Quality of Primary Care for Children With Disabilities Enrolled in Medicaid

Quality of Primary Care for Children With Disabilities Enrolled in Medicaid Alyna T. Chien, MD, MS; Karen A. Kuhlthau, PhD; Sara L. Toomey, MD, MPhil, MPH, MSc; Jessica A. Quinn, MS; Megumi J. Okumura, MD, MAS; Dennis Z. Kuo, MD, MHS; Amy J. Houtrow, MD, PhD, MPH; Jeanne Van Cleave, MD; Mary Beth Landrum, PhD; Jisun Jang, MA; Isabel Janmey, BS; Michael J. Furdyna, BA; Mark A. Schuster, MD, PhD From the Division of General Pediatrics, Department of Medicine (Drs Chien, Toomey, Ms Quinn, Dr Schuster), The Clinical Research Center (Ms Jang), Boston Children’s Hospital, Department of Pediatrics (Drs Chien, Kuhlthau, Toomey, Van Cleave, Schuster), Department of Health Care Policy (Dr Landrum), Harvard Medical School, Center for Child and Adolescent Health Research and Policy, Department of General Pediatrics, Massachusetts General Hospital for Children (Drs Kuhlthau, Van Cleave), Boston, Mass; Division of General Pediatrics, University of California San Francisco Beinoff Children’s Hospital (Dr Okumura); Division of General Pediatrics, Department of Pediatrics, University of California San Francisco School of Medicine (Dr Okumura), San Francisco, Calif; Department of Pediatrics, University of Arkansas for Medical Sciences College of Medicine, Little Rock, Ark (Dr Kuo); Division of Pediatric Rehabilitation Medicine, Children’s Hospital of Pittsburgh (Dr Houtrow); Department of Physical Medicine and Rehabilitation, University of Pittsburgh School of Medicine (Dr Houtrow), Pittsburgh, Pa; Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa (Mr Furdyna); and Case Western Reserve University School of Medicine, Case Western Reserve University, Cleveland, Ohio (Ms Janmey) Conflict of Interest: The authors declare that they have no conflict of interest. Address correspondence to Alyna T. Chien, MD, MS, Division of General Pediatrics, Department of Medicine, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115-5737 (e-mail: [email protected]). Received for publication May 2, 2016; accepted October 28, 2016.

ABSTRACT OBJECTIVE: The quality of primary care delivered to Medicaid-insured children with disabilities (CWD) is unknown. We used the newly validated CWD algorithm (CWDA) to examine CWD prevalence among Medicaid enrollees 1 to 18 years old, primary care quality for CWD, and differences in primary care quality for CWD and non-CWD. METHODS: Cross-sectional study using 2008 Medicaid Analytic eXtract claims data from 9 states, including children with at least 11 months of enrollment (N ¼ 2,671,922 enrollees). We utilized CWDA to identify CWD and applied 12 validated or endorsed pediatric quality measures to assess preventive/screening, acute, and chronic disease care quality. We compared quality for CWD and non-CWD unmatched and matched on age, sex, and number of nondisabling chronic conditions and outpatient encounters. RESULTS: CWDA identified 5.3% (n ¼ 141,384) of our study population as CWD. Care quality levels for CWD were below 50% on 8 of 12 quality measures (eg, adolescent well visits

[44.9%], alcohol/drug treatment engagement [24.9%]). CWD care quality was significantly better than the general population of non-CWD by þ0.9% to þ15.6% on 9 measures, but significantly worse for 2 measures, chlamydia screening (3.4%) and no emergency department visits for asthma (5.0%; all P < .01 to .001). Differences in care quality between CWD and nonCWD were generally smaller or changed direction when CWD were compared to a general population or matched group of non-CWD. CONCLUSIONS: One in 20 Medicaid-insured children is CWD, and the quality of primary care delivered to CWD is suboptimal. Areas needing improvement include preventive/screening, acute care, and chronic disease management.

KEYWORDS: children; disabilities; Medicaid; pediatrics; quality of care

ACADEMIC PEDIATRICS 2016;-:1–7

WHAT’S NEW

various barriers may hinder their full and effective participation in society on an equal basis with others.”1,2(p4) Current population surveys that use World Health Organization and United Nations concepts and definitions find that the prevalence of CWD in the United States is 5% to 8% and rising.3–5 CWD account for a substantial proportion of spending in Medicaid, and their spending is increasing.6,7 Like all children, as well as vulnerable subpopulations of children, CWD benefit from high-quality primary care; all children require appropriate preventive, acute, and chronic disease care to avoid or mitigate illness.8 High-quality primary care may have an even greater

A total of 5.3% of Medicaid-insured children are children with disabilities, and care quality for this population is suboptimal on 8 of 12 validated or endorsed pediatric quality measures. Preventive/screening, acute care, and chronic disease management all need improvement.

