Video Abstract

Video Abstract

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OBJECTIVES:

The medical home is central to providing quality health care for children. Access to the medical home has historically been tracked by using the National Survey of Children With Special Health Care Needs and the National Survey of Children’s Health (NSCH). Between 2012 and 2015, the NSCH was redesigned, combining the 2 surveys into a single, annual assessment. In this study, we provide the latest estimates of medical home access among children in the United States.

METHODS:

We used data from the 2016 NSCH (N = 50 212). Medical home access was defined as a composite measure composed of 5 subcomponents (usual source of care, personal doctor or nurse, referral access, receipt of care coordination, and receipt of family-centered care) for 50 177 US children aged 0 to 17 years. We conducted bivariate analyses and logistic regression to examine the sociodemographic and health characteristics associated with reported attainment of the medical home composite measure and each subcomponent. Analyses were survey weighted.

RESULTS:

In 2016, 43.2% of children with special health care needs (CSHCN) and 50.0% of non-CSHCN were reported to have access to a medical home. Attainment of the medical home composite measure varied significantly by sociodemographic characteristics among both CSHCN and non-CSHCN, as did attainment rates for each of the 5 subcomponents. The medical complexity of CSHCN was also associated with attainment rates of all outcomes.

CONCLUSIONS:

The medical home incorporates elements of care considered necessary for providing comprehensive, quality care. Our results indicate that there is still room to improve access to the medical home among all children.

What’s Known on This Subject:

The medical home is widely considered a key component of care for all children. Medical home access has historically been tracked with 2 surveys. The National Survey of Children’s Health was redesigned, combining the 2 surveys into a single annual assessment.

What This Study Adds:

In this study, we present the latest estimates of medical home access and identify sociodemographic and health factors associated with access among children with and without special health care needs. Disparities in access persist with differences observed by special need status.

The American Academy of Pediatrics defines a medical home as a model of primary health care that is accessible, family-centered, continuous, comprehensive, coordinated, compassionate, and culturally effective.1 For >2 decades, the Health Resources and Services Administration’s Maternal and Child Health Bureau (HRSA MCHB) has promoted this model as a key feature of care for children with special health care needs (CSHCN),2,3 defined as those children “who have or are at increased risk for a chronic physical, developmental, behavioral, or emotional condition and who also require health and related services of a type or amount beyond that required by children generally.”4 The medical home is vital for the care of CSHCN because they use more health care services and have more unmet health needs than other children.5,6 In addition, the model is now considered a standard for ensuring the provision of quality health care for all children, and studies have shown that both children with and without special health care needs (SHCN) benefit from care consistent with this model.7,10 

Since 2001, HRSA MCHB has tracked the proportion of children with access to a medical home through the HRSA MCHB–sponsored National Survey of Children With Special Health Care Needs (NS-CSHCN) and National Survey of Children’s Health (NSCH). Both surveys incorporated the key components of the American Academy of Pediatrics definition of the medical home into survey items used to create a composite medical home measure based on parent- and/or caregiver-reported experiences and perceptions.11 Between 2012 and 2015, HRSA MCHB redesigned the NSCH, combining the NSCH and NS-CSHCN into 1 survey and moving to an annual administration using an address-based sample and a self-administered, Web-based or paper survey instrument.12 The 2016 NSCH contains the first year of data from the redesigned survey.

Because of differences in survey sampling methodology and modes of administration, the 2016 NSCH represents a new set of baseline data for medical home access. In this article, we provide updated estimates of medical home access. Additionally, given the differences in need and use of health care services between CSHCN and non-CSHCN, we provide estimates separately for CSHCN and non-CSHCN as well as an examination of the sociodemographic and health factors associated with medical home access in each group.

We used data from the 2016 NSCH, a cross-sectional, nationally representative sample of noninstitutionalized children aged 0 to 17 years. The NSCH is funded and directed by HRSA MCHB and fielded by the US Census Bureau. It produces both national and state-level estimates of children’s physical and emotional health as well as information on family, community, and health care–related factors that can impact children’s health and well-being.

The new NSCH12 retained the 2-phased data collection strategy with an adult (parent or caregiver) in each household knowledgeable about the child responding to the survey.13 A screener questionnaire was used to determine the number of eligible children residing at an address and if they qualified as CSHCN. For the second stage topical survey, data were collected on 1 randomly selected eligible child from each household. Data collection occurred from June 2016 to February 2017. Sampling weights were produced to account for nonresponse and to ensure that survey estimates could be generalized to the noninstitutionalized population of US children aged 0 to 17 years. The overall weighted response rate for the survey was 40.7%, representing a final sample of 50 212 children. This study included 50 177 children with nonmissing medical home status (ie, <1% of children did not have valid responses to the medical home survey items). This study did not require institutional review board review because the data are publicly available.14 

Outcomes

We examined the HRSA MCHB medical home composite measure, which includes the following 5 subcomponents: (1) having a usual source of care (USOC), (2) having a personal doctor or nurse (PDN), (3) receiving needed referrals (REFs), (4) receiving needed care coordination (CC), and (5) receiving family-centered care (FCC).11 

Two subcomponents, USOC and PDN, applied to all children in the sample. USOC was defined as parental or caregiver report of a child having a usual source of sick care exclusive of the hospital emergency department, and PDN was defined as parental or caregiver report of a child having ≥1 persons who are thought of as the child’s PDN. The remaining 3 subcomponents were pertinent only for children whose parent or caregiver indicated the child needed the specified services. In other words, REF only applied to children reported to need referrals (N = 9141), CC only to children reported to need CC (N = 27 030), and FCC only to children who had a visit with a health care professional in the past 12 months (N = 44 036). The FCC subcomponent was defined by using 5 survey items assessing whether the child’s doctor or other health care providers (1) spent enough time with the child, (2) listened carefully to the child, (3) showed sensitivity to family values, (4) provided the specific information needed concerning the child, and (5) helped the family feel like a partner in the child’s care. Parental and caregiver reports of “always” or “usually” to all 5 items qualified as meeting FCC. CC was defined as parental or caregiver responses of “usually” for getting needed help with CC and, when needed, of being “very satisfied” with the doctor’s communication with other health care providers and with the school, child care provider, or special education. Children achieving all pertinent subcomponents were coded as having a medical home.

Independent Variables

We included 7 sociodemographic variables historically associated with medical home access,15,19 including child age (0–5, 6–11, and 12–17 years), sex (male or female), race and ethnicity (Hispanic, non-Hispanic white, non-Hispanic black, or non-Hispanic other), primary language spoken at home (English or any other language), insurance coverage at the time of the survey (uninsured, public insurance only, or private insurance), household income as a proportion of the federal poverty level (FPL) (<100%, 100%–199%, 200%–399%, and ≥400%), and household education (less than high school, high school, or more than high school). For CSHCN (identified by the 5-item CSHCN screener),20 we also included a count of the number of qualifying SHCN screening items (1–5 inclusive) met. This variable was intended to capture the complexity of health care needs because we theorized that children who met more qualifiers (eg, medications, elevated service use, functional limitations, behavioral therapies, and special therapies) would require more services and/or types of services.

All analyses were stratified by CSHCN status. We first conducted bivariate analyses to examine the sociodemographic and health characteristics associated with outcomes using χ2 tests with design-based F statistics. We then used logistic regression to assess the adjusted associations of sociodemographic and health characteristics with the outcomes. In regression analyses among CSHCN, we also controlled for the number of SHCN qualifiers.

