BACKGROUND:

Children frequently receive low-value services that do not improve health, but it is unknown whether the receipt of these services differs between publicly and privately insured children.

METHODS:

We analyzed 2013–2014 Medicaid Analytic eXtract and IBM MarketScan Commercial Claims and Encounters databases. Using 20 measures of low-value care (6 diagnostic testing measures, 5 imaging measures, and 9 prescription drug measures), we compared the proportion of publicly and privately insured children in 12 states who received low-value services at least once or twice in 2014; the proportion of publicly and privately insured children who received low-value diagnostic tests, imaging tests, and prescription drugs at least once; and the proportion of publicly and privately insured children eligible for each measure who received the service at least once.

RESULTS:

Among 6 951 556 publicly insured children and 1 647 946 privately insured children, respectively, 11.0% and 8.9% received low-value services at least once, 3.9% and 2.8% received low-value services at least twice, 3.2% and 3.8% received low-value diagnostic tests at least once, 0.4% and 0.4% received low-value imaging tests at least once, and 8.4% and 5.5% received low-value prescription drug services at least once. Differences in the proportion of eligible children receiving each service were typically small (median difference among 20 measures, public minus private: +0.3 percentage points).

CONCLUSIONS:

In 2014, 1 in 9 publicly insured and 1 in 11 privately insured children received low-value services. Differences between populations were modest overall, suggesting that wasteful care is not highly associated with payer type. Efforts to reduce this care should target all populations regardless of payer mix.

What’s Known on This Subject:

Previous studies suggest that children frequently receive low-value services that do not improve health, but whether the receipt of these services differs between privately and publicly insured children is unknown.

What This Study Adds:

Among publicly and privately insured children in 12 states, 11.0% and 8.9% received 1 of 20 low-value services during 2014, respectively. This small difference suggests that wasteful care is not highly associated with payer type.

Low-value services are health care interventions that are more expensive and equally or less effective than an alternative, including doing nothing.1  Reducing the provision of low-value services could decrease health care spending while maintaining or even improving outcomes.2,3  Nationally, major efforts are underway to achieve this goal, including campaigns to increase public and clinician awareness of low-value services (eg, Choosing Wisely) as well as payment and delivery reforms that aim to incentivize the delivery of efficient care (eg, accountable care organizations).46  In children, quality improvement efforts have been focused on low-value services across a broad range of settings, including inappropriate antibiotic prescribing in primary care offices, unnecessary imaging for minor head trauma in emergency departments, and overuse of bronchodilators during hospitalization for bronchoilitis.714 

Little is known about which factors predict the receipt of low-value services in children, a gap that impedes the optimal targeting of limited quality improvement resources. One potentially important factor is patient payer type. Compared with privately insured children, publicly insured children covered by Medicaid or the Children’s Health Insurance Program (CHIP) may have different rates of receipt of low-value services for several reasons. First, publicly insured children may face barriers to accessing care regardless of whether it is of low value or high value.15  Second, families of privately insured children often face cost-sharing that may deter the receipt of low-value services.1,16  Third, clinicians may have greater financial incentives to order low-value services for privately insured children because of higher reimbursement.1,17,18  Finally, payer type might serve as a surrogate for other factors that affect the receipt of low-value services, such as systematic bias, patient beliefs regarding health care, and clinician quality.1922  Previous research reveals that the quality of care for publicly insured children lags behind that of privately insured children on many dimensions, including access to care, exacerbations of ambulatory care–sensitive conditions such as asthma, and quality of communication with clinicians.15  If similar disparities exist in the receipt of low-value services, then efforts to reduce wasteful care may be more efficient if they target the design of public insurance programs or the settings in which publicly insured children are frequently seen, such as safety-net facilities.

Our objective for this study was to determine the degree to which the receipt of low-value services differs between publicly and privately insured children. To achieve this objective, we used data from 8.6 million children from 12 states and 20 claims-based measures of low-value services that we developed in a previous publication.16 

In spring 2019, we conducted a cross-sectional analysis of the 2013–2014 Medicaid Analytic eXtract (MAX) databases from 12 states. MAX data are research-friendly versions of Medicaid claims submitted by states to the Centers for Medicare and Medicare Services. At the time of writing, 2014 MAX data from only 17 states were available to researchers. Of these states, we excluded 2 because of concerns about the reliability of “encounter data” submitted by comprehensive managed care organizations and 3 because of small sample sizes.23  MAX data include claims from CHIP enrollees when CHIP funds are used to expand eligibility for Medicaid but not when these funds are used to create a stand-alone CHIP program. We used the MAX Person Summary file to determine demographic characteristics, the MAX Inpatient and Other Therapy files to identify medical claims, and the MAX Prescription Drug file to identify prescription drug claims.

We also conducted a cross-sectional analysis of the 2013–2014 IBM MarketScan Commercial Claims and Encounters database. This database includes claims from >47 million enrollees aged 0 to 64 years who receive private insurance coverage from medium-to-large employers across the United States.24  We used the MarketScan inpatient, outpatient, and facility files to identify medical claims and the pharmacy file to identify prescription drug claims. To align with available data for publicly insured children, we only examined enrollees who resided in 1 of the 12 states. We used 2014 as the year of analysis and data from 2013 as a “look-back period” for relevant diagnosis codes used in measure inclusion and exclusion criteria.

Because of the use of de-identified data, the Institutional Review Boards of the University of Michigan Medical School and the University of Chicago exempted this study from human subjects review.

We included publicly insured children covered by Medicaid or CHIP who were 0 to 18 years old, continuously insured with full benefits throughout 2013 and 2014, and not dually eligible for Medicare at any point during this period. We included privately insured children who were 0 to 18 years old and continuously insured throughout 2013 and 2014.

A detailed discussion of the development of the 20 claims-based measures of low-value pediatric service was published previously.16  Briefly, in the fall of 2015, we compiled a list of >400 low-value services by reviewing sources such as Choosing Wisely recommendations, and identified 20 that could be classified as low-value using the data elements in the claims. The 20 measures included 6 diagnostic tests, 7 imaging tests, and 9 prescription drugs (Table 1; a full list of codes used in the measures is included in the Supplemental Information).

