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Graafsma J, Murphy RM, van de Garde EMW, Karapinar-Çarkit F, Derijks HJ, Hoge RHL, Klopotowska JE, van den Bemt PMLA. The use of artificial intelligence to optimize medication alerts generated by clinical decision support systems: a scoping review. J Am Med Inform Assoc 2024:ocae076. [PMID: 38641410 DOI: 10.1093/jamia/ocae076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 03/21/2024] [Accepted: 03/28/2024] [Indexed: 04/21/2024] Open
Abstract
OBJECTIVE Current Clinical Decision Support Systems (CDSSs) generate medication alerts that are of limited clinical value, causing alert fatigue. Artificial Intelligence (AI)-based methods may help in optimizing medication alerts. Therefore, we conducted a scoping review on the current state of the use of AI to optimize medication alerts in a hospital setting. Specifically, we aimed to identify the applied AI methods used together with their performance measures and main outcome measures. MATERIALS AND METHODS We searched Medline, Embase, and Cochrane Library database on May 25, 2023 for studies of any quantitative design, in which the use of AI-based methods was investigated to optimize medication alerts generated by CDSSs in a hospital setting. The screening process was supported by ASReview software. RESULTS Out of 5625 citations screened for eligibility, 10 studies were included. Three studies (30%) reported on both statistical performance and clinical outcomes. The most often reported performance measure was positive predictive value ranging from 9% to 100%. Regarding main outcome measures, alerts optimized using AI-based methods resulted in a decreased alert burden, increased identification of inappropriate or atypical prescriptions, and enabled prediction of user responses. In only 2 studies the AI-based alerts were implemented in hospital practice, and none of the studies conducted external validation. DISCUSSION AND CONCLUSION AI-based methods can be used to optimize medication alerts in a hospital setting. However, reporting on models' development and validation should be improved, and external validation and implementation in hospital practice should be encouraged.
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Affiliation(s)
- Jetske Graafsma
- Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, 9713GZ, The Netherlands
| | - Rachel M Murphy
- Department of Medical Informatics Amsterdam UMC, University of Amsterdam, Amsterdam, 1000GG, The Netherlands
- Amsterdam Public Health Institute, Digital Health and Quality of Care, Amsterdam, 1105AZ, The Netherlands
| | - Ewoudt M W van de Garde
- Department of Pharmacy, St Antonius Hospital, Utrecht, 3430AM, The Netherlands
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht University, Utrecht, 3584CS, The Netherlands
| | - Fatma Karapinar-Çarkit
- Department of Clinical Pharmacy and Toxicology, Maastricht University Medical Center, Maastricht, 6229HX, The Netherlands
- Department of Clinical Pharmacy, CARIM, Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, 6229ER, The Netherlands
| | - Hieronymus J Derijks
- Department of Pharmacy, Jeroen Bosch Hospital, Den Bosch, 5200ME, The Netherlands
| | - Rien H L Hoge
- Department of Pharmacy, Wilhelmina Hospital, Assen, 9401RK, The Netherlands
| | - Joanna E Klopotowska
- Department of Medical Informatics Amsterdam UMC, University of Amsterdam, Amsterdam, 1000GG, The Netherlands
- Amsterdam Public Health Institute, Digital Health and Quality of Care, Amsterdam, 1105AZ, The Netherlands
| | - Patricia M L A van den Bemt
- Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, 9713GZ, The Netherlands
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2
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Bakker T, Klopotowska JE, Dongelmans DA, Eslami S, Vermeijden WJ, Hendriks S, Ten Cate J, Karakus A, Purmer IM, van Bree SHW, Spronk PE, Hoeksema M, de Jonge E, de Keizer NF, Abu-Hanna A. The effect of computerised decision support alerts tailored to intensive care on the administration of high-risk drug combinations, and their monitoring: a cluster randomised stepped-wedge trial. Lancet 2024; 403:439-449. [PMID: 38262430 DOI: 10.1016/s0140-6736(23)02465-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 10/27/2023] [Accepted: 11/02/2023] [Indexed: 01/25/2024]
Abstract
BACKGROUND Drug-drug interactions (DDIs) can harm patients admitted to the intensive care unit (ICU). Yet, clinical decision support systems (CDSSs) aimed at helping physicians prevent DDIs are plagued by low-yield alerts, causing alert fatigue and compromising patient safety. The aim of this multicentre study was to evaluate the effect of tailoring potential DDI alerts to the ICU setting on the frequency of administered high-risk drug combinations. METHODS We implemented a cluster randomised stepped-wedge trial in nine ICUs in the Netherlands. Five ICUs already used potential DDI alerts. Patients aged 18 years or older admitted to the ICU with at least two drugs administered were included. Our intervention was an adapted CDSS, only providing alerts for potential DDIs considered as high risk. The intervention was delivered at the ICU level and targeted physicians. We hypothesised that showing only relevant alerts would improve CDSS effectiveness and lead to a decreased number of administered high-risk drug combinations. The order in which the intervention was implemented in the ICUs was randomised by an independent researcher. The primary outcome was the number of administered high-risk drug combinations per 1000 drug administrations per patient and was assessed in all included patients. This trial was registered in the Netherlands Trial Register (identifier NL6762) on Nov 26, 2018, and is now closed. FINDINGS In total, 10 423 patients admitted to the ICU between Sept 1, 2018, and Sept 1, 2019, were assessed and 9887 patients were included. The mean number of administered high-risk drug combinations per 1000 drug administrations per patient was 26·2 (SD 53·4) in the intervention group (n=5534), compared with 35·6 (65·0) in the control group (n=4353). Tailoring potential DDI alerts to the ICU led to a 12% decrease (95% CI 5-18%; p=0·0008) in the number of administered high-risk drug combinations per 1000 drug administrations per patient, after adjusting for clustering and prognostic factors. INTERPRETATION This cluster randomised stepped-wedge trial showed that tailoring potential DDI alerts to the ICU setting significantly reduced the number of administered high-risk drug combinations. Our list of high-risk drug combinations can be used in other ICUs, and our strategy of tailoring alerts based on clinical relevance could be applied to other clinical settings. FUNDING ZonMw.
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Affiliation(s)
- Tinka Bakker
- Department of Medical Informatics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Methodology, Amsterdam Public Health, Amsterdam, Netherlands.
