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HSRProj (Health Services Research Projects in Progress)

Information about ongoing health services research and public health projects

Identifying and predicting patients with preventable high utilization
Investigator (PI): Kaushal, Rainu
Performing Organization (PO): (Current): Cornell University, Weill Cornell Medical College, Department of Population Health Sciences / (646) 962-8009
Supporting Agency (SA): Patient-Centered Outcomes Research Institute (PCORI)
Initial Year: 2016
Final Year: 2020
Record Source/Award ID: PCORI/HSD-1604-35187
Funding: Total Award Amount: $1,807,765
Award Type: Contract
Award Information: PCORI: More information and project results (when completed)
Abstract: This project, Identifying and Predicting Patients with Preventable High Utilization, involves 20 New York City, Chicago, and Florida health systems, who share a commitment to conducting patient-centered research to improve the care they provide to patients. They participate in three clinical data research networks (CDRNs): New York City Clinical Data Research Network (NYC-CDRN), Chicago Area Patient-Centered Outcomes Research Network (CAPriCORN), and OneFlorida. CDRNs are networks funded by the Patient-Centered Outcomes Research Institute (PCORI) to bring together health systems, patients, clinicians, researchers, and others to develop data infrastructure to support patient-centered research. Together, they are part of a national research data network called PCORnet. The focus of our project is patients with high health care use. The health and health care for some of these patients, defined as those with preventable high use, can be improved if they are identified early and provided targeted help. For example, a given patient may benefit from transportation assistance while another may benefit from coordination of multiple prescriptions. Health systems and clinicians often do not have full information on the conditions or needs of their patients and therefore do not know which patients would benefit most from assistance. They are also unable to predict which patients will become high users of health care in the future. During the project planning phase, health system leaders and patients, including 60 executives and 22 patients from the 20 health systems participating in this project, prioritized the topic of patients with high health care use. They described the need for better information and tools to help them identify and predict which patients could benefit from an intervention. CDRNs are well placed to help health systems improve health care delivery given their expertise and experience preparing complete sets of data on patients from multiple sources. We will create, in collaboration with patients and health systems, data sets and tools to identify and predict patients with current or future preventable high health care use using information from a variety of sources, including patients' medical records, health plans' records, census surveys, and neighborhood surveys. By bringing this data together, we can create a more complete picture of patients' health as well as potential social issues (e.g., poverty) that could affect their health. We will develop collaboration across patients, clinicians, health system leaders, and scientists using best practices for patient-centered research developed by PCORI. This will ensure that our final products will be useful for health care providers and their patients. Finally, we will share our results through open-source venues and discussions, within PCORnet and more broadly, to ensure that we continue to build this tremendous resource, PCORnet, to improve health and health care across the country.
MeSH Terms:
  • Chicago
  • Delivery of Health Care
  • Florida
  • Health Services Accessibility
  • * Health Services Research
  • Humans
  • Medical Records
  • New York City
  • Outcome Assessment, Health Care
  • Patient-Centered Care
  • Residence Characteristics
  • Transportation
Country: United States
State: New York
Zip Code: 10065
UI: 20164078
Project Status: Ongoing
Record History: ('2019: Project extended to 2020 ',) ('2017: Project extended to 2019',)