Validation of algorithms to identify adverse perinatal outcomes in the Medicaid Analytic Extract database.

BACKGROUND: The Medicaid Analytic eXtract (MAX) is a health care utilization database from publicly insured individuals that has been used for studies of drug safety in pregnancy. Claims-based algorithms for defining many important maternal and neonatal outcomes have not been validated. OBJECTIVE: To validate claims-based algorithms for identifying selected pregnancy outcomes in MAX using hospital medical records. METHODS: The medical records of mothers who delivered between 2000 and 2010 within a single large healthcare system were linked to their claims in MAX. Claims-based algorithms for placental abruption, preeclampsia, postpartum hemorrhage, small for gestational age, and noncardiac congenital malformation were defined. Fifty randomly sampled cases for each outcome identified using these algorithms were selected, and their medical records were independently reviewed by two physicians to confirm the presence of the diagnosis of interest; disagreements were resolved by a third physician reviewer. Positive predictive values (PPVs) and 95% confidence intervals (CIs) of the claims-based algorithms were calculated using medical records as the gold standard. RESULTS: The linked cohort included 10,899 live-birth pregnancies. The PPV was 92% (95% CI, 82%-97%) for placental abruption, 82% (95% CI, 70%-91%) for preeclampsia, 74% (95% CI, 61%-85%) for postpartum hemorrhage, 92% (95% CI, 82%-97%) for small for gestational age, and 86% (95% CI, 74%-94%) for noncardiac congenital malformation. CONCLUSIONS: Across the perinatal outcomes considered, PPVs ranged between 74% and 92%. These PPVs can inform bias analyses that correct for outcome misclassification.

Determinants of Depressive Symptoms at 1 Year Following ICU Discharge in Survivors of ≥ 7 Days of Mechanical Ventilation: Results From the RECOVER Program, a Secondary Analysis of a Prospective Multicenter Cohort Study.

BACKGROUND: Moderate to severe depressive symptoms occur in up to one-third of patients at 1 year following ICU discharge, negatively affecting patient outcomes. This study evaluated patient and caregiver factors associated with the development of these symptoms. METHODS: This study used the Rehabilitation and Recovery in Patients after Critical Illness and Their Family Caregivers (RECOVER) Program (Phase 1) cohort of 391 patients from 10 medical/surgical university-affiliated ICUs across Canada. We determined the association between patient depressive symptoms (captured by using the Beck Depression Inventory II [BDI-II]), patient characteristics (age, sex, socioeconomic status, Charlson score, and ICU length of stay [LOS]), functional independence measure (FIM) motor subscale score, and caregiver characteristics (Caregiver Assistance Scale and Center for Epidemiologic Studies-Depression Scale) by using linear mixed models at time points 3, 6, and 12 months. RESULTS: BDI-II data were available for 246 patients. Median age at ICU admission was 56 years (interquartile range, 45-65 years), 143 (58%) were male, and median ICU LOS was 19 days (interquartile range, 13-32 days). During the 12-month follow-up, 67 of 246 (27.2%) patients had a BDI-II score ≥ 20, indicating moderate to severe depressive symptoms. Mixed models showed worse depressive symptoms in patients with lower FIM motor subscale scores (1.1 BDI-II points per 10 FIM points), lower income status (by 3.7 BDI-II points; P = .007), and incomplete secondary education (by 3.8 BDI-II points; P = .009); a curvilinear relation with age (P = .001) was also reported, with highest BDI-II at ages 45 to 50 years. No associations were found between patient BDI-II and comorbidities (P = .92), sex (P = .25), ICU LOS (P = .51), or caregiver variables (Caregiver Assistance Scale [P = .28] and Center for Epidemiologic Studies Depression Scale [P = .74]). CONCLUSIONS: Increased functional dependence, lower income, and lower education are associated with increased severity of post-ICU depressive symptoms, whereas age has a curvilinear relation with symptom severity. Knowledge of risk factors may inform surveillance and targeted mental health follow-up. Early mobilization and rehabilitation aiming to improve function may serve to modify mood disorders.