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Population health management (PHM) is an important approach to promote wellness and deliver health care to targeted individuals who meet criteria for preventive measures or treatment. A critical component for any PHM program is a data analytics platform that can target those eligible individuals.

To identify the risk factors home healthcare (HHC) clinicians associate with patient deterioration and understand how clinicians respond to and document these risk factors.

The purpose of this study was to develop a framework to assess the quality of healthcare data sources.

Adoption of electronic health records (EHRs) and health information exchange (HIE) is a key tool to improving the quality of care in assisted living communities (ALC). We examined whether EHRs were being used in ALC to support HIE in 2010 and 2018. We found that adoption of EHR and HIE functions increased substantially over the study period. However, adoption of HIE functions lagged significantly behind EHR functions in both 2010 [...]

The US Preventive Services Task Force (USPSTF) requires the estimation of lifetime pack-years to determine lung cancer screening eligibility. Leading electronic health record (EHR) vendors calculate pack-years using only the most recently recorded smoking data. The objective was to characterize EHR smoking data issues and to propose an approach to addressing these issues using longitudinal smoking data.

To facilitate patient disease subset and risk factor identification by constructing a pipeline which is generalizable, provides easily interpretable results, and allows replication by overcoming electronic health records (EHRs) batch effects.

Respiratory support status is critical in understanding patient status, but electronic health record data are often scattered, incomplete, and contradictory. Further, there has been limited work on standardizing representations for respiratory support. The objective of this work was to (1) propose a practical terminology system for respiratory support methods; (2) develop (meta-)heuristics for constructing respiratory support episodes; and (3) evaluate the utility of respiratory support information for mortality prediction.

After deploying a clinical prediction model, subsequently collected data can be used to fine-tune its predictions and adapt to temporal shifts. Because model updating carries risks of over-updating/fitting, we study online methods with performance guarantees.

Electronic health records (EHRs) contain a large quantity of machine-readable data. However, institutions choose different EHR vendors, and the same product may be implemented differently at different sites. Our goal was to quantify the interoperability of real-world EHR implementations with respect to clinically relevant structured data.

Given that electronic clinical quality measures (eCQMs) are playing a central role in quality improvement applications nationwide, a stronger evidence base demonstrating their reliability is critically needed. To assess the reliability of electronic health record-extracted data elements and measure results for the Elective Delivery and Exclusive Breast Milk Feeding measures (vs manual abstraction) among a national sample of US acute care hospitals, as well as common sources of discrepancies and [...]