Policy & Priorities: Rethinking University Research with State - - PowerPoint PPT Presentation

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Policy & Priorities: Rethinking University Research with State - - PowerPoint PPT Presentation

May 13, 2023 206 likes •584 views

Policy & Priorities: Rethinking University Research with State Data Grand Rounds: NIH HCS Collaboratory and PCORnet | 6/29/18 Aaron McKethan, PhD | @a_mckethan Chief Data Officer, NC Department of HHS | aaron.mckethan@dhhs.nc.gov Assistant

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Policy & Priorities: Rethinking University Research with State Data

Grand Rounds: NIH HCS Collaboratory and PCORnet | 6/29/18 Aaron McKethan, PhD | @a_mckethan Chief Data Officer, NC Department of HHS | aaron.mckethan@dhhs.nc.gov Assistant Professor of Population Health Sciences, Duke School of Medicine Senior Policy Fellow, Duke-Margolis Center for Health Policy | aaron.mckethan@duke.edu

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Three-part punchline

  • 1. States need help developing analytic priorities
  • 2. Start with the simplest available research methods
  • 3. Consider policy implications from the beginning

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Analytic priorities

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Analytic priorities

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Analytic priorities

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“How many OB- GYNs billed at least one claim in Harnett County in 2017?”

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Analytic priorities

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“How many OB- GYNs billed at least one claim in Harnett County in 2017?” “What was the fiscal impact of shifting to Medicaid managed care?”

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Analytic priorities

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“How many OB- GYNs billed at least one claim in Harnett County in 2017?” “What was the fiscal impact of shifting to Medicaid managed care?” The opportunity space for policy-oriented health services researchers

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Analytic priorities

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Analytic priorities

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  • 1. What do we already know?
  • …and where is policy not aligned with available evidence?
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Analytic priorities

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  • 1. What do we already know?
  • …and where is policy not aligned with available evidence?
  • 2. What do we not know?
  • …and how valuable would it be to know?
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Analytic priorities

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  • 1. What do we already know?
  • …and where is policy not aligned with available evidence?
  • 2. What do we not know?
  • …and how valuable would it be to know?
  • 3. What are the highest-priority questions?
  • …that can be answered with available data?
  • …that can inform specific policy actions in the near term?
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Example: Prescription Opioids

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https://files.nc.gov/ncdhhs/documents/NC%20Opioid%20Action%20Plan%20Metrics_April%202018%20V2.pdf

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0% 1% 2% 3% 4% 5% 6% 7% 8% 200,000 400,000 600,000 800,000 1,000,000 1,200,000

2013 2014 2015 2016 2017

Number of opioid prescription claims and percentage of all Medicaid prescription claims that are opioids Number of claims Percentage of all prescription claims

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55.6 53.6 53.7 51.6 48.6 16.3 16.5 16.8 17.4 17.1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 44 46 48 50 52 54 56 58 2013 2014 2015 2016 2017

Average morphine milligram equivalents (MME) per day and average days's supply per prescription Average Morphine Milligram Equivalent (MME) per day Average days' supply per prescription Days MME

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10 20 30 40 50 60 70 80 90 100

Average MME/day per prescription in 2017 by county, with state average comparison 100 counties MME

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smallest population largest population

4,000+ 1,000,000+

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Measure specification is from Pharmacy Quality Alliance: “Concurrent Use of Opioids and Benzodiazepines”

0% 5% 10% 15% 20% 25% 30% 5 10 15 20 25 30

2013 2014 2015 2016 2017

Thousands Number and percentage of Medicaid beneficiaries 18 to 64 years old with concurrent use of prescription opioids and benzodiazepines, 2013-2017 Number of beneficiaries Percentage of beneficiaries

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DRAFT

Measure specification is from Pharmacy Quality Alliance: “Concurrent Use of Opioids and Benzodiazepines”

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Gaston Robeson Rockingham Scotland Cumberland Durham Mecklenburg Wake 100 200 300 400 500 600 500 1000 1500 2000 2500 3000 3500

Those in Denominator with 30+ Days Overlapping Benzodiazepine Rxs Beneficiaries 18-64 Who Received 2+ Opioid Prescriptions for a Total of 15+ Days

County variation in rate of concurrent opioids and benzodiazepines, 2017

Rural Urban

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Measure specification for denominator is from Pharmacy Quality Alliance: “Concurrent Use of Opioids and Benzodiazepines”

0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 200 400 600 800 1,000 1,200 1,400

2013 2014 2015 2016 2017

Number and percentage of concurrent opioid and benzodiazepine users 18-64 with a fill of naloxone in the previous 24 months, 2013-2017

Number of beneficiaries Percentage of beneficiaries

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NC Opioid Symposium: Developing an Analytic Agenda

  • What are the most important ‘known unknowns’?
  • >70 experts (including government officials)
  • Medicaid claims and controlled substances data

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What else do we not know re: opioid prescribing and use?

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McKethan A., Powell E., Patel A., Daniels C., Campbell H., Marshall S., & Proescholdbell S.

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NC Opioid Symposium - Examples

  • “Does proactively informing prescribers on where they fall on opioid

prescribing metrics change prescribing behavior?”

  • “What has the effect of the STOP Act been on prescribing behaviors,
  • pioid action plan metrics, and other outcomes?”
  • “Is geographic clustering of harm reduction strategies associated with

reduced negative outcomes?”

  • “What is the current rate of referral from the hospital (E.D., inpatient)

to treatment?”

  • “What are the predictors of success in treatment in OBOTs? What are

the best metrics to define treatment success (retention, relapse, etc.)?”

  • “What is the best set of outcomes and metrics that can be used across

treatment studies?”

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And 100+ more

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DHHS Data Lab

  • Data sharing and research agreements with:

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State-University Partnership Learning Network (SUPLN) Multi-State Medicaid OUD Project

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Principal Investigator: Julie Donohue, PhD (Pitt) Selected Draft Measures

  • Initiation and engagement of alcohol and other drug dependence treatment
  • Continuity of pharmacotherapy for opioid use disorder
  • Follow-up after Emergency Department visit for alcohol and other drug

abuse or dependence States

  • Kentucky
  • Maryland
  • Michigan
  • North Carolina
  • Ohio
  • Pennsylvania

http://www.academyhealth.org/SUPLN

  • Virginia
  • West

Virginia

  • Wisconsin
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Opportunities for PCORnet

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https://pcornet.org/

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Three-part punchline

  • 1. States need help developing analytic priorities
  • 2. Start with the simplest available research methods
  • 3. Consider policy implications from the beginning

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24% - Social Circumstances

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  • 1. Better front-end technology
  • 2. Benchmarking and business processes at county level
  • 3. Measurement and support for health plans
  • 4. Measurement and support for medical home providers
  • 5. Collaboration with community-based organizations
  • 6. Other

How can we use these data products?

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Three-part punchline

  • 1. States need help developing analytic priorities
  • 2. Start with the simplest available research methods
  • 3. Consider policy implications from the beginning

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Policy Implications

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Introduction Data & Methods Results Discussion Policy Implications Conclusions Background Methods Results Discussion Background Methods Results Discussion Conclusion

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Policy Implications

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Paraphrase: “Thus, policy makers could further encourage these trends by continuing to invest in education and training.”

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Three-part punchline

  • 1. States need help developing analytic priorities
  • 2. Start with the simplest available research methods
  • 3. Consider policy implications from the beginning

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