0:04

this week, us news & report

0:08

it's list the hospitals for 2022

0:10

every year, the publication

0:12

attempts, to rank and rate healthcare centers

0:14

in country it's a monumental

0:17

for data journalist been harder and his

0:19

team, ranked

0:21

hospitals is by studying tens

0:23

of millions of receipts of the federal government receives

0:26

from the several thousand us hospitals

0:28

in each year, did work drawers,

0:30

both praise and criticism depending

0:32

where a might on the list, it

0:35

also raises a lot of questions like

0:38

how do you compare very different kinds

0:40

of hospitals and had he

0:42

get people to trust rankings some

0:45

people don't trust them and some

0:47

argue that they do more harm than good doctor

0:50

care and doing metics of washington university

0:52

in st louis as raided the raiders

0:55

they'd she's skeptical

0:57

even with all the data in the world's you

0:59

couldn't get it right

1:02

from the for economics radio network mrs

1:04

economics md i'm bob agenda

1:07

i'm an economist and i'm also medical doctor

1:09

episode i dissect

1:11

an interesting question at the sweet spot between

1:13

health and economics today

1:16

on the show were going to talk about hospital

1:18

rankings what are they get rights

1:20

and would have they get wrong when it comes

1:22

to hospital quality will talk

1:24

to been harder about how he tries to

1:27

get an accurate picture of what hospitals

1:29

are doing and to care and joint metics

1:32

about why that's so hard to

1:47

then harder i'm the cheese health

1:49

analysis of us news world report i

1:52

am a data journalist by background with

1:55

data journalism were focused on understanding

1:57

how data can shed light on the questions

1:59

sting it's not all that different actually

2:02

than being a healthcare economists perhaps

2:04

i'm and maybe a little bit more of us you know

2:06

a one trick researcher because we've been doing

2:09

the same study for thirty three years every

2:11

year since ninety ninety us news

2:13

and world report has released it's list of

2:15

best hospitals around the country there's

2:18

the on a rope which designates the twenty

2:20

highest performing hospitals overall

2:23

then , are rankings for particular specialties

2:25

like cancer and orthopedics hospitals

2:28

are also rated on how are they perform certain

2:30

procedures and treat certain conditions

2:33

then harder has been overseeing the us

2:35

news best hospitals list for more than twelve

2:38

years a lot has changed in medicine

2:40

during that time and then and his team

2:42

have tried to keep this year

2:44

that includes a new rating that almost every

2:46

hospital will be paying attention to but

2:49

first i had a really straightforward question

2:52

the hospital rankings for

2:56

the for consumers and the reason hostels pay a

2:58

lot of attention to them is that consumers by lot of attention

3:00

to them were helping them make data

3:03

informed decisions when decisions called patient decision

3:05

support we don't have

3:07

decision support for better things we do right

3:10

what is it about hospital care that you think

3:12

is fundamentally different medicine,

3:15

black art to average where

3:17

is most us would feel comfortable rating

3:20

the swim goggles we got on amazon

3:22

when it comes to healthcare,

3:24

it's more challenging it's

3:26

hard for an individual patient to tell did

3:28

i get the right care? did i get the right care the right

3:30

time and the right place that's why

3:33

we can bring these other data sets and these other

3:35

methodologies to provide them with a more comprehensive

3:37

and see how do envision

3:39

actually using these rankings quick

3:42

question? so most healthcare is delivered locally

3:45

and it should be a few nida few nida

3:47

or even heart surgery there is most

3:50

likely hospital in your community or nearby

3:52

that will be a good choice for you we are

3:54

not looking to send people traveling

3:56

across the country for routine care certainly

3:59

griffey limits or choices than

4:02

our health insurance can also limit our choices

4:04

in certain ways we're using medicare

4:06

data and medicare beneficiaries

4:09

do actually have quite a bit of hospital choice

4:11

even within their region

4:13

or their community than soon

4:15

want to make sure that when they're choosing

4:18

they understand which hospitals have strong

4:20

quality in the service a need and which ones

4:22

may not have the same strain

4:24

would you do the hospital rankings how

4:27

do you make sure that what you're doing is in

4:29

line with what the most recent

4:31

evidence a methodological

4:33

knowledge is i read a

4:35

lot of medical journals particularly those that

4:38

focus on hospital quality and understanding

4:40

variations and care and disparities and care

4:43

i also talk to academics to researchers

4:45

