Business Case for Hospital Chatbots
Business Case for a New Economic Opportunity
Athena Healthcare center is located in Iowa. It provides healthcare services for patients looking for affordable, quality care. The institution also provides supportive and practical holistic care for the patients that have been pre-diagnosed with various illnesses and those who need healthcare support.
Developing chatbots for this hospital will motivate the nurses, who are often overwhelmed by the many patients who visit the institution (Buchanan et al., 2020). The business care aims to present a report detailing how developing chatbots can affect the hospital for the next five years and the cost-benefit analysis.
It also focuses on the business evaluation through the risk and opportunity assessment to introduce the new project. The project will also provide ways to reduce risks through setting various maximize profits and minimizing costs simultaneously.
Opportunities Associated With the Proposed Economic Initiative
Chatbots are being applied in various fields, including healthcare and medicine, for human-like knowledge transfer and communication. Machine learning is a subset of artificial intelligence that has been proven helpful in healthcare and can develop complex dialog management and conversational flexibility (Buchanan et al., 2020).
Artificial intelligence is at the forefront of transforming various aspects of our lives by modifying how healthcare organizations’ information is analyzed and improving decision-making through reasoning, problem-solving, and learning. Machine learning is a subset of AI that improves its performances based on the data provided to a generic algorithm from experience rather than defining rules in traditional approaches.
Chatbots are also known as smart bots. These computer programs can hold conversations with an individual over the internet. These can also be physical entities designed to socially interact with humans and other bots (Xu et al., 2021). The predetermined responses are generated through user input on the text and accessing relevant knowledge. Problems arise when dealing with complex situations in dynamic environments and managing conversational social practices according to specific contexts and unique communication strategies.
Chatbots have been proven to be applicable to various healthcare components that often involve face-to-face interactions in the healthcare environment (Xu et al., 2021). With their ability to have complex dialog management and conversational flexibility, integration of chatbot technology into clinical practice may reduce costs, improve patient outcomes and refine workflow efficiencies.
Studies have found positive benefits of healthcare chatbots in managing one’s health for improved physical, behavioral and psychological outcomes (Rodriguez‐Arrastia et al., 2022). It can also be used for administrative purposes to reduce overcrowding in the healthcare industry. Due to the opportunities provided by this relatively new technology, potential limitations and areas of concern may arise that could potentially harm users.
Concerns regarding accuracy, lack of empathy, cybersecurity, and technology maturity are reported as potential factors linked with the delay in chatbot acceptability or integration into healthcare (Buchanan et al., 2020).
Chatbots increase the possibility of gaining patients’ trust long before visiting the facility. When patients need information about various procedures or need to book appointments, they go through it before deciding to visit the hospital (Rodriguez‐Arrastia et al., 2022). When they find chatbots, they are connected to specialists or get an appointment, and therefore, the trust level increases significantly. It reduces time wastage due to waiting in the hospital queues.
Risks Associated With the Economic Initiative and Ways to Address Them
Doctors often experience a challenge in handling patients due to the use of chatbots in the healthcare system, making it a major risk in the industry. With chatbots, even the simplest symptoms can be magnified into something serious (Cheng & Jiang, 2020). On the other hand, the bots take time to update symptoms, so older people and patients with poor internet are likely not to get accurate information or connection to relevant caregivers due to internet issues (Hauser-Ulrich et al., 2020).
With the help of the bots, patients with chronic conditions keep their conditions managed by following the recommendation of the bot; hence have zero interest in visiting the hospitals manually (Palanica et al., 2019). This, therefore, leaves nurses and doctors without anyone to attend to hence putting the facility at a loss due to insufficient money flow.
Cost-Benefit Analysis of the Proposed Economic Initiative
- Initial cost to pay the app developers
- Payment for content writers responsible for creating app content (Palanica et al., 2019)
- Payment for people responsible for debugging the chatbots (Cheng & Jiang, 2020)
- Annual service cost or system upgrade
- Provides patients with reliable information
- Minimizes workload for the health professionals (Hauser-Ulrich et al., 2020)
- Reduces to and from trips to the hospital for the patients
- Eliminates the possibilities of medical errors during diagnosis and treatment process
Ways to Control Costs and Maximize Benefit
The first priority for the hospital when developing chatbots is to ensure that the cost is under control to maximize profits (Hauser-Ulrich et al., 2020). Therefore, rather than hiring developers for the hospital to create the bots, the hospital can opt to outsource the job to developers who are qualified to handle the task. With outsourcing, the hospital will not have to keep spending money to pay the developers’ monthly salaries. This will therefore minimize expenses and guarantee that the facility spends less money as the initial investment for the chatbots.
Another way of controlling costs for the hospital is by optimizing the team. Using simple design and custom graphics are also effective ways that can be used to control costs and ensure that the hospital has functional chatbots (Palanica et al., 2019).
It is also critical for hospitals to conduct comprehensive research on the use of bots before starting the development process. This way, it will be easy for the hospital to make informed decisions on how the bot should look and what features to include to present the hospital’s real image (Cheng & Jiang, 2020).
Once the chatbots are developed and fully functional, the hospital is expected to have a regular updating plan. Updating the system regularly guarantees that maintenance costs will be minimal and the bot will remain functional throughout the seasons.
The inclusion of chatbots in the healthcare system is profitable for both the patients and the caregivers. It enhances the process of giving and receiving healthcare, allowing both the health professionals and patients to experience comfort. The initiative also guarantees that the hospital operations are transparent for all involved bodies. With this initiative, the hospitals also can minimize flow and guarantee there is sufficient room for patients in critical conditions to see physicians where necessary.
Buchanan, C., Howitt, M. L., Wilson, R., Booth, R. G., Risling, T., & Bamford, M. (2020). Predicted influences of artificial intelligence on the domains of nursing: scoping review. JMIR Nursing, 3(1), e23939. doi: 10.2196/23939
Cheng, Y., & Jiang, H. (2020). AI‐Powered mental health chatbots: Examining users’ motivations, active communicative action and engagement after mass‐shooting disasters. Journal of Contingencies and Crisis Management, 28(3), 339-354. https://doi.org/10.1111/1468-5973.12319
Hauser-Ulrich, S., Künzli, H., Meier-Peterhans, D., & Kowatsch, T. (2020). A smartphone-based health care chatbot to promote self-management of chronic pain (SELMA): pilot randomized controlled trial. JMIR mHealth and uHealth, 8(4), e15806. https://preprints.jmir.org/preprint/15806
Palanica, A., Flaschner, P., Thommandram, A., Li, M., & Fossat, Y. (2019). Physicians’ perceptions of chatbots in health care: cross-sectional web-based survey. Journal of Medical Internet Research, 21(4), e12887. https://preprints.jmir.org/preprint/12887
Rodriguez‐Arrastia, M., Martinez‐Ortigosa, A., Ruiz‐Gonzalez, C., Ropero‐Padilla, C., Roman, P., & Sanchez‐Labraca, N. (2022). Experiences and perceptions of final‐year nursing students of using a chatbot in a simulated emergency situation: A qualitative study. Journal of Nursing Management. DOI:10.1111/jonm.13630
Xu, L., Sanders, L., Li, K., & Chow, J. C. (2021). Chatbot for Health Care and Oncology Applications Using Artificial Intelligence and Machine Learning: Systematic Review. JMIR Cancer, 7(4), e27850. doi: 10.2196/27850