Introduction:Moral sensitivity is one criterion for competent professional ethics. This sensitivity can be reinforced by specific educational practices. The purpose of this study was to investigate the impact of professional ethics-based education on the ethical sensitivity of health information technology students. Method:This quasi-experimental pre-post study was conducted in 2022 with 49 students. A researcher-created questionnaire based on Lutzen was used for data collection. Data were analyzed using descriptive statistics and paired t-tests. Findings:Students' moral sensitivity score was 7.4 ± 0.7 before and 7.6 ± 0.8 after, a significant increase in post scores (P=0.031). The moral sensitivity score of students who had not previously received professional ethics training was statistically significantly increased by case-based learning. Results:The professional ethics-based teaching method was effective in increasing the moral sensitivity of health information technology students, so it is recommended to use this method of teaching medical ethics courses.
Bexar Data Dive, an online data platform, was created to increase accessibility and use of health and social determinants of health data, such as education, economic barriers to healthcare, and hospitalization rates, to decrease racial/ethnic health disparities throughout Bexar County. A model of user-centered design helped us incorporate community input into the platform. We conducted four interviews and five focus groups to gather information on how people use data - specifically beginner and intermediate-level data users from various educational, governmental, and nonprofit organizations. Then, we launched a community survey to assess specific data needs. Lastly, once the alpha version of Bexar Data Dive was ready, we conducted user testing sessions to measure usability, identify bugs, and gather final feedback before launch. Our findings included many recommendations for incorporating user-centered design in health data management. Participants wanted a health data tool that was easy to use, had the indicators they commonly need, and would provide visualizations for presentations, grants, and other projects.
This systematic literature review seeks to collate the evidence of the evolution of the role of healthcare information systems (HIS) executive in the United States (US) and to identify the significant events which have influenced the development of this role and its impact on the transformation of healthcare organizations. The HIS executive has evolved over time from the manager responsible for in-house computers, advanced data processing (ADP), communication systems, and system conversions to a participatory member of the executive leadership team responsible for delivering technology solutions which transform the delivery of healthcare. The changes in the responsibilities and the attributes of HIS executives have been driven by changes in technology, standardization of clinical data, government regulation, and the ever-changing reimbursement and business environment. The responsibilities and titles of the HIS executive will evolve and adapt as the business environment and the expectations of consumers and payers change.
Purpose:The study purpose was to describe the availability of sex, gender identity, and sexual orientation (SOGI) data in a large, Catholic health system. Methods:A retrospective chart review on the Sisters of St. Mary (SSM) Health database was conducted from January 1, 2012, to March 27, 2024. The availability of SOGI data and number of sexual and gender minority patients was reported. Results:Among the 5,759,869 records, data on sex was available for the majority of the population (99.9 percent); data on gender identity and sexual orientation were reported for smaller proportions (7.4 percent and 4.5 percent, respectively). Sex and gender were reported among 7.4 percent of the population. A total of 4,567 gender minority and 14,644 sexual minority patients were seen. Conclusion:Though SOGI data were largely unavailable in the SSM Health database, the system has the capacity to separately record sex, gender, and sexual orientation, with a range of response options to capture gender and sexual orientation diversity.
Clinicians dedicate significant time to clinical documentation, incurring opportunity cost. Artificial Intelligence (AI) tools promise to improve documentation quality and efficiency. This systematic review overviews peer-reviewed AI tools to understand how AI may reduce opportunity cost. PubMed, Embase, Scopus, and Web of Science databases were queried for original, English language research studies published during or before July 2024 that report a new development, application, and validation of an AI tool for improving clinical documentation. 129 studies were extracted from 673 candidate studies. AI tools improve documentation by structuring data, annotating notes, evaluating quality, identifying trends, and detecting errors. Other AI-enabled tools assist clinicians in real-time during office visits, but moderate accuracy precludes broad implementation. While a highly accurate end-to-end AI documentation assistant is not currently reported in peer-reviewed literature, existing techniques such as structuring data offer targeted improvements to clinical documentation workflows.
