Thirty years ago, Sue Sheridan welcomed her first child, Cal, into the world. At 16 hours of age, a clinician observed that he was jaundiced and entered this assessment into his medical record. But Sheridan didn’t know that. She sensed something was wrong and asked repeatedly about her concerns. She was pegged as a ‘nervous mother’ and reassured. Upon discharge, the nurse’s note again described neonatal jaundice ‘from head to toe’, signalling the need for monitoring and testing. Sheridan was not informed of the potential seriousness of this condition or what symptoms to look for. On day 3, a paediatrician assessed a limp and lethargic infant. On day 4, Sheridan—still concerned—returned to the hospital. There, the bilirubin level returned at 34.6 mg/dL. Cal incurred severe brain damage from kernicterus, diagnosed months later.

Today, Sheridan—and nearly all parents in the USA—would have access to their child’s electronic medical record, including...

Background

Children represent fewer than 10% of emergency medical services (EMS) encounters in the USA. We evaluated whether agency-level paediatric volume is associated with the quality of prehospital care provided.

Methods

We conducted a retrospective analysis of 7104 agencies that contributed data consistently to the 2022–2023 National Emergency Medical Services Information System database, including children (<18 years) from an out-of-hospital EMS encounter. We assessed outcomes based on adherence to paediatric-specific quality benchmarks using mixed-effects models.

Results

We identified 3 403 925 paediatric encounters (median age 10 years; IQR 3–15). The annual paediatric volumes serviced by the study agencies per year ranged from 0.5 to 62 443. Six measures had a positive association with EMS volume, one measure had a negative association with EMS volume and four measures had no association with EMS volume. Higher volumes were associated with beta agonist administration for asthma/wheeze (adjusted OR (aOR) 1.08 per twofold increase in volume, 95% CI 1.06 to 1.11), epinephrine for anaphylaxis (aOR 1.09, 95% CI 1.05 to 1.08), vital signs assessment in trauma (aOR 1.05, 95% CI 1.04 to 1.07), benzodiazepines for status epilepticus (aOR 1.21, 95% CI 1.17 to 1.25), oxygen or positive pressure ventilation for hypoxia (aOR 1.06, 95% CI 1.04 to 1.09) and naloxone for opioid overdose (aOR 1.08, 95% CI 1.02 to 1.14). Higher paediatric volume was negatively associated with improvement of pain status in trauma (aOR 0.96, 95% CI 0.95 to 0.97). Paediatric volume was not associated with management of hypoglycaemia (aOR 1.01, 95% CI 0.97 to 1.06) or hypotension (aOR 0.98, 95% CI 0.92 to 1.04), or analgesia (0.99, 95% CI 0.97 to 1.01) and pain assessment (aOR 1.01, 95% CI 0.99 to 1.04) in trauma.

Conclusion

Higher paediatric volume EMS agencies had better adherence to some paediatric care quality measures but showed no association or an inverse association with others. Efforts to improve prehospital paediatric care quality should pay special attention to low-volume agencies.

Background

Guideline concordance is associated with improved patient outcomes. Accurately quantifying the concordance between provided care and guideline recommendations offers valuable insights into the alignment of care with established guidelines and supports proactive approaches for improving the quality of care. Traditional models for calculating guideline concordance are effective in assessing clinical performance via cohort averages. However, these models fail at the individual patient level by not accounting for past clinical activities and their timing, which may give a distorted impression of the actual alignment between guideline recommendations and received care.

Objectives

To develop a model for evaluating guideline concordance that provides accurate concordance scores at the individual patient level.

Methods

The newly developed ratio model incorporates past clinical activities and their timing (ie, past clinical trajectories), resulting in accurate, patient-centred concordance scores. We discuss its advantages and limitations and showcase its performance using clinical indicators for patients with type 2 diabetes mellitus.

Results

The ratio model demonstrates enhanced precision in evaluating guideline concordance at the individual level and better reflects the clinical trajectory of individual patients. While primarily designed to produce accurate individual patient scores, the model is also effective for assessing clinical performance through cohort averages. The ratio model is adaptable to diverse clinical contexts requiring regular follow-up, including chronic disease management, vaccination programmes, cancer surveillance and routine health screenings.

