Children From Low-income Families Lack Health Insurance for Which of the Following Reasons?

J Health Care Poor Underserved. Author manuscript; available in PMC 2016 Jun 30.

Published in concluding edited course every bit:

PMCID: PMC4928707

NIHMSID: NIHMS796024

Obtaining Health Care Services for Low-Income Children: A Hierarchy of Needs

Jennifer E. DeVoe, MD, DPhil, Alan Due south. Graham, MD, Heather Angier, BA, Alia Baez, BA, and Lisa Krois, MPH

Abstract

Introduction

Basic health care is across the attain of many families, partly due to lack of wellness insurance. Many of those with insurance also experience unmet need and limited admission. In this study, depression-income parents illuminate barriers to obtaining health care services for their children.

Methods

We surveyed a random sample of families from Oregon'southward food stamp population with children eligible for public insurance, based on household income. Mixed-methods included: (1) multivariable analysis of data from 2,681 completed surveys, and (2) qualitative study of written narratives from 722 parents.

Results

Lack of health insurance was the nearly consistent predictor of unmet health care needs in the quantitative analysis. Qualitatively, wellness insurance instability, lack of admission to services despite having insurance, and unaffordable costs were major concerns.

Conclusions

Parents in this low-income population view insurance coverage equally different from access to services, and reported a hierarchy of needs. Insurance was the primary business; access and costs were secondary.

Keywords: Insurance coverage, access to health care, master health care, Medicaid, children's health, underserved populations

Ideally, all children in the United states of america would accept stable access to loftier-quality health intendance, but many barriers make this goal before long unattainable. These barriers have been described as voltage drops, or resistance points, where children drop from the wellness intendance arrangement like voltage from an electrical current.¹ In that location is a wealth of data describing the multitude of barriers for low-income children, who often experience several barriers simultaneously^i–vi simply a clear hierarchical framework to define the relative importance of each barrier is defective.

Uninsurance, known to inhibit access to intendance,^7–11 significantly affects U.Southward. children: amidst the most 47 one thousand thousand uninsured Americans, over nine million are uninsured children.^12,thirteen A majority of these uninsured children qualify for publicly-funded insurance programs, such as Medicaid and the State Children's Health Insurance Programs (SCHIP), just have either lost coverage or go disenrolled due to various barriers.^13–xvi Oregon has a high charge per unit of uninsured children,^13,17 and over lx% of uninsured Oregon children appeared to be eligible for some form of public coverage in 2004—a college percentage than is estimated for uninsured children nationally.^11,eighteen Every bit struggles to reauthorize SCHIP continue,^19–22 Oregon and several other states are focused on enrolling uninsured just eligible low-income children.

In this context, it is important to step back and examine the role that insurance plays in helping depression-income children obtain necessary health care and to consider how it compares with other factors affecting admission. Past research has concluded that most low-income parents are familiar with Medicaid and SCHIP, but restrictive regulations and disruptive organizational structures keep public health insurance out of accomplish for some depression-income families and contribute to coverage instabilities for others.^{14,17,23–41} Less is known almost how parents feel about public insurance offerings and whether they believe that getting and maintaining coverage is worth the effort required. Despite the wealth of evidence linking insurance to better health intendance outcomes, how much does wellness insurance matter to poor families? As well, beyond health insurance coverage, what factors practise low-income parents identify as major influences on whether their children'south wellness intendance needs are met or not?

Most previous studies of factors influencing children'due south health care admission take focused on patterns of insurance enrollment and service utilization.^{14,17,40,42,43} Study methods often include the utilize of authoritative data, claims data, secondary analysis of national surveys, and fundamental informant interviews, all of which are several steps removed from the actual life experiences of poor and underserved families. Nosotros collected information straight from low-income parents nigh the importance of health insurance and other possible factors affecting access to health intendance for their children. This study was part of a larger effort, the Oregon Children's Admission to Health Care Survey (CAHS), which was launched in 2005, shortly affer Medicaid reforms. In the early 1990s, the Oregon Health Plan (OHP) was a national model for innovative Medicaid program expansions that facilitated more comprehensive insurance coverage for unabridged families.⁴⁴ Equally happened in many states, a fiscal crisis in Oregon at the turn of the century led to the implementation of cost containment policies for the OHP starting in 2003, including benefit reductions and increased premiums.⁴⁵ These changes have been associated with the loss of insurance for thousands of adults in Oregon's low-income families.^46–48

Although Oregon's cutbacks were targeted at adults, children may have been indirectly afflicted. The CAHS nerveless cross-sectional, statewide information from low-income families in Oregon's food stamp population to assess the potential impacts of Medicaid policy changes on children. For this newspaper, we conducted a quantitative assay of factors associated with children's unmet health care needs from all survey respondents and a qualitative analysis of written comments from responses to a concluding open up-ended survey question that asked, "Is there annihilation else you would like to tell united states of america?" With this mixed-methods approach, we had ii primary aims: (1) to examine, both quantitatively and qualitatively, whether parents from this low-income population believed wellness insurance coverage for their children was important; and (two) to learn more than from parents about factors that affect their efforts to obtain necessary intendance for their children.

