Opioid-related ADEs following surgery were associated with significantly increased LOS and hospitalization costs. These ADEs occurred more frequently in patients receiving higher doses of opioids.

BackgroundAlthough for more than a decade healthcare systems have attempted to provide evidence-based mental health treatments, the availability and use of psychotherapies remains low. A significant need exists to identify simple but effective implementation strategies to adopt complex practices within complex systems of care. Emerging evidence suggests that facilitation may be an effective integrative implementation strategy for adoption of complex practices. The current pilot examined the use of external facilitation for adoption of cognitive behavioral therapy (CBT) in 20 Department of Veteran Affairs (VA) clinics.MethodsThe 20 clinics were paired on facility characteristics, and 23 clinicians from these were trained in CBT. A clinic in each pair was randomly selected to receive external facilitation. Quantitative methods were used to examine the extent of CBT implementation in 10 clinics that received external facilitation compared with 10 clinics that did not, and to better understand the relationship between individual providers' characteristics and attitudes and their CBT use. Costs of external facilitation were assessed by tracking the time spent by the facilitator and therapists in activities related to implementing CBT. Qualitative methods were used to explore contextual and other factors thought to influence implementation.ResultsExamination of change scores showed that facilitated therapists averaged an increase of 19% [95% CI: (2, 36)] in self-reported CBT use from baseline, while control therapists averaged a 4% [95% CI: (-14, 21)] increase. Therapists in the facilitated condition who were not providing CBT at baseline showed the greatest increase (35%) compared to a control therapist who was not providing CBT at baseline (10%) or to therapists in either condition who were providing CBT at baseline (average 3%). Increased CBT use was unrelated to prior CBT training. Barriers to CBT implementation were therapists' lack of control over their clinic schedule and poor communication with clinical leaders.ConclusionsThese findings suggest that facilitation may help clinicians make complex practice changes such as implementing an evidence-based psychotherapy. Furthermore, the substantial increase in CBT usage among the facilitation group was achieved at a modest cost.

CTEPH and PAH patients incurred higher costs and used more resources than controls in the baseline and follow-up periods.

Objective: This study examines the prevalence of various cardiometabolic risk (CMR) factors that may contribute to metabolic syndrome in a primary care setting. These risk factors were accessed with use of a national electronic health record database. Methods: In the database, from January 1, 2003 to December 31, 2004, patients aged 18 to 64 years with information regarding CMR factors were identified by clinical (biometrics), diagnosis (ICD-9 codes) or treatment (prescriptions) information. Results:The study population consisted of 475,651 patients with information on indicators of CMR, excluding patients with bariatric surgery or a body mass index (BMI) ≥ 35 kg/ m 2 . Of these, 72,593 (!5.3%) and 55,928 (11.8%) had metabolic syndrome according to the National Cholesterol Education Program (NCEP) and International Diabetes Federation (IDF) criteria, respectively. In addition, 162,521 (34.2%) had BMI (≥27 kg/m 2 ) as a risk factor. High blood pressure was identified as a risk factor in 266,371 patients (56.0%). High triglycerides were identified as a risk factor in 10.7% of the population, low high-density lipoprotein in 16.0%, impaired-fasting glucose in 8.8%, diabetes in 7.2%, and metabolic syndrome (diagnosis) in 0.1%. A total of 178,055 (37.4% of the study population) subjects had positive indicators of CMR as defined by the NCEP and IDF. Results indicated that obesity is the most prevalent CMR factor representing 90.6% of this at-risk population. Conclusions: The distribution of CMR factors in a primary care database is similar to that established by prospective national health surveys. A key source of identification of risk factors are clinical outcomes including BMI and lab values. Future studies on metabolic syndrome need to link clinically based information with more readily available treatment and diagnosis information.

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This study provides a foundation for understanding how SGAs impact weight gain in a naturalistic, as opposed to a clinical trial, setting and provides evidence that there are differential risks of weight gain between SGAs. Because of negative long-term health effects of weight gain, physicians need to take all factors into consideration when recommending pharmaceutical therapy for patients with severe mental illness.

The economic benefit of varenicline is improved over bupropion, despite the increased initial cost of varenicline.