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Data-Driven Multidisciplinary Approaches to Reduce Prescription Drug Abuse in Kentucky Analytical Models Using PDMP Data Svetla Slavova, PhD Huong Luu, MD, MPH 2017 BJA Grantee National Meeting March 30-31, 2017 Study 1: Trends and


  1. Data-Driven Multidisciplinary Approaches to Reduce Prescription Drug Abuse in Kentucky Analytical Models Using PDMP Data Svetla Slavova, PhD Huong Luu, MD, MPH 2017 BJA Grantee National Meeting March 30-31, 2017

  2. Study 1: Trends and Disparities of Opioid Prescribing in Kentucky (preliminary results)

  3. Historically High Opioid Prescribing in Kentucky

  4. McDonald DC, Carlson K, Izrael D. Geographic variation in opioid prescribing in the U.S. J Pain. 2012;13(10):988-96. doi:10.1016/j.jpain.2012.07.007.

  5. Rate of Patients with Opioid Prescriptions by County, Kentucky, 2012

  6. Slavova, S., Bunn, T., & Gao, W. (2015). Drug Overdose Hospitalizations in Kentucky, 2000-2013. KIPRC. Retrieved from http://www.mc.uky.edu/kiprc/projects/ddmarpdak/pdf/Drug_Overdose_Hospitalizations_2000-2013.pdf

  7. Table 1: Characteristics of drug intoxication deaths, adult Kentucky residents, 2013-2014 a . By Involved opioid Demographic All Drugs (Rate per 100,000) Pharmaceutical opioids Heroin- Fentanyl- Rate per excluding Characteristics No. (%) related related 100,000 morphine and N=415 N=151 fentanyl N=634 All 1,971 (100) 29 6.1 2.2 9.3 Gender Males 1,209 (61) 37 8.8 3.0 10.4 Females 762 (39) 22 3.2 1.5 8.2 Race Black 69 (4) 13 3.1 c * 2.8 c White 1,885 (96) 31 6.4 2.5 10.0 Other 17 (<1) 14 * * * Age groups 1.3 c 18-24 131 (7) 15 7.4 2.3 25-34 403 (20) 36 13.1 3.6 9.8 35-44 518 (26) 46 8.4 3.5 15.1 45-54 540 (27) 44 6.3 3.0 15.3 55-64 313 (16) 27 2.6 1.7 10.4 65+ 66 (3) 5 * * 2.0 Region Appalachian counties 626 (32) 34 2.0 2.4 16.4 Non-Appalachian counties 1,345 (68) 27 7.6 2.2 6.7 Marital status Divorced 662 (34) Single 643 (33) Married 528 (27) Widowed 95 (5) Not classified 43 (2) Place of death ED/outpatient 348 (18) Inpatient 190 (10) Residence 1,078 (55) Other 355 (18) Manner of deaths Unintentional 1,750 (89) Suicide/Self-harm 105 (5) Undetermined 116 (6) a Data were provisional at the time of the analysis. b The reported rates could be different from rates reported elsewhere because the study population was limited to adult Kentucky residents (i.e., 18 years of age or older) who died in Kentucky from drug intoxications/poisonings. c Rates were marked as unreliable when they were based on less than 20 deaths * Rates based on less than 10 counts were suppressed according to the state data reporting policy. Slavova S, Bunn TL, LaMantia S, Corey T, Ingram V., Linking death certificates, post-mortem toxicology, and prescription history data for better identification of populations at increased risk for drug intoxication deaths, Pharmaceutical Medicine , 2017, DOI: 10.1007/s40290-017-0185-7

  8. Research Questions: 1) Are there any positive changes in opioid prescribing in Kentucky in recent years? • Decline in the number/rate of patients with opioid prescriptions? • Decline in the number/rate of patients with high daily dose of morphine milligram equivalent? 2) Are there significant differences in opioid prescribing for Appalachian vs. Non-Appalachian Kentucky residents?

