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Assessing and Predicting Medical Needs in a Disaster

Develop a Data Platform to Conduct Patient Centered Outcomes Research Related to Medically Related Disaster Response and Recovery
  • Agency for Healthcare Research and Quality (AHRQ)
  • Office of the Assistant Secretary for Preparedness and Response (ASPR)
Start Date
  • 6/15/2018
  • Use of Clinical Data for Current Research


STATUS: Completed Project


The Department of Health and Human Services (HHS) leads the US public health and medical response to disasters and emergencies. These disasters occur in all geographic regions, yet every geography has distinct disaster types and distinct medical needs. Often, researchers are unable to address geographic differences when designing studies, which leads to inaccurate and non-generalizable results. ASPR focuses specifically on preventing, preparing for, and responding to the adverse health effects of public health emergencies and disasters. They coordinate the National Disaster Medical System, a group of professionals who supplement health systems and response capabilities in emergency settings. In the midst of Hurricane Harvey, ASPR and the AHRQ collaborated to explore the use of Healthcare Cost and Utilization Project (HCUP) data to predict medical needs by region. HCUP is a group of health care databases and software tools developed through an AHRQ sponsored Federal-State-Industry partnership. These databases bring together data collection efforts at multiple levels to create a resource with national encounter-level health care data.

This project aimed to close the gap in understanding how to tailor disaster medical response to the local level for each event. The project focused on the creation of a data platform that can be used to conduct patient-centered outcomes research (PCOR) related to disaster response and recovery operations. The initial platform consists of public facing statistical query pathways that provides access to statistical tables, maps, and graphic on patient health outcomes and a restricted access set of analytic files derived from the HCUP that can be accessed by researchers at AHRQ, ASPE, ASPR, and other federal partners. The restricted file can be integrated with supplemental data sources on disaster impacts and emergency interventions at the county level. This initial platform tested whether questions about state and county-level health care disaster-related needs can be answered and tracked over time. In turn, analyses reflected the health needs of specific populations, thus improving information to deploy appropriate medical expertise. This project explored comparative effectiveness research (CER) and PCOR questions such as comparing differences between communities directly affected by disaster versus other comparable communities for outcomes. Eventually, researchers can use this data to assess different interventions based on disaster type and population.


The purpose of this project was to develop a data platform to conduct PCOR related to medically related disaster response and recovery.

Project Objectives:

  • Create a disaster-relevant analytic platform available with two levels of access.

  • Design a reporting system that can collect and share real-time reporting of medical encounters during a disaster response.

  • Pilot test the database and platform via an operational disaster training exercise, and engage researchers to evaluate whether data can predict medical needs in a disaster.


  • The AHRQ team completed the development of enhanced HCUP databases and supplemental analytic files. Over the course of the project, AHRQ processed 63 quarterly data files which included emergency department, ambulatory surgery, and inpatient files from 11 states.

  • The AHRQ project team created the HCUP Hurricane Data Resource and data dictionary for use by federal researchers. The HCUP Hurricane Data Resource includes 25 analytic data files that include aggregate patient or county-level hospital utilization, county-level storm and community characteristics, and population-based utilization statistics, and hospital-level characteristics.

  • The AHRQ team also developed the HCUP Fast States Hurricane Impact on Hospital Users, a public-facing statistical query system. The Fast Stats hurricane topic allows users to graph and download data files on hospital utilization by hurricane, age, condition, and setting.

  • The ASPR project team enhanced capabilities for real-time reporting of existing emergency management systems and new data sources, such as the Red Cross National Shelter System data, to capture stays in shelters, medical needs at those shelters, and facilities operating during disasters.




Below is a list of ASPE-funded PCORTF projects that are related to this project

Capstone for Outcomes Measures Harmonization Project - The AHRQ Capstone project objective is to improve the collection and use of outcomes measures by linking clinical data to two different registries, and pilot-testing the bi-directional exchange of data between the registries and clinical sites. This project expands data capacity for PCOR by collecting electronic health data from multiple clinical sites on patient outcomes associated with treatment for depression; transferring the collected data to electronic patient registries for research; and developing infrastructure and tools to allow replication.

Improving the Mortality Data Infrastructure for Patient-Centered Outcomes – Comprised of all U.S. mortality events since 1979, the National Death Index (NDI) database allows researchers to match entries in the NDI to those participating in longitudinal clinical and epidemiologic studies to determine both fact and cause of death. A significant challenge with the NDI has been the lag between the date of death and the availability of the record for matching purposes. The Centers for Disease Control and Prevention National Center for Health Statistics (NCHS) worked to improve the infrastructure to support more timely and complete mortality data collection through more timely delivery of state death records (e.g., cause of death) to the NDI database and through linking NDI records with nationally collected hospital datasets to obtain a more complete picture of patient care.