who have studied the sorts of data that we study we

4:48

learn a lot from them we also talked

4:50

a lot to hospital leaders what i

4:52

think it's sort of a purity on steroids

4:54

rights we polish our methods

4:56

openly and then we take feedback from anybody

4:59

wants to give it com a little bit about the

5:01

methods that you use so

5:04

the way we rank hospitals is

5:06

by studying tens of millions

5:08

of receipts as a federal government receives

5:10

from the several thousand u s hospitals

5:12

each year so every time

5:14

a person who has medicare as their insurance

5:16

guess hospitalized possible charges

5:18

the us taxpayer for their care and then

5:21

we at u s news get a copy

5:23

of the resulting receipt those receipts

5:25

give us important details of a to patiently now old

5:27

they are we know what diseases they had we know

5:29

what procedures doctors used to treat them we

5:32

know what happened to them after they were discharged from hospital

5:35

so you might think at first well receipts

5:37

that doesn't sound very helpful in understanding

5:39

hospital quality but it's actually very

5:41

powerful tool and i think an analogy might

5:44

help your listeners here imagine for imagine moment

5:46

that you had millions of receipts

5:48

for meals eaten in various restaurants one

5:52

family of four goes the same restaurant every friday

5:54

night and they get a couple cheeseburgers and a couple

5:56

adams of a kids' menu but every

5:58

friday like clockwork they go back to the same restaurant

6:01

and they were a cheeseburger you ,

6:03

infer that their family likes that she's birds

6:06

and multiply that across across

6:08

of families and you're pretty quickly

6:10

get an idea of which restaurants

6:13

make good cheeseburgers and which ones

6:15

which imagine a couple numbers

6:17

the same family go to different restaurants once

6:19

a year on the same date and

6:21

a splurge on multi course meal and a pricey

6:24

bottle of wine he can picture of

6:26

that restaurant already from just the behavior

6:28

of the diners who are using and and what they do

6:30

their in both cases you get a sense

6:32

of what kind of meal the restaurant serves

6:34

what kind of clientele it might have just

6:37

from studying the receipts and when you add millions

6:39

of data points like that together if

6:41

you analyze them in analyze thoughtful

6:44

and sophisticated way you can and for

6:46

can great deal about which hospitals

6:48

are good and what they're good good

6:52

i feel like there is a difference though between

6:54

that analogy the and

6:57

how something like that gets operationalize

6:59

in the real world you know we have things like

7:01

yeah they provide consumer

7:04

base reviews of restaurants

7:06

but that's different than what you do because you're

7:08

tried to actually measure the quality of hospital

7:11

a hospital be when we're evaluating

7:13

hospitals we ask not just which

7:15

hospitals are good but what they're good at right so

7:18

if a patient needs knee replacement

7:20

for example we want to identify which

7:22

hospitals are likely to get the best outcomes

7:24

for them lowest cancer mortality

7:26

lowest chance of ending up in the emergency room the

7:28

next day most chance of an infection

7:31

resulting from the surgery we

7:33

also look at patient experience there is actually a national

7:35

survey of patients who have been

7:37

in hospitals that is conducted by the

7:39

federal government and so we take into account

7:42

whether patients tend to have a good experience or

7:44

bad experience in a particular hospital so

7:46

there's actually a number of different organizations

7:49

including the federal government through centers

7:51

for medicare medicaid services cms

7:53

death rate hospitals i'm

7:56

curious as to how the us

7:58

news approach differs

8:00

from cms and other ranking

8:02

system

8:03

we use some of the same data

8:05

that cms uses and yet we

8:08

do arrive at quite different answers about

8:10

hospital quality and some cases and

8:12

i think there are a couple of reasons for this for one thing us

8:14

news focuses on specific services that

8:17

hospitals provide so we build

8:19

several different indicators of quality around

8:21

a particular service a heart attack or stroke

8:23

care and evaluate does hospitals in

8:25

that service lines cms takes

8:28

a broader approach looking at a bunch

8:30

of different measures and and i'm wishing them

8:32

together into an overall assessment

8:34

which i think is less meaningful for patients

8:36

because it doesn't help them make the decision that they're facing

8:38

which is where i go to get care for the thing it's

8:41

ailing me the other

8:43

differences that we get lots of input

8:45

both from researchers and from

8:48

clinicians and hospital leaders as

8:50

a result we've really been able to refine our

8:52

methods of are many years or setting

8:54

cms has a bit more inertia when it comes

