THE IMPACT OF THE UTHEALTH MEDICAL LEGAL PARTNERSHIP ON UTILIZATION - - PowerPoint PPT Presentation

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WINSTON LIAW, MD MPH ANGELA STOTTS, PhD THOMAS NORTHRUP, PhD ALVIN CHEN ROBERT SUCHTING, PhD CHRISTINE BAKOS‐BLOCK, PhD, LCSW CHRSITIAN PINEDA ALISSA CHEN ASRA WALIUDDIN, MD DONGNI YANG, MD, PhD THOMAS MURPHY, MD

THE IMPACT OF THE UTHEALTH MEDICAL LEGAL PARTNERSHIP ON UTILIZATION AND HEALTH HARMING LEGAL NEEDS

FUNDER: TEXAS ACADEMY OF FAMILY PHYSICIANS FOUNDATION

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Background

• Vast literature connects unmet social needs to undesirable health outcomes
• Calls for tighter integration between public health and primary care to

address these social determinants of health (SDOH)

• Medical legal partnership (MLP)
• Embeds lawyers into clinics
• Address health‐harming legal needs
• Low‐income households average between 1 and 3 legal problems
• Over 300 nationally
• Evaluated in a randomized controlled trial (pediatric population)

WHO Commission on Social Determinants of Health, World Health Organization, eds. Closing the Gap in a Generation: Health Equity through Action on the Social Determinants of Health: Commission on Social Determinants of Health Final Report. Geneva, Switzerland: World Health Organization, Commission on Social Determinants of Health; 2008. Institute of Medicine C on IP. Primary Care and Public Health: Exploring Integration to Improve Population Health. Washington (DC): National Academy Press; 2012. Sege R, Preer G, Morton SJ, et al. Medical‐Legal Strategies to Improve Infant Health Care: A Randomized Trial. Pediatrics. 2015;136(1):97‐106. doi:10.1542/peds.2014‐2955.

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Unsafe housing Housing subsidies Wrongly denied social security Wrongly denied food stamps Legal problems interfering with employment Guardianship issues affecting access to care

Economic strain Limited self‐care Access to care ↓ Basic needs for survival Depression Stress

Inefficient utilization ↓ Quality of life

Model for How Health‐harming Legal Needs (HHLNs) Affect Health

UTHealth launched a medical legal partnership (April, 2018)

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Objectives

• Assess whether access to the MLP was associated with lower urgent

care, emergency department, and hospital visits compared to individuals without access

• Describe the HHLNs identified and services provided by the MLP

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Methods

• Design: Cohort study
• Setting:
• MLP access: 3 community‐based primary care clinics
• MLP staff contacted patients via telephone to assess and address their legal

issues

• No MLP access: 1 community‐based primary care clinic
• Participants:
• 18 or older
• Patients with an appointment were offered screening
• Screened positive for HHLN
• Valid email address

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Methods

• Developed a screening instrument
• Literature review
• Existing screening tools
• Assess the most common health‐harming legal needs
• National Center for Medical‐Legal Partnership
• Screening tools used at other MLPs
• Existing social need screening tools
• I‐HELP (National Center for Medical‐Legal Partnership)
• PRAPARE (National Association of Community Health Centers)
• Accountable Health Communities screening tool
• Collaborated with the university’s legal counsel and non‐profit legal services

partner (Lone Star Legal Aid)

Billioux A, Verlander K, Anthony S, Alley D. Standardized Screening for Health‐Related Social Needs in Clinical Settings. Accountable Health Communities Screen Tool Discuss Pap. 2017:2017.

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Methods

6 months prior to screening Date of screening 6 months after screening 6‐month follow up survey emailed Pre‐screening Post‐screening

• Measures
• Utilization: Email survey responses
• Respondents were entered into a $100 raffle
• Urgent care, emergency department, hospital visits
• Legal issues and legal benefits:
• Screening instrument responses
• Lone Star Legal Aid
• April 16, 2018 to February 1, 2019
• Demographic variables (age, gender, race / ethnicity, language): Electronic Health Record
• Analyses
• Descriptive statistics and bivariate analyses, by MLP access
• Chi‐square to test associations for categorical variables
• Poisson regression was used to model whether MLP access was associated with reduced

utilization, controlling for the pre‐screening count

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Email Responders, by Demographics

Intervention Control N % N % p‐value

Number of Respondents 124 86 Number of Individuals Receiving the Survey 437 474 Response Rate 28.4% 18.1%

