Transcript Starting Risk - TheMedicalGuide

The Health Insurance Broker
as Risk Manager
some slides from July 25 lecture in Westborough, MA
Gary Fradin
[email protected]
508-878-3785
Slide # 1
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Lecture outline
Putting consumerism into Consumer Driven
1. The need to manage healthcare risks
2. Utilization risks (today’s focus)
– Which tests? Preference-sensitive decisions
3. Employee risks
– Who gets sick? Disease patterns by income, status
4. One tool for managing test and Rx risks
– Out of 100 people like me….
5. Treatment variation risks
6. Conclusion: the high deductible / self insured world
Slide # 2
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Our point of departure:
Wennberg, Tracking Medicine, page 117
It is not the prices, it is the use
of care – the volume –
that matters more
Slide # 3
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Consumer Driven
Physician Driven
Government Driven
85% of medicine involves choices. Whose?
Different risk management tools for each type
– Consumer driven = consumer decides
• Facilities … also treatments, tests, medications etc
• Management tool: teach consumers how to decide
• Test: sometimes disagree with your doc, gov’t
recommendations
– Fact / Value distinction
• Fact: Vitamin D strengthens bones & stresses kidneys
• Value: how to weigh facts. Risk averse? Conservative? Which
effect more important to you?
Slide # 4
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Different risk management tools
Not today’s lecture
• Physician driven: physician decides
– Management tool: alter physician behavior
– Managed care / Kaiser Permanente
• Government driven: gov’t decides
– VHA: excellent outcomes at lower costs
– Mandates: e.g. free cancer screening ($ incentive)
– Process: USPSTF, expert committee recommends,
Medicare funds, private carriers follow
Physician and Government Driven:
Someone decides for you
Slide # 5
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Part 1:
Americans spend more on healthcare than anyone else
Slide # 6
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Americans Get More of Almost Everything
OECD Health at a Glance 2011, OECD Health Data 2012
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But Americans aren’t more satisfied
‘Not feeling the benefits of high spending’ Khoury and Brown, 3/31/09, Gallup.com
Slide # 12
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Americans don’t enjoy better outcomes:
Infant mortality rates
Deaths/1000 live births, OECD Health Data 2012
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Life Expectancy at Birth
ibid
Slide # 14
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Life expectancy age 65, males
ibid
Slide # 15
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Summary i
John Wennberg, Dartmouth Med School, Tracking Medicine, page 4
Much of healthcare is of
questionable value
For example
Slide # 16
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Stress Tests
From the American College of Cardiology
choosingwisely.org
• 1. Don’t perform stress cardiac imaging in the
initial evaluation of patients without cardiac
symptoms unless high-risk markers are present.
• 2. Don’t perform annual stress cardiac as part of
routine follow-up in asymptomatic patients.
• This practice may lead to unnecessary invasive
procedures without any proven impact on patients’
outcomes.
Slide # 17
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Back MRIs
from American Academy of Family Physicians
106,000 members; choosingwisely.org
• Don’t do imaging for low back pain within
the first six weeks, unless red flags are
present.
• …Imaging of the lower spine before six weeks
does not improve outcomes, but does increase
costs. Low back pain is the fifth most common
reason for all physician visits.
Slide # 18
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And many more…
ChoosingWisely has
• 5 recommendations from each of
• 26 medical societies =
• 130 medical tests and procedures that
patients should not get…
According to the medical society whose
members provide those services!
Slide # 19
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Part 2
Utilization risks
in a Consumer Driven world
Preference-sensitive decision making
the essence of consumer driven
Which medical risks concern you?
Which medical interventions appeal to you?
How to make an informed decision?
Ask the right questions and get
useful information
Slide # 20
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Noise vs. Useful Info
What is this car’s gas mileage?
(how many lives/1000 screened does this test save over 10 years?)
Noise
•
•
•
•
•
•
•
Very good gas mileage
30% better than competitors
Highly rated for gas mileage
Most buyers recommend
Autobuyer.com rates ‘buy’
> 350 miles on a tank of gas
Owners average less than
$1000 in gas per year *
•
* compared to national average of
$1800
Slide # 21
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Useful Info
• 28 miles highway / 22
miles city
Background
 1 million internal substances, functions
or chemicals that we can measure,
analyze and test
Newman, Hippocrates’ Shadow, page 202
20,000/week
Which to worry about?
