Discuss about the Software For Medical Analysis And Research.
Medical software firms engage in delivering and developing systems, solutions, products or services within a medical space. The needs they serve include:
Medical record keeping: these are services and software for utilization by different size companies from large hospitals to a clinic with only one doctor or government company keeping biometrics.
Content and networking management solutions: these software programs are utilized for several reasons, such as integrating different medical bodies, for instance, drug firms to pharmacies, medical representative, labs, among others or patients to hospitals.
Medical practice management: applied to streamline and improve the process of medical practice from appointment booking to issuing prescriptions to charging a fee and payment. These applications can be utilized at large hospitals and small hospitals.
Web-based portals medical services: these portals extend from a simple clinic listing on a website to booking for an appointment to advertising and promotional solutions (Johnson, 2012). These prepared goods can be bought as a personalized theme for new website or be a repeated service to offer advertising, promotion and booking of an appointment.
Hospital management: these are services and software that support different functions in the management and running of large hospitals. A clinical owned by a doctor may find a software for medical record keeping enough, but big hospital will require other programs to maintain timeline of several doctors, management of inventory of different equipment in the hospital, its payment and billing systems and other programs to be utilized by a security worker of a hospital.
Middleware or software to operate a medical device or instrument: a certain device may be developed by firm B, but the software that makes it work may be developed by Firm C.
Software for medical analysis and research: the stream concentrates on offering applications, software and systems to medical research organizations, intended at automating and facilitating their research work.
The following are some of the vendors that offer systems that meet the health information system requirements:
MEDITECH provides software for medical companies of different sizes and types. Some of the software programs the company provides include: revenue cycle, referral and scheduling management, cost accounting, general accounting, supply chain management, patient discharge instructions, behavioral health solutions, management of health information, archiving and scanning, management of emergency department, data repository, human resource planning, management of operating room, and home health solutions.
Intersystems organization is a privately held technology and software systems vendor for rapid application development, healthcare information systems, database management that is highly performing, and integration. The products of the vendor are the InterSystems application development environment and Cache DBMS, DeepSee installed business intelligence, Ensemble connection channel and the healthcare informatics channel of HealthShare.
The software of eClinicalWorks is used to store about one in five health data of America. The organization provides a detailed electronic health record solution with practice management comprising of the following elements:
eClinicalWorks benefit ambulatory categories of different sizes: small and large health systems, correctional health services, large hospital systems, medium, individual, large and small provider practices and 33 percent of the society health centers of the country. Customers of eClinicalWorks are specialists in basic care practices and almost every expertise.
With the cloud-based services arrival and the mHealth ability to transfer information outside the medical setting via these portals, the market entry cost for several heath IT vendors has considerably decreased. It is predicted that that the general expenditure for cloud will increase to approximately $150, and some suggest that 30 % of healthcare companies are planning to utilize cloud services to offer extensive services and minimize expenses (Jun & Jun, 2011). However, as many healthcare information is moved to cloud base, there are doubts whether the federal regulations permit it. Several hosting firms provide HIPAA-compliant cloud services. While many are careful from making unconditional claims, reporting that they only offer HIPAA expertise and Support, some assure compliance. It is dishonest and misleading. As such, HIPAA compliance should be understood first.
Security and privacy regulations are concentrated on applying rules connected to the data protection. For HIPAA it links particularly to trackable electronic health information referred to as ePHI (electronic protected health information). These regulations are unlimited to information kept on a server or production data. Whatever is kept with a cloud provider is probably a portion of the ePHI that is handled and thus need to safeguard.
Besides, while a cloud provider can provide guarantee about technical data security (physical security, encryption level, redundancy, among others), they lack control over who ones offer access to. If policies have not been established that have control on data access or that make sure those granted the access have knowledge of their responsibilities, then even the most technically safe platform can be endangered by individuals broadcasting information that should be confidential (Alashoor, 2014). Therefore, for a company to be HIPAA-compliant, it must set comprehensive policies that address the whole firm. That is something that cannot be offered by a cloud provider, in spite of what they say.
That does not mean that cloud providers cannot support compliance program of a firm. Reliable providers will assist the client acquire their service in a complaint way by signing a business colleague compliance, a major HIPAA requirement. They will assist in conducting a vendor risk analysis and offer HIPAA policy consultancy and templates. Some may collaborate with other parties that offer wider agreement management support. However, in spite of their efforts, it is the responsibility of the customer to effect an agreement framework that addresses beyond cloud storage.
It is doubtless that cloud is transforming the medical industry. And as the IT vendors provide the affordable and creative solutions, many providers are acknowledging that the cloud provides the ability to cut expenses and innovate. However, with the rapid transformation, regulatory evolution and education is needed to make sure that the change occurs in a way that consistently safeguard sensitive information of a patient.
Software Development Lifecycle (SDLC) is the process that software industry follows to develop, design and test quality software. The aim of SDLC approach is to produce a software of high quality that is within timelines and budget. There two SDLC methodologies are adaptive and predictive methodologies. Adaptive methodology is applied when the impending software involves unspecified or unknown results. It involves dividing the software project into different elements over unidentified timeframe to permit for flexibility in managing the course and path of the project. An example of adaptive SDLC is agile software development methodology (Kim, 2016). Predictive methodology, on the other hand, is applied when the results of software projects are known and specified. An example of predictive SDLC is waterfall methodology.
