Implementation and evaluation of an integrated computerized asthma management system in a pediatric emergency department: a randomized clinical trial

The role of information systems in emergency department decision-making-a literature review

OBJECTIVES

Healthcare providers employ heuristic and analytical decision-making to navigate the high-stakes environment of the emergency department (ED). Despite the increasing integration of information systems (ISs), research on their efficacy is conflicting. Drawing on related fields, we investigate how timing and mode of delivery influence IS effectiveness. Our objective is to reconcile previous contradictory findings, shedding light on optimal IS design in the ED.

MATERIALS AND METHODS

We conducted a systematic review following PRISMA across PubMed, Scopus, and Web of Science. We coded the ISs' timing as heuristic or analytical, their mode of delivery as active for automatic alerts and passive when requiring user-initiated information retrieval, and their effect on process, economic, and clinical outcomes.

RESULTS

Our analysis included 83 studies. During early heuristic decision-making, most active interventions were ineffective, while passive interventions generally improved outcomes. In the analytical phase, the effects were reversed. Passive interventions that facilitate information extraction consistently improved outcomes.

DISCUSSION

Our findings suggest that the effectiveness of active interventions negatively correlates with the amount of information received during delivery. During early heuristic decision-making, when information overload is high, physicians are unresponsive to alerts and proactively consult passive resources. In the later analytical phases, physicians show increased receptivity to alerts due to decreased diagnostic uncertainty and information quantity. Interventions that limit information lead to positive outcomes, supporting our interpretation.

CONCLUSION

We synthesize our findings into an integrated model that reveals the underlying reasons for conflicting findings from previous reviews and can guide practitioners in designing ISs in the ED.

Application of a user experience design approach for an EHR-based clinical decision support system

Objective

We applied a user experience (UX) design approach to clinical decision support (CDS) tool development for the specific use case of pediatric asthma. Our objective was to understand physicians' workflows, decision-making processes, barriers (ie, pain points), and facilitators to increase usability of the tool.

Materials and methods

We used a mixed-methods approach with semi-structured interviews and surveys. The coded interviews were synthesized into physician-user journey maps (ie, visualization of a process to accomplish goals) and personas (ie, user types). Interviews were conducted via video. We developed physician journey maps and user personas informed by their goals, systems interactions, and experiences with pediatric asthma management.

Results

The physician end-user personas identified were: efficiency, relationship, and learning. Features of a potential asthma CDS tool sought varied by physician practice type and persona. It was important to the physician end-user that the asthma CDS tool demonstrate value by lowering workflow friction (ie, difficulty or obstacles), improving the environment surrounding physicians and patients, and using it as a teaching tool. Customizability versus standardization were important considerations for uptake.

Discussion

Different values and motivations of physicians influence their use and interaction with the EHR and CDS tools. These different perspectives can be captured by applying a UX design approach to the development process. For example, with the importance of customizability, one approach may be to build a core module with variations depending on end-user preference.

Conclusion

A UX approach can drive design to help understand physician-users and meet their needs; ultimately with the goal of increased uptake.

Implemented machine learning tools to inform decision-making for patient care in hospital settings: a scoping review

OBJECTIVES

To identify ML tools in hospital settings and how they were implemented to inform decision-making for patient care through a scoping review. We investigated the following research questions: What ML interventions have been used to inform decision-making for patient care in hospital settings? What strategies have been used to implement these ML interventions?

DESIGN

A scoping review was undertaken. MEDLINE, Embase, Cochrane Central Register of Controlled Trials (CENTRAL) and the Cochrane Database of Systematic Reviews (CDSR) were searched from 2009 until June 2021. Two reviewers screened titles and abstracts, full-text articles, and charted data independently. Conflicts were resolved by another reviewer. Data were summarised descriptively using simple content analysis.

SETTING

Hospital setting.

PARTICIPANT

Any type of clinician caring for any type of patient.

INTERVENTION

Machine learning tools used by clinicians to inform decision-making for patient care, such as AI-based computerised decision support systems or "'model-based'" decision support systems.

PRIMARY AND SECONDARY OUTCOME MEASURES

Patient and study characteristics, as well as intervention characteristics including the type of machine learning tool, implementation strategies, target population. Equity issues were examined with PROGRESS-PLUS criteria.

RESULTS

After screening 17 386 citations and 3474 full-text articles, 20 unique studies and 1 companion report were included. The included articles totalled 82 656 patients and 915 clinicians. Seven studies reported gender and four studies reported PROGRESS-PLUS criteria (race, health insurance, rural/urban). Common implementation strategies for the tools were clinician reminders that integrated ML predictions (44.4%), facilitated relay of clinical information (17.8%) and staff education (15.6%). Common barriers to successful implementation of ML tools were time (11.1%) and reliability (11.1%), and common facilitators were time/efficiency (13.6%) and perceived usefulness (13.6%).

CONCLUSIONS

We found limited evidence related to the implementation of ML tools to assist clinicians with patient healthcare decisions in hospital settings. Future research should examine other approaches to integrating ML into hospital clinician decisions related to patient care, and report on PROGRESS-PLUS items.

FUNDING

Canadian Institutes of Health Research (CIHR) Foundation grant awarded to SES and the CIHR Strategy for Patient Oriented-Research Initiative (GSR-154442). SCOPING REVIEW REGISTRATION: https://osf.io/e2mna.

Understanding the impacts of health information systems on patient flow management: A systematic review across several decades of research

Background

Patient flow describes the progression of patients along a pathway of care such as the journey from hospital inpatient admission to discharge. Poor patient flow has detrimental effects on health outcomes, patient satisfaction and hospital revenue. There has been an increasing adoption of health information systems (HISs) in various healthcare settings to address patient flow issues, yet there remains limited evidence of their overall impacts.

Objective

To systematically review evidence on the impacts of HISs on patient flow management including what HISs have been used, their application scope, features, and what aspects of patient flow are affected by the HIS adoption.

Methods

A systematic search for English-language, peer-review literature indexed in MEDLINE and EMBASE, CINAHL, INSPEC, and ACM Digital Library from the earliest date available to February 2022 was conducted. Two authors independently scanned the search results for eligible publications, and reporting followed the PRISMA guidelines. Eligibility criteria included studies that reported impacts of HIS on patient flow outcomes. Information on the study design, type of HIS, key features and impacts was extracted and analysed using an analytical framework which was based on domain-expert opinions and literature review.

Results

Overall, 5996 titles were identified, with 44 eligible studies, across 17 types of HIS. 22 studies (50%) focused on patient flow in the department level such as emergency department while 18 studies (41%) focused on hospital-wide level and four studies (9%) investigated network-wide HIS. Process outcomes with time-related measures such as ‘length of stay’ and ‘waiting time’ were investigated in most of the studies. In addition, HISs were found to address flow problems by identifying blockages, streamlining care processes and improving care coordination.

Conclusion

HIS affected various aspects of patient flow at different levels of care; however, how and why they delivered the impacts require further research.

