Student Presentations
SSRCA - 2014
Summer Student Research and Clinical Assistantship Program
University of Wisconsin
School of Medicine and Public Health
Department of Family Medicine
Life course predictors of asthma risks in a
large clinical population: age, sex, and BMI
Saamia Masoom, Aman Tandias, Jarjieh Fang, Dr. David Hahn,
Dr. Theresa Guilbert, Dr. Yingqi Zhao & Dr. Larry Hanrahan
Department of Family Medicine, University of Wisconsin School of Medicine and Public
Health
Summer Student Research and Clinical Assistantship (SSRCA) Program
Summer 2014
University of Wisconsin Department of Family Medicine
Background
Family
history of
asthma
BMI
History of
allergies
Asthma
Exposure
to
allergens
Others
Rasmussen & Hancox (2014)
University of Wisconsin Department of Family Medicine
Background
BMI
Asthma
(Control)
Saint-Pierre, et. Al (2006)
University of Wisconsin Department of Family Medicine
Background
Sex
BMI
• Pediatric males
• Adult females
Asthma
(Control)
Sex hormone interactions? Linked underlying inflammation?
Egan, et. Al (2013), Chen, et. Al (2013), Beckett, et. Al (2001), Zierau, et. Al (2012)
University of Wisconsin Department of Family Medicine
Purpose
Does this relationship hold in a large clinical population?
Sex
BMI
• Pediatric males
• Adult females
Asthma
(Control)
University of Wisconsin Department of Family Medicine
Methods
University of Wisconsin Electronic Health Record Public
Health Information Exchange (UW eHealth-PHINEX)
Clinical Data
• UW Departments of Family Medicine,
Internal Medicine, Pediatrics
• 2007-2012
Community Level Data
• US Census Bureau
• Esri Business Analyst
Guilbert, et. Al (2012), Tomasello, et. Al (2014)
University of Wisconsin Department of Family Medicine
Methods
• ≥2 encounters ≥2 years
apart
PHINEX
• ICD-9 493.xx
Asthma
Controlled
No Asthma
Uncontrolled
• ≥2 adverse events ≥90 days
apart
University of Wisconsin Department of Family Medicine
Methods
Stratified by:
Age
Group
• 0-4, 5-11, 12-17, 18-40, 41-59, 60+
BMI
Category
• Normal
• Obese
* According to CDC age-appropriate guidelines
Sex
• Male
• Female
University of Wisconsin Department of Family Medicine
Results
298,847
PHINEX
40,011
Asthma
No Asthma
(13.4%)
6,554
Controlled
Uncontrolled
(16.4% of patients
with asthma)
University of Wisconsin Department of Family Medicine
Asthma Prevalence vs. Age (BMI x Sex)
30.0%
25.0%
Asthma Prevalence
20.0%
Normal BMI Female
15.0%
Obese Female
Normal BMI Male
Obese Male
10.0%
5.0%
0.0%
05 to 11
12 to 17
18 to 40
41 to 59
Age as of last BMI measurement
University of Wisconsin Department of Family Medicine
60+
Odds ratio of asthma prevalence in obese patients compared to
normal BMI vs. age, stratified by sex
2.5
2
Odds Ratio
1.5
Male
Female
1
0.5
0
05 to 11
12 to 17
18 to 40
Age as of last BMI measurement
41 to 59
University of Wisconsin Department of Family Medicine
60+
Uncontrolled Asthma Prevalence vs. Age (BMI x Sex)
35.0%
Uncontrolled Asthma Prevalence
30.0%
25.0%
20.0%
Normal BMI Female
Obese Female
Normal BMI Male
15.0%
Obese Male
10.0%
5.0%
0.0%
05 to 11
12 to 17
18 to 40
41 to 59
Age as of last BMI measurement
University of Wisconsin Department of Family Medicine
60+
Odds ratio of uncontrolled asthma prevalence in obese patients
compared to normal BMI vs. age, stratified by sex
3
2.5
Odds ratio
2
1.5
Male
Female
1
0.5
0
05 to 11
12 to 17
18 to 40
Age as of last BMI measurement
41 to 59
University of Wisconsin Department of Family Medicine
60+
Summary
• Asthma prevalence
• Higher in obese pediatric males and obese adult
females
• OR of association between obesity and asthma
• Similar in pediatric males/females
• Significantly greater in adult females
• Similar but non-significant patterns observed for
uncontrolled asthma
University of Wisconsin Department of Family Medicine
Implications
• Alignment of a large, clinical population with
smaller epidemiological studies
• Epidemiological predictive value
• Future targeted diagnosis and treatment methods
• Biology of association
• Female sex hormone interaction vs. underlying
inflammation linked to both asthma and obesity
University of Wisconsin Department of Family Medicine
References
Beckett WS, Jacobs DR, Yu X, Iribarren C, Williams OD (2001) Asthma Is Associated with Weight Gain in Females but Not Males,
Independent of Physical Activity. Am J Respir Crit Care Med 164: 2045–2050. doi:10.1164/ajrccm.164.11.2004235.
