Transcript Performance Measurement Data

Performance
Measurement Data
Susan Weigl, Quality Consultant
NYS DOH AIDS INSTITUTE
Title I Quality Management Program
May 26, 2005
Why data? A quick review…
 The
heart of the scientific approach is
collecting and using data to guide your
thinking
 QI
is a variation of the scientific approach:
It’s systematic way for individuals and
teams to solve problems and improve
processes
Data and Problem Solving
 Enhances
knowledge, experience, insight
and intuition
 Three
ways data helps in problem solving:
1. separates what you think is happening
from what is really happening
2. establishes a baseline
3. helps avoid putting ineffective solutions
in place
When is data used in the
improvement process ?
 To
establish the baseline
 To gather more detailed information on a
process to help select a solution
 To assess how well an improvement is
functioning
 To demonstrate to others an improvement
action – comparison to baseline
 To monitor an improvement to make sure it
is not slipping
Performance data and HIV care

Most HIV quality programs use quality of care
indicators

Generally, indicators are based on specific
standards of care derived from formal guidelines
or through formal group decision-making
methods
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Review organizations/software - NYCSHRO,
IPRO, HIVQUAL
Criteria for selecting indicators for
measurement
 Relevance
 Measurability
 Improvability
 Validity
Tips for Effective Measurement
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Collect data that measures some aspect of the
process to be improved
Collect data that will inform your choices for
testing changes
Plot data over time
Seek usefulness, not perfection
Define the population
Use sampling
Integrate measurement into the daily routine
Use qualitative and quantitative data
How can data help set quality
priorities ?
 Goals
need to be prioritized in order to
conserve resources, gain staff focus and
buy-in and direct efforts towards issues
that most need it
How can data help set quality
priorities ?
Three criteria to consider:
1. Frequency – how many patients did this
effect?
2. Impact – what is the effect on patient’s
health if they did not receive this care?
3. Feasibility – can you realistically do
something about the problem?