Unmasking Alternative Funding Programs Comparator Study

Authors

Ryan Moore

Department of Biostatistics

Vanderbilt University Medical Center

Published

October 20, 2025

Study details

Title

Unmasking Alternative Funding Programs: Frequency and Impact of Specialty Medication Carve Out Models

Authors

Autumn Zuckerman, PharmD, BCPS, CSP1, Martha Stutsky2, Chloe Kim2, Rebecca Freedman3, Alicia Verret4, Taylor Lager4, Claire Ozoral4, Jennifer Loucks5, Stephanie Barrus6, Samantha Curry7, Kama Thomas7, Lisa Cristofaro8, Kristin Sigmon9, Darina Georgieva9, Jennifer Carter9, Diana Gabelman10, Alex Nelson10, Karen Thomas11, Katie Williford1, Amanda Kibbons1, Laura Moore1, Ryan Moore12, Leena Choi12

1Vanderbilt Specialty Pharmacy, Vanderbilt Health;
2Shields Health Solutions;
3Cleveland Clinic Specialty Pharmacy;
4Ochsner Health;
5University of Kansas Health System;
6University of Utah Health;
7Froedtert Health Pharmacy Solutions;
8University of Rochester Medical Center;
9Medical University of South Carolina;
10MetroHealth System, Case Western Reserve University School of Medicine;
11University of Illinois Chicago;
12Department of Biostatistics, Vanderbilt University Medical Center

Key findings

Results from this multisite national study demonstrate that AFPs:

  • Significantly reduce the likelihood of accessing therapy
  • Significantly increase time to treatment in patients able to access therapy
  • Take advantage of manufacturer patient assistance programs (PAP) meant for uninsured or underinsured patients
  • Are associated with more treatment gaps and adverse clinical outcomes compared to traditional pharmacy benefits
  • Increase complexity in accessing life-altering specialty medication therapies, placing time and resource burdens on patients and pharmacy staff

Descriptive Statistics

Analysis

Demographics

Characteristic N AFP
AFP, N = 2601 Non-AFP, N = 5001
Age 716

    Mean (SD)
46.3 (14.3) 51.7 (16.9)
    Median (IQR)
49.0 (36.0 - 58.0) 53.0 (40.0 - 64.0)
    Range
2.0 - 77.0 4.0 - 93.0
    Missing
17 27
Sex 757

    Male
93 (36.2%) 239 (47.8%)
    Female
163 (63.4%) 259 (51.8%)
    Other
1 (0.39%) 2 (0.40%)
    Missing
3 0
Ethnicity 760

    Not Hispanic, Latino/a, or Spanish origin
233 (89.6%) 460 (92.0%)
    Hispanic or Latino
7 (2.69%) 11 (2.20%)
    Unknown
1 (0.38%) 0 (0%)
    Decline to Answer
3 (1.15%) 11 (2.20%)
    Mexican, Mexican American, or Chicano/a
1 (0.38%) 2 (0.40%)
    Puerto Rican
2 (0.77%) 3 (0.60%)
    Cuban
0 (0%) 1 (0.20%)
    Other Hispanic, Latino/a, or Spanish origin
4 (1.54%) 3 (0.60%)
    Not available
9 (3.46%) 9 (1.80%)
Race 760

    White
216 (83.1%) 401 (80.2%)
    Black or African American
26 (10.0%) 74 (14.8%)
    American Indian or Alaska Native
0 (0%) 2 (0.40%)
    Other Asian
3 (1.15%) 4 (0.80%)
    Native Hawaiian or Other Pacific Islander
2 (0.77%) 0 (0%)
    Other
5 (1.92%) 8 (1.60%)
    Decline to Answer
3 (1.15%) 8 (1.60%)
    Chinese
0 (0%) 1 (0.20%)
    Vietnamese
0 (0%) 1 (0.20%)
    Asian Indian
1 (0.38%) 0 (0%)
    Not available
4 (1.54%) 1 (0.20%)
Clinic 760