TABLE 1

Claims-Based Measures of 20 Low-Value Services in Children

No.ServiceInclusion CriteriaExclusion CriteriaDenominator
Population-based screening for vitamin D deficiency 25-hydroxy vitamin D blood test No diagnosis potentially warranting testing on day of test or previous claimsa (osteomalacia, rickets, hyperparathyroidism, osteoporosis, pathologic fracture, obesity, sarcoidosis, hepatic failure, chronic kidney disease, inflammatory bowel disease, cystic fibrosis, celiac disease, failure to thrive, malnutrition, eating disorder, developmental motor delay, long-term glucocorticoid use) All children 
   No diagnosis of vitamin D deficiency in previous claimsa  
   No diagnosis indicating pregnancy on day of test  
   Exclude children with complex chronic conditionsb (eg, children with risk factors for severe vitamin D deficiency, such as malabsorption or poor nutrition)  
Skin prick test or IgE blood tests in children with atopic dermatitis Skin prick test or allergen-specific IgE blood test and diagnosis of atopic dermatitis on day of test No other diagnoses potentially warranting testing on day of test (food allergy, anaphylaxis, asthma, allergic or chronic rhinitis, allergic conjunctivitis, allergic colitis or gastroenteritis, history of penicillin allergy) Children with a diagnosis of atopic dermatitis during the year 
Testing for RSV in children with bronchiolitis Test for RSV (eg, rapid RSV test) or respiratory viral panel and diagnosis of bronchiolitis on day of test Exclude infants aged <90 d (may be part of a sepsis workup) Children with a diagnosis of bronchiolitis during the year 
   Exclude testing associated with hospitalizationc (may be required for grouping patients per hospital policy)  
   Exclude children who received Synagis prophylaxis in the previous 30 d (breakthrough RSV infection may prompt discontinuation of prophylaxis)  
   Exclude children with complex chronic conditionsb (could influence decision to initiate influenza therapy in these high-risk patients)  
Blood tests in children with a simple febrile seizure Blood cell count or electrolytes and diagnosis of simple febrile seizure on day of test Exclude infants aged <1 y (blood cell count may be part of an evaluation for central nervous system infections in this age group) Children with a diagnosis of simple febrile seizure during the year 
   No diagnosis for complex febrile seizure, vomiting and/or diarrhea, or dehydration on day of test (could warrant blood or electrolyte testing)  
   Exclude testing associated with hospitalizationc  
   Exclude children with complex chronic conditionsb (eg, children with epilepsy or congenital neurologic anomalies)  
Cervical cancer screening with human papilloma virus test or Papanicolaou test in children Human papilloma virus test or Papanicolaou test No diagnosis potentially warranting testing on day of test or previous claima (abnormal Papanicolaou test, dysplasia or malignancy of cervix, vagina, and /or vulva) Female children aged ≥14 y 
   Exclude children with complex chronic conditionsb (eg, children with HIV or other immunodeficiency)  
Testing for Group A Streptococcus pharyngitis in children aged <3 y Test for Group A Streptococcus pharyngitis (eg, rapid strep test or throat culture) in children aged <3 y Exclude testing associated with hospitalizationc Children aged <3 y 
   No diagnosis indicating exposure to communicable diseases on day of test (eg, sick contact with strep throat)  
   Exclude children with complex chronic conditionsb (eg, children with immunodeficiency)  
Face or nose radiograph in children with head or face trauma Radiographs of face or nose and diagnosis of head or face trauma on same day of test No additional restrictions Children with a diagnosis of head or face trauma during the year 
Ultrasound in children with cryptorchidism Ultrasound of scrotum, pelvis, abdomen, or retroperitoneum and diagnosis of cryptorchidism on day of test Exclude imaging in neonates aged ≤28 d (ultrasound may be part of an evaluation for a disorder of sex development in neonatal period) Children with a diagnosis of cryptorchidism during the year 
   No diagnosis potentially warranting imaging on day of test or previous claima (indeterminate sex, adrenogenital disorder, hypospadias, obesity)  
Sinus imaging in children with acute sinusitis Paranasal sinus radiograph, maxillofacial CT scan, or face MRI and diagnosis of acute sinusitis on day of test No diagnosis of acute sinusitis between 180 and 30 d before imaging Children with a diagnosis of acute sinusitis during the year 
   No diagnosis of chronic sinusitis on day of imaging or previous 180 d  
   No other diagnosis potentially warranting imaging on day of test (orbital cellulitis, cranial nerve palsy, meningismus, seizures, visual disturbances, exophthalmos, altered mental status, nasal polyps)  
   Exclude imaging associated with hospitalizationc  
   Exclude children with complex chronic conditionsb (eg, children with cystic fibrosis or immunodeficiency)  
10 Neuroimaging in children with a simple febrile seizure Head CT scan or brain MRI and diagnosis of simple febrile seizure on day of test No other diagnosis potentially warranting imaging on day of test (complex febrile seizure, focal neurologic examination abnormalities, head or face trauma) Children with a diagnosis of simple febrile seizure during the year 
   Exclude imaging associated with hospitalizationc  
   Exclude children with complex chronic conditionsb (eg, children with epilepsy, congenital neurologic anomalies, ventriculoperitoneal shunt)  
11 Neuroimaging in children with headache Head CT scan or brain MRI and diagnosis of headache on day of test in children No diagnosis potentially warranting imaging on day of test (convulsions, syncope, head or face trauma, posttraumatic headache, complicated headache syndromes, bleeding disorders, history of stroke, focal neurologic examination abnormalities) Children aged ≥12 y with a diagnosis of headache during the year 
   Exclude imaging associated with hospitalizationc  
   Exclude children with complex chronic conditionsb (eg, children with cancer or hydrocephalus)  
12 Cough and cold medications in children aged <6 y Drug claim for cough or cold medicationd in children aged <6 y No additional exclusions Children aged <6 y 
13 Oral antibiotics for acute upper respiratory infections Drug claim for oral antibiotic within 3 d of a diagnosis of acute upper respiratory infection No other diagnosis potentially warranting oral antibiotics on the same day of the index diagnosis of acute upper respiratory infection or in the following 3 de Children with a diagnosis of acute upper respiratory infection during the year 
14 Oral antibiotics for acute OME Drug claim for oral antibiotic within 3 d of a diagnosis of acute OME No other diagnosis potentially warranting oral antibiotics on the same day of the index diagnosis of acute OME or in the following 3 de Children with a diagnosis of acute OME during the year 
   No diagnosis of acute OME between 180 and 90 d before the index diagnosis  
   No diagnosis of chronic OME on the day of the index diagnosis or in the previous 180 d  
15 Oral antibiotics for acute otitis externa Drug claim for oral antibiotic within 3 d of a diagnosis of acute otitis externa No other diagnosis potentially warranting oral antibiotics on the same day of the index diagnosis of acute otitis externa or in the following 3 de Children with a diagnosis of acute otitis externa during the year 
   No diagnosis of acute otitis externa during the 30 d before the index diagnosis  
   No diagnosis of chronic or malignant otitis externa on the same day of the index diagnosis or during the previous 180 d  
   Exclude children with complex chronic conditionsb (eg, children with immunodeficiency)  
16 Oral antibiotics after tonsillectomy Drug claim for oral antibiotic within 3 d of tonsillectomy No other diagnosis potentially warranting oral antibiotics on the same day of the tonsillectomy or in the following 3 de Children undergoing tonsillectomy during the year 
   Exclude children with complex chronic conditionsb (eg, children requiring endocarditis prophylaxis because of heart disease or implants)  
17 Oral antibiotics for bronchiolitis Drug claim for oral antibiotic within 3 d of a diagnosis of bronchiolitis No other diagnosis potentially warranting oral antibiotics on the same day of the index diagnosis of bronchiolitis or in the following 3 de Children with a diagnosis of bronchiolitis during the year 
18 Oral corticosteroids for bronchiolitis Drug claim for oral corticosteroid within 3 d of a diagnosis of bronchiolitis Exclude children with complex chronic conditionsb (eg, children taking steroids for other conditions) Children with a diagnosis of bronchiolitis during the year 
19 Short-acting β-agonists for bronchiolitis Drug claim for inhaled short-acting β-agonist within 3 d of a diagnosis of bronchiolitis Limit to first-time wheezing (defined as no diagnosis of wheezing, bronchiolitis, or asthma before the index diagnosis of bronchiolitis) Children with a diagnosis of bronchiolitis during the year 
   Exclude children with complex chronic conditionsb (eg, patients with chronic lung disease)  
20 Acid blockers for infants with uncomplicated gastroesophageal reflux Drug claim for oral H2 blocker or oral proton pump inhibitor in infants aged <1 y No diagnosis potentially warranting acid blockade on the same day of drug claim or in previous claima (failure to thrive, wt loss, underweight, irritability, excessive crying, apnea, apparently life-threatening event, gastritis, peptic ulcer, gastrointestinal bleed) Infants aged <1 y 
   Exclude children with complex chronic conditionsb (eg, children with risk factors for severe gastroesophageal reflux disease, such as neurologic impairment)  
