HEALTH INFORMATION TECHNOLOGY AND THE CHANGING NATURE OF MEDICATION ERRORS IN PAEDIATRIC INTENSIVE CARE – A DELPHI PROCESS

Author(s):  
Moninne HOWLETT
2018 ◽  
Vol 103 (2) ◽  
pp. e2.37-e2
Author(s):  
Moninne Howlett ◽  
Brian Cleary ◽  
Cormac Breatnach

AimsThe term ‘medication error’ has numerous definitions, impeding comparison between studies and is susceptible to subjectivity.1 The Delphi Process is widely used in health research to achieve consensus and has been previously used to define and specify medication error scenarios in both paediatric and adult settings.2,3 Novel technology-generated errors are emerging with increasing use of health information technology (HIT).4 Application of earlier Delphi studies to novel errors and those common in the prescribing of infusions in paediatric intensive care is limited. This study aims to achieve consensus on medication error scenarios identified in a paediatric intensive care unit (PICU) that have not been previously defined.MethodsStage 1 identified the scenarios requiring consensus. These were grouped into 3 error categories: electronic prescribing, smart-pump and prescribing of PICU infusions. Stage 2 selected a multidisciplinary expert panel using both purposive and convenience sampling. Stage 3 involved iterative rounds of consensus using paper-based and newer e-Delphi techniques. Participants independently scored on a 9-point scale their extent of agreement on the inclusion of each scenario as an error. Median and inter-quartile ranges were used to assess group consensus and to provide controlled feedback after each round.Results19 scenarios requiring consensus were identified. A panel of 37 participants was selected, comprising of 15 doctors, 13 nurses and 9 pharmacists. 35 participants were from the study site, 1 pharmacist from a local PICU and 1 from a local NICU. Round 1 achieved consensus on 11 scenarios, increasing to 14 in Round 2. Round 3 consisted of 2 scenarios, both electronic prescribing related. Individual opinion on these was diverse, with 1 remaining equivocal after round 3. Some differences between healthcare professionals were found, but were only significant (p<0.05) for two and three scenarios in rounds 2 and 3 respectively.ConclusionThe Delphi Process can successfully be employed to reach consensus on HIT-generated novel errors. The complexity of electronic prescribing systems is evident in the included errors and the difficulty in obtaining consensus. In contrast, the broad consensus reached on all smart-pump scenarios reflects the known risks associated with infusion pumps. The included scenarios highlight the limitation of smart-pump technology as a single intervention. Further similar studies are likely to be required as more novel errors emerge with increased HIT implementation across the entire medication use process. This extended tool should add to the quality of future paediatric medication error studies across a broad range of settings.ReferencesLisby M, Nielsen LP, Brock B, et al. How are medication errors defined? A systematic literature review of definitions and characteristics. Int J Qual Health Care2010;22(6):507–18.Dean B, Barber N, Schachter M. What is a prescribing error?Qual Health Care2000;9(4):232–7.Ghaleb MA, Barber N, Dean Franklin B, et al. What constitutes a prescribing error in paediatrics?Qual Saf Health Care2005;14(5):352–7.Walsh KE, Landrigan CP, Adams WG, et al. Effect of computer order entry on prevention of serious medication errors in hospitalised children. Paediatrics2008;121(3):e421–7.


2014 ◽  
Vol 23 (01) ◽  
pp. 58-66 ◽  
Author(s):  
T. G. Kannampallil ◽  
V. L. Patel

