TASK DEFINITION: In this task, you are given a passage which has a question and the context. You have to generate an answer to the question based on the information present in the context.
PROBLEM: Context: Trauma centers are currently benchmarked on mortality outcomes alone. However, pay-for-performance measures may financially penalize centers based on complications. Our objective was to determine whether the results would be similar to the current standard method of mortality-based benchmarking if trauma centers were profiled on complications.', 'We analyzed data from the National Trauma Data Bank from 2007 to 2010. Patients 16 years or older with blunt or penetrating injuries and an Injury Severity Score (ISS) of 9 or higher were included. Risk-adjusted observed-to-expected (O/E) mortality ratios for each center were generated and used to rank each facility as high, average, or low performing. We similarly ranked facilities on O/E morbidity ratios defined as occurrence of any major complication. Concordance between hospital performance rankings was evaluated using a weighted κ statistic. Correlation between morbidity- and mortality-based O/E ratios was assessed using Pearson coefficients. Sensitivity analyses were performed to mitigate the competing risk of death for the morbidity analyses.', 'A total of 449,743 patients from 248 facilities were analyzed. The unadjusted morbidity and mortality rates were 10.0% and 6.9%, respectively. No correlation was found between morbidity- and mortality-based O/E ratios (r = -0.01). Only 40% of the centers had similar performance rankings for both mortality and morbidity. Of the 31 high performers for mortality, only 11 centers were also high performers for morbidity. A total of 78 centers were ranked as average, and 11 ranked as low performers on both outcomes. Comparison of hospital performance status using mortality and morbidity outcomes demonstrated poor concordance (weighted κ = 0.03, p = 0.22).\Question: Does benchmarking trauma centers on mortality alone reflect quality of care : implications for pay-for-performance?

SOLUTION: Mortality-based external benchmarking does not identify centers with high complication rates. This creates a dichotomy between current trauma center profiling standards and measures used for pay-for-performance. A benchmarking mechanism that reflects all measures of quality is needed.

PROBLEM: Context: The measurement of affective symptoms in older persons who decline cognitively is uncertain. The authors investigated whether mood variability predicts dementia in patients with age-related macular degeneration (AMD).', 'Three-year observational study after a clinical trial.', 'Community follow-up of outpatients ascertained from retina clinics.', 'One hundred sixty patients with AMD.', "Geriatric Depression Scale (GDS) administered every 2 weeks for 6 months to subjects; Informant Questionnaire for Cognitive Decline in the Elderly (IQCODE) administered to subjects' knowledgeable informants.", 'Twenty-three subjects (14.4%) declined cognitively. Age, education, baseline GDS score > or =5, and variability in GDS scores (i.e., fluctuations between adjacent time points) were associated with cognitive decline. For GDS variability, each 1 unit increase in the residual standard deviation (SD) of the GDS increased the risk for cognitive decline by 93% (IDR = 1.92; 95% CI [1.27-2.91]). Thus, subjects with a residual SD of 1 were nearly twice as likely to become demented as subjects with no variability in GDS scores. The risk for subjects with SDs of 2 increased more than threefold (IDR = 3.68; 95% CI [1.61-8.47]). A multiple regression analysis showed that GDS variability was a significant risk factor for dementia after controlling for significant covariates.\Question: Does variability in depressive symptoms predict cognitive decline in age-related macular degeneration?

SOLUTION: These data suggest a useful approach to conceptualizing and measuring depressive symptoms in older persons. Variability in self-reported mood may be an early sign of dementia and may offer new insights into the neurobiological mechanisms linking depression and cognition

PROBLEM: Context: To develop a scale and survey the measurement of patient adherence and patient recruitment, and to explore how these methods impact the results in randomized controlled trials of interventions to improve patient adherence to medications.', 'Analytic survey of a purposively selected sample of patient adherence intervention trials from a systematic review, assessing the quality of adherence measurement and patient recruitment methods.', 'We identified 44 different measures of adherence, with qualities ranging from valid and objective to unreliable and subjective. The median overall quality of measures of adherence was 5 (interquartile range [IQR], 3; range, 0-9, 9 is high quality). The quality of the measures was associated with variation in the estimate of adherence (Spearman r\xa0=\xa00.66; 95% confidence interval: 0.39, 0.83). The median overall quality of patient recruitment methods was 2 (IQR, 1; maximum score 6, higher is better). There was no significant correlation between the power of the trial to detect an effect and the quality of the patient recruitment methods.\Question: Are adherence measurement and patient recruitment methods poor in intervention trials to improve patient adherence?

SOLUTION:
Measurement and recruitment methods in adherence trials varied considerably, and most methods were of low quality. Adherence research could be advanced by using higher quality measures of adherence and better selection and baseline assessment of study participants.