Conclusions

The ratio model provides accurate and patient-centred guideline concordance scores. The model’s enhanced precision at the individual level creates opportunities for research and clinical applications, including integration into clinical decision support systems.

Objectives

Many hospitals use fall prevention alarms, despite the limited evidence of effectiveness. The objectives of this study were (1) to identify, conceptualise and select strategies to deimplement fall prevention alarms and (2) to obtain feedback from key stakeholders on tailoring selected deimplementation strategies for the local hospital context.

Methods

Hospital staff working on fall prevention participated in group concept mapping (GCM) to brainstorm strategies that could be used for fall prevention alarm deimplementation, sort statements into conceptually similar categories and rate statements based on importance and current use. Hospital staff also participated in site-specific focus groups to discuss current fall prevention practices, strategies prioritised through GCM and theory-informed strategies recommended by the study team, and potential barriers/facilitators to deimplementing fall prevention alarms.

Results

90 hospital staff across 13 hospitals brainstormed, rated and sorted strategies for alarm deimplementation. Strategies that were rated as highly important but underutilised included creating/revising staff roles to support fall prevention (eg, hiring or designating mobility technicians) and revising policies and procedures to encourage tailored rather than universal fall precautions. 192 hospital staff across 22 hospitals participated in site-specific focus groups. Participants provided feedback on each strategy’s relevance for their site (eg, if site currently has a mobility technician) and local barriers or facilitators (eg, importance of having separate champions for day and night shift). Findings were used to develop a tailored implementation package for each site that included a core set of strategies (eg, external facilitation, education, audit-and-feedback, champions), a select set of site-specific strategies (eg, designating a mobility technician to support fall prevention) and guidance for how to operationalise and implement each strategy given local barriers and facilitators.

Conclusion

Findings from this study can be used to inform future programmes and policies aimed at deimplementing fall prevention alarms in hospitals.

Purpose

Misgendering of transgender and non-binary (TGNB) individuals in healthcare settings can lead to worsened mental and physical health outcomes and decreased utilisation of care. Few studies have investigated the factors that contribute to this phenomenon. The purpose of this study was to apply qualitative methods to explore sources of misgendering, its perceived impact, prevention strategies and clinician responses to accidentally misgendering a patient, as identified by TGNB patients and gender-affirming care clinicians.

Methods

Between April and June 2022, 20 semi-structured interviews were performed at an academic medical centre in Southern California. Participants were recruited via purposive sampling and included: (1) TGNB patients (n=8) recruited from an interdisciplinary gender-affirming urological practice and (2) gender-affirming care clinicians (n=12) recruited from a regional interdisciplinary Gender Health conference, three of whom identified as TGNB. Interviews were conducted in person or virtually using an open-ended topic guide, audio recorded and transcribed verbatim. Inductive thematic analysis was performed by two independent study personnel who hand-coded the transcripts.

Results

Four overarching themes were identified: (1) misgendering originates from multiple sources, (2) misgendering discourages individual access to healthcare, creates community hesitation and its perceived impact is modified by setting and intentionality, (3) building a gender-affirming healthcare system requires integration of behaviour, policy and technology and (4) clinicians respond to accidental misgendering by acknowledging, apologising, advancing and acting.

Conclusion

Our data suggest that misgendering arises from both interpersonal communication and structural factors within healthcare systems, leading to perceived harm and diminished TGNB access to health services. Any potential solution to reduce this phenomenon will require a multifaceted approach integrating behavioural, technological and institutional policy strategies with system-level implementation efforts.

Background

Access to electronic health records (EHRs) has the potential to improve the quality of care. Clinical notes, free-text entries documenting clinicians’ observations and decisions, are central to EHRs. Sharing these notes may reduce information asymmetry, enhance transparency and empower patients. However, their impact on care quality remains unclear.

Aim

To assess the impact of sharing clinical notes online with patients on the domains of quality as defined by the Institute of Medicine (ie, patient-centredness, effectiveness, efficiency, safety, timeliness and equity).