CHILDREN

WITH DISABILITIES (CWD) have been defined by the World Health Organization and United Nations as children with “long-term physical, mental, intellectual or sensory impairments which in interaction with

ACADEMIC PEDIATRICS Copyright ª 2016 by Academic Pediatric Association

1

Volume -, Number -–- 2016

2

CHIEN ET AL

impact on CWD because of their multiple vulnerabilities or lack of reserves—for example, missing a high lead level for CWD may worsen existing intellectual limitations or functional abilities.9 Until recently, in order to glean a population-level understanding of care quality for CWD, stakeholders had to extrapolate from single-center studies focused on children with a particular diagnosis (eg, autism, hearing impairment),10,11 national studies of children with special health care needs who may have chronic but not necessarily disabling conditions (eg, eczema),12,13 or from investigations of quality of care for adults with disabilities.14,15 Available studies suggest that CWD may not be receiving recommended primary care if physicians are focused on the underlying disabling condition at the expense of preventive care (eg, children with spina bifida not receiving immunizations) or if they systematically underestimate the needs of CWD (eg, screening for sexually transmitted infections).16–19 Conversely, other studies have shown that CWD may be receiving elements of recommended primary care at higher rates if their higher levels of utilization are associated with receiving elements of recommended primary care.6,7,20,21 Through the Children’s Health Insurance Program Reauthorization Act (CHIPRA) of 2009, the tool needed to identify CWD became available, allowing us to examine whether large populations of CWD are systematically receiving recommended elements of primary care quality.22 The Children with Disabilities algorithm (CWDA), published last year, allows stakeholders to use claims data to identify CWD, a distinct subgroup of children separate from those with acutely complex illnesses or chronic but not disabling conditions.22 CWDA can be used with a set of claims-based primary care measures considered clinically important has been validated by pediatric clinicians and researchers and endorsed for public use. These measures are beginning to form the basis of payment in Medicaid and commercial contracts, so it is important to see the degree to which CWD receive these elements of care.12,21,23–25 In addition, claims data that include care delivered across care settings (primary care and specialty) and institutions (community and hospitalbased) are increasingly available for public use, although the availability of Medicaid claims tends to lag behind that for Medicare and commercial plans. The new opportunity to examine primary care quality for large populations of CWD also opens the door for comparing care for CWD to non-CWD groups. If care quality for CWD is broadly comparable to care for non-CWD, then improving care quality for CWD may be tightly related to improving care for children generally. If care quality is worse for CWD than non-CWD for certain elements of care, then improvement efforts may need to target CWD more specifically. If care quality for CWD is better than non-CWD, then perhaps care delivery for CWD may provide insight into how to improve care for non-CWD. In this study, we focused on children insured by Medicaid because Medicaid disproportionately insures CWD and children living at or near the federal poverty

ACADEMIC PEDIATRICS

line.6,26–28 Specifically, the goals of this study were to examine the prevalence of CWD among Medicaid enrollees; the primary care quality for CWD using endorsed and commonly used primary care quality measures; and the differences in care quality for CWD and non-CWD in analyses that reflect non-CWD who are clinically similar to CWD except for a disabling condition, as well as non-CWD who reflect the general population of children without disabilities.

PATIENTS AND METHODS STUDY DESIGN AND DATA SOURCE We implemented a cross-sectional study design using deidentified 2008 Medicaid Analytic eXtract (MAX) claims data from 9 states (Arizona, Indiana, Kansas, Kentucky, Missouri, New Jersey, New Mexico, Virginia, Wisconsin) whose data quality was deemed usable for research by Medicaid; we did not use data from states that had substantial missing (eg, lacked outpatient claims in their data sets) or incomplete (eg, no data in the International Classification of Diseases, 9th Revision [ICD-9], fields) information.29,30 We excluded enrollees with incomplete claims data due to insurance benefit design (eg, those with dual eligibility, waivers, or plans with restricted benefits such as family planning services only). We could not include children enrolled in the Children’s Health Insurance Programs because these data were not available. Of the 4,170,199 one- to 18-year-old enrollees remaining, we included the 2,671,922 with $11 months of enrollment because the quality measures are assessed on an annual basis. Enrollees could be in either fee-for-service or managed care plans. This study was approved by the Boston Children’s Hospital institutional review board. STUDY POPULATION AND INDEPENDENT VARIABLES We used MAX variables for age, sex, and race/ethnicity (Table 1). Children were considered to be CWD if their MAX data contained at least one of the 669 ICD-9 codes in CWDA.22 CWDA was developed using the World Health Organization and United Nations definitions of disability and was focused on identifying ICD-9 codes with a $75% likelihood of representing long-term functional impairment (eg, profound intellectual disabilities, bilateral sensory hearing loss, Down syndrome).22 In contrast to other algorithms, CWDA unifies a clinically heterogeneous group of diagnoses according to their likelihood of experiencing limitations in function, thereby facilitating studies that researchers have not otherwise been able to conduct because of extremely low prevalence levels of individual diagnoses.22 Because CWD can also have nondisabling chronic conditions (eg, allergic rhinitis, lactose intolerance), we used the Agency for Healthcare Research and Quality’s Chronic Condition Indicator (CCI) tool to describe the number of chronic nondisabling conditions co-occurring among CWD and non-CWD groups within our study population.31 We removed the CCI codes that appeared in CWDA and then calculated the percentage of CWD and non-CWD

