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The American Journal of Managed Care December 2013
Implementing Effective Care Management in the Patient-Centered Medical Home
Catherine A. Taliani, BS; Patricia L. Bricker, MBA; Alan M. Adelman, MD, MS; Peter F. Cronholm, MD, MSCE, FAAFP; and Robert A. Gabbay, MD, PhD
Cost Utility of Hub-and-Spoke Telestroke Networks From Societal Perspective
Bart M. Demaerschalk, MD, MSc; Jeffrey A. Switzer, DO; Jipan Xie, MD, PhD; Liangyi Fan, BA; Kathleen F. Villa, MS; and Eric Q. Wu, PhD
Generic Initiation and Antidepressant Therapy Adherence Under Medicare Part D
Yuhua Bao, PhD; Andrew M. Ryan, PhD; Huibo Shao, MS; Harold Alan Pincus, MD; and Julie M. Donohue, PhD
Economics of Genomic Testing for Women With Breast Cancer
Robert D. Lieberthal, PhD
Impact of Electronic Prescribing on Medication Use in Ambulatory Care
Ashley R. Bergeron, MPH; Jennifer R. Webb, MA; Marina Serper, MD; Alex D. Federman, MD, MPH; William H. Shrank, MD, MSHS; Allison L. Russell, BA; and Michael S. Wolf, PhD, MPH
Medication Utilization and Adherence in a Health Savings Account-Eligible Plan
Paul Fronstin, PhD; Martin-J. Sepulveda, MD; and M. Christopher Roebuck, PhD, MBA
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Characteristics of Low-Severity Emergency Department Use Among CHIP Enrollees
Justin Blackburn, PhD; David J. Becker, PhD; Bisakha Sen, PhD; Michael A. Morrisey, PhD; Cathy Caldwell, MPH; and Nir Menachemi, PhD, MPH
Dietary Diversity Predicts Type of Medical Expenditure in Elders
Yuan-Ting Lo, PhD; Mark L. Wahlqvist, MD; Yu-Hung Chang, PhD; Senyeong Kao, PhD; and Meei-Shyuan Lee, DPH

Characteristics of Low-Severity Emergency Department Use Among CHIP Enrollees

Justin Blackburn, PhD; David J. Becker, PhD; Bisakha Sen, PhD; Michael A. Morrisey, PhD; Cathy Caldwell, MPH; and Nir Menachemi, PhD, MPH
Barriers to less resource-intensive settings may contribute to use of the emergency department for low-severity conditions.
Objectives: To describe patient characteristics among those utilizing the emergency department (ED) for low-severity conditions (ie, conditions potentially treatable or manageable in a primary care setting).

Study Design: A pooled cross-sectional study of administrative claims for ED visits among enrollees in Alabama’s Children’s Health Insurance Program (CHIP), ALL Kids, from January 1, 1999, through December 31, 2010.

Methods: Severity of visit was categorized based on primary diagnosis code using an established claims-based algorithm. Logistic regression was used to identify patient characteristics that predicted low-severity ED visits relative to high-severity visits.

Results: Of a total of 141,709 qualifying ED visits, 97,961 (69%) were classified as low severity, 33,941 (24%) as intermediate severity, and 9807 (7%) as high severity. Based on absolute risk differences, we found that among children utilizing the ED, low-severity visits were more likely than high-severity visits among children who were noncompliant with recommended well-child care (1.2 percentage points, 95% confidence interval [CI], 0.4-1.9); children who were nonurban residents (urban vs isolated: 1.6 percentage points, 95% CI, 1.0-2.2; urban vs small rural: 1.1 percentage points, 95% CI, 0.5-1.7); children without chronic disease (10.3 percentage points, 95% CI, 9.9-10.7) and children whose ED visits were on Sunday versus weekdays (0.9 percentage point, 95% CI, 0.6-1.3), and on Saturday versus weekdays (1.2 percentage points; 95% CI, 0.8-1.6).

Conclusions: Our results suggest that improving access to primary care on weekends and in rural areas are potential ways to improve the efficient use of ED services.

Am J Manag Care. 2013;19(12):e391-e399
We investigated whether emergency department (ED) use for low-severity conditions among low-income children was associated with modifiable characteristics using claims data from a Children’s Health Insurance Program that is similar to private insurance. We found that among children having a visit to the ED:
  • Older age, male sex, African American race, presence of chronic disease, and compliance with recommended well-child care were associated with decreased likelihood of low-severity visits (relative to high-severity visits).

