The percentage of individuals ≥18 years of age with ≥1 initial opioid prescriptions for >7 cumulative days’ supply during the measurement year.
Measure Specs
General Information
Opioid misuse, addiction, and overdose remain a public health crisis affecting social and economic welfare in the United States. Drug overdoses involving an opioid accounted for 79,358 deaths in 2023, resulting in an age-adjusted drug overdose death rate that has more than tripled since 2013 and increased five-fold since 2003.(1) While synthetic opioids such as fentanyl are a substantial driver of increased mortality, the prescription opioid epidemic has not abated: nearly 8.6 million Americans reported misusing prescription opioids in 2023.(2) Prescription opioid safety remains an important priority, and quality measures serve as valuable tools to promote opioid safety and improve the quality of care for patients.
A large body of scientific evidence, described in detail in section 2.2 Evidence of Measure Importance, has established an association between greater duration of initial opioid exposure and significant risks, including increased likelihood for long-term opioid use, misuse, and overdose. To highlight, a retrospective cohort study by Shah et al. published in the CDC Morbidity and Mortality Weekly Report found that the probability of long-term opioid use increased with each additional day supplied past the third day when initiating opioid therapy; the probability of long-term use was more than twice as high for individuals who received greater than 7 days’ supply.
Based on this evidence, regulatory bodies have issued recommendations and instituted policies regarding the duration of therapy for initial opioid prescribing. In its 2022 Clinical Practice Guideline for Prescribing Opioids for Pain, the Centers for Disease Control and Prevention (CDC) provided updated recommendations regarding duration of initial opioid prescriptions.(3) The recommendations state that “when opioids are needed for acute pain, clinicians should prescribe no greater quantity than needed for the expected duration of pain severe enough to require opioids.” This recommendation is category A (applies to all persons; most patients should receive the recommended course of action) and evidence type 4 (clinical experience and observations, observational studies with important limitations, or randomized clinical trials with several major limitations).
Additionally, federal regulatory requirements and published guidance from the Centers for Medicare & Medicaid Services (CMS) note that Medicare plan sponsors are expected to implement real-time opioid safety edits at the point of sale, including an edit to limit initial opioid prescription fills for opioid naïve beneficiaries to no more than a 7 days’ supply.(4) An internal analysis of Part D data from 2018 to 2023 conducted by CMS showed that the percentage of Part D claims for opioids (excluding medications used for opioid use disorder) with 7 days’ supply or less increased from 18.4% in 2018 to 27.7% in 2023 after the implementation of enhanced opioid safety edits at the point of sale in 2019.(5) This measure serves as a retrospective complement to these edits.
To help ensure consistent application of these clinical recommendations and efforts to ensure safe initial opioid prescribing, measurement serves as a critical tool. The PQA Initial Opioid Prescribing for Long Duration measure evaluates initial opioid prescriptions for greater than 7 days’ supply, which are associated with increased risk of long-term opioid use, misuse, and overdose. Use of this measure to evaluate the performance of health plans is intended to reduce these risks, in turn leading to reduced health care resource utilization and improved quality of life. Because the measure only captures initial opioid prescriptions in individuals with no opioid history in the preceding 90 days, and does not penalize subsequent prescriptions for ongoing pain, it is not anticipated to result in unintended consequences related to access, discontinuation, or abrupt tapering in patients currently undergoing long-term opioid therapy.
References
1. Garnett MF, Minino AM. Drug overdose deaths in the United States, 2003-2023. NCHS Data Breif, No. 522. National Center for Heath Statistics. Updated December 2024. Accessed April 18, 2025. https://www.cdc.gov/nchs/data/databriefs/db522.pdf
2. Substance Abuse and Mental Health Services Administration. Key substance use and mental health indicators in the United States: Results from the 2023 National Survey on Drug Use and Health. Vol. NSDUH Series H-59. 2024. Accessed April 18, 2025. https://www.samhsa.gov/data/report/2023-nsduh-annual-national-report
3. Dowell D, Ragan KR, Jones CM, Baldwin GT, Chou R. CDC Clinical Practice Guideline for Prescribing Opioids for Pain - United States, 2022. MMWR Recomm Rep. Nov 4 2022;71(3):1-95. doi:10.15585/mmwr.rr7103a1
4. Centers for Medicare & Medicaid Services. Contract Year (CY) 2025 Medicare Part D Opioid Safety Edits – Submission Instructions, Recommendations, and Reminders. 2024. Accessed April 18, 2025. https://www.cms.gov/files/document/cy-2025-opioid-safety-edit-submission-instructions.pdf
5. Centers for Medicare & Medicaid Services. Medicare and Medicaid Programs; Contract Year 2026 Policy and Technical Changes to the Medicare Advantage Program, Medicare Prescription Drug Benefit Program, Medicare Cost Plan Program, and Programs of All-Inclusive Care for the Elderly. 2024. p. 427.
This measure is calculated using standard data from medical claims, prescription claims, and health plan administrative enrollment data. These data fields are highly standardized across the healthcare industry and are a common data source for quality measures. The attached value sets include the full universe of codes required to calculate the measure.
Numerator
The number of individuals from the denominator with >7 cumulative days’ supply for all opioid prescription claims within any opioid initiation period.
The numerator includes individuals from the denominator with >7 cumulative days’ supply for all opioid prescription claims within any opioid initiation period.
Use the steps below to identify the numerator population.
Step 1: For each individual in the denominator population, identify all initial opioid prescriptions and corresponding opioid initiation periods, defined as the date of service of the initial opioid prescription plus two days (since individuals may have multiple initial opioid prescription dates with a negative medication history, there may be multiple opioid initiation periods).
Step 2: For each individual, starting with each initial opioid prescription, sum the days’ supply of all opioid prescription claims within each opioid initiation period (i.e., date of service for the initial opioid prescription + 2 days).
For example, if the date of service for an initial opioid prescription is March 15, identify any opioid prescription claims from March 15 through March 17.
Note:
- The prescription claims can be for the same or different opioids.
- For multiple opioid claims with the same date of service, calculate the number of days covered by an opioid using the prescription claim with the longest days’ supply.
- For multiple opioid claims with different dates of service, sum the days’ supply for all the prescription claims regardless of overlapping days’ supply.
- If the opioid initiation period extends beyond the end of the measurement year, the opioid initiation period is truncated to the last day of the measurement year.
Step 3: Count the unique individuals with >7 cumulative days’ supply for all opioid prescription claims during any opioid initiation period in the measurement year.
Denominator
The denominator includes individuals ≥18 years of age, who are continuously enrolled during the measurement period and lookback period, with ≥1 prescription claims for an opioid and a negative medication history for any opioid medication during the 90-day lookback period.
The denominator includes individuals ≥18 years of age as of the first day of the measurement year (MY) with ≥1 prescription claims for an opioid during the MY, with continuous enrollment during the MY and 90 days prior to the index prescription start date (IPSD) and a negative medication history for any opioid medication during the 90-day lookback period. IPSD is defined as the earliest date of service for an opioid medication during the measurement year.
Individuals in hospice or palliative care at any time during the MY or 90 days prior to the IPSD, individuals with a cancer or sickle cell disease diagnosis during the MY or 90 days prior to the IPSD, and individuals receiving treatment for cancer-related pain during the MY or 90 days prior to the IPSD are excluded from the measure.
Complete the steps below to determine the denominator population.
Step 1: Identify individuals ≥18 years of age as of the first day of the measurement year.
Step 2: Identify individuals with ≥1 prescription claims for an opioid (Medication Table, OPIOIDS: Opioids) during the measurement year.
Step 3: Identify individuals continuously enrolled during the measurement year and the 90 days prior to the IPSD.
Step 4: Identify individuals with a negative medication history, defined as individuals with no prescription claims for opioids with a date of service for any opioid medication during the lookback period (a period of 90 days prior to each opioid prescription claim).
For example, an individual has opioid prescription claims on August 1, September 15 and December 20. For each of these dates of service, use the lookback period of 90 days to determine if the individual had no prescription claims for opioids. For example, for August 1, determine whether the individual had no prescription claims for opioids from May 3 – July 31. Repeat for the September 15 and December 20 opioid prescription claims.
Note:
- The prescription claims can be for the same or different opioids.
- Count the unique individuals (i.e., if an individual has multiple lookback periods, count the individual only once in the denominator).
Step 5: Exclude individuals who met at least one of the following during the measurement year or the 90 days prior to the IPSD:
- Hospice
- Cancer diagnosis
- Sickle cell disease
- Palliative care
- Cancer-related pain
Medication Table OPIOIDS: Opioids
Benzhydrocodone, butorphanol, codeine, dihydrocodeine, fentanyl, hydrocodone, hydromorphone, levorphanol, meperidine, methadone, morphine, opium, oxycodone, oxymorphone, pentazocine, tapentadol, tramadol
(Note: Includes combination products. Excludes the following: injectable formulations; opioid cough and cold products; sublingual sufentanil [used in a supervised setting]; and all buprenorphine products, as buprenorphine, a partial opioid agonist, is not expected to be associated with overdose risk in the same dose-dependent manner as doses for full agonist opioids.)
Exclusions
Individuals with cancer, sickle cell disease, in hospice or palliative care, or receiving cancer-related pain treatment at any point during the measurement year or the 90 days prior to the index prescription start date (IPSD) are excluded from the denominator.
Hospice exclusion: Exclude any individuals in hospice care at any time during the measurement year or 90 days prior to the IPSD.
