{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T06:08:30Z","timestamp":1774332510498,"version":"3.50.1"},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,5,31]],"date-time":"2022-05-31T00:00:00Z","timestamp":1653955200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,5,31]],"date-time":"2022-05-31T00:00:00Z","timestamp":1653955200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Inform Decis Mak"],"published-print":{"date-parts":[[2022,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Adverse drug events (ADEs) can be prevented by deploying clinical decision support systems (CDSS) that directly assist physicians, via computerized order entry systems, and clinical pharmacists performing medication reviews as part of medical rounds. However, physicians using CDSS are known to be exposed to the alert-fatigue phenomenon. Our study aimed to assess the performance of PharmaCheck\u2014a CDSS to help clinical pharmacists detect high-risk situations with the potential to lead to ADEs\u2014and its impact on clinical pharmacists\u2019 activities.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>Twenty clinical rules, divided into four risk classes, were set for the daily screening of high-risk situations in the electronic health records of patients admitted to our General Internal Medicine Department. Alerts to clinical pharmacists encouraged them to telephone prescribers and suggest any necessary treatment adjustments. PharmaCheck\u2019s performance was assessed using the intervention\u2019s positive predictive value (PPV), which characterizes the proportion of interventions for each alert triggered. PharmaCheck\u2019s impact was assessed by considering clinical pharmacists as a filter for ruling out futile alerts and by comparing the final clinical PPV with a pharmacist (the proportion of interventions that led to a change in the medical regimen) to the final clinical PPV without a pharmacist.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>Over 132\u00a0days, 447 alerts were triggered for 383 patients, leading to 90 interventions (overall intervention PPV\u2009=\u200920.1%). By risk class, intervention PPVs made up 26.9% (n\u2009=\u200965\/242) of abnormal laboratory value alerts, 3.1% (4\/127) of alerts for contraindicated medications or medications to be used with caution, 28.2% (20\/71) of drug\u2013drug interaction alerts, and 14.3% (1\/7) of inadequate mode of administration alerts. Clinical PPVs reached 71.0% (64\/90) when pharmacists filtered alerts and 14% (64\/242) if they were not doing it.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>PharmaCheck enabled clinical pharmacists to improve their traditional processes and broaden their coverage by focusing on 20 high-risk situations. Alert management by pharmacists seemed to be a more effective way of preventing risky situations and alert-fatigue than a model addressing alerts to physicians exclusively. Some fine-tuning could enhance PharmaCheck's performance by considering the information quality of triggers, the variability of clinical settings, and the fact that some prescription processes are already highly secured.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12911-022-01885-8","type":"journal-article","created":{"date-parts":[[2022,5,31]],"date-time":"2022-05-31T17:03:14Z","timestamp":1654016594000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Development and assessment of PharmaCheck: an electronic screening tool for the prevention of twenty major adverse drug