Chen YC, Dong GH, Lin KC, Lee YL (2013) Gender difference of childhood overweight and obesity in predicting the risk of incident
asthma: a systematic review and meta-analysis. Obes Rev 14: 222–231. doi:10.1111/j.1467-789X.2012.01055.x.
Egan KB, Ettinger AS, Bracken MB (2013) Childhood body mass index and subsequent physician-diagnosed asthma: a systematic
review and meta-analysis of prospective cohort studies. BMC Pediatr 13: 121. doi:10.1186/1471-2431-13-121.
Guilbert TW, Arndt B, Temte J, Adams A, Buckingham W, et al. (2012) The theory and application of UW ehealth-PHINEX, a clinical
electronic health record-public health information exchange. WMJ Off Publ State Med Soc Wis 111: 124–133.
Rasmussen F, Hancox RJ (2014) Mechanisms of obesity in asthma. Curr Opin Allergy Clin Immunol 14: 35–43.
doi:10.1097/ACI.0000000000000024.
Saint-Pierre P, Bourdin A, Chanez P, Daures J-P, Godard P (2006) Are overweight asthmatics more difficult to control? Allergy 61: 79–
84. doi:10.1111/j.1398-9995.2005.00953.x.
Tomasallo CD, Hanrahan LP, Tandias A, Chang TS, Cowan KJ, et al. (2014) Estimating Wisconsin Asthma Prevalence Using Clinical
Electronic Health Records and Public Health Data. Am J Public Health 104: e65–e73. doi:10.2105/AJPH.2013.301396.
Zierau O, Zenclussen AC, Jensen F (2012) Role of female sex hormones, estradiol and progesterone, in mast cell behavior. Mol Innate
Immun 3: 169. doi:10.3389/fimmu.2012.00169.
University of Wisconsin Department of Family Medicine
Dropout Characteristics of Opioid Dependent
Offenders in Community-Based Treatment
Shawn Wayne, M2
Randy Brown, MD, PhD
Opioid Epidemic
Role Drug Treatment Court (DTC)
• An individual with untreated addiction to illicit substances
commits an average of 63 crimes per year.2
– Intervention!
• Reduces recidivism and illicit drug use, through obligatory,
–
–
–
–
Counseling
Medical treatment
Judicial supervision
Social services
• In exchange for dismissal/ reduction of charges
Medical Treatment
Medications:
• Methadone [Federally accredited facilities]
• Suboxone (Buprenorphine/ Naloxone)
Pilot Study:
• Suboxone Tx in physicians office (PO) effective, however did not
reduce HIV risk behaviors
Specialist Stabilization Period:
• Optimizing treatment, given limited resources
• Compare Suboxone Tx PO to Suboxone Tx Specialty Care followed
by Tx PO.
Study Structure
Opioid Offenders
Dane County Drug
Treatment Court
Subjects
Consented and
Randomized
Suboxone Tx
MHS-3 Months
PO-7 Months
Treatment (Tx):
• Suboxone (Buprenorphine/ Naloxone)
Study Arms:
• Physician Office (PO) for 10 months
• Specialty Care at Madison Health
Services (MHS) followed by 7 months
of PO care.
Data Collection
• Baseline
• Monthly
Suboxone Tx
PO-10 Months
Data Collection Instruments:
Surveys:
• TLFB (Timeline Feedback)
– Measures drug-use for the previous 14-days
• ASI (Addiction Severity Index)
– Accesses drug use, SES, legal circumstances
• CMR (Circumstances, Motivation, and Readiness)
• RAB (Risk Assessment Battery)
– HIV/AIDS risk assessment
Court Reports
Unforeseen Difficulties
• Recruitment
– 18 unique subjects enrolled since November 2013
– Reassessed inclusion criteria
– Restructuring of Dane County DC in December 2013
• Potential impediment to recruitment process
• Dropout
– 50% dropout (DO) prior
– Transportation
– Recidivism
– Inability to fill prescription
– Expected DO (20-40%) with
Suboxone Tx
Dropout Comparisons:
No difference in rate of DO between Tx
Demographics:
• No difference in age or gender between DO status groups
Baseline Drug Use:
• No difference in drug use 14-days prior to intake between DO (p=0.36)
• Heroin use was not statistically different between Tx or DO status
Other:
• Individuals with self-reported drug participated depression, anxiety, and
confusion, may be less likely to drop out
• Motivation difference observed between DO statuses, on the importance of
stopping use over everything else (p=0.049)
Significance of Motivation:
• MHS
• A lack of self-reported motivation associated with DO status
amongst participants assigned to MHS. (N=8)
–
–
–
–
Importance of treatment (p=0.013)
Serious legal problems (p=0.035)
Importance of legal counsel (p=0.031)
Outside interference (p=0.057)
• No significant difference between DO status across Tx
Discussion:
Findings:
• No difference in DO status between Tx arms
• Heroin use and age not be prognostic of DO
• Motivation significant in DO outcome for MHS Tx
Rationale:
• MHS requires daily dosing, a more intensive treatment model than weekly PO
• Motivation, thus may be important for predicting success at MHS
Conclusions:
• Preliminary support of predictive baseline figures between Tx arms
• Personalized DC treatment
Limitations:
• Sample size
• Baseline Comparison
• Extraneous Circumstances (Transportation, Legal, Family etc.)