No.ServiceInclusion CriteriaExclusion CriteriaDenominator
Population-based screening for vitamin D deficiency 25-hydroxy vitamin D blood test No diagnosis potentially warranting testing on day of test or previous claimsa (osteomalacia, rickets, hyperparathyroidism, osteoporosis, pathologic fracture, obesity, sarcoidosis, hepatic failure, chronic kidney disease, inflammatory bowel disease, cystic fibrosis, celiac disease, failure to thrive, malnutrition, eating disorder, developmental motor delay, long-term glucocorticoid use) All children 
   No diagnosis of vitamin D deficiency in previous claimsa  
   No diagnosis indicating pregnancy on day of test  
   Exclude children with complex chronic conditionsb (eg, children with risk factors for severe vitamin D deficiency, such as malabsorption or poor nutrition)  
Skin prick test or IgE blood tests in children with atopic dermatitis Skin prick test or allergen-specific IgE blood test and diagnosis of atopic dermatitis on day of test No other diagnoses potentially warranting testing on day of test (food allergy, anaphylaxis, asthma, allergic or chronic rhinitis, allergic conjunctivitis, allergic colitis or gastroenteritis, history of penicillin allergy) Children with a diagnosis of atopic dermatitis during the year 
Testing for RSV in children with bronchiolitis Test for RSV (eg, rapid RSV test) or respiratory viral panel and diagnosis of bronchiolitis on day of test Exclude infants aged <90 d (may be part of a sepsis workup) Children with a diagnosis of bronchiolitis during the year 
   Exclude testing associated with hospitalizationc (may be required for grouping patients per hospital policy)  
   Exclude children who received Synagis prophylaxis in the previous 30 d (breakthrough RSV infection may prompt discontinuation of prophylaxis)  
   Exclude children with complex chronic conditionsb (could influence decision to initiate influenza therapy in these high-risk patients)  
Blood tests in children with a simple febrile seizure Blood cell count or electrolytes and diagnosis of simple febrile seizure on day of test Exclude infants aged <1 y (blood cell count may be part of an evaluation for central nervous system infections in this age group) Children with a diagnosis of simple febrile seizure during the year 
   No diagnosis for complex febrile seizure, vomiting and/or diarrhea, or dehydration on day of test (could warrant blood or electrolyte testing)  
   Exclude testing associated with hospitalizationc  
   Exclude children with complex chronic conditionsb (eg, children with epilepsy or congenital neurologic anomalies)  
Cervical cancer screening with human papilloma virus test or Papanicolaou test in children Human papilloma virus test or Papanicolaou test No diagnosis potentially warranting testing on day of test or previous claima (abnormal Papanicolaou test, dysplasia or malignancy of cervix, vagina, and /or vulva) Female children aged ≥14 y 
   Exclude children with complex chronic conditionsb (eg, children with HIV or other immunodeficiency)  
Testing for Group A Streptococcus pharyngitis in children aged <3 y Test for Group A Streptococcus pharyngitis (eg, rapid strep test or throat culture) in children aged <3 y Exclude testing associated with hospitalizationc Children aged <3 y 
   No diagnosis indicating exposure to communicable diseases on day of test (eg, sick contact with strep throat)  
   Exclude children with complex chronic conditionsb (eg, children with immunodeficiency)  
Face or nose radiograph in children with head or face trauma Radiographs of face or nose and diagnosis of head or face trauma on same day of test No additional restrictions Children with a diagnosis of head or face trauma during the year 
Ultrasound in children with cryptorchidism Ultrasound of scrotum, pelvis, abdomen, or retroperitoneum and diagnosis of cryptorchidism on day of test Exclude imaging in neonates aged ≤28 d (ultrasound may be part of an evaluation for a disorder of sex development in neonatal period) Children with a diagnosis of cryptorchidism during the year 
   No diagnosis potentially warranting imaging on day of test or previous claima (indeterminate sex, adrenogenital disorder, hypospadias, obesity)  
Sinus imaging in children with acute sinusitis Paranasal sinus radiograph, maxillofacial CT scan, or face MRI and diagnosis of acute sinusitis on day of test No diagnosis of acute sinusitis between 180 and 30 d before imaging Children with a diagnosis of acute sinusitis during the year 
   No diagnosis of chronic sinusitis on day of imaging or previous 180 d  
   No other diagnosis potentially warranting imaging on day of test (orbital cellulitis, cranial nerve palsy, meningismus, seizures, visual disturbances, exophthalmos, altered mental status, nasal polyps)  
   Exclude imaging associated with hospitalizationc  
   Exclude children with complex chronic conditionsb (eg, children with cystic fibrosis or immunodeficiency)  
10 Neuroimaging in children with a simple febrile seizure Head CT scan or brain MRI and diagnosis of simple febrile seizure on day of test No other diagnosis potentially warranting imaging on day of test (complex febrile seizure, focal neurologic examination abnormalities, head or face trauma) Children with a diagnosis of simple febrile seizure during the year 
   Exclude imaging associated with hospitalizationc  
   Exclude children with complex chronic conditionsb (eg, children with epilepsy, congenital neurologic anomalies, ventriculoperitoneal shunt)  
11 Neuroimaging in children with headache Head CT scan or brain MRI and diagnosis of headache on day of test in children No diagnosis potentially warranting imaging on day of test (convulsions, syncope, head or face trauma, posttraumatic headache, complicated headache syndromes, bleeding disorders, history of stroke, focal neurologic examination abnormalities) Children aged ≥12 y with a diagnosis of headache during the year 
   Exclude imaging associated with hospitalizationc  
   Exclude children with complex chronic conditionsb (eg, children with cancer or hydrocephalus)  
12 Cough and cold medications in children aged <6 y Drug claim for cough or cold medicationd in children aged <6 y No additional exclusions Children aged <6 y 
13 Oral antibiotics for acute upper respiratory infections Drug claim for oral antibiotic within 3 d of a diagnosis of acute upper respiratory infection No other diagnosis potentially warranting oral antibiotics on the same day of the index diagnosis of acute upper respiratory infection or in the following 3 de Children with a diagnosis of acute upper respiratory infection during the year 
14 Oral antibiotics for acute OME Drug claim for oral antibiotic within 3 d of a diagnosis of acute OME No other diagnosis potentially warranting oral antibiotics on the same day of the index diagnosis of acute OME or in the following 3 de Children with a diagnosis of acute OME during the year 
   No diagnosis of acute OME between 180 and 90 d before the index diagnosis  
   No diagnosis of chronic OME on the day of the index diagnosis or in the previous 180 d  
15 Oral antibiotics for acute otitis externa Drug claim for oral antibiotic within 3 d of a diagnosis of acute otitis externa No other diagnosis potentially warranting oral antibiotics on the same day of the index diagnosis of acute otitis externa or in the following 3 de Children with a diagnosis of acute otitis externa during the year 
   No diagnosis of acute otitis externa during the 30 d before the index diagnosis  
   No diagnosis of chronic or malignant otitis externa on the same day of the index diagnosis or during the previous 180 d  
   Exclude children with complex chronic conditionsb (eg, children with immunodeficiency)  
16 Oral antibiotics after tonsillectomy Drug claim for oral antibiotic within 3 d of tonsillectomy No other diagnosis potentially warranting oral antibiotics on the same day of the tonsillectomy or in the following 3 de Children undergoing tonsillectomy during the year 
   Exclude children with complex chronic conditionsb (eg, children requiring endocarditis prophylaxis because of heart disease or implants)  
17 Oral antibiotics for bronchiolitis Drug claim for oral antibiotic within 3 d of a diagnosis of bronchiolitis No other diagnosis potentially warranting oral antibiotics on the same day of the index diagnosis of bronchiolitis or in the following 3 de Children with a diagnosis of bronchiolitis during the year 
18 Oral corticosteroids for bronchiolitis Drug claim for oral corticosteroid within 3 d of a diagnosis of bronchiolitis Exclude children with complex chronic conditionsb (eg, children taking steroids for other conditions) Children with a diagnosis of bronchiolitis during the year 
19 Short-acting β-agonists for bronchiolitis Drug claim for inhaled short-acting β-agonist within 3 d of a diagnosis of bronchiolitis Limit to first-time wheezing (defined as no diagnosis of wheezing, bronchiolitis, or asthma before the index diagnosis of bronchiolitis) Children with a diagnosis of bronchiolitis during the year 
   Exclude children with complex chronic conditionsb (eg, patients with chronic lung disease)  
20 Acid blockers for infants with uncomplicated gastroesophageal reflux Drug claim for oral H2 blocker or oral proton pump inhibitor in infants aged <1 y No diagnosis potentially warranting acid blockade on the same day of drug claim or in previous claima (failure to thrive, wt loss, underweight, irritability, excessive crying, apnea, apparently life-threatening event, gastritis, peptic ulcer, gastrointestinal bleed) Infants aged <1 y 
   Exclude children with complex chronic conditionsb (eg, children with risk factors for severe gastroesophageal reflux disease, such as neurologic impairment)  

