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| ID | Type | Description | Link |
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| 5K23DK132454 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) | NIH |
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The HEAL-Tx is a 90-day intervention, in which a Health Advocate works with eligible families to identify and apply for community-based resources, alert healthcare providers to challenges the family is encountering, and guide health system navigation (e.g., coordinating appointments). Families in the control arm will receive a printed handout that provides contact information for local community-based resources. Families in the treatment arm will receive HEAL-Tx.
HEAL-Tx trial is a Type 1 hybrid effectiveness-implementation trial across 6 U.S. transplant centers (UCSF, Seattle Children's Hospital, Stanford University, Children's Healthcare of Atlanta, University of Pittsburgh, Children's Hospital of Colorado.) Children/families will be screened for material economic hardship as part of standard of care during their transplant hospitalization using the 10-question Accountable Healthcare Communities tool. Families who report material economic hardship will be approached for study participation, and those who consent will be randomized to either the control or treatment arm. Participants in the control arm will receive enhanced standard of care: they will receive a printed handout with a list of resources specific to their hardship and their home ZIP code. They will also receive a follow-up call at 45-days with a reminder of the suggested resources. Participants in the treatment arm will receive a customized 90-day Health Advocate intervention. Both the treatment and control arm group will complete a baseline interview and a close-out 90-day interview to assess outcomes and experiences with the intervention. The treatment arm will have one additional interview at the 45-day timepoint. Once both arms complete treatment, they will have data extracted from their medical records at the 1, and 2-year timepoint.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Health Advocate Intervention | Experimental | The caregiver will receive 90-days of tailored health advocate intervention |
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| Enhanced Control | Active Comparator | The caregiver will receive a printed sheet of resources once and a follow-up call at the 45-day timepoint with a reminder of the suggested resources. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Health advocate | Behavioral | The health advocate is a trained individual who is not a part of the medical team. They work directly with the caregivers of patients who have received a liver transplantation to assist them with navigating the healthcare system, find resources, and relay any concerns to their medical team. They work with an assigned family for 90-days and tailor their intervention to meet the families social needs. |
| Measure | Description | Time Frame |
|---|---|---|
| Time-to-TCMR between 90 days and 2 years post-transplant using Kaplan-Meir plots. | After the perioperative period, it is an objective outcome closely linked with poor adherence/challenges with self-management. Investigators found strong associations between material economic hardship and TCMR episodes of TCMR increase risks of graft failure/death post-transplant and early TCMR increases risk of late TCMR and vulnerability to infections. All analyses will be intention-to-treat. Investigators will use Kaplan-Meier plots to descriptively compare survival distributions of the primary outcome (TCMR) by trial arm. We will compare time-to-TCMR between treatment arms using Cox regression. For participants recruited in years 1 & 2 of the study period, we will collect 2 years of follow-up data. For participants recruited in year 3, we will apply administrative censoring after 1 year of follow up data. | Through study completion, an average of 1 year up to 2 years. |
| Measure | Description | Time Frame |
|---|---|---|
| Measurement of incidence of Medication Level Variability Index >2.0 using generalized linear mixed effect models. | An MLVI >2.0 predicted late TCMR, even after accounting for other causes of tacrolimus fluctuations. In the first 6 months after transplant, tacrolimus levels can fluctuate based on physiological changes associated with transplant. After 6 months, fluctuations are most likely related to poor adherence. Investigators will measure the incidence of MLVI >2.0 between 6 months - 1 year, and 1year and 2 years. If a patient has an episode of TCMR within this time, investigators will only collect tacrolimus levels preceding this event. Investigators will calculate MLVI based on available levels for 6 months - 1 year, and for 1year - 2 years. Investigators will use generalized linear mixed effects models for dichotomous outcomes to analyze MLVI >2.0. Models will also include random effects for each patient, and fixed effects that include trial arm, time since randomization and site. If differences in groups are observed, interaction terms may be introduced to assess heterogeneity in trends. |
