Nursing

Data Stewardship Standards and Guidelines

The purpose of this assignment is to develop data stewardship standards for clinical and public health entities.

Data is essential to progress when it comes to health care information technology and HMIS. The collecting, interpreting, and modeling of data allows information technology specialists, health care administrators, and clinical practitioners to provide the highest quality patient diagnoses, treatment, and care. But the data are only effective when users have appropriate access and understand how to read the data, and when the integrity of the data is sound.

Read the scenario “Aligning Clinical and Public Health Data Standards Through Partnership With the Public Health Data Standards Consortium,” located before Chapter 10 in the textbook.

Using the information provided in conjunction with your own research, create a plan to enforce data stewardship standards across the clinical and public health sectors as a result of this AHIMA/PHDSC merger.

In a 1,000-1,250-word plan, elaborate on the following points:

Overarching goal for the alignment of both clinical and public data standards.
Differences between clinical and public health data use and how this partnership will minimize those disparities.
Similarities between clinical and public health data use and how this partnership will capitalize on those parallels.
Your proposal for new data stewardship standards and guidelines.
Action plan: What will be the first steps in standardizing these data stewardship guidelines and how do you plan to go about managing this process? How do you intend to ensure and maintain consistency in data stewardship standards across the clinical and public health sectors? Who will have access to what data? How will data be collected and stored? How will confidentiality be maintained throughout this process?
How will this collaboration affect patients, health care practitioners, and both public and private health care organizations?
How will this partnership strengthen the infrastructure of health information systems and technology?
You are required to use at least two scholarly references in addition to your textbook for this assignment.

ANSWER

Advancements in technology in the different spheres of human activity have similarly spread to the health sector. The success of digital infrastructure in health largely relies on the ability of different bodies within the health industry to govern and steward the changes effectively. A major standard is the management of data collected and managed from the health management information systems. To health care administrators, clinical practitioners, and health information technologists, the ability to provide patient diagnoses, care, and treatment are only effective when the data is effectively and efficiently available in legible formats and integrity standards. Data stewardship standards are, therefore, vital in health as in any other field. This essay attempts to develop data stewardship standards for clinical and public health entities to enhance data sharing for effective health assessment and treatment.

It is vital to achieving the alignment of both clinical and public data standards. It can improve clinical research through enhanced data quality, integration, facilitation to partners, use of digital software tools, communication amongst teams, and adherence to regulatory reviews and audits. Secondly, standardization would be instrumental in the conversion of research data to fit the application in the wide range of the practice of health administration (Rosenbaum 2010). Thirdly, the development of standards would aim at more cooperation and collaborative input from experts, including their analysis and consensus. Fourthly, scientific and clinical skills and expertise are required to determine how the data can fit retroactively to standards and harmonize terminology. The four form the foundation of the overarching goals for the alignment of both clinical and public data standards (Rosenbaum 2010).

As professions, public health differs greatly from clinical health. Public health works from the perspective of populations and communities, while clinical health examines individuals, a profession manned by doctors, nurses, dentists, and opticians, among others. Public health approaches treatment from numbers, for instance, how many people in a particular geographical region have asthma and what puts them at risk. Professionals in public health will work on the reduction of exposure to cut down on numbers. Additionally, they will examine the number of people with or without proper access to doctors and the quality of care directed at ensuring a healthy community. From the kind of work described, it occurs more than often that the data with either of the two differs from each other. For example, public health data could indicate that a surge in the infection rate of SARS is a decline in the wearing of protective masks, which is analytical epidemiology (Mikles et al., 2017). However, clinical data could identify another cause that is more subtle and personal such as organ cardiology. Unless the two bodies work together, the data will be highly inaccurate.

The major similarities between clinical and public health data are that they both contribute to health literacy and help in achieving the role of knowledge in health. The communication process of both public health data and clinical health data inherently contributes to this knowledge, which is information put in a useful context. The endeavor towards the improvement of health in the community requires the joined effort of practitioners in both clinical and public health sectors. Building synergy between public health professionals and clinical health professionals is the only way to promote the universal practice of disease control.

An approach to data stewardship standards and guidelines applies two main components, data ownership, and access and health information privacy. Data ownership suggests a position advocated for by market forces where data access would be through payment for information. The purpose of stewardship in data ownership would be the acquisition of this health information that would be required and essential in the goal to achieve patient safety, quality, comparative effectiveness, and population health (Grossmann et al., 2011). Governments and organizations with a desire for access and use of data would negotiate with the governance in the health industry. This option as a way forward is important as it recognizes data ownership rights. The resulting problem with this is the cost, which would mean a double charge in the taxpayer, once for individual health and second for public health support programs. The second approach targeted at an improvement of this is the consideration of health information as a public commodity availed for use by “entities structured and operated in accordance with the principles of data stewardship” (Grossmann et al., 2011). These entities could receive directions from governments and granted the authority to collect, prepare, and support the use of health information. This makes a better way forward and though with some limitations to certain uses of data, offers a better approach.

The first step and most important step for this approach is the designation of certain health data privileges to uses that arouse public interest. Further access would be conditional to a public policy designed by federal health programs. Data from health research would be aggregated, managed, and prepared by entities of data stewardship who could further provide licenses for data for use by a researcher after proven compliance and responsibilities. Through this, data will maintain confidentiality, availability, and integrity for subsequent uses while assuring the effectiveness of the flow of data, which is essential for a health system. The process will aim at assuring privacy and promoting trust. A good example is the Alzheimer’s Clinical Trial Database, which is a modeling tool implemented for the quantitative prediction of patient populations (Institute of Medicine). The database merges data from both public health and diverse clinical sources and provides analysis into the distinction emerging from a modeling tool to perform the test, prevention, and treatment of Alzheimer’s disease more accurately. A central collection of data units provided by this trial could enable global contributions from worldwide health experts to point to more comprehension of the disease.

In conclusion, it is clear that digital data is a vital component to the understanding of health and disease control. This is a huge lesson considering the current epidemic of COVID-19, in which initial handling of information led to a leak of infected persons around the globe, a mistake that the world is still reeling from. Instance transfer of health information is vital, and perhaps the only thing that keeps the human race from extinction. Sharing of data enables the development of precautions and the foundation of vaccines that prevented generations after generations from diseases that would have otherwise been catastrophic. In the age of information, digital health data requires policies that support the application of health data for the betterment of human health and survival.

References

Institute of Medicine (US). Sharing Clinical Research Data: Workshop Summary. Washington (DC): National Academies Press (US); 2013 Mar 29. 5, Standardization to Enhance Data Sharing. Available from: https://www.ncbi.nlm.nih.gov/books/NBK137818/

Institute of Medicine (US); Grossmann C, Powers B, McGinnis JM, editors. Digital Infrastructure for the Learning Health System: The Foundation for Continuous Improvement in Health and Health Care: Workshop Series Summary. Washington (DC): National Academies Press (US); 2011. 6, Stewardship, and Governance in the Learning Health System. Available from: https://www.ncbi.nlm.nih.gov/books/NBK83560/

Mikles, S. P., Wiltz, J. L., Reed-Fourquet, L., Painter, I. S., & Lober, W. B. (2017). Utilizing Standard Data Transactions and Public-Private Partnerships to Support Healthy Weight Within the Community. EGEMS (Washington, DC), 5(1), 21. https://doi.org/10.5334/egems.242

Rosenbaum S. Data governance and stewardship: designing data stewardship entities and advancing data access. Health Serv Res. 2010;45(5 Pt 2):1442-1455. doi:10.1111/j.1475-6773.2010.01140