ACADEMIC PEDIATRICS

QUALITY OF PRIMARY CARE

Table 1. Study Population: 2008 Medicaid Analytic eXtract Data From 9 States Characteristic

CWD, n (%)

Prevalence 141,384 (5.3) Age* 1–5 y 42,290 (29.9) 6–12 y 61,339 (43.4) 13–18 y 37,755 (26.7) Male sex* 90,337 (63.9) Race/ethnicity* White 71,302 (50.4) Black 24,704 (17.5) Hispanic 21,218 (15.0) Native American 3,823 (2.7) Asian/Pacific Islander 1,314 (0.9) Other/unknown 19,023 (13.5) Non-CWDA CCI*† 0 CCI 30,808 (21.8) 1 CCI 47,575 (33.7) 2 CCIs 31,584 (22.3) 3 CCIs 16,334 (11.5) 4þ CCIs 15,083 (10.7) No. of outpatient encounters in year*‡ 0–1 15,773 (11.2) 2–3 19,342 (13.7) 4–8 37,486 (26.5) 9þ 68,783 (48.7) Had emergency department 51,238 (36.2) visit in year*

Non-CWD, n (%) 2,530,538 (94.7) 755,561 (29.9) 1,047,154 (41.4) 727,823 (28.8) 1,272,566 (50.3) 1,133,363 (45.2) 618,564 (24.4) 552,403 (21.8) 86,228 (3.4) 40,610 (1.6) 88,370 (3.5) 1,545,557 (61.1) 684,531 (27.1) 218,401 (8.6) 60,011 (2.4) 22,038 (0.9) 895,236 (35.4) 634,487 (25.1) 655,487 (25.9) 345,328 (13.7) 692,621 (27.4)

CWD indicates children with disabilities; and CCI, chronic condition indicator. Data are for 2,671,922 subjects (Arizona, Indiana, Kansas, Kentucky, Missouri, New Jersey, New Mexico, Virginia, and Wisconsin). †Non-CWDA chronic conditions (ie, CCI34 codes). ‡Excluding emergency department visits. *P < .001.

groups with 0, 1, 2, 3, and 4þ non-CWDA CCIs (ie, chronic conditions that are not indicative of disability). QUALITY MEASURES We used all available validated or endorsed claimsbased pediatric measures to assess preventive services (eg, recommended well-visits, chlamydia screening), acute illness care (eg, appropriate treatment of upper respiratory infections), and common chronic disease management (eg, follow-up attention-deficit/hyperactivity disorder [ADHD] care after stimulant prescription).32,33 These claims-based measures of pediatric primary care have been reviewed and validated by expert panels of pediatricians, endorsed by quality entities like the National Quality Forum, and highlighted for use by state and federal organizations (eg, the Center for Medicare and Medicaid Services).23–25 Medicaid and commercial health plans are using these measures in pay-for-performance and alternative quality contracts (Table 2 and Online Appendix).23–25 We followed Healthcare Effectiveness Data and Information Set (HEDIS) specifications and oriented all measures so that lower values indicate poorer-quality care and divided the number of children who had claims corresponding to the recommended element by the total number of children who were eligible for each measure to calculate the percent per-