events"],"prefix":"10.1186","volume":"22","author":[{"given":"Christian","family":"Skalafouris","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jean-Luc","family":"Reny","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J\u00e9r\u00f4me","family":"Stirnemann","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Olivier","family":"Grosgurin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fran\u00e7ois","family":"Eggimann","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Damien","family":"Grauser","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel","family":"Teixeira","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Megane","family":"Jermini","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christel","family":"Bruggmann","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pascal","family":"Bonnabry","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bertrand","family":"Guignard","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,5,31]]},"reference":[{"key":"1885_CR1","doi-asserted-by":"publisher","first-page":"306","DOI":"10.1136\/qshc.2004.010611","volume":"13","author":"T Morimoto","year":"2004","unstructured":"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;13:306\u201314.","journal-title":"Qual Saf Health Care"},{"issue":"Suppl 3","key":"1885_CR2","doi-asserted-by":"publisher","first-page":"S360","DOI":"10.1590\/S0102-311X2009001500003","volume":"25","author":"FG Cano","year":"2009","unstructured":"Cano FG, Rozenfeld S. Adverse drug events in hospitals: a systematic review. Cad Saude Publica. 2009;25(Suppl 3):S360-372.","journal-title":"Cad Saude Publica"},{"key":"1885_CR3","doi-asserted-by":"crossref","unstructured":"Batel Marques F, Penedones A, Mendes D, Alves C. A systematic review of observational studies evaluating costs of adverse drug reactions. Clinicoecon Outcomes Res. 2016 [cited 2021 May 6];8:413\u201326. Available from: https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC5003513\/","DOI":"10.2147\/CEOR.S115689"},{"key":"1885_CR4","doi-asserted-by":"crossref","unstructured":"Leape LL, Brennan TA, Laird N, Lawthers AG, Localio AR, Barnes BA, et al. The nature of adverse events in hospitalized patients. Results of the Harvard Medical Practice Study II. N Engl J Med. 1991;324:377\u201384.","DOI":"10.1056\/NEJM199102073240605"},{"key":"1885_CR5","unstructured":"Medication Errors and Adverse Drug Events. [cited 2021 May 6]; Available from: https:\/\/psnet.ahrq.gov\/primer\/medication-errors-and-adverse-drug-events"},{"key":"1885_CR6","doi-asserted-by":"crossref","unstructured":"Wolfe D, Yazdi F, Kanji S, Burry L, Beck A, Butler C, et al. Incidence, causes, and consequences of preventable adverse drug reactions occurring in inpatients: A systematic review of systematic reviews. PLoS One. 2018 [cited 2021 May 6];13. Available from: https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC6181371\/","DOI":"10.1371\/journal.pone.0205426"},{"key":"1885_CR7","unstructured":"Preventing Medication Errors: Quality Chasm Series. [cited 2021 May 6]; Available from: https:\/\/psnet.ahrq.gov\/issue\/preventing-medication-errors-quality-chasm-series"},{"key":"1885_CR8","doi-asserted-by":"crossref","unstructured":"Hakkarainen KM, Hedna K, Petzold M, H\u00e4gg S. Percentage of Patients with Preventable Adverse Drug Reactions and Preventability of Adverse Drug Reactions\u00a0\u2013\u00a0A Meta-Analysis. PLoS One. 2012 [cited 2021 Oct 27];7:e33236. Available from: https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC3305295\/","DOI":"10.1371\/journal.pone.0033236"},{"key":"1885_CR9","doi-asserted-by":"crossref","unstructured":"Agrawal A. Medication errors: prevention using information technology systems. Br J Clin Pharmacol. 2009 [cited 2021 May 6];67:681\u20136. Available from: https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC2723209\/","DOI":"10.1111\/j.1365-2125.2009.03427.x"},{"key":"1885_CR10","doi-asserted-by":"crossref","unstructured":"Beeler PE, Bates DW, Hug BL. Clinical decision support systems. Swiss Medical Weekly. 