Methods

Study population and data collection

To identify a large group of families with children who were likely eligible for public insurance coverage, the study sample was fatigued from all 84,087 Oregon families enrolled in the federal food stamp program at the terminate of January 2005 with children betwixt the ages of one and 18 years of historic period. At that time, both the public insurance and nutrient stamp programs required a household income less than 185% of the federal poverty level and proof of the child'south U.S. citizenship. (Families with only children under one twelvemonth of historic period were excluded due to different public insurance enrollment procedures for these infants.) A stratified, random sample of 10,175 nutrient postage stamp families was drawn with purposeful oversampling to ensure adequate representation from rural areas and uninsured families. A focal child was and so randomly selected from each household, and parents were clearly instructed to answer survey questions about only this child. Later four-waves of mailing from March–May 2005, we excluded 1,539 families who had moved out of country or to another location with no forwarding address information available. Completed surveys were received from ii,681 of the 8,636 eligible households in the random sample (for a 31% response rate). This response rate is consequent with other similar surveys of Medicaid-eligible populations.^three,48,49

Information from the 2,681 completed surveys were used in the quantitative analysis. The additional written comments from 722 parents were used in the qualitative analysis. Demographic characteristics of the original sample were like to those responding to the survey and those contributing boosted written narratives. (Data bachelor from lead writer upon request.) For the quantitative analysis, nosotros assigned private response weights depending on the probability of original selection into the random sample. To account for non-response, final weights assigned to each respondent case were further adapted using a raking ratio interpretation procedure.^50,51 All reported quantitative results accept been weighted back to the overall written report population of 84,087 households, unless otherwise described. (More than data most the raking ratio interpretation process available from the pb writer upon request.)

Survey instrument

The Oregon Children's Access to Wellness Care Survey was adult to allow parents to study about various wellness-related issues for one randomly-selected focal child during the previous year. Survey questions were grouped into four major sections: kid's health insurance status, child'due south access to diverse wellness care services, child's demographic data, and family information (primarily demographics and parental insurance data, collected only from the parent/guardian who completed the survey). Most survey questions were adjusted from widely accustomed and validated national surveys.^52–55 Written at a fifth grade reading level, the mail-render survey instrument contained 62 questions with multiple-pick response options and a last open up-ended question: "Is there annihilation else you would like to tell the states?" For validity testing of the cocky-administered instrument, cerebral interviews were conducted during a pilot test phase with a small sample of low-income parents. Surveys were translated into Castilian and Russian (the two most common non-English language languages among this population) and so independently back-translated to ensure fidelity of translation. The Oregon Health & Scientific discipline Academy Institutional Review Board approved the survey and all aspects of the study protocol (OHSU eIRB# 1717).

Quantitative analysis

The quantitative analysis used a standard bivariate and multivariate analytical arroyo. Five issue variables were measured pertaining to access that measured unmet health care needs (medical, prescription and dental), delayed urgent care, and ambulatory care visits (see Appendix for details on these variables). In addition to children's health insurance status as the chief predictor variable, chi-foursquare bivariate analyses facilitated the identification of several other independent variables significantly associated with at least ane of the outcome variables amid the depression-income study population (p<.05). These covariates included age, race/ethnicity, parental employment, household income, parental insurance status, place of residence, and whether or non the child had a usual source of care. Because Oregon'southward predominant minority population is Hispanic and a large number of Hispanics in the sample reported Hispanic as their race, we created a combination race/ethnicity covariate (White, non-Hispanic; Hispanic, any race; non-White, non-Hispanic). Rural residence was determined based on ZIP code designations from the Oregon Role of Rural Health. These covariates are consistent with conceptual models of health services utilization described previously past Aday, Andersen, and others.⁵⁶ No significant (p<.05) interactions between the master children'southward health insurance predictor variable and the other covariates were noted.

Later on choice of all meaning variables, nosotros practical a series of logistic regression models to assess independent associations between each predictor variable and each outcome variable, while controlling for all other potentially confounding factors. SPSS 14.0 software with the complex samples module was used to carry statistical tests and make estimates with variance adjustment required for the circuitous sampling design of the survey (SPSS 14.0 for Windows, Chicago: SPSS Inc.).