  9. Method: Repeated Measures Regression Negative Binomial Generalized Estimating Equations (GEE) Modeling Variables Data Sources Count Outcome Variables (unit of analysis: county-quarter) (1) Number of patients with opioid prescriptions* KASPER/Office of Inspector (Offset=Log of population) General (OIG), 2012 – 2015 (2) Number of patients receiving more than three days with 100 MME or more* KASPER/OIG, 2012 - 2015 (Offset=Log of population) (3) Number of patients receiving more than three days with 100 MME or more* KASPER/OIG, 2012 - 2015 (Offset= Log of patients with opioid prescriptions*) Covariates: (1) Region: Appalachian vs. Non-Appalachian (2) Rate of ED visits due to injury excluding poisoning per 1,000 population Outpatient Claims Data, Office of Health Policy, 2012 - 2015 (3) Age-adjusted rate of invasive cancer incidence per 100,000 population Kentucky Cancer Registry, 2010 - (average rate over previous two years ) 2014 (4) Rate of buprenorphine prescriptions (per 1,000 population) KASPER/OIG, 2012 - 2015 (5) Percent of persons ages 55+ with opioid prescriptions* KASPER/OIG, 2012 - 2015 * Excluding prescriptions of buprenorphine or buprenorphine/naloxone combination

  10. GEE model: Number of patients with opioid prescriptions Offset: Log of population RR Q1-12 =1.25 (1.16 -1.36) RR Q1-12 =1.25 (1.16 -1.36) RR Q4-15 =1.23 (1.14 -1.32)

  11. GEE model: Number of patients with high daily MME dose Offset: Log of population RR Q1-12 =1.35 (1.20 -1.52) RR Q4-15 =1.09 (0.96 -1.23)

  12. GEE model: Number of patients with high daily MME dose Offset: Log of patients with opioid prescriptions RR Q4-15 =0.92 (0.83 -1.01) RR Q1-12 =1.10 (1.002 -1.21)

  13. http://www.chfs.ky.gov/os/oig/kaspertrendreports

  14. • If the ACME is 100 or greater, a warning symbol will appear along with a note that increased clinical vigilance may be appropriate. • This warning threshold was established by consensus of the KASPER Advisory Council members based on a recommendation from the Kentucky Injury Prevention and Research Center. • For patients with an ACME of 100 or greater, the last page of the report will also include information and links to additional resources about naloxone prescribing and dispensing to help in situations where a provider believes the patient may be at risk of an overdose. • The Kentucky Board of Medical Licensure advises that when a patient’s MED level reaches the 100 threshold, prescribers are expected to increase safeguards (such as increased monitoring and the use of naloxone) and that ongoing treatment be supported by increased documentation of clinical reasoning. KASPER Tips: Morphine Equivalent Dose and Naloxone Information on KASPER Reports, http://www.chfs.ky.gov/os/oig/KASPERtips

  15. Study 2: Transition from non-medical prescription opioid use to heroin among Kentucky residents who died from heroin-related intoxication deaths

  16. Data sources: Linked death certificates, post-mortem toxicology, and PDMP data for 2013-2014 • Kentucky overdose decedents; Results: • Kentucky heroin intoxication decedents had substantial exposures to legally acquired prescription opioids in the years before their death; 91% of decedents had PDMP records for opioid analgesics (excluding • buprenorphine) during the 5 years before death; • 77% had opioid prescriptions filled within two-years before death; • 20% had a history of continuous opioid use (COU) during the two years before death (COU defined as at least 90 days’ supply in a six-month period, and with gaps between prescriptions of no more than 30 days); • 41% did not meet the criteria for COU but had a history of high-dose opioid use (≥50 MME daily ).

  17. Study 3: Ecological analysis of fentanyl overdose deaths

  18. • The number of fentanyl submissions to state police crime labs increased 10 times (from 17 in 2013 to 178 in 2014), • The number of fentanyl prescriptions decreased 7% statewide from 2013 to 2014. • Fentanyl-related overdose deaths nearly tripled from 2013 to 2014. • Counties with increased number of fentanyl submissions reported an increased number of fentanyl- related deaths. Slavova S, Bunn TL, LaMantia S, Corey T, Ingram V., Linking death certificates, post-mortem toxicology, and prescription history data for better identification of populations at increased risk for drug intoxication deaths, Pharmaceutical Medicine , 2017, DOI: 10.1007/s40290-017-0185-7

  19. Acknowledgements: This work was supported by Grant No. 2014-PM-BX-0010 (Data-Driven Multidisciplinary Approaches to Reducing Prescription Abuse in Kentucky) awarded by the Bureau of Justice Assistance (BJA). BJA is a component of the Department of Justice’s Office of Justice Program, which includes the Bureau of Justice Statistics, the National Institute of Justice, the Office of Juvenile Justice and Delinquency Prevention, the Office of Victims Crime, and the SMART Office. Points of view or opinions in this document are those of the authors and do not necessarily represent the official position or policies of the U.S. Department of Justice. The authors would like to acknowledge the members of the KASPER staff with the Office of Inspector General, and the Kentucky Department for Public Health for their support of this project.

  20. Svetla Slavova ssslav2@email.uky.edu

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