scholarly journals Direct Observational Study of Interfaced Smart-Pumps in Pediatric Intensive Care

2020 ◽  
Vol 11 (04) ◽  
pp. 659-670
Author(s):  
Moninne M. Howlett ◽  
Cormac V. Breatnach ◽  
Erika Brereton ◽  
Brian J. Cleary
Keyword(s):  
Intensive Care ◽  
Pediatric Intensive Care ◽  
The United States ◽  
Error Rates ◽  
Electronic Prescribing ◽  
Pediatric Hospital ◽  
Reduction Strategies ◽  
Smart Pumps ◽  
Smart Pump ◽  
Pump Infusion

Abstract Background Processes for delivery of high-risk infusions in pediatric intensive care units (PICUs) are complex. Standard concentration infusions (SCIs), smart-pumps, and electronic prescribing are recommended medication error reduction strategies. Implementation rates in Europe lag behind those in the United States. Since 2012, the PICU of an Irish tertiary pediatric hospital has been using a smart-pump SCI library, interfaced with electronic infusion orders (Philips ICCA). The incidence of infusion errors is unknown. Objectives To determine the frequency, severity, and distribution of smart-pump infusion errors in PICUs. Methods Programmed infusions were directly observed at the bedside. Parameters were compared against medication orders and autodocumented infusion data. Identified deviations were categorized as medication errors or discrepancies. Error rates (%) were calculated as infusions with errors and errors per opportunities for error (OEs). Predefined definitions, multidisciplinary consensus and grading processes were employed. Results A total of 1,023 infusions for 175 patients were directly observed over 27 days between February and September 2017. The drug library accommodated 96.5% of infusions. Compliance with the drug library was 98.9%. A total of 133 infusions had ≥1 error (13.0%); a further 58 (5.7%) had ≥1 discrepancy. From a total of 4,997 OEs, 153 errors (3.1%) and 107 discrepancies (2.1%) were observed. Undocumented bolus doses were most commonly identified (n = 81); this was the only deviation in 36.1% (n = 69) of infusions. Programming errors were rare (0.32% OE). Errors were minor, with just one requiring minimal intervention to prevent harm. Conclusion The error rates identified are low compared with similar studies, highlighting the benefits of smart-pumps and autodocumented infusion data in PICUs. A range of quality improvement opportunities has been identified.

scholarly journals P19 Direct observational study of infusion errors associated with smart-pump technology in paediatric intensive care

2020 ◽  
Vol 105 (9) ◽  
pp. e15.2-e16
Author(s):  
Moninne Howlett ◽  
Erika Brereton ◽  
Cormac Breatnach ◽  
Brian Cleary
Keyword(s):  
Intensive Care ◽  
Intensive Care Units ◽  
The United States ◽  
Error Rates ◽  
Paediatric Intensive Care ◽  
Electronic Prescribing ◽  
List Type ◽  
Paediatric Hospital ◽  
Smart Pumps ◽  
Smart Pump

AimsProcesses for delivery of high-risk infusions in paediatric intensive care units (PICUs) are complex. Standard concentration infusions (SCIs), smart-pumps and electronic prescribing are recommended medication error reduction strategies.1 2 Implementation rates are low in Irish and UK hospitals.2 3 Since 2012, the PICU of an Irish tertiary paediatric hospital has been using a smart-pump SCI library, interfaced with electronic infusion orders (Philips ICCA®). The incidence of infusion errors is unknown. This study aims to determine the frequency, severity and distribution of smart-pump infusion errors and to identify contributory factors to the occurrence of infusion errors.MethodsProgrammed infusions are directly observed at the bedside. Parameters are compared against medication orders and auto-populated infusion data. Identified deviations are categorised as either medication errors or discrepancies. Five opportunities for error (OEs) were identified: programming, administration, documentation, assignment, data transfer. Error rates (%) are calculated as: infusions with errors; and errors per OE. Pre-defined definitions, multi-disciplinary consensus and grading processes are employed.ResultsA total of 1023 infusions for 175 patients were directly observed on 27 days between February and September 2017. 74% of patients were under 1 year, 32% under 1 month. The drug-library accommodated 96.5% of all infusions. Compliance with the drug-library was 98.9%. 55 infusions had ≥ 1 error (5.4%); a further 67 (6.3%) had ≥ 1 discrepancy. From a total of 4997 OEs, 72 errors (1.4%) and 107 discrepancies (2.1%) were observed. Documentation errors were most common; programming errors were rare (0.32% OE). Errors are minor, with just one requiring minimal intervention to prevent harm.ConclusionThis study has highlighted the benefits of smart-pumps and auto-populated infusion data in the PICU setting. Identified error rates are low compared to similar studies.4 The findings will contribute to the limited existing knowledge base on impact of these interventions on paediatric infusion administration errors.ReferencesInstitute for Safe Medication Practices, ISMP. 2018–2019 Targeted medication safety best practices for hospitals2018 [Available from: http://www.ismp.org/tools/bestpractices/TMSBP-for-Hospitalsv2.pdf [Accessed: June 2019]Oskarsdottir T, Harris D, Sutherland A, et al. A national scoping survey of standard infusions in paediatric and neonatal intensive care units in the United Kingdom. J Pharm Pharmacol 2018;70:1324–1331.Howlett M, Curtin M, Doherty D, Gleeson P, Sheerin M, Breatnach C. Paediatric standardised concentration infusions – A national solution. Arch Dis Child. 2016;101:e2.Blandford A, Dykes PC, Franklin BD, et al. Intravenous Infusion Administration: A comparative study of practices and errors between the United States and England and their Implications for patient safety. Drug Saf. 2019;42:1157–1165