  • Living in an isolated rural town and visits on weekend days were associated with increased likelihood of low-severity visits (relative to high-severity visits).
From 1997 through 2007, emergency department (ED) visits in the United States increased by 23%, or 11% per capita.1 Many of these ED visits were for low-severity conditions and potentially could have been avoided with the provision of effective primary care.2,3 These visits increase ED overcrowding, wait times, and financial strain on public health insurance programs.2,4

Use of ED services for low-severity conditions is often interpreted as a marker of a failing primary care delivery system. The reliance  on ED care may result from limited access to other, less intensive care settings,5 either because of geography, insurance coverage, or other psychosocial factors.6,7 Low-severity ED visits often result from the inability of patients to obtain swift “reassurance” or advice in the primary care setting.8,9 Reducing barriers to primary care could reduce low-severity ED utilization and downstream costs through improved prevention and management. For instance, children with greater continuity of primary care have fewer hospitalizations and ED visits.10 Furthermore, access to high-quality primary care, as defined by Consumer assessment of Healthcare Providers and Systems surveys, is associated with lower ED utilization for low-severity conditions among Medicaid children.11 

There is a sizable literature examining the individual characteristics associated with low-severity ED visits. For example, previous research among pediatric populations suggests that low-severity ED visits are more common among nonwhites,12,13 rural residents,13 individuals with low socioeconomic status,14 and those lacking access to primary care.12,13 Although research has shown that adult Medicaid enrollees are more  likely to use the ED for low-severity conditions,15 less is known about the predictors of low-severity ED utilization among the publicly insured, especially children.

This study investigates the characteristics of enrollees in ALL Kids (Alabama’s Children’s Health Insurance Program [CHIP]) who  utilized ED services for low-severity conditions. An improved understanding of the determinants of low-severity ED visits holds the key to better designing a system that targets unnecessary utilization of an expensive and scarce resource. Given prior literature, predictors of limited access to primary care (eg, nonwhite race, rural residence, weekend visit) were hypothesized to be associated with children’s visits to the ED for low-severity conditions.


Study Design and Population

This study utilized a pooled cross-sectional design. The study population comprised enrollees in ALL Kids, Alabama’s CHIP. ALL Kids covers legal Alabama residents younger than 19 years with family incomes from 101% to 200% of the federal poverty level (FPL). In 2010, eligibility was expanded to children living in families with incomes of 300% of the FPL. Alabama is 1 of 15 states with a free-standing CHIP that operates independently of the Alabama Medicaid program and provides enrollees with access to a more extensive private insurance provider network.16 Children enrolled in ALL Kids benefit from full medical, pharmaceutical, and dental coverage from the Blue Cross Blue Shield of Alabama (BCBSAL) preferred provider network. Enrollees pay an annual premium and copayments for various services. The unit of analysis in this study was claims from ED visits from 1999 to 2010, during which 299,906 unique children were enrolled in the ALL Kids program. This study received approval from the University of Alabama at Birmingham Institutional Review Board for Human Use.

Classifying ED Visits

Revenue center codes 450 through 459 were used to identify ED visits from medical claims. ED visits resulting in hospitalization were excluded. The ED physician’s primary International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis code was then used to classify each visit by severity based on an algorithm developed at New York University (NYU) by Billings and colleagues.17 The original NYU algorithm assigned every ED visit a probability of belonging to each of 4 severity categories: (1) nonemergent, (2) emergent/primary care treatable, (3) emergent/ED care needed, and (4) emergent/ED care needed, not preventable/avoidable. Injuries and conditions requiring specialty care (eg, those related to drugs, alcohol, or mental health) were excluded from the 4 categories. Some ICD-9-CM diagnosis codes were not included in the original algorithm, and ED visits for these conditions were excluded from our analysis.

We used the method developed by Wharam and colleagues18 to convert the NYU severity category probabilities into a single-dimensional measure of severity. This approach used the sum of the probabilities for the 2 categories in which ED care is needed to assign visits to 1 of 3 severity categories: high severity (>75% probability that ED care was needed); intermediate severity (25%-75% probability that ED care was needed); and low severity (<25% probability that ED care was needed). The severity category groupings utilized in this study have been associated with subsequent hospitalizations and death.18

