Medical Claims Monitor: Monitoring the Impact of COVID-19 Across the Healthcare Continuum Based on Claims Data
- 3/2020-5/2020 Pt2
- 3/2020-5/2020 Pt3
- 3/2020-5/2020 Pt4
- 3/2020-5/2020 Pt5 Retro View
- 6/2020-8/2020 Pt2
- 6/2020-8/2020 Pt3
- 7/2020-9/2020 Retro View
- 8/2020-10/2020 Retro View
- 9/2020-11/2020 Retro View
- 10/2020-12/2020 Retro View
- 12/2020-2/2021 Early View
- 1/2021-3/2021 Early View
- Low Prevalence of Certain Illnesses
Medical Claims Monitor: Monitoring the Impact of COVID-19 Across the Healthcare Continuum Based on Claims Data - overview
Healthcare expenditures have been rising for decades; there are numerous studies of this phenomenon in the literature. A recent study, for example, identifies disease prevalence, service utilization, unit price, and service intensity, along with population growth and aging, as fundamental factors associated with this ongoing increase of healthcare spending in the US. The global pandemic of COVID-19 has caused additional shocks to the healthcare industry. These new pressures are more dramatic in magnitude and more widespread in scope. For example, it is reported in the news media that lockdown measures in the Spring postponed many cataract surgeries and hospitals were left to tackle huge backlogs when restrictions were relaxed in the Summer. Delays in cancer screening also attracted the news media’s attention. As the fight against the pandemic continues, the healthcare patterns will continue to change in unforeseeable ways. Continuously monitoring for these changes, quantifying their impact, and reporting them in a timely manner is critical to empower decision makers.
This research project provides such a capability and service. By employing recent research innovations, it systematically surveils a vast amount of medical claims data provided by IBM® MarketScan® Research Databases and discovers significant changes in the fundamental factors from tens of millions of elements in the continuum of healthcare services.
This website will report selected top drivers found in the analysis with a monthly cadence. The drivers will be organized by various viewpoints, including medical episodes, outpatient procedures, and inpatient admissions.
The target period for an analysis is a three-month rolling window in which relevant claims are characterized and aggregated by month, and the resulting characteristics are compared to those in the same period of the previous year for change detection.
A report for each target period will be provided initially in the month when the relevant claims data first become available (typically 6-8 weeks after the target period). The initial report will be revised and updated a month later when additional data become available.
The researchers on this project are solely responsible for the content of the reports.
Thomas Halvorson (email@example.com), Content Consultant
Italo Buleje (firstname.lastname@example.org), Software Engineering Support