Discussion
Posting 1:
As we all know that computers and laptops are becoming an essential element in today’s fastest-growing world. People can manage their work easily, they can work remotely, they can manage work, finance (through websites), social life (Facebook, WhatsApp). These days, people are mostly spending more time with their mobile devices and laptops. These days, people are also using a lot of computers, IT services to develop their products and services better and make their customers happy. IT is everywhere, it is in Health, Sports, Space, Finance, and Business. Now all those IT services providers are human beings who provide and develop those services and human beings can make mistakes while working or developing things. Here we will take an example of a Health Care data system. I reviewed an article about structuring, reuse, and analysis of electronic data using the Oral Health and Disease Ontology (Dun). In that article, it was mentioned about the poor data management into the Health Care Industry and the steps about how to make an improvement. A key challenge in the Health industry is managing customer data into the database. Customer data is a very critical asset for all the IT companies and managing them, store them, and process them through the way it keeps secured and not comes into the wrong hand is very critical. Also into the Oral Health Care, dentists have to do many procedures and all the procedures require patient’s personal information, storing them at each time and process with the right encryption, also make sure all the patient’s data are secured through the network traffic and they are stored into the database with some right information so that it can be retrieved. Also, we have to keep checking that all the patients' data are stored in the replica sets too, sometimes the Health care industries have many branches around the globe and if they are trying to access data from another country, then it took a long time so the Health Care industry has to use distributed database and make sure if we update anything related to one patient’s data, it applies to all the replicas of the databases.
References
Duncan, W. D. (n.d.). Structuring, reuse, and analysis of electronic dental data using the Oral Health and Disease Ontology. Journal of Biomedical Semantics. 8/20/2020, Vol. 11 Issue 1, pN.PAG-N.PAG. 1p.
Posting 2:
In the computer world, the implementation of the database server is very significant for maintaining and processing data according to the required operations. Hence, we need to design the database system well and make the data work properly without any disturbance. Mostly we can see bad situations if we don't have a good server design. As a developer, we need to understand the type of database model to solve the challenges of the information system. Normally we are faced with the column, the tables, the procedures and the activation functions in the database. Lack of normalization, indexing issues, integrity references, primary keys, redundancy and name translation in the database design. When we avoid the purpose of the data, we can get a bad response from the database. For example, the designer wants to know what he will get when he gives the input for the requested function. In the real-time scenario, we don't use the same data model to retrieve the huge number of records from the organization's database. Hence, it should be managed by the data volume through database efficiency and usability when designing the database. However, we also need to consider entities, record sizes, and their policies. Mostly the database follows normalization roles and layouts to give problems. However, we can avoid performance issues through some software techniques. If we can use the third normalization and the appropriate layout to get good results from the database in the company. It happens between database queries and gross operations (Bavin, M. R. (2018)).
Redundancy is another negative impact for getting negative results. Hence, business logic wants to keep the upgrade version and have the perfect development documentation. It could lead to corrupt system data easily. To ignore integrity constraints, we need to focus on data quality. It is based on the company logic. In this case, views are useful for quickly examining the data and quickly obtaining queries via indexes. We have also collected and aggregated the functions without writing any code. While we are making the transaction, we need to securely protect the data in the system and provide the integer ID or primary key in the database design (Lubián, F. J. L., & Esteves, J. (2017)).
References:
Bavin, M. R. (2018). Examining the use of knowledge management in a university department.
Lubián, F. J. L., & Esteves, J. (2017). Value in a Digital World: How to assess business models and measure value in a digital world. Springer.
Posting 3:
Implementation of new technology is advocated by many, expecting that it makes our lives easy and improves efficiency. Sometimes such good intentions are not enough to support a successful implementation. There are a few critical elements that determine the success of the project. The project depends on a few factors like selecting a reliable vendor with the right solutions, planning proper milestones and timelines, leadership dedicated to the project success, and involving the right people in the decision-making process. The implementation project under scrutiny here is of healthcare technology in a rural hospital. The failure of such projects are much more critical and have massive implications for patient health. Adding to the preexisting issues with the current technology in healthcare and its complicated nature failure of such projects are much more critical and have massive implications on patient health (Miller et al., 2015).
The rural hospital devices a plan to implement an integrated information system consisting of an electronic medical record and computerized physician order entry in the hospital in 2004. It took four years to complete the implementation and faced many issues along the way. The first set back was a loss of personnel in leadership positions. First was the Clinical Implementation Coordinator, whose primary responsibility was to work with the clinical staff, the nurses, and clinicians to train and support the new technology. The second was the Project Manager with the IT vendor. The replacement coordinator, who needed a good grasp of clinical knowledge and IT, did not have any clinical experience. And even after replacing the project manager, the timeline for implementation was not adjusted, and the hospital expected work to be done according to the tight schedule established previously (Øvretveit, Scott, Rundall, Shortell & Brommels, 2007).