| | - Joanna E Klopotowska
- Department of Medical Informatics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Digital Health, Amsterdam Public Health, Amsterdam, Netherlands
| | - Dave A Dongelmans
- Department of Intensive Care Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Quality of Care, Amsterdam Public Health, Amsterdam, Netherlands
| | - Saeid Eslami
- Department of Medical Informatics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Pharmaceutical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Wytze J Vermeijden
- Department of Intensive Care, Medisch Spectrum Twente, Enschede, Netherlands
| | - Stefaan Hendriks
- Department of Intensive Care, Albert Schweitzer Ziekenhuis, Dordrecht, Netherlands
| | - Julia Ten Cate
- Department of Intensive Care, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Attila Karakus
- Department of Intensive Care Diakonessenhuis Utrecht, Utrecht, Netherlands
| | - Ilse M Purmer
- Department of Intensive Care, Haga Hospital, The Hague, Netherlands
| | | | - Peter E Spronk
- Department of Intensive Care Medicine, Gelre Hospitals, Apeldoorn, Netherlands
| | - Martijn Hoeksema
- Zaans Medisch Centrum, Department of Anesthesiology, Intensive Care and Pain Management, Zaandam, Netherlands
| | - Evert de Jonge
- Department of Intensive Care, Leiden University Medical Center, Leiden, Netherlands
| | - Nicolette F de Keizer
- Department of Medical Informatics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Quality of Care, Amsterdam Public Health, Amsterdam, Netherlands
| | - Ameen Abu-Hanna
- Department of Medical Informatics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Methodology, Amsterdam Public Health, Amsterdam, Netherlands
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3
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Klopotowska JE, Leopold JH, Bakker T, Yasrebi-de Kom I, Engelaer FM, de Jonge E, Haspels-Hogervorst EK, van den Bergh WM, Renes MH, Jong BTD, Kieft H, Wieringa A, Hendriks S, Lau C, van Bree SHW, Lammers HJW, Wierenga PC, Bosman RJ, de Jong VM, Slijkhuis M, Franssen EJF, Vermeijden WJ, Masselink J, Purmer IM, Bosma LE, Hoeksema M, Wesselink E, de Lange DW, de Keizer NF, Dongelmans DA, Abu-Hanna A. Adverse drug events caused by three high-risk drug-drug interactions in patients admitted to intensive care units: A multicentre retrospective observational study. Br J Clin Pharmacol 2024; 90:164-175. [PMID: 37567767 DOI: 10.1111/bcp.15882] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 08/03/2023] [Accepted: 08/05/2023] [Indexed: 08/13/2023] Open
Abstract
AIMS Knowledge about adverse drug events caused by drug-drug interactions (DDI-ADEs) is limited. We aimed to provide detailed insights about DDI-ADEs related to three frequent, high-risk potential DDIs (pDDIs) in the critical care setting: pDDIs with international normalized ratio increase (INR+ ) potential, pDDIs with acute kidney injury (AKI) potential, and pDDIs with QTc prolongation potential. METHODS We extracted routinely collected retrospective data from electronic health records of intensive care units (ICUs) patients (≥18 years), admitted to ten hospitals in the Netherlands between January 2010 and September 2019. We used computerized triggers (e-triggers) to preselect patients with potential DDI-ADEs. Between September 2020 and October 2021, clinical experts conducted a retrospective manual patient chart review on a subset of preselected patients, and assessed causality, severity, preventability, and contribution to ICU length of stay of DDI-ADEs using internationally prevailing standards. RESULTS In total 85 422 patients with ≥1 pDDI were included. Of these patients, 32 820 (38.4%) have been exposed to one of the three pDDIs. In the exposed group, 1141 (3.5%) patients were preselected using e-triggers. Of 237 patients (21%) assessed, 155 (65.4%) experienced an actual DDI-ADE; 52.9% had severity level of serious or higher, 75.5% were preventable, and 19.3% contributed to a longer ICU length of stay. The positive predictive value was the highest for DDI-INR+ e-trigger (0.76), followed by DDI-AKI e-trigger (0.57). CONCLUSION The highly preventable nature and severity of DDI-ADEs, calls for action to optimize ICU patient safety. Use of e-triggers proved to be a promising preselection strategy.
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Affiliation(s)
- Joanna E Klopotowska
- Department of Medical Informatics, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health, Amsterdam, The Netherlands
| | - Jan-Hendrik Leopold
- Department of Medical Informatics, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health, Amsterdam, The Netherlands
| | - Tinka Bakker
- Department of Medical Informatics, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health, Amsterdam, The Netherlands
| | - Izak Yasrebi-de Kom
- Department of Medical Informatics, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health, Amsterdam, The Netherlands
| | - Frouke M Engelaer
- Department of Intensive Care, Leiden University Medical Center, Leiden, The Netherlands
| | - Evert de Jonge
- Department of Intensive Care, Leiden University Medical Center, Leiden, The Netherlands
| | - Esther K Haspels-Hogervorst
- Department of Critical Care, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Walter M van den Bergh
- Department of Critical Care, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Maurits H Renes
- Department of Critical Care, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Bas T de Jong
- Department of Intensive Care, Isala Hospital, Zwolle, The Netherlands
| | - Hans Kieft
- Department of Intensive Care, Isala Hospital, Zwolle, The Netherlands
| | - Andre Wieringa
- Department of Clinical Pharmacy, Isala Hospital, Zwolle, The Netherlands
| | - Stefaan Hendriks
- Department of Intensive Care, Albert Schweitzer Hospital, Dordrecht, The Netherlands
| | - Cedric Lau
- Department of Hospital Pharmacy, Albert Schweitzer Hospital, Dordrecht, The Netherlands
| | - Sjoerd H W van Bree
- Department of Intensive Care, Hospital Gelderse Vallei, Ede, The Netherlands
| | | | - Peter C Wierenga
- Department of Hospital Pharmacy, Hospital Gelderse Vallei, Ede, The Netherlands
| | - Rob J Bosman
- Department of Intensive Care Medicine, OLVG Hospital, Amsterdam, The Netherlands
| | - Vincent M de Jong
- Department of Intensive Care Medicine, OLVG Hospital, Amsterdam, The Netherlands
| | - Mirjam Slijkhuis
- Department of Clinical Pharmacy, OLVG Hospital, Amsterdam, The Netherlands
| | - Eric J F Franssen
- Department of Clinical Pharmacy, OLVG Hospital, Amsterdam, The Netherlands
| | - Wytze J Vermeijden
- Department of Intensive Care, Medisch Spectrum Twente, Enschede, The Netherlands
| | - Joost Masselink
- Department of Hospital Pharmacy, Medisch Spectrum Twente, Enschede, The Netherlands
| | - Ilse M Purmer
- Department of Intensive Care, Haga Hospital, The Hague, The Netherlands
| | - Liesbeth E Bosma
- Department of Hospital Pharmacy, Haga Hospital, The Hague, The Netherlands
| | - Martin Hoeksema
- Department of Intensive Care, Zaans Medisch Centrum, Zaandam, The Netherlands
| | - Elsbeth Wesselink
- Department of Hospital Pharmacy, Zaans Medisch Centrum, Zaandam, The Netherlands
| | - Dylan W de Lange
- Department of Intensive Care, University Medical Center, University Utrecht, Utrecht, The Netherlands
| | - Nicolette F de Keizer
- Department of Medical Informatics, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health, Amsterdam, The Netherlands
| | - Dave A Dongelmans
- Department of Intensive Care, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Cardiovascular Sciences, Pulmonary Hypertension & Thrombosis, Amsterdam, The Netherlands
| | - Ameen Abu-Hanna
- Department of Medical Informatics, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health, Amsterdam, The Netherlands
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4
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Yasrebi-de Kom IAR, Dongelmans DA, Abu-Hanna A, Schut MC, de Lange DW, van Roon EN, de Jonge E, Bouman CSC, de Keizer NF, Jager KJ, Klopotowska JE. Acute kidney injury associated with nephrotoxic drugs in critically ill patients: a multicenter cohort study using electronic health record data. Clin Kidney J 2023; 16:2549-2558. [PMID: 38045998 PMCID: PMC10689186 DOI: 10.1093/ckj/sfad160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Indexed: 12/05/2023] Open
Abstract
Background Nephrotoxic drugs frequently cause acute kidney injury (AKI) in adult intensive care unit (ICU) patients. However, there is a lack of large pharmaco-epidemiological studies investigating the associations between drugs and AKI. Importantly, AKI risk factors may also be indications or contraindications for drugs and thereby confound the associations. Here, we aimed to estimate the associations between commonly administered (potentially) nephrotoxic drug groups and AKI in adult ICU patients whilst adjusting for confounding. Methods In this multicenter retrospective observational study, we included adult ICU admissions to 13 Dutch ICUs. We measured exposure to 44 predefined (potentially) nephrotoxic drug groups. The outcome was AKI during ICU admission. The association between each drug group and AKI was estimated using etiological cause-specific Cox proportional hazard models and adjusted for confounding. To facilitate an (independent) informed assessment of residual confounding, we manually identified drug group-specific confounders using a large drug knowledge database and existing literature. Results We included 92 616 ICU admissions, of which 13 492 developed AKI (15%). We found 14 drug groups to be associated with a higher hazard of AKI after adjustment for confounding. These groups included established (e.g. aminoglycosides), less well established (e.g. opioids) and controversial (e.g. sympathomimetics with α- and β-effect) drugs. Conclusions The results confirm existing insights and provide new ones regarding drug associated AKI in adult ICU patients. These insights warrant caution and extra monitoring when prescribing nephrotoxic drugs in the ICU and indicate which drug groups require further investigation.
