Using NEMSIS to report annual air medical transport statistics.

OBJECTIVE: The objective of this study was to use the National Emergency Medical Services Information System (NEMSIS) dataset to generate national air medical transport statistics. METHODS: Retrospective review of the 2021 NEMSIS dataset to identify all air medical transfers, both fixed- and rotor-wing. Transfers where then subcategorized into interfacility and scene responses. Frequencies for each category were generated and reported. RESULTS: A total of 317,267 air medical transfers were completed in 2021. These included 19,421 (6 %) with missing incident location code data. Of the 297,706 transfers with valid location codes, 208,689 (70%) were interfacility transfers, and 89,016 (30%) were scene responses. CONCLUSION: These preliminary results are consistent with other national estimates and achieve representation of all states and territories. Future work will include longitudinal analysis of NEMSIS datasets and direct survey of transport programs to establish long-term reliability.

Applications of Artificial Intelligence in Helicopter Emergency Medical Services: A Scoping Review.

OBJECTIVE: Recent systematic reviews of acute care medicine applications of artificial intelligence (AI) have focused on hospital and general prehospital uses. The purpose of this scoping review was to identify and describe the literature on AI use with a focus on applications in helicopter emergency medical services (HEMS). METHODS: A literature search was performed with specific inclusion and exclusion criteria. Articles were grouped by characteristics such as publication year and general subject matter with categoric and temporal trend analyses. RESULTS: We identified 21 records focused on the use of AI in HEMS. These applications included both clinical and triage uses and nonclinical uses. The earliest study appeared in 2006, but over one third of the identified studies have been published in 2021 or later. The passage of time has seen an increased likelihood of HEMS AI studies focusing on nonclinical issues; for each year, the likelihood of a nonclinical focus had an odds ratio of 1.3. CONCLUSION: This scoping review provides overview and hypothesis-generating information regarding AI applications specific to HEMS. HEMS AI may be ultimately deployed in nonclinical arenas as much as or more than for clinical decision support. Future studies will inform future decisions as to how AI may improve HEMS systems design, asset deployment, and clinical care.

High-risk diagnosis combinations in patients undergoing interhospital transfer: a retrospective observational study.

BACKGROUND: There is limited research on individual patient characteristics, alone or in combination, that contribute to the higher levels of mortality in post-transfer patients. The purpose of this work is to identify significant combinations of diagnoses that identify subgroups of post-interhospital transfer patients experiencing the highest levels of mortality. METHODS: This was a retrospective cross-sectional study using structured electronic health record data from a regional health system between 2010-2017. We employed a machine learning approach, association rules mining using the Apriori algorithm to identify diagnosis combinations. The study population includes all patients aged 21 and older that were transferred within our health system from a community hospital to one of three main receiving hospitals. RESULTS: Overall, 8893 patients were included in the analysis. Patients experiencing mortality post-transfer were on average older (70.5 vs 62.6 years) and on average had more diagnoses in 5 of the 6 diagnostic subcategories. Within the diagnostic subcategories, most diagnoses were comorbidities and active medical problems, with hypertension, atrial fibrillation, and acute respiratory failure being the most common. Several combinations of diagnoses identified patients that exceeded 50% post-interhospital transfer mortality. CONCLUSIONS: Comorbid burden, in combination with active medical problems, were most predictive for those experiencing the highest rates of mortality. Further improving patient level prognostication can facilitate informed decision making between providers and patients to shift the paradigm from transferring all patients to higher level care to only transferring those who will benefit or desire continued care, and reduce futile transfers.

High-Flow Nasal Cannula in Transport: Process, Results, and Considerations.