We also conducted sensitivity analyses. For non-CSHCN, we ran the adjusted models with an additional variable, reported general health status (excellent or very good, good, or fair or poor), to examine the inclusion of a variable analogous to the number of SHCN qualifiers among CSHCN. Also, because we analyzed models for REF and CC only for children who were reported to need those services, we examined the sociodemographic factors associated with the probability of reporting the need for services.

All analyses were conducted by using complete case analysis and were weighted to be representative of noninstitutionalized children aged 0 to 17 years. Regression results are presented as average marginal effects (AMEs), which provide the absolute difference in the probability of a binary outcome occurring.21,22 FPL was multiply imputed for 18.56% of the sample because of item nonresponse.23 We used public data files created by the US Census Bureau.14 All analyses were conducted by using Stata version 15 (Stata Corp, College Station, TX). Results are reported as significant if they have P values <.05.

Overall, 43.2% of CSHCN and 50.0% of non-CSHCN were reported by their parent or caregiver to have access to a medical home in 2016 (Table 1). Attainment rates for each of the 5 medical home subcomponents were higher than for the medical home composite measure overall, ranging from 62.3% for the receipt of CC among CSHCN to 87.3% for the receipt of FCC among non-CSHCN. Attainment rates for USOC and PDN were higher among CSHCN than non-CSHCN (82.1% vs 79.1% and 79.3% vs 70.9%, respectively), whereas attainment rates were higher among non-CSHCN for the remainder of outcomes. The subcomponent with the highest attainment rate for both CSHCN and non-CSHCN was the receipt of FCC (82.6% and 87.3%).

TABLE 1

Prevalence of Access to a Medical Home and Its 5 Subcomponents According to Selected Sociodemographic Characteristics of CSHCN and Non-CSHCN in 2016

