Allostatic load and uterine fibroids: role in pathogenesis and racial disparities.

Drug related problems (DRPs) such as medication errors and adverse drug events (ADEs), which are adverse unintended consequences of medication use, are a common and major concern among hospitalised patients [,]. ADEs represent a major contributor to morbidity and mortality, with inpatient ADE rates ranging from 2.4% to 30% [–]. A previous systematic review of nine studies comprising >4,000 admissions found that 19% of inpatients experienced an ADE, of which one-third were considered preventable []. ADEs incur considerable health care costs, resulting in approximately $3.5 billion USD expenditure annually in the United States and £2.2 billion annually in the British National Health Service [,]. Clinical pharmacists play a critical role in minimising medication-related harm by detecting, resolving and preventing DRPs through clinical and pharmacovigilance activities, such as medication reconciliation and medication review []. Inpatient clinical pharmacy services are effective in reducing DRPs, with one study estimating a saving of approximately AUD $4.5 million annually in healthcare expenditure across eight major government-funded teaching hospitals in Australia []. However, comprehensive pharmacist services cannot be provided to all hospital inpatients due to workforce shortages (e.g., high ratios of patients to pharmacists), finite healthcare budgets, and increasing number and acuity of hospital admissions [,]. As a result, pharmacists must explicitly prioritise which patients receive medication reviews and other clinical pharmacy services. One study conducted in the UK reported that clinical pharmacists spend one hour daily prioritising patients and another half an hour gathering the clinical or laboratory data necessary for reconciling patients’ medication lists []. Hence, risk-prediction tools that assist healthcare professionals in streamlining medication reconciliation and targeting medication reviews to high-risk patients are a high priority. This is in line with international guideline recommendations for maximizing the value and impact of pharmacist services [–]. Risk prediction tools use patient and medication-related factors to estimate the risk of an adverse event such as ADE [] to help identify and prioritise patients []. Directing health professionals to those most at risk can thereby reduce the risk of patient harm, improve efficiency in clinical practice, and limit avoidable hospital utilisation such as additional length of stay or readmission []. Although multiple risk prediction tools have been developed to identify patients at risk of DRPs, prior systematic reviews report that none have been implemented into routine clinical practice [,]. The growing availability of electronic medical record systems in hospitals and advances in artificial intelligence represent promising opportunities to implement automated patient prioritisation tools [,]. However, to support the development and implementation of effective digital health solutions, a comprehensive understanding of existing tools, including their performance, and commonly reported risk factors is required.