BACKGROUND:

Children with complex chronic conditions (CCCs) require a disproportionate share of health care services and have high mortality rates, but little is known about their end-of-life care.

METHODS:

We performed a retrospective population-based analysis using a California State administrative database of children aged 1 to 21 years with a CCC who died of disease-related causes between 2000 and 2013. Rates of and sociodemographic and clinical factors associated with previously defined inpatient end-of-life intensity indicators were determined. The intensity indicators included: (1) hospital death, (2) receipt of a medically intense intervention within 30 days of death (ICU admission, cardiopulmonary resuscitation, hemodialysis, and/or intubation), and (3) having ≥2 intensity markers (including hospital death).

RESULTS:

There were 8654 children in the study population with a mean death age of 11.8 years (SD 6.8). The 3 most common CCC categories were neuromuscular (47%), malignancy (43%), and cardiovascular (42%). Sixty-six percent of the children died in the hospital, 36% had a medically intense intervention in the last 30 days of life, and 35% had ≥2 intensity markers. Living in a low-income neighborhood was associated with increased odds of hospital death, a medically intense intervention, and ≥2 intensity markers. Hispanic and “other” race and/or ethnicity were associated with hospital death and ≥2 intensity markers. Age 15 to 21 years was associated with hospital death, a medically intense intervention, and ≥2 intensity markers.

CONCLUSIONS:

Sociodemographic disparities in the intensity of end-of-life care for children with CCCs raise concerns about whether all children are receiving high-quality and goal-concordant end-of-life care.

What’s Known on This Subject:

Children with complex chronic conditions require a disproportionate share of health care services and have high mortality rates, but little is known about their end-of-life care, particularly the inpatient intensity of end-of-life care.

What This Study Adds:

Sixty-six percent of children with complex chronic conditions die in the hospital, and 36% receive a medically intense intervention (eg, intubation, hemodialysis) at end-of-life. Intense inpatient end-of-life care is most common among adolescents, non–African American minority children, and children from poorer communities.

Children with complex chronic conditions (CCCs) are among the most vulnerable children in the United States. They have chronic conditions that involve “different organ systems or 1 organ system severely enough to require specialty pediatric care and probably some degree of hospitalization in a tertiary care center.”1 Though a small proportion of US children, children with CCCs account for ∼30% of pediatric health care costs, with ∼80% of expenditures in the inpatient setting.2,4 Families of children with CCCs report unmet medical needs, lack of care coordination, poor provider communication, and psychological and social burdens of care.5,8 Furthermore, they experience a high risk of mortality, with >20% of child deaths and 40% of child inpatient deaths attributed to CCCs.9,10 

However, end-of-life care for children with CCCs remains poorly understood. The American Academy of Pediatrics calls for a palliative approach to children with life-threatening illnesses,11 including symptom management and goals of care communication. Thus, basic information about end-of-life care for children with CCCs is needed. The last US population-based study used to assess death location among children with CCCs (1989–2003) revealed that >80% of children with CCCs died in the inpatient setting.9 In 2 recent studies, the authors examined children who died within children’s hospitals but not children who died at home or non–children’s hospitals.12,13 Hospitalization and medically intense interventions (eg, intubation) play an important role in aspects of care for children with CCCs but may not be beneficial at the end of life.14,16 Although sociodemographic disparities in intensity of end-of-life care have been found in pediatric oncology patients17,18 and in death location for children with CCCs,1,9,19 sociodemographic variation was not examined in previous US population-based studies of intensity of end-of-life care (beyond location) in children with CCCs.12 

There is an urgent need to examine patterns of end-of-life care, including clinical and sociodemographic variation, in US children with CCCs to better understand the needs of children and families during these critical times. We assessed socioeconomic and clinical disparities in the rates of medically intense end-of-life care (hospital death, procedures [eg, intubation], or ICU admission in the last 30 days of life) for all California children with a CCC.

We conducted a retrospective (2000–2013) population-based analysis using the California Office of Statewide Health Planning and Development (OSHPD) private discharge data linked to death certificates. OSHPD links the final hospital discharge and death certificate data at the individual level. Every California hospital (except prison hospitals and federal facilities) reports discharge information (including age, sex, race and/or ethnicity, payer, residence zip code, and associated International Classification of Diseases, Ninth Revision [ICD-9] or International Classification of Diseases, 10th Revision codes) to OSHPD. Age, location, and cause of death are reported in the death certificate. The Stanford University Institutional Review Board and the California Committee for Protection of Human Subjects approved the study. Reporting guidelines for administrative data studies were used.20 

The study included California residents age 1 to 21 years at the time of death with an ICD-9 or International Classification of Diseases, 10th Revision code for a CCC as the cause of death on their death certificate (allowing capture of patients not admitted in their last year) or as the discharge diagnosis within 1 year of death. Patients age <1 year were excluded because end-of-life care for neonates is distinct. Patients who died because of peripartum events or unintentional injuries (except medical errors) were excluded to capture deaths related to the CCC rather than a sudden event, such as trauma (Fig 1). CCCs were defined as described by Feudtner et al,21 with modifications to ensure diagnoses were listed under the organ system associated with the pediatric specialist most likely to assume the patient’s primary care because authors of future studies and potential interventions may target individual specialties (ie, diabetes and endocrinology). After iterative review of the CCC rates in our population by 3 pediatricians, these modifications included the following: (1) removing the neonatal and/or prematurity category because we were excluding those age <1 year and wanted CCCs that were cared for by specific subspecialists over the disease course; (2) moving tracheostomy tube–related and gastrostomy tube–related codes to “technology dependence” (n = 2587 resorted; no removal of patients); (3) dropping unspecified aplastic anemia and pancytopenia because they were too broad and not consistent with clinical practice rates (n = 2112; removal of 497 patients); and (4) re-sorting 6 diagnoses (n = 112 patients) to different categories (cerebral vessel anomalies and neurofibromatosis 1 moved to neuromuscular; Fabry disease, sphingolipid disorders, ichthyosis, and gangliosidosis moved to metabolic).

FIGURE 1

Consolidated Standards of Reporting Trials diagram of study population.

FIGURE 1

Consolidated Standards of Reporting Trials diagram of study population.

Close modal

Markers of inpatient intensity of end-of-life care have been previously described.15,16,22,23 These included hospital death, invasive procedures (hemodialysis, intubation, cardiopulmonary resuscitation [CPR]), and ICU admission in the last 30 days of life.15,22,23 ICD-9 codes were previously described.18,23,24 Because codes pertain to an entire admission, not a specific day, procedures were included if they were coded during an admission that occurred within 30 days of death. Dependent variables used in the regression analysis were the following: (1) hospital death, (2) a medically intense intervention (hemodialysis, CPR, intubation, or ICU admission) in the last 30 days of life, and (3) ≥2 intensity markers (including hospital death).