CovariatesUnweighted NHad Medical Home Overall, % (SE)Had USOC, % (SE)Had PDN, % (SE)Received Needed Referrals, % (SE)Received Effective CC, % (SE)Received FCC % (SE)
CSHCNNon-CSHCNCSHCN (N = 11 387)Non-CSHCN (N = 38 790)CSHCN (N = 11 244)Non-CSHCN (N = 38 335)CSHCN (N = 11 329)Non-CSHCN (N = 38 603)CSHCN (N = 3959)Non-CSHCN (N = 5182)CSHCN (N = 8916)Non-CSHCN (N = 18 114)CSHCN (N = 10 727)Non-CSHCN (N = 33 309)
Total population 11 392 38 820 43.16 (1.00) 50.02 (0.57) 82.14 (0.96) 79.08 (0.53) 79.28 (0.96) 70.93 (0.56) 74.38 (1.74) 80.54 (1.46) 62.31 (1.12) 76.22 (0.72) 82.57 (0.98) 87.32 (0.46) 
Sex               
 Male 6432 19 301 42.59 (1.32) 50.20 (0.81) 81.90 (1.28) 79.27 (0.72) 79.39 (1.22) 70.74 (0.80) 71.81 (2.55) 81.48 (1.94) 62.30 (1.43) 76.29 (1.08) 82.37 (1.29) 87.71 (0.59) 
 Female 4960 19 519 43.95 (1.53) 49.84 (0.81) 82.48 (1.43) 78.89 (0.77) 79.13 (1.52) 71.12 (0.80) 77.95 (2.06) 79.51 (2.20) 62.32 (1.80) 76.14 (0.94) 82.85 (1.50) 86.95 (0.70) 
Age, y               
 0–5 1682 12 812 43.64 (2.66) 53.03*** (0.97) 82.41 (2.45) 81.11*** (0.91) 82.62 (2.11) 73.04* (0.92) 72.86 (4.61) 82.73 (2.13) 63.75 (2.58) 77.48 (1.22) 81.34 (2.55) 88.84* (0.63) 
 6–11 3848 11 162 41.87 (1.67) 48.81*** (1.07) 81.53 (1.55) 80.83*** (0.94) 76.99 (1.65) 69.93* (1.10) 76.26 (2.61) 81.23 (2.80) 59.38 (2.02) 73.73 (1.38) 83.53 (1.51) 85.76* (0.98) 
 12–17 5862 14 846 44.14 (1.37) 47.86*** (0.93) 82.60 (1.39) 75.00*** (0.90) 79.97 (1.38) 69.58* (0.90) 73.49 (2.37) 77.48 (2.71) 64.32 (1.49) 77.32 (1.14) 82.20 (1.47) 87.03* (0.78) 
Race and ethnicity               
 Hispanic 1203 4320 36.34*** (2.91) 36.09*** (1.48) 75.31*** (2.88) 71.00*** (1.58) 71.38*** (3.05) 61.01*** (1.65) 71.71 (4.53) 70.83*** (4.19) 63.63 (3.06) 70.95*** (2.19) 76.10*** (2.65) 79.28*** (1.57) 
 Non-Hispanic white 8110 27 207 47.95*** (1.06) 59.75*** (0.57) 86.78*** (0.78) 85.46*** (0.44) 84.00*** (0.76) 76.86*** (0.50) 78.33 (1.73) 86.85*** (1.09) 61.32 (1.24) 79.34*** (0.68) 86.56*** (0.96) 91.90*** (0.36) 
 Non-Hispanic black 808 2063 38.93*** (2.75) 40.24*** (1.79) 76.08*** (3.14) 73.05*** (1.62) 73.43*** (2.84) 66.08*** (1.79) 65.10 (5.84) 80.39*** (3.97) 67.81 (3.24) 74.72*** (2.44) 76.35*** (3.57) 82.03*** (1.48) 
 Non-Hispanic other 1271 5230 39.58*** (2.62) 46.65*** (1.43) 82.65*** (2.07) 73.96*** (1.39) 81.61*** (1.92) 70.75*** (1.33) 74.41 (4.17) 72.19*** (5.34) 55.86 (2.65) 73.65*** (1.68) 84.42*** (1.90) 86.48*** (0.92) 
Primary language spoken at home               
 English 10 933 35 754 44.93** (0.97) 53.73*** (0.57) 83.58** (0.89) 81.49*** (0.48) 81.36*** (0.83) 73.40*** (0.53) 74.81 (1.72) 84.47*** (1.21) 62.30 (1.12) 78.06*** (0.67) 84.22*** (0.93) 89.10*** (0.42) 
 Any other language 385 2763 27.85** (4.93) 30.80*** (1.82) 71.14** (4.96) 66.16*** (2.12) 59.08*** (5.58) 58.52*** (2.11) 70.47 (7.56) 60.51*** (5.68) 61.68 (5.57) 63.67*** (3.16) 61.93*** (5.61) 74.83*** (2.17) 
Insurance coverage at time of survey               
 Uninsured 326 1454 30.71*** (5.19) 23.80*** (2.10) 64.93*** (4.85) 58.26*** (2.93) 57.75*** (5.28) 44.48*** (2.89) 66.29* (11.27) 57.81*** (12.19) 72.40* (5.54) 64.88*** (4.58) 65.06*** (6.44) 74.65*** (3.47) 
 Any public 3576 7407 35.93*** (1.64) 39.96*** (1.18) 77.56*** (1.68) 73.37*** (1.13) 75.81*** (1.68) 65.42*** (1.20) 70.15* (2.88) 74.25*** (2.67) 59.40* (1.98) 72.03*** (1.59) 77.20*** (1.72) 81.80*** (1.06) 
 Private 7343 29 360 52.11*** (1.09) 59.19*** (0.60) 89.29*** (0.71) 85.53*** (0.48) 85.36*** (0.75) 77.50*** (0.52) 80.74* (1.46) 86.78*** (1.36) 63.82* (1.19) 79.24*** (0.74) 89.49*** (0.69) 91.06*** (0.42) 
Household income as a proportion of the FPL, %               
 <100 1377 3552 32.30*** (2.30) 36.78*** (1.64) 70.96*** (2.56) 67.56*** (1.70) 68.56*** (2.70) 60.93*** (1.84) 71.14* (3.82) 71.21*** (4.67) 61.56 (3.11) 72.43*** (2.30) 73.36*** (2.71) 81.29*** (1.57) 
 100–200 1932 6071 39.30*** (2.42) 40.11*** (1.47) 81.55*** (2.18) 74.22*** (1.38) 78.01*** (2.32) 64.44*** (1.69) 69.05* (4.50) 74.49*** (3.90) 59.76 (2.88) 71.31*** (2.28) 78.60*** (2.73) 81.97*** (1.45) 
 200–400 3402 12 124 46.38*** (2.07) 53.10*** (1.04) 84.50*** (1.95) 81.53*** (0.98) 82.45*** (1.56) 72.76*** (0.93) 75.71* (3.15) 83.64*** (2.24) 63.08 (2.18) 76.76*** (1.25) 85.38*** (1.80) 88.23*** (0.82) 
 ≥400 4681 17 073 53.74*** (1.46) 63.52*** (0.80) 90.81*** (1.27) 88.18*** (0.56) 87.48*** (0.97) 80.82*** (0.67) 82.16* (2.47) 88.78*** (1.18) 64.17 (1.53) 80.67*** (1.02) 91.03*** (1.03) 93.18*** (0.48) 
Household education               
 Less than high school 251 845 34.58*** (5.25) 28.05*** (2.67) 65.63*** (5.15) 57.76*** (3.19) 63.32*** (5.31) 50.81*** (3.15) 63.03 (8.61) 62.18** (8.56) 72.82* (5.17) 76.54 (4.53) 74.24** (5.14) 73.98*** (3.71) 
 High school 1440 4580 34.59*** (2.29) 37.16*** (1.45) 69.47*** (2.79) 70.12*** (1.43) 71.95*** (2.86) 62.06*** (1.54) 75.94 (3.88) 78.00** (3.92) 65.56* (2.94) 72.98 (2.20) 77.83** (2.74) 83.27*** (1.24) 
 More than high school 9441 32 458 47.54*** (1.05) 57.06*** (0.58) 88.55*** (0.81) 84.88*** (0.44) 84.20*** (0.73) 76.53*** (0.51) 76.43 (1.87) 83.80** (1.31) 60.82* (1.22) 76.86 (0.72) 85.32** (1.00) 89.57*** (0.43) 
No. of qualifiers for CSHCN               
 1 5074 — 48.91*** (1.53) — 79.40 (1.59) — 77.46* (1.45) — 82.71*** (2.28) — 72.93*** (1.73) — 85.91*** (1.51) — 
 2 2465 — 46.12*** (2.31) — 83.31 (1.97) — 77.43* (2.25) — 79.58*** (3.47) — 63.98*** (2.41) — 85.62*** (1.78) — 
 3 1957 — 38.30*** (2.02) — 85.47 (1.81) — 82.90* (1.93) — 70.66*** (3.50) — 56.65*** (2.40) — 82.22*** (2.13) — 
 4 1112 — 32.73*** (3.44) — 83.14 (3.11) — 78.99* (3.34) — 65.83*** (5.94) — 49.98*** (3.43) — 69.55*** (3.54) — 
 5 799 — 27.56*** (3.24) — 85.51 (2.50) — 87.82* (2.29) — 58.76*** (5.63) — 39.21*** (3.68) — 74.39*** (3.84) — 
CovariatesUnweighted NHad Medical Home Overall, % (SE)Had USOC, % (SE)Had PDN, % (SE)Received Needed Referrals, % (SE)Received Effective CC, % (SE)Received FCC % (SE)
CSHCNNon-CSHCNCSHCN (N = 11 387)Non-CSHCN (N = 38 790)CSHCN (N = 11 244)Non-CSHCN (N = 38 335)CSHCN (N = 11 329)Non-CSHCN (N = 38 603)CSHCN (N = 3959)Non-CSHCN (N = 5182)CSHCN (N = 8916)Non-CSHCN (N = 18 114)CSHCN (N = 10 727)Non-CSHCN (N = 33 309)
Total population 11 392 38 820 43.16 (1.00) 50.02 (0.57) 82.14 (0.96) 79.08 (0.53) 79.28 (0.96) 70.93 (0.56) 74.38 (1.74) 80.54 (1.46) 62.31 (1.12) 76.22 (0.72) 82.57 (0.98) 87.32 (0.46) 
Sex               
 Male 6432 19 301 42.59 (1.32) 50.20 (0.81) 81.90 (1.28) 79.27 (0.72) 79.39 (1.22) 70.74 (0.80) 71.81 (2.55) 81.48 (1.94) 62.30 (1.43) 76.29 (1.08) 82.37 (1.29) 87.71 (0.59) 
 Female 4960 19 519 43.95 (1.53) 49.84 (0.81) 82.48 (1.43) 78.89 (0.77) 79.13 (1.52) 71.12 (0.80) 77.95 (2.06) 79.51 (2.20) 62.32 (1.80) 76.14 (0.94) 82.85 (1.50) 86.95 (0.70) 
Age, y               
 0–5 1682 12 812 43.64 (2.66) 53.03*** (0.97) 82.41 (2.45) 81.11*** (0.91) 82.62 (2.11) 73.04* (0.92) 72.86 (4.61) 82.73 (2.13) 63.75 (2.58) 77.48 (1.22) 81.34 (2.55) 88.84* (0.63) 
 6–11 3848 11 162 41.87 (1.67) 48.81*** (1.07) 81.53 (1.55) 80.83*** (0.94) 76.99 (1.65) 69.93* (1.10) 76.26 (2.61) 81.23 (2.80) 59.38 (2.02) 73.73 (1.38) 83.53 (1.51) 85.76* (0.98) 
 12–17 5862 14 846 44.14 (1.37) 47.86*** (0.93) 82.60 (1.39) 75.00*** (0.90) 79.97 (1.38) 69.58* (0.90) 73.49 (2.37) 77.48 (2.71) 64.32 (1.49) 77.32 (1.14) 82.20 (1.47) 87.03* (0.78) 
Race and ethnicity               
 Hispanic 1203 4320 36.34*** (2.91) 36.09*** (1.48) 75.31*** (2.88) 71.00*** (1.58) 71.38*** (3.05) 61.01*** (1.65) 71.71 (4.53) 70.83*** (4.19) 63.63 (3.06) 70.95*** (2.19) 76.10*** (2.65) 79.28*** (1.57) 
 Non-Hispanic white 8110 27 207 47.95*** (1.06) 59.75*** (0.57) 86.78*** (0.78) 85.46*** (0.44) 84.00*** (0.76) 76.86*** (0.50) 78.33 (1.73) 86.85*** (1.09) 61.32 (1.24) 79.34*** (0.68) 86.56*** (0.96) 91.90*** (0.36) 
 Non-Hispanic black 808 2063 38.93*** (2.75) 40.24*** (1.79) 76.08*** (3.14) 73.05*** (1.62) 73.43*** (2.84) 66.08*** (1.79) 65.10 (5.84) 80.39*** (3.97) 67.81 (3.24) 74.72*** (2.44) 76.35*** (3.57) 82.03*** (1.48) 
 Non-Hispanic other 1271 5230 39.58*** (2.62) 46.65*** (1.43) 82.65*** (2.07) 73.96*** (1.39) 81.61*** (1.92) 70.75*** (1.33) 74.41 (4.17) 72.19*** (5.34) 55.86 (2.65) 73.65*** (1.68) 84.42*** (1.90) 86.48*** (0.92) 
Primary language spoken at home               
 English 10 933 35 754 44.93** (0.97) 53.73*** (0.57) 83.58** (0.89) 81.49*** (0.48) 81.36*** (0.83) 73.40*** (0.53) 74.81 (1.72) 84.47*** (1.21) 62.30 (1.12) 78.06*** (0.67) 84.22*** (0.93) 89.10*** (0.42) 
 Any other language 385 2763 27.85** (4.93) 30.80*** (1.82) 71.14** (4.96) 66.16*** (2.12) 59.08*** (5.58) 58.52*** (2.11) 70.47 (7.56) 60.51*** (5.68) 61.68 (5.57) 63.67*** (3.16) 61.93*** (5.61) 74.83*** (2.17) 
Insurance coverage at time of survey               
 Uninsured 326 1454 30.71*** (5.19) 23.80*** (2.10) 64.93*** (4.85) 58.26*** (2.93) 57.75*** (5.28) 44.48*** (2.89) 66.29* (11.27) 57.81*** (12.19) 72.40* (5.54) 64.88*** (4.58) 65.06*** (6.44) 74.65*** (3.47) 
 Any public 3576 7407 35.93*** (1.64) 39.96*** (1.18) 77.56*** (1.68) 73.37*** (1.13) 75.81*** (1.68) 65.42*** (1.20) 70.15* (2.88) 74.25*** (2.67) 59.40* (1.98) 72.03*** (1.59) 77.20*** (1.72) 81.80*** (1.06) 
 Private 7343 29 360 52.11*** (1.09) 59.19*** (0.60) 89.29*** (0.71) 85.53*** (0.48) 85.36*** (0.75) 77.50*** (0.52) 80.74* (1.46) 86.78*** (1.36) 63.82* (1.19) 79.24*** (0.74) 89.49*** (0.69) 91.06*** (0.42) 
Household income as a proportion of the FPL, %               
 <100 1377 3552 32.30*** (2.30) 36.78*** (1.64) 70.96*** (2.56) 67.56*** (1.70) 68.56*** (2.70) 60.93*** (1.84) 71.14* (3.82) 71.21*** (4.67) 61.56 (3.11) 72.43*** (2.30) 73.36*** (2.71) 81.29*** (1.57) 
 100–200 1932 6071 39.30*** (2.42) 40.11*** (1.47) 81.55*** (2.18) 74.22*** (1.38) 78.01*** (2.32) 64.44*** (1.69) 69.05* (4.50) 74.49*** (3.90) 59.76 (2.88) 71.31*** (2.28) 78.60*** (2.73) 81.97*** (1.45) 
 200–400 3402 12 124 46.38*** (2.07) 53.10*** (1.04) 84.50*** (1.95) 81.53*** (0.98) 82.45*** (1.56) 72.76*** (0.93) 75.71* (3.15) 83.64*** (2.24) 63.08 (2.18) 76.76*** (1.25) 85.38*** (1.80) 88.23*** (0.82) 
 ≥400 4681 17 073 53.74*** (1.46) 63.52*** (0.80) 90.81*** (1.27) 88.18*** (0.56) 87.48*** (0.97) 80.82*** (0.67) 82.16* (2.47) 88.78*** (1.18) 64.17 (1.53) 80.67*** (1.02) 91.03*** (1.03) 93.18*** (0.48) 
Household education               
 Less than high school 251 845 34.58*** (5.25) 28.05*** (2.67) 65.63*** (5.15) 57.76*** (3.19) 63.32*** (5.31) 50.81*** (3.15) 63.03 (8.61) 62.18** (8.56) 72.82* (5.17) 76.54 (4.53) 74.24** (5.14) 73.98*** (3.71) 
 High school 1440 4580 34.59*** (2.29) 37.16*** (1.45) 69.47*** (2.79) 70.12*** (1.43) 71.95*** (2.86) 62.06*** (1.54) 75.94 (3.88) 78.00** (3.92) 65.56* (2.94) 72.98 (2.20) 77.83** (2.74) 83.27*** (1.24) 
 More than high school 9441 32 458 47.54*** (1.05) 57.06*** (0.58) 88.55*** (0.81) 84.88*** (0.44) 84.20*** (0.73) 76.53*** (0.51) 76.43 (1.87) 83.80** (1.31) 60.82* (1.22) 76.86 (0.72) 85.32** (1.00) 89.57*** (0.43) 
No. of qualifiers for CSHCN               
 1 5074 — 48.91*** (1.53) — 79.40 (1.59) — 77.46* (1.45) — 82.71*** (2.28) — 72.93*** (1.73) — 85.91*** (1.51) — 
 2 2465 — 46.12*** (2.31) — 83.31 (1.97) — 77.43* (2.25) — 79.58*** (3.47) — 63.98*** (2.41) — 85.62*** (1.78) — 
 3 1957 — 38.30*** (2.02) — 85.47 (1.81) — 82.90* (1.93) — 70.66*** (3.50) — 56.65*** (2.40) — 82.22*** (2.13) — 
 4 1112 — 32.73*** (3.44) — 83.14 (3.11) — 78.99* (3.34) — 65.83*** (5.94) — 49.98*** (3.43) — 69.55*** (3.54) — 
 5 799 — 27.56*** (3.24) — 85.51 (2.50) — 87.82* (2.29) — 58.76*** (5.63) — 39.21*** (3.68) — 74.39*** (3.84) — 