CT, computed tomography; IgE, immunoglobulin E; OME, otitis media with effusion; RSV, respiratory syncytial virus.

a

“Previous claim” refers to all claims from January 1, 2013, to the day before the service.

b

Defined as children with an ICD-9-CM diagnosis or procedure code indicating a complex chronic condition on any claim from January 1, 2013, to the day of the service; codes were based on a widely used algorithm.25 

c

Defined as a test occurring on or between the admission and discharge dates for a hospitalization.

d

Defined as medications containing pseudoephedrine, phenylephrine, guaifenesin, dextromethorphan, brompheniramine, chlorpheniramine, homatropine and hydrocodone, codeine and promethazine, and codeine and pyrilamine. Diphenhydramine was excluded because it is commonly used for indications other than cough and cold.

e

Bacterial infections such as acute suppurative otitis media, urinary tract infection, pneumonia, and cellulitis.

For each measure, we defined a group of children who were eligible for the service. In some cases, eligibility was age based (eg, group A Streptococcus testing for children aged <3 years). In other cases, eligibility was based on the occurrence of a particular diagnosis code in the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM). For example, the denominator for the measure used to assess oral antibiotics for acute upper respiratory infections included all children with a claim containing a diagnosis code for this condition during 2014.

In our previous publication, we created broad and narrow versions of the 20 measures.16  In this study, we chose only to use the narrow, specific versions to maximize the probability that the measures only captured care that was, in fact, of low value. The specification of measures was similar, except that we added additional ICD-9-CM diagnosis codes that could warrant antibiotics as exclusions in the 5 antibiotic measures. These additional codes were based on a recently published classification scheme of diagnosis codes that was developed to assess the appropriateness of outpatient antibiotic prescribing.8 

For each patient in the sample, we assessed the receipt of the following in 2014: (1) any of the 20 low-value services at least once, (2) any of the 20 services at least twice, (3) any of the 6 low-value diagnostic tests at least once, (4) any of the 5 low-value imaging tests at least once, and (5) any of the 9 low-value prescription drug services at least once. Among patients eligible for each measure, we assessed the receipt of the low-value service at least once in 2014.

We used descriptive statistics to describe the demographic characteristics of the sample and calculate unadjusted differences in the proportion of publicly and privately insured children with each of the above outcomes. To assess adjusted differences in the receipt of low-value services by payer type, we created an analytic extract derived from data from both publicly and privately insured children and then used logistic regression to model the occurrence of each outcome as a function of payer type (public versus private), controlling for age, sex, and state. To improve interpretability, we calculated average marginal effects (AMEs) of public insurance coverage, which represented the difference in predicted probabilities if children were publicly versus privately insured, holding age, sex, and state at their observed values.26 

To examine whether differences by payer type may be greater in some states than in others, we calculated the median and range of unadjusted differences in the proportion of publicly and privately insured children in each state who received low-value (1) services, (2) diagnostic tests, (3) imaging tests, and (4) prescription drugs at least once in 2014. Additionally, we fit a multilevel linear probability model for the receipt of at least 1 low-value service in 2014. This model included age, sex, and payer type as level 1 predictors, a random state intercept, and a random slope for payer type. The random state intercept allowed the overall level of receipt of low-value services to vary between states, whereas the random slope allowed the association between payer type and receipt of low-value services to vary between states. We calculated the SDs of the random state intercepts (ie, the variability between states in overall receipt of low-value services) and of the random slopes (ie, the variability between states in the association between payer type and receipt of low-value services).

Analyses were performed by using SAS version 9.4 (SAS Institute Inc, Cary, NC) and Stata version 15.1 SE (Stata Corp, College Station, TX). A 2-sided P < .05 was considered statistically significant.

The MAX Other Therapy file (outpatient services) only contains 2 diagnosis-code fields, whereas the MarketScan outpatient file contains 4. In a sensitivity analysis, we examined the degree to which results changed when only using data from the first 2 diagnosis-code fields of the MarketScan outpatient file. Additionally, we examined whether results changed when excluding a large state that constituted a disproportionate share of both publicly and privately insured children in the sample.

A total of 6 951 556 publicly insured children and 1 647 946 privately insured children met inclusion criteria, representing a combined sample size of 8 599 502 children. Compared with privately insured children, a higher proportion of publicly insured children in the sample were young children aged 0 to 5 years. The proportion of children who were female was similar between populations (Table 2).

TABLE 2

Demographic Characteristics of Sample

CharacteristicPublicly Insured (n = 6 951 556), n (%)Privately Insured (n = 1 835 680), n (%)
Age group, y   
 0–5 2 492 541 (35.9) 482 798 (29.3) 
 6–11 2 365 804 (34.0) 499 904 (30.3) 
 12–18 2 093 211 (30.1) 665 244 (40.4) 
Female sex 3 394 563 (48.8) 805 346 (48.9) 
Statea   
 1 2 923 214 (42.1) 427 867 (26.0) 
 2 574 448 (8.3) 262 433 (15.9) 
 3 170 916 (2.5) 36 184 (2.2) 
 4 118 283 (1.7) 58 846 (3.6) 
 5 585 713 (8.4) 109 748 (6.7) 
 6 588 391 (8.5) 243 395 (14.8) 
 7 282 710 (4.1) 52 165 (3.2) 
 8 330 911 (4.8) 102 221 (6.2) 
 9 258 079 (3.7) 44 081 (2.7) 
 10 456 207 (6.6) 124 237 (7.5) 
 11 579 006 (8.3) 124 467 (7.6) 
 12 83 678 (1.2) 62 302 (3.8) 
Race and/or ethnicityb   
 White, non-Hispanic 2 299 060 (33.1) Not reported 
 Black or African American, non-Hispanic 1 654 323 (23.8) Not reported 
 American Indian or Alaskan native, non-Hispanic 36 622 (0.5) Not reported 
 Asian, native Hawaiian, or Pacific Islander, non-Hispanic 269 428 (3.9) Not reported 
 Hispanic or Latino 2 182 700 (31.4) Not reported 
 >1 race 50 728 (0.7) Not reported 
 Unknown 458 695 (6.7) Not reported 
CharacteristicPublicly Insured (n = 6 951 556), n (%)Privately Insured (n = 1 835 680), n (%)
Age group, y   
 0–5 2 492 541 (35.9) 482 798 (29.3) 
 6–11 2 365 804 (34.0) 499 904 (30.3) 
 12–18 2 093 211 (30.1) 665 244 (40.4) 
Female sex 3 394 563 (48.8) 805 346 (48.9) 
Statea   
 1 2 923 214 (42.1) 427 867 (26.0) 
 2 574 448 (8.3) 262 433 (15.9) 
 3 170 916 (2.5) 36 184 (2.2) 
 4 118 283 (1.7) 58 846 (3.6) 
 5 585 713 (8.4) 109 748 (6.7) 
 6 588 391 (8.5) 243 395 (14.8) 
 7 282 710 (4.1) 52 165 (3.2) 
 8 330 911 (4.8) 102 221 (6.2) 
 9 258 079 (3.7) 44 081 (2.7) 
 10 456 207 (6.6) 124 237 (7.5) 
 11 579 006 (8.3) 124 467 (7.6) 
 12 83 678 (1.2) 62 302 (3.8) 
Race and/or ethnicityb   
 White, non-Hispanic 2 299 060 (33.1) Not reported 
 Black or African American, non-Hispanic 1 654 323 (23.8) Not reported 
 American Indian or Alaskan native, non-Hispanic 36 622 (0.5) Not reported 
 Asian, native Hawaiian, or Pacific Islander, non-Hispanic 269 428 (3.9) Not reported 
 Hispanic or Latino 2 182 700 (31.4) Not reported 
 >1 race 50 728 (0.7) Not reported 
 Unknown 458 695 (6.7) Not reported 
a