A partial success with implementing the bar-coding system to scan supplies, but not all medication made the hospital believe they were on the right track. Within the first two years of initiation, change of leadership and success of barcode scanning was followed by reports of scanner malfunction, missing codes for the barcodes, slow computers, and inadequate equipment. These problems lead to a delay in several initially planned modules to be implemented by the end of the second year.
These problems exposed that vendor choice for such an important and gigantic implementation may not have been the best. Three out of seven managers voiced concerns over the quality of software and equipment. Many modules that were promised to be delivered a year prior were still in development stages, confirming the concerns regarding the choice of vendor. The mistrust in the vendor and technology problems with implemented modules only increased the chaos in the last two years of the project. Increased turnover at the hospital, interim management, and non-clinical personnel, making a clinical practice decision fueled the fire (Øvretveit, Scott, Rundall, Shortell & Brommels, 2007).
The EMR launch in the final year of implementation was not received well by the physicians as they were not familiar with the workflow. The support staff who were of clerical background failed to support the users and the physicians (Miller et al., 2015).
These problems could have been avoided by choosing a well-experienced vendor with reliable and trustworthy solutions. Leadership plays a significant role in the success of any project. Securing the right people as managers and coordinators could have helped with the timeline and turnover issues in this implementation (Chaudhry et al., 2006). Any project should have a well thought out schedule. Without planning for contingencies and having buffer time, any project facing few hurdles is doomed. Businesses and sponsors should have a realistic idea of the timeline and expenditure for success. Another crucial aspect often overlooked, like in this implementation is involving the end-users or clinical staff in this case in decision making during the execution (Aydin et al., 2004). Since they are the end-users of the implemented technology for whom the technology is created, they need to accept, familiarize, and train on the software for successful implementation and use.
References
Aydin, C., Bolton, L., Donaldson, N., Brown, D., Buffum, M., Elashoff, J., & Sandhu, M. (2004). Creating and Analyzing a Statewide Nursing Quality Measurement Database. Journal Of Nursing Scholarship, 36(4), 371-378. doi: 10.1111/j.1547-5069.2004.04066.x
Chaudhry, B., Wang, J., Wu, S., Maglione, M., Mojica, W., & Roth, E. et al. (2006). Systematic Review: Impact of Health Information Technology on Quality, Efficiency, and Costs of Medical Care. Annals Of Internal Medicine, 144(10), 742. doi: 10.7326/0003-4819-144-10-200605160-00125
Miller, A., Moon, B., Anders, S., Walden, R., Brown, S., & Montella, D. (2015). Integrating computerized clinical decision support systems into clinical work: A meta-synthesis of qualitative research. International Journal Of Medical Informatics, 84(12), 1009-1018. doi: 10.1016/j.ijmedinf.2015.09.005
Øvretveit, J., Scott, T., Rundall, T., Shortell, S., & Brommels, M. (2007). Implementation of electronic medical records in hospitals: two case studies. Health Policy, 84(2-3), 181-190. doi: 10.1016/j.healthpol.2007.05.013
Posting 4:
In the PC world, the use of the database server is enormous to keep pace and process information based on the required activities. In this way, we need to plan the database structure well and process the information appropriately without disturbing influences. For the most part we can see the dire circumstances on the off chance that we don't have a large server facility. As a designer, we need to understand database model sorting to solve data framework challenges. Usually we are faced with the section, tables, systems and database activation capabilities. Lack of standardization, sorting problems, righteousness references, essential keys, repetition and transformation of names in the database structure.
When we keep a strategic distance from the reason for the information, we can get a terrible reaction from the database. For example, the planner must realize what he will get when he contributes to the required capacity (Rossel, S. (2017)).
In the continuous situation, we don't use the same information model to retrieve the huge number of records from the database of the action association. A along these lines should be addressed in volume information through database productivity and ease of use when we are structuring the database. However, we must also think about the elements, the measurement of the memories and their strategies. Generally, the database pursues standardization work and formats to give problems. Be that as it may, we can keep ourselves away from the problems of the exhibition through some product strategies. On the off chance that we can use a third standardization and a suitable format to get great results from the database in the organization. Occurs between database requests and muck activities (Kouzis-Loukas, D. (2016)).
References:
Rossel, S. (2017). Continuous Integration, Delivery, and Deployment: Reliable and faster software releases with automating builds, tests, and deployment. Packt Publishing Ltd.
Kouzis-Loukas, D. (2016). Learning scrapy. Packt Publishing Ltd.