The adaptive software allows stakeholders to engage extensively before the start, during and after each stage of the project (Beyer, 2010). Through the involvement, the approach allows clients to collaborate with the team of development since it involves interaction between the client and the team during each stage. Secondly, adaptive methodology acknowledges transparency. The client and the developers team cooperate in every stage of the project (Wear, 2013). The developers illustrate the status of the project to the client before the kick off, during and after each project stage, thus allowing the clients to have a conceptual view of what their expectation is and allows them to share their take with the team of development. Furthermore, it allows for early delivery because of the in depth involvement of the users prior to, during, and after each phase of the development of the software. As suggested by (Jayashree & Babu, 2014), adaptive methodologies concentrate more on the end users translating to more acceptable software because they ensure that all their requirements are captured and thus ensures total satisfaction.
As discussed above adaptive methodologies have numerous benefits, however, it has a few setbacks. This approach demands for continuous involvement of the clients and consumes much of the user’s time during project’s lifetime. Also during the software development process, a lot of adjustments have to be made because of putting in more of the user’s opinions which may be different from the initial requirements. It is costly because of the continuous testing during the development of the software as put across by (Vohra and Krishnamurthi, 2012).
Predictive methodologies are simple to follow and understand. This is because the approach is characterized by defined phases and steps at the initial commissioning of the project. (Lee, 2014) argues that proving and laying down the steps under which the project will follow makes it easier for the software development team to deliver quality product on time, within the budget, and which meets the specified requirements layout in the initial stages. Secondly, the approach makes it simple to predict the timeframe and budget because the expected outcome is known and can be visualized as argued by (Chauhan, Babar & Benatallah, 2016). Other advantages of this approach include easy management and clearly specified deliverables, budget, and timeline.
Predictive SDLC is easy to manage with predictable deliverable budget, and timelines, however it has some cons. First, this approach has no working software until the final phases of the development process. Reviews and testing process is done at the later stages of the software development (McHugh, McCaffery & Casey, 2013). For projects which are complex this approach is not recommended because the deliverables cannot be predetermined in the initial stages.
The predictive SDLC is not usable for complex object-oriented projects. The methodology is only usable for smaller projects where all the requirements are defined at the initial stage and the expected end results determined at the project initiation stage (Mohammed, Niazi, Alshayeb & Mahmood, 2017). Furthermore, this approach cannot be used for project that requirements are not clear.
Between adaptive and predictive SDLC approaches, adaptive SDLC approach is recommended to be used during the development of the My Health Record project. This is because the platform will be used by several users, and thus developing it using adaptive approach is the best choice because users are engaged during the entire project life cycle.
Conclusion
Undoubtedly cloud is transforming the medical industry. As the IT vendors provide the affordable and creative solutions, many providers are acknowledging that the cloud provides the ability to cut expenses and innovate. Nevertheless, with the rapid transformation, regulatory evolution and education is needed to make sure that the change occurs in a way that consistently safeguard sensitive information of a patient. When it comes to development of a project such as My Health Record, user specification is a very important aspect. Its completeness can be possible by applying the adaptive methodology since the requirements are gathered continuously from the start to the end of every element and thus guarantee the requirements’ satisfaction in the final product.
References
Alashoor, T. (2014). Cloud computing: a review of security issues and solutions. International Journal Of Cloud Computing, 3(3), 228. doi: 10.1504/ijcc.2014.064760
Beyer, H. (2010). User-Centered Agile Methods. Synthesis Lectures On Human-Centered Informatics, 3(1), 1-71. doi: 10.2200/s00286ed1v01y201002hci010
Chauhan, M., Babar, M., & Benatallah, B. (2016). Architecting cloud-enabled systems: a systematic survey of challenges and solutions. Software: Practice And Experience. doi: 10.1002/spe.2409
Jayashree, K., & Babu, S. (2014). Implementation of Embedded Agile Methodology. International Journal Of Computer Applications, 87(11), 30-34. doi: 10.5120/15254-3953
Johnson, M. (2012). Software Companies. Materials And Methods, 2. doi: 10.13070/mm.en.2.143
Jun, L., & Jun, W. (2011). Cloud Computing Based Solution to Decision Making. Procedia Engineering, 15, 1822-1826. doi: 10.1016/j.proeng.2011.08.339
Kim, t. (2016). Software development project management using Agile methodology. The Journal Of The Institute Of Internet Broadcasting And Communication, 16(1), 155-162. doi: 10.7236/jiibc.2016.16.1.155
Lee, M. (2014). Software Quality Factors and Software Quality Metrics to Enhance Software Quality Assurance. British Journal Of Applied Science & Technology, 4(21), 3069-3095. doi: 10.9734/bjast/2014/10548
McHugh, M., McCaffery, F., & Casey, V. (2013). Adopting agile practices when developing software for use in the medical domain. Journal Of Software: Evolution And Process, 26(5), 504-512. doi: 10.1002/smr.1608
Mohammed, N., Niazi, M., Alshayeb, M., & Mahmood, S. (2017). Exploring software security approaches in software development lifecycle: A systematic mapping study. Computer Standards & Interfaces, 50, 107-115. doi: 10.1016/j.csi.2016.10.001
Vohra, R. & Krishnamurthi, L. (2012). Principles of Pricing. Cambridge: Cambridge University Press.
Wear, N. (2013). Sunshine on Secure Software. Cork: BookBaby.
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