3

formance level. In total, we examined preventive/screening services (4 measures), acute conditions (2 measures), and chronic disease (6 measures total across 3 conditions: asthma, ADHD, and alcohol/drug dependence).32 We included care delivered in any outpatient setting so that if elements of recommended primary care are being delivered by specialists, it is reflected in these measures. CWD COMPARISONS TO UNMATCHED NON-CWD AND MATCHED NON-CWD We compared rates of primary care quality between CWD and 2 different populations of non-CWD: first, an unmatched group of non-CWD who represent the general population of non-CWD, and second, a matched group of non-CWD who are similar to CWD except in the disabling condition. The comparison of CWD with the matched sample of non-CWD provides the ability to compare care quality net of differences in the characteristics used for matching. When we matched, we used information about: demographics (age 1 year, sex), chronic conditions (number of non-CWD chronic conditions captured via CCIs), and number of outpatient encounters in a year; we did not match on race/ethnicity. We observed how differences in care quality may vary depending on who was being used for comparison. STATISTICAL ANALYSIS For our first aim of assessing CWD prevalence in Medicaid, we used CWDA to identify the number of children with at least one CWDA-qualifying code in 2008. For our second aim of evaluating primary care quality for Medicaid-insured CWD, we followed HEDIS specifications for the subset of children with at least one CWDAqualifying code to calculate rates of primary care quality in this population of Medicaid-insured children. For our third aim, we used a 1-to-1 matching scheme to avoid collinearity among matching variables. We calculated the difference between CWD and nonCWD quality such that positive values represent that CWD were receiving better care quality than non-CWD and negative values represent that CWD were receiving worse quality of care than non-CWD. We used chisquare and McNemar’s tests to assess the significance of the differences for unmatched and matched samples, respectively. We used SAS 9.3 (SAS Institute, Cary, NC) and P < .05 to test significant associations. We examined the degree to which the CWD and nonCWD quality comparisons were consistent across both unmatched and matched analyses to provide insight into the role utilization may hold for differences in care quality. When performance rate differences between CWD and non-CWD are similar when compared to the general population of non-CWD as well as the matched group of non-CWD, then it suggests that utilization does not play a substantial role in the quality difference. When the performance rate differences between CWD and non-CWD are substantially different when compared to the general population of non-CWD and the matched group of

4

CHIEN ET AL

ACADEMIC PEDIATRICS

Table 2. Pediatric Primary Care Quality Measures Measure

Description

Prevention/screening Well visits, child Well visits, adolescents Chlamydia screening Lead screening Acute care Strep pharyngitis testing Upper respiratory infection treatment Asthma No ED visit Asthma controller medication ADHD Initiation follow-up Subsequent follow-up Alcohol/drug dependence Treatment initiation Treatment engagement

Percentage of enrollees during measurement year who had at least: One well-child visits with primary care physician. One comprehensive well-care visit. One test for chlamydia (female patients only). One capillary or venous lead blood test by their second birthday. Percentage of enrollees who were not dispensed antibiotic for: Group A streptococcus (Strep) pharyngitis without Strep test. Upper respiratory infection. Percentage of enrollees with asthma during measurement year who: Did not have visit to ED for asthma. Were dispensed controller medication for persistent asthma for at least 50% of available treatment period within year. Percentage of enrollees with ADHD as of Index Prescription Start Date who had: At least 1 follow-up visit with practitioner within 30 d of starting stimulant. At least 2 follow-up visits with practitioner within 270 d after initiation period. Percentage of enrollees with new episode of alcohol/drug dependence who had: At least 1 alcohol/drug treatment encounter within 14 d of initial diagnosis. Two or more additional alcohol/drug treatment encounters within 30 d of initial diagnosis.

Age Group, y 3–6 12–18 16–18 1–2 2–18 1–18 5–18 5–18

6–12 6–12 13–17 13–17

ADHD indicates attention-deficit/hyperactivity disorder; ED, emergency department; and Strep, group Streptococcus.

non-CWD (eg, switch signs), it may suggest that utilization is playing a role in quality performance.

RESULTS STUDY POPULATION CWDA identified 5.3% (n ¼ 141,384) of Medicaidenrolled children from 9 states as CWD (Table 1). CWD and the general population of non-CWD differed in significant but small ways in terms of age (CWD group was slightly younger), gender (more boys among CWD), and race/ethnicity (more children with white race/ethnicity among CWD). CWD also tended to have at least one or more nondisabling CCIs, but having multiple CCIs did not necessarily signify CWD (eg, 82.6% of children with two or more CCIs were not CWD). A significantly greater proportion of CWD had more than one outpatient encounter in the year when compared to the general population of non-CWD (88.8% vs 64.6%, respectively); CWD were also significantly more likely than unmatched nonCWD to visit the emergency department (ED) for any reason (36.2% vs 27.4%, respectively). All P values were <.001. CWD and the matched non-CWD had the same distribution of age, gender, race/ethnicity, and number of nondisabling CCIs (data not shown). CARE QUALITY FOR CWD CWD received recommended care at rates below 50% on 8 of 12 recommended care measures (Table 3): adolescent well visits (44.9%), chlamydia screening (42.5%), lead screening (47.3%), group Streptococcus (Strep) testing before pharyngitis treatment (48.4%), no ED visits for asthma (48.8%), both follow-up measures for ADHD (48.5% after initial visit, 47.5% subsequently), and alcohol/drug treatment engagement (24.9%). CWD care levels were between 50% to 75% for 3 of 12 measures: recommended number of child well visits (64.7%), controller