Decreasing Misdiagnoses of Urinary Tract Infections in a Pediatric Emergency Department

BACKGROUND AND OBJECTIVES

Urinary tract infection (UTI) is a common diagnosis in the emergency department (ED), often resulting in empirical antibiotic treatment before culture results. Diagnosis of a UTI, particularly in children, can be challenging and misdiagnosis is common. The aim of this initiative was to decrease the misdiagnosis of uncomplicated pediatric UTIs by 50% while improving antimicrobial stewardship in the ED over 4 years.

METHODS

By using the Model for Improvement, 3 interventions were developed: (1) an electronic UTI diagnostic algorithm, (2) a callback system, and (3) a standardized discharge antibiotic prescription. Outcome measures included the percentage of patients with UTI misdiagnosis (prescribed antibiotics, but urine culture results negative) and antibiotic days saved. As a balancing measure, positive urine culture results without a UTI diagnosis were reviewed for ED return visits or hospitalization. Statistical process control and run charts were used for analysis.

RESULTS

From 2017 to 2021, the mean UTI misdiagnosis decreased from 54.6% to 26.4%. The adherence to the standardized antibiotic duration improved from 45.1% to 84.6%. With the callback system, 2128 antibiotic days were saved with a median of 89% of patients with negative culture results contacted to discontinue antibiotics. Of 186 patients with positive urine culture results with an unremarkable urinalysis, 14 returned to the ED, and 2 were hospitalized for multiresistant organism UTI treatment.

CONCLUSIONS

A UTI diagnostic algorithm coupled with a callback system safely reduced UTI misdiagnoses and antibiotic usage. Embedding these interventions electronically as a decision support tool, targeted audit and feedback, reminders, and education all supported long-term sustainability.

Recent trends of healthcare information and communication technologies in pediatrics: a systematic review

As information communication technology (ICT) has advanced, the healthcare industry has embraced it to reduce medical costs, improve health outcomes, and increase patient satisfaction. Healthcare ICT revolutionizes pediatric healthcare. This study aimed to categorize and synthesize findings from the literature regarding the application of ICT in pediatric patients. This systematic review is based on a comprehensive search of Embase, MEDLINE, and Google Scholar. Study selection and coding were performed independently by 2 researchers, followed by narrative categorization. To reflect current trends in ICT for pediatrics, we adopted the Hype cycle technology classification developed by the advisory and information technology firm, Gartner, and the classification of digital health interventions by the World Health Organization. This study included a total of 135 studies. The analysis revealed 7 main types of ICT for pediatrics: (1) telehealth (39 papers), (2) precision medicine (2 papers), (3) automated decision support systems (17 papers), (4) electronic health records (7 papers), (5) patient portals (7 papers), (6) artificial intelligence (AI) (39 papers), and (7) mobile and wearable technologies (20 papers). In particular, we consistently found references to ICT for pediatrics as well as changing and improving healthcare for children. Further studies are required to determine how we can improve ICT productivity for pediatrics, particularly through AI. This study's results will help healthcare delivery organizations and technology companies consider the future direction of pediatric healthcare.

eHealth Tools That Assess and Track Health and Well-being in Children and Young People: Systematic Review

Background

eHealth tools that assess and track health outcomes in children or young people are an emerging type of technology that has the potential to reform health service delivery and facilitate integrated, interdisciplinary care.

Objective

The aim of this review is to summarize eHealth tools that have assessed and tracked health in children or young people to provide greater clarity around the populations and settings in which they have been used, characteristics of digital devices (eg, health domains, respondents, presence of tracking, and connection to care), primary outcomes, and risks and challenges of implementation.

Methods

A search was conducted in PsycINFO, PubMed or MEDLINE, and Embase in April 2020. Studies were included if they evaluated a digital device whose primary purpose was to assess and track health, focused on children or young people (birth to the age of 24 years), reported original research, and were published in peer-reviewed journals in English.

Results

A total of 39 papers were included in this review. The sample sizes ranged from 7 to 149,329 participants (median 163, mean 5155). More studies were conducted in urban (18/39, 46%) regions than in rural (3/39, 8%) regions or a combination of urban and rural areas (8/39, 21%). Devices were implemented in three main settings: outpatient health clinics (12/39, 31%), hospitals (14/39, 36%), community outreach (10/39, 26%), or a combination of these settings (3/39, 8%). Mental and general health were the most common health domains assessed, with a single study assessing multiple health domains. Just under half of the devices tracked children’s health over time (16/39, 41%), and two-thirds (25/39, 64%) connected children or young people to clinical care. It was more common for information to be collected from a single informant (ie, the child or young person, trained health worker, clinician, and parent or caregiver) than from multiple informants. The health of children or young people was assessed as a primary or secondary outcome in 36% (14/39) of studies; however, only 3% (1/39) of studies assessed whether using the digital tool improved the health of users. Most papers reported early phase research (formative or process evaluations), with fewer outcome evaluations and only 3 randomized controlled trials. Identified challenges or risks were related to accessibility, clinical utility and safety, uptake, data quality, user interface or design aspects of the device, language proficiency or literacy, sociocultural barriers, and privacy or confidentiality concerns; ways to address these barriers were not thoroughly explored.

Conclusions

eHealth tools that assess and track health in children or young people have the potential to enhance health service delivery; however, a strong evidence base validating the clinical utility, efficacy, and safety of tools is lacking, and more thorough investigation is needed to address the risks and challenges of using these emerging technologies in clinical care. At present, there is greater potential for the tools to facilitate multi-informant, multidomain assessments and longitudinally track health over time and room for further implementation in rural or remote regions and community settings around the world.

Implementation of a structured emergency nursing framework results in significant cost benefit

Background

Patients are at risk of deterioration on discharge from an emergency department (ED) to a ward, particularly in the first 72 h. The implementation of a structured emergency nursing framework (HIRAID) in regional New South Wales (NSW), Australia, resulted in a 50% reduction of clinical deterioration related to emergency nursing care. To date the cost implications of this are unknown. The aim of this study was to determine any net financial benefits arising from the implementation of the HIRAID emergency nursing framework.

Methods

This retrospective cohort study was conducted between March 2018 and February 2019 across two hospitals in regional NSW, Australia. Costs associated with the implementation of HIRAID at the study sites were calculated using an estimate of initial HIRAID implementation costs (AUD) ($492,917) and ongoing HIRAID implementation costs ($134,077). Equivalent savings per annum (i.e. in less patient deterioration) were calculated using projected estimates of ED admission and patient deterioration episodes via OLS regression with confidence intervals for incremental additional deterioration costs per episode used as the basis for scenario analysis.

Results

The HIRAID-equivalent savings per annum exceed the costs of implementation under all scenarios (Conservative, Expected and Optimistic). The estimated preliminary savings to the study sites per annum was $1,914,252 with a payback period of 75 days. Conservative projections estimated a net benefit of $1,813,760 per annum by 2022–23. The state-wide projected equivalent savings benefits of HIRAID equalled $227,585,008 per annum, by 2022–23.

Conclusions

The implementation of HIRAID reduced costs associated with resources consumed from patient deterioration episodes. The HIRAID-equivalent savings per annum to the hospital exceed the costs of implementation across a range of scenarios, and upscaling would result in significant patient and cost benefit.

