Grand Hospital faces at least three problems that need addressing through the improvement of quality of care. First, radiology skills and services are inadequate. The hospital needs highly qualified radiologists working daily around the clock. Second, there is the problem of handling psychiatric patients, which should be addressed by enhancing psychiatry staff in terms of numbers, qualifications, and credentials. A significant number of behavioral health patients present pose a threat to themselves, other patients, and staff. Third, voluntary staff members are not always present. Intensivist physician services need to be available during their absence. The three problems could be ameliorated by pursuing a telemedicine avenue.
Telemedicine entails the delivery of healthcare online, whereby essential medical information flows between health practitioners and their patients. Telemedicine is used to encourage and facilitate self-care via remote monitoring to provide consultations to patients who for various reasons are not able to physically attend appointments, as well as within hospital settings (Eze, Mateus, & Cravo, 2020). It follows that it is also possible to use telemedicine to deliver quality care to Grand Hospital, in the sense of several highly qualified medical practitioners ‘working from home’. Moreover, the fact that telemedicine is not widely used in OECD countries (Eze et al., 2020) informs its choice as a strategy.
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Telemedicine can solve Grand Hospital’s workforce problem in three ways. One, there are hospitals in which qualified health practitioners have easily manageable workloads and so may have extra time to earn more. Grand Hospital could capitalize on their availability and expertise by having them remotely deliver care to the hospital. There may also be health academicians and researchers who may be willing to apply their knowledge and expertise in real medical practice. They could provide the quality services Grand Hospital needs via telemedicine. Another source of human resources would be companies, universities, and research institutions that specialize in machine learning (ML), deep learning (DL), and Artificial Intelligence (AI). ML, DL, and AI are highly effective in the areas of radiology (Yasaka & Abe, 2018) and psychiatry (E. Lin et al., 2020). The aforementioned solutions are viable via the use of telemedicine.
That said, the electronic health information conveyed and stored to support telemedicine would need to be governed. The following steps will be employed in creating information governance. 1 The first step will require a review of policies and procedures for inputting data into patient administration electronic systems. The second step will consist of an audit to verify compliance with set standards. The third step will mandate data output audits, focusing on the quality of clinical coding. Before full implementation of the third step, the informational governance initiative will incorporate standards regarding data management, security, and privacy and confidentiality issues.
The success of telemedicine implementation in Grand Hospital will require the assignment of responsibilities to key players. The hospital’s management will be responsible for availing the necessary resources and putting in place the roadmap for the initiation and implementation of telemedicine. That will later include finding workforce sources and keeping them working. The hospital's IT department will be responsible for putting in place the necessary communication infrastructure needed for telemedicine to operate smoothly. Their role will also include implementing the necessary security procedures to ensure patient privacy and confidentiality, as well as prevent sabotage of healthcare delivery over the network. Patients will provide the necessary information for healthcare providers to deliver care via telemedicine.
References
Emmanuel, T., Dall'Ora, C., Ewings, S., & Griffiths, P. (2020). Are long shifts, overtime and
staffing levels associated with nurses’ opportunity for educational activities, communication and continuity of care assignments? A cross-sectional study. International Journal of Nursing Studies Advances , 100002.
Eze, N. D., Mateus, C., & Cravo, O. H. T. (2020). Telemedicine in the OECD: An umbrella
review of clinical and cost-effectiveness, patient experience and implementation. PLoS ONE , 15 (8), 1–24. https://doi.org/10.1371/journal.pone.0237585
Lin, E., Lin, C.-H., & Lane, H.-Y. (2020). Precision Psychiatry Applications with
Pharmacogenomics: Artificial Intelligence and Machine Learning Approaches. International Journal of Molecular Sciences , 21 (3), 969. https://doi.org/10.3390/ijms21030969
Yasaka, K., & Abe, O. (2018). Deep learning and artificial intelligence in radiology: Current
applications and future directions. PLoS Medicine , 15 (11), 1–4. https://doi.org/10.1371/journal.pmed.1002707
1 Informed by Huston, J. L. (2005). Information governance standards for managing e-health information. Journal of
telemedicine and telecare , 11 (2_suppl), 56-58.
