Potentially Preventable Emergency Room (ED) Visits Updated May 22, - PowerPoint PPT Presentation

Potentially Preventable Emergency Room (ED) Visits Updated May 22, 2013 0

Methodology/Definitions • Timeframe: March 2012 – February 2013 • Patient’s County of Residence: Bastrop, Burnet, Caldwell, Hays, Travis, Williamson and Other • < 65 in age • Potentially Preventable ED Visits  Non-Emergent – Care not required within 12 hours  Emergent, Primary Care Treatable – Required treatment within 12 hours, but could have been in a primary care setting  Emergent, ED Care Needed, Preventable/Avoidable – Required treatment within 12 hours, but the urgency of the condition could have been avoided with better primary care • Potentially Preventable ED by Clinic User and Clinic Non-User  Clinic Non-User: ED patients with no clinic visit, within timeframe  Clinic User: ED patients with a clinic visit • Patients are classified as Behavioral Health (BH) patients if they had a BH diagnosis at any clinic, ED, IP or OP encounter during the timeframe 1 March 2012-February 2013

Facts • ICare  575,395 Total Unique Patients  3,179,156 Total Encounters  268,367 Unique ED Patients  597,015 ED Encounters • Study  135,788 Unique Patients  241,000 ED Encounters  141,822 or 58.8% Potentially Preventable ED Visits  83,929 ED Encounters with Clinic User During Timeframe  67,513 ED Encounters with Medical Home at ED Encounter 2 March 2012-February 2013

Demographics - Age 81,823 85,000 2.0 Unique Patients 8.7% 71,247 1.8 67,998 0-17 Years 65,000 1.6 36.3% Unique Patients/ED Encounters 27.1% 18-30 Years 1.4 49,348 31-50 Years 51-64 Years 45,000 1.2 37,778 36,801 Rate 1.0 27.8% 25,000 0.8 19,942 ED Encounters 8.3% 11,851 0.6 34.0% 5,000 0.4 0-17 Years 28.2% 18-30 Years 0-17 Years 18-30 Years 31-50 Years 51-64 Years 0.2 31-50 Years 51-64 Years -15,000 0.0 Unique Patients ED Encounters Rate 29.6% • Age ranges of patients in the ICare system are predominantly split between the 0-18 and 19- 44 ranges (each being about 39%-41% of all patients), followed by the 45-64 range (about 17% of patients). There is only a small number of patients in ICare over 65 years old (4% overall) 3 March 2012-February 2013

Top 5 Frequent Primary Diagnosis Codes for ED Visit Age 0-17 780.6 FEVER UNSPECIFIED • Headache and/or cough 786.2 COUGH 787.03 VOMITING ALONE frequent primary diagnosis in 465.9 ACUTE URI UNSPEC all age groups 782.1 NONSPECIF SKIN ERUPT OT • Dental Disorder Age 18-30  0-17, 102 nd 648.93 OT CURRENT COND ANTEPARTUM  18-30, 5 th 789.09 ABDOM PAIN OT/MULTI SITE 784 HEADACHE  31-50, 7 th 789 ABDOM PAIN UNSP SITE  51-64, 18th 525.9 DENTAL DISORDER UNSPEC Age 31-50 789.09 ABDOM PAIN OT/MULTI SITE 784 HEADACHE 729.5 PAIN IN LIMB 786.2 COUGH 724.2 LUMBAGO Age 51-64 729.5 PAIN IN LIMB 789.09 ABDOM PAIN OT/MULTI SITE 786.5 UNSPECIFIED CHEST PAIN 784 HEADACHE 786.2 COUGH 4 March 2012-February 2013

Demographics - Gender 150,000 2.0 Unique Patients 133,437 1.8 120,000 1.6 Female 47.1% 107,559 Unique Patients/ED Encounters 52.9% Male 1.4 90,000 1.2 Rate 71,778 1.0 ED Encounters 63,998 60,000 0.8 0.6 44.6% Female Male 55.4% 30,000 0.4 0.2 0 0.0 Female Male Unique Patients ED Encounters Rate 5 March 2012-February 2013

Demographics – Race/Ethnicity 140,000 2.0 Unique Patients 9.8% 1.8 122,243 120,000 Black 38.5% 1.6 Hispanic Unique Patients/ED Encounters Other 100,000 1.4 White 47.2% 86,425 1.2 4.6% 80,000 Rate 1.0 64,045 ED Encounters 60,000 9.7% 0.8 52,209 Black 35.9% 0.6 40,000 Hispanic Other 23,482 0.4 White 20,000 50.7% 13,339 3.7% 0.2 8,860 6,185 0 0.0 Hispanic White Black Other Unique Patients ED Encounters Rate 6 March 2012-February 2013

