Factors Associated With Not Having a Personal Health

Transcription

Factors Associated With Not Having a Personal Health
SUPPLEMENT ARTICLE
Factors Associated With Not Having a Personal
Health Care Provider for Children in Florida
Mary Beth Zeni, ScDa, William Sappenfield, MD, MPHb, Dan Thompson, MPHb, Hailin Chen, MSb
a
College of Nursing, Florida State University, Tallahassee, Florida; bFlorida Department of Health, Family Health Services Division, Tallahassee, Florida
The authors have indicated they have no financial interests relevant to this article to disclose.
ABSTRACT
OBJECTIVE. National recommendations by the American Academy of Pediatrics and
the National Association of Pediatric Nurse Practitioners promote that all children
obtain quality primary care through a consistent medical provider who can better
assess, diagnose, and monitor a child’s health. The purpose of this article was to
identify characteristics of children in Florida without a personal health care provider.
METHODS. Florida data (N ⫽ 2116) from the 2003 National Survey of Children’s
Health were analyzed by using bivariate and multivariate methods. The dependent, or outcome, variable was a personal health care provider, defined in the
National Survey of Children’s Health as a personal doctor or nurse.
RESULTS. In Florida, 20.1% of children (0 –17 years of age) do not have a personal
health care provider compared with 16.7% in the United States. Children at
greatest risk are those without health insurance. Other significant risk factors
include family poverty up to 100% of federal poverty level, poverty level 100% to
199%, poverty level unknown, poverty level 200% to 399%, children aged 5 to 12
years, children aged 13 to 17 years, and Hispanic ethnicity. All the factors in the
Florida model were also significant in the national model.
www.pediatrics.org/cgi/doi/10.1542/
peds.2006-2089J
doi:10.1542/peds.2006-2089J
Key Words
children, primary health care
Abbreviations
AAP—American Academy of Pediatrics
NSCH—National Survey of Children’s
Health
OR— odds ratio
CI— confidence interval
Accepted for publication Sep 15, 2006
Address correspondence to Mary Beth Zeni,
ScD, Florida State University, College of
Nursing, 413 Duxbury Hall, Tallahassee, FL
32306. E-mail: mzeni@nursing.fsu.edu
PEDIATRICS (ISSN Numbers: Print, 0031-4005;
Online, 1098-4275); published in the public
domain by the American Academy of
Pediatrics
CONCLUSIONS. Lack of a personal health care provider is driven by larger community
issues of health insurance, socioeconomic status, and ethnicity, including race, on
a national level. To achieve the goal of a personal health care provider for children,
a multifaceted approach needs to be considered. Knowing which children are
without a personal health care provider provides valuable information for state
policy-makers, program planners, and evaluators.
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N
ATIONAL PROFESSIONAL ORGANIZATIONS, including
the American Academy of Pediatrics (AAP) and the
National Association of Pediatric Nurse Practitioners,
have established position statements to promote the attainment of quality primary care for all children and
adolescents through a personal doctor or nurse, or
through a personal health care provider.1,2 A personal
health care provider can consistently assess, diagnose,
and monitor a child’s health.3,4 The provider can ensure
continuity of care, offer a substantially higher level of
comprehensive care compared with children without a
personal doctor or nurse, and advance culturally effective care.5,6 A personal doctor or nurse who knows the
child can refer her/him for both basic preventive services, such as oral health care, and specialty services if
needed, such as speech and language evaluations, and
monitor the outcome of referrals.
