Ongoing management of monitor alarms is important for reducing alarm fatigue among clinicians (e.g., nurses, physicians). Strategies to enhance clinician engagement in active alarm management in pediatric acute care have not been well explored. Access to alarm summary metrics may enhance clinician engagement. To lay the foundation for intervention development, we sought to identify functional specifications for formulating, packaging, and delivering alarm metrics to clinicians. Our team of clinician scientists and human factors engineers conducted focus groups with clinicians from medical-surgical inpatient units in a children's hospital. We inductively coded transcripts, developed codes into themes, and grouped themes into "current state" and "future state." We conducted five focus groups with 13 clinicians (eight registered nurses and five doctors of medicine). In the current state, information exchanged among team members about alarm burden is initiated by nurses on an ad hoc basis. For a future state, clinicians identified ways in which alarm metrics could help them manage alarms and described specific information, such as alarm trends, benchmarks, and contextual data, that would support decision-making. We developed four recommendations for future strategies to enhance clinicians' active management of patient alarms: (1) formulate alarm metrics for clinicians by categorizing alarm rates by type and summarizing alarm trends over time, (2) package alarm metrics with contextual patient data to facilitate clinicians' sensemaking, (3) deliver alarm metrics in a forum that facilitates interprofessional discussion, and (4) provide clinician education to establish a shared mental model about alarm fatigue and evidence-based alarm-reduction strategies.
Ongoing management of monitor alarms is important for reducing alarm fatigue among clinicians (e.g., nurses, physicians). Strategies to enhance clinician engagement in active alarm management in pediatric acute care have not been well explored. Access to alarm summary metrics may enhance clinician engagement. To lay the foundation for intervention development, we sought to identify functional specifications for formulating, packaging, and delivering alarm metrics to clinicians. Our team of clinician scientists and human factors engineers conducted focus groups with clinicians from medical-surgical inpatient units in a children's hospital. We inductively coded transcripts, developed codes into themes, and grouped themes into "current state" and "future state." We conducted five focus groups with 13 clinicians (eight registered nurses and five doctors of medicine). In the current state, information exchanged among team members about alarm burden is initiated by nurses on an ad hoc basis. For a future state, clinicians identified ways in which alarm metrics could help them manage alarms and described specific information, such as alarm trends, benchmarks, and contextual data, that would support decision-making. We developed four recommendations for future strategies to enhance clinicians' active management of patient alarms: (1) formulate alarm metrics for clinicians by categorizing alarm rates by type and summarizing alarm trends over time, (2) package alarm metrics with contextual patient data to facilitate clinicians' sensemaking, (3) deliver alarm metrics in a forum that facilitates interprofessional discussion, and (4) provide clinician education to establish a shared mental model about alarm fatigue and evidence-based alarm-reduction strategies.
Clinical units and their nursing staffs are heterogeneous. Advances in data and analytics provide opportunities to better match patient needs with nurse competencies. Building upon a previous publication on a unit profile dashboard, team members now describe development of a nursing dashboard aggregating characteristics of staff on each clinical unit of the hospital. This article describes methods, challenges, and future directions for nurse leaders to use the dashboards to optimize care delivery and patient and nurse outcomes.
BACKGROUND: Methods of sustaining the deimplementation of overused medical practices (i.e., practices not supported by evidence) are understudied. In pediatric hospital medicine, continuous pulse oximetry monitoring of children with the common viral respiratory illness bronchiolitis is recommended only under specific circumstances. Three national guidelines discourage its use for children who are not receiving supplemental oxygen, but guideline-discordant practice (i.e., overuse) remains prevalent. A 6-hospital pilot of educational outreach with audit and feedback resulted in immediate reductions in overuse; however, the best strategies to optimize sustainment of deimplementation success are unknown.
