A strategy to identify event specific hospitalizations in large health claims databases.

BACKGROUND: Health insurance claims data offer a unique opportunity to study disease distribution on a large scale. Challenges arise in the process of accurately analyzing these raw data. One important challenge to overcome is the accurate classification of study outcomes. For example, using claims data, there is no clear way of classifying hospitalizations due to a specific event. This is because of the inherent disjointedness and lack of context that typically come with raw claims data. METHODS: In this paper, we propose a framework for classifying hospitalizations due to a specific event. We then tested this framework in a private health insurance claims database (Symphony) with approximately 4 million US adults who tested positive with COVID-19 between March and December 2020. Our claims specific COVID-19 related hospitalizations proportion is then compared to nationally reported rates from the Centers for Disease Control by age. RESULTS: Across all ages (18 +) the total percentage of Symphony patients who met our definition of hospitalized due to COVID-19 was 7.3% which was similar to the CDC's estimate of 7.5%. By age group, defined by the CDC, our estimates vs. the CDC's estimates were 18-49: 2.7% vs. 3%, 50-64: 8.2% vs. 9.2%, and 65 + : 14.6% vs. 28.1%. CONCLUSIONS: The proposed methodology is a rigorous way to define event specific hospitalizations in claims data. This methodology can be extended to many different types of events and used on a variety of different types of claims databases.

Diagnoses during the First Three Years of Life for Children with Prenatal Opioid Exposure and Neonatal Abstinence Syndrome Using a Large Maternal Infant Data Hub.

PURPOSE: The purpose of this study was to examine patterns of health and developmental outcomes in children with prenatal opioid exposure (POE) and neonatal abstinence syndrome (NAS) compared to children without exposure during the first three years of life. DESIGN AND METHODS: This was a secondary data analysis of the Maternal and Infant Data Hub (MIDH), a de-identified dataset originating from the Midwest region of the United States, consisting of newborn billing records and corresponding maternal and child electronic medical records. For these analyses, the repository included data on more than 20,000 children born between 2013 and 2019. Diagnoses were identified with International Classification of Diseases, ninth and tenth Revision, Clinical Modification codes (ICD-9/10-CM). Firth logistic regression was used to assess whether incidence of each diagnosis code differed by exposure group. RESULTS: Among 20,389 children in the dataset, 13,173 were unexposed; 455 were POE, and 199 were POE + NAS. There were significant differences in frequency of diagnoses between groups, specifically regarding growth and development, infection, mental health, musculoskeletal, neonatal, sensory, and social issues. When comparing exposed groups, children with POE + NAS experienced more negative health outcomes than children with only POE across all years. CONCLUSIONS: This study implicates POE as a significant variable associated with many health and developmental outcomes of children during the first three years of life. PRACTICE IMPLICATIONS: It is crucial to understand and identify health risks observed more frequently in exposed children during such a critical period of growth and brain development.

Retirement risk factors, exercise management and muscle mass in US senior horses.

BACKGROUND: Information on the management and health of US senior horses (≥15 years of age) is currently limited. OBJECTIVES: Provide information on (1) primary use of US senior horses, (2) reasons and risk factors for horse retirement, (3) exercise management, (4) prevalence of low muscle mass and (5) risk factors for, and owner-perceived consequences of, low muscle mass. STUDY DESIGN: Online survey. METHODS: Survey responses from 2717 owners of U.S.-resident senior horses (≥15 years of age) were analysed descriptively and inferentially, using ordered and binomial logistic regression, ANOVA and the Kruskal-Wallis test. RESULTS: The most frequently reported primary uses were pleasure riding/driving (38.5%) and full retirement (39.8%). Most horses (61.5%) were retired between 15 and 24 years of age, with health problems being the main reason. Age, female sex, Thoroughbred breed and various medical conditions were identified as risk factors for retirement. In working horses (i.e., those not retired or semi-retired), exercise intensity was negatively associated with age. The owner-reported prevalence of low muscle mass in all horses was 17.2% (95%CI = 15.7-18.7). In those affected by low muscle mass, the ability to work and welfare-related aspects were commonly perceived to be impaired. Increasing age, sex (gelding), pituitary pars intermedia dysfunction, osteoarthritis, laminitis and primary use (retired and semi-retired vs. use for competition) were identified as risk factors for owner-reported low muscle mass. MAIN LIMITATIONS: Potential response, recall and sampling bias. Causal relationships cannot be established. CONCLUSIONS: Although structured exercise into old age may provide health benefits (as seen in elderly people), a large proportion of horses were fully retired in the current study. Senior horses were mainly retired for health problems and characterising these problems may aid in extending their work/active life. Low muscle mass was perceived to affect horses' welfare and ability to work, and identification of prevention and treatment strategies is therefore warranted.