Gender

Female 80 64.5% 57 66.3% 0.8

Age

18‐44 75 60.5% 35 40.7% 0.01 45‐64 41 33.1% 37 43.0% 65 or older 8 6.5% 14 16.3%

Race / Ethnicity

Black 75 60.5% 53 61.6% 0.9 Hispanic or Latino 18 14.5% 14 16.3% White 14 11.3% 9 10.5% Asian 1 0.8% 0.0% Other 14 11.3% 9 10.5% Not Answered 2 1.6% 1 1.2%

Language

English 107 86.3% 81 94.2% 0.3 Spanish 3 2.4% 1 1.2% Arabic 2 1.6% 0.0% Other 3 2.4% 0.0% Unknown 9 7.3% 4 4.7%

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Mean Pre and Post Urgent Care, Emergency Department, and Hospital Visits in Intervention and Control Clinics

Intervention Control Mean SE Mean SE Urgent Care Total 5.06 0.19 4.48 0.19 Pre‐screening 2.90 0.13 2.38 0.13 Post‐screening 2.15 0.11 2.09 0.13 Emergency Department Total 3.69 0.11 2.26 0.11 Pre‐screening 1.98 0.08 1.19 0.09 Post‐screening 1.72 0.07 1.07 0.08 Hospital Visits Total 1.33 0.09 2.34 0.11 Pre‐screening 0.61 0.06 1.19 0.09 Post‐screening 0.72 0.06 1.15 0.08

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Mean Pre and Post Urgent Care, Emergency Department, and Hospital Visits in Intervention and Control Clinics

Having access to the MLP was related to a 58% increase in # ER visits relative to those with no MLP access. Rate Ratio (RR) = 1.581, p < 0.001. Having access to the MLP was not related to change in # UC visits relative to those with no MLP access. Rate Ratio (RR) = 1.004, p = 0.963. Having access to the MLP was related to a 41% decrease in # hospital visits relative to those with no MLP access. Rate Ratio (RR) = 0.592, p < 0.001. URGENT CARE EMERGENCY DEPARTMENT HOSPITAL

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Health‐Harming Legal Need Screening Responses

• Intervention Group:
• Health insurance coverage: 61%
• Personal safety: 58%
• Transportation: 57%
• Control Group
• Income: 62%
• Health insurance coverage: 61%
• Oven or stove not working: 58%

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Medical Legal Partnership Case Referrals, Issues, and Benefits

N % Total Case Referrals 559

Legal Issues Identified (Open and Closed Cases)*

Government Benefits (e.g., social security, food stamps) 52 22.9% Family (e.g., custody, divorce, domestic violence) 47 20.7% Housing (e.g., subsidized housing, landlord) 43 18.9% Estate Planning (e.g., wills and estates) 39 17.2% Health Insurance (e.g., Medicare and Medicaid) 18 7.9% Finances (e.g. bankruptcy, collection, debtor relief) 12 5.3% Employment (e.g., employee rights, wage claims) 12 5.3% Education (e.g., special education) 4 1.8%

Legal Benefits Provided (Closed Cases)*

Obtained advice and counsel or litigation advocacy services in an income maintenance matter 50 24.3% Obtained advice and counsel on a family matter not involving domestic violence 40 19.4% Obtained advice and counsel, non‐litigation advocacy services, or a decision in a housing matter 39 18.9% Obtained advice and counsel or non‐litigation advocacy services in a health matter 19 9.2% Obtained advice on a miscellaneous matter 19 9.2% Obtained advice and counsel or non‐litigation advocacy services on a consumer/finance matter 12 5.8% Obtained advice and counsel on an employment matter 11 5.3% Obtained a living will, health proxy, or health care power of attorney 8 3.9% Obtained advice and counsel or non‐litigation advocacy services on an education matter 3 1.5% Obtained advice and counsel or non‐litigation advocacy services in an individual rights matter 2 1.0% Obtained advice and counsel on a domestic violence matter 1 0.5% Obtained, preserved or increased spousal support 1 0.5% Obtained, preserved or increased Supplemental Security Income benefits 1 0.5%

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Conclusions

• MLP addresses a wide range of issues
• 41% decrease in the number of hospital visits
• Needs to be confirmed using more rigorous methods
• Average hospital stay is $9,700
• 58% increase in the number of emergency department visits
• Due to increase in resources?
• Confounders?

Pfunter A, Wier LM, Steiner C. Statistical Brief #146: Costs for Hospital Stays in the United States, 2010.; 2013.

