East Regional PMP. PMP Center of Excellence Update. Baltimore, MD April 6, 2011

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1 East Regional PMP Meeting: PMP Center of Excellence Update Baltimore, MD April 6, 2011

2 US Surgeon General s Expert Panel on Prescription Drug Abuse in Youth: March

3 Sources of Prescription Drugs for Abuse by Youth Common Understanding: Dominant source is from a friend or relative Given for free Purchased from them Stolen from them Prescriptions to youth are only a minor source Questionss: Does this hold true for all youth? Does this hold true in all locales? Will this hold true in the future, or is it changing?

4 What Can PMPs Tell Us About Use of Controlled Substances by Youth? Preliminary examination of data to demonstrate the kinds of analyses that are possible.

5 A Very Special Thanks to: Very Preliminary Analysis Maine PMP South Carolina PMP Wyoming PMP

6 Charleston County, SC South Carolina PMP and its vendor, HID, provided: Opioidprescriptions, prescriptions, Schedule IIandIII III Dispensed by SC Pharmacies in 2010 By county of patients residences We examined: City of Charleston and surrounding communities a metropolitan county Use of Opioids by youth compared to all ages

7 Opiate Utilization in Charleston County, SC (1/1/ /31/10) Qnty Dispensed (in %) # of Recipients (in %) ges Percenta Age

8 Charleston County, SC Opioid prescriptions only in Schedules II and III Users by age group How many of us were aware that a community could have almost as many individuals aged receiving opioid prescriptions as those aged 50 59, even if their use of prescriptions is less? Spartanburg County has a similar pattern Future Analyses Is this an emerging pattern? How prevalent is this in the rest of the county? What are the implications for abuse and misuse; i.e. is the use of opioids by youth for legitimate medical care?

9 Days of Supply: Charleston County, SC Age 0 9 average is 20 dosage units per day Age average is 10 Other ages average is 5 The pattern is similar in Spartanburg Future Analyses Is this an emerging pattern? How prevalent is this in the rest of the county? What are the implications for abuse and misuse?

10 The State of Maine Maine PMP provided: Schedules II, IIIandIVprescriptions IV Dispensed by Maine Pharmacies in 2009 Data for the entire state We examined: Use of prescriptions by youth age 25 and under, Comparison of junior high, senior high, and post high school age groups to one another and to the rest of all age users, by percentages

11 Maine Prescription Monitoring Program FY2010 Data Drug Categories of Dispensed Schedules II IV Drugs by Age Group N=434, Opioids Perc centage of Perso ons in Category Stimulants Sedatives Other 0 <= Age Groups

12 Maine Prescription Monitoring Program FY 2010 Data Payment Sources for Dispensed Schedules II IVIV Prescription Drugs Percent tage of payment source used by age group > Commercial insurance Medicaid Private (e.g., cash) Other Age Groups

13 Use of Controlled Substances by Youth in Maine Caveat: Timedid not permita rerun using rates per population This needs to be done, particularly as the number of years in each age group varied We plan to rerun the data with rates.

14 Use of Controlled Substances by Youth in Maine Preliminary observations and questions from the data: After high school, youth appear to have obtained more opioid prescriptions compared to younger ages. Is this related to employment and the ability to pay for the prescriptions through commercialinsurance? insurance? Related questions: Isthis related to increases in injuries, disease, other sources of pain? Is this related to leaving parental supervision?

15 What Can PMPs Tell Us About Prescription Drug Abuse by Youth? Preliminary examination of data to demonstrate the kinds of analyses that are possible.

16 Wyoming Wyoming PMP provided: Data for 296 persons who exceeded WY PMP s high threshold for Doctor Shoppers state population 544,000 Generally, one month s data for each person, i.e. the month they exceeded threshold; unsolicited reports were sent to prescribers Schedule II through V plus Carisoprodol and Ultram Dispensed by WY Pharmacies Statewidet We examined: Doctor shoppers by 10 year age groupings Use of Opioids by youth compared to all ages

17 Individuals Identified as Doctor Shoppers in WY PMP Database, Associated Prescriptions and Non liquid Doses, by Age Grouping %_ indiv %_prescr %_qty_disp

18 Wyoming Doctor Shoppers Observations: The WY doctor shoppers are younger than general population who obtain prescriptions more than 60% of the doctor shoppers are age 39 and under This is unlike general use in Charleston, SC data highest group 50 to 59 The quantities of prescriptions and dosage units obtained by younger doctor shoppers is similar to older doctor shoppers The peak in This is unlike general use in Charleston, SC data peak was 50 to 59 Different than general use in Charleston, SC, the 29 and under ages obtained the same level of prescriptions and dosage units as did older doctor shoppers.

