This document summarizes a presentation on using prescription drug monitoring program (PDMP) data for public health purposes. State and local health officials in Washington State work with de-identified PDMP data to coordinate opioid abuse prevention and mitigation efforts. Examples are given of data reports generated for counties, including opioid prescribing rates, concurrent opioid and benzodiazepine prescriptions, and changes over time. Challenges with PDMP data are discussed, such as de-duplicating patient records and processing large datasets. The goal is to provide actionable information to local jurisdictions to inform resource allocation and policies.
Dr. Tom Frieden, Director of the Centers for Disease Control and Prevention, keynote presentation at the National Rx Drug Abuse & Heroin Summit on March 30, 2016.
Dr. Tom Frieden, Director of the Centers for Disease Control and Prevention, keynote presentation at the National Rx Drug Abuse & Heroin Summit on March 30, 2016.
PDMP: Prescription Behavior Surveillance System - The Value and Applications of De-identified PDMP Data in Public Health Surveillance - Dr. Peter Kreiner and Mike Small
March 02, 2018
Value-based health care is one of the most pressing topics in health care finance and policy today. Value-based payment structures are widely touted as critical to controlling runaway health care costs, but are often difficult for health care entities to incorporate into their existing infrastructures. Because value-based health care initiatives have bipartisan support, it is likely that these programs will continue to play a major role in both the public and private health insurance systems. As such, there is a pressing need to evaluate the implementation of these initiatives thus far and to discuss the direction that American health care financing will take in the coming years.
To explore this important issue, the Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School collaborated with Ropes & Gray LLP to host a one-day conference on value-based health care. This event brought together scholars, health law practitioners, and health care entities to evaluate the impact of value-based health care on the American health care system.
For more information, visit our website at: http://petrieflom.law.harvard.edu/events/details/will-value-based-care-save-the-health-care-system
Community Needs Assessment Marion County Marion County FLynellBull52
Community Needs Assessment
Marion County
Marion County Florida
Located in Central Florida with a population of 343, 778.
Marion county is in central Florida.
2
Social Determinants
Factors included in this category, generational poverty, widespread homelessness, persistent issue of overweight and obesity, lack of affordable housing, shortage of healthcare and dental care providers, water fluoridation is lacking in most communities, struggling and failing schools, and built environment impedes access to recreation areas and safe places for physical activity.
Addressing social determinants of health is important for improving health and reducing health disparities.
3
Marion County Most Utilized Hospitals
Hospital NameNumber of DischargesFlorida Hospital Ocala15,739Ocala Regional Medical Center8,940West Marion Community6,532
Medical Resources Available
Clinical and nutrition services
Wellness programs
Environmental health
Infectious Disease services
Clinical and nutrition services include - Supplements for women and children, immunizations throughout various locations within the county, dental services, family planning, and centers which treat sexually transmitted diseases.
Wellness programs which include – disease prevention and management such as diabetes. Weight programs, children healthy promotional programs, and health education.
Environmental health which includes - Environmental Health programs are essential to public health. They work to achieve a safe and healthy environment for the community. Environmental Health staff monitor conditions that could present a threat to health and safety of the public.
Infectious Disease services which involves, The Florida Department of Health in Marion County is responsible for the surveillance of reportable communicable diseases, including enteric diseases, vaccine-preventable diseases, invasive bacterial diseases, arthropod-borne diseases, and others. Infectious disease control programs are designed to protect the residents and visitors of Marion County
5
Community Needs Assessment
Marion County community needs include, access to primary prevention and healthcare, oral health, mental and behavioral health, education and training.
Primary prevention efforts are focused on preventing illness and injury before it happens. Prevention includes environmental and policy change as well as education, behavior revision and lasting investments in systems that encourage healthy living.
Oral health influences physical, emotional, and social well-being. Poor oral health causes pain and disability. With pain and disability hinders work and school which causes issues with attendance and performance. Oral issues will in turn costs residents, taxpayers and healthcare systems millions of dollars to treat.
Mental and physical health are equally important factors for overall health and quality of life. Mental and behavior health includes emotional, psychological and social we ...
Oncology Big Data: A Mirage or Oasis of Clinical Value? Michael Peters
The title of the presentation, Oncology Big Data: A Mirage or Oasis of Clinical Value, reflects what I believe the field of Oncology is challenged with on a growing basis, from a clinical and business side perspective.