Impact of a care bundle for patients with blunt chest injury (ChIP): A multicentre controlled implementation evaluation

Background

Blunt chest injury leads to significant morbidity and mortality. The aim of this study was to evaluate the effect of a multidisciplinary chest injury care bundle (ChIP) on patient and health service outcomes. ChIP provides guidance in three key pillars of care for blunt chest injury—respiratory support, analgesia and complication prevention. ChIP was implemented using a multi-faceted implementation plan developed using the Behaviour Change Wheel.

Methods

This controlled pre-and post-test study (two intervention and two non-intervention sites) was conducted from July 2015 to June 2019. The primary outcome measures were unplanned Intensive Care Unit (ICU) admissions, non-invasive ventilation use and mortality.

Results

There were 1790 patients included. The intervention sites had a 58% decrease in non-invasive ventilation use in the post- period compared to the pre-period (95% CI 0.18–0.96). ChIP was associated with 90% decreased odds of unplanned ICU admissions (95% CI 0.04–0.29) at the intervention sites compared to the control groups in the post- period. There was no significant change in mortality. There were higher odds of health service team reviews (surgical OR 6.6 (95% CI 4.61–9.45), physiotherapy OR 2.17 (95% CI 1.52–3.11), ICU doctor OR 6.13 (95% CI 3.94–9.55), ICU liaison OR 55.75 (95% CI 17.48–177.75), pain team OR 8.15 (95% CI 5.52 –-12.03), analgesia (e.g. patient controlled analgesia OR 2.6 (95% CI 1.64–3.94) and regional analgesia OR 8.8 (95% CI 3.39–22.79), incentive spirometry OR 8.3 (95% CI 4.49–15.37) and, high flow nasal oxygen OR 22.1 (95% CI 12.43–39.2) in the intervention group compared to the control group in the post- period.

Conclusion

The implementation of a chest injury care bundle using behaviour change theory was associated with a sustained improvement in evidence-based practice resulting in reduced unplanned ICU admissions and non-invasive ventilation requirement.

Trial registration

ANZCTR: ACTRN12618001548224, approved 17/09/2018

Accuracy of Asthma Computable Phenotypes to Identify Pediatric Asthma at an Academic Institution

OBJECTIVES

Asthma is a heterogenous condition with significant diagnostic complexity, including variations in symptoms and temporal criteria. The disease can be difficult for clinicians to diagnose accurately. Properly identifying asthma patients from the electronic health record is consequently challenging as current algorithms (computable phenotypes) rely on diagnostic codes (e.g., International Classification of Disease, ICD) in addition to other criteria (e.g., inhaler medications)-but presume an accurate diagnosis. As such, there is no universally accepted or rigorously tested computable phenotype for asthma.

METHODS

We compared two established asthma computable phenotypes: the Chicago Area Patient-Outcomes Research Network (CAPriCORN) and Phenotype KnowledgeBase (PheKB). We established a large-scale, consensus gold standard (n = 1,365) from the University of California, Los Angeles Health System's clinical data warehouse for patients 5 to 17 years old. Results were manually reviewed and predictive performance (positive predictive value [PPV], sensitivity/specificity, F1-score) determined. We then examined the classification errors to gain insight for future algorithm optimizations.

RESULTS

As applied to our final cohort of 1,365 expert-defined gold standard patients, the CAPriCORN algorithms performed with a balanced PPV = 95.8% (95% CI: 94.4-97.2%), sensitivity = 85.7% (95% CI: 83.9-87.5%), and harmonized F1 = 90.4% (95% CI: 89.2-91.7%). The PheKB algorithm was performed with a balanced PPV = 83.1% (95% CI: 80.5-85.7%), sensitivity = 69.4% (95% CI: 66.3-72.5%), and F1 = 75.4% (95% CI: 73.1-77.8%). Four categories of errors were identified related to method limitations, disease definition, human error, and design implementation.

CONCLUSION

The performance of the CAPriCORN and PheKB algorithms was lower than previously reported as applied to pediatric data (PPV = 97.7 and 96%, respectively). There is room to improve the performance of current methods, including targeted use of natural language processing and clinical feature engineering.

Implementation of a hospital-wide multidisciplinary blunt chest injury care bundle (ChIP): Fidelity of delivery evaluation

BACKGROUND

Ineffective intervention for patients with blunt chest wall injury results in high rates of morbidity and mortality. To address this, a blunt chest injury care bundle protocol (ChIP) was developed, and a multifaceted plan was implemented using the Behaviour Change Wheel.

OBJECTIVE

The purpose of this study was to evaluate the reach, fidelity, and dose of the ChIP intervention to discern if it was activated and delivered to patients as intended at two regional Australian hospitals.

METHODS

This is a pretest and post-test implementation evaluation study. The proportion of ChIP activations and adherence to ChIP components received by eligible patients were compared before and after intervention over a 4-year period. Sample medians were compared using the nonparametric median test, with 95% confidence intervals. Differences in proportions for categorical data were compared using the two-sample z-test.

RESULTS/FINDINGS

Over the 19-month postimplementation period, 97.1% (n = 440) of eligible patients received ChIP (reach). The median activation time was 134 min; there was no difference in time to activation between business hours and after-hours; time to activation was not associated with comorbidities and injury severity score. Compared with the preimplementation group, the postimplementation group were more likely to receive evidence-based treatments (dose), including high-flow nasal cannula use (odds ratio [OR] = 6.8 [95% confidence interval {CI} = 4.8-9.6]), incentive spirometry in the emergency department (OR = 7.5, [95% CI = 3.2-17.6]), regular analgesia (OR = 2.4 [95% CI = 1.5-3.8]), regional analgesia (OR = 2.8 [95% CI = 1.5-5.3]), patient-controlled analgesia (OR = 1.8 [95% CI = 1.3-2.4]), and multiple specialist team reviews, e.g., surgical review (OR = 9.9 [95% CI = 6.1-16.1]).

CONCLUSIONS

High fidelity of delivery was achieved and sustained over 19 months for implementation of a complex intervention in the acute context through a robust implementation plan based on theoretical frameworks. There were significant and sustained improvements in care practices known to result in better patient outcomes. Findings from this evaluation can inform future implementation programs such as ChIP and other multidisciplinary interventions in an emergency or acute care context.

Implementation strategies in emergency management of children: A scoping review

BACKGROUND

Implementation strategies are vital for the uptake of evidence to improve health, healthcare delivery, and decision-making. Medical or mental emergencies may be life-threatening, especially in children, due to their unique physiological needs when presenting in the emergency departments (EDs). Thus, practice change in EDs attending to children requires evidence-informed considerations regarding the best approaches to implementing research evidence. We aimed to identify and map the characteristics of implementation strategies used in the emergency management of children.

METHODS

We conducted a scoping review using Arksey and O'Malley's framework. We searched four databases [Medline (Ovid), Embase (Ovid), Cochrane Central (Wiley) and CINAHL (Ebsco)] from inception to May 2019, for implementation studies in children (≤21 years) in emergency settings. Two pairs of reviewers independently selected studies for inclusion and extracted the data. We performed a descriptive analysis of the included studies.