METHODS: The Eliminating Monitor Overuse (EMO) trial will compare two deimplementation strategies in a hybrid type III effectiveness-deimplementation trial. This longitudinal cluster-randomized design will be conducted in Pediatric Research in Inpatient Settings (PRIS) Network hospitals and will include baseline measurement, active deimplementation, and sustainment phases. After a baseline measurement period, 16-19 hospitals will be randomized to a deimplementation strategy that targets unlearning (educational outreach with audit and feedback), and the other 16-19 will be randomized to a strategy that targets unlearning and substitution (adding an EHR-integrated clinical pathway decision support tool). The primary outcome is the sustainment of deimplementation in bronchiolitis patients who are not receiving any supplemental oxygen, analyzed as a longitudinal difference-in-differences comparison of overuse rates across study arms. Secondary outcomes include equity of deimplementation and the fidelity to, and cost of, each deimplementation strategy. To understand how the deimplementation strategies work, we will test hypothesized mechanisms of routinization (clinicians developing new routines supporting practice change) and institutionalization (embedding of practice change into existing organizational systems).
DISCUSSION: The EMO trial will advance the science of deimplementation by providing new insights into the processes, mechanisms, costs, and likelihood of sustained practice change using rigorously designed deimplementation strategies. The trial will also advance care for a high-incidence, costly pediatric lung disease.
TRIAL REGISTRATION: ClinicalTrials.gov, NCT05132322 . Registered on November 10, 2021.
<p>Home pulse oximeters prescribed for infants with cardiorespiratory conditions generate many false alarms, which create caregiver stress and sleep disturbance and can lead to unsafe practices. Additionally, relationships among oximeters, alarms, and everyday living demands are not well understood. Therefore, we aimed to gather parent perspectives on home pulse oximetry monitoring during the problem analysis phase of a quality improvement (QI) initiative.</p>
<p><strong>Methods: </strong>We purposively sampled and interviewed parents of infants prescribed home pulse oximeters and receiving local home care company services. We based questions on systems engineering frameworks previously used in healthcare. Data were coded iteratively and analyzed deductively (theoretical frameworks) and inductively (emerging themes).</p>
<p><strong>Results: </strong>Generally, themes aligned with theoretical frameworks. Parents expressed dissatisfaction with the number of false alarms home pulse oximeters generate, which parents primarily attributed to poor probe adhesiveness and the inability of oximeters to account for infant movement. Interviews highlighted the burden associated with poor device tones and portability. Device-related issues had negative repercussions for the entire family related to sleep quality, mobility, and social interactions. Universally, parents developed workarounds, including cessation of monitoring.</p>
<p><strong>Conclusions: </strong>Parents of infants monitored at home using pulse oximetry face many challenges, resulting in compromises in safety. Continuing to instruct parents to comply with prescribed monitoring recommendations may be unrealistic. Instead, we suggest re-engineering the home monitoring system with the needs and goals of children and their families at the center. Our description of adapting qualitative research and systems engineering methods may benefit others developing QI work.</p>
<p><em><strong>Background: </strong></em>A comorbidity summary score may support early and systematic identification of women at high risk for adverse obstetric outcomes. The objective of this study was to conduct the initial development and validation of an obstetrics comorbidity risk score for automated implementation in the electronic health record (EHR) for clinical use. <em><strong>Methods: </strong></em>The score was developed and validated using EHR data for a retrospective cohort of pregnancies with delivery between 2010 and 2018 at Kaiser Permanente Northern California, an integrated health care system. The outcome used for model development consisted of adverse obstetric events from delivery hospitalization (<em>e.g.