Complications of Serious Pediatric Conditions in the Emergency Department: Definitions, Prevalence, and Resource Utilization

Published:August 02, 2019DOI:https://doi.org/10.1016/j.jpeds.2019.06.064

      Objectives

      To define and measure complications across a broad set of acute pediatric conditions in emergency departments using administrative data, and to assess the validity of these definitions by comparing resource utilization between children with and without complications.

      Study design

      Using local consensus, we predefined complications for 16 acute conditions including appendicitis, diabetic ketoacidosis, ovarian torsion, stroke, testicular torsion, and 11 others. We studied patients under age 18 years using 3 data years from the Healthcare Cost and Utilization Project Statewide Databases of Maryland and New York. We measured complications by condition. Resource utilization was compared between patients with and without complications, including hospital length of stay, and charges.

      Results

      We analyzed 27 087 emergency department visits for a serious condition. The most common was appendicitis (n = 16 794), with 24.3% of cases complicated by 1 or more of perforation (24.1%), abscess drainage (2.8%), bowel resection (0.3%), or sepsis (0.9%). Sepsis had the highest mortality (5.0%). Children with complications had higher resource utilization: condition-specific length of stay was longer when complications were present, except ovarian and testicular torsion. Hospital charges were higher among children with complications (P < .05) for 15 of 16 conditions, with a difference in medians from $3108 (testicular torsion) to $13 7694 (stroke).

      Conclusions

      Clinically meaningful complications were measurable and were associated with increased resource utilization. Complication rates determined using administrative data may be used to compare outcomes and improve healthcare delivery for children.

      Keywords

      Abbreviations:

      CCC (Complex chronic condition), ED (Emergency department), ICD-9 (International Classification of Diseases, 9th Revision), ICD-10 (International Classification of Diseases, 10th Revision), LOS (Length of stay), SDB (Statewide emergency department and inpatient database)
      Timely evaluation, stabilization, and optimal management of serious emergency conditions are major goals of emergency departments (EDs). For serious conditions such as sepsis and appendicitis, timely and effective management reduces the risk of complications and morbidity.
      • Paul R.
      • Neuman M.I.
      • Monuteaux M.C.
      • Melendez E.
      Adherence to PALS sepsis guidelines and hospital length of stay.
      • Papandria D.
      • Goldstein S.D.
      • Rhee D.
      • Salazar J.H.
      • Arlikar J.
      • Gorgy A.
      • et al.
      Risk of perforation increases with delay in recognition and surgery for acute appendicitis.
      • Von Titte S.N.
      • McCabe C.J.
      • Ottinger L.W.
      Delayed appendectomy for appendicitis: causes and consequences.
      • Naiditch J.A.
      • Lautz T.B.
      • Daley S.
      • Pierce M.C.
      • Reynolds M.
      The implications of missed opportunities to diagnose appendicitis in children.
      Measuring complications across a broad set of clinicians and institutions would provide a means to compare health system performance, determine risk factors for poor outcomes, and direct efforts toward appropriate resource allocation for the highest-risk conditions.
      Most serious conditions in children are uncommon, which makes precise measurement of complication rates challenging.
      • Michelson K.A.
      • Hudgins J.D.
      • Burke L.G.
      • Lyons T.W.
      • Monuteaux M.C.
      • Bachur R.G.
      • et al.
      Trends in severe pediatric emergency conditions in a national cohort, 2008 to 2014.
      Infrastructure for research and quality measurement varies considerably between institutions.
      • Adler-Milstein J.
      • Holmgren A.J.
      • Kralovec P.
      • Worzala C.
      • Searcy T.
      • Patel V.
      Electronic health record adoption in US hospitals: the emergence of a digital “advanced use” divide.
      Infrastructure to measure and report care quality is less common in rural and nonacademic centers; thus, most current understanding of complication rates is based on data from urban, academic centers, which may not reflect outcomes nationally.
      • Heisey-Grove D.M.
      Variation in rural health information technology adoption and use.
      • Andrews A.L.
      • Kazley A.S.
      • Basco W.T.
      • Teufel R.J.
      Lower rates of EMR use in rural hospitals represent a previously unexplored child health disparity.
      • DesRoches C.M.
      • Worzala C.
      • Joshi M.S.
      • Kralovec P.D.
      • Jha A.K.
      Small, nonteaching, and rural hospitals continue to be slow in adopting electronic health record systems.
      Measuring outcomes and complications of illness is also challenging when patients visit more than 1 institution in an illness episode, as patients may be lost to follow-up.
      • Michelson K.A.
      • Lyons T.W.
      • Bachur R.G.
      • Monuteaux M.C.
      • Finkelstein J.A.
      timing and location of emergency department revisits.
      Population-based claims databases provide a means to measure the outcomes from EDs of all types and in illness episodes spanning multiple institutions.
      • Michelson K.A.
      • Lyons T.W.
      • Hudgins J.D.
      • Levy J.A.
      • Monuteaux M.C.
      • Finkelstein J.A.
      • et al.
      Use of a national database to assess pediatric emergency care across united states emergency departments.
      Such approaches overcome the limitations of traditional clinical data measurement that rely on collection of clinical data from small cohorts of patients and institutions.
      To measure complications of illness using claims data, definitions of complications would need to be developed based on the diagnoses, procedures, and resources utilized. Currently, a concise, usable, and validated list of condition-specific complications measurable in claims data does not exist.
      Our objective was to define a list of condition-specific, short-term complications measurable from claims data across a set of serious pediatric emergency diagnoses, without respect to preventability. To focus our investigation, we selected serious pediatric conditions that might be sensitive to the timeliness of diagnosis. We then measured complications across EDs in 2 states and compared resource utilization between children with and without complications of illness to provide evidence of the validity of complication definitions.

      Methods

      We conducted a population-based cohort study of ED visits in 2 states among children under age 18 years. We used the Healthcare Cost and Utilization Project Statewide Emergency Department Databases and Statewide Inpatient Databases (collectively SDBs) of Maryland (January 2013-Septemeber 2015) and New York (January 2011-September 2013). In each state, visits from October-December were not included to allow for accurate assessment of post-visit utilization outcomes during those months. The SDBs capture all statewide ED visits and include standardized demographic, disposition, diagnosis, and charge information as billed at the time of the encounter. The SDBs also include identifiers to allow tracking patients between different ED visits and facilities.
      • Healthcare Cost and Utilization Project
      User Guide: HCUP Supplemental Variables Used For Revisit Analysis.
      The 2 states have a population of 5.6 million children who are geographically, racially, and ethnically, diverse.
      • United States Census Bureau
      State Population by Characteristics: 2010-2017.
      We analyzed each patient's earliest ED visit with a diagnosis of a serious condition (Table I). These conditions were selected to represent a spectrum of severity, frequency, and complexity of diagnoses in which optimal emergency care reduces the risk of complications, known as emergency-sensitive conditions. Because no consensus list of such conditions exists for children, we adapted a list intended for adults.
      • Berthelot S.
      • Lang E.S.
      • Quan H.
      • Stelfox H.T.
      What are emergency-sensitive conditions? A survey of Canadian emergency physicians and nurses.
      Diagnoses that, in children, are extremely rare (such as myocardial infarction) or poorly defined (such as other disorders of the brain) were removed. We added conditions we believed to be sensitive to delays in diagnosis among children (such as intussusception or new-onset diabetic ketoacidosis). We decided not to include conditions that are important and serious but for which diagnosis codes lack specificity for case identification (such as pneumonia).
      • Williams D.J.
      • Shah S.S.
      • Myers A.
      • Hall M.
      • Auger K.
      • Queen M.A.
      • et al.
      Identifying pediatric community-acquired pneumonia hospitalizations.
      Our list was not intended to be comprehensive, but rather represented a sample of conditions that would likely be emergency sensitive in children. From the initial list of conditions, we excluded any with fewer than 104 ED visits during the study period. This number was needed to achieve 95% CIs no greater than 10 percentage points away from the complication rate estimate.
      Table 1Definitions of serious conditions included in the study, arranged in descending order of incidence
      Condition
      References for types of complications are given in superscript.
      Inclusion Criteria
      All codes are ICD-9 diagnosis codes. Any digit may substitute for x.
      Condition-specific OutcomesOutcome-defining Diagnosis and Procedure Codes
      Codes are procedure codes unless otherwise specified. Any digit may substitute for x.
      Appendicitis
      • Papandria D.
      • Goldstein S.D.
      • Rhee D.
      • Salazar J.H.
      • Arlikar J.
      • Gorgy A.
      • et al.
      Risk of perforation increases with delay in recognition and surgery for acute appendicitis.
      • Naiditch J.A.
      • Lautz T.B.
      • Daley S.
      • Pierce M.C.
      • Reynolds M.
      The implications of missed opportunities to diagnose appendicitis in children.
      • Aarabi S.
      • Sidhwa F.
      • Riehle K.J.
      • Chen Q.
      • Mooney D.P.
      Pediatric appendicitis in New England: Epidemiology and outcomes.
      • Flum D.
      • Morris A.
      • Koepsell T.
      • Dellinger E.
      Has misdiagnosis of appendicitis decreased over time? A population-based analysis.
      ICD-9 540-542
      • -
        Diagnosis of appendiceal perforation
      • -
        Abdominal abscess drainage
      • -
        Bowel resection
      • -
        Any diagnosis of sepsis
      • -
        ICD-9 diagnosis 540.0-1
      • -
        ICD-9 47.2, 54.91, 97.82 or CPT 44900
      • -
        ICD-9 17.31-39, 45.61-83, 46.02
      • -
        ICD-9 diagnosis 785.52, 995.91-92
      Sepsis
      • Balamuth F.
      • Weiss S.L.
      • Neuman M.I.
      • Scott H.
      • Brady P.W.
      • Paul R.
      • et al.
      Pediatric severe sepsis in U.S. children’s hospitals.
      ICD-9 785.52, 995.91-92

