Column A. Each "Penalty" is the cost of Initial Treatment in Column B multiplied by the US ratio of admissions to readmissions (Column D). 

1. A Congressional agency, MedPAC, confirms that the penalty per excess readmission [Col A]= "Payment rate for the initial DRG [Col B] ... ×  [Col D] 1 / national readmission rate for the condition" (p.99). 
2. The law and Medicare's explanation have more complex wording, but are equivalent to this multiplication. An example is in this spreadsheet.
3. Congress told Medicare how much to penalize hospitals which have "excess" readmissions, and told Medicare to decide which treatments would face penalties. Medicare chose to apply penalties to the conditions in Table A (see timing). "Excess" readmissions means above the US average, adjusted for patient mix. 

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. 

1. Unscheduled readmissions of Medicare patients, for almost any reason at most Medicare and VA hospitals count in the readmission rate of the hospital where the initial visit happened.
2. Penalties are only charged at hospitals with 25 or more admissions for a condition
3. Some types of admissions are excluded, which exempts them from penalties.

Column D. "US Ratio of Admit to Readmit" is one divided by Column C.

1. American Hospital Association thinks penalties are so large that using Admit as the numerator must be a "technical error" (p.4), but they agree that is what the law says. 

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:

1. $227 million total penalties in 2014, divided by 6,300 excess readmissions per year, since there were 18,902 total penalties in the 3 base years they show
2. $280 million total penalties in 2013, divided by 7,000 excess readmissions per year--20,947 in 3 years shown
3. Difference  between 2013 and 2014 is budget inaccuracy, not real change
4. $420 million total penalties in FY2016 (p.2064), divided by 8,051 excess readmissions per year -- 24,153 in 3 years shown (at 2,666 hospitals, p.2064)

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: 

1. Make all the multipliers 1, not 4 to 21, so each penalty would be smaller, but 
2. Set the standard at fewer readmissions than the national average.
3. If MedPAC's recommendation is adopted, more hospitals and more readmissions would be penalized, and total penalties would be the same (p.101). 
4. With Congress polarized on the healthcare law, amendments seem unlikely.

Note I. Medicare has an interesting map of readmission rates by county and race. Choose readmissions under "measure."
​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

• 20 patients with 15% chance of readmission, so 3 return, and
  
• 20 patients with 35% chance of readmission, so 7 return

If this hospital makes no special efforts, it would have a total of 10 readmissions. Assuming other US hospitals reduce total readmissions 20% as Medicare wants, the new national average and the penalty cutoff will drop to 8, and our hospital above will pay for 2 penalties over the new national average.

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.

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:

• Find Records by pressing Ctrl and F at the same time, and type what you want into the search box. If you know which column it's in, Highlight that column by clicking the letter atop the column, before  you press Ctrl-F, and the search will be much faster.
• Rows start with 1, and Columns start with A. You can move around the spreadsheet with the arrow keys, the page down and page up keys, and the sliders on the right and bottom sides of the window, if they appear.
• Click a Cell and a little window just above the letters at the top of the columns shows you the number or formula in that cell, or Type something new to replace what's there.

Select Records (Filter), such as a State, or Specialty:

1. If small ▼Triangles already appear near the top of each column, skip to step 5. If you don't see triangles, start with step 2.
2. Click the letter at the top of the column showing State, or whichever column you want to select on.
3. Click Data. The Data menu is found alongside File, Home, Insert...
4. Click Filter (you may have to first click Sort-and-Filter). After you click Filter, a small ▼Triangle will appear near the top of the selected column(s).
5. Left-click the triangle, to see a little menu where you can de-select All, then Click the state(s) or specialty(ies) you want. Click OK, and only your state(s) or specialties will appear. You can get the others back, by clicking the little triangle again and selecting All. The little menu under the triangle has its own little slider to go up and down the list; All is at the top of the list.
6. The triangle may hide some of the column heading. You can remove the triangle by again clicking Data, then Filter.
7. To select a range of records, such as costs over $1,000, click Number Filters in the little menu under the triangle in the costs column, then click Greater Than, then fill in $1,000 ($ and comma are optional), then click OK. Number Filters can even give you Between 1,000-2,000, or Top 1 to 500, or Above or Below Average. Sometimes they're called Text Filters, with similar choices.
8. You can filter several columns, like female Pain doctors in Virginia and DC.

