1. Risk Assessment Farrokh Alemi, Ph.D.

2. 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.

3. 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.

4. 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.

5. 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

6. 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

7. 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

8. 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.

9. 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.

10. Computerized Severity Index ICD9 codes Key clinical findings

11. Best Approach Ease of use Cost of gathering information Accuracy Face validity

12. Differences Among Indices Type of Score Source of Data Patient Management Categories IntervalDiagnoses codes APACHEInterval Key clinical finding MedisgroupOrdinal Key Clinical finding Computerized Severity Index OrdinalBoth Computerized Disease Staging OrdinalDiagnoses codes

13. Accuracy of Predictions Percent Correctly Classified Patient Management Categories81 APACHE76 Medisgroup79 Computerized Severity Index77 Computerized Disease Staging82 Predicting every one will survive76

14. What to do? Rely on a combination Rely on known indicators of prognosis Rely on consensus of experts

15. Risk of Fall The ability to ambulate Steadiness of gait Presence of certain chronic medical conditions Number of medications Mental status History of falls

16. 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 http://gunston.gmu.edu/708/RiskPChart.htm

17. Take Home Lesson It is best to use multiple methods of measuring severity