medications for asthma for at least half of the treatment period (55.7%), and alcohol/drug treatment initiation (51.5%). CARE QUALITY FOR CWD VERSUS NON-CWD When compared to the general population of non-CWD, care quality for CWD was significantly better than that for non-CWD for 4 of 6 measures of prevention/screening and acute care and 5 of 6 measures of chronic disease management (P < .01 to .001 for all; Figure). When compared to the matched group of non-CWD, care quality for CWD was significantly worse than that for non-CWD on 4 of 6 measures of prevention/screening and acute care, but significantly better than that for non-CWD on 5 of 6 measures of chronic disease management (P < .01 to .001 for all; Figure). For 5 measures, comparative assessments of care quality for CWD versus non-CWD changed sign or became nonsignificant when we compared CWD to the general population of non-CWD rather than matched non-CWD. For example, for child well visit rates, CWD received recommended care more frequently than unmatched non-CWD, but less frequently than matched non-CWD (þ6.1% unmatched, P < .001; 0.9% matched, P ¼ .006). For the appropriate upper respiratory infection treatment, differences in care quality between CWD and non-CWD lost significance when between matched and unmatched comparisons (0.6% matched, P ¼ .12; þ0.9% unmatched, P ¼ .003). Considering ED visits for asthma, CWD were significantly more able to avoid the ED in matched comparisons (þ6.0%, P < .001), but significantly less able to avoid ED visits for asthma than non-CWD in unmatched comparisons (5.0%, P < .001). For alcohol/drug treatment engagement, CWD appeared to be significantly less likely to be engaged in treatment in matched comparisons (0.9%, P ¼ .04) and more likely to be engaged in alcohol/drug treatment in unmatched comparison (þ2.6%, P ¼ .004).

ACADEMIC PEDIATRICS

QUALITY OF PRIMARY CARE

5

Table 3. Performance on Primary Care Quality Measures for CWD Non-CWD Unmatched

CWD Performance Measure Prevention/screening Well visit, child Well visit, adolescent Chlamydia screening Lead screening Acute care Strep pharyngitis testing Upper respiratory infection treatment Asthma No emergency department visits Asthma controller medication Attention-deficit/hyperactivity disorder Initiation follow-up Subsequent follow-up Alcohol/drug dependence Treatment initiation Treatment engagement

Matched*

n

%

n

%

P

n

%

P

41,981 44,500 2,944 9,313

64.7 44.9 42.5 47.3

717,749 859,619 70,627 174,350

58.7 37.4 45.8 44.9

<.001 <.001 <.001 <.001

41,150 44,491 2,944 8,982

65.6 44.6 48.8 42.2

.006 .3956 <.001 <.001

5,232 12,232

48.4 90.2

85,747 157,733

48.7 89.3

.69 .003

5,228 12,143

51.7 90.7

<.001 .12

7,145 6,592

48.8 55.7

56,374 53,145

53.8 40.1

<.001 <.001

6,495 6,472

46.9 48.7

<.001 <.001

11,718 11,157

48.5 47.5

75,537 74,195

40.2 38.7

<.001 <.001

11,606 11,047

42.9 41.9

<.001 <.001

2,868 2,868

51.5 24.9

10,658 10,658

41.0 22.3

<.0001 .004

2,828 2,828

45.9 27.1

<.001 .04

CWD indicates children with disabilities; and Strep, group Streptococcus. *Matched non-CWD with CWD for age, sex, number of chronic conditions, and number of outpatient encounters.

DISCUSSION This study fills several long-standing gaps in our understanding of care quality for CWD. To begin, it provides the first claims-based estimate of CWD prevalence among Medicaid enrollees. Our identification of 5.3% of 2008 Medicaid-enrolled children as being CWD is on par with survey-based estimations of CWD conducted during the same period of time,4,5 suggesting some consistency of results between two very different methods for identifying CWD. Second, to our knowledge, it is the first study to document the degree to which Medicaid-insured CWD are receiving recommended primary care across a broad range of measures that span the scope of primary care (preventive/screening, acute, and chronic care).10,14–19,21 It is highly concerning that less than half of Medicaidenrolled CWD experience recommended care on 8 of 12 measures. While levels of care are comparably suboptimal for both CWD and non-CWD groups, such gaps in preventive, acute, and chronic disease care may have a greater impact on CWD because of their multiple vulnerabilities or lack of reserves (eg, missing a high lead level for CWD may worsen existing intellectual limitations and compound existing difficulties with functional ability).9 Third, this study adds nuance to prior concerns that providers may routinely underdeliver preventive/screening services to CWD.14–19 Whether compared to the general population of children without disabilities or children who are matched on key demographic, nondisabling clinical, and utilization characteristics, CWD are significantly less likely to receive chlamydia screening than non-CWD, as previously conjectured,16 and more likely to receive lead screening than their non-CWD counterparts. Awareness of the contrast in preventive/screening performances (eg, lead screening is conducted in toddler-