- Hospice indicator from the enrollment database, if available (e.g., Medicare); or
- ≥1 claim, encounter, or medical record. See Value Set, Hospice Encounter; and Value Set, Hospice Intervention (e.g., Medicaid, commercial).
Cancer diagnosis exclusion: Exclude any individual with cancer during the measurement year or 90 days prior to the IPSD.
- ≥1 claim with cancer in the primary diagnosis or any other diagnosis fields. See Value Set, Cancer.
Sickle cell disease exclusion: Any individual with sickle cell disease during the measurement year or 90 days prior to the IPSD.
- ≥1 claim with sickle cell disease (SCD) in the primary diagnosis or any other diagnosis fields. See Value Set, Sickle Cell Disease.
Palliative care exclusion: Exclude any individual in palliative care during the measurement year or 90 days prior to the IPSD.
- ≥1 claim with palliative care in the primary diagnosis or any other diagnosis fields during the measurement year. See Value Set, Palliative Care.
Cancer-related pain exclusion: Exclude any individual receiving treatment for cancer-related pain during the measurement year or 90 days prior to the IPSD.
- ≥1 claim with cancer-related pain in the primary diagnosis or any other diagnosis fields. See Value Set, Cancer-Related Pain.
Measure Calculation
Denominator:
Step 1: Identify individuals ≥18 years of age as of the first day of the measurement year.
Step 2: Identify individuals with ≥1 prescription claims for an opioid (Medication Table, OPIOIDS: Opioids) during the measurement year.
Step 3. Identify individuals continuously enrolled during the measurement year and the 90 days prior to the IPSD.
Step 4: Identify individuals with a negative medication history for any opioid medication during the lookback period.
- For example, an individual has opioid prescription claims on August 1, September 15 and December 20. For each of these dates of service, use the lookback period of 90 days to determine if the individual had no prescription claims for opioids. For example, for August 1, determine whether the individual had no prescription claims for opioids from May 3 – July 31. Repeat for the September 15 and December 20 opioid prescription claims.
Note:
- The prescription claims can be for the same or different opioids.
- Count the unique individuals (i.e., if an individual has multiple lookback periods, count the individual only once in the denominator).
Step 5: Identify individuals who met at least one of the following during the measurement year or the 90 days prior to the IPSD: hospice, cancer, sickle cell disease, palliative care, or cancer-related pain.
To identify individuals in hospice:
- Use the hospice indicator from the enrollment database, if available (e.g., Medicare); or
- ≥1 claim, encounter, or medical record. See Value Set, Hospice Encounter; and Value Set, Hospice Intervention (e.g., Medicaid, commercial).
To identify individuals with cancer:
- ≥1 claim with cancer in the primary diagnosis or any other diagnosis fields. See Value Set, Cancer.
To identify individuals with sickle cell disease:
- ≥1 claim with sickle cell disease (SCD) in the primary diagnosis or any other diagnosis fields. See Value Set, Sickle Cell Disease.
To identify individuals with palliative care:
- ≥1 claim with palliative care in the primary diagnosis or any other diagnosis fields. See Value Set, Palliative Care.
To identify individuals with cancer-related pain:
- ≥1 claim with cancer-related pain in the primary diagnosis or any other diagnosis fields. See Value Set, Cancer-Related Pain.
Medication Table OPIOIDS: Opioids
Benzhydrocodone, butorphanol, codeine, dihydrocodeine, fentanyl, hydrocodone, hydromorphone, levorphanol, meperidine, methadone, morphine, opium, oxycodone, oxymorphone, pentazocine, tapentadol, tramadol
(Note: Includes combination products. Excludes the following: injectable formulations; opioid cough and cold products; sublingual sufentanil [used in a supervised setting]; and all buprenorphine products, as buprenorphine, a partial opioid agonist, is not expected to be associated with overdose risk in the same dose-dependent manner as doses for full agonist opioids.)
Step 6: Subtract the individuals identified in Step 5 (exclusions) from the population identified through Steps 1-4. The remaining individuals represent the denominator.
Numerator Population
Step 7: For each individual in the denominator population, identify all initial opioid prescriptions and corresponding opioid initiation periods.
Step 8: For each individual, starting with each initial opioid prescription, sum the days’ supply of all opioid prescription claims within each opioid initiation period (i.e., date of service for the initial opioid prescription + 2 days).
For example, if the date of service for an initial opioid prescription is March 15, identify any opioid prescription claims from March 15 through March 17.
Note:
- The prescription claims can be for the same or different opioids.
- For multiple opioid claims with the same date of service, calculate the number of days covered by an opioid using the prescription claim with the longest days’ supply.
- For multiple opioid claims with different dates of service, sum the days’ supply for all the prescription claims regardless of overlapping days’ supply.
- If the opioid initiation period extends beyond the end of the measurement year, the opioid initiation period is truncated to the last day of the measurement year.
Step 9: Count the unique individuals with >7 cumulative days’ supply for all opioid prescription claims during any opioid initiation period in the measurement year. This is the numerator.
Measure Rate
Step 10: Divide the number of individuals in the numerator (Step 9) by the denominator (Step 6) and multiply by 100. This the measure rate reported as a percentage.
- Note: Report the rates separately by line of business (e.g., Medicare, Medicaid, Commercial). For Medicare, report rates for low-income subsidy (LIS) and non-LIS populations separately.
The measure is stratified by the following lines of business for the health plan:
•Commercial
•Medicare
•Medicaid
PQA also recommends stratification of Medicare plans by Low-Income Subsidy status.
Definition: Medicare Low-Income Subsidy (LIS) - A subsidy paid by the Federal government to the drug plan for Medicare beneficiaries who need extra help with their prescription drug costs due to limited income and resources. Medicare beneficiaries apply for the LIS with the Social Security Administration or their State Medicaid agency.(1)
The Medicare Master Beneficiary Summary file contains the Cost Share Group variable used to identify LIS status.(2) There are 12 monthly variables - 01 through 12 at the end of the variable name corresponds with the month (e.g., 01 is January and 12 is December). CMS identifies beneficiaries with fully-subsidized Part D coverage by looking for individuals that have values of 01, 02, or 03 for the month. Other beneficiaries who are eligible for the LIS but do not receive a full subsidy have values of 04, 05, 06, 07, or 08. The remaining values indicate that the individual is not eligible for subsidized Part D coverage.
Within the Part D program, performance rates are also stratified by the contract type: Medicare Advantage Prescription Drug Plan (MAPD) contracts and standalone prescription drug plan (PDP) contracts. In this program, the term “contract” is synonymous with “health plan.”
References
1. Centers for Medicare & Medicaid Services. Guidance to States on the Low-Income Subsidy. 2009. Accessed April 18, 2025. https://www.cms.gov/medicare/eligibility-and-enrollment/lowincsubmedicareprescov/downloads/statelisguidance021009.pdf
2. Chronic Conditions Warehouse Virtual Research Data Center. Medicare Beneficiary Summary File (MBSF) Base with Medicare Part A, B, C, and D Codebook. Version 1.8. 2025. Accessed April 18, 2025. https://www2.ccwdata.org/documents/10280/19022436/codebook-mbsf-abcd.pdf
If the denominator used to calculate the measure is less than 30, the organization should note in performance reports an insufficient sample size for measurement purposes on that measure and should not report the rate.
Depending on the nature of the quality program, this minimum denominator may not be applied. For example, the Medicare Part D Patient Safety Reports are provided confidentially to health plans for quality improvement; within this program, no minimum denominators are applied to ensure maximum transparency for health plans, even those with small populations.
Point of Contact
COPYRIGHT 2025 PQA, INC. ALL RIGHTS RESERVED. PQA retains all rights of ownership to the measures contained in this Manual and Value Sets and can rescind or alter the measures at any time. No use of any PQA measure is authorized without prior PQA approval of such use. All uses of PQA measures are subject to such conditions as PQA specifies, and certain uses of the measures may be subject to a licensing agreement specifying the terms of use and the licensing fee. Users of the measure shall not have the right to alter, enhance, or otherwise modify the measures.
Ben Shirley
Alexandria, VA
United States
Ben Shirley
Pharmacy Quality Alliance
Alexandra, VA
United States
Importance
Evidence
As this measure is being submitted for maintenance review, a literature review was conducted to identify new evidence that has emerged since initial endorsement. This new evidence, along with the results of the literature review supporting initial endorsement, is synthesized below starting with the relevant clinical guidelines and then providing the published literature in chronological order of publication date.
In its 2022 Clinical Practice Guideline for Prescribing Opioids for Pain, the Centers for Disease Control and Prevention (CDC) provided updated recommendations regarding duration of initial opioid prescriptions.(1) The recommendations state that “when opioids are needed for acute pain, clinicians should prescribe no greater quantity than needed for the expected duration of pain severe enough to require opioids.” This recommendation is category A (applies to all persons; most patients should receive the recommended course of action) and evidence type 4 (clinical experience and observations, observational studies with important limitations, or randomized clinical trials with several major limitations).
Additionally, in April 2023, the Food and Drug Administration (FDA) announced required updates to the prescribing information for all opioid pain medicines to provide additional guidance for safe use. In this Drug Safety Communication,(2) the FDA stated, “Data also suggest that many acute pain conditions treated in the outpatient setting require no more than a few days of an opioid pain medicine, although the dose and duration of treatment needed to adequately manage pain will vary based on the underlying cause and individual patient factors.” These newly implemented updates reflect continued emphasis on appropriate use with a particular focus on duration.
