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Addressing Health Literacy and Health Communication in Diabetes and Obesity Russell L. Rothman MD MPP Associate Professor, Internal Medicine & Pediatrics.

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Presentation on theme: "Addressing Health Literacy and Health Communication in Diabetes and Obesity Russell L. Rothman MD MPP Associate Professor, Internal Medicine & Pediatrics."— Presentation transcript:

1 Addressing Health Literacy and Health Communication in Diabetes and Obesity Russell L. Rothman MD MPP Associate Professor, Internal Medicine & Pediatrics Director, Center for Health Services Research Chief, Internal Medicine/Pediatrics Section Co-Director, Community Engaged Research, VICTR Associate Director, Center for Diabetes Translational Research Vanderbilt University Medical Center

2 Presenter Disclosure Disclosed no conflict of interest.

3 Why inadequate diabetes care? Provider Knowledge Attitudes/Beliefs Behaviors Incentives Health Communication Skills Provider Knowledge Attitudes/Beliefs Behaviors Incentives Health Communication Skills Community Cultural beliefs Access to Care Access to Diet Access to Exercise Environmental Factors Community Cultural beliefs Access to Care Access to Diet Access to Exercise Environmental Factors Patient Physiology/genetics SES factors Knowledge/Attitudes/Beliefs Behaviors/ Adherence Health Literacy Patient Physiology/genetics SES factors Knowledge/Attitudes/Beliefs Behaviors/ Adherence Health Literacy System Insurance/Financing Focus on Acute Care Lack of EMR Bureaucracy System Insurance/Financing Focus on Acute Care Lack of EMR Bureaucracy Quality

4 Increasing Concern about Literacy and Numeracy Skills

5 Literacy is a Complex Skill IOM, Health Literacy, 2004 Literacy Cultural and Conceptual Knowledge SpeakingReadingNumeracyListeningWriting Print LiteracyOral Literacy

6 Poor Health Literacy is Common Health literacy: “the capacity to obtain, process, and understand basic health information and services needed to make appropriate health decisions.” Over 90 million Adult Americans have poor literacy skills and over 110 million have poor quantitative skills Difficulty navigating health system, understanding materials and recommendations, performing self-care, etc.

7 Numeracy is an Important Component “The ability to understand and use numbers and math skills in daily life” Calculations, deduction/logic, interpretation of graphs/labels, time, probability, etc. Highly correlated with literacy, but not perfect Calvin and Hobbs, Bill Watterson, Universal Press Syndicate, Released on: Friday, Oct 10th Rothman et al, J Health Comm, 2009

8 Why is literacy important in health care and research? Patients with low literacy have: – Trouble reading prescriptions, following medical instructions – Trouble understanding educational materials – Trouble interpreting and applying numbers to health situations – Trouble consenting to research or procedures – Difficulty answering survey items or other measures – Difficulty following research protocols

9 Why is numeracy important in health care? Patients with low numeracy may have trouble: – Understanding dosages of medications – Understanding the timing of when to take medications or have them refilled – Interpreting nutritional information – Understanding volume status – Interpreting blood sugars, adjusting insulin – Understanding risks and probability

10 What it is like for patients…

11 Many Outcomes Associated with Literacy Health Outcomes/Services General health status Hospitalization Mortality Emergency department use Depression Diabetes control HIV control Prostate Cancer Stage BMI Mammography Pap smear, STD Screening Immunizations Cost Behaviors Breastfeeding Behavioral problems Adherence to medication Smoking, Substance abuse Knowledge Food label and portion size understanding Birth control knowledge Emergency department instructions Asthma knowledge Hypertension knowledge DeWalt, JGIM 2004 McCormack, Annals of Internal Medicine 2011

12 Literacy/Numeracy & Diabetes Literacy skills needed: – Knowledge of disease prevention and disease – Understanding of educational materials – Performance of self-management tasks – Interaction with medical system Numeracy skills needed: – Understanding of risk and probability – Understanding weight status – Understanding medications – Understanding nutrition information – Understanding exercise – Interpreting glucose and other measures