aged children and only requires parental consent, whereas chlamydia screening is performed in adolescents from whom exposure information and consent may be difficult to gather from those with a disability) can suggest potential reasons for differences in care quality. The fact that there is substantial room for improvement in the areas of chronic disease care suggests that stakeholders will need to improve chronic disease care for CWD. This is the case even if those conditions are not the disabling condition and even though CWD may receive modestly higher quality chronic disease care than non-CWD on available measures for asthma and ADHD (even achieving fewer ED visits for CWD with asthma on matched comparisons). However, the mixed performance on alcohol/drug treatment measures demonstrates that care quality for one condition may not confer quality for another. Importantly, our study illustrates how stratifying quality assessments by populations of interest and matching them on key characteristics allows us to increase our awareness of issues that might be systemic for CWD. When compared to the general population of non-CWD, care quality for CWD was significantly worse than that for non-CWD for 2 measures: chlamydia screening (3.4%) and no ED visits for asthma (5%) (both P < .001). However, when CWD are similar to non-CWD in age, sex, number of nondisabling chronic conditions and utilization, the number of quality measures for which care quality is better for CWD than non-CWD and the magnitude by which that quality is better diminishes substantially. As payment reforms continue to move toward capitated or global payments,12 those interested in improving care quality for CWD and closing gaps in care between CWD and non-CWD groups will have to ask if and how the delivery system can deliver a greater number of care elements within the same number of face-to-face encounters.

6

CHIEN ET AL

ACADEMIC PEDIATRICS Non-CWD Unmatched on Age, Sex, Chronic Conditions and Encounters Non-CWD Matched on Age, Sex, Chronic Conditions and Encounters

* p < .05 CWD receive better care

CWD receive worse care

PREVENTION/SCREENING Well-Visits Child Well-Visits Adolescent

+7.5 ***

+0.3 -6.4 ***

*** p < .001

+6.1***

-0.9 **

Chlamydia Screening

** p < .01

-3.4 *** +2.4 ***

Lead Screening

+5.6 ***

ACUTE CARE Pharyngitis Testing

-3.3 ***

Upper Respiratory Infection Treatment

-0.3 + 0.9 **

-0.6

ASTHMA

-5 ***

No ED Visits for Asthma

+1.9 ***

Asthma Controller Medication

+15.6 ***

+ 7 ***

ATTENTION DEFICIT HYPERACTIVITY DISORDER

ADHD Initiation Follow-up

+5.6 ***

ADHD Continuation Follow-up

+5.7 ***

+ 8.3 *** + 8.8 ***

ALCOHOL/DRUG DEPENDENCE Alcohol/Drug Treatment Initiation

+10.5 ***

+ 5.6 ***

Alcohol/Drug Treatment Engagement

+ 2.6 **

-2.2 * -10

-5

0

5

10

15

20

Figure. Matched and unmatched differences in care quality between CWD and non-CWD.

Our study has several limitations. First, this study examines care quality for children insured by Medicaid in 9 states with data quality deemed usable for research.29,30 The quality of care experienced by children who are not continuously insured, insured in states without Medicaid claims of suitable quality to be used for research, by other insurance sources, or in more recent years may be different from what we describe here. Second, validated pediatric primary care quality measures in common use still do not address all aspects of primary care quality that may be important to children generally or to CWD specifically, as outlined by the Institute of Medicine.34–36 It is vital to examine other dimensions of care quality (eg, access, experience of care) for CWD. As required by the available claims-based measures, this study examines care quality for children insured by Medicaid for at least 11 months within a year. It is unclear how shorter periods of Medicaid insurance may affect quality assessment, but any potential bias introduced by those who are continuously insured by Medicaid is likely to affect CWD and non-CWD groups equally.23–25 Last, although the overall prevalence of CWD identified by CWDA is on par with survey-based estimations of CWD, the methods for ascertaining specific conditions are different enough that we are not able to directly compare rates of individual diagnoses. We focus our attention on the year 2008 because it was the most recent year of Medicaid data available when all the CWD-relevant tools became available, so it reflects the earliest time point that this study could have feasibly been done; and because it reflects a point in time just before

the passage of the child-oriented CHIPRA of 2009 and the adult-oriented Affordable Care Act of 2010, so serves as a benchmark for postreform observations. Opportunities to use large claims-based datasets to study care quality for large populations are becoming increasingly available. We illustrate here that CWDA has the potential to highlight whether there are systemic problems for CWD. Future large-scale assessments like this one are likely to provide patients, physicians, and policy makers (especially those with an interest in Medicaid and Supplemental Security Income populations)6 with the ability to appreciate the scale of the quality challenges facing CWD and allow these stakeholders to create effective, data-driven improvement plans for CWD as a group like they have for those with specific diagnoses (eg, ImproveCareNow for patients with inflammatory bowel disease).37