Future Investigation: Criminality
• Drug use and criminality
– Income generating crimes, disorderly conduct, possession, etc.
• Predictive value of Criminality
– DO, recidivism, positive UAs
Is Criminality a prognostic marker for Tx arms?
• Increased judicial supervision reduced positive UAs and
sanctions amongst other “high risk” DO participants
Does daily dispensing at MHS may have similar effect?
Future Investigation: Criminality
Hypothesis: MHS Tx improves DC outcomes; graduation rate,
recidivism, and drug use, amongst DC participants with a
more extensive criminal history than PO Tx.
• IRB revision
– CCAP and Court Reports
• Criminality metric (adapted Gordon et al. 2013)
– Frequency
– Variety
– Severity
To be continued... Questions?
Literature Cited
•
•
•
•
•
•
•
•
Brown, Randall. Community‐Based Treatment for Opioid Dependent Offenders: A Pilot Study. The
American Journal on Addictions, 22: 500–502, 2013.
SAMHSA. Results from the 2008 National Survey on Drug Use and Health: National Findings.
Rockville, MD: Substance Abuse and Mental Health Services Administration, Office of Applied
Studies;2009.
Nurco DN. A long-term program of research on drug use and crime. Subst. Use Misuse. Jul
1998;33(9):1817- 1837.
Stein MD, Cioe P, Friedmann PD. Buprenorphine retention in primary care. J Gen Internal Med.
2005;20:1038–1041.
Sinha R, Easton C. Substance abuse and criminality. Journal of the American Academy of Psychiatry
& the Law. 1999;27(4):513-526.
Brecht ML, Anglin MD, Wang JC. Treatment effectiveness for legally coerced versus voluntary
methadone maintenance clients. The American Journal of Drug and Alcohol Abuse. 1993;19(1):89106.
“Early-Phase Outcomes from a Randomized Trial of Intensive Judicial Supervision in an Australian
Drug Court,” Jones C.G.A. (2013) Criminal Justice and Behavior, 40 (4), pp. 453-468.
Gordon, Michael. “The Severity, Frequency, and Variety of Crime in Heroin-Dependent Prisoners
Enrolled in a Buprenorphine Clinical Trial” 2012. The Prison Journal December 2013 vol. 93 no. 4
390-410.
HOW DOCTORS BIRTH
How our experiences shape our practice
Carly Kruse, MSc, Ildi Martonffy, MD
Background and Objectives
• History of birthing stories as a space for women to share
experiences
• Ken Murray’s “How Doctor’s Die: It’s not like the rest of
us, but should be”1
• Descriptive study utilizing both qualitative and quantitative
tools to explore birthing experience of female physicians
• Objectives:
1.
2.
3.
4.
Examine birthing preferences and birthing realities
Explore maternal care approaches before and after motherhood
Investigate breastfeeding expectations
Analyze changes in breastfeeding counseling due to personal
experiences
Methods
• 29 question survey distributed to members of UW Family
Medicine Department, UW Obstetrics and Gynecology
Department, and the Academy of Breastfeeding Medicine
• 45 physicians and 1 Nurse practitioner responded
• 43 eligible participants based on medical specialty, gender, and
experience of at least one live birth delivery
• 30 minute in-person follow-up interviews
• General interview guide approach with standardized open-ended
questions
• 20 participants interested
• 7 completed
Participants
Age at
Participation
25-34
35-44
45-54
>54
n
%*
5
15
11
7
11.6
34.9
25.6
16.3
Current Residence
n
%*
Wisconsin
Outside WI
29
15
67.4
34.9
Specialty
n
%*
Family Medicine
OB/GYNE
Other
Multiple
28
8
4
2
65.1
18.6
9.3
4.7
Relationship Status
n
%*
Single
Domestic Partnership
Married
Separated/Divorced
Age at start of
residency
20-24
25-29
30-34
0
2
41
1
0
4.7
95.3
2.3
n
%*
2
34
5
4.7
79.1
11.6
Age at first birth
n
%*
15-19
20-24
25-29
30-34
35-39
1
4
13
19
4
2.3
9.3
30.2
44.2
9.3
*Percentages are calculated using n=43 for all questions whether or not all participants
responded to that question
Prenatal Methods
Percentage of respondents utilizing prenatal support
methods during one or more pregnancy
100.0%
80.0%
60.0%
40.0%
20.0%
71.4%
50.0%
35.7%
25.0%
14.3%
0.0%
0.0%
Birthing Class
Birth Plan
Fam Med
Doula
OBY/GYNE
National average of doula utilization = 6%2
“Met with a doula to talk about letting go and not always being in
control” – Interviewee 006
Percentage of survey participants
(n=43)
Delivery Methods
100.0
Type of Delivery for First Birth
90.0
80.0
70.0
58.1
60.0
50.0
40.0
30.0
20.0
4.7
10.0
18.6
11.6
4.7
0.0
Non-instrumental
Vaginal
Instrumental Vaginal Elective Cesarean
Section
Emergency
Cesarean Section
Non-emergent,
unplanned Cesarean
Section
Interventional Method used during one or more deliveries
21.88
Episiotomy
Vacuum Extraction
12.5
Forceps
12.5
Artificial Rupture of the
membrane
53.13
18.8
Intrauterine Pressure Catheter
28.1
Cervican Ripening
65.6
Pitocin
0
10
20
*n=32 with 63 responses
30
40
50
60
70
% of Respondents reporting use of intervention
80
90
100
Breastfeeding
• All participants breastfed for at least 1 of their births and
90.7% breastfed all babies
• 76.7% breastfed for more than 6 months on average
“There was no question whether or not I would breastfeed.”