OBJECTIVE: The current coronavirus disease 2019 pandemic has increased interest in the use of high-flow nasal cannula (HFNC) in the transport setting. The purpose of this report was to outline the clinical workflow of using HFNC in transport and the results of a retrospective chart review of patients undergoing interhospital transfer on HFNC. METHODS: We conducted a retrospective chart review of all patient transfers using HFNC between January 2018 and June 2019. The primary data abstracted from patient charts included patient demographics, transport distance, HFNC settings including flow rate in liters per minute and fraction of inspired oxygen (Fio2), and vital signs. RESULTS: There was a total of 220 patients, 148 pediatric and 72 adult patients. Both pediatric groups experienced statistically significant reductions in heart rate, systolic blood pressure, and diastolic blood pressure. The most common flow rate for both pediatric groups was 10 L/min and 50 L/min for adults. For pediatrics, the most common settings ranged between 30% and 50% Fio2, with the most common setting being 30% Fio2. The adult Fio2 settings ranged from 30% to 100% Fio2, with the 2 most common settings being 50% Fio2 and 80% Fio2. No patients were intubated during the transport encounter. CONCLUSION: Our study provides evidence that HFNC is feasible and tolerated by patients and is an additional option for noninvasive ventilation in transport across the age continuum. Future studies are needed to compare HFNC with other noninvasive modalities that include assessing patient tolerance and comfort as contributing factors and to identify indications and contraindications for use in the transport setting.

Challenges Frequently Encountered in the Secondary Use of Electronic Medical Record Data for Research.

The wide adoption of electronic medical records and subsequent availability of large amounts of clinical data provide a rich resource for researchers. However, the secondary use of clinical data for research purposes is not without limitations. In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we conducted a systematic review to identify current issues related to secondary use of electronic medical record data via MEDLINE and CINAHL databases. All articles published until June 2018 were included. Sixty articles remained after title and abstract review, and four domains of potential limitations were identified: (1) data quality issues, present in 91.7% of the articles reviewed; (2) data preprocessing challenges (53.3%); (3) privacy concerns (18.3%); and (4) potential for limited generalizability (21.7%). Researchers must be aware of the limitations inherent to the use of electronic medical record data for research and consider the potential effects of these limitations throughout the entire study process, from initial conceptualization to the identification of adequate sources that can provide data appropriate for answering the research questions, analysis, and reporting study results. Consideration should also be given to using existing data quality assessment frameworks to facilitate use of standardized data quality definitions and further efforts of standard data quality reporting in publications.

Usefulness of a Simulated Helicopter Transport Experience for Medical Resident Training.

OBJECTIVE: This study evaluated the usefulness of a medical transport simulation to increase residents' understanding of medical transport. METHODS: Twenty-four medical residents participated in an intensive half-day medical transport simulation experience. Two questionnaires were administered, a pre/postsimulation questionnaire containing 11 questions that assessed the impact of the simulation training and a questionnaire that assessed realism of the flight simulator. RESULTS: There were statistically significant differences between the pre/postsimulation questions assessing perceived level of knowledge, experience, and training of transferring a patient in a helicopter with a mean change of 25 points on a 0 to 100 scale (P ≤ .001) and awareness of obstacles to treating patients during air transport exhibiting a mean change of 28 (P ≤ .001). The mean stress level for all participants increased from 32 (0-100 scale) before the start of the simulation to 47 during the simulation and decreased to 31 after the simulation (F2,46 = 20.67, P ≤ .001). CONCLUSION: The findings from this study provide evidence that the air medical simulation experience increases residents' perceived awareness of the context and difficulties of transferring a patient by helicopter and that the experience would influence their medical decision making in their future practice related to patient transfers.

Establishing Transport Statistics: Results From the Medevac Transport Statistics Survey.

OBJECTIVE: The purpose of this article was to report the results of a national survey of medical transport programs to establish national estimates of critical care transports and use those results combined with other data sources to generate annual transport volume estimates. METHODS: An online survey was administered to collect transport statistics from medical transport programs registered in the Association of Air Medical Services Atlas and Database of Air Medical services in 2015. RESULTS: Roughly 20% of all registered programs participated. An estimated 640,000 critical care transports are conducted annually; an additional breakdown by mode of transfer is presented. CONCLUSION: Low participation rates preclude establishing precise critical care transport statistics. Future participation is encouraged to enable more accurate data reporting to establish resources that can support research and policy initiatives.

