Group Case 1: Patient No Show Data

Group Case 1: Patient No Show Data

Patients not showing up for an appointment impose a significant cost on health providers. By some estimates, patient “No-shows” are as high as 30%. A consulting firm is working on trying to improve the efficiency of doctors’ offices. For this assignment, you will need the file NoShow.xls. It contains a sample of doctor’s visits with three variables: patient’s age, whether the patient was a No Show, and whether they received a text message reminder. No shows also include late visits since when a patient is too late, they often need to be rescheduled. For this assignment you may ignore age.

The issue(s): The consultant wants to inform doctor’s offices on how best to reduce No-shows. To do so, you want to know whether text messages are effective in reducing no-shows.

Use the data and the tools in module 1, to inform the consultancy on the above issue.

To help you, I have provided some questions to help you get started.  KEEP IN MIND THAT IN THE “REAL WORLD” YOU WON’T BE GIVEN SUCH QUESTIONS. SO, YOU WILL NEED TO LEARN TO START THINKING IN THIS WAY ON YOUR OWN. You can start the assignment this week, but you will not be able to answer all the questions until you have watched next week’s lectures.  

Questions:

1. Provide an estimate of the probability (or percentage) of patients who are no shows.
2. Graphically provide a summary of Now Shows
3. Use a tabular method (table) to describe the relationship between the variables: Now Shows and Text.
4. Use your answer to (3) to study how closely No Shows are related to Text. I.e. Do Text messages improve No Shows?
5. How does the concept of conditional probability aid your analysis of 4?
6. Provide an interval estimate of the probability of No Shows.

Deliverable

Write up a 1 to 1 ½ page statistical report that summarizes your findings. Please submit 1 pdf file/group by copying and pasting graphs, tables etc., from excel into a document and converting to pdf. The summary should:

(a) broadly follow the 7-step process outlined in Lecture 1 of this course,

 (b) clearly depict all figures (include labels and legends for axis in graphs),

 (c) Correctly use the data describe the issue

  (d) Offer a conclusion/decision as to whether text messaging is a good way to reduce No Shows.

For a sample on how to write such a statistical report see the file Sample Case Reports.

This assignment is 40 points (out of a total of 200 points).