8:56

to making improvements to methodology

8:59

and any one of the limitations that

9:01

cms has to deal with his that's

9:03

it as a bunch of measures that it uses that are

9:05

not very strong measures they actually probably

9:08

provide misleading information about hospital

9:10

quality an example of this would

9:12

beat infection rates you

9:16

think infection something you wanna avoid

9:18

hospital that for put a higher rate

9:20

is a horse hospital makes sense

9:22

but in fact what the evidence shows is that

9:25

hospitals that report higher

9:27

infection rates are tracking there

9:29

and sections better and actually seem to be making

9:31

more progress at reducing infections

9:33

or some other hospitals may think they have low infection

9:36

rates and they tell the government they have one section

9:38

rates that actually they've got rating problems

9:40

with infections that they're just unaware of and

9:42

they're not doing anything to remediate when

9:45

i look at the hospital rankings i sort of thing

9:48

is there really there really difference to me between

9:50

her husband strength two or three vs

9:53

six or seven am curious what

9:55

do big as a discriminatory ability of

9:57

the rankings yeah that's a great question

10:00

i would not make much of the difference between

10:02

the number five a number six hospital or the number

10:04

thirty a number thirty one hospital any

10:06

specialty we identify safety best hospitals

10:09

and we are quite convinced that those

10:11

city hospitals are significantly

10:14

better than your average hospital

10:16

that you might go to for similar care now

10:18

is the sixty first hospital any difference on the top

10:20

fifty maybe not the thresholds

10:23

are somewhat arbitrary but

10:25

i think the rankings give people some

10:27

continuous information that is

10:29

useful for most you're a stick standpoint the at

10:31

the top ten are really really good and

10:33

the toxicity of are exceptionally good too

10:37

in issues rankings your including

10:39

a new health equity measurement

10:41

how did it change rankings

10:42

social disparities racial disparities

10:45

economic disparities are the

10:47

most important issue of the day when it

10:49

comes to evaluating healthcare patience

10:51

and a being assigned in a sense to different hospitals

10:54

whether you consider that patient choice or

10:56

in a result of historical

10:58

structural racism in contemporary special racism

11:01

that pushes certain types of patients

11:03

away from some more spit on there is

11:05

a great deal of segregation by dimensions

11:08

of race of the socio economic

11:10

status of language within

11:12

our healthcare system today even though hospitals

11:14

have been forbidden from being segregated

11:16

from more than fifty years as a result

11:19

there's a great deal of opportunity

11:21

for hospitals to be miss

11:23

measured if you're not taking appropriate

11:26

accounting of the differences

11:28

in these disparities in a

11:31

tree and have you gotten

11:33

any feedback already from how systems

11:36

about this measure ah we

11:38

have gotten feedback from health systems and just to be

11:40

clear about this it's not a factor in

11:42

our rankings in the sense that are on a roll

11:44

is not yet influenced by these

11:46

health equity measures are we are naming

11:48

names here we're looking at different

11:50

dimensions of disparities and

11:53

over time we will better understand what

11:55

component of these disparities is

11:58

attributable to the hospital so for

12:00

example this year we have

12:02

identified by hospital the

12:04

, disparity and outcomes for

12:06

a number surgical conditions so

12:09

if a patient has a knee replacement surgery

12:11

for example or a colon cancer

12:13

surgery it's are they more likely to end up

12:15

needing to come back to the hospital for fall

12:17

of theres they're black than if they're whites that

12:20

disparity exists across the

12:22

country and someone who's actually worse

12:24

at the honorable hospitals it's

12:26

clear that across the nation

12:29

these disparities are deeply

12:31

entrenched very prevalent and they certainly

12:33

need to be addressed into why have those

12:35

health equity measures that you're reporting not

12:38

made it into the honor roll rankings u

12:41

when they're mature they will be okay we're

12:43

still working on them were still taking

12:45

feedback from researchers and members

12:48

of the public and hospital leaders

12:50

the i think some hospitals have said when

12:52

we point out hey your patient populations

12:55

much wider and much wealthier

12:57

than the surrounding community is it will

12:59

we really can't help that it's the patients twists

13:02

and on some level that may be true but

13:04

i think it's important to understand why

13:07

er patients choosing perhaps to go

13:09

