Disparities in the Financial Burden of Cancer Care and Access to - - PowerPoint PPT Presentation

Disparities in the Financial Burden of Cancer Care and Access to Cancer Treatment during the Early Affordable Care Act Implementation Period

Jennifer Tsui, PhD, MPH AcademyHealth Annual Research Meeting June 25, 2017

Costs of Cancer Care

• $173 billion in 2020
• 18.1 million cancer

survivors by 2020, 30% more than 2010

• Increasing:
• ut-of-pocket costs
• ral/prescription

therapies

• long-term

management

Mariotto AB, Yabroff KR, Shao Y, Feuer EJ, Brown ML. Projections of the Cost of Cancer Care in the U.S.: 2010-2020. J Natl Cancer Inst. 2011

Financial Hardship and Cancer Care

• Patients facing high financial hardship (FH) for cancer care

are more likely to delay/forgo treatment & report lower QoL.1,2

• FH more likely among younger (<65 yrs), minority

(Hispanic/African American), lower-income cancer patients. 3,4

• Unclear whether ACA provisions are ameliorating disparities

in FH related to cancer care.5

• Few studies have examined financial hardship and cancer

care among newly diagnosed cancer patients during the initial ACA implementation period.

1Kent et al. Cancer 2013 2 Weaver et a;. Cancer 2010 3Jagsi et al. J Clin Onc. 2014 4 Yabroff et al. J Clin Onc. 2016 5 McNulty et al. Curr Hem Malig Rep. 2015

• Investigate disparities in cancer care by insurance type,

co-morbidities, demographic factors during early ACA implementation period (2012-2015)

• Medicaid expansion January 1, 2014

Study Overview

• Population-based study examining cancer care access,

treatment, and outcomes in New Jersey

• 6th highest state in overall cancer incidence

https://statecancerprofiles.cancer.gov/index.html

Overall Cancer Incidence 2010-2014

Study Population

• The New Jersey State Cancer Registry (NJSCR) - one of

20 Surveillance, Epidemiology, and End Result (SEER) Program regions of the NCI

• Inclusion criteria:

First primary breast or colorectal cancer Stages I, II, III Diagnosed in Jan 2012 – Dec 2014 21-79 yrs Known insurance status at diagnosis NJ resident at time of diagnosis Alive at time of contact Not currently enrolled in another NJSCR study

Sampling and Recruitment

Sampling:

• Systematic random sampling by cancer site, diagnosis year

and gender (for colorectal cancer only)

• Stratified by age (21-64 years vs. > 65 years)
• Oversampled for Medicaid-insured and uninsured

Recruitment:

• Mailed self-administered survey (~75 items)
• September 2015 - August 2016
• $15 incentive
• Response rate of 24%

Study Aims

1. Examine reports of financial hardship (FH) from cancer care in a population-based diverse sample of breast and colorectal cancer patients in New Jersey

• Diagnosed and initiated treatment during the early

ACA implementation period: 2012-2014 2. Assess the impact of financial hardship on access to cancer care, treatment decisions, and quality of life 3. Explore the extent of racial/ethnic and insurance-based disparities in FH

Demographic and Clinical Characteristics

Breast Colorectal n=310 n=200 Age at DX <50 years 32.6 14.5 50-64 years 43.9 53.5 65+ years 23.5 32.0 Race/Ethnicity Hispanic 17.4 10.5 NH-Black 6.1 9.5 NH-API/Other 11.9 13.0 NH-White 64.5 67.0 Insurance at dx Uninsured 17.8 19.4 Private 32.4 28.4 Medicaid 16.7 19.4 Medicare 22.9 22.3 Other Public 10.2 10.6 Breast Colorectal n=310 n=200 AJCC Stage Stage 0/I 52.9 24.0 Stage II 33.2 37.5 Stage III 13.9 38.5 Treatment(s) received* Surgery 93.9 94.5 Chemotherapy 55.2 57.5 Radiation therapy 71.0 23.0 Co-morbidities none 47.1 36.5 1 20.0 20.0 2-3 21.9 28.0 4+ 11.0 15.5

* Not mutually exclusive

Financial Hardship by Race/Ethnicity

22.3 28.8 45.1 53.7 32.0 33.3 61.3 74.6 20.7 26.9 40.7 48.5 23.7 26.3 34.2 44.7 26.3 42.1 63.2 73.7

20 40 60 80 100 Borrowed money or go into debt Made financial sacrifices Worried about paying large medical bills Any financial hardship

Total Hispanic NH White NH Black NH Asian/PI

p=0.51 p=0.21 p=0.003 p<0.001

Financial Hardship by Insurance at Diagnosis

22.4 28.8 45.1 53.7 32.9 42.9 62.6 68.1 23.0 29.7 46.1 53.3 20.0 28.2 40.0 55.3 10.3 11.1 33.3 39.3