The CDC guideline recommendation, and the IOP-LD measure’s threshold of a 7 days’ supply, is supported by the following body of epidemiologic evidence.
A retrospective analysis by Tehrani et al. published in 2017 used Medicaid claims from 2005-2014, including approximately 6 million Medicaid enrollees ages 18-64 without a cancer diagnosis, to explore trends in prescribed days’ supply for opioids.(3) The authors found that over the course of the study, the average days’ supply of opioids increased considerably for all opioids except for morphine. Oxycodone days’ supply increased 4.5 days (a 37% increase) during the study period, while hydrocodone, hydromorphone, oxymorphone, and tapentadol increased by 4, 2.5, 3, and 5 days, respectively. Notably, there was no observed decline in median days’ supplied for any opioid after 2013, when the opioid epidemic gained national attention. Further evaluation of a commercial cohort during the same timeframe exhibited similar, but even steeper increases in days’ supply for opioids.
In research published in 2018, Shah et al. performed a retrospective cohort study using a random sample from a nationally representative database of the commercially insured population in the United States from 2006-2015 to explore relationships between initial opioid prescription characteristics and likelihood of long-term use.(4) The study examined 1,294,247 patients aged 18 years or older who met inclusion criteria and received initial opioid prescriptions, defined as those with no opioid prescriptions in the preceding 6 months of continuous enrollment. The study found that the probability of long-term opioid use increased with each additional day supplied when initiating opioid therapy, following the third day supplied. Specifically, the probability of long-term use was more than twice as high for individuals who received greater than 7 days’ supply, when compared to those with at least one days’ supply (13.5% vs. 6.0%). In conclusion, the authors expressly note that their findings are consistent with CDC recommendations and suggest that limiting initial opioid prescriptions to 7 or fewer days’ supply (and ideally no greater than 3 days’ supply) reduces the risk of unintentional long-term opioid use.
Additional research published by Shah et al. in 2018 provided further evidence that greater days’ supply for initial opioid prescriptions is associated with a lower likelihood of opioid discontinuation.(5) In a retrospective cohort study examining a total of 1,353,902 opioid naïve individuals (defined as individuals with at least 12 months without an opioid prescription prior to their initial prescription) from 2006-2015 who met inclusion criteria, the authors examined the relationship between initial opioid prescription characteristics and probability of opioid discontinuation among opioid naïve patients, controlling for patient level factors. The authors reported that even controlling for patient factors and underlying pain etiologies, the results are consistent with earlier findings suggesting a dose-response relationship between days’ supply and likelihood of discontinuation (see citation 4), with hazard ratios for discontinuation of 0.70 (95% CI 0.70-0.71) for a 3-4 day supply, 0.48 (95% CI 0.47-0.48) for a 5-7 day supply, 0.37 (95% CI 0.37-0.38) for an 8-10 day supply, and 0.32 for an 11-14 day supply of opioids (95% CI 0.31-33), where a 1-2 day supply is the reference group.
In 2018, Zhang et al. conducted a retrospective cohort study of 403,664 privately insured patients and 107,509 Medicare Advantage patients who initiated opioid therapy between 2011 and 2013, to determine how characteristics of these initial prescriptions, including days’ supply, affect risk for high-risk opioid use in the following 18 months.(6) Initial opioid prescriptions were defined as opioid prescriptions among patients who did not have any opioid prescriptions within a lookback period of six months. The authors found that an initial opioid prescription consisting of greater than 7 days’ supply, versus a 3 or fewer days’ supply reference group, was associated with a significant (p<0.001) increase in high-risk opioid use, including overlapping opioid prescriptions (7% increase, 95% CI 6.2%-7%), concurrent use of opioids and benzodiazepines (8.7% increase, 95% CI 8.2%-9.2%), receiving opioids with a daily average dosage of 120 or more morphine milligram equivalents (MME) in the long term (4.8% increase, 95% CI 4.5%-5.2%), and use of opioids in each quarter of the 18 months following the index prescription (15% increase, 95% CI 15.0%-15.6%).
Brat et al. conducted a retrospective cohort study in 2018 that explored opioid prescribing patterns after surgery and found additional evidence regarding initial opioid prescribing and opioid misuse, defined as a composite of diagnosis codes for opioid abuse, dependence, or overdose.(7) The study used surgical claims from a linked medical and pharmacy administrative database from 2008-2016, and included 568,612 opioid naïve patients, defined as patients who had used 7 or fewer days of opioids in the 60 days preceding the surgery, and who received a postsurgical opioid. The authors note that duration of use, rather than dosage, was most strongly associated with opioid misuse, with an estimated increase rate of 20% of opioid misuse per each week of an opioid prescription after adjusting for covariates (95% CI 18.5%-21.4%). These findings remained consistent after sensitivity analyses, including removing the most common ICD code for opioid dependence and relying entirely on specific abuse and overdose codes.
A 2018 comparative study by Mojtabai analyzed trends in prescription opioid use among U.S. adults from 1999-2000 and 2013-2014.(8) Results showed a significant increase in the prevalence of prescription opioid use among the study population, with approximately 80 percent of use being characterized as long-term in 2013-2014. This increased prevalence of long-term prescription opioid use has significant implications, as such use was associated with poorer physical health status, concurrent use of benzodiazepines, and a history of heroin use.
A 2019 study by Durand et al. of 46,399 opioid-naive injured workers, defined as individuals with no opioid prescriptions in the 60 days prior to injury, from 2013-2015 examined the relationship between initial opioid prescription characteristics and long-term opioid use.(9) The authors found that initial prescription length, rather than demographic or injury characteristics, was the strongest predictor of long-term opioid use, which was defined as having an opioid supplied for 45 or more days in the 90 days after the injury. The study found that in comparison to a reference group of <5 days’ supply, a 5-9 day supply was associated with a significant increase in the odds of long-term use (adjusted OR 1.83, 95% CI 1.56-2.14). This dose-response trend between days’ supply and odds of long-term opioid use continued with greater days’ supply, including 10-19 days (adjusted OR 4.73, 95% CI 3.90-5.75) and 20 days or more (OR 28.94, 95% CI 23.44-35.72).
A 2019 study performed by Hadlandsmyth et al. replicated Shah’s methodology to examine the relationship between initial opioid exposures and long-term use. The study examined 19,600 patients in the Veteran’s Health Administration who received an initial opioid prescription (defined as prescriptions with no opioid prescriptions in the preceding year) and met criteria for long-term opioid use within one year of follow-up. The authors corroborated Shah’s findings, with initial opioid prescriptions for 7 days or fewer serving as a reference group, and greater days’ supply associated with increased risk of long-term opioid use, including 8-14 days (adjusted OR 1.44, 95% CI 1.38-1.51), 15-21 days (adjusted OR 2.43, 95% CI 2.30-2.56), 22-30 days (adjusted OR 7.35, 95% CI 8.09-7.62), and greater than 30 days (adjusted OR 15.5, 95% CI 14.7-16.4).(10)
In a 2019 study, Mundkur et al. conducted a retrospective cohort study using 2014 data, examining the frequency of refills among adults who filled an opioid analgesic prescription within 7 days of an initial outpatient visit for 10 acute pain conditions (n=176,607).(11) For adults who received an initial prescription of 7 days’ supply, the adjusted probability of refill ranged from 0.11 (95% CI 0.09-0.14) for headache to 0.41 (0.19-0.68) for musculoskeletal injury. Using a lack of refill as a surrogate for adequately managed pain, authors suggest that their findings show that for most cases, a 7 days’ supply of opioid analgesics is sufficient (if not more than necessary). However, the authors note that refills are an imperfect marker and may reflect physical dependence, withdrawal, or the need for additional pain control that could possibly be managed by nonopioid alternatives.
In a 2020 study, Riva et al. performed a systematic review and meta-analysis of observational studies from inception to 2020 to explore factors associated with persistent opioid use following initial prescriptions for acute musculoskeletal injury. Initial prescriptions for greater than 7 days’ supply (5 cohorts; n= 2,087,624 patients) demonstrated a consistent association with increased risk for prolonged opioid use (median absolute risk increase 4.5%).(12)
In a 2020 retrospective cohort study, Weiner et al. evaluated the characteristics of initial opioid prescriptions among opioid-naïve patients and their associations with chronic opioid use using Ohio prescription drug monitoring program data from 2010-2017 (n=4,252,809 patients).(13) Chronic use was defined as at least six opioid prescriptions in one year and either one or more years between the first and last prescription or an average of less than or equal to 30 days not covered by an opioid during that year. Days’ supply, as well as quantity, were found to be significantly associated with chronic use; the average days’ supply among patients with no chronic use was 6.8 days while the average days’ supply among patients with chronic use was 12.3 days (p<0.001).
In a 2022 retrospective cohort study by Weiner et al., authors assessed the patient and prescription-related factors associated with opioid-related fatal or nonfatal overdose among opioid-naïve adult patients.(14) Analyses were conducted by combining claims data from 2013-2018 with several public health data sets to create the Oregon Comprehensive Opioid Risk Registry. To be considered opioid naive, individuals must not have had more than 1 index prescription; an opioid use disorder-related buprenorphine formulation as the index prescription or in the index period; or any opioid prescriptions, opioid-related hospitalizations, or emergency department visits in the 12 months before the index prescription dispense date. Index opioid prescriptions were found to be associated with a significantly higher overdose rate per 100,000 person-years when the days’ supply was greater than 7 days (191.3, 95% CI 163.1-224.4) compared to less than or equal to 7 days (108.9, 95% CI 99.9-118.7).