Qualitative assay

The qualitative analysis team included a various group of health services researchers including a family unit physician, a doctorally-prepared quantitative and qualitative senior researcher, a medical student jointly enrolled in a public health master's program, and a inquiry associate from our rural exercise-based inquiry network. We also received feedback during the process from two land policy researchers.

Initially, we identified our sub-sample of 722 parents who contributed narrative comments sufficient for analysis and then, aided by SPSS 14.0 software, confirmed that this sub-sample had similar demographic characteristics to those of survey respondents and those of the total eligible sample. Subsequently this preliminary review, each team fellow member independently read the narratives and assigned themes. We then met to create a codebook of tree nodes using NVivo qualitative software 7.0 (NVivo7, Melbourne: QSR International Pty Ltd).

We repeated our individual reviews with codebook guidance and met regularly to conduct the narrative analysis using adjusted immersion/crystallization techniques.⁵⁷ During these meetings, we revised the codebook to reflect the multiple interpretations of all squad members and policy inquiry collaborators. We and then subjected each text entry to line-by-line coding and re-reviewed it for relevance to the established nodes.

Subsequently the discovery of 3 major subthemes directly relevant to children's wellness intendance access barriers, we conducted a further in-depth analysis to run across if the child'due south health insurance status was associated with unlike reporting of three subthemes. Nosotros likewise examined whether reports were unlike based on whether or non the child had a usual source of care. For this analysis, we conducted matrix-coded queries in NVivo with imported health insurance data from matched entries in the complete SPSS dataset. In a final authors' meeting to synthesize quantitative and qualitative study findings, information technology became axiomatic that families reported their needs in a hierarchical order. We designed a conceptual model—The Snowman Model—to illustrate this hierarchy of needs amid this low-income population for obtaining children'southward health care.

Results

Quantitative assay

In the bivariate analyses, having wellness insurance and a usual source of care were the two covariates most consistently associated with better access to health care in all five outcomes measured. Racial and ethnic differences were meaning in all measures; withal, the highest rates of unmet need were not consistently seen amid the same grouping. Parental health insurance was significantly associated with all measures except unmet prescription need. Parental employment appeared significant when considering unmet medical and dental needs, and household income was significantly associated with unmet prescription demand. Rural children had college rates of unmet medical and dental needs than others (Table 1).

Table 1

Pct OF CHILDREN WITH UNMET HEALTH CARE NEEDS AND Access PROBLEMS

	Unmet medical demand	Unmet prescription need	Big problem getting dental intendance	Rarely or never got immediate care	No doctor visits in past year
Demographic characteristics	Weighted %	Weighted %	Weighted %	Weighted %	Weighted %
Total	16.ane%	22.0%	26.0%	21.vii%	13.eight%
Historic period
one–four years of age	12.1%	19.1%	fifteen.five%	20.8%	seven.9%
5–9 years of historic period	xv.viii%	xx.5%	26.9%	21.6%	13.iv%
10–14 years of age	xx.2%	23.9%	34.ii%	22.3%	17.0%
15–18 years of historic period	17.5% (p<.02)	27.iv% (p<.08)	29.ix% (p<.01)	22.eight% (p<.96)	20.seven% (p<.01)
Race/ethnicity a
White, not Hispanic	xiv.8%	24.0%	28.one%	16.4%	x.5%
Hispanic, whatever race	17.ii%	19.3%	25.2%	44.iii%	26.8%
Not-White,   non-Hispanic	22.4% (p<.05)	14.6% (p<.04)	14.four% (p<.01)	21.3% (p<.01)	11.6% (p<.01)
Parental employment b
Employed or   self-employed	18.four%	24.two%	28.7%	23.3%	fourteen.6%
Not currently   employed	14.three% (p<.04)	20.5% (p<.11)	23.7% (p<.04)	twenty.1% (p<.24)	xiii.1% (p<.43)
Household income
>133% FPL	19.9%	32.9%	29.eight%	21.i%	12.3%
101%–133% FPL	twenty.nine%	29.0%	30.6%	21.7%	16.two%
51%–100% FPL	12.v%	21.one%	26.1%	17.viii%	xi.2%
ane%–50% FPL	xvi.6%	twenty.8%	24.0%	24.4%	14.8%
Zero income	17.1% (p<.08)	16.0% (p<.01)	22.0% (p<.24)	21.1% (p<.41)	14.8% (p<.41)
Kid'due south insurance status
Kid insured	13.v%	20.one%	22.0%	eighteen.5%	10.nine%
Child uninsured	37.6% (p<.01)	38.7% (p<.01)	threescore.0% (p<.01)	51.8% (p<.01)	38.5% (p<.01)
Parent insurance condition c
Parent insured	13.v%	21.one%	62.2%	18.5%	10.five%
Parent uninsured	22.v% (p<.01)	23.9% (p<.25)	37.8% (p<.01)	thirty.one% (p<.01)	xx.5% (p<.01)
Place of residence d
Urban	14.2%	20.1%	22.v%	21.6%	14.nine%
Rural	18.3% (p<.04)	24.iii% (p<.06)	thirty.3% (p<.01)	21.8% (p<.92)	12.6% (p<.21)
Usual source of care
Yes usual source   of intendance	fourteen.3%	21.i%	23.three%	18.8%	10.7%
	29.3%	29.5%	46.five%	46.1%	45.six%
No usual source of care	(p<.01)	(p<.04)	(p<.01)	(p<.01)	(p<.01)