Summary Objectives: Recent federal mandates and incentives have spurred the rapid growth, development and adoption of health information technology (HIT). While providing significant benefits for better data integration, organization, and availability, recent reports have raised questions regarding their potential to cause medication errors, decreased clinician performance, and lowered efficiency. The goal of this survey article is to (a) examine the theoretical and foundational models of human factors and ergonomics (HFE) that are being advocated for achieving patient safety and quality, and their use in the evaluation of health-care systems; (b) and the potential for macroergonomic HFE approaches within the context of current research in biomedical informatics. Methods: We reviewed literature (2007-2013) on the use of HFE approaches in healthcare settings, from databases such as Pubmed, CINAHL, and Cochran. Results: Based on the review, we discuss the systems-oriented models, their use in the evaluation of HIT, and examples of their use in the evaluation of EHR systems, clinical workflow processes, and medication errors. We also discuss the opportunities for better integrating HFE methods within biomedical informatics research and its potential advantages. Conclusions: The use of HFE methods is still in its infancy - better integration of HFE within the design lifecycle, and quality improvement efforts can further the ability of informatics researchers to address the key concerns regarding the complexity in clinical settings and develop HIT solutions that are designed within the social fabric of the considered setting.


2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Katharine T. Adams ◽  
Zoe Pruitt ◽  
Sadaf Kazi ◽  
Aaron Z. Hettinger ◽  
Jessica L. Howe ◽  
...  

2017 ◽  
Vol 52 (4) ◽  
pp. 1330-1348 ◽  
Author(s):  
Myles Leslie ◽  
Elise Paradis ◽  
Michael A. Gropper ◽  
Simon Kitto ◽  
Scott Reeves ◽  
...  

2019 ◽  
Vol 26 (4) ◽  
pp. 3072-3087
Author(s):  
Judith Thomas ◽  
Maria R Dahm ◽  
Julie Li ◽  
Johanna I Westbrook ◽  
Andrew Georgiou

The purpose of this qualitative study was to identify differences in the utilisation of an electronic medical record test–result management system between two acute care departments. Field observations (130 min) and semi-structured interviews (n = 24) were conducted in the Intensive Care Unit and Emergency Department of an Australian hospital. Work processes identified from audio transcripts were modelled using business process modelling. Comparison of the Emergency Department and Intensive Care Unit identified the following: (1) test ordering variations according to clinical roles, (2) differences in the use of electronic medical record functionality according to specific demands of the clinical environment and (3) the non-linear components of the test–result management process. Variations were identified in the number of process decisions, external collaborations and temporal process workflows. Modelling the business processes, collaboration and communication needs of individual clinical environments can aid in enhancing the quality and appositeness of health information technology interventions and thus contribute to improving patient safety. Future health information technology interventions/evaluations aimed at improving the safety of test–result management processes need to address both the nuances of the clinical environment and accommodate the individual work practices of clinicians within that environment.


JAMIA Open ◽  
2018 ◽  
Vol 1 (1) ◽  
pp. 32-41
Author(s):  
Onur Asan ◽  
Richard J Holden ◽  
Kathryn E Flynn ◽  
Kathy Murkowski ◽  
Matthew C Scanlon

Abstract Objective To explore perceptions of critical care providers about a novel collaborative inpatient health information technology (HIT) in a pediatric intensive care unit (PICU) setting. Methods This cross-sectional, concurrent mixed methods study was conducted in the PICU of a large midwestern children’s hospital. The technology, the Large Customizable Interactive Monitor (LCIM), is a flat panel touch screen monitor that displays validated patient information from the electronic health record. It does not require a password to login and is available in each patient’s room for viewing and interactive use by physicians, nurses, and families. Quantitative data were collected via self-administered, standardized surveys, and qualitative data via in-person, semistructured interviews between January and April 2015. Data were analyzed using descriptive statistics and inductive thematic analysis. Results The qualitative analysis showed positive impacts of the LCIM on providers’ workflow, team interactions, and interactions with families. Providers reported concerns regarding perceived patient information overload and associated anxiety and burden for families. Sixty percent of providers thought that LCIM was useful for their jobs at different levels, and almost 70% of providers reported that LCIM improved information sharing and communication with families. The average overall satisfaction score was 3.4 on a 0 to 6 scale, between “a moderate amount” and “pretty much.” Discussion and Conclusion This study provides new insight into collaborative HIT in the inpatient pediatric setting and demonstrates that using such technology has the potential to improve providers’ experiences with families and just-in-time access to EHR information in a format more easily shared with families.


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