Demographics - County Unique Patients 180,000 Bastrop 4.2% 0.5% 3.1% 174,220 Burnet 6.0% 14.5% 150,000 Caldwell 0.7% Unique Patients/ED Encounters Hays 120,000 Other 96,360 Travis 90,000 Williamson 71.0% 60,000 ED Encounters 3.9% 0.4% Bastrop 3.1% 33,510 13.9% 5.5% 30,000 Burnet 19,720 0.9% 13,350 9,341 7,523 Caldwell 2,143 923 8,140 5,667 4,248 972 671 Hays 0 Other Travis Unique Patients ED Encounters Williamson 72.3% 7 March 2012-February 2013

Demographics – Behavioral Health 3.00 Unique Patients 183,507 180,000 16.1% 2.50 Unique Patients/ED Encounters 150,000 BH - Yes 2.00 BH- No 113,910 120,000 Rate 1.50 83.9% 90,000 ED Encounters 1.00 57,703 60,000 23.9% 0.50 30,000 21,868 BH - Yes BH- No 0 0.00 BH - Yes BH- No 76.1% Unique Patients ED Encounters Rate • Patients are classified as BH patients if they had a BH diagnosis at any clinic, ED, IP, or OP encounter during the timeframe • The ED rate among BH patients is 1.64 times greater than the ED rate among non-BH patients 8 March 2012-February 2013

Demographic Summary • 0-17 age group had the largest number of unique patients and encounters, while 18-30 age group had the highest rate of encounters per person  Headache and/or cough frequent primary diagnosis in all age groups • 52.9% Female, while overall ICare 55.0% • 47.2% Hispanic, while overall ICare 42.7% • BH patients accounted for 16.1% of patients and 23.9% of encounters 9 March 2012-February 2013

Patient Location to Nearest Facility • Only hospitals and clinics that Clinic User Clinic Non-User submit data to the ICC were Unique Unique included in distance Patients Percent Patients Percent calculations TOTAL 31,968 100.0 68,737 100.0 • Includes Travis and Williamson Nearest Facility County residents whose exact Clinic 26,018 81.4 54,165 78.8 address were able to be Hospital 5,950 18.6 14,572 21.2 geocoded Distance to Clinic 3 3 For patients under age 18, the • <1 mi 11,749 36.8 23,549 34.3 distance was calculated to the 1-1.99 mi 9,448 29.6 20,505 29.8 nearest Family Practice or 2-4.99 mi 8,178 25.6 17,779 25.9 Pediatric clinic. For adults 5-9.99 mi 1,790 5.6 5,163 7.5 aged 18+, the distance was 10+ mi 803 2.5 1,741 2.5 calculated to the nearest Distance to Hospital 4 Family Practice clinic <1 mi 2,581 8.1 5,521 8.0 4 For adult patients, Dell • 1-1.99 mi 5,188 16.2 12,103 17.6 Children's Hospital was 2-4.99 mi 18,849 59.0 40,162 58.4 excluded from distance 5-9.99 mi 3,761 11.8 8,187 11.9 calculations 10+ mi 1,589 5.0 2,764 4.0 • Distance to facility does not seem to be a factor 10 March 2012-February 2013

Patient Location to Nearest Facility Average Percent Percent Living Average Distance to Receiving Closer to a Clinic Distance to Treatment Treatment at than Treatment Nearest Hospital Hospital Nearest Hospital Hospital Age Group Children 3.45 5.96 39.0% 93.4% Adults 3.48 5.79 36.4% 89.4% Day/Time Weekday During Clinic Hours 3.5 5.92 36.7% 90.9% Weekday During Non-Clinic Hours 3.45 5.75 37.9% 90.6% Weekend 3.45 5.88 37.3% 90.9% • Only hospitals and clinics that submit data to the ICC were included in distance calculations. • Includes Travis and Williamson County residents whose exact address was able to be geocoded. • For patients under age 18, the distance was calculated to the nearest Family Practice or Pediatric clinic. For adults aged 18+, the distance was calculated to the nearest Family Practice clinic. • For adult patients, Dell Children's Hospital was excluded from distance calculations. 11

Zip Codes with 50+ Patients >5 Miles from Clinic • 90.6% of patients live within 5 miles of a clinic, while 64.8% live within 2 miles • 83.8% of patients live within 5 miles of a hospital, while 25.8% live within 2 miles 12 March 2012-February 2013

Patients with Clinic Visits • Patients with clinic visits tend to live in or near Central Austin 13 March 2012-February 2013

Patients with No Clinic Visits • Patients with no clinic visits tend to live in SE and Central Austin 14 March 2012-February 2013

BH Patients • BH patients tend to live in or near Central Austin as well as East of I35 15 March 2012-February 2013

NYU Algorithm • Developed by the NYU Center for Health and Public Service Research to help classify ED utilization.  Developed with the advice of a panel of ED and primary care physicians  Based on an examination of a sample of almost 6,000 full ED records (1994 & 1999)  Abstracted data included the initial complaint, presenting symptoms, vital signs, medical history, age, gender, diagnoses, procedures performed, and resources used in the ED. 16 March 2012-February 2013 Source: New York University ED Algorithm, available at http://wagner.nyu.edu