RESULTS

We included 87 studies from a total of 9,607 retrieved citations. Most of the studies were before and after study design (n = 68, 61%) conducted in North America (n = 63, 70%); less than one-tenth of the included studies (n = 7, 8%) were randomized controlled trials (RCTs). About one-third of the included studies used a single strategy to improve the uptake of research evidence. Dissemination strategies were more commonly utilized (n = 77, 89%) compared to other implementation strategies; process (n = 47, 54%), integration (n = 49, 56%), and capacity building and scale-up strategies (n = 13, 15%). Studies that adopted capacity building and scale-up as part of the strategies were most effective (100%) compared to dissemination (90%), process (88%) and integration (85%).

CONCLUSIONS

Studies on implementation strategies in emergency management of children have mostly been non-randomized studies. This review suggests that 'dissemination' is the most common strategy used, and 'capacity building and scale-up' are the most effective strategies. Higher-quality evidence from randomized-controlled trials is needed to accurately assess the effectiveness of implementation strategies in emergency management of children.

Impact of type of health care provider on long term asthma control

OBJECTIVE

Asthma prevalence is high and adherence to asthma guidelines is still less than adequate. The main objective of this study was to determine if there were significant differences in outcome measures if asthma care was provided per guidelines either by physicians (pediatric pulmonologists) or specialty trained advance practice nurses (APNs).

METHODS

This was a three-year, prospective cohort study of children referred by their primary care providers to a tertiary care center for better asthma control. Patients were provided asthma care per NAEPP guidelines including asthma education. Results were compared over time and between patients followed by physicians or APNs. Alpha level of significance was ≤0.05.

RESULTS

The sample included 471 children, ages 2-17 years (mean = 6.4 ± 2.4 years). Physicians and APN's provided asthma care. Of the 471 children enrolled in the study, 176 (37%) were followed for the full three-year study period. At the initial visit, physician group reported more short courses of oral steroids and more unscheduled visits to PCP for acute asthma care in the past 6 months compared to those followed by APNs (<0.05 for all). Among the total cohort and both subgroups, there were significant improvements in mean Asthma Control Test (ACT), acute care need and mean days/month with asthma symptoms over a three-year period (p < 0.05). There was significantly more improvement in use of oral steroids and urgent care visits in physician group (p < 0.05).

CONCLUSION

When asthma guidelines are followed, improvements in asthma control are achieved in children in both the MD and APN groups.

Analytics with artificial intelligence to advance the treatment of acute respiratory distress syndrome

Artificial intelligence (AI) has found its way into clinical studies in the era of big data. Acute respiratory distress syndrome (ARDS) or acute lung injury (ALI) is a clinical syndrome that encompasses a heterogeneous population. Management of such heterogeneous patient population is a big challenge for clinicians. With accumulating ALI datasets being publicly available, more knowledge could be discovered with sophisticated analytics. We reviewed literatures with big data analytics to understand the role of AI for improving the caring of patients with ALI/ARDS. Many studies have utilized the electronic medical records (EMR) data for the identification and prognostication of ARDS patients. As increasing number of ARDS clinical trials data is open to public, secondary analysis on these combined datasets provide a powerful way of finding solution to clinical questions with a new perspective. AI techniques such as Classification and Regression Tree (CART) and artificial neural networks (ANN) have also been successfully used in the investigation of ARDS problems. Individualized treatment of ARDS could be implemented with a support from AI as we are now able to classify ARDS into many subphenotypes by unsupervised machine learning algorithms. Interestingly, these subphenotypes show different responses to a certain intervention. However, current analytics involving ARDS have not fully incorporated information from omics such as transcriptome, proteomics, daily activities and environmental conditions. AI technology is assisting us to interpret complex data of ARDS patients and enable us to further improve the management of ARDS patients in future with individual treatment plans.

Effects of Computerized Decision Support Systems on Practitioner Performance and Patient Outcomes: Systematic Review

Background

Computerized decision support systems (CDSSs) are software programs that support the decision making of practitioners and other staff. Other reviews have analyzed the relationship between CDSSs, practitioner performance, and patient outcomes. These reviews reported positive practitioner performance in over half the articles analyzed, but very little information was found for patient outcomes.

Objective

The purpose of this review was to analyze the relationship between CDSSs, practitioner performance, and patient medical outcomes. PubMed, CINAHL, Embase, Web of Science, and Cochrane databases were queried.

Methods

Articles were chosen based on year published (last 10 years), high quality, peer-reviewed sources, and discussion of the relationship between the use of CDSS as an intervention and links to practitioner performance or patient outcomes. Reviewers used an Excel spreadsheet (Microsoft Corporation) to collect information on the relationship between CDSSs and practitioner performance or patient outcomes. Reviewers also collected observations of participants, intervention, comparison with control group, outcomes, and study design (PICOS) along with those showing implicit bias. Articles were analyzed by multiple reviewers following the Kruse protocol for systematic reviews. Data were organized into multiple tables for analysis and reporting.

Results

Themes were identified for both practitioner performance (n=38) and medical outcomes (n=36). A total of 66% (25/38) of articles had occurrences of positive practitioner performance, 13% (5/38) found no difference in practitioner performance, and 21% (8/38) did not report or discuss practitioner performance. Zero articles reported negative practitioner performance. A total of 61% (22/36) of articles had occurrences of positive patient medical outcomes, 8% (3/36) found no statistically significant difference in medical outcomes between intervention and control groups, and 31% (11/36) did not report or discuss medical outcomes. Zero articles found negative patient medical outcomes attributed to using CDSSs.

Conclusions

Results of this review are commensurate with previous reviews with similar objectives, but unlike these reviews we found a high level of reporting of positive effects on patient medical outcomes.

Impact of asthma severity on long-term asthma control

Background: Asthma is a common childhood disease with significant morbidity. Severe asthma accounts for just 4-6% of patients, but this group is more difficult to treat and is responsible for up to 40% of asthma expenses.Objective: The relationship between asthma severity and control is not well characterized. The main objective of this study was to determine impact of asthma severity on asthma control over time.Methods: This was a three year, prospective observational cohort study at a tertiary care children's hospital. Results were compared over time and between patients with severe and non-severe persistent asthma. Intervention included therapy based on severity and control, accompanied by a NAEPP (EPR-3) guidelines based structured asthma education program.Results: The sample included 471 children referred from primary care offices with the diagnosis of persistent asthma, mean age 6.4 ± 2.4 years. Forty-one children (8.7%) had severe persistent asthma and 430 (91.3%) children had non-severe persistent asthma (mild-moderate persistent). Our sample size decreased over the three-year period and the number of patients completing the third year were 176 (38%) and among them 20 (11.4%) had severe asthma. At the initial visit, children with severe persistent asthma had significantly more acute care needs, more daily symptoms, and lower mean Asthma Control Test™ scores compared to children with non-severe persistent asthma. Differences between groups decreased within six months with significant improvements in most indicators persisting throughout three-year follow up in both groups (p < 0.05).Conclusion: Asthma control improves independent of severity if asthma guidelines are followed.