13 Literacy and Diabetes Outcomes Schillinger, JAMA, 2002

14 Numeracy and Food Labels

15 Study Design Design: Cross sectional survey Setting: Primary care clinic Instruments: – Demographics – Food Label Usage and Attitudes – Assessed literacy with REALM – Assessed numeracy with WRAT3 – 26 item food label survey Rothman et al, AM J Prev Med, November 2006

16 Demographics Variable (n=200)Avg (SD) or Percent Age43 (15) Female72% African American25% Family Income < $20,00025% Private Insurance75% HS education or less33% Chronic Illness requiring dietary restriction41% BMI (n=151)30 (7) Reads Food Labels89%

17 Literacy, Numeracy, Food Labels Variable (n=200)Percent Literacy (REALM) <= 8 th Grade23% Numeracy (WRAT) <= 8 th Grade63% Food Label Score (Range 30% - 100%)69% (19%) Internal Reliability (KR 20)0.87

18 Calculating Fiber Intake How many grams of dietary fiber are in 5 candies? Correct Response: 1 gram Percent Correct 66 %

19 Nutrition Score by Characteristics Variable (n=200)Mean Nutrition Score (SD) p value Age < 65 ≥ 65 yrs 70 (21) 59 (19) 0.04 Gender Female Male 67 (21) 74 (20) 0.04 Race White Black Other 74 (19) 57 (18) 77 (18) < Private Insurance Yes No 73 (20) 59 (19) < Chronic Illness* Yes No 65 (20) 72 (20) 0.04 BMI < 30 ≥ (21) 66 (20) 0.04

20 Nutrition Score Correlations Higher performance on the food label survey was significantly correlated with: – Higher education (r=0.44) – Higher income (r=0.56) – Higher literacy (r=0.52) – Higher numeracy (r=0.67)

21 Conclusions Patient comprehension of food labels was fair. Comprehension was worse when patient needed to apply serving sizes, or perform multi-step math. Comprehension was worse for patients who were obese or had chronic illness Comprehension was highly correlated with math and literacy skills

22 Literacy, Numeracy, Food Labels

23 Portion Size Study Enrolled 164 pts Asked to serve “single serving” of 4 items, and then told to serve actual amount (in oz or grams) 2/3 had inaccurate estimation of portion sizes Poor estimation linked with literacy and numeracy 20 Years AgoToday 590 calories 333 calories 1,025 calories 500 calories 85 Calories 250 Calories Huizinga et al, Am J of Prev Med, 2009

24 Numeracy and Diabetes

25 Diabetes and Numeracy Study Design: Cross sectional survey Setting: Endocrine and Primary Care Clinics Instruments: – Demographics – A1C and Meter Downloads – Assessed literacy with REALM – Assessed math skills with WRAT3 – Diabetes Knowledge (DKT), Self Care (SSCA) – Assess diabetes numeracy with DNT Cavanaugh et al, Annals of Internal Medicine, 2009

26 Demographics Variable (n=398)Number (%) or Mean (SD) Age, yrs (SD)54.2 (12.9) Female, No. (%)202 (51) Race, No. (%) White Black Other 249 (63) 134 (34) 14 ( 3) Education, No. (%) ≤ High School or GED Some college College or more 168 (43) 115 (29) 109 (28) Literacy Status (REALM), No (%) ≤ -8 th grade ≥ High School 124 (31) 273 (69) Numeracy Skills (WRAT), No (%) ≤ 8 th grade ≥ High School 276 (69) 122 (31) Type 2 Diabetes (%)341 (86) On Insulin (%)241 (61) A1C (SD)7.6 (1.7)

27 Overall DNT Results Mean score 61% (SD 25%) Range 5%-100% Internal Reliability: 0.95 Trouble Spots – Interpreting serving sizes – Fractions or decimals – Applying multi-step regimens (ex. sliding scale and carb-ratios) – Applying titration instructions

28 Serving Size If you ate the entire bag of chips, how many total grams of carbohydrate would you eat? Correct Response: 63 gms Correct: 44%

29 Monitoring Your target blood sugar is between 60 and 120. Please circle the values below that are in the target range (circle all that apply): Correct Response: Circle 118 only Percent Correct: 74%

30 Insulin Correction Scale (I) You are told to follow the sliding scale shown here. The sliding scale indicates the amount of insulin you take based upon your blood sugar levels: Percent Correct: 85%

