Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
PDMPs as Prevention Tools
Presenters:
• Tina Farales, Department of Justice Administrator, Prescription Drug
Monitoring Pr...
Disclosures
Chris Baumgartner; Tina Farales; Peter Kreiner,
PhD; Neal D. Traven, PhD; and John L. Eadie have
disclosed no ...
Disclosures
• All planners/managers hereby state that they or their
spouse/life partner do not have any financial
relation...
Learning Objectives
1. Explain how state and county public health officials
use de-identified PDMP data to coordinate opio...
De-Duplicated/De-Identified Data
PDMPs as Prevention Tools
Mike Small has disclosed no relevant, real or
apparent personal or professional financial
relationships with proprietary e...
PDMPs as Prevention Tools
De-Duplicated/De-Identified Data
Learning Objectives:
Identify challenges of using PDMP data for...
California Health and Safety Code section § 11165. (a)
To assist health care practitioners in their efforts to ensure appr...
The prescription drug epidemic is predominantly a public health
Problem. Public Health program design, implementation and
...
The clinical community requires a much more informative data
Presentation than CURES 1.0’s simple provisioning of a basic
...
The Public Can and Should Know
The PDMPs store the most informative data regarding the current
public health crisis.
The p...
De-Duplication
PDMP patient data lacks positive identifiers.
Name:
Mike Small, Michael Small, Michael J. Small, Mikey Smal...
De-Duplication
Name and DOB and Zip(5) OR Name and Street Address and City
Mike Small Michael J. Small
04/19/1963 04/19/19...
De-Duplication
Every day approximately 145K new Rx records are added to the CURES 2.0
data base. With this new data, the a...
De-Identified Data
Anonymized Patient ID
Anonymized Prescriber ID
Anonymized Pharmacy ID
Patient Birth Year
Patient Gender...
De-Identified Data Normalization
With PDMPs in 49 states and all territories, it is important to normalize
PDMP de-identif...
Examples: CURES California County Data Shared with
State and County Departments of Public Health
• Opioid prescribing rate...
California Opioid Prescribing Rates per 1,000 Residents,
by County, 2013
Opioid prescriptions per 1,000 population
386.2 -...
California: Average Opioid Dosage per 1,000 Residents
in 2013, by County
Dosage in MMEs
306.2 - 599
599 - 745.9
745.9 - 12...
California: Percent of Opioid Patients Receiving > 100 MME
During a 30-Day Period in 2013, by County
Percent with > 100 MM...
California: Patients with Concurrent Opioid
and Benzodiazepine Prescriptions, Per 1,000 Residents, by County, 2013
Concurr...
California: Change in Opioid Prescribing Rates,
2010 to 2013, by County
Change in opioid prescribing rates
< -3 Std. Dev.
...
California: Change in Average Opioid Dosage Rate,
2010 to 2013, by County
Dosage change 2010 to 2013
< -3 Std. Dev.
-3 - -...
California: Change in Number of Waivered Physicians,
2010 to 2013, by County
Change in waivered physicians
-2 - -1 Std. De...
Observations
• Several northern counties with relatively small
population were highest in rates of risk indicators
(e.g., ...
Thank You!
PDMP Track: Linking and
Mapping PDMP Data
Chris Baumgartner, WA State Dept. of Health
Neal Traven, WA State Dept. of Health
Disclosure Statement
• Chris Baumgartner and Neal Traven have
disclosed no relevant, real or apparent
personal or professi...
Learning Objectives
1. Explain how state and county public health officials
use de-identified PDMP data to coordinate opio...
Unintentional Prescription Opioid Overdose Deaths
Washington 1995-2014
Source: Washington State Department of Health, Deat...
Unintentional Opioid Overdose Deaths Washington 1995-2014
Source: Washington State Department of Health, Death Certificates
WA State Unintentional Poisonings
Workgroup (UPWG)
• Began quarterly meetings in June 2008
• Representatives from public &...
2016 Washington State Interagency
Opioid Working Plan
33
Goal 1: Prevent opioid misuse and abuse
• Improve prescribing pra...
Opioid Plan - Goal 4 Strategies
1. Improve PDMP functionality to document and
summarize patient and prescriber patterns to...
35
County Profiles Project
• Provide information – counts, rates, maps, analyses – to
Local Health Jurisdictions (LHJs), f...