Sort in Any Order You Want:

• Choose cells to sort: Highlight any area by left-clicking the upper left corner, then shift-left-clicking the lower right corner, or Drag your mouse from one corner to another while holding the left key , or Click the letter atop any column to highlight a column, or Click the number left of any row to highlight a row
• Click Data at the top of the screen, then click Sort. Answer the questions to expand to all columns or rows. Then you will see a window of sorting choices.
• To keep headings at the top, be sure the box is clicked for "My data has headers"
• Normally it moves Rows up and down to put them in order. Click Options to move Columns right and left into order
• In the Sort By box, click the ▼ triangle, and choose a column (or row) to sort by
• If you want subsorting (such as by state and then by revenue within state), you may need to click Add Level and fill in the second item to sort by
• Click OK. A file over 100,000 records may take a few seconds to a minute to sort, depending on your computer's speed.

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

• Insert a new row to hold the average, by right-clicking the Number to the left of a row, like row 2: On the menu which appears, left-click Insert
• Click a cell in the new row, probably in column T
• Type into that cell (don't forget the equals):  =Average(T3:T50000)

• Include the full range you want, which depends how big your spreadsheet is

• Press enter, the formula should disappear, and a number will appear.
• =Average( ) gives the average of numbers, including zeros, but ignoring blanks. It includes rows you hid with Filter. To do a lot of work on one state, you may want to delete all the others, so your averages or sums are just that state. Save Frequently.
• You can also use =Sum( ) or =Median( ) or many other functions (click Help)

Calculate a Ratio, or Difference Suppose you want the Ratio or Difference of Columns K and L:

• Insert a new column by right-clicking the Letter atop a column: On the menu which appears, left-click Insert
• Click a cell in the new column, on the row where you want the first ratio, such as row 2
• Type into that cell the ratio you want from that row (don't forget the equals): =K2/L2
• Press enter, the formula should disappear, and a number will appear.
• Then put your cursor over the lower right corner of the cell. Your cursor becomes a +; double-click it and blank cells below it will fill all the way to the bottom. Click some of those to see how the formula appears as it goes down the page.
• Formulas can use / * -  + ( ) and many other functions described in Help.
• If cells have too many decimal places, right-click the cell, column or row: On the menu which appears left-click Format cells: In the window of format choices which appear, click Number and the number of decimal places you want, then OK

Summary Tables (Pivot) can count or sum records in categories. For example if you want average revenue by state:

• Select state and revenue columns by left-clicking the letter of the left column, then shift-left-clicking the letter of the right column (every column in the range must have label in first row)
• Excel 2010: Click Insert (or in Excel 2003: click Data) then click PivotTable. Answer any questions, and it will open a new page.
• 2010: On the right side of the screen, drag a category, like State, down to Row Labels or Column Labels. (2003: click a category, then use ▼triangle to add the category to rows, columns, or data.)
• Move any variable, maybe State again, to Values (called Data in 2003). Be sure it appears there as "Count of.." Notice the summary table on the left side of the screen now shows the count of rows for each state
• 2010: Drag a numeric variable, like revenue, to Values. It will develop a little arrow, Left-click the little arrow to choose "Value Field Settings.." and then Sum, Count, Average, Max, Min, etc. (2003: Add a numeric variable, like revenue, to Data. See where it appears on the table as Count of. Right-click it: On the menu which appears, left-click Pivot Table Field and then Sum, Count, Average, Max, Min, etc.)
• The summary table on the left can give you the count of rows in each state, and the average and/or sum of as many variables as you wish, for each state.
• You could also do rows for each type of hospital or other category in your data
• 2010: If the menu of variables on the right side of the screen disappears, click anywhere in the table on the left side of the screen, and the right side will reappear. (2003: A Pivot Table bar floats on the page, with a button on the right end to hide or show the Field List.)
• 2010: If you want some states, but not others, move your cursor to the upper right corner where the state variable is listed. When you point at a variable there, a ▼triangle will appear to the right of the variable name. Click the triangle, then de-select as many states as you wish.

