Analysis of Opioid Overdoses and Naloxone Standing Orders in New - - PowerPoint PPT Presentation
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
Catherine R. Counts, PhD, MHA AcademyHealth Annual Research Meeting June 27, 2017
@CatherineCounts #ARM17
@CatherineCounts #ARM17
@CatherineCounts #ARM17
164 92 81 13 34 4 174 211 166 48 105 18 50 100 150 200 250 Homicides Drug Related Opioids Fentanyl Cocaine Meth
Recorded Deaths Drug Present During Autopsy
Accidental Drug Related Deaths in Orleans Parish
2015 2016
@CatherineCounts #ARM17
suspected opioid overdoses and naloxone distribution points (NDPs) in Orleans Parish
@CatherineCounts #ARM17
1481 known to have occurred within Orleans Parish
@CatherineCounts #ARM17
@CatherineCounts #ARM17
Gender N Percent Male 1124 75.4% Female 361 24.2% Unknown 5 0.3% Grand Total 1490 Race and Ethnicity N Percent New Orleans 2015** White 753 50.5% 34.3% Black 693 46.5% 59.5% Hispanic 24 1.6% 1.4% Other Race 18 1.2% 1.4% Asian 2 0.1% 3.4% Grand Total 1490 Age Average 39.9 Median 37 Maximum 91 Minimum 18
** Source: American Community Survey 2015
technique is used to describe clustering / dispersion patterns for certain events
whether the distribution is dispersed
significant the observed pattern is
#ARM17 @CatherineCounts
Observed Mean Distance = 108 meters Expected Mean Distance = 384 meters
Neighbor Ratio = 0.28 Z score = -52
@CatherineCounts #ARM17
@CatherineCounts #ARM17
@CatherineCounts #ARM17
@CatherineCounts #ARM17
Race and Ethnicity N ANN ratio Z-score Interpretation White 749 0.26
African American 688 0.29
Asian 2 2.09 2.9 Not significant Hispanic 24 0.62
Other 15 0.45
#ARM17 @CatherineCounts
@CatherineCounts #ARM17
@CatherineCounts #ARM17
@CatherineCounts #ARM17
neighborhoods regardless of their socio- demographic composition
populations
sufficient
@CatherineCounts #ARM17
@CatherineCounts #ARM17
OD victims race Census tract White pop. Census tract African Am pop. Census tract Other race pop. Census tract Median HH 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
@CatherineCounts #ARM17
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
Research Objective To analyze spatial distributions of opioid
Louisiana (New Orleans) with comparisons of neighborhood demographics and proximity to naloxone distribution points (NDP) from January 1, 2015 through November 15, 2016. Study Design Local EMS provider data of all naloxone administrations for suspected OOD was used to (1) map out the exact GPS location of OODs, (2) identify clusters and hotspots for OODs throughout the city and (3) evaluate possible associations between OODs clusters and the socio-demographic characteristics of the surrounding neighborhoods, defined through Census 2010 data at the census tract level. Analysis further used the location of NDPs in New Orleans to evaluate their 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 a large pharmacy chain (n=13), one locally owned pharmacy and a safety net hospital retail pharmacy.
Principal Findings
EMS intervention mapping provides uniquely refined insights on OODs spatial patterns at a very large scale. OODs distribution throughout New Orleans indicates 1) an occurrence through all neighborhoods regardless of their socio-demographic composition, consistent with epidemiologic findings at the national level, and 2) strong clustering patterns possibly suggesting two OOD victim populations- residents and transients (including tourists). Physical proximity to NDPs does not seem to decrease OOD risk.
Population Studied All patients that received EMS administered naloxone were initially included (n=1839). Those that received a single dose, did not improve after the injection and had no other recorded indicators of drug overdose were excluded (n=1487). Between January 2015 and November 15, 2016, 1,487 OODs (mean=2.2 per day, range 0-11 per day) were recorded. Compared to the socio-demographic composition
Caucasian males were
victims were between 18 and 40 years old. These findings are consistent with epidemiologic data from national level research. Nearest neighbor analysis and hotspot mapping outlined clusters and high-risk areas. OODs were recorded throughout New Orleans neighborhoods regardless of racial or economic make-up, with the most significant concentrations recorded in and around downtown, a preferred tourist destination. Out of all OOD dispatch locations, 44.9% (n = 667) occurred less than 1 kilometer from one of the 15 naloxone delivery points in New Orleans, with 64 cases recorded less than 200 meters from an NDP. The average distance to the nearest NDP was 1.7 km and the median distance was 1.0 km. Preliminary analysis of fatal
further away from NDP than revived/transported patients. Conclusion Policy/Practice Implications Strengthening naloxone accessibility as a potential life-saving commodity for OOD victims may require more than passive availability strategies such as standing orders. Research suggests location-optimizing strategies targeting hotspots might help close some gaps by better accounting for diversity within the target population. As the opioid epidemic expands, further research is needed to understand additional determinants of naloxone access and use.
Figure 1: Opioid overdose hotspots overlaid by naloxone delivery points Figure 3: African American opioid overdose hotspots Figure 2: Caucasian opioid overdose hotspots
points (NDPs)
level
@CatherineCounts #ARM17