It is more efficient for children and adolescents to
receive care from a personal doctor or nurse because the
provider knows the child and can quickly ascertain
changes in status and initiate treatment to prevent complications. The establishment of a personal doctor or
nurse may decrease inappropriate use of the emergency
department, further promoting effective use of health
care dollars.7
A personal health care provider is one of the characteristics of a medical home as defined in a 2004 AAP
policy statement.1 Healthy People 2010 data suggests that
93% of children and youth 17 years of age and younger
currently have a specific source of ongoing care, with the
goal to increase the percentage to 97% by the year
2010.8
It was recently reported that 43.0% of Florida children have a medical home compared with 46.1% of US
children aged 0 through 17 years of age, and that 83.3%
of these children have a personal doctor or nurse compared with 79.9% of Florida children.9
Although others have examined factors associated
with a medical home and components of a medical
home, especially in relation to children with special
health care needs,3,4 none have investigated the issue in
the context of the theoretical framework of Aday and
Andersen’s Access to Medical Care model.10 The Aday
and Andersen Access to Medical Care Model emphasizes
that health policy can affect 2 inputs: characteristics of
the health care delivery system and the populations at
risk. These 2 inputs can change the 2 outputs of the
model, the use of health care services and consumer
satisfaction with the services.10 Investigating characteristics of the population at risk may lead to effective
health policies that will improve use of health services.
Through the National Survey of Children’s Health
(NSCH), we were able to study Florida children at risk of
not having a personal health care provider.
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ZENI et al
METHODS
The data used for the study are from the public-use data
set for the 2003 NSCH, described briefly in the article by
Kogan and Newacheck11 in this issue. There were 2116
completed interviews in Florida. Human subjects approval was given by the Florida State University Institutional Review Board, and the study was deemed exempt
from review by the Florida Department of Health.
The dependent variable for the study was based on
the question: A personal doctor or nurse is a health care
professional who knows your child well and is familiar
with your child’s health history. This can be a general
doctor, a pediatrician, a specialist doctor, a nurse practitioner, or a physician assistant. Do you have 1 or more
persons you think of as [your child’s] personal doctor or
nurse? The 4 possible answers to this question were:
“yes,” “no,” “don’t know,” and “refused.” The latter 2
responses were treated as missing values (n ⫽ 7).
The independent variables for the study were selected
based on the 3 components of a population at risk in the
Access to Medical Care model: predisposing, enabling,
and need. The predisposing component includes variables that describe properties that exist before the onset
of an illness; the enabling component describes the
means and resources individuals and families have available to facilitate the use of services; and the need component refers to illness level.10 Additional variables were
selected from the survey that reflected contemporary
issues, such as whether the parents and/or child were
born in the United States, primary language, and
whether an interpreter is needed when accessing health
care.
Initially, a total of 22 independent variables were
selected. However, concerns about possible multicolinearity between child born in the United States, father
born in the United States, mother born in the United
States, primary language not English, and need for an
interpreter when accessing health care services resulted
in not including the above noted variables in the analysis. The results of the correlations analysis justified
using Hispanic ethnicity because relatively high correlation was noted with the following 4 variables for both
the US and Florida data sets: Hispanic, mother not born
in the United States, father not born in the United States,
and primary language not English.
Predisposing Factors
The following were predisposing factors:
● child’s age (defined as ⬍1, 1– 4, 5–12, or 13–17 years
of age);
● gender;
● ethnicity (defined as Hispanic or not Hispanic);
● race (defined as black, not black, or unknown);
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● family structure (defined as 2-parent family, meaning
2 biological parents or a biological/stepparent family,
and a single-parent family, meaning a 1-parent family); and
● education level of highest member in household (de-
fined as less than high school, high school graduate, or
more than high school).
Need Factors
The following were need factors:
● Presence of a moderate or severe chronic condition:
the child had to have at least one of the common acute
and chronic conditions listed in subdomain 3 of the
NSCH and a severity rating of moderate or severe. The
conditions included learning disability, emotional, behavioral, and physical conditions.
● Presence of a special health care need: a special health
care need was defined as the child needing 1 or more
of the 5 indicators from Children with Special Health
Care Need Screener in subdomain 2 of the NSCH:
prescription medications, special services, physical
limitation, special therapy, and counseling. The special
need lasted or was expected to last 12 months or
longer and was because of a medical, behavioral, or
other health condition.