to one hospital or another and if they're

13:11

black and they tend to go to this hospital

13:13

and not that hospital why is that

13:16

the mean is it gonna be the case at hospitals that

13:18

for gay well will fall

13:21

in their ranking somewhat depending on how much you wait

13:23

that equity measure some , them well

13:25

some of them or not but i think

13:27

that more important impact is that by

13:29

making it transparent to the public

13:32

making it matter to hospitals that

13:34

we can help drives health care as

13:36

a hole in the right direction direction

13:38

year when we first debuted our

13:40

health equity measures i spoke

13:43

with the ceo bottom medical center kate walsh

13:46

on medical center's not necessarily medical center's their foreign

13:48

dignitaries fly to but and trees and incredibly

13:50

diverse population avast and residents and

13:53

is waiting rooms with a lot different than the waiting

13:55

rooms and neighboring hospitals and so i asked her

13:57

why by the medical center

14:00

was black latino immigrant

14:02

patients at a higher rate than these other hospitals

14:04

and she said you know it's not because were easier

14:06

to get to tell because we're closer to their home

14:09

it's because we have translators for immigrant patience

14:11

is because we pride three a food supply

14:14

for families you're experiencing food insecurity

14:16

it's because we help find jobs for

14:18

patients are unemployed and addressing those

14:20

social determinants of health is something that

14:22

is really important to many patients so

14:24

i think awesome make choices to and they can

14:26

make choices to create the right

14:28

opportunity to draw the patients that they want the sir

14:31

then harder

14:33

and his team at us news and world report

14:35

are trying to help people decide where

14:38

to get the best care they're also

14:40

trying to says quality in medicine it's

14:42

not easy work and been know there are always

14:44

be think they can do better

14:46

coming up a hospital rankings

14:48

and ratings are imperfect do we need they

14:51

come to really different decisions

14:52

that which hospitals are best which i

14:55

think points out that trouble with the whole

14:57

enterprise really i'm bob regina

15:00

and mrs freakonomics mvp

15:14

the us news and world report's best hospitalist

15:17

or twenty twenty two was published this

15:19

week and this year the top

15:21

five include mayo clinic in

15:23

minnesota and number one followed

15:25

by cedar sinai medical center in los

15:27

angeles and why you llangollen

15:30

hospitals in new york

15:31

revealing clinic in ohio and

15:34

then johns hopkins hospital in baltimore

15:37

did u c l a medical center tied

15:39

for fifth see see these rankings

15:42

out rankings the world

15:42

then you want to use them as a consumer but

15:45

at the same time since quality measurement

15:47

is what i study it made

15:49

me wonder a lot about what are the things that actually

15:51

underlie these rankings why are they

15:53

like they are and should they be that way that's

15:56

doctor karen joint metics a cardiologist

15:58

and researcher at was

15:59

in university in st louis

16:02

he thinks a lot about hospital quality

16:04

how to measure it had a improve it then

16:07

she thinks a lot about hospital rankings

16:09

you heard in my conversation with

16:11

been harder the us news isn't

16:13

the only organization measuring

16:15

and comparing hospitals

16:17

the government run centers for medicare

16:19

and medicaid services the issues his

16:21

own waiting

16:23

who did a private company healthgrades and

16:25

the nonprofit watchdog leapfrog

16:28

between eighteen carat and some colleagues

16:31

published a review of those for raking

16:33

systems code reading the

16:35

raiders it was important work

16:37

that has race as many questions as

16:39

it tried to answer including

16:41

this one the you trust the rankings

16:44

than a scale of one to ten how much would you trust them

16:47

that where the us news rankings

16:49

see it six

16:51

okay but let me is unpack that a

16:53

little bit summer so i

16:56

don't think that looking at the difference between

16:58

who ranks number two in here semper fi

17:00

as on those rankings is meaningful comparing

17:03

hospitals in different areas with different

17:06

patience with different payment systems

17:08

with difference whether i mean who

17:10

was raped yeah and it's not meaningful

17:12

for patients either and i actually

17:14

don't think that the primary purpose

17:17

of those reports of us news

17:19

in particular is for people to make choices

17:21

between the entities that are less said

17:24

the it's primary benefit is to get people talking

17:26

about quality so it's popular

17:28

and it's financially viable because

17:30

it's catchy and to people want to compare

17:32

things you can compare

17:34

these are microwaves like of course they want to compare