scholarly journals The Impact of Technology on Prescribing Errors in Pediatric Intensive Care: A Before and After Study

2020 ◽  
Vol 11 (02) ◽  
pp. 323-335 ◽  
Author(s):  
Moninne M. Howlett ◽  
Eileen Butler ◽  
Karen M. Lavelle ◽  
Brian J. Cleary ◽  
Cormac V. Breatnach
Keyword(s):  
Intensive Care ◽  
New Technology ◽  
Tertiary Care ◽  
Pediatric Intensive Care ◽  
Error Rates ◽  
Electronic Prescribing ◽  
Prescribing Errors ◽  
Before And After ◽  
The Impact ◽  
Before And After Study

Abstract Background Increased use of health information technology (HIT) has been advocated as a medication error reduction strategy. Evidence of its benefits in the pediatric setting remains limited. In 2012, electronic prescribing (ICCA, Philips, United Kingdom) and standard concentration infusions (SCIs)—facilitated by smart-pump technology—were introduced into the pediatric intensive care unit (PICU) of an Irish tertiary-care pediatric hospital. Objective The aim of this study is to assess the impact of the new technology on the rate and severity of PICU prescribing errors and identify technology-generated errors. Methods A retrospective, before and after study design, was employed. Medication orders were reviewed over 24 weeks distributed across four time periods: preimplementation (Epoch 1); postimplementation of SCIs (Epoch 2); immediate postimplementation of electronic prescribing (Epoch 3); and 1 year postimplementation (Epoch 4). Only orders reviewed by a clinical pharmacist were included. Prespecified definitions, multidisciplinary consensus and validated grading methods were utilized. Results A total of 3,356 medication orders for 288 patients were included. Overall error rates were similar in Epoch 1 and 4 (10.2 vs. 9.8%; p = 0.8), but error types differed (p < 0.001). Incomplete and wrong unit errors were eradicated; duplicate orders increased. Dosing errors remained most common. A total of 27% of postimplementation errors were technology-generated. Implementation of SCIs alone was associated with significant reductions in infusion-related prescribing errors (29.0% [Epoch 1] to 14.6% [Epoch 2]; p < 0.001). Further reductions (8.4% [Epoch 4]) were identified after implementation of electronically generated infusion orders. Non-infusion error severity was unchanged (p = 0.13); fewer infusion errors reached the patient (p < 0.01). No errors causing harm were identified. Conclusion The limitations of electronic prescribing in reducing overall prescribing errors in PICU have been demonstrated. The replacement of weight-based infusions with SCIs was associated with significant reductions in infusion prescribing errors. Technology-generated errors were common, highlighting the need for on-going research on HIT implementation in pediatric settings.

scholarly journals The prevalence and characteristics of rapid response systems in hospitals with pediatric intensive care units in Japan and barriers to their use

2020 ◽  
Vol 32 (5) ◽  
pp. 325-331
Author(s):  
Taiki Haga ◽  
Hiroshi Kurosawa ◽  
Junji Maruyama ◽  
Katsuko Sakamoto ◽  
Ryo Ikebe ◽  
...  
Keyword(s):  
Intensive Care ◽  
Intensive Care Units ◽  
Pediatric Intensive Care ◽  
The United States ◽  
Rapid Response ◽  
Full Time ◽  
Pediatric Intensive Care Units ◽  
Rapid Response Systems ◽  
Significant Difference ◽  
Response Systems

Abstract Objective The use of pediatric rapid response systems (RRSs) to improve the safety of hospitalized children has spread in various western countries including the United States and the United Kingdom. We aimed to determine the prevalence and characteristics of pediatric RRSs and barriers to use in Japan, where epidemiological information is limited. Design A cross-sectional online survey. Setting All 34 hospitals in Japan with pediatric intensive care units (PICUs) in 2019. Participants One PICU physician per hospital responded to the questionnaire as a delegate. Main outcome measures Prevalence of pediatric RRSs in Japan and barriers to their use. Results The survey response rate was 100%. Pediatric RRSs had been introduced in 14 (41.2%) institutions, and response teams comprised a median of 6 core members. Most response teams employed no full-time members and largely comprised members from multiple disciplines and departments who served in addition to their main duties. Of 20 institutions without pediatric RRSs, 11 (55%) hoped to introduce them, 14 (70%) had insufficient knowledge concerning them and 11 (55%) considered that their introduction might be difficult. The main barrier to adopting RRSs was a perceived personnel and/or funding shortage. There was no significant difference in hospital beds (mean, 472 vs. 524, P = 0.86) and PICU beds (mean, 10 vs. 8, P = 0.34) between institutions with/without pediatric RRSs. Conclusions Fewer than half of Japanese institutions with PICUs had pediatric RRSs. Operating methods for and obstructions to RRSs were diverse. Our findings may help to popularize pediatric RRSs.