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Affiliation(s)
- Izak A R Yasrebi-de Kom
- Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, Amsterdam, The Netherlands
- Amsterdam Public Health, Amsterdam, The Netherlands
| | - Dave A Dongelmans
- Amsterdam Public Health, Amsterdam, The Netherlands
- Amsterdam UMC location University of Amsterdam, Department of Intensive Care Medicine, Amsterdam, The Netherlands
| | - Ameen Abu-Hanna
- Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, Amsterdam, The Netherlands
- Amsterdam Public Health, Amsterdam, The Netherlands
| | - Martijn C Schut
- Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, Amsterdam, The Netherlands
- Amsterdam Public Health, Amsterdam, The Netherlands
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Laboratory Medicine, Amsterdam, The Netherlands
| | - Dylan W de Lange
- Department of Intensive Care and Dutch Poison Information Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Eric N van Roon
- Department of Clinical Pharmacy and Pharmacology, Medical Center Leeuwarden, Leeuwarden, The Netherlands
| | - Evert de Jonge
- Department of Intensive Care, Leiden University Medical Center, Leiden, The Netherlands
| | - Catherine S C Bouman
- Amsterdam UMC location University of Amsterdam, Department of Intensive Care Medicine, Amsterdam, The Netherlands
- Amsterdam Institute for Infection and Immunity, Amsterdam, The Netherlands
| | - Nicolette F de Keizer
- Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, Amsterdam, The Netherlands
- Amsterdam Public Health, Amsterdam, The Netherlands
| | - Kitty J Jager
- Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, Amsterdam, The Netherlands
- Amsterdam Public Health, Amsterdam, The Netherlands
| | - Joanna E Klopotowska
- Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, Amsterdam, The Netherlands
- Amsterdam Public Health, Amsterdam, The Netherlands
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5
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Murphy RM, Dongelmans DA, Kom IYD, Calixto I, Abu-Hanna A, Jager KJ, de Keizer NF, Klopotowska JE. Drug-related causes attributed to acute kidney injury and their documentation in intensive care patients. J Crit Care 2023; 75:154292. [PMID: 36959015 DOI: 10.1016/j.jcrc.2023.154292] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 03/14/2023] [Accepted: 03/14/2023] [Indexed: 03/25/2023]
Abstract
PURPOSE To investigate drug-related causes attributed to acute kidney injury (DAKI) and their documentation in patients admitted to the Intensive Care Unit (ICU). METHODS This study was conducted in an academic hospital in the Netherlands by reusing electronic health record (EHR) data of adult ICU admissions between November 2015 to January 2020. First, ICU admissions with acute kidney injury (AKI) stage 2 or 3 were identified. Subsequently, three modes of DAKI documentation in EHR were examined: diagnosis codes (structured data), allergy module (semi-structured data), and clinical notes (unstructured data). RESULTS n total 8124 ICU admissions were included, with 542 (6.7%) ICU admissions experiencing AKI stage 2 or 3. The ICU physicians deemed 102 of these AKI cases (18.8%) to be drug-related. These DAKI cases were all documented in the clinical notes (100%), one in allergy module (1%) and none via diagnosis codes. The clinical notes required the highest time investment to analyze. CONCLUSIONS Drug-related causes comprise a substantial part of AKI in the ICU patients. However, current unstructured DAKI documentation practice via clinical notes hampers our ability to gain better insights about DAKI occurrence. Therefore, both automating DAKI identification from the clinical notes and increasing structured DAKI documentation should be encouraged.
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Affiliation(s)
- Rachel M Murphy
- Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, Meibergdreef 9, Amsterdam, the Netherlands; Amsterdam Public Health, Digital Health, Amsterdam, the Netherlands; Amsterdam Public Health, Quality of Care, Amsterdam, the Netherlands.
| | - Dave A Dongelmans
- Amsterdam Public Health, Quality of Care, Amsterdam, the Netherlands; Amsterdam UMC location University of Amsterdam, Department of Intensive Care Medicine, Meibergdreef 9, Amsterdam, the Netherlands
| | - Izak Yasrebi-de Kom
- Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, Meibergdreef 9, Amsterdam, the Netherlands; Amsterdam Public Health, Methodology, Amsterdam, the Netherlands
| | - Iacer Calixto
- Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, Meibergdreef 9, Amsterdam, the Netherlands; Amsterdam Public Health, Methodology, Amsterdam, the Netherlands; Amsterdam Public Health, Mental Health, Amsterdam, the Netherlands
| | - Ameen Abu-Hanna
- Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, Meibergdreef 9, Amsterdam, the Netherlands; Amsterdam Public Health, Methodology, Amsterdam, the Netherlands; Amsterdam Public Health, Aging & Later Life, Amsterdam, the Netherlands
| | - Kitty J Jager
- Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, Meibergdreef 9, Amsterdam, the Netherlands; Amsterdam Public Health, Quality of Care, Amsterdam, the Netherlands; Amsterdam Public Health, Aging & Later Life, Amsterdam, the Netherlands; Amsterdam Cardiovascular Sciences, Pulmonary hypertension & thrombosis, Amsterdam, the Netherlands
| | - Nicolette F de Keizer
- Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, Meibergdreef 9, Amsterdam, the Netherlands; Amsterdam Public Health, Digital Health, Amsterdam, the Netherlands; Amsterdam Public Health, Quality of Care, Amsterdam, the Netherlands
| | - Joanna E Klopotowska
- Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, Meibergdreef 9, Amsterdam, the Netherlands; Amsterdam Public Health, Digital Health, Amsterdam, the Netherlands; Amsterdam Public Health, Quality of Care, Amsterdam, the Netherlands
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6
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Yasrebi-de Kom IAR, Dongelmans DA, de Keizer NF, Jager KJ, Schut MC, Abu-Hanna A, Klopotowska JE. Electronic health record-based prediction models for in-hospital adverse drug event diagnosis or prognosis: a systematic review. J Am Med Inform Assoc 2023; 30:978-988. [PMID: 36805926 PMCID: PMC10114128 DOI: 10.1093/jamia/ocad014] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 01/13/2023] [Accepted: 02/01/2023] [Indexed: 02/22/2023] Open
Abstract
OBJECTIVE We conducted a systematic review to characterize and critically appraise developed prediction models based on structured electronic health record (EHR) data for adverse drug event (ADE) diagnosis and prognosis in adult hospitalized patients. MATERIALS AND METHODS We searched the Embase and Medline databases (from January 1, 1999, to July 4, 2022) for articles utilizing structured EHR data to develop ADE prediction models for adult inpatients. For our systematic evidence synthesis and critical appraisal, we applied the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS). RESULTS Twenty-five articles were included. Studies often did not report crucial information such as patient characteristics or the method for handling missing data. In addition, studies frequently applied inappropriate methods, such as univariable screening for predictor selection. Furthermore, the majority of the studies utilized ADE labels that only described an adverse symptom while not assessing causality or utilizing a causal model. None of the models were externally validated. CONCLUSIONS Several challenges should be addressed before the models can be widely implemented, including the adherence to reporting standards and the adoption of best practice methods for model development and validation. In addition, we propose a reorientation of the ADE prediction modeling domain to include causality as a fundamental challenge that needs to be addressed in future studies, either through acquiring ADE labels via formal causality assessments or the usage of adverse event labels in combination with causal prediction modeling.
