Of critical concern to hospitals today is the prevention of postoperative (surgical site) infections that often result in increased lengths of stays for patients, increased resource demands and costs, loss of public trust and lawsuits, and needless pain and suffering for patients and their families. While all surgical patients have the potential to develop a postoperative infection, the main challenge is to identify key risk factors (both patient centered and operational) through an electronic early-warning system to reduce the likelihood of a postoperative infection from occurring. Currently, most postoperative infection risk prevention practices encompass limited use of informatics technologies or do not maximize the potential benefits. In addition, from a research perspective, there has been more focus on extrapolating electronically housed data (eg, from progress notes, operative notes, laboratory, pharmacy, radiology) retrospectively to describe poor patient outcomes for benchmarking purposes (revealing poor results and opportunities for improvement) rather than using similar sources of real-time data to prevent poor patient outcomes from occurring. This article proposes that standardized indicators, both patient centered and operational, linked to the patient's electronic health record could allow for implementation of 24/7, "real-time" monitoring/surveillance to implement well-timed preventive interventions scaled to each patient and facility to assist caregivers in reducing the numbers of postoperative infections and improve the overall quality and costs of patient care.

Objective Socioeconomic status (SES) influences disease outcomes in rheumatoid arthritis (RA) patients. Differences in medication use may partly explain this association. A scoping review was used to identify research conducted on this topic and determine what knowledge gaps remain. Methods Medline, Embase, and PsychInfo were searched from their inception until February 2022 for studies that assessed SES and medication use as an outcome variable. Data was extracted on the use of specific SES measures, medication use, and whether differences in SES variables were associated with differences in medication use. Results We identified 2,103 studies, of which 81 were selected for inclusion. Included studies originated most frequently from the US (42%); the mean ± SD age of participants was 55.9 ± 6.8 years, and most were female (75%). Studies measured a median of 4 SES variables (interquartile range 3–6), with educational, area‐level SES, and income being the most frequent measurements used. Patients' race and/or ethnicity were documented by 34 studies. Studies primarily assessed the likelihood of prescription of disease‐modifying antirheumatic drugs or dispensation, medication adherence, or treatment delays. A majority of studies documented at least 1 SES measure associated with a difference in medication use. Conclusion There is some evidence that SES affects use of medications in patients with RA; however, multiple definitions of SES have been utilized, making comparisons between studies difficult. Prospective studies with consistently defined SES will be needed to determine whether differences in medication use accounts for the poorer outcomes experienced by patients of lower SES.

No abstract

No abstract