Advanced Formulas

• ^ means exponent so =2^3 means 2 cubed or 8, and 2^.1 means tenth root of 2
• You'll get warnings in cells where you divide by zero. You can avoid them by typing conditions: =IF(condition , result if condition is true , result if false): =IF(sum(L2)<>0,K2/L2," ")
• Excel often objects if you compare text to a number, but the sum of text is zero, which can be compared to a number as shown above. <> means "not equal to"
• When you copy a cell down a column, cell references generally change: K2/L2, K3/L3, K4/L4, etc. If some should not change (suppose L2 is a national average, and you want all the Ks as a ratio to that national average), then put in the first cell K2/L$2, and it will fill down as K3/L$2, K4'L$4, etc. The $ does not affect the value, and does not turn it into cash (which is done with Format Cell). The $ just says not to change 2. Similarly $L2 means to keep L, and $L$2 means to keep both L and 2.
• Besides clicking the bottom right of a cell, you can copy it by using Edit, or highlighting an area and using Ctrl-R to copy to the right, or Ctrl-D to copy down
  
  Why Excel
  This site uses Excel, since Google Sheets are limited to 2 million cells and Open Office is limited to 65,536 rows. The files here have hundreds of thousands of doctors with 20-60 cells for each, so they need the size of Excel or QuattroPro. These instructions cover Excel, since more people have it. You can do the same work in QuattroPro.
  

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): 

• when randomly selecting a card from a deck, the probability of selecting a spade is 13/52 = 25%.
• The odds of selecting a card with a spade are 25%/75% = 1:3.
• Clinicians usually are interested in knowing probabilities, whereas gamblers think in terms of odds...
• Differences between 2 different groups... can be compared using odds ratios [or]... relative risk ratio, which is the ratio of 2 probabilities...
• The odds ratio... can be interpreted as whether someone with the risk factor is more or less likely... to experience the outcome of interest... For example, an odds ratio for men of 2.0 could correspond to the situation in which the probability for some event is 1% for men and 0.5% for women. An odds ratio of 2.0 also could correspond to a probability of an event occurring 50% for men and 33% for women, or to a probability of 80% for men and 67% for women.
• Second, and less well known, the magnitude of the odds ratio... is scaled by an arbitrary factor (equal to the square root of the variance of the unexplained part of binary outcome)... [A]dding more independent explanatory variables to the model will increase the odds ratio of the variable of interest (eg, treatment) due to dividing by a smaller scaling factor.

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.

Hospitals have cut admissions for the diagnoses which face readmission penalties. Most publicity has been about cutting the readmission rate, which they have also done, but that just shifts penalties to other hospitals without cutting the total paid across the US. Especially for large hospital chains, they gain nothing from lower penalties at one hospital if that raises penalties at their other hospitals.

The only way hospitals overall can reduce the national total of penalties they pay is by treating fewer patients. The arithmetic behind this statement is explained here.

The national total of penalties mathematically equals the penalty per excess readmission, times the number of excess readmissions. Excess means above the national average readmission rate.

A. Example of One Hospital

Consider a hospital with a patient mix similar to the national average (adjustments for patient mix are small, so most hospitals end up like the national average). Suppose this hospital admits 500 patients for one of the treatments subject to readmission penalties.

If the hospital readmits 125 patients, it has a 25% readmission rate.

Suppose the national readmission rate is 20%. At this hospital that national rate would have meant 100 readmissions expected.

