Writing Committee for the ENRICHD Investigators C ARDIOVASCULAR DISEASE IS THE leading cause of death and a major cause of morbidity and disability in the United States, with an estimated 6 million people having symptomatic coronary heart disease (CHD). 1 Recent studies 2-7 have shown that depression and low perceived social support (LPSS) are associated with increased cardiac morbidity and mortality in CHD patients. In patients with CHD, the prevalence of major depression is nearly 20% and the prevalence of minor depression is approximately 27%. 8-10 After an acute myocardial infarction (MI), depression is a risk factor for mortality independent of cardiac disease severity. 4,6 A recent randomized clinical trial found that the antidepressant sertraline hydrochloride was effective in treating recurrent depression in patients with either an acute MI or an episode of unstable angina. 11 However, no clinical trial has examined whether treating depression with counseling or antidepressants after an acute MI improves survival or reduces cardiac risk. The absence of social support is also a risk factor for cardiac morbidity and mortality in patients with CHD. 2,3,5,7 No clinical trial has tested the effects of increasing social support on clinical end points following acute MI, although

Standard inference procedures for regression analysis make assumptions that are rarely satisfied in practice. Adjustments must be made to insure the validity of statistical inference. These adjustments, known for many years, are used routinely by some health researchers but not by others. We review some of these methods and give an example of their use in a health services study for a continuous and a count outcome. For the continuous outcome, we describe retransformation using the smear factor, accounting for missing cases via multiple imputation and attrition weights and improving results with bootstrap methods. For the count outcome, we describe zero inflated Poisson and negative binomial models and the two-part model to account for overabundance of zero values. Recent advances in computing and software development have produced user-friendly computer programs that enable the data analyst to improve prediction and inference based on regression analysis.

• Background Improving communication and collaboration among doctors and nurses can improve satisfaction among participants and improve patients’ satisfaction and quality of care. • Objective To determine the impact of a multidisciplinary intervention on communication and collaboration among doctors and nurses on an acute inpatient medical unit. • Methods During a 2-year period, an intervention unit was created that differed from the control unit by the addition of a nurse practitioner to each inpatient medical team, the appointment of a hospitalist medical director, and the institution of daily multidisciplinary rounds. Surveys about communication and collaboration were administered to personnel in both units. Physicians were surveyed at the completion of each rotation on the unit; nurses, biannually. • Results Response rates for house staff (n = 111), attending physicians (n = 45), and nurses (n = 123) were 58%, 69%, and 91%, respectively. Physicians in the intervention group reported greater collaboration with nurses than did physicians in the control group (P < .001); the largest effect was among the residents. Physicians in the intervention group reported better collaboration with the nurse practitioners than with the staff nurses (P < .001). Physicians in the intervention group also reported better communication with fellow physicians than did physicians in the control group (P = .006). Nurses in both groups reported similar levels of communication (P = .59) and collaboration (P = .47) with physicians. Nurses in the intervention group reported better communication with nurse practitioners than with physicians (P < .001). • Conclusions The multidisciplinary intervention resulted in better communication and collaboration among the participants.

Collaborative physician/nurse practitioner multidisciplinary care management of hospitalized medical patients reduced LOS and improved hospital profit without altering readmissions or mortality.