1. The Use of NHAMCS Emergency Department Research

2. Jim Edwards, BS. Research Associate Department of Emergency Medicine University of Illinois College of Medicine Chicago, IL

3. Objectives Explain the NHAMCS database Implementation of database Recent publications

4. Description National Hospital Ambulatory Medical Care Survey Collect data on the utilization of services and provision of care in ED

5. Description National sample General and short stay hospitals No federal, military, or VA 50 states and D.C. Began annually in 1992

6. Description Four stage sampling –Geographically defined areas –Hospitals within areas (~500) –ED within hospitals (some > 1) –Pt visits within ED (~24,000)

7. Description CDC personal train hospital staff on data collection Data on Patient Record Form during random 4 week recording period

8. Patient Record Form

9. Description Data Description Demographics Payment Complaints Diagnoses Imagining, labs, procedures

10. Description Data Description Meds Providers Reason for injury Wait time

11. Description Data Description Pain Disposition Place of injury Hospital characteristics Initial V/S in 2002

12. Coding Description A Reason for Visit Classification (NCHS) ICD-9-CM Drug coding classification system (NCHS) National Drug Code Directory

14. SPSS Statistical program User friendly Handles more cases than Excel

15. SPSS Download data file Download documentation Merge files if needed

22. Joseph and Ward: New-Onset AF Results Conversion rate after 48 hrs –Sotalol 88% –Amiodarone 77% –Digoxin 58% –P < 0.05 when sotalol compared to digoxin Time to conversion  SR –Sotalol 13.0  2.5 –Amiodarone 18.1  2.9 –Digoxin 26.9  3.4 –P < 0.05 when sotalol and amiodarone compared to digoxin

26. SPSS Imputed variables –Diagnosis –Reason for visit –Drugs –Age ranges

27. SPSS Dummy variables –One or none –Allows calculation of 2x2 tables IV Narc (1) No IV Narc (0) Admit (1) 75 75% 5 5% Discharged (0) 5 5% 15 15%

28. Patient Demographics Calculations N ( %) Sex Male264 (65) Female143 (35) Age, y Mean41.5 ± 15.3 Median40.0 <18 12 ( 3) 18-64359 (88) >65 36 ( 9) Ethnicity White356 (88) Black 38 ( 9) Other 13 ( 3)

29. Patient Demographics Calculations Pain Level at Presentation None 7 ( 2) Mild 49 (12) Moderate102 (25) Severe102 (25) Unknown147 (36) Mode of Arrival Walk-in348 (86) Ambulance 36 ( 9) Unknown 23 ( 6)

30. Patient Demographics Calculations Diagnosis (n = 443) Renal colic (788.0)155 (35) Calculus of the kidney (592.0)188 (42) Calculus of the ureter (592.1) 78 (18) Unspecified urinary calculus (592.9) 6 ( 4) Hydronephrosis (591.0) 6 ( 1) Disposition Admitted 59 (15)

31. Procedures Calculations N ( %) Diagnostic study400 (98) Other x-ray132 (32) CT 89 (22) US 20 ( 5) U/A319 (78) CBC225 (55) Procedure Pain medication346 (85) IV fluids251 (62) Foley 12 ( 3)

32. Medications Calculations Medication Class N ( %) Narcotic277 (68) Nonnarcotic216 (53) NSAID 191 (47) Other nonnarcotic 25 ( 6) Antiemetic140 (34) Narcotic and NSAID139 (34) Narcotic and other nonnarcotic 10 ( 2) Narcotic and antiemetic124 (31) Nonnarcotic and antiemetic 80 ( 0)

33. Medications Calculations AgentN ( %) Parenteral Agents Narcotics Meperidine 84 (21) Morphine sulfate 59 (15) Hydromorphone 37 ( 9) Meperidine/Promethazine 11 ( 3) Buprenorphine 6 ( 2) Botorphanol tartrate 4 ( 1) NSAIDs Ketorolac190 (47) Anti-emetics Promethazine 88 (22) Prochlorperazine 32 ( 8) Droperidol 11 ( 3) Hydroxyzine 7 ( 2) Metaclopramide 4 ( 1)

34. Odds Ratio/Pain Medication Calculations N (%)OR95% CIp-value Ethnicity White306 (86)1.70.76-3.680.23 Non-white 40 (79) Age <65318 (86)1.70.68-4.200.30 >65 53 (78) Pain Severity Severe 97 (95)4.01.40-12.310.01 Moderate, mild, or none131 (83) Severe or moderate185 (91)2.91.26-6.850.01 Mild or none 43 (77)

35. Logistic Regression/Pain Medication Calculations OR95% CIp-value Ethnicity White 1.20.57-2.390.69 Age <65 2.50.78-8.140.12 Pain Severity Severe 2.60.88-7.810.08 Severe or moderate 2.20.91-5.290.08

36. Advantages No data collection needed IRB exemption Large number of cases Free Large sample

37. Disadvantages Lack of information –Drug doses, route, meds before ED –No pain relief measures –No VS –No lab or radiology results

38. Conclusions No data collection Can get lost in the database Having and knowing ALL the documentation is key

39. Conclusions Lack of information Next year vital signs

40. Contact Information Jim Edwards –Jedwar10@uic.eduJedwar10@uic.edu –Pager 9714