Later controlling for all covariates, health insurance was the just predictor significantly associated with all five measures of health care admission (Table 2). Compared with insured children (reference group = ane.00), uninsured children were more likely to report unmet medical need (adapted odds ratio [OR] 2.97, 95% conviction interval [CI] one.94, 4.56); unmet prescription demand (OR 2.55, 95% CI 1.68, 3.87); unmet dental need (OR 5.39, 95% CI 3.67, vii.ninety); delayed urgent care (OR 3.88, 95% CI 2.30, vi.53); and no doctor visit in the past year (OR ii.40, 95% CI 1.51, 3.82). Moving beyond wellness insurance, disparities in reported access to care were about prominent based on age, race/ethnicity, rural/urban residence, and whether the kid had a usual source of intendance. Compared with children aged 1–4 years, older children had college rates of unmet dental need and delayed immediate care. Compared with White, non-Hispanic children, Hispanics beyond all racial categories had a college likelihood of delayed urgent care (OR 3.36, 95% CI 2.thirteen–5.31) and no md visits (OR 3.54, 95% CI 2.31–5.42). Non-White, non-Hispanic racial minorities reported more unmet medical need (OR two.08, 95% CI ane.16–three.70). Compared with children living in urban areas, rural children had higher rates of unmet medical demand (OR 1.39, 95% CI 1.01–1.92), and more significant problems accessing dental intendance (OR 1.37, 95% CI 1.04–i.80). Compared with children with a usual source of intendance, the about significant outcomes associated with having no usual source of care were higher odds of experiencing delays in care (OR 2.24, 95% CI i.35–three.72), big problems accessing dental care (OR two.11, 95% CI i.33–three.33), and no doctor visits in the past year (OR half-dozen.twenty, 95% CI iii.83–10.04).

