Abstract Session E1: Organization of Care and Chronic Disease Management Moderator: Nancy A. Rigotti, MD UNDERSTANDING VARIATION IN PCP REFERRAL PATTERNS IN A LARGE MULTISPECIALTY PRACTICE GROUP Michael L. Barnett 1 ; Thomas D. Sequist 1,2 . 1 Brigham and Women's Hospital, Boston, MA; 2 Partners Healthcare System, Boston, MA. (Tracking ID #1937624) BACKGROUND: Primary care physicians (PCPs) generate the vast majority of specialty referrals, and the decision to refer directly impacts health care quality, patient experiences, and spending. We analyzed referral rates among PCPs to characterize the relative contribution of patient and physician characteristics to the probability of referral, as well as the long term impact on utilization among PCPs with high rates of referral. METHODS: We analyzed electronic health record data within a large multispecialty group practice that requires electronic referral orders. We enrolled 78,485 patients 18 years and older who visited 142 PCPs during a baseline referral rate measurement period (2005-2006), and then analyzed subsequent specialist referrals among these patients from 2007-2011. We collected information on patient age, gender, race, Charlson comorbidity score (2005-2006), and number of subsequent specialist appointments (2007-2011). To calculate PCP referral rates, we estimated a mixed effects logistic regression model using 2005-2006 data adjusted for patient characteristics, using a random intercept term to account for correlation within individual PCPs. We calculated the ratio of the PCP's adjusted referral rate estimated from the fitted random intercept over the expected referral rate estimated with the same model without the random intercept. We multiplied this ratio by the average referral rate in the entire cohort to calculate the case-mix adjusted referral rate for each PCP. We used the c-statistic to assess the relative contribution of patient and physician characteristics in this model. We next categorized PCPs according to their quintile of adjusted referral rate and examined the characteristics of the PCPs and their patient panels, testing for trends using logistic regression. In the period from 2007-2011, we estimated the adjusted probability with logistic and negative binomial models that patients with PCPs in the different referral quintiles received any specialty referral, the average number of referrals per patient, and the average number of specialty visits. RESULTS: From 2007-2011, the PCPs placed 102,276 referral orders, representing 74% of the total referrals for this cohort (additional referrals came from urgent care physicians). The five most commonly referred specialties were orthopedic surgery (23%), dermatology (15%), otorhinolaryngology (9%), gastroenterology (9%), and general surgery (8%). Physicians with more female, non- white and younger patients as well as those with fewer comorbidities were more likely to be in the highest referral quintile, as were physicians with fewer patient encounters and smaller panels (all p<0.001, Table). The c-statistic for a logistic regression model to predict referrals using patient characteristics alone was 0.56, while the mixed effects model with a physician-level random intercept alone had a c-statistic of 0.68, which was unchanged after incorporating patient characteristics into the model. The adjusted average rate of referral per 100 patient visits was 5.2, 16.3, 21.0, 25.6, and 36.2 by quintile of referral rate among PCPs, with an overall average of 17.4. Adjusting for age, sex, race, and comorbidities, the average patient with a PCP in the highest quintile of referral rate had a 77% (95% CI 76-78) probability of receiving a referral and had 2.2 (95% CI 2.1-2.3) referrals on average from 2007-2011, compared to a 36% (95% CI 35-37) chance of receiving a referral and 0.59 (95% CI 0.57-0.61) average number of referrals in lowest quintile. From 2007-2011, in the 12 months subsequent to a referral, patients of PCPs in the highest referral quartile experienced an average of 3.6 (95% CI 3.4-3.8) follow-up specialist visits versus 0.53 (95% CI 0.51-0.56) visits among patients of PCPs in the lowest referral quartile. CONCLUSIONS: We observe wide variation among PCPs in specialty referral rates, which is explained in large part by physician characteristics as opposed to patient characteristics. This variation has substantial long-term implications, with patients seen by PCPs in the highest quintile of referral rates experiencing dramatically more specialist visits over time. Our analyses suggest that physician- level interventions are needed to address this variation which may be due to physician subjectivity in the decision to refer patients. Table: Patient and Physician Characteristics, by Referral Quintile