In a 2022 retrospective cohort study, Young et al. evaluated potential impacts of prescribing limits by examining the relationship between length of initial opioid prescriptions and risk of prolonged opioid use.(15) This study identified opioid naïve adults undergoing surgery (n=1,060,596) using Medicare claims from 2007-2017. Among the 70.0% of these patients who received a postoperative opioid, increased days’ supply of the initial prescription was associated with increasing risk of prolonged opioid use, ranging from 0.7% (1 day supply) to 4.4% (15 or more days’ supply). In evaluating prescribing limits, a limit of 4 days was associated with the largest reduction in absolute risk from 24.4 to 19.6 per thousand patients, suggesting the 7-day threshold used in the IOP-LD measure may be relatively less restrictive.
In a 2024 study, Nguyen et al. found the likelihood of an opioid refill within 90 days increased with greater initial prescription duration based on a retrospective cohort study focused on outpatient pain visits from 2013-2018 (n=220,797).(16) Within the cohort, 22.4% of patients received greater than 7 days’ supply, and 23.5% of patients had a refill during the follow-up window; longer initial prescription length was associated with greater adjusted likelihood of a refill for all conditions although magnitudes of effect varied. Per the authors’ analyses, about 1-3 fewer patients would receive a refill within 3 months for every 100 patients initially prescribed 3 vs. 7 days’ supply of opioids for most pain diagnoses.
References:
1. Dowell D, Ragan KR, Jones CM, Baldwin GT, Chou R. CDC Clinical Practice Guideline for Prescribing Opioids for Pain - United States, 2022. MMWR Recomm Rep. Nov 4 2022;71(3):1-95. doi:10.15585/mmwr.rr7103a1
2. U.S. Food & Drug Administration. FDA Drug Safety Communication. U.S. Department of Health & Human Services. Updated April 13, 2023. Accessed April 18, 2025. https://www.fda.gov/media/167058/download
3. Tehrani AB, Henke RM, Ali MM, Mutter R, Mark TL. Trends in average days' supply of opioid medications in Medicaid and commercial insurance. Addict Behav. Jan 2018;76:218-222. doi:10.1016/j.addbeh.2017.08.005
4. Shah A, Hayes CJ, Martin BC. Characteristics of Initial Prescription Episodes and Likelihood of Long-Term Opioid Use - United States, 2006-2015. MMWR Morb Mortal Wkly Rep. Mar 17 2017;66(10):265-269. doi:10.15585/mmwr.mm6610a1
5. Shah A, Hayes CJ, Martin BC. Factors Influencing Long-Term Opioid Use Among Opioid Naive Patients: An Examination of Initial Prescription Characteristics and Pain Etiologies. J Pain. Nov 2017;18(11):1374-1383. doi:10.1016/j.jpain.2017.06.010
6. Zhang Y, Johnson P, Jeng PJ, et al. First Opioid Prescription and Subsequent High-Risk Opioid Use: a National Study of Privately Insured and Medicare Advantage Adults. J Gen Intern Med. Dec 2018;33(12):2156-2162. doi:10.1007/s11606-018-4628-y
7. Brat GA, Agniel D, Beam A, et al. Postsurgical prescriptions for opioid naive patients and association with overdose and misuse: retrospective cohort study. BMJ. Jan 17 2018;360:j5790. doi:10.1136/bmj.j5790
8. Mojtabai R. National trends in long-term use of prescription opioids. Pharmacoepidemiol Drug Saf. May 2018;27(5):526-534. doi:10.1002/pds.4278
9. Durand Z, Nechuta S, Krishnaswami S, Hurwitz EL, McPheeters M. Prevalence and Risk Factors Associated With Long-term Opioid Use After Injury Among Previously Opioid-Free Workers. JAMA Netw Open. Jul 3 2019;2(7):e197222. doi:10.1001/jamanetworkopen.2019.7222
10. Hadlandsmyth K, Lund BC, Mosher HJ. Associations between initial opioid exposure and the likelihood for long-term use. J Am Pharm Assoc (2003). Jan-Feb 2019;59(1):17-22. doi:10.1016/j.japh.2018.09.005
11. Mundkur ML, Franklin JM, Abdia Y, et al. Days' Supply of Initial Opioid Analgesic Prescriptions and Additional Fills for Acute Pain Conditions Treated in the Primary Care Setting - United States, 2014. MMWR Morb Mortal Wkly Rep. Feb 15 2019;68(6):140-143. doi:10.15585/mmwr.mm6806a3
12. Riva JJ, Noor ST, Wang L, et al. Predictors of Prolonged Opioid Use After Initial Prescription for Acute Musculoskeletal Injuries in Adults: A Systematic Review and Meta-analysis of Observational Studies. Ann Intern Med. Nov 3 2020;173(9):721-729. doi:10.7326/M19-3600
13. Weiner SG, Chou SC, Chang CY, et al. Prescription and Prescriber Specialty Characteristics of Initial Opioid Prescriptions Associated with Chronic Use. Pain Med. Dec 25 2020;21(12):3669-3678. doi:10.1093/pm/pnaa293
14. Weiner SG, El Ibrahimi S, Hendricks MA, et al. Factors Associated With Opioid Overdose After an Initial Opioid Prescription. JAMA Netw Open. Jan 4 2022;5(1):e2145691. doi:10.1001/jamanetworkopen.2021.45691
15. Young JC, Dasgupta N, Chidgey BA, et al. Impacts of Initial Prescription Length and Prescribing Limits on Risk of Prolonged Postsurgical Opioid Use. Med Care. Jan 1 2022;60(1):75-82. doi:10.1097/MLR.0000000000001663
16. Nguyen AP, Palzes VA, Binswanger IA, et al. Association of initial opioid prescription duration and an opioid refill by pain diagnosis: Evidence from outpatient settings in ten US health systems. Prev Med. Feb 2024;179:107828. doi:10.1016/j.ypmed.2023.107828
Measure Impact
Patient involvement is a critical component of PQA’s systematic, transparent, and consensus-based measure development and maintenance process. PQA gathered patient input prior to and during the development of the IOP-LD measure through the convening of a Patient and Caregiver Advisory Panel (PCAP). The PCAP was a group of 12 individuals, selected by PQA staff through a nomination process, to provide patient and caregiver input into the measure development process and thereby reflect patients’ perspectives in PQA measures. Selected individuals self-identified as patients, caregivers, patient advocates, or more than one of these roles. Three participants also worked as healthcare professionals.
In a survey following the introduction of three measure concepts focused on initial opioid prescribing, including IOP-LD, all PCAP members were asked, “Is the evaluation of initial opioid prescriptions important to patients and caregivers?” All respondents indicated “Yes.”
Further, the CDC curates patients’ frequently asked questions about prescription opioids.(1) These questions, listed below, illustrate patients’ concerns about risks of opioid use, misuse, and overdose. This underscores the value and meaningfulness of the IOP-LD measure to patients.
- Will I develop an opioid use disorder?
- How do I take and store opioids properly?
- Can I avoid side effects and risks of opioids?
- What increases my risk of overdose from opioids and other drugs?
Finally, PQA’s transparent, systematic, consensus-based measure maintenance process includes two patient representatives on the Measure Update Panel, which reviews and evaluates potential changes to measures, including updates made to the IOP-LD measure since its original development. Substantive changes to measures are further reviewed by PQA’s Quality Metrics Expert Panel, which also includes two patient representatives. These individuals help ensure the ongoing importance and meaningfulness of PQA measures to patients.
References:
1. Centers for Disease Control and Prevention. Patients' Frequently Asked Questions About Prescription Opioids. U.S. Department of Health & Human Services. Updated November 1, 2024. Accessed April 18, 2025. https://www.cdc.gov/overdose-prevention/manage-treat-pain/patients-faqs.html
Performance Gap
The Pharmacy Quality Alliance (PQA) reviewed IOP-LD measure scores using data from the measure’s implementation by CMS in Medicare Part D. Specifically, PQA calculated the distribution of rates using data from the Part D Patient Safety Reports from calendar years 2020-2022. These datasets, provided by CMS directly and confidentially to PQA, include contract-level data from both MAPDs and PDPs participating in the Part D program. The number of included contracts and patients are as follows:
- 2020 – MAPD: 680 contracts, 2,825,411 patients; PDP: 60 contracts, 3,206,213 patients
- 2021 – MAPD: 736 contracts, 3,171,556 patients; PDP: 60 contracts, 3,106,406 patients
- 2022 – MAPD: 785 contracts, 3,418,304 patients; PDP: 55 contracts, 2,968,052 patients
The numerator and denominator in the Part D Patient Safety Reports are measured using beneficiary member-years, which represent the number of beneficiaries covered by a contract adjusted for the portion of the year during which they were enrolled (e.g., six months of enrollment equals 0.5 member-years). Where whole numbers are required for various analyses in subsequent sections (e.g., signal-to-noise reliability), rounding to the next highest integer was applied.