Which to get screened for?
Which to take meds for?
Slide # 22
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Different kinds of tests
• Screening: asymptomatic people,
according to a calendar
• Diagnostic: symptomatic people
• Also public (population) health vs.
individual decision: different perspectives
Slide # 23
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Some potential tests
partial list of ‘A’ from WebMD
• Abdominal MRI (look
for tumors)
• Abdominal Tap
(screen for liver cancer)
• Abdominal
Ultrasound (liver,
gallbladder, liver
evaluation)
• Acoustic reflect test
(screening for hearing
problems)
Slide # 24
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• Activated Partial
Thromboplastin
Time (test of blood
clotting)
• Adrenocorticotropic
Hormone test (check
for problems in pituitary
or adrenal glands)
Some cancer risks
National Cancer Institute and SEER Stat Fact Sheets
40 different cancers listed
Cancer Type
New cases/year
Vulva
4,700
Testicular
7,920
Cervix
12,340
Stomach
21,600
Pancreatic
45,220
Thyroid
60,220
Kidney and renal pelvis 65,150
Colon
142,820
Slide # 25
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Deaths/year
990
370
4,030
10,990
38,460
1,850
13,680
50,830
Some medical risks
(thousands more)
•
•
•
•
•
•
•
•
Ankylosing Spondylitis
Osgood-Schlatter's disease
Dercum's disease
Uterine leiomyosarcoma
Tardive Dyskinesia
Lupus (various forms)
Gaucher’s disease
Male breast cancer
Slide # 26
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Just because a test or treatment
exists doesn’t mean you should
have it!*
* Even if free!
Consumer Driven vs.
Physician Driven vs.
Government Driven
Slide # 27
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How to decide
A 4-step program
Useful info vs. Noise
• Determine Starting Risk
– Chance of a specific bad event without medical care
• Determine Modified Risk
– Chance of same specific event with medical care
• Determine Treatment Benefit * (next slide)
– Impact of medical care: Starting Risk – Modified Risk
• Determine Treatment Risk(s) / Harms
– Harms caused by the medical care
Slide # 28
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* 3 potential reasons for treatment benefits:
1. Better treatments
2. Earlier treatment of symptomatic people (due
to more widespread education)
3. Early treatment of asymptomatic people,
from screening
Slide # 29
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Starting Risk
• Why you don’t wear a bike helmet when
you walk
Slide # 30
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Case study #1
Would you have this test?
Considerations
Starting Risk: Do you need the test?
Modified Risk
Treatment Benefit
Treatment Harms
Slide # 31
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4 in 1000 die over 10 years;
99.6% chance of not dying.
Modified Risk:
Does the test work well enough to have?
Considerations
Starting Risk: Do you need the test?
4 in 1000 die over 10 years;
99.6% chance of not dying.
Modified Risk: How many still die
with the test and associated care?
3 in 1000 still die over 10 years
Treatment Benefit
Treatment Harms
Slide # 32
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Treatment Benefits:
Does the test work well enough to have?
Considerations
Starting Risk: Do you need the test?
4 in 1000 die over 10 years;
99.6% chance of not dying.
Modified Risk: How many still die
with the test and associated care?
3 in 1000 still die over 10 years
Treatment Benefit: How many benefit
by avoiding death?
1 fewer death per 1000 people over 10
years
Treatment Harms
Slide # 33
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Treatment Harms:
Is the test too dangerous for you?
Consideration
Treatment Harms: How many harmed
by the test and associated care?
Half the people tested over 10 yrs get a
false positive test result
A third of people correctly diagnosed
are not helped by the test; wouldn’t be
harmed anyway by the disease.
About 7-10 people receive treatment
(inpatient, invasive) to save 1 life
Slide # 34
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Summary:
Would you have this test?
Considerations
Starting Risk: Do you need the test?
4 in 1000 die over 10 years;
99.6% chance of not dying.
Modified Risk: How many still die with the
test and associated care?