Kana Enomoto, Acting Administrator, Substance Abuse and Mental Health Services Administration, keynote presentation at the National Rx Drug Abuse & Heroin Summit March 29, 2016
ARTIFICIAL INTELLIGENCE IN HEALTHCARE.pdfAnujkumaranit
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. It encompasses tasks such as learning, reasoning, problem-solving, perception, and language understanding. AI technologies are revolutionizing various fields, from healthcare to finance, by enabling machines to perform tasks that typically require human intelligence.
Ethanol (CH3CH2OH), or beverage alcohol, is a two-carbon alcohol
that is rapidly distributed in the body and brain. Ethanol alters many
neurochemical systems and has rewarding and addictive properties. It
is the oldest recreational drug and likely contributes to more morbidity,
mortality, and public health costs than all illicit drugs combined. The
5th edition of the Diagnostic and Statistical Manual of Mental Disorders
(DSM-5) integrates alcohol abuse and alcohol dependence into a single
disorder called alcohol use disorder (AUD), with mild, moderate,
and severe subclassifications (American Psychiatric Association, 2013).
In the DSM-5, all types of substance abuse and dependence have been
combined into a single substance use disorder (SUD) on a continuum
from mild to severe. A diagnosis of AUD requires that at least two of
the 11 DSM-5 behaviors be present within a 12-month period (mild
AUD: 2–3 criteria; moderate AUD: 4–5 criteria; severe AUD: 6–11 criteria).
The four main behavioral effects of AUD are impaired control over
drinking, negative social consequences, risky use, and altered physiological
effects (tolerance, withdrawal). This chapter presents an overview
of the prevalence and harmful consequences of AUD in the U.S.,
the systemic nature of the disease, neurocircuitry and stages of AUD,
comorbidities, fetal alcohol spectrum disorders, genetic risk factors, and
pharmacotherapies for AUD.
Anti ulcer drugs and their Advance pharmacology ||
Anti-ulcer drugs are medications used to prevent and treat ulcers in the stomach and upper part of the small intestine (duodenal ulcers). These ulcers are often caused by an imbalance between stomach acid and the mucosal lining, which protects the stomach lining.
||Scope: Overview of various classes of anti-ulcer drugs, their mechanisms of action, indications, side effects, and clinical considerations.
Title: Sense of Smell
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the primary categories of smells and the concept of odor blindness.
Explain the structure and location of the olfactory membrane and mucosa, including the types and roles of cells involved in olfaction.
Describe the pathway and mechanisms of olfactory signal transmission from the olfactory receptors to the brain.
Illustrate the biochemical cascade triggered by odorant binding to olfactory receptors, including the role of G-proteins and second messengers in generating an action potential.
Identify different types of olfactory disorders such as anosmia, hyposmia, hyperosmia, and dysosmia, including their potential causes.
Key Topics:
Olfactory Genes:
3% of the human genome accounts for olfactory genes.
400 genes for odorant receptors.
Olfactory Membrane:
Located in the superior part of the nasal cavity.
Medially: Folds downward along the superior septum.
Laterally: Folds over the superior turbinate and upper surface of the middle turbinate.
Total surface area: 5-10 square centimeters.
Olfactory Mucosa:
Olfactory Cells: Bipolar nerve cells derived from the CNS (100 million), with 4-25 olfactory cilia per cell.
Sustentacular Cells: Produce mucus and maintain ionic and molecular environment.
Basal Cells: Replace worn-out olfactory cells with an average lifespan of 1-2 months.
Bowman’s Gland: Secretes mucus.
Stimulation of Olfactory Cells:
Odorant dissolves in mucus and attaches to receptors on olfactory cilia.
Involves a cascade effect through G-proteins and second messengers, leading to depolarization and action potential generation in the olfactory nerve.
Quality of a Good Odorant:
Small (3-20 Carbon atoms), volatile, water-soluble, and lipid-soluble.
Facilitated by odorant-binding proteins in mucus.
Membrane Potential and Action Potential:
Resting membrane potential: -55mV.
Action potential frequency in the olfactory nerve increases with odorant strength.
Adaptation Towards the Sense of Smell:
Rapid adaptation within the first second, with further slow adaptation.
Psychological adaptation greater than receptor adaptation, involving feedback inhibition from the central nervous system.