Table 2

Adapted ODDS OF CHILD HAVING UNMET Health CARE NEEDS AND ACCESS PROBLEMS

	Unmet medical need	Unmet prescription need	Big problem getting dental intendance	Rarely or never got immediate care	No medico visits in by year
	N=72,077 (n=2313)	North=71,453 (n=2291)	North=71,192 (n=2286)	N=49,574 (n=1572)	N=72,819 (n=2336)
Demographic characteristics	Adjusted OR (95% CI)	Adjusted OR (95% CI)	Adapted OR (95% CI)	Adapted OR (95% CI)	Adjusted OR (95% CI)
Age
1–iv years of age	ane.00	1.00	one.00	1.00	1.00
5–9 years of age	1.25 (0.80, 1.95)	0.98 (0.68, 1.43)	1.98 (1.35, 2.92)	0.88 (0.54, 1.44)	one.78 (1.06, 2.98)
10–xiv years of age	1.71 (1.08, 2.68)	one.31 (0.89, 1.93)	2.57 (1.74, iii.82)	1.13 (0.67, one.89)	2.93 (1.71, 5.03)
15–18 years of age	i.37 (0.85, 2.20)	1.42 (0.93, 2.15)	two.08 (one.32, 3.26)	1.00 (0.60, one.65)	iv.39 (2.50, 7.69)
Race/ethnicity a
White, not Hispanic	i.00	1.00	ane.00	i.00	i.00
Hispanic, any race	0.96 (0.61, 1.52)	0.73 (0.48, ane.10)	0.77 (0.52, one.14)	iii.36 (ii.13, five.31)	3.54 (2.31, 5.42)
Non-White,   non-Hispanic	2.08 (ane.xvi, iii.lxx)	0.68 (0.37, one.22)	0.31 (0.17, 0.55)	1.45 (0.72, 2.92)	0.93 (0.45, i.91)
Parental employment b
Employed/self-employed	1.00	i.00	i.00	1.00	1.00
Not employed	0.79 (0.56, 1.11)	0.xc (0.67, i.21)	0.95 (0.72, i.26)	0.73 (0.49, 1.07)	1.01 (0.69, 1.47)
Household monthly income
>133% FPL	i.00	1.00	1.00	1.00	1.00
101%–133% FPL	1.43 (0.77, ii.66)	1.04 (0.63, 1.71)	1.40 (0.84, 2.33)	one.50 (0.73, 3.12)	1.54 (0.68, 3.48)
51%–100% FPL	0.75 (0.42, ane.36)	0.64 (0.40, 1.02)	0.99 (0.62, 1.58)	ane.12 (0.threescore, 2.x)	0.93 (0.45, 1.94)
1%–50% FPL	ane.xi (0.63, 1.96)	0.64 (0.forty, i.01)	0.92 (0.57, 1.48)	1.52 (0.83, ii.75)	1.11 (0.54, two.30)
Zippo income	1.39 (0.69, 2.79)	0.47 (0.26, 0.84)	0.82 (0.44, ane.52)	1.49 (0.67, 3.32)	1.25 (0.54, two.93)
Kid's insurance status
Child insured	1.00	1.00	1.00	1.00	1.00
Child uninsured	two.97 (ane.94, 4.56)	two.55 (1.68, 3.87)	5.39 (3.67, vii.90)	3.88 (2.thirty, six.53)	2.40 (i.51, 3.82)
Parent insurance status c
Parent insured	1.00	i.00	i.00	1.00	ane.00
Parent uninsured	1.48 (ane.04, 2.12)	0.89 (0.64, i.22)	0.82 (0.60, ane.x)	i.08 (0.70, 1.68)	ane.xviii (0.eighty, 1.76)
Place of residence d
Urban	1.00	one.00	one.00	1.00	i.00
Rural	1.39 (i.01, 1.92)	1.eighteen (0.90, ane.55)	1.37 (1.04, 1.80)	1.00 (0.seventy, ane.45)	0.73 (0.51, i.04)
Usual source of care
Yep usual source of care	i.00	1.00	1.00	1.00	ane.00
No usual source of intendance	ane.44 (0.ninety, 2.31)	1.03 (0.66, ane.61)	2.11 (i.33, iii.33)	2.24 (ane.35, 3.72)	6.twenty (3.83, 10.04)

Qualitative analysis

The 722 respondents who provided boosted written comments wrote passionate narratives about numerous difficulties obtaining health care for themselves and their children. Consistent with findings from the quantitative assay nigh how insurance coverage was a key predictor associated with the lowest rates of unmet wellness intendance need, narrative respondents were most concerned about a total lack of parental insurance coverage (36%) and significant insurance coverage gaps for their children (23%). Other comments related to two additional sub-themes near access barriers (23%) and cost barriers for children (20%). In a closer examination of the three themes that parents related direct to children's unmet health care needs—coverage gaps, lack of access, and unaffordable costs—the rates of reporting about each theme appeared to differ based on the electric current and continuous health insurance condition of the focal kid. Fewer reporting differences were noted based on whether or non the child had a usual source of care (Table 3).

Table three

PERCENTAGE OF PARENTS REPORTING THREE MAJOR THEMES INFLUENCING CHILD'S UNMET HEALTH CARE NEEDS, BY CHILD'S Electric current INSURANCE STATUS AND USUAL SOURCE OF Intendance

	Total	Child's electric current insurance status			Child'south 12-month insurance coverage		Kid's usual source of care?
Themes	All respondents Due north=722	Public insurance N=401	Uninsured North=135	Individual insurance (or philharmonic) N=176	Continuous 12-month coverage N=431	Coverage gap in past 12 months North=275	No usual source of care N=92	Yeah usual source of intendance North=591
Insurance coverage discontinuities (gaps)	23%	18%	42%	17%	18%	29%	20%	23%
Difficulty accessing health care services	23%	26%	thirteen%	xx%	23%	20%	27%	21%
Unaffordable costs of medical care	20%	fifteen%	15%	32%	xix%	20%	15%	twenty%

Note: Kid'southward insurance status and usual source of care missing for a pocket-sized number of respondents (totals exercise not equal 722).

Not surprisingly, gaps in children's insurance coverage was the most commonly cited business organization among parents with uninsured children. Among all families, parents with children currently uninsured were more likely to share concerns about coverage gaps for their children than those with current children'southward coverage. Most oft, parental comments expressed frustration with inflexibilities in the public arrangement, such every bit income requirements and age limits. For example,

• My enhance at work did non outweigh my loss of [Medicaid] benefits. Maybe I should work less then I can qualify again. [Child: vi yrs, male, non-Hispanic American Indian, public health insurance, rural, household income between 101–133% FPL, parent currently uninsured.]