3 in 1000 still die over 10 years
Treatment Benefit: How many benefit by
avoiding death?
1 fewer death per 1000 people over 10
years
Treatment Harms: How many harmed by
the test and associated care?
50% false positives over 10 yrs.
30% of true positive results are
unnecessarily diagnosed and not helped by
the test.
About 7-10 people receive treatment
(invasive, aggressive) to save 1 life
Slide # 35
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What is this test and condition?
• Mammography for breast cancer
• Benefit and risk data for 50 year old
woman over 10 years
Slide # 36
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References
• Starting Risk: Risk Charts, Woloshin, Journal National
Cancer Institute, June 5, 2002
• Mammography Benefit: Otis Brawley est that
mammography + better breast awareness reduces breast
cancer mortality by 15 – 30%, various articles, American
Cancer Society website, How We Do Harm
• Mammography risks: US Preventive Services Task Force,
Woloshin, JAMA, 2010
Slide # 37
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‘big’ or ‘small’ impact
‘good’ gas mileage
• 1 in 100 - 150 heart attacks prevented is
‘major’, ‘significant’ or ‘big benefit’
• But .6 in 100 - 150 diabetes caused is
‘rare’, ‘infrequent’ or ‘minor’
Slide # 38
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Get numbers!
But you need to ask the right questions to get the right
numbers
Slide # 39
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Downside
of bad decision making, failure to get numbers (1)
• Vioxx , painkiller ‘as good as aspirin with fewer
stomach bleeds’ 1999 - 2005
– Merck settled, 2010, for
• 20,000 heart attacks
• 12,000 strokes
• 3,500 deaths Voreacos, Merck paid 3,468 death claims, Bloomberg, 7/27/10
• May have caused up to 140,000 heart attacks Bhattacharya,
Up to 140,000 heart attacks linked to Vioxx, New Scientist, January 2005
Slide # 40
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Downside
of bad decision making, failure to get numbers (2)
Harris, Research ties diabetes drug to heart woes, NY Times, 2/19/10
• Avandia, $3.2 billion sales 2006
• US gov’t report: if all people taking Avandia
switched to a safer drug, would avoid
– 500 heart attacks per month
– 300 heart failures per month
• 304 people died during 3rd quarter, 2009 alone
Slide # 41
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Part 3: Modifying starting risk
who’s most likely to need medical care?
• The impact of income / status / class
– Whitehall ‘status’
– NEJM ‘class’
• Issue: focus risk management education
and wellness programs at the people
most likely to get sick
– Not only the conditions most likely to cause illness
Slide # 42
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Sir Michael Marmot
Director of the Whitehall studies
globetrotter.berkeley.edu/people2/marmot
• Firstly, just looking at heart disease, it was not the case
that people in high stress jobs had a higher risk of heart
attack, rather it went exactly the other way: people at
the bottom of the hierarchy had a higher risk of heart
attacks.
• Secondly, it was a social gradient. The lower you were
in the hierarchy, the higher the risk. So it wasn't top
versus bottom, but it was graded.
• And, thirdly, the social gradient applied to all the major
causes of death.
Slide # 43
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Marmot’s example
Remember – this study was from 1970s – early 2000s
• How many times have you called the telephone company,
and, in exasperation, asked to speak to the person's
supervisor? You do this because the discretion of the
lower-status [and lower paid] person to make decisions is
limited
•
Boss derides secretary for making mistakes, destroys her self confidence
• ‘Underling’ given instructions by manager that are inefficient ‘I like
reports this way’ – even if underling has better way to do it
• Cleaner gets reprimanded for washing floors incorrectly…
But bank president doesn’t get fired for making a bad loan!
Slide # 44
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Class – the ignored determinant of the
nation’s health
NEJM, Sept 9, 2004
• Differences in rates of premature death,
illness and disability are closely tied to socioeconomic status
• Unhealthy behavior and lifestyle alone do
not explain the poor health of those in lower
classes
• There is something about lower
socioeconomic status itself that
increases the risk of premature death
Slide # 45
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Other examples
Drexler, The People’s Epidemiologists, Harvard Magazine, March 2006
• Smoking cessation attempts same for working class
and higher class people. Success rates vary. Will power?
Social supports?
– Or because job so boring that lighting up only way to
break the tedium?
Slide # 46
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Breast cancer survival rates
Bouchardy et al, Social class is an important and independent prognostic factor of
breast cancer mortality, International Journal of Cancer, Vol 119, Issue 5, March 2006
• In this study, we clearly demonstrate that breast cancer
patients of low Socio-Economic Status have a
significantly increased risk of dying as a result of breast
cancer compared to the risk in patients of high SES.
• Low SES patients were diagnosed at a later stage, had
different tumor characteristics and more often received
suboptimal treatment.
• However, these important prognostic factors
explained less than 50% of the overmortality
linked to low SES.
Slide # 47
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ibid.
Even after adjusting for all these
factors, the risk of dying of breast
cancer remained 70% higher among
patients of low SES than that among
patients of high SES.
Slide # 48
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Summary observations
Drexler, Harvard Magazine
• ‘an individual’s health can’t be torn from
context and history. We are both social
and biological beings….
• and the social is every bit as
real as the biological’
Slide # 49
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Back to Michael Marmot
• The social gradient applied to all the
major causes of death -- to
cardiovascular disease, to
gastrointestinal disease, to renal disease,
to stroke, to accidental and violent deaths,
to cancers that were not related to
smoking as well as cancers that were
related to smoking -- all the major causes
of death.
Slide # 50
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• We see similar findings in the United
States, in Canada, in Australia, New
Zealand, and most European countries
that looked for it.
Slide # 51
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• we looked at the usual risk factors that one believes that
are related to lifestyle -- smoking prime among them,
but plasma cholesterol, related in part to fatty diet and
an overweight, sedentary lifestyle.
• We asked how much of the social gradient in coronary
disease could be accounted for by smoking, blood
pressure, cholesterol, overweight, and being sedentary.
• The answer was somewhere
between a quarter and a third, no
more.
Slide # 52
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• we looked at never smokers, and we
found the same gradient in never smokers
as we found in smokers.
• two-thirds, at least, of this gradient is
unexplained….
Slide # 53
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Bell curve: % of employees with various disease factors
(smoking, obesity, cholesterol, blood pressure, blood sugar, etc)
What causes disease?
Slide # 54
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# employees by income
Who gets sick?
Slide # 55
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Risk management example:
Hypothetical company
• 10 employees earn > $250,000 (high status)
• 100 earn < $35,000 (low status, $15/hour, 45 hours/wk)
• According to Marmot
– For every 1 heart attack in the highly
compensated group….
–30 in the lowest income group
• (3x the risk) x (10x the number of employees)
Slide # 56
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Marmot
• we showed very clear social differences in
people's experience of the workplace -how much control they had at work, how
fairly they were treated at work, how
interesting their work was.
• All of which correlated to disease
and mortality rates
Slide # 57
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Summary so far
• Much medical care provides no benefit
• ‘Necessary’ and ‘unnecessary’ defined by
each consumer
– Requires consumer involvement and education
• ‘Treatment benefit’ = starting risk –
modified risk
• ‘Starting risk’ and ‘treatment benefit’
defined by both biology and demography
Slide # 58
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Part 4:
Managing Preventive Test and Rx Risks
Does ‘better safe than sorry’
mean anything?
Slide # 59
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4 questions to ask
when you research, advise, talk to physicians
Phrasing is critical!
• 1. Out of 100 people like me, how many will
have the bad medical event without medical
intervention?
• 2. Out of 100 people like me, how many will
still have the bad medical event with medical
intervention?
• 3. Out of 100 like me, how many benefit by
avoiding the bad medical event?
• 4. Out of 100 people like me, how many
harmed by the test and treatment?
Slide # 60
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Out of 100 people…
• Absolute risk reduction
• Question requires answer of a number
• Reason: avoid relative risk reduction
numbers
Slide # 61
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relative risk reduction always exaggerates
Absolute risk reduction
• Starting risk: 2 in 100
• Modified risk: 1 in 100
• Risk reduction: 1 in 100
• Summary statement: This
treatment benefits 1% of
people who have it.
