 Vogel EA, Billups SJ, Herner SJ, Delate T. Prescriber-Based Clinical Decision Support Systems. Renal Drug Dosing. Effectiveness of Outpatient Pharmacist-Based vs. Appl Clin Inform 2016; 7 (03) 731-744