Capstone Project: Quality Assurance System Integration

Capstone Project: Quality Assurance System Integration

Quality assurance system integration refers to the merger of quality assurance subsystems to enhance efficiency and quality (Luttig, n. d.). Organizations integrate their quality assurance systems to enable them reduce the costs of operations. There are categories of quality assurance and methods that can be utilized to enhance quality assurance in an organization.

Quality Assurance Categories

Completeness: – this refers to the nature of the database (Chemuturi, 2010). A complete quality assurance database implies that all the data matches the known standards for, table structure, typology, projection, precision, and other data-related model requirements.

Validity: -validity refers to the degree of accuracy in the organization’s quality assurance database (Chemuturi, 2010). A valid database should have a definite domain and range. Therefore, the database’s validity focuses on whether the database’s values are complete, accurate, and rationally consistent.

Logical Consistency: -logical consistency is the determination of the relationships between values of two, three, or more attributes that are functionally-related. One may determine the logical consistency of a quality assurance database by conducting a physical examination of the objects; then correlating the findings with what is contained in or shown by the database (Chemuturi, 2010).

Physical Consistency: -This is the measure of the topological and geographical extent precision of one’s database (Chemuturi, 2010). The database is said to achieve physical consistency if its infrastructural components such as control rooms are physically compliant with the database’s descriptions.

Referential Integrity: -This is the measure of the relationships between two or more related tables with special reference to their foreign or primary key relationships (Chemuturi, 2010). Often, foreign and primary keys must be present and must link the data sets in the tables based on the pre-identified rules for each of the tables.

Positional Accuracy: -this is the measure of how consistent every object’s real spatial position matches with the content of the database (Chemuturi, 2010). Positional error is often introduced by incorrect cartographic interpretations or digital storage correctness inaccuracies.

Quality Assurance Methods

Continuing Education: Continuing educational is a regular-professional based education program that is offered to an organization’s workforce. Often, organizations have their own varied professional content that included technicians, clerks, and those at the management level (Resch-Genger, 2008). Continuous education programs are offered to each category of workers to update their professional skills. In practice, continuing education is a domain of the registered professionals such as nurses and teachers. Such professionals are usually required to complete a certain amount of credit hours a year for their licenses to be renewed by the regulator (Resch-Genger, 2008). However, other professionals can be subjected to continuing education to improve their professional skills. For example, IT technicians may be subjected to regular training to enable them enhance their skills on hacking, malware software, and cyber attacks, among other skills.

Disseminating Practice Guidelines: -This refers to the issuance of rules and guidance to the organization employees on the ideal professional and personal conduct within the organization (Resch-Genger, 2008). In most cases, such guidelines are in the form of how-to-do manual which offers step-by-step guidance on what one needs to do in a given scenario. For example, the National Health Medical Research Council (NHMRC) publishes clinical research guidelines to assist clinicians in making informed decisions in their day-to-day operations. Similarly, other professional organizations publish their own professional guidelines to enhance best practices by their professional workforce.

Continuous Improvement: -Continuous improvement or continuous quality improvement refers to the continuous institutional improvement process (Resch-Genger, 2008). This method has four main components that are continuously performed to assure quality: planning, implementing, checking, and implementation. First and foremost, the organization should plan for the action to be taken. Once the plan is in place, the management of the organization implements the plan. Thereafter, the management evaluates the progress of the implementation process to identify whether it is accomplishing its objectives. The evaluation is then followed by carrying out changes on the plan before proceeding with the implementation process. After the plan has been implemented, the management would draft a new plan to enhance changes to the plan. Therefore, continuous improvement is a continuous implementation of plans to assure that there is quality.

In addition, continuous improvement requires the cooperation of all the workers. Usually, the policy directive starts from the top management then trickles to the action teams via the quality improvement team. Action teams incorporate all the departmental or sub-departmental employees and their manager. It is the work of the action teams to implement the action plans from the quality improvement team. As a rule, action team members are members of the same professional or department; therefore each team implements an action plan that is relevant to their line of profession.

