RESUMEN
STUDY OBJECTIVES: We examined the performance of a simple algorithm to accurately distinguish cases of diagnosed obstructive sleep apnea (OSA) and noncases using the electronic health record (EHR) across six health systems in the United States. METHODS: Retrospective analysis of EHR data was performed. The algorithm defined cases as individuals with ≥ 2 instances of specific International Classification of Diseases (ICD)-9 and/or ICD-10 diagnostic codes (327.20, 327.23, 327.29, 780.51, 780.53, 780.57, G4730, G4733 and G4739) related to sleep apnea on separate dates in their EHR. Noncases were defined by the absence of these codes. Using chart reviews on 120 cases and 100 noncases at each site (n = 1,320 total), positive predictive value (PPV) and negative predictive value (NPV) were calculated. RESULTS: The algorithm showed excellent performance across sites, with a PPV (95% confidence interval) of 97.1 (95.6, 98.2) and NPV of 95.5 (93.5, 97.0). Similar performance was seen at each site, with all NPV and PPV estimates ≥ 90% apart from a somewhat lower PPV of 87.5 (80.2, 92.8) at one site. A modified algorithm of ≥ 3 instances improved PPV to 94.9 (88.5, 98.3) at this site, but excluded an additional 18.3% of cases. Thus, performance may be further improved by requiring additional codes, but this reduces the number of determinate cases. CONCLUSIONS: A simple EHR-based case-identification algorithm for diagnosed OSA showed excellent predictive characteristics in a multisite sample from the United States. Future analyses should be performed to understand the effect of undiagnosed disease in EHR-defined noncases. This algorithm has wide-ranging applications for EHR-based OSA research.
Asunto(s)
Registros Electrónicos de Salud , Apnea Obstructiva del Sueño , Algoritmos , Humanos , Clasificación Internacional de Enfermedades , Estudios Retrospectivos , Apnea Obstructiva del Sueño/diagnósticoRESUMEN
OBJECTIVE: To evaluate the incidence of clinically important traumatic brain injury (ciTBI) in children presenting to a community hospital setting and identified factors associated with computed tomography (CT) use. STUDY DESIGN: Retrospective cohort study of consecutive children presenting with blunt head trauma to a community emergency department or clinic over 12 months. Logistic regression models were used to compare differences in characteristics between patients who received and did not receive CT scans. RESULTS: Of 1007 patients, 62% male, age 14 days-18 years (270 <2 years, 737 ≥2 years), 189 (18%) had CT scans, 2 (0.2%) showed evidence of ciTBI on CT, 13 (1.3%) hospitalized, and none required neurosurgical intervention or died. Factors associated with CT use in patients ≥2 years: history of vomiting (OR 4.08, 95% CI 2.08-7.99, P < .001), change in behavior (OR 2.83, 95% CI 1.63-4.91, P < .001), headache (OR 3.4, 95% CI 1.87-6.16, P < .001), loss of consciousness (OR 2.83, 95% CI 1.38-5.8, P = .004), and abnormal neurologic examination (OR 26.18, 95% CI 2.26-303.05, P = .009). Patients were more likely to receive CT scans in community emergency departments than clinics (OR 7.04, 95% CI 2.40-20.65, P = .002). CONCLUSION: Patients in our community hospital setting are at low risk of ciTBI. The clinical indicators used to determine the need for CT in patients with more significant mechanisms of injury to pediatric or academic centers may not apply to this group. Future studies are required to determine which clinical indications are significant in this setting.
Asunto(s)
Traumatismos Cerrados de la Cabeza/diagnóstico por imagen , Tomografía Computarizada por Rayos X , Adolescente , Algoritmos , Niño , Preescolar , Servicios de Salud Comunitaria , Femenino , Hospitales Comunitarios , Humanos , Lactante , Recién Nacido , Modelos Logísticos , Masculino , Análisis Multivariante , Examen NeurológicoRESUMEN
This paper reviews methodological and theoretical fidelity of secondhand smoking (SHS) intervention studies (n = 29) that target protection of children in their home. In 2005, interventions were evaluated in terms of treatment fidelity according to guidelines provided by Borrelli et al. of the National Institutes of Health Behavior Change Consortium. The degree of fidelity was evaluated based on the percentage of criteria met; the inter-rater reliability based on percent agreement across independent raters was 0.78. Analysis indicated that studies with higher treatment fidelity were more likely to obtain statistically significant results (p = .003) with the average fidelity rating of 0.74 for statistically significant studies vs. 0.50 for statistically non-significant studies. Higher treatment fidelity was also significantly associated with being a more recent investigation (year 2000 or later), an efficacy as compared to effectiveness trial, more intensive as compared to less intensive intervention, a trial in the U.S. as compared to foreign nations, and having a theoretical basis. After taking all other variables into account, only treatment fidelity was significantly related to study outcome (p = .052). Ratings of treatment fidelity were ranked and compared to previous rankings based on 342 behavioral change interventions; the rank-ordered correlation between previous and current ratings was 0.84, although median fidelity ratings were 0.10 points lower in the previous than in the present study (0.52 vs. 0.62; intraclass correlation = 0.79). Improvements to the treatment fidelity evaluation guidelines were suggested, including the consideration of theoretical fidelity. Enhancing methodological and theoretical fidelity will speed identification of valid theoretical precepts that will, in turn, guide effective public health prevention programs.