Research Article of International Journal of Hospital Pharmacy
Assessing the strengths and weaknesses of a computer assisted medication review in hospitalized patient
Kim P.G.M. Hurkens1, Carlota Mestres-Gonzalvo2, Hugo A.J.M. de Wit2, Rob Janknegt2, Frans Verhey3, Jos M.G.A. Schols 4,6, Fabienne Magdelijns 5, Coen D.A. Stehouwer5,6, Bjorn Winkens 6, 7, Wubbo Mulder5 and P. Hugo M. van der Kuy2
1Department of Internal Medicine, section of Geriatric Medicine, Zuyderland Medical Centre, PO box 5500, Sittard-Geleen-Heerlen, the Netherlands;
2Department of Clinical Pharmacy and Toxicology, Zuyderland Medical Centre, PO box 5500, Sittard-Geleen-Heerlen, the Netherlands;
3Alzheimer Centre Limburg, School of Mental Health and Neuroscience, Maastricht University Medical Centre, PO box 5800, Maastricht, the Netherlands;
4Department of Family Medicine and Department Health Services Research, Maastricht University Medical Centre, PO box 616, 6200 MD Maastricht, the Netherlands;
5Department of Internal Medicine, Maastricht University Medical Centre, PO box 5800, Maastricht, the Netherlands;
6School for Public Health and Primary Care (CAPHRI), Maastricht University Medical Centre, PO box 616, 6200 MD Maastricht, the Netherlands;
7Department of Methodology and Statistics, Maastricht University Medical Centre, PO box 616, 6200 MD Maastricht, the Netherlands.
Introduction Medication reviews are an essential part of daily routine at a hospital ward but are prone to mistakes. With this study we want to assess the strengths and weaknesses of a Clinical Decision Support System (CDSS) and evaluate the additional value on the reduction of medication errors compared with manual medication reviews.
Materials and Methods We gathered all remarks related to (potential) errors in the current medication regime (notifications) regarding medication errors for 332 patients from 12 grand rounds of the internal medicine ward and orthopedic ward at the Maastricht University Medical Centre during four months. Simultaneously, we electronically extracted data regarding the patient’s medication list, laboratory data and patient characteristics and entered these data into our CDSS.
Results and Discussion One hundred thirty-eight notifications were made during grand rounds. One-hundred and seventy-nine relevant alerts were reported by the CDSS. Only three of the relevant notifications were reported by both. Overall, errors regarding indication without medication and medication without indication were most frequently noticed during grand rounds and contraindications or side effects were most frequently noticed by the CDSS. The CDSS may be a relevant addition to the manual performed medication reviews in the hospital. The strength of the present CDSS lies in the detection of errors regarding contraindications and side effects. Future developments include optimizing the cut off values at which the CDSS should provide an alert is an important next step in improving the CDSS. Additionally, in order to increase notifications about indication without medication and medication without indication, the medical history should be incorporated into the CDSS. Finally, relevance on patient outcome should be determined.
Keywords: Clinical decision support system, clinical rules, medication review, medication safety, polypharmacy
How to cite this article:
Hurkens et al.,. Assessing the strengths and weaknesses of a computer assisted medication review in hospitalized patients. International Journal of Hospital Pharmacy, 2017,2:6. DOI: 10.28933/IJHP-2017-10-0101
1. Leendertse AJ, Egberts AC, Stoker LJ, van den Bemt PM: Frequency of and risk factors for preventable medication-related hospital admissions in the Netherlands. Arch Intern Med 2008, 168(17):1890-1896.
2. Mannesse CK, Derkx FH, de Ridder MA, Man in ‘t Veld AJ, van der Cammen TJ: Contribution of adverse drug reactions to hospital admission of older patients. Age and ageing 2000, 29(1):35-39.
3. Bradley M, Motterline N, Padmanabhan S, Cahir C, Williams T, Huges C: Potentially inappropriate prescribing among older people in the United Kingdom. BMC Geriatrics 2014, 14(72).
4. Fialova D, Onder G: Medication erros in elderly people: contributing factors and future perspectives. British Journal of Clinical Pharmacology 2009, 67(6):641-645.