17:36

how to the of slimmest are practically

17:38

useful that actually as bitchy

17:41

the conversation and saying we should measure this

17:43

and we should compete as actually incredibly valuable

17:46

how do you think about quality hospital

17:48

care

17:49

hospital care and quality

17:51

our concepts it seems so simple

17:54

and then when you dig into them it turns out that they're

17:56

not nearly as straightforward as you think they

17:58

have to be so measuring something

18:00

like this a hospital give everyone having

18:03

a heart attack the appropriate care within

18:05

the appropriate time is reasonable

18:07

straightforward don't you think

18:09

about how does a hospital provide

18:11

care for diabetes or what

18:13

is their care for cancer it becomes

18:16

much much more complicated i

18:18

, probably even

18:20

with all the data in the world's you couldn't

18:22

get it right and

18:25

i think it's because sentimentally

18:27

people aren't widgets so

18:29

when we're measuring what happens to people

18:31

with slots as complex diseases who are getting

18:33

lots of complex care understanding

18:36

how much their outcomes reflect what a hospital

18:38

does versus the community

18:40

in which someone lives their ability to access

18:43

care of the other com abilities

18:45

they have all the other complexities in their

18:47

life he , of stop being

18:49

able to attribute everything to a hospital

18:51

or health system and so

18:53

almost no matter how good the data was coming

18:55

out of a hospital i'm not sure that you could ever

18:58

really understand how well

19:00

a certain healthcare entity delivers

19:03

healthcare

19:04

i know you got some work where you've actually

19:07

tried to rate the

19:09

actual raiders

19:10

so our purpose an undertaking the

19:12

project to look across the available systems

19:15

was to sort of get a better handle for who's

19:17

doing what well not to say

19:19

that anyone was terrific are terrible and

19:22

, we ended up digging into the methodology

19:24

and the way that they're presented i think

19:26

where we landed was actually the all of them left

19:29

quite a bit to be desired but

19:31

they had different he maybe serve different

19:33

purposes

19:35

the us news world report for example

19:38

realize very heavily on reputation and

19:40

in doing so essentially ranks essentially big

19:42

academic and some non academic

19:44

but big well see well

19:47

resourced hospital systems

19:49

around the country and they do

19:51

so through a combination of pretty

19:53

methodologically rigorous work

19:55

around some outcome some processes

19:57

and then a big black bags reputation

19:59

the survey

20:01

which is frankly what gets the mass

20:03

generals him the cedar

20:05

sinai is and the big names points

20:08

right to that's what people mention his reputation

20:11

but that's really what drives what lot of the rankings

20:14

and so i think that's have some utility

20:16

if you want to know who are the big leaders

20:18

and medicine it's , unreasonable

20:21

to use that ranking system and

20:23

the other hand you have something like cms medicare

20:28

has , series of star ratings and

20:30

they've undergone a lot of muscle logic

20:32

change over the last five years years

20:34

they essentially are trying to

20:37

rank everybody on one on

20:40

they essentially take a whole bunch of different ratings

20:42

on safety mortality rate admissions process

20:44

ease of cetera and they roll them up

20:47

into a star and the downside

20:49

of that was that you actually had actually bunch of small

20:52

house they have provided very few

20:54

this is getting the highest ranking speakers

20:56

they didn't have enough patience the contribute

20:58

to the tough measures sister the only

21:01

graded on ten out of one hundred questions in

21:03

your grade and the ten easy ones and

21:05

you do well you look terrific haven't

21:08

actually taken the same test cms

21:11

, done some work to try to break

21:13

hospitals into buckets into make each

21:15

group sort of competing against each other seem

21:17

a little more a light which has helped

21:20

but the biggest limitation for them has really been

21:22

trying to figure out how to compare hospitals that

21:24

compare so very different from each other on each single

21:26

scale

21:30

then there's leapfrog which is very focused

21:32

on patient safety and so

21:35

has the prose of having

21:37

some information about safety that know the other

21:39

groups do then healthgrades

21:42

the way that their methodology works because

21:44

they tend to reward a lot of individual

21:46

things the easy a

21:48

lot of winners were very different there's

21:51

like seven hundred dust hundred hospitals in the

21:53

us some people might say that's

21:55

actually real that's a quality works places are

21:57

good it the visual things and you said