Definition of Characteristic Variables

The BCBSAL claims data and enrollment files provided information regarding enrollees’ demographic characteristics including age, sex, zip code of residence, and cost-sharing group that corresponds to their FPL: low-fee group (101%-150% of FPL); fee group (151%-200% of FPL); and those whose family income is 200% to 300% of FPL. A federally exempt group, primarily children of Native American descent, is considered the no-fee group. Data obtained from BCBSAL contained adjudicated claims, fewer than 3% of which contained missing or problematic data such as nonunique identifiers; these data were excluded. Other data collected by ALL Kids during the application process were used to determine enrollee’s race and were merged with the BCBSAL enrollee data. Rural status was determined from the zip code of residence, which was converted to Rural Urban Commuting Area (RUCA) codes using the zip code approximation method and subsequently categorized into 4 levels: urban focused, large rural city/town focused, small rural town focused, and isolated small rural town focused.19 Chronic disease status was determined by the presence of any condition that might involve extensive ongoing management, including human immunodeficiency virus infection, cancer, anemia or coagulation disorders, diabetes, cystic fibrosis, schizophrenic disorders, developmental disorders, infantile cerebral palsy, epilepsy, muscular dystrophy, heart and circulatory diseases or defects, asthma, rheumatoid arthritis, spina bifida, birth trauma, spinal cord injury, and hearing loss.20

As a proxy for access to primary care, the proportion of children in each zip code receiving well-child care consistent with the Healthcare Effectiveness Data and Information Set (HEDIS) recommendation in the previous year was calculated using data from the complete ALL Kids enrollment and claims  files. The HEDIS criteria are defined for the first 15 months of life, age 3 to 6 years, and age 12 years and older.21 To simplify, the current analysis defined appropriate well-child care as 6 well-child visits within the first 15 months of life and at least 1 visit for children aged 2 years to 19 years. This area-level measure captured access within the geographical area and did not suffer from the endogeniety of individual-specific adherence to the HEDIS guidelines. Quartiles based on the proportion of children in each zip code meeting the measure were defined as fewer than 22.3% for very low, 22.4% to 33.5% for low, 33.6% to 44.1% for intermediate, and 44.2% or more for high.

Statistical Methods

All analyses were performed using STATA/MP release 12.1 for Windows (StataCorp LP, College Station, Texas). The bivariate associations between patient characteristics and ED use were assessed using cross-tabs (all covariates were categorical) with statistical significance determined using a x2 statistic. Next, we used multivariate logistic regression to identify the independent effect of individual characteristics on the use of ED services for low-severity versus high-severity conditions. These regressions allowed us to observe differences in patient characteristics between the low-severity and the high-severity ED populations.

We present odds ratios and 95% confidence intervals (CIs) from the logistic regressions for each covariate. However, given the well-known problems of misinterpreting odds ratios when the outcome is not “rare,”22,23 we also calculated and present marginal effects—also known as absolute risk differences—associated with that covariate (henceforth, marginal effects will be referred to as risk differences). Essentially, risk differences capture the impact of the covariate on the predicted probability of the outcome compared with the reference category. The magnitude is in the natural metric, percentage points, and represents the slope of the logistic curve evaluated at the sample mean. Standard errors for the risk differences were calculated from the standard errors for the underlying beta coefficients using the delta method. We estimated Huber/White heteroscedasticity-consistent standard errors using a variance-covariance matrix that allows for correlated errors (clustering) among individuals with repeated visits.24


A total of 251,480 visits to the ED were identified during the study period. Mental health, alcohol, and drugrelated visits (n = 1028) represented 0.4% of claims and were excluded. Visits for which the diagnosis was unclassifiable by the algorithm totaled 7906 (3.1%) and were excluded. There were 100,584 ED visits for injuries (40%), a heterogeneous group ranging from minor to life-threatening conditions that were not categorized by the Billings and colleagues17 algorithm and were therefore excluded. Visits with missing covariates (n = 253) were excluded. Of the remaining 141,709 visits, 97,961 were classified as low severity (69%), 33,941 as intermediate severity (24%), and 9807 as high severity (7%). The 141,709 severity-classified ED visits occurred among 73,530 unique children (59.4% with a single visit and 20.7% with 2 visits); 95% of our data came from children having 5 or fewer ED visits over a span of 12 years. Our main analysis was restricted to low- and high-severity visits (n = 107,768), which occurred among 61,179 children (63.5% had 1 visit, 20% had 2 visits). The vast majority (95%) of children had 4 or fewer visits.

The most common diagnoses for each severity category are shown in Table 1. Low-severity visits were primarily diagnoses related to upper respiratory infections or other cold-like  conditions. Abdominal pain was the primary diagnosis among 18% of intermediate-severity claims, followed by a diverse mix of other conditions. High-severity visits had several asthma-related diagnoses—in all, more than 50% of these visits had an asthma-related diagnosis.

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