Brief report: Improving communication of diagnostic uncertainty to families of hospitalized children.

OBJECTIVES: Diagnostic uncertainty is not reliably communicated to patients and caregivers. This study aims to identify barriers and facilitators to effective communication of diagnostic uncertainty, including development of potential tools and strategies for improvement, as perceived by healthcare professionals and caregivers. METHODS: We completed structured interviews with providers and caregivers of hospitalized children with uncertain diagnoses (UD). The interview guides addressed barriers to communication, key components for communication of uncertainty, and qualities of effective communication. The interviews concluded with respondents prioritizing potential interventions to improve communication of uncertainty. Interviews were audio recorded, transcribed, and independently analyzed by two team members to identify common themes. RESULTS: Ten provider and five caregiver interviews were conducted. Common barriers to communication of uncertainty included time constraints, language barriers, and lack of clear definition of UD. Caregiver suggestions for improvement included sharing expectations of the diagnostic process and use of both written and visual communication tools. Interview respondents favored interventions of a sign summarizing the key components of diagnostic uncertainty for display in patient rooms and a structured diagnostic pause during daily rounds. CONCLUSIONS: We identified several potential interventions that may enhance communication of diagnostic uncertainty and better engage patients and caregivers in the diagnostic process.

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

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 incorporated with prescribing data from EHRs, smart pump records (SPRs) are capable of shedding light on actions that take place during the medication use process. However, harmoniz-ing the 2 sources is hindered by multiple technical challenges, and the data quality and utility of SPRs have not been fully realized. OBJECTIVE: This study aims to evaluate the quality and utility of SPRs incorporated with EHR data in detecting medication administration errors. Our overarching hypothesis is that SPRs would contribute unique information in the med-ication use process, enabling more comprehensive detection of discrepancies and potential errors in medication administration. METHODS: We evaluated the medication use process of 9 high-risk medications for patients admitted to the neonatal inten-sive care unit during a 1-year period. An automated algorithm was developed to align SPRs with their medica-tion orders in the EHRs using patient ID, medication name, and timestamp. The aligned data were manually re-viewed by a clinical research coordinator and 2 pediatric physicians to identify discrepancies in medication ad-ministration. The data quality of SPRs was assessed with the proportion of information that was 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 understand the detec-tion power and capabilities of SPR and EHR data. RESULTS: Approximately 70% of the SPRs contained valid patient IDs and medication names, making them feasible for data integration. After combining the 2 sources, the investigative team reviewed 2307 medication orders with 10,575 medication administration records (MARs) and 23,397 SPRs. A total of 321 MAR and 682 SPR dis-crepancies were identified, with vasopressors showing the highest discrepancy rates, followed by narcotics and total parenteral nutrition. Compared with EHR MARs, substantial dosing discrepancies were more commonly detectable using the SPRs. The concordance analysis showed little overlap between MAR and SPR discrepan-cies, with most discrepancies captured by the SPR data. CONCLUSIONS: We integrated smart infusion pump information with EHR data to analyze the most error-prone phases of the medication lifecycle. The findings suggested that SPRs could be a more reliable 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.

Human-Based Errors Involving Smart Infusion Pumps: A Catalog of Error Types and Prevention Strategies.

Over 4000 preventable injuries due to medication errors occur each year in any given hospital. Smart pumps have been widely introduced as one means to prevent these errors. Although smart pumps have been implemented to prevent errors, they fail to prevent specific types of errors in the medication administration process and may introduce new errors themselves. As a result, unique prevention strategies have been implemented by providers. No catalog of smart pump error types and prevention strategies currently exists. The aim of this study is to review and catalog the types of human-based errors related to smart pump use identified in the literature and to summarize the associated error-prevention strategies. We searched MEDLINE, PubMed, PubMed Central, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) for literature pertaining to human-based errors associated with smart pumps. Studies related to smart pump implementation, other types of pumps, and mechanical failures were excluded. Final selections were mapped for error types and associated prevention strategies. A total of 1177 articles were initially identified, and 105 articles were included in the final review. Extraction of error types and prevention strategies resulted in the identification of 18 error types and ten prevention strategies. Through a comprehensive literature review, we compiled a catalog of smart pump-related errors and associated prevention strategies. Strategies were mapped to error types to provide an initial framework for others to use as a resource in their error reviews and improvement work. Future research should assess the application of the resources provided by this review.