Psychiatric disease in surgically treated colorectal cancer patients.

BACKGROUND: Underlying psychiatric conditions may affect outcomes of surgical treatment for colorectal cancer (CRC) because of complex clinical presentation and treatment considerations. We hypothesized that patients with psychiatric illness (PSYCH) would have evidence of advanced disease at presentation, as manifested by higher rates of colorectal surgery performed in the presence of obstruction, perforation, and/or peritonitis (OPP-surgery). MATERIALS AND METHODS: Using data from the 2007-2011 National Inpatient Sample, we identified patients with a diagnosis of CRC undergoing colorectal surgery. In addition to somatic comorbid conditions flagged in the National Inpatient Sample, we used the Clinical Classification Software to identify patients with PSYCH, including schizophrenia, delirium/dementia, developmental disorders, alcohol/substance abuse, and other psychiatric conditions. Our study outcome was OPP-surgery. In addition to descriptive analysis, we conducted multivariable logistic regression analysis to analyze the independent association between each of the PSYCH conditions and OPP-surgery, after adjusting for patient demographics and somatic comorbidities. RESULTS: Our study population included 591,561 patients with CRC and undergoing colorectal cancer surgery, of whom 60.6% were aged 65 years or older, 49.4% were women, and 6.3% had five or more comorbid conditions. Then, 17.9% presented with PSYCH. The percent of patients undergoing OPP-surgery was 13.9% in the study population but was significantly higher for patients with schizophrenia (19.3%), delirium and dementia (18.5%), developmental disorders (19.7%), and alcohol/substance abuse (19.5%). In multivariable analysis, schizophrenia, delirium/dementia, and alcohol/substance abuse were each independently associated with increased rates of OPP-surgery. CONCLUSIONS: Patients with PSYCH may have obstacles in receiving optimal care for CRC. Those with PSYCH diagnoses had significantly higher rates of OPP-surgery. Additional evaluation is required to further characterize the clinical implications of advanced disease presentation for patients with PSYCH diagnoses and colorectal cancer.

Patient Safety Events during Critical Care Transport.

OBJECTIVE: Patient safety events (PSEs) occurring during interfacility transport have not been studied comprehensively in critical care transport (CCT) teams in the United States. The purpose of this research was to investigate the type and frequency of PSEs during CCT between hospitals; to explore the impact of patient stability, vulnerability, complexity, predictability, and resiliency; and to examine if the nurse factors of licensure or experience and transport factors of duration or mode of transport influence the frequency of PSEs. The study was conducted at a large hospital-based quaternary health care system in the Midwestern United States. METHODS: This was a retrospective, descriptive correlational study using chart review. The study selected 50 sequential qualifying cases with PSEs and randomly selected control cases reviewed at a single site over a 5-month period. RESULTS: The rate of PSEs was 27.7 events per 1,000 patient contacts. Of 9 reported adverse event types, new or recurrent hypoxia had the greatest frequency. Hypoxia, when present at the time of initial CCT contact, was associated with the PSE occurrence (P = .046). Duration of transport was a significant predictor of PSEs (P = .025). CONCLUSION: Pretransport hypoxia and duration of transport are independent predictors for intratransport PSEs, particularly intratransport hypoxia.

Flying Lessons for Clinicians: Developing System 2 Practice.

There is a long history of adopting lessons learned from aviation to improve health care practice. Two of the major practices that have successfully transferred include using a checklist and simulation. Training and simulation technology is currently underdeveloped for nurses and health care providers entering critical care transport. This article describes a pedagogical approach adopted from aviation to develop a new simulation platform and program of research to develop the science of critical care transport nursing education.

Response of Flight Nurses in a Simulated Helicopter Environment.