2014 [cited 2021 May 6];144. Available from: https:\/\/smw.ch\/article\/doi\/smw.2014.14073","DOI":"10.4414\/smw.2014.14073"},{"key":"1885_CR11","first-page":"923","volume":"192","author":"SP Slight","year":"2013","unstructured":"Slight SP, Nanji KC, Seger DL, Cho I, Volk LA, Bates DW. Overrides of clinical decision support alerts in primary care clinics. Stud Health Technol Inform. 2013;192:923.","journal-title":"Stud Health Technol Inform"},{"key":"1885_CR12","doi-asserted-by":"publisher","unstructured":"Hammar T, Lidstr\u00f6m B, Petersson G, Gustafson Y, Eiermann B. Potential drug-related problems detected by electronic expert support system: physicians\u2019 views on clinical relevance. Int J Clin Pharm. 2015 [cited 2021 May 7];37:941\u20138. Available from: https:\/\/doi.org\/10.1007\/s11096-015-0146-8","DOI":"10.1007\/s11096-015-0146-8"},{"key":"1885_CR13","doi-asserted-by":"publisher","first-page":"1465","DOI":"10.1001\/archinternmed.2009.252","volume":"169","author":"SN Weingart","year":"2009","unstructured":"Weingart SN, Simchowitz B, Padolsky H, Isaac T, Seger AC, Massagli M, et al. An empirical model to estimate the potential impact of medication safety alerts on patient safety, health care utilization, and cost in ambulatory care. Arch Intern Med. 2009;169:1465\u201373.","journal-title":"Arch Intern Med"},{"key":"1885_CR14","doi-asserted-by":"crossref","unstructured":"Ancker JS, Edwards A, Nosal S, Hauser D, Mauer E, Kaushal R. Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system. BMC Med Inform Decis Mak. 2017 [cited 2021 May 7];17. Available from: https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC5387195\/","DOI":"10.1186\/s12911-017-0430-8"},{"key":"1885_CR15","doi-asserted-by":"publisher","first-page":"955","DOI":"10.1001\/archinte.166.9.955","volume":"166","author":"PJ Kaboli","year":"2006","unstructured":"Kaboli PJ, Hoth AB, McClimon BJ, Schnipper JL. Clinical pharmacists and inpatient medical care: a systematic review. Arch Intern Med. 2006;166:955\u201364.","journal-title":"Arch Intern Med"},{"key":"1885_CR16","doi-asserted-by":"publisher","first-page":"687","DOI":"10.1007\/s11096-015-0137-9","volume":"37","author":"I Rotta","year":"2015","unstructured":"Rotta I, Salgado TM, Silva ML, Correr CJ, Fernandez-Llimos F. Effectiveness of clinical pharmacy services: an overview of systematic reviews (2000\u20132010). Int J Clin Pharm. 2015;37:687\u201397.","journal-title":"Int J Clin Pharm"},{"key":"1885_CR17","doi-asserted-by":"crossref","unstructured":"Frontini R, Miharija-Gala T, Sykora J. EAHP survey 2010 on hospital pharmacy in Europe: parts 4 and 5. Clinical services and patient safety. European Journal of Hospital Pharmacy: Science and Practice. 2013 [cited 2021 May 7];20:69\u201373. Available from: https:\/\/ejhp.bmj.com\/content\/20\/2\/69","DOI":"10.1136\/ejhpharm-2013-000285"},{"key":"1885_CR18","unstructured":"Messerli M, Maes KA, Hersberger KE, Lampert ML. Mapping clinical pharmacy practice in Swiss hospitals: a cross-sectional study. Eur J Hosp Pharm. 2016 [cited 2018 Jul 19];ejhpharm-2015\u2013000868. Available from: https:\/\/ejhp.bmj.com\/content\/early\/2016\/02\/26\/ejhpharm-2015-000868"},{"key":"1885_CR19","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1016\/j.ejim.2015.05.012","volume":"26","author":"B Guignard","year":"2015","unstructured":"Guignard B, Bonnabry P, Perrier A, Dayer P, Desmeules J, Samer CF. Drug-related problems identification in general internal medicine: The impact and role of the clinical pharmacist and pharmacologist. Eur J Intern Med. 2015;26:399\u2013406.","journal-title":"Eur J