States are not identified to protect confidentiality of data contributors.

b

Race and/or ethnicity data are only available in MAX data. Data represent race and/or ethnicity as recorded by state Medicaid programs in the MAX Person Summary (enrollment) file.

Among publicly and privately insured children in the sample, respectively, 11.0% and 8.9% received low-value services at least once in 2014 (AME: 2.8 percentage points; 95% confidence interval [CI]: 2.7 to 2.8), and 3.9% and 2.8% received low-value services at least twice (AME: 2.3 percentage points; 95% CI: 2.2 to 2.3). Furthermore, 3.2% and 3.8% received any of the 6 low-value diagnostic tests at least once in 2014 (AME: 0.2 percentage points; 95% CI: −0.009 to 0.5), 0.4% and 0.4% received any of the 5 low-value imaging tests at least once in 2014 (AME: 0.02 percentage points; 95% CI: 0.01 to 0.03), and 8.4% and 5.5% received any of the 9 low-value prescription drug services at least once in 2014 (AME: 3.6 percentage points; 95% CI: 3.6 to 3.6) (Fig 1).

FIGURE 1

AMEs of public insurance coverage on the receipt of low-value services. Boxes represent point estimates, whereas horizontal lines represent 95% CIs. RSV, respiratory syncytial virus.

FIGURE 1

AMEs of public insurance coverage on the receipt of low-value services. Boxes represent point estimates, whereas horizontal lines represent 95% CIs. RSV, respiratory syncytial virus.

Close modal

For each of the 20 measures, Table 3 reveals the proportion of eligible patients who received the service at least once during 2014. Unadjusted differences in these proportions by payer type were typically small (median difference among 20 measures, public minus private: −0.3 percentage points), as were AMEs (median: +0.1 percentage points) (Fig 1). Publicly insured children were significantly more likely to receive 6 of the 9 low-value prescription drug services; of these 6 services, 5 were related to antibiotic overuse. No consistent association with payer type was observed among the 6 low-value diagnostic testing measures or among the 5 imaging measures.

TABLE 3

Differences in the Receipt of Low-Value Services in Children by Payer Type, 2014 MAX and MarketScan

MeasurePublicly Insured, n = 6 951 556Privately Insured, n = 1 835 680Difference in % of Eligible Children Affected (Public Minus Private)aAME of Public Insurance Coverage (95% CI)
No. Eligible Children% of Eligible Children Affected% of Publicly Insured Children AffectedNo. Eligible Children% of Eligible Children Affected% of Privately Insured Children Affected
Screening for vitamin D deficiency 6 951 556 0.8 0.8 1 647 946 1.3 1.3 −0.4 −0.2b (−0.2 to −0.2) 
Allergy tests for eczema 164 881 2.1 0.0 36 768 2.6 0.1 −0.6 −0.4b (−0.5 to −0.2) 
RSV testing for bronchiolitis 130 526 11.8 0.2 21 973 17.4 0.2 −5.7 −1.3b (−1.8 to −0.7) 
Blood tests for simple febrile seizures 15 979 13.5 0.0 1871 16.3 0.0 −2.8 −3.4b (−5.2 to −1.6) 
Cervical cancer screening 690 563 1.6 0.2 235 911 1.9 0.3 −0.3 0.2b (1.6 to 2.7) 
Group A Streptococcus test in young children 1 244 621 11.1 2.0 273 566 12.3 2.0 −1.2 0.2b (0.2 to 0.3) 
Face or nose radiograph for head or face trauma 319 535 3.4 0.2 69 959 3.7 0.2 −0.3 0.1 (−0.1 to 0.2) 
Ultrasound for cryptorchidism 11 067 29.2 0.0 1946 20.0 0.0 9.2 7.8b (5.7 to 9.9) 
Sinus imaging for acute sinusitis 316 479 0.6 0.0 119 860 0.6 0.0 0.0 0.0 (−0.1 to 0.04) 
Neuroimaging for simple febrile seizures 15 979 2.8 0.0 1871 3.6 0.0 −0.9 −0.8 (−1.7 to 0.1) 
Neuroimaging for headache 141 119 7.5 0.2 39 535 8.1 0.2 −0.5 −0.2 (−0.5 to 0.1) 
Cough and cold medications in young children 2 492 541 8.5 3.0 482 798 3.2 0.9 5.3 4.6b (4.5 to 4.7) 
Oral antibiotics for acute URI 1 517 072 18.8 4.1 280 128 15.0 2.5 3.8 3.9b (3.7 to 4.0) 
Oral antibiotics for acute otitis media with effusion 158 054 45.4 1.0 44 987 34.1 0.9 11.3 10.9b (10.4 to 11.4) 
Oral antibiotics for acute otitis externa 96 323 25.3 0.3 29 374 24.3 0.4 1.0 0.6b (0.1 to 1.2) 
Oral antibiotics after tonsillectomy 36 342 29.0 0.2 8326 27.5 0.1 1.5 0.4 (−0.6 to 1.5) 
Oral antibiotics for bronchiolitis 130 526 21.4 0.4 21 973 15.3 0.2 6.1 3.6b (3.0 to 4.1) 
Oral corticosteroids for bronchiolitis 130 526 24.0 0.5 21 973 18.1 0.2 6.0 5.1b (4.5 to 5.7) 
Short-acting β-agonists for bronchiolitis 130 526 24.4 0.5 21 973 28.5 0.4 −4.2 −2.3b (−3.0 to −1.7) 
Acid blockers for reflux in infants 436 878 2.8 0.2 151 552 6.3 0.6 −3.5 −3.4b (−3.6 to −3.3) 
MeasurePublicly Insured, n = 6 951 556Privately Insured, n = 1 835 680Difference in % of Eligible Children Affected (Public Minus Private)aAME of Public Insurance Coverage (95% CI)
No. Eligible Children% of Eligible Children Affected% of Publicly Insured Children AffectedNo. Eligible Children% of Eligible Children Affected% of Privately Insured Children Affected
Screening for vitamin D deficiency 6 951 556 0.8 0.8 1 647 946 1.3 1.3 −0.4 −0.2b (−0.2 to −0.2) 
Allergy tests for eczema 164 881 2.1 0.0 36 768 2.6 0.1 −0.6 −0.4b (−0.5 to −0.2) 
RSV testing for bronchiolitis 130 526 11.8 0.2 21 973 17.4 0.2 −5.7 −1.3b (−1.8 to −0.7) 
Blood tests for simple febrile seizures 15 979 13.5 0.0 1871 16.3 0.0 −2.8 −3.4b (−5.2 to −1.6) 
Cervical cancer screening 690 563 1.6 0.2 235 911 1.9 0.3 −0.3 0.2b (1.6 to 2.7) 
Group A Streptococcus test in young children 1 244 621 11.1 2.0 273 566 12.3 2.0 −1.2 0.2b (0.2 to 0.3) 
Face or nose radiograph for head or face trauma 319 535 3.4 0.2 69 959 3.7 0.2 −0.3 0.1 (−0.1 to 0.2) 
Ultrasound for cryptorchidism 11 067 29.2 0.0 1946 20.0 0.0 9.2 7.8b (5.7 to 9.9) 
Sinus imaging for acute sinusitis 316 479 0.6 0.0 119 860 0.6 0.0 0.0 0.0 (−0.1 to 0.04) 
Neuroimaging for simple febrile seizures 15 979 2.8 0.0 1871 3.6 0.0 −0.9 −0.8 (−1.7 to 0.1) 
Neuroimaging for headache 141 119 7.5 0.2 39 535 8.1 0.2 −0.5 −0.2 (−0.5 to 0.1) 
Cough and cold medications in young children 2 492 541 8.5 3.0 482 798 3.2 0.9 5.3 4.6b (4.5 to 4.7) 
Oral antibiotics for acute URI 1 517 072 18.8 4.1 280 128 15.0 2.5 3.8 3.9b (3.7 to 4.0) 
Oral antibiotics for acute otitis media with effusion 158 054 45.4 1.0 44 987 34.1 0.9 11.3 10.9b (10.4 to 11.4) 
Oral antibiotics for acute otitis externa 96 323 25.3 0.3 29 374 24.3 0.4 1.0 0.6b (0.1 to 1.2) 
Oral antibiotics after tonsillectomy 36 342 29.0 0.2 8326 27.5 0.1 1.5 0.4 (−0.6 to 1.5) 
Oral antibiotics for bronchiolitis 130 526 21.4 0.4 21 973 15.3 0.2 6.1 3.6b (3.0 to 4.1) 
Oral corticosteroids for bronchiolitis 130 526 24.0 0.5 21 973 18.1 0.2 6.0 5.1b (4.5 to 5.7) 
Short-acting β-agonists for bronchiolitis 130 526 24.4 0.5 21 973 28.5 0.4 −4.2 −2.3b (−3.0 to −1.7) 
Acid blockers for reflux in infants 436 878 2.8 0.2 151 552 6.3 0.6 −3.5 −3.4b (−3.6 to −3.3) 