OBJECTIVE: The purpose of this study was to determine if a helicopter flight simulator could provide a useful educational platform by creating experiences similar to those encountered by actual flight nurses. METHODS: Flight nurse (FN) and non-FN participants completed a simulated emergency scenario in a flight simulator. Physiologic and psychological stress during the simulation was measured using heart rate and perceived stress scores. A questionnaire was then administered to assess the realism of the flight simulator. RESULTS: Subjects reported that the overall experience in the flight simulator was comparable with a real helicopter. Sounds, communications, vibrations, and movements in the simulator most approximated those of a real-life helicopter environment. Perceived stress levels of all participants increased significantly from 27 (on a 0-100 scale) before simulation to 51 at the peak of the simulation and declined thereafter to 28 (P < .001). Perceived stress levels of FNs increased significantly from 25 before simulation to 54 at the peak of the simulation and declined thereafter to 30 (P < .001). Perceived stress levels of non-FNs increased significantly from 31 before simulation to 49 at the peak of the simulation and declined thereafter to 25 (P < .001). There were no significant differences in perceived stress levels between FNs and non-FNs before (P = .58), during (P = .63), or after (P = .55) simulation. FNs' heart rates increased significantly from 77 before simulation to 100 at the peak of the simulation and declined thereafter to 72 (P < .001). CONCLUSION: The results of this study suggest that simulation of a critical care scenario in a high-fidelity helicopter flight simulator can provide a realistic helicopter transport experience and create physiologic and psychological stress for participants.

NATIONAL INCIDENCE OF MEDICAL TRANSFER: PATIENT CHARACTERISTICS AND REGIONAL VARIATION.

The aim of this descriptive study was to establish and describe the national incidence, cost, and outcomes of patients that undergo medical transfer. Using discharge data from the Nationwide Inpatient Sample 2011, Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality, the dataset was analyzed using weighted frequency distribution. Approximately 1.6 million patients are transferred yearly. Transferred patients experience a mean length of stay of 9.3 days (std dv 13.5) versus 4.3 days for patients not transferred (std dv 6.0), and cost more than twice as much (mean $19,234) versus those not transferred (mean $9,469). Additionally, patients who undergo inter-facility transfer cost an additional $15.8 billion annually. Interhospital patient transfers require closer scrutiny regarding appropriateness and future policy implications.

Ethical considerations for conducting a randomized controlled trial in transport.

Although recent studies support the rapid transfer of patients experiencing time-sensitive emergencies, limited data exist to support the use of air transport for nonurgent patient transfers. The nature of medical transport and the heterogeneity of patients who are transferred present unique challenges in designing and conducting clinical research trials that could contribute to the evidence-based decision making for patient care and transport. The current regulatory framework presents several barriers to conducting such research in the medical transport setting. We present a hypothetic study that randomizes patients to either ground or air transport as an exemplar. We discuss informed consent, risk, and the impracticality of conducting community consultations in a medical transport setting. Finally, recommendations for potential changes to current regulations are presented. These are directed at facilitating the conduct of emergency research through a system of oversight that integrates characteristics of quality improvement and health services research.

Use of arterial catheters in the management of acute aortic dissection.

