Opportunities to improve diagnosis in emergency transfers to the pediatric intensive care unit.

2023

05/2023

1553-5606

BACKGROUND: Late recognition of in-hospital deterioration is a source of preventable harm. Emergency transfers (ET), when hospitalized patients require intensive care unit (ICU) interventions within 1 h of ICU transfer, are a proximal measure of late recognition associated with increased mortality and length of stay (LOS).

OBJECTIVE: To apply diagnostic process improvement frameworks to identify missed opportunities for improvement in diagnosis (MOID) in ETs and evaluate their association with outcomes.

DESIGN, SETTINGS, AND PARTICIPANTS: A single-center retrospective cohort study of ETs, January 2015 to June 2019. ET criteria include intubation, vasopressor initiation, or 60 mL/kg fluid resuscitation 1 h before to 1 h after ICU transfer. The primary exposure was the presence of MOID, determined using SaferDx. Cases were screened by an ICU and non-ICU physician. Final determinations were made by an interdisciplinary group. Diagnostic process improvement opportunities were identified.

MAIN OUTCOME AND MEASURES: Primary outcomes were in-hospital mortality and posttransfer LOS, analyzed by multivariable regression adjusting for age, service, deterioration category, and pretransfer LOS.

RESULTS: MOID was identified in 37 of 129 ETs (29%, 95% confidence interval [CI] 21%-37%). Cases with MOID differed in originating service, but not demographically. Recognizing the urgency of an identified condition was the most common diagnostic process opportunity. ET cases with MOID had higher odds of mortality (odds ratio 5.5; 95% CI 1.5-20.6; p = .01) and longer posttransfer LOS (rate ratio 1.7; 95% CI 1.1-2.6; p = .02).

CONCLUSION: MOID are common in ETs and are associated with increased mortality risk and posttransfer LOS. Diagnostic improvement strategies should be leveraged to support earlier recognition of clinical deterioration.

10.1002/jhm.13103

J Hosp Med

37143201

Clinical decision support with a comprehensive in-EHR patient tracking system improves genetic testing follow up.

2023

04/2023

1527-974X

OBJECTIVE: We sought to develop and evaluate an electronic health record (EHR) genetic testing tracking system to address the barriers and limitations of existing spreadsheet-based workarounds.

MATERIALS AND METHODS: We evaluated the spreadsheet-based system using mixed effects logistic regression to identify factors associated with delayed follow up. These factors informed the design of an EHR-integrated genetic testing tracking system. After deployment, we assessed the system in 2 ways. We analyzed EHR access logs and note data to assess patient outcomes and performed semistructured interviews with users to identify impact of the system on work.

RESULTS: We found that patient-reported race was a significant predictor of documented genetic testing follow up, indicating a possible inequity in care. We implemented a CDS system including a patient data capture form and management dashboard to facilitate important care tasks. The system significantly sped review of results and significantly increased documentation of follow-up recommendations. Interviews with key system users identified a range of sociotechnical factors (ie, tools, tasks, collaboration) that contribute to safer and more efficient care.

DISCUSSION: Our new tracking system ended decades of workarounds for identifying and communicating test results and improved clinical workflows. Interview participants related that the system decreased cognitive and time burden which allowed them to focus on direct patient interaction.

CONCLUSION: By assembling a multidisciplinary team, we designed a novel patient tracking system that improves genetic testing follow up. Similar approaches may be effective in other clinical settings.

10.1093/jamia/ocad070

J Am Med Inform Assoc

37080563

Classification of Health Information Technology Safety Events in a Pediatric Tertiary Care Hospital.

2023

04/2023

1549-8425

OBJECTIVE: State agencies have developed reporting systems of safety events that include events related to health information technology (HIT). These data come from hospital reporting systems where staff submit safety reports and nurses, in the role of safety managers, review, and code events. Safety managers may have varying degrees of experience with identifying events related to HIT. Our objective was to review events potentially involving HIT and compare those with what was reported to the state.

METHODS: We performed a structured review of 1 year of safety events from an academic pediatric healthcare system. We reviewed the free-text description of each event and applied a classification scheme derived from the AHRQ Health IT Hazard Manager and compared the results with events reported to the state as involving HIT.

RESULTS: Of 33,218 safety events for a 1-year period, 1247 included key words related to HIT and/or were indicated by safety managers as involving HIT. Of the 1247 events, the structured review identified 769 as involving HIT. In comparison, safety managers only identified 194 of the 769 events (25%) as involving HIT. Most events, 353 (46%), not identified by safety managers were documentation issues. Of the 1247 events, the structured review identified 478 as not involving HIT while safety managers identified and reported 81 of these 478 events (17%) as involving HIT.

CONCLUSIONS: The current process of reporting safety events lacks standardization in identifying health technology contributions to safety events, which may minimize the effectiveness of safety initiatives.

10.1097/PTS.0000000000001119

J Patient Saf

37094555

Clinician Perspectives on Specifications for Metrics to Inform Pediatric Alarm Management.

2023

18-25

12/2023

0899-8205

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.