– Interviewee 001
• Publically shamed for breastfeeding in public while
simultaneously feeling social pressure to breastfeed
exclusively (Interviewees 001, 002, 004)
• Undertrained and Unknowledgeable
“she [my daughter] was teaching me about breastfeeding”
– Interviewee 003
• Expected “to be successful” (009) and breastfeed
“exclusively” (008)
Impact on Care Practices
• Prenatal Counseling
• More breastfeeding education
• Fewer birth plans:
“Goal of labor that everyone end up healthy, but how we get there is
unimportant” – Interviewee 007
• Labor Support
• Woman-centered approaches
“take more cues from the laboring woman” -005
• Normalization of deliveries and expectations
• Breastfeeding Counseling
• Remove social pressures: “Stop shoulding yourself” – Interviewee 004
• Become more informed
• Pediatric Care
“I considered my most important job as being a mother. My profession
was being a doctor. These were mutually reinforcing roles” -015
Discussion
• Overall approach to care today shaped by experience of
entire course of pregnancy from prenatal to postnatal to
motherhood
• Three common themes
• Increased Empathy
“I can help frame their expectation for their own experience better than I
could before my own pregnancies and births” -006
• Increased awareness of social pressure put on women to
parent or birth in a particular way
“Mostly that I try to reassure women that the societal pressures about what
pregnancy, labor, birth and new motherhood look like are kind of BS ways to
make women feel bad about themselves” -001
• Increased advocacy for empowerment
Because I was able to achieve my birth and breastfeeding goals, I believe
other women have the power to do it too, when they have the right support” 002
Limitations
• Small sample size
• Generalizability
• Self-selection bias
• Family Medicine participants = 65.1%
• OB/GYNE Participants = 18.6%
• Retrospective self-reporting
Conclusion
• Do doctors birth differently than other women?
• Evidence that personal experiences construct the way
physicians approach and counsel patients
• Future research:
• How successful are physicians with leveraging empathy to address
empowerment?
• How do we teach non-parents in medical training all that doctors have
garnered from personal experiences?
“It’s hard for physicians to have a clue if they haven’t breastfed
before—a nuanced skill that is learned and passed on through
generations.”
- Interviewee 001
References
1.
2.
3.
4.
Murray, K. How Doctors Die: It’s Not Like the Rest of Us, But It
Should Be. Zocalo Public Square. Nov. 2011 retrieved from
<http://www.zocalopublicsquare.org/2011/11/30/how-doctorsdie/ideas/nexus/>.
Declercq, E., et al. Listening to Mothers III Pregnancy and Birth:
Report of the Third National U.S. Survey of Women’s Childbearing
Experiences. May 2013 retrieved from
<http://transform.childbirthconnection.org/wpcontent/uploads/2013/06/LTM-III_Pregnancy-and-Birth.pdf>.
Osterman, M., et al. Primary Cesarean Delivery Rates, by State:
Results from the Revised Birth Certificate, 2006-2012. National
Vital Statistics Reports. 63(1) Jan. 2014 retrieved from
<http://www.cdc.gov/nchs/data/nvsr/nvsr63/nvsr63_01.pdf>.
Division of Nutrition, Physical Activity, and Obesity. Breastfeeding
Report Card: United States 2013. National Center for Chronic
Disease Prevention and Health Promotion. 2013 retrieved from
<http://www.cdc.gov/breastfeeding/pdf/2013breastfeedingreportcar
d.pdf>.
MENTAL HEALTH
PREDICTS
COMMON COLD
OCCURRENCE
By Lizzie Maxwell
Background

The cost of ARI in US
 $40

billion non-influenza ARI1
Poor mental health as risk factor for ARI
 Yuki
Adam et al.
 DSM-IV
 Sheldon
mental disorders  increased ARI incidence2
Cohen et al.
 Increased
stress  increased ARI incidence3
Rakel D, Mundt M, Ewers T, et al. Value associated with mindfulness meditation and moderate
exercise intervention in acute respiratory infection: the MEPARI study. 2013
Methods

MEPARI and MEPARI-2
 Spearman
rank-order correlation
 Psychosocial
Measures (baseline)
 SF12
 ARI
Measures (throughout study)
 Incidence
 Duration and Severity
SF-12 Health Survey
12 Questions
 Generic
 Health-Related Quality of Life
 2 Summary Scores:

Physical
Mental
SF-12 Mental

During the last 4 weeks did you…
 Accomplish
less than you would like?
 Do work/activities less carefully than usual?

How many times over the last 4 weeks
have you…
 Felt
calm and peaceful?
 Had a lot of energy?
 Felt downhearted and blue?