PURPOSE: The aim of this study was to investigate the relationship between the use of invasive arterial blood pressure (IBP) monitoring and reaching established aggressive medical management goals in acute aortic dissection. METHODS: Data were collected through a retrospective chart review of patients diagnosed with acute aortic syndromes of the thoracic cavity who required transport to tertiary care over a 28-month period. The 2010 American Heart Association medical management goals of thoracic aortic disease were used as hemodynamic end points. RESULTS: A total of 208 patients were included, with 113 (54%) diagnosed at least in part with acute Stanford Type A aortic dissections and the remaining 95 (46%) having isolated Stanford Type B dissections. Emergency departments made up 158 (76%) of transfer departments; 129 (62%) patients had IBP catheters placed. The highest mean systolic blood pressures (SBPs) recorded were 165 mm Hg in the IBP group versus 151 mm Hg when noninvasive blood pressure (NIBP) cuffs were used (P < .01). The mean decrease in SBP during transport was 51 mm Hg in the IBP group versus 34 mm Hg in the NIBP group (P < .001). The difference between the last reported NIBP and the first IBP was noted as 19 mm Hg higher. The IBP group met the SBP goal more frequently than the NIBP group (P < .05) when the SBP was noted as greater than 140 mm Hg during transport. Bedside time increased only 6 minutes with IBP placement (P < .007). CONCLUSION: Patients with IBP catheters were noted to be more aggressively managed with antihypertensive medications, met hemodynamic goals more frequently, and had only 6 minutes longer bedside times. These findings support the placement of IBP catheters by emergency departments and critical care transport (CCT) teams in patients with acute aortic syndromes requiring interfacility transport to definitive care.

Decreasing door-to-balloon times via a streamlined referral protocol for patients requiring transport.

PURPOSES: The objective of this study was to evaluate the effectiveness of a streamlined interfacility referral protocol in reducing door-to-balloon (D2B) times for patients experiencing acute ST-segment elevation myocardial infarction (STEMI). BASIC PROCEDURES: In a retrospective database review, we compared D2B times for patients requiring interfacility transfer after the implementation of a streamlined referral protocol. All patients undergoing interfacility transport with a referring diagnosis of STEMI were eligible for inclusion. Quality management databases were reviewed by trained abstractors using standardized data entry forms for D2B times from July 2009 through June 2010. Median D2B times with interquartile ranges are reported. MAIN FINDINGS: A total of 133 patients exhibited complete data and were included in the analysis, 54 of which were transferred via the streamlined referral protocol. Streamlined referral patients exhibited a median D2B time of 101 minutes (interquartile range, 88-128) vs a median D2B time of 122 minutes (interquartile range, 99-157) for the traditional referral group (P = .001). Door-to-balloon times of 90 minutes or less were achieved in 13% of the traditional referral patients and in 30% of the streamlined protocol group (odds ratio, 2.9; 95% confidence interval, 1.2-7). PRINCIPAL CONCLUSION: The implementation of a streamlined referral protocol has significantly reduced D2B times for patients diagnosed with STEMI that required interfacility transport for intervention.

Early examination of the middle-range theory of flight nursing expertise.

Reliance on expert flight nurses to move critically ill or injured patients generates considerable need for these nurses to obtain advanced education and maintain clinical expertise. The newly proposed middle-range theory of flight nursing expertise provided an initial framework to guide education and training in this rapidly changing specialty, but the framework had yet to be compared to the actual experiences of flight nurses in research. A cooperative inquiry approach was used to guide an investigation into the validity of the theory. The study consisted of two cycles of inquiry. In the first cycle, post-flight questionnaires were administered after patient missions to assess the presence or absence of each concept described in the theory. In the second cycle, individual interviews were used to further explore the flight nurses' decision-making during patient transport missions. Data collected from flight nurses about their decision-making on patient transport missions supported the presence of all the concepts in the newly proposed theory. Another concept, partner cuing, emerged as a concept to be added to the theory, while the concept decision-making, was revised to expanded decision-making. The importance of partner cuing was confirmed by flight nurses as reflecting their expanded decision-making during patient missions.

Subcategorizing EHR diagnosis codes to improve clinical application of machine learning models.