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Affiliation(s)
- Izak A R Yasrebi-de Kom
- Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, Amsterdam, The Netherlands.,Amsterdam Public Health, Amsterdam, The Netherlands
| | - Dave A Dongelmans
- Amsterdam Public Health, Amsterdam, The Netherlands.,Amsterdam UMC location University of Amsterdam, Department of Intensive Care Medicine, Amsterdam, The Netherlands
| | - Nicolette F de Keizer
- Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, Amsterdam, The Netherlands.,Amsterdam Public Health, Amsterdam, The Netherlands
| | - Kitty J Jager
- Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, Amsterdam, The Netherlands.,Amsterdam Public Health, Amsterdam, The Netherlands.,Amsterdam Cardiovascular Sciences, Pulmonary Hypertension & Thrombosis, Amsterdam, The Netherlands
| | - Martijn C Schut
- Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, Amsterdam, The Netherlands.,Amsterdam Public Health, Amsterdam, The Netherlands.,Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Clinical Chemistry, Amsterdam, The Netherlands
| | - Ameen Abu-Hanna
- Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, Amsterdam, The Netherlands.,Amsterdam Public Health, Amsterdam, The Netherlands
| | - Joanna E Klopotowska
- Amsterdam UMC location University of Amsterdam, Department of Medical Informatics, Amsterdam, The Netherlands.,Amsterdam Public Health, Amsterdam, The Netherlands
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7
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Klopotowska JE, Kuks PFM, Wierenga PC, Stuijt CCM, Arisz L, Dijkgraaf MGW, de Keizer N, Smorenburg SM, de Rooij SE. The effect of structured medication review followed by face-to-face feedback to prescribers on adverse drug events recognition and prevention in older inpatients - a multicenter interrupted time series study. BMC Geriatr 2022; 22:505. [PMID: 35715742 PMCID: PMC9206349 DOI: 10.1186/s12877-022-03118-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 04/27/2022] [Indexed: 11/10/2022] Open
Abstract
Background The effectiveness of interventions to improve medication safety in older inpatients is unclear, given a paucity of properly designed intervention studies applying clinically relevant endpoints such as hospital-acquired preventable Adverse Drug Events (pADEs) and unrecognized Adverse Drug Events (uADEs). Therefore, we conducted a quality improvement study and used hospital-acquired pADEs and uADEs as main outcomes to assess the effect of an intervention aimed to improve medication safety in older inpatients. Method The study followed an interrupted time series design and consisted of three equally spaced sampling points during baseline and during intervention measurements. Each sampling point included between 80 to 90 patients. A total of 500 inpatients ≥65 years and admitted to internal medicine wards of three Dutch hospitals were included. An expert team retrospectively identified and assessed ADEs via a structured patient chart review. The findings from baseline measurement and meetings with the internal medicine and hospital pharmacy staff were used to design the intervention. The intervention consisted of a structured medication review by hospital pharmacists, followed by face-to-face feedback to prescribers, on average 3 days per week. Results The rate of hospital-acquired pADEs per 100 hospitalizations was reduced by 50.6% (difference 16.8, 95% confidence interval (CI): 9.0 to 24.6, P < 0.001), serious hospital-acquired pADEs by 62.7% (difference 12.8, 95% CI: 6.4 to 19.2, P < 0.001), and uADEs by 51.8% (difference 11.2, 95% CI: 4.4 to 18.0, P < 0.001). Additional analyses confirmed the robustness of the intervention effect, but residual bias cannot be excluded. Conclusions The intervention significantly decreased the overall and serious hospital-acquired pADE occurrence in older inpatients, and significantly improved overall ADE recognition by prescribers. Trial registration International Standard Randomized Controlled Trial Number Register, trial registration number: ISRCTN64974377, registration date (date assigned): 07/02/2011. Supplementary Information The online version contains supplementary material available at 10.1186/s12877-022-03118-z.
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Affiliation(s)
- Joanna E Klopotowska
- Amsterdam University Medical Centers location University of Amsterdam, Medical Informatics, Amsterdam, The Netherlands. .,Amsterdam Public Health, Quality of Care, Amsterdam, The Netherlands.
| | - Paul F M Kuks
- Amsterdam University Medical Centers location University of Amsterdam, Pharmacy and Clinical Pharmacology, Amsterdam, The Netherlands
| | - Peter C Wierenga
- Gelderse Vallei Hospital, Hospital Pharmacy, Ede, The Netherlands
| | - Clementine C M Stuijt
- Center of Excellence on Parkinson's disease (Punt voor Parkinson), Groningen, The Netherlands
| | - Lambertus Arisz
- Amsterdam University Medical Centers location University of Amsterdam, Internal Medicine, Amsterdam, The Netherlands
| | - Marcel G W Dijkgraaf
- Amsterdam University Medical Centers location University of Amsterdam, Epidemiology and Data Science, Amsterdam, The Netherlands.,Amsterdam Public Health, Methodology, Amsterdam, the Netherlands
| | - Nicolette de Keizer
- Amsterdam University Medical Centers location University of Amsterdam, Medical Informatics, Amsterdam, The Netherlands.,Amsterdam Public Health, Quality of Care, Amsterdam, The Netherlands
| | - Susanne M Smorenburg
- Amsterdam University Medical Centers location University of Amsterdam, Internal Medicine, Amsterdam, The Netherlands
| | - Sophia E de Rooij
- Amstelland Hospital, Board of Directors, Amstelveen, The Netherlands
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8
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Bakker T, Dongelmans DA, Nabovati E, Eslami S, de Keizer NF, Abu-Hanna A, Klopotowska JE. Heterogeneity in the identification of potential drug-drug interactions in the intensive care unit: A systematic review, critical appraisal, and reporting recommendations. J Clin Pharmacol 2021; 62:706-720. [PMID: 34957573 PMCID: PMC9303874 DOI: 10.1002/jcph.2020] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 12/19/2021] [Indexed: 11/25/2022]
Abstract
Patients admitted to the intensive care unit (ICU) are frequently exposed to potential drug‐drug interactions (pDDIs). However, reported frequencies of pDDIs in the ICU vary widely between studies. This can be partly explained by significant variation in their methodological approach. Insight into methodological choices affecting pDDI frequency would allow for improved comparison and synthesis of reported pDDI frequencies. This study aimed to evaluate the association between methodological choices and pDDI frequency and formulate reporting recommendations for pDDI frequency studies in the ICU. The MEDLINE database was searched to identify papers reporting pDDI frequency in ICU patients. For each paper, the pDDI frequency and methodological choices such as pDDI definition and pDDI knowledge base were extracted, and the risk of bias was assessed. Each paper was categorized as reporting a low, medium, or high pDDI frequency. We sought associations between methodological choices and pDDI frequency group. Based on this comparison, reporting recommendations were formulated. Analysis of methodological choices showed significant heterogeneity between studies, and 65% of the studies had a medium to high risk of bias. High risk of bias, small sample size, and use of drug prescriptions instead of administrations were related to a higher pDDI frequency. The findings of this review may support researchers in designing a reliable methodology assessing pDDI frequency in ICU patients. The reporting recommendations may contribute to standardization, comparison, and synthesis of pDDI frequency studies, ultimately improving knowledge about pDDIs in and outside the ICU setting.
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Affiliation(s)
- Tinka Bakker
- Amsterdam UMC (location AMC), Department of Medical Informatics, Amsterdam, The Netherlands
| | - Dave A Dongelmans
- Amsterdam UMC (location AMC), Department of Intensive Care Medicine, Amsterdam, The Netherlands
| | - Ehsan Nabovati
- Health Information Management Research Center, Kashan University of Medical Sciences, Kashan, Iran
| | - Saeid Eslami
- Amsterdam UMC (location AMC), Department of Medical Informatics, Amsterdam, The Netherlands.,Pharmaceutical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Nicolette F de Keizer
- Amsterdam UMC (location AMC), Department of Medical Informatics, Amsterdam, The Netherlands
| | - Ameen Abu-Hanna
- Amsterdam UMC (location AMC), Department of Medical Informatics, Amsterdam, The Netherlands
| | - Joanna E Klopotowska
- Amsterdam UMC (location AMC), Department of Medical Informatics, Amsterdam, The Netherlands
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9
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Kuks PFM, Klopotowska JE, van Agtmael MA. [Drug-related health damage]. Ned Tijdschr Geneeskd 2021; 165:D6111. [PMID: 35138704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Gurwitz and colleagues showed that a complex intervention, aimed at a reduction of drug-related adverse events and medication errors immediately after hospital discharge, did not result in a significant outcome difference between the intervention and control groups. We feel that the intervention lacked standardization, that a better outcome might have been achieved by intervening prior to hospital discharge, that more details about the nature of observed medication errors and acceptance of the intervenor recommendations should have been reported. Also, the number of unpreventable adverse drug events was higher in the intervention (n = 37) than in the control group (n = 27), suggesting a Hawthorne effect. The small number of adverse drug events detected overall points to a low sensitivity of the detection method used. We recommend that future studies be designed differently, including a stronger focus on physician-pharmacist collaboration, patient participation and improved communication between the hospital and general practice.