The hospital has 25 excess readmissions (= 125 ~ 100).

Since readmission rates are fairly well spread above and below the average, close to half of patients are in hospitals with below-average readmission rates, and half are in hospitals with above-average readmission rates. The latter thus have excess readmissions and pay penalties on them. These hospitals face choices described below,

B. Cutting Admissions Cuts the Penalty, for Any or All Hospitals

Suppose the example hospital cuts admissions 4% without changing its 25% readmission rate:

When a hospital cuts admissions (from 500 to 480) while keeping a similar readmission rate (25%) in that smaller pool of admissions, it reduces four important counts:

• admissions (to 480),
• readmissions (to 120 = 25% of 480),
• expected readmissions (to 96, which is 20% of 480), and
• excess readmissions (to 24, which is 120 ~ 96).

Thus they reduce their excess admissions from 25 to 24, cutting their own penalties and the national total of penalties.

If all hospitals cut admissions similarly, they all cut their penalties, even when their readmission rates do not fall.

Data show hospitals have reduced admissions for heart failure, heart attack and pneumonia, and thus reduced the total national penalties.

C. Cutting Readmissions in the Same Way at All Hospitals Leaves All Penalties the Same

Suppose all hospitals, on average, cut readmissions four percent (from 20% to 19.2%) without cutting admissions. They get no benefit, because the penalty per excess readmission goes up; it is controlled by another formula:

The penalty per excess readmission equals the cost of initial treatment divided by the national readmission rate (MedPac June'13 p.99).

For example suppose the initial treatment averages $6,000. A national readmission rate of 20% means a penalty of $6,000 / 0.2 = $30,000. But when the national readmission rate drops to 19.2%, the penalty becomes $6,000 / 0.192 = $31,250.

Suppose the hospital in the example above cuts readmissions 4% (same as the nation) from 125 to 120, without cutting admissions. Now it faces expected readmissions of 96 (= 500 x .192), and has 24 excess readmissions. Its penalty was $750,000 (= 25 x $30,000), and still is $750,000 (= 24 x $31,250).

When admissions stay the same and the national readmission rate goes down, the penalty per excess readmission goes up, and every hospital which manages to cut at the same rate as the nation keeps the same penalty.

D. Cutting Readmissions at Some Hospitals Shifts the Penalty

Hospitals shift the penalty to other hospitals when they cut readmissions. Suppose a hospital cuts its readmission rate by 4% instead of cutting admissions:

If other hospitals on average don't cut their readmission rates, so the national average stays at 20%, the example hospital's expected readmissions do not change (100 = 500 x 20%). The hospital's total readmissions fall from 125 to 120, so excess readmissions drop from 25 to 20, and the hospital's penalty drops 20%.

Now think nationally, where many hospitals cut readmissions. Think of a million patients with 200,000 readmissions (20%).

• (a) 500,000 patients were at hospitals with readmissions below average, and
• (b) 500,000 were at hospitals with readmissions above average. 
• 300,000 each of groups (a) and (b) are at hospitals which cut their readmission rates by an average of 1% of admissions (such as from 25% to 24% of admissions at a particular hospital, or or 19% to 18%), so 6,000 admissions are no longer readmitted.
• 200,000 patients remain at hospitals with excess readmissions which on average make no change in their excess readmissions (some rise a little, some fall a little)
• Hospitals in group (b) which cut readmissions (call them "cutters") saved penalties on 3,000 excess readmissions
• National readmission rate will drop by 6,000 or 0.6% of the million admissions, from 200,000 to 194,000, which is from 20% to 19.4%
• All hospitals face an expected readmission rate which has dropped by 0.6 percentage points (readmissions as percent of admissions at each hospital)
• 500,000 patients at hospitals with readmissions above average (including cutter hospitals) face a lower cutoff for excess readmissions. The cutoff used to be 20% or 100,000, now it is 19.4% or 97,000, which adds 3,000 new excess readmissions, 1,800 at the cutter hospitals, 1,200 at the non-cutter hospitals
• Cutter hospitals cut their net excess readmissions by 1,200, not 3,000
• Penalty per excess readmission will rise from $30,000 to $30,928 (= $6,000 / .194)
• Cutter hospitals pay the higher penalty on all their other excess readmissions. If their 300,000 patients averaged 21% readmissions, which are now down to 20% readmissions, they had excess readmissions 21% ~ 20% = 3,000, and now have 20% ~ 19.4% = 1,800. So penalties dropped by $34 million, from $90 million to $56 million
• If the 200,000 patients at non-cutter hospitals also averaged 21% readmissions, they had excess 21% ~ 20% = 2,000 and now have 21% ~ 19.4% = 3,200, so penalties rose by $39 million, from $60 million to $99 million
• An unknown number of the 500,000 patients are at hospitals with readmissions between 19.4% and 20% which now also have excess readmissions and pay penalties.