Intern Med"},{"key":"1885_CR20","unstructured":"The most popular database for modern apps. MongoDB. [cited 2021 Jan 7]. Available from: https:\/\/www.mongodb.com\/3"},{"key":"1885_CR21","unstructured":"The Professional Client, IDE & GUI for MongoDB. Studio 3T. [cited 2021 Jan 7]. Available from: https:\/\/studio3t.com\/"},{"key":"1885_CR22","doi-asserted-by":"publisher","unstructured":"Berner ES, La Lande TJ. Overview of Clinical Decision Support Systems. In: Berner ES, editor. Clinical Decision Support Systems: Theory and Practice. Cham: Springer International Publishing; 2016 [cited 2021 Apr 15]. p. 1\u201317. Available from: https:\/\/doi.org\/10.1007\/978-3-319-31913-1_1","DOI":"10.1007\/978-3-319-31913-1_1"},{"key":"1885_CR23","unstructured":"NHS England. Never events. [cited 2021 Jan 7]. Available from: https:\/\/www.england.nhs.uk\/publication\/never-events\/"},{"key":"1885_CR24","unstructured":"Institute for safe Medication Practices. ISMP\u2019s List of High-Alert Medications. ISMP; Available from: http:\/\/www.ismp.org\/tools"},{"key":"1885_CR25","doi-asserted-by":"crossref","unstructured":"Luyet A-V, Gunten VJ, Turini P, Beney J. NP-011 Mediscreen: implementation of a tool for detecting patients at risk of adverse drug events via the electronic medical record. Eur J Hosp Pharm. 2019 [cited 2021 Jan 7];26:A295\u2013A295. Available from: https:\/\/ejhp.bmj.com\/content\/26\/Suppl_1\/A295.1","DOI":"10.1136\/ejhpharm-2019-eahpconf.636"},{"key":"1885_CR26","doi-asserted-by":"crossref","unstructured":"Lavan AH, Gallagher P. Predicting risk of adverse drug reactions in older adults. Ther Adv Drug Saf. 2016 [cited 2021 Apr 9];7:11\u201322. Available from: https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC4716390\/","DOI":"10.1177\/2042098615615472"},{"key":"1885_CR27","doi-asserted-by":"publisher","first-page":"923","DOI":"10.1002\/pds.3634","volume":"23","author":"O Urbina","year":"2014","unstructured":"Urbina O, Ferr\u00e1ndez O, Grau S, Luque S, Mojal S, Marin-Casino M, et al. Design of a score to identify hospitalized patients at risk of drug-related problems. Pharmacoepidemiol Drug Saf. 2014;23:923\u201332.","journal-title":"Pharmacoepidemiol Drug Saf"},{"key":"1885_CR28","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1056\/NEJM198908033210507","volume":"321","author":"SC Montamat","year":"1989","unstructured":"Montamat SC, Cusack BJ, Vestal RE. Management of drug therapy in the elderly. N Engl J Med. 1989;321:303\u20139.","journal-title":"N Engl J Med"},{"key":"1885_CR29","doi-asserted-by":"crossref","unstructured":"Jha AK, Laguette J, Seger A, Bates DW. Can Surveillance Systems Identify and Avert Adverse Drug Events? A Prospective Evaluation of a Commercial Application. J Am Med Inform Assoc. 2008 [cited 2020 Aug 6];15:647\u201353. Available from: https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC2528042\/","DOI":"10.1197\/jamia.M2634"},{"key":"1885_CR30","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1186\/s12911-019-0748-5","volume":"19","author":"C Quintens","year":"2019","unstructured":"Quintens C, De Rijdt T, Van Nieuwenhuyse T, Simoens S, Peetermans WE, Van den Bosch B, et al. Development and implementation of \u201cCheck of Medication Appropriateness\u201d (CMA): advanced pharmacotherapy-related clinical rules to support medication surveillance. BMC Med Inform Decis Mak. 2019;19:29.","journal-title":"BMC Med Inform Decis Mak"},{"key":"1885_CR31","doi-asserted-by":"crossref","unstructured":"Rommers MK, Zwaveling J, Guchelaar H-J, Teepe-Twiss IM. Evaluation of rule effectiveness and positive predictive value of clinical rules in a Dutch clinical decision support system in daily hospital pharmacy practice. Artif Intell Med. 2013 [cited 2020 Aug 6];59:15\u201321. Available from: http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0933365713000535","DOI":"10.1016\/j.artmed.2013.04.001"},{"key":"1885_CR32","doi-asserted-by":"crossref","unstructured":"Ib\u00e1\u00f1ez-Garcia S, Rodriguez-Gonzalez C, Escudero-Vilaplana V, Martin-Barbero ML, Marzal-Alfaro B, De la Rosa-Trivi\u00f1o JL, et al. Development and Evaluation of a Clinical Decision Support System to Improve Medication Safety. Appl Clin Inform. 