Clinical variables included CCC category21 and number of CCCs. Sociodemographic variables included death age, sex, race and/or ethnicity, payer, median household income in residence zip code (based on the 2004 federal poverty level [FPL]), metropolitan statistical area, death year, and distance from home to pediatric specialty center. Variables were abstracted from the death certificate when available or, otherwise, from last hospital discharge record.

Descriptive statistics were calculated for each dependent and independent variable. Children who had multiple CCCs were included in descriptive statistics for each of their CCC categories. Separate multivariable logistic regression models were constructed to evaluate clinical and sociodemographic factors associated with the 3 dependent variables. Because the independent variables were selected a priori, all variables were used in the multivariable analysis. In sensitivity analyses, rates of intensity markers were calculated separately for patients who (1) died in the hospital and at home (in case only the patients who died in the hospital were receiving intense end-of-life care) and (2) had a surgical procedure (to determine if intubations were only with anesthesia). Regression models were constructed with and without technology dependence as an independent variable to ensure that children with technology dependence were not skewing overall study results. SAS version 9.1 (SAS Institute, Inc, Cary, NC) was used.

The 8654 children in the study population (Fig 1) had a mean death age of 11.8 years (SD 6.8). Overall, 43% died between 15 and 21 years (Table 1). The 3 most common CCC categories were neuromuscular (47%), malignancy (43%), and cardiovascular (42%) (Table 1). Twenty-six percent had 1 CCC category, 32% had 2 CCC categories, and 42% had ≥3 CCC categories. The most common race and/or ethnicity was Hispanic (44%) followed by non-Hispanic white (33%). The majority of patients were publicly insured (64%) and lived in areas with a median family income 2 to 4 times the FPL (60%).

TABLE 1

Sociodemographic and Clinical Characteristics of Study Population

CharacteristicsN = 8654, n (%)
Age at death, y  
 1–4 1890 (21.8) 
 5–9 1451 (16.8) 
 10–14 1612 (18.6) 
 15–21 3701 (42.8) 
Sex  
 Male 4865 (56.2) 
 Female 3788 (43.8) 
Race and/or ethnicity  
 Non-Hispanic white 2831 (32.7) 
 African American 854 (9.9) 
 Hispanic 3833 (44.3) 
 Other 1136 (13.1) 
Insurance status  
 HMO 1031 (11.9) 
 Private 2119 (24.5) 
 Public or self-pay 5501 (63.6) 
Median household income in county  
 <2 times the FPL 2419 (28.0) 
 2–4 times the FPL 5191 (60.0) 
 >4 times the FPL 888 (10.3) 
Year of death  
 2000–2004 3676 (42.5) 
 2005–2009 3196 (36.9) 
 2010–2013 1782 (20.6) 
Metropolitan statistical area  
 Rural 619 (7.2) 
 Urban 8035 (92.9) 
Distance closest specialty care center, miles  
 <6 2079 (24.0) 
 6–20 3450 (39.9) 
 21+ 3124 (36.1) 
Chronic condition diagnosis  
 Cardiovascular disease 3672 (42.4) 
 Congenital and/or genetic 1586 (18.3) 
 Gastrointestinal 1630 (18.8) 
 Hematologic and/or immunologic 1272 (14.7) 
 Malignancy 3749 (43.3) 
 Metabolic 2081 (24.1) 
 Neuromuscular 4039 (46.7) 
 Renal 2100 (24.3) 
 Respiratory 1015 (11.7) 
No. chronic conditions  
 1 2242 (25.9) 
 2 2744 (31.7) 
 ≥3 3688 (42.4) 
Gastrostomy tube or tracheostomy tube present 2587 (29.9) 
CharacteristicsN = 8654, n (%)
Age at death, y  
 1–4 1890 (21.8) 
 5–9 1451 (16.8) 
 10–14 1612 (18.6) 
 15–21 3701 (42.8) 
Sex  
 Male 4865 (56.2) 
 Female 3788 (43.8) 
Race and/or ethnicity  
 Non-Hispanic white 2831 (32.7) 
 African American 854 (9.9) 
 Hispanic 3833 (44.3) 
 Other 1136 (13.1) 
Insurance status  
 HMO 1031 (11.9) 
 Private 2119 (24.5) 
 Public or self-pay 5501 (63.6) 
Median household income in county  
 <2 times the FPL 2419 (28.0) 
 2–4 times the FPL 5191 (60.0) 
 >4 times the FPL 888 (10.3) 
Year of death  
 2000–2004 3676 (42.5) 
 2005–2009 3196 (36.9) 
 2010–2013 1782 (20.6) 
Metropolitan statistical area  
 Rural 619 (7.2) 
 Urban 8035 (92.9) 
Distance closest specialty care center, miles  
 <6 2079 (24.0) 
 6–20 3450 (39.9) 
 21+ 3124 (36.1) 
Chronic condition diagnosis  
 Cardiovascular disease 3672 (42.4) 
 Congenital and/or genetic 1586 (18.3) 
 Gastrointestinal 1630 (18.8) 
 Hematologic and/or immunologic 1272 (14.7) 
 Malignancy 3749 (43.3) 
 Metabolic 2081 (24.1) 
 Neuromuscular 4039 (46.7) 
 Renal 2100 (24.3) 
 Respiratory 1015 (11.7) 
No. chronic conditions  
 1 2242 (25.9) 
 2 2744 (31.7) 
 ≥3 3688 (42.4) 
Gastrostomy tube or tracheostomy tube present 2587 (29.9) 

HMO, health maintenance organization.

Sixty-six percent of the patients died in the hospital (Table 2). The categories of CCCs with the highest rates of hospital death were hematologic and/or immunologic (80%), renal (76%), and cardiovascular (76%). Patients with cardiovascular, hematologic and/or immunologic, metabolic, renal, and respiratory conditions were more likely to die in the hospital than others. Patients with malignancies were less likely to die in the hospital (Table 3).

TABLE 2

Rates and Number of Children Affected by Each End-of-Life Intensity Outcome by CCC Category