      AND Hospitalized or died
      • -
        Mechanical ventilation
      • -
        Dialysis
      • -
        ECMO
      • -
        Cardiopulmonary resuscitation
      • -
        Death
      • -
        ICD-9 31.1, 96.04, 96.70-72 or CPT 31500
      • -
        ICD-9 39.95, 54.98
      • -
        ICD-9 39.65-66
      • -
        ICD-9 99.60, 99.63 or CPT 92950
      Diabetic ketoacidosis
      • DeCourcey D.D.
      • Steil G.M.
      • Wypij D.
      • Agus M.S.D.
      Increasing use of hypertonic saline over Mannitol in the treatment of symptomatic cerebral edema in pediatric diabetic Ketoacidosis: an 11-year retrospective analysis of mortality.
      • Tieder J.S.
      • McLeod L.
      • Keren R.
      • Luan X.
      • Localio R.
      • Mahant S.
      • et al.
      Variation in resource use and readmission for diabetic ketoacidosis in children’s hospitals.
      • Kuppermann N.
      • Ghetti S.
      • Schunk J.E.
      • Stoner M.J.
      • Rewers A.
      • McManemy J.K.
      • et al.
      Clinical trial of fluid infusion rates for pediatric diabetic ketoacidosis.
      ICD-9 250.1x

      AND No previous diagnosis of diabetes (250.xx)

      AND Hospitalized or died
      • -
        Cerebral edema
      • -
        Coma
      • -
        Mechanical ventilation
      • -
        Discharge to rehabilitation facility
      • -
        Death
      • -
        ICD-9 diagnosis 348.5
      • -
        ICD-9 diagnosis 250.3x or 780.01
      • -
        ICD-9 31.1, 31.42, 96.04, 96.70-72 or CPT 31500
      Intussusception
      • Bekdash B.
      • Marven S.S.
      • Sprigg A.
      Reduction of intussusception: defining a better index of successful non-operative treatment.
      • Beres A.L.
      • Baird R.
      An institutional analysis and systematic review with meta-analysis of pneumatic versus hydrostatic reduction for pediatric intussusception.
      • Samad L.
      • Marven S.
      • El Bashir H.
      • Sutcliffe A.G.
      • Cameron J.C.
      • Lynn R.
      • et al.
      Prospective surveillance study of the management of intussusception in UK and Irish infants.
      • Rice-Townsend S.
      • Chen C.
      • Barnes J.N.
      • Rangel S.J.
      Variation in practice patterns and resource utilization surrounding management of intussusception at freestanding Children’s Hospitals.
      ICD-9 560.0
      • -
        Bowel resection
      • -
        Intestinal perforation
      • -
        ICD-9 17.31-39, 45.41, 45.61-83, 46.02
      • -
        ICD-9 diagnosis 569.83
      Testicular torsion
      • Cost N.G.
      • Bush N.C.
      • Barber T.D.
      • Huang R.
      • Baker L.A.
      Pediatric testicular torsion: Demographics of National orchiopexy versus orchiectomy rates.
      • Zhao L.C.
      • Lautz T.B.
      • Meeks J.J.
      • Maizels M.
      Pediatric testicular torsion epidemiology using a national database: incidence, risk of orchiectomy and possible measures toward improving the quality of care.
      ICD-9 608.20
      • -
        Orchiectomy
      • -
        ICD-9 62.3-63.42, 63.72 or CPT 54520-54522, 54690
      Orbital cellulitis
      • Carifi M.
      • Dall’Olio D.
      • Carifi G.
      Predicting the need for surgical intervention in pediatric orbital cellulitis.
      • Murphy C.
      • Livingstone I.
      • Foot B.
      • Murgatroyd H.
      • MacEwen C.J.
      Orbital cellulitis in Scotland: current incidence, aetiology, management and outcomes.
      • Erickson B.P.
      • Lee W.W.
      Orbital cellulitis and subperiosteal abscess: a 5-year outcomes analysis.
      ICD-9 376.01-02

      AND Hospitalized or died
      • -
        Any cranial surgery
      • -
        Any sinus surgery
      • -
        Any orbital surgery
      • -
        ICD-9 1.21, 1.24-25, 1.31-2.01, 2.06-07, 2.12, 2.21-41, 2.92, 2.99
      • -
        ICD-9 22.00-9
      • -
        ICD-9 16.01-09, 16.22-59, 16.92-99
      Mastoiditis
      • Loh R.
      • Phua M.
      • Shaw C.K.L.
      Management of paediatric acute mastoiditis: systematic review.
      • Lin H.W.
      • Shargorodsky J.
      • Gopen Q.
      Clinical strategies for the management of acute mastoiditis in the pediatric population.
      ICD-9 383.00-02, 383.9
      • -
        Any cranial surgery
      • -
        Any sinus surgery
      • -
        Any ear surgery excluding myringotomy
      • -
        Intracranial venous sinus thrombosis
      • -
        ICD-9 1.21, 1.24-25, 1.31-2.99
      • -
        ICD-9 18.21, 22.00-9
      • -
        ICD-9 19.0-9, 20.21-23, 20.41-49, 20.59-62 20.79
      • -
        ICD ICD-9 diagnosis 437.5
      Septic arthritis
      • Faust S.N.
      • Clark J.
      • Pallett A.
      • Clarke N.M.P.
      Managing bone and joint infection in children.
      ICD-9 711.0x

      AND Hospitalized or died
      • -
        Any diagnosis of sepsis
      • -
        ICD-9 diagnosis 785.52, 995.91-92
      Ovarian torsion
      • Guthrie B.D.
      • Adler M.D.
      • Powell E.C.
      Incidence and trends of pediatric ovarian torsion hospitalizations in the United States, 2000-2006.
      • Lass A.
      The fertility potential of women with a single ovary.
      ICD-9 620.5
      • -
        Oophorectomy
      • -
        Salpingectomy
      • -
        Hysterectomy
      • -
        ICD-9 65.24-49 or CPT 58661, 58720, 58920, 58940
      • -
        ICD-9 66.4-66.69, 66.92 or CPT 58700
      • -
        ICD-9 68.31-79, 68.9, or CPT 58150
      Bacterial meningitis
      • Proulx N.
      • Frechette D.
      • Toye B.
      • Chan J.
      • Kravcik S.
      Delays in the administration of antibiotics are associated with mortality from adult acute bacterial meningitis.
      • McIntyre P.B.
      • Macintyre C.R.
      • Gilmour R.
      • Wang H.
      A population based study of the impact of corticosteroid therapy and delayed diagnosis on the outcome of childhood pneumococcal meningitis.
      ICD-9 320.x

      AND No co-diagnosis of Lyme disease (088.81)

      AND Hospitalized or died
      • -
        Any diagnosis of seizure
      • -
        Mechanical ventilation
      • -
        Any neurosurgery
      • -
        Discharge to rehabilitation facility
      • -
        Death
      • -
        ICD-9 diagnosis 345.x, 780.3x
      • -
        See sepsis
      • -
        ICD-9 1.10, 1.24-26, 1.39, 1.52-59, 2.21-34, 2.39, 2.42-43
      Empyema
      • Goldin A.B.
      • Parimi C.
      • Lariviere C.
      • Garrison M.M.
      • Larison C.L.
      • Sawin R.S.
      Outcomes associated with type of intervention and timing in complex pediatric empyema.
      • Muszynski J.A.
      • Knatz N.L.
      • Sargel C.L.
      • Fernandez S.A.
      • Marquardt D.J.
      • Hall M.W.
      Timing of correct parenteral antibiotic initiation and outcomes from severe bacterial community-acquired pneumonia in children.
      ICD-9 510.x

      AND Hospitalized or died
      • -
        Mechanical ventilation
      • -
        Dialysis
      • -
        ECMO
      • -
        Cardiopulmonary resuscitation
      • -
        Death
      • -
        Any diagnosis of sepsis
      • -
        See sepsis
      Stroke
      • O’Brien J.E.
      • Dumas H.M.
      Hospital length of stay, discharge disposition, and reimbursement by clinical program group in pediatric post-acute rehabilitation.
      • Fox C.K.
      • Johnston S.C.
      • Sidney S.
      • Fullerton H.J.
      High critical care usage due to pediatric stroke: results of a population-based study.
      ICD-9 433.x1, 434.x1, 437.1

      AND Hospitalized or died
      • -
        Mechanical ventilation
      • -
        Discharge to rehabilitation facility
      • -
        Death
      • -
        ICD-9 31.1, 31.42, 96.04, 96.70-72 or CPT 31500
      Encephalitis
      • Sasaki J.
      • Chegondi M.
      • Raszynski A.
      • Totapally B.R.
      Outcome of children with acute encephalitis and refractory status epilepticus.
      • Thakur K.T.
      • Motta M.
      • Asemota A.O.
      • Kirsch H.L.
      • Benavides D.R.
      • Schneider E.B.
      • et al.
      Predictors of outcome in acute encephalitis.
      • Singh T.D.
      • Fugate J.E.
      • Rabinstein A.A.
      The spectrum of acute encephalitis: causes, management, and predictors of outcome.
      • Pillai S.C.
      • Hacohen Y.
      • Tantsis E.
      • Prelog K.
      • Merheb V.
      • Kesson A.
      • et al.
      Infectious and autoantibody-associated encephalitis: clinical features and long-term outcome.
      • DuBray K.
      • Anglemyer A.
      • LaBeaud A.D.
      • Flori H.
      • Bloch K.
      • Joaquin K.S.
      • et al.
      Epidemiology, outcomes, and predictors of recovery in childhood encephalitis.
      ICD-9 323.01, 323.41, 323.81, 323.9