20 40 60 80 100

Borrowed money or go into debt Made financial sacrifices Worried about paying large medical bills Any financial hardship

Total No insurance Private insurance Medicaid Medicare

p<0.001 P=0.001 p<0.001 p=0.001

Financial Hardship by Change in Insurance Between Diagnosis and Treatment

22.4 28.8 45.1 53.7 18.8 24.3 39.4 49.3 25.7 32.4 50.0 56.7 20.5 36.4 45.5 52.3 44.7 48.9 78.7 82.9

20 40 60 80 100 Borrowed money or go into debt Made financial sacrifices Worried about paying large medical bills Any financial hardship

Total No insurance change Change in insurance type Gained insurance between dx to trt No insurance at dx and trt

p=0.001 p=0.00 P<0.001 P<0.001

Financial Hardship by Diagnosis Year

54 51 38 68 54 53 39 85 49 55 48 83 51 59 42 69 50 64 41 85 50 59 60 82

20 40 60 80 100 2012-2013 2014

Insurance at Dx Insurance at Trt Change in Insurance

Adjusted Models for Cancer Care Access

Did not receive all needed cancer care Treatment Decisions Treatment delay OR 95% CI OR 95% CI OR 95% CI Any Financial Hardship 3.55** (1.53-8.23) 2.29** (1.35-3.89) 1.47+ (0.95-2.25) Insurance at Treatment Private 1.0 1.0 1.0 Uninsured 1.16 (0.35-3.89) 1.07 (0.49-2.34) 2.00+ (0.98-4.06) Medicaid 0.94 (0.33-2.70) 1.52 (0.78-2.94) 2.17** (1.23-3.85) Medicare 0.88 (0.30-2.61) 0.48+ (0.22-1.07) 1.10 (0.61-2.00) Year of Dx 2012-2013 1.0 1.0 1.0 2014 1.07 (0.49-2.33) 1.30 (0.75-2.27) 1.57+ (0.99-2.50)

+ p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001

Models adjusted for age at dx, marital status, \stage, household income, race/ethnicity, # of co-morbidities

Financial Hardship and Quality of Life

Summary & Implications

• High rates of FH among cancer cases in early ACA period.
• Borrow money/go into debt (22%) vs MEPS Cancer Supp 2011(7.1%) 1
• Made financial sacrifices (28%) vs. MEPS (9.4%)
• Worrying about medical bills (45%) vs MEPS (23%)
• FH highest among Hispanics & APIs (75%) and uninsured (68%).
• FH continues to impact access to care, care decisions, and QoL.
• Similar rates of treatment delays between Medicaid and uninsured

groups and increasing rates of treatment delays in 2014:

• Transitional expansion year
• Changing composition of Medicaid patients
• System-level barriers to timely care

1 Yabroff et al. J Clin Oncol. 2016

Next Steps

• Further exploration of financial hardship specific to 1.) cancer

patients gaining coverage and 2.) stages of the care continuum

• Concurrent study of a Medicaid-cancer registry linkage to

examine patterns of care and reasons for treatment delays

• Mixed methods study of Medicaid providers to identify care

delivery processes that impact access/barriers, timeliness and management of cancer care (ACS MRSG 2017-2022)

• Inform and develop strategies to address cancer care-related

financial hardship, particularly for vulnerable groups.

Acknowledgements

Rutgers Cancer Institute of New Jersey

• David Rotter
• Carolina Lozada

Rutgers School of Public Health

• Dirk Moore
• Kitaw Demissie

Rutgers Center for State Health Policy

• Joel C. Cantor

New Jersey State Cancer Registry

• Antoinette Stroup
• Natalia Herman
• Aishwarya Kulkarni
• Jie Li

Sidney Kimmel Cancer Center at Jefferson

• Grace Lu-Yao

This project was supported by the Rutgers Biomedical Health Sciences Team Science

• Initiative. The New Jersey State Cancer Registry is funded by NCI SEER Program

contract #HHSN261201300021I, the CDC NPCR #5U58DP003931-02, the State of New Jersey, and the Rutgers Cancer Institute of New Jersey.

Questions? jennifer.tsui@rutgers.edu

Total breast and colorectal cases diagnosed in 2012-2014 in NJSCR (n=35,107) Target sample based on sampling frame (n=2408) Records excluded (n=21,446)

• Stage IV
• Diagnosed outside of 2012-

2014 period

• Diagnosed outside the state
• f NJ
• Age<20 years or age>79

years

• Absence of invasive cancer
• Actively enrolled in other

studies Eligible cases contacted by mail (n=2366) Total breast and colorectal cancer participants in IMPACT study (n=534) Records excluded (n=1832)

• Ineligible: based on survey

screener, incomplete survey, incorrect address

• Active refusal
• Passive refusal
• Deceased post contact

Eligible cases (n=13,661) Records excluded (n=11,253) based on sampling frame Records excluded (n=42)

• Deceased
• MD refused