19 Wyoming Doctor Shoppers Observation: Those 25 and under are 12.2% of the total WY doctor shoppers. At about 8 Rx and 300 dosage units per month for each of these young doctor shopper, what quantities of prescription drugs could they divert into abuse if WY were not monitoring and sending out unsolicited reports upon their exceeding the threshold? Given the relatively high thresholds used in WY, what additional young doctorshopping may be underway? Question for further analysis: Is youthful doctor shopping increasing, at least in some areas y pp g g of the country, compared to previous understandings?

20 Additional Areas for Analysis

21 Age specific rates of ED visits for nonmedical use of opioid analgesics (OAs) and benzodiazepines (BZDs) United States 2004and2008 MMWR June 18 benzodiazepines (BZDs) United States, 2004 and 2008 MMWR June 18, 2010

22 Drug Overdose among Youth PMP s Roles Should Emergency Departments routinely request PMP data when treating overdose victims to determine what drugs were obtained prior to overdose? Should prescribers and pharmacies by notified when persons to whom they prescribed overdose on the prescribed drugs? Should researchers examine PMP records for overdose victims to determine the extent to which prescribed drugs were involved?

23 Florida Newborns in Withdrawal per 1,00 00 Rate Rate per 1, Source: Herald Tribune, Sarasota Florida, July 18, 2010 Data Attributed to Florida Dept. of Health Years ICD code Drug withdrawal in newborn (drug is not specified)

24 Washington State Newborns in Withdrawal YEAR Rate of Newborns in Withdrawal per 1, Source: Washington State Department of Health ICD code Drug withdrawal in newborn (drug is not specified)

25 Maternal treatment with opioid analgesics and risk for birth defects Study by Cheryl S. Broussard, PhD; et al CONCLUSION: Consistent with some previous investigations, our study shows an association between early pregnancy maternal opioid analgesic treatment and certain birth defects. This information should be considered by women and their physicians who are making treatment decisions during pregnancy.

26 Increases in Newborn Withdrawal and Maternal Use of Opioids Risk of Birth Defects To what extent do these issues reflect use and abuse of prescription drugs by youth of child bearing age? Should Ob/Gyn physicians request PMP reports to determine Patients in pain treatment with opioids who don t advise their Ob/Gyn? Patients who are doctor shopping and refuse to disclose this? Should pediatricians obtain PMP Reports, i.e. should they continue to perceive prescription abuse as only for adults? Should researchers examine maternal PMP records when newborns areborn inwithdrawal /babiesareborn are born withdefects to determine if prescribed drugs were involved?

27 Other Lines of Inquiry for PMP Data Is youthful doctor shopping limited to a few states or is it more widespread? Is it increasing? To what extent does doctor shopping provide drugs for youth to abuse? Which drugs are involved in youthful doctor shopping; are they the same as for adults or the same in all areas? To what extent are youth obtaining drug Cocktails from prescribers, i.e.: Opioids id (e.g. Shdl Schedule II Oxycodone or Shdl Schedule III Hd Hydrocodone) d Benzodiazepines (e.g. Schedule IV Alprazolam) Muscle Relaxant (Unscheduled Carisoprodol/Soma 13 PMPs collect)

28 The Prescription Monitoring Program Center of Excellence at Brandeis University

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30 Prescription Monitoring Program Center of Excellence Briefing on PMP Effectiveness 2.1 Prescription Monitoring Programs: An Effective Tool in Curbing the Prescription Drug Abuse Epidemic February 2011

31 Prescription Monitoring Program Center of Excellence Notes From the Field Prescription Monitoring Program Center of Excellence PMP Management Tools Prescription Monitoring Program Center of Excellence PMP Study Analysis

32 PMP Center of Excellence Expert Panel 5 PMPRepresentatives Alliance of States with PMPs ATTC AATOD BJA CDC Carnevale Associates Coalition Against Ins. Fraud DEA FDA Health Insurance Carrier IJIS Institute t NASCSA National CAPT NMPI ONDCP SAMHSA Tufts Medical School Veterans Administration

33 COE Work in Selected Areas MA spatial analyses of questionable activity GA and neighboring state PMPs PMPs and prevention Exploring pilotproject project withwy Doctor shopping study Further work with ME and MA PMP data

34 Rates of Doctor Shopping Associated with OxyContin in MA, 1996 Rates per 100 of doctor shopping, by quintile "Source: Massachusetts Dept. of Public Health in partnership with Brandeis University"

35 Rates of Doctor Shopping Associated with OxyContin in MA, 1998 Rates of doctor shopping x 100, per quintile "Source: Massachusetts Dept. of Public Health in partnership with Brandeis University"