CCC Category (n)Hospital Death, n (%)Medically Intense Intervention, n (%)≥2 Intensity Markers, n (%)CPR, n (%)Hemodialysis, n (%)ICU Admission, n (%)Intubation, n (%)
Overall (8654) 5721 (66.1) 3107 (35.9) 3046 (35.2) 969 (11.2) 377 (4.4) 2911 (33.6) 2064 (23.9) 
Cardiovascular (3672) 2774 (75.5)a 1569 (42.7)a 1541 (42.0)a 642 (17.5)a 224 (6.1)a 1452 (39.5)a 1057 (28.8)a 
Congenital and/or genetic (1586) 1037 (65.4) 595 (37.5) 580 (36.6) 172 (10.8)a 40 (2.5) 567 (35.8) 368 (23.2) 
Gastrointestinal (1630) 1125 (69.0) 549 (37.5) 539 (33.1) 166 (10.2) 79 (2.5) 511 (31.3) 358 (22.0) 
Hematologic and/or immunologic (1272) 1013 (79.6)a 430 (33.8) 426 (33.5) 136 (10.7) 111 (8.7)a 391 (30.7) 314 (24.7) 
Malignancy (3749) 2365 (63.1) 830 (22.1) 818 (21.8) 201 (5.4) 115 (3.1) 779 (20.8) 630 (16.8) 
Metabolic (2081) 1539 (74.0) 814 (39.1)a 800 (38.4)a 206 (9.9) 114 (5.5) 766 (36.8)a 535 (25.7)a 
Neuromuscular (4039) 2659 (65.8) 1635 (40.5)a 1600 (39.6)a 426 (10.5) 105 (2.6) 1577 (39.0)a 979 (24.2) 
Renal (2100) 1604 (76.4)a 806 (38.4) 788 (37.5) 235 (11.2)a 377 (18.0)a 727 (34.6) 558 (26.6)a 
Respiratory (1015) 717 (70.6) 375 (36.9) 357 (35.2) 90 (8.9) 20 (2.0) 361 (35.6) 173 (17.0) 
CCC Category (n)Hospital Death, n (%)Medically Intense Intervention, n (%)≥2 Intensity Markers, n (%)CPR, n (%)Hemodialysis, n (%)ICU Admission, n (%)Intubation, n (%)
Overall (8654) 5721 (66.1) 3107 (35.9) 3046 (35.2) 969 (11.2) 377 (4.4) 2911 (33.6) 2064 (23.9) 
Cardiovascular (3672) 2774 (75.5)a 1569 (42.7)a 1541 (42.0)a 642 (17.5)a 224 (6.1)a 1452 (39.5)a 1057 (28.8)a 
Congenital and/or genetic (1586) 1037 (65.4) 595 (37.5) 580 (36.6) 172 (10.8)a 40 (2.5) 567 (35.8) 368 (23.2) 
Gastrointestinal (1630) 1125 (69.0) 549 (37.5) 539 (33.1) 166 (10.2) 79 (2.5) 511 (31.3) 358 (22.0) 
Hematologic and/or immunologic (1272) 1013 (79.6)a 430 (33.8) 426 (33.5) 136 (10.7) 111 (8.7)a 391 (30.7) 314 (24.7) 
Malignancy (3749) 2365 (63.1) 830 (22.1) 818 (21.8) 201 (5.4) 115 (3.1) 779 (20.8) 630 (16.8) 
Metabolic (2081) 1539 (74.0) 814 (39.1)a 800 (38.4)a 206 (9.9) 114 (5.5) 766 (36.8)a 535 (25.7)a 
Neuromuscular (4039) 2659 (65.8) 1635 (40.5)a 1600 (39.6)a 426 (10.5) 105 (2.6) 1577 (39.0)a 979 (24.2) 
Renal (2100) 1604 (76.4)a 806 (38.4) 788 (37.5) 235 (11.2)a 377 (18.0)a 727 (34.6) 558 (26.6)a 
Respiratory (1015) 717 (70.6) 375 (36.9) 357 (35.2) 90 (8.9) 20 (2.0) 361 (35.6) 173 (17.0) 
a

The highest 3 rates in each category.

TABLE 3

Adjusted Odds of Having a Hospital Death, a Medically Intense Intervention, or ≥2 Intensity Markers