      AND Hospitalized or died
      • -
        Any diagnosis of seizure
      • -
        Mechanical ventilation
      • -
        Any neurosurgery
      • -
        Discharge to rehabilitation facility
      • -
        Death
      • -
        See bacterial meningitis
      Ectopic pregnancy
      • Hoover K.W.
      • Tao G.
      • Kent C.K.
      Trends in the diagnosis and treatment of ectopic pregnancy in the United States.
      ICD-9 633.x0
      • -
        Laparotomy/laparoscopy
      • -
        Fallopian operations
      • -
        Salpingectomy or salpingo-oophorectomy
      • -
        ICD-9 54.19-21 or CPT 49999
      • -
        ICD-9 66.01-02, 66.71-79, 66.99, 74.2 or CPT 59121, 59130, 59150
      • -
        ICD-9 66.22-69, 66.92 or CPT 58679-58700, 59120, 59135-6, 59151
      Myocarditis
      • Ghelani S.J.
      • Spaeder M.C.
      • Pastor W.
      • Spurney C.F.
      • Klugman D.
      Demographics, trends, and outcomes in pediatric acute myocarditis in the United States, 2006 to 2011.
      • Rajagopal S.K.
      • Almond C.S.
      • Laussen P.C.
      • Rycus P.T.
      • Wypij D.
      • Thiagarajan R.R.
      Extracorporeal membrane oxygenation for the support of infants, children, and young adults with acute myocarditis: a review of the Extracorporeal Life Support Organization registry.
      ICD-9 074.23, 422.0, 422.90, 422.91, 422.99

      AND Hospitalized or died
      • -
        Mechanical ventilation
      • -
        Dialysis
      • -
        ECMO
      • -
        CPR
      • -
        Any diagnosis of cardiac arrest
      • -
        Heart transplant or circulatory support device
      • -
        Death
      • -
        ICD-9 31.1, 96.04, 96.70-72 or CPT 31500
      • -
        ICD-9 39.95, 54.98
      • -
        ICD-9 39.65-66
      • -
        ICD-9 99.60, 99.63 or CPT 92950
      • -
        ICD-9 diagnosis 427.41, 427.5
      • -
        ICD-9 37.51-68 or CPT 92950
      Compartment syndrome
      • von Keudell A.G.
      • Weaver M.J.
      • Appleton P.T.
      • Bae D.S.
      • Dyer G.S.M.
      • Heng M.
      • et al.
      Diagnosis and treatment of acute extremity compartment syndrome.
      ICD-9 958.90-92

      AND Hospitalized or died
      • -
        Debridement
      • -
        Amputation
      • -
        83.32-39, 83.44-49
      • -
        ICD-9 84.00-19, 84.91
      CPR, cardiopulmonary resuscitation; CPT, Current Procedural Terminology; ECMO, extracorporeal membrane oxygenation.
      Diagnosis codes were found in the International Classification of Diseases (Clinical Modification), 9th Revision (ICD-9). Patients were eligible for inclusion only on the first visit for a condition. Definitions of condition-specific complications are shown; patients had a condition-specific complication if they met any of the criteria.
      References for types of complications are given in superscript.
      All codes are ICD-9 diagnosis codes. Any digit may substitute for x.
      Codes are procedure codes unless otherwise specified. Any digit may substitute for x.

       Selection of Participants

      Cases were identified using International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) diagnosis codes used previously in code validation studies or for case-finding (Table I). For certain conditions, children are uniformly hospitalized; we identified such conditions as those with hospitalization rates >80% (eg, sepsis). For the 10 such conditions, listed in Table I as requiring hospitalization to meet the case definition, we excluded from analysis children who were coded as not being hospitalized to improve the specificity of case identification. For patients with diabetic ketoacidosis, we were most interested in new presentations of diabetes in which diagnosis is more challenging, so we included only patients with no prior diagnosis of any diabetic condition (ICD-9 250.1x) in the SDB.
      The same patient could appear in the study more than once if they had more than 1 study condition. We only included the earliest visit for a particular condition so as not to erroneously identify visits for complications as index visits. We excluded transferred patients for whom there were no data from the receiving facility, as we could not determine a final diagnosis or assess the presence of complications.

       Variables

      Visit characteristics were obtained from database fields. If 1 or more transfers occurred, ED characteristics were determined from the final ED, as we assumed that is where definitive care occurred. ED-level characteristics included Maryland or New York location and urban-rural location. Visit-level characteristics included patient age (<1, 1-4, 5-7, 8-11, and >11 years), sex, race, ethnicity, socioeconomic status, and presence of a complex chronic condition (CCC).
      • Feudtner C.
      • Hays R.M.
      • Haynes G.
      • Geyer J.R.
      • Neff J.M.
      • Koepsell T.D.
      Deaths attributed to pediatric complex chronic conditions: national trends and implications for supportive care services.
      To assess socioeconomic status, we used the quartile of median income for the patient's zip code.
      • Berkowitz S.A.
      • Traore C.Y.
      • Singer D.E.
      • Atlas S.J.
      Evaluating area-based socioeconomic status indicators for monitoring disparities within health care systems: Results from a primary care network.
      We assessed the presence of CCCs by determining whether any diagnosis of a CCC, as defined by Feudtner et al, appeared in the SDBs at an earlier visit for a given patient.
      • Feudtner C.
      • Hays R.M.
      • Haynes G.
      • Geyer J.R.
      • Neff J.M.
      • Koepsell T.D.
      Deaths attributed to pediatric complex chronic conditions: national trends and implications for supportive care services.
      CCCs include serious, chronic, and disabling conditions such as malignancies and neuromuscular disorders.
      We determined the incidence of each serious condition by dividing the number of first-time cases by the total number of at-risk child-years. At-risk child-years were determined by totaling the states' child populations (age <18 years of age) for each data year using the national census.
      • United States Census Bureau
      State Population by Characteristics: 2010-2017.
      We subtracted 25% from the final data year for each state because we did not include the final 3 months of visits.

       Outcomes

      Outcomes included condition-specific complications and utilization measures. Complications were defined prior to data analysis by review of the evidence base and by consensus among the study investigators (references to evidence shown in Table I). To develop the condition-specific complication definitions, 2 investigators first developed a general outline of the types of outcomes complicating each condition; for instance, perforation is a known complication of appendicitis; seizures are known to complicate bacterial meningitis. Complications included procedures that are frequently indicated but represent a complicated course of disease, such as surgical treatment of ectopic pregnancy, or orchiectomy instead of testicular detorsion in testicular torsion. Complications were chosen without regard to preventability, as our goal was to identify outcomes that patients would view as a worse course of illness than in uncomplicated cases. Next, the lead author specified the diagnosis, procedure, and disposition codes that mapped to each outcome. To be as inclusive of complicated outcomes as possible, we generated a list of all procedures performed during ED visits for each condition; procedures missed in our initial mapping were added to the list of complication-defining codes. Once the draft list of specific diagnosis, procedure, and disposition codes was developed, it was reviewed by each study author individually, and 1 additional external reviewer. These comprised 4 academic pediatric emergency medicine physicians and 1 academic pediatrician and safety expert across three institutions. All were blinded to the rates of complications that the chosen procedures would identify. To make the final complications definitions as specific as possible, procedures without unanimous approval were removed from the list of outcomes.
      Condition-specific outcomes were specified using multiple data fields: (1) ICD-9 diagnoses at or after the index visit, (2) ICD-9 or Current Procedural Terminology procedures performed during or after the index visit, (3) and SDB-specific fields such as disposition.
      To assess the validity of complications definitions, we compared utilization between children with and without complications. Utilization measures included hospitalization rate (for the index visit), hospital length of stay ([LOS], for those hospitalized), and charges (combining any ED and hospital charges). Hospital LOS and charges were determined for the index encounter, and separately for all encounters starting within 30 days of the index encounter. For each condition, we also determined the median number of encounters within 30 days of the index encounter, and cumulative revisit rates from 1 to 90 days after index discharge, stratified by whether a complication occurred. Revisits were defined as a visit to an ED or hospitalization after the index discharge.

       Analyses

      Demographics were reported by condition. Condition-specific outcomes were included if they occurred during the index encounter. Encounters that ended after the 30-day window were included in the calculation, but were uncommon, comprising 2.2% of encounters. We reported condition-specific outcome rates using proportions and binomial exact 95% CIs.
      Total charges and hospital LOS were reported using medians and IQR; hospitalization rates were reported using proportions. Patients who died on the index encounters were excluded from these calculations, as they frequently had very little resource utilization. To determine whether condition-specific median hospital LOS or charges differed between patients with and without complications, we used separate univariable median regressions with bootstrapped 95% CIs and P values for each condition. Differences in hospitalization rates were determined using the Fisher exact test. P values with a 2-sided alpha of 0.05 were considered significant.
      Data were analyzed using R v 3.5.0 (R Foundation, Vienna, Austria). The Institutional Review Board deemed this study exempt from review. Small observation counts between 1 and 10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.