SEs are reported in parentheses. SEs and P values were generated by using χ2 tests with design-based F statistics. —, not applicable.

*

P < .05;

**

P < .01;

***

P < .001.

Medical Home

Among both CSHCN and non-CSHCN, rates of reported medical home attainment varied significantly by race and ethnicity, the primary language spoken at home, insurance coverage, household income, and household education (Table 1). For both groups, the rate of reported attainment was lowest among Hispanic children (36.3% and 36.1%), followed by non-Hispanic black children (38.9% and 40.2%), and it was highest among non-Hispanic white children (48.0% and 59.8%). Children living in households in which English was not the primary language and those that were uninsured at the time of the survey were less likely to have medical home access; rates of reported medical home attainment also increased with household income for both groups. Children residing in households in which at least 1 primary caregiver or parent had more than a high school education reported a higher prevalence of medical home access (47.5%) than those in homes with high school or less than high school education (34.6% for both). In addition, rates of reported medical home attainment among CSHCN decreased with increasing numbers of SHCN qualifiers (48.9% among children qualifying on 1 criterion versus 27.6% among those meeting 5 qualifying criteria). Among non-CSHCN, the rate of reported attainment decreased with increases in age group (53.0% among children aged 0–5 years versus 47.9% among adolescents aged 12–17).

Subcomponents

For reported USOC, PDN, and FCC, patterns generally mirrored those for the medical home composite with the following 2 exceptions: results for reported USOC among CSHCN did not vary significantly by the number of CSHCN qualifiers, and rates of reported PDN increased with increasing numbers of CSHCN qualifiers (77.5% among children qualifying on 1 criterion versus 87.8% among those meeting 5 qualifying criteria).

Among CSHCN, reported REF varied only by insurance coverage, household income, and the number of SHCN qualifiers. As with medical home access, rates of reported attainment were lowest among uninsured children and highest among children in households with incomes ≥400% of the FPL, and they decreased with increasing numbers of CSHCN qualifiers. Results among non-CSHCN were similar to the medical home composite results except that child age was not significant.