Enabling Factors
The following were enabling factors:
● poverty status (defined as below poverty level, 100%–
199% poverty level, 200%–399% poverty level, poverty level unknown, or poverty level of ⱖ400%); and
● health insurance status (defined as health insurance
with no gaps in past year, health insurance with some
gaps in coverage the past year, or no health
insurance).
Statistical Analysis
SUDAAN software12 was used for the regression analysis
to account for the complex sampling survey design. SAS
software13 was also used to perform correlation functions
not available in SUDAAN. Scaled or normalized weights
were used for SAS functions such that the sum of the
scaled weights was equal to the unweighted sample size,
but the scaled weights were proportional to the complex
sample weights.
Regression analysis was used to assess the independent association of the selected variables of the Access to
Medical Care model with the dependent variable. The
independent variables were examined by using logistic
regression to estimate adjusted odds ratios (ORs) and
95% confidence intervals (CIs). Multicolinearity among
all of the variables was assessed by using Pearson’s correlation coefficient with scaled weights.
RESULTS
Sample and Population Characteristics
Overall, 20.1%, or an estimated 783 000, of Florida children ⬍18 years old did not have a personal health care
provider compared with 16.7%, or an estimated
12 078 000, nationally. A significant difference was
found between US and Florida children without a personal health care provider by using ␹2 analysis (P ⫽
.0008). Table 1 presents weighted frequencies of Florida
data for the dependent and independent variables in the
model.
Bivariate Findings
Table 2 presents the prevalence of no personal health
care provider by each individual variable. As a child’s age
increased, the likelihood of not having a personal health
care provider also increased. Florida children from
households with a high school education or less were
more likely to not have a personal health care provider
TABLE 1 Frequencies of Florida Children Without a Personal Health
Care Provider and Independent Variables
Variable
Total, no personal health care provider
Predisposing factors
Child age ⬍1 y
Child age 1–4 y
Child age 5–12 y
Child age 13–17 y
Male gender
Female gender
Hispanic ethnicity
Non-Hispanic ethnicity
Black race
Nonblack race
1-parent family
2-parent family
Highest education level in household less than
high school
Highest education level in household high
school
Highest education level in household greater
than high school
Need factors
Presence of a moderate or severe chronic
condition
No moderate or severe chronic condition
Presence of special health care need
No special health care need
Enabling factors
Family below poverty level
Family 100%–199% poverty level
Family 200%–399% poverty level
Family poverty level unknown
Family ⱖ400% poverty level
Health insurance with no gaps
Health insurance with gaps in past year
No health insurance
N
(Weighted)
%
(Weighted)
783 000
20.1
214 000
839 000
1 770 000
1 085 000
1 997 000
1 906 000
739 000
3 126 000
799 000
3 109 000
1 207 000
2 566 000
295 000
5.5
21.5
45.2
27.8
51.2
48.8
19.1
80.9
20.5
79.6
32.0
68.0
7.6
1 059 000
27.2
2 539 000
65.2
574 000
14.7
3 334 000
708 000
3 200 000
85.3
18.1
81.9
652 000
984 000
1 033 000
368 000
871 000
3 105 000
542 000
243 000
16.7
25.2
26.4
9.4
22.3
79.8
13.9
6.3
Data source: NSCH, 2003.