CONCLUSIONS We used a newly developed claims-based algorithm to establish the prevalence of CWD among child enrollees of Medicaid from 9 states. Primary care quality for CWD is suboptimal across a range of services—preventive/ screening, acute, and chronic. Greater utilization of the health care system among CWD may confer greater opportunities to deliver quality health care, but providers should also consider methods for increasing the content of care during existing visits. We hope that inquiries like this can alert stakeholders—patients, their families, clinicians, public health and quality reporting officials, and state Medicaid

ACADEMIC PEDIATRICS

officers—to the quality needs of CWD and ultimately lead to care improvements for CWD and non-CWD alike.

ACKNOWLEDGMENTS Supported in part by the US Department of Health and Human Services Agency for Healthcare Research and Quality and Centers for Medicare & Medicaid Services, CHIPRA Pediatric Quality Measures Program Centers of Excellence (grant U18 HS 020513; PI, Mark A. Schuster, MD, PhD).

SUPPLEMENTARY DATA Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.acap.2016.10.015.

REFERENCES 1. World Health Organization. International Classification of Functioning, Disability, and Health: ICF. Geneva: World Health Organization; 2001. 2. United Nations. Convention on the Rights of Persons With Disabilities and Optional Protocol. Available at: http://www.un.org/disabilities/ documents/convention/convoptprot-e.pdf; 2006. Accessed September 22, 2015. 3. US Census Bureau. Disability Characteristics. 2013 American Community Survey 1-Year Estimates. Available at: http://factfinder.census. gov/faces/tableservices/jsf/pages/productview.xhtml?pid¼ACS_13_ 1YR_S1810&prodType¼table; 2013. 4. Houtrow AJ, Larson K, Olson LM, et al. Changing trends of childhood disability, 2001–2011. Pediatrics. 2014;134:530–538. 5. Halfon N, Houtrow A, Larson K, et al. The changing landscape of disability in childhood. Future Child. 2012;22:13–42. 6. Kuhlthau K, Perrin JM, Ettner SL, et al. High-expenditure children with Supplemental Security Income. Pediatrics. 1998;102(3 pt 1): 610–615. 7. Newacheck PW, Inkelas M, Kim SE. Health services use and health care expenditures for children with disabilities. Pediatrics. 2004; 114:79–85. 8. American Academy of Pediatrics Committee on Practice and Ambulatory Medicine; Bright Futures Periodicity Schedule Workgroup. 2016 recommendations for preventive pediatric health care. Pediatrics. 2016;137:1–3. 9. Canfield RL, Henderson CR, Cory-Slechta DA, et al. Intellectual impairment in children with blood lead concentrations below 10 microg per deciliter. N Engl J Med. 2003;348:1517–1526. 10. Megargel E, Broder-Fingert S. Autism and hospitals: a difficult match. Acad Pediatr. 2012;12:469–470. 11. Boss EF, Niparko JK, Gaskin DJ, et al. Socioeconomic disparities for hearing-impaired children in the United States. Laryngoscope. 2011; 121:860–866. 12. Chien AT, Song Z, Chernew ME, et al. Two-year impact of the alternative quality contract on pediatric health care quality and spending. Pediatrics. 2014;133:96–104. 13. Mangione-Smith R, DeCristofaro AH, Setodji CM, et al. The quality of ambulatory care delivered to children in the United States. N Engl J Med. 2007;357:1515–1523. 14. Iezzoni LI, McCarthy EP, Davis RB, et al. Mobility impairments and use of screening and preventive services. Am J Public Health. 2000; 90:955–961. 15. Chan L, Doctor JN, MacLehose RF, et al. Do Medicare patients with disabilities receive preventive services? A population-based study. Arch Phys Med Rehabil. 1999;80:642–646. 16. Murphy NA, Elias ER. Sexuality of children and adolescents with developmental disabilities. Pediatrics. 2006;118:398–403. 17. Raddish M. The immunization status of children with spina bifida. Arch Pediatr Adolesc Med. 1993;147:849–853. 18. Kuhlthau K, Walker DK, Perrin JM, et al. Assessing managed care for children with chronic conditions. Health Aff (Millwood). 1998;17:42–52.