Reported receipt of CC among CSHCN varied by insurance coverage, household education, and the number of CSHCN qualifiers. Rates of reported attainment were highest among children uninsured at the time of the survey (72.4% vs 59.4% among any public insurance and 63.8% among private) and among those in households reporting less than high school education (72.8% vs 65.6% with high school and 60.8% with more than high school). As with the medical home composite results, rates of reported attainment of CC decreased with increasing numbers of SHCN qualifiers. Among non-CSHCN, reported attainment of CC varied only by race and ethnicity, primary language, insurance coverage, and household income; patterns were similar to those seen for the medical home composite.

Medical Home

As shown in Table 2, among CSHCN, meeting ≥3 qualifying criteria for SHCN, living in a household in which English was not the primary language (AME = −0.13, P = .019), living in a household with an income <100% of the FPL (AME = −0.11, P = .005), and being privately insured (AME = 0.13, P = .026) remained significantly associated with rates of reported medical home attainment after adjustment. In particular, compared with children with 1 qualifier for SHCN, those with 5 qualifiers were 21.0 percentage points (P < .001) less likely to have a reported medical home. Among non-CSHCN, all sociodemographic characteristics that were significant in the unadjusted analyses remained significant after adjustment. In sensitivity analyses, controlling for general health status among non-CSHCN did not significantly alter the results for any of the outcomes (results not shown).

TABLE 2

AMEs of Selected Sociodemographic Characteristics on Medical Home Among CSHCN and Non-CSHCN

CovariatesMarginal Effect (SE)
Had Medical Home (CSHCN)Had Medical Home (Non-CSHCN)
Sex (reference = female)   
 Male 0.007 (0.019) −0.001 (0.011) 
Age, y (reference = 0–5 y)   
 6–11 −0.001 (0.032) −0.032* (0.014) 
 12–17 −0.005 (0.030) −0.041** (0.013) 
Race and ethnicity (reference = non-Hispanic white)   
 Hispanic −0.027 (0.031) −0.113*** (0.018) 
 Non-Hispanic black 0.005 (0.030) −0.116*** (0.020) 
 Non-Hispanic other −0.064* (0.028) −0.097*** (0.016) 
Primary language spoken at home (reference = English)   
 Any other language −0.126* (0.053) −0.070** (0.023) 
Insurance coverage at the time of survey (reference = uninsured)   
 Any public 0.068 (0.059) 0.174*** (0.027) 
 Private 0.130* (0.058) 0.228*** (0.027) 
Household income as a proportion of the FPL (reference = ≥400%), %   
 <100 −0.112** (0.039) −0.090*** (0.023) 
 100–200 −0.047 (0.031) −0.107*** (0.019) 
 200–400 −0.050* (0.023) −0.063*** (0.013) 
Household education (reference = less than high school)   
 High school −0.037 (0.062) −0.008 (0.037) 
 More than high school 0.001 (0.061) 0.091* (0.036) 
No. of qualifiers for CSHCN (reference = 1)   
 2 −0.011 (0.027) — 
 3 −0.102*** (0.024) — 
 4 −0.150*** (0.039) — 
 5 −0.206*** (0.038) — 
CovariatesMarginal Effect (SE)
Had Medical Home (CSHCN)Had Medical Home (Non-CSHCN)
Sex (reference = female)   
 Male 0.007 (0.019) −0.001 (0.011) 
Age, y (reference = 0–5 y)   
 6–11 −0.001 (0.032) −0.032* (0.014) 
 12–17 −0.005 (0.030) −0.041** (0.013) 
Race and ethnicity (reference = non-Hispanic white)   
 Hispanic −0.027 (0.031) −0.113*** (0.018) 
 Non-Hispanic black 0.005 (0.030) −0.116*** (0.020) 
 Non-Hispanic other −0.064* (0.028) −0.097*** (0.016) 
Primary language spoken at home (reference = English)   
 Any other language −0.126* (0.053) −0.070** (0.023) 
Insurance coverage at the time of survey (reference = uninsured)   
 Any public 0.068 (0.059) 0.174*** (0.027) 
 Private 0.130* (0.058) 0.228*** (0.027) 
Household income as a proportion of the FPL (reference = ≥400%), %   
 <100 −0.112** (0.039) −0.090*** (0.023) 
 100–200 −0.047 (0.031) −0.107*** (0.019) 
 200–400 −0.050* (0.023) −0.063*** (0.013) 
Household education (reference = less than high school)   
 High school −0.037 (0.062) −0.008 (0.037) 
 More than high school 0.001 (0.061) 0.091* (0.036) 
No. of qualifiers for CSHCN (reference = 1)   
 2 −0.011 (0.027) — 
 3 −0.102*** (0.024) — 
 4 −0.150*** (0.039) — 
 5 −0.206*** (0.038) — 

SEs are reported in parentheses. —, not applicable.

*

P < .05;

**

P < .01;

***

P < .001.

Subcomponents

Among CSHCN, the number of SHCN qualifiers remained significantly associated with all 5 medical home subcomponents (see Table 3). Compared with children qualifying on 1 criterion, those qualifying on 5 criteria were more likely to have a reported USOC (AME = 0.065, P = .022) and PDN (AME = 0.10, P < .001) and were less likely to have reported REF (AME = −0.23, P < .001), CC (AME = −0.33, P < .001), and FCC (AME = −0.11, P = .006). Except for non-Hispanic black CSHCN (who were 7.3 percentage points more likely to have reported CC), race and ethnicity were not significant. Speaking any language other than English at home remained negatively associated with reported PDN rates and the receipt of FCC. Insurance coverage remained positively associated with reported USOC, PDN, and receipt of FCC rates; both children with private and public insurance were 11 to 12 percentage points less likely to have reported CC (P = .023 and .038, respectively). For both reported PDN and receipt of FCC rates, household income <100% of the FPL remained negatively associated with attainment. More than high school education remained positively associated with reported USOC rates and negatively associated with reported CC (AME = −0.12, P = .020). Sensitivity analyses revealed that parents or caregivers reporting more than high school education were 15.0 percentage points (P = .012) more likely to report a child needed CC.

TABLE 3

AMEs of Selected Sociodemographic Characteristics on 5 Medical Home Subcomponents Among CSHCN

