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Risk Assessment
Farrokh Alemi, Ph.D.
Session Objectives
1. Discuss the role of risk assessment in the
TQM process.
2. Describe the five severity indices
presented in the course.
3. Compare and contrast the indices based on
the sources of data used, scores produced,
and accuracy of predictions.
Why measure severity?
• One way to measure quality of health care
is to compare outcomes for a group of
patients to outcomes observed for other
patients with similar severity of illness.
• When we want to do so, it is important to
separate the influence of the patients'
severity of illness from the quality of care.
What is severity?
• What is severity?
• Severity is the progression of the disease
when left untreated.
• Severity is prognosis under ideal levels of
care.
• Some patients are further along in their
illness than others.
How to measure severity?
• Statistical analysis of outcomes of care
– Sample may not be relevant
• Expert opinions
– Expert consensus maybe false
• Patient’s self insight
– Only felt symptoms affect self insight
Sources of Data
• ICD9 codes
– Readily available
– Maybe gamed
– Reflect whole visit
• Key clinical findings
– Requires chart review
– Maybe masked by treatment
– Reflects condition on admission
Disease Staging
1. Stage 1 includes conditions with no
complications and minimal risk for the
patient.
2. Stage 2 includes problems which are
contained in one organ or system.
3. Stage 3 includes problems in multiple sites
and general systemic problems.
4. Stage 4 is death
APACHE
• Deviations from norm on 12 physiological
variables like heart rate, blood oxygen level,
or respiratory rate.
• Age of the patient.
• Chronic illness include coma.
Medisgroup
• At level 0, there are no clinical findings.
• At level 1, there are minimal abnormal findings.
• At level 2, there are either acute findings or
findings with an unclear potential for organ
failure.
• At level 3, there are clinical findings with high
potential for imminent organ failure.
• At level 4, organ failure is indicated.
Computerized Severity Index
• ICD9 codes
• Key clinical findings
Best Approach
•
•
•
•
Ease of use
Cost of gathering information
Accuracy
Face validity
Differences Among Indices
Patient Management
Categories
Type of
Score
Source of Data
Interval
Diagnoses codes
Ordinal
Key clinical
finding
Key Clinical
finding
Both
Ordinal
Diagnoses codes
APACHE
Interval
Medisgroup
Computerized Severity
Index
Computerized Disease
Staging
Ordinal
Accuracy of Predictions
Patient Management Categories
APACHE
Medisgroup
Computerized Severity Index
Computerized Disease Staging
Predicting every one will survive
Percent Correctly Classified
81
76
79
77
82
76
What to do?
• Rely on a combination
• Rely on known indicators of prognosis
• Rely on consensus of experts
Risk of Fall
• The ability to ambulate
• Steadiness of gait
• Presence of certain chronic medical
conditions
• Number of medications
• Mental status
• History of falls
Analyze Data
• At different time periods the risk for fall can
be calculated for each patient
• Now we can analyze whether the number of
falls exceeds what could be expected from
patient conditions
• See example data at following address
http://gunston.gmu.edu/708/RiskPChart.htm
Take Home Lesson
• It is best to use multiple methods of
measuring severity