explaining contraceptive risk to patients sponsored by association of reproductive health...
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Explaining Contraceptive Risk to PatientsSponsored by Association of Reproductive Health ProfessionalsPlanned Parenthood® Federation of America
A component of You Decide: Making Informed Health Decisions about Hormonal ContraceptionSupported by an independent educational grant from Ortho Women’s Health and Urology
Expert Medical Advisory CommitteeJames R. Allen, MD, MPH
Medical AdvisorAmerican Social Health Association Washington, DC
Vanessa Cullins, MD, MPH, MBA (co-chair) Vice President for Medical AffairsPlanned Parenthood Federation of America New York, NY
Linda Dominguez, RN-C, NPAssistant Medical DirectorPlanned Parenthood of New Mexico Albuquerque, NM
Julie Downs, PhD Research FacultyCarnegie Mellon University Department of Social and Decision SciencesPittsburgh, PA
Martin Fishbein, PhDProfessor, Annenberg Public Policy Center University of Pennsylvania Philadelphia, PA
Kamini Geer, MD Fellow, Family PlanningMontefiore Medical Center Department of Social and Family MedicineBronx, NY
David Grimes, MD (co-chair) Vice President Biomedical AffairsFamily Health International Durham, NC
Joel Shuster, PharmD, BCPPProfessor of Clinical PharmacyTemple University School of PharmacyClinical Pharmacy ConsultantEpiscopal Hospital Temple University School of Pharmacy Philadelphia, PA
Eshauna Smith, MPA Program ManagerPro-Choice Public Education Project (PEP) New York, NY
Scott Spear, MD Director of Clinical ServicesUniversity Health Services Associate Professor of Pediatrics (CHS) University of Wisconsin-MadisonMadison, WI
James Trussell, BPhil, PhD DirectorOffice of Population ResearchPrinceton University Princeton, NJ
Sandy Worthington, MSN, RNC, CNMProgram DirectorPlanned Parenthood Federation of America Philadelphia, PA
Learning Objectives
1. Define relative risk, attributable risk and absolute risk
2. List three different means of presenting risk and describe the advantages of each
3. Identify at least three patient characteristics to consider when counseling about risks and benefits
4. Describe at least one patient education tool that can be used to effectively communicate the risks and benefits of hormonal contraceptives
Case Study: Alyssa Smith
> 25 year old nonsmoker, 3 children> Satisfied user of DMPA for 3 years> Past contraceptive history
– Patch caused nausea– Difficulty remembering to
take oral contraceptives (OCs)– Not interested in IUD – Not interested in vaginal insertion methods
Case Study, Alyssa Smith (cont’d)
Primary care clinic stopped prescribing DMPA
Physician said, “It’s bad for bones” but provided no specifics
Ms. Smith left without a plan for an effective contraceptive method
Pregnancy within 3 months
Early medication abortion
Case Study (cont.)
> Specific risks were explained and placed in context by another provider
> Ms. Smith was comfortable with risks and benefits of DMPA
> She decided to resume DMPA
Risk Misperception & the Provider
Chaker AM. Wall Street Journal November 22, 2005.
Risk Misperception & the Patient
“…incorrect perceptions of excess risk of contraceptive products may lead women to use them less than effectively or not at all.”
Gardner J, Miller L. J Womens Health 2005
Misperception Affects Health Decisions: OC Discontinuation
> In 1995, the British Committee on Safety of Medicines warned of possible increased risk of VTE among users of 3rd generation OCs
> Many women stopped taking OCs> Prescribing patterns changed> Pregnancy and abortion numbers increased> Deemed a “non-epidemic”
Chasen-Taber L, Stampfer M. N Engl J Med 2001; Drife L. Drug Saf 2002; Furedi A, Paintin D. Lancet 1998;
Spitzer WO. Hum Reprod 1997. .
Unintended Pregnancy Rates by Age, 2001
Age
0102030405060708090
100
Perc
enta
ge o
fpr
egna
ncie
s un
inte
nded
15-19 20-24 25-29 30-34 35-39 >40
Finer LB, Henshaw SK. Perspect Sexual Reprod Health 2006.
Definition of Risk
“The possibility of suffering harm or loss.”
The American Heritage Dictionary of the English Language
Risk Calculations
> Allow researchers to hypothesize about causality> Allow consumers and clinicians to weigh the pros and cons of
treatment interventions> Allow epidemiologists to calculate the degree to which a
disease or event is attributable to a particular hazard
Hennekens CH, Buring JE. Epidemiology in Medicine 1987.
