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

Simon, Tamara D.; Cawthon, Mary Lawrence; Popalisky, Jean; Mangione-Smith, Rita

doi:10.1542/hpeds.2016-0173

Cited by 65 publications

(35 citation statements)

References 10 publications

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“…28 We determined patient chronic medical complexity using the Pediatric Medical Complexity Algorithm Version 2 applied to 2014-2016 inpatient and outpatient claims. 29 This algorithm is used to identify children with 3 levels of chronic medical complexity: complex chronic disease, noncomplex chronic disease, and no chronic disease. 29 Matching To address differences in patients and conditions managed in the 3 settings, we used coarsened-exact matching, 30 which prunes observations to achieve covariate balance between groups.…”

Section: Patient and Visit Characteristicsmentioning

confidence: 99%

“…29 This algorithm is used to identify children with 3 levels of chronic medical complexity: complex chronic disease, noncomplex chronic disease, and no chronic disease. 29 Matching To address differences in patients and conditions managed in the 3 settings, we used coarsened-exact matching, 30 which prunes observations to achieve covariate balance between groups. Instead of matching to a fixed number of visits, coarsened-exact matching matches DTC telemedicine visits to many matched urgent care visits and PCP visits and then weights each stratum or matched set.…”

Section: Patient and Visit Characteristicsmentioning

confidence: 99%

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Antibiotic Prescribing During Pediatric Direct-to-Consumer Telemedicine Visits

et al. 2019

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BACKGROUND AND OBJECTIVES: Use of commercial direct-to-consumer (DTC) telemedicine outside of the pediatric medical home is increasing among children, and acute respiratory infections (ARIs) are the most commonly diagnosed condition at DTC telemedicine visits. Our objective was to compare the quality of antibiotic prescribing for ARIs among children across 3 settings: DTC telemedicine, urgent care, and the primary care provider (PCP) office. METHODS:In a retrospective cohort study using 2015-2016 claims data from a large national commercial health plan, we identified ARI visits by children (0-17 years old), excluding visits with comorbidities that could affect antibiotic decisions. Visits were matched on age, sex, chronic medical complexity, state, rurality, health plan type, and ARI diagnosis category. Within the matched sample, we compared the percentage of ARI visits with any antibiotic prescribing and the percentage of ARI visits with guideline-concordant antibiotic management.RESULTS: There were 4604 DTC telemedicine, 38 408 urgent care, and 485 201 PCP visits for ARIs in the matched sample. Antibiotic prescribing was higher for DTC telemedicine visits than for other settings (52% of DTC telemedicine visits versus 42% urgent care and 31% PCP visits; P , .001 for both comparisons). Guideline-concordant antibiotic management was lower at DTC telemedicine visits than at other settings (59% of DTC telemedicine visits versus 67% urgent care and 78% PCP visits; P , .001 for both comparisons).CONCLUSIONS: At DTC telemedicine visits, children with ARIs were more likely to receive antibiotics and less likely to receive guideline-concordant antibiotic management compared to children at PCP visits and urgent care visits.WHAT'S KNOWN ON THIS SUBJECT: Authors of previous studies identified concerns about antibiotic prescribing for adults using direct-to-consumer (DTC) telemedicine. No study has examined antibiotic prescribing during pediatric DTC telemedicine visits.WHAT THIS STUDY ADDS: Compared with urgent care and primary care visits, children receiving care for acute respiratory infections during DTC telemedicine visits are more likely to receive antibiotics and less likely to receive guideline-concordant antibiotic management.

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Section: Patient and Visit Characteristicsmentioning

confidence: 99%

Section: Patient and Visit Characteristicsmentioning

confidence: 99%

Antibiotic Prescribing During Pediatric Direct-to-Consumer Telemedicine Visits

et al. 2019

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“…Additional outcomes were healthcare service usage and in-hospital mortality. To investigate the impacts of patient characteristics and complexity of comorbid conditions on the group of 3GCs-resistant participants, the Pediatric Medical Complexity Algorithm (PMCA) [25,26] was employed and compared between sensitive and resistant groups (Supplementary Materials Table S1). To understand the contribution of an E. coli bloodstream infection around the time of an episode of E. coli CA-UTI, we investigated the discharge diagnosis of bacterial bloodstream infections from the index hospitalization.…”