36
Our Inspiration
Oregon PDMP County Reports
• Approximately 20 tables
o Age-group counts and rates
o Specific drugs or d...
37
Question:
• What kinds of information will be most valuable to Local Health
Jurisdictions in developing programs regard...
38
Seven county-level LHJs volunteered to
participate in shaping the profile reports
Department of Health convened
telecon...
LHJ Advisory Group counties
Clallam Snohomish
Grant
Spokane
Klickitat
Thurston
Clark
Table 3. Top 10 Controlled Substances by Number of County
Residents Receiving Such Medications
Table 5. Unique Recipient C...
So … where are we now on
the County Profiles project?
We ran into a few
problems and issues in the
PMP dataset
42
PMP Data Issues (I)
• Database size, Security
o Highly confidential information
 Analysis on non-networked computer
 ...
43
PMP Data Issues (II)
• Clustering and Linking to Individual Recipients
o Tradeoffs in Under- or Over- clustering
 Unde...
44
PMP Data Issues (III)
• Reference Databases
o DEA Numbers
 Available at no charge to State Agencies
 Real-time snapsh...
45
0
400
800
1,200
1,600
2,000
All Controlled
Substances
Opioids Benzodiazepines Stimulants Sedatives
Prescriptionsper1,00...
46
Prescriptions per 1,000 Population:
All Controlled Substances, 2014
 2,050-2,800
 1,800-2,050
 1,650-1,800
 1,450-1...
47
 1,330-1,700
 1,060-1,330
 925-1,060
 850-925
 400-850
Whatcom
Skagit
Clallam
San
Juan
Island
Jefferson
Grays
Harb...
48
 375-500
 340-375
 317-340
 265-317
 140-265
Whatcom
Skagit
Clallam
San
Juan
Island
Jefferson
Grays
Harbor
Snohomi...
49
 225-300
 198-225
 165-198
 150-165
 80-150
Whatcom
Skagit
Clallam
San
Juan
Island
Jefferson
Grays
Harbor
Snohomis...
50
 165-315
 145-165
 132-145
 119-132
 65-119
Whatcom
Skagit
Clallam
San
Juan
Island
Jefferson
Grays
Harbor
Snohomis...
51
Drug Name
N of
Tablets/Capsules
Prescriptions per
1,000 State Residents
Hydrocodone 2,690,470 386
Oxycodone 1,779,532 2...
52
Clallam Clark Garfield Snohomish
Hydrocodone 472 Hydrocodone 386 Hydrocodone 903 Hydrocodone 392
Oxycodone 449 Oxycodon...
Since we started the County Profiles project…
• Greatly increased attention has been paid to opioids –
nationally, statewi...
And as we look ahead…
• We believe we are close to resolving the pitfalls and problems
we have encountered
• Documentation...
Contacts
Chris Baumgartner, PMP Director
chris.baumgartner@doh.wa.gov
Neal Traven, PMP Epidemiologist
neal.traven@doh.wa.g...
PDMPs as Prevention Tools
Presenters:
• Tina Farales, Department of Justice Administrator, Prescription Drug
Monitoring Pr...
Upcoming SlideShare
Loading in …5
×

Rx16 pdmp tues_1230_1_small_2kreiner_3baumgartner_4traven

612 views

Published on

PDMPs as Prevention Tools

Published in: Health & Medicine
  • Be the first to comment

  • Be the first to like this

Rx16 pdmp tues_1230_1_small_2kreiner_3baumgartner_4traven

  1. 1. PDMPs as Prevention Tools Presenters: • Tina Farales, Department of Justice Administrator, Prescription Drug Monitoring Program, California Department of Justice • Peter Kreiner, PhD, Senior Scientist, Brandeis University • Chris Baumgartner, Drug Systems Director, Washington State Department of Health • Neal D. Traven, PhD, Epidemiologist, Prescription Monitoring Program, Washington State Department of Health PDMP Track Moderator: John L. Eadie, Coordinator, Public Health and Prescription Drug Monitoring Program Project, National Emerging Threat Initiative, National HIDTA Assistance Center, and Member, Rx and Heroin Summit National Advisory Board
  2. 2. Disclosures Chris Baumgartner; Tina Farales; Peter Kreiner, PhD; Neal D. Traven, PhD; and John L. Eadie have disclosed no relevant, real, or apparent personal or professional financial relationships with proprietary entities that produce healthcare goods and services.