Equity
Equity
Evidence of Known Disparities:
We note that literature provides evidence of a variety of disparities related to opioids and initial opioid prescribing, many of which were recently addressed in the CMS Proposed Rule CMS-4208-P, excerpted below.(1)
“According to the CDC, there are widening disparities among various population groups for overdose death rates, which have recently been driven by illicitly manufactured fentanyl use.301 In 2020, the overdose death rates per 100,000 people increased by 44% for the Black population and 39% for American Indian and Alaska Native (AI/AN) population compared to 2019. Additionally, among Black males 65 years and older, the overdose death rate was nearly seven times more than their White male counterparts of the same age group.
Additionally, officials from the Substance Abuse and Mental Health Services Administration (SAMHSA), CDC, and the National Institute on Drug Abuse published a study that followed a cohort of 136,762 Medicare beneficiaries who experienced an index nonfatal drug overdose in 2020.302 This population consisted primarily of Hispanic (5.8%), non-Hispanic Black (10.9%), and non-Hispanic White (78.8%) beneficiaries. The researchers followed the beneficiaries 12 months after the initial index nonfatal drug overdose and found that 23,815 beneficiaries (17.4%) had at least one more nonfatal drug overdose and 1,323 beneficiaries (1.0%) died of a fatal overdose. The study found that opioids were involved in 72.2% of these fatal drug overdoses.
Differences are seen in the Medicare Part D population based on internal analysis of PDE [prescription drug event] and administrative claims data by CMS. In 2023, the percentages of non-MOUD opioid Part D users were 24% for Black beneficiaries, 24% for AI/AN beneficiaries, and 22% for White beneficiaries. We found that overall, the number of Part D beneficiaries with a primary opioid overdose claim decreased from 32,120 in 2018 to 28,365 in 2023 (0.83 per 1,000 to 0.62 per 1,000 Part D beneficiaries). The opioid overdose rates varied among the Part D population in 2023 (January 1, 2023 to December 31, 2023): 1.52 per 1,000 AI/AN Part D beneficiaries, 1.35 per 1,000 Black Part D beneficiaries, and 0.57 per 1,000 White Part D beneficiaries.
The disparities in opioid overdose rates existing among different population groups, as highlighted by CMS’s internal data analysis, underscore the urgency to address the widening gap in health outcomes. As discussed previously, there is room for improvement and variations in IOP-LD rates among Part D sponsors. The IOP-LD measure is a preventative-focused quality measure that addresses initial prescription opioid exposure to reduce the likelihood of long-term opioid use and reduce the risk of opioid overdose.
301. CDC Newsroom Release. Overdose death rates increased significantly for Black, American Indian/Alaska Native people in 2020: https://www.cdc.gov/media/releases/2022/s0719-overdose-rates-vs.html.
302. JAMA Internal Medicine: Overdose, Behavioral Health Services, and Medications for Opioid Use Disorder After a Nonfatal Overdose: https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2820177.”
Methodology:
The measure has been used in Medicare Part D quality programs since 2020, where measure rates are reported at the contract level. Measure performance data made available by CMS do not include beneficiary-level demographic information; therefore, empirical assessment of differences in IOP-LD performance scores among socio-contextual variables is not feasible using data from implementation.
During the original development of IOP-LD, the measure concept was tested in Medicare, Medicaid, and commercial data samples from 2014, 2016, and 2017. Four testing organizations calculated measure rates and provided results to PQA. To better understand how the measure affects different subpopulations, these results were stratified by sex (male, female), age group (18-50, 51-64, 65-84, greater than or equal to 85 years), and Low-Income Subsidy (LIS) status (LIS, non-LIS), based on standard data elements that were available to all tester organizations at the time
PQA explored options to perform analyses on more recent data but were unable to provide results for this optional element of the submission.
Results/Interpretation
Across four testing organizations, overall IOP-LD measure rates ranged from 43.0%-50.9% in Medicare, 25.9%-26.3% in commercial, and 15.1%-28.3% in Medicaid, revealing differences in performance across lines of business. Stratified measure rates also highlighted differences among several subpopulations.
Across all Medicare samples, female patients had consistently higher (worse) measure rates, with scores approximately 8% higher than males. These results stood in contrast to sex-stratified rates reported in commercial and Medicaid data, where female patients, on average, had rates between 0.8% and 5.3% lower than males.
Age-stratified results showed higher rates in Medicare patients aged 51-64 and 85 and older compared to those aged 65-84. In commercial and Medicaid samples, measure rates increased with each subsequent age stratum, with patients aged 18-50 having the lowest scores and those aged 85 and older having the highest scores.
A focused evaluation of 183,545 Medicare beneficiaries enrolled in PDPs showed that LIS recipients had a higher measure rate than non-LIS individuals by approximately 2%, indicating that those with greater financial need have worse performance on the measure on average.
These results draw attention to differences in performance among various subpopulations. They notably demonstrated the increased prevalence of initial long-term opioid prescribing in older adults. Such prescribing was especially prominent in the Medicare population, more than three-quarters of whom are aged 65 or older, in 2016 and 2017. These findings raise concern given the noted risk of opioid overdose in older adults.
However, average IOP-LD measure rates in Medicare have since decreased by more than half following the implementation of enhanced opioid safety edits by CMS in 2019 as well as the uptake and use of IOP-LD in quality programs. This suggests that health plans have been able to successfully implement strategies to improve performance on the measure and can continue to identify and address disparities in performance.
Anticipated Impact
Differences in performance across subpopulations described above can provide valuable information for health plans seeking to understand vulnerable subgroups amongst their covered populations and close gaps in care. As a claims-based measure, calculation of IOP-LD is relatively straightforward and can be stratified by sociodemographic beneficiary information when available to support identification of disparities and efforts to improve health equity.
Also of note, the PQA Health Equity Technical Expert Panel (TEP) recently provided several recommendations for stratification of PQA measures on a program-by-program basis, including for the IOP-LD measure. The Health Equity TEP’s top priorities for stratification in Medicare Part D included age, sex, geography, and race/ethnicity. PQA has shared these recommendations with program administrators, who are ultimately responsible for decisions about stratified reporting.
Beyond a programmatic approach, individual health plans can also use their data internally to stratify by recommended variables and identify interventions that seek to reduce disparities. To support this broad approach, PQA published the PQA Health Equity Technical Expert Panel’s recommendations and has disseminated them to promote broad adoption.
References
1. Medicare and Medicaid Programs; Contract Year 2026 Policy and Technical Changes to the Medicare Advantage Program, Medicare Prescription Drug Benefit Program, Medicare Cost Plan Program, and Programs of All-Inclusive Care for the Elderly, 89 Fed. Reg. 99,340 (Dec. 10, 2024). https://www.govinfo.gov/content/pkg/FR-2024-12-10/pdf/2024-27939.pdf
Feasibility
Feasibility
The IOP-LD measure has been implemented in the Medicare Part D Patient Safety Reports since 2020 and Part D Display page since program year 2023 (2021 data). During this time, no feasibility challenges were reported with the use of the measure. All required data elements are routinely generated and readily available in structured fields. No concerns with missing data have been identified.
Although the measure has not yet been implemented in the Medicaid Adult Core Set, no issues with feasibility were identified by the workgroup during their evaluation of the measure and resulting recommendation to add the measure to the Medicaid Adult Core Set.
No changes to the measure since initial endorsement have impacted feasibility.
Measured entities (health plans) are not anticipated to face significant costs or burden due to implementation of the IOP-LD measure. Prescription and medical claims data, which are needed for measure calculation, are routinely generated by plans. However, costs may arise due to acquisition of other relevant data or analytic tools.
Standalone Part D prescription drug plans (PDPs) may not have timely access to medical claims data and could experience related delays, though such data are only needed to apply the measure’s exclusions. Of note, AB2D–an Application Programming Interface (API) recently developed by CMS–helps to provide PDPs with Medicare Parts A and B (medical) data in an efficient and secure manner. More information is available at https://ab2d.cms.gov/.
IOP-LD is a population-level measure that does not require the collection or reporting of any patient-identifying information. Further, the measure’s specifications indicate that an organization should not report a measure rate in instances where the denominator includes fewer than 30 individuals, which reduces concerns about small sample sizes that may compromise confidentiality.
No adjustments have been made to the measure’s specifications in response to feasibility concerns.
Proprietary Information
All uses of PQA measures are subject to such conditions as PQA specifies, and certain uses of the measures may be subject to a licensing agreement specifying the terms of use and the licensing fee. Government agencies do not pay a license royalty.
Scientific Acceptability
Testing Data
PQA conducted reliability testing using the Medicare Part D Patient Safety Report data from calendar years 2020, 2021, and 2022. We conducted validity testing using the Medicare Part D Display data from calendar years 2021 and 2022. Both datasets include contract-level data from both MAPD and PDP contracts.
Empirical validity testing was conducted using data from the Medicare Part D Display for calendar years 2021 and 2022. The Medicare Part D Display data provides contract-level scores for the IOP-LD measure and other measures on which PQA performed convergent validity testing. However, these data only include measure rates and do not provide denominator size by contract. As a result, they cannot be used for reliability testing.
Reliability testing was conducted using data from the Medicare Part D Patient Safety Report program from calendar years 2020, 2021, and 2022. Medicare Part D Patient Safety Reports include rate, denominator, and numerator data by contract, which are required to calculate signal-to-noise reliability using the Adams approach.
For reliability and validity testing, PQA utilized data sources that are reflective of the real-world implementation of this measure in the Medicare Part D Patient Safety Report and Medicare Part D Display programs.
Reliability testing was conducted across three years of Medicare Part D Patient Safety Report data (2020-2022) and represented a total of 2,376 Part D contracts and 18,695,942 beneficiaries in the IOP-LD eligible population across the three years.
