Drchrono EHR : This software is a patient care platform which helps in offering customization at the point of care and on the go. Apart from it the software also includes the scheduling practice, billing and patient reminder activities (Software Advice, 2006).
NueMD: This particular software offers the clients of the vendor a cloud based software and the maintenance of the billing services of the medicines for the practices of all types. Some of the characteristics of NueMD have been discussed in brief below:
Cloud computing based system is a recent and fast-growing area of the development in the medical field. On-demand access to the virtual field, endless resources in combination with the pay per usage model allows for the new ways of the development, delivering and utilizing services. Cloud computing system is growing the interest towards several medical organizations all over the world but adoption of the cloud computing is not that easy task because there are many issues associated with its adoption, which are required to be eliminated. Cloud computing in health care system is one of the solutions for medical organizations for the purpose of managing data in an efficient manner and using the flexible, scalable and affordable platforms.
Strengths: The strengths of the cloud computing system in the healthcare sector comprise of cost-effectiveness, innovation, and flexibility, simplifying cost, compliant facilities, flexible, maintenance cost reduction, controlling resources, time and location. Usage of the cloud computing in the healthcare sector leads to a reduction in cost because it does not require any start-up expenditures. healthcare organizations face lack of enough resources and also cannot afford the intensive expenses Cloud computing has the capability of providing all of them. Easy access to the records of the patients in any time and anywhere leads to increment in collaboration amongst the doctors and patients, so the quality of the services towards patients will be enhanced. strength of the system keeping in mind the environment where we are thinking of implementing the project will be that: users will be having unlimited access to the software using the devices, user will not be chained to one single stationary computer, data will be easily shared with the systems and the system will be having its own information technology support (Viswanathan, 2018).
Weaknesses: Absence of the strengths is considered as a weakness, so the weakness of cloud-based computing system in the healthcare sector comprises: Training needs, high speed of internet connection needs, integration with software is also tough. Implementation of the cloud-based computing system in the health care system is not an easy task as there are many factors which are involved in the adoption and implementation and also the software is more dependent on the cloud-based service provider. many of the hospitals do not even internet connection to connect to the cloud, so in this case, it is very hard to implement the cloud computing. Internet connection is a fundamental and essential need for connecting the cloud and usage. The weakness which our project will basically feel will that: turning over the data, security, availability and the control to the third party means that the medical organization will not be having any control (Viswanathan, 2018).
Now days every company is following a set procedure of SDLC technique for the purpose of designing, developing and testing the quality of the software. The approach of the SDLC goals towards developing the higher quality software which is actually in the budget and within estimated timelines. There are two kinds of approaches of SDLC which are known as: predictive and adaptive methodologies. The approach of adaptive measure is implemented only when the software which is in hand associates with the unknown outcomes. For instance the agile software development is one of the pattern of adaptive SDLC. On the other side, the predictive SDLC is implemented in such type of projects that are having specified outcomes and even their outcome variables are known. The technology of waterfall falls under the category of predictive SDLC towards the development of the software (Software Testing Genius, 2018; Halvorsen, 2017; ICAI, 2017).
Advantage of Predictive SDLC: This kind of SDLC is very easy understanding and in following the pattern. The methodology illustrates varied types of stages that are followed by the starting towards the implementation of the software. The steps are quite easy in understanding and this is the reason why the developers find it easy to understand the process ad come up with the quality software maintenance within the frame of time and also within the budget which is specified. The predictive SDLC also allows for quite easy and manageable predictions of the budget analysis. As the end results of the process are quite known and the final product also visualizes at the starting stage of the development of the software, the predictive SDLC makes it easy for the teams for coming up with the budgets which are expected as well as the expected frame of the time needed for completing the projects (Georgetown, 2018).
Disadvantage of Predictive SDLC: In this kind of SDLC approach, no software is produced until the late stage arrives of the development of the software. The software product is generated at the late stage of the processing of the development. The software testing is also done at the last stage of the life cycle modeling. Such technique is of not much usage for the complex objects in project. Such type of methodology is of use for the project which are small time, in which all the needs are clarified at the starting stage and even the expected results of end analyzed at the project starting stage. The other side, this methodology is not good wherein all the needs are not known or at the risk of change within the time. The methodology of predictive approach is quite inapplicable for the projects that are of long time and are even of the ongoing time because of the rigidity and the strict guideline (The University of Texas, 2017).