  3. 3. Disclosures • All planners/managers hereby state that they or their spouse/life partner do not have any financial relationships or relationships to products or devices with any commercial interest related to the content of this activity of any amount during the past 12 months. • The following planners/managers have the following to disclose: – John J. Dreyzehner, MD, MPH, FACOEM – Ownership interest: Starfish Health (spouse) – Robert DuPont – Employment: Bensinger, DuPont & Associates-Prescription Drug Research Center
  4. 4. Learning Objectives 1. Explain how state and county public health officials use de-identified PDMP data to coordinate opioid abuse prevention and mitigation efforts. 2. Identify challenges of using PDMP data for public health purposes. 3. Describe the Washington State model for providing PDMP data to local jurisdictions to inform their resource allocation and policy decisions. 4. Provide accurate and appropriate counsel as part of the treatment team.
  5. 5. De-Duplicated/De-Identified Data PDMPs as Prevention Tools
  6. 6. Mike Small has disclosed no relevant, real or apparent personal or professional financial relationships with proprietary entities that produce health care goods and services. Peter Kreiner has disclosed no relevant, real or apparent personal or professional financial relationships with proprietary entities that produce health care goods and services.
  7. 7. PDMPs as Prevention Tools De-Duplicated/De-Identified Data Learning Objectives: Identify challenges of using PDMP data for public health purposes Explain how state and county public health officers use de-identified PDMP data to coordinate opioid abuse prevention and mitigation efforts.
  8. 8. California Health and Safety Code section § 11165. (a) To assist health care practitioners in their efforts to ensure appropriate prescribing, ordering, administering, furnishing, and dispensing of controlled substances, law enforcement and regulatory agencies in their efforts to control the diversion and resultant abuse of Schedule II, Schedule III, and Schedule IV controlled substances, and for statistical analysis, education, and research, the Department of Justice shall . . . maintain the Controlled Substance Utilization Review and Evaluation System (CURES)…
  9. 9. The prescription drug epidemic is predominantly a public health Problem. Public Health program design, implementation and success measurement is typically data and research driven. PDMP data can and should assist the public health sector with the means to devise data driven mitigation strategies and the ability to measure the success of those efforts. Support the Public Health Sector
  10. 10. The clinical community requires a much more informative data Presentation than CURES 1.0’s simple provisioning of a basic 12-month PAR. Today’s technology can provide a better “eye” on prescribers’ patients; and is capable of providing both proactive and reactive reporting of patient prescription activity. Technology is also capable of denoting treatment exclusivity compacts, and providing prescribers an ability to communicate securely across health care plans. Enhance Informational Delivery
  11. 11. The Public Can and Should Know The PDMPs store the most informative data regarding the current public health crisis. The public debate should not be deprived of the vast, telling data housed by the PDMP. Analytics An analytics engine, however expensive, is essential for the delivery of optimal PDMP information.
  12. 12. De-Duplication PDMP patient data lacks positive identifiers. Name: Mike Small, Michael Small, Michael J. Small, Mikey Small, Mike Smalls DOB: 06/19/1953, 06/19/1935, 06/19/1963 Address: 2101 Columbus Avenue, Sacramento, CA 95814 2101 Columbus Street, Sacramento, CA 95814 1201 Columbus Boulevard, San Diego, CA 95828
  13. 13. De-Duplication Name and DOB and Zip(5) OR Name and Street Address and City Mike Small Michael J. Small 04/19/1963 04/19/1963 2101 Columbus Ave 2100 Columbia Way Sacramento, CA 95814 Sacramento, CA 95814 Mikey Small 04/19/1963 1201 Columbus Boulevard San Diego, CA 92111 Michael Small Mike Smalls 04/19/1936 04/19/1963 2101 Columbus Avenue 2101 Columbus Ave. Sacramento, CA 95814 Sacramento, CA 95814 One Mike Small Entity
  14. 14. De-Duplication Every day approximately 145K new Rx records are added to the CURES 2.0 data base. With this new data, the analytics engine must re-resolve patient, prescriber and dispenser entities across the 1TB database every night in order to produce daily CURES 2.0 Patient safety messaging alerts. The de-duplicated data also contributes to the quarterly and annual systematic production of a statewide and 58 county de-identified data sets for use by public health officers and researchers.