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Affiliation(s)
- Paul F M Kuks
- Amsterdam UMC, Apotheek, Amsterdam
- Contact: Paul F.M. Kuks
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10
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Yasrebi-de Kom IAR, Dongelmans DA, Abu-Hanna A, Schut MC, de Keizer NF, Kellum JA, Jager KJ, Klopotowska JE. Incorrect application of the KDIGO acute kidney injury staging criteria. Clin Kidney J 2021; 15:937-941. [PMID: 35498879 PMCID: PMC9050561 DOI: 10.1093/ckj/sfab256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Indexed: 11/14/2022] Open
Abstract
Background Recent research demonstrated substantial heterogeneity in the Kidney Disease: Improving Global Outcomes (KDIGO) acute kidney injury (AKI) diagnosis and staging criteria implementations in clinical research. Here we report an additional issue in the implementation of the criteria: the incorrect description and application of a stage 3 serum creatinine (SCr) criterion. Instead of an increase in SCr to or beyond 4.0 mg/dL, studies apparently interpreted this criterion as an increase in SCr by 4.0 mg/dL. Methods Using a sample of 8124 consecutive intensive care unit (ICU) admissions, we illustrate the implications of such incorrect application. The AKI stage distributions associated with the correct and incorrect stage 3 SCr criterion implementations were compared, both with and without the stage 3 renal replacement therapy (RRT) criterion. In addition, we compared chronic kidney disease presence, ICU mortality rates and hospital mortality rates associated with each of the AKI stages and the misclassified cases. Results Where incorrect implementation of the SCr stage 3 criterion showed a stage 3 AKI rate of 29%, correct implementation revealed a rate of 34%, mainly due to shifts from stage 1 to stage 3. Without the stage 3 RRT criterion, the stage 3 AKI rates were 9% and 19% after incorrect and correct implementation, respectively. The ICU and hospital mortality rates in cases misclassified as stage 1 or 2 were similar to those in cases correctly classified as stage 1 instead of stage 3. Conclusions While incorrect implementation of the SCr stage 3 criterion has significant consequences for AKI severity epidemiology, consequences for clinical decision making may be less severe. We urge researchers and clinicians to verify their implementation of the AKI staging criteria.
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Affiliation(s)
- Izak A R Yasrebi-de Kom
- Department of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Dave A Dongelmans
- Department of Intensive Care, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Ameen Abu-Hanna
- Department of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Martijn C Schut
- Department of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Nicolette F de Keizer
- Department of Medical Informatics, Amsterdam Public Health Research Institute>, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - John A Kellum
- Department of Critical Care Medicine, The Center for Critical Care Nephrology, Pittsburgh, USA
| | - Kitty J Jager
- Department of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Joanna E Klopotowska
- Department of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
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11
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Bakker T, Abu-Hanna A, Dongelmans DA, Vermeijden WJ, Bosman RJ, de Lange DW, Klopotowska JE, de Keizer NF, Hendriks S, Ten Cate J, Schutte PF, van Balen D, Duyvendak M, Karakus A, Sigtermans M, Kuck EM, Hunfeld NGM, van der Sijs H, de Feiter PW, Wils EJ, Spronk PE, van Kan HJM, van der Steen MS, Purmer IM, Bosma BE, Kieft H, van Marum RJ, de Jonge E, Beishuizen A, Movig K, Mulder F, Franssen EJF, van den Bergh WM, Bult W, Hoeksema M, Wesselink E. Clinically relevant potential drug-drug interactions in intensive care patients: A large retrospective observational multicenter study. J Crit Care 2020; 62:124-130. [PMID: 33352505 DOI: 10.1016/j.jcrc.2020.11.020] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 11/16/2020] [Accepted: 11/27/2020] [Indexed: 11/28/2022]
Abstract
PURPOSE Potential drug-drug interactions (pDDIs) may harm patients admitted to the Intensive Care Unit (ICU). Due to the patient's critical condition and continuous monitoring on the ICU, not all pDDIs are clinically relevant. Clinical decision support systems (CDSSs) warning for irrelevant pDDIs could result in alert fatigue and overlooking important signals. Therefore, our aim was to describe the frequency of clinically relevant pDDIs (crpDDIs) to enable tailoring of CDSSs to the ICU setting. MATERIALS & METHODS In this multicenter retrospective observational study, we used medication administration data to identify pDDIs in ICU admissions from 13 ICUs. Clinical relevance was based on a Delphi study in which intensivists and hospital pharmacists assessed the clinical relevance of pDDIs for the ICU setting. RESULTS The mean number of pDDIs per 1000 medication administrations was 70.1, dropping to 31.0 when considering only crpDDIs. Of 103,871 ICU patients, 38% was exposed to a crpDDI. The most frequently occurring crpDDIs involve QT-prolonging agents, digoxin, or NSAIDs. CONCLUSIONS Considering clinical relevance of pDDIs in the ICU setting is important, as only half of the detected pDDIs were crpDDIs. Therefore, tailoring CDSSs to the ICU may reduce alert fatigue and improve medication safety in ICU patients.
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Affiliation(s)
- Tinka Bakker
- Amsterdam UMC (location AMC), Department of Medical Informatics, Meibergdreef 9, 1105, AZ, Amsterdam, the Netherlands.
| | - Ameen Abu-Hanna
- Amsterdam UMC (location AMC), Department of Medical Informatics, Meibergdreef 9, 1105, AZ, Amsterdam, the Netherlands.
| | - Dave A Dongelmans
- Amsterdam UMC (location AMC), Department of Intensive Care Medicine, Meibergdreef 9, 1105, AZ, Amsterdam, the Netherlands.
| | - Wytze J Vermeijden
- Department of Intensive Care, Medisch Spectrum Twente, Koningsplein 1, 7512, KZ, Enschede, the Netherlands.
| | - Rob J Bosman
- Department of Intensive Care, Onze Lieve Vrouwe Gasthuis, Oosterpark 9, 1091, AC, Amsterdam, the Netherlands.
| | - Dylan W de Lange
- Department of Intensive Care and Dutch Poison Information Center, University Medical Center Utrecht, University Utrecht, Heidelberglaan 100, 3584, CX, Utrecht, the Netherlands.
| | - Joanna E Klopotowska
- Amsterdam UMC (location AMC), Department of Medical Informatics, Meibergdreef 9, 1105, AZ, Amsterdam, the Netherlands.
| | - Nicolette F de Keizer
- Amsterdam UMC (location AMC), Department of Medical Informatics, Meibergdreef 9, 1105, AZ, Amsterdam, the Netherlands.