31 Insulin Correction Scale (II) After seeing the Doctor, you are given the following instruction to lower a high blood sugar level before a meal: “ Starting with a blood sugar of 120, take 1 unit of Humalog insulin for each 50 points of blood sugar.” How much insulin should you take for a blood sugar of 375? 43. ANSWER _________ units Percent Correct: 37% (accept 5-6units)

32 DNT and other measures Higher DNT scores are sig. correlated with higher: – education (r=0.51) – literacy (r=0.50) – math skills (r=0.64) – diabetes knowledge (r=0.78) – Frequency of glucose monitoring (r=0.21) and lower: – A1C (r= -0.08, p =0.11) –In multivariate analysis, each 10 point increase in DNT score was correlated with a 0.1 point decrease in A1C (p<0.05).

33 Conclusions Performance on DNT was fair/poor Disconnect between what is taught and what patients can do. Performance on DNT was correlated with literacy and math skills. Performance on DNT was also correlated with A1C, when adjusted for other covariates.

34 Communicating: What can you do? Use low literacy and picture based materials Individualize education Teach concepts in a simplified manner Use teach back technique Address cultural issues Shared goal setting

35 Sample Low Literacy Materials

36 Teaching Concepts Limit advice to key concepts. Focus on behaviors and actions Focus on one concept at a time; partition information Use concrete terms and examples Make info culturally relevant and personal Avoid Jargon! Practice patient centered communication and shared goal setting

37 Teachback technique Clinician Explains New Concept Patient Recalls and Comprehends Clinician Clarifies and Tailors Explanation Clinician Reassesses Patient Recall and Comprehension Clinician Assesses Patient recall and Comprehension New Concept: Health Information, Advice, or Change in Management Adherence Schillinger, Arch Int Med, 2003

38 Cultural Challenges Language – Use Language Appropriate Handouts – Use a translator! Family Structure – Multiple caregivers Health Beliefs – Dissonance from the “biomedical model” Campinha-Bacote, 2003

39 Shared Goal Setting Let patient or family initiate – Practice “reflective” listening” – Provide affirmation of positive behaviors – Show empathy for challenges Choose goal that is realistic and attainable – Can offer a few choices and settle on goals together – Roll with resistance (don’t challenge patients who resist change; instead ask them to come up with solutions) – Assess their confidence in achieving the goal Be concrete Set a time for accomplishing goal – Let them know it is up to them to make change! – Promote a “you can do it” approach!

40 Literacy Interventions

41 Initial Diabetes Intervention 217 Patients with T2DM 112 Interv. R 105 Control 95 Control 98 Interv. Baseline 1 Year Follow-Up Initial Pharmacist Session 99 Control 105 Interv. 6 Month Follow-Up

42 Intervention Diabetes Education Evidence-based medication algorithms Database to track and manage patient outcomes Diabetes Care Coordinator Addressed literacy by using: – Individualized verbal education – Low literacy material – Teaching concepts in a simplified manner – “Teach back” techniques to confirm learning

43 Significant Clinical Improvements at 12 months VariableControl (n=95) Intervention (n=98) Difference A1C (%)-1.2%-2.1% 0.9% (0.8,1.0) SBP (mmHg) (2.3,16.1) DBP (mmHg) (1.1,8.6) ASA (mmHg)+6%+47%41% (25-55) T. Chol. (mg/dL) (-4, 35) Rothman AM J Med, 2005

44 Literacy was an Important Factor Low Literacy PatientsHigh Literacy Patients

45 Diabetes and Numeracy RCT

46 46 DLNET Toolkit Wolff K et al. The Diab Educ 2009 Text at 5 th grade reading level Color coding Pictures for key concepts Step-by-step instructions Simplified medication instructions Practice skills worksheets

47 47 Study Demonstrates Value of Addressing Health Literacy Cavanaugh KL et al. Diabetes Care 2009 *Adjusting for age, gender, race, type of diabetes, income level, site of intervention and baseline DNT score and Hba1c levels *P = 0.03