Association Between Statewide School Closure and COVID-19 Incidence and Mortality in the US.

Importance: In the US, states enacted nonpharmaceutical interventions, including school closure, to reduce the spread of coronavirus disease 2019 (COVID-19). All 50 states closed schools in March 2020 despite uncertainty if school closure would be effective. Objective: To determine if school closure and its timing were associated with decreased COVID-19 incidence and mortality. Design, Setting, and Participants: US population-based observational study conducted between March 9, 2020, and May 7, 2020, using interrupted time series analyses incorporating a lag period to allow for potential policy-associated changes to occur. To isolate the association of school closure with outcomes, state-level nonpharmaceutical interventions and attributes were included in negative binomial regression models. States were examined in quartiles based on state-level COVID-19 cumulative incidence per 100 000 residents at the time of school closure. Models were used to derive the estimated absolute differences between schools that closed and schools that remained open as well as the number of cases and deaths if states had closed schools when the cumulative incidence of COVID-19 was in the lowest quartile compared with the highest quartile. Exposures: Closure of primary and secondary schools. Main Outcomes and Measures: COVID-19 daily incidence and mortality per 100 000 residents. Results: COVID-19 cumulative incidence in states at the time of school closure ranged from 0 to 14.75 cases per 100 000 population. School closure was associated with a significant decline in the incidence of COVID-19 (adjusted relative change per week, -62% [95% CI, -71% to -49%]) and mortality (adjusted relative change per week, -58% [95% CI, -68% to -46%]). Both of these associations were largest in states with low cumulative incidence of COVID-19 at the time of school closure. For example, states with the lowest incidence of COVID-19 had a -72% (95% CI, -79% to -62%) relative change in incidence compared with -49% (95% CI, -62% to -33%) for those states with the highest cumulative incidence. In a model derived from this analysis, it was estimated that closing schools when the cumulative incidence of COVID-19 was in the lowest quartile compared with the highest quartile was associated with 128.7 fewer cases per 100 000 population over 26 days and with 1.5 fewer deaths per 100 000 population over 16 days. Conclusions and Relevance: Between March 9, 2020, and May 7, 2020, school closure in the US was temporally associated with decreased COVID-19 incidence and mortality; states that closed schools earlier, when cumulative incidence of COVID-19 was low, had the largest relative reduction in incidence and mortality. However, it remains possible that some of the reduction may have been related to other concurrent nonpharmaceutical interventions.

Cardiorespiratory and Pulse Oximetry Monitoring in Hospitalized Children: A Delphi Process.

OBJECTIVES: Cardiorespiratory and pulse oximetry monitoring in children who are hospitalized should balance benefits of detecting deterioration with potential harms of alarm fatigue. We developed recommendations for monitoring outside the ICU on the basis of available evidence and expert opinion. METHODS: We conducted a comprehensive literature search for studies addressing the utility of cardiorespiratory and pulse oximetry monitoring in common pediatric conditions and drafted candidate monitoring recommendations based on our findings. We convened a panel of nominees from national professional organizations with diverse expertise: nursing, medicine, respiratory therapy, biomedical engineering, and family advocacy. Using the RAND/University of California, Los Angeles Appropriateness Method, panelists rated recommendations for appropriateness and necessity in 3 sequential rating sessions and a moderated meeting. RESULTS: The panel evaluated 56 recommendations for intermittent and continuous monitoring for children hospitalized outside the ICU with 7 common conditions (eg, asthma, croup) and/or receiving common therapies (eg, supplemental oxygen, intravenous opioids). The panel reached agreement on the appropriateness of monitoring recommendations for 55 of 56 indications and on necessity of monitoring for 52. For mild or moderate asthma, croup, pneumonia, and bronchiolitis, the panel recommended intermittent vital sign or oximetry measurement only. The panel recommended continuous monitoring for severe disease in each respiratory condition as well as for a new or increased dose of intravenous opiate or benzodiazepine. CONCLUSIONS: Expert panel members agreed that intermittent vital sign assessment, rather than continuous monitoring, is appropriate management for a set of specific conditions of mild or moderate severity that require hospitalization.

