Smart pumps improve medication safety but increase alert burden in neonatal care

Melton, Kristin; Timmons, Kristen; Walsh, Kathleen E.; Meinzen‐Derr, Jareen; Kirkendall, Eric S.

doi:10.1186/s12911-019-0945-2

Cited by 19 publications

(8 citation statements)

References 32 publications

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“…As observed in our studies, minor discrepancies are typically more numerous (Table 4) [10]. Other studies have also noted that medication errors are numerous but are often small and associated with low rates of harm [7,[16][17][18][19]. The risk of calling out these frequent, small discrepancies is an increase in workload and decrease in overall attention.…”

Section: Principal Findingssupporting

confidence: 76%

“…This effect, however, is heavily dependent on user compliance and utilization of specific functionalities vendor products afford, including dose error reduction software [6]. As with EHRs, infusion pump alerts are another source of alert burden and are subject to alert fatigue, which raises a trade-off between potential safety benefits and increased workload for providers [7]. Smart pumps, compared with their analogue counterparts, generate a lot of data to log user interaction with the pumps (eg, pausing of pump infusions and pump alert overrides) and the pump status (eg, infusion start and infusion complete), which are associated with granular timestamps.…”

Section: Introductionmentioning

confidence: 99%

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Integrating and Evaluating the Data Quality and Utility of Smart Pump Information in Detecting Medication Administration Errors: Evaluation Study (Preprint)

Ni¹,

Lingren²,

Huth³

et al. 2020

Preprint

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BACKGROUND At present, electronic health records (EHRs) are the central focus of clinical informatics given their role as the primary source of clinical data. Despite their granularity, the EHR data heavily rely on manual input and are prone to human errors. Many other sources of data exist in the clinical setting, including digital medical devices such as smart infusion pumps. When incorpo-rated with prescribing data from the EHRs, smart pump records (SPR) are capable of shedding light on actions taking place during the medication use process. Nevertheless, harmonizing the two sources is hindered by multiple technical challenges, and the usability and utility of SPRs have not been realized. OBJECTIVE In this study we incorporated SPRs with EHR data to evaluate their usability and utility in detecting medication administration errors. Our overarching hypothesis was that SPRs would contribute unique information in the medication use process, enabling more comprehensive detection of discrepancies and potential errors in medication administration. METHODS We evaluated the medication use process of nine high-risk medications for patients admitted to the neonatal intensive care unit during a one-year period. An automated algorithm was developed to align SPRs with their medication orders in the EHRs using patient ID, medication name and timestamp. The aligned data were manually reviewed by a clinical research coordinator and two pediatric physicians to identify discrepancies in medication administration. The usability of SPRs was assessed with the proportion of usable data that were linked to valid EHR orders. To evaluate their utility, we compared the frequency and severity of discrepancies captured by the SPR and EHR data respectively. A novel concordance assessment was also developed to under-stand the detection power and capabilities of SPR and EHR data. RESULTS Approximately 70% of the SPRs contained valid patient IDs and medication names, making them usable for data integration. After combing the two sources, the investigative team re-viewed 2307 medication orders with 10575 medication administration records (MARs) and 23397 SPRs. A total of 321 MAR and 682 SPR discrepancies were identified, with vasopressors showing the highest discrepancy rates, followed by narcotics and total parenteral nutrition. Compared to EHR MARs, substantial dosing discrepancies were more detectable using the SPRs. The concordance analysis showed little overlap between MAR and SPR discrepancies, with most discrepancies captured by the SPR data. CONCLUSIONS We integrated smart infusion pump information with EHR data to make visible the most error-prone phases of the medication lifecycle. The findings suggested that SPRs could be a more re-liable data source for medication error detection. Ultimately, it is imperative to integrate SPR information with EHR data to fully detect and mitigate medication administration errors in the clinical setting.

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Section: Principal Findingssupporting

confidence: 76%

Section: Introductionmentioning

confidence: 99%

Integrating and Evaluating the Data Quality and Utility of Smart Pump Information in Detecting Medication Administration Errors: Evaluation Study (Preprint)

Ni¹,

Lingren²,

Huth³

et al. 2020

Preprint

Self Cite

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“…They aim to remove the element of human error when setting up infusion pumps. Studies have demonstrated a reduction in programming error rates but with the introduction of new error types—for example, overriding pump warnings and outdated drug libraries 63–67 . A recent NHS funded review of infusion devices recommended that advisory boards of relevant multiprofessional organizations should develop validated national drug libraries for smart infusion pumps 68 .…”

Section: Discussionmentioning

confidence: 99%

“…Studies have demonstrated a reduction in programming error rates but with the introduction of new error types-for example, overriding pump warnings and outdated drug libraries. [63][64][65][66][67] A recent NHS funded review of infusion devices recommended that advisory boards of relevant multiprofessional organizations should develop validated national drug libraries for smart infusion pumps. 68 This could be a positive step in the development of smart pumps and their role in reducing programming errors for PN infusions.…”

Section: Recommendationsmentioning

confidence: 99%

National evaluation of harm associated with patient safety incident reports related to the provision of parenteral nutrition to patients, using a national incident reporting system