Hospital Death, aOR (95% CI)Medically Intense Intervention, aOR (95% CI)≥2 Intensity Markers, aOR (95% CI)
Age at death, y    
 1–4 0.9 (0.8–1.0) 1.0 (0.8–1.1) 1.1 (0.9–1.3) 
 5–9 Reference Reference Reference 
 10–14 1.2 (1.0–1.4)a 1.1 (0.9–1.3) 1.1 (0.9–1.3) 
 15–21 1.4 (1.2–1.6)a 1.4 (1.2–1.6)a 1.3 (1.1–1.5)a 
Sex    
 Male Reference Reference Reference 
 Female 1.2 (1.1–1.3)a 1.1 (1.0–1.2) 1.1 (1.0–1.2) 
Insurance    
 HMO Reference Reference Reference 
 Private 1.1 (0.9–1.3) 0.9 (0.7–1.0) 0.9 (0.8–1.1) 
 Public 1.2 (1.0–1.4)a 0.9 (0.8–1.1) 1.0 (0.9–1.1) 
Median household income    
 <2 times the FPL 1.2 (1.0–1.5)a 1.3 (1.1–1.6)a 1.3 (1.1–1.6)a 
 2–4 times the FPL 1.2 (1.0–1.4)a 1.2 (1.0–1.4)a 1.2 (1.0–1.4)a 
 >4 times the FPL Reference Reference Reference 
Race and/or ethnicity    
 Non-Hispanic white Reference Reference Reference 
 African American 1.0 (0.8–1.1) 1.1 (0.9–1.3) 1.2 (1.0–1.4) 
 Hispanic 1.3 (1.2–1.5)a 1.1 (1.0–1.2) 1.3 (1.1–1.4)a 
 Other 1.2 (1.0–1.4)a 1.0 (0.9–1.2) 1.3 (1.1–1.5)a 
Metropolitan statistical area    
 Rural Reference Reference Reference 
 Urban 1.0 (0.8–1.2) 1.0 (0.9–1.3) 1.0 (0.8–1.2) 
Year of death    
 2000–2004 Reference Reference Reference 
 2005–2009 0.8 (0.7–0.9)a 0.9 (0.8–1.0) 0.9 (0.8–1.0) 
 2010–2013 0.8 (0.7–0.9)a 1.0 (0.9–1.1) 0.9 (0.8–1.1) 
Distance from home to pediatric specialty center, miles    
 <6 Reference Reference Reference 
 6–20 1.3 (1.1–1.5)a 1.2 (1.0–1.3)a 1.2 (1.0–1.3)a 
 21+ 1.3 (1.1–1.4)a 1.1 (1.0–1.3)a 1.2 (1.1–1.3)a 
No. chronic conditions    
 1 Reference Reference Reference 
 2 1.1 (1.0–1.3) 1.0 (0.8–1.1) 1.0 (0.8–1.1) 
 ≥3 1.1 (0.8–1.5) 1.0 (0.8–1.3) 0.9 (0.7–1.2) 
CCC diagnosis (reference: no diagnosis in that category)    
 Cardiovascular disease 1.9 (1.7–2.2)a 1.6 (1.4–1.8)a 2.3 (2.0–2.6)a 
 Congenital and/or genetic 0.9 (0.7–1.0) 0.8 (0.7–0.9)a 0.8 (0.7–1.0)a 
 Gastrointestinal 1.0 (0.9–1.2) 0.7 (0.6–0.8)a 1.3 (1.1–1.4)a 
 Hematologic and/or immunologic 2.0 (1.6–2.3)a 0.9 (0.8–1.1) 1.8 (1.6–2.1)a 
 Malignancy 0.7 (0.6–0.9)a 0.3 (0.3–0.3)a 0.4 (0.3–0.5)a 
 Metabolic 1.5 (1.3–1.7)a 1.3 (1.2–1.5)a 1.5 (1.3–1.7)a 
 Neuromuscular 1.1 (1.0–1.3) 1.2 (1.1–1.4)a 1.5 (1.3–1.7)a 
 Renal 1.7 (1.4–1.9)a 1.3 (1.1–1.5)a 2.0 (1.7–2.3)a 
 Respiratory 1.2 (1.0–1.4)a 0.8 (0.7–1.0)a 1.4 (1.2–1.7)a 
Hospital Death, aOR (95% CI)Medically Intense Intervention, aOR (95% CI)≥2 Intensity Markers, aOR (95% CI)
Age at death, y    
 1–4 0.9 (0.8–1.0) 1.0 (0.8–1.1) 1.1 (0.9–1.3) 
 5–9 Reference Reference Reference 
 10–14 1.2 (1.0–1.4)a 1.1 (0.9–1.3) 1.1 (0.9–1.3) 
 15–21 1.4 (1.2–1.6)a 1.4 (1.2–1.6)a 1.3 (1.1–1.5)a 
Sex    
 Male Reference Reference Reference 
 Female 1.2 (1.1–1.3)a 1.1 (1.0–1.2) 1.1 (1.0–1.2) 
Insurance    
 HMO Reference Reference Reference 
 Private 1.1 (0.9–1.3) 0.9 (0.7–1.0) 0.9 (0.8–1.1) 
 Public 1.2 (1.0–1.4)a 0.9 (0.8–1.1) 1.0 (0.9–1.1) 
Median household income    
 <2 times the FPL 1.2 (1.0–1.5)a 1.3 (1.1–1.6)a 1.3 (1.1–1.6)a 
 2–4 times the FPL 1.2 (1.0–1.4)a 1.2 (1.0–1.4)a 1.2 (1.0–1.4)a 
 >4 times the FPL Reference Reference Reference 
Race and/or ethnicity    
 Non-Hispanic white Reference Reference Reference 
 African American 1.0 (0.8–1.1) 1.1 (0.9–1.3) 1.2 (1.0–1.4) 
 Hispanic 1.3 (1.2–1.5)a 1.1 (1.0–1.2) 1.3 (1.1–1.4)a 
 Other 1.2 (1.0–1.4)a 1.0 (0.9–1.2) 1.3 (1.1–1.5)a 
Metropolitan statistical area    
 Rural Reference Reference Reference 
 Urban 1.0 (0.8–1.2) 1.0 (0.9–1.3) 1.0 (0.8–1.2) 
Year of death    
 2000–2004 Reference Reference Reference 
 2005–2009 0.8 (0.7–0.9)a 0.9 (0.8–1.0) 0.9 (0.8–1.0) 
 2010–2013 0.8 (0.7–0.9)a 1.0 (0.9–1.1) 0.9 (0.8–1.1) 
Distance from home to pediatric specialty center, miles    
 <6 Reference Reference Reference 
 6–20 1.3 (1.1–1.5)a 1.2 (1.0–1.3)a 1.2 (1.0–1.3)a 
 21+ 1.3 (1.1–1.4)a 1.1 (1.0–1.3)a 1.2 (1.1–1.3)a 
No. chronic conditions    
 1 Reference Reference Reference 
 2 1.1 (1.0–1.3) 1.0 (0.8–1.1) 1.0 (0.8–1.1) 
 ≥3 1.1 (0.8–1.5) 1.0 (0.8–1.3) 0.9 (0.7–1.2) 
CCC diagnosis (reference: no diagnosis in that category)    
 Cardiovascular disease 1.9 (1.7–2.2)a 1.6 (1.4–1.8)a 2.3 (2.0–2.6)a 
 Congenital and/or genetic 0.9 (0.7–1.0) 0.8 (0.7–0.9)a 0.8 (0.7–1.0)a 
 Gastrointestinal 1.0 (0.9–1.2) 0.7 (0.6–0.8)a 1.3 (1.1–1.4)a 
 Hematologic and/or immunologic 2.0 (1.6–2.3)a 0.9 (0.8–1.1) 1.8 (1.6–2.1)a 
 Malignancy 0.7 (0.6–0.9)a 0.3 (0.3–0.3)a 0.4 (0.3–0.5)a 
 Metabolic 1.5 (1.3–1.7)a 1.3 (1.2–1.5)a 1.5 (1.3–1.7)a 
 Neuromuscular 1.1 (1.0–1.3) 1.2 (1.1–1.4)a 1.5 (1.3–1.7)a 
 Renal 1.7 (1.4–1.9)a 1.3 (1.1–1.5)a 2.0 (1.7–2.3)a 
 Respiratory 1.2 (1.0–1.4)a 0.8 (0.7–1.0)a 1.4 (1.2–1.7)a 

aOR, adjusted odds ratio; HMO, health maintenance organization; —, not applicable.

a

Significant at P < .05.

The sociodemographic factors associated with hospital death were adolescence (10–14 years: odds ratio [OR] = 1.2 [95% confidence interval (CI) 1.0–1.4]; 15–21 years: OR = 1.4 [95% CI 1.2–1.6]; reference: 5–9 years), Hispanic ethnicity (OR = 1.3 [95% CI 1.2–15]; reference: non-Hispanic white), “other” race and/or ethnicity (OR = 1.2 [95% CI 1.0–1.4]), and a low-income neighborhood (<2 times the FPL: OR = 1.2 [95% CI 1.0–1.5]; 2–4 times the FPL: OR = 1.2 [95% CI 1.0–1.4]; reference: >4 times the FPL). Other factors associated with hospital death included female sex, public insurance, death in 2000–2004, and living >5 miles from a specialty center (Table 3).

Thirty-six percent of patients had a medically intense inpatient intervention in the last 30 days of life, with 11% receiving CPR, 4% receiving hemodialysis, 24% intubated, and 34% with ICU admission (Table 2). The CCCs with the highest rates of medically intense interventions at the end of life were cardiovascular (43%) and neuromuscular (41%) disorders. Children with cardiovascular, metabolic, neuromuscular, and renal conditions were more likely to have medically intense interventions than others. Patients with a congenital and/or genetic, gastrointestinal, malignancy, or respiratory CCC were less likely to have medically intense interventions (Table 3).

The sociodemographic factors associated with inpatient medically intense interventions were late adolescence (15–21 years: OR = 1.4 [95% CI 1.2–1.6]; reference: 5–9 years), low-income neighborhood (<2 times the FPL: OR = 1.3 [95% CI 1.1–1.6]; 2–4 times the FPL: OR = 1.2 [95% CI 1.0–1.4]; reference: 4 times the FPL), and living >6 miles from a specialty center (6–20 miles: OR = 1.2 [95% CI 1.0–1.3]; ≥21 miles: OR = 1.1 [95% CI 1.0–1.3]; reference: <6 miles).