CovariatesMarginal Effect (SE)
Had a USOCHad a PDNReceived Needed ReferralsReceived Effective CCReceived FCC
Sex (reference = female)      
 Male 0.001 (0.017) 0.000 (0.017) −0.028 (0.029) 0.024 (0.022) 0.010 (0.018) 
Age, y (reference = 0–5 y)      
 6–11 −0.003 (0.027) −0.057* (0.025) 0.043 (0.046) −0.046 (0.032) 0.025 (0.025) 
 12–17 −0.004 (0.027) −0.044 (0.023) 0.001 (0.043) −0.001 (0.029) −0.004 (0.025) 
Race and ethnicity (reference = non-Hispanic white)      
 Hispanic −0.043 (0.026) −0.028 (0.026) −0.028 (0.026) 0.031 (0.034) −0.020 (0.027) 
 Non-Hispanic black −0.014 (0.028) −0.019 (0.024) −0.019 (0.024) 0.073* (0.035) −0.034 (0.029) 
 Non-Hispanic other −0.024 (0.022) −0.002 (0.021) −0.002 (0.021) −0.052 (0.036) −0.005 (0.022) 
Primary language spoken at home (reference = English)      
 Any other language −0.023 (0.042) −0.129* (0.052) 0.005 (0.072) −0.029 (0.060) −0.155** (0.058) 
Insurance coverage at the time of survey (reference = uninsured)      
 Any public 0.100* (0.047) 0.121* (0.053) 0.06 (0.11) −0.120* (0.053) 0.097 (0.056) 
 Private 0.147** (0.047) 0.138** (0.052) 0.11 (0.11) −0.110* (0.053) 0.148** (0.056) 
Household income as a proportion of the FPL (reference = ≥400%), %      
 <100 −0.064 (0.036) −0.090** (0.031) −0.052 (0.052) −0.069 (0.045) −0.090** (0.032) 
 100–200 −0.017 (0.032) −0.026 (0.028) −0.074 (0.049) −0.044 (0.034) −0.055 (0.029) 
 200–400 −0.042 (0.030) −0.033 (0.018) −0.060 (0.037) −0.018 (0.025) −0.047* (0.022) 
Household education (reference = less than high school)      
 High school 0.001 (0.048) 0.023 (0.049) 0.102 (0.083) −0.054 (0.055) −0.005 (0.039) 
 More than high school 0.116* (0.046) 0.090 (0.047) 0.059 (0.082) −0.122* (0.052) −0.006 (0.038) 
No. of qualifiers for CSHCN (reference = 1)      
 2 0.046* (0.022) 0.019 (0.023) −0.010 (0.037) −0.089** (0.028) −0.009 (0.021) 
 3 0.059* (0.023) 0.049* (0.022) −0.110** (0.040) −0.153*** (0.031) −0.037 (0.024) 
 4 0.054 (0.035) 0.025 (0.031) −0.143* (0.058) −0.234*** (0.037) −0.153*** (0.035) 
 5 0.065* (0.028) 0.103*** (0.026) −0.227*** (0.060) −0.328*** (0.040) −0.110** (0.040) 
CovariatesMarginal Effect (SE)
Had a USOCHad a PDNReceived Needed ReferralsReceived Effective CCReceived FCC
Sex (reference = female)      
 Male 0.001 (0.017) 0.000 (0.017) −0.028 (0.029) 0.024 (0.022) 0.010 (0.018) 
Age, y (reference = 0–5 y)      
 6–11 −0.003 (0.027) −0.057* (0.025) 0.043 (0.046) −0.046 (0.032) 0.025 (0.025) 
 12–17 −0.004 (0.027) −0.044 (0.023) 0.001 (0.043) −0.001 (0.029) −0.004 (0.025) 
Race and ethnicity (reference = non-Hispanic white)      
 Hispanic −0.043 (0.026) −0.028 (0.026) −0.028 (0.026) 0.031 (0.034) −0.020 (0.027) 
 Non-Hispanic black −0.014 (0.028) −0.019 (0.024) −0.019 (0.024) 0.073* (0.035) −0.034 (0.029) 
 Non-Hispanic other −0.024 (0.022) −0.002 (0.021) −0.002 (0.021) −0.052 (0.036) −0.005 (0.022) 
Primary language spoken at home (reference = English)      
 Any other language −0.023 (0.042) −0.129* (0.052) 0.005 (0.072) −0.029 (0.060) −0.155** (0.058) 
Insurance coverage at the time of survey (reference = uninsured)      
 Any public 0.100* (0.047) 0.121* (0.053) 0.06 (0.11) −0.120* (0.053) 0.097 (0.056) 
 Private 0.147** (0.047) 0.138** (0.052) 0.11 (0.11) −0.110* (0.053) 0.148** (0.056) 
Household income as a proportion of the FPL (reference = ≥400%), %      
 <100 −0.064 (0.036) −0.090** (0.031) −0.052 (0.052) −0.069 (0.045) −0.090** (0.032) 
 100–200 −0.017 (0.032) −0.026 (0.028) −0.074 (0.049) −0.044 (0.034) −0.055 (0.029) 
 200–400 −0.042 (0.030) −0.033 (0.018) −0.060 (0.037) −0.018 (0.025) −0.047* (0.022) 
Household education (reference = less than high school)      
 High school 0.001 (0.048) 0.023 (0.049) 0.102 (0.083) −0.054 (0.055) −0.005 (0.039) 
 More than high school 0.116* (0.046) 0.090 (0.047) 0.059 (0.082) −0.122* (0.052) −0.006 (0.038) 
No. of qualifiers for CSHCN (reference = 1)      
 2 0.046* (0.022) 0.019 (0.023) −0.010 (0.037) −0.089** (0.028) −0.009 (0.021) 
 3 0.059* (0.023) 0.049* (0.022) −0.110** (0.040) −0.153*** (0.031) −0.037 (0.024) 
 4 0.054 (0.035) 0.025 (0.031) −0.143* (0.058) −0.234*** (0.037) −0.153*** (0.035) 
 5 0.065* (0.028) 0.103*** (0.026) −0.227*** (0.060) −0.328*** (0.040) −0.110** (0.040) 

SEs are reported in parentheses.

*

P < .05;

**

P < .01;

***

P < .001.

Among non-CSHCN, results for USOC, PDN, and FCC were similar to those from the unadjusted analyses (Table 4). However, for REF, almost all variables lost significance in the adjusted analyses. In addition, for CC, race and ethnicity lost significance, and household education became significant; non-CSHCN in households with high school or more than high school education were 9.9 percentage points (P = .008) and 11.3 percentage points (P = .001) less likely to report attainment. As with CHSCN, sensitivity analyses revealed that parents or caregivers reporting more than high school education were more likely to report a need for CC (AME = 0.089, P = .012).

TABLE 4

AMEs of Selected Sociodemographic Characteristics on 5 Medical Home Subcomponents Among Non-CSHCN