Methodology

A systematic review was conducted with no time limit, using CINAHL, Cochrane, OVID Embase, HMIC, Medline/PubMed and PsycINFO. A narrative synthesis method was employed to extract the study characteristics, and reported outcomes were organised using the six IOM quality domains. The risk of bias of included studies was assessed using the Risk of Bias in Non-randomised Studies of Interventions (ROBINS-I) tool.

Results

Nineteen studies involving 203 152 participants met inclusion criteria. Outcomes included patient-centredness (n=16), patient safety (n=14), equity (n=6), efficiency (n=4), timeliness (n=0) and effectiveness (n=0). Patient-centredness studies reported high satisfaction (n=6), increased engagement (n=11) and stronger patient–provider trust (n=7). Patient safety studies noted improvements in medication adherence (n=4) and note accuracy (n=5), alongside privacy concerns (n=5). Equity studies found benefits for minority (n=3) and less-educated patients (n=2), with one reporting equitable outcomes (n=1). No significant changes in efficiency were observed (n=4).

Discussion

Online sharing of clinical notes with patients positively impacted self-reported patient-centredness and patient safety, particularly benefiting underserved populations. However, privacy concerns must be effectively addressed, and robust safeguarding is essential to mitigate confidentiality issues. Further research is needed to evaluate the long-term impact on timeliness, effectiveness and efficiency of care.

Background

Intraoperative hypothermia can lead to adverse clinical outcomes and avoidable financial and environmental costs. Environmentally preferable warming practices have been identified, including using reusable resistive blankets, extending the life cycle of forced air warming (FAW) garments and minimising flannel blanket use. This study integrates existing environmental data with best practices and quality improvement methodology to develop an optimised patient warming pathway (OPWP). This pathway was adapted to our local context, implemented and evaluated.

Methods

The OPWP was developed using a scoping review, prior environmental impact assessment and root cause analysis. It was tailored to the workflows, patient population and warming practices at a tertiary care hospital and implemented using a multifaceted approach encompassing nine PDSA (Plan-Do-Study-Act) cycles. Major interventions included expanding pre-warming criteria to meet best practice guidelines, preserving the FAW Flex Gown, staff education and training, behaviourally informed strategies, gamification and policy development. Pre-intervention and post-intervention audits assessed environmental and financial savings, incidence of hypothermia and patient-reported outcomes (PROs).

Results

The OPWP recommends preferential use of the resistive blanket for intraoperative warming, preservation of the Flex Gown for postoperative use when warming with FAW and minimising flannel blanket use. A modified pathway was implemented using FAW with preservation of a single Flex Gown throughout the perioperative journey. From pre-intervention (N=51) to post-intervention (N=64), flannel blanket use decreased from an average of 6 to 3 per patient (p<0.01). Active warming increased from 55% to 80% (p=0.04) preoperatively and from 0% to 55% (p<0.01) postoperatively. There was no significant change in the incidence of hypothermia (18% to 15%, p=0.77) and PROs remained favourable. Implementation of this pathway could lead to annual environmental savings of 940 339 kg of carbon dioxide equivalents and cost savings of $C117 978.

Conclusions

This study demonstrates the successful implementation of an evidence-based and environmentally sustainable perioperative warming pathway to achieve low-carbon, high-quality patient care.

Artificial intelligence (AI) has great potential to assist healthcare staff and organisations in maintaining and improving the quality and safety of healthcare1 in the face of workforce shortages, rising service demand and escalating costs. Despite hundreds of regulator-approved AI-enabled tools internationally, relatively few feature in routine clinical care,2 in part due to inattention to how AI tools integrate into sociotechnical healthcare environments.3 In this Viewpoint, based on our experience as AI implementation researchers, we discuss what we see as seven key barriers to the adoption of AI in healthcare and offer some solutions.

AI literacy and engagementUnderdeveloped professional skills and consumer understanding

AI will never be adopted at scale unless health professionals better understand AI and its limitations, acquire competencies in co-designing, co-evaluating and effectively using AI tools, undertake continual vigilance of AI tool performance and avoid over-reliance on AI with...

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