COVID-19 Pandemic Impact on the National Health Care Surveys

While underscoring the need for timely, nationally representative data in ambulatory, hospital, and long-term-care settings, the COVID-19 pandemic posed many challenges to traditional methods and mechanisms of data collection. To continue generating data from health care and long-term-care providers and establishments in the midst of the COVID-19 pandemic, the National Center for Health Statistics had to modify survey operations for several of its provider-based National Health Care Surveys, including quickly adding survey questions that captured the experiences of providing care during the pandemic. With the aim of providing information that may be useful to other health care data collection systems, this article presents some key challenges that affected data collection activities for these national provider surveys, as well as the measures taken to minimize the disruption in data collection and to optimize the likelihood of disseminating quality data in a timely manner. (Am J Public Health. 2021;111(12):2141–2148. https://doi.org/10.2105/AJPH.2021.306514 )

Machine Learning for Medical Coding in Health Care Surveys

This exploratory study evaluates the use of machine learning classifiers to perform automated medical coding for large statistical healthcare surveys.

Machine Learning for Medical Coding in Health Care Surveys

This exploratory study evaluates the use of machine learning classifiers to perform automated medical coding for large statistical healthcare surveys.