RESUMO
Blood transfusion is a common medical intervention for patients with sickle cell disease (SCD) and disease related complications. While patients with SCD are at risk for all transfusion related adverse events defined by the National Healthcare Safety Network (NHSN) Biovigilance Component Hemovigilance Module Surveillance Protocol, they are uniquely susceptible to certain adverse events. This review discusses risk factors, mitigation strategies, and management recommendations for alloimmunization, hemolytic transfusion reactions, hyperviscosity and transfusion-associated iron overload in the context of SCD.
Assuntos
Anemia Falciforme , Reação Transfusional , Humanos , Transfusão de Eritrócitos/efeitos adversos , Transfusão de Eritrócitos/métodos , Reação Transfusional/complicações , Segurança do Sangue , Transfusão de Sangue/métodosAssuntos
Anemia Falciforme , Microangiopatias Trombóticas , Anemia Falciforme/complicações , Anemia Falciforme/tratamento farmacológico , Anticorpos Monoclonais Humanizados/uso terapêutico , Proteínas do Sistema Complemento , Humanos , Microangiopatias Trombóticas/tratamento farmacológico , Microangiopatias Trombóticas/etiologiaAssuntos
Encefalite Antirreceptor de N-Metil-D-Aspartato/terapia , Dislipidemias/complicações , Troca Plasmática/métodos , Encefalite Antirreceptor de N-Metil-D-Aspartato/complicações , Antipsicóticos/efeitos adversos , Criança , Feminino , Humanos , Piperazinas/efeitos adversos , Plasmaferese , Receptores de N-Metil-D-Aspartato/metabolismo , Tiazóis/efeitos adversosRESUMO
BACKGROUND: Pediatric patient blood management (PBM) programs require continuous surveillance of errors and near misses. However, most PBM programs rely on passive surveillance methods. Our objective was to develop and evaluate a set of automated trigger tools for active surveillance of pediatric PBM errors. MATERIALS AND METHODS: We used the Rand-UCLA method with an expert panel of pediatric transfusion medicine specialists to identify and prioritize candidate trigger tools for all transfused blood products. We then iteratively developed automated queries of electronic health record (EHR) data for the highest priority triggers. Two physicians manually reviewed a subset of cases meeting trigger tool criteria and estimated each trigger tool's positive predictive value (PPV). We then estimated the rate of PBM errors, whether they reached the patient, and adverse events for each trigger tool across four years in a single pediatric health system. RESULTS: We identified 28 potential triggers for pediatric PBM errors and developed 5 automated trigger tools (positive patient identification, missing irradiation, unwashed products despite prior anaphylaxis, transfusion lasting >4 hours, over-transfusion by volume). The PPV for ordering errors ranged from 38-100%. The most frequently detected near miss event reaching patients was first transfusions without positive patient identification (estimate 303, 95% CI: 288-318 per year). The only adverse events detected were from over-transfusions by volume, including 4 adverse events detected on manual review that had not been reported in passive surveillance systems. DISCUSSION: It is feasible to automatically detect pediatric PBM errors using existing data captured in the EHR that enable active surveillance systems. Over-transfusions may be one of the most frequent causes of harm in the pediatric environment.
RESUMO
Smartphone-based telehealth holds the promise of shifting healthcare from the clinic to the home, but the inability for clinicians to conduct remote palpation, or touching, a key component of the physical exam, remains a major limitation. This is exemplified in the assessment of acute abdominal pain, in which a physician's palpation determines if a patient's pain is life-threatening requiring emergency intervention/surgery or due to some less-urgent cause. In a step towards virtual physical examinations, we developed and report for the first time a "touch-capable" mHealth technology that enables a patient's own hands to serve as remote surrogates for the physician's in the screening of acute abdominal pain. Leveraging only a smartphone with its native accelerometers, our system guides a patient through an exact probing motion that precisely matches the palpation motion set by the physician. An integrated feedback algorithm, with 95% sensitivity and specificity, enabled 81% of tested patients to match a physician abdominal palpation curve with <20% error after 6 attempts. Overall, this work addresses a key issue in telehealth that will vastly improve its capabilities and adoption worldwide.