Helping Doctors and Patients Make Sense of Health Statistics

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Helping Doctors and Patients Make Sense of Health Statistics. Supplemental Reading 2. Overview. Few understand health statistics Mammography screening recues the risk of dying from breast cancer by 25% in fact means that _____________________will die of the disease. - PowerPoint PPT Presentation

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Helping Doctors and Patients Make Sense of Health StatisticsSupplemental Reading 2

Overview• Few understand health statistics• Mammography screening recues the risk of dying from breast

cancer by 25% in fact means that _____________________will die of the disease.

• Common to patients, journalists, and physicians • Created by nontransparent framing of information (sometimes

intentional)

• Have serious consequences • Not cognitive biases alone• Emotional nature of interaction• _____________________

• Potential solutions• Education (patients and physicians)• frequency statements vs. single event probabilities • _____________________• mortality vs. survival rate• natural vs. conditional probabilities

• Value of statistical literacy

Contraceptive pill scare• Finding = Oral contraceptive pills increased the risk of blood clots

by _____________________• Info passed on to 190,000 general practitioners • Caused anxiety, distressed women stopped taking pill

How big is 100% • Increased from _____________________ people to 2/7000 people. • Absolute risk was only 1 in 7000, relative risk was 100%

• Typically,• Absolute: _____________________• Relative risk tend to look big esp. if base rate is low

• Pill scare contributed to +13,000 abortions in the following year (+$76 million spent additionally)

• For every + abortion, there was an additional birth, esp. in teenagers• +800 for girls under 16

• Abortions and pregnancies increased_____________________

Few gynecologists understand positive mammograms

• Key stat: chances that a woman who tests positive actually has breast cancer• Mammograms produce many _____________________• Women have the right to know

• If you’re a woman who just received a positive screening mammogram, and asks your Dr.: • “Do I have breast cancer for certain, or what are the chances?

99%? 90% 50% or less?” • 160 gynecologists were provided information to make answer

this question

Answer: _____________________ (most Drs. Chose A or B; 21% got it right)

• Conditional probabilities: includes sensitivity and the false-positive rate

• _____________________: more transparent

• After training, 89% got it right• Many physicians do no know the _____________________ that a person has a disease given a positive screening test

Higher survival does not mean longer life

• Rudy Giuliani: • Britain: _____________________ diagnosed with prostate cancer• 28 died within 5 years (~43%)• In US: 82% 5 year survival rate

5 year survival rate

Key difference: _____________________Screening biases survival in 2 ways:

* affects timing of diagnosis (lead-team bias)* affects the nature of diagnosis by including people with

nonprogressive cancer (overdiagnosis bias)

Lead-time bias• Patients diagnosed with prostate cancer at 67 yr old, all die by

70 • Same group diagnosed at 60, all still die at 70• 5 year survival rate is 100% but _____________________

Overdiagnosis bias• Detection of pseudodisease – meets pathologic definition but

will never progress to cancer• _____________________

• Changes in 5 year survival rate completely uncorrelated with changes in mortality

• Knowing about changes in SURVIVAL tells you NOTHING about changes in MORTALITY

• Giuliani wrong (WHY)• __________________________________________

• Real story is mortality rate• US: 26/100,000 die • Britain: 27/100,000 die

Examples Illustrate• Collective statistical literacy of patients, physicians, and

politicians… • The more wide spread the literacy, the easier to manipulate

What is statistical literacy? • Basic competency in health statistic• Comparing survival rates with different screening policies: non-

sense• Minimal statistical literacy in health

Minimal statistical literacy in health

• Learning to live with uncertainty • There is no certainty and no zero-risk, but only risks that are more

or less acceptable • Smoking vs. not smoking• BRCA1/2• Bilateral mastectomy

Minimal statistical literacy in health• Questions to ask about all risks• Risk of what? (e.g., dying, getting disease, developing symptom)• Time frame? (10 years vs. life time)• How big? (expressed in _____________________–13/1000)

Minimal statistical literacy in health

• Questions to ask about all risks (Cont.)• Does it apply to me? (age, sex, similar health problems)• Screening tests have benefits and harms

• + finding disease earlier• - costs, inconvenience, false alarm, overdiagnosis—overtreatment

• Detection _____________________

Minimal statistical literacy in health

• Screen tests can make two errors: • False positive (false alarm)• False negative (miss)

• Understand how to translate probabilities into natural frequencies

• Study: undercover at 20 AIDS counselors: “If one is not infected with HIV, is it possible to have a positive test result?”

Minimal statistical literacy in health

• Understand that the goal of screening is not to simply the early detection of d_____________________disease; it is mortality reduction or improvement of quality of life.

Minimal statistical literacy in health

• Treatments have benefits and harms• More is not always better

• Understand the size of the benefit and harm • Ask for _____________________ (not relative) of outcomes w/

and w/out treatment• Questions about the science behind the numbers (e.g., quality

of study)• What conflicts of interest exist?

Prevalence of health statistical illiteracy

Consequences• Susceptibility to manipulations of anxieties and hopes• Informed consent and shared decision making undermined

Causes of health illiteracy • Paternalism and trust• Determinism and illusion of certainty • Conflicts of interest

Potential solutions• Teach statistical literacy in school • Too late in school• With representations that confuse young minds• Boring examples that kill motivation• Teachers who are unversed in statistics

• Transparency • Numbers, not only words• Data tables: Drug fact boxes• Transparent numbers