Cutting readmissions at some hospitals reduces their penalties, and shifts the penalties to hospitals which did not reduce readmissions as much. Whether the shifting is exact depends on the detailed distribution of readmission rates among the hospitals

E. Other Approaches Do Not Cut the National Total of Penalties

The penalty and national total of penalties could theoretically be reduced by cutting the cost of initial treatment, but Medicare already cuts it as much as they think they can.

Arithmetically the only other way to reduce the national total of penalties is to narrow the dispersion of hospitals below the national rate: raising readmissions in hospitals below the national average. This lets more readmissions be in low hospitals than high hospitals. This does not cause the low-rate hospitals a penalty, and it cuts the number of excess readmissions for high-rate hospitals. No one advocates this or is working on it, and hospitals could not count on it as a strategy.

F. Formulas

US Total =
(penalty per excess readmission) x (number of excess readmissions)

Which is:
(initial payment / readmission rate) x (number of excess readmissions)

Which is:
(initial payment / [total readmissions / total admissions] ) x (number of excess readmissions)

Which is:
(initial payment x total admissions / total readmissions) x (number of excess readmissions)

So US Total =
(initial payment) x (total admissions) x (number of excess readmissions / total readmissions)

The last parenthesis, excess over total readmissions, reflects the dispersion of readmission rates. For example a ratio of 0.04 means the average penalized hospital has 4% more readmissions than the national average.

The ratio of excess over total readmissions has risen for pneumonia and dropped for heart conditions:
2012-15    2008-11
4.06%        3.91%        Pneumonia
3.27%        3.70%        Heart Failure
2.94%        4.07%        Heart Attacks
4.77%                           Hip & Knee Replacements
3.58%                           COPD
3.39%                           Coronary Bypasses

G. Graphs of Heart Failure

The third graph, below, shows excess readmissions. They are the readmissions above the national average rate, between the dark blue and light blue lines in the graph. As discussed at the end of section F, the national total of readmission penalties depends on the ratio of excess to total readmissions. This ratio can be brought down by bringing every hospital's rate closer to the average, as shown with the red dashes. This would mean raising readmission rates at hospitals with below-average rates, which is implausible.

A more plausible alternative of reducing all readmission rates at all hospitals does move down the dark blue and light blue lines, and does not change the ratio of excess to total readmissions, so it does not reduce the national total of readmission penalties.

In the readmissions spreadsheet the dollar penalties for each diagnosis, at each hospital, are estimated by multiplying the number of excess readmissions at each hospital, times the US average penalty adjusted for the local cost level. The US average includes the "Base Operating DRG Payment Amount = Wage-adjusted DRG operating amount + new technology payment, if applicable". DRG stands for Diagnostic Related Groups.

Formal readmissions penalty rules are at 42 CFR 412.152 and 154.

The number of excess readmissions at each hospital, for each diagnosis, derives from two numbers in Medicare's "Readmissions Supplemental File" for the current year:

1. Medicare provides the ratio of each hospital's own readmission rate, to the national readmission rate (adjusted for patient mix): (readmit@hosp/admit@hosp) / (readmit@US/admit@US)
   
2. The readmissions spreadsheet subtracts one from that ratio to get just the excess readmission rate at each hospital (still as fraction of national readmission rate): (excess@hosp/admit@hosp) / (readmit@US/admit@US)
3. The spreadsheet then multiplies by the national readmission rate (readmit@US/admit@US), to get the hospital's own excess readmission rate:  (excess@hosp/admit@hosp)
4. The spreadsheet then multiplies by the number of admissions at the hospital (also provided by Medicare, in the same file) to get the number of excess readmissions at the hospital: (excess@hosp)

Medicare's full payment calculation is described in the Payments section. For the local cost level at each hospital, the readmissions spreadsheet calculates a weighted average of 2 numbers, which Medicare provides in the "Impact File" for the current year:

1. Wage index for labor-related share of operations
2. Cost of living factor for nonlabor share of operations (1 except in Alaska and Hawaii)

Besides dollar estimates described above, the readmissions spreadsheet also shows penalties as a percent of hospital revenue for each of the 6 diagnoses affected. Section F below explains how this is estimated.

In the financial spreadsheet the total readmission penalty at each hospital is Medicare's Readmissions Adjustment Factor times each hospital's "wage-adjusted DRG operating payment plus any applicable new technology add-on... [including] adjustment for transfers" (42 CFR 412.152), same base as VBP, with a different adjustment factor. Subtotals for the 5 diagnoses are based on the national cost of treatment and each hospital's excess readmissions, as shown in the readmissions spreadsheet.

The dollar amounts of VBP penalties and bonuses in the financial spreadsheet are estimated by multiplying a VBP Adjustment Factor times Medicare's "wage-adjusted DRG operating payment plus any applicable new technology add-on... [including] adjustment for transfers" (42 CFR 412.160, DRG means Diagnostic Related Groups). Medicare's public financial statements do not separate DRG into operating and capital, so the spreadsheet finds what percent is operating at each hospital, generally 93%.

Medicare provides the Adjustment Factors in .zip files, and calculates them from several measures (pdf item 25). The percent adjustments are scaled so the worst penalty is no more than 1.5% in FY 2015, 1.75% in 2016, 2% in 2017+, and the total bonuses equal the total penalties. After Medicare's correction, the actual range in 2015 was from a 1.24% penalty to a 2.09% bonus.

Formal VBP rules are at 42 CFR 412.160 to 167.

This "Value Based Purchasing" applies to hospitals, and is not the same as the "Value-Based Payment Modifier" also called "Value Modifier," which applies to doctors and doctor groups.

Electronic health records are problematic, since they have enabled vast breaches of medical privacy for 30,000,000 patients. Great systems are rare, though ideally they would show key information clearly in the way that each clinician needs it. Bad systems are not read by clinicians, are full of errors, generate erroneous prescriptions, and interrupt doctors when listening to patients. (Thoughtful article on referrals and funny video.) Electronic records often send prescriptions to pharmacies electronically, but far fewer can send a cancellation order to correct a mistake or cancel refills. Only a third of prescribers and 40% of pharmacies ​use software certified to handle cancellations, so only about 13% of cancellations can be expected to go through. Pharmacies often generate refills automatically, so patients can get undesired medicine for long periods, thinking their doctor ordered it.

Finding electronic records for a patient is hard, since most names and birth dates are common. Other items like address, phone number, and insurance number can change. All items can have typos. Addresses can be abbreviated many different ways. Some people do not want to give their Social Security numbers, which can have typos too. In the last 100 years, there are only 36,500 unique birth dates. Some names are more common than that, and even names held by just a few thousand people can have common birth dates, since some names were common in some years. Medical systems try to avoid matching you to anyone else's records, so they may not match you to your own records if there is any ambiguity. Study by Pew.