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TABLE 2 Prevalence of Florida Children Without a Personal Health
Care Provider by Predisposing, Need, and Enabling Factors
Variable
Predisposing factors
Child age ⬍1 y
Child age 1–4 y
Child age 5–12 y
Child age 13–17 y
Male gender
Female gender
Hispanic ethnicity
Non-Hispanic ethnicity
Black race
Nonblack race
1-parent family
2-parent family
Highest education level in household less than
high school
Highest education level in household high
school
Highest education level in high school above
high school
Need factors
Presence of a moderate or severe chronic
condition
No moderate or severe chronic condition
Presence of special health care need
No special health care need
Enabling factors
Family below poverty level
Family 100%–199% poverty level
Family 200%–399% poverty level
Family poverty level unknown
Family ⱖ400% poverty level
Health insurance with no gaps
Health insurance with gaps in past year
No health insurance
N
(Weighted)
%
(Weighted)
21 000
146 000
349 000
267 000
400 000
384 000
241 000
532 000
192 000
591 000
327 000
412 000
109 000
9.8
17.4
19.8
24.7
20.0
20.2
32.6
17.1
24.2
19.1
27.2
16.1
37.0
289 000
27.4
383 000
15.1
110 000
19.3
672 000
115 000
669 000
20.2
6.2
21.0
233 000
241 000
149 000
88 000
73 000
494 000
147 000
140 000
35.7
24.6
14.5
23.9
8.4
15.9
27.5
57.5
children who did not have health insurance in the last
12 months. The lack of a personal health care provider
was not noted for Florida children 1 to 4 years old
(borderline significant for adjusted only), reporting a
moderate or severe chronic condition, with a special
health care need, black, from households with a high
school education or less, and with health insurance gaps
in the past year.
Differences Between Florida and the United States
Nationally, we found similar findings in addition to the
following factors being significantly associated with not
having a personal health care provider: children 1 to 4
years old, black, from single parent families, from households with a high school education or less, and children
with gaps in health insurance coverage the past 12
months. US children with moderate or severe chronic
conditions and with a special health care need were
significantly less likely to not have a personal health care
provider (US analyses are available on request).
Among all possible pairs of the independent variables,
Pearson’s correlation coefficients (r) ⬎0.30 were found
for only 3 pairs of variables for Florida data: (a) less than
a high school education and federal poverty levels
⬍100% (0.32), (b) more than a high school education
and federal poverty level ⬍100% (0.33), and (c) more
than a high school education and federal poverty levels
⬎400% (0.34). Multicolinearity was noted among an
additional pair of US variables: less than a high school
education and Hispanic ethnicity (0.36). We decided
that the analytical value of these variables warranted
including them in the model, although the correlations
may result in larger CIs for the affected ORs.
Data source: NSCH, 2003.
compared with children from households with above a
high school education. Florida children with reported
gaps in health insurance coverage in the previous 12
months and those children with no health insurance
have a higher percentage of not having a personal health
care provider than did children with full health insurance coverage the past year. The percentage of Florida
children without a personal health care provider decreased as the family’s percentage above the federal
poverty level increased. Hispanic children were also at a
higher risk of not having a personal health care provider.
Multivariate Findings
Results of the multivariate logistic regression analysis are
provided in Table 3. Findings indicated the following
Florida children are significantly more likely to not have
a personal health care provider: children 5 to 17 years
old, of Hispanic ethnicity, from families below the federal poverty level, from federal poverty levels between
100% and 399% and from unknown poverty levels, and
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ZENI et al
DISCUSSION
The findings of this study support that mainly predisposing and enabling factors from the Access to Medical Care
model were associated with Florida children not having
a personal health care provider. Significant predisposing
factors were children between 5 and 17 years of age,
with adolescents at a higher risk, and Hispanic ethnicity.
Significant enabling factors associated with Florida children not having a personal health care provider included: children from households below the federal poverty level, 100% to 199% of poverty level, 200% to
399% of poverty level, and unknown poverty level.
Florida children with some health insurance coverage in
past year were more likely to have a personal health care
provider compared with children without insurance.