  15. 15. De-Identified Data Anonymized Patient ID Anonymized Prescriber ID Anonymized Pharmacy ID Patient Birth Year Patient Gender Patient Zip Code Patient County Patient State Prescriber Zip Code Prescriber County Prescriber State Pharmacy Zip Code Pharmacy County Pharmacy State Product Name NDC Drug Form Strength Quantity Days Supply Date Filled Refill Number Payment Code Prescriber Specialty Prescriber Board Certification Indicator • Personally identifying information redacted. • Anonymized patient IDs maintained to be consistent from report to report. • Generated quarterly and annually for each county and the entire state.
  16. 16. De-Identified Data Normalization With PDMPs in 49 states and all territories, it is important to normalize PDMP de-identified data sets for national level research and analysis.
  17. 17. Examples: CURES California County Data Shared with State and County Departments of Public Health • Opioid prescribing rates (minus buprenorphine formulations thought to be associated with MAT) • Average opioid dosage/Percent of residents with high (> 100 MME) average daily dosage • Concurrent opioid and benzodiazepine prescriptions • Change in opioid prescribing rates, 2010 – 2013 • Change in average opioid dosage, 2010 – 2013 • Change in number of waivered physicians, 2010 - 2013
  18. 18. California Opioid Prescribing Rates per 1,000 Residents, by County, 2013 Opioid prescriptions per 1,000 population 386.2 - 568.7 568.7 - 678.3 678.3 - 961.4 961.4 - 1163.8 1163.8 - 1767.1
  19. 19. California: Average Opioid Dosage per 1,000 Residents in 2013, by County Dosage in MMEs 306.2 - 599 599 - 745.9 745.9 - 1201.4 1201.4 - 1721.9 1721.9 - 2732.7 Resident
  20. 20. California: Percent of Opioid Patients Receiving > 100 MME During a 30-Day Period in 2013, by County Percent with > 100 MME 3.7 - 8.1 8.1 - 9.8 9.8 - 15.2 15.2 - 23.2 23.2 - 41.1 Residents per 1,000 Number of Residents per 1,000 For at Least 30 Days During 2013, by County
  21. 21. California: Patients with Concurrent Opioid and Benzodiazepine Prescriptions, Per 1,000 Residents, by County, 2013 Concurrent prescription rate per 1,000 3.5 - 8 8 - 11.7 11.7 - 16.6 16.6 - 25 25 - 41 Residents per 1,000 with Both by County, 2013
  22. 22. California: Change in Opioid Prescribing Rates, 2010 to 2013, by County Change in opioid prescribing rates < -3 Std. Dev. -3 - -2 Std. Dev. -2 - -1 Std. Dev. -1 - 0 Std. Dev. Mean 0 - 1 Std. Dev. 1 - 2 Std. Dev.
  23. 23. California: Change in Average Opioid Dosage Rate, 2010 to 2013, by County Dosage change 2010 to 2013 < -3 Std. Dev. -3 - -2 Std. Dev. -2 - -1 Std. Dev. -1 - 0 Std. Dev. Mean 0 - 1 Std. Dev. 1 - 2 Std. Dev. 2 - 3 Std. Dev.
  24. 24. California: Change in Number of Waivered Physicians, 2010 to 2013, by County Change in waivered physicians -2 - -1 Std. Dev. -1 - 0 Std. Dev. Mean 0 - 1 Std. Dev. 1 - 2 Std. Dev. 2 - 3 Std. Dev.
  25. 25. Observations • Several northern counties with relatively small population were highest in rates of risk indicators (e.g., Del Norte, Lassen, Plumas, Tehama, Trinity), suggesting need for treatment and prevention • Two of these (Plumas and Trinity) also had high percent increases in average MMEs per resident, 2010 – 2013, and low percent increases in number of physicians waivered to prescribe buprenorphine for medically-assisted treatment over the same period
  26. 26. Thank You!