Slide # 62
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Relative risk reduction
• Starting risk: 2 in 100
• Modified risk: 1 in 100
• Risk reduction: 1 in 2
• Summary statement: This
treatment cuts your risk
by 50%, or
• 50% fewer heart attacks,
breast cancer deaths, etc
Avoid all this confusion…
Ask
Out of 100 people…..
Slide # 63
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Out of 100 people
like me
• Reported, advertised data often best case
– We generally don’t know the population
• Many of our treatments haven’t been rigorously
studied, and even if they have, large swaths of
the population are woefully underrepresented
in clinical trials — the very old, the very sick,
women, members of racial and ethnic
minorities, children, pregnant women and those
low on the socioeconomic scale. Uncertainty is Hard for
Doctors, Danielle Orfi MD, NY Times, 6/6/13
Slide # 64
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ATPIII
Third Report of the National Cholesterol Education Program Expert Panel on Detection,
Evaluation and Treatment of High Blood Cholesterol in Adults, pages II-31 and II-32
• “Two primary prevention studies with statins
were the West of Scotland Coronary
Prevention Study and the Air Force/Texas
Atherosclerosis Prevention Study”
• “In both trials, statin therapy
significantly reduced relative risk
for major coronary events”
Slide # 65
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West of Scotland
a Whitehall-type analysis
Quotes from various BBC reports
• Glasgow ‘world’s heart attack capital’ BBC, 1999
• A stressful job, where people have little control
over their work, increased the risk of heart
disease by half. ‘Glasgow heart disease leader’ BBC Nov 21, 2000
• ‘Scots have worse rates of heart disease than
their bad lifestyles would explain’ BBC, ‘English have
healthier hearts’ 2007
What was Glasgow’s economic situation?
Slide # 66
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Breakthrough Glasgow: Ending the Costs of Social Breakdown, 2008, bbc.co.uk
• Nearly 110,000 working-age residents in
Glasgow are economically inactive,
accounting for almost 30 per cent of Glasgow’s
total working-age population.
• Researchers developed a new category to
describe Glasgow residents: Shettleston Man
Slide # 67
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• Shettleston Man is the collective name given
for a group of men in Shettleston.
• Shettleston Man’s life expectancy is 63, he
lives in social housing and is terminally out
of work.
• His white blood cell count is killing him due
to the stress of living in deprivation.
Does this sound like your clients?
Slide # 68
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Who participates in drug trials?
• Boston Metro: lots of medical trial ads
• Boston Globe, New York Times: no
medical trial ads
What does this suggest?
Slide # 69
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Out of 100 people like me, how many avoid the
bad medical event?
• Different types of outcomes:
• Test outcomes: how you perform on a
test
– Obesity, cholesterol, blood pressure etc
• Patient outcomes: medical events
– Heart attack, stroke, die of breast cancer
How closely do test outcomes
correlate to patient outcomes?
Slide # 70
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ZETIA example
difference between test and patient outcomes
• Test benefit:
• in a clinical study, people who added ZETIA to
their statin medication reduced their bad
cholesterol on average by an additional 25%
compared with 4% in people who added a placebo.
Parade magazine 9/11/11
• Patient benefit
• ZETIA has not been shown to prevent
heart disease or heart attacks ibid.
• ZETIA annual sales: about $2 billion
Slide # 71
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Niacin
Thomas, NY Times, Dec 20, 2012, Merck Says Niacin Drug Has Failed Large Trials
Herper, Forbes, Dec 20, 2012, Why Merck’s Niacin Failure Will Scare Drug Researchers
• Niacin (B3) raises HDL (good) cholesterol and slightly
lowers LDL (bad).
– ‘has been used for 40 years to help millions of patients
control their cholesterol’ (Herper)…
– including Niaspin, Abbott Labs, annual sales $900 million
• But 4 year study of 26,000 people found no
reduction heart attacks, strokes, deaths or
procedures
Higher HDL ≠ fewer heart attacks
Test benefit ≠ patient benefit
Slide # 72
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When you know the patient benefit…
and even if the test or treatment is free …
Are the benefits good enough for you?