2023

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BackgroundParenteral nutrition (PN)–related patient safety incidents have been associated with harm. Large‐scale studies are scarce, and little is known about contributory factors. This study evaluated PN‐related incident reports that described harm using a national database.Materials and MethodsA retrospective evaluation of incident reports involving PN in England and Wales reported to the National Reporting and Learning System between 2015 and 2020. We described frequency by degree of reported harm and incident characteristics. Content analysis was undertaken to understand contributory factors for reports related to moderate/severe harm or death.Results12,907 incident reports were identified. After screening, 2242 were evaluated; 1879 (83.8%) reported no harm, 309 (13.8%) low harm, 47 (0.02%) moderate harm, 4 (0.002%) severe harm, 3 (0.001%) deaths. The most reported age group, medication process, and error category were neonates (<28 days) (n = 570/1923, 29.6%), administration (n = 1126/2242, 50%), and omitted medication/ingredient (n = 291/2242, 13%), respectively. Content analysis of reports related to moderate/severe harm and death revealed patient age of <1 year, dependence on home PN (HPN), comorbidities, and staff errors as contributory factors.ConclusionsThis is the first evaluation of PN‐related incident reports in England and Wales to our knowledge. We demonstrated a low frequency of reports related to moderate or severe harm or death. More incidents were reported for neonates and during the administration processes. To reduce harm, systems/procedures that reduce errors in high‐risk patients (eg, neonates, patients receiving HPN) need to be established within organizations. Database limitations of voluntary reporting systems were recognized.

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“…In contrast, smart interfaces can improve patient safety and allow clinicians to make more precise, direct, and prompt treatment adjustments and circumvent the need to translate a clearly formed therapeutic intent into an unintuitive sequence of manual programming steps. 2 Furthermore, frequently contacted physical touch controls like buttons and dials on anesthesia monitors and machines 3 can be reservoirs for transmissible nosocomial pathogens. Buttons and dials are difficult to sanitize, and pathogens can prove difficult to eradicate 4 despite precautions such as frequent washing of hands 5 and changing of gloves.…”

mentioning

confidence: 99%

Controlling Anesthesia Hardware With Simple Hand Gestures: Thumbs Up or Thumbs Down?

Owens

Connor

2020

Anesthesia &Amp; Analgesia

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BACKGROUND: Modern consumer electronic devices and automobiles are often controlled by interfaces that sense physical gestures and spoken commands. In contrast, patient monitors and anesthesia devices are typically equipped with panel-mounted buttons, dials, and keyboards. The increased use of noncontact gesture-based interfaces in anesthesia may improve patient safety through more intuitive and prompter control of equipment and also through reduced rates of surface contamination. A novel gesture-based controller was designed and retrofitted to a standard GE Solar 8000M patient monitor. This type of technical innovation is rare, due to closely held proprietary input control systems on commercially produced clinical equipment. Nevertheless, we hypothesized that anesthesiologists would find a contactless gesture interface straightforward to use. METHODS: A gesture-based interface system was developed to control a Solar 8000M patient monitor using a millimeter-wave radar sensor. The system was programmed to detect noncontact “rotate” and “press” gestures to control the patient monitor by implementing a virtual trim knob for interface control. Fifty anesthesiologists tested a prototype interface and evaluated usability by completing a short questionnaire incorporating modified Likert scales. These evaluations were performed in a nonpatient care environment so that respondents were not adversely task loaded during assessment, also allaying any ethical or safety concerns regarding use of this novel interface for patient management. RESULTS: Anesthesia hardware was controlled reliably with 2 distinct gestures above the gesture sensor. The gesture-based interface generally was well received by anesthesiologists (8.09; confidence interval, 8.06–8.12 on a 10-point scale), who preferred the simpler “press” gesture to the “rotate” gesture (8.45; 8.39–8.51 vs 7.73; 7.67–7.79 on a 10-point scale; P = .005). The correlation between the preference scores for the 2 gestures from each anesthesiologist was strong (Pearson r = 0.49; 0.25–0.68; P < .001). Advancing level of training (resident, fellow, attending 1–10 years, attending >10 years) was not correlated with preference scores for either gesture (Spearman ρ = −0.02; −0.30 to 0.26; P = .87 for “press” and Spearman ρ = 0.08; −0.20 to 0.35; P = .58 for “rotate”). CONCLUSIONS: The use of gesture sensing for controlling anesthesia equipment was well received by a cohort of anesthesiologists. Even though the simpler “press” gesture was preferred over the “rotate” gesture, the intrarespondent correlation indicates that the preference for gestures as a whole is the stronger effect. No adverse relationship was found between acceptability and anesthesia experience level. Gesture sensing is a promising new area to simplify and improve the interaction between the anesthesiologist and the anesthesia workstation.

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Smart pumps improve medication safety but increase alert burden in neonatal care

Cited by 19 publications

References 32 publications

Integrating and Evaluating the Data Quality and Utility of Smart Pump Information in Detecting Medication Administration Errors: Evaluation Study (Preprint)

Integrating and Evaluating the Data Quality and Utility of Smart Pump Information in Detecting Medication Administration Errors: Evaluation Study (Preprint)

National evaluation of harm associated with patient safety incident reports related to the provision of parenteral nutrition to patients, using a national incident reporting system

Controlling Anesthesia Hardware With Simple Hand Gestures: Thumbs Up or Thumbs Down?

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