ARI Outcomes

Incidence
 Do
you think you have/are coming down with a cold
 1 of 4 common cold symptoms
 Score > 2 on Jackson Scale


Duration
Severity
 WURSS-24
Demographics
n
353
% Female
77.6%
Mean Age
54.2 (10.4)
% Education < Bachelors
degree
% Income < $50,000
71.4%
58.1%
SF-12 Mental
Results
Graph courtesy of Joseph Chase
# ARI
Explanations




Stress as a common risk factor4
Mental illness’ effect on immunity5
Unfounded symptoms6
Healthy vs unhealthy behaviors4
Limitations

Analysis has thus far included intervention groups
 Potential

effects of interventions?
Next steps…
Results
Instrument
Incidence rho
(p-value)
Duration rho
(p-value)
Severity rho
(p-value)
SF-12 Mental
-0.11 (0.045)
-0.09 (0.080)
-0.09 (0.078)
PANAS -
0.09 (0.086)
0.08 (0.137)
0.11 (0.040)
PHQ 9
-0.06 (0.230)
-0.02 (0.663)
0.01 (0.913)
MAAS
-0.11 (0.045)
-0.1 (0.065)
-0.09 (0.095)
Table courtesy of Joseph Chase
References






1. Rakel D, Mundt M, Ewers T, et al. Value associated with mindfulness
meditation and moderate exercise intervention in acute respiratory infection:
the MEPARI study. Family Practice. 2013; 30(4): 390-7
2. Adam Y, Meinlschmidt G, Lieb R. Associations between mental disorders and
the common cold in adults: A population-based cross-sectional study. Journal of
Psychosomatic Research. 2012; 74(2013): 69-73.
3. Cohen S, Tyrrell DA, Smith AP. Psychological stress and susceptibility to the
common cold. New England Journal of Medicine. 1991; 325(9): 606-612.
4. Cohen S, Miller G. (2001). Stress, immunity, and susceptibility to upper
respiratory infection. In Psychoneuroimmunology (3rd Ed., Vol. 2, pp: 499-509).
Academic Press
5. Copeland W, Shanahan L, Costello EJ. Cumulative depression episodes
predicts later c-reactive protein levels: a prospective analysis. Biology
Psychiatry. 2012; 71(1):15-21.
6. Cohen S, Doyle W, Turner R, et al. Emotional style and susceptibility to the
common cold. Psychosomatic Medicine.2003; 65(4):652-657.
Community Health Assessment in
the Wausau Hmong Population:
Preliminary Survey of Wausau
Hmong Community Leaders
Pajin Vang MPH, MD candidate
Dr. Kevin Thao MD, MPH
SSRCA Department of Family Medicine
Today’s Talk
• Introduction
– Who are Hmong?
– What is HHC
– What is SHOW
• MiniSHOW of Wausau Hmong community
• Preliminary Surveys
Who are Hmong?
• Hmong History
– U.S. Hmong cultural ancestry as ethnic minority in
China
– Resettled in mountains of Laos, Thailand, North
Vietnam
– After Vietnam War and Secret War, fled and relocated
to Thailand refugee camps
– Came to U.S. as political refugees after 1975
– Hmong are largest ethnic Asian population in
Wisconsin
What is HHC
Hmong Health Council
• Central Wisconsin
• South Central Wisconsin
• Hmong Health Council( HHC) is an
independent coalition of Hmong healthcare
providers, community leaders, members and
partners working together to improve the
health of Hmong Americans
What is SHOW?
• Survey of the Health of Wisconsin
• Gathers data across Wisconsin
• Annual surveys
– up to 1000 people/year age 21-74
• Measures:
–
–
–
–
–
health behaviors,
mental health,
access to health care,
beliefs in health care,
environment
• Partner with HHC
Target Population:
Central Wisconsin Hmong
• Midwest has largest Hmong population in the
nation
– Wausau is 2nd largest Hmong community in Wisconsin
• Hmong Health issues
– Pre migration/refugee camps
– Post migration
• Increased risk for obesity, hypertension,
hyperlipidemia, cardiovascular disease, diabetes
• Mini Health Assessment
– Pilot project in Wausau Hmong community
– General health assessment of Hmong Wisconsin
Community using SHOW methods
– 10-30 households
– Will we be able to reproduce similar study to
SHOW’s pilot neighborhood study?
• Preliminary Surveys
– Introduce the project to the community leaders
• 10 community leaders to be surveyed
– Will they want to participate?
– Will they answer all the questions?
– Survey translated to Hmong
What we learned so far
• Survey takes 2 hours in Hmong, 1hour in
Hmonglish
• Some things cannot be directly translated
• Some concepts are difficult to explain or
understand:
– Scales (rate from 0-10)
– Genes/DNA
Questions?
• References
– http://hmonghealthcouncil.wordpress.com/about
/
– http://www.med.wisc.edu/show/about-survey-ofthe-health-of-wisconsin/36193
– http://www.hndinc.org/cmsAdmin/uploads/dlc/H
ND-Census-Report-2013.pdf
– Her C, Mundt M. Risk prevalence for type 2
diabetes mellitus in adult Hmong in Wisconsin: a
pilot study. WMJ 2005;104(5):70-7.