Thirty-five percent of the patients had ≥2 intensity markers (Table 2). Children with cardiovascular (42%) and neuromuscular (40%) conditions had the highest rates of ≥2 intensity markers. Children with cardiovascular, gastrointestinal, hematologic and/or immunologic, metabolic, neuromuscular, renal, and respiratory CCCs were more likely to have ≥2 intensity markers, and children with congenital and/or genetic and malignancy CCCs were less likely to have ≥2 intensity markers (Table 3).

The sociodemographic factors associated with ≥2 intensity markers were late adolescence (15–21 years: OR = 1.3 [95% CI 1.1–1.5]; reference: 5–9 years), ethnic minority status (Hispanic: OR = 1.3 [95% CI 1.1–1.4]; other: OR 1.3 [95% CI 1.1–1.5]; reference: non-Hispanic white), living >6 miles from a specialty center (6–20 miles: OR = 1.2 [95% CI 1.0–1.3]; ≥21 miles: OR = 1.2 [95% CI 1.1–1.3]; reference: <6 miles), and low-income neighborhood (<2 times the FPL: OR = 1.3 [95% CI 1.1–1.6]; 2–4 times the FPL: OR = 1.2 [95% CI 1.0–1.4]; reference: >4 times the FPL).

For each CCC, patients who died in the hospital and at home both had medically intense interventions (hospital: 52%; home: 5%) and ≥2 intensity markers (hospital: 52%; home: 3%), with higher rates in patients with hospital death. Patients with and without surgical procedures received intense interventions (Supplemental Table 4). Adding technology dependence as an independent variable did not change the direction or significance of findings.

We observed high-intensity end-of-life care and sociodemographic disparities in end-of-life care for children with CCCs. Overall, 66% of children with CCCs died in the hospital, 36% received an inpatient medically intense intervention, and 35% had ≥2 intensity markers. We found that end-of-life care varied by neighborhood income, age, and race and/or ethnicity in addition to diagnosis. To our knowledge, the only population-level variations in intensity of end-of-life care in children with CCCs previously reported were the following: (1) diagnosis associated with intensity of end-of-life care of children with CCCs who died in children’s hospitals12; (2) sex, race and/or ethnicity, and CCC category associated with death location1,9; (3) diagnosis, age, minority status, distance between home and hospital, and site of care associated with intensity of end-of-life care in California children with cancer18; and (4) age, income, and diagnosis associated with death location in Canada.19 Particularly striking is the association between neighborhood income and intensity of end-of-life care. These sociodemographic variations raise concerns about whether the 20 000 US children that die annually of disease-related causes25 are receiving quality end-of-life care that is consistent with patient and family goals (goal-concordant care).

In adult oncology, high medical intensity at end of life is considered poor-quality care because medically intense end-of-life care is generally not goal concordant26,27 and is associated with worse bereaved-family outcomes.28,29 Children with CCCs have less predictable clinical trajectories, and some acute episodes have a high chance of cure and meaningful recovery, making medically intense care appropriate. Nonetheless, all children with similar chronic conditions (same CCC category) should receive equally high-quality and high-intensity end-of-life care, regardless of sociodemographic status. These economic-, racial-, and age-related disparities raise concerns about whether all children with CCCs are receiving equally high-quality care.

Low-income children with CCCs are receiving higher-intensity end-of-life care than their more affluent counterparts, even when controlling for race and/or ethnicity and insurance. It is unknown whether families from low-income neighborhoods desire more intense end-of-life care or whether this disparity is due to systemic bias. Home-based supportive care service access could play a role because patients in low-income counties have less hospice access.30 It is unlikely that pediatric disease-specific specialty access plays a role because publicly insured Californian children (presumably of lower income) have more access to specialists than privately insured children,31 and, in oncology, higher-intensity end-of-life care is associated with community hospitals.18,24 However, it is unknown how socioeconomic status affects palliative care access or acceptance. As at a single academic center, children who died in a code situation were less likely to have had a palliative care consult than children who died in other situations (eg, after withdrawing or not escalating care)13; differential access to palliative care could produce end-of-life disparities. Toxic stress associated with poverty may affect decision-making, particularly in high-stress situations.32,34 The timing of end-of-life conversations affects end-of-life care,35 allowing provider bias to impact end-of-life care. This disparity could also be due to differential access to efficacious therapy if low-income children have less access to curative therapies, such as organ transplant.31 

Independent of this socioeconomic disparity, non–African American minority children are more likely to receive intense end-of-life care than non-Hispanic white children. Racial and/or ethnic disparities in end-of-life care exist in oncology patients of all ages.18,24,36,40 African American and Hispanic children with CCCs (1989–2003) were more likely to die in the hospital than non-Hispanic white children.9 African Americans were most likely to die in code situations than in other situations (eg, after withdrawing or not escalating care) at a single children’s hospital.13 This racial and/or ethnic variation may be, partly, due to religious or cultural differences.41,42 However, there are differences in how end-of-life wishes are enacted for minority versus non-minority adult oncology patients,43,44 raising concerns that differing patient preferences are not the only contributing factors to ethnic disparities in end-of-life care.

Finally, adolescents are more likely to have intense end-of-life care. Adolescents with cancer receive more intense end-of-life care than their younger counterparts.18 End-of-life decision-making in adolescents is complex, with psychological and legal implications.45 Little is known about end-of-life wishes in adolescents; 1 study revealed that the majority of adolescents with cancer wanted a natural death.46 The vast majority of both adolescents who are chronically ill and adolescents who are healthy want be a part of end-of-life decision-making.47 Adolescents consider end-of-life planning aides helpful and acceptable,48 pediatric advance care planning improves the congruence between end-of-life wishes of adolescents with HIV and/or AIDS and their parents,49 and palliative care involvement in adolescents with cancer is associated with lower-intensity end-of-life care.50 

These findings suggest 3 critical pathways of future research: (1) to determine if these disparities in end-of-life care are due to patient and/or family preferences, system and/or provider biases, or both; (2) to understand how intensity of end-of-life care in children with CCCs affects family bereavement; and (3) to explore interventions used to ensure that patients with CCCs are receiving goal-concordant end-of-life care. Future studies should examine risk factors for high-intensity end-of-life care within each CCC category, determine which patients are not receiving goal-concordant care, and examine how intensity of end-of-life care affects bereaved-family outcomes. Programs aimed at improving end-of-life care may be most successful if they are focused on children with CCCs who are cared for by the same subspecialty. We propose that authors of follow-up studies target the subspecialties with the highest rates of high-intensity end-of-life care (cardiology, hematology and/or immunology, congenital and/or genetics, and nephrology) or the greatest number of patients receiving high-intensity end-of-life care (cardiology, oncology, and neurology). Treatment preference discussions during periods of greater health may be helpful for children with CCCs who have acute or chronic episodes to avoid the stress of decision-making during acute crises.51 Programs to improve end-of-life care for children with CCCs will need to reflect that 20% of Americans have limited English proficiency,52 50% have limited health literacy,53 and families with a child with a CCC are dealing with a complex medical system.7 Therefore, improving end-of-life care for children with CCCs will require a cultural, literacy-sensitive, and systems approach.54,56 

