This article evaluates the accuracy of reporting do not resuscitate (DNR) orders in administrative data for use in risk-adjusted hospital assessments. We compared DNR reporting by 48 California hospitals in 2005 patient discharge data (PDD) with gold-standard assessments made by registered nurses (RNs) who reabstracted 1,673 records of patients with myocardial infarction, pneumonia, or heart failure. The PDD agreed with the RN reabstraction in 1,411 (84.3%) cases. The administrative data did not reflect a DNR order in 71 of 512 records where the RN indicated there was (14% false negative rates), and reflected a DNR order in 191 of 1,161 records where the RN indicated there was not (16% false positive rate). The accuracy of DNR was more problematic for patients who died, suggesting that hospital-reported DNR is problematic for capturing patient preferences for resuscitation that can be used for risk-adjusted outcomes assessments.

Objective

To evaluate how the accuracy of present-on-admission (POA) reporting affects hospital 30-day acute myocardial infarction (AMI) mortality assessments.

Data sources

A total of 2005 California patient discharge data (PDD) and vital statistics death files.

Study design

We compared hospital performance rankings using an established model assessing hospital performance for AMI with (1) a model incorporating POA indicators of whether a secondary condition was a comorbidity or a complication of care, and (2) a simulation analysis that factored POA indicator accuracy into the hospital performance assessment. For each simulation, we changed POA indicators for six major acute risk factors of AMI mortality. The probability of POA being changed depended on patient and hospital characteristics.

Principal findings

Comparing the performance rankings of 268 hospitals using the established model with that using the POA indicator, 67 hospitals' (25 percent) rank differed by ≥10 percent. POA reporting inaccuracy due to overreporting and underreporting had little additional impact; POA overreporting contributed to 4 percent of hospitals' difference in rank compared to the POA model and POA underreporting contributed to <1 percent difference.

Conclusion

Incorporating POA indicators into risk-adjusted models of AMI care has a substantial impact on hospital rankings of performance that is not primarily attributable to inaccuracy in POA hospital reporting.

Background

The 2010 Affordable Care Act relies on Federally Qualified Health Centers (FQHCs) and FQHC look-alikes (look-alikes) to provide care for newly insured patients, but ties increased funding to demonstrated quality and efficiency.

Purpose

To compare FQHC and look-alike physician performance with private practice primary care physicians (PCPs) on ambulatory care quality measures.

Methods

The study was a cross-sectional analysis of visits in the 2006-2008 National Ambulatory Medical Care Survey. Performance of FQHCs and look-alikes on 18 quality measures was compared with private practice PCPs. Data analysis was completed in 2011.

Results

Compared to private practice PCPs, FQHCs and look-alikes performed better on six measures (p<0.05); worse on diet counseling in at-risk adolescents (26% vs 36%, p=0.05); and no differently on 11 measures. Higher performance occurred in ACE inhibitors use for congestive heart failure (51% vs 37%, p=0.004); aspirin use in coronary artery disease (CAD; 57% vs 44%, p=0.004); β-blocker use for CAD (59% vs 47%, p=0.01); no use of benzodiazepines in depression (91% vs 84%, p=0.008); blood pressure screening (90% vs 86%, p<0.001); and screening electrocardiogram (EKG) avoidance in low-risk patients (99% vs 93%, p<0.001). Adjusting for patient characteristics yielded similar results, except that private practice PCPs no longer performed better on any measures.

Conclusions

FQHCs and look-alikes demonstrated equal or better performance than private practice PCPs on select quality measures despite serving patients who have more chronic disease and socioeconomic complexity. These findings can provide policymakers with some reassurance as to the quality of chronic disease and preventive care at Federally Qualified Health Centers and look-alikes, as they plan to use these health centers to serve 20 million newly insured individuals.

Astronauts experience bone loss after the long spaceflight missions. Identifying specific regions that undergo the greatest losses (e.g. the proximal femur) could reveal information about the processes of bone loss in disuse and disease. Methods for detecting such regions, however, remains an open problem. This paper focuses on statistical methods to detect such regions. We perform statistical parametric mapping to get t-maps of changes in images, and propose a new cross-validation method to select an optimum suprathreshold for forming clusters of pixels. Once these candidate clusters are formed, we use permutation testing of longitudinal labels to derive significant changes.

Background

Radiation dose metrics vary by the calibration reference phantom used to report doses. By convention, 16-cm diameter cylindrical polymethyl-methacyrlate phantoms are used for head imaging and 32-cm diameter phantoms are used for body imaging in adults. Actual usage patterns in children remain under-documented.

Objective

This study uses the University of California San Francisco International CT Dose Registry to describe phantom selection in children by patient age, body region and scanner manufacturer, and the consequent impact on radiation doses.

Materials and methods

For 106,837 pediatric computed tomography (CT) exams collected between Jan. 1, 2015, and Nov. 2, 2020, in children up to 17 years of age from 118 hospitals and imaging facilities, we describe reference phantom use patterns by body region, age and manufacturer, and median and 75th-percentile dose-length product (DLP) and volume CT dose index (CTDI_vol) doses when using 16-cm vs. 32-cm phantoms.

Results

There was relatively consistent phantom selection by body region. Overall, 98.0% of brain and skull examinations referenced 16-cm phantoms, and 95.7% of chest, 94.4% of abdomen and 100% of cervical-spine examinations referenced 32-cm phantoms. Only GE deviated from this practice, reporting chest and abdomen scans using 16-cm phantoms with some frequency in children up to 10 years of age. DLP and CTDI_vol values from 16-cm phantom-referenced scans were 2-3 times higher than 32-cm phantom-referenced scans.

Conclusion

REFERENCE PHANTOM SELECTION IS HIGHLY CONSISTENT, WITH A SMALL BUT SIGNIFICANT NUMBER OF ABDOMEN AND CHEST SCANS (~5%) USING 16-CM PHANTOMS IN YOUNGER CHILDREN, WHICH PRODUCES DLP VALUES APPROXIMATELY TWICE AS HIGH AS EXAMS REFERENCED TO 32-CM PHANTOMS.

Astronauts experience bone loss after the long spaceflight missions. Identifying specific regions that undergo the greatest losses (e.g. the proximal femur) could reveal information about the processes of bone loss in disuse and disease. Methods for detecting such regions, however, remains an open problem. This paper focuses on statistical methods to detect such regions. We perform statistical parametric mapping to get t-maps of changes in images, and propose a new cross-validation method to select an optimum suprathreshold for forming clusters of pixels. Once these candidate clusters are formed, we use permutation testing of longitudinal labels to derive significant changes.