Associations vs. Causality
> An association does not always mean exposure caused outcome
> It could be due to random chance or bias
Grimes DA, Schulz KF. Lancet 2002.
Commonly Used Risk Calculations
Absolute Risk
> Absolute risk is– The percentage of people in a group who experience a
discrete event– The number of people with event/the total # of people at risk
NY Academy of Medicine. www.emeb.org 2005. Misselbrook D, Armstrong D. Fam Practice 2002.
Example of Absolute Risk
> Of 100,000 women on 3rd generation OCs, 30 will develop venous thromboembolism (VTE) per year
Mills A. Hum Reprod 1997.
Absolute risk
30 per 100,000 woman-years
Absolute Risk Reduction
> Absolute risk reduction is:– The difference in risk of the outcome between those exposed
and those not exposed – Risk in exposed – risk in unexposed
> Reflects the reduction in risk associated with an intervention
NY Academy of Medicine. www.emeb.org 2005.
Example of Absolute Risk Reduction
> Of 100,000 women on 2nd generation OCs, 15 will develop VTE per year
Mills A. Hum Reprod 1997.
Absolute risk
15 per 100,000 woman-years
Absolute risk reduction
30 - 15 =15 per 100,000 woman-years
Attributable Risk
> Similar to absolute risk reduction> Attributable risk is:
– The difference in risk of the outcome between those exposed and those not exposed
– Risk in exposed – rate in unexposed> Reflects degree of risk associated with exposure
BMJ Collections 2006.
Relative Risk
> Frequency in exposed group divided by frequency in unexposed group
> Reflects likelihood of developing the outcome based on exposure
> Used to identify an association between exposure and outcome
> Similar to odds ratio
Grimes DA, Schulz KF. Lancet 2002.Hennekens CH, Buring JE. Epidemiology in Medicine 1987.
Odds Ratio
> Used to identify an association between exposure and outcome in a case-control study
> Similar to relative risk
Hennekens CH, Buring JE. Epidemiology in Medicine 1987.
Example of Relative Risk
Mills A. Hum Reprod 1997.
Absolute risk
3rd Generation OCs
30 per 100,000 woman-years
Absolute risk
2nd Generation OCs
15 per 100,000 woman-years
Relative risk = 30 / 15 = 2
Interpreting Relative Risk
Hennekens CH, Buring JE. Epidemiology in Medicine 1987.
Relative risk = 1
No increase in risk in exposed group
compared with unexposed group
Relative risk > 1
Increased risk in exposed group
Relative risk < 1
Decreased risk in exposed group
Example of Relative Risk: Induction of Labor & Cesarean Delivery
= 2
Risk of cesarean delivery with elective induction of labor 20%
Risk of cesarean delivery with spontaneous onset of labor 10%
Relative risk with induction: 20% 10%
Grimes DA, Schulz KF. Lancet 2002.
Example of Relative Risk (cont.)
> Interpretation: the risk of cesarean delivery with elective induction of labor is 2 times that associated with spontaneous labor, or, stated alternatively, twice as high
Grimes DA, Schulz KF. Lancet 2002.
Example of Relative Risk (cont.)
> Interpretation: the risk of cesarean delivery with elective induction of labor is 2 times that associated with spontaneous labor, or, stated alternatively, twice as high
Graph of relative risk of 2
0.1
1
10
Re
lati
ve
ris
k (
log
sc
ale
)
Increased risk
Decreased risk
Grimes DA, Schulz KF. Lancet 2002..
Example of Relative Risk, #2: Infection after Cesarean Delivery
= 0.5
Rate with prophylactic antibiotics 6%
Rate without prophylactic antibiotics: 12%
Relative risk: 6% 12%
Grimes DA, Schulz KF. Lancet 2002..
Example of Relative Risk, #2 (cont.)
> Interpretation: Use of prophylactic antibiotics (the exposure of interest) is associated with a 50% reduction in risk of infection, or, stated alternatively, one-half the risk
Graph of relative risk of 0.5
0.1
1
10
Re
lati
ve
ris
k (
log
sc
ale
)
Increased risk
Decreased risk
Grimes DA, Schulz KF. Lancet 2002.
Comparing Relative Risk
Zone of increased risk
Zone of reduced risk
2 and 0.5 are equal in strength but opposite in direction, one harmful and one protective
2
0.5
Graph of relative risks of 2 and 0.5
0.1
1
10
Rel
ativ
e R
isk
(lo
g s
cale
)
Grimes DA, Schulz KF. Lancet 2002.
