Executive summary
Four months ago, a hospital approached us inquiring whether we would be capable as TechSoft Company creates software that would help them achieve more with less effort. In a hospital setting, a lot of paperwork requires doctors, nurses, and other personnel to work even more than they are supposed to. The extra time that they spend on paperwork could be utilized in matters concerning the patients. This is the main reason that the hospital, through its manager, approached us.
Our company is focused on providing software solutions to different issues in various sectors. In the case of this hospital, we set to advise on creating a system that will help store, verify, and help in the diagnosis of patients based on the information fed into it. The hospital needed a software system guided by the concept of artificial intelligence and machine learning to help reduce the workload for the doctors who had been noticed to suffer from the negative effects of burnout.
After establishing a plan and understanding how many developers are needed to complete this project, the hospital received a budget for the project and the amount they are supposed to pay upfront and after completion. The project took two months and two weeks to complete. The initial plan anticipated that it would take two months, but it took two more weeks because we opted for the agile method. The agile approach was preferred because the development had to work closely with the hospital to understand and integrate different requirements until the final product suited its needs.
Introduction
Four months ago, a hospital approached us inquiring whether we would be capable as TechSoft Company creates software that would help them achieve more with less effort. In a hospital setting, a lot of paperwork requires doctors, nurses, and other personnel to work even more than they are supposed to. The extra time they spend on paperwork could be utilized in patient matters. This is the main reason the hospital approached us through its manager. Our company is focused on providing software solutions to different issues in various sectors. In the case of this hospital, we set to advise on creating a system that will help store, verify, and help in the diagnosis of patients based on the information fed into it. The hospital needed a software system guided by the concept of artificial intelligence and machine learning to help reduce the workload for the doctors who had been noticed to suffer from the negative effects of burnout. The system would be able to carry out routine tasks for the hospital. For instance, when a patient is admitted to a hospital for the first time, their information has to be recorded and stored for future reference. Sometimes, due to fatigue and exhaustion, the individuals recording this information make a mistake, making it hard for a doctor to retrieve it.
The artificial intelligence technology guiding the system offers a range of possibilities in the healthcare industry that had not been seen before. For instance, apart from just storing information of patients, the system can receive information about the signs and symptoms of the patients and suggest a diagnosis. The field of artificial intelligence explores the capabilities of a machine and how it can act like a human being. For instance, a machine is taught to think and reason like people. This means that in the same way a doctor notices certain symptoms in an individual and recommends a path for them to follow, whether testing or a particular drug, it is the same way the system does. This paper evaluates a current management information system and directs on ways to improve it using artificial intelligence and machine learning.
Analysis
Analysis of Current MIS
The new system is set to perform incredibly and even allow the doctors and other healthcare providers in the hospital to offer better care to patients. This is largely due to the technologies that guide the performance of this system, artificial intelligence and machine learning. By integrating these key technologies, we can recreate the reality that most individuals are used to. Computers and algorithms can handle large chunks of data faster and more precisely than the best human at their work. The technologies can also study and reveal patterns and predict the next event that can be the key to the diagnosis as well as treatment of patients.
According to the incredible influence enhancement to the medical industry, many individuals’ lives will be saved, and a lot of money will be saved, which is usually wasted after the wrong diagnosis. Machine learning methods get better the more data they get exposed to. The medical industry is full of data, and this is great considering what machine learning requires. Because of various storage systems, privacy and ownership issues, and lack of elaborate procedure that enables individuals to relay information quickly, a significant amount of assessment is not presently being conducted that would garner massive outcomes for doctors and their patients and hospitals.
Much of the artificial intelligence work conducted to this point in the medical field is aimed at identifying plus diagnosing illnesses. Utilizing the technology to assess DNA to diagnose conditions to smartphone applications that can establish a concussion plus gauge other issues, like lung function, disease, and wellness observation, is a priority of machine learning explorations. Because heart condition is the number one killer of people worldwide, it is not a shock that initiative plus focus from numerous artificial intelligence developers concerns heart condition analysis plus prevention. Presently, the procedure for checking a person’s risk factor for a certain condition is by checking at the risk factors advised by top medical experts, including blood pressure, and age, among others.
Nevertheless, this is a simple approach and does not consider medications someone might already be consuming. The well-being of a patient’s other biological systems, plus other factors, could raise the chances of heart illness. For example, numerous study teams from two top universities are working closely to improve machine learning algorithms that can forecast an individual in greater danger and when in danger of heart attack. Initial findings of the artificial intelligence algorithms were primarily better at forecasting heart illnesses than experts in the field.