  27. 27. PDMP Track: Linking and Mapping PDMP Data Chris Baumgartner, WA State Dept. of Health Neal Traven, WA State Dept. of Health
  28. 28. Disclosure Statement • Chris Baumgartner and Neal Traven have disclosed no relevant, real or apparent personal or professional financial relationships with proprietary entities that produce health care goods and services.
  29. 29. Learning Objectives 1. Explain how state and county public health officials use de-identified PDMP data to coordinate opioid abuse prevention and mitigation efforts. 2. Identify challenges of using PDMP data for public health purposes. 3. Describe the Washington State model for providing PDMP data to local jurisdictions to inform their resource allocation and policy decisions. 4. Provide accurate and appropriate counsel as part of the treatment team.
  30. 30. Unintentional Prescription Opioid Overdose Deaths Washington 1995-2014 Source: Washington State Department of Health, Death Certificates
  31. 31. Unintentional Opioid Overdose Deaths Washington 1995-2014 Source: Washington State Department of Health, Death Certificates
  32. 32. WA State Unintentional Poisonings Workgroup (UPWG) • Began quarterly meetings in June 2008 • Representatives from public & private organizations: • State/local health agencies, tribal authorities, insurers, law enforcement, substance abuse prevention/treatment, poison control, health professional associations, academic institutions, etc… • Developed short-term actions • Increase provider and public education • Identify methods to reduce diversion through emergency departments • Increase surveillance • Support evaluation of practice guidelines for providers treating chronic, non-cancer pain • Support prescription monitoring program
  33. 33. 2016 Washington State Interagency Opioid Working Plan 33 Goal 1: Prevent opioid misuse and abuse • Improve prescribing practices Goal 2: Treat opioid dependence • Expand access to treatment Goal 3: Prevent deaths from overdose • Distribute naloxone to people who use heroin Goal 4: Use data to monitor and evaluate • Optimize and expand data sources
  34. 34. Opioid Plan - Goal 4 Strategies 1. Improve PDMP functionality to document and summarize patient and prescriber patterns to inform clinical decision making 2. Utilize the PDMP for public health surveillance and evaluation 3. Continue and enhance efforts to monitor opioid use and opioid-related morbidity and mortality 4. Monitor progress towards goals and strategies and evaluate the effectiveness of our interventions
  35. 35. 35 County Profiles Project • Provide information – counts, rates, maps, analyses – to Local Health Jurisdictions (LHJs), for use in building their programmatic solutions • Time trends in prescription drug use o Which drugs are commonly prescribed? o How frequently are they used? o In combination with other Controlled Substances? • Geographic patterns of drug use o Apply online mapping tools o “Overdose and At-Risk Behaviors” o Identify “treatment deserts”
  36. 36. 36 Our Inspiration Oregon PDMP County Reports • Approximately 20 tables o Age-group counts and rates o Specific drugs or drug classes • Little analysis o No comparisons between counties o No time trends o No graphics or maps o Brief, generic discussion • One-time effort? o County reports not published for 2013, 2014, 2015 Using this as our takeoff point…
  37. 37. 37 Question: • What kinds of information will be most valuable to Local Health Jurisdictions in developing programs regarding Controlled Substances? Answer: • We aren’t really sure, so let’s ask them! Action: • Invited all LHJs to join Advisory Workgroup, to collaborate with the PMP in designing a report framework that will contain the most useful information. LHJ Advisory Workgroup (I)
  38. 38. 38 Seven county-level LHJs volunteered to participate in shaping the profile reports Department of Health convened teleconferences, which discussed: • Cross-referencing LHJ wishlists to available PMP data fields • Useful counts, groupings, summaries selected • Decision to adjust, where appropriate, by age group and gender LHJ Advisory Workgroup (II)
