Jessica L. Bettenhausen

Multiple Behavior Change Intervention to Improve Detection of Unmet Social Needs and Resulting Resource Referrals.

OBJECTIVE It is critical that pediatric residents learn to effectively screen families for active and addressable social needs (ie, negative social determinants of health). We sought to determine 1) whether a brief intervention teaching residents about IHELP, a social needs screening tool, could improve resident screening, and 2) how accurately IHELP could detect needs in the inpatient setting. METHODS During an 18-month period, interns rotating on 1 of 2 otherwise identical inpatient general pediatrics teams were trained in IHELP. Interns on the other team served as the comparison group. Every admission history and physical examination (H&P) was reviewed for IHELP screening. Social work evaluations were used to establish the sensitivity and specificity of IHELP and document resources provided to families with active needs. During a 21-month postintervention period, every third H&P was reviewed to determine median duration of continued IHELP use. RESULTS A total of 619 admissions met inclusion criteria. Over 80% of intervention team H&Ps documented use of IHELP. The percentage of social work consults was nearly 3 times greater on the intervention team than on the comparison team (P < .001). Among H&Ps with documented use of IHELP, specificity was 0.96 (95% confidence interval 0.87-0.99) and sensitivity was 0.63 (95% confidence interval 0.50-0.73). Social work provided resources for 78% of positively screened families. The median duration of screening use by residents after the intervention was 8.1 months (interquartile range 1-10 months). CONCLUSIONS A brief intervention increased resident screening and detection of social needs, leading to important referrals to address those needs.

Hospitalizations of Low-Income Children and Children With Severe Health Conditions: Implications of the Patient Protection and Affordable Care Act

Hospitalizations of Low-Income Children and Children With Severe Health Conditions: Implications of the Patient Protection and Affordable Care Act Medicaid reimbursement often falls below health care costs (Medicaid shortfall). Therefore, hospitals face financial losses from caring for both uninsured and Medicaid-insured patients. The US government provides disproportionate share hospital (DSH) payments to institutions with large uninsured and Medicaid populations. Anticipating decreased numbers of uninsured patients, the Patient Protection and Affordable Care Act (ACA) reduces DSH payments.1 The ACA also penalizes hospitals for readmissions.2 There will not be large decreases in the number of uninsured children since only a small percentage of children are uninsured. In contrast, a high percentage of children have Medicaid insurance, and institutions will continue to face Medicaid shortfalls. The loss of DSH payments may not be matched by reductions in financial losses from decreases in the number of uninsured patients. In addition, the readmission penalties of the ACA may not adequately adjust for low-income patients or patients with severe health condi-

Childhood obesity and in‐hospital asthma resource utilization

OBJECTIVE To examine the relationship between pediatric obesity and inpatient length of stay (LOS), resource utilization, readmission rates, and total billed charges for in-hospital status asthmaticus. DESIGN/METHODS We conducted a cross-sectional study of patients 5 to 17 years old hospitalized with status asthmaticus to 1 free-standing childrens hospital system over 12 months. Only hospitalized patients initially treated in the hospitals emergency department were included to ensure all therapies/charges were examined. Patients with complex chronic conditions, pneumonia, or lacking recorded body mass index (BMI) were excluded. The primary exposure was BMI percentile for age. The primary outcome was LOS (in hours). Secondary outcomes were 90-day readmission rate, billed charges, and resource utilization: number of albuterol treatments, chest radiographs, intravenous fluids, intravenous or intramuscular steroids, and intensive care unit admission. Bivariate, adjusted Poisson and logistic regression model analyses were performed. RESULTS Five hundred eighteen patients met inclusion criteria. Most had a normal BMI (59.7%); 36.7% were overweight or obese. LOS, readmissions, and resource utilization outcomes were not associated with BMI category on bivariate analyses. After adjustment for demographic/clinical characteristics, LOS decreased by 2% for each decile increase in BMI percentile for age. BMI percentile for age was not associated with billed charges, readmissions, or other measures of resource utilization. CONCLUSIONS Although BMI decile for age is inversely associated with LOS for in-hospital pediatric status asthmaticus, the effect likely is not clinically meaningful.

Socioeconomic Status and Hospitalization Costs for Children with Brain and Spinal Cord Injury

OBJECTIVE To determine if household income is associated with hospitalization costs for severe traumatic brain injury (TBI) and spinal cord injury (SCI). STUDY DESIGN Retrospective cohort study of inpatient, nonrehabilitation hospitalizations at 43 freestanding childrens hospitals for patients <19 years old with unintentional severe TBI and SCI from 2009-2012. Standardized cost of care for hospitalizations was modeled using mixed-effects methods, adjusting for age, sex, race/ethnicity, primary payer, presence of chronic medical condition, mechanism of injury, injury severity, distance from residence to hospital, and trauma center level. Main exposure was zip code level median annual household income. RESULTS There were 1061 patients that met inclusion criteria, 833 with TBI only, 227 with SCI only, and 1 with TBI and SCI. Compared with those with the lowest-income zip codes, patients from the highest-income zip codes were more likely to be older, white (76.7% vs 50.4%), have private insurance (68.9% vs 27.9%), and live closer to the hospital (median distance 26.7 miles vs 81.2 miles). In adjusted models, there was no significant association between zip code level household income and hospitalization costs. CONCLUSIONS Children hospitalized with unintentional, severe TBI and SCI showed no difference in standardized hospital costs relative to a patients home zip code level median annual household income. The association between household income and hospitalization costs may vary by primary diagnosis.