This shows the power of the two technologies and shows optimism in the healthcare sector and especially this hospital that will be able to offer better treatment to their patients. In the past, doctors were the ones who directed CT scans and even read and interpreted the results. The new system can learn how to read the scans and suggest a diagnosis for a patient. This gives a physician enough time to concentrate on the right treatment options.
After the project finished and the final product was launched, it was proper for the team to conduct testing on numerous patients with different conditions. On the other hand, for every task that was given to the system, a substitute healthcare provider had to carry out to test whether the system was more accurate than the human or not. To be fair to the client, that is the hospital, and we requested that they provide the best professionals in every area of medicine. For instance, while testing how the system learns to read and interpret scan results, the hospital had to provide the best physician who is much experienced. After a series of tests, it was discovered that the system had a success rate of 99%, while the human expert had a success rate of 90%. Looking at the difference, it shows that the patients will benefit a lot once the system is fully incorporated into the operations of the hospital.
There are times that a system can fail because it is fed with wrong information as it is used to a certain kind of information. The hospital needed to see whether the system was able to identify the information that was wrong and suggest the right alternatives. With this, various patients with different conditions with signs and symptoms similar to other conditions were used as participants. The system was fed with information on their conditions and indicators. The system, in this case, showed a success of 98%. The majority of the time, the system was able to identify a flaw in the information and suggest alternatives. The system satisfied the hospital management concerning their needs. Also, apart from performing diagnosis tasks, the system can do away with paper documents.
In many organizations, companies are still utilizing paper documents to store information that is crucial in their operations, not only in the healthcare sector. The problem with this is that the paper documents can get lost, which can cause much damage to the organizations. For instance, it is easy in the case of a fire accident for paper documents to be destroyed. Organizations are required to evaluate their operations after every year. Financial statements and reports are important to the running of an organization, and they ensure that proper planning is done to create more opportunities for an organization to develop. In case such documents get destroyed, it is hard for the organization’s management to conduct planning for the organization’s future. In the case of a healthcare organization, this could prove very disastrous and could to many patients to suffer more since their medical history is not easily accessible.
The system will allow the hospital to easily back up data concerning organizational operations and enable easy and faster access. With paper documents and the number of patients visiting the hospital increasing, the number of paper documents storing information is a lot. If the history on a certain patient is in need, it becomes hard for the personnel in charge to retrieve the information. With the system, the patient’s medical history data is one click away, which makes it convenient. The project is huge and successful based on the requirements of the client. The number of individuals required and committed to the project’s development was huge and offered a blueprint for how future projects need to be carried out.
The agile approach was selected because the development team had to work hand in hand with the client to understand and incorporate different requirements until the final product suited their needs. Agile methodology is based on repetitive development whereby requirements plus solutions change via cooperation amongst self-organizing cross-functional groups. The eventual value of this approach is that it allows development teams to deliver value quicker, with better quality as well as predictability and more propensities to respond to change. The approach generally promotes a disciplined project management procedure that encourages usual examination as well as adaptation. It also emphasizes a leadership perspective that promotes teamwork, culpability, and self-drive. It is responsible for a collection of practices to allow quick delivery of the best quality software and a business strategy that aligns development with client needs.
Recommendations for Improvements
Looking at the previous system that the client used in their operations, many issues were conducted manually and this posed a great risk for the client and their customers. It is possible for a human to make mistakes, especially when they feel like they have done a lot of work and are exhausted. By integrating these key technologies, we can recreate the reality that most individuals are used to. Computers and algorithms can handle large chunks of data with more speed and precision than the best human at their work. The technologies can also study and reveal patterns and predict the next event that can be the key to the diagnosis as well as treatment of patients.
According to the incredible influence enhancement to the medical industry, many individuals’ lives will be saved, and a lot of money will be saved, which is usually wasted after the wrong diagnosis. Machine learning methods get better the more data they get exposed to. The medical industry is full of data, and this is great considering what machine learning requires. Because of various storage systems, privacy and ownership issues, and lack of elaborate procedure that enables individuals to relay information quickly, a significant amount of assessment is not presently being conducted that would garner massive outcomes for doctors and their patients and hospitals.