Disease-Management & Financial Implications
of the Addition of a Health Coach/Nutritionist
in Two Family Medicine Clinics
Kristin Magliocco
Dennis Baumgardner MD, Tiffany Mullen DO,
Kristen Reynolds MD
Presentation Outline
•
•
•
•
•
•
•
•
Background
Expected Outcomes
Methods
Data Collection
Preliminary Data
Limitations of the Study
Concluding Remarks
Literature Cited
Background: Chronic Disease
•
•
•
•
80% of healthcare spending1
Leads to preventable deaths2
Lifestyle changes
Patients’ disease maintenance goals are not met1
▫ Diabetes: 43%
▫ Hypertension: 50%
▫ Hyperlipidemia: 80%
Background: Self-Management Support
• “Systematic provision of education and
supportive interventions to increase patients’
skills and confidence in managing their health
conditions”
-Institute of Medicine
• Improves clinical outcomes for chronic disease4
Background: Health Coaching
•
•
•
•
•
Empowerment1
Motivational interviewing2
Active role for patient3
Goal setting for what is feasible in daily life5
Follow-up7,8
Expanding the Healthcare Team
• Time is limiting factor for clinicians6
• Non-clinician personnel5,6,7
▫
▫
▫
▫
Medical Assistants1
Dietitians9
Medical/Nursing Students10
Successful Peers11,12
• Dual-trained Nutritionist/Health Coach
Expected Outcomes
• Primary outcome: Improved clinical outcomes
• Secondary outcome: Financial benefits for patients
Methods
•
•
•
•
Retrospective chart review
Each patient is own control
2 integrative Family Medicine clinics
Referrals to Nutritionist/Health Coach by PCP
▫ Inclusion Criteria by Diagnosis





Diabetes
Hypertension
Hyperlipidemia, Hypercholesterolemia
Metabolic Syndrome
Obesity (BMI > 30)
Data Collection
Preliminary Data
6.2 ± 0.316
Preliminary Data
129.38 ± 8.876
82.40 ± 3.978
Preliminary Data
211.71 ± 30.587
53.86 ± 13.459
129.86 ± 39.599
140.86 ± 71.913
Preliminary Data
36.62 ± 7.915
Limitations of the Study
• Low patient enrollment so far
• Cash payments for appointments
▫ Creates biases
• Variation in follow-up
▫ Follow-up shown to be essential14
Concluding Remarks
• Study is ongoing
• Potential future impact for chronic disease
Literature Cited
1.
2.
3.
4.
5.
6.
7.
8.
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11.
12.
13.
14.
Willard-Grace R, DeVore D, Chen EH, Danielle H, Bodenheimer T, and Thom DH.The effectiveness of medical assistant health
coaching for low-income patients with uncontrolled diabetes, hypertension, and hyperlipidemia: protocol for a randomized controlled
trial and baseline characteristics of the study population. BMC Family Practice 2013, (14):27.
Bennett H, Laird K, Margolius D, Ngo V, Thom DH, and Bodenheimer T. The effectiveness of health coaching, home blood pressure
monitoring, and home-titration in controlling hypertension among low-income patients: protocol for a randomized controlled trial.
BMC Public Health 2009, (9): 456.
Howard LM and Hagen BF. Experiences of person with type 2 diabetes receiving health coaching: an exploratory qualitative study.
Education for Health 2012, 25(1): 66-69.
Norris SL, Engelgau MM, Narayn KMV. Effectiveness of self-management training in type 2 diabetes. Diabetes Care 2001, 24(3): 561587.
Chen EH, Thom DH, Hessler DM, Phengrasamy L, Hammer H, Saba G, and Bodenheimer, T. Using the teamlet model to improve
chronic care in an academic primary care practice. Journal of General Internal Medicine 2010, 25 Suppl 4:S610-614.
Yarnall KSH, Ostbye T, Krause KM, Pollak KI, Gradison M, Michener JL. Family physicians as team leaders: “time” to share the care.
Prev Chronic Dis. 2009, 6(2): A59.
Margolius D, Wong J, Goldman ML, Rouse-Iniguez J, and Bodenheimer T. Delegating responsibility from clinicians to nonprofessional
personnel: the example of hypertension control. Journal of the American Board of Family Medicine 2012, 5(2): 209-215.
Margolius D, Bodenheimer T, Bennett H, Wong J, Ngo V, Padilla G, and Thom DH. Health coaching to improve hypertension
treatment in a low-income, minority population. Annals of Family Medicine 2012, 10(3): 199-205.
Battista MC, Labonte M, Menard J, Jean-Denis F, Houde G, Ardilouze JL, and Perron P. Dietitian-coached management in
combination with annual endocrinologist follow up improves global metabolic and cardiovascular health in diabetic participants in 24
months. Applied Physiology, Nutrition, and Metabolism 2012, 37(4): 610-620.
Leung LB, Busch AM, Nottage SL, Arellano N, Glieberman E, Busch NJ, and Smith SR. Approach to antihypertensive adherence: a
feasibility study on the use of student health coaches for uninsured hypertensive adults. Behavioral Medicine 2012, 38(1): 19-27.
