Patients and oncology are the primary users of the developed workflow. “Developing plan for patient schedule” is the identified opportunities for the process enhancement (Marcilly, 2019). The significance of scheduling is to help the navigator understand the period of accessing patients’ details. At the same time, staffing selection is a significant feature in process improvement since it permits the navigator to select critical stakeholders who will support him in executing the oncological functions.
The opportunities addressed by the future state workflow include it offers navigators a framework to enable them to execute their tasks suitably. Further, the future state workflow simplifies and summarizes the oncology program process (CARLSSON & MELANDER, 2021). The future workflow can be integrated with the information technology to offer navigator evidence-based solutions.
The future state workflow reduces the number of steps and optimizes electronic documentation. The documentation process can be enhanced by establishing a standardized process of future state workflow. Therefore, the optimization process needs to be effective and discover approaches for enhancement (Fridsma, 2019). Another consideration of future state workflow is that they should be developed by ensuring that there are minimal regulatory changes that can interfere or hinder the process. The expectation is that workflow will process an enormous amount of data, enhancing the effectiveness of post-operation care, medical propositions, and oncological process. Lastly, the step has been minimized, and the most significant steps have been retained.
The effect of future state workflow is that it will influence patient care on a large scale. For example, future state workflow will enhance communication between different stakeholders, patient care, and billing (Hauth et al., 2019). At the same time, clinical and practice management needs will also increase. The future state workflow will ease patient documentation and tracking since it is electronically oriented.
The future workflow can be modified according to users’ requirements. The user of future state workflow are oncology navigators; this implies that they can convert the paperwork into an electronic document. The future state workflow will provide guidelines when the oncology navigator is conducting diagnosis (Parimbelli et al., 2018). At the same time, future state workflow allows the navigator to access the referral information of the patient after performing diagnosis. Furthermore, the navigator will utilize the workflow to review features such as the most appropriate specialist, screening information, and insurance firm before the patient visit any specialist.
The future state workflow can be improved using the following plan. First, the workflow should be evaluated and make sure that all the processes are working. The first step aims to assess the functionality of the workflow processes and pinpoint the possible errors within the specific process. Secondly, the significant areas of emphasis should be transformed to eliminate potential loopholes in the future state workflow. The next step is the breakdown of the future state workflow process and make sure that they are viable and smaller stages. Breaking this process into a smaller and viable process will ensure that the stages are discrete and personalized toward the anticipated outcome. Lastly, every detail should be electronically documented to enhance efficiency (Voss et al., 2017).
CARLSSON, F., & MELANDER, G. (2021). Risk and Vulnerability Analysis Management for Increased Crisis Preparedness and Resilience: A Qualitative Case Study on the Importance of a Systematized Workflow within the Swedish Healthcare.
Fridsma, D. B. (2019). Strengthening our profession by defining clinical and health informatics practice. Journal of the American Medical Informatics Association, 26(7), 585-585.
Hauth, F., Bizu, V., App, R., Lautenbacher, H., Tenev, A., Bitzer, M., … & Gani, C. (2019). Electronic patient-reported outcome measures in radiation oncology: initial experience after workflow implementation. JMIR mHealth and uHealth, 7(7), e12345.
Marcilly, R. (2019). Exploring mHealths Fit to Workflow in Homecare–A Case Study in Sweden. Context Sensitive Health Informatics: Sustainability in Dynamic Ecosystems, 265, 54.
Parimbelli, E., Wilk, S., Kingwell, S., Andreev, P., & Michalowski, W. (2018). Shared Decision-Making Ontology for a Healthcare Team Executing a Workflow, an Instantiation for Metastatic Spinal Cord Compression Management. In AMIA Annual Symposium Proceedings (Vol. 2018, p. 877). American Medical Informatics Association.
Voss, J., Garcia, J. A., Proctor, W. C., & Evans, R. T. (2017, November). Automated system health and performance benchmarking platform: high performance computing test harness with Jenkins. In Proceedings of the HPC Systems Professionals Workshop (pp. 1-8).