  39. 39. LHJ Advisory Group counties Clallam Snohomish Grant Spokane Klickitat Thurston Clark
  40. 40. Table 3. Top 10 Controlled Substances by Number of County Residents Receiving Such Medications Table 5. Unique Recipient Count and Usage Rate for Most Common Opioid, by Age-Sex Group Table 13. Unique Recipient Count and Usage Rate for All Benzodiazepines and for Most Common Benzodiazepine, by Source of Payment Table 19. Unique Recipient Count and Usage Rate for Opioid and Benzodiazepine Combination, by Age-Sex Group Figure 3. Time Trends in the Proportion of Patients Exhibiting At-risk Behavior Among Opioid Users, in County and Statewide Proposed Profile Content: Examples
  41. 41. So … where are we now on the County Profiles project? We ran into a few problems and issues in the PMP dataset
  42. 42. 42 PMP Data Issues (I) • Database size, Security o Highly confidential information  Analysis on non-networked computer  Encryption with BitLocker o 45.0 million prescription records as of 07/20/2015  Add almost 1 million records per month o Processing power  Dedicated SQL server  Analytic workstation with lots of RAM • Fully-identified Data o Prescribers (>130K), Dispensers (~3,300) – DEA #, Address o Recipients (>5.2M, or is it really 4.1M??) – Name, Address, DOB o Create alternate identifiers for use by external researchers  Maintain crosswalks between full and alternate identifiers
  43. 43. 43 PMP Data Issues (II) • Clustering and Linking to Individual Recipients o Tradeoffs in Under- or Over- clustering  Under- = Overestimate Number of Recipients  Over- = Overestimate Number of High-Risk Recipients o Improve accuracy of clustering  Machine learning  Better clustering algorithms • Data cleaning and editing o Non-human recipients (Species Code?) o Malformed or unknown identifiers (DEA, NDC, Zip Code) o Data entry and/or upload errors  Really? 11.9 billion doses of tramadol?  Correct street, city, Zip, county … but state code is blank  State code defaults to WA, so we see things like: Atlanta, 30318, Fulton, WA Louisville, 40206, Jefferson, WA
  44. 44. 44 PMP Data Issues (III) • Reference Databases o DEA Numbers  Available at no charge to State Agencies  Real-time snapshot, possibly retrospective views o NDC Codes  Obtain from FDA’s database, very frequently updated  Linking Packaging and Product tables  Morphine Equivalent Dose reference o NPI  Prescriber specialty o Zip Code  Frequent redrawing, addition of new ones  Use 3-digit to identity state  What to do about non-existent Zip codes?
  45. 45. 45 0 400 800 1,200 1,600 2,000 All Controlled Substances Opioids Benzodiazepines Stimulants Sedatives Prescriptionsper1,000Residents CY 2012 CY 2013 CY 2014 Prescriptions per 1,000 Residents, 2012-2014 Washington State, by Class of Controlled Substance
  46. 46. 46 Prescriptions per 1,000 Population: All Controlled Substances, 2014  2,050-2,800  1,800-2,050  1,650-1,800  1,450-1,650  700-1,450 Whatcom Skagit Clallam San Juan Island Jefferson Grays Harbor Snohomish Mason King Kitsap Pierce Thurston Pacific Lewis Wahkiakum Cowlitz Clark Skamania Douglas Chelan Whitman Okanogan Walla Walla Asotin Spokane Pend OreilleFerry Stevens Kittitas Yakima Grant Klickitat Lincoln Adams Benton Garfield Columbia Franklin
  47. 47. 47  1,330-1,700  1,060-1,330  925-1,060  850-925  400-850 Whatcom Skagit Clallam San Juan Island Jefferson Grays Harbor Snohomish Mason King Kitsap Pierce Thurston Pacific Lewis Wahkiakum Cowlitz Clark Skamania Douglas Chelan Whitman Okanogan Walla Walla Asotin Spokane Pend OreilleFerry Stevens Kittitas Yakima Grant Klickitat Lincoln Adams Benton Garfield Columbia Franklin Prescriptions per 1,000 Population: Pain Relievers (Opioids), 2014
  48. 48. 48  375-500  340-375  317-340  265-317  140-265 Whatcom Skagit Clallam San Juan Island Jefferson Grays Harbor Snohomish Mason King Kitsap Pierce Thurston Pacific Lewis Wahkiakum Cowlitz Clark Skamania Douglas Chelan Whitman Okanogan Walla Walla Asotin Spokane Pend OreilleFerry Stevens Kittitas Yakima Grant Klickitat Lincoln Adams Benton Garfield Columbia Franklin Prescriptions per 1,000 Population: Tranquilizers (Benzodiazepines), 2014