» Mammography
» Statins
» Blood sugar lowering meds
» Knee surgery, etc
Consider risks too!
Slide # 73
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Better safe than sorry?
No!
• There are risks and benefits of testing…
– And risks and benefits of not testing.
• Benefits and risks of taking preventive meds
– And benefits and risks of not taking
• Individual decision…
if you have the right tools
Slide # 74
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Broker’s role
• 1. Empower people to make their own
medical decisions …
– with their doc, of course!
• 2. Provide them with decision-making
tools
– Right questions to ask, info to get
Slide # 75
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Part 5:
Utilization by provider
Another example of risk mgt tools for consumer driven / preference driven
• Similar patients get different care
but similar outcomes in
– Different regions
– From different hospitals
– From different specialists
• Potentially big impact on cost
– With potentially no impact on outcomes!
Slide # 76
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Utilization by region
Mastectomies per 100,000 Medicare women,
2010, Dartmouth Atlas
Slide # 77
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Breast cancer incidence per 100K women
American Cancer Society, Cancer Facts and Figures, 2011-2012
Slide # 78
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Breast cancer mortality per 100,000 women
http://www.cancer.org/acs/groups/content/@epidemiologysurveilance/documents/do
cument/acspc-030975.pdf
Slide # 79
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Consumer Driven Risk Mgt tool
Am I in a high or low utilization region?
Explain what utilization means
Can I have referral for 2nd opinion in a
different utilization region?
Slide # 80
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Utilization by Hospital: C-sections
Min 490 deliveries
mass.gov/birth report, 2009
Slide # 81
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Why the differences?
Globe, Why Caesarean birth rates differ at area hospitals, June 7, 2010
•
Dr. Lauren Smith, Medical Director, Mass DPH:
– “There are a complex array of factors that
contribute in each individual case to whether
or not a woman delivers vaginally or via
caesarean … some of those are factors are at
the hospital level, such as how do they
organize the staffing of their labor and
delivery units, what are the resources that
might be available”
Other states looked into same phenomenon
Slide # 82
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Big impact on costs:
C-sections cost about $5,000 more!
Slide # 83
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Consumer Driven Risk Mgt Tool
What are the C-section rates at my local
hospitals?
Do I increase or decrease my risks – or my
baby’s - by using a different hospital?
Requires outcome data by hospital
Slide # 84
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Beware of choosing hospital network
based on price
You need to know utilization rates also!
Slide # 85
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Lower priced hospitals?
C-section rates
Slide # 86
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Possible broker actions
Not ‘go to lowest priced hospital’
• 1. Publicize C-section rates
• 2. Reference-based pricing to hospitals with
lowest C-section rates, not lowest negotiated
vaginal delivery prices
• 3. Reduce employee contribution to hospitals
with lower C-section rates
Need to incorporate utilization rates
with listed prices to manage risk!
Slide # 87
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Massachusetts inpatient coronary angiography
per 1000 Medicare, 2010
Slide # 88
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The concerns:
• 1. The cost. Perhaps $5,000/angiogram
• 2. The findings.
– Since most people who are middle-aged and older
have atherosclerosis, the angiogram will more
often than not show a narrowing. Inevitably, the
patient gets a stent. Kolata, NY Times, 3/21/04
• 3. Stent insertion costs about $11,000
Wieffering, Patients and taxpayers bear the cost of stent wars, Star Tribune,
6/18/2011
Slide # 89
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Morale
Where you go is what you get
Risk Mgt Tool:
Ask the right questions!
• Am I in a high or low utilization region?
• How frequently does the test lead to treatment?
• How frequently does the treatment help?
(out of 100 people like me….)
Slide # 90
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Impact of High Deductibles and Self Insurance
•
•
•
•
Change the incentives
Change the risk-management focus
From physician driven, control physicians
To consumer driven, empower consumers
– Both cost and quality-based decision
making
Slide # 91
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Conclusion:
Stages of facing new broker realities
Wennberg
• Stage 1. “The data are wrong”
• Stage 2. “The data are right, but it’s not a
problem”
• Stage 3. “The data are right, it is a
problem, but it is not my problem”
• Stage 4. “I accept the burden
of improvement”
Slide # 92
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