</em>, eclampsia, hemorrhage, death). Candidate predictors included maternal age, parity, multiple gestation, and any maternal diagnoses assigned in health care encounters in the 12 months before admission for delivery. We used penalized regression for variable selection, logistic regression to fit the model, and internal validation for model evaluation. We also evaluated prenatal model performance at 18 weeks of pregnancy. <em><strong>Results:</strong></em> The development cohort ( = 227,405 pregnancies) had an outcome rate of 3.8% and the validation cohort ( = 41,683) had an outcome rate of 2.9%. Of 276 candidate predictors, 37 were included in the final model. The final model had a validation c-statistic of 0.72 (95% confidence interval [CI] 0.70-0.73). When evaluated at 18 weeks of pregnancy, discrimination was modestly diminished (c-statistic 0.68 [95% CI 0.67-0.70]). <em><strong>Conclusions:</strong></em> The obstetric comorbidity score demonstrated good discrimination for adverse obstetric outcomes. After additional appropriate validation, the score can be automated in the EHR to support early identification of high-risk women and assist efforts to ensure risk-appropriate maternal care.</p>
<p><strong>BACKGROUND AND OBJECTIVES: </strong>Continuous pulse oximetry (oxygen saturation [Spo]) monitoring in hospitalized children with bronchiolitis not requiring supplemental oxygen is discouraged by national guidelines, but determining monitoring status accurately requires in-person observation. Our objective was to determine if electronic health record (EHR) data can accurately estimate the extent of actual Spo monitoring use in bronchiolitis.</p>
<p><strong>METHODS: </strong>This repeated cross-sectional study included infants aged 8 weeks through 23 months hospitalized with bronchiolitis. In the validation phase at 3 children's hospitals, we calculated the test characteristics of the Spo monitor data streamed into the EHR each minute when monitoring was active compared with in-person observation of Spo monitoring use. In the application phase at 1 children's hospital, we identified periods when supplemental oxygen was administered using EHR flowsheet documentation and calculated the duration of Spo monitoring that occurred in the absence of supplemental oxygen.</p>
<p><strong>RESULTS: </strong>Among 668 infants at 3 hospitals (validation phase), EHR-integrated Spo data from the same minute as in-person observation had a sensitivity of 90%, specificity of 98%, positive predictive value of 88%, and negative predictive value of 98% for actual Spo monitoring use. Using EHR-integrated data in a sample of 317 infants at 1 hospital (application phase), infants were monitored in the absence of oxygen supplementation for a median 4.1 hours (interquartile range 1.4-9.4 hours). Those who received supplemental oxygen experienced a median 5.6 hours (interquartile range 3.0-10.6 hours) of monitoring after oxygen was stopped.</p>
<p><strong>CONCLUSIONS: </strong>EHR-integrated monitor data are a valid measure of actual Spo monitoring use that may help hospitals more efficiently identify opportunities to deimplement guideline-inconsistent use.</p>
<p><strong>BACKGROUND AND OBJECTIVES: </strong>Physiologic monitor alarms occur at high rates in children's hospitals; ≤1% are actionable. The burden of alarms has implications for patient safety and is challenging to measure directly. Nurse workload, measured by using a version of the National Aeronautics and Space Administration Task Load Index (NASA-TLX) validated among nurses, is a useful indicator of work burden that has been associated with patient outcomes. A recent study revealed that 5-point increases in the NASA-TLX score were associated with a 22% increased risk in missed nursing care. Our objective was to measure the relationship between alarm count and nurse workload by using the NASA-TLX.</p>
<p><strong>METHODS: </strong>We conducted a repeated cross-sectional study of pediatric nurses in a tertiary care children's hospital to measure the association between NASA-TLX workload evaluations (using the nurse-validated scale) and alarm count in the 2 hours preceding NASA-TLX administration. Using a multivariable mixed-effects regression accounting for nurse-level clustering, we modeled the adjusted association of alarm count with workload.</p>
<p><strong>RESULTS: </strong>The NASA-TLX score was assessed in 26 nurses during 394 nursing shifts over a 2-month period. In adjusted regression models, experiencing >40 alarms in the preceding 2 hours was associated with a 5.5 point increase (95% confidence interval 5.2 to 5.7; < .001) in subjective workload.</p>
<p><strong>CONCLUSION: </strong>Alarm count in the preceding 2 hours is associated with a significant increase in subjective nurse workload that exceeds the threshold associated with increased risk of missed nursing care and potential patient harm.</p>