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

BACKGROUND: Smart pumps have been widely adopted but there is limited evidence to understand and support their use in pediatric populations. Our objective was to assess whether smart pumps are effective at reducing medication errors in the neonatal population and determine whether they are a source of alert burden and alert fatigue in an intensive care environment. METHODS: Using smart pump records, over 370,000 infusion starts for continuously infused medications used in neonates and infants hospitalized in a level IV NICU from 2014 to 2016 were evaluated. Attempts to exceed preset soft and hard maximum limits, percent variance from those limits, and pump alert frequency, patterns and salience were evaluated. RESULTS: Smart pumps prevented 160 attempts to exceed the hard maximum limit for doses that were as high as 7-29 times the maximum dose and resulted in the reprogramming or cancellation of 2093 infusions after soft maximum alerts. While the overall alert burden from smart pumps for continuous infusions was not high, alerts clustered around specific patients and medications, and a small portion (17%) of infusions generated the majority of alerts. Soft maximum alerts were often overridden (79%), consistent with low alert salience. CONCLUSIONS: Smart pumps have the ability to improve neonatal medication safety when compliance with dose error reducing software is high. Numerous attempts to administer high doses were intercepted by dosing alerts. Clustered alerts may generate a high alert burden and limit safety benefit by desensitizing providers to alerts. Future efforts should address ways to improve alert salience.

Nurse Responses to Physiologic Monitor Alarms on a General Pediatric Unit.

BACKGROUND: Hospitalized children generate up to 152 alarms per patient per day outside of the intensive care unit. In that setting, as few as 1% of alarms are clinically important. How nurses make decisions about responding to alarms, given an alarm's low specificity for detecting clinical deterioration, remains unclear. OBJECTIVE: Our objective was to describe how bedside nurses think about and act upon monitor alarms for hospitalized children. DESIGN, SETTING, PARTICIPANTS: This was a qualitative study that involved the direct observation of nurses working on a general pediatric unit at a large children's hospital. MEASUREMENTS: We used a structured tool that included predetermined categories to assess nurse responses to monitor alarms. Data on alarm frequency and type were pulled from bedside monitors. RESULTS: We conducted 61.3 patient-hours of observation with nine nurses, in which we documented 207 nurse responses to patient alarms. For 67% of alarms heard outside of the room, the nurse decided not to respond without further assessment. Nurses most commonly cited reassuring clinical context (eg, medical team in room), as the rationale for alarm nonresponse. The nurse deemed clinical intervention necessary in only 14 (7%) of the observed responses. CONCLUSION: Nurses rely on clinical and contextual details to determine how to respond to alarms. Few of the alarm responses in our study resulted in a clinical intervention. These findings suggest that multiple system-level and educational interventions may be necessary to improve the efficacy and safety of continuous monitoring.

Factors Influencing Use of Continuous Physiologic Monitors for Hospitalized Pediatric Patients.