• I was 5 dollars over poverty and lost Oregon Health Plan [OHP]. [Child: four yrs, female, Hispanic White, public health insurance, urban, household income between 51–100% FPL, parent currently has public insurance.]

• With no wellness insurance and no firsthand means of obtaining insurance, I experience very vulnerable. It'south scary to think about getting sick with no way to go medical care. [Kid: 17 yrs, female, Hispanic White, public health insurance, rural, household income between i–l% FPL, parent currently uninsured.]

• I lost my OHP considering of the premiums. I was barely able to go past and had to pay an extra $20 to OHP. [Child: iv yrs, female person, non-Hispanic White, public health insurance, urban, household income between i–50% FPL, parent currently has public insurance.]

Admission barriers topped the listing of concerns for parents with publicly-insured children (26% reported access vs. 15% unaffordable costs and 18% insurance gaps). Similarly, a greater proportion of families with current public insurance coverage for their children reported access barriers (26%) than of families with uninsured children (xiii%) or privately-insured children (20%). These admission comments were nearly often about a shortage of providers or non-covered services. Examples to illustrate these points include:

• It is great that we accept the OHP but it is very hard to find a doctor or dentist that will accept you. We have to drive for 1.v hours just to see a dentist for a check-up or cleaning. [Child: 5 yrs, male, not-Hispanic White, public health insurance, rural, household income between 51–100% FPL, parent currently has public insurance.]

• He was never able to get in to see a doctor considering no one was taking whatever new patients. Therefore it wasn't even worth having him on OHP … [Child: seven yrs, male, not-Hispanic White, private wellness insurance, urban, household income between 133–185% FPL, parent currently has private insurance.]

• [We need] more plans, better dental, and more doctors to choose from. Recently, one of us got sick and not i physician could see us in the office. Nosotros need more than doctors available. [Child: fifteen yrs, female, non-Hispanic White, public health insurance, rural, household income between 51–100% FPL, parent currently has public insurance.]

One parent reported not applying for public insurance coverage considering of the access difficulties:

• I've heard that it'due south hard to find doctors who are accepting new OHP patients. We are by and large healthy, so we are risking it. [Child: 10 yrs, female, non-Hispanic White, uninsured, urban, household income between 101–133% FPL, parent currently uninsured.]

Cost barriers were a concern to a greater proportion of parents of privately-insured children (32%) than of those with publicly-insured (15%) or uninsured children (15%). With cost concerns at the summit of their list (32%) compared with insurance gaps and a lack of access (17% and 20%, respectively), many of these families described making hard choices most their children'south health due to cost:

• The md orders prescriptions, then we tin can't get them because they cost so much. [Child: 9 yrs, female, non-Hispanic White, public health insurance, urban, household income between 51–100% FPL, parent currently has public insurance.]

• We make sure our children become the medical care and medications they need, simply sometimes this leaves us without money for other things. [Child: 15 yrs, female, non-Hispanic White, individual health insurance, rural, household income between 101–133% FPL, parent currently has individual insurance.]

• I have to pay a lot out of pocket [for employer-sponsored insurance] and can't afford it, and then my son goes without. [Kid: 15 yrs, male, not-Hispanic White, uninsured, rural, household income betwixt 1–fifty% FPL, parent currently has private insurance.]

• I was actually relieved when my husband lost his chore because information technology made my son eligible for coverage again. In that location is no feeling in the world worse than trying to effigy out if y'all should really have an injured child to the doctor or not considering of lack of money. [Kid: 3 yrs, male, non-Hispanic Black and American Indian, public health insurance, rural, household income between 1–50% FPL, parent currently uninsured.]

• I believe we don't qualify for OHP because nosotros had a COBRA selection, just we couldn't afford it because it was $763—more my rent. [Child: ix yrs, male, non-Hispanic White, individual health insurance, urban, household income betwixt 133–185% FPL, parent currently has private insurance.]

Summary of findings

In the quantitative assay, having health insurance was nearly consistently associated with the lowest rates of unmet need. Even with insurance, some parents reported difficulty obtaining necessary health care services for their children. I in 5 insured children rarely or never got immediate care every bit soon as it was needed. Qualitatively, parents were profoundly concerned most their children's unmet needs and almost often identified children'southward insurance coverage gaps, lack of access to health care services, and frustrations most the costs of medical care equally the major contributing factors. Concerns virtually the difficulties accessing necessary health intendance services and unaffordable costs were more common among families with health insurance coverage (publicly-insured and privately-insured, respectively), while uninsured families were more than focused on obtaining and maintaining insurance coverage.

