ibrahim kamara, ms, mph, sc.d torrance brown, mph june 2011
TRANSCRIPT
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Methodological Challenges in Analyzing The Hospital Preparedness Data
As it Relates to Response
Ibrahim Kamara, MS, MPH, Sc.D Torrance Brown, MPH
Program Evaluation Section (PES)State and Local Initiatives TeamOffice of Preparedness & Emergency Operations (OPEO)Office of the Assistant Secretary for Preparedness & Response (ASPR)
June 2011
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Outlines/Introduction
BackgroundPurposeCurrent HPP CapabilitiesData Collection ApproachAnalytic ApproachResults of Selected SnapshotsMethodological IssuesRecommendationsNext Steps
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Learning Objectives
Understand the status of the HPP data assessment and its response capabilities
Obtain a better understanding of the HPP data collection, analytic approaches, and results of selected snapshots
Understand some of the obvious methodological challenges of the data as it relates to response
Obtain a better understanding of the next steps
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Background & Purpose
The goal of the Hospital Preparedness Program (HPP) is to ensure awardees use cooperative agreement funds to maintain, refine, and to the extent enhance the capacities and capabilities of their healthcare entities for exercising and improving all-hazards preparedness plans, including pandemic influenza.
Purpose Background Mandatory Formula Awards
• State/Territory Departments of Public Health and Directly funded metro areas (LA, Chicago, NYC, & DC); 62 Awardees
Authorizing Legislation• Established in 2002 under the
Public Health Security & Bioterrorism Preparedness & response Act of 2002
• Pandemic and All-Hazards Preparedness Act (PAHPA) signed in December 2006.
Program Foci• Capacity 2002-2006• Capabilities 2007-Present
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HPP Capabilites
HPP Overarching Requirements National Incident Management System (NIMS) Education and Preparedness Training Exercises, Evaluation, and Corrective Actions Needs of At-Risk Populations
Level 1 Sub-Capabilities Interoperable Communication Systems Tracking of Bed Availability (HAvBED) ESAR-VHP Fatality Management Partnership/Coalition Development
Level 2 Sub-Capabilities Alternate Care Sites Mobile Medical Assets Pharmaceutical Caches Personal Protective Equipment Decontamination
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Data Collection
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Analytic Approach
Data is analyzed using SAS, Excel, and Geographic Information System (GIS) mapping for graphical depiction
Descriptive Statistics Continuous data~ weighted and un-weighted
means or median, std. errors or Confidence interval (CI)
Discreet data ~ proportions, comparative ratios, percentages and CI to profile proxy indices as “snapshots” for situational awareness
Inferential statistics from varied multiple regression analysis
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Graphical distribution of States by Rate of Participating Hospitals, 2009
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Results: Selected HPP Data Snapshot(EOY 2007, 2008, 2009)
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Results: Selected HPP Data Snapshot(EOY 2007, 2008, 2009)
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Results: Selected HPP Data Snapshot(EOY 2007, 2008, 2009)
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Results: Selected HPP Data Snapshot(EOY 2007, 2008, 2009)
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Results: Selected HPP Data Snapshot(EOY 2007, 2008, 2009)
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Results: Selected HPP Data Snapshot(EOY 2007, 2008, 2009)
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Results: Selected HPP Data Snapshot(EOY 2007, 2008, 2009)
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Results: Selected HPP Data Snapshot(EOY 2007, 2008, 2009)
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Methodological Issues/Challenges
Subjectivity Measurement indicators are determined from a listing of indicators used in other models
determined by expert panel process Bias
Differences between awardees’ response on their capabilities Inconsistent interpretation of the indices/measures among awardees Lack of specificity on capabilities definitions
Weighting Lack of weighting techniques for prioritization of indicators
Mathematical nomenclatures/combinations Lack of consistent units in summing indicators relating to item being measured Indicators are unit less and mathematics or arithmetic combinations can be odd The values sometimes do not represent anything outside of the context in which the
situation is being compared Selection of Indicators
Not based on tested theoretical concepts, and an understanding of the relationship of the indicators, and statistical relationships
Data Sources Source of the data used to create indicators that describe the measure were defined through the
availability of existing datasets, rather than data that represents vulnerability
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Recommendations
Data should be from objective sources and reasonable accessible
Indicators should be standardized and normalized to make community comparison
Indicators should be thoroughly validated with scientific reasoning or concepts
There should be a consensus agreement on the type, scope, and appropriateness of measures and indicators
The indicators and measures should be applicable to field experiences within an institutional framework
The conceptual framework should require collaborative process to determine measures’ importance
Qualitative techniques such as surveys or case studies should be conducted to assess the reliability of data.
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Next Steps: Developmental Measurement
Framework Resilient Healthcare Communities
Community Integration/CQI (After Actions)
Communications (Situation Awareness)
Safety & Security Patient Tracking Fatality Management Crisis Standard of Care
Surge Beds Exercises Staff Training NIMS Emergency
Management Procedures & Planning
Coalition Governance
Countermeasures, Supplies & PPE (CDC Grant Alignment)
Medical Evacuation Shelter in Place Plan Volunteer Management (ESAR-
VHP/MRC) Decontamination Isolation
Goal
Candidate Capabiliti
es
Measurement
Approach
Formative and Summative (Process & Performance Outcomes)
1. How well-prepared are healthcare coalitions to respond to mass casualty and catastrophic events, and then return to normal daily operations?
2. How well prepared are health care organizations to respond to daily stressors and events that challenge resources and then return to normal operations as a result of participating in a healthcare coalition?
Questions
Healthcare Coalitions/Health Care Organizations
Candidate
Measure
s
Pilot Testing, Primary Data Collection, Grant Alignment Coordination, and External Data Sources
In Development (Interview Questionnaire for Healthcare Coalitions, Evidenced Based Measures, Existing Relevant
HPP Measures, and Existing Grant Alignment
Outcome
s
Unit of Analysi
s