2019 [cited 2021 Apr 8];10:513\u201320. Available from: https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC6637024\/","DOI":"10.1055\/s-0039-1693426"},{"key":"1885_CR33","doi-asserted-by":"publisher","first-page":"658","DOI":"10.1592\/phco.31.7.658","volume":"31","author":"SM Wilhelm","year":"2011","unstructured":"Wilhelm SM, Kale-Pradhan PB. Estimating creatinine clearance: a meta-analysis. Pharmacotherapy. 2011;31:658\u201364.","journal-title":"Pharmacotherapy"},{"key":"1885_CR34","doi-asserted-by":"crossref","unstructured":"Bouquegneau A, Vidal\u2010Petiot E, Moranne O, Mariat C, Boffa J, Vrtovsnik F, et al. Creatinine\u2010based equations for the adjustment of drug dosage in an obese population. Br J Clin Pharmacol. 2016 [cited 2021 Apr 16];81:349\u201361. Available from: https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC4833161\/","DOI":"10.1111\/bcp.12817"},{"key":"1885_CR35","doi-asserted-by":"crossref","unstructured":"Sutton RT, Pincock D, Baumgart DC, Sadowski DC, Fedorak RN, Kroeker KI. An overview of clinical decision support systems: benefits, risks, and strategies for success. npj Digital Med. 2020 [cited 2021 Apr 15];3:1\u201310. Available from: https:\/\/www.nature.com\/articles\/s41746-020-0221-y","DOI":"10.1038\/s41746-020-0221-y"},{"key":"1885_CR36","unstructured":"Electronic Health Record Problem Lists: Accurate Enough for Risk Adjustment?. AJMC. [cited 2021 Apr 16]. Available from: https:\/\/www.ajmc.com\/view\/electronic-health-record-problem-lists-accurate-enough-for-risk-adjustment"},{"key":"1885_CR37","unstructured":"One list to rule them all and many semantics to bind them: Building a shared, scalable and sustainable source for the problem oriented medical record. JMIR Preprints. [cited 2021 Apr 18]. Available from: https:\/\/preprints.jmir.org\/preprint\/29174"},{"key":"1885_CR38","doi-asserted-by":"crossref","unstructured":"Carli D, Fahrni G, Bonnabry P, Lovis C. Quality of Decision Support in Computerized Provider Order Entry: Systematic Literature Review. JMIR Med Inform. 2018 [cited 2021 Feb 11];6:e7170. Available from: https:\/\/medinform.jmir.org\/2018\/1\/e3","DOI":"10.2196\/medinform.7170"},{"key":"1885_CR39","doi-asserted-by":"crossref","unstructured":"Wasylewicz ATM, Scheepers-Hoeks AMJW. Clinical Decision Support Systems. In: Kubben P, Dumontier M, Dekker A, editors. Fundamentals of Clinical Data Science. Cham (CH): Springer; 2019 [cited 2021 Apr 22]. Available from: http:\/\/www.ncbi.nlm.nih.gov\/books\/NBK543516\/","DOI":"10.1007\/978-3-319-99713-1_11"},{"key":"1885_CR40","doi-asserted-by":"crossref","unstructured":"DeFronzo R, Fleming GA, Chen K, Bicsak TA. Metformin-associated lactic acidosis: Current perspectives on causes and risk. Metabolism. 2016 [cited 2021 Apr 22];65:20\u20139. Available from: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0026049515003066","DOI":"10.1016\/j.metabol.2015.10.014"},{"key":"1885_CR41","doi-asserted-by":"crossref","unstructured":"Mlad\u011bnka P, Applov\u00e1 L, Pato\u010dka J, Costa VM, Remiao F, Pourov\u00e1 J, et al. Comprehensive review of cardiovascular toxicity of drugs and related agents. Med Res Rev. 2018 [cited 2021 Apr 22];38:1332\u2013403. Available from: https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC6033155\/","DOI":"10.1002\/med.21476"},{"key":"1885_CR42","doi-asserted-by":"crossref","unstructured":"Miller K, Mosby D, Capan M, Kowalski R, Ratwani R, Noaiseh Y, et al. Interface, information, interaction: a narrative review of design and functional requirements for clinical decision support. J Am Med Inform Assoc. 