MINDFULNESS BASED COGNITIVE THERAPY VERSUS A HEALTH ENHANCEMENT PROGRAM FOR TREATMENT RESISTANT DEPRESSION: A RANDOMIZED CONTROLLED TRIAL Mitchell D. Feldman 1 ; Erin P. Gillung 2 ; Kevin Delucchi 3 ; Stuart J. Eisendrath 4 . 1 UCSF, San Francisco, CA; 2 UCSF, San Francisco, CA; 3 UCSF, San Francisco, CA; 4 UCSF, San Francisco, CA. (Tracking ID #1927292) BACKGROUND: Major depressive disorder (MDD) is the leading cause of disability in the developed world, yet broadly effective treatments remain elusive. Up to 40% of patients are unresponsive to at least two trials of antidepressant medication and are thus labeled as having treatment- resistant depression (TRD). There is an urgent need for cost-effective, non-pharmacologic, evidence-based treatments for TRD. Prior research has demonstrated that Mindfulness-Based Cognitive Therapy (MBCT) is an effective treatment for major depression, but it has not been previously studied in patients with TRD. MBCT is based on a combination of mindfulness meditation with elements of cognitive behavior therapy. The purpose of this study was to evaluate whether (MBCT) is an effective augmentation of antidepressants for adults with MDD who failed to respond to standard pharmacotherapy. METHODS: Randomized controlled trial of MBCT versus an active comparator condition, the Health-Enhancement Program (HEP), comprised of physical fitness, nutrition and music therapy. Participants were age 18 years and older with TRD who had failed to respond to two or more antidepressant trials. All participants were taking antidepressants at the time of enrollment. One hundred seventy three participants were recruited from primary care and other settings and randomly assigned to 8 weekly group sessions of MBCT or HEP. Treatment response and depression remission rates were assessed at weeks 4 and follow-up weeks 8, 24, 36 and 52 using the clinician-rated Hamilton Depression Severity Rating Scale (HDRS). HDRS response and remission rates and mean HDRS total scores were compared between treatment conditions using a GEE-based repeated measures model accounting for clustering by cohort. The models included treatment condition, assessment point, and their interaction. RESULTS: Significant improvement was seen in rates of response (p=<.001), remission (p<.01), severity (p<.001) and percent reduction in severity score (p<.01). No significant differences between treatment groups were found. A significant condition-x-time interaction was observed for both the severity score and percent reduction indicating that the MBCT continued to improve at Week 8 while the improvement in the HEP condition leveled off. CONCLUSIONS: Both MBCT and HEP produced improvement in patients with treatment-resistant depression over 8 weeks. While the differences between conditions were not statistically significant, differences in course of improvement suggests differences in long-term follow-ups (underway) may be significant. Clinical Characteristics of Adults with Treatment-Resistant Depression Receiving Mindfulness-Based Cognitive Therapy (MBCT) or the Health Enhancement Program (HEP) MBCT (N=87) HEP (N=86) Variable Mean SD Mean SD Age at depression onset 18.8 10.9 3.5 13.2 Total # depressive episodes (months) 3.6 2.6 78.5 2.4 Length of current depressive episode (months) 84.4 119.5 17.4 93.5 HAM-D Score 18.3 3.4 3.5 Single episode (%) 20.7 22.1 ≥3 lifetime episodes 62.2 58.0 Previous treatment for depression (%) Hospitalization 16.1 18.6 Suicide Attempt 19.0 20.5 Recruitment Source % GIM 34.5 36.1 Psychiatry Clinic 43.7 39.5 Community 24.4 24.4 HAM-D = Hamilton Depression Rating Scale Depression Outcomes over Time for Adults with Treatment-Resistant Depression Receiving Mindfulness-Based Cognitive Therapy (MBCT) or the Health Enhancement Program (HEP) MBCT Group (N=87) HEP Group (N=86) Outcome Variable Mean ± SD Mean ± SD HAM-D Mean Score Baseline 18.3 ± 3.4 17.4 ± 3.5 Week 4 13.8 ± 4.7 12.8 ± 4.3 Week 8 11.4 ± 4.9 12.5 ± 5.0 HAM-D Percent Reduction Week 4 0.23 ± 0.20 0 .24 ± 0.24 Week 8 0.36 ± .25 0.25 ± 0.27 HAM-D = Hamilton Depression Rating Scale. Reduction rates were calculated as mean percent change from baseline to weeks 4 and 8.
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