      Results

      Consensus definitions for case identification, previous literature guiding outcomes definitions, and final definitions of outcomes for the 16 analyzed conditions are shown in Table I. There were 5.7 million child ED visits among 2.7 million unique patients seen during the study period. We included 29 103 index visits (0.5% of all statewide pediatric visits) for serious conditions, among 28 580 unique patients. We planned on analyzing the following conditions totaling 261 visits, but excluded them for failing to meet our prespecified power criterion of 104 visits: cranial or spinal abscess (n = 102), pulmonary embolism (95), necrotizing fasciitis (54), and cranial venous sinus thrombosis (10). We also excluded 2015 visits (6.9%) because of transfer to another hospital with no available data. Thus, we analyzed 26 827 visits among 26 323 children with at least 1 of the 16 conditions that met our power threshold. Appendicitis was the most common condition with an incidence of 1086 cases per million child-years. Demographic characteristics of the cohort are shown in Table II (available at www.jpeds.com).

       Main Results

      Condition-specific complication estimates are shown in Table III. Appendicitis, the most frequent condition, was associated with a complication in 24.3% of cases (95% CI 23.7-25.0). Complications were not mutually exclusive and included perforation in 24.1%, abscess drainage in 2.8%, sepsis in 0.9%, and bowel resection in 0.5%. Ovarian torsion had the highest rate of complications, with 59.0% of patients experiencing oophorectomy or salpingectomy. Mortality was highest in stroke (8.4%) and sepsis (5.0%).
      Table IIIFrequency of complications by serious condition
      Conditions (N)ComplicationFrequency, n (%, 95% CI)
      Appendicitis (16 794)
      • Any complication
        • -
          Appendiceal perforation
        • -
          Abdominal abscess drainage
        • -
          Bowel resection
        • -
          Sepsis
      4088 (24.3, 23.7-25.0)

      4049 (24.1, 23.5-24.8)

      462 (2.8, 2.5-3.0)

      46 (0.3, 0.2-0.4)

      145 (0.9, 0.7-1.0)
      Sepsis (2808)
      • Any complication
        • -
          Mechanical ventilation
        • -
          Dialysis
        • -
          ECMO
        • -
          Cardiopulmonary resuscitation
        • -
          Death
      631 (22.5, 20.9-24.1)

      592 (21.1, 19.6-22.6)

      43 (1.5, 1.1-2.1)

      23 (0.8, 0.5-1.2)

      54 (1.9, 1.4-2.5)

      140 (5.0, 4.2-5.9)
      Diabetic ketoacidosis (1504)
      • Any complication
        • -
          Cerebral edema
        • -
          Coma
        • -
          Mechanical ventilation
        • -
          Discharge to rehabilitation facility
        • -
          Death
      18 (1.2, 0.7-1.9)

      11 (0.7, 0.4-1.3)

      0 (0.0, 0.0-0.2)

      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.


      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.


      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.
      Intussusception (1257)
      • Any complication
        • -
          Bowel resection
        • -
          Intestinal perforation
      74 (5.9, 4.7-7.3)

      74 (5.9, 4.7-7.3)

      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.
      Testicular torsion (956)Orchiectomy193 (20.2, 17.7-22.9)
      Orbital cellulitis (692)
      • Any complication
        • -
          Any cranial surgery
        • -
          Any sinus surgery
        • -
          Any orbital surgery
      88 (12.1, 9.8-14.8)

      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.


      68 (9.8, 7.7-12.3)

      54 (7.8, 5.9-10.1)
      Mastoiditis (644)
      • Any complication
        • -
          Any cranial surgery
        • -
          Any sinus surgery
        • -
          Any ear surgery excluding myringotomy
        • -
          Intracranial venous sinus thrombosis
      55 (8.5, 6.5-11.0)

      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.


      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.


      48 (7.5, 5.5-9.8)

      0 (0.0, 0.0-0.6)
      Septic arthritis (458)Any diagnosis of sepsis42 (9.2, 6.7-12.2)
      Ovarian torsion (329)
      • Any complication
        • -
          Oophorectomy
        • -
          Salpingectomy
        • -
          Hysterectomy
      194 (59.0, 53.4-64.3)

      172 (52.3, 46.7-57.8)

      32 (9.7, 6.7-13.5)

      0 (0.0, 0.0-1.1)
      Bacterial meningitis (323)
      • Any complication
        • -
          Any diagnosis of seizure
        • -
          Mechanical ventilation
        • -
          Any neurosurgery
        • -
          Discharge to rehabilitation facility
        • -
          Death
      118 (36.5, 31.3-42.0)

      58 (18.6, 14.5-23.3)

      48 (14.9, 11.2-19.2)

      60 (18.6, 14.5-23.3)

      12 (3.7, 1.9-6.4)

      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.
      Empyema (252)
      • Any complication
        • -
          Mechanical ventilation
        • -
          Dialysis
        • -
          ECMO
        • -
          Cardiopulmonary resuscitation
        • -
          Death
        • -
          Any diagnosis of sepsis
      79 (31.3, 25.7-37.5)

      50 (19.8, 15.1-25.3)

      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.


      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.


      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.


      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.


      49 (19.4, 14.7-24.9)
      Stroke (226)
      • Any complication
        • -
          Mechanical ventilation
        • -
          Discharge to rehabilitation facility
        • -
          Death
      112 (49.6, 42.9-56.3)

      93 (41.2, 34.7-47.9)

      46 (20.4, 15.3-26.2)

      19 (8.4, 5.1-12.8)
      Encephalitis (159)
      • Any complication
        • -
          Any diagnosis of seizure
        • -
          Mechanical ventilation
        • -
          Any neurosurgery
        • -
          Discharge to rehabilitation facility
        • -
          Death
      83 (52.2, 44.2-60.2)

      66 (41.5, 33.8-49.6)

      32 (20.1, 14.2-27.2)

      11 (6.9, 3.5-12.0)

      17 (10.7, 6.4-16.6)

      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.
      Ectopic pregnancy (151)
      • Any complication
        • -
          Laparotomy/laparoscopy
        • -
          Fallopian operations
        • -
          Salpingectomy or salpingo-oophorectomy
      70 (46.4, 38.2-54.6)

      17 (11.3, 6.7-17.4)

      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.


      60 (39.7, 31.9-48.0)
      Myocarditis (142)
      • Any complication
        • -
          Mechanical ventilation
        • -
          Dialysis
        • -
          ECMO
        • -
          CPR
        • -
          Any diagnosis of cardiac arrest
        • -
          Heart transplant or circulatory support device
        • -
          Death
      30 (21.1, 14.7-28.8)

      27 (19.0, 12.9-26.4)

      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.


      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.


      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.


      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.


      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.


      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.
      Compartment syndrome (132)
      • Any complication
        • -
          Debridement
        • -
          Amputation
      25 (18.9, 12.6-26.7)

      25 (18.9, 12.6-26.7)

      0 (0.0, 0.0-2.8)
      Multiple types of complications could occur in a single patient.
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements.
      Across all conditions, children with complications of their serious condition had the same or longer hospital LOS for encounters beginning within 30 days. There was no difference in median hospital LOS for ovarian torsion and testicular torsion. Differences in median LOS for other conditions ranged from 1 day (ectopic pregnancy) to 18 days (stroke, P < .05 for each comparison, Figure 1 and Table IV [Table IV available at www.jpeds.com]). Similarly, total charges for all encounters beginning within 30 days were higher among patients with complications across all conditions except diabetic ketoacidosis ($8786, 95% CI −12 269, +29 841). Differences in median charges ranged from $3108 (testicular torsion) to $137 694 (stroke). Among conditions where we did not mandate hospitalization for inclusion, index encounter hospitalization rates were significantly higher among children with complications, with risk differences varying from 20.2% (testicular torsion) to 52.1% (ectopic pregnancy) (Figure 1).
      Figure thumbnail gr1
      Figure 1Resource utilization by condition among those with and without complications. Condition-specific median hospital LOS and total hospital charges are shown for both index encounters and for all encounters beginning within 30 days (black: patients without complications, gray: patients with complications). Ranges represent the 25th-75th percentiles. Hospitalization rates from the index encounter are shown, excluding conditions where hospitalization is required for case identification.
      Revisit rates are shown in Figure 2 by condition and time window. Revisit rates were higher among patients with complications of their illness compared with those without. The exceptions to that were among visits for ectopic pregnancy and ovarian torsion, in which patients without complications had higher revisit rates.
      Figure thumbnail gr2
      Figure 2Revisit rates after diagnosis of a serious condition depending on whether the patient had complications. The cumulative proportions of index encounters with a subsequent encounter from 1 to 90 days after ED or hospital discharge are shown. Proportions are given by serious condition, with the denominator of all analyzed encounters, excluding children who died on the index encounter. The dotted lines indicate 95% binomial CIs of the daily cumulative revisit proportion.

