To predict the risk of hospital-acquired pressure injury using machine learning compared with standard care.

We obtained electronic health records (EHRs) to structure a multilevel cohort of hospitalised patients at risk for pressure injury and then calibrate a machine learning model to predict future pressure injury risk. Optimisation methods combined with multilevel logistic regression were used to develop a predictive algorithm of patient-specific shifts in risk over time. Machine learning methods were tested, including random forests, to identify predictive features for the algorithm. We reported the results of the regression approach as well as the area under the receiver operating characteristics (ROC) curve for predictive models.

Hospitalised inpatients.

EHRs of 35 001 hospitalisations over 5 years across 2 academic hospitals.

Longitudinal shifts in pressure injury risk.

The predictive algorithm with features generated by machine learning achieved significantly improved prediction of pressure injury risk (p

These data could help hospitals conserve resources within a critical period of patient vulnerability of hospital-acquired pressure injury which is not reimbursed by US Medicare; thus, conserving between 30 000 and 90 000 labour-hours per year in an average 500-bed hospital. Hospitals can use this predictive algorithm to initiate a quality improvement programme for pressure injury prevention and further customise the algorithm to patient-specific variation by facility.

There is a substantial lack of inter-facility referral systems for emergency obstetrical and neonatal care in rural areas of sub-Saharan Africa. Data on the costs and cost-effectiveness of such systems that reduce preventable maternal and neonatal deaths are scarce.

We aimed to determine the cost-effectiveness of a non-governmental organisation (NGO)-run inter-facility referral system for emergency obstetrical and neonatal care in rural Southern Madagascar by analysing the characteristics of cases referred through the intervention as well as its costs.

We used secondary NGO data, drawn from an NGO’s monitoring and financial administration database, including medical and financial records.

We performed a descriptive and a cost-effectiveness analysis, including a one-way deterministic sensitivity analysis.

1172 cases were referred over a period of 4 years. The most common referral reasons were obstructed labour, ineffective labour and eclampsia. In total, 48 neonates were referred through the referral system over the study period. Estimated cost per referral was US$336 and the incremental cost-effectiveness ratio (ICER) was US$70 per additional life-year saved (undiscounted, discounted US$137). The sensitivity analysis showed that the intervention was cost-effective for all scenarios with the lowest ICER at US$99 and the highest ICER at US$205 per additional life-year saved. When extrapolated to the population living in the study area, the investment costs of the programme were US$0.13 per person and annual running costs US$0.06 per person.

In our study, the inter-facility referral system was a very cost-effective intervention. Our findings may inform policies, decision-making and implementation strategies for emergency obstetrical and neonatal care referral systems in similar resource-constrained settings.

This study evaluated the prevalence and correlates of guideline non-adherence for common childhood illnesses in low-resource settings.

We used secondary cross-sectional data from eight healthcare facilities in six Asian and African countries.

A total of 2796 children aged 2–23 months hospitalised between November 2016 and January 2019 with pneumonia, diarrhoea or severe malnutrition (SM) and without HIV infection were included in this study.

We identified children treated with full, partial or non-adherent initial inpatient care according to site-specific standard-of-care guidelines for pneumonia, diarrhoea and SM within the first 24 hours of admission. Correlates of guideline non-adherence were identified using generalised estimating equations.

Fully adherent care was delivered to 32% of children admitted with diarrhoea, 34% of children with pneumonia and 28% of children with SM when a strict definition of adherence was applied. Non-adherence to recommendations was most common for oxygen and antibiotics for pneumonia; fluid, zinc and antibiotics for diarrhoea; and vitamin A and zinc for SM. Non-adherence varied by site. Pneumonia guideline non-adherence was more likely among patients with severe disease (OR 1.82; 95% CI 1.38, 2.34) compared with non-severe disease. Diarrhoea guideline non-adherence was more likely among lower asset quintile groups (OR 1.16; 95% CI 1.01, 1.35), older children (OR 1.10; 95% CI 1.06, 1.13) and children presenting with wasting (OR 6.44; 95% CI 4.33, 9.57) compared with those with higher assets, younger age and not wasted.

Non-adherence to paediatric guidelines was common and associated with older age, disease severity, and comorbidities, and lower household economic status. These findings highlight opportunities to improve guidelines by adding clarity to specific recommendations.

The Modern Innovative Solutions to Improve Outcomes in Asthma, Breathlessness and Chronic Obstructive Pulmonary Disease (COPD) (MABC) service aimed to enhance disease management for chronic respiratory conditions through specialist multidisciplinary clinics, predominantly in the community. This study assesses the outcomes of these clinics.

This study used a prospective, longitudinal, participatory action research approach.

The study was conducted in primary care practices across Hampshire, UK.

Adults aged 16 years and above with poorly controlled asthma or COPD, as well as those with undifferentiated breathlessness not under specialist care, were included.

Participants received care through the multidisciplinary, specialist-led MABC clinics.

Primary outcomes included disease activity, quality of life and healthcare utilisation. Secondary outcomes encompassed clinic attendance, diagnostic changes, patient activation, participant and healthcare professional experiences and cost-effectiveness.

A total of 441 participants from 11 general practitioner practices were recruited. Ninety-six per cent of participants would recommend MABC clinics. MABC assessments led to diagnosis changes for 64 (17%) participants with asthma and COPD and treatment adjustments for 252 participants (57%). Exacerbations decreased significantly from 236 to 30 after attending the clinics (p

Specialist-supported multidisciplinary teams in MABC clinics improved diagnosis accuracy and adherence to guidelines. High patient satisfaction, disease control improvements and reduced exacerbations resulted in decreased unscheduled healthcare use and cost savings.

NCT03096509.

Current treatment decision-making in high-grade soft-tissue sarcoma (STS) care is not informed by individualised risks for different treatment options and patients’ preferences. Risk prediction tools may provide patients and professionals insight in personalised risks and benefits for different treatment options and thereby potentially increase patients’ knowledge and reduce decisional conflict. The VALUE-PERSARC study aims to assess the (cost-)effectiveness of a personalised risk assessment tool (PERSARC) to increase patients’ knowledge about risks and benefits of treatment options and to reduce decisional conflict in comparison with usual care in high-grade extremity STS patients.

The VALUE-PERSARC study is a parallel cluster randomised control trial that aims to include at least 120 primarily diagnosed high-grade extremity STS patients in 6 Dutch hospitals. Eligible patients (≥18 years) are those without a treatment plan and treated with curative intent. Patients with sarcoma subtypes or treatment options not mentioned in PERSARC are unable to participate. Hospitals will be randomised between usual care (control) or care with the use of PERSARC (intervention). In the intervention condition, PERSARC will be used by STS professionals in multidisciplinary tumour boards to guide treatment advice and in patient consultations, where the oncological/orthopaedic surgeon informs the patient about his/her diagnosis and discusses benefits and harms of all relevant treatment options. The primary outcomes are patients’ knowledge about risks and benefits of treatment options and decisional conflict (Decisional Conflict Scale) 1 week after the treatment decision has been made. Secondary outcomes will be evaluated using questionnaires, 1 week and 3, 6 and 12 months after the treatment decision. Data will be analysed following an intention-to-treat approach using a linear mixed model and taking into account clustering of patients within hospitals.

The Medical Ethical Committee Leiden-Den Haag-Delft (METC-LDD) approved this protocol (NL76563.058.21). The results of this study will be reported in a peer-review journal.

NL9160, NCT05741944.