The findings support previous studies that a child’s
health status is not the only predictor of access to consistent health care and emphasize the need to implement
a multifaceted approach to ensure access for all children.4,14–16 Although the Florida findings did not note
significance with children who experienced gaps in
health care coverage in the past 12 months, significance
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TABLE 3 Characteristics of Florida Children Without a Personal Health Care Provider
Variable
Predisposing factors
Child age ⬍1 y
Child age 1–4 y
Child age 5–12 y
Child age 13–17 y
Male gender
Female gender
Hispanic ethnicity
Non-Hispanic ethnicity
Black race
Non-black race
1-parent family
2-parent family
Highest education level in household less than high school
Highest education in household high school
Highest education in household above high school
Need factors
Absence of a moderate or severe chronic condition
Presence of a moderate or severe chronic condition
Absence of special health care need
Presence of special health care need
Enabling factors
Family below poverty level
Family 100%–199% poverty level
Family 200%–399% poverty level
Family poverty level unknown
Family ⱖ400% poverty level
Health insurance with no gaps
No health insurance in past year
Health insurance with gaps in past year
Unadjusted OR
(95% CI)
Adjusted OR
(95% CI)
Referent
1.94 (0.96–3.94)
2.27 (1.17–4.42)
3.01 (1.54–5.90)
0.99 (0.75–1.31)
Referent
1.90 (1.33–2.71)
Referent
1.35 (0.94–1.95)
Referent
1.95 (1.46–2.62)
Referent
3.29 (2.01–5.40)
2.12 (1.55–2.91)
Referent
Referent
2.05 (1.01–4.16)
2.97 (1.51–5.85)
3.77 (1.90–7.50)
1.09 (0.80–1.47)
Referent
1.91 (1.34–2.73)
Referent
1.17 (0.76–1.80)
Referent
1.37 (0.97–1.92)
Referent
1.30 (0.71–2.39)
1.24 (0.84–1.84)
Referent
Referent
0.95 (0.64–1.42)
Referent
0.73 (0.50–1.08)
Referent
0.77 (0.47–1.25)
Referent
0.74 (0.46–1.19)
6.08 (3.82–9.70)
3.57 (2.31–5.51)
1.85 (1.20–2.86)
3.45 (2.00–5.94)
Referent
Referent
7.15 (4.45–11.50)
2.00 (1.36–2.93)
3.87 (2.15–6.94)
2.51 (1.50–4.22)
1.74 (1.09–2.76)
2.31 (1.25–4.25)
Referent
Referent
4.04 (2.45–6.67)
1.33 (0.88–2.01)
Data source: NSCH, 2003.
was noted in the US analysis. Previous studies have
noted that gaps in health insurance coverage are as
important a consideration as lack of health insurance.17,18
Studies have also documented the vulnerability experienced by children living in poverty, Hispanic children,
and black children in accessing health care.19 The needs
of adolescents for established medical care have been
documented in the literature.20
Limitations of the study include the respondents’ correct understanding of the question pertaining to personal health care provider and questions about health
conditions. Health conditions reported by parents or
guardians were not confirmed through review of medical documentation. Hispanic ethnicity did not take into
account cultural variations among groups who would
identify as Hispanic.
A personal health care provider is an important component of the concept medical home. The Aday and
Andersen Access to Medical Care model provides a conceptual framework to study access to a personal health
care provider through examining one of the inputs in
the model, characteristics of the population at risk,
through predisposing, enabling, and need factors.
Analyzing characteristics of the at-risk population (ie,
Florida children without a personal health care provider)
can lead to effective health policy and, ideally, evidencebased interventions. For example, the model proposes
that health policy influences the use of services by a risk
population. Availability of health insurance is one such
policy. Expanding child health insurance coverage
through adding the State Children’s Health Insurance
Program has been shown to increase the percentage of
children with a usual source of care.21 Such expansion
reduces the hospitalization rate of children for ambulatory care sensitive conditions because of improved access
to primary care.22 Important health policy considerations
for Florida include addressing the need for full health
insurance coverage for all children and maintaining uninterrupted health insurance coverage, especially as
Florida explores Medicaid and State Children’s Health
Insurance Program reforms.
