By Jason Burke
"A hands-on, analytics street map for healthiness leadersThe industry-wide transformation happening around the future health and existence sciences environment is mandating that businesses undertake new decision-making features, in line with technological know-how and real-world info. Analytics might be a required competency for the fashionable health and wellbeing firm; this booklet is ready easy methods to "cross the chasm." the final word analytics advisor for Read more...
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Additional resources for Health analytics : gaining the insights to transform health care
Example text
Six months? A year? And how do you handle patients who contracted influenza before receiving the inoculation? How far ahead of the inoculation in time will you set the rule? This example is easy compared to trying to understand treatment efficacy for complex, chronic, and/or comorbid diseases such as cancer, diabetes, and cardiovascular disease. The exercise is not one of counting— it is about sequencing clinical, administrative, financial, and behavioral events and measurements in such a way that meaningful questions can be asked and answered.
Notice that these five continents are not dependent on whether an organization is a provider, payer, pharmaceutical, biotechnology, government, or any other specific type of health organization. Despite differing market structures, business models, and incentives, most health care organizations have similar analytical needs: how to identify the best treatments, how to operate more profitably, how to engage customers more effectively, etc. Though the motivations behind undertaking analytical initiatives may vary, the analyses, their corresponding data, and even the analytical models and software that produce the results are comparable.
All of these are examples of how people use descriptive statistics. Descriptive statistics are very useful for doing exactly what their name implies—describing things, answering “what” types of questions. They are much less useful for answering why or how questions. For 3GC03 05/31/2013 12:35:13 Page 37 STATISTICS ◀ 37 those questions, you need inferential statistics, which empower us to explore the relationships between concepts and draw inferences from what we observe. Through inferential statistics, we can test hypotheses, detect correlations between otherwise unrelated entities, and extrapolate beyond our observable data to the unobserved.