This study also reveals the need for both inpatient and community-based palliative care services for children with CCCs. Thirty-four percent of children with CCCs died at home, with an increase over time. This is an extension of the 1989–2003 trends, revealing higher rates of home death in later years.9 This home-death trend reveals the need for pediatric-appropriate hospice services. Given known socioeconomic disparities in adult hospice access30,57 and the specialized home care needs of children with CCCs,58 this will likely require partnerships between local agencies and pediatric specialty centers, education, and policy change.59 It is still unknown how the concurrent care provision of the Affordable Care Act has affected hospice use in children with CCCs, but its success requires pediatric-appropriate hospice care. For the 66% of children with CCCs dying in the hospital, the most recent survey of pediatric hospitals (2012) revealed that 30% did not have a pediatric palliative care program, and those that did reported variable staffing and services.60 Because pediatric palliative care consultation is associated with a lower likelihood of having a code at the end of life,13 this gap in pediatric palliative care coverage may be contributing to higher-intensity end-of-life care for some. Ensuring that the pediatric palliative care workforce is positioned to meet the needs of the growing population of children with CCCs is essential.

Although this study highlights critical disparities in end-of-life care of children with CCCs, it has limitations. This study is limited to California, which has more safety-net programs than many states (eg, home-base pediatric palliative care waiver for children on Medicaid61), so results may not be generalizable beyond California. However, almost 1 in 8 US children live in California. This is the first known use of the CCC classifications in this data set. However, the CCC rates were reviewed by 3 pediatricians for face validity and were similar to those of Feudtner and co-workers.12 The data set only reports whether an intervention occurred during an admission, not the day it occurred. We designed our study to underestimate intensity rates by only including ICD-9 codes that occurred during admissions entirely within the time frame of interest (missing procedures that occurred in the 13% of patients admitted the entire last 30 days of life) and designed ICU codes to underreport ICU admissions. Additionally, we do not capture procedures performed outside the hospital or in the emergency department. Therefore, the actual rates of medically intense end-of-life care are likely higher. Finally, there are other important aspects of end-of-life care (access to home hospice, symptom control, palliative care consultation, advance directives, timing of end-of-life conversations [and who has the conversation], and bereaved-family outcomes) beyond the scope of this study and data set. Instead, this study is focused on inpatient intensity of end-of-life care.

In this first population-based study to examine variation in intensity of end-of-life care in US children with CCCs, we found disparities associated with income, race and/or ethnicity, and age. These variations raise concerns that low-income children, minority children, and adolescents may not be receiving as high-quality end-of-life care as their counterparts. To meet the national standard for a palliative approach to the care of children with life-threatening conditions, there is an urgent need to learn more about end-of-life care practices and patient and family preferences and to identify systemic opportunities (eg, hospice access) to reduce preventable disparities in pediatric end-of-life care.

Dr Johnston conceptualized and designed the study, interpreted the data, drafted the initial manuscript, and reviewed and revised the manuscript; Dr Bogetz aided in study design, interpreted the data, drafted portions of the manuscript, and reviewed and revised the manuscript; Ms Saynina performed the data analysis and reviewed and revised the manuscript; Drs Chamberlain, Bhatia, and Sanders aided in study design, interpreted the data, and reviewed and revised the manuscript; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

FUNDING: No external funding.

COMPANION PAPER: A companion to this article can be found online at www.pediatrics.org/cgi/doi/10.1542/peds.2019-0511.

The Center for Policy, Outcomes, and Prevention provided data access and data analyst time at no cost.