OBJECTIVES: Continuous physiologic monitors (CPMs) generate frequent alarms and are used for up to 50% of children who are hospitalized outside of the ICU. Our objective was to assess factors that influence the decision to use CPMs. METHODS: In this qualitative study, we used group-level assessment, a structured method designed to engage diverse stakeholder groups. We recruited clinicians and other staff who work on a 48-bed hospital medicine unit at a freestanding children's hospital. We developed a list of open-ended prompts used to address CPM use on inpatient units. Demographic data were collected from each participant. We conducted 6 sessions to permit maximum participation among all groups, and themes from all sessions were merged and distilled. RESULTS: Participants (n = 78) included nurses (37%), attending physicians (17%), pediatric residents (32%), and unit staff (eg, unit coordinator; 14%). Participants identified several themes. First, there are patient factors (eg, complexity and instability) for which CPMs are useful. Second, participants perceived that alarms have negative effects on families (eg, anxiety and sleep deprivation). Third, CPMs are often used as surrogates for clinical assessments. Fourth, CPM alarms cause anxiety and fatigue for frontline staff. Fifth, the decision to use CPMs should be, but is not often, a team decision. Sixth, and finally, there are issues related to the monitor system's setup that reduces its utility. CONCLUSIONS: Hospital medicine staff identified patient-, staff-, and system-level factors relevant to CPM use for children who were hospitalized. These data will inform the development of system-level interventions to improve CPM use and address high alarm rates.

Using Quality Improvement to Introduce and Standardize the National Early Warning Score (NEWS) for Adult Inpatients at a Children's Hospital.

INTRODUCTION: The population of adults with childhood-onset chronic illness is growing across children's hospitals and constitutes a high risk population. National Early Warning Score (NEWS) is among the most recently validated adult early warning scores (EWSs) for early recognition of and response to clinical deterioration. Our aim was to implement and standardize NEWS scoring in 80% of patients age 21 and older admitted to a children's hospital. METHODS: Our intervention was tested on a single unit of our children's hospital. The primary process measure was the percentage of NEWS documented within 1 hour of routine nursing assessments, and was tracked using a run chart. Improvement activities focused on effective training, key stakeholder buy-in, increased awareness, real-time mitigation of failures, accountability for adherence, and action-oriented response. We also tracked the distribution of NEWS values and medical emergency team calls. RESULTS: The percentage of NEWS documented with routine nursing assessments for patients age 21 and over increased from 0% to 90% within 15 weeks and remained at 77% or greater for 17 weeks. Our distribution of NEWS values was similar to previously reported NEWS distribution. CONCLUSIONS: A nurse-driven adult early warning system for inpatients age 21 and older at a children's hospital can be achieved through a standardized EWS assessment process, incorporation into the electronic health record, and charge nurse and key stakeholder oversight. Furthermore, implementation of an adult EWS being used at a pediatric institution and our distribution of NEWS values were comparable to distribution published from adult hospitals.

Using Address Information to Identify Hardships Reported by Families of Children Hospitalized With Asthma.

OBJECTIVE: Socioeconomic hardship is common among children hospitalized for asthma but often not practically measurable. Information on where a child resides is universally available. We sought to determine the correlation between neighborhood-level socioeconomic data and family-reported hardships. METHODS: Caregivers of 774 children hospitalized with asthma answered questions regarding income, financial strain, and primary care access. Addresses were geocoded and linked to zip code-, census tract-, and block group-level (neighborhood) data from the US Census. We then compared neighborhood median household income with family-reported household income; percentage of neighborhood residents living in poverty with family-reported financial strain; and percentage of neighborhood households without an available vehicle with family-reported access to primary care. We constructed heat maps and quantified correlations using Kendall rank correlation coefficient. Receiver operator characteristic curves were used to assess predictive abilities of neighborhood measures. RESULTS: The cohort was 57% African American and 73% publicly-insured; 63% reported income <$30,000, 32% endorsed ≥4 financial strain measures, and 38% reported less than adequate primary care access. Neighborhood median household income was significantly and moderately correlated with and predictive of reported household income; neighborhood poverty was similarly related to financial strain; neighborhood vehicle availability was weakly correlated with and predictive of primary care access. Correlations and predictions provided by zip code measures were similar to those of census tract and block group. CONCLUSIONS: Universally available neighborhood information might help efficiently identify children and families with socioeconomic hardships. Systematic screening with area-level socioeconomic measures has the potential to inform resource allocation more efficiently.