Validity testing was conducted across two years of Medicare Part D Display data (2021-2022) and represented a total of 699 contracts in 2021 and 725 contracts in 2022. The number of beneficiaries per contract is not reported within Part D Display data; however, it is expected that the vast majority of Medicare Part D beneficiaries are represented within the data reported.
The Medicare Part D Patient Safety Reports and Medicare Part D Display data provide contract-level information, but do not contain beneficiary-level demographic information such as age, sex, or race. The demographics of Medicare beneficiaries receiving opioid prescriptions has been the subject of previous studies, with evidence suggesting that older beneficiaries and white beneficiaries are more likely to receive opioids.(1,2) As a result, older and white beneficiaries may constitute a relatively larger portion of the eligible population of the IOP-LD measure.
The distribution of eligible population size by contract for the Medicare Part D Patient Safety Reports is provided below by year and contract type (MAPD or PDP), after limiting contracts to only those with 30 or more individuals in the denominator.
In 2020, the average number of beneficiaries was 4,155 (SD: 12,768) in MAPD contracts and 53,436 (SD: 128,505) for PDPs. In 2021, the average number of beneficiaries was 4,309 (SD: 13,846) in MAPD contracts and 51,773 (SD: 124,648) for PDPs. In 2022, the average number of beneficiaries was 4,354 (SD: 14,417) in MAPD contracts and 53,964 (SD: 138,923) for PDPs.
References:
1. Raman SR, Bush C, Karmali RN, Greenblatt LH, Roberts AW, Skinner AC. Characteristics of New Opioid Use Among Medicare Beneficiaries: Identifying High-Risk Patterns. J Manag Care Spec Pharm. Sep 2019;25(9):966-972. doi:10.18553/jmcp.2019.25.9.966
2. Chronic Conditions Warehouse. All CCW Medicare Enrollment Charts Data 2022. U.S. Department of Health & Human Services. Accessed April 18, 2025. https://www2.ccwdata.org/documents/10280/19099067/medicare-charts-enrollment-data.xlsx?t=1688130677673
Reliability
Using the data described in section 5.1.1 and 5.1.2, the reliability of the computed measure scores was measured as the ratio of signal-to-noise. This analysis was conducted to evaluate the differences between contract-level measure scores by comparing the proportion of variance that is attributable to consistent measurement (signal) compared to non-systematic or random error (noise); this is represented in the data as the variation in measure scores between contracts (signal) and variation within a single contract (noise).
The beta-binomial method published by Adams in 2009)(1) was used to calculate reliability for individual contracts grouped by measure year (2020-2022) and health plan type (MAPD, PDP). Reliability scores range from 0-1, with a score of 0 signifying that all variation is due to measurement error. A value of 1 signifies that the variation represents true differences in performance scores between contracts. In accordance with PQA guidance, contracts with less than 30 individuals in the denominator were not included for analysis.
References:
1. Adams JL. The reliability of provider profiling: a tutorial. 2009. Accessed September 20, 2024. https://www.rand.org/pubs/technical_reports/TR653.html
The statistical results of signal-to-noise reliability testing are presented in Tables 2a-2f by contract type and calendar year. The results suggest a high level of reliability across all contracts with all 2020, 2021, and 2022 MAPD contracts meeting the minimum required reliability value of 0.6 and more than 90% of 2020, 2021, and 2022 PDP contracts meeting the minimum required reliability value of 0.6.
The results of the signal-to-noise reliability testing demonstrate that IOP-LD is a highly reliable measure for each contract type and calendar year. This demonstrates that the differences in performance scores seen between contracts are due to actual differences in performance rather than measurement error.
Validity
Systematic Assessment of Face Validity
PQA uses a systematic, transparent, evidence- and consensus-based measure development process. This process, used in 2018-2019 to develop the IOP-LD measure, is outlined below:
• Step 1: Measure concepts for development are prioritized by PQA staff based on input from PQA’s Measure Advisement Group, Implementation Advisory Panel, and Patient and Caregiver Advisory Panel. Environmental scans are conducted to identify whether similar measures exist, ensuring harmonization and avoiding duplication. Selected concept ideas are considered to represent areas in which there are measurement and performance gaps to have the greatest chance of implementation in existing measure sets and performance systems, and to align with the National Quality Strategy.
• Step 2: PQA Measure Development Teams (MDTs) and Task Forces (TFs), composed of experts in all phases of drug use and management, discuss and draft specifications for measure concepts that may be appropriate for development into fully specified performance measures. The MDTs/TFs focus on specific aspects of the medication-use system and/or specific therapeutic areas and benefit by having their development work reviewed by larger groups, Stakeholder Advisory Panels. They may also receive input from the Patient & Caregiver Advisory Panel, Implementation Advisory Panel, and Risk Adjustment Advisory Panel.
• Step 3: PQA MDTs/TFs recommend measure concepts to the PQA Quality Metrics Expert Panel (QMEP) for evaluation and refinement. The QMEP reviews and provides an initial assessment of the measure concept focusing on the criterion of importance (i.e., evidence supports that measurement can have a positive impact on healthcare quality). The QMEP votes to approve the measure concept to move forward for testing.
• Step 4: PQA staff prepare technical specifications (including National Drug Code [NDC] lists) for pilot testing and use MDT/TF and QMEP recommendations to formulate a testing plan for each draft measure.
• Step 5: PQA selects partners to test the draft measures. These partners are often PQA member health plans or academic institutions with expertise in quality and performance measure testing that also have access to the data sources needed to calculate the measure rates. The testing partner implements the draft technical specifications within their existing datasets and provides a report to PQA that details testing results and recommendations for modifications of the technical specifications.
• Step 6: The QMEP reviews the testing results and recommendations and determines final criteria for the measure based on the findings. The QMEP provides a final assessment of the draft measures’ feasibility and reliability and recommends whether measures should move forward for PQA endorsement consideration. 90% (18/20) QMEP members recommended that the measure move forward for PQA endorsement consideration.
• Step 7: The Measure Validity Panel (MVP), an independent group of individuals not involved in the development or review of the measure concept or draft measure, determines through discussion and vote whether the performance measure score is an accurate reflection of quality and can distinguish good from poor performance (i.e., face validity). Through discussion and vote, the MVP determines whether the performance measure scores have face validity.
• Step 8: Performance measures that are recommended by the QMEP for endorsement consideration by the PQA membership are posted on the PQA web site for member review, written comments are requested, and a webinar for member organizations is held to gather feedback and address any questions. This process allows members to discuss their views on the measures in advance of the voting period.
• Step 9: PQA member organizations vote on endorsement of the performance measure.
Empirical Validity Testing
Empirical validity testing of the IOP-LD measure used a convergent validity approach to assess the association between performance on the IOP-LD measure and other conceptually-related measures. Correlations in expected directions between measures that capture similar aspects of quality and/or benefit from overlapping or similar interventions provide evidence of validity.
The PQA team began by reviewing measures included on the Part D Display page, where the IOP-LD scores are publicly reported and can be compared to other publicly reported measures. PQA initially limited the list of measures to those that assess medication use quality, then further refined the list to only those that evaluate medication safety. The resulting four measures include Concurrent Use of Opioids and Benzodiazepines (COB), Use of Opioids at High Dosage in Persons Without Cancer (OHD), Polypharmacy: Use of Multiple Anticholinergic Medications in Older Adults (POLY-ACH), and Polypharmacy: Use of Multiple CNS-Active Medications in Older Adults (POLY-CNS). Much like IOP-LD, these are health plan level measures intended to reduce potentially inappropriate medication use, in turn leading to reduced health care resource utilization and improved patient safety. A lower rate indicates better performance for all measures included in this assessment.
An analysis of rates indicated non-normal distributions, so the Spearman correlation coefficient was used to assess the association between performance on the IOP-LD measure and the four related measures. It was hypothesized that measure scores for IOP-LD would be weakly-to-moderately correlated with measure scores for COB, POLY-ACH, and POLY-CNS included in the analysis in the positive direction. It is expected that health plans perform similarly on several quality measures that aim to reduce potentially inappropriate medication use, likely through an organizational approach to implementation of medication management programs, safety edits, physician outreach and education, and other services. However, strong associations between these measures were not expected as differences in performance across related but different metrics can still be caused by various factors (e.g., measure or population-specific nuances, health plan priorities).
Measure scores for IOP-LD and OHD were not hypothesized to be correlated due to significant differences in the characteristics of the measures’ eligible populations: the IOP-LD measure primarily captures acute opioid use while OHD primarily captures chronic opioid use. As a result, clinical considerations and intervention types may be significantly different between these two measures, and regulatory requirements also differ between initial opioid prescribing versus high-dose, longer-term opioid prescribing.
Face Validity
Through discussion and vote, the Measure Validity Panel (MVP), described in section 5.3.3, determined that the IOP-LD measure had face validity. Of the 7 MVP members who voted on the face validity of IOP-LD, 100% agreed or strongly agreed that the scores obtained from the measure as specified will provide an accurate reflection of quality and can be used to distinguish good and poor quality between contracts.
Empirical Validity
The results of the criterion validity testing are presented in the attachment by calendar year. The results are consistently statistically significant (where expected), in the expected directions, and at expected strengths.
Strengths of association are interpreted using the following scale: Very Weak (0-0.19) / Weak (0.20-0.39) / Moderate (0.40-0.59) / Strong (0.60-0.79) / Very Strong (0.80-1).(1) We note that given the typical strengths of associations seen in quality measure convergent validity testing, these interpretations may be conservative.