2017 [cited 2021 Apr 8];25:585\u201392. Available from: https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC6018977\/","DOI":"10.1093\/jamia\/ocx118"},{"key":"1885_CR43","doi-asserted-by":"crossref","unstructured":"Wright A, Sittig DF, Ash JS, Feblowitz J, Meltzer S, McMullen C, et al. Development and evaluation of a comprehensive clinical decision support taxonomy: comparison of front-end tools in commercial and internally developed electronic health record systems. J Am Med Inform Assoc. 2011 [cited 2021 Apr 23];18:232\u201342. Available from: https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC3078666\/","DOI":"10.1136\/amiajnl-2011-000113"},{"key":"1885_CR44","unstructured":"Netgen. Introduction de l\u2019ac\u00e9nocoumarol \u00e0 l\u2019aide d\u2019un algorithme de prescription. Revue M\u00e9dicale Suisse. [cited 2021 Apr 22]. Available from: https:\/\/www.revmed.ch\/RMS\/2010\/RMS-235\/Introduction-de-l-acenocoumarol-a-l-aide-d-un-algorithme-de-prescription"},{"key":"1885_CR45","doi-asserted-by":"publisher","unstructured":"Lagreula J, Maes F, Wouters D, Quennery S, Dalleur O. Optimizing pharmacists\u2019 detection of prescribing errors: Comparison of on-ward and central pharmacy services. J Clin Pharm Ther. [cited 2021 Apr 23];n\/a. Available from: https:\/\/onlinelibrary.wiley.com\/doi\/abs\/https:\/\/doi.org\/10.1111\/jcpt.13339","DOI":"10.1111\/jcpt.13339"},{"key":"1885_CR46","doi-asserted-by":"publisher","unstructured":"Bedouch P, Tessier A, Baudrant M, Labarere J, Foroni L, Calop J, et al. Computerized physician order entry system combined with on-ward pharmacist: analysis of pharmacists\u2019 interventions. J Eval Clin Pract. 2012 [cited 2021 Apr 23];18:911\u20138. Available from: https:\/\/onlinelibrary.wiley.com\/doi\/abs\/https:\/\/doi.org\/10.1111\/j.1365-2753.2011.01704.x","DOI":"10.1111\/j.1365-2753.2011.01704.x"},{"key":"1885_CR47","doi-asserted-by":"publisher","unstructured":"Becker ML, Baypinar F, Pereboom M, Lilih S, van der Hoeven RTM, Giezen TJ, et al. The effect of medication related clinical decision support at the time of physician order entry. Int J Clin Pharm. 2021 [cited 2021 Apr 29];43:137\u201343. Available from: https:\/\/doi.org\/10.1007\/s11096-020-01121-1","DOI":"10.1007\/s11096-020-01121-1"},{"key":"1885_CR48","doi-asserted-by":"crossref","unstructured":"Skalafouris C, Samer C, Stirnemann J, Grosgurin O, Eggimann F, Grauser D, et al. Electronic monitoring of potential adverse drug events related to lopinavir\/ritonavir and hydroxychloroquine during the first wave of COVID-19. Eur J Hosp Pharm. 2021;ejhpharm-2020\u2013002667.","DOI":"10.1136\/ejhpharm-2020-002667"},{"key":"1885_CR49","doi-asserted-by":"crossref","unstructured":"Cuvelier E, Robert L, Musy E, Rousseli\u00e8re C, Marcilly R, Gautier S, et al. The clinical pharmacist\u2019s role in enhancing the relevance of a clinical decision support system. Int J Med Inform. 2021 [cited 2021 Nov 29];155:104568. Available from: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1386505621001945","DOI":"10.1016\/j.ijmedinf.2021.104568"},{"key":"1885_CR50","first-page":"640","volume":"281","author":"L Robert","year":"2021","unstructured":"Robert L, Rousseliere C, Beuscart J-B, Gautier S, Chazard E, Decaudin B, et al. Integration of explicit criteria in a clinical decision support system through evaluation of acute kidney injury events. Stud Health Technol Inform. 