      Discussion

      Across a broad set of serious childhood diseases, complications were common and identifiable using a large, population-based claims database. When complications occurred, they were associated with increased hospitalizations, longer hospitalizations, and higher charges per patient, all lending validity to the definitions of complications.
      Our reported complication rates are similar to previous studies. For patients with appendicitis, the rate of appendiceal perforation has been reported to be 25%-29%, similar to our rate of 24%.
      • Naiditch J.A.
      • Lautz T.B.
      • Daley S.
      • Pierce M.C.
      • Reynolds M.
      The implications of missed opportunities to diagnose appendicitis in children.
      • Aarabi S.
      • Sidhwa F.
      • Riehle K.J.
      • Chen Q.
      • Mooney D.P.
      Pediatric appendicitis in New England: Epidemiology and outcomes.
      • Flum D.
      • Morris A.
      • Koepsell T.
      • Dellinger E.
      Has misdiagnosis of appendicitis decreased over time? A population-based analysis.
      Mortality in pediatric sepsis varies, ranging from 5% to 15% depending on whether only children with severe sepsis and shock are included.
      • Schlapbach L.J.
      • Straney L.
      • Alexander J.
      • MacLaren G.
      • Festa M.
      • Schibler A.
      • et al.
      Mortality related to invasive infections, sepsis, and septic shock in critically ill children in Australia and New Zealand, 2002–13: a multicentre retrospective cohort study.
      • Balamuth F.
      • Weiss S.L.
      • Hall M.
      • Neuman M.I.
      • Scott H.
      • Brady P.W.
      • et al.
      Identifying pediatric severe sepsis and septic shock: accuracy of diagnosis codes.
      In this study, sepsis mortality among children with and without shock (5%) was at the low end of the previously reported range, given our inclusion of children without severe sepsis or shock. Our results suggest that the rate of oophorectomy or salpingectomy across hospitals of all types is substantially higher than previously reported in pediatric hospitals: 63% vs 35%.
      • Campbell B.T.
      • Austin D.M.
      • Kahn O.
      • McCann M.C.
      • Lerer T.J.
      • Lee K.
      • et al.
      Current trends in the surgical treatment of pediatric ovarian torsion: we can do better.
      This could be due to setting-specific differences in patients or management approaches, and underscores the need for outcomes measurement across settings. The 6.8% bowel resection rate in intussusception in this study is similar to rates reported in the US but is lower than that reported in the United Kingdom (16.8%).
      • Bekdash B.
      • Marven S.S.
      • Sprigg A.
      Reduction of intussusception: defining a better index of successful non-operative treatment.
      • Samad L.
      • Marven S.
      • El Bashir H.
      • Sutcliffe A.G.
      • Cameron J.C.
      • Lynn R.
      • et al.
      Prospective surveillance study of the management of intussusception in UK and Irish infants.
      Similar complication rates between other data sources and our estimates exist for death or rehabilitation in stroke
      • Goeggel Simonetti B.
      • Cavelti A.
      • Arnold M.
      • Bigi S.
      • Regényi M.
      • Mattle H.P.
      • et al.
      Long-term outcome after arterial ischemic stroke in children and young adults.
      ; mechanical ventilation or extracorporeal membrane oxygenation in empyema
      • Goldin A.B.
      • Parimi C.
      • Lariviere C.
      • Garrison M.M.
      • Larison C.L.
      • Sawin R.S.
      Outcomes associated with type of intervention and timing in complex pediatric empyema.
      ; seizure, mechanical ventilation, or death in encephalitis; and orchiectomy in testicular torsion.
      • Cost N.G.
      • Bush N.C.
      • Barber T.D.
      • Huang R.
      • Baker L.A.
      Pediatric testicular torsion: Demographics of National orchiopexy versus orchiectomy rates.
      We found lower complication rates than seen in previous studies for patients with bacterial meningitis,
      • Takhar S.S.
      • Ting S.A.
      • Camargo C.A.
      • Pallin D.J.
      U.S. emergency department visits for meningitis, 1993-2008.
      myocarditis,
      • Ghelani S.J.
      • Spaeder M.C.
      • Pastor W.
      • Spurney C.F.
      • Klugman D.
      Demographics, trends, and outcomes in pediatric acute myocarditis in the United States, 2006 to 2011.
      and diabetic ketoacidosis.
      • Kuppermann N.
      • Ghetti S.
      • Schunk J.E.
      • Stoner M.J.
      • Rewers A.
      • McManemy J.K.
      • et al.
      Clinical trial of fluid infusion rates for pediatric diabetic ketoacidosis.
      Overall, the validity of our approach for most conditions is supported by our findings that the rates obtained using the methods reported here are consistent with other studies using a range of data sources, methods, and settings.
      The complications in this study represent a comparatively worse courses of illness, but may not have been avoidable by actions of healthcare providers and systems. For instance, a late presentation of ectopic pregnancy may mandate surgical management. Appendiceal perforation in appendicitis is more common in younger children and is frequently identified on a child's first presentation.
      • Naiditch J.A.
      • Lautz T.B.
      • Daley S.
      • Pierce M.C.
      • Reynolds M.
      The implications of missed opportunities to diagnose appendicitis in children.
      However, regardless of preventability, these complications result in higher rates of surgery, time spent in hospitals, and hospital charges; all outcomes of importance to patients and society. In cases where complications are attributable to late presentations for care, opportunities may exist to promote patients' access to earlier care.
      Hospital utilization was generally higher in children with complications of their condition, corroborating the overall more complicated course of these patients. There were some exceptions. For instance, among patients with ovarian or testicular torsion, inpatient LOS was similar regardless of complication, which is understandable because the post-operative course would not be different. Median charges were higher for all conditions with complications except diabetic ketoacidosis, in which complications were too uncommon to identify a statistical difference in charges. Revisits were similar or higher among children with disease complications, except in ovarian torsion and ectopic pregnancy. We speculate that in ovarian torsion, for uncomplicated cases in which oophorectomy is not performed at the index visit, patients are at greater risk for needing subsequent care related to attempts at salvaging the ovary; in ectopic pregnancy, medical management may be less likely to be successful initially and may result in additional visits to care.
      • Barnhart K.T.
      Ectopic pregnancy.
      Although timely diagnoses may not avert complications in all cases, comparative evaluation of EDs or health systems would allow for identification of predictors of high complication rates. It would also allow for identification of priority conditions for efforts to reduce complications and thereby increase the health of populations. Measuring the outcomes of many illnesses in large claims datasets is a powerful tool to develop a snapshot of the healthcare of populations. Another advantage of claims data is their utility for measuring outcomes in institutions and systems that do not publish their results, which are disproportionately rural and nonacademic.
      • Adler-Milstein J.
      • Holmgren A.J.
      • Kralovec P.
      • Worzala C.
      • Searcy T.
      • Patel V.
      Electronic health record adoption in US hospitals: the emergence of a digital “advanced use” divide.
      • Heisey-Grove D.M.
      Variation in rural health information technology adoption and use.
      • Andrews A.L.
      • Kazley A.S.
      • Basco W.T.
      • Teufel R.J.
      Lower rates of EMR use in rural hospitals represent a previously unexplored child health disparity.
      • DesRoches C.M.
      • Worzala C.
      • Joshi M.S.
      • Kralovec P.D.
      • Jha A.K.
      Small, nonteaching, and rural hospitals continue to be slow in adopting electronic health record systems.
      Because virtually all healthcare institutions and systems use common billing methods for insured patients (public and private), these data represent a true cross-section of the population. Thus, although measuring complications in this way does not allow for attribution of complications to disease severity or to the care provided, it provides the means to observe outcomes of patients in hospitals not otherwise easily assessed.
      This study overcomes the weaknesses of prior studies that consider data from a single institution or type of institution. There are several other strengths. First, we analyzed a broad range of conditions. Second, we were able to follow children between hospitals to measure their hospital utilization. Third, the definitions of conditions and complications overcomes nongranular diagnosis groupings. For example, although the Diagnosis Grouping System has strengths for grouping conditions in pediatric emergency care, diagnostic categories are insufficiently granular to study single conditions.
      • Alessandrini E.A.
      • Alpern E.R.
      • Chamberlain J.M.
      • Shea J.A.
      • Gorelick M.H.
      A new diagnosis grouping system for child emergency department visits.
      These results should be interpreted in the context of several limitations. First, for some conditions, there were very few cases. Second, the process for development of the list of complications did not include input from a wide range of specialties or institutions. This type of input would be critical to the development of robust quality measures of complication rates. However, the complications fell into previously accepted categories and these reviewers were blinded to complication rates. Third, the procedures used to identify complications may not be comprehensive, though the common procedures for each condition were considered for inclusion. Fourth, we included each patient's first apparent visit for a given condition, but we would have missed an earlier diagnosis if it occurred prior to the beginning of our data. Fifth, our methods did not allow for case reviews of individual patients that could have allowed us to assess variability in coding between institutions; however, our complication rates were generally consistent with past reports using clinical data. Sixth, we could not assess long-term complications, though serious complications for the diseases we included would usually occur relatively quickly. Seventh, our data preceded the implementation of International Classification of Diseases, 10th Revision (ICD-10) and, thus cannot immediately be applied to ICD-10 data. The codes we report for identifying conditions and complications will require the creation of valid ICD-9 to ICD-10 crosswalks, which have successfully been developed for other conditions.
      • Khera R.
      • Dorsey K.B.
      • Krumholz H.M.
      Transition to the ICD-10 in the United States.
      • Columbo J.A.
      • Kang R.
      • Trooboff S.W.
      • Jahn K.S.
      • Martinez C.J.
      • Moore K.O.
      • et al.
      Validating publicly available crosswalks for translating icd-9 to icd-10 diagnosis codes for cardiovascular outcomes research.
      Finally, validity will be increased by applying these definitions to different data sources and populations to ensure similar performance.
      In conclusion, we defined and measured clinically meaningful complications across 16 serious childhood emergency conditions using a large, 2-state, population-based claims database. Complications were common for each condition and were associated with higher resource utilization for most conditions. The use of these definitions can facilitate efforts to identify condition-specific predictors and outcomes of serious pediatric emergency conditions, and can contribute to comparative analysis of complication rates across settings.

      Data statement

      Data sharing statement available at www.jpeds.com.
      We thank Pradip Chaudhari, MD from Children's Hospital of Los Angeles for his critical review of the procedure codes used in our definitions of complications.