Comparative Risk of Venous ThromboembolismIn
cid
ence
of
VT
E p
er 1
00,0
00w
om
an-y
ears
Shulman LP, Goldzieher JW. J Reprod Med 2003.Chang J, et al. In: Surveillance Summaries 2003.
0
20
40
60PregnancyHigh-dose OCLow-dose OCGeneral population
Risk & Health Decisions
Decisions about risk are not technical,but value decisions.
Baker B. In: Risk Communication and Health 1999.
Causes of Risk Misperception about Hormonal Contraceptives
> Lack of understanding of statistics> Psychological factors> Media influence> Factors that affect risk perception and interpretation
Media Influence
> Positive: widespread dispersion of reproductive health information
> Negative: misperception of contraceptive risks– Incomplete information;
“sound bites”– Business of selling news; “if it bleeds,
it leads”– Risks not put in context– TV ads conclude with adverse events
Grimes DA. In: Oral Contraceptives and Breast Cancer 1989.
Degree of OC Discontinuation Related to Media Event
0
2
4
6
8
10
12
14
16
0 1 2 3 4 5 6
Per
cen
tag
e
Months after eventJones EF, et al. Fam Plann Perspect 1980.
Grimes DA. In: Oral Contraceptives and Breast Cancer 1989.
Temporal Relationship Between Product Launch & Reported Adverse Events
Hartnell NR, Wilson JP. Pharmacotherapy 2004.Weber JCP. In: Iatrogenic Diseases 1986.
Nu
mb
er o
f R
epo
rts
400
200
0
82 -
83 2 3 4 5 6 7 8 991
- 92 11 12 13 14 15 16 17
99 -
00
Year/Month
Factors that Affect Perception & Interpretation of Risk
> Factors related to the individual> Factors related to risk presentation> Factors related to the characteristics of the risk
Factors Related to the Individual
> Culture> Literacy level and education> Developmental stage> Human tendencies
– Underestimate effectiveness and overestimate risk of hormonal contraception
– Optimism-pessimism bias
Noone J. Clin Excell Nurse Pract 2000; Hubertus AAMV. Br J Obstet Gynecol 2001; Grimes DA, Snively GR. Obstet Gynecol 1999; Steinberg L. Ann NY Acad Sci 2004; Mann L, et al. J Adolesc 1989; Steinberg L. Trends
Cogn Sci 2005; Edwards JE, et al. Br J Fam Plann 2000; Bowling A, Ebrahim S. Qual Health Care 2001.
Developmental Stage
> By age 15, reasoning is fully developed in hypothetical situations
> Early adolescence: puberty causes increase in reward sensitivity
> Later adolescence: self-regulation systems develop
Steinberg L. Ann NY Acad Sci 2004.Luna B, Sweeney JA. Ann NY Acad Sci 2004.
Factors Related to Risk Presentation
> Framing effects (positive or negative)> Uncertainty> Trust
Edwards A, et al. BMJ 2002.Bennett P. Dept Health UK 1997.
Factors Related to the Characteristics of the Risk
> People worry more about risks that– The individual cannot control– Are involuntary– Are associated with particular dread– Are novel or unfamiliar– Result from man-made sources– Are more easily recalled
Harvard Center for Risk Statistics 2003. Bennett P. In: Risk Communication and Public Health
Estimated & Actual Mortality Rates
Bennett P. In: Risk Communication and Public Health 1999.
Estim
ated
num
ber o
f dea
ths
per y
ear 106
105
104
103
102
10
1106105104103102101
Actual number of deaths per year
BotulismTornado
Smallpox Vaccination
Flood
ElectrocutionAsthma
TB
Pregnancy
Homicide
Motor VehicleAccidents
AllAccidents All Disease
All CancerHeart Disease
StrokeStomach Cancer
Diabetes
Understanding Risk: Relative Effectiveness of Contraceptives
Steiner MJ, et al. Obstet Gynecol 2003.
WHO Decision Aid on Contraceptive Effectiveness
World Health Organization 2006.
Tools: Categories Table
Effectiveness Group Typical Success RateProtection Against
STDs/AIDS
Sterilization (male & female)
More effective(for all users)
no
Implants no
Hormone shot no
Intrauterine device (hormonal) no
Intrauterine device (copper) no
Birth control pills (combined pill & mini) Effective no
Barrier methods
Less effective
yes
Spermicide limited
Natural methods no
Adapted from Steiner MJ, et al. Obstet Gynecol 2003.
Comprehension of Contraceptive Effectiveness by Teaching Method
Pre/post percent improvement in correct score by teaching method
0% 40%
Pill vs.condom
Hormoneshot
vs. pill
Numbers (FDA)
Numbers & categories (WHO)
Categories
Steiner MJ, et al. Obstet Gynecol 2003.