22:00

community hospital showing up as the safest

22:02

and the best for some in a relatively

22:04

straightforward procedure those

22:06

, the for biggies and they really do have very

22:08

offsetting strengths and weaknesses but

22:11

they come to really different decisions about

22:13

which hospitals are best which i think

22:15

points out the trouble with the whole enterprise

22:18

really

22:20

do you think that the ranking systems

22:22

where the us news or were report or

22:25

cms have one

22:27

of the intended effect switches to get

22:29

hospice to improve

22:30

i think there's good evidence that they don't drive

22:32

a dramatic improvement

22:34

the

22:35

people have been pushing towards improving

22:37

care for decades millennia

22:39

probably and since isn't some sense that means

22:42

this isn't that then right you keep sort of pushing

22:44

forward to make oh care better but

22:46

, think where we tend to push his

22:48

in high tech exciting new areas

22:51

and maybe not as much on or people

22:53

washing their hands rape rape

22:56

so that i think as the benefit of these

22:58

programs is move in a conversation for

23:00

it on measurement and on the sort of system

23:02

ness of all this but this certainly

23:05

don't think

23:05

edit optimal

23:11

the have a sense of what the ranking systems do

23:13

well and what are they just

23:15

not good read it all

23:17

so

23:18

they have a slightly different answer than i would

23:20

have a year ago okay service

23:23

would they do well so i do

23:25

think there are places where there are good

23:28

reasonably valid process measures

23:30

reasonably valid safety measures reasonably

23:33

valid outcome measures i

23:35

think us news world report does the best job

23:37

as some of those because they do some accounting for social

23:39

risk where they have really

23:42

fallen down in my opinion is

23:44

equity even so the old

23:46

measures and many of the current measures

23:48

are not only inequitable

23:50

that potentially equity reducing like

23:53

actively equity reducing as opposed

23:55

to the leverage to try to

23:57

improve equity

23:59

the attack

23:59

it'll be because that's an important statement

24:02

of a strong statement what you mean by the systems

24:04

are equity reducing

24:07

though if you set up strong incentive

24:09

to make you or care and outcomes

24:11

look better and you don't

24:14

appropriately control for how

24:16

patients differ between hospitals you set

24:18

up and census people to avoid sex

24:20

or otherwise high risk patients

24:23

and so you can set up systems were

24:25

you don't control for example

24:28

for poverty if you don't control

24:30

for poverty then you're holding

24:32

hospitals accountable for say readmission

24:34

rates you are going to see the

24:37

performance and hostile that serve a high proportion

24:39

of for the right disadvantage patients

24:41

you're creating disincentives to

24:43

go find the sickest most vulnerable patients

24:46

who need that care the most we should

24:48

be doing the opposite which is to say

24:50

how can we and sent these big

24:52

powerful hospitals and health systems to

24:54

go sign the people who need them and

24:57

start actually keeping people healthy

25:02

having a set of quality measures that ignores

25:04

equity and then actually set

25:06

up incentives to stay away from high

25:08

risk patients i think it's not

25:10

how we want to be driving our health systems forward

25:13

us user will report is moving towards

25:15

including various measures of quality

25:17

at least reporting it it might find it's way

25:19

into the actual rankings at some point in time do

25:22

you think that that's something that's should be weighed

25:24

heavily in the rankings

25:25

the do you have to say that's

25:27

what we're driving towards any have to measure at

25:30

and you have to report it you

25:32

can't just take readmissions and say here's

25:34

your readmission rates for black patients years your

25:36

readmission rates for right patience and

25:38

as that hi

25:40

you are bad some of the equity

25:43

measures that have then shared by us news

25:45

for example look at disparities

25:48

in preventable hospitalizations

25:50

in a community so you're

25:52

looking at the difference for black versus white

25:54

patients in st louis this

25:56

is deterring

25:58

her her and her

25:59

his miami versus

26:02

portland maine the racial

26:04

composition of those places the

26:06

degree to which residential segregation and

26:08

other historically races practices

26:11

has influenced health outcomes in those

26:13

places is very very different

26:15

from each other and so it creates

26:17

all sorts of difficult questions about

26:20

what does equity look like

26:24

if there's one thing then that you could do

26:27

differently with all the rankings

26:29

more would it be kill killing

26:33