Leahey TM and Wing RR. A randomized controlled pilot study testing three types of health coaches for obesity treatment: professional,
peer, and mentor. Obesity 2013, 21(5): 928-934.
Ghorob A, Vivas MM, De Vore D, Ngo V, Bodenheimer T, Chen E, and Thom DH. The effectiveness of peer health coaching in
improving glycemic control among low-income patients with diabetes: protocol for a randomized controlled trial. BMC Public Health
2011, (11):208.
Evans JG, Sutton DR, Dajani LH, Magee JS, Silva RA, Roura MF, Wadud K, Pucell JA, Travaglini S, Segel SA, Sultan S, Roffman MS,
Ayad SS, Boria-Hart NL, and Smith SM. A novel endocrinology-based wellness program to reduce medication expenditures and
improve glycemic outcomes. Diabetes & Metabolic Syndrome: Clinical Research & Review 2013, (7): 87-90.
Siminerio L, Ruppert KM, and Gabbay RA. Who can provide diabetes self-management support in primary care? Findings from a
randomized controlled trial. The Diabetes Educator 2013, 39(5): 705-713.
Questions?
NEGATIVE PAP SMEAR,
POSITIVE HPV:
WHAT DOES IT MEAN?
Lindsey Anderson
Faculty Mentor: Sarina Schrager, M.D., M.S.
CERVICAL CANCER
 2010 Incidence: 12,200 cervical cancer diagnoses
 2010 Mortality: 4,200 deaths
 Easily treated if caught early
 Human papilloma virus (HPV) infection prerequisite
 Cervical intraepithelial neoplasia I, II, III (CIN)
 HPV 16, 18, 31, 33, 45
CERVICAL CANCER SCREENING
 Pap smear cytology
 Negative
 Atypical squamous cells of undetermined significance (ASCUS)
 Low grade squamous intraepithelial lesion (LSIL)
 High grade squamous intraepithelial lesion (HSIL)
 HPV DNA tests
 16, 18 DNA genotyping
 Follow-up
 Conization (Cone biopsy)
 Loop Electrosurgical Excision Procedure (LEEP)
 Hysterectomy
SCREENING GUIDELINES
 New guidelines in place 2012
 Co-testing for women ages 30-65
 Hope to decrease number of colposcopies
 Both negative = co-test again in 5 years
CHART REVIEW
 Case finding with data lists from all UW clinics
 DFM patients with colposcopies done
 DFM patients with pap smears done
 November 2012-April 2014
785 charts
66 negative pap/positive HPV
56 had a colposcopy
6 abnormal colposcopies
2 referred to further procedures
NEGATIVE PAP SMEAR, POSITIVE HPV
 56 women
 59 procedures total
 29 biopsies
 23 normal (79.3%)
 30 endocervical curettage
 28 normal (93.3%)
 18 women had both biopsy and ECC
 12 all normal (66.7%)
ABNORMAL COLPOSCOPY
 Three Cervical Intraepithelial Neoplasia I (CIN I)
 60% resolve to normal in one year
 One CIN I/normal
 One CIN II-III
 Referred for LEEP
 One CIN III/carcinoma-in-situ
 Referred for possible hysterectomy
NORMAL
COLPOSCOPY
 Smoking Status
 56% current/former smokers
 HPV Prevalence
ABNORMAL
COLPOSCOPY
 Smoking Status
 50% current/former smokers
 HPV Prevalence
 80% were HPV 16+
 83.3% were HPV 16+
 18% were HPV 18+
 16.7% were HPV 18+
 Previous Abnormal Pap Smear
 34% had a previous abnormal pap
smear
 Previous Abnormal Pap Smear
 50% had a previous abnormal pap
smear
 ***47% more likely to have had a
previous abnormal pap smear***
REFERENCES
 Saslow et al. 2012. “American Cancer Society, American Society for
Colposcopy and Cervical Pathology, and American Society for Clinical
Pathology Screening Guidelines for the Prevention and Early Detection
of Cervical Cancer” Journal of Lower Genital Tract Disease 16(3):0.
 Discacciati MG et al. 2014. “Prognostic value of DNA and mRNA e6/e7
of human papillomavirus in the evolution of cervical intraepithelial
neoplasia grade 2”. Biomark Insights 13(9):15-22.
 American Cancer Society. Cancer Facts & Figures 2010. Atlanta:
American Cancer Society; 2010.
Improving treatment completion rates
for latent tuberculosis infection: a
review of two treatment regimens at a
community health center
Gregory Lines, MPH
MD candidate 2017
University of Wisconsin School of Medicine and Public Health
7/18/14
Faculty Mentor: Paul Hunter, M.D.
Department of Family Medicine
University of Wisconsin School of Medicine and Public Health
Sarah Bleything, PA
Sixteenth Street Community Health Center, Milwaukee, WI
Introduction: Latent tuberculosis
infection (LTBI)
• Estimated that 11 million people in the U.S. are
infected with M. tuberculosis.
• 10% lifetime risk of conversion to active TB among
healthy patients
• Treatment of LTBI is necessary for controlling and
eliminating active TB in the United States.