     
  • CCC

    complex chronic condition

  •  
  • CI

    confidence interval

  •  
  • CPR

    cardiopulmonary resuscitation

  •  
  • FPL

    federal poverty level

  •  
  • ICD-9

    International Classification of Diseases, Ninth Revision

  •  
  • OR

    odds ratio

  •  
  • OSHPD

    Office of Statewide Health Planning and Development

1
Feudtner
C
,
Christakis
DA
,
Connell
FA
.
Pediatric deaths attributable to complex chronic conditions: a population-based study of Washington State, 1980-1997.
Pediatrics
.
2000
;
106
(
1, pt 2
):
205
209
[PubMed]
2
Berry
JG
,
Ash
AS
,
Cohen
E
,
Hasan
F
,
Feudtner
C
,
Hall
M
.
Contributions of children with multiple chronic conditions to pediatric hospitalizations in the United States: a retrospective cohort analysis.
Hosp Pediatr
.
2017
;
7
(
7
):
365
372
[PubMed]
3
Cohen
E
,
Berry
JG
,
Camacho
X
,
Anderson
G
,
Wodchis
W
,
Guttmann
A
.
Patterns and costs of health care use of children with medical complexity.
Pediatrics
.
2012
;
130
(
6
). Available at: www.pediatrics.org/cgi/content/full/130/6/e1463
[PubMed]
4
Neff
JM
,
Sharp
VL
,
Muldoon
J
,
Graham
J
,
Myers
K
.
Profile of medical charges for children by health status group and severity level in a Washington State health plan.
Health Serv Res
.
2004
;
39
(
1
):
73
89
[PubMed]
5
Berry
JG
,
Ziniel
SI
,
Freeman
L
, et al
.
Hospital readmission and parent perceptions of their child’s hospital discharge.
Int J Qual Health Care
.
2013
;
25
(
5
):
573
581
[PubMed]
6
Berry
JG
,
Hall
DE
,
Kuo
DZ
, et al
.
Hospital utilization and characteristics of patients experiencing recurrent readmissions within children’s hospitals.
JAMA
.
2011
;
305
(
7
):
682
690
[PubMed]
7
Kuo
DZ
,
Cohen
E
,
Agrawal
R
,
Berry
JG
,
Casey
PH
.
A national profile of caregiver challenges among more medically complex children with special health care needs.
Arch Pediatr Adolesc Med
.
2011
;
165
(
11
):
1020
1026
[PubMed]
8
Contro
N
,
Larson
J
,
Scofield
S
,
Sourkes
B
,
Cohen
H
.
Family perspectives on the quality of pediatric palliative care.
Arch Pediatr Adolesc Med
.
2002
;
156
(
1
):
14
19
[PubMed]
9
Feudtner
C
,
Feinstein
JA
,
Satchell
M
,
Zhao
H
,
Kang
TI
.
Shifting place of death among children with complex chronic conditions in the United States, 1989-2003.
JAMA
.
2007
;
297
(
24
):
2725
2732
[PubMed]
10
Simon
TD
,
Berry
J
,
Feudtner
C
, et al
.
Children with complex chronic conditions in inpatient hospital settings in the United States.
Pediatrics
.
2010
;
126
(
4
):
647
655
[PubMed]
11
Section on Hospice and Palliative Medicine
;
Committee on Hospital Care
.
Pediatric palliative care and hospice care commitments, guidelines, and recommendations.
Pediatrics
.
2013
;
132
(
5
):
966
972
[PubMed]
12
Ananth
P
,
Melvin
P
,
Feudtner
C
,
Wolfe
J
,
Berry
JG
.
Hospital use in the last year of life for children with life-threatening complex chronic conditions.
Pediatrics
.
2015
;
136
(
5
):
938
946
[PubMed]
13
Trowbridge
A
,
Walter
JK
,
McConathey
E
,
Morrison
W
,
Feudtner
C
.
Modes of death within a children’s hospital.
Pediatrics
.
2018
;
142
(
4
):
e20174182
[PubMed]
14
Zhang
B
,
Wright
AA
,
Huskamp
HA
, et al
.
Health care costs in the last week of life: associations with end-of-life conversations.
Arch Intern Med
.
2009
;
169
(
5
):
480
488
[PubMed]
15
Earle
CC
,
Park
ER
,
Lai
B
,
Weeks
JC
,
Ayanian
JZ
,
Block
S
.
Identifying potential indicators of the quality of end-of-life cancer care from administrative data.
J Clin Oncol
.
2003
;
21
(
6
):
1133
1138
[PubMed]
16
National Quality Forum
. Available at: www.qualityforum.org/Home.aspx. Accessed April 3, 2015
17
Kassam
A
,
Sutradhar
R
,
Widger
K
, et al
.
Predictors of and trends in high-intensity end-of-life care among children with cancer: a population-based study using health services data.
J Clin Oncol
.
2017
;
35
(
2
):
236
242
18
Johnston
EE
,
Alvarez
E
,
Saynina
O
,
Sanders
L
,
Bhatia
S
,
Chamberlain
LJ
.
Disparities in the intensity of end-of-life care for children with cancer.
Pediatrics
.
2017
;
140
(
4
):
e20170671
[PubMed]
19
Widger
K
,
Seow
H
,
Rapoport
A
,
Chalifoux
M
,
Tanuseputro
P
.
Children’s end-of-life health care use and cost.
Pediatrics
.
2017
;
139
(
4
):
e20162956
[PubMed]
20
Benchimol
EI
,
Smeeth
L
,
Guttmann
A
, et al;
RECORD Working Committee
.
The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement.
PLoS Med
.
2015
;
12
(
10
):
e1001885
[PubMed]
21
Feudtner
C
,
Feinstein
JA
,
Zhong
W
,
Hall
M
,
Dai
D
.
Pediatric complex chronic conditions classification system version 2: updated for ICD-10 and complex medical technology dependence and transplantation.
BMC Pediatr
.
2014
;
14
:
199
[PubMed]
22
Earle
CC
,
Neville
BA
,
Landrum
MB
, et al
.
Evaluating claims-based indicators of the intensity of end-of-life cancer care.
Int J Qual Health Care
.
2005
;
17
(
6
):
505
509
[PubMed]
23
Barnato
AE
,
Farrell
MH
,
Chang
CC
,
Lave
JR
,
Roberts
MS
,
Angus
DC
.
Development and validation of hospital “end-of-life” treatment intensity measures.
Med Care
.
2009
;
47
(
10
):
1098
1105
[PubMed]
24
Johnston
EE
,
Alvarez
E
,
Saynina
O
,
Sanders
L
,
Bhatia
S
,
Chamberlain
LJ
.
End-of-life intensity for adolescents and young adults with cancer: a Californian population-based study that shows disparities.
J Oncol Pract
.
2017
;
13
(
9
):
e770
e781
[PubMed]
25
Centers for Disease Control and Prevention
. Ten leading causes of death and injury. 2013. Available at: www.cdc.gov/injury/wisqars/leadingcauses.html. Accessed October 22, 2015
26
Weeks
JC
,
Cook
EF
,
O’Day
SJ
, et al
.
Relationship between cancer patients’ predictions of prognosis and their treatment preferences [published correction appears in JAMA. 2000;283(2):203].
JAMA
.
1998
;
279
(
21
):
1709
1714
[PubMed]
27
McCarthy
EP
,
Phillips
RS
,
Zhong
Z
,
Drews
RE
,
Lynn
J
.
Dying with cancer: patients’ function, symptoms, and care preferences as death approaches.
J Am Geriatr Soc
.
2000
;
48
(
suppl 5
):
S110
S121
[PubMed]
28
Wright
AA
,
Zhang
B
,
Ray
A
, et al
.
Associations between end-of-life discussions, patient mental health, medical care near death, and caregiver bereavement adjustment.
JAMA
.
2008
;
300
(
14
):
1665
1673
[PubMed]
29
Wright
AA
,
Keating
NL
,
Ayanian
JZ
, et al
.
Family perspectives on aggressive cancer care near the end of life.
JAMA
.
2016
;
315
(
3
):
284
292
[PubMed]
30
Carlson
MD
,
Bradley
EH
,
Du
Q
,
Morrison
RS
.
Geographic access to hospice in the United States.
J Palliat Med
.
2010
;
13
(
11
):
1331
1338
[PubMed]
31
Chamberlain
LJ
,
Chan
J
,
Mahlow
P
,
Huffman
LC
,
Chan
K
,
Wise
PH
.
Variation in specialty care hospitalization for children with chronic conditions in California.
