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Context.--Two major categories of laboratories performing nonwaived testing under the Clinical Laboratory Improvement Amendments of 1988 (CLIA) are the Certificate of Accreditation (CoA) and Certificate of Compliance (CoC) laboratories. Accreditation organizations collect more detailed laboratory personnel information than the Centers for Medicare & Medicaid Services (CMS) Quality Improvement and Evaluation System (QIES). Objective.--To estimate total numbers of testing personnel and testing volumes in CoA and CoC laboratories, by laboratory type and state. Design.--We developed a statistical inference method by using the respective correlations between testing personnel counts and test volume by laboratory type. Results.--QIES reported 33 033 active CoA and CoC laboratories in July 2021. We estimated testing personnel to be 328 000 (95% CI, 309 000-348 000), which is supported by the count of 318 780 reported by the US Bureau of Labor Statistics. There were twice as many testing personnel in hospital laboratories as in independent laboratories (158 778 versus 74 904, P < .001). Independent laboratories had the highest test volume per person, which was twice as high as physician office laboratories (62 228 versus 30102, P < .001). Hospital and independent laboratories comprised 34% of all CoA and CoC laboratories but performed the largest portion of testing (81 %). Physician office laboratories, accounting for 44% of all CoA and CoC laboratories, performed a comparatively low proportion of total tests (9%). Conclusions.--Numbers of testing personnel vary considerably by laboratory type and across states. These data can provide valuable insight when assessing laboratory workforce training needs and planning for public health emergencies. doi: 10.5858/arpa.2022-0345-0A, Clinical laboratory testing plays a critical role in health care, public health surveillance, and emergency response. A detailed study by the Lewin Group for the Centers for Disease Control and [...]

Influenza is a common cause of illness and death in the United States and affects persons of all ages (1). Risk for complications from infection is higher in subpopulations, such [...]

Introduction: In 2021, among all age groups, falls ranked as the third leading cause of unintentional injury death in the USA. Unlike fatal data, which rely on death certificates as the gold standard, there is not a gold standard for non-fatal data. Non-fatal falls data are often based on insurance claims or administrative billing data. The purpose of our study is to compare three claims databases to estimate rates of unintentional fall-related hospitalisations in 2019, the most recent year of available data across the three sources., Methods: Three databases were used to produce incidence rates of fall-related hospitalisations for the year 2019: (1) Merative MarketScan research databases, (2) Centers for Medicare and Medicaid Services (CMS) data and (3) Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample. Inpatient falls were identified using International Classification of Diseases, 10th Revision, Clinical Modification codes. Incidence rates per 100 000 people were then produced across all three datasets by payer type. Unadjusted incidence rate ratios were estimated with corresponding 95% CIs., Results: There were wide disparities among fall rates between the three datasets by payer type. HCUP had the highest rate of falls among Medicare (1087.6 per 100 000) and commercial enrollees (74.7 per 100 000), while CMS had the highest rates of falls among Medicaid enrollees (148.0 per 100 000)., Conclusions: This study shows wide variation in fall hospitalisation rates based on the claims data used to estimate rates. This study suggests that database selection is an important consideration when determining incidence of non-fatal falls., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: Current methods used to measure incidence of traumatic brain injury (TBI) underestimate its true public health burden. The use of self-report surveys may be an approach to improve these estimates. An important step in public health surveillance is to define a public health problem using a case definition. The purpose of this article is to outline the process that the Centers for Disease Control and Prevention undertook to refine a TBI case definition to be used in surveillance using a self-report survey., Setting: Survey., Participants: A total of 10 030 adults participated via a random digit-dial telephone survey from September 2018 to September 2019., Main Measures: Respondents were asked whether they had sustained a hit to the head in the preceding 12 months and whether they experienced a series of 12 signs and symptoms as a result of this injury., Design: Head injuries with 1 or more signs/symptoms reported were initially categorized into a 3-tiered TBI case definition (probable TBI, possible TBI, and delayed possible TBI), corresponding to the level of certainty that a TBI occurred. Placement in a tier was compared with a range of severity measures (whether medical evaluation was sought, time to symptom resolution, self-rated social and work functioning); case definition tiers were then modified in a stepwise fashion to maximize differences in severity between tiers., Results: There were statistically significant differences in the severity measure between cases in the probable and possible TBI tiers but not between other tiers. Timing of symptom onset did not meaningfully differentiate between cases on severity measures; therefore, the delayed possible tier was eliminated, resulting in 2 tiers: probable and possible TBI., Conclusion: The 2-tiered TBI case definition that was derived from this analysis can be used in future surveillance efforts to differentiate cases by certainty and from noncases for the purpose of reporting TBI prevalence and incidence estimates. The refined case definition can help researchers increase the confidence they have in reporting survey respondents' self-reported TBIs as well as provide them with the flexibility to report an expansive (probable + possible TBI) or more conservative (probable TBI only) estimate of TBI prevalence., Competing Interests: Dr Corrigan's effort was supported in part by a grant from the National Institute on Disability, Independent Living, and Rehabilitation Research to Ohio State University (Grant 90DPTB0026). NIDILRR is a Center within the Administration for Community Living (ACL), Department of Health and Human Services (HHS). The contents of this publication do not necessarily represent the policy of NIDILRR, ACL, or HHS, and you should not assume endorsement by the Federal Government. For the remaining authors, no conflicts of interest were declared.