RSV, respiratory syncytial virus; URI, upper respiratory infection.

a

May not exactly equal the difference in the numbers in the third and sixth columns because of rounding.

b

Statistically significant (95% CI does not contain 0).

For each state, Table 4 reveals differences in the proportion of publicly and privately insured children who received any of the 20 low-value services at least once in 2014. Differences ranged from −2.1 to 11.7 percentage points but were typically small (median difference, public minus private: 2.6 percentage points). Similarly, differences in the proportion of publicly and privately insured patients who received low-value diagnostic tests, imaging tests, and prescription drug services at least once in 2014 varied among the 12 states but were also typically small (median differences each: ≤2.5 percentage points).

TABLE 4

State-Level Unadjusted Differences in Receipt of Low-Value Services by Payer Type

State% of Children in State Receiving Any Low-Value Service At Least Once in 2014% of Children in State Receiving Any Low-Value Diagnostic Test At Least Once in 2014% of Children in State Receiving Any Low-Value Imaging Test At Least Once in 2014% of Children in State Receiving Any Low-Value Prescription Drug Service At Least Once in 2014
PublicPrivateDifferencePublicPrivateDifferencePublicPrivateDifferencePublicPrivateDifference
7.6 6.0 1.7 1.2 2.5 −1.4 0.3 0.3 −0.1 6.4 3.3 3.1 
15.0 10.2 4.8 4.4 4.2 0.3 0.4 0.4 0.0 11.8 6.6 5.2 
12.0 9.2 2.8 4.0 3.1 0.8 0.4 0.4 0.0 9.0 6.5 2.5 
7.4 5.2 2.3 2.5 1.7 0.8 0.3 0.3 0.1 5.2 3.4 1.7 
13.5 15.5 −2.1 3.7 5.1 −1.4 0.6 0.7 −0.1 10.6 11.9 −1.4 
9.0 7.3 1.7 3.8 3.5 0.3 0.4 0.5 0.0 5.5 3.8 1.7 
9.1 7.4 1.7 5.5 4.7 0.9 0.3 0.3 0.0 4.2 3.0 1.1 
26.6 14.9 11.7 5.7 4.4 1.3 0.5 0.5 0.1 23.7 11.8 11.9 
11.2 8.4 2.8 3.5 3.5 0.1 0.4 0.5 0.0 8.4 5.2 3.3 
10 17.4 13.3 4.1 7.2 7.0 0.2 0.4 0.5 −0.1 11.4 7.1 4.3 
11 13.3 10.9 2.3 4.8 4.6 0.2 0.6 0.5 0.1 9.5 6.9 2.5 
12 9.3 5.8 3.5 3.8 2.4 1.4 0.3 0.3 0.1 5.9 3.4 2.5 
Median 11.6 8.8 2.6 3.9 3.9 0.3 0.4 0.5 0.0 8.7 5.9 2.5 
Minimum 7.4 5.2 −2.1 1.2 1.7 −1.4 0.3 0.3 −0.1 4.2 3.0 −1.4 
Maximum 26.6 15.5 11.7 7.2 7.0 1.4 0.6 0.7 0.1 23.7 11.9 11.9 
Range 19.2 10.3 13.8 6.0 5.3 2.8 0.3 0.4 0.2 19.5 8.9 13.3 
State% of Children in State Receiving Any Low-Value Service At Least Once in 2014% of Children in State Receiving Any Low-Value Diagnostic Test At Least Once in 2014% of Children in State Receiving Any Low-Value Imaging Test At Least Once in 2014% of Children in State Receiving Any Low-Value Prescription Drug Service At Least Once in 2014
PublicPrivateDifferencePublicPrivateDifferencePublicPrivateDifferencePublicPrivateDifference
7.6 6.0 1.7 1.2 2.5 −1.4 0.3 0.3 −0.1 6.4 3.3 3.1 
15.0 10.2 4.8 4.4 4.2 0.3 0.4 0.4 0.0 11.8 6.6 5.2 
12.0 9.2 2.8 4.0 3.1 0.8 0.4 0.4 0.0 9.0 6.5 2.5 
7.4 5.2 2.3 2.5 1.7 0.8 0.3 0.3 0.1 5.2 3.4 1.7 
13.5 15.5 −2.1 3.7 5.1 −1.4 0.6 0.7 −0.1 10.6 11.9 −1.4 
9.0 7.3 1.7 3.8 3.5 0.3 0.4 0.5 0.0 5.5 3.8 1.7 
9.1 7.4 1.7 5.5 4.7 0.9 0.3 0.3 0.0 4.2 3.0 1.1 
26.6 14.9 11.7 5.7 4.4 1.3 0.5 0.5 0.1 23.7 11.8 11.9 
11.2 8.4 2.8 3.5 3.5 0.1 0.4 0.5 0.0 8.4 5.2 3.3 
10 17.4 13.3 4.1 7.2 7.0 0.2 0.4 0.5 −0.1 11.4 7.1 4.3 
11 13.3 10.9 2.3 4.8 4.6 0.2 0.6 0.5 0.1 9.5 6.9 2.5 
12 9.3 5.8 3.5 3.8 2.4 1.4 0.3 0.3 0.1 5.9 3.4 2.5 
Median 11.6 8.8 2.6 3.9 3.9 0.3 0.4 0.5 0.0 8.7 5.9 2.5 
Minimum 7.4 5.2 −2.1 1.2 1.7 −1.4 0.3 0.3 −0.1 4.2 3.0 −1.4 
Maximum 26.6 15.5 11.7 7.2 7.0 1.4 0.6 0.7 0.1 23.7 11.9 11.9 
Range 19.2 10.3 13.8 6.0 5.3 2.8 0.3 0.4 0.2 19.5 8.9 13.3 