| Measure | Description | Time Frame |
|---|---|---|
| Implementation outcomes using the RE-AIM model. | Reach: Differences in EHR-abstracted sociodemographic characteristics and center differences (enrolled vs. declined) Adoption: Differences in adoption by clinician type Implementation: Identify factors from enrollment associated with quantitative implementation measures Maintenance: Investigators will analyze whether attrition rates differ by type Investigators will collect interviews from both treatment arms at baseline and the 90-day timepoint. Patients in the treatment arm will have one additional qualitative interview (45-day timepoint.) The interviews will be recorded and transcribed. Codebooks will be developed for the caregiver, health advocate and clinician informant interviews using COM-B components to identify barriers and facilitators to adoption, implementation and maintenance. Investigators will iteratively refine and update the codebooks during data collection, allowing for open coding to occur to capture inductive codes. Each transcript will be coded by two coders. |
Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Sharad Wadhwani, MD, MPH | University of California, San Francisco | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of California, San Francisco | San Francisco | California | 94158 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 17584404 | Background | Monette S, Seguin L, Gauvin L, Nikiema B. Validation of a measure of maternal perception of the child's health status. Child Care Health Dev. 2007 Jul;33(4):472-81. doi: 10.1111/j.1365-2214.2006.00713.x. | |
| 11926838 | Background | Minkovitz CS, O'Campo PJ, Chen YH, Grason HA. Associations between maternal and child health status and patterns of medical care use. Ambul Pediatr. 2002 Mar-Apr;2(2):85-92. doi: 10.1367/1539-4409(2002)0022.0.co;2. |
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| Related Info | View source |
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| Enhanced Control | Behavioral | Caregivers in the control arm will receive enhanced standard of care: they will be given a handout with a list of resources specific to their hardship and their home ZIP code. They will receive a follow-up call at 45 days with a reminder of the suggested resources. |
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| Through study completion, an average of one year up to 2 years. |
| Change in Parent-Reported Social Needs Score From Baseline to 90 Days (SIREN-Informed PRO Measure) | Parent-reported social needs will be assessed using a SIREN-informed patient-reported outcome measure. Scores will be calculated at baseline and 90 days. Change scores will be compared between treatment arms using a t-test, and the primary analysis will use linear regression (ANCOVA) with the baseline score as a covariate to estimate the mean difference in change between groups. | Baseline and 90-days post enrollment |
| Liver inflammation (ALT or GGT >50) and overimmunosuppression (positive EBV or CMV PCR) at years 1 and 2 using linear mixed effects models. | Investigators will use generalized linear mixed effects models for dichotomous outcomes to analyze liver inflammation and overimmunosuppression. Models will include random effects for each patient, and fixed effects for trial arm, time since randomization (allowing investigators to assess trends), and site. | An average of 1 year up to 2 years. |
| Parent-Reported Social Service Utilization (Count of Services Received) | Parents will report whether social services were received in the 90-day period following enrollment. Investigators will summarize utilization using counts and percentages and compare across centers using chi-square tests. | 90-days post enrollment |
| Change in Parent-Reported Social Service Utilization From Baseline to 90 Days | Receipt of social services will be recorded at baseline and 90 days. The change in utilization will be compared between treatment arms using t-tests and modeled using ANCOVA with baseline utilization as a covariate. | Baseline and 90 days post-enrollment |
| Parent-Reported Social Needs Score at Baseline (SIREN-Informed PRO Measure) | Baseline social needs scores will be summarized using medians and quartiles for continuous measures. | Baseline |
| Parent-Reported Social Needs Score at 90 Days (SIREN-Informed PRO Measure) | Follow-up social needs scores at 90 days will be summarized and compared across centers using Kruskal-Wallis tests. | 90-days post enrollment |
| Baseline, Day-45 (treatment arm only), 90-day timepoints |
| 31046080 | Background | Witte J, Mehlis K, Surmann B, Lingnau R, Damm O, Greiner W, Winkler EC. Methods for measuring financial toxicity after cancer diagnosis and treatment: a systematic review and its implications. Ann Oncol. 2019 Jul 1;30(7):1061-1070. doi: 10.1093/annonc/mdz140. |