Treatment and outcome of adult patients with acute asthma in emergency departments in Australasia, South East Asia and Europe: Are guidelines followed? AANZDEM/EuroDEM study

OBJECTIVE

Asthma exacerbations are common presentations to ED. Key guideline recommendations for management include administration of inhaled bronchodilators, systemic corticosteroids and titrated oxygen therapy. Our aim was to compare management and outcomes between patients treated for asthma in Europe (EUR) and South East Asia/Australasia (SEA) and compliance with international guidelines.

METHODS

In each region, prospective, interrupted time series studies were performed including adult (age >18 years) patients presenting to ED with the main complaint of dyspnoea during three 72 h periods. This was a planned sub-study that included those with an ED primary diagnosis of asthma. Data was collected on demographics, clinical features, treatment in ED, diagnosis, disposition and in-hospital outcome. The results of interest were differences in treatment and outcome between EUR and SEA cohorts.

RESULTS

Five hundred and eighty-four patients were identified from 112 EDs (66 EUR and 46 SEA). The cohorts had similar demographics and co-morbidity patterns, with 89% of the cohort having a previous diagnosis of asthma. There were no significant differences in treatment between EUR and SEA patients - inhaled beta-agonists were administered in 86% of cases, systemic corticosteroids in 66%, oxygen therapy in 44% and antibiotics in 20%. Two thirds of patients were discharged home from the ED.

CONCLUSION

The data suggests that compliance with guideline-recommended therapy in both regions, particularly corticosteroid administration, is sub-optimal. It also suggests over-use of antibiotics.

Reducing pediatric asthma hospital length of stay through evidence-based quality improvement and deployment of computerized provider order entry

Objective: Evaluate the impact of multi-component quality improvement for pediatric asthma care focusing on serial use of an evidence-based clinical pathway via paper order sets, pathway integration into computerized provider order entry (CPOE), use of a clinical respiratory score (CRS) and a discharge checklist. Methods: Outcomes were assessed over three intervention periods and 50 months on: time to beta-agonist and steroid first administration, frequency of readmissions and hospital length of stay. A general linear model estimated mean log(LOS) over time and between study periods. Time to discharge was transformed using the natural logarithm. Results: No improvements in time to first beta-agonist or steroid administration were observed. There was a reduction in 100-day readmissions (p = 0.008): decreasing from 7.4 to 2.1% after introduction of paper order sets and CRS (adjusted p = 0.04); to 3.9% after CPOE implementation (adjusted p = 0.53) and to 2.2% when a discharge checklist was added (adjusted p = 0.01). There was a statistically significant reduction in LOS between study periods (p = 0.015). The geometric mean LOS in hours during study periods 1-4 were: 34.8 (95% CI: 32.2, 37.6), 29.3 (95% CI: 27.5, 31.3), 29.0 (95% CI: 27.0, 31.3) and 23.1 (95% CI: 22.1, 24.2). Pair-wise comparisons between periods were statistically significant (adjusted p ≤ 0.003), except for Periods 2 and 3 (adjusted p = 0.83). Conclusions: Hospital length of stay and 100-day readmissions rate in a predominantly Hispanic, Medicaid patient population were reduced by utilization of an evidence-based best practices asthma management pathway and CRS within CPOE, combined with a checklist to expedite discharge.

Scope and Influence of Electronic Health Record-Integrated Clinical Decision Support in the Emergency Department: A Systematic Review

STUDY OBJECTIVE

As electronic health records evolve, integration of computerized clinical decision support offers the promise of sorting, collecting, and presenting this information to improve patient care. We conducted a systematic review to examine the scope and influence of electronic health record-integrated clinical decision support technologies implemented in the emergency department (ED).

METHODS

A literature search was conducted in 4 databases from their inception through January 18, 2018: PubMed, Scopus, the Cumulative Index of Nursing and Allied Health, and Cochrane Central. Studies were included if they examined the effect of a decision support intervention that was implemented in a comprehensive electronic health record in the ED setting. Standardized data collection forms were developed and used to abstract study information and assess risk of bias.

RESULTS

A total of 2,558 potential studies were identified after removal of duplicates. Of these, 42 met inclusion criteria. Common targets for clinical decision support intervention included medication and radiology ordering practices, as well as more comprehensive systems supporting diagnosis and treatment for specific disease entities. The majority of studies (83%) reported positive effects on outcomes studied. Most studies (76%) used a pre-post experimental design, with only 3 (7%) randomized controlled trials.

CONCLUSION

Numerous studies suggest that clinical decision support interventions are effective in changing physician practice with respect to process outcomes such as guideline adherence; however, many studies are small and poorly controlled. Future studies should consider the inclusion of more specific information in regard to design choices, attempt to improve on uncontrolled before-after designs, and focus on clinically relevant outcomes wherever possible.

Recent Advances in Technology and Its Applications to Pediatric Emergency Care

Advances in technology are continuously transforming medical care, including pediatric emergency medicine. The increasing adoption of point-of-care ultrasound examination can improve timely diagnoses without radiation and aids the performance of common procedures. The recent dramatic increase in electronic health record adoption offers an opportunity for enhanced clinical decision-making support. Simulation training and advances in technologies can provide continued proficiency training despite decreasing opportunities for pediatric procedures and cardiorespiratory resuscitation performance. This article reviews these and other recent advances in technology that have had the greatest impact on the current practice of pediatric emergency medicine.

Development and implementation of a mobile device-based pediatric electronic decision support tool as part of a national practice standardization project

Objective

Implementing evidence-based practices requires a multi-faceted approach. Electronic clinical decision support (ECDS) tools may encourage evidence-based practice adoption. However, data regarding the role of mobile ECDS tools in pediatrics is scant. Our objective is to describe the development, distribution, and usage patterns of a smartphone-based ECDS tool within a national practice standardization project.

Materials and Methods

We developed a smartphone-based ECDS tool for use in the American Academy of Pediatrics, Value in Inpatient Pediatrics Network project entitled "Reducing Excessive Variation in the Infant Sepsis Evaluation (REVISE)." The mobile application (app), PedsGuide, was developed using evidence-based recommendations created by an interdisciplinary panel. App workflow and content were aligned with clinical benchmarks; app interface was adjusted after usability heuristic review. Usage patterns were measured using Google Analytics.

Results

Overall, 3805 users across the United States downloaded PedsGuide from December 1, 2016, to July 31, 2017, leading to 14 256 use sessions (average 3.75 sessions per user). Users engaged in 60 442 screen views, including 37 424 (61.8%) screen views that displayed content related to the REVISE clinical practice benchmarks, including hospital admission appropriateness (26.8%), length of hospitalization (14.6%), and diagnostic testing recommendations (17.0%). Median user touch depth was 5 [IQR 5].

Discussion

We observed rapid dissemination and in-depth engagement with PedsGuide, demonstrating feasibility for using smartphone-based ECDS tools within national practice improvement projects.

Conclusions

ECDS tools may prove valuable in future national practice standardization initiatives. Work should next focus on developing robust analytics to determine ECDS tools' impact on medical decision making, clinical practice, and health outcomes.