5. Classen D, Resar R, Griffin F, Federico F, Frankel T, Kimmel N, Whittington J, Frankel A, Seger A, James B: Global Trigger Tool shows that adverse events in hospitals may be ten times greater than previosly measured. Health Affairs 2011, 30(4).
6. Langelaan M, de Bruijne M, Baines R, Broekens M, Hammink K, Schilp J, Verweij L, Asscheman H, Wagner C: Monitor Zorggerelateerde Schade 2011/2012, dossieronderzoek in Nederlandse ziekenhuizen. In.: EMGO+ Instituut Nederlands Instituut voor onderzoek van de gezondheidszorg; 2013.
7. Classen DC, Pestotnik SL, Evans RS, Lloyd JF, Burke JP: Adverse drug events in hospitalized patients. Excess length of stay, extra costs, and attributable mortality. JAMA 1997, 277(4):301-306.
8. Damen NL, Baines R, Wagner C, Langelaan M: Medication-related adverse events during hospitalization: a retrospective patient record review study in The Netherlands. Pharmacoepidemiol Drug Saf 2017, 26(1):32-39.
9. Aljadhey H, Mahmoud MA, Mayet A, Alshaikh M, Ahmed Y, Murray MD, Bates DW: Incidence of adverse drug events in an academic hospital: a prospective cohort study. Int J Qual Health Care 2013, 25(6):648-655.
10. Blenkinsopp A, Bond C, Raynor D: Medication Reviews. 2012 2012, 74(4):573-580.
11. Hurkens K, Mestres-Gonzalvo C, de Wit H, van der Kuy H, Janknegt R, Verhey F, Schols J, Stehouwer C, Winkens B, Mulder W: Usually available clinical and laboratory data are insufficient for a valid medication review: a crossover study. Journal of Nutrition, Health and Aging 2015 (in press).
12. Hurkens K, Mestres-Gonzalvo C, de Wit H, van der Kuy H, Janknegt R, Verhey F, Schols J, Stolk L, Stehouwer C, Mulder W: A Survey on Medication Reviews in Older Patients: Substantial Variation in Daily Practice. Gerontology & Geriatric Research 2013, 2(4).
13. Jaspers MW, Smeulers M, Vermeulen H, Peute LW: Effects of clinical decision-support systems on practitioner performance and patient outcomes: a synthesis of high-quality systematic review findings. J Am Med Inform Assoc 2011, 18(3):327-334.
14. Garg AX, Adhikari NK, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J, Sam J, Haynes RB: Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA 2005, 293(10):1223-1238.
15. Shiffman RN, Liaw Y, Brandt CA, Corb GJ: Computer-based guideline implementation systems: a systematic review of functionality and effectiveness. J Am Med Inform Assoc 1999, 6(2):104-114.
16. Kilsdonk E, Peute L, Knijnenburg S, Jaspers M: Factors known to influence acceptance of clinical decision support systems. Studies in Health Technology and Informatics 2011, 169.
17. de Wit H, Mestres Gonzalvo C, Hurkens K, Mulder W, Janknegt R, Verhey F, Schols J, van der Kuy P: Development of a computer system to support medication reviews in nursing homes. International Journal Clinical Pharmacology 2013, 36(2):220-221.
18. de Wit H, Mestres Gonzalvo C, Cardenas J, Derijks H, Janknegt R, van der Kuy P, Winkens B, Schols J: Evaluation of clinical rules in a standalone pharmacy based clinical decision support system for hospitalized and nursing home patients. International Journal of Medical Informatics 2015, 84(6):396-405.
19. de Wit H, Hurkens K, Mestres Gonzalvo C, Smid M, Sipers W, Winkens B, Mulder W, Janknegt R, Verhey F, van der Kuy P et al: The support of medication reviews in hospitalised patients using a clinical decision support system. SpringerPlus 2016, 5(871).
20. KNMG: Richtlijn elektronisch voorschrijven. In.; 2013.
21. de Wit HA, Mestres Gonzalvo C, Hurkens KP, Mulder WJ, Janknegt R, Verhey FR, Schols JM, van der Kuy PH: Development of a computer system to support medication reviews in nursing homes. Int J Clin Pharm 2013, 35(5):668-672.
