Student Presentations SSRCA - 2014 Summer Student Research ...

Student Presentations SSRCA - 2014 Summer Student Research ...

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 Exposur e to allergen s Asthm a Rasmussen & Hancox (2014) University of Wisconsin Department of Family Medicine Others

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 gan, et. Al (2013), Chen, et. Al (2013), inflammation? Beckett, et. Al (2001), Zierau, et. Al (2012) University of Wisconsin Department of Family Medicine Purpose

oes 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 eHealthPHINEX) 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 PHINEX ICD-9 493.xx Asthma Controlled 2 encounters 2 years apart

No Asthma Uncontroll ed 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 Categor y 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 (13.4%)

Controlled No Asthma Uncontroll ed 6,554 (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 Obese Female Normal BMI Male Obese Male 15.0% 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 41 to 59 Age as of last BMI measurement University of Wisconsin Department of Family Medicine 60+

Uncontrolled Asthma Prevalence vs. Age (BMI x Sex) 30.0% Uncontrolled Asthma Prevalence 25.0% 20.0% Normal BMI Female Obese Female Normal BMI Male Obese Male 15.0% 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 2.5 2 O ddsratio 1.5 Male Female 1

0.5 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+ 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: 20452050. 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: 222231. doi:10.1111/j.1467789X.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:10.1186/1471-2431-13121. Guilbert TW, Arndt B, Temte J, Adams A, Buckingham W, et al. (2012) The theory and application of UW ehealthPHINEX, a clinical electronic health record-public health information exchange. WMJ Off Publ State Med Soc Wis 111: 124133. Rasmussen F, Hancox RJ (2014) Mechanisms of obesity in asthma. Curr Opin Allergy Clin Immunol 14: 3543. 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: 7984. 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: e65e73. 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. CommunityBased Treatment for Opioid Dependent Offenders: A Pilot Study. The American Journal on Addictions, 22: 500502, 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;20:10381041. 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):89-106. 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 Murrays How Doctors Die: Its not like the rest of us, but should be1 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 Ageat Participation 25-34 35-44 45-54 >54 n

%* RelationshipStatus n %* 5 15 11 7 11.6 34.9 25.6

16.3 0 2 41 1 0 4.7 95.3 2.3 CurrentResidence n

%* n %* Wisconsin Outside WI 29 15 67.4 34.9 Single

Domestic Partnership Married Separated/Divorced Ageatstartof residency 20-24 25-29 30-34 2 34 5 4.7 79.1 11.6

Specialty n %* Ageatfirstbirth n %* Family Medicine OB/GYNE Other

Multiple 28 8 4 2 65.1 18.6 9.3 4.7 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% 14.3% 0.0%

25.0% 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 Interventional Method used during one or more deliveries

Episiotomy 21.88 Vacuum Extraction 12.5 Forceps 12.5 Artificial Rupture of the membrane 53.13

Intrauterine Pressure Catheter 18.8 Cervican Ripening 28.1 Pitocin 65.6 0 10 20

30 40 50 % of Respondents reporting use of intervention *n=32 with 63 responses 60 70

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? Its hard for physicians to have a clue if they havent breastfed beforea nuanced skill that is learned and passed on through generations. - Interviewee 001 References

1. Murray, K. How Doctors Die: Its Not Like the Rest of Us, But It Should Be. Zocalo Public Square. Nov. 2011 retrieved from . 2. Declercq, E., et al. Listening to Mothers III Pregnancy and Birth: Report of the Third National U.S. Survey of Womens Childbearing Experiences. May 2013 retrieved from . 3. 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 . 4. 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

://www.cdc.gov/breastfeeding/pdf/2013breastfeedingreportcard.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 mental disorders increased ARI incidence2 Sheldon 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 < 71.4%

Bachelors degree % Income < $50,000 58.1% SF-12 Mental Results Graph courtesy of Joseph Chase # 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 (pvalue) Duration rho (pvalue) Severity rho (pvalue) 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: 499509). 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 Todays 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 SHOWs 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-of-t he-health-of-wisconsin/ 36193 http://www.hndinc.org/cmsAdmin/uploads/dlc/HN D-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. 9. 10. 11. 12. 13. 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): 561-587. 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 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 30 endocervical curettage

23 normal (79.3%) 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 ABNORMAL

COLPOSCOPY Smoking Status Smoking Status 56% current/former smokers HPV Prevalence 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 52.1 % (49/94) INH/RPT (DOT)

77.8% (35/45) Total 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, MVAs Quality of life: QALYs, ODI, Health Score Methods Categorical costs estimated

Group Comparison Statistical methods Means, SDs, CIs 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

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