Development and Validation of the Pediatric Medical Complexity Algorithm (PMCA) Version 2.0.

Background And Objectives: The Pediatric Medical Complexity Algorithm (PMCA) was developed to stratify children by level of medical complexity. We sought to refine PMCA and evaluate its performance based on the duration of eligibility and completeness of Medicaid data.

Methods: PMCA version 1.

The effectiveness of family-centered transition processes from hospital settings to home: a review of the literature.

Background And Objectives: The quality of care transitions is of growing concern because of a high incidence of postdischarge adverse events, poor communication with patients, and inadequate information transfer between providers. The objective of this study was to conduct a targeted literature review of studies examining the effectiveness of family-centered transition processes from hospital- and emergency department (ED)-to-home for improving patient health outcomes and health care utilization.

Methods: We conducted an electronic search (2001-2012) of PubMed, CINAHL, Cochrane, PsycInfo, Embase, and Web of Science databases.

Stratification of children by medical complexity.

Objective: To stratify children using available software, Clinical Risk Groups (CRGs), in a tertiary children's hospital, Seattle Children's Hospital (SCH), and a state's Medicaid claims data, Washington State (WSM), into 3 condition groups: complex chronic disease (C-CD); noncomplex chronic disease (NC-CD), and nonchronic disease (NC).

Methods: A panel of pediatricians developed consensus definitions for children with C-CD, NC-CD, and NC. Using electronic medical record review and expert consensus, a gold standard population of 700 children was identified and placed into 1 the 3 groups: 350 C-CD, 100 NC-CD, and 250 NC.

Improving care for pediatric diabetic ketoacidosis.

Objective: We sought to create and implement recommendations from an evidence-based pathway for hospital management of pediatric diabetic ketoacidosis (DKA) and to sustain improvement. We hypothesized that development and utilization of standard work for inpatient care of DKA would lead to reduction in hypokalemia and improvement in outcome measures.

Methods: Development involved systematic review of published literature by a multidisciplinary team.

Nutrition Interventions to Optimize Pediatric Wound Healing: An Evidence-Based Clinical Pathway.

Background and Objective: There is no accepted nutrition approach for wound healing in children. Our aims were to determine optimal nutrition support for pediatric wound healing. Methods: We applied local methods to create evidence- and consensus-based recommendations, supported by implementation tools, including algorithms, clinical decision supports, and measures.

Pediatric medical complexity algorithm: a new method to stratify children by medical complexity.

Objectives: The goal of this study was to develop an algorithm based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM), codes for classifying children with chronic disease (CD) according to level of medical complexity and to assess the algorithm's sensitivity and specificity.

Methods: A retrospective observational study was conducted among 700 children insured by Washington State Medicaid with ≥1 Seattle Children's Hospital emergency department and/or inpatient encounter in 2010. The gold standard population included 350 children with complex chronic disease (C-CD), 100 with noncomplex chronic disease (NC-CD), and 250 without CD.

Identifying children with lifelong chronic conditions for care coordination by using hospital discharge data.

Background: Children with lifelong chronic conditions (LLCC) are costly, of low prevalence, and a high proportion of patients at children's hospitals. Few methods identify these patients.

Objectives: We sought to identify children with LLCC in hospital discharge data for care coordination by using clinical risk groups (CRGs), to evaluate the accuracy of this methodology compared with a chart review and to investigate accuracy according to condition groups.

Care management for children with special needs: Part II: the role of primary care.

This study documents care management services in 2 pediatric clinics for children with or at risk for a chronic condition during 8 months in 2005. Patients were identified by the clinic staff from a list provided by the health plan of patients at risk for or with a chronic condition. Care management services were documented for 161 of 189 selected patients.

Care management for children with special needs: part I: the role of health plans.

This study documents screening methods and services provided by health plan case managers for high need children in a Washington State health plan. Enrollees were screened to identify 315 children who had or were at risk of developing a chronic condition and were high users of health services. From this group, 46 children/families could be contacted and needed case management.

Using medical billing data to evaluate chronically ill children over time.

This study evaluates stability of chronic condition identification in children older than 4 years in a health plan billing data using Clinical Risk Groups. A total of 31,055 children were continuously enrolled for 4 years; 7.5% (2,334) identified with a chronic condition status in year 1, 2002, and another 15.

Identifying and classifying children with chronic conditions using administrative data with the clinical risk group classification system.

Objective: To identify and categorize children with chronic health conditions using administrative data.

Methods: The Clinical Risk Groups (CRGs) system is used to classify children, aged 0-18 years, in a mid-sized health plan into mutually exclusive categories and severity groups. Enrollees are categorized into 9 health status groups--healthy, significant acute, and 7 chronic conditions--and are then stratified by severity.