| | | | - S Hendriks
- Department of Intensive Care, Albert Schweitzer Ziekenhuis, Dordrecht, The Netherlands
| | - J Ten Cate
- Department of Intensive Care, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - P F Schutte
- Department of Intensive Care, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - D van Balen
- Department of Pharmacy & Pharmacology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - M Duyvendak
- Department of Hospital Pharmacy, Antonius Hospital, Sneek, The Netherlands
| | - A Karakus
- Department of Intensive Care Diakonessenhuis Utrecht, Utrecht, The Netherlands
| | - M Sigtermans
- Department of Intensive Care Diakonessenhuis Utrecht, Utrecht, The Netherlands
| | - E M Kuck
- Department of Hospital Pharmacy, Diakonessenhuis Utrecht, Utrecht, The Netherlands
| | - N G M Hunfeld
- Department of Intensive Care, Erasmus MC, Rotterdam, The Netherlands; Department of Hospital Pharmacy, ErasmusMC, Rotterdam, The Netherlands
| | - H van der Sijs
- Department of Hospital Pharmacy, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - P W de Feiter
- Department of Intensive Care, Franciscus Gasthuis & Vlietland, Rotterdam, The Netherlands
| | - E-J Wils
- Department of Intensive Care, Franciscus Gasthuis & Vlietland, Rotterdam, The Netherlands
| | - P E Spronk
- Department of Intensive Care Medicine, Gelre Hospitals, Apeldoorn, The Netherlands
| | - H J M van Kan
- Department of Clinical Pharmacy, Gelre Hospitals, Apeldoorn, The Netherlands
| | - M S van der Steen
- Department of Intensive Care, Ziekenhuis Gelderse Vallei, Ede, The Netherlands
| | - I M Purmer
- Department of Intensive Care, Haga Hospital, The Hague, The Netherlands
| | - B E Bosma
- Department of Hospital Pharmacy, Haga Hospital, The Hague, The Netherlands
| | - H Kieft
- Department of Intensive Care, Isala Hospital, Zwolle, The Netherlands
| | - R J van Marum
- Department of Clinical Pharmacology, Jeroen Bosch Hospital, 's-Hertogenbosch, The Netherlands; Amsterdam UMC (location VUmc), Department of Elderly Care Medicine, Amsterdam, The Netherlands
| | - E de Jonge
- Department of Intensive Care, Leiden University Medical Center, Leiden, The Netherlands
| | - A Beishuizen
- Department of Intensive Care, Medisch Spectrum Twente, Enschede, The Netherlands
| | - K Movig
- Department of Clinical Pharmacy, Medisch Spectrum Twente, Enschede, The Netherlands
| | - F Mulder
- Department of Pharmacology, Noordwest Ziekenhuisgroep, Alkmaar, The Netherlands
| | - E J F Franssen
- OLVG Hospital, Department of Clinical Pharmacy, Amsterdam, The Netherlands
| | - W M van den Bergh
- Department of Critical Care, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - W Bult
- Department of Critical Care, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands; Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - M Hoeksema
- Zaans Medisch Centrum, Department of Anesthesiology, Intensive Care and Painmanagement, Zaandam, The Netherlands
| | - E Wesselink
- Department of Clinical Pharmacy, Zaans Medisch Centrum, Zaandam, The Netherlands
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12
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Schutijser BCFM, Klopotowska JE, Jongerden IP, Wagner C, de Bruijne MC. Feasibility of reusing routinely recorded data to monitor the safe preparation and administration of injectable medication: A multicenter cross-sectional study. Int J Med Inform 2020; 141:104201. [PMID: 32531726 DOI: 10.1016/j.ijmedinf.2020.104201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Revised: 04/28/2020] [Accepted: 05/24/2020] [Indexed: 11/18/2022]
Abstract
BACKGROUND Reusing routinely recorded data from electronic hospital records (EHR) may offer a less-time consuming, and more real time alternative for monitoring compliance by nurses with a protocol for the safe preparation and administration of injectable medication. However, at present it is unknown if the data necessary to calculate the quality indicators (QIs) are recorded in EHRs, or if these data are suitable for automated QI calculation. Therefore, the aim of this study was to determine the feasibility of monitoring compliance by nurses with a protocol for the safe injectable medication preparation and administration by reusing routinely recorded EHR data for the automated calculation of QIs. METHODS A cross-sectional study in 12 Dutch hospitals (October 2015-May 2016). The checks included in the currently prevailing national protocol for the safe preparation and administration of injectable medication were translated into 16 data elements required to calculate the QIs. At each hospital, one interview was conducted using a structured questionnaire to decide whether the data elements were available in EHRs. To present these results, descriptive statistics were used. RESULTS In total, 20 health-care professionals were interviewed and four different EHR systems were evaluated. The availability of data elements was comparable between the four evaluated EHR systems. Nine of the 16 required data elements were recorded in EHRs, eight in a structured format. The seven missing data elements were mainly related to checks such as 'gather all materials needed' or 'conduct hand hygiene'. Furthermore, changes were identified in the process for the preparation and administration of injectable medication. These changes are mostly related to the increased use of electronic medication administration registration and barcode medication administration systems. CONCLUSIONS Reusing EHR data to monitor compliance by nurses with the currently prevailing protocol for the safe preparation and administration of injectable medication is not entirely feasible. A decision should be made on which checks should be recorded in the EHRs and which checks should be audited in order to minimize the registration burden for nurses. Moreover, the currently prevailing protocol should be revised to bring it in line with work-as-done. Our results can be used as guidance for such a revision and also for designing new QIs that can be calculated by reusing routinely recorded EHR data.
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Affiliation(s)
- B C F M Schutijser
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands.
| | - J E Klopotowska
- Department of Medical Informatics, Amsterdam UMC, Academic Medical Center Amsterdam, the Netherlands
| | - I P Jongerden
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands
| | - C Wagner
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; NIVEL, Netherlands Institute for Health Services Research, Utrecht, the Netherlands
| | - M C de Bruijne
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands
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13
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Bakker T, Klopotowska JE, Eslami S, de Lange DW, van Marum R, van der Sijs H, de Jonge E, Dongelmans DA, de Keizer NF, Abu-Hanna A. The effect of ICU-tailored drug-drug interaction alerts on medication prescribing and monitoring: protocol for a cluster randomized stepped-wedge trial. BMC Med Inform Decis Mak 2019; 19:159. [PMID: 31409338 PMCID: PMC6692933 DOI: 10.1186/s12911-019-0888-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Accepted: 08/02/2019] [Indexed: 11/10/2022] Open
Abstract
Background Drug-drug interactions (DDIs) can cause patient harm. Between 46 and 90% of patients admitted to the Intensive Care Unit (ICU) are exposed to potential DDIs (pDDIs). This rate is twice as high as patients on general wards. Clinical decision support systems (CDSSs) have shown their potential to prevent pDDIs. However, the literature shows that there is considerable room for improvement of CDSSs, in particular by increasing the clinical relevance of the pDDI alerts they generate and thereby reducing alert fatigue. However, consensus on which pDDIs are clinically relevant in the ICU setting is lacking. The primary aim of this study is to evaluate the effect of alerts based on only clinically relevant interactions for the ICU setting on the prevention of pDDIs among Dutch ICUs. Methods To define the clinically relevant pDDIs, we will follow a rigorous two-step Delphi procedure in which a national expert panel will assess which pDDIs are perceived clinically relevant for the Dutch ICU setting. The intervention is the CDSS that generates alerts based on the clinically relevant pDDIs. The intervention will be evaluated in a stepped-wedge trial. A total of 12 Dutch adult ICUs using the same patient data management system, in which the CDSS will operate, were invited to participate in the trial. Of the 12 ICUs, 9 agreed to participate and will be enrolled in the trial. Our primary outcome measure is the incidence of clinically relevant pDDIs per 1000 medication administrations. Discussion This study will identify pDDIs relevant for the ICU setting. It will also enhance our understanding of the effectiveness of alerts confined to clinically relevant pDDIs. Both of these contributions can facilitate the successful implementation of CDSSs in the ICU and in other domains as well. Trial registration Nederlands Trial register Identifier: NL6762. Registered November 26, 2018.
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Affiliation(s)
- T Bakker
- Department of Medical Informatics, Amsterdam UMC (location AMC), Amsterdam, The Netherlands.
