Mapping 123 million neonatal, infant and child deaths between 2000 and 2017.

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2-to end preventable child deaths by 2030-we need consistently estimated data at the subnational level regarding child mortality rates and trends.

Does adding clinical data to administrative data improve agreement among hospital quality measures?

Background: Hospital performance measures based on patient mortality and readmission have indicated modest rates of agreement. We examined if combining clinical data on laboratory tests and vital signs with administrative data leads to improved agreement with each other, and with other measures of hospital performance in the nation's largest integrated health care system.

Methods: We used patient-level administrative and clinical data, and hospital-level data on quality indicators, for 2007-2010 from the Veterans Health Administration (VA).

Classification of patients with incident non-specific low back pain: implications for research.

Background Context: Comparing research studies of low back pain is difficult because of heterogeneity. There is no consensus among researchers on inclusion criteria or the definition of an episode.

Purpose: This study aimed to determine pattern(s) of recurrent non-specific low back pain from data collected over 27 months.

Cost-utility of cognitive behavioral therapy for low back pain from the commercial payer perspective.

Study Design: Markov cost-utility model.

Objective: To evaluate the cost-utility of cognitive behavioral therapy (CBT) for the treatment of persistent nonspecific low back pain (LBP) from the perspective of US commercial payers.

Summary Of Background Data: CBT is widely deemed clinically effective for LBP treatment.

Partnering With VA Stakeholders to Develop a Comprehensive Patient Safety Data Display: Lessons Learned From the Field.

Health care systems are increasingly burdened by the large numbers of safety measures currently being reported. Within the Veterans Administration (VA), most safety reporting occurs within organizational silos, with little involvement by the frontline users of these measures. To provide a more integrated picture of patient safety, the study team partnered with multiple VA stakeholders and engaged potential frontline users at 2 hospitals to develop a Guiding Patient Safety (GPS) tool.

Advanced diagnostic imaging in privately insured patients: recent trends in utilization and payments.

Recent studies have reported that the rate of growth in utilization of noninvasive diagnostic imaging has slowed, with a concomitant reduction in total payments to providers in the Medicare Part B fee-for-service population. Utilization and payment growth trends in commercially insured populations, however, are not as well understood. We used the Truven Health Analytics MarketScan® Commercial Claims and Encounters database containing more than 29 million individuals to investigate commercially insured population trends in utilization of and payments for CT, MRI, PET, and ultrasound procedures in the years 2007-2011.

Medical and surgical readmissions in the Veterans Health Administration: what proportion are related to the index hospitalization?

Background: Readmissions are an attractive quality measure because they offer a broad view of quality beyond the index hospitalization. However, the extent to which medical or surgical readmissions reflect quality of care is largely unknown, because of the complexity of factors related to readmission. Identifying those readmissions that are clinically related to the index hospitalization is an important first step in closing this knowledge gap.

Comparison of the Agency for Healthcare Research and Quality Patient Safety Indicator Rates Among Veteran Dual Users.

This study compares rates of 11 Agency for Healthcare Research and Quality Patient Safety Indicators (PSIs) among 266 203 veteran dual users (ie, those with hospitalizations in both the Veterans Health Administration [VA] and the private sector through Medicare fee-for-service coverage) during 2002 to 2007. PSI risk-adjusted rates were calculated using the PSI software (version 3.1a).

Approximate models for aggregate data when individual-level data sets are very large or unavailable.

In this article, we study a Bayesian hierarchical model for profiling health-care facilities using approximately sufficient statistics for aggregate facility-level data when the patient-level data sets are very large or unavailable. Starting with a desired patient-level model, we give several approximate models and the corresponding summary statistics necessary to implement the approximations. The key idea is to use sufficient statistics from an approximate model fitted by matching up derivatives of the models' log-likelihood functions.