CovariatesMarginal Effect (SE)
Had USOCHad PDNReceived Needed ReferralsReceived Effective CCReceived FCC
Sex (reference = female)      
 Male 0.002 (0.010) −0.005 (0.011) 0.020 (0.025) 0.001 (0.014) 0.0023 (0.0090) 
Age, y (reference = 0–5 y)      
 6–11 −0.002 (0.012) −0.020 (0.014) −0.016 (0.032) −0.027 (0.018) −0.027* (0.011) 
 12–17 −0.054*** (0.012) −0.025* (0.013) −0.055 (0.028) −0.006 (0.017) −0.015 (0.010) 
Race and ethnicity (reference = non-Hispanic white)      
 Hispanic −0.051** (0.016) −0.069*** (0.017) −0.046 (0.042) −0.034 (0.024) −0.065*** (0.016) 
 Non-Hispanic black −0.066*** (0.016) −0.054** (0.019) −0.014 (0.040) −0.012 (0.027) −0.060*** (0.014) 
 Non-Hispanic other −0.096*** (0.015) −0.046** (0.015) −0.100** (0.038) −0.034 (0.020) −0.043*** (0.011) 
Primary language spoken at home (reference = English)      
 Any other language −0.002 (0.018) −0.008 (0.021) −0.098 (0.051) −0.146*** (0.033) −0.051* (0.021) 
Insurance coverage at the time of survey (reference = uninsured)      
 Any public 0.114*** (0.029) 0.188*** (0.031) 0.070 (0.079) 0.099* (0.048) 0.069* (0.021) 
 Private 0.146*** (0.029) 0.216*** (0.031) 0.144 (0.078) 0.126** (0.048) 0.091** (0.030) 
Household income as a proportion of the FPL (reference = ≥400%), %      
 <100 −0.081*** (0.020) −0.070** (0.021) −0.066 (0.050) −0.051 (0.035) −0.051** (0.017) 
 100–200 −0.063*** (0.016) −0.079*** (0.020) −0.047 (0.036) −0.064* (0.028) −0.069*** (0.015) 
 200–400 −0.048*** (0.012) −0.058*** (0.012) −0.034 (0.026) −0.026 (0.018) −0.042*** (0.010) 
Household education (reference = less than high school)      
 High school 0.053 (0.032) 0.027 (0.035) 0.036 (0.063) −0.099** (0.037) 0.010 (0.029) 
 More than high school 0.132*** (0.030) 0.104** (0.033) 0.022 (0.058) −0.113** (0.034) 0.022 (0.028) 
CovariatesMarginal Effect (SE)
Had USOCHad PDNReceived Needed ReferralsReceived Effective CCReceived FCC
Sex (reference = female)      
 Male 0.002 (0.010) −0.005 (0.011) 0.020 (0.025) 0.001 (0.014) 0.0023 (0.0090) 
Age, y (reference = 0–5 y)      
 6–11 −0.002 (0.012) −0.020 (0.014) −0.016 (0.032) −0.027 (0.018) −0.027* (0.011) 
 12–17 −0.054*** (0.012) −0.025* (0.013) −0.055 (0.028) −0.006 (0.017) −0.015 (0.010) 
Race and ethnicity (reference = non-Hispanic white)      
 Hispanic −0.051** (0.016) −0.069*** (0.017) −0.046 (0.042) −0.034 (0.024) −0.065*** (0.016) 
 Non-Hispanic black −0.066*** (0.016) −0.054** (0.019) −0.014 (0.040) −0.012 (0.027) −0.060*** (0.014) 
 Non-Hispanic other −0.096*** (0.015) −0.046** (0.015) −0.100** (0.038) −0.034 (0.020) −0.043*** (0.011) 
Primary language spoken at home (reference = English)      
 Any other language −0.002 (0.018) −0.008 (0.021) −0.098 (0.051) −0.146*** (0.033) −0.051* (0.021) 
Insurance coverage at the time of survey (reference = uninsured)      
 Any public 0.114*** (0.029) 0.188*** (0.031) 0.070 (0.079) 0.099* (0.048) 0.069* (0.021) 
 Private 0.146*** (0.029) 0.216*** (0.031) 0.144 (0.078) 0.126** (0.048) 0.091** (0.030) 
Household income as a proportion of the FPL (reference = ≥400%), %      
 <100 −0.081*** (0.020) −0.070** (0.021) −0.066 (0.050) −0.051 (0.035) −0.051** (0.017) 
 100–200 −0.063*** (0.016) −0.079*** (0.020) −0.047 (0.036) −0.064* (0.028) −0.069*** (0.015) 
 200–400 −0.048*** (0.012) −0.058*** (0.012) −0.034 (0.026) −0.026 (0.018) −0.042*** (0.010) 
Household education (reference = less than high school)      
 High school 0.053 (0.032) 0.027 (0.035) 0.036 (0.063) −0.099** (0.037) 0.010 (0.029) 
 More than high school 0.132*** (0.030) 0.104** (0.033) 0.022 (0.058) −0.113** (0.034) 0.022 (0.028) 

SEs are reported in parentheses.

*

P < .05;

**

P < .01;

***

P < .001.

Over the past 2 decades, the medical home model has become widely accepted as an effective health care delivery model for all children. However, our results indicate that there is still room for improvement, given that only 43.2% of CSHCN and 50.0% of non-CSHCN were reported by their parents or caregivers to receive care that met all criteria for a medical home in 2016. These attainment rates serve as a new baseline from which we can track progress in medical home access and its subcomponents among CSHCN and non-CSHCN.

Historically, >90% of both CSHCN and non-CSHCN were reported by a parent or caregiver to have a USOC and a PDN, with lower reported rates for other medical home subcomponents, particularly receipt of FCC and CC.15,17,19 However, we found the highest attainment for both groups was the receipt of FCC (82.6% and 87.3%). It is possible that these rates suggest that improvements have been made across the board in parent and caregiver perceptions of family engagement, although it will be important to see if these rates remain or change with future years of data. Despite higher overall rates, we still found important differences in attainment by language, household income, and insurance coverage. In particular, results for households in which English is not the primary language suggest a continued need for medical interpretation and translation services to improve the provision of FCC and to facilitate family-professional partnerships.18,24 In addition, we found that having a PDN was the subcomponent with the lowest attainment rate among non-CSHCN (71%). One possibility is that non-CSHCN could be more likely to use large group, urgent care, or school-based practices in which they are less likely to see the same clinician each time. This is an important topic for future research in addition to examining whether having a PDN is critical for non-CSHCN who are generally healthy, especially if they have a USOC.

Our findings also underscore the continued importance of medical home access for all children. Nearly half of non-CSHCN and three-fourths of CSHCN needed some form of CC, yet both had low attainment rates for CC (62.3% and 76.2%, respectively). Effective CC has been linked to decreased unmet specialty care needs and other care outcomes.25,26 Our results reveal that sustained efforts to support effective CC are needed.

The factors associated with reported medical home attainment were not consistent between CSHCN and non-CSHCN. All sociodemographic characteristics except sex were significantly associated with reported medical home attainment among non-CSHCN. However, age, race and ethnicity, household income, and household education were not consistently associated with reported medical home attainment or related subcomponents among CSHCN. Because the concept of the medical home was first emphasized specifically for CSHCN,2,3 it is possible that the sustained focus among this population has led to reductions in some sociodemographic disparities noted in previous analyses15,17 that have not yet been replicated among non-CSHCN. Additionally, among CSHCN, those with more complex needs were less likely to attain a medical home. It may be that as the number of SHCN qualifiers increases, the need for coordinated services provided by multiple care teams also increases, thereby increasing the potential for unmet care events and reduced medical home access.

One similarity between the results for CSHCN and non-CSCHN was the association between household education and reported receipt of effective CC. For both groups, children whose parents or caregivers reported more than high school education were significantly less likely to report a receipt of CC. Although this was an unexpected finding, our sensitivity analyses indicated that parents and caregivers who reported more than high school education were more likely to report that their child needed CC in the first place. Our results may indicate parental and caregiver perceptions of need influence the perception of the receipt of CC. The results for insurance status and CC among CSHCN were also surprising, and future research is needed to better understand this relationship.

There are several limitations to this study. First, because data from the NSCH are based on parental and caregiver reports, there is potential for bias due to a lack of knowledge or recall. However, the use of parental and caregiver reports for medical home attainment provides a valuable patient-family assessment of this national measure because parents and caregivers are integral parts of the medical home process. Second, the cross-sectional nature of the data limits our ability to interpret causality; all results from this study represent associations and not causal relationships. Third, there is the potential for bias in the results because of survey nonresponse; however, survey weights were used to attenuate the bias. Finally, although the medical home and its subcomponents were defined by using the same survey questions as those in the previous NSCH and NS-CSHCN, differences in survey sampling methodology preclude direct comparisons and trend analyses with estimates from the previous surveys.

Results from this analysis of the 2016 NSCH reveal that half of non-CSHCN and less than half of CSHCN were reported to have received care consistent with the medical home model in 2016. We found that sociodemographic and health-related disparities in the attainment of the medical home and its subcomponents persist, although our results also indicate that the factors associated with access to a medical home are different for CSHCN and non-CSHCN.