      Appendix

      Table IIDemographic characteristics of the cohort by condition
      All visits for any condition over study periodAppendicitisBacterial meningitisCompartment syndromeDiabetic ketoacidosisEctopic pregnancyEmpyemaEncephalitisIntussusceptionMastoiditisMyocarditisOrbital cellulitisOvarian torsionSepsisSeptic arthritisStrokeTesticular torsion
      N5 728 75316 794323132150415125215912576441426923292808458226956
      Incidence (per million child-y)n/a108620.98.597.29.816.310.381.341.69.244.721.3181.529.614.661.8
      Age
       <1661 493 (11.5)11 (0.1)190 (58.8)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      0 (0.0)23 (9.1)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      376 (29.9)50 (7.8)22 (15.5)84 (12.1)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      963 (34.3)28 (6.1)52 (23.0)14 (1.5)
       1-41 813 395 (31.7)679 (4.0)37 (11.5)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      165 (11.0)0 (0.0)110 (43.7)29 (18.2)650 (51.7)211 (32.8)16 (11.3)242 (35.0)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      643 (22.9)130 (28.4)43 (19.0)47 (4.9)
       5-7829 439 (14.5)2001 (11.9)22 (6.8)11 (8.3)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      0 (0.0)45 (17.9)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      115 (9.1)137 (21.3)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      116 (16.8)14 (4.3)264 (9.4)97 (21.2)18 (8.0)19 (2.0)
       8-11856 355 (14.9)4978 (29.6)30 (9.3)20 (15.2)428 (28.5)0 (0.0)24 (9.5)27 (17.0)44 (3.5)118 (18.3)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      114 (16.5)56 (17.0)290 (10.3)99 (21.6)32 (14.2)102 (10.7)
       12+1 568 071 (27.4)9125 (54.3)44 (13.6)92 (69.7)756 (50.3)151 (100)50 (19.8)67 (42.1)72 (5.7)128 (19.9)88 (62.0)136 (19.7)244 (74.2)648 (23.1)104 (22.7)81 (35.8)774 (81.0)
      State
       Maryland1 247 390 (21.8)3034 (18.1)60 (18.6)28 (21.2)279 (18.6)27 (17.9)44 (17.5)26 (16.4)178 (14.2)121 (18.8)23 (16.2)95 (13.7)54 (16.4)776 (27.6)93 (20.3)50 (22.1)298 (31.2)
       New York4 481 363 (78.2)13 760 (81.9)263 (81.4)104 (78.8)1225 (81.4)124 (82.1)208 (82.5)133 (83.6)1079 (85.8)523 (81.2)119 (83.8)597 (86.3)275 (83.6)2032 (72.4)365 (79.7)176 (77.9)658 (68.8)
      Sex
       Female2 701 419 (47.2)6546 (39.0)145 (44.9)23 (17.4)800 (53.2)151 (100)108 (42.9)75 (47.2)451 (35.9)268 (41.6)45 (31.7)268 (38.7)329 (100)1411 (50.2)185 (40.4)102 (45.1)0 (0.0)
       Male3 027 203 (52.8)10 248 (61.0)178 (55.1)109 (82.6)704 (46.8)0 (0.0)144 (57.1)84 (52.8)806 (64.1)376 (58.4)97 (68.3)424 (61.3)0 (0.0)1397 (49.8)273 (59.6)124 (54.9)956 (100)
      Race
       White1 936 594 (34.4)8929 (53.7)142 (44.2)64 (48.5)736 (49.4)31 (20.7)122 (48.4)59 (37.3)518 (41.4)305 (47.8)63 (44.7)255 (37.1)157 (48.2)942 (34.0)214 (47.0)95 (42.2)376 (39.9)
       Black1 588 067 (28.2)1438 (8.6)68 (21.2)38 (28.8)372 (24.9)56 (37.3)48 (19.0)38 (24.1)273 (21.8)94 (14.7)36 (25.5)199 (29.0)58 (17.8)763 (27.5)92 (20.2)71 (31.6)304 (32.2)
       Hispanic1 307 073 (23.2)3946 (23.7)53 (16.5)21 (15.9)216 (14.5)43 (28.7)38 (15.1)31 (19.6)263 (21.0)161 (25.2)23 (16.3)115 (16.7)62 (19.0)631 (22.8)67 (14.7)21 (9.3)139 (14.7)
       Asian/PI165 228 (2.9)597 (3.6)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      20 (1.3)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      21 (8.3)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      140 (5.1)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
       Native American27 222 (0.5)70 (0.4)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      0 (0.0)11 (0.7)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      0 (0.0)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      19 (0.7)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
       Other611 302 (10.8)1653 (9.9)39 (12.1)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      136 (9.1)19 (12.7)23 (9.1)24 (15.2)130 (10.4)59 (9.2)15 (10.6)87 (12.7)36 (11.0)275 (9.9)68 (14.9)30 (13.3)88 (9.3)
      Hispanic
       No4 088 044 (75.8)12 030 (75.3)264 (83.3)108 (83.7)1220 (85.0)99 (69.7)208 (84.6)120 (79.5)961 (78.5)445 (73.4)115 (83.3)543 (82.5)261 (80.8)2070 (76.6)379 (85.0)201 (90.5)759 (84.5)
       Yes1 307 073 (24.2)3946 (24.7)53 (16.7)21 (16.3)216 (15.0)43 (30.3)38 (15.4)31 (20.5)263 (21.5)161 (26.6)23 (16.7)115 (17.5)62 (19.2)631 (23.4)67 (15.0)21 (9.5)139 (15.5)
      Child Home
       Urban5 266 403 (92.1)15 401 (92.0)302 (94.1)119 (91.5)1390 (92.6)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      238 (94.4)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      1205 (96.2)583 (90.8)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      654 (94.6)314 (95.4)2657 (94.9)434 (95.0)211 (93.8)912 (95.5)
       Rural451 341 (7.9)1345 (8.0)19 (5.9)11 (8.5)111 (7.4)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      14 (5.6)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      48 (3.8)59 (9.2)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      37 (5.4)15 (4.6)142 (5.1)23 (5.0)14 (6.2)43 (4.5)
      CCC
       No4 988 420 (96.0)16 189 (96.4)173 (53.6)120 (90.9)1375 (91.4)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      194 (77.0)73 (45.9)1166 (92.8)574 (89.1)69 (48.6)629 (90.9)261 (79.3)1529 (54.5)404 (88.2)75 (33.2)934 (97.7)
       Yes208 897 (4.0)605 (3.6)150 (46.4)12 (9.1)129 (8.6)
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      58 (23.0)86 (54.1)91 (7.2)70 (10.9)73 (51.4)63 (9.1)68 (20.7)1279 (45.5)54 (11.8)151 (66.8)22 (2.3)
      PI, Pacific Islander.
      Cells with counts 1-10 were censored in accordance with Healthcare Cost and Utilization Project data use requirements. In cases where a single cell was censored and the cell count could be deduced, the next smallest cell count was also censored. Numbers do not all sum to 100% due to missing data.
      Table IVHospital utilization by serious condition for the initial encounter and for all encounters within 30 days of the diagnosis visit, among patients who did not die during the index visit
      ConditionsComplicationsHospitalization rate, n (%)
      The case definitions mandated no discharge for sepsis, diabetic ketoacidosis, orbital cellulitis, septic arthritis, bacterial meningitis, empyema, stroke, encephalitis, myocarditis, and compartment syndrome.
      Inpatient days per patient, median (IQR)Encounters per patient, meanCharges per patient, median thousands of USD (IQR)
      Initial encounterInitial encounterAll encountersAll encountersInitial encounterAll encounters
      AppendicitisNo8908 (70.2)1 (1, 2)1 (0, 2)1.1113.8 (8.2, 20.2)14.3 (8.5, 20.8)
      Yes3869 (94.8)5 (3, 7)5 (3, 8)1.1826.0 (15.9, 42.7)28.1 (16.9, 45.8)
      SepsisNo2177 (100)5 (3, 9)5 (3, 11)1.2120.6 (9.1, 52.3)23.2 (9.8, 60.7)
      Yes491 (100)20 (10, 41)21 (12, 44)1.20157.5 (73.0, 344.8)179.7 (80.1, 385.1)
      Diabetic ketoacidosisNo1486 (100)2 (1, 3)2 (1, 3)1.0711.8 (6.8, 19.5)12.1 (6.9, 20.0)
      Yes15 (100)4 (2, 7)4 (2, 7)1.2021.1 (13.8, 61.1)21.1 (13.8, 61.1)
      IntussusceptionNo913 (77.6)1 (1, 2)1 (1, 2)1.267.3 (4.1, 13.1)8.3 (4.8, 15.3)
      Yes73 (100)6 (4, 8)6 (4, 9)1.2745.4 (28.3, 67.2)47.1 (30.2, 83.9)
      Testicular torsionNo237 (31.1)1 (0, 1)0 (0, 0)1.105.2 (3.1, 9.5)5.4 (3.3, 9.7)
      Yes99 (51.3)1 (0, 1)0 (0, 1)1.138.4 (5.6, 12.3)8.6 (5.8, 12.7)
      Orbital cellulitisNo606 (100)3 (2, 4)3 (2, 4)1.1411.8 (6.9, 18.2)12.2 (7.1, 19.7)
      Yes83 (100)6 (4, 8)6 (4, 9)1.2033.6 (19.9, 77.6)38.9 (20.6, 81.7)
      MastoiditisNo364 (62.0)3 (2, 4)2 (0, 3)1.166.7 (1.9, 14.2)7.1 (2.1, 15.8)
      Yes55 (100)5 (3, 9)7 (4, 10)1.3338.0 (16.3, 66.9)40.5 (21.8, 81.9)
      Septic arthritisNo416 (100)5 (3, 7)5 (4, 8)1.2428.4 (15.5, 48)30.7 (17.0, 55.4)
      Yes42 (100)14 (7, 31)14 (8, 31)1.0579.1 (48.3, 208.1)79.1 (48.3, 208.1)
      Ovarian torsionNo67 (49.6)1 (1, 2)1 (0, 2)1.2512.8 (6.5, 20.4)15.1 (7.5, 23.5)
      Yes170 (87.6)2 (1, 3)1 (1, 3)1.0920.0 (13.2, 29.5)20.8 (13.7, 29.6)
      Bacterial meningitisNo205 (100)10 (4, 14)10 (6, 15)1.2336.4 (16.1, 81.3)40.7 (18.3, 85.9)
      Yes111 (100)19 (12, 28)20 (12, 32)1.21129.6 (60.7, 242.8)141.6 (73.2, 270.0)
      EmpyemaNo173 (100)9 (6, 13)10 (7, 14)1.1862.3 (33.1, 93.1)65.3 (36.7, 99.2)
      Yes78 (100)16 (10, 25)17 (11, 27)1.18104.3 (66.9, 173.7)106.8 (68.6, 186.3)
      StrokeNo114 (100)5 (3, 9)6 (4, 12)1.3142.9 (25.1, 80.0)51.5 (27.1, 111)
      Yes93 (100)19 (12, 33)25 (13, 39)1.23161.0 (91.0, 339.5)223.6 (93.0, 364.4)
      EncephalitisNo76 (100)5 (3, 8)6 (4, 9)1.2139.5 (14.9, 66)47.0 (20.7, 86.6)
      Yes77 (100)11 (4, 26)11 (6, 30)1.2690.1 (27.5, 262.9)94.6 (43.8, 297.8)
      Ectopic pregnancyNo13 (16.5)1 (1, 2)0 (0, 0)1.572.5 (1.4, 4.5)3.9 (1.7, 7.4)
      Yes48 (68.6)2 (1, 2)1 (0, 2)1.0713.4 (8.4, 19.9)13.4 (8.4, 20.2)
      MyocarditisNo112 (100)3 (2, 5)3 (2, 6)1.2225.1 (16, 48.4)31.1 (18.1, 52.8)
      Yes26 (100)12 (2, 21)14 (12, 31)1.27138.3 (65.6, 170.0)167.6 (116.7, 325.1)
      Compartment syndromeNo107 (100)7 (4, 14)7 (4, 16)1.2443.2 (28.8, 93.8)43.9 (29.1, 107.4)
      Yes25 (100)16 (8, 21)16 (8, 21)1.1686.3 (61.0, 151.3)89.1 (62.8, 151.3)
      Utilization is stratified by the presence condition-specific complications during the index encounter.
      The case definitions mandated no discharge for sepsis, diabetic ketoacidosis, orbital cellulitis, septic arthritis, bacterial meningitis, empyema, stroke, encephalitis, myocarditis, and compartment syndrome.