References:
1. T D V Swinscow. Statistics at Square One, Ninth Edition. 1997. BMJ Publishing Group. Accessed September 20, 2024. https://www.bmj.com/about-bmj/resources-readers/publications/statistics-square-one
Based upon the PQA Measure Validity Panel’s and Quality Metrics Expert Panel’s assessments, described in section 5.3.3, the IOP-LD measure has been determined to have face validity.
The correlations produced in our empirical validity analyses showed statistically significant, weak-to-moderate positive correlations of IOP-LD measure rates with rates for COB, POLY-CNS, and POLY-ACH. These correlations were in the expected (positive) direction, suggesting that health plans perform similarly on several quality measures that aim to reduce potentially inappropriate medication use, likely through the implementation of consistent medication management programs and services. Effect sizes were also consistent with our hypotheses.
Additionally, as expected, analyses revealed negligible correlations between IOP-LD and OHD, with the relationship only statistically significant in one year at a very weak effect size. While the IOP-LD measure assesses initial opioid prescribing–that is, opioid prescriptions for individuals who have not received an opioid prescription in the previous 90 days–the OHD measure includes opioid users with two or more opioid prescriptions totaling 15 or greater total days’ supply and therefore captures a high number of chronic opioid users versus opioid naïve individuals.
Furthermore, OHD assesses the proportion of such opioid users receiving an average daily dosage greater than or equal to 90 MME over a period of 90 or more days. As such, the types of interventions that may be deployed by a plan to improve performance on these measures may differ vastly, especially considering that individuals receiving opioids at high dosage are clinically dissimilar to those receiving initial opioid prescriptions and have unique risk/benefit considerations. This is also reflected in differing CMS regulatory requirements for drug utilization reviews for initial opioid prescribing for long duration versus the dispensing of high dose opioids greater than 90 MME.(1) General sensitivities around opioid tapering, along with the relative lack of available guidance on opioid tapering protocols in chronic pain, further differentiate how health plans may approach improving performance on OHD compared to IOP-LD.
As with all convergent validity testing, these analyses are subject to limitations. In particular, the options for measures to assess IOP-LD against are limited by available data; only certain measures are publicly reported for comparison to IOP-LD, and these measures are not perfect comparators. However, these findings provide reasonable empirical evidence that IOP-LD is a valid measure of health plan quality, and a valuable tool that health plans can use to improve the quality of care for their members.
References:
1. Centers for Medicare & Medicaid Services. A Prescriber’s Guide to Medicare Prescription Drug (Part D) Opioid Policies. 2024. Accessed April 18, 2025. https://www.cms.gov/files/document/mln2886155-prescribers-guide-medicare-prescription-drug-part-d-opioid-policies.pdf
Risk Adjustment
Use & Usability
Use
Health Plan
Usability
This measure is intended for retrospective, population-level analysis and is not intended to serve as a guide for individual patient care decisions. However, measured entities can use the measure to identify opportunities to decrease initial opioid prescriptions for long duration that may place patients at increased risk for long-term opioid use, misuse, overdose, and other negative outcomes.
Health plans can utilize various strategies to identify such opportunities. This may include implementing safety edits for days’ supply limits for initial opioid fills that prompt an additional safety and appropriateness review to be conducted prior to dispensing an initial opioid prescription for long duration. Federal regulations (42 CFR § 423.153(c)(2)) require that Medicare Part D plan sponsors must have “Concurrent drug utilization review systems, policies, and procedures designed to ensure that a review of the prescribed drug therapy is performed before each prescription is dispensed to an enrollee in a sponsor's Part D plan, typically at the point-of-sale or point of distribution.(1) The review must include, but not be limited to,
(i) Screening for potential drug therapy problems due to therapeutic duplication.
(ii) Age/gender-related contraindications.
(iii) Over-utilization and under-utilization.
(iv) Drug-drug interactions.
(v) Incorrect drug dosage or duration of drug therapy.
(vi) Drug-allergy contraindications.
(vii) Clinical abuse/misuse.”
Per published guidance from CMS,(2,3) “to help prevent and combat prescription opioid overuse through improved concurrent DUR [drug utilization review], sponsors are expected to implement real-time opioid safety edits at the POS [point-of-sale], including an edit to limit initial opioid prescription fills for opioid naïve beneficiaries to no more than a 7 days’ supply.”
An internal analysis conducted by CMS of Part D prescription drug event (PDE) data from 2018 to 2023 showed that the percentage of Part D claims for opioids (excluding medications used for opioid use disorder) with 7 days’ supply or less positively increased from 18.4% in 2018 to 27.7% in 2023 after the implementation of enhanced opioid safety edits at POS in 2019.(2) For the IOP-LD measure specifically, measure rates have decreased by roughly 1-2% per year in both MAPD and PDP lines of business, as shown in Section 2.4 Performance Gap.
Additionally, Medicare plan sponsors are required to establish a drug management program (DMP) for beneficiaries at risk for misuse or abuse of frequently abused drugs, and beneficiaries with potential patterns of opioid misuse or with a history of opioid-related overdose are to be included in DMPs per the established retrospective criteria codified at § 423.153(f).
Given these regulatory requirements and observed reductions in initial opioid-prescribing of long duration, there is ample evidence that health plans can implement effective strategies to improve performance on this measure.
References:
1. Centers for Medicare & Medicaid Services. 42 CFR § 423.153 Drug utilization management, quality assurance, medication therapy management (MTM) programs, drug management programs, and access to Medicare Parts A and B claims data extracts. 2025. Accessed April 18, 2025. https://www.ecfr.gov/current/title-42/chapter-IV/subchapter-B/part-423/subpart-D/section-423.153
2. Centers for Medicare & Medicaid Services. Contract Year (CY) 2025 Medicare Part D Opioid Safety Edits – Submission Instructions, Recommendations, and Reminders. 2024. Accessed April 18, 2025. https://www.cms.gov/files/document/cy-2025-opioid-safety-edit-submission-instructions.pdf
3. Centers for Medicare & Medicaid Services. Medicare Part D Opioid Safety Edit Reminders and Recommendations and Frequently Asked Questions (FAQs). 2022. Accessed April 18, 2025. https://www.cms.gov/files/document/cy-2023-opioid-safety-edit-reminders-and-recommendations.pdf
4. Centers for Medicare & Medicaid Services. Medicare and Medicaid Programs; Contract Year 2026 Policy and Technical Changes to the Medicare Advantage Program, Medicare Prescription Drug Benefit Program, Medicare Cost Plan Program, and Programs of All-Inclusive Care for the Elderly. 2024. p. 427.
PQA surveys measure licensees to understand the use of PQA measures and related needs. Across 300 responses received since 2021, none have included comments specifically related to performance, implementation concerns, or unintended consequences associated with the IOP-LD measure.
PQA also provides no-cost technical assistance to measure users and the public. Since 2022, PQA has received a total of seven technical assistance requests regarding the IOP-LD measure. Six of those requests sought clarification of the measure’s specifications; one request was related to the measure’s value sets. Each question received is reviewed for potential specification updates.
PQA is in regular contact with the program administrator for the Medicare Part D quality program (i.e., CMS), where the IOP-LD measure is in use. The CMS Part C&D team has not raised specific questions or concerns with the implementation of the IOP-LD measure within the program.
In response to feedback received through PQA technical assistance channels, PQA has made minor modifications to the measure’s specifications to improve clarity, outlined below:
--Added language to improve clarity for the Negative Medication History definition to note that for an individual to have a negative medication history, there should be no prescription claims for opioids “with a date of service” in the lookback period.
--Removed language from the Eligible Population note section, related to calculating days’ supply, that was not applicable to the denominator. The removed language was applicable only to the numerator and therefore was not removed from the numerator note.
PQA maintains measures using a transparent, systematic, consensus-based process that involves several multistakeholder panels, including the Measure Update Panel (MUP) and Quality Metrics Expert Panel (QMEP). Potential changes to measures are considered by the PQA team and discussed and voted on by the aforementioned panels. Additional refinements to the IOP-LD measure specifications were made through this process in response to updated evidence. These included adding new exclusions for individuals receiving palliative care or with cancer-related pain.
Across MAPDs and PDPs, average measure scores improved (i.e., decreased, as a lower score indicates better performance) each year from 2020 to 2022. Overall rates across MAPDs decreased from 21.0% in 2020, to 18.9% in 2021 and 18.2% in 2022. Rates among PDPs decreased from 15.7% in 2020, to 14.0% in 2021 and 12.9% and 2022.
These trends are promising and evidence that the measure is an effective tool to reduce high-risk initial opioid prescriptions. However, there is still room for improvement. Among MAPD contracts in 2022, contracts in the tenth decile had an average rate of 54.5% with a maximum of 89.6%.
There were no unexpected findings during the implementation of this measure.
Comments
Staff Preliminary Assessment
CBE #3558 Staff Preliminary Assessment
Importance
Strengths
- A clear logic model is provided, depicting the relationships between inputs (e.g., health plans, providers, and pharmacies), activities (e.g., health plans implement opioid edits, providers evaluate patients’ pain management needs, and pharmacies adhere to health plan edits), and desired outcomes (e.g., reduced number of initial opioid prescriptions with >7 days’ supply and reduced risk of long-term opioid use, misuse, and overdose). This model demonstrates how the measure's implementation will lead to the anticipated outcomes.