Background: Current methods of traumatic brain injury (TBI) morbidity surveillance in the United States have primarily relied on hospital-based data sets. However, these methods undercount TBIs as they do not include TBIs seen in outpatient settings and those that are untreated and undiagnosed. A 2014 National Academy of Science Engineering and Medicine report recommended that the Centers for Disease Control and Prevention (CDC) establish and manage a national surveillance system to better describe the burden of sports- and recreation-related TBI, including concussion, among youth. Given the limitations of TBI surveillance in general, CDC took this recommendation as a call to action to formulate and implement a robust pilot National Concussion Surveillance System that could estimate the public health burden of concussion and TBI among Americans from all causes of brain injury. Because of the constraints of identifying TBI in clinical settings, an alternative surveillance approach is to collect TBI data via a self-report survey. Before such a survey was piloted, it was necessary for CDC to develop a case definition for self-reported TBI., Objective: This article outlines the rationale and process the CDC used to develop a tiered case definition for self-reported TBI to be used for surveillance purposes., Conclusion: A tiered TBI case definition is proposed with tiers based on the type of sign/symptom(s) reported the number of symptoms reported, and the timing of symptom onset., Competing Interests: For the remaining authors, no conflicts of interest were declared. The authors declare no conflicts of interest.

We estimated the effectiveness of four monovalent pandemic influenza A (H1N1) vaccines (three unadjuvanted inactivated, one live attenuated) available in the U.S. during the pandemic. Patients with acute respiratory illness presenting to inpatient and outpatient facilities affiliated with four collaborating institutions were prospectively recruited, consented, and tested for influenza. Analyses were restricted to October 2009 through April 2010, when pandemic vaccine was available. Patients testing positive for pandemic influenza by real-time RT-PCR were cases; those testing negative were controls. Vaccine effectiveness was estimated in logistic regression models adjusted for study community, patient age, timing of illness, insurance status, enrollment site, and presence of high-risk medical conditions. Pandemic virus was detected in 1,011 (15%) of 6,757 enrolled patients. Fifteen (1%) of 1,011 influenza positive cases and 1,042 (18%) of 5,746 test-negative controls had record-verified pandemic vaccination >14 days prior to illness onset. Adjusted effectiveness (95% confidence interval) for pandemic vaccines combined was 56% (23%, 75%). Adjusted effectiveness for inactivated vaccines alone (79% of total) was 62% (25%, 81%) overall and 32% (-92%, 76%), 89% (15%, 99%), and -6% (-231%, 66%) in those aged 0.5 to 9, 10 to 49, and 50+ years, respectively. Effectiveness for the live attenuated vaccine in those aged 2 to 49 years was only demonstrated if vaccination >7 rather than >14 days prior to illness onset was considered (61%∶ 12%, 82%). Inactivated non-adjuvanted pandemic vaccines offered significant protection against confirmed pandemic influenza-associated medical care visits in young adults.