    Cardiology
5 (1.92%) 10 (2.00%)
    Dermatology
27 (10.4%) 54 (10.8%)
    Endocrinology
5 (1.92%) 10 (2.00%)
    GI/IBD
40 (15.4%) 78 (15.6%)
    Hepatology (non-hepatitis)
3 (1.15%) 6 (1.20%)
    HIV
9 (3.46%) 18 (3.60%)
    HCV
3 (1.15%) 6 (1.20%)
    Other Infectious Diseases
1 (0.38%) 2 (0.40%)
    Oncology/hematology
49 (18.8%) 95 (19.0%)
    Non-MS Neurology
7 (2.69%) 12 (2.40%)
    MS
26 (10.0%) 44 (8.80%)
    Pediatric Inflammatory
2 (0.77%) 4 (0.80%)
    Pediatric, Other
0 (0%) 0 (0%)
    Pulmonology
6 (2.31%) 12 (2.40%)
    Rheumatology
62 (23.8%) 122 (24.4%)
    Transplant
2 (0.77%) 4 (0.80%)
    Other
13 (5.00%) 23 (4.60%)
Referral Status 760

    Continuing therapy
146 (56.2%) 276 (55.2%)
    New medication
114 (43.8%) 224 (44.8%)
1 n (%)

Medication Access and Time to Access

Descriptive statistics

Characteristic N AFP
AFP, N = 2601 Non-AFP, N = 5001
Medication access 760

    Yes
216 (83.1%) 470 (94.0%)
    No
29 (11.2%) 23 (4.60%)
    Unsure
10 (3.85%) 6 (1.20%)
    Unknown
5 (1.92%) 1 (0.20%)
Referral Outcome 760

    Filled by a US pharmacy (original product or alternative)
79 (30.4%) 443 (88.6%)
    Filled through manufacturer PAP
85 (32.7%) 24 (4.80%)
    Filled by a non-US pharmacy
42 (16.2%) 0 (0%)
    Medication changed to medical benefit medication
8 (3.08%) 15 (3.00%)
    Patient lost to follow up during access process
15 (5.77%) 7 (1.40%)
    Patient changed insurance to get medication approved
15 (5.77%) 0 (0%)
    Nonstart- never accessed treatment
7 (2.69%) 3 (0.60%)
    Therapy no longer needed/Pursued for clinical reasons during access process
1 (0.38%) 5 (1.00%)
    Filled at HSSP covered by internal grant
5 (1.92%) 0 (0%)
    Filled through Manufacturer Bridge Program
2 (0.77%) 1 (0.20%)
    Filled using samples or internal supply
1 (0.38%) 1 (0.20%)
    Other
0 (0%) 1 (0.20%)
Time to access 698

    Mean (SD)
41.3 (34.1) 14.6 (18.0)
    Median (IQR)
31.5 (18.0 - 55.0) 8.0 (5.0 - 16.0)
    Range
0.0 - 184.0 0.0 - 129.0
Applied for manufacturer patient assistance programs (PAP) 760

    No
90 (34.6%) 452 (90.4%)
    Yes
170 (65.4%) 48 (9.60%)
PAP approved 225

    Yes
85 (48.0%) 40 (83.3%)
    No
92 (52.0%) 8 (16.7%)
PAP denial reason 100

    Identified AFP enrollment
39 (44.8%) 0 (0%)
    Unknown
23 (26.4%) 0 (0%)
    Other
15 (17.2%) 6 (46.2%)
    Overqualified financially
7 (8.05%) 4 (30.8%)
    Incomplete PAP enrollment paperwork
3 (3.45%) 3 (23.1%)
PA submitted 755

    Yes
190 (73.1%) 296 (59.8%)
    No
70 (26.9%) 199 (40.2%)
Appeal submitted 121

    No
63 (72.4%) 12 (35.3%)
    Yes
24 (27.6%) 22 (64.7%)
1 n (%)

Figures

Medication access analysis

Group Non-AFP / Continuing therapy, N = 1461 AFP / Continuing therapy, N = 2761 Non-AFP / New medication, N = 1141 AFP / New medication, N = 2241
Medication access



    No 15 (10.3%) 6 (2.2%) 14 (12.3%) 17 (7.6%)
    Unknown 5 (3.4%) 1 (0.4%) 0 (0.0%) 0 (0.0%)
    Unsure 0 (0.0%) 0 (0.0%) 10 (8.8%) 6 (2.7%)
    Yes 126 (86.3%) 269 (97.5%) 90 (78.9%) 201 (89.7%)
1 n (%)
Mixed-Effects Logistic Regression Results: Medication Access (Unknown is dropped)
95% CI for OR
Term Log(OR) Odds Ratio Lower Upper P-value
Intercept 2.294 9.914 4.224 23.267 <0.001
AFP status: Non-AFP vs AFP 1.163 3.200 1.755 5.835 <0.001
Referral: New vs continuing -0.673 0.510 0.273 0.953 0.035