Advantages of the Adaptive SDLC: The adaptive approach of the SDLC offers some type of opportunity for the extensive engagement of the stakeholder before the kick off the projects, during and after the stages of the project. Through the engagement processing, the approach mainly offers the high degree of the client collaboration with the team as it gets involved in the extensive interaction type in between the development team and the client during each and every stage (Tutorialspoint, 2018). The process of communication helps the customers in evaluating and understanding the project stages one by one and one after the other. The processing allows them in sharing the views and adding some needs whenever the demand or need arise. The interaction in between the client and the development team aids the team for understanding the vision which is being followed by the client. The strategy followed by adoptive approach allows the early delivery of the project. This happens because of the extensive level involvement of the clients before and after the stages of the development of eth software. Apart from it, there happens speedy developments which comes up in the software delivery
Disadvantages of the Adaptive SDLC approach: The adaptive approach of the SDLC demands for extensive involvement in case the user takes up as the representative which is associated with the time and the level of commitment during the project lifetime. Much of the timinings is wasted because in many of the cases that are engaged during the session of testing and gets disengaged in the session of development. The approach of adaptive SDLC involves lot of emergence requirement and evolution during the project lifetime. The future needs in many of the cases forces the project in taking longer time in completion than the time which is anticipated and in other cases, the project also becomes quite big than it was earlier visualized in the starting (Cerritos College, 2017; Idea, 2005).
The approach of adaptive SDLC is considered to be one of the best methodology for the implementation purpose during the development medical health record maintenance project. As the project is completely based on maintenance of health records so it is expected that the software will be sued by many types of users. So, development of such software through adaptive approach is the best approach, as in this methodology, extensive involvement of the user is employed before and after the steps in the development process. The completion of the needs of the user is quite crucial aspect of the automated health related project. This particular approach can be made possible with the use of the adaptive methodology of SDLC since the requirements are collaterally right from the starting towards the completion of the components and hence the hence assuring satisfaction of the needs in the end product. The project health record maintenance is a project which involves various types of elements and is also object oriented in the nature. SO it is quite visible that the approach of predictive SDLC is not suitable for the project. The approach of adaptive methodology is also ideal for the project.
References
Cerritos College. (2017). System Analysis And Design In A Changing World. Retrieved from Cerritos.edu: https://web.cerritos.edu/sfuschetto/SitePages/CIS201/LectureNotesOnTalonNet/Chapter08Lecture.pdf
Georgetown. (2018). Pros and Cons of Predictive Analysis. Retrieved from Scsonline.georgetown.edu: https://scsonline.georgetown.edu/programs/masters-technology-management/resources/pros-and-cons-predictive-analysis
Halvorsen, H.-P. (2017). The Software Development: A Practical Approach. Retrieved from Home.hit.no: https://home.hit.no/~hansha/documents/software/software_development/resources/Software%20Development.pdf
ICAI. (2017). System Development Life Cycle Methodology. Retrieved from Icaiknowledgegateway.org: https://www.icaiknowledgegateway.org/littledms/folder1/chapter-2-system-development-life-cycle-methodology.pdf
Idea. (2005). Adaptive vs. Predictive: Is the end clear? Retrieved from Idea.org: https://www.idea.org/blog/2005/12/02/adaptive-vs-predictive-is-the-end-clear/
Software Advice. (2006). Athenahealth EHR Software. Retrieved from Softwareadvice.com: https://www.softwareadvice.com/medical/athenacollector-athenaclinicals-profile/
Software Advice. (2006). Drchrono EHR Software. Retrieved May 24, 2018, from Softwareadvice.com: https://www.softwareadvice.com/medical/drchrono-profile/
Software Advice. (2006). NueMD Medical Billing Software. Retrieved from Softwareadvice.com: https://www.softwareadvice.com/medical/nuesoft-nuemd-complete-profile/
Software Testing Genius. (2018). Software Development Life Cycle. Retrieved from Softwaretestinggenius.com: https://www.softwaretestinggenius.com/download/Lifecycle.pdf
The University of Texas. (2017). The System Development Life Cycle. Retrieved from https://www.scribd.com/document/356686962/2-SDLC-Adaptive-and-Predictive
Tutorialspoint. (2018). Adaptive Software Development – Lifecycle. Retrieved from Tutorialspoint.com: https://www.tutorialspoint.com/adaptive_software_development/adaptive_software_development_lifecycle.htm
Viswanathan, P. (2018, May 22). Pros and Cons of Cloud Computing. Retrieved from Llifewire.com: https://www.lifewire.com/cloud-computing-explained-2373125
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