Designing Management Information Systems with Uniform Data Elements: -this implies that the organization’s information systems have the same data table outlook, similar rules of data entry, and algorithms. Overall, uniform data elements make it easier for the organization’s workforce to process and analyze data. In addition, uniform data elements make it easier to train staff on how the information technology works because the basic rules of operation are the same. For example, data tables for an in-patient hospital might have elements such as the name of the patient, credit card number, state or country of birth, current physical address, age, gender, and marital status (Ghorbani, Ahmadi, Sadoughi, & Ghanei, 2012). Such data allows the hospital workforce to minimize data-related errors.

Conducting Comparative Research: -Comparative research helps in identification of how similar organizations work to enable one to copy such organization (Resch-Genger, 2008). Usually, comparative researches are done at a national or regional level. Such research helps the organization to seek expert analysis, user analysis and evaluations, cost analysis and other aspects of the programs run by similar institutions before adopting universal measures to enhance quality. Comparative research also enables organizations to make informed decisions on the effectiveness of policies and how to accomplish better results.

The objective of comparative research is to avail new information on the technology, management policy, or organization’s structure to the organization’s performance. Researchers conduct investigations to discover information such as the latest cyber attacks, how they are executed, and trends in data management tools (Resch-Genger, 2008).  Such information is then used to train the organization’s workforce and measure that can be used to mitigate potential threats to the organization such as cyber attacks.

Quality Controls (Q.C.): -quality controls refer to the review of the factors and elements related to the organization’s performance. Often, such evaluation focuses on three main aspects: First, job management enhances professionalism and integrity service delivery processes such as record keeping. Secondly, quality controls place emphasis on staff competences in knowledge and experiences. Thirdly, quality controls focus on soft elements and attributes such as personal confidence, organizational culture, staff motivation, and quality-related aspects. Essentially, quality control targets aspects that promote quality in the organization. Thus, the organization emphasizes such attributes with the hope to assure quality.

Continuous Improvement Use in Supporting Quality Assurance for the Hospital Integration Project

            Continuous improvement method is the best method for supporting quality assurance for the hospital project because it enhances continuous quality within the organization. As a norm, continuous quality improvement requires frequent evaluation of the quality assurance system integration project to mitigate any current or future challenges. Continuous improvement will ensure that the merged hospital quality assurance system continuous undergo reviews and evaluation to improve its performance. For example, over time, the hospital will be in a position to identify the cost implication of the system before making changes (Luttig, n. d.).

In addition, continuous improvement will enable the hospital to update its data system on continues basis to comply with the dynamics affecting the IT industry. This is because of the fact that the IT industry is subject to frequent cyber attacks. Continuous improvement will also enable the hospital staff to adapt to the new system since it is critical in transforming the hospital staff’s culture towards the newly integrated quality assurance system (Dlllard, Gladd, and Hutton, (n. d.). The method will further make use of other methods such as comparative research thereby enabling the hospital’s action teams to ensure quality for the entire hospital.

 

References

Top of Form

Chemuturi, M. (2010). Mastering software quality assurance. Boca Raton, Fla: J. Ross.

Top of Form

Chorafas, D. N. (2013). Quality control applications. London: Springer.

Bottom of Form

Bottom of Form

Dlllard, J. W., Gladd, R. E., Hutton, V. (n. d.). Laboratory software applications development: Quality assurance considerations. Retrieved 23, October, 2013, from, http://www.bgladd.com/papers/ITORL1.PDF

Ghorbani, N. R., Ahmadi, M., Sadoughi, F., & Ghanei, M. (2012). Developing data elements for research information system in health; a starting point for systems integration. Iranian Journal of Public Health, 41(12), 30–39.

Luttig, D. (n. d.). A proven approach for successful systems integration. FIS Position Paper. Retrieved 23, October, 2013, from,http://www.fisglobal.com/ucmprdpub/groups/public/documents/document/C011355.pdf

Top of Form

Resch-Genger, U. (2008). Standardization and quality assurance in fluorescence measurements. Berlin: Springer. Bottom of Form

Last Completed Projects

Are you looking for a similar paper or any other quality academic essay? Then look no further. Our research paper writing service is what you require. Our team of experienced writers is on standby to deliver to you an original paper as per your specified instructions with zero plagiarism guaranteed. This is the perfect way you can prepare your own unique academic paper and score the grades you deserve.

Use the order calculator below and get started! Contact our live support team for any assistance or inquiry.

[order_calculator]