Icd Social Codes: An Underutilized Resource for Tracking Social Needs

Background: Social determinants of health (SDH) data collected in health care settings could have important applications for clinical decision-making, population health strategies, and the design of performance-based incentives and penalties. One source for cataloging SDH data is the International Statistical Classification of Diseases and Related Health Problems (ICD). Objective: To explore how SDH are captured with ICD Ninth revision SDH V codes in a national inpatient discharge database. Materials and Methods: Data come from the 2013 Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample, a national stratified sample of discharges from 4363 hospitals from 44 US states. We estimate the rate of ICD-9 SDH V code utilization overall and by patient demographics and payer categories. We additionally estimate the rate of SDH V code utilization for: (a) the 5 most common reasons for hospitalization; and (b) the 5 conditions with the highest rates of SDH V code utilization. Results: Fewer than 2% of overall discharges in the National Inpatient Sample were assigned an SDH V code. There were statistically significant differences in the rate of overall SDH V code utilization by age categories, race/ethnicity, sex, and payer (all P<0.001). Nevertheless, SDH V codes were assigned to <7% of discharges in any demographic or payer subgroup. SDH V code utilization was highest for major diagnostic categories related to mental health and alcohol/substance use-related discharges. Conclusions: SDH V codes are infrequently utilized in inpatient settings for discharges other than those related to mental health and alcohol/substance use. Utilization incentives will likely need to be developed to realize the potential benefits of cataloging SDH information.

The Effect of Lowering Public Insurance Income Limits on Hospitalizations for Low-Income Children

Using 3 eligibility scenarios, we describe how reductions in income limits for public insurance affects hospitalizations of children currently insured publicly. BACKGROUND AND OBJECTIVES: Thirty million children are currently covered by public insurance; however, the future funding and structure of public insurance are uncertain. Our objective was to determine the number, estimated costs, and demographic characteristics of hospitalizations that would become ineligible for public insurance reimbursement under 3 federal poverty level (FPL) eligibility scenarios. METHODS: In this retrospective cohort study using the 2014 State Inpatient Databases, we included all pediatric (age <18) hospitalizations in 14 states from January 1, 2014, to December 31, 2014, with public insurance as the primary payer. We linked each patient’s zip code to the American Community Survey to determine the likelihood of the patient being below 3 different public insurance income eligibility thresholds (300%, 200%, and 100% of the FPL). Multiple simulations were used to describe newly ineligible hospitalizations under each threshold. RESULTS: In 775 460 publicly reimbursed hospitalizations in 14 states, reductions in eligibility limits to 300%, 200%, or 100% of the FPL would have resulted in large numbers of newly ineligible hospitalizations (∼155 000 [20% of hospitalizations] for 300%, 440 000 [57%] for 200%, and 650 000 [84%] for 100% of the FPL), equaling

Length of Stay and Cost of Pediatric Readmissions

1.2,

Association of Income Inequality With Pediatric Hospitalizations for Ambulatory Care–Sensitive Conditions

3.1, and

Medicaid Expenditures Among Children With Noncomplex Chronic Diseases

4.4 billion of estimated child hospitalization costs, respectively. Patient demographics differed only slightly under each eligibility threshold. CONCLUSIONS: Reducing public insurance eligibility limits would have resulted in numerous pediatric hospitalizations not covered by public insurance, shifting costs to families, other insurers, or hospitals. Without adequately subsidized commercial insurance, this reflects a potentially substantial economic hardship for families and hospitals serving them.

The Inpatient Blindside: Comorbid Mental Health Conditions and Readmissions among Hospitalized Children

This study is a retrospective analysis of the cumulative impact of LOS and cost of pediatric readmissions on health care resource use conducted by using the NRD. BACKGROUND AND OBJECTIVES: Readmissions burden the health care system. Despite increasing attention to readmission rates, little is known about the duration and cost of readmissions. The objective of this study was to assess, nationally, the length of stay (LOS) and costs for 30-day readmissions in children. METHODS: We performed a retrospective analysis of 30-day readmissions by using the 2013 Nationwide Readmissions Database. We used generalized linear mixed effects models adjusted for important clinical and demographic factors to assess LOS and cost for index admissions, readmissions, and the episode of care (index admission plus readmission). RESULTS: A total of 125 183 (4.5%) children had a 30-day readmission; 87.1% of readmissions were to the same hospital. Readmitted children had an adjusted episode LOS that was 2 times longer (5.8 vs 2.9 days) and total costs that were 2.3 times higher (