2021;281:640\u20134.","journal-title":"Stud Health Technol Inform"},{"key":"1885_CR51","unstructured":"Home - MedBase. [cited 2021 Apr 29]. Available from: https:\/\/www.medbase.fi\/en\/"},{"key":"1885_CR52","unstructured":"M\u00e9dicaments: \u00eatre vigilant mais \u00e0 bon escient!. Fondation priv\u00e9e des HUG. [cited 2021 Apr 29]. Available from: https:\/\/www.fondationhug.org\/Medicaments_vigilance"},{"key":"1885_CR53","doi-asserted-by":"crossref","unstructured":"Huibers CJA, Sallevelt BTGM, de Groot DA, Boer MJ, van Campen JPCM, Davids CJ, et al. Conversion of STOPP\/START version 2 into coded algorithms for software implementation: a multidisciplinary consensus procedure. Int J Med Inform. 2019 [cited 2021 Jan 8];125:110\u20137. Available from: http:\/\/www.sciencedirect.com\/science\/article\/pii\/S1386505618308190","DOI":"10.1016\/j.ijmedinf.2018.12.010"},{"key":"1885_CR54","doi-asserted-by":"crossref","unstructured":"Desnoyer A, Blanc A-L, Pourcher V, Besson M, Fonzo-Christe CC, Desmeules JA, et al. PIM-Check: development of an international prescription-screening checklist designed by a Delphi method for internal medicine patients. BMJ Open. 2017 [cited 2018 Jul 5];7:e016070. Available from: https:\/\/archive-ouverte.unige.ch\/unige:98702","DOI":"10.1136\/bmjopen-2017-016070"},{"key":"1885_CR55","unstructured":"La revue Pharma-Flash du service de pharmacologie et toxicologie clinique \u00e0 Gen\u00e8ve aux HUG. [cited 2021 Jan 8]. Available from: https:\/\/www.hug.ch\/pharmacologie-toxicologie-cliniques\/pharma-flash"}],"container-title":["BMC Medical Informatics and Decision Making"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-022-01885-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12911-022-01885-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-022-01885-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,31]],"date-time":"2022-05-31T17:05:46Z","timestamp":1654016746000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcmedinformdecismak.biomedcentral.com\/articles\/10.1186\/s12911-022-01885-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,31]]},"references-count":55,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,12]]}},"alternative-id":["1885"],"URL":"https:\/\/doi.org\/10.1186\/s12911-022-01885-8","relation":{},"ISSN":["1472-6947"],"issn-type":[{"value":"1472-6947","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,31]]},"assertion":[{"value":"15 August 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 May 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 May 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The project was submitted to the Ethics Committee of the Canton of Geneva, Switzerland (Req-2019-01266) that approved experimental protocol, and the need for informed consent was waived as this quality-improvement study was set up as standard practice not falling within the scope of the Swiss law on research on human beings: the project was part quality improvement of care process without the objective of being a scientific research on human diseases or on the structure and functioning of the human body. All methods were performed in accordance with the relevant guidelines and regulations. Clinical pharmacist\u2019s interventions were exclusively dedicated to physicians who finally decided on a prescription change. All patients admitted to the internal medicine department under cover of clinical pharmacy services were eligible as no exclusion criteria was defined. Patients did not provide informed consent as this service was implemented as standard of care.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"All authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"146"}}