Table A. Readmission Penalties, Paid by Hospitals, for Six Conditions
Column A. Each "Penalty" is the cost of Initial Treatment in Column B multiplied by the US ratio of admissions to readmissions (Column D).
Column B. The "Average Base Payment" is an average of Medicare's detailed payments, by diagnosis from October 2014 to September 2015 (FY 2015). There are different payment levels for patients with and without other unrelated illnesses, and the average payment here is weighted by the number of patients having each payment level.
Column C. "US Average Readmissions" above were updated in Hospital Compare 26 July 2017.
Column D. "US Ratio of Admit to Readmit" is one divided by Column C.
Column E. "Each Condition" is the total of Medicare's counts of admissions, by diagnosis
Note F. Medicare does not provide as much detail as this table, but its data support an estimate of $52,000 average penalty per excess readmission in 2016, $36,000 in 2014 and $40,000 in 2013:
Note G. Medicare adjusts readmission rates for patient mix at each hospital, to level the playing field, but the adjustments have a very poor fit, explaining only 3-5% of the variation in readmissions.
Note H. MedPAC looked at the multipliers (shown in Column D), and recommended the law should change to:
Note J. Penalties for each hospital depend on constants in Table 1, and factors for each hospital in the Impact file each year.
Patients come to hospitals with a range of conditions which might bring them back later. Medicare provides software to predict which are most likely to come back.
To see how hospitals are affected, here is a simple example of
To reduce readmissions, a hospital needs to put effort where it has the best chance of reducing them. Working on the 20 patients who have 3 readmissions among them has little payoff. Working on the other 20, who have 7 readmissions among them, has a much better chance of avoiding some readmissions.
Part of the effort will be to cure patients well and refer them to good follow-up care. This has limited potential, because hospitals have little influence on patients after they leave.
An additional approach is to convince patients not to seek treatment any more, and hospice groups vocally support this direction. Every extra health problem raises the patients' odds of readmission and also raises their vulnerability to pressure for comfort care, "Do Not Resuscitate" orders and hospice. The line between appropriate advice and inappropriate pressure is easy to cross when hospitals have strong financial incentives.
This page first discusses Excel, then statistics in general near the bottom of the page.
Help with Excel
This is a simple introduction to some Excel commands which are helpful with the large spreadsheets of medical data on the site. The commands here work in Excel 2010 and Excel 2003.
When you open an excel spreadsheet from the web, it may ask if you want to "enable editing." You'll need to say Yes to make any changes in your copy, or to "find all" entries of a certain type, or filter, or sort.
If the spreadsheet was slow to download, click File/Save As a couple times with new names, so you can get back to the original version without downloading again.
If you need extra help, many people who work in bookkeeping or finance are good with Excel spreadsheets, or you can search the web.
Basics. Most of you already know these:
Undo a Sort or anything: press Ctrl and Z at the same time. You can do this repeatedly to back up to previous versions, sometimes as far as the last time you saved the file
Save Frequently, with new names, so you can go back to previous versions if you need to.
Calculate an Average or Sum: Suppose you want Average of Column T
Help with Statistics
For subscribers, AMA has advice for using statistics with large data files, a checklist, a series discussing medical databases, and an article comparing "odds ratios," probabilities, and "relative risk ratios" (emphasis added):
There are excellent articles on statistical analysis of health data in the British Medical Journal, though it requires a subscription, which you may find at a university or hospital library.
A. Example of One Hospital
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