Using Big Data Science to Examine Variations in Care Quality

Big data science plays a crucial role in the healthcare sector, particularly within the nursing/care home industry. This chapter aims to demonstrate the utilization of big data analytics in addressing complex research inquiries concerning online ratings and care quality in nursing homes. In the first case, we employ big data analytics to identify potential instances of rating inflation among nursing homes in the United States. Our analysis reveals a significant correlation between changes in star ratings and the profits of nursing homes. Furthermore, we demonstrate how this association can lead to rating inflation. Subsequently, we develop a prediction model to assess the extent of inflation, allowing us to identify 6%–8.5% of nursing homes as probable inflators. In the subsequent case, we investigate the variations in performance among nursing homes in the United States during the COVID-19 pandemic using big data analytics techniques. We summarize the distinguishing characteristics of nursing homes that are more susceptible to experiencing substantial outbreaks of COVID-19. Additionally, we provide insights to aid policymakers in implementing measures to control the spread of COVID-19 within nursing homes. Given the similarities between the UK care home rating system and the US nursing home rating system, such as the utilization of ordinal ratings and a combination of measures in the rating generation, the methodologies and findings presented in this section also offer valuable insights for potential applications in the UK.