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Limitations and Next Steps

• Limitations
• Low response rate
• Recall bias
• Did not control for baseline health, medical conditions, or insurance

status

• Next steps
• Randomized controlled trial to assess the effectiveness of the MLP
• Primary outcome: stress
• Additional outcomes: anxiety, depression, quality of life, urgent care /

ED / hospital visits, resolution of health‐harming legal needs

A Prescription for Wellness: Exercise Referrals for Patients at a Federally‐Qualified Health Center

Presented by Zachary Sartor, MD TAFP Annual Session and Primary Care Summit 2019 Original Research Authors: Kelly R. Ylitalo, PhD; Mariela Gutierrez, BS; Wendy Cox, MPH; Gabriel Benavidez, MPH; Brock Niceler, MD; Jackson O. Griggs, MD

Disclosures

• No personal conflicts of interest to disclose.
• This project was supported, in part, by the Episcopal Health

Foundation and by the National Institute on Aging of the National Institutes of Health.

• The content is solely the responsibility of the authors and

does not necessarily represent the official views of the funding agencies.

• FQHC in Waco, TX
• 57,894 individual patients
• 40% Hispanic, 30% White, 26%

African‐American

• 80% fall below federal poverty

line

• 68 physicians, 10 dentists, 14

APP, 10 therapists

• 230,000 visits annually

Waco Family Health Center: Who We Are

Cardio Room Multi‐Purpose Room

Training Kitchen

Cardio Room

Multi‐Purpose Room

Training Kitchen

Physician Prescribe Wellness Center Membership

Orientation and Evaluation One‐on‐One Training with Fitness Advisor Independent Exercise (w/ loose

supervision by Fitness Advisors) Graduation and Transition to Community Program (e.g., YMCA, Church, City)

Background and Purpose

• Physical activity (PA) improves quality of life and prevents or

delays chronic disease

• Consultation and planning with a health care provider,

specifically in the form of an exercise “prescription,” may increase PA

• Utilization patterns and success of such programs are not well

understood, particularly among underserved populations

Objectives

• Assess the initial 20 months of participation in an exercise

prescription program

• Determine if program participants reported changes in self‐

efficacy, self‐regulation, and/or PA behavior over time

Methodology

• All adult patients from October 1, 2017 through December 31,

2018 who received an exercise prescription were included

• Baseline and follow‐up surveys about self‐reported PA behavior

[1], self‐efficacy [2], and self‐regulation strategies [2] obtained

• T‐tests and chi‐square tests were used to compare patients who

did and did not participate in their exercise program

• Change in PA behavior, self‐efficacy, and self‐regulation strategies

was measured using paired t‐tests

• Multivariate linear regression was used to determine if self‐

efficacy or self‐regulation predicted behavior change

Total Prescriptions 1,162 Age 44.9 ± 14.6 years Sex Female 79% Male 21% Race/Ethnicity Hispanic/Latino 38% Non‐Hispanic White 20% Black 42% Prevalence of Diabetes 39%

Who Filled Their Prescription?

• 51% initiated exercise at the Wellness Center
• Patients who initiated exercise were older than those who did

not

• 46.9 vs. 42.8 years; p<0.001
• No difference in sex, race/ethnicity, body mass index, or

diabetes

• Program initiators completed 7.9 ± 11.8 visits during follow‐up

Longitudinal Follow‐up

• 162 patients completed the longitudinal follow‐up
• Number of visits to the Wellness Center was not associated

with PA at follow‐up after completion of the program

• Baseline self‐efficacy score (p<0.001) and average self‐

regulation strategies score (p=0.01) were significantly associated with PA at follow‐up

• Even after adjusting for baseline PA

Implications for Practice

• Self‐efficacy and the use of self‐regulatory strategies were

associated with PA behavior

• Exercise referral programs that aim to increase PA may benefit

from targeted screening efforts to identify older patients with higher self‐efficacy or self‐regulation who are poised to gain most from program resources

Questions?

References

[1] Craig CL, Marshall AL, Sjöström M, the IPAQ Consensus Group, the IPAQ Reliability and Validity Study Group. International Physical Activity Questionnaire (IPAQ): 12‐country reliability and validity. Medicine & Science in Sports & Exercise. 2003;35:1381‐1391. [2] Carlson JA, Sallis JF, Wagner N, Calfas KJ, Patrick K, Groesz LM, Norman

• GJ. Brief physical activity‐related psychosocial measures: reliability and

construct validity. J Phys Act Health. 2012;9(8):1178‐86.