Unadjusted differences may not exactly equal the difference in the numbers from the “Public” and “Private” columns because of rounding.

Some states had higher-than-average levels of receipt of low-value service regardless of payer type. Among publicly and privately insured children, respectively, the median proportions receiving low-value services at least once in 2014 were 11.6% and 8.8% among the 12 states, but in 1 state, these proportions were 26.6% and 14.9%. In the multilevel model, there was variation across states in differences by payer type (SD of random slopes: 2.8 percentage points), but this variation was smaller than the variation across states in overall receipt of low-value services (SD of random intercepts: 3.7 percentage points).

When searching only the first 2 diagnosis-code fields of the MarketScan outpatient file, the proportion of privately insured children receiving any of the 20 low-value services at least once increased from 8.9% to 9.0%. The AME of public insurance coverage for this outcome decreased from 2.8 to 2.7 percentage points (95% CI: 2.6 to 2.7).

When excluding the large populous state from the analysis, the proportion of publicly insured children receiving any of the 20 low-value services at least once increased from 11.0% to 13.5%, and it increased from 8.9% to 9.9% in privately insured children. The AME of public insurance coverage for this outcome increased from 2.8 to 2.9 percentage points (95% CI: 2.8 to 2.9).

Using 20 claims-based measures and data from 8.6 million children in 12 states, we found that 11.0% of publicly insured children and 8.9% of privately insured children received low-value services at least once in 2014. In adjusted analyses that accounted for age, sex, and state, public insurance was associated with a 2.8-percentage-point higher probability of receiving any of the 20 low-value services at least once in 2014. The largest difference was observed in the receipt of low-value prescription drug services, whereas no substantial differences were observed in the probability of receiving low-value diagnostic or imaging tests. Among the 20 measures, the magnitude of differences by payer type was generally small, and the direction of differences was not uniform. Taken as a whole, our findings suggest that all children frequently receive low-value services and that payer type is not associated with large differences in wasteful care. Consequently, efforts to reduce such care should target all populations regardless of payer mix.

We compared the receipt of low-value services between publicly and privately insured children across a broad range of treatments, conditions, and settings. In adjusted analyses, having public insurance was associated with a 2.8-percentage-point higher probability of receiving any of the 20 low-value services at least once during the year. Furthermore, we found that the direction of differences among the 20 services did not vary in a consistent manner. For example, for the 9 low-value prescription drug measures, having public insurance was associated with a higher probability of receiving inappropriate antibiotics, a lower probability of receiving acid blockers for uncomplicated infant reflux, and a lower probability of receiving steroids and short-acting β-agonists for bronchiolitis. Although a 2.8-percentage-point difference is not negligible at the population level given the sheer number of publicly insured children in the United States, its magnitude does not justify preferentially focusing efforts to reduce waste on publicly insured children over privately insured children, particularly because the direction of differences by payer type varies between services. Our findings are consistent with those of previous studies of receipt of low-value services in adults. For example, the authors of 1 study found that 14.9% of publicly insured adults and 11.4% of privately insured adults in Oregon received 1 of 15 low-value services in 2013. The authors of this study also failed to find a consistent pattern in the direction of differences by payer type among the 15 services.17 

The absence of a large disparity by payer type is reassuring given that publicly insured children frequently receive lower-quality care in other domains compared with privately insured children.15  However, any reassurance should be tempered by the high prevalence of wasteful care in both populations. Using just 20 measures, we found that ∼1 in 9 publicly insured children and 1 in 11 privately insured children received low-value services in 2014. The true proportion of children who receive low-value services is undoubtedly much higher. Indeed, although our measures captured a broad range of services, they still only captured a subset of the small number of services that can be identified as being of low value in claims data.

At the state level, the median difference by payer type in the proportion of children receiving low-value services was small, consistent with the main analysis. Furthermore, there was substantial variability between states in the overall level of receipt of low-value services. Although exploring geographic variation was beyond the scope of this study, we note that low-value antibiotic prescriptions were highly prevalent services and that the proportion of children receiving low-value prescription drug services varied between states. Collectively, these findings suggest that inappropriate antibiotic prescribing may be an important driver of between-state variation in the receipt of low-value services, consistent with previous studies revealing variation in inappropriate antibiotic prescribing between US Census regions.27  The substantial between-state variation suggests that efforts to reduce low-value services may lead to greater improvements in certain geographic areas (ie, those with higher prevalence of wasteful care).

This study has a number of limitations. First, we relied on older data because MAX data beyond 2014 are currently unavailable because of the ongoing transition to a new Centers for Medicare and Medicare Services system for Medicaid claim submission (Transformed Medicaid Statistical Information System).28  Quality improvement efforts since 2014 may have reduced some of the services we examined, although a recent study revealed that 10.6% of privately insured children received inappropriate antibiotics during 2016.8,13,14  Second, differences in coding practices for publicly and privately insured children may have affected results. Finally, because of the lack of clinical details in claims data, our measures may misclassify appropriate services as being of low value or may fail to capture all low-value services.16,29,30  Misclassification would affect estimates of the absolute level of low-value service receipt, but estimates of differences may be less impacted because any bias is unlikely to be differential between publicly and privately insured children.

Both privately and publicly insured children frequently receive low-value services. Publicly insured children were more likely to receive low-value services, but the overall modest magnitude of this difference, coupled with the inconsistent direction of differences by payer type among services, suggests that wasteful care in children is not highly associated with payer type. Future research to identify factors that do drive wasteful care could facilitate the optimal targeting of quality improvement resources.

Drs Chua, Schwartz, Volerman, Conti, and Huang conceptualized and designed the study, analyzed and interpreted the data, reviewed and revised the manuscript, approved the final manuscript as submitted, and agree to be accountable for all aspects of the work.

FUNDING: Supported by a grant to Dr Chua (Academic Pediatric Association Young Investigator Award). Dr Chua is also supported by a career development award from the National Institute on Drug Abuse (grant 1K08DA048110-01). Funded by the National Institutes of Health (NIH).