the could take twenty six you do

26:35

a killer get do

26:36

so equity for sure and i think

26:38

that includes picking equity sensitive

26:41

measures so for example we know that

26:43

black patients much more likely to

26:46

suffer disproportionate burden of

26:48

cardiovascular disease and stroke so diabetes

26:50

and hypertension chronic kidney disease find things

26:52

where you know that if we improve you're going

26:55

to disproportion the benefit people who have

26:57

been so disproportionately harmed in the past

26:59

so that would be number one second thing

27:02

is that the , now you

27:04

get a readmission rates

27:06

are score rates are safety score based

27:08

on three years of data with a two year lag

27:11

without singer now what to do about it

27:13

that doesn't in center hospital to start working

27:15

on it there is no reason

27:18

and this day and age that , can't

27:20

be getting hospitals near

27:22

real time feedback on the stuff that isn't

27:25

gordon

27:29

is there a rule that patients playing all

27:31

this

27:31

i think people expect that you should be able to get better

27:33

information than you can lots ,

27:35

hospitals have gone to something like my

27:37

chart or patients have access to their own data

27:40

now when i round in the hospital in the mornings

27:42

often patience has seen their lots of for i have

27:44

said their logged into their my chart

27:47

and the results pop up the sinister backs in the lab

27:49

and so the walked into a room and i'm like oh are we

27:51

to suit your kidney function as and the patient bilic

27:53

oh yeah my current news on play five the summer come from

27:55

one point settings expect a citizen

27:58

to their

27:58

there's actually degree

27:59

the easements and you know folks can

28:02

understand and fall the along and sort of

28:04

be a little bit more part of their care if

28:06

we give them the data to do

28:09

it's been harder told us earlier these

28:11

rankings are for patients and

28:13

according to us news and world report

28:16

nearly one hundred thousand people visit

28:18

their best hospitals website each day

28:21

looking for information about healthcare providers

28:24

here enjoyed metics and her colleagues have

28:26

raise red flags about hospital rankings

28:29

but she acknowledges that while we might

28:31

not learn as much as we'd like to from

28:33

ranking hospitals we still

28:35

need to try to measure how good a job

28:37

they're doing figuring out what

28:39

quality means in medicine seems

28:42

like it's to be easy says a lot of

28:44

data to work with and a lot of smart

28:46

people analyzing it but

28:48

hospitals are big busy places

28:50

spread out across a large country

28:53

and full of all different kinds of patience

28:56

as you peruse this year's annual list

28:58

of best hospitals and wonder as

29:00

i did y massachusetts general

29:02

hospital is not ranked number one you

29:05

can also maybe appreciate the work that

29:07

goes into assembling this list and

29:10

whether waiters need to keep on improving

29:12

to says like the hospitals they

29:14

judge that's it for today

29:16

show i want to take my guess been

29:18

harder in dr karen joint metics and

29:21

thanks to you of course for listening let

29:23

us know what you thought about this episode send

29:25

us an email at babu at freakonomics

29:28

dot com or leave or leave

29:30

wherever you get your podcasts coming

29:33

up next week on for economics m d we're

29:35

gonna talk about a trend that has been hard

29:37

to miss livni during the twenty twenty

29:40

to twenty twenty one school year school

29:42

shootings hit their highest level since

29:44

reliable record keeping began twenty

29:47

twenty was a phenomenal here in

29:49

terms of fun sales we'll explore

29:51

the tricky link between school shootings

29:53

and gun sales as well as how these

29:55

horrific events continue to save

29:57

the lives of all the people who lived

29:59

through the

30:00

because the shooting is non say it also

30:02

doesn't mean that doesn't have

30:04

clinton next week on the

30:06

show the hidden consequences

30:08

of school shootings thanks

30:10

again for listening

30:13

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also have helped us with some sort of clemente

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interval real cottage alina

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coleman and even dufner

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original music composed by lewis carroll

30:58

if you like they sell or any

31:00

other so in the for economics radio network

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31:23

if you had to go to a hospital and

31:25

be treated by a physician economists would

31:28

hospital would you go to are

31:30

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31:33

they call they call for a reason to assess

31:35

assess assess as