Prevalence of adverse events in pediatric intensive care units in the United States*

2010 ◽  
Vol 11 (5) ◽  
pp. 568-578 ◽  
Author(s):  
Swati Agarwal ◽  
David Classen ◽  
Gitte Larsen ◽  
Nancy M. Tofil ◽  
Leslie W. Hayes ◽  
...  
Keyword(s):  
United States ◽  
Intensive Care ◽  
Adverse Events ◽  
Intensive Care Units ◽  
Pediatric Intensive Care ◽  
The United States ◽  
Pediatric Intensive Care Units

P33 Health information technology and the changing nature of medication errors in paediatric intensive care – a modified delphi process

2018 ◽  
Vol 103 (2) ◽  
pp. e2.37-e2
Author(s):  
Moninne Howlett ◽  
Brian Cleary ◽  
Cormac Breatnach
Keyword(s):  
Information Technology ◽  
Intensive Care ◽  
Medication Error ◽  
Health Information ◽  
Medication Errors ◽  
Delphi Process ◽  
Paediatric Intensive Care ◽  
Electronic Prescribing ◽  
Prescribing Error ◽  
Smart Pump

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.

Developing a drug library for smart pumps in a pediatric intensive care unit

2012 ◽  
Vol 54 (3) ◽  
pp. 155-161 ◽  
Author(s):  
Silvia Manrique-Rodríguez ◽  
Amelia Sánchez-Galindo ◽  
Cecilia M. Fernández-Llamazares ◽  
Jesús López-Herce ◽  
Isabel García-López ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Pediatric Intensive Care Unit ◽  
Pediatric Intensive Care ◽  
Smart Pumps

Nosocomial Infections in Pediatric Intensive Care Units in the United States

PEDIATRICS ◽  
1999 ◽  
Vol 103 (4) ◽  
pp. e39-e39 ◽  
Author(s):  
Michael J. Richards ◽  
Jonathan R. Edwards ◽  
David H. Culver ◽  
Robert P. Gaynes ◽  
Keyword(s):  
United States ◽  
Intensive Care ◽  
Intensive Care Units ◽  
Nosocomial Infections ◽  
Pediatric Intensive Care ◽  
The United States ◽  
Pediatric Intensive Care Units

Impact of Pediatric Intensive Care Unit Admission on Family Financial Status and Productivity: A Pilot Study

2017 ◽  
Vol 34 (11-12) ◽  
pp. 973-977 ◽  
Author(s):  
Maureen E. Clark ◽  
Brian M. Cummings ◽  
Karen Kuhlthau ◽  
Natalie Frassica ◽  
Natan Noviski
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Pediatric Intensive Care Unit ◽  
Work Productivity ◽  
Pediatric Intensive Care ◽  
The United States ◽  
Mitigation Strategies ◽  
Annual Income ◽  
Normal Life ◽  
The Impact

Objective: A child’s pediatric intensive care unit (PICU) admission may have wide-ranging family implications. We assessed nonmedical out-of-pocket expenses (NMOOPEs) and disruptions in work and normal life for parents with a child admitted to the PICU for at least 2 days with acute, new onset, or exacerbation of a critical condition. Design: We conducted a prospective, single-center study; administered a daily verbal response survey on NMOOPEs; stratified families by annual income (<$50 999, $51-99 000, >$100 000); and calculated daily expenditures (DEs), estimated daily budgets (DBs), and percentage of NMOOPEs (%DE/DB). We used a modified caregiver version of the Work Productivity and Activity Impairment Scale to assess the impact of PICU admission on work-related and normal life activities. Setting: The PICU in an academic, tertiary medical center in the United States. Patients: Patients admitted to PICU. Interventions: None. Measurements and Main Results: The study included 38 families, with median length of PICU stay of 3 days (range 3-13). The mean total NMOOPE was $127 ± $107 (range $5-$511). Financial impact of DB in the 3 annual income groups ranged from 0% to 136% (median 36%), 5% to 18% (median 10%), and 4% to 39% (median 16%), respectively. Total work absenteeism for cohort was 78 days. High levels of distraction were reported in working families, and normal daily activities were interrupted or suspended. Conclusions: PICU hospitalization results in a range of direct NMOOPEs of varying burden on families and additional work productivity impact. Further research to understand the array of financial implications on families and additional mitigation strategies are needed.

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