Identifying Children with Lifelong Chronic Conditions for Care Coordination by Using Hospital Discharge Data

Neff, John M.; Clifton, Holly; Park, Kathleen J.; Goldenberg, Caren; Popalisky, Jean; Stout, James; Danielson, Benjamin

doi:10.1016/j.acap.2010.08.009

Cited by 39 publications

(30 citation statements)

References 21 publications

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“…Furthermore, encounters for conditions that do not result in a claim will not be captured in administrative data. Any manual assessment of medical records data are subject to human error; however, the reviewer for the present study is experienced in this type of review 22 and brought cases in which she was unsure to the physician panel for evaluation. Assignment of the body system and progressive flags to ICD-9-CM codes in PMCA was based on the clinical experience of 2 authors; others may thus disagree with our designations of whether a condition is progressive or with body system assignments for conditions.…”

Section: Discussionmentioning

confidence: 99%

Pediatric Medical Complexity Algorithm: A New Method to Stratify Children by Medical Complexity

Simon

Cawthon

Stanford³

et al. 2014

Pediatrics

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373

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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. An existing ICD-9-CM–based algorithm called the Chronic Disability Payment System was modified to develop a new algorithm called the Pediatric Medical Complexity Algorithm (PMCA). The sensitivity and specificity of PMCA were assessed. RESULTS: Using hospital discharge data, PMCA’s sensitivity for correctly classifying children was 84% for C-CD, 41% for NC-CD, and 96% for those without CD. Using Medicaid claims data, PMCA’s sensitivity was 89% for C-CD, 45% for NC-CD, and 80% for those without CD. Specificity was 90% to 92% in hospital discharge data and 85% to 91% in Medicaid claims data for all 3 groups. CONCLUSIONS: PMCA identified children with C-CD (who have accessed tertiary hospital care) with good sensitivity and good to excellent specificity when applied to hospital discharge or Medicaid claims data. PMCA may be useful for targeting resources such as care coordination to children with C-CD.

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Section: Discussionmentioning

confidence: 99%

Pediatric Medical Complexity Algorithm: A New Method to Stratify Children by Medical Complexity

Simon

Cawthon

Stanford³

et al. 2014

Pediatrics

Self Cite

373

282

View full text Add to dashboard Cite

show abstract

“…Furthermore, encounters for conditions that do not result in a claim, or claims not submitted by managed care organizations to Medicaid, will not be captured in Medicaid administrative data. Any manual assessment of medical records data is subject to human error; however, the independent reviewer for this study is experienced in this type of review 4,9 and brought cases where she was unsure to the physician panel for evaluation. We also anticipate the need for additional changes to and additional validation work on PMCA to ensure compatibility with the recent widespread adoption of International Classification of Diseases, Tenth Revision, Clinical Modification codes.…”

Section: Discussionmentioning

confidence: 99%

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

Simon

Cawthon

Popalisky³

et al. 2017

Hospital Pediatrics

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“…21 There are also proprietary software algorithms available. 22,23 Our method of assignment to hospitals may have misattributed some patients, although we did note high localization indices. Furthermore, our analysis does not distinguish whether the variation in care is driven by inpatient, outpatient, or emergency care and cannot link the variation encountered to patient outcomes.…”

Section: Figurementioning

confidence: 92%

Hospital Variation in Health Care Utilization by Children With Medical Complexity

et al. 2015

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BACKGROUND: Although children with medical complexity have high health care needs, little is known about the variation in care provided between centers. This information may be particularly useful in identifying opportunities to improve quality and reduce costs. METHODS:We conducted a retrospective population-based observational cohort study using all payer claims databases for children aged 30 days to ,18 years residing in Maine, New Hampshire, and Vermont from 2007 to 2010. We identified hospital-affiliated cohorts (n = 6) of patients (n = 8216) with medical complexity by using diagnostic codes from both inpatient and outpatient claims. Children were assigned to the hospital where they received the most inpatient days, or their outpatient visits if no hospitalization occurred. Outcomes of interest included patient encounters, medical imaging, and diagnostic testing. Adjusted relative rates were calculated with overdispersed Poisson regression models.RESULTS: Adjusting for patient characteristics, the number of inpatient (relative rate 0.84 vs 2.28) and intensive care days (relative rate 0.45 vs 1.28) varied by more than twofold, whereas office (relative rate 0.77 vs 1.12) and emergency department visits (relative rate 0.71 vs 1.37) varied to a lesser extent. There was also marked variation in the use of imaging, and other diagnostic tests, with particularly high variation in electrocardiography (relative rate 0.35 vs 2.81) and head MRI (relative rate 0.72 vs 2.12).CONCLUSIONS: Depending on where they receive care, children with medical complexity experience widely different patterns of utilization. These findings indicate the need for identifying best practices for this growing patient population.WHAT'S KNOWN ON THIS SUBJECT: Children with medical complexity require a disproportionate amount of health services due to a multitude of chronic severe illness, and their impact on the health care system appears to be increasing. WHAT THIS STUDY ADDS:This study provides one of the first comparisons of health care utilization patterns for children with medical complexity between medical centers in a population-based cohort.

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Identifying Children with Lifelong Chronic Conditions for Care Coordination by Using Hospital Discharge Data

Cited by 39 publications

References 21 publications

Pediatric Medical Complexity Algorithm: A New Method to Stratify Children by Medical Complexity

Pediatric Medical Complexity Algorithm: A New Method to Stratify Children by Medical Complexity

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

Hospital Variation in Health Care Utilization by Children With Medical Complexity

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