Statistical Inference 3 Springboard

A. Initial observations based on the plot above Overall, rate of readmissions is trending down with increasing number of discharges With lower number of discharges, there is a greater incidence of excess rate of readmissions (area shaded red) With higher number of discharges, there is a greater incidence of lower rates of readmissions (area shaded green)

B. Statistics In hospitals/facilities with number of discharges < 100, mean excess readmission rate is 1.023 and 63% have excess readmission rate greater than 1 In hospitals/facilities with number of discharges > 1000, mean excess readmission rate is 0.978 and 44% have excess readmission rate greater than 1

C. Conclusions There is a significant correlation between hospital capacity (number of discharges) and readmission rates. Smaller hospitals/facilities may be lacking necessary resources to ensure quality care and prevent complications that lead to readmissions.

D. Regulatory policy recommendations Hospitals/facilties with small capacity (< 300) should be required to demonstrate upgraded resource allocation for quality care to continue operation. Directives and incentives should be provided for consolidation of hospitals and facilities to have a smaller number of them with higher capacity and number of discharges.

Preliminary report was read, Null and Alternate Hpothesis was set up, observations for hospitals with < 100 Dicharges and hospitals with > 1000 discharges were grouped, A t-test and joint plot was used to ome up with conclusions

1. Markdown syntax: http://nestacms.com/docs/creating-content/markdown-cheat-sheet
2. Experiment information and data source: http://www.povertyactionlab.org/evaluation/discrimination-job-market-united-states
3. Scipy statistical methods: http://docs.scipy.org/doc/scipy/reference/stats.html
4. Markdown syntax: http://nestacms.com/docs/creating-content/markdown-cheat-sheet
5. Formulas for the Bernoulli distribution: https://en.wikipedia.org/wiki/Bernoulli_distribution