     
  • AME

    average marginal effect

  •  
  • CHIP

    Children’s Health Insurance Program

  •  
  • CI

    confidence interval

  •  
  • ICD-9-CM

    International Classification of Diseases, Ninth Revision, Clinical Modification

  •  
  • MAX

    Medicaid Analytic eXtract

1
Gruber
J
,
Maclean
JC
,
Wright
B
,
Wilkinson
E
,
Volpp
KG
.
The impact of increased cost-sharing on utilization of low value services: evidence from the state of Oregon. 2017. Available at: https://ssrn.com/abstract=2903099. Accessed June 24, 2019
2
Berwick
DM
,
Hackbarth
AD
.
Eliminating waste in US health care
.
JAMA
.
2012
;
307
(
14
):
1513
1516
3
Chua
KP
,
Conti
RM
,
Freed
GL
.
Appropriately framing child health care spending: a prerequisite for value improvement
.
JAMA
.
2018
;
319
(
11
):
1087
1088
4
Cassel
CK
,
Guest
JA
.
Choosing wisely: helping physicians and patients make smart decisions about their care
.
JAMA
.
2012
;
307
(
17
):
1801
1802
5
Schwartz
AL
,
Chernew
ME
,
Landon
BE
,
McWilliams
JM
.
Changes in low-value services in year 1 of the Medicare pioneer accountable care organization program
.
JAMA Intern Med
.
2015
;
175
(
11
):
1815
1825
6
Colla
CH
,
Mainor
AJ
,
Hargreaves
C
,
Sequist
T
,
Morden
N
.
Interventions aimed at reducing use of low-value health services: a systematic review
.
Med Care Res Rev
.
2017
;
74
(
5
):
507
550
7
Coon
ER
,
Young
PC
,
Quinonez
RA
,
Morgan
DJ
,
Dhruva
SS
,
Schroeder
AR
.
2017 update on pediatric medical overuse: a review
.
JAMA Pediatr
.
2018
;
172
(
5
):
482
486
8
Chua
KP
,
Fischer
MA
,
Linder
JA
.
Appropriateness of outpatient antibiotic prescribing among privately insured US patients: ICD-10-CM based cross sectional study
.
BMJ
.
2019
;
364
:
k5092
9
Cohen
E
,
Rodean
J
,
Diong
C
, et al
.
Low-value diagnostic imaging use in the pediatric emergency department in the United States and Canada [published correction appears in JAMA Pediatr. 2019;173(8):801]
.
JAMA Pediatr
.
2019
;
173
(
8
):
e191439
10
Tchou
MJ
,
Hall
M
,
Shah
SS
, et al;
Pediatric Research in Inpatient Settings (PRIS) Network
.
Patterns of electrolyte testing at children’s hospitals for common inpatient diagnoses
.
Pediatrics
.
2019
;
144
(
1
):
e20181644
11
Gerber
JS
,
Prasad
PA
,
Fiks
AG
, et al
.
Effect of an outpatient antimicrobial stewardship intervention on broad-spectrum antibiotic prescribing by primary care pediatricians: a randomized trial
.
JAMA
.
2013
;
309
(
22
):
2345
2352
12
Kuppermann
N
,
Holmes
JF
,
Dayan
PS
, et al;
Pediatric Emergency Care Applied Research Network (PECARN)
.
Identification of children at very low risk of clinically-important brain injuries after head trauma: a prospective cohort study
.
Lancet
.
2009
;
374
(
9696
):
1160
1170
13
Mussman
GM
,
Lossius
M
,
Wasif
F
, et al
.
Multisite emergency department inpatient collaborative to reduce unnecessary bronchiolitis care
.
Pediatrics
.
2018
;
141
(
2
):
e20170830
14
Ralston
SL
,
Atwood
EC
,
Garber
MD
,
Holmes
AV
.
What works to reduce unnecessary care for bronchiolitis? A qualitative analysis of a national collaborative
.
Acad Pediatr
.
2017
;
17
(
2
):
198
204
15
Agency for Healthcare Research and Quality
.
Findings on children’s health care quality and disparities. 2010. Available at: https://www.ahrq.gov/sites/default/files/wysiwyg/research/findings/nhqrdr/nhqrdr09/children.pdf. Accessed June 24, 2019
16
Chua
KP
,
Schwartz
AL
,
Volerman
A
,
Conti
RM
,
Huang
ES
.
Use of low-value pediatric services among the commercially insured
.
Pediatrics
.
2016
;
138
(
6
):
e21061809
17
Charlesworth
CJ
,
Meath
TH
,
Schwartz
AL
,
McConnell
KJ
.
Comparison of low-value care in Medicaid vs commercially insured populations
.
JAMA Intern Med
.
2016
;
176
(
7
):
998
1004
18
Morgan
DJ
,
Brownlee
S
,
Leppin
AL
, et al
.
Setting a research agenda for medical overuse
.
BMJ
.
2015
;
351
:
h4534
19
Andersen
R
,
Newman
JF
.
Societal and individual determinants of medical care utilization in the United States
.
Milbank Mem Fund Q Health Soc
.
1973
;
51
(
1
):
95
124
20
Andersen
RM
.
Revisiting the behavioral model and access to medical care: does it matter?
J Health Soc Behav
.
1995
;
36
(
1
):
1
10
21
Institute of Medicine (US) Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care
. In:
Smedley
BD
,
Stith
AY
,
Nelson
AR
, eds.
Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care
.
Washington, DC
:
National Academies Press (US)
22
Bach
PB
,
Pham
HH
,
Schrag
D
,
Tate
RC
,
Hargraves
JL
.
Primary care physicians who treat blacks and whites
.
N Engl J Med
.
2004
;
351
(
6
):
575
584
23
Byrd
VLH
,
Dodd
AH
.
Assessing the Usability of Encounter Data for Enrollees in Comprehensive Managed Care: 2010-2011
.
Baltimore, MD
:
Centers for Medicare and Medicaid Services
;
2015
24
Hansen
LG
,
Chang
S
.
Health research data for the real world: the MarketScan databases. 2011. Available at: http://truvenhealth.com/portals/0/assets/PH_11238_0612_TEMP_MarketScan_WP_FINAL.pdf. Accessed October 15, 2018
25
Feudtner
C
,
Finestein
J
,
Zhong
W
,
Hall
M
,
Dai
D
.
Pediatric complex chronic conditions classification system version 2: updated for ICD-10 and complex medical technology dependence and transplantation
.
BMC Pediatrics
.
2014
;
14
:
199
26
Norton
EC
,
Dowd
BE
,
Maciejewski
ML
.
Marginal effects-quantifying the effect of changes in risk factors in logistic regression models
.
JAMA
.
2019
;
321
(
13
):
1304
1305
27
Fleming-Dutra
KE
,
Hersh
AL
,
Shapiro
DJ
, et al
.
Prevalence of inappropriate antibiotic prescriptions among US ambulatory care visits, 2010-2011
.
JAMA
.
2016
;
315
(
17
):
1864
1873
28
Centers for Medicare and Medicaid Services
.
Medicaid Analytic eXtract (MAX) general information. 2019. Available at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Computer-Data-and-Systems/MedicaidDataSourcesGenInfo/MAXGeneralInformation.html. Accessed June 25, 2019
29
Schwartz
AL
,
Landon
BE
,
Elshaug
AG
,
Chernew
ME
,
McWilliams
JM
.
Measuring low-value care in Medicare
.
JAMA Intern Med
.
2014
;
174
(
7
):
1067
1076
30
Isaac
T
,
Rosenthal
MB
,
Colla
CH
, et al
.
Measuring overuse with electronic health records data
.
Am J Manag Care
.
2018
;
24
(
1
):
19
25

Competing Interests

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

FINANCIAL DISCLOSURE: Dr Schwartz has been compensated as a consultant by the Medicare Payment Advisory Commission to aid in their efforts to measure low-value care in Medicare for research purposes; the other authors have indicated they have no financial relationships relevant to this article to disclose.

Supplementary data