Patients Decision Aid System Based on FHIR Profiles

Patients are becoming more and more involved in clinical decision-making process. Several factors support this process. Advances in omics allows individualization of diagnosis and treatment. Patient awareness and easy availability of data on the Internet allows patients to become informed decision makers when it comes even to disease management. Mass media emphasize the issue of medical errors, making patients demanding for quality in medical care. In some healthcare settings, patents face a problem of interpreting medical data and making decisions on treatment tactics without having a doctor, who could potentially support them. Delegating this task to a Patient Decision Aide system can add automatically generated recommendations to result reports without adding significant workload on the doctors, increase patients' motivation and support their decisions. We have implemented a patient decision aid system based on the productions rules, which: Collects data from available sources; Automatically analyses and interprets laboratory test results; Recommends running additional tests for a more precise diagnostic; Delivers automatically generated reports to doctors and patients in a natural language. To achieve semantic interoperability with other systems we have implemented a FHIR engine. The knowledge base has been organized as a graph structure. The application is structured as a set of lightly coupled services, which implement the logic of the decision support system. In total, we have modelled 365 nodes of test components, 5084 nodes of inference rules, 49932 connections and 3072 blocks of text for medical certificates. The findings of the research provide a deep understanding of how the semantically interoperable clinical decision support systems are implemented. Advances in notification the patients with the elements of patient decision aid is important for clinical data management, and for patients' empowerment and protection. We suppose that the system empowering patients in such way can play a meaningful role in helping patients to make informed decisions during the process of diagnostics and treatment.

Identifying Asthma Exacerbation-Related Emergency Department Visit Using Electronic Medical Record and Claims Data

Background  Asthma exacerbation leading to emergency department (ED) visit is prevalent, an indicator of poor control of asthma, and is a potentially preventable clinical outcome.

Objective  We propose to utilize multiple data elements available in electronic medical records (EMRs) and claims database to create separate algorithms with high validity for clinical and research purposes to identify asthma exacerbation-related ED visit among the general population.

Methods  We performed a retrospective study with inclusion criteria of patients aged 4 to 40 years, a visit to Geisinger ED from January 1, 2006, to October 28, 2013, with asthma on their problem list. Different electronic data elements including chief complaints, vitals, season, smoking, medication use, and discharge diagnoses were obtained to create the algorithm. A stratified random sample was generated to select the charts for review. Chart review was performed to classify patients with asthma-related ED visit, that is, the gold standard. Two reviewers performed the chart review and validation was done on a small subset.

Results  There were 966 eligible ED visits in the EMR sample and 731 in the claims sample. Agreement between reviewers was 95.45% and kappa statistic was 0.91. Mean age of the EMR sample was 22 years, and mostly white (93%). Multiple models conventionally used in studies were evaluated and the final model chosen included principal diagnosis, bronchodilator, and steroid use for both algorithms, chief complaints for EMR, and secondary diagnosis for claims. Area under the curve was 0.93 (95% confidence interval: 0.91–0.94) and 0.94 (0.93–0.96), respectively, for EMR and claims data, with positive predictive value of > 94%. The algorithms are visually presented using nomograms.

Conclusion  We were able to develop two separate algorithms for EMR and claims to identify asthma exacerbation-related ED visit with excellent diagnostic ability and varying discrimination threshold for clinical and research purposes.

Review of implementation strategies to change healthcare provider behaviour in the emergency department

OBJECTIVES

Advances in emergency medicine research can be slow to make their way into clinical care, and implementing a new evidence-based intervention can be challenging in the emergency department. The Canadian Association of Emergency Physicians (CAEP) Knowledge Translation Symposium working group set out to produce recommendations for best practice in the implementation of a new science in Canadian emergency departments.

METHODS

A systematic review of implementation strategies to change health care provider behaviour in the emergency department was conducted simultaneously with a national survey of emergency physician experience. We summarized our findings into a list of draft recommendations that were presented at the national CAEP Conference 2017 and further refined based on feedback through social media strategies.

RESULTS

We produced 10 recommendations for implementing new evidence-based interventions in the emergency department, which cover identifying a practice gap, evaluating the evidence, planning the intervention strategy, monitoring, providing feedback during implementation, and desired qualities of future implementation research.

CONCLUSIONS

We present recommendations to guide future emergency department implementation initiatives. There is a need for robust and well-designed implementation research to guide future emergency department implementation initiatives.

Health Information Technology Continues to Show Positive Effect on Medical Outcomes: Systematic Review

Background

Health information technology (HIT) has been introduced into the health care industry since the 1960s when mainframes assisted with financial transactions, but questions remained about HIT’s contribution to medical outcomes. Several systematic reviews since the 1990s have focused on this relationship. This review updates the literature.

Objective

The purpose of this review was to analyze the current literature for the impact of HIT on medical outcomes. We hypothesized that there is a positive association between the adoption of HIT and medical outcomes.

Methods

We queried the Cumulative Index of Nursing and Allied Health Literature (CINAHL) and Medical Literature Analysis and Retrieval System Online (MEDLINE) by PubMed databases for peer-reviewed publications in the last 5 years that defined an HIT intervention and an effect on medical outcomes in terms of efficiency or effectiveness. We structured the review from the Primary Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA), and we conducted the review in accordance with the Assessment for Multiple Systematic Reviews (AMSTAR).

Results

We narrowed our search from 3636 papers to 37 for final analysis. At least one improved medical outcome as a result of HIT adoption was identified in 81% (25/37) of research studies that met inclusion criteria, thus strongly supporting our hypothesis. No statistical difference in outcomes was identified as a result of HIT in 19% of included studies. Twelve categories of HIT and three categories of outcomes occurred 38 and 65 times, respectively.

Conclusions

A strong majority of the literature shows positive effects of HIT on the effectiveness of medical outcomes, which positively supports efforts that prepare for stage 3 of meaningful use. This aligns with previous reviews in other time frames.

Validation of asthma recording in electronic health records: a systematic review

Objective

To describe the methods used to validate asthma diagnoses in electronic health records and summarize the results of the validation studies.

Background

Electronic health records are increasingly being used for research on asthma to inform health services and health policy. Validation of the recording of asthma diagnoses in electronic health records is essential to use these databases for credible epidemiological asthma research.

Methods

We searched EMBASE and MEDLINE databases for studies that validated asthma diagnoses detected in electronic health records up to October 2016. Two reviewers independently assessed the full text against the predetermined inclusion criteria. Key data including author, year, data source, case definitions, reference standard, and validation statistics (including sensitivity, specificity, positive predictive value [PPV], and negative predictive value [NPV]) were summarized in two tables.

Results

Thirteen studies met the inclusion criteria. Most studies demonstrated a high validity using at least one case definition (PPV >80%). Ten studies used a manual validation as the reference standard; each had at least one case definition with a PPV of at least 63%, up to 100%. We also found two studies using a second independent database to validate asthma diagnoses. The PPVs of the best performing case definitions ranged from 46% to 58%. We found one study which used a questionnaire as the reference standard to validate a database case definition; the PPV of the case definition algorithm in this study was 89%.