  49. 49. 49  225-300  198-225  165-198  150-165  80-150 Whatcom Skagit Clallam San Juan Island Jefferson Grays Harbor Snohomish Mason King Kitsap Pierce Thurston Pacific Lewis Wahkiakum Cowlitz Clark Skamania Douglas Chelan Whitman Okanogan Walla Walla Asotin Spokane Pend OreilleFerry Stevens Kittitas Yakima Grant Klickitat Lincoln Adams Benton Garfield Columbia Franklin Prescriptions per 1,000 Population: Stimulants, 2014
  50. 50. 50  165-315  145-165  132-145  119-132  65-119 Whatcom Skagit Clallam San Juan Island Jefferson Grays Harbor Snohomish Mason King Kitsap Pierce Thurston Pacific Lewis Wahkiakum Cowlitz Clark Skamania Douglas Chelan Whitman Okanogan Walla Walla Asotin Spokane Pend OreilleFerry Stevens Kittitas Yakima Grant Klickitat Lincoln Adams Benton Garfield Columbia Franklin Prescriptions per 1,000 Population: Sedatives, 2014
  51. 51. 51 Drug Name N of Tablets/Capsules Prescriptions per 1,000 State Residents Hydrocodone 2,690,470 386 Oxycodone 1,779,532 255 Zolpidem 737,864 106 Alprazolam 600,700 86 Lorazepam 587,326 84 Dextroamphetamine/Amphetamine 547,771 79 Clonazepam 494,936 71 Codeine 458,487 66 Methylphenidate 440,009 63 Morphine 312,270 45 Ten Most Frequently Prescribed Drugs, 2014: Statewide, Tablets and Capsules only Population estimate = 6,968,170 WA Office of Financial Management, Population Unit
  52. 52. 52 Clallam Clark Garfield Snohomish Hydrocodone 472 Hydrocodone 386 Hydrocodone 903 Hydrocodone 392 Oxycodone 449 Oxycodone 258 Morphine 191 Oxycodone 329 Codeine 74 Codeine 64 Oxycodone 189 Codeine 67 Methadone 74 Morphine 56 Codeine 113 Morphine 50 Morphine 67 Tramadol 31 Tramadol 84 Buprenorphine 41 Five Most Frequently Prescribed Opioids, 2014: Selected Counties, Prescriptions per 1,000 Population Population estimates: Clallam 72,500 Clark 442,800 Garfield 2,240 Snohomish 741,000 WA Office of Financial Management, Population Unit
  53. 53. Since we started the County Profiles project… • Greatly increased attention has been paid to opioids – nationally, statewide, and locally o Frequent reports in newspapers, TV news o Locally produced documentaries o Frontline on PBS, reported from King and Kitsap Counties • Developing the state’s Interagency Opioid Working Plan o PMP database now seen as a vital data source for public health efforts at surveillance, monitoring, and evaluation o As part of the Working Plan, the County Profiles project will provide information on trends in opioid prescribing and use o Dissemination of PMP reports, including the Profiles project, beyond Local Health Jurisdictions
  54. 54. And as we look ahead… • We believe we are close to resolving the pitfalls and problems we have encountered • Documentation is being written so that the scripts and programs that emerged from our deep dive into the PMP data will be maintained and, when necessary, updated • Going back to the raw datasets obtained from our vendor, we will build “clean” data files that will be placed on our secure SQL server • The one-time code written thus far will be converted to scripts and macros so as to “automate” production of reports and analyses • GIS views of the PMP data and other layers will continue to be developed and studied • And maybe we’ll finally be able to catch our breath!
  55. 55. Contacts Chris Baumgartner, PMP Director chris.baumgartner@doh.wa.gov Neal Traven, PMP Epidemiologist neal.traven@doh.wa.gov 55
  56. 56. PDMPs as Prevention Tools Presenters: • Tina Farales, Department of Justice Administrator, Prescription Drug Monitoring Program, California Department of Justice • Peter Kreiner, PhD, Senior Scientist, Brandeis University • Chris Baumgartner, Drug Systems Director, Washington State Department of Health • Neal D. Traven, PhD, Epidemiologist, Prescription Monitoring Program, Washington State Department of Health PDMP Track Moderator: John L. Eadie, Coordinator, Public Health and Prescription Drug Monitoring Program Project, National Emerging Threat Initiative, National HIDTA Assistance Center, and Member, Rx and Heroin Summit National Advisory Board

×