48 Diabetes Nutrition Education Study (DINES)

49 49 Carb Counting vs Plate Method

50 Results Demonstrate Value of Simpler Diabetes Education

51 New Standards for Diabetes Education Diabetes Care, 2012, in press

52 PRIDE Study PaRtnering to Improve Diabetes Education Goal to address health communication issues to improve diabetes care in middle TN Collaboration between TN Dept. of Health, Vanderbilt, and Meharry 5 year NIDDK R18 study Cluster RCT with 10 Clinics and 400 diabetes patients Develop a sustainable model for improved diabetes care

53 Pride Materials

54 HIT approaches for Diabetes Web-based and mobile phone intervention to promote problem solving skills and self-care in adolescents with diabetes Use of electronic patient portal to address medication adherence

55 Childhood Obesity 1 in 4 preschoolers in the US are overweight/obese Overweight in infancy associated with increased risk for overweight in adulthood Weight gain in first few months of life associated with increased CV risks in adulthood “Obesogenic” behaviors start early in infancy and are very common!

56 Pediatric Obesity Prevention Over 26% of all preschoolers are overweight or obese Study involves Vanderbilt, UNC, NYU, UMiami and 865 English and Spanish speaking families addressing health literacy and numeracy to prevent early childhood obesity Trained pediatric residents in health communication skills Provide toolkit of materials to use with families (Greenlight)

57 Greenlight Toolkit Materials 1-2 Booklets per Well Child Visit – 1 CORE booklet focused on key behaviors – 1-3 SUPPLEMENTAL booklets (Provider Chooses) – Booklets are 2-6 pages and end with goal setting Designed to be used interactively during the visit Available in English and Spanish


59 Baseline Demographics Child CharacteristicsMean (SD) or n (%) Child Age, weeks9.3 (1.8) Child Gender, Male429 (49) Child weight at 2 months (kg)5.36 (0.78) Parent Characteristics Parent Age, years27.7 (6.1) Relationship to Child, Mother 839 (95. 6) Parent Non-US Born428 (49.0) Parent Race/Ethnicity Hispanic White, non-Hispanic Black, non-Hispanic Other, non-Hispanic 436 (50) 154 (18.0) 239 (27.0) 46 (5.0) Parent Language, Spanish303 (35.0) Parent Education, Less than HS Graduate227 (26.1) Income (annual) <$10,000 $10,000-$19,999 $20,000-$39,999 >$40, (31) 229 (27.0) 204 (24.0) 137 (15.9) WIC729 (85%) Medicaid740 (85%) # of Adults in home, >1782 (90.0) # of Children in home, >1524 (60.2)

60 Obesogenic Behaviors are Common Behaviors at 2 month visitTotal (n=863) Type of Feeding Formula only Mostly formula, and some breast milk Equal formula and breastmilk Mostly breast milk, and some formula Breast milk only 385 (44.6) 127 (14.7) 11 (1.3) 175 (20.3) 165 (19.1) Sweet drinks 26 (3.0) Early introduction of solids98 (11.6)

61 Behaviors at 2 months Infant feeding style and practices In last 2 weeks, how often put to sleep while drinking a bottle At most sleep times Sometimes, at least once a day Sometimes, but not every day Never 108 (12.5) 119 (13.8) 143 (16.6) 491 (57.0) I try to get my child to finish her breast milk or formula Always Most of the time Half of the time Seldom or infrequently Never 324 (37.6) 149 (17.3) 75 (8.7) 103 (11.9) 211 (24.5) When my baby cries, I immediately feed him/her Always Most of the time Half of the time Seldom or infrequently Never 175 (20.3) 119 (13.8) 184 (21.4) 176 (20.4) 207 (24.0) When my child has a bottle, I prop it up Always Most of the time Half of the time Seldom or infrequently Never 31 (3.7) 24 (2.9) 37 (4.4) 102 (12.2) 643 (76.8)

62 Behaviors at 2 months Physical Activity-related Practices Tummy time, minutes, d (Median, Inter-quartile range)12.5 [ ] Tummy time 30 minutes or more <30 minutes 288 (33.5) 571 (66.5) Television Exposure, minutes [interquartile range]346 [60-480] Television watching, minutes [interquartile range]25 [ ] Television watching Any None 429 (49.8) 432 (50.2) I watch TV while feeding my baby Always Most of the time Half of the time Seldom or infrequently Never 72 (8.4) 101 (11.7) 223 (25.9) 252 (29.2) 214 (24.8)

