Sensitivity of billing claims for cardiovascular disease events among kidney transplant recipients.

BACKGROUND AND OBJECTIVES: Billing claims are increasingly examined beyond administrative functions as outcomes measures in observational research. Few studies have described the performance of billing claims as surrogate measures of clinical events among kidney transplant recipients. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We investigated the sensitivity of Medicare billing claims for clinically verified cardiovascular diagnoses (five categories) and procedures (four categories) in a novel database linking Medicare claims to electronic medical records of one transplant program. Cardiovascular events identified in medical records for 571 Medicare-insured transplant recipients in 1991 through 2002 served as reference measures. RESULTS: Within a claims-ascertainment period spanning +/-30 d of clinically recorded dates, aggregate sensitivity of single claims was higher for case definitions incorporating Medicare Parts A and B for diagnoses and procedures (90.9%) compared with either Part A (82.3%) or Part B (84.6%) alone. Perfect capture of the four procedures was possible within +/-30 d or with short claims window expansion, but sensitivity for the diagnoses trended lower with all study algorithms (91.2% with window up to +/-90 d). Requirement for additional confirmatory diagnosis claims did not appreciably reduce sensitivity. Sensitivity patterns were similar in the early compared with late periods of the study. CONCLUSIONS: Combined use of Medicare Parts A and B billing claims composes a sensitive measure of cardiovascular events after kidney transplant. Further research is needed to define algorithms that maximize specificity as well as sensitivity of claims from Medicare and other insurers as research measures in this population.

Happily putting the pieces together: a test of two explanations for the effects of mood on group-level information processing.

Research on mood and information processing reveals two explanations for how moods might influence decision-making in a group. Moods may alter group decision making because happy moods are more likely than sad moods to (a) increase people's reliance on accessible knowledge or (b) broaden people's focus so they can build on their knowledge. Consistent with the hypothesis that happy moods broaden-and-build on people's knowledge, across two experiments, happy moods promoted group performance more than sad moods because happy moods helped group members move beyond their initial preferences and focus broadly on the full range of information that each group member could provide. Experiment 2 built on these findings by demonstrating that the effects of mood on group performance were particularly strong when the critical information was uniquely, rather than commonly, distributed to group members. These experiments clarify the role of mood in group decision making and suggest that a differential focus on unique/critical information relative to common/non-critical information may be a key mechanism in understanding the effects of mood on group decision making.