Data Sharing for Effective Health Assessment and Treatment.

Use MC Library databases and the Internet to conduct search
Select appropriate sources using evaluation criteria
Summarize, assess, and reflect on sources
practice MLA documentation
Instructions:

First, review the link to Library Resources on the Course Content page for help with conducting research, evaluating sources, and other MLA formatting questions that you may have.

Second, read about annotated bibliographies and see visual examples on Purdue OWL website.

Third, annotate 5 sources on your topic proposed in the earlier assignment (Topic Proposal). For each entry include complete citation information and a brief summary and evaluation paragraph (about 100 words) covering these areas:

Three main points of the information in the source or the arguable position presented in the source.
An evaluative statement on the accuracy, credibility, objectivity, currency, comprehensiveness, and authority of the source (see pp. 289-294).
How this source helps you understand the issue, if it supports your prediction about the issue or makes you look at the issue differently.
Your main reason for choosing this source.

ANSWER

Annotated Bibliography

McGinnis, J. Michael, Brian Powers, and Claudia Grossmann, eds. “Digital infrastructure for the learning health system: the foundation for continuous improvement in health and health care: workshop series summary.” (2011).

McGinnis et al (2011) provides that 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.

Downey, Autumn S., and Steve Olson, eds. Sharing clinical research data: workshop summary. National Academies Press, 2013.

Downey and Olson (2013) indicate that 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 endeavour 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.

Mikles, Sean P., et al. “Utilizing Standard Data Transactions and Public-Private Partnerships to Support Healthy Weight Within the Community.” eGEMs 5.1 (2017).

Mikles et al., (2017) offer that 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.

Rosenbaum, Sara. “Data governance and stewardship: designing data stewardship entities and advancing data access.” Health services research 45.5p2 (2010): 1442-1455.

Rosenbaum (2010) indicate that it is vital to achieve 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

Gordon, William J., and Christian Catalini. “Blockchain technology for healthcare: facilitating the transition to patient-driven interoperability.” Computational and structural biotechnology journal 16 (2018): 224-230.

Gordon et al., (2018) indicate that 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.