1 40 1 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource June 2022 List Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Citation List Month June 2022 List URL Address <a href="http://doi.org/10.1001/jamapediatrics.2022.0687" target="_blank" rel="noreferrer noopener">http://doi.org/​10.1001/jamapediatrics.2022.0687</a> Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Prevalence of Children With Medical Complexity and Associations With Health Care Utilization and In-Hospital Mortality Publisher An entity responsible for making the resource available JAMA Pediatrics Date A point or period of time associated with an event in the lifecycle of the resource 2022 Subject The topic of the resource Children; Health care utilization; Hospital; Medical complexity; Mortality Creator An entity primarily responsible for making the resource Leyenaar JK; Schaefer AP; Freyleue SD; Austin AM; Simon TD; Van Cleave J; Moen EL; O'Malley AJ; Goodman DC Description An account of the resource IMPORTANCE: Children with medical complexity (CMC) have substantial health care needs and frequently experience poor health care quality. Understanding the population prevalence and associated health care needs can inform clinical and public health initiatives. OBJECTIVE: To estimate the prevalence of CMC using open-source pediatric algorithms, evaluate performance of these algorithms in predicting health care utilization and in-hospital mortality, and identify associations between medical complexity as defined by these algorithms and clinical outcomes. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study used all-payer claims data from Colorado, Massachusetts, and New Hampshire from 2012 through 2017. Children and adolescents younger than 18 years residing in these states were included if they had 12 months or longer of enrollment in a participating health care plan. Analyses were conducted from March 12, 2021, to January 7, 2022. EXPOSURES: The pediatric Complex Chronic Condition Classification System, Pediatric Medical Complexity Algorithm, and Children With Disabilities Algorithm were applied to 3 years of data to identify children with complex and disabling conditions, first in their original form and then using more conservative criteria that required multiple health care claims or involvement of 3 or more body systems. MAIN OUTCOMES AND MEASURES: Primary outcomes, examined over 2 years, included in-hospital mortality and a composite measure of health care services, including specialized therapies, specialized medical equipment, and inpatient care. Outcomes were modeled using logistic regression. Model performance was evaluated using C statistics, sensitivity, and specificity. RESULTS: Of 1 936 957 children, 48.4% were female, 87.8% resided in urban core areas, and 45.1% had government-sponsored insurance as their only primary payer. Depending on the algorithm and coding criteria applied, 0.67% to 11.44% were identified as CMC. All 3 algorithms had adequate discriminative ability, sensitivity, and specificity to predict in-hospital mortality and composite health care services (C statistic = 0.76 [95% CI, 0.73-0.80] to 0.81 [95% CI, 0.78-0.84] for mortality and 0.77 [95% CI, 0.76-0.77] to 0.80 [95% CI, 0.79-0.80] for composite health care services). Across algorithms, CMC had significantly greater odds of mortality (adjusted odds ratio [aOR], 9.97; 95% CI, 7.70-12.89; to aOR, 69.35; 95% CI, 52.52-91.57) and composite health care services (aOR, 4.59; 95% CI, 4.44-4.73; to aOR, 18.87; 95% CI, 17.87-19.93) than children not identified as CMC. CONCLUSIONS AND RELEVANCE: In this study, open-source algorithms identified different cohorts of CMC in terms of prevalence and magnitude of risk, but all predicted increased health care utilization and in-hospital mortality. These results can inform research, programs, and policies for CMC. Identifier An unambiguous reference to the resource within a given context <a href="http://doi.org/10.1001/jamapediatrics.2022.0687" target="_blank" rel="noreferrer noopener">10.1001/jamapediatrics.2022.0687</a> Rights Information about rights held in and over the resource Article information provided for research and reference use only. PedPalASCNET does not hold any rights over the resource listed here. All rights are retained by the journal listed under publisher and/or the creator(s). 2022 April 2022 List Austin AM Children Freyleue SD Goodman DC Health Care Utilization Hospital JAMA Pediatrics Leyenaar JK Medical Complexity Moen EL Mortality O'Malley AJ Schaefer AP Simon TD Van Cleave J