EMS Geo-referenced Data Analysis of Opioid Overdoses and Naloxone Standing Orders in New Orleans Catherine R. Counts, PhD, MHA AcademyHealth Annual Research Meeting June 27, 2017
Acknowledgments • New Orleans EMS • Dr. Jeffrey Elder • Medical Director • Carl Flores • Chief of EMS • Jordan Ehrich • Liaison to Information technology • Co-authors • Dr. Arthur Mora • Dr. Julie Hernandez #ARM17 @CatherineCounts
Opioid Epidemic in Louisiana • 2009 • 10 “heroin related” deaths • 2014 • 777 drug overdose deaths • 16.9 per 100,000 • 2015 • 861 drug overdose deaths • 19 per 100,000 • 12.4% increase in rate of death from 2014 #ARM17 @CatherineCounts
Opioid Epidemic in New Orleans Accidental Drug Related Deaths in Orleans Parish 250 211 200 174 166 164 Recorded Deaths 150 105 2015 92 100 2016 81 48 50 34 18 13 4 0 Homicides Drug Related Opioids Fentanyl Cocaine Meth Drug Present During Autopsy #ARM17 @CatherineCounts
Policy & Organizational Changes • August 1, 2014 • Act 392 of the 2014 Regular Legislative Session • First responders can administer naloxone without prescription • August 1, 2015 • Act 192 of the 2015 Regular Legislative Session • Allows for standing orders • Removes risk of persecution for helping victim • January 2016 • New Orleans Health Department issues standing order • Naloxone available for purchase at two locations in NOLA • June 2016 • Naloxone available for purchase at all CVS locations in NOLA #ARM17 @CatherineCounts
Objective • Evaluate the spatial relationship between suspected opioid overdoses and naloxone distribution points (NDPs) in Orleans Parish #ARM17 @CatherineCounts
Our Data • New Orleans EMS naloxone usage • January 1, 2015 - November 15, 2016 (N = 1839) • From electronic patient care reporting system • Excluded • Under 18 • Single dose AND • No improvement after the injection AND • No other indicators of a drug overdose • Final sample of 1490 suspected overdoses, with 1481 known to have occurred within Orleans Parish #ARM17 @CatherineCounts
#ARM17 @CatherineCounts
Description of population Age Gender N Percent 75.4% Average 39.9 Male 1124 24.2% Female 361 Median 37 0.3% Maximum 91 Unknown 5 Minimum 18 Grand Total 1490 Race and Ethnicity N Percent New Orleans 2015** 50.5% White 753 34.3% 46.5% Black 693 59.5% 1.6% Hispanic 24 1.4% 1.2% Other Race 18 1.4% 0.1% Asian 2 3.4% Grand Total 1490 ** Source: American Community Survey 2015
Average Nearest Neighbor (ANN) • This spatial analysis technique is used to describe clustering / Observed Expected dispersion patterns for Mean Distance Mean Distance certain events = 108 meters = 384 meters • ANN ratio indicates Avg. Nearest whether the Neighbor Ratio Z score = -52 distribution is dispersed = 0.28 • Z-scores indicate how significant the observed pattern is #ARM17 @CatherineCounts
Hotspots of all Naloxone Use #ARM17 @CatherineCounts
Hotspots of Naloxone Use - Zoom #ARM17 @CatherineCounts
Caucasian Hotspots of Naloxone Use #ARM17 @CatherineCounts
African American Hotspots of Naloxone Use #ARM17 @CatherineCounts
Description of population Race and Ethnicity N ANN ratio Z-score Interpretation White 749 0.26 -38.4 Clustered (significant) African American 688 0.29 -35.2 Clustered (significant) Asian 2 2.09 2.9 Not significant Hispanic 24 0.62 -3.5 Not significant Other 15 0.45 -4.04 Not significant #ARM17 @CatherineCounts
Naloxone Distribution Points vs. EMS Naloxone Usage Hotspots #ARM17 @CatherineCounts
Naloxone Distribution Points vs. EMS Naloxone Usage Hotspots - Zoom #ARM17 @CatherineCounts
Limitations • Naloxone use doesn’t equal an overdose • EMS protocols • Provider impressions and biases • Strict inclusion criteria • Deaths may be missed • No data for overdoses that didn’t use 911 • Nearest Neighbor • Not weighted by population, next step • Potentially underestimating the signficance #ARM17 @CatherineCounts
Conclusions and Implications • Suspected overdoses occur through all neighborhoods regardless of their socio- demographic composition • Strong clustering patterns suggest two victim populations • EMS data is an untapped resource • Passive policy changes may be necessary but not sufficient • Distribution points exists, but barriers present • Community specific interventions • More research required #ARM17 @CatherineCounts
Future Opportunities • Include other first responder data • More socio-demographic analysis • Linking to naloxone dispensation data • Assumption that standing orders are being used • Evaluate barriers to access • Evaluate other potential distribution locations • Community health centers • Rehabilitation centers #ARM17 @CatherineCounts