Discussion

In the low-income population studied, parents of insured children were less likely than parents of uninsured children to written report unmet children's health intendance needs. Similarly, narrative responses from a subset of these parents revealed that wellness insurance coverage for both parents and children matters greatly to this population. When describing their experiences navigating the wellness care system, parents made distinctions betwixt insurance coverage and access to services, and in that location seemed to exist a bureaucracy of concerns. Insurance coverage was the master concern; access and costs were secondary. Reporting of these three themes was disproportionate, depending on the child's insurance condition, further demonstrating the primary importance of insurance.

We created a modified Venn diagram (the Snowman Model) to depict this hierarchy of needs, synthesizing our quantitative and qualitative findings (Effigy 1). The largest, anchoring snowball is stable and continuous insurance coverage. Once a health insurance foundation is secured and covers the unabridged family, and then families tin direct attention towards accessing services and worrying about costs. Gaining easy access to services is the next concern to arise, and has two major arms: provider acceptance of insurance and insurance coverage of services. For families with public insurance every bit the foundation, there was more than concern about admission barriers. In this population, if the insurance plan does not accept provisions for sure services or if providers do not accept the coverage, in that location are limited options for obtaining the care. In this example, cost was probably not reported as a problem because most of the children were going without the services. Subsequently the barriers of obtaining insurance and access are overcome, the next concern is price, represented by the superlative of the snowman. For those with individual insurance, admission may have been somewhat better simply at college, and oftentimes unaffordable, costs. While there is a bureaucracy, all three elements—insurance, access, and cost—are related. Over all three themes is the sense of emotional and financial security that comes when the snowman is balanced. If stable insurance begins to melt away, admission and cost become unstable (metaphorically, the snowman leans over). Somewhen, the snowman collapses (melts) requiring a fresh showtime in rebuilding again. Once insurance is solidly in place, information technology still takes continued effort to achieve optimal access at an affordable price.

The Snowman Model—a hierarchy of needs for obtaining health care.

Previous studies have demonstrated that pregnant access and utilization barriers exist for poor, uninsured children.^8,ix As confirmed by our study, insurance status is not a static miracle and parental concerns extend to the instability of coverage. Parents constantly fear the loss of insurance, which tin be devastating to a kid's care. Even brusk insurance gaps are increasingly recognized equally frequent and significant barriers to care.⁵⁸ Gaps act in a "dose-response" manner to inhibit access to care and increment unmet medical need—the longer the gap, the worse the problems with access.^59–61

Having stable, continuous insurance is associated with better access to health intendance and less unmet need,^eleven but insurance alone is non a guarantee of access to health care. As recently reported, fifty-fifty privately-insured children exercise non get optimal quality health intendance up to 50% of the time.⁴ Beyond insurance, many other factors affect whether children have unmet health care need. As other hazard factors mount, including linguistic communication barriers, lack of parental education, and poverty, children experience greater barriers to accessing care.ⁱⁱ

Findings from this study contribute to current discussions about how insurance coverage, while of import, may non provide unfettered access to quality health treat low-income children. This written report confirms that parents are aware of these factors, and goes beyond past research in using a mixed-methods approach to develop a conceptual framework of the hierarchy of wellness care needs for depression-income children (the Snowman Model in Figure ane). This hierarchical model of health intendance needs illustrates the need to restructure the current wellness intendance organisation in the United States beyond measures that expand insurance coverage.

Report considerations

Estimation of the information hither requires consideration of some of import problems. First, families already continued to at least i organisation of public benefits (food stamps) may encounter fewer health insurance coverage problems than the low-income population generally. In add-on, every state has a unique wellness insurance environment, so parental perspectives may differ depending on how the state administers public insurance programs. Because the information from this study tin can but be generalized to Oregon'due south food stamp population, these results may understate the prevalence of insurance instabilities amid all depression-income families. This study, nevertheless, does capture the relationship between lack of insurance and college rates of unmet need.

Second, for budgetary reasons, the survey was simply administered in English language, Spanish, and Russian; telephone follow-up was not possible. Although the survey was written at a fifth-grade reading level with no writing requirement, information technology is also likely that low literacy rates amidst this population contributed to a lack of response from many potential participants. While our response rate is comparable to other like studies of Medicaid-eligible populations, even some that employed telephone follow-up and personal interviews, response bias remains an important consideration. The comprehensive nutrient postage stamp authoritative database allowed u.s.a. to business relationship for slight demographic differences between respondents and not-respondents in the weighting process. The raking ratio estimation adjustments for non-response were also conducted to further address this anticipated bias.

