March 09 ~ 10, 2024, Virtual Conference
Omosalewa Itauma1, 2 and Itauma Itauma3, 1Department of Obstetrics & Gynecology, Wayne State University School of Medicine, Michigan, USA, 2Department of Obstetrics & Gynecology, Central Michigan University College of Medicine, Michigan, USA, 3DeVos Graduate School of Management, Northwood University, Michigan, USA
The increasing demand on healthcare systems has amplified the burden on physicians and other healthcare practitioners, with a huge portion of time dedicated to documenting patient encounters. Prolonged charting periods not only contribute to decreased physician productivity but also emerge as a prominent factor in physician burnout. This study investigates the potential of Artificial Intelli gence (AI) to mitigate this challenge, focusing on AI-powered medical scribing as a solution to alleviate the burden o f traditional charting methods in documentation of patient encounters and improve overall physician productivity. This research contributes to the ongoing discourse on the role of AI in healthcare and seeks to inform healthcare practitioners, administrators, and policymakers about the potential benefits of integrating AI-powered medical scribing to improve physician efficiency and mitigate the impact of extensive charting on overall productivity and well-being.
Physician Productivity, Artificial Intelligence (AI) scribes, Electronic Health Records, Charting, Physician Burnout.
Hashimi Mohammad Badar, Al-khshbi Arafat Hussein, Brechard Raphael, Petragallo Samuel, Fuhrer Caroline
Health Resources and Services Availability Monitoring System (HeRAMS) is a system that maintains up-to-date master health facility list, assigns and maintains unique ID for each health facility, offers APIs for integration with other information systems, provides information on functionality and accessibility of health facility, and provides information on availability of essential health services and impediments for partial or not availability [2][4]. This paper explores the potentials and opportunities that come with HeRAMS for interoperability of health information systems and health system development in emergency and development settings. This study also proposes a conceptual framework for enhancing the integration and interoperability of HeRAMS with other health information systems and an approach for integration of external systems together by leveraging HeRAMS as a mediator. The paper concludes with a recommendation of the next steps to be taken.
HeRAMS, Interoperability, digital health, health information management, systems integration.
Joshua Hopkins and Datonye B. Omunguye-George, Northwood University, Midland, MI, USA
The purpose of this paper is to highlight the current technological developments in diagnostic cardiovascular care. Echocardiography, a widely known imaging tool is used to extract insights about a patients’ cardiac anatomy and perform necessary treatments or procedures based on their diagnoses. AI models are fed with huge amounts of raw cardiac data and use deep learning algorithms to identify images with remarkable speed and accuracy. AI applications in computer vision offer key benefits in the healthcare industry. Companies such as Siemens are the key players – the commercialization of new AI technology has enabled healthcare organizations to streamline workflows, reduce errors, and lower costs. Potentially, there will be no reproducibility issues thereby redirecting clinical efforts towards patient treatment planning and research to prevent uptrends of heart disease.
Echocardiography, Convolutional Neural Networks, Artificial Intelligence, Medical Imaging, Patient monitoring, Clinical Analysis.
Bagyendera Moses1, Nabende Peter1, Godman Brian2, 3, Nabukenya Josephine1, 1Department of Information Systems, Makerere University, Kampala PO Box 7062, Uganda, 2Strathclyde Institute of Pharmacy and Biomedical Sciences, Strathclyde University, Glasgow G4 0RE, UK, 3School of Pharmacy, Sefako Makgatho Health Sciences University, Ga-Rankuwa, Pretoria 0208, South Africa
In Uganda, the deficiency in syntactic interoperability standards for Health Information Exchange (HIE) hampers the exchange of healthcare information, limiting equitable access to quality health data and services. Addressing this gap, we adopted a three-phase study approach using HIV and TB programs as case studies. Key informant interviews with electronic health information experts revealed challenges like limited standardization guidelines, insufficient capacity, and data safety concerns. A framework supporting syntactic interoperability data standards was developed, gaining 94% approval from participants. The framework encompassed all stakeholders involved in data standards development according to 68% of respondents. Additionally, 88% agreed that the framework facilitated the development of clear, well-defined, and precise standards systematically. The derived syntactic interoperability data standards, while endorsed by 96% of respondents, must consider changing selection criteria over time. Implementing these standards promises improved service delivery, enhanced quality, equity, outcomes, and safety of patients in Uganda, crucial objectives given the substantial burden of infectious and non-communicable diseases.
Data use, eHealth, Electronic Health Records, Syntactic Interoperability standards, Hospitals.