Primary Sensations of Smell:
Camphoraceous, Musky, Floral, Pepperminty, Ethereal, Pungent, Putrid.
Odor Detection Threshold:
Examples: Hydrogen sulfide (0.0005 ppm), Methyl-mercaptan (0.002 ppm).
Some toxic substances are odorless at lethal concentrations.
Characteristics of Smell:
Odor blindness for single substances due to lack of appropriate receptor protein.
Behavioral and emotional influences of smell.
Transmission of Olfactory Signals:
From olfactory cells to glomeruli in the olfactory bulb, involving lateral inhibition.
Primitive, less old, and new olfactory systems with different path
micro teaching on communication m.sc nursing.pdfAnurag Sharma
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
Explore natural remedies for syphilis treatment in Singapore. Discover alternative therapies, herbal remedies, and lifestyle changes that may complement conventional treatments. Learn about holistic approaches to managing syphilis symptoms and supporting overall health.
New Directions in Targeted Therapeutic Approaches for Older Adults With Mantl...i3 Health
i3 Health is pleased to make the speaker slides from this activity available for use as a non-accredited self-study or teaching resource.
This slide deck presented by Dr. Kami Maddocks, Professor-Clinical in the Division of Hematology and
Associate Division Director for Ambulatory Operations
The Ohio State University Comprehensive Cancer Center, will provide insight into new directions in targeted therapeutic approaches for older adults with mantle cell lymphoma.
STATEMENT OF NEED
Mantle cell lymphoma (MCL) is a rare, aggressive B-cell non-Hodgkin lymphoma (NHL) accounting for 5% to 7% of all lymphomas. Its prognosis ranges from indolent disease that does not require treatment for years to very aggressive disease, which is associated with poor survival (Silkenstedt et al, 2021). Typically, MCL is diagnosed at advanced stage and in older patients who cannot tolerate intensive therapy (NCCN, 2022). Although recent advances have slightly increased remission rates, recurrence and relapse remain very common, leading to a median overall survival between 3 and 6 years (LLS, 2021). Though there are several effective options, progress is still needed towards establishing an accepted frontline approach for MCL (Castellino et al, 2022). Treatment selection and management of MCL are complicated by the heterogeneity of prognosis, advanced age and comorbidities of patients, and lack of an established standard approach for treatment, making it vital that clinicians be familiar with the latest research and advances in this area. In this activity chaired by Michael Wang, MD, Professor in the Department of Lymphoma & Myeloma at MD Anderson Cancer Center, expert faculty will discuss prognostic factors informing treatment, the promising results of recent trials in new therapeutic approaches, and the implications of treatment resistance in therapeutic selection for MCL.
Target Audience
Hematology/oncology fellows, attending faculty, and other health care professionals involved in the treatment of patients with mantle cell lymphoma (MCL).
Learning Objectives
1.) Identify clinical and biological prognostic factors that can guide treatment decision making for older adults with MCL
2.) Evaluate emerging data on targeted therapeutic approaches for treatment-naive and relapsed/refractory MCL and their applicability to older adults
3.) Assess mechanisms of resistance to targeted therapies for MCL and their implications for treatment selection
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...kevinkariuki227
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
Title: Sense of Taste
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the structure and function of taste buds.
Describe the relationship between the taste threshold and taste index of common substances.
Explain the chemical basis and signal transduction of taste perception for each type of primary taste sensation.
Recognize different abnormalities of taste perception and their causes.