Conclusion

Attaining high PPVs (>80%) is possible using each of the discussed validation methods. Identifying asthma cases in electronic health records is possible with high sensitivity, specificity or PPV, by combining multiple data sources, or by focusing on specific test measures. Studies testing a range of case definitions show wide variation in the validity of each definition, suggesting this may be important for obtaining asthma definitions with optimal validity.

Are emergency department clinical pathway interventions adequately described, and are they delivered as intended? A systematic review

Introduction

The accurate reproduction of clinical interventions and the evaluation of provider adherence in research publications improve the evaluation and implementation of research findings into clinical practice. We sought to examine the proportion of clinical pathway publications in an emergency department setting that adequately reported the following: (1) the exact reproduction of the clinical pathway that was implemented in the study, (2) the adherence to and correct execution of the clinical pathway intervention, and (3) the presence of a pre-implementation education phase.

Methods

We performed a descriptive systematic review of the literature from 2006 to 2015 using MEDLINE, EMBASE, CENTRAL, and CINAHL. All types of prospective trial designs were eligible. Validated clinical pathway criteria were used to identify relevant publications. Two reviewers independently collected data using a piloted data abstraction tool. Risk of bias was assessed using the Cochrane Effective Practice and Organization of Care Group Risk of Bias Tool and the Newcastle-Ottawa Scale.

Results

We identified 5947 publications, 44 of which met our inclusion criteria. The formal clinical pathway was fully reproduced in 27 (61%) publications, partially reproduced in 9 (21%), and not reproduced in 8 (18%). Only 14 (32%) studies reported whether at least one decision step was executed correctly. The presence of a pre-implementation education phase was reported in 33 (75%) studies.

Conclusion

The underreporting of intervention elements may present a barrier to both the evaluation and accurate replication of clinical pathway interventions. These finding may be useful for the elaboration of complex intervention reporting guidelines, improved reporting in future clinical pathway publications, and improved knowledge translation and exchange of clinical pathway interventions.

Personalization and Patient Involvement in Decision Support Systems: Current Trends

OBJECTIVES

This survey aims at highlighting the latest trends (2012-2014) on the development, use, and evaluation of Information and Communication Technologies (ICT) based decision support systems (DSSs) in medicine, with a particular focus on patient-centered and personalized care.

METHODS

We considered papers published on scientific journals, by querying PubMed and Web of ScienceTM. Included studies focused on the implementation or evaluation of ICT-based tools used in clinical practice. A separate search was performed on computerized physician order entry systems (CPOEs), since they are increasingly embedding patient-tailored decision support.

RESULTS

We found 73 papers on DSSs (53 on specific ICT tools) and 72 papers on CPOEs. Although decision support through the delivery of recommendations is frequent (28/53 papers), our review highlighted also DSSs only based on efficient information presentation (25/53). Patient participation in making decisions is still limited (9/53), and mostly focused on risk communication. The most represented medical area is cancer (12%). Policy makers are beginning to be included among stakeholders (6/73), but integration with hospital information systems is still low. Concerning knowledge representation/management issues, we identified a trend towards building inference engines on top of standard data models. Most of the tools (57%) underwent a formal assessment study, even if half of them aimed at evaluating usability and not effectiveness.

CONCLUSIONS

Overall, we have noticed interesting evolutions of medical DSSs to improve communication with the patient, consider the economic and organizational impact, and use standard models for knowledge representation. However, systems focusing on patient-centered care still do not seem to be available at large.

Validation of descriptive clinical pathway criteria in the systematic identification of publications in emergency medicine

Background

Heterogeneity in both the definition and terminology of clinical pathways presents a challenge to the systematic identification of primary studies for review purposes. Recently developed clinical pathway identification criteria may facilitate both the identification and assessment of clinical pathway studies. The goal of this publication is the validation of these five criteria in a descriptive systematic review of actively implemented clinical pathway studies in the emergency department setting. The main outcome measure is the inter-rater agreement of investigators using the clinical pathway criteria.

Methods

We performed a systematic literature search from 2006 to 2015 using MEDLINE, EMBASE, CENTRAL, and CINAHL. All types of prospective trial designs were eligible. We identified relevant publications using the above-mentioned clinical pathway criteria. Two reviewers independently collected data using a piloted data abstraction tool.

Results

We identified 5947 publications, with 472 potentially relevant full text publications retrieved. Of these, 357 did not meet preliminary study inclusion criteria, leaving 115 publications where the clinical pathway criteria were applied. Ultimately, 44 publications were included. The inter-rater agreement of the criteria was very good (κ = 0.81, 95% Confidence Interval = 0.70–0.92). The vast majority of studies were excluded because the intervention did not meet the criterion of being multidisciplinary in nature.

Conclusion

These criteria are a useful instrument to reliably identify clinical pathway publications for systematic review purposes in an emergency department setting. Future modification of these criteria may improve their usefulness. Particular attention should be placed on clarifying what is meant by multidisciplinary involvement within the context of clinical pathway interventions, with specific emphasis placed on delineating the level of involvement of each discipline and their decision-making responsibility.

The soft computing-based approach to investigate allergic diseases: a systematic review

BACKGROUND

Early recognition of inflammatory markers and their relation to asthma, adverse drug reactions, allergic rhinitis, atopic dermatitis and other allergic diseases is an important goal in allergy. The vast majority of studies in the literature are based on classic statistical methods; however, developments in computational techniques such as soft computing-based approaches hold new promise in this field.

OBJECTIVE

The aim of this manuscript is to systematically review the main soft computing-based techniques such as artificial neural networks, support vector machines, bayesian networks and fuzzy logic to investigate their performances in the field of allergic diseases.

METHODS

The review was conducted following PRISMA guidelines and the protocol was registered within PROSPERO database (CRD42016038894). The research was performed on PubMed and ScienceDirect, covering the period starting from September 1, 1990 through April 19, 2016.

RESULTS

The review included 27 studies related to allergic diseases and soft computing performances. We observed promising results with an overall accuracy of 86.5%, mainly focused on asthmatic disease. The review reveals that soft computing-based approaches are suitable for big data analysis and can be very powerful, especially when dealing with uncertainty and poorly characterized parameters. Furthermore, they can provide valuable support in case of lack of data and entangled cause-effect relationships, which make it difficult to assess the evolution of disease.

CONCLUSIONS

Although most works deal with asthma, we believe the soft computing approach could be a real breakthrough and foster new insights into other allergic diseases as well.

Paediatric ED BiPAP continuous quality improvement programme with patient analysis: 2005-2013

OBJECTIVE

In paediatric moderate-to-severe asthmatics, there is significant bronchospasm, airway obstruction, air trapping causing severe hyperinflation with more positive intraplural pressure preventing passive air movement. These effects cause an increased respiratory rate (RR), less airflow and shortened inspiratory breath time. In certain asthmatics, aerosols are ineffective due to their inadequate ventilation. Bilevel positive airway pressure (BiPAP) in acute paediatric asthmatics can be an effective treatment. BiPAP works by unloading fatigued inspiratory muscles, a direct bronchodilation effect, offsetting intrinsic PEEP and recruiting collapsed alveoli that reduces the patient's work of breathing and achieves their total lung capacity quicker. Unfortunately, paediatric emergency department (PED) BiPAP is underused and quality analysis is non-existent. A PED BiPAP Continuous Quality Improvement Program (CQIP) from 2005 to 2013 was evaluated using descriptive analytics for the primary outcomes of usage, safety, BiPAP settings, therapeutics and patient disposition.