10.2345/0899-8205-57.1.18

Biomed Instrum Technol

37084247

Clinical decision support with a comprehensive in-EHR patient tracking system improves genetic testing follow up.

2023

04/2023

1527-974X

OBJECTIVE: We sought to develop and evaluate an electronic health record (EHR) genetic testing tracking system to address the barriers and limitations of existing spreadsheet-based workarounds.

MATERIALS AND METHODS: We evaluated the spreadsheet-based system using mixed effects logistic regression to identify factors associated with delayed follow up. These factors informed the design of an EHR-integrated genetic testing tracking system. After deployment, we assessed the system in 2 ways. We analyzed EHR access logs and note data to assess patient outcomes and performed semistructured interviews with users to identify impact of the system on work.

RESULTS: We found that patient-reported race was a significant predictor of documented genetic testing follow up, indicating a possible inequity in care. We implemented a CDS system including a patient data capture form and management dashboard to facilitate important care tasks. The system significantly sped review of results and significantly increased documentation of follow-up recommendations. Interviews with key system users identified a range of sociotechnical factors (ie, tools, tasks, collaboration) that contribute to safer and more efficient care.

DISCUSSION: Our new tracking system ended decades of workarounds for identifying and communicating test results and improved clinical workflows. Interview participants related that the system decreased cognitive and time burden which allowed them to focus on direct patient interaction.

CONCLUSION: By assembling a multidisciplinary team, we designed a novel patient tracking system that improves genetic testing follow up. Similar approaches may be effective in other clinical settings.

10.1093/jamia/ocad070

J Am Med Inform Assoc

37080563

Clinician Perspectives on Specifications for Metrics to Inform Pediatric Alarm Management.

2023

18-25

12/2023

0899-8205

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.

10.2345/0899-8205-57.1.18

Biomed Instrum Technol

37084247

Returning integrated genomic risk and clinical recommendations: The eMERGE study.

2023

100006

04/2023

1530-0366

PURPOSE: Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk.

METHODS: To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results.

RESULTS: GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022.

CONCLUSION: Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

10.1016/j.gim.2023.100006

Genet Med

36621880

Sustainable deimplementation of continuous pulse oximetry monitoring in children hospitalized with bronchiolitis: study protocol for the Eliminating Monitor Overuse (EMO) type III effectiveness-deimplementation cluster-randomized trial.

2022

72

10/2022

1748-5908

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.

10.1186/s13012-022-01246-z

Implement Sci

36271399

Leveraging EHR Data to Evaluate the Association of Late Recognition of Deterioration With Outcomes.

2022

447-460

05/2022

2154-1671

OBJECTIVES: Emergency transfers (ETs), deterioration events with late recognition requiring ICU interventions within 1 hour of transfer, are associated with adverse outcomes. We leveraged electronic health record (EHR) data to assess the association between ETs and outcomes. We also evaluated the association between intervention timing (urgency) and outcomes.

METHODS: We conducted a propensity-score-matched study of hospitalized children requiring ICU transfer between 2015 and 2019 at a single institution. The primary exposure was ET, automatically classified using Epic Clarity Data stored in our enterprise data warehouse endotracheal tube in lines/drains/airway flowsheet, vasopressor in medication administration record, and/or ≥60 ml/kg intravenous fluids in intake/output flowsheets recorded within 1 hour of transfer. Urgent intervention was defined as interventions within 12 hours of transfer.

RESULTS: Of 2037 index transfers, 129 (6.3%) met ET criteria. In the propensity-score-matched cohort (127 ET, 374 matched controls), ET was associated with higher in-hospital mortality (13% vs 6.1%; odds ratio, 2.47; 95% confidence interval [95% CI], 1.24-4.9, P = .01), longer ICU length of stay (subdistribution hazard ratio of ICU discharge 0.74; 95% CI, 0.61-0.91, P < .01), and longer posttransfer length of stay (SHR of hospital discharge 0.71; 95% CI, 0.56-0.90, P < .01). Increased intervention urgency was associated with increased mortality risk: 4.1% no intervention, 6.4% urgent intervention, and 10% emergent intervention.

CONCLUSIONS: An EHR measure of deterioration with late recognition is associated with increased mortality and length of stay. Mortality risk increased with intervention urgency. Leveraging EHR automation facilitates generalizability, multicenter collaboratives, and metric consistency.

10.1542/hpeds.2021-006363

Hosp Pediatr

35470399

Clinical Decision Support Stewardship: Best Practices and Techniques to Monitor and Improve Interruptive Alerts.

2022

560-568

05/2022

1869-0327

Interruptive clinical decision support systems, both within and outside of electronic health records, are a resource that should be used sparingly and monitored closely. Excessive use of interruptive alerting can quickly lead to alert fatigue and decreased effectiveness and ignoring of alerts. In this review, we discuss the evidence for effective alert stewardship as well as practices and methods we have found useful to assess interruptive alert burden, reduce excessive firings, optimize alert effectiveness, and establish quality governance at our institutions. We also discuss the importance of a holistic view of the alerting ecosystem beyond the electronic health record.

10.1055/s-0042-1748856

Appl Clin Inform

35613913