QUALITY OF PRIMARY CARE

7

19. Palfrey JS, Levy JC, Gilbert KL. Use of primary care facilities by patients attending specialty clinics. Pediatrics. 1980;65:567–572. 20. Perrin JM, Kuhlthau K, McLaughlin TJ, et al. Changing patterns of conditions among children receiving Supplemental Security Income disability benefits. Arch Pediatr Adolesc Med. 1999;153:80–84. 21. Chien AT, Li Z, Rosenthal MB. Improving timely childhood immunizations through pay for performance in Medicaid-managed care. Health Serv Res. 2010;45(6 pt 2):1934–1947. 22. Chien AT, Kuhlthau KA, Toomey SL, et al. Development of the children with disabilities algorithm. Pediatrics. 2015;136:e871–e878. 23. Mangione-Smith R, Schiff J, Dougherty D. Identifying children’s health care quality measures for Medicaid and CHIP: an evidenceinformed, publicly transparent expert process. Acad Pediatr. 2011; 11(3 suppl):S11–S21. 24. Chien A, Colman M, Ross L. Qualitative insights into how pediatric pay-for-performance programs are being designed. Acad Pediatr. 2009;9:185–191. 25. Chien AT, Conti RM, Pollack HA. A pediatric-focused review of the performance incentive literature. Curr Opin Pediatr. 2007;19:719–725. 26. US Department of Health and Human Services; Health Resources and Services Administration; Maternal and Child Health Bureau. Health Care Financing for CSHCN. Available at: http://mchb.hrsa.gov/ chusa12/hsfu/pages/hcfc.html; 2012. Accessed September 10, 2014. 27. National Center for Children in Poverty. Low-Income Children in the United States: National and State Trend Data, 1998–2008. New York, NY, 2009. Available at: http://www.nccp.org/publications/pdf/text_ 907.pdf. Accessed June 3, 2014. 28. US Department of Health and Human Services; Health Resources and Services Administration. The National Survey of Children With Special Health Care Needs Chartbook, 2005–2006. Rockville, Md: US Department of Health and Human Services; 2008. 29. Dodd A, Nysenbaum J, Zlatinov A. Medicaid Policy Brief: Assessing the Usability of the MAX 2007 Inpatient and Prescription Encounter Data for Enrollees in Comprehensive Managed Care. Available at: https://www.cms.gov/Research-Statistics-Data-and-Systems/ComputerData-and-Systems/MedicaidDataSourcesGenInfo/Downloads/MAXTA_ Usability_MAX_2007_IP_and_RX_EncounterData.pdf. Accessed September 22, 2015. 30. Byrd V, Dodd A, Malsberger R, et al. Medicaid Policy Brief: Assessing the Usability of Max 2008 Encounter Data for Enrollees in Comprehensive Managed Care. Available at: https://www.cms.gov/ Research-Statistics-Data-and-Systems/Computer-Data-and-Systems/ MedicaidDataSourcesGenInfo/Downloads/MAX_IB7_EncounterData_ 071312.pdf. Accessed September 22, 2015. 31. Healthcare Cost and Utilization Project. HCUP Chronic Condition Indicator. Available at: http://www.hcup-us.ahrq.gov/toolssoftware/ chronic/chronic.jsp; 2014. 32. National Committee for Quality Assurance. HEDIS 2013. Volume 2: Technical Specifications. Available at: http://www.ncqa.org/hedisquality-measurement/hedis-measures/hedis-2013. 33. Center for Medicare and Medicaid Services. CHIPRA Initial Core Set of Children’s Health Care Quality Measures. Available at: https:// www.medicaid.gov/Medicaid-CHIP-Program-Information/By-Topics/ Quality-of-Care/CHIPRA-Initial-Core-Set-of-Childrens-Health-CareQuality-Measures.html; 2016. Accessed April 14, 2016. 34. Institute of Medicine. Child and Adolescent Health and Health Care Quality: Measuring What Matters. Washington, DC: National Academies Press; 2011. 35. Liptak GS, Orlando M, Yingling JT, et al. Satisfaction with primary health care received by families of children with developmental disabilities. J Pediatr Health Care. 2006;20:245–252. 36. Toomey SL, Chien AT, Elliott MN, et al. Disparities in unmet need for care coordination: the National Survey of Children’s Health. Pediatrics. 2013;131:217–224. 37. Crandall W, Kappelman MD, Colletti RB, et al. ImproveCareNow: the development of a pediatric inflammatory bowel disease improvement network. Inflamm Bowel Dis. 2011;17:450–457.