BackgroundOnly a small minority of trauma victims develops post-traumatic stress disorder (PTSD), suggesting that victims vary in their predispositions to the PTSD response to stressors. It is assumed that the role of predispositions in PTSD varies by trauma severity: when stressors are less severe, predispositions play a bigger role. In this study, we test whether the role of intelligence in PTSD varies by trauma severity. Specifically, does low intelligence plays a bigger part among victims of lower magnitude stressors than among victims of extreme stressors?MethodsData come from a longitudinal study of randomly selected sample in Southeast Michigan (n = 713). IQ was measured at age 6. PTSD was measured at age 17, using the NIMH-DIS for DSM-IV. Stressors were classified as extreme if they involved assaultive violence (e.g. rape, sexual assault, threatened with a weapon); other stressors in the list (e.g. disaster, accidents) were classified as lower magnitude. Assaultive violence victims had experienced assaultive violence plus other event types or only assaultive violence. Victims of other stressors were participants who had never experienced assaultive violence. We compared the influence of age 6 IQ on PTSD among persons exposed to assaultive violence vs. other stressors, using multinomial logistic regression.ResultsRelative risk ratio (RRR) for PTSD associated with a one point drop in age 6 IQ among victims of assaultive violence was 1.04 (95% CI 1.01, 1.06); among victims of other stressors, it was 1.03 (95% CI 0.99, 1.06). A comparison of the two RRRs indicates no significant difference between the two estimates (p = 0.652). IQ does not play a bigger role in PTSD among victims of other stressors than it does among victims of assaultive violence.ConclusionsLower IQ exerts an adverse PTSD effect on trauma victims, with no evidence of variability by the severity of trauma they have experienced.

BACKGROUND:The real world implementation of chronic care management model varies greatly. One aspect of this variation is the delivery mode. Two contrasting strategies include provider-delivered care management (PDCM) and health plan-delivered care management (HPDCM). OBJECTIVE: We aimed to compare the effectiveness of PDCM vs. HPDCM on improving clinical outcomes for patients with chronic diseases. DESIGN: We used a quasi-experimental two-group prepost design using the difference-in-differences method. PATIENTS: Commercially insured patients, with any of the five chronic diseases-congestive heart failure, chronic obstructive pulmonary disease, coronary heart disease, diabetes, or asthma, who were outreached to and engaged in either PDCM or HPDCM were included in the study. MAIN MEASURES: Outreached patients were those who received an attempted or actual contact for enrollment in care management; and engaged patients were those who had one or more care management sessions/encounters with a care manager. Effectiveness measures included blood pressure, low density lipoprotein (LDL), weight loss, and hemoglobin A1c (for diabetic patients only). Primary endpoints were evaluated in the first year of follow-up. KEY RESULTS: A total of 4,000 patients were clustered in 165 practices (31 in PDCM and 134 in HPDCM). The PDCM approach demonstrated a statistically significant improvement in the proportion of outreached patients whose LDL was under control: the proportion of patients with LDL < 100 mg/dL increased by 3 % for the PDCM group (95 % CI: 1 % to 6 %) and 1 % for the HPDCM group (95 % CI: −2 % to 5 %). However, the 2 % difference in these improvements was not statistically significant (95 % CI: −2 % to 6 %). The HPDCM approach showed 3 % [95 % CI: 2 % to 6 %] improvement in overall diabetes care among outreached patients and significant reduction in obesity rates compared to PDCM (4 %, 95 % CI: 0.3 % to 8 %). CONCLUSIONS: Both care management delivery modes may be viable options for improving care for patients with chronic diseases. In this commercially insured population, neither PDCM nor HPDCM resulted in substantial improvement in patients' clinical indicators in the first year. Different care management strategies within the provider-delivered programs need further investigation.

Background: To address the increasing burden of chronic disease, many primary care practices are turning to care management and the hiring of care managers to help patients coordinate their care and self-manage their conditions. Care management is often, but not always, proving effective at improving patient outcomes, but more evidence is needed. Methods: In this pair-matched cluster randomized trial, 5 practices implemented care management and were compared with 5 comparison practices within the same practice organization. Targeted patients included diabetic patients with a hemoglobin A1c >9% and nondiabetic obese patients. Clinical values tracked were A1c, blood pressure, low-density lipoprotein, microalbumin, and weight. Results: Clinically important improvements were demonstrated in the intervention versus comparison practices, with diabetic patients improving A1c control and obese patients experiencing weight loss. There was a 12% relative increase in the proportion of patients meeting the clinical target of A1c <7% (95% CI, 3%-20%), and 26% of obese nondiabetic patients in chronic care management practices lost 5% or more of their body weight as compared with 10% of comparison patients (adjusted relative improvement, 15%; CI, 2%-28%). Conclusions: These findings add to the growing evidence-base for the effectiveness of care management as an effective clinical practice with regard to improving diabetes- and obesity-related outcomes.