Finally, there is ever the potential for recall bias with self-reported data. To minimize call up bias, validated questions were used from national surveys that ask respondents to recall events and occurrences only in the past 12 months, and several questions pertained to similar topics. Narrative responses to the open up-concluded question may accept been biased by the content of the survey, which included specific queries virtually health insurance coverage for both children and parents, access to wellness care, and costs of health care. These questions did, however, provide several opportunities to report barriers and concerns about admission to health care. It is significant that, later on completing the survey, many parents still felt compelled to write farther narratives about their situations. Finally, it is possible that we received narrative responses from merely those families who encountered the most difficulties with the arrangement, and so the results may not be generalizeable to all families. The sub-sample, however, does have demographic characteristics similar to the original population.

Conclusions and Policy Implications

Every bit a foundation for children to have adequate access to health intendance, families must exist able to obtain and maintain stable insurance coverage. Parents of low-income children are greatly concerned most maintaining wellness insurance coverage for both their children and themselves, yet current fiscal constraints have led many states to terminate public wellness insurance coverage for parents and to increase restrictions on continuous children's coverage. Chiefly, SCHIP has dramatically improved access to care and decreased unmet demand for children.⁶² Unfortunately, re-authorization and/or expansion of SCHIP at the federal level faced substantial opposition from the executive co-operative in 2007.^19,63 SCHIP continues to be vulnerable, with current funding simply temporarily extended via short-term continuing resolutions. Concurrently, in the United States, the number of uninsured children is dramatically increasing—one in v U.S. children in poverty is uninsured.⁶⁴ If SCHIP is not reauthorized, let lonely expanded, many more children will face the pivotal bulwark of uninsurance.

Low-income parents who overcome the uninsurance barrier to obtain insurance coverage for their children will still face up concerns about gaining acceptable access to the health care system. Public cost containment efforts continually target reductions in public health insurance payments to providers, forcing providers in turn to limit the number of publicly-insured patients they serve. This cascade affects access. Even if insurance coverage is attainable for some low-income families, many of them have difficulty accessing necessary wellness care services and cannot afford medical intendance costs. Broader and more than comprehensive reforms, beyond those that incrementally expand coverage, are needed to ensure quality, cost-constructive, integrated intendance for U.S. children and adults.^65,66

Acknowledgments

Support: The study was funded by a grant from the Wellness Resources and Services Administration (HRSA) obtained past the Function for Oregon Health Policy and Research. Jen DeVoe'southward fourth dimension on this projection was supported by grant numbers v-F32-{"blazon":"entrez-nucleotide","attrs":{"text":"HS014645","term_id":"310672629","term_text":"HS014645"}}HS014645 and 1-K08-HS16181 from the Bureau for Health care Research and Quality (AHRQ). Alia Baez's time on this project was supported by a medical student research grant from the Oregon University of Family unit Physicians.

Appendix—Outcome Variables Pertaining to Unmet Wellness Care Needs for Children

Outcome variable	Respective Survey Question(s)
Unmet Medical Demand	• In the terminal 12 months, was there any time when YOUR  CHILD needed medical care, but did Non get it? [yes/no]
Unmet Prescription Need	• In the last 12 months, was in that location ever a fourth dimension YOUR Child  needed prescription medicines but you could Not afford to  fill the prescription? (DO NOT count gratuitous samples equally a filled prescription.) [yes/no]
Unmet Dental Need (Big Problem Getting Dental Care)	• In the terminal 12 months, how much of a problem, if whatever, was  information technology to go dental treat your kid? [dichotomized: big  problem, not a problem/small problem]
Delayed Urgent Care (Rarely or never Got Immediate Care)	• In the final 12 months, when YOUR CHILD needed intendance  right away for an illness, injury, or condition, how often did  your child get care as shortly equally you wanted information technology? INCLUDED  Choice TO OPT OUT IF CHILD DID NOT Need Care
	• [dichotomized: rarely/never; always/ordinarily]
No Doc Visits	• In the last 12 months, how many times did y'all take YOUR  Child to a doctor's part or clinic for care? (Exercise Non include emergency room or hospital visits. Your best estimate is fine.) [continuous variable, dichotomized as no medico  visits/yes doctor visits in past year]

Footnotes

Prior Presentations: Qualitative themes presented at Guild of Teachers of Family Medicine, Annual Coming together, April 28, 2007, Chicago; Conceptual Model presented at North American Primary Care Research Group Annual Coming together, October xv–18, 2007, Vancouver, British Columbia.

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