| | - J E Klopotowska
- Department of Medical Informatics, Amsterdam UMC (location AMC), Amsterdam, The Netherlands
| | - S Eslami
- Department of Medical Informatics, Amsterdam UMC (location AMC), Amsterdam, The Netherlands.,Pharmaceutical Research Center, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran
| | - D W de Lange
- Department of Intensive Care and Dutch Poison Information Center, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - R van Marum
- Department of Geriatrics, Jeroen Bosch Hospital, s-Hertogenbosch, The Netherlands.,Department of General Practice and Elderly Care Medicine, Amsterdam UMC (location VUmc), Amsterdam, The Netherlands
| | - H van der Sijs
- Department of Hospital Pharmacy, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - E de Jonge
- Department of Intensive Care, Leiden University Medical Center, Leiden, The Netherlands
| | - D A Dongelmans
- Department of Intensive Care Medicine, Amsterdam UMC (location AMC), Amsterdam, The Netherlands
| | - N F de Keizer
- Department of Medical Informatics, Amsterdam UMC (location AMC), Amsterdam, The Netherlands
| | - A Abu-Hanna
- Department of Medical Informatics, Amsterdam UMC (location AMC), Amsterdam, The Netherlands
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14
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Schutijser BCFM, Klopotowska JE, Jongerden IP, Spreeuwenberg PMM, De Bruijne MC, Wagner C. Interruptions during intravenous medication administration: A multicentre observational study. J Adv Nurs 2018; 75:555-562. [PMID: 30334590 DOI: 10.1111/jan.13880] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Revised: 07/25/2018] [Accepted: 10/02/2018] [Indexed: 11/27/2022]
Abstract
AIMS The aim of this study was to determine the frequency and cause of interruptions during intravenous medication administration, which factors are associated with interruptions and to what extent interruptions influence protocol compliance. BACKGROUND Hospital nurses are frequently interrupted during medication administration, which contributes to the occurrence of administration errors. Errors with intravenous medication are especially worrisome, given their immediate therapeutic effects. However, knowledge about the extent and type of interruptions during intravenous medication administration is limited. DESIGN Multicentre observational study. METHODS Data were collected during two national evaluation studies (2011 - 2012 & 2015 - 2016). Nurses were directly observed during intravenous medication administration. An interruption was defined as a situation where a break during the administration was needed or where a nurse was distracted but could process without a break. Interruptions were categorized according to source and cause. Multilevel logistic regression analyses were conducted to assess the associations between explanatory variables and interruptions or complete protocol compliance. RESULTS In total, 2,526 intravenous medication administration processes were observed. During 291 (12%) observations, nurses were interrupted 321 times. Most interruptions were externally initiated by other nurses (19%) or patients (19%). Less interruptions occurred during the evening (odds ratio: 0.23 [95% confidence interval: 0.08-0.62]). Do-not-disturb vests were worn by 61 (2%) nurses. No significant association was found between being interrupted and complete protocol compliance. CONCLUSION An interruption occurred in every eight observed intravenous medication administration, mainly caused by other nurses or patients. One needs to consider critically which strategies effectively improve safety during the high-risk nursing-task of intravenous medication administration.
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Affiliation(s)
- Bernadette C F M Schutijser
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Joanna E Klopotowska
- Department of Medical Informatics, Amsterdam UMC, Academic Medical Center, Amsterdam, The Netherlands
| | - Irene P Jongerden
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | | | - Martine C De Bruijne
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Cordula Wagner
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,NIVEL, Netherlands Institute for Health Services Research, Utrecht, The Netherlands
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15
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Werumeus Buning A, Klopotowska JE, Duyvendak M, Engelen LJLPG, Arts J. Patient empowerment through provision of a mobile application for medication reconciliation: a proof of concept study. ACTA ACUST UNITED AC 2016. [DOI: 10.1136/bmjinnov-2015-000110] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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16
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Boeker EB, Ram K, Klopotowska JE, de Boer M, Creus MT, de Andrés AL, Sakuma M, Morimoto T, Boermeester MA, Dijkgraaf MGW. An individual patient data meta-analysis on factors associated with adverse drug events in surgical and non-surgical inpatients. Br J Clin Pharmacol 2015; 79:548-57. [PMID: 25199645 PMCID: PMC4386940 DOI: 10.1111/bcp.12504] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2014] [Accepted: 09/02/2014] [Indexed: 11/30/2022] Open
Abstract
AIM The incidence of adverse drug events (ADEs) in surgical and non-surgical patients may differ. This individual patient data meta-analysis (IPDMA) identifies patient characteristics and types of medication most associated with patients experiencing ADEs and suggests target areas for reducing harm and implementing focused interventions. METHODS Authors of eligible studies on preventable ADEs (pADEs) were approached for collaboration. For assessment of differences among (non-)surgical patients and identification of associated factors descriptive statistics, Pearson chi-square, Poisson and logistic regression analyses were performed. For identification of high risk drugs (HRDs), a model was developed based on frequency, severity and preventability of medication related to ADEs. RESULTS Included were 5367 patients from four studies. Patients aged ≥ 77 years experienced more ADEs and pADEs compared with patients aged ≤ 52 years (odds ratios (OR) 2.12 (95% CI 1.70, 2.65) and 2.55 (95% CI 1.70, 3.84), respectively, both P < 0.05). Polypharmacy on admission also increased the risk of ADEs (OR 1.21 (95% CI 1.03, 1.44), P < 0.05) and pADEs (OR 1.85 (95% CI 1.34, 2.56), P < 0.05). pADEs were associated with more severe harm than non-preventable ADEs (54% vs. 32%, P < 0.05). The top five HRDs were antibiotics, sedatives, anticoagulants, diuretics and antihypertensives. Events associated with HRDs included diarrhoea or constipation, abnormal liver function test and central nervous system events. Most pADEs resulted from prescribing errors (90%). CONCLUSION Elderly patients with polypharmacy on admission and receiving antibiotics, sedatives, anticoagulants, diuretics or antihypertensives were more prone to experiencing ADEs. Efficiency in prevention of ADEs may be improved by targeted vigilance systems for alertness of physicians and pharmacists.
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Affiliation(s)
- Eveline B Boeker
- Department of Surgery, Academic Medical Center, Amsterdam, The Netherlands
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17
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Klopotowska JE, Wierenga PC, Stuijt CCM, Arisz L, Dijkgraaf MGW, Kuks PFM, Asscheman H, de Rooij SE, Lie-A-Huen L, Smorenburg SM. Adverse drug events in older hospitalized patients: results and reliability of a comprehensive and structured identification strategy. PLoS One 2013; 8:e71045. [PMID: 23940688 PMCID: PMC3733642 DOI: 10.1371/journal.pone.0071045] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2012] [Accepted: 06/28/2013] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Older patients are at high risk for experiencing Adverse Drug Events (ADEs) during hospitalization. To be able to reduce ADEs in these vulnerable patients, hospitals first need to measure the occurrence of ADEs, especially those that are preventable. However, data on preventable ADEs (pADEs) occurring during hospitalization in older patients are scarce, and no 'gold standard' for the identification of ADEs exists. METHODOLOGY The study was conducted in three hospitals in the Netherlands in 2007. ADEs were retrospectively identified by a team of experts using a comprehensive and structured patient chart review (PCR) combined with a trigger-tool as an aid. This ADE identification strategy was applied to a cohort of 250 older hospitalized patients. To estimate the intra- and inter-rater reliabilities, Cohen's kappa values were calculated. PRINCIPAL FINDINGS In total, 118 ADEs were detected which occurred in 62 patients. This ADE yield was 1.1 to 2.7 times higher in comparison to other ADE studies in older hospitalized patients. Of the 118 ADEs, 83 (70.3%) were pADEs; 51 pADEs (43.2% of all ADEs identified) caused serious patient harm. Patient harm caused by ADEs resulted in various events. The overall intra-rater agreement of the developed strategy was substantial (κ = 0.74); the overall inter-rater agreement was only fair (κ = 0.24). CONCLUSIONS/SIGNIFICANCE The ADE identification strategy provided a detailed insight into the scope of ADEs occurring in older hospitalized patients, and showed that the majority of (serious) ADEs can be prevented. Several strategy related aspects, as well as setting/study specific aspects, may have contributed to the results gained. These aspects should be considered whenever ADE measurements need to be conducted. The results regarding pADEs can be used to design tailored interventions to effectively reduce harm caused by medication errors. Improvement of the inter-rater reliability of a PCR remains challenging.
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Affiliation(s)
- Joanna E Klopotowska
- Department of Hospital Pharmacy, Academic Medical Center, Amsterdam, the Netherlands.