22. Corp I: IBM SPSS Statistics for Windows. Released 2013.
23. Flynn N, Dawnay A: A simple electronic alert for acute kidney injury. Ann Clin Biochem 2015, 52(Pt 2):206-212.
24. Seidling HM, Klein U, Schaier M, Czock D, Theile D, Pruszydlo MG, Kaltschmidt J, Mikus G, Haefeli WE: What, if all alerts were specific – estimating the potential impact on drug interaction alert burden. Int J Med Inform 2014, 83(4):285-291.
25. Carspecken CW, Sharek PJ, Longhurst C, Pageler NM: A clinical case of electronic health record drug alert fatigue: consequences for patient outcome. Pediatrics 2013, 131(6):e1970-1973.
26. van der Sijs H, Aarts J, Vulto A, Berg M: Overriding of drug safety alerts in computerized physician order entry. J Am Med Inform Assoc 2006, 13(2):138-147.
27. Hsieh TC, Kuperman GJ, Jaggi T, Hojnowski-Diaz P, Fiskio J, Williams DH, Bates DW, Gandhi TK: Characteristics and consequences of drug allergy alert overrides in a computerized physician order entry system. J Am Med Inform Assoc 2004, 11(6):482-491.
28. Pearson SA, Moxey A, Robertson J, Hains I, Williamson M, Reeve J, Newby D: Do computerised clinical decision support systems for prescribing change practice? A systematic review of the literature (1990-2007). BMC Health Serv Res 2009, 9:154.
29. Moja L, Kwag KH, Lytras T, Bertizzolo L, Brandt L, Pecoraro V, Rigon G, Vaona A, Ruggiero F, Mangia M et al: Effectiveness of computerized decision support systems linked to electronic health records: a systematic review and meta-analysis. Am J Public Health 2014, 104(12):e12-22.
30. Helmons PJ, Suijkerbuijk BO, Nannan Panday PV, Kosterink JG: Drug-drug interaction checking assisted by clinical decision support: a return on investment analysis. J Am Med Inform Assoc 2015, 22(4):764-772.
31. Khajouei R, Jaspers MW: The impact of CPOE medication systems’ design aspects on usability, workflow and medication orders: a systematic review. Methods Inf Med 2010, 49(1):3-19.
32. Liu JL, Wyatt JC, Deeks JJ, Clamp S, Keen J, Verde P, Ohmann C, Wellwood J, Dawes M, Altman DG: Systematic reviews of clinical decision tools for acute abdominal pain. Health Technol Assess 2006, 10(47):1-167, iii-iv.
33. Cresswell K, Majeed A, Bates DW, Sheikh A: Computerised decision support systems for healthcare professionals: an interpretative review. Inform Prim Care 2012, 20(2):115-128.
34. Hamm CW, Bassand JP, Agewall S, Bax J, Boersma E, Bueno H, Caso P, Dudek D, Gielen S, Huber K et al: ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation: The Task Force for the management of acute coronary syndromes (ACS) in patients presenting without persistent ST-segment elevation of the European Society of Cardiology (ESC). Eur Heart J 2011, 32(23):2999-3054.
35. Barkun AN, Bardou M, Kuipers EJ, Sung J, Hunt RH, Martel M, Sinclair P, International Consensus Upper Gastrointestinal Bleeding Conference G: International consensus recommendations on the management of patients with nonvariceal upper gastrointestinal bleeding. Ann Intern Med 2010, 152(2):101-113.
36. Bhatt DL, Scheiman J, Abraham NS, Antman EM, Chan FK, Furberg CD, Johnson DA, Mahaffey KW, Quigley EM, Harrington RA et al: ACCF/ACG/AHA 2008 expert consensus document on reducing the gastrointestinal risks of antiplatelet therapy and NSAID use: a report of the American College of Cardiology Foundation Task Force on Clinical Expert Consensus Documents. J Am Coll Cardiol 2008, 52(18):1502-1517.
37. Ojeleye O, Avery A, Gupta V, Boyd M: The evidence for the effectiveness of safety alerts in electronic patient medication record systems at the point of pharmacy order entry: a systematic review. BMC Med Inform Decis Mak 2013, 13:69.
This work and its PDF file(s) are licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.