     
  • AME

    average marginal effect

  •  
  • CC

    care coordination

  •  
  • CSHCN

    children with special health care needs

  •  
  • FCC

    family-centered care

  •  
  • FPL

    federal poverty level

  •  
  • HRSA MCHB

    Health Resources and Services Administration’s Maternal and Child Health Bureau

  •  
  • NSCH

    National Survey of Children’s Health

  •  
  • NS-CSHCN

    National Survey of Children With Special Health Care Needs

  •  
  • PDN

    personal doctor or nurse

  •  
  • REF

    receiving needed referral

  •  
  • SHCN

    special health care needs

  •  
  • USOC

    usual source of care

Dr Lichstein conceptualized and designed the study, conducted all analyses, drafted the initial manuscript, and reviewed and revised the manuscript; Drs Ghandour and Mann conceptualized and designed the study, provided detailed feedback on analyses and findings, and critically 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.2018-2594.

1
Medical Home Initiatives for Children With Special Needs Project Advisory Committee
;
American Academy of Pediatrics
.
The medical home.
Pediatrics
.
2002
;
110
(
1 pt 1
):
184
186
[PubMed]
2
Sia
C
,
Tonniges
TF
,
Osterhus
E
,
Taba
S
.
History of the medical home concept.
Pediatrics
.
2004
;
113
(
suppl 5
):
1473
1478
[PubMed]
3
Perrin
JM
,
Romm
D
,
Bloom
SR
, et al
.
A family-centered, community-based system of services for children and youth with special health care needs.
Arch Pediatr Adolesc Med
.
2007
;
161
(
10
):
933
936
[PubMed]
4
McPherson
M
,
Arango
P
,
Fox
H
, et al
.
A new definition of children with special health care needs.
Pediatrics
.
1998
;
102
(
1 pt 1
):
137
140
[PubMed]
5
Newacheck
PW
,
Strickland
B
,
Shonkoff
JP
, et al
.
An epidemiologic profile of children with special health care needs.
Pediatrics
.
1998
;
102
(
1 pt 1
):
117
123
[PubMed]
6
Silver
EJ
,
Stein
RE
.
Access to care, unmet health needs, and poverty status among children with and without chronic conditions.
Ambul Pediatr
.
2001
;
1
(
6
):
314
320
[PubMed]
7
Homer
CJ
,
Klatka
K
,
Romm
D
, et al
.
A review of the evidence for the medical home for children with special health care needs.
Pediatrics
.
2008
;
122
(
4
). Available at: www.pediatrics.org/cgi/content/full/122/4/e922
[PubMed]
8
Hadland
SE
,
Long
WE
.
A systematic review of the medical home for children without special health care needs.
Matern Child Health J
.
2014
;
18
(
4
):
891
898
[PubMed]
9
Long
WE
,
Bauchner
H
,
Sege
RD
,
Cabral
HJ
,
Garg
A
.
The value of the medical home for children without special health care needs.
Pediatrics
.
2012
;
129
(
1
):
87
98
[PubMed]
10
Cooley
WC
,
McAllister
JW
,
Sherrieb
K
,
Kuhlthau
K
.
Improved outcomes associated with medical home implementation in pediatric primary care.
Pediatrics
.
2009
;
124
(
1
):
358
364
[PubMed]
11
Child and Adolescent Health Measurement Initiative
.
Measuring Medical Home for Children With Special Health Care Needs and the National Survey of Children’s Health
.
Portland, OR
:
Data Resource Center for Child and Adolescent Health
;
2009
12
Ghandour
RM
,
Jones
JR
,
Lebrun-Harris
LA
, et al
.
The Design and Implementation of the 2016 National Survey of Children’s Health.
Matern Child Health J
.
2018
;
22
(
8
):
1093
1102
13
US Census Bureau
. 2016 National Survey of Children’s Health methodology report. 2018. Available at: https://census.gov/content/dam/Census/programs-surveys/nsch/tech-documentation/methodology/2016-NSCH-Methodology-Report.pdf. Accessed February 26, 2018
14
US Census Bureau
. National Survey of Children’s Health (NSCH): 2016 NSCH data release. 2018. Available at: https://www.census.gov/data/datasets/2016/demo/nsch/nsch2016.html. Accessed October 20, 2017
15
Strickland
B
,
McPherson
M
,
Weissman
G
,
van Dyck
P
,
Huang
ZJ
,
Newacheck
P
.
Access to the medical home: results of the National Survey of Children with Special Health Care Needs.
Pediatrics
.
2004
;
113
(
suppl 5
):
1485
1492
[PubMed]
16
Strickland
BB
,
Jones
JR
,
Ghandour
RM
,
Kogan
MD
,
Newacheck
PW
.
The medical home: health care access and impact for children and youth in the United States.
Pediatrics
.
2011
;
127
(
4
):
604
611
[PubMed]
17
Strickland
BB
,
Singh
GK
,
Kogan
MD
,
Mann
MY
,
van Dyck
PC
,
Newacheck
PW
.
Access to the medical home: new findings from the 2005-2006 National Survey of Children with Special Health Care Needs.
Pediatrics
.
2009
;
123
(
6
). Available at: www.pediatrics.org/cgi/content/full/123/6/e996
[PubMed]
18
Yu
S
,
Lin
S
,
Strickland
B
.
Disparities in health care quality indicators among US children with special health care needs according to household language use.
Int J MCH AIDS
.
2015
;
4
(
1
):
3
12
[PubMed]
19
Zickafoose
JS
,
Davis
MM
.
Medical home disparities are not created equal: differences in the medical home for children from different vulnerable groups.
J Health Care Poor Underserved
.
2013
;
24
(
3
):
1331
1343
[PubMed]
20
Bethell
CD
,
Read
D
,
Stein
RE
,
Blumberg
SJ
,
Wells
N
,
Newacheck
PW
.
Identifying children with special health care needs: development and evaluation of a short screening instrument.
Ambul Pediatr
.
2002
;
2
(
1
):
38
48
[PubMed]
21
Onukwugha
E
,
Bergtold
J
,
Jain
R
.
A primer on marginal effects–part I: theory and formulae.
Pharmacoeconomics
.
2015
;
33
(
1
):
25
30
[PubMed]
22
Onukwugha
E
,
Bergtold
J
,
Jain
R
.
A primer on marginal effects-part II: health services research applications.
Pharmacoeconomics
.
2015
;
33
(
2
):
97
103
[PubMed]
23
U.S. Census Bureau
. 2016 National Survey of Children’s Health: guide to analysis with multiply imputed data. 2018. Available at: https://www.census.gov/content/dam/Census/programs-surveys/nsch/tech-documentation/methodology/NSCH-Guide-to-Analysis-with-Multiply-Imputed-Data.pdf. Accessed January 20, 2018
24
Morales
LS
,
Elliott
M
,
Weech-Maldonado
R
,
Hays
RD
.
The impact of interpreters on parents’ experiences with ambulatory care for their children.
Med Care Res Rev
.
2006
;
63
(
1
):
110
128
[PubMed]
25
Boudreau
AA
,
Perrin
JM
,
Goodman
E
,
Kurowski
D
,
Cooley
WC
,
Kuhlthau
K
.
Care coordination and unmet specialty care among children with special health care needs.
Pediatrics
.
2014
;
133
(
6
):
1046
1053
[PubMed]
26
Turchi
RM
,
Berhane
Z
,
Bethell
C
,
Pomponio
A
,
Antonelli
R
,
Minkovitz
CS
.
Care coordination for CSHCN: associations with family-provider relations and family/child outcomes.
Pediatrics
.
2009
;
124
(
suppl 4
):
S428
S434
[PubMed]

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.