      Supplementary Data

      References

        • Paul R.
        • Neuman M.I.
        • Monuteaux M.C.
        • Melendez E.
        Adherence to PALS sepsis guidelines and hospital length of stay.
        Pediatrics. 2012; 130: e273-e280
        • Papandria D.
        • Goldstein S.D.
        • Rhee D.
        • Salazar J.H.
        • Arlikar J.
        • Gorgy A.
        • et al.
        Risk of perforation increases with delay in recognition and surgery for acute appendicitis.
        J Surg Res. 2013; 184: 723-729
        • Von Titte S.N.
        • McCabe C.J.
        • Ottinger L.W.
        Delayed appendectomy for appendicitis: causes and consequences.
        Am J Emerg Med. 1996; 14: 620-622
        • Naiditch J.A.
        • Lautz T.B.
        • Daley S.
        • Pierce M.C.
        • Reynolds M.
        The implications of missed opportunities to diagnose appendicitis in children.
        Acad Emerg Med. 2013; 20: 592-596
        • Michelson K.A.
        • Hudgins J.D.
        • Burke L.G.
        • Lyons T.W.
        • Monuteaux M.C.
        • Bachur R.G.
        • et al.
        Trends in severe pediatric emergency conditions in a national cohort, 2008 to 2014.
        Pediatr Emerg Care. 2018; (in press)
        • Adler-Milstein J.
        • Holmgren A.J.
        • Kralovec P.
        • Worzala C.
        • Searcy T.
        • Patel V.
        Electronic health record adoption in US hospitals: the emergence of a digital “advanced use” divide.
        J Am Med Inform Assoc. 2017; 24: 1142-1148
        • Heisey-Grove D.M.
        Variation in rural health information technology adoption and use.
        Health Aff. 2016; 35: 365-370
        • Andrews A.L.
        • Kazley A.S.
        • Basco W.T.
        • Teufel R.J.
        Lower rates of EMR use in rural hospitals represent a previously unexplored child health disparity.
        Hosp Pediatr. 2014; 4: 211-216
        • DesRoches C.M.
        • Worzala C.
        • Joshi M.S.
        • Kralovec P.D.
        • Jha A.K.
        Small, nonteaching, and rural hospitals continue to be slow in adopting electronic health record systems.
        Health Aff. 2012; 31: 1092-1099
        • Michelson K.A.
        • Lyons T.W.
        • Bachur R.G.
        • Monuteaux M.C.
        • Finkelstein J.A.
        timing and location of emergency department revisits.
        Pediatrics. 2018; 141: e20174087
        • Michelson K.A.
        • Lyons T.W.
        • Hudgins J.D.
        • Levy J.A.
        • Monuteaux M.C.
        • Finkelstein J.A.
        • et al.
        Use of a national database to assess pediatric emergency care across united states emergency departments.
        Acad Emerg Med. 2018; 25: 1355-1364
        • Healthcare Cost and Utilization Project
        User Guide: HCUP Supplemental Variables Used For Revisit Analysis.
        • United States Census Bureau
        State Population by Characteristics: 2010-2017.
        • Aarabi S.
        • Sidhwa F.
        • Riehle K.J.
        • Chen Q.
        • Mooney D.P.
        Pediatric appendicitis in New England: Epidemiology and outcomes.
        J Pediatr Surg. 2011; 46: 1106-1114
        • Flum D.
        • Morris A.
        • Koepsell T.
        • Dellinger E.
        Has misdiagnosis of appendicitis decreased over time? A population-based analysis.
        JAMA. 2001; 286: 1748-1753
        • Balamuth F.
        • Weiss S.L.
        • Neuman M.I.
        • Scott H.
        • Brady P.W.
        • Paul R.
        • et al.
        Pediatric severe sepsis in U.S. children’s hospitals.
        Pediatr Crit Care Med. 2014; 15: 798-805
        • DeCourcey D.D.
        • Steil G.M.
        • Wypij D.
        • Agus M.S.D.
        Increasing use of hypertonic saline over Mannitol in the treatment of symptomatic cerebral edema in pediatric diabetic Ketoacidosis: an 11-year retrospective analysis of mortality.
        Pediatr Crit Care Med. 2013; 14: 694-700
        • Tieder J.S.
        • McLeod L.
        • Keren R.
        • Luan X.
        • Localio R.
        • Mahant S.
        • et al.
        Variation in resource use and readmission for diabetic ketoacidosis in children’s hospitals.
        Pediatrics. 2013; 132: 229-236
        • Kuppermann N.
        • Ghetti S.
        • Schunk J.E.
        • Stoner M.J.
        • Rewers A.
        • McManemy J.K.
        • et al.
        Clinical trial of fluid infusion rates for pediatric diabetic ketoacidosis.
        N Engl J Med. 2018; 378: 2275-2287
        • Bekdash B.
        • Marven S.S.
        • Sprigg A.
        Reduction of intussusception: defining a better index of successful non-operative treatment.
        Pediatr Radiol. 2013; 43: 649-656
        • Beres A.L.
        • Baird R.
        An institutional analysis and systematic review with meta-analysis of pneumatic versus hydrostatic reduction for pediatric intussusception.
        Surgery. 2013; 154: 328-334
        • Samad L.
        • Marven S.
        • El Bashir H.
        • Sutcliffe A.G.
        • Cameron J.C.
        • Lynn R.
        • et al.
        Prospective surveillance study of the management of intussusception in UK and Irish infants.
        Br J Surg. 2012; 99: 411-415
        • Rice-Townsend S.
        • Chen C.
        • Barnes J.N.
        • Rangel S.J.
        Variation in practice patterns and resource utilization surrounding management of intussusception at freestanding Children’s Hospitals.
        J Pediatr Surg. 2013; 48: 104-110
        • Cost N.G.
        • Bush N.C.
        • Barber T.D.
        • Huang R.
        • Baker L.A.
        Pediatric testicular torsion: Demographics of National orchiopexy versus orchiectomy rates.
        J Urol. 2011; 185: 2459-2463
        • Zhao L.C.
        • Lautz T.B.
        • Meeks J.J.
        • Maizels M.
        Pediatric testicular torsion epidemiology using a national database: incidence, risk of orchiectomy and possible measures toward improving the quality of care.
        J Urol. 2011; 186: 2009-2013
        • Carifi M.
        • Dall’Olio D.
        • Carifi G.
        Predicting the need for surgical intervention in pediatric orbital cellulitis.
        Am J Ophthalmol. 2014; 158: 1099
        • Murphy C.
        • Livingstone I.
        • Foot B.
        • Murgatroyd H.
        • MacEwen C.J.
        Orbital cellulitis in Scotland: current incidence, aetiology, management and outcomes.
        Br J Ophthalmol. 2014; 98: 1575-1578
        • Erickson B.P.
        • Lee W.W.
        Orbital cellulitis and subperiosteal abscess: a 5-year outcomes analysis.
        Orbit. 2015; 34: 115-120
        • Loh R.
        • Phua M.
        • Shaw C.K.L.
        Management of paediatric acute mastoiditis: systematic review.
        J Laryngol Otol. 2018; 132: 96-104
        • Lin H.W.
        • Shargorodsky J.
        • Gopen Q.
        Clinical strategies for the management of acute mastoiditis in the pediatric population.
        Clin Pediatr (Phila). 2010; 49: 110-115
        • Faust S.N.
        • Clark J.
        • Pallett A.
        • Clarke N.M.P.
        Managing bone and joint infection in children.
        Arch Dis Child. 2012; 97: 545-553
        • Guthrie B.D.
        • Adler M.D.
        • Powell E.C.
        Incidence and trends of pediatric ovarian torsion hospitalizations in the United States, 2000-2006.
        Pediatrics. 2010; 125: 532-538
        • Lass A.
        The fertility potential of women with a single ovary.
        Hum Reprod Update. 1999; 5: 546-550
        • Proulx N.
        • Frechette D.
        • Toye B.
        • Chan J.
        • Kravcik S.
        Delays in the administration of antibiotics are associated with mortality from adult acute bacterial meningitis.