• 9 months daily isoniazid (INH)
• 12 weekly doses of isoniazid (INH) and
rifapentine (RPT) directly observed (CDC
recommendation 2011)
• 4 months daily rifampin (RIF)
Introduction
• Major limitation of LTBI treatment is adherence.
• Individual clinics report between 5% and 60%
completion for 6 months INH of those
initiating treatment
• INH monotherapy and INH/RPT have similar
efficacy (Sterling, NEJM)
Study objective:
To compare treatment completion rates
among patients accepting LTBI treatment with
12 weekly doses of isoniazid (INH) and
rifapentine (RPT) directly observed to those
accepting 9 months of daily isoniazid (INH)
monotherapy.
Methods
Study setting: Sixteenth Street Community Centers
Parkway Health Center, Milwaukee, WI
• Federally Qualified Health Center
• Patient population is low-income, predominantly Hispanic
Study Design and Ethics:
• Retrospective cohort study, review of EMR
• IRB approval at SSCHC
Study Participants:
• All patients accepting treatment for LTBI in 2012 and 2013
• INH monotherapy and INH/RPT combined therapy (DOT)
Methods
Data Collection:
• Retrospective review of LTBI patient log and Electronic Medical Records
Clinical Outcome:
• Treatment completion
Predictor of Interest:
• Treatment group (INH/RPT vs. INH only)
Variables :
• Demographic information (age, sex, race, ethnicity)
• Comorbidities (Smoking status, Diabetes mellitus, history of Injection drug use,
chronic kidney disease, HIV status)
• Elevated liver function tests (ALT, AST) , above normal and 3x normal
• Relationship with the clinic
• Resident distance from clinic (calculated by GoogleMaps)
• No. visits in year preceding treatment acceptance
• No. years a patient at the clinic
Results: participant eligibility
n=139; INH/RPT – 45, INH only - 94
Results
Baseline characteristics of study and control groups
Results: overall completion rates
Patients agreeing to LTBI treatment, n = 139:
INH only
INH/RPT (DOT)
Total
52.1 % (49/94)
77.8% (35/45)
60.4 (84/139)
Patients initiating LTBI treatment, n=102
INH only
INH/RPT (DOT)
Total
73.1 % (49/67)
100% (35/35)
82.4% (84/102)
Results: Logistic regression
analysis, n = 139
Univariate logistic regression for DOT group compared to INH only:
(OR 3.21; 95% CI, 1.43 – 7.23; P=0.005)
Discussion
• 12 week DOT regimen with INH/RPT combined therapy
can achieve higher completion rates than selfadministered INH monotherapy in a community health
center serving predominantly low-income Hispanics
• Greater success may be attributed to:
• shorter treatment regimen
• directly observed therapy
• Reduced hepatotoxicity
• More research is needed to better predict who is most
likely to complete treatment
Acknowledgments
I would like to thank the following for their participation in this project:
Paul Hunter, M.D. - UW Department of Family Medicine
Sarah Bleything, PA, - SSCHC
Sixteenth Street Community Health Center
Milwaukee Health Department
Meditation for chronic low back pain
in patients prescribed opioids:
A cost analysis
Aleksandra Zgierska, MD, PhD
James Ircink, BS
Background/Significance
• US healthcare system most expensive in world
– Yet lags in quality/efficiency
• Chronic low back pain affects 80% of US adults
– Significant economic burden
• Long-term opioids is common tx
– Current opioid abuse epidemic
Background/Significance
• Alternative treatments warranted
– Improved quality of life, reduced cost
• Meditation has promise to improve health
– Limited evidence in CLBP
– Low cost, sustained results
• Costs yet to be estimated in this population
Methods
• 35 adults with CLBP treated with daily opioids
• Randomized to
(i) meditation + standard of care
(ii) standard of care only
• Patient-reported data via surveys at baseline, 8
weeks, and 26 weeks:
– Cost: Meds, health care utilization, productivity, MVA’s
– Quality of life: QALY’s, ODI, Health Score
Methods
• Categorical costs estimated
• Group Comparison
• Statistical methods
– Means, SD’s, CI’s
– Small, pilot trial  effect sizes
Results: Baseline
Mean (n=35)
Demographics
Age
52
Years of Back Pain
14.2
Years of Opioids
7.9
Individual Gross Income
$18,291
Household Gross Income
$36,089
Health Measures
ODI Score
67
Health Score
53
QALY Score
0.581
Results: Baseline (past 6 mo.)
Health Care Utilization
Office Visit Costs
Urgent Care Visit Costs
Individual Mental Health Visit Costs
Group Mental Health Visit Cost
Inpatient Day Cost
Emergency Room Visit Costs
Total Health Care Utilization Cost (SD)
Productivity
Cost Due to Missed Work Days
Cost Due to Missed Leisure Days
Total Productivity Cost (SD)
Motor Vehicle Accidents
Costs Due to Motor Vehicle Accidents
Mean $ (n=35)
1138
59
391
29
2075
459
$4151 (6463)
1976
2868
$4844 (7243)
.06
$509
Results Pending…
• Medication data
• Meditation-efficacy analyses
Preliminary Conclusions
• The opioid-treated CLBP population is costly
Questions?
2014 SSRCA
Thanks