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Stuijt CCM, Klopotowska JE, van Driel CK, Le N, Binnekade J, van der Kleij B, van der Schors T, van den Bemt P, Lie-A-Huen L. Improving medication administration in nursing home residents with swallowing difficulties: sustainability of the effect of a multifaceted medication safety programme. Pharmacoepidemiol Drug Saf 2012. [DOI: 10.1002/pds.3373] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
| | - Joanna E. Klopotowska
- Academic Medical Centre; Department of Hospital Pharmacy; Amsterdam; the Netherlands
| | | | - Nhut Le
- University of Utrecht; Faculty of Pharmacy; Utrecht; the Netherlands
| | - Jan Binnekade
- Academic Medical Centre; Department of Intensive Care; Amsterdam; the Netherlands
| | - Bea van der Kleij
- Westfriesgasthuis; Department of Hospital Pharmacy; Hoorn; the Netherlands
| | | | | | - Loraine Lie-A-Huen
- Academic Medical Centre; Department of Hospital Pharmacy; Amsterdam; the Netherlands
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Wierenga PC, Klopotowska JE, Smorenburg SM, van Kan HJ, Bijleveld YA, Dijkgraaf MG, de Rooij SE. Quality indicators for in-hospital pharmaceutical care of Dutch elderly patients: development and validation of an ACOVE-based quality indicator set. Drugs Aging 2011; 28:295-304. [PMID: 21428464 DOI: 10.2165/11587700-000000000-00000] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
BACKGROUND In 2001, the ACOVE (Assessing Care Of Vulnerable Elders) quality indicators (QIs) were developed in the US to measure the quality of care of vulnerable elderly patients. However, the ACOVE QI set was developed mainly to assess the overall quality of care of community-dwelling vulnerable elders (as opposed to hospitalized elderly). Therefore, they need to be adapted when used in a non-US hospital setting. In addition, the ACOVE QIs depend on patient and caretaker interviews to assess the quality of care. OBJECTIVE The aim of this study was to develop and validate a set of explicitly phrased QIs to measure (without the need for interviews) the quality of pharmaceutical care of elderly hospitalized patients in the Netherlands. STUDY DESIGN The QI set was developed based on the ACOVE QIs, Dutch national guidelines, evidence from the literature and expert opinion. The QI set focused on in-hospital pharmaceutical care and was evaluated in terms of whether the QIs were able to assess the quality of care using medical records and a hospital information system. In three review rounds, the QI set was adapted and judged on face and content validity. The feasibility of implementation of the QI set and inter-rater reliability were determined. SETTING The study was conducted between September 2007 and August 2008 in a tertiary 1002-bed university hospital. RESEARCH TEAM: Two pharmacists were responsible for the selection and adaptation of QIs. An internist-geriatrician, a physician with experience in quality assurance and internal medicine and a senior hospital pharmacist formed the expert panel responsible for reviewing the QIs. MEASUREMENTS Fleiss' κ values and the intraclass correlation coefficient were calculated for inter-rater reliability. RESULTS An 87-item QI set was accepted by the expert panel. Of this set, 49 QIs were based on ACOVE QIs and 38 QIs were newly added. The QI set demonstrated excellent inter-rater reliability and good feasibility. CONCLUSIONS We developed a valid and reliable set of QIs to efficiently assess the quality of the in-hospital pharmaceutical care provided to elderly Dutch patients.
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Affiliation(s)
- Peter C Wierenga
- Department of Clinical Pharmacy, Academic Medical Center, Amsterdam, The Netherlands.
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Klopotowska JE, Wierenga PC, de Rooij SE, Stuijt CC, Arisz L, Kuks PF, Dijkgraaf MG, Lie-A-Huen L, Smorenburg SM. The effect of an active on-ward participation of hospital pharmacists in Internal Medicine teams on preventable Adverse Drug Events in elderly inpatients: protocol of the WINGS study (Ward-oriented pharmacy in newly admitted geriatric seniors). BMC Health Serv Res 2011; 11:124. [PMID: 21612624 PMCID: PMC3126701 DOI: 10.1186/1472-6963-11-124] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2011] [Accepted: 05/25/2011] [Indexed: 11/23/2022] Open
Abstract
Background The potential of clinical interventions, aiming at reduction of preventable Adverse Drug Events (preventable ADEs) during hospital stay, have been studied extensively. Clinical Pharmacy is a well-established and effective service, usually consisting of full-time on-ward participation of clinical pharmacists in medical teams. Within the current Hospital Pharmacy organisation in the Netherlands, such on-ward service is less feasible and therefore not yet established. However, given the substantial incidence of preventable ADEs in Dutch hospitals found in recent studies, appears warranted. Therefore, "Ward-Oriented Pharmacy", an on-ward service tailored to the Dutch hospital setting, will be developed. This service will consist of multifaceted interventions implemented in the Internal Medicine wards by hospital pharmacists. The effect of this service on preventable ADEs in elderly inpatients will be measured. Elderly patients are at high risk for ADEs due to multi-morbidity, concomitant disabilities and polypharmacy. Most studies on the incidence and preventability of ADEs in elderly patients have been conducted in the outpatient setting or on admission to a hospital, and fewer in the inpatient setting. Moreover, recognition of ADEs by the treating physicians is challenging in elderly patients because their disease presentation is often atypical and complex. Detailed information about the performance of the treating physicians in ADE recognition is scarce. Methods/Design The design is a multi-centre, interrupted time series study. Patients of 65 years or older, consecutively admitted to Internal Medicine wards will be included. After a pre-measurement, a Ward-Oriented Pharmacy service will be introduced and the effect of this service will be assessed during a post-measurement. The primary outcome measures are the ADE prevalence on admission and ADE incidence during hospital stay. These outcomes will be assessed using structured retrospective chart review by an independent expert panel. This assessment will include determination of causality, severity and preventability of ADEs. In addition, the extent to which ADEs are recognised and managed by the treating physicians will be considered. Discussion The primary goal of the WINGS study is to assess whether a significant reduction in preventable ADEs in elderly inpatients can be achieved by a Ward-Oriented Pharmacy service offered. A comprehensive ADE detection method will be used based on expert opinion and retrospective, trigger-tool enhanced, chart review. Trial registration ISRCTN: ISRCTN64974377
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Affiliation(s)
- Joanna E Klopotowska
- Department of Hospital Pharmacy, Academic Medical Centre, Amsterdam, The Netherlands.
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Klopotowska JE, Kuiper R, van Kan HJ, de Pont AC, Dijkgraaf MG, Lie-A-Huen L, Vroom MB, Smorenburg SM. On-ward participation of a hospital pharmacist in a Dutch intensive care unit reduces prescribing errors and related patient harm: an intervention study. Crit Care 2010; 14:R174. [PMID: 20920322 PMCID: PMC3219276 DOI: 10.1186/cc9278] [Citation(s) in RCA: 133] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/20/2010] [Revised: 06/29/2010] [Accepted: 10/04/2010] [Indexed: 11/10/2022]
Abstract
Introduction Patients admitted to an intensive care unit (ICU) are at high risk for prescribing errors and related adverse drug events (ADEs). An effective intervention to decrease this risk, based on studies conducted mainly in North America, is on-ward participation of a clinical pharmacist in an ICU team. As the Dutch Healthcare System is organized differently and the on-ward role of hospital pharmacists in Dutch ICU teams is not well established, we conducted an intervention study to investigate whether participation of a hospital pharmacist can also be an effective approach in reducing prescribing errors and related patient harm (preventable ADEs) in this specific setting. Methods A prospective study compared a baseline period with an intervention period. During the intervention period, an ICU hospital pharmacist reviewed medication orders for patients admitted to the ICU, noted issues related to prescribing, formulated recommendations and discussed those during patient review meetings with the attending ICU physicians. Prescribing issues were scored as prescribing errors when consensus was reached between the ICU hospital pharmacist and ICU physicians. Results During the 8.5-month study period, medication orders for 1,173 patients were reviewed. The ICU hospital pharmacist made a total of 659 recommendations. During the intervention period, the rate of consensus between the ICU hospital pharmacist and ICU physicians was 74%. The incidence of prescribing errors during the intervention period was significantly lower than during the baseline period: 62.5 per 1,000 monitored patient-days versus 190.5 per 1,000 monitored patient-days, respectively (P < 0.001). Preventable ADEs (patient harm, National Coordinating Council for Medication Error Reporting and Prevention severity categories E and F) were reduced from 4.0 per 1,000 monitored patient-days during the baseline period to 1.0 per 1,000 monitored patient-days during the intervention period (P = 0.25). Per monitored patient-day, the intervention itself cost €3, but might have saved €26 to €40 by preventing ADEs. Conclusions On-ward participation of a hospital pharmacist in a Dutch ICU was associated with significant reductions in prescribing errors and related patient harm (preventable ADEs) at acceptable costs per monitored patient-day. Trial registration number ISRCTN92487665
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Affiliation(s)
- Joanna E Klopotowska
- Department of Hospital Pharmacy, Academic Medical Center, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands.
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