INTERVENTIONS

PED BiPAP CQIP descriptive analytics.

SETTING

Academic PED.

PARTICIPANTS

1157 patients.

INTERVENTIONS

A PED BiPAP CQIP from 2005 to 2013 for the usage, safety, BiPAP settings, therapeutic response parameters and patient disposition was evaluated using descriptive analytics.

PRIMARY AND SECONDARY OUTCOMES

Safety, usage, compliance, therapeutic response parameters, BiPAP settings and patient disposition.

RESULTS

1157 patients had excellent compliance without complications. Only 6 (0.5%) BiPAP patients were intubated. BiPAP median settings: IPAP 18 (16,20) cm H₂O range 12-28; EPAP 8 cmH₂O (8,8) range 6-10; inspiratory-to-expiratory time (I:E) ratio 1.75 (1.5,1.75). Pediatric Asthma Severity score and RR decreased (p<0.001) while tidal volume increased (p<0.001). Patient disposition: 325 paediatric intensive care units (PICU), 832 wards, with 52 of these PED ward patients were discharged home with only 2 hours of PED BiPAP with no returning to the PED within 72 hours.

CONCLUSIONS

BiPAP is a safe and effective therapeutic option for paediatric patients with asthma presenting to a PED or emergency department. This BiPAP CQIP showed significant patient compliance, no complications, improved therapeutics times, very low intubations and decreased PICU admissions. CQIP analysis demonstrated that using a higher IPAP, low EPAP with longer I:E optimises the patient's BiPAP settings and showed a significant improvement in PAS, RR and tidal volume. BiPAP should be considered as an early treatment in the PED severe or non-responsive moderate asthmatics.

Improved quality-of-life of caregivers of children with asthma through guideline-based management

OBJECTIVE

The quality of life (QOL) of caregivers of children with asthma may be related to children's responses to asthma management.

AIM

To evaluate change in QOL over time of caregivers of children with asthma through guideline-based management.

DESIGN

This was a 3-year prospective cohort study of children with asthma referred to our pediatric asthma center. Families completed Pediatric Asthma Caregiver's Quality of Life Questionnaire (PACQLQ), the Asthma Control Test™ (ACT), and reported the number of days/month of albuterol use and wheezing at each clinic visit.

RESULTS

We enrolled 143 children, ages 7-17 years (mean = 10.6 ± 2.9), 56.6% male, 70.6% Caucasian. Patients were managed by the same MD (n = 65,45.5%) or APN (n = 78,54.5%) over time. The mean total PACQLQ significantly increased over the 3-year period (F = 67.418, p < .001). Total scores at the first visit were 4.8 ± 1.6, which improved to 6.1 ± 1 at the 3-month follow-up visit. This improvement was sustained at the 1, 2, and 3-year clinic visits. PACQLQ emotional function (F = 60.798, p < .001) and activity limitation (F = 41.517, p < .001) domains significantly improved as well. PACQLQ scores were significantly associated with improved ACT scores (r = .37 to .47, p < .05), fewer days/month of albuterol use (r = -.25 to -.36., p < .05), and wheezing (r = -.28 to -.33, p < .05). There were no significant differences in PACQLQ, or asthma clinical outcome measures between MD and APN providers.

CONCLUSION

Use of National Asthma Education and Prevention Program (NAEPP) guidelines significantly improved QOL of caregivers of children with asthma and in asthma-related symptoms. Improvements over time were independent of type of providers.

The asthma prediction rule to decrease hospitalizations for children with asthma

PURPOSE OF REVIEW

The aim of the present review was to discuss the challenges around clinical decision-making for hospitalization of children with acute asthma exacerbations and the development, internal validation, and future potential of the asthma prediction rule (APR) to provide meaningful clinical decision-support that might decrease unnecessary hospitalizations.

RECENT FINDINGS

The APR was developed and internally validated using predictor variables available before treatment in the emergency department, and performed well to predict 'need-for-hospitalization.' Oxygen saturation on room air and expiratory phase prolongation were most strongly associated with need-for-hospitalization.

SUMMARY

Research on prediction rules in pediatric asthma is rare. We developed and internally validated the APR using clinically intuitive predictor variables that are available at the bedside. Before incorporation into electronic decision-support the APR must undergo external validation and an impact analysis to determine if use of this tool will change clinician behavior and improve patient outcomes.

Knowledge translation studies in paediatric emergency medicine: A systematic review of the literature

AIM

Systematic review of knowledge translation studies focused on paediatric emergency care to describe and assess the interventions used in emergency department settings.

METHODS

Electronic databases were searched for knowledge translation studies conducted in the emergency department that included the care of children. Two researchers independently reviewed the studies.

RESULTS

From 1305 publications identified, 15 studies of varied design were included. Four were cluster-controlled trials, two patient-level randomised controlled trials, two interrupted time series, one descriptive study and six before and after intervention studies. Knowledge translation interventions were predominantly aimed at the treating clinician, with some targeting the organisation. Studies assessed effectiveness of interventions over 6-12 months in before and after studies, and 3-28 months in cluster or patient level controlled trials. Changes in clinical practice were variable, with studies on single disease and single treatments in a single site showing greater improvement.

CONCLUSIONS

Evidence for effective methods to translate knowledge into practice in paediatric emergency medicine is fairly limited. More optimal study designs with more explicit descriptions of interventions are needed to facilitate other groups to effectively apply these procedures in their own setting.

Evaluation methods used on health information systems (HISs) in Iran and the effects of HISs on Iranian healthcare: a systematic review

OBJECTIVES

The most important goal of a health information system (HIS) is improvement of quality, effectiveness and efficiency of health services. To achieve this goal, health care systems should be evaluated continuously. The aim of this paper was to study the impacts of HISs in Iran and the methods used for their evaluation.

METHODS

We systematically searched all English and Persian papers evaluating health information systems in Iran that were indexed in SID, Magiran, Iran medex, PubMed and Embase databases until June 2013. A data collection form was designed to extract required data such as types of systems evaluated, evaluation methods and tools.

RESULTS

In this study, 53 out of 1103 retrieved articles were selected as relevant and reviewed by the authors. This study indicated that 28 studies used questionnaires to evaluate the system and in 27 studies the study instruments were distributed within a research population. In 26 papers the researchers collected the information by means of interviews, observations, heuristic evaluation and the review of documents and records. The main effects of the evaluated systems in health care settings were improving quality of services, reducing time, increasing accessibility to information, reducing costs and decreasing medical errors.

CONCLUSION

Evaluation of health information systems is central to their development and enhancement, and to understanding their effect on health and health services. Despite numerous evaluation methods available, the reviewed studies used a limited number of methods to evaluate HIS. Additionally, the studies mainly discussed the positive effects of HIS on health care services.