Vascular access for the infusion of medications and solutions requires timely assessment, planning, insertion, and assessment. traditional vascular access is reactive, painful, and ineffective, often resulting in the exhaustion of peripheral veins prior to consideration of other access options. Evidence suggests clinical pathways improve outcomes by reducing variations and establishing processes to assess and coordinate care, minimizing fragmentation and cost. Implementation of a vascular access clinical pathway leads to the intentional selection of the best vascular access device for the patient specific to the individual diagnosis, treatment plan, current medical condition, and the patient's vessel health (1). the Vessel Health and Preservation (VHP) programme incorporates evidence-based practices focused on timely, intentional proactive device selection implemented within 24 hours of admission into any acute facility. VHP is an all-inclusive clinical pathway, guiding clinicians from device selection through patient discharge, including daily assessment. Initiation of the VHP programme within a facility provides a systematic pathway to improve vascular access selection and patient care, allowing for the reduction of variations and roadblocks in care while increasing positive patient outcomes and satisfaction. Patient safety and preservation of vessel health is the ultimate goal.

Frontline medical care providers, led by process design specialists, can successfully redesign episodic processes to consistently deliver evidence-based medicine, which may improve patient outcomes and reduce resource use.

A provider-driven pay-for-performance process for CABG, enabled by an electronic health record system, can reliably deliver evidence-based care, fundamentally alter reimbursement incentives, and may ultimately improve outcomes and reduce resource use.

The free lateral arm flap is a very reliable option for defect coverage at the forearm and hand for small and medium size defects. A satisfactory aesthetic appearance, an excellent tissue quality, and frequent primary donor site closure are great advantages for selecting this flap.

Purpose While more advanced COVID-19 necessitates medical interventions and hospitalization, patients with mild COVID-19 do not require this. Identifying patients at risk of progressing to advanced COVID-19 might guide treatment decisions, particularly for better prioritizing patients in need for hospitalization. Methods We developed a machine learning-based predictor for deriving a clinical score identifying patients with asymptomatic/mild COVID-19 at risk of progressing to advanced COVID-19. Clinical data from SARS-CoV-2 positive patients from the multicenter Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS) were used for discovery (2020-03-16 to 2020-07-14) and validation (data from 2020-07-15 to 2021-02-16). Results The LEOSS dataset contains 473 baseline patient parameters measured at the first patient contact. After training the predictor model on a training dataset comprising 1233 patients, 20 of the 473 parameters were selected for the predictor model. From the predictor model, we delineated a composite predictive score (SACOV-19, Score for the prediction of an Advanced stage of COVID-19) with eleven variables. In the validation cohort (n = 2264 patients), we observed good prediction performance with an area under the curve (AUC) of 0.73 ± 0.01. Besides temperature, age, body mass index and smoking habit, variables indicating pulmonary involvement (respiration rate, oxygen saturation, dyspnea), inflammation (CRP, LDH, lymphocyte counts), and acute kidney injury at diagnosis were identified. For better interpretability, the predictor was translated into a web interface. Conclusion We present a machine learning-based predictor model and a clinical score for identifying patients at risk of developing advanced COVID-19.