Medical practice variability refers to differences in treatment and clinical outcomes that cannot be solely explained by patient characteristics or medical conditions. This variability can lead to inconsistent outcomes, especially in complex environments like pediatric inpatient wards. Standardization of care protocols is proposed as a way to reduce this inconsistency.
Medical practice variability refers to differences in treatment and clinical outcomes that cannot be solely explained by patient characteristics or medical conditions. This variability can lead to inconsistent outcomes, especially in complex environments like pediatric inpatient wards. Standardization of care protocols is proposed as a way to reduce this inconsistency. One key area of variability is the diagnosis and treatment of respiratory infections, particularly distinguishing bacterial from viral bronchial infections. Due to the lack of definitive clinical criteria, there is widespread antibiotic use (65-80% of cases), despite ongoing debate about their effectiveness. Implementing standardized management protocols in pediatric wards aims to reduce such variability and improve clinical outcomes. This study will attempt to measure variability in outcomes based on treatment variables, identifying sources of medical variability and their impact.
Study Type
OBSERVATIONAL
Enrollment
380
HGNPE
Buenos Aires, Argentina
Variability in the treatment:Length of Hospital Stay
* Definition: Total number of full calendar days from admission to pediatric ward until medical discharge. * Measurement: Recorded in patient's medical record. Calculated as discharge date - admission date. * Type of Variable: Continuous (days). * Analysis: Mean/median days compared between groups after Propensity Score Matching.
Time frame: 2 years
Explore Clinical outcomes
* Definition: Incidence of adverse events during hospitalization, including nosocomial infections, escalation to ICU, or other significant medical complications. * Measurement: Categorical (Yes/No for each complication) documented in medical record with onset and resolution dates. * Type of Variable: Binary for each event; total count of events per patient can also be analyzed. * Analysis: Proportion of patients experiencing ≥1 complication compared between groups after Propensity Score Matching.
Time frame: 2 years
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