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A WebBased Tool for Quality and Utilization Reporting

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MONAHRQ My Own Network, powered by AHRQ. Transforming your health care data into information ... payer. race. How do you get there? Import Data Wizard ... – PowerPoint PPT presentation

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Title: A WebBased Tool for Quality and Utilization Reporting


1
A Web-Based Tool for Quality and Utilization
Reporting
  • Anne Elixhauser

September 14, 2009
2
MONAHRQ My Own Network, powered by AHRQ
Transforming your health care data into
information about health, costs, and quality of
care.
3
Rationale
  • Why should it be so expensive to generate and put
    out basic information?
  • Why should information be so hard to get?
  • Why does every organization have to reinvent the
    wheel?

4
From Data to Information to
Action
Hospital discharge data can generate valuable
healthcare information
Information can be used to make decisions
Hospital discharge data are already being
collected
Quality of care in hospitals
Utilization and costs of care in hospitals
Rates of diseases in particular areas
Preventable hospital stays that indicate
breakdowns in care
Rates of procedures in particular areas
5
Key features of MONAHRQ
Currently based on hospital discharge data
Host user downloads MONAHRQ software from AHRQ
website
Software
Host user applies software to own data locally
  • Internally to better understand own data and to
    answer questions
  • To member organizations, e.g., through a
    password protected site
  • Publicly to provide information to the community

Host user creates local website on their own
server
Host user makes website available
6
The End User Website
State Healthcare Information Portal
  • Select the information you want
  • QUALITY INDICATORS
  • AVOIDABLE HOSPITALIZATIONS
  • RATES
  • UTILIZATION

7
Two quality paths to choose from
8
Consumer path on Quality Indicators
Arrays information on up to four hospitals for
the indicators selected. Click on any indicator
and get detailed information in graphic form.
9
Details in graphic form
Get details for each hospital in rank order,
compared to the state average.
10
Detailed path on Quality Indicators
The detailed path provides more information for
each indicator.
11
Overall results for the state
  • Information on specific indicators for the entire
    dataset
  • numerators
  • denominators
  • observed, expected and risk-adjusted rates
  • confidence intervals
  • Click on indicator for hospital-specific
    information

12
Results by individual hospital
State Healthcare Information Portal
  • Information on
  • numerators
  • denominators
  • observed, expected and risk-adjusted rates
  • confidence intervals

13
Potentially Avoidable Hospitalizations
Potentially Avoidable Hospitalizations based
on AHRQs Prevention Quality Indicators (PQIs
ambulatory care sensitive conditions)
14
Potentially Avoidable Hospitalization Path
Rates for avoidable admissions by county
Highest rates in dark blue, lowest rates in
light blue Click on Summary Table for more
details
15
Potential cost savings associated with reducing
preventable admissions
Details on avoidable admissions by county,
including cost savings. Can download to Excel.
16
Rates of Conditions and Procedures Path
Rates of health conditions and procedures Use
county populations as the denominator in
prevalence rates
17
Groupings of diagnoses and procedures
Can get information on prevalence of conditions
or procedures by DRG, MDC, or CCS
18
Search function
State Healthcare Information Portal
19
Tabular results by county
For all counties in the state numbers of
discharges and rate per 1,000 population. Click
on Map to view graphic display.
20
Map of rates by county
Rates for specific conditions and procedures by
county Highest rates in dark blue, lowest
rates in light blue
21
Utilization path
Utilization statistics (similar to information
from HCUPnet)
22
Utilization across all conditions, entire state
  • All conditions for entire database, listed by
    number of discharges
  • Click on any column header to re-sort by
  • charges/costs
  • LOS
  • percent died or
  • condition/procedure

23
Utilization on individual conditions
State Healthcare Information Portal
Can also search for utilization information on
individual conditions
24
for individual hospitals
25
Detailed utilization for all hospitals
  • Information on
  • numbers of discharges,
  • charges,
  • costs,
  • length of stay,
  • percent died
  • for all hospitals individually.
  • National, regional, and state benchmarks included.

Counties
26
More details for individual hospitals
  • The same information is available for individual
    hospitals, by
  • age group
  • gender
  • payer
  • race

27
How do you get there?
28
Import Data Wizard
  • The Import Data Wizard takes you through a
    step-by-step process of
  • importing your data,
  • mapping it to the format required by MONAHRQ,
  • analyzing the data, and
  • defining your hospitals and regions.

29
Select your data file
30
Map data elements
You map your data to the format required by
MONAHRQ by clicking and dragging data elements.
31
Map input values
You then define your data elements to values
understood by MONAHRQ (based on UB04 standard).
32
Load your data
33
Run analysis
34
Build your website
35
MONAHRQ Website Wizard
The Website Wizard takes you through a
step-by-step process of processing your data and
building your website.
36
Cell suppression and other parameters
Set thresholds for cell suppression (to protect
confidentiality) and other parameters.
37
Select which measures to include in website
Can specify which QIs to include. Measures
endorsed by the National Quality Forum are
identified.
38
Customize your website
  • Specify your website
  • where it should be stored
  • which pages you want to include
  • specifics about the style
  • insert your logo
  • what the website calls your data

39
The final product
40
What makes MONAHRQ unique?
Empowers organizations and consumers to use data
to make informed decisions
  • Organizations create and host
  • their own website and upload their own data
  • Local organizations do quality reporting using a
    standard, validated method
  • End users draw together multiple data sources
  • providing information at the local level
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