RESUMO
AIM: To characterize antibiotic (ab) prescriptions in children. METHODS: Evaluation of outpatient ab prescriptions in a 3-year cohort of children in primary care using a data warehouse (Massachusetts Health Disparities Repository) by comorbid conditions, demographics, and clinical indication. RESULTS: A total of 15 208 children with nearly 120 000 outpatient visits were included. About one third had a comorbid condition (most commonly asthma). Among the 30 000 ab prescriptions, first-line penicillins and macrolides represented the most frequent ab (70%), followed by cephalosporins (16%). Comorbid children had 54.3 ab prescriptions/100 child-years versus 38.8 in children without comorbidity; ab prescription was higher in urinary tract infections (>60% of episodes), otitis, lower respiratory tract infections (>50%), especially in comorbid children and children under 2 year old. Ab prescriptions were significantly associated with younger age, emergency room visit, comorbid children, and acute infections. DISCUSSION: A clinical data warehouse could help in designing appropriate antimicrobial stewardship programs and represent a potential assessment tool.
Assuntos
Antibacterianos/uso terapêutico , Uso de Medicamentos , Prescrição Inadequada/estatística & dados numéricos , Infecções Respiratórias/tratamento farmacológico , Infecções Urinárias/tratamento farmacológico , Assistência Ambulatorial/métodos , Gestão de Antimicrobianos , Criança , Pré-Escolar , Estudos de Coortes , Data Warehousing , Prescrições de Medicamentos/estatística & dados numéricos , Feminino , Humanos , Lactente , Masculino , Massachusetts , Testes de Sensibilidade Microbiana , Pacientes Ambulatoriais/estatística & dados numéricos , Infecções Respiratórias/diagnóstico , Estudos Retrospectivos , Infecções Urinárias/diagnósticoRESUMO
Care and outcomes for individuals living with sickle cell disease (SCD) vary across institutions and communities. The Hemoglobinopathy Learning Collaborative (HLC) seeks to improve outcomes across the life course through improvement science. Faculty identified five key drivers of improved outcomes: a strong community network; knowledgeable, proactive individuals, families and providers; reliable identification and follow-up; seamless co-management between primary and specialty care; and appropriate treatment for acute episodes. Using a modified Delphi process, we selected improvement measures aligned with the drivers. Data are collected via a Web-based system linked to a reporting portal. Participating teams include consumers, community organizations and primary and specialty care providers. This commentary reviews the context of SCD in the U.S.; describes the framework, measures, and technology infrastructure already created for the HLC; reports on the early experience of teams; highlights the initiative's challenges and opportunities; and reflects on its implications in the setting of health reform.