Policy recommendations could be directed toward
children of Hispanic ethnicity or children living in poverty to ensure that vulnerable groups have a personal
health care provider. These populations are at moderateto-high risk for not having a personal provider, even
after adjusting for each other, race, household education, number of parents, and health insurance. Access to
health care for Hispanic/Latino children in the United
States reportedly varies by country or region of origin
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S65
and by generation resulting from immigration.23,24 Other
access barriers suggested beyond the ones identified in
this study include those related to the family: parental
health beliefs, health behaviors, source of health advice,
language problems, and cultural differences; and those
related to the provider: language services, provider practices and behaviors, cultural competency, impaired quality of care, excessive waiting times, and proportionately
fewer Hispanic health professionals.25,26 These issues suggest potential actions by both policymakers and providers in Florida. Another limitation of this study was that
health insurance and income were the few enabling
study variables available. Enabling factors are perceived
to be more mutable and able to improve access.27 Future
studies can address additional components of the Aday
and Andersen model, such as the overall ability to access
needed health care services and satisfaction with services
received.
Another group in Florida at high risk for not having a
personal provider is adolescents. Before the onset of
sexual activity, teens generally need and use fewer preventive health services than young children. In other
communities, not having a personal provider frequently
relates to the variety of providers that teens can use and
the potential use of different providers for different
needs.28 Care for medically emancipated conditions and
confidential services for adolescents are limited among
primary care practices and significant disagreement between office staff and physicians over policies have been
shown.29 Adolescents frequently do not receive needed
care because of hiding issues from parents, potential
costs, and time constraints.30 Health care alternatives are
needed for Florida adolescents to ensure access to health
care.
The Access to Medical Care Model can also identify
strengths in current health policy. The findings that Florida children with a moderate or severe chronic condition
and children with a special health care need did not
significantly lack a personal health care provider could
be viewed as an asset, because the results suggest current
health policy and programs are ensuring that children
with greater health care needs have access to a personal
health care provider.
CONCLUSIONS
Pediatricians and collaborators can advocate to ensure
that all children and adolescents have access to a personal health care provider. The NSCH can assist states
and regions to study children at risk for not having a
personal provider. Results from analyses can provide the
foundation to support the development of evidencebased health policy.
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PEDIATRICS Volume 119, Supplement 1, February 2007
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S67
Factors Associated With Not Having a Personal Health Care Provider for
Children in Florida
Mary Beth Zeni, William Sappenfield, Dan Thompson and Hailin Chen
Pediatrics 2007;119;S61
DOI: 10.1542/peds.2006-2089J
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PEDIATRICS is the official journal of the American Academy of Pediatrics. A monthly
publication, it has been published continuously since 1948. PEDIATRICS is owned, published,
and trademarked by the American Academy of Pediatrics, 141 Northwest Point Boulevard, Elk
Grove Village, Illinois, 60007. Copyright © 2007 by the American Academy of Pediatrics. All
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Downloaded from pediatrics.aappublications.org by guest on February 6, 2015
Factors Associated With Not Having a Personal Health Care Provider for
Children in Florida
Mary Beth Zeni, William Sappenfield, Dan Thompson and Hailin Chen
Pediatrics 2007;119;S61
DOI: 10.1542/peds.2006-2089J
The online version of this article, along with updated information and services, is
located on the World Wide Web at:
http://pediatrics.aappublications.org/content/119/Supplement_1/S61.full.html
PEDIATRICS is the official journal of the American Academy of Pediatrics. A monthly
publication, it has been published continuously since 1948. PEDIATRICS is owned,
published, and trademarked by the American Academy of Pediatrics, 141 Northwest Point
Boulevard, Elk Grove Village, Illinois, 60007. Copyright © 2007 by the American Academy
of Pediatrics. All rights reserved. Print ISSN: 0031-4005. Online ISSN: 1098-4275.
Downloaded from pediatrics.aappublications.org by guest on February 6, 2015