BACKGROUND: Electronic health record (EHR) data is commonly used for secondary purposes such as research and clinical decision support. However, reuse of EHR data presents several challenges including but not limited to identifying all diagnoses associated with a patient's clinical encounter. The purpose of this study was to assess the feasibility of developing a schema to identify and subclassify all structured diagnosis codes for a patient encounter. METHODS: To develop a subclassification schema we used EHR data from an interhospital transport data repository that contained complete hospital encounter level data. Eight discrete data sources containing structured diagnosis codes were identified. Diagnosis codes were normalized using the Unified Medical Language System and additional EHR data were combined with standardized terminologies to create and validate the subcategories. We then employed random forest to assess the usefulness of the new subcategorized diagnoses to predict post-interhospital transfer mortality by building 2 models, one using standard diagnosis codes, and one using the new subcategorized diagnosis codes. RESULTS: Six subcategories of diagnoses were identified and validated. The subcategories included: primary or admitting diagnoses (10%), past medical, surgical or social history (9%), problem list (20%), comorbidity (24%), discharge diagnoses (6%), and unmapped diagnoses (31%). The subcategorized model outperformed the standard model, achieving a training AUROC of 0.97 versus 0.95 and testing model AUROC of 0.81 versus 0.46. DISCUSSION: Our work demonstrates that merging structured diagnosis codes with additional EHR data and secondary data sources provides additional information to understand the role of diagnosis throughout a clinical encounter and improves predictive model performance. Further work is necessary to assess if subcategorizing produces benefits in interpreting the results of prognostic models and/or operationalizing the results in clinical decision support applications.

Flight nursing expertise: towards a middle-range theory.

AIM: This paper presents a middle-range Theory of Flight Nursing Expertise. BACKGROUND: Rotary-wing (helicopter) medical transport has grown rapidly in the USA since its introduction, particularly during the past 5 years. Patients once considered too sick to transport are now being transported more frequently and over longer distances. Many limitations are imposed by the air medical transport environment and these require nurses to alter their practice. DATA SOURCES: A literature search was conducted using Pubmed, Medline, CINAHL, secondary referencing and an Internet search from 1960 to 2008 for studies related to the focal concepts in flight nursing. DISCUSSION: The middle-range Theory of Flight Nursing Expertise is composed of nine concepts (experience, training, transport environment of care, psychomotor skills, flight nursing knowledge, cue recognition, pattern recognition, decision-making and action) and their relationships. Five propositions describe the relationships between those concepts and how they apply to flight nursing expertise. IMPLICATIONS FOR NURSING: After empirical testing, this theory may be a useful tool to assist novice flight nurses to attain the skills necessary to provide safe and competent care more efficiently, and may aid in designing curricula and programmes of research. CONCLUSION: Research is needed to determine the usefulness of this theory in both rotary and fixed-wing medical transport settings, and to examine the similarities and differences related to expertise needed for different flight nurse team compositions. Curriculum and training innovations can result from increased understanding of the concepts and relationships proposed in this theory.

Using UMLS for electronic health data standardization and database design.

OBJECTIVE: Patients that undergo medical transfer represent 1 patient population that remains infrequently studied due to challenges in aggregating data across multiple domains and sources that are necessary to capture the entire episode of patient care. To facilitate access to and secondary use of transport patient data, we developed the Transport Data Repository that combines data from 3 separate domains and many sources within our health system. METHODS: The repository is a relational database anchored by the Unified Medical Language System unique concept identifiers to integrate, map, and standardize the data into a common data model. Primary data domains included sending and receiving hospital encounters, medical transport record, and custom hospital transport log data. A 4-step mapping process was developed: 1) automatic source code match, 2) exact text match, 3) fuzzy matching, and 4) manual matching. RESULTS: 431 090 total mappings were generated in the Transport Data Repository, consisting of 69 010 unique concepts with 77% of the data being mapped automatically. Transport Source Data yielded significantly lower mapping results with only 8% of data entities automatically mapped and a significant amount (43%) remaining unmapped. DISCUSSION: The multistep mapping process resulted in a majority of data been automatically mapped. Poor matching of transport medical record data is due to the third-party vendor data being generated and stored in a nonstandardized format. CONCLUSION: The multistep mapping process developed and implemented is necessary to normalize electronic health data from multiple domains and sources into a common data model to support secondary use of data.