Using Data on Healthcare Processes

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You work at Holy Mercy Hospital as the health information department manager. The hospital’s quality manager comes to you with a question. The Centers for Disease Control has just changed recommendations for tetanus booster immunizations (Td) in adults. Instead of every 10 years for adult booster immunization, the CDC now says every adult patient admitted to a hospital for surgery should have had a Td booster in the past 4 years. (NOTE: This policy change is fictitious, used only for the purposes of this exercise.)

Your quality manager knows that you, as health information manager, have data on hospital admissions and might have information in the records on immunizations. She wants an informative report, not just the raw data. You will develop this report on a historic sample of patients to predict possible effects of this policy.

At first, you scratch your head. It could take a long time to count back days from the hospital admissions. You figure out you need to compare the hospital admission date with the tetanus immunization date. You check your data. Fortunately these data are saved as date fields. You should be able to compute the information.

Your task:

Adult patients are those over age 18. For the purposes of this analysis, assume that all patients in the database were surgical patients.

  1. Download the Patient Information Excel datasheet for the sample of patients.
  2. Open the spreadsheet.
  3. Add one column on the right called Days Td to Admit. Add another column to its right called, Years Td to Admit.
  4. Compute the Days Td to admit by subtracting Tetanus Date from Admission Date. Compute the Years Td to admit.
  5. Determine which patients and how many would not have complied with the new policy because their boosters were not recent enough. What is the rate of patients out of compliance, as a percentage of the total sample? Remember to exclude children.
  6. Create a new worksheet in the Patient Information Excel datasheet and prepare a table of patients who would be out of compliance, including patient names, birthdates, admission dates, and number of years Td to Admit for the quality manager. Indicate this information was from a sample, not the entire hospital.
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