Preeclampsia is a frequent syndrome and its cause has been linked to multiple factors, making prevention of the syndrome a continuous challenge. One of the suggested risk factors for preeclampsia is advanced maternal age. In the Western countries, maternal age at first delivery has been steadily increasing, yet few studies have examined women of advanced maternal age with preeclampsia. The purpose of this registry-based study was to compare the obstetric outcomes in primiparous and preeclamptic women younger and older than 35 years.

The relationship between nurses’ job satisfaction and their perceptions of quality of care has been examined in previous studies. There is little evidence, however, about relationships between the job satisfaction of nursing staff and quality of care perceived by the patients. The aim of this study was to analyze, how the job satisfaction of nursing staff, organizational characteristics (hospital and unit type), and patients’ age relate to patients’ perceptions of the quality of care.

In this paper, we focus on providing a narrative review of healthcare services in which artificial intelligence (AI) based services are used as part of the operations and analyze key elements to create successful AI-based services for healthcare. The benefits of AI in healthcare are measured by how AI is improving the healthcare outcomes, help caregivers in work, and reducing healthcare costs. AI market in healthcare sector have also a high market potential with 28% global compound annual growth rate. This paper will collect outcomes from multiple perspectives of healthcare sector including financial, health improvement, and care outcome as well as provide proposals and key factors for successful implementation of AI methods in healthcare. It is shown in this paper that AI implementation in healthcare can provide cost reduction and same time provide better health outcome for all.

Medication administration errors may contribute to patient mortality, thus additional understanding of such incidents is required. To analyse medication administration errors reported in acute care resulting in death, to identify the drugs concerned, and to describe medication administration error characteristics (location of error, error type, patient's age) by drug group. Medication administration errors reported in acute care in 2007 ̶ 2016 (n = 517,384) were obtained from the National Reporting and Learning System for England and Wales. Incidents reported as resulting in death (n = 229) were analysed. Drugs were classified by two researchers using the British National Formulary. Drug categories were described by medication administration errors' year, location, patient age, and error category based on the incidents' original classification. Errors were most often reported on wards (66.4%, n = 152), and in patients aged over 75 years (41.5%, n = 95). The most common error category was omitted medicine or ingredient (31.4%, n = 72); most common drug groups were cardiovascular (20.1%, n = 46) and nervous system (10.0%, n = 23). Most errors in patients under 12 years concerned drugs to treat infection; cardiovascular drugs were most common among other age groups. In order to prevent these most serious of medication administration errors, interventions should focus on avoiding dose omissions, and administration of drugs for patients over 75 years old, as well as safe administration of parenteral anticoagulants and antibacterial drugs.