Section: Outcome Measurementsmentioning

confidence: 99%

Trends in Antimicrobial Susceptibility of Escherichia coli Isolates in a Taiwanese Child Cohort with Urinary Tract Infections between 2004 and 2018

et al. 2020

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The aim of this study was to investigate the annual incidence of Escherichia coli isolates in urinary tract infections (UTIs) and the antimicrobial resistance of the third-generation cephalosporin (3GCs) to E. coli, including the factors associated with the resistance in hospitalized children in Taiwan. A large electronic database of medical records combining hospital admission and microbiological data during 2004–2018 was used to study childhood UTIs in Taiwan. Annual incidence rate ratios (IRR) of E. coli in children with UTIs and its resistant rate to the 3GCs and other antibiotics were estimated by linear Poisson regression. Factors associated with E. coli resistance to 3GCs were assessed through multivariable logistic regression analysis. E. coli UTIs occurred in 10,756 unique individuals among 41,879 hospitalized children, with 92.58% being community associated based on urine culture results reported within four days after the hospitalization. The overall IRR E. coli UTI was 1.01 (95% confidence interval (CI) 0.99–1.02) in community-associated (CA) and 0.96 (0.90–1.02) in healthcare-associated infections. The trend in 3GCs against E. coli increased (IRR 1.18, 95% CI 1.13–1.24) over time in CA-UTIs. Complex chronic disease (adjusted odds ratio (aOR), 2.04; 95% CI, 1.47–2.83) and antibiotics therapy ≤ 3 months prior (aOR, 1.49; 95% CI, 1.15–1.94) were associated with increased risk of 3GCs resistance to E. coli. The study results suggested little or no change in the trend of E. coli UTIs in Taiwanese youths over the past 15 years. Nevertheless, the increase in 3GCs-resistant E. coli was substantial. Interventions for children with complex chronic comorbidities and prior antibiotic treatment could be effective in reducing the incidence of 3GCs-resistant E. coli in CA-UTIs in this region and more generally.

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“…Age was categorized based on clinical criteria for children's growth (0-1, 2-4, [5][6][7][8][9][10][11][12][13][14]. Sex was a stratification variable.…”

Section: Exposure Variable and Covariatesmentioning

confidence: 99%

Socioeconomic inequalities in children under 15 with medical complexity: A population-based study

Carrilero

Ruiz-Muñoz

Dalmau-Bueno

et al. 2019

Preprint

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Background Health inequalities from the first stages of life onwards have consequences for children’s health status and for their future development. Children’s health is profoundly affected by the socioeconomic position (SEP) of their parents. The situation is even more disruptive in children with medically complex (CMC) conditions. The aim of this study is to describe the characteristics and related pathologies of CMC in Catalonia, and to assess the presence of socioeconomic inequalities.Methods Cross-sectional study and cluster analysis of the diseases in the CMC population under the age of 15 in Catalonia in 2016 using administrative data. Each pathology cluster obtained was described and its association with socioeconomic position (SEP) determined. The Adjusted Morbidity Groups (Catalan acronym GMA) classification system was used to identify the CMC. Main outcome measures: SEP, GMA score, sex, and age distribution were recorded in both populations (CMC and non-CMC) and in each of the clusters identified.Results 71% of the CMC population have at least one parent with no employment or an annual income of less than €18,000. Four comorbidity clusters were identified in CMC: respiratory (47%), neurodevelopmental (18%), hemato-oncological (12%), and perinatal disorders (23%). CMC experience higher levels of poverty and social disadvantage in all clusters. SES-cluster association results were: in the respiratory OR, 2.1 in boys and 2.1 in girls; in the neurodevelopmental disease, OR 2.0 in boys and 1.8 in girls; in the hemato-oncology OR, 1.7 in boys and 1.8 in girls; and in the perinatal OR, 1.7 in boys and 1.8 in girls.Conclusions There are socioeconomic health inequalities in childhood across a broad spectrum of health outcomes. Children with lower SEP are more likely to have CMC conditions. All clusters showed SEP inequalities and respiratory and neurodevelopment clusters are the most prevalent.

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

Abstract: A B S T R A C T 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.

Cited by 65 publications

References 10 publications

Antibiotic Prescribing During Pediatric Direct-to-Consumer Telemedicine Visits

Antibiotic Prescribing During Pediatric Direct-to-Consumer Telemedicine Visits

Trends in Antimicrobial Susceptibility of Escherichia coli Isolates in a Taiwanese Child Cohort with Urinary Tract Infections between 2004 and 2018

Socioeconomic inequalities in children under 15 with medical complexity: A population-based study

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