Key Topics:
Significance of Taste Sensation:
Differentiation between pleasant and harmful food
Influence on behavior
Selection of food based on metabolic needs
Receptors of Taste:
Taste buds on the tongue
Influence of sense of smell, texture of food, and pain stimulation (e.g., by pepper)
Primary and Secondary Taste Sensations:
Primary taste sensations: Sweet, Sour, Salty, Bitter, Umami
Chemical basis and signal transduction mechanisms for each taste
Taste Threshold and Index:
Taste threshold values for Sweet (sucrose), Salty (NaCl), Sour (HCl), and Bitter (Quinine)
Taste index relationship: Inversely proportional to taste threshold
Taste Blindness:
Inability to taste certain substances, particularly thiourea compounds
Example: Phenylthiocarbamide
Structure and Function of Taste Buds:
Composition: Epithelial cells, Sustentacular/Supporting cells, Taste cells, Basal cells
Features: Taste pores, Taste hairs/microvilli, and Taste nerve fibers
Location of Taste Buds:
Found in papillae of the tongue (Fungiform, Circumvallate, Foliate)
Also present on the palate, tonsillar pillars, epiglottis, and proximal esophagus
Mechanism of Taste Stimulation:
Interaction of taste substances with receptors on microvilli
Signal transduction pathways for Umami, Sweet, Bitter, Sour, and Salty tastes
Taste Sensitivity and Adaptation:
Decrease in sensitivity with age
Rapid adaptation of taste sensation
Role of Saliva in Taste:
Dissolution of tastants to reach receptors
Washing away the stimulus
Taste Preferences and Aversions:
Mechanisms behind taste preference and aversion
Influence of receptors and neural pathways
Impact of Sensory Nerve Damage:
Degeneration of taste buds if the sensory nerve fiber is cut
Abnormalities of Taste Detection:
Conditions: Ageusia, Hypogeusia, Dysgeusia (parageusia)
Causes: Nerve damage, neurological disorders, infections, poor oral hygiene, adverse drug effects, deficiencies, aging, tobacco use, altered neurotransmitter levels
Neurotransmitters and Taste Threshold:
Effects of serotonin (5-HT) and norepinephrine (NE) on taste sensitivity
Supertasters:
25% of the population with heightened sensitivity to taste, especially bitterness
Increased number of fungiform papillae
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists Saeid Safari
Preoperative Management of Patients on GLP-1 Receptor Agonists like Ozempic and Semiglutide
ASA GUIDELINE
NYSORA Guideline
2 Case Reports of Gastric Ultrasound
MANAGEMENT OF ATRIOVENTRICULAR CONDUCTION BLOCK.pdfJim Jacob Roy
Cardiac conduction defects can occur due to various causes.
Atrioventricular conduction blocks ( AV blocks ) are classified into 3 types.
This document describes the acute management of AV block.
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. 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. 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. 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.
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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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
27. PDMP Track: Linking and
Mapping PDMP Data
Chris Baumgartner, WA State Dept. of Health
Neal Traven, WA State Dept. of Health
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. 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. Unintentional Prescription Opioid Overdose Deaths
Washington 1995-2014
Source: Washington State Department of Health, Death Certificates
31. Unintentional Opioid Overdose Deaths Washington 1995-2014
Source: Washington State Department of Health, Death Certificates
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. 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. 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
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
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
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
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. LHJ Advisory Group counties
Clallam Snohomish
Grant
Spokane
Klickitat
Thurston
Clark
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. So … where are we now on
the County Profiles project?
We ran into a few
problems and issues in the
PMP dataset
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
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
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?
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
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
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
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
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
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
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. 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. 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. Contacts
Chris Baumgartner, PMP Director
chris.baumgartner@doh.wa.gov
Neal Traven, PMP Epidemiologist
neal.traven@doh.wa.gov
55
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
Editor's Notes
Correction: average opioid dosage in MMEs per resident in 2013.
Correction: Number of residents per 1,000 receiving > 100 MME daily for at least 30 days during 2013
Correction: Residents per 1,000 with both opioid and benzodiazepine prescriptions for at least 30 days
Change in MME per resident per year.
30
31
I wanted to begin this talk with a bit of history about how this work started. Back in 2008, the Washington State Department of Health began a quarterly workgroup in June 2008 focused on preventing prescription, misuse, abuse and overdose. The purpose of the group was to coordinate the prevention activities already underway, set up a forum for continuing communication, and to come up with short term actions that we could work on together.
I’ve included examples of who is represented on the workgroup. It is relevant to this discussion to point out that there were several emergency department physicians who attended these meetings.
During the first few meetings we developed a charter, which outlines the short term actions.
County 2014 populations, notes:
Clallam (72 K) – Olympic Peninsula, rural, mountainous, Forks
Clark (440 K) – across from Portland, urban, America’s Vancouver
Grant (93 K) – rural, agricultural, Grand Coulee
Klickitat (21 K) – rural, many residents shop in Oregon
Snohomish (740 K) – urban/suburban
Spokane (485 K) – WA’s 2nd largest city
Thurston (264 K) – Olympia
Point out that we’ve combined names as displayed in the database. We believe that it doesn’t matter whether it comes with acetaminophen, ibuprofen, or aspirin – we’re interested only in the hydrocodone.