Communicating Contraceptive Effectiveness (cont.)
> Given only effectiveness category information, women overestimated pregnancy risk
> When later shown percentage tables, majority reported rate accurately
> Authors recommended category tools with general range of risk shown within each category
Steiner MJ, et al. Obstet Gynecol 2003.
Understanding Risk: Cardiovascular Adverse Events
> Cardiovascular events: most common major adverse events associated with combined OC use– Venous thromboembolism (VTE) – Stroke– Myocardial infarction (MI)
Farley TMM, et al. Contraception 1998.
Cardiovascular Events
13.6 33.924.348.6
72.8
9.8 24.6
19.7
49.2
45.8
13745.8
137
4.21.7 24.3
Nonsmoker Nonuser Nonsmoker OC user Smoker Nonuser Smoker OC User
Venous thrombo-embolismIschemic strokeHemorrhagic strokeMyocardial infarction
Eve
nts
(p
er m
illi
on
wo
man
-yea
rs)
(Women 30-34 years old)
Farley TMM, et al. Contraception 1998.
Cardiovascular Mortality
10.2
21.8
6.1
12.3
2.7
0.51 1.37.37.32.5
2.7
0.92
Nonsmoker Nonuser Nonsmoker OC user Smoker OC user
Venous thromboembolismIschemic strokeHemorrhagic strokeMyocardial infarction
Dea
ths
(per
mil
lio
n w
om
an-y
ears
)
(Women 30-34 years old)
Farley TMM, et al. Contraception 1998.
Cardiovascular Adverse Events in Context
> Context is important– Incidence is low in reproductive age women, with or
without OC use– Smoking and OC use have a synergistic effect on
cardiovascular event incidence and mortality at all ages
Farley TMM, et al. Contraception 1998.
Cardiovascular Adverse Events: Weighing the Risks & Benefits
> For most women, non-contraceptive benefits of combined hormonal contraceptives outweigh the risks
Burkman R, et al. Am J Obstet Gynecol 2004.
Cardiovascular Adverse Events:Screening for Risk Factors
10.2 6.1
21.821.8
12.3
7.4
2.7
2.7
Smoker OC user Smoker BP Checked OC User
Venous thromboembolismIschemic strokeHemorrhagic strokeMyocardial infarction
Dea
ths
(per
mil
lio
n w
om
an-y
ears
)
(Women 30-34 years old)
Farley TMM, et al. Contraception 1998.
Communicating Risk: The How To’s
What to ask Patient needs & concerns
What to consider Relevant factors
What to use Tools
What to do Guidance
Patient Needs & Concerns: What to Ask
> How important is it to avoid pregnancy right now?> How important is privacy regarding contraception?> Do you have concerns about a particular contraceptive? > What side effects are you willing to accept?> Are you comfortable with methods that require insertion
in the vagina?
Factors Relevant to Risk Communication
> Level of trust> Framing effects> Cultural, literacy, and developmental effects> Not strictly an intellectual issue> Risk comparisons can be misleading
Tools: Numerical Data
> Try different ways to explain numerical data
SAY “3 of every 10 women develop nausea”
ALSO SAY “You have a 30% chance of nausea”
Gigerenzer G, Edwards A. BMJ 2003.
Tools: Numerical Data (cont.)
> Avoid shifting denominators in proportions
Grimes DA, Snively GR. Obstet Gynecol 1999. Gigerenzer G, Edwards A. BMJ 2003.
SAY “Headache developed in 3 of every 1000 women”
NOT “Headache developed in 1 of every 333 women”
Tools: Numerical Data (cont.)
> Use absolute risk
Gigerenzer G, Edwards A. BMJ 2003; Farley TMM, et al. Contraception 1998; Sloman SA, et al. Organizational Behavior and Human Decision Processes 2003.
SAY “Of every 1 million OC users, 4 develop heart attack each year compared with 2 nonusers.”
NOT “OC use doubles the risk of heart attack”
Tools: Descriptive Terms
Risk level
High <1 in 100
Moderate 1 to 10 in 1,000
Low 1 to 10 in 10,000
Very low 1 to 10 in 100,000
Minimal 1 to 10 in 1 million
Calman KC. BMJ 1996.Berry DC, et al. Drug Saf 2003.
Tools: Risk Comparisons
Skydiving 100 Driving 20 Pregnancy 11.5Riding a bicycle 0.8Airplane crash 0.4Using OC* 0.06
*Nonsmoker, under age 35
Trussell J, Jordan B. Contraception in press. Chang J, et al. MMWR 2003.
