Quality-of-care issue and a data set
The use of health information technology has positively impacted patient care across the world (Kaufman, Roberts, Merrill, Lai & Bakken, 2006; Gruber, Cummings, Leblanc & Smith, 2009; Hannah et al., 2011). Nurses and other healthcare professionals aim to deliver quality healthcare to patients. However, several quality-of-care issues compromise the standards of healthcare offered to patients. The issue of errors within healthcare organizations negatively impacts quality patient care. Clinical errors within a healthcare organization are introduced by healthcare professionals as they administer care to patients. For instance, a physician could prescribe the wrong medications to a patient. Therefore, the patient’s condition could worsen because the medications could not have therapeutic benefits. Also, compounding errors could occur when errors are introduced to healthcare settings by external factors. For example, contamination of pharmaceutical products with pathogenic organisms could result in the deaths and morbidity of many patients within a healthcare organization. The issue of errors was chosen because errors present major quality-of-care challenges as healthcare professionals endeavor to provide quality healthcare to patients (Hannah et al., 2011).
The web-based data set that was chosen was “Healthy People 2010”, which was accessed from the Center for Disease Control and Prevention (CDC). The data set contains comprehensive data on various aspects of health from 1998 to 2010. The wide variety of healthcare parameters contained within the dataset makes it a holistic database for accessing and comparing analysis of the healthcare parameters. Also, the characterization of data across the years allows the public and healthcare professionals to examine the trends of healthcare across the years in comparison with the implementation of various healthcare reforms and advancements.
The website’s available data sets
The CDC website contains the following sets of data related to healthcare: mortality, births, cancer statistics, population health statistics, vaccine statistics, occupational health data, AIDS public-use data, and environmental health data. Many of the categories of data sets on the website have subcategories. For example, mortality has the following subcategories: infant deaths, multiple causes of death, detailed mortality, and compressed mortality. Also, the environmental aspect has the following subcategories: daily sunlight, daily precipitation, daily fine particulate matter, and daily land surface temperatures. The data sets have tables and graphs showing analysis of healthcare-related data.
How the data sets could be used to support evidence-based clinical practices and improve the quality of care
The data sets support evidence-based clinical care by providing up-to-date clinical data analysis that is crucial in promoting information-driven clinical decisions (Hannah et al., 2011). The data sets play crucial roles in providing vital clinical facts to healthcare personnel as they seek to offer quality healthcare to patients. The published data in the data sets are verified and could be relied upon by healthcare professionals when they aim to provide healthcare-related to the parameters in the data sets. For example, clinicians can know the effectiveness of a certain disease vaccine by accessing a vaccine data set on the website. Therefore, they could offer the vaccine to an individual based on the findings they learn from the data set. However, they could not vaccinate an individual when the effectiveness of the vaccine is reported to be low or when the vaccine is found to have adverse side effects in humans. Therefore, data sets are important healthcare resources that ensure evidence-based clinical practices are adopted by healthcare professionals. Clinicians could access the data sets and learn better approaches to managing various conditions and diseases (Schlotzer & Madsen, 2010; Hannah et al., 2011). For example, they could learn about the drug efficacy levels of a medication targeted to cure a chronic disease. Thus, access to data sets could improve the quality of healthcare within healthcare organizations.
Gruber, D., Cummings, G. G., Leblanc, L., & Smith, D. L. (2009). Factors influencing outcomes of clinical information systems implementation: a systematic review. Computers Informatics Nursing, 27(3), 151-163.
Hannah, K. J., DuLong, D., Newbold, S. K., Sensmeier, J. E., Skiba, D. J., Troseth, M. R.,… & Douglas, J. V. (Eds.). (2011). Nursing informatics: Where technology and caring meet. New York, NY: Springer.
Kaufman, D., Roberts, W. D., Merrill, J., Lai, T. Y., & Bakken, S. (2006). Applying an evaluation framework for health information system design, development, and implementation. Nursing research, 55(2), 37-42.
Schlotzer, A., & Madsen, M. (2010). Health information systems: requirements and characteristics. Studies in health technology and informatics, 151(1), 156.