36 2005 Prescriptions Associated with Questionable Activity (Rates per 100,000 Prescriptions) by Pharmacy Town Questionable activity rates "Source: Massachusetts Dept. of Public Health in partnership with Brandeis University"

37 2005 Opioid-related Health Overdose Problems Rate per 100,000 by Town Rate per 100,000 Quintiles "Source: Massachusetts Dept. of Public Health in partnership with Brandeis University"

38 Work with GA and Neighboring State PMPs PMP data for prescriptions written in GA and filled in NC, SC, AL, and LA for a 12 month period Data made available by HID (IT vendor for all four states) by GAZip Code How do geographic prescription patterns by GA Zip Code compare with what we might expect? E.g., more prescriptions in border Zip Codes

39 Controlled Substances Dosage Units Prescribed by Georgia Prescribers but Dispensed in Other States AK VT WA* OR NV CA ID AZ UT MT WY CO NM ND MN SD WI NE IA IL KS MO OK AR MS NY MI PA OH IN KY TN GA AL WV VA NC SC ME NH MA RI CT NJ DE MD DC HI TX LA FL 0.4 Million Dosage Units 3.0 Million Dosage Units 9.8 million Dosage Units *Washington has temporarily suspended d its PMP operations due to budgetary constraints. t 12.5 Million Dosage Units

40 Average Number of Patients per GA Prescriber for Prescriptions Filled in SC in 2009, by GA Zip Code Legend Average number of patients per prescriber

41 Average Number of Patients per GA Prescriber for Prescriptions Filled in AL in 2009, by GA Zip Code Legend Average number of patients per prescriber

42 Average Number of Prescriptions per Patient, 2009 Prescriptions Originating in GA and Filled in AL, by GA Zip Code Legend Average number of prescriptions per patient

43 GA Zip Codes with More Than 100 Patients per Prescriber and More Than Two Prescriptions per Patient, on Average, for Prescriptions Filled in AL in 2009 Legend GA Zip Codes meeting (1) or not meeting (0) the criteria 0 1

44 Prevention Implications PMP data from neighboring states can help highlight potential drug problem areas in a focal state, whether or not PMP data is available in thefocal state Data from different neighboring states can reveal different aspects of a problem (e.g., border communities) A complete needs assessment may involve assembling data from multiple state PMPs

45 PMPs and Prevention COE collaboration with Carnevale & Assoc. to develop recommendations for how PMP data can be used to support prevention SAMHSA expected to OK report s release soon COE currently working with WY PMP, Dept. of Health, and prevention practitioners to explore pilot use of PMP data for prevention

46 Wyoming: Number of Controlled Substance Prescriptions by Zip Code Aug., July, Number of prescriptions, in quintiles

47 Wyoming: Number of Prescriptions per Person by Zip Code Aug., July, Number of prescriptions per person, in quintiles

48 Wyoming: Nunber of Prescriptions Associated with Doctor Shopping Behavior per 10,000 Prescriptions, by Zip Code Aug., July, Proportion of prescriptions associated with doctor shopping, in quintiles

49 Wyoming: Zip Codes with Population Greater than 1,000 and High Doctor Shopping Rates (Number of Prescriptions Associated with Doctor Shopping per 10,000 Prescriptions) Aug., July, Legend Pop < 1000 or doctor shopping rate < 20 Pop > 1000 and doctor shopping rate between 20 and 60 Pop > 1000 and doctor shopping rate > 60

50 Work with WY: Next Steps Analyze doctor shopping rates in relation to Zip Code demographic data In MA, white, middle class communities associated with highest rates of doctor shopping/questionable activity Work with Steve Butler of Univ. of Wyoming to develop PMP data into community profiles usable by local prevention practitioners Work with Dept. of Health to access death certificate and hospital ldischarge data

51 Doctor Shopping Study Analyze individual and community level characteristics associated with individuals meeting questionable activity thresholds Data from MA, ME, WY, possibly SC and other states MA prescriber surveys Accompanying and follow up to unsolicited report Preliminary results suggest questionable activity threshold capturing high proportion of doctor shoppers

52 Further Work with ME and MA Maine s longitudinal database De identified but with same ID # across nearly six years of data Examine prescription histories leading up to meeting doctor shopping thresholdh Prescription histories after triggering unsolicited report Massachusetts data Track prescription histories for individuals on whom unsolicited report is sent, and individuals with similar prescription patterns on whom no report is sent

53 Contact Information Peter Kreiner, Ph.D. Principal Investigator PMP Center of Excellence Brandeis University Wbi Website:

54 Contact Information John Eadie, MPA Director PMP Center of Excellence Brandeis University Wbi Website: