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Preventable hospital stays and Medicare spending per enrollee

Where Preventable hospital stays is higher, Medicare spending per enrollee tends to be higher. The link is weak: +0.36 across 3,048 counties, on a scale from −1 (opposite) to +1 (in step). That figure compares places with the same population density, income and education, so those differences can't explain it. It holds inside states too. Measured separately within each of 39 states, the middle value of the link is +0.31.

Holds after adjusting

Every place, plotted

One dot for each place reporting both measures. Hover over or tap a dot to see its name and values. The thin line is the straight line that best fits the dots. The bold line, shown for counties, is the link after adjusting for density, income and education. A dot far from the lines is a place that does not follow the pattern.

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What each measure is

Preventable hospital stays

Hospital stays per 100,000 people on Medicare for illnesses that good care from a regular doctor should have prevented. It measures access to care, as seen through hospital stays.

County Health Rankings · County Health Rankings v005

Medicare spending per enrollee

What Medicare spent per person in a year, for people in traditional Medicare, where Medicare pays each doctor and hospital bill itself. Medicare pays more for the same care where wages and rents are high. This figure takes those price gaps out, so it shows how much care people used, not what it cost locally. It is not adjusted for how sick people are. It leaves out people in private Medicare Advantage plans.

CMS Medicare Geographic Variation Public Use File · CMS Medicare Geographic Variation PUF, national/state/county, all ages, TOT_MDCR_STDZD_PYMT_PC

Highest and lowest

Where each measure is highest and lowest among the places reporting both (2023), with the other measure beside it. This is shown for every size of place where both are published. Metro-area values are added up from their counties. A measure that cannot be added up across counties, such as a middle value (median), has no metro figure. Counts are shown per 1,000 residents, since raw totals would only list the largest places. Cities and towns and ZIP codes are shown where the Census survey or the CDC publishes them; most other sources stop at the county. They are shown for places of 5,000 residents or more, and only where the survey’s margin of error is small enough for the figure to be usable. The CDC publishes its health estimates for cities in a version adjusted for age, so places with older or younger people can be compared fairly, but not for ZIP codes.

Counties

By preventable hospital stays

Preventable hospital staysMedicare spending per enrollee
Highest
Mingo County, WV10,32211,041
Logan County, WV9,81311,303
Claiborne County, MS9,00616,895
Monroe County, KY8,90210,920
Conecuh County, AL8,85111,929
Lowest
Beaverhead County, MT1339,843
San Miguel County, CO2216,774
Bristol Bay Borough, AK33410,406
Grant County, OR3419,127
Pitkin County, CO37511,090

By Medicare spending per enrollee

Preventable hospital staysMedicare spending per enrollee
Highest
Miller County, GA4,15527,129
Hamilton County, KS2,54524,463
Greer County, OK4,49422,580
Oglala Lakota County, SD2,13221,799
Upton County, TX2,13820,975
Lowest
Arthur County, NE2,3296,331
Southeast Fairbanks Census Area, AK1,1356,465
Boundary County, ID6716,576
Hanson County, SD2,0486,656
Billings County, ND3,0796,729
States

By preventable hospital stays

Preventable hospital staysMedicare spending per enrollee
Highest
West Virginia3,93811,334
Louisiana3,42713,805
Mississippi3,35613,474
Kentucky3,33611,853
Alabama3,32712,787
Lowest
Hawaii1,5178,203
Utah1,53511,400
Idaho1,5439,990
Colorado1,69510,671
Montana1,7729,198

By Medicare spending per enrollee

Preventable hospital staysMedicare spending per enrollee
Highest
Louisiana3,42713,805
Oklahoma2,97913,690
Florida3,07413,686
Mississippi3,35613,474
Texas2,96813,288
Lowest
Hawaii1,5178,203
Oregon1,8029,019
Alaska2,0399,082
Montana1,7729,198
Vermont2,1309,315
Metro areas

By preventable hospital stays

Preventable hospital staysMedicare spending per enrollee
Highest
Durant, OK7,20916,536
Dubuque, IA6,3918,984
Moultrie, GA6,05313,248
Charleston-Mattoon, IL5,70711,507
Douglas, GA5,46011,382
Lowest
Baker City, OR5678,175
Breckenridge, CO7468,521
Steamboat Springs, CO8818,773
Bedford, IN91611,556
Hailey, ID9959,883

By Medicare spending per enrollee

Preventable hospital staysMedicare spending per enrollee
Highest
Bogalusa, LA4,75617,954
Rio Grande City-Roma, TX4,46017,395
Vernon, TX3,74017,093
Alice, TX2,99416,760
Durant, OK7,20916,536
Lowest
Fairbanks-College, AK1,2867,065
Hilo-Kailua, HI1,7167,474
Kapaa, HI1,6977,492
Sheridan, WY2,5727,495
Kahului-Wailuku, HI1,2587,870

Counties furthest from the pattern

Compared with the straight line that best fits all 3,061 counties: the five with far more Medicare spending per enrollee than their preventable hospital stays would suggest, and the five with far less.

Preventable hospital staysMedicare spending per enrollee
Above the line
Miller County, GA4,15527,129
Hamilton County, KS2,54524,463
Oglala Lakota County, SD2,13221,799
Upton County, TX2,13820,975
Greer County, OK4,49422,580
Below the line
Mingo County, WV10,32211,041
Logan County, WV9,81311,303
Emmons County, ND4,9847,870
Dubuque County, IA6,3918,984
Grant County, ND8,36110,514

Two series, one county

Both measures over time for a county you pick. The two charts are stacked, so they share only the years along the bottom. You can pick from the thirty largest counties reporting both. This panel covers 2010–2024, and a measure published only once shows as a single dot.

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Every version of the link

Each row measures the same link, from −1 to +1, in a different way. If the rows mostly agree, the link does not depend on one choice of method.

Before adjusting for anything+0.4353,048 counties reporting both
After adjusting for density, income and education+0.365the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size+0.361size taken out as well as density
Also comparing only within each state+0.282each county is compared only with others in its own state, so this is no longer a comparison between states
Giving bigger counties more weight+0.365the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 282 equally weighted counties
Middle value inside single states+0.311the link worked out inside each of 39 states with at least 20 counties reporting
Using ranks, after adjusting+0.391uses each county’s rank, not its value, so a few extreme counties cannot create the link

How much to believe it

Could it be chance?

The p-value is the chance of seeing a link this strong if there were really none. A value of 0.05 or less means the link is unlikely to be chance. Very small values are written in short form: 3.1e-16 means 0.00000000000000031, and the bigger the number after “e-”, the smaller the value. Treating every county as a separate case gives p = 2.5e-96. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 9.1e-8. The site tested 29,403 pairs, and testing so many turns up some flukes. The q-value allows for that too. For this pair it is 2.4e-95.

Do nearby places look alike?

Moran’s I measures how much nearby places look alike: 0 means no map pattern, and higher means neighbours are more similar. For the part of each county that the adjustment leaves unexplained, it is +0.50 (p = 0.001). That unexplained part still clusters on the map. So some regional factor shared by both measures is not accounted for.

Did they change together?

The figures above compare counties at one moment. This asks a different question: where preventable hospital stays rose most, did Medicare spending per enrolleemove too? Each county’s change is compared with the average change in its own state. That takes out ups and downs that hit a whole region at once. Each change is the gap between two estimates that both contain some error. That error pulls these links towards zero, so a weak one is weak partly for that reason. The q column shows whether a link could be a fluke, allowing for the many pairs tested: 0.05 or less means it is unlikely to be chance.

PeriodCountiesChange togetherWithin statesq
2014–2019 the main test: each Census survey figure averages five years, and these two do not overlap; before the pandemic————
2019–2023 a repeat check: its two five-year survey figures both include 2019, and it covers the COVID years3,050+0.17+0.156.1e-7

Measured over the nearest years published: Preventable hospital stays: 2019–2022 for the 2019–2023 row.

Not measurable over the main period, so only the second period is shown. How change is measured.

Related pairs

Association only. Nothing here shows that either measure changes the other. This describes counties, not the people in them. Two measures going together across places does not mean the same people have both. How the US county data works · Explore Preventable hospital stays and Medicare spending per enrollee