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Preventable Hospitalization Costs and Mapping Tool Web Conference: Presentation

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On June 16, 2008, Melanie Chansky presented the AHRQ Preventable Hospitalization Costs and Mapping Tool on a Web conference. This is the text version of the event's slide presentation. The event's slide presentation is available in PowerPoint® and PDF formats: (PowerPoint file, 2.4 MB; PDF File, 116 KB; PDF Help).

>Slides: 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30

Slide 1: Preventable Hospitalization Costs and Mapping Tool

June 16, 2008

Marybeth Farquhar
Agency for Healthcare Research and Quality

Melanie Chansky
Battelle Centers for Public Health Research and Evaluation

On the top of the slide are the logos for the Department of Health & Human Services and the Agency for Healthcare Research and Quality (AHRQ).

This presentation uses a template with a blue background and a header with the AHRQ and Department of Health & Human Services logos on the left and the HCUP logo on the right.

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Slide 2: Webinar Overview

  • Overview of Mapping Tool
  • Demonstration
  • Overview of Data
  • Interpretation and Use of Results
  • Future Plans

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Slide 3: Overview of Mapping Tool

Overview of Mapping Tool.

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Slide 4: AHRQ Quality Indicators (QIs)

  • Use existing hospital discharge data, based on readily available data elements
  • Incorporate severity adjustment methods (APR-DRGs, comorbidity groupings and hierarchical modeling)
  • Five modules: Inpatient, Patient Safety, Prevention, Pediatric, and Neonatal

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Slide 5: Preventable Hospitalization Costs and Mapping Tool

The mapping tool is a new QI software application designed to help organizations to:

  • Better understand geographical patterns of potentially preventable hospital admission rates for selected health problems.
  • Allocate resources more effectively by calculating potential cost savings if admission rates are reduced.

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Slide 6: Main Functions of the PHC Tool

  • Creation of maps that show the rates of hospital admission for selected health problems on a county-by-county basis.
  • Calculation of potential cost savings that may occur if the number of hospital admissions for selected health problems in each county is reduced.
  • Ability to place additional information about local populations onto maps to indicate the number of persons who are at greatest risk for those health problems in each county.

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Slide 7: It processes all Prevention QIs...

  • PQI 1 Diabetes Short-term Complications Admission Rate
  • PQI 2 Perforated Appendix Admission Rate
  • PQI 3 Diabetes Long-term Complications Admission Rate
  • PQI 5 Chronic Obstructive Pulmonary Disease Admission Rate
  • PQI 7 Hypertension Admission Rate
  • PQI 8 Congestive Heart Failure Admission Rate >
  • PQI 9 Low Birth Weight Rate
  • PQI 10 Dehydration Admission Rate
  • PQI 11 Bacterial Pneumonia Admission Rate
  • PQI 12 Urinary Tract Infection Admission Rate
  • PQI 13 Angina without Procedure Admission Rate
  • PQI 14 Uncontrolled Diabetes Admission Rate
  • PQI 15 Adult Asthma Admission Rate
  • PQI 16 Lower-extremity Amputation Rate among Diabetic Patients

There is no longer a PQI 4 and PQI 6.

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Slide 8: ... and all area-level Pediatric QIs

  • PDI 14 Asthma Admission Rate
  • PDI 15 Diabetes Short-term Complications Admission Rate
  • PDI 16 Gastroenteritis Admission Rate
  • PDI 17 Perforated Appendix Admission Rate
  • PDI 18 Urinary Tract Infection Admission Rate

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Slide 9: Tool Demonstration

Tool Demonstration.

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Slide 10: Questions?

This slide shows a map of the United States that is color-coded by county.

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Slide 11: Overview of Data

Overview of Data.

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Slide 12: Underlying Data Used by the Tool

  • Current indicator specifications
  • Cost-to-charge ratios
  • Census data

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Slide 13: User-provided data

  • Most tool functions require data provided by the user
  • Certain data elements are required for creating maps and calculating county-level QI rates
  • Some data elements are optional – cost savings and population data

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Slide 14: Required Variables

The following variables must be present in your data file:

  • Age (patient age in whole years)
  • Ageday (patient age in days)
  • Sex (sex coded 1 for male, 2 for female)
  • DX1 (ICD-9-CM primary diagnosis)
  • PR1 (ICD-9-CM primary procedure)
  • MDC (major diagnostic category)
  • DRG (diagnosis related group)
  • PSTCO (county of patient residence)
  • Atype (admission type)
  • Asource (admission source)

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Slide 15: Optional Variables

The following variables are optional, but are needed if the user wants the PHC tool to calculate potential cost savings:

  • Totchg (total charges)
  • Hospid (State Inpatient Database hospital identifier)

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Slide 16: Optional Population Dataset

A second dataset is required if users wish to overlay population information on maps. This dataset must include the following variables:

  • County (State FIPS code followed by county FIPS code)
  • Sex (sex coded 1 for male, 2 for female)
  • Age (age group coded 1 for 0-17, 2 for 18-39, and 3 for 40+)
  • Pop (population by sex and age cells)

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Slide 17: Data Problems

  • Most reported problems are related to the user datasets.
  • The QI team can provide technical assistance with your dataset if you cannot solve your problem with the information provided here.

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Slide 18: Outputs

  • All outputs are automatically placed in the folder where your dataset is located
  • Outputs include:
    • CSV file
    • Excel file
    • Maps

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Slide 19: CSV & Excel Files Include:

  • Numerator count of flagged cases
  • Denominator count of the at-risk population
  • Observed rate
  • Risk-adjusted rate
  • Standard error of risk-adjusted rate
  • Whether county is significantly higher or lower than statewide rate
  • Potential cost savings associated with a 10% reduction in flagged cases (optional)

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Slide 20: Maps

  • Separate maps will be created for each selected QI
  • Files will be named after the QI, e.g., PQI14 , PQI1
  • Can be opened and manipulated using any graphics program or picture viewer

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Slide 21: Interpretation and Use of Results

Interpretation and Use of Results.

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Slide 22: There are many possible uses for mapping tool data…

  • Public Reporting
  • Intervention Targeting
  • Tracking Intervention Impact
  • Identification of Best Practices

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Slide 23: …but several issues that must be addressed to effectively use the data

  • Data leaves you with more questions: Are these rates reasonable? Do they present significant quality concerns?
  • Excel data needs to be manipulated to present a more dynamic, appealing, and concise data display.

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Slide 24: Sources of Comparison Data

State benchmarks (provided by tool)

  • PQI and PDI User Guides
  • HCUPnet

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Slide 25: Presentation of Data

  • Focus on using maps for presentations of data
  • Focus on using Excel outputs for further analysis or as source data for new graphics
  • Consider creating concise narrative data summaries

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Slide 26: Future Plans

Future Plans.

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Slide 27: We're exploring ways to improve the mapping tool…

  • Incorporation into Windows QI Software
  • Allow for mapping below the county-level (zip-code, etc.)
  • Other ideas??

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Slide 28: Further Info on the Mapping Tool

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Slide 29: Additional Assistance

Technical Assistance:

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Slide 30: Questions?

This slide shows a map of the United States that is color-coded by county.

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Current as of May 2009

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