Time to medication access analysis

Descriptive statistics

Group Non-AFP / Continuing therapy, N = 276 AFP / Continuing therapy, N = 146 Non-AFP / New medication, N = 224 AFP / New medication, N = 114
time_to_access



    Median [IQR] (range: Range) 7.0 [4.0, 14.0] (range: 0.0, 117.0) 33.5 [14.3, 55.8] (range: 0.0, 184.0) 11.0 [5.0, 21.0] (range: 0.0, 129.0) 29.0 [19.0, 53.5] (range: 2.0, 155.0)
    Unknown 1 20 17 24

Survival Model

Cox proportional hazards with site frailty (HR > 1 = faster access)
Term HR 95% CI p-value
AFP status: Non-AFP vs AFP 3.37 [2.82, 4.03] <0.001
Referral: New vs continuing 0.86 [0.72, 1.01] 0.068

Figures

Treatment Gaps and Urgent Supply Use

Characteristic N afp
Non-AFP, N = 5001 AFP, N = 2601
Treatment gap 428

    No
265 (94.0%) 79 (54.1%)
    Yes
5 (1.77%) 51 (34.9%)
    Unknown
12 (4.26%) 16 (11.0%)
    Missing
218 114
Samples provided 760

    No
474 (94.8%) 219 (84.2%)
    Yes
10 (2.00%) 31 (11.9%)
    Unsure
16 (3.20%) 10 (3.85%)
Courtesy fill provided 259

    No
0 (NA%) 168 (64.9%)
    Not needed or requested
0 (NA%) 53 (20.5%)
    Yes
0 (NA%) 38 (14.7%)
    Missing
500 1
1 n (%)

Poor clinical outcomes

Characteristic N afp
Non-AFP, N = 5001 AFP, N = 2601
Any poor clinical outcomes 760

    No poor clinical outcome
493 (98.6%) 232 (89.2%)
    Poor clinical outcome
7 (1.40%) 28 (10.8%)
1 n (%)

Poor clinical outcome description

Characteristic afp Overall, N = 7571
Non-AFP, N = 5001 AFP, N = 2571
Disease progression/worsening/flare 4 (0.80%) 23 (8.95%) 27 (3.57%)
Disease-related non-scheduled clinic visit 0 (0%) 4 (1.56%) 4 (0.53%)
Disease-related urgent care/ED visit 1 (0.20%) 1 (0.39%) 2 (0.26%)
Disease-related hospitalization 2 (0.40%) 0 (0%) 2 (0.26%)
None of the above 479 (95.8%) 117 (45.5%) 596 (78.7%)
Unsure 14 (2.80%) 112 (43.6%) 126 (16.6%)
1 n (%)

Human resources communications

HR communication descriptions

Characteristic N afp
Non-AFP, N = 5001 AFP, N = 2601
Communicated with HR dept about access process 257

    Yes
0 (NA%) 19 (7.39%)
    No
0 (NA%) 84 (32.7%)
    Unknown
0 (NA%) 154 (59.9%)
    Missing
500 3
1 n (%)
Characteristic N = 7571
Appeal to override AFP process 10 (1.32%)
Voiced concern about the AFP process 5 (0.66%)
Discussed explanation of benefits/AFP process 5 (0.66%)
Other 1 (0.13%)
Unknown 3 (0.40%)
1 n (%)

Pharmacy Staff Time

Descriptive statistics

Characteristic N afp
Non-AFP, N = 500 AFP, N = 260
Pharmacist time spent on access process 749

    Mean (SD)
1.1 (1.0) 3.7 (3.8)
    Median (IQR)
1.0 (0.5 - 1.5) 2.0 (1.0 - 4.0)
    Range
0.0 - 8.0 0.5 - 30.0
    Missing
1 10