Harvard Center for Risk Analysis 2006.Bennett P. In: Risk Communication and Public Health 1999.
Annual Risk of Death (per 100,000)
Tools: Diagrams
> Categories table> Numbers and categories table> Flower diagram> Paling Perspective Scale> Paling Palette
Tools: Categories Table
Effectiveness Group Typical Success RateProtection Against
STDs/AIDS
Sterilization (male & female)
More effective(for all users)
no
Implants no
Hormone shot no
Intrauterine device (hormonal) no
Intrauterine device (copper) no
Birth control pills (combined pill & mini) Effective no
Barrier methods
Less effective
yes
Spermicide limited
Natural methods no
Adapted from Steiner MJ, et al. Obstet Gynecol 2003.
Tools: Numbers & Categories TableEffectiveness Group Family Planning Method
Typical-Use Rate of Pregnancy
Lowest Expected Rate of Pregnancy
More effective(for all users)
Male and female sterilization 0.2%-0.5% 0.1%-0.5%
Implants 0.1% 0.1%
Hormone shot 0.3% 0.3%
Intrauterine devices (copper and progesterone) 0.8%-2% 0.6%-1.5%
Effective Birth control pills 5% 0.1%-0.5%
Less effective
Male latex condoms 14% 3%
Diaphragm 20% 6
Cervical cap 20%-40% 9%-26%
Female condoms 21% 5%
Spermicide 26% 6%
Withdrawal 19% 4%
Natural family planning 20% 1%-9%
No method 85% 85%
Adapted from Steiner MJ, et al. Obstet Gynecol 2003.
1 in 1T1 in 10B 1 in 1B
1 in 100M
1 in 10M
1 in 100K
1 in 10K
1 in 100 1 in 10 1 in 1
Tools: Paling Perspective Scale®
Paling J. BMJ 2003.
Fig. 2 Paling Perspective Scale® - for giving perspective to risks of low order of probability.
Risks from smallpox: for the 115M Americans over the age of 30 - previously vaccinated and DO NO live in a major metropolitan area
Look at the consequencesas well as the odds
Risk of death from vaccination:1 in 2 million
Risk of Smallpox Infection: 1 in 100M people (or less)
Death from Smallpoxif not vaccinated post exposure: 1 in 1.7B (or less)
Death from Smallpoxif vaccinated post exposure: 1 in 100B (or less)
Estimates of Specific Risks
RISK INCREASING
1 in 100B 1 in 1M 1 in 1K
Tools: Paling Palette®
Paling J. BMJ 2003.
Guidance
> Remember to present absolute risk > Use different forms of numerical data to explain risk> Be aware of framing effects> Use risk comparisons with care> Have multiple, complementary tools available
Decision Aid for Risk Communication
1. Clarify situation2. Provide information
– “On the benefit side…”– “On the harm side…”
3. Clarify patient’s values4. Screen for implementation problems
O’Connor A, et al. BMJ 2003.
Case Study: Michelle Gavin
> 19-year-old college student> Using patch for 6 months
O’Connor A et al. BMJ 2003.
“I want off the patch—it killed that girl in New York”
Case Study: Michelle Gavin
1. Clarify situation2. Provide information 3. Clarify patient’s values4. Screen for implementation problems
O’Connor A et al. BMJ 2003.
Tips for Effective Communication
Center for Urban Transportation Studies UWM 2006.
Be an active listener
Eliminate internal & external distractions
Present information in several ways
Ensure understanding
zKnow your purpose
Communication: What Patients Want
> Explain the reasoning behind your questions> Present the options (pro and con) and let her know what she
can do> Treat woman as a partner
Pro Choice Public Education Project 2004.
Tips for Communicating About Alarming Media Reports
> Gather reputable information: PPFA, ARHP, ACOG, CDC
> Review relevant editorials in peer-reviewed journals
> Help patients gain perspective
Learning Objectives
1. Define relative risk, attributable risk and absolute risk
2. List three different means of presenting risk and describe the advantages of each
3. Identify at least three patient characteristics to consider when counseling about risks and benefits
4. Describe at least one patient education tool that can be used to effectively communicate the risks and benefits of hormonal contraceptives
Summary
> A misperception of risks about contraception may unnecessarily limit a women’s choices
> Risk perception is affected by a number of factors> Clinicians should consider relevant factors and expert
guidance about risk communication> Several tools are available to aid
risk communication
A Final Thought
Two times a very rare event is still a very rare event.
David Grimes, MD 2006.