Appendix
Census Tract Comparison Census tract Census tract Census tract Census tract OD victims race Median HH White pop. African Am pop. Other race pop. income Caucasian 39.7% 53.4% 6.9% $ 11,642 African American 24.6% 69.0% 6.4% $9,556 New Orleans White 34.3% African American 59.5% Other 6.2 % Median HH income $36,964
EMS Naloxone use by Census Tract #ARM17 @CatherineCounts
EMS Geo-referenced Data Analysis of Opioid Overdoses and Naloxone Standing Orders in New Orleans Catherine R. Counts, PhD, MHA¹ – Julie Hernandez, PhD, MA² - Arthur Mora, PhD, MHA² ¹University of Washington School of Medicine ²Tulane University School of Public Health and Tropical Medicine Principal Findings Research Objective Between January 2015 and Nearest neighbor analysis and 1 kilometer from one of the 15 To analyze spatial distributions of opioid November 15, 2016, 1,487 OODs hotspot mapping outlined clusters naloxone delivery points in New overdoses (OODs) in Orleans Parish, (mean=2.2 per day, range 0-11 per and high-risk areas. OODs were Orleans, with 64 cases recorded less Louisiana (New Orleans) with day) were recorded. Compared to recorded throughout New Orleans than 200 meters from an NDP. The comparisons of neighborhood the socio-demographic composition neighborhoods regardless of racial or average distance to the nearest NDP demographics and proximity to of New Orleans’ population, economic make-up, with the most was 1.7 km and the median distance naloxone distribution points (NDP) from Caucasian males were significant concentrations recorded was 1.0 km. January 1, 2015 through November 15, overrepresented among OODs in and around downtown, a 2016. victims. Two-thirds of the OODs preferred tourist destination. Preliminary analysis of fatal victims were between 18 and 40 overdoses indicate victims were not years old. These findings are Out of all OOD dispatch locations, further away from NDP than Study Design consistent with epidemiologic data 44.9% (n = 667) occurred less than revived/transported patients. from national level research. Conclusion Local EMS provider data of all naloxone administrations for suspected OOD was EMS intervention mapping provides uniquely used to (1) map out the exact GPS refined insights on OODs spatial patterns at a location of OODs, (2) identify clusters very large scale. OODs distribution throughout and hotspots for OODs throughout the New Orleans indicates 1) an occurrence through all neighborhoods regardless of their city and (3) evaluate possible socio-demographic composition, consistent associations between OODs clusters with epidemiologic findings at the national and the socio-demographic level, and 2) strong clustering patterns characteristics of the surrounding possibly suggesting two OOD victim populations- residents and transients neighborhoods, defined through Census (including tourists). 2010 data at the census tract level. Analysis further used the location of Physical proximity to NDPs does not seem to NDPs in New Orleans to evaluate their decrease OOD risk. potential impact on OODs patterns through distance analysis. During the study period, publicly available naloxone was offered through a standing pharmacy order at all stores of Policy/Practice Implications a large pharmacy chain (n=13), one Figure 1: Opioid overdose hotspots overlaid by naloxone delivery points locally owned pharmacy and a safety Strengthening naloxone accessibility as a potential life-saving commodity for net hospital retail pharmacy. OOD victims may require more than passive availability strategies such as Population Studied standing orders. Research suggests location-optimizing strategies targeting All patients that received EMS hotspots might help close some gaps by better accounting for diversity within administered naloxone were initially the target population. As the opioid included (n=1839). Those that received epidemic expands, further research is a single dose, did not improve after the needed to understand additional injection and had no other recorded determinants of naloxone access and indicators of drug overdose were use. excluded (n=1487). Figure 2: Caucasian opioid overdose hotspots Figure 3: African American opioid overdose hotspots
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