Pediatrics
.
2010
;
125
(
6
):
1190
1199
[PubMed]
32
Institute of Medicine
. Health literacy: a prescription to end confusion. Available at: www.nationalacademies.org/hmd/Reports/2004/Health-Literacy-A-Prescription-to-End-Confusion.aspx. Accessed April 4, 2018
33
Agency for Healthcare Research and Quality
. AHRQ health literacy universal precautions toolkit. Available at: https://www.ahrq.gov/professionals/quality-patient-safety/quality-resources/tools/literacy-toolkit/index.html. Accessed April 4, 2018
34
Shonkoff
JP
,
Garner
AS
;
Committee on Psychosocial Aspects of Child and Family Health
;
Committee on Early Childhood, Adoption, and Dependent Care
;
Section on Developmental and Behavioral Pediatrics
.
The lifelong effects of early childhood adversity and toxic stress.
Pediatrics
.
2012
;
129
(
1
). Available at: www.pediatrics.org/cgi/content/full/129/1/e232
[PubMed]
35
Mack
JW
,
Cronin
A
,
Keating
NL
, et al
.
Associations between end-of-life discussion characteristics and care received near death: a prospective cohort study.
J Clin Oncol
.
2012
;
30
(
35
):
4387
4395
[PubMed]
36
Miesfeldt
S
,
Murray
K
,
Lucas
L
,
Chang
CH
,
Goodman
D
,
Morden
NE
.
Association of age, gender, and race with intensity of end-of-life care for Medicare beneficiaries with cancer.
J Palliat Med
.
2012
;
15
(
5
):
548
554
[PubMed]
37
Sharma
G
,
Freeman
J
,
Zhang
D
,
Goodwin
JS
.
Trends in end-of-life ICU use among older adults with advanced lung cancer.
Chest
.
2008
;
133
(
1
):
72
78
[PubMed]
38
Guadagnolo
BA
,
Liao
KP
,
Giordano
SH
,
Elting
LS
,
Shih
YC
.
Variation in intensity and costs of care by payer and race for patients dying of cancer in Texas: an analysis of registry-linked Medicaid, Medicare, and dually eligible claims data.
Med Care
.
2015
;
53
(
7
):
591
598
[PubMed]
39
Earle
CC
,
Neville
BA
,
Landrum
MB
,
Ayanian
JZ
,
Block
SD
,
Weeks
JC
.
Trends in the aggressiveness of cancer care near the end of life.
J Clin Oncol
.
2004
;
22
(
2
):
315
321
[PubMed]
40
Johnston
EE
,
Alvarez
E
,
Saynina
O
,
Sanders
LM
,
Bhatia
S
,
Chamberlain
LJ
.
Inpatient utilization and disparities: the last year of life of adolescent and young adult oncology patients in California.
Cancer
.
2018
;
124
(
8
):
1819
1827
[PubMed]
41
Contro
N
,
Davies
B
,
Larson
J
,
Sourkes
B
.
Away from home: experiences of Mexican American families in pediatric palliative care.
J Soc Work End Life Palliat Care
.
2010
;
6
(
3–4
):
185
204
[PubMed]
42
Doran
G
,
Downing Hansen
N
.
Constructions of Mexican American family grief after the death of a child: an exploratory study.
Cultur Divers Ethnic Minor Psychol
.
2006
;
12
(
2
):
199
211
[PubMed]
43
Loggers
ET
,
Maciejewski
PK
,
Jimenez
R
, et al
.
Predictors of intensive end-of-life and hospice care in Latino and white advanced cancer patients.
J Palliat Med
.
2013
;
16
(
10
):
1249
1254
[PubMed]
44
Mack
JW
,
Paulk
ME
,
Viswanath
K
,
Prigerson
HG
.
Racial disparities in the outcomes of communication on medical care received near death.
Arch Intern Med
.
2010
;
170
(
17
):
1533
1540
[PubMed]
45
Wilson
MJW
.
Legal and psychological considerations in adolescents’ end-of-life choices
.
Northwest Univ Law Rev
.
2015
;
109
:
203
222
46
Jacobs
S
,
Perez
J
,
Cheng
YI
,
Sill
A
,
Wang
J
,
Lyon
ME
.
Adolescent end of life preferences and congruence with their parents’ preferences: results of a survey of adolescents with cancer.
Pediatr Blood Cancer
.
2015
;
62
(
4
):
710
714
[PubMed]
47
Lyon
ME
,
McCabe
MA
,
Patel
KM
,
D’Angelo
LJ
.
What do adolescents want? An exploratory study regarding end-of-life decision-making.
J Adolesc Health
.
2004
;
35
(
6
):
529.e1
529.e6
[PubMed]
48
Wiener
L
,
Ballard
E
,
Brennan
T
,
Battles
H
,
Martinez
P
,
Pao
M
.
How I wish to be remembered: the use of an advance care planning document in adolescent and young adult populations.
J Palliat Med
.
2008
;
11
(
10
):
1309
1313
[PubMed]
49
Lyon
ME
,
D’Angelo
LJ
,
Dallas
RH
, et al
.
A randomized clinical trial of adolescents with HIV/AIDS: pediatric advance care planning.
AIDS Care
.
2017
;
29
(
10
):
1287
1296
[PubMed]
50
Snaman
JM
,
Kaye
EC
,
Lu
JJ
,
Sykes
A
,
Baker
JN
.
Palliative care involvement is associated with less intensive end-of-life care in adolescent and young adult oncology patients.
J Palliat Med
.
2017
;
20
(
5
):
509
516
[PubMed]
51
Edwards
JD
,
Kun
SS
,
Graham
RJ
,
Keens
TG
.
End-of-life discussions and advance care planning for children on long-term assisted ventilation with life-limiting conditions.
J Palliat Care
.
2012
;
28
(
1
):
21
27
[PubMed]
52
US Census Bureau
. Language spoken at home by ability to speak English for the population 5 years and over (Hispanic or Latino). Available at: https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_14_1YR_B16006&prodType=table. Accessed April 27, 2018
53
Kutner
M
,
Greenberg
E
,
Jin
Y
,
Paulsen
C
. The health literacy of America’s adults: results from the 2003 National Assessment of Adult Literacy. Available at: https://nces.ed.gov/pubs2006/2006483.pdf. Accessed April 27, 2018
54
Volandes
AE
,
Ariza
M
,
Abbo
ED
,
Paasche-Orlow
M
.
Overcoming educational barriers for advance care planning in Latinos with video images.
J Palliat Med
.
2008
;
11
(
5
):
700
706
[PubMed]
55
Volandes
AE
,
Paasche-Orlow
M
,
Gillick
MR
, et al
.
Health literacy not race predicts end-of-life care preferences.
J Palliat Med
.
2008
;
11
(
5
):
754
762
[PubMed]
56
Rosenberg
AR
,
Starks
H
,
Unguru
Y
,
Feudtner
C
,
Diekema
D
.
Truth telling in the setting of cultural differences and incurable pediatric illness: a review.
JAMA Pediatr
.
2017
;
171
(
11
):
1113
1119
[PubMed]
57
Virnig
BA
,
Ma
H
,
Hartman
LK
,
Moscovice
I
,
Carlin
B
.
Access to home-based hospice care for rural populations: identification of areas lacking service.
J Palliat Med
.
2006
;
9
(
6
):
1292
1299
[PubMed]
58
Lindley
LC
,
Mixer
SJ
,
Mack
JW
.
Home care for children with multiple complex chronic conditions at the end of life: the choice of hospice versus home health.
Home Health Care Serv Q
.
2016
;
35
(
3–4
):
101
111
[PubMed]
59
Gans
D
,
Hadler
MW
,
Chen
X
, et al
.
Cost analysis and policy implications of a pediatric palliative care program.
J Pain Symptom Manage
.
2016
;
52
(
3
):
329
335
[PubMed]
60
Feudtner
C
,
Womer
J
,
Augustin
R
, et al
.
Pediatric palliative care programs in children’s hospitals: a cross-sectional national survey.
Pediatrics
.
2013
;
132
(
6
):
1063
1070
[PubMed]
61
Assembly Bill 1745, Chapter 330. Medi-Cal: Pediatric palliative care benefit. (Ca 2006)

Competing Interests

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

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