FRESH PRODUCE PRESCRIPTION PROGRAM

Seeking a healthier and happier tomorrow Rachel Rube, DO Family Medicine Residency Faculty Physician Waco Family Health Center

• No relevant financial

affiliations to disclose.

Financial Disclosures

What Is a “Produce Prescription”?

• Provision for box of fresh fruits & vegetables
• “Treatment” for broad array of conditions
• Element of preventive wellness programs

Produce Prescription Programs (PPP)

• Cooperation between local farmers’ markets,

community health clinics, community‐based

• rganizations (CBOs), and research institutions
• Targets at‐risk patients in population(s)
• Federal government proposed $4 million for

PPP pilot for each fiscal year 2019 through 2023 (Agriculture Improvement Act of 2018)

Why Focus on Food?

40 million people food insecure

in 2017

Numerous

comorbid

conditions

Why Focus on Food?

PPP’s “reduce the social cost of attitudinal

change…and the financial cost of behavioral change“

PPP at Waco Family Health Center (FHC)

Basic Construct

Harvest

Prescribe Educate

Patient Surveys Physician Surveys

Study Population

• 90% + live at or below 200% of Federal

Poverty Guidelines

• 15,568 uninsured patients served through

discounted fee program (Good Health Card)

• 1,475 homeless patients

24%

41%

30% 5%

Black/AA Hispanic/Latino NH White Other

Black/ AA 27% Hispan ic/Lati no 40% NH White 25% Other 8%

Identifiers for Prescribing

Most common identifiers noted per prescribers were:

• Chronic conditions
• Obesity status
• Low SES
• Food insecurity

PPP: The Numbers

Pilot 2017 Fall 2017 Spring 2018 Fall 2018 Spring 2019 Length Of Season ‐‐ ‐‐ 12 weeks 9 weeks 12 weeks Boxes Delivered 1000 680 1360 (112/wk) 1053 (117/wk) 1497 (130/wk) Prescriptions 648 371 1175 (98/wk) 909 (101/wk) 1356 (113/wk) Boxes To Patients ‐‐ ‐‐ 1329* (97.7%) 1051 (99.8%) 1480 (98.9%) Initial Surveys 418 278 (no surveys) 956 761 1038 Refill Surveys 70 19 (no surveys) 241 187 276 Missing Surveys ‐‐ ‐‐ 132 (9.9%) 103 (9.8%) 183 (12.3%) Cost Per Box $15/box $15/box $15/box $15/box $15/box

Barriers to Healthy Eating

Cost

63%

Time Access Taste

32.1% 23.9% 21.6% 33.3% 25.4%

Knowledge

Barriers identified in pilot survey reflective of study population’s:

• Socioeconomic status
• Education level
• Food insecurity*

Baseline Produce Intake

0% 10% 20% 30% 40% 50% 60% Fruits Vegetables 0 to 1 cup 1 to 2 cups 2 or more cups

• Participants who never run out of food were

4 times more likely to increase

vegetable consumption over time relative to participants who sometimes or often run

• ut of food.
• OR=4.0; 95% CI: 1.15, 13.9; p=0.03

Change Over Time

2+ cups (n=9) 1 – 2 c (n=18) ½ – 1 c (n=15) <½ cup (n=14) None (n=9) 2+ cups (n=15) 1 – 2 c (n=20) ½ – 1 c (n=9) <½ cup (n=14) None (n=0) 2+ cups (n=3) 1 – 2 c (n=8) ½ – 1 c (n=3) <½ cup (n=2) None (n=0)

Baseline Follow Up #1 Follow Up #2

3 6 4 5 1 2 1

The Next Steps…

• Evaluate food literacy
• Long term follow up
• Additional health metrics
• Tailor care to optimize community

impact

• Expand academic‐practice partnership

References

• Swartz H. Produce rx programs for diet‐based chronic disease prevention.

AMA J Ethics. October 2018: Vol 20, issue 10: E960‐973.

• Ridberg RA et al. Effect of a fruit and vegetable prescription program on

children’s fruit and vegetable consumption. Prev Chron Dis. Jun 13 2019. Volume 16.

• America's Health Rankings analysis of U.S. Department of Agriculture,

Household Food Security in the United States Report, United Health Foundation, AmericasHealthRankings.org, Accessed 2019.

• https://www.dietaryguidelines.gov/about‐dietary‐guidelines/purpose‐dietary‐

guidelines

• Ylitalo K and Griggs. J Wellness Center: an academic‐practice partnership to

improve community health. 2017.