Quantitative Research
Healthcare relies on quantitative research for evidence-based practice in nursing, for organizational structure, design, and marketing, for public health and value-based purchasing issues, safety, and a practically unlimited array of other uses. Using quantitative research methods generates numerical data: data that can be used to generate statistics, to track patterns reliably using metrics, and to make fairly accurate predictions based on quantitative modeling. The research methods used in quantitative studies are often scrutinized carefully, ensuring consistency, reliability, and validity. Therefore, effective healthcare service delivery and operations depend on quantitative research.
Implications for Knowledge Generation in Healthcare
Both quantitative and qualitative research contributes to knowledge generation in healthcare. The implications of each depend on the ontological and epistemological frameworks used by stakeholders. For example, a positivist framework emphasizes the importance of numerical, quantifiable data for determining the efficacy of treatment interventions or marketing methods used in healthcare. A phenomenological approach deems human subjective perceptions to be worthy of attention, important ways of knowing how patients perceive their interactions with nurses or how they respond to therapeutic interventions. Quantitative research might be attractive for its mathematical infallibility but also presents distinct...
(Health Insurance Coverage, 2009). This is just a little higher than what was reported in the state of Pennsylvania over the last two-year period, which was at 25% (Krawczeniuk, 2009). "The number of uninsured rose 2.2 million between 2005 and 2006 and has increased by almost 8 million people since 2000" (Health Insurance Coverage, 2009). Most Americans are provided with health insurance coverage through their employers. But in today's society
Figure 1 portrays the state of Maryland, the location for the focus of this DRP. Figure 1: Map of Maryland, the State (Google Maps, 2009) 1.3 Study Structure Organization of the Study The following five chapters constitute the body of Chapter I: Introduction Chapter II: Review of the Literature Chapter III: Methods and Results Chapter IV: Chapter V: Conclusions, Recommendations, and Implications Chapter I: Introduction During Chapter I, the researcher presents this study's focus, as it relates to the
As a result, millions of Americans remain unable to bear the heavy financial toll of medical expenses. Indeed, the problem of a lack of insurance for many is related to the problem of the cost of healthcare. So confirms the article by Consumer Reports (CR) (2008), which finds that "health-insurance premiums have grown faster than inflation or workers' earnings over the past decade, in parallel with the equally rapid
Transparency empowers consumers to become better shoppers. Economists assert that transparency stimulates productivity, for example, in exchange for money, one individual obtaining fair value. In every aspect, except healthcare, Davis points out, transparency, is supported. The contemporary dearth of transparency in healthcare has led to many Americans not being able to effectively shop for the best quality of service at acute care hospitals. Davis argues that transparency permits consumers,
(Findlay, 2001, 90 -- 119) (McLeod, 2003, pp. 895 -- 908) What is the possibility of bias entering the study? If the study is susceptible to bias, state and explain the type of bias that may enter the study and what steps can be incorporated to minimize the entry of bias. The possibility for bias in the study is low. The reason why, is because researchers will have limited access to
Cost analysis methods, 2011, U.S. National Library of Medicine). This will give a picture of the efficacy of the drug, its financial costs, its impact upon society, and impact upon the patient. When a drug is new, data must first be accrued on the drug itself before it can be compared with similar treatments. What type of economic evaluation should be used when comparing outcomes and costs of two diabetes
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