AFP Identification

Characteristic N N = 2611
Method of AFP Identification 254
    Access approved, but forced to sign up for AFP
72 (28.3%)
    Access approved, patient must apply for PAP
1 (0.39%)
    Access denied, patient must apply for PAP
6 (2.36%)
    Access denied, patient must contact AFP
55 (21.7%)
    AFP contacted clinic for therapy change
2 (0.79%)
    AFP contacted clinic to apply for PAP
11 (4.33%)
    AFP contacted patient directly
7 (2.76%)
    Identified by PAP
9 (3.54%)
    No option to submit PA or appeal, directed to PAP
45 (17.7%)
    On BI, ineligible for HSSP, contact AFP
30 (11.8%)
    Prescription required to be sent internationally
14 (5.51%)
    Unknown
2 (0.79%)
    Missing
7
1 n (%)

Patient Stories

Common scenarios experienced by pharmacy staff

  • Lack of communication or inability to reach AFP
  • Required to apply for manufacturer PAP as first step
  • Use of “shell pharmacies” – U.S. pharmacies that source product internationally
  • Fills or shipments not authorized by the prescribing provider or from an unknown provider
  • Delays with international deliveries and medication destruction at the border

Patient 1 – 34-year-old, Stage IV colorectal cancer

  • PA submitted → denied (no appeal process)
  • Required to apply for PAP → denied (AFP enrollment)
  • Required passport and telehealth with PriceMD (not cancer provider)
  • Received 3-month supply from international pharmacy
    Time to access: ~5 months PharmD time: 15 hours

Patient 2 – 51-year-old, severe Crohn’s disease

  • PA submitted → denied (no appeal option)
  • Required to apply for PAP → denied
  • IV re-induction required
  • Appeal to AFP → approved for Canadian pharmacy fill
  • Canadian worker strike delayed delivery
  • Temporary U.S. pharmacy fill allowed
    Time to access: ~5 months PharmD time: 10 hours

Patient 3 – 55-year-old, primary biliary cirrhosis

  • PAP denied → required Medicaid → denied → re-applied → denied again
  • Allowed to fill at Accredo with Foundation grant and maximizer program
    Time to access: 1 month PharmD time: 6 hours

Patient 4 – 55-year-old, severe Crohn’s disease

  • 1st PAP denied → 2nd PAP denied
  • U.S. pharmacy Rx filled internationally
    Time to access: 2 months PharmD time: 2 hours

Patient 5 – 33-year-old, ulcerative pancolitis

  • PA approved
  • Samples provided after 19 days without response
  • AFP requested 3-month supply
  • Another sample sent; received medication via international pharmacy
    Time to access: 2 months PharmD time: 3 hours

Patient 6 – 35-year-old, ulcerative pancolitis

  • AFP, Accredo, and Cigna each waiting on one another
  • AFP eventually approved Accredo fill
    Time to access: 2 months PharmD time: 1.5 hours

Patient 7 – 50-year-old, severe psoriasis

  • PA denied → PAP denied → appeal approved
  • One fill at Kroger; maintenance from GlobalRx (Canada, NZ, Australia, England)
    Time to access: 3 weeks PharmD time: 4 hours

Patient 8 – 36-year-old, severe Crohn’s disease

  • Mid-year insurance change required Intercept Rx
  • Provider faxed new Rx (e-scribe not accepted)
  • Medication shipped from Canada by unknown provider
    Time to access: 3 weeks PharmD time: 2 hours

Patient 9 – 63-year-old, mantle cell lymphoma

  • Initial fill via GlobalRx (Australia)
  • Refill halted due to tariffs; AFP allowed one-time U.S. override
  • Refill delays ≥ 3 weeks
    Time to access refill: > 1 month PharmD time: 0.5 hours

Acknowledgements

This study was completed by the Vanderbilt Health System Specialty Pharmacy Outcomes Research Consortium, including:
Vanderbilt Health, Shields Health Solutions, Ochsner Health, Cleveland Clinic Specialty Pharmacy, Froedtert Health Pharmacy Solutions, University of Utah Health, Medical University of South Carolina, University of Kansas Health System, Cleveland Clinic Foundation, MetroHealth System, University of Rochester Medical Center, and University of Illinois Chicago.

This work was supported by Vanderbilt University Medical Center biostatisticians Ryan Moore, MS, and Leena Choi, PhD.

Note: Data collection continued through 2025. Analyses are ongoing, and a manuscript including 2024–2025 data is anticipated in Fall 2026.