        QJM. 2005; 98: 291-298
        • McIntyre P.B.
        • Macintyre C.R.
        • Gilmour R.
        • Wang H.
        A population based study of the impact of corticosteroid therapy and delayed diagnosis on the outcome of childhood pneumococcal meningitis.
        Arch Dis Child. 2005; 90: 391-396
        • Goldin A.B.
        • Parimi C.
        • Lariviere C.
        • Garrison M.M.
        • Larison C.L.
        • Sawin R.S.
        Outcomes associated with type of intervention and timing in complex pediatric empyema.
        Am J Surg. 2012; 203: 665-673
        • Muszynski J.A.
        • Knatz N.L.
        • Sargel C.L.
        • Fernandez S.A.
        • Marquardt D.J.
        • Hall M.W.
        Timing of correct parenteral antibiotic initiation and outcomes from severe bacterial community-acquired pneumonia in children.
        Pediatr Infect Dis J. 2011; 30: 295-301
        • O’Brien J.E.
        • Dumas H.M.
        Hospital length of stay, discharge disposition, and reimbursement by clinical program group in pediatric post-acute rehabilitation.
        J Pediatr Rehabil Med. 2013; 6: 29-34
        • Fox C.K.
        • Johnston S.C.
        • Sidney S.
        • Fullerton H.J.
        High critical care usage due to pediatric stroke: results of a population-based study.
        Neurology. 2012; 79: 420-427
        • Sasaki J.
        • Chegondi M.
        • Raszynski A.
        • Totapally B.R.
        Outcome of children with acute encephalitis and refractory status epilepticus.
        J Child Neurol. 2014; 29: 1638-1644
        • Thakur K.T.
        • Motta M.
        • Asemota A.O.
        • Kirsch H.L.
        • Benavides D.R.
        • Schneider E.B.
        • et al.
        Predictors of outcome in acute encephalitis.
        Neurology. 2013; 81: 793-800
        • Singh T.D.
        • Fugate J.E.
        • Rabinstein A.A.
        The spectrum of acute encephalitis: causes, management, and predictors of outcome.
        Neurology. 2015; 84: 359-366
        • Pillai S.C.
        • Hacohen Y.
        • Tantsis E.
        • Prelog K.
        • Merheb V.
        • Kesson A.
        • et al.
        Infectious and autoantibody-associated encephalitis: clinical features and long-term outcome.
        Pediatrics. 2015; 135: e974-e984
        • DuBray K.
        • Anglemyer A.
        • LaBeaud A.D.
        • Flori H.
        • Bloch K.
        • Joaquin K.S.
        • et al.
        Epidemiology, outcomes, and predictors of recovery in childhood encephalitis.
        Pediatr Infect Dis J. 2013; 32: 1
        • Hoover K.W.
        • Tao G.
        • Kent C.K.
        Trends in the diagnosis and treatment of ectopic pregnancy in the United States.
        Obstet Gynecol. 2010; 115: 495-502
        • Ghelani S.J.
        • Spaeder M.C.
        • Pastor W.
        • Spurney C.F.
        • Klugman D.
        Demographics, trends, and outcomes in pediatric acute myocarditis in the United States, 2006 to 2011.
        Circ Cardiovasc Qual Outcomes. 2012; 5: 622-627
        • Rajagopal S.K.
        • Almond C.S.
        • Laussen P.C.
        • Rycus P.T.
        • Wypij D.
        • Thiagarajan R.R.
        Extracorporeal membrane oxygenation for the support of infants, children, and young adults with acute myocarditis: a review of the Extracorporeal Life Support Organization registry.
        Crit Care Med. 2010; 38: 382-387
        • von Keudell A.G.
        • Weaver M.J.
        • Appleton P.T.
        • Bae D.S.
        • Dyer G.S.M.
        • Heng M.
        • et al.
        Diagnosis and treatment of acute extremity compartment syndrome.
        Lancet. 2015; 386: 1299-1310
        • Berthelot S.
        • Lang E.S.
        • Quan H.
        • Stelfox H.T.
        What are emergency-sensitive conditions? A survey of Canadian emergency physicians and nurses.
        CJEM. 2015; 17: 154-160
        • Williams D.J.
        • Shah S.S.
        • Myers A.
        • Hall M.
        • Auger K.
        • Queen M.A.
        • et al.
        Identifying pediatric community-acquired pneumonia hospitalizations.
        JAMA Pediatr. 2013; 167: 851
        • Feudtner C.
        • Hays R.M.
        • Haynes G.
        • Geyer J.R.
        • Neff J.M.
        • Koepsell T.D.
        Deaths attributed to pediatric complex chronic conditions: national trends and implications for supportive care services.
        Pediatrics. 2001; 107: e99
        • Berkowitz S.A.
        • Traore C.Y.
        • Singer D.E.
        • Atlas S.J.
        Evaluating area-based socioeconomic status indicators for monitoring disparities within health care systems: Results from a primary care network.
        Health Serv Res. 2015; 50: 398-417
        • Schlapbach L.J.
        • Straney L.
        • Alexander J.
        • MacLaren G.
        • Festa M.
        • Schibler A.
        • et al.
        Mortality related to invasive infections, sepsis, and septic shock in critically ill children in Australia and New Zealand, 2002–13: a multicentre retrospective cohort study.
        Lancet Infect Dis. 2015; 15: 46-54
        • Balamuth F.
        • Weiss S.L.
        • Hall M.
        • Neuman M.I.
        • Scott H.
        • Brady P.W.
        • et al.
        Identifying pediatric severe sepsis and septic shock: accuracy of diagnosis codes.
        J Pediatr. 2015; 167: 1295-1300.e4
        • Campbell B.T.
        • Austin D.M.
        • Kahn O.
        • McCann M.C.
        • Lerer T.J.
        • Lee K.
        • et al.
        Current trends in the surgical treatment of pediatric ovarian torsion: we can do better.
        J Pediatr Surg. 2015; 50: 1374-1377
        • Goeggel Simonetti B.
        • Cavelti A.
        • Arnold M.
        • Bigi S.
        • Regényi M.
        • Mattle H.P.
        • et al.
        Long-term outcome after arterial ischemic stroke in children and young adults.
        Neurology. 2015; 84: 1941-1947
        • Takhar S.S.
        • Ting S.A.
        • Camargo C.A.
        • Pallin D.J.
        U.S. emergency department visits for meningitis, 1993-2008.
        Acad Emerg Med. 2012; 19: 632-639
        • Barnhart K.T.
        Ectopic pregnancy.
        N Engl J Med. 2009; 361: 379-387
        • Alessandrini E.A.
        • Alpern E.R.
        • Chamberlain J.M.
        • Shea J.A.
        • Gorelick M.H.
        A new diagnosis grouping system for child emergency department visits.
        Acad Emerg Med. 2010; 17: 204-213
        • Khera R.
        • Dorsey K.B.
        • Krumholz H.M.
        Transition to the ICD-10 in the United States.
        JAMA. 2018; 320: 133
        • Columbo J.A.
        • Kang R.
        • Trooboff S.W.
        • Jahn K.S.
        • Martinez C.J.
        • Moore K.O.
        • et al.
        Validating publicly available crosswalks for translating icd-9 to icd-10 diagnosis codes for cardiovascular outcomes research.
        Circ Cardiovasc Qual Outcomes. 2018; 11

      Linked Article

      • Pediatric emergency care—A method to drive action
        The Journal of PediatricsVol. 214
        • In Brief
          Most pediatric emergency department (ED) care occurs in non-pediatric EDs, and EDs vary widely in their readiness to care for pediatric cases and in the access of children to high pediatric-readiness emergency care (J Pediatr 2018;194:225-32). At the same time, research regarding pediatric ED outcomes reflects practice in urban academic centers. We lack ways to objectively and efficiently compare pediatric care across EDs. Although adult providers have established methodology to do so using administrative data, we have lacked a comparable approach in pediatrics.
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