63 Racial/Ethnic Differences HispanicBlack, non-HispanicOther, non-Hispanic Outcome, N Overall p-value for Race/Ethnicity AOR, [95% CI] p-value AOR, [95% CI] p-value AOR, [95% CI] p-value More formula than BM, [0.43, 1.17] [0.82, 2.10] [0.33, 1.26] Bottle to bed, [0.61, 1.78] [1.25, 3.12] [1.12, 4.57] Finish BM/formula, [1.20, 3.11] [1.09, 2.41] [0.46, 1.68] Immediately feed, [0.78, 1.96] [0.70, 1.57] [1.65, 5.74] <0.001 Bottle propping, [1.25, 4.88] [1.71, 5.43] < [0.92, 5.58] TV while feeding, [0.66, 1.63] [0.87, 1.92] [0.24, 0.86] Active TV Watching, [ ] [ ] [0.28, 1.19] Tummy Time, [0.40, 0.97] [0.58, 1.28] [0.28, 1.003] Perrin et al, Pediatrics, 2014

64 Literacy and Behaviors Behavior n AOR* (Low Lit vs Adeq. Literacy) 95% CIp-value Feeding Practices: Diet content-related Type of feeding: More formula than BM Feeding Practices: Feeding style-related Gets child to finish BM or formula Immediately feeds when baby cries Props the bottle Watches TV while feeding baby Does not let child decide how much to eat Physical activity-related behaviors Television watching Television watching: Any Tummy time: None *Controlling for child gender, child out of home care, WIC status; parent age, race/ethnicity, language; number of adults in the home, number of children in the home, income; recruitment site Yin et al, J Pediatrics, 2014

65 Conclusions Low literacy and numeracy common Even patients with good literacy and numeracy can struggle to navigate our complex system and perform self-care! Patients with lower literacy/numeracy have worse knowledge, behavior, and outcomes Interventions that use low literacy materials and improved communication skills can improve outcomes!

66 Acknowledgements UNC – Eliana Perrin MD MPH – Joanne Propst-Finkle JD – Alice Ammerman PhD RD – Michael Pignone MD MPH – Darren DeWalt MD MPH – Morris Weinberger PhD – John Buse MD PhD CDE – Robb Malone PharmD CDE – Betsy Bryant PharmD CDE – Victoria Hawke RD – Britton Crigler BS, James Joyner BA Miami/Stanford – Lee Sanders MD MPH – Vivian Franco MPH – Lee Sanders, MD, MPH – Anna Maria Patino Fernandez, PhD – Daniela Quesada, MPH – Sheah Rarback, RD – Sarah Messiah, PhD – Lourdes Forster, MD Vanderbilt/ Meharry – Tom Elasy MD MPH, Robert Dittus MD MPH – Kerri Cavanaugh MD MPH, Mimi Huizinga MD MPH – Dianne Davis RD CDE, Becky Gregory RD CDE – Ken Wallston PhD. Phil Ciampa MD – Ayumi Shintani PhD, Tebeb Gebretsadik MPH – Disha Kumar BS, Jessica Sparks BA, Ryan Housam BA, Hilary Weiss BS, Kirbee Bearden – Shari Barkin MD MHs – Kathleen Wolf MSN, FNP-BC, ADM-BC – Sunil Kripalani MD – Heidi Silver RD PhD – Richard White MD (Meharry) NYU – Shonna Yin MD MSc – Linda van Schaick PhD – MaryJo Messito MD – Elaine Galland RD – Benard Dreyer, MD – Alan Mendelsohn, MD Previous Funding Support: RWJ Clinic Scholars Program, UNC Department of Medicine, Vanderbilt Diabetes Center, Vanderbilt DRTC, Vanderbilt Center for Health Services Research, Pfizer Clear Health Communication Initiative, ADA (Novo Nordisk), K23/R03, AADE Current Funding Support: NIDDK (R18), NICHD (R01), NCATS (VICTR), NIDDK (P30), PCORI

67 Questions

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