Much of the artificial intelligence work conducted to this point in the medical field is aimed at identifying plus diagnosing illnesses. Utilizing the technology to assess DNA to diagnose conditions to smartphone applications that can establish a concussion plus gauge other issues, like lung function, disease, and wellness observation, is a priority of machine learning explorations. Because heart condition is the number one killer of people worldwide, it is not a shock that initiative plus focus from numerous artificial intelligence developers concerns heart condition analysis plus prevention. Presently, the procedure for checking a person’s risk factor for a certain condition is by checking the risk factors advised by top medical experts, including blood pressure, and age, among others.
Nevertheless, this is a simple approach and does not consider medications someone might already be consuming. The well-being of a patient’s other biological systems, plus other factors, could raise the chances of heart illness. For example, numerous study teams from two top universities are working closely to improve machine learning algorithms that can forecast an individual in greater danger and when in danger of heart attack. Initial findings of the artificial intelligence algorithms were primarily better at forecasting heart illnesses than experts in the field.
This shows the power of the two technologies and shows optimism in the healthcare sector and especially this hospital that will be able to offer better treatment to their patients. In the past, doctors were the ones who directed CT scans and even read and interpreted the results. The new system can learn how to read the scans and suggest a diagnosis for a patient. This gives a physician enough time to concentrate on the right treatment options.
It is, therefore, important to improve the existing system with the integration of artificial intelligence and machine learning.
To complete a project, a team needs a realistic plan and considers various issues that may arise. For instance, in the case of this project, the project team had to consider time flexibility because of the possibility of changing the client’s requirements (Eriksson et al., 2017). Creating a project plan that fails to consider that the client can change needs is the first step in failing. The plan must leave room for such events. Another approach is allowing the team to identify the goals and objectives of the system and understand what the client desires. In an organization, whether small or big, the most important thing is to ensure that every individual who is part of the system is on the same page.
This means that everyone knows what the target is and is committed to. For instance, the main aim of this project was to create a system that would lift the extra burden placed on healthcare providers at the hospital. The end product was supposed to act as an assistant to doctors, nurses, and other personnel. Every team member’s understanding is great and ensures that the development work happens seamlessly (Eriksson et al., 2017). Apart from everyone on the team understanding the goal, the most underrated thing in project management is the spirit of togetherness.
Top organizations have an edge over others because they understand the importance of everyone getting along well. A toxic environment full of unresolved conflicts does not promote growth, and when individuals are working on the same project and do not understand one another, it becomes hard to achieve set goals. It was important before starting that we recognize and solve any disputes among team members (Eriksson et al., 2017). During the project development, if a conflict arose between any members, the issue would be dealt with, and the involved would be allowed to come to terms with one another.
Project management is very important, and there are certain aspects to take care of if one desires to be sought out by clients for big projects. A project must meet the client’s requirements and be delivered on time (Eriksson et al., 2017). Clients are specific on time, and in the case of this project, the hospital needed a solution to their problem of doctors burning out and giving a less accurate performance. To achieve this, there are certain approaches the project team had to follow. For instance, the whole team needed to be on the same page regarding the goals and objectives of the project. Understanding the reason behind the project ensures that the work is done with ease and everyone is moving at the same pace. Apart from that, the team had to develop a spirit of togetherness. It was realized that to complete a huge project; all conflict issues had to be resolved before the commencement of the project. This was done to eliminate the stagnation during the project because members of the project team could not get along well.
Conclusions
In the paper, it is evident that the project was successful and met the client’s performance needs. The world is transitioning from organizations that rely on paper to organizations that are going paperless. It is important to keep up with the new technology trends to ensure that work is more efficient and accurate. Human beings are prone to fatigue and can often make mistakes that can cost organizations a lot of money and lead to harm to another person. For instance, if an auditor in an organization makes a mistake on a company’s financial statements, the organization might lose a lot of money. Whereas if a wrong diagnosis is given by a doctor, a patient might lose their life. Having systems that can help professionals in their work is important and can lead to better results.
For instance, it is designed with the capability to read and interpret diagnosis results in this case. It can also store large chunks of information that are easily accessible when needed. This allows healthcare providers to concentrate more on the proper way of administering treatment to their patients. A doctor was required to retrieve information for a patient and diagnose and treat them in the past. This made it hard for them to concentrate on their main work, which is treatment. By the time a day shift ends, the doctor has served a few patients. With the new system, the doctor can serve more patients and be less tired, which increases accuracy.
Reference
Eriksson, P. E., Larsson, J., & Pesämaa, O. (2017). Managing complex projects in the infrastructure sector—A structural equation model for flexibility-focused project management. International journal of project management, 35(8), 1512-1523.