- The problem this measure addresses presents a significant public health concern, with drug overdoses involving opioids in the U.S. accounting for 79,358 deaths and 8.6 million Americans reporting prescription opioid misuse in 2023. Evidence suggests that the probability of long-term opioid use increases with each additional day past the third day of initiating opioid therapy.
- The measure is supported by a comprehensive literature review, including a systematic review with high evidence quality and 13 high quality empirical studies, demonstrating a clear net benefit in terms of reducing initial opioid prescriptions with >7 days’ supply.
- Data from the Part D Patient Safety Reports from calendar years 2020-2022 show a performance gap. In 2022, the decile ranges were from 5.1% to 54.5% across Medicare Advantage prescription drug plan (MAPD) contracts and from 6.4% to 19.2% across Medicare Part D prescription drug plan (PDP) contracts, indicating variation in measure performance and less than optimal performance across the target population.
- Description of patient input supports the conclusion that the measured process is meaningful with at least moderate certainty. Patient input was obtained through a Patient and Caregiver Advisory Panel (PCAP) consisting of patients, caregivers, and patient advocates, some of whom also worked as healthcare professionals.
Limitations
- Some of the evidence present used data that went as far back as 2006. For example, the developer cites a 2017 retrospective analysis of average days’ supply for opioids among Medicaid enrollees which used Medicaid claims from 2005-2014. Additionally, the developer cites a recommendation from CDC’s 2022 Clinical Practice Guideline for Prescribing Opioids for Pain which is evidence type 4 (clinical experience and observations, observational studies with important limitations, or randomized clinical trials with several major limitations) suggesting a lower level of confidence.
Rationale
- This maintenance measure meets all criteria for 'Met' due to the significance of the problem it addresses, its robust evidence base, a documented performance gap, and well-articulated logic model, making it essential for addressing opioid use, misuse, and overdose.
Closing Care Gaps
Strengths
- The developer cites the CMS Proposed Rule CMS-4208-P which describes disparities in overdose death rates by race, ethnicity, and age.
Limitations
- The analysis revealed significant differences in performance scores by sex, age, and financial need. However, these findings were from the original development of the measure, when the measure concept was tested in Medicare, Medicaid, and commercial data samples from 2014, 2016, and 2017. The developer indicates that empirical assessment of performance scores among socio-contextual variables is not feasible using data from the measure’s implementation as the measure performance data made available by CMS do not include beneficiary-level demographic information. The developer indicates that they explored options to assess this domain using recent data but were unable to provide results. However, the developer did note individual health plans can use their data internally to stratify by recommended variables and identify interventions that seek to reduce disparities.
Rationale
- While the measure attempts to assess gaps in care for opioid overdoses, the developer indicated that measure performance data made available by CMS do not include beneficiary-level demographic information which would enable them to assess differences in performance scores across sociocontextual variables. The developer did provide findings from analyses conducted at the original development of the measure which differences across several populations. This limits the ability to provide a comprehensive understanding of the differences in performance across different populations.
Feasibility Assessment
Strengths
- All required data elements are routinely generated during care delivery, and required elements are available from digital or electronic sources.
- The developer indicated there have been no changes to the measure since initial endorsement that impact the measure’s feasibility.
- The developer stated that no feasibility issues were found requiring adjustment of the final measure’s specifications.
- The developer described the costs and burden associated with data collection and data entry, validation, and analysis. They indicated that that measured entities are not anticipated to experience significant costs or burdens associated with implementation; however, there may be costs associated with acquiring other relevant data and analytics tools. They noted that Standalone Part D prescription drug plans (PDPs) experience delays related to not having timely access to medical claims data; however, CMS has recently developed the AB2D Application Programming Interface (API) to help address this issue.
- The developer described how all required data elements can be collected without risk to patient confidentiality as the measure is at the population level and does not require the collection or reporting of any patient-identifying information. Additionally, the measure specifications indicated that an organization should not report a measure rate when the denominator includes fewer than 30 individuals.
- Any fees, licensing, or other requirements to use any aspect of the measure (e.g., value/code set, risk model, programming code, algorithm) are clearly described and justified
Limitations
- None identified.
Rationale
- This maintenance measure meets all criteria for 'Met' due to its well-documented feasibility assessment, clear and implementable data collection strategy and transparent handling of patient confidentiality, burden, licensing, and fees. These factors collectively ensure that the measure can be implemented effectively and sustainably in a real-world healthcare setting.
Scientific Acceptability
Strengths
- The developer explains the signal-to-noise methodology they used to estimate accountable entity-level reliability.
- Data used for testing were collected in calendar years 2020-2022, all within the last five years.
- The developer reported reliability above the threshold of 0.6 for every MAPD contract for each year tested and for at least 90% of PDP contracts for each year.
Limitations
- None identified.
Rationale
- The developer reported accountable entity-level reliability based on data collected within the last three to five years. Reported signal-to-noise reliability estimates for 100% and at least 90% of entities were above the threshold of 0.6 for MAPD and PDP contracts, respectively.
Strengths
- The developer provides an Importance Table, Logic Model, and Face Validity (N=7 with consensus), providing a plausible causal association between the entity response to the measure and the measure focus. Empirical support for ruling out confounders includes adequate reliability, no risk-adjustment (process), and a correlation with a related process measures with (and without) construct overlap (Concurrent Use of Opioids and Benzodiazepines [COB], Polypharmacy: Use of Multiple Anticholinergic Medications in Older Adults , Polypharmacy: Use of Multiple CNS-Active Medications in Older Adults [POLY-CNS] [WITH], Use of Opioids at High Dosage in Persons Without Cancer [WITHOUT]). The developer provides a justification for the construct overlap, and also for the absence of overlap. Empirical support for ruling-in responsible mechanisms includes several empirical studies and reports (e.g., Point-of-Sale Safety Edits, Concurrent Drug Utilization Review [DUR], Drug Management Programs [DMPs], Clinical Guidelines [e.g., CDC 2022 Guidelines], Educational Outreach and Use of Patient Advisory Panels).
Limitations
- Opportunities to strengthen the inference of validity, that do not impact the domain rating, include:
- Residual risk for confounders includes poor to fair correlation that cannot rule out the influence of confounders. Therefore, the explanation is not a justification for the magnitude of the correlation (r=0.25, 0.22 (COB); r=0.37, 0.33 (POLY-ACH), r=0.47, 0.49 (POLY-CNS)) and leaves 50-75% of the causal factors for the risk-adjusted performance unexplained.
- Residual risk for confounders not ruled out includes: Clinical scenarios involving complex or severe pain, patient prior pain management experiences, substance use history, or expectations.
- There is no direct empirical support for whether the responsible mechanisms account for the association between the entity response to the measure and the measure focus. Residual risk for a responsible mechanism includes the potential counter-acting mechanisms (Regulatory Guidance and Enforcement [CMS, FDA]).
Rationale
- The measure developer provides some support for the causal claim that the entity response to the measure is causally related to the measure focus. The developer provides empirical support for ruling out confounders (always with some residual risk of unstated or unexamined confounders) and for ruling in responsible mechanisms (always with some residual risk that the explicit mechanisms are only partially responsible for the measure focus).
Use and Usability
Strengths
- The measure is currently used in the CMS Medicare Part D Display Page.The developer provides a summary of how accountable entities can use the measure results to improve performance. Specifically, measured entities can use the measure to identify opportunities to minimize the duration of initial opioid prescriptions that ultimately reduce patients’ risk for long-term opioid use, misuse, and overdose.
- The developer surveys measure licensees to understand the use of their measures and related needs. They also receive feedback through their no-cost technical assistance to measure users and the public. The developer stays in contact with the CMS program administrator for the Medicare Part D program. The developer noted that only clarification questions on the measure specifications have been received.
- The developer noted that updates to the measure specifications were made to address feedback received, which included minor language modifications for clarity.
- The developer reports improvements in performance from 2020 to 2022, in which the overall measure scores decreased from 21.0% in 2020, to 18.9% in 2021 and 18.2% in 2022 across MAPDs and from 15.7% in 2020, to 14.0% in 2021 and 12.9% and 2022 across PDPs, which supports the argument that this measure is usable.
The developer reported no unexpected findings.
Limitations
- None identified.
Rationale
- For maintenance endorsement, the measure is actively used in at least one accountability application, with a systematic feedback approach that allows for continuous updates based on stakeholder feedback. The measure also demonstrates a positive trend in performance results, affirming its ongoing usability. The developer reported no unexpected findings.
Public Comments
Initial Opioid Prescribing for Long Duration (IOP-LD)
I am writing in support of the PQA measure, Initial Opioid Prescribing for Long Duration (IOP-LD) (CBE #3558), which is under review for maintenance.
Prescription opioids remain a major contributor to the public health crisis that has affected the social and economic welfare of millions of Americans. Opioid misuse, addiction, and overdose have remained prevalent in recent years. A wide body of evidence has shown that initial opioid exposure for a long duration is associated with a greater likelihood for high-risk and long-term opioid use, misuse, overdose, and other negative outcomes. The PQA Initial Opioid Prescribing for Long Duration (IOP-LD) measure evaluates initial opioid prescriptions for greater than 7 days’ supply, which are associated with increased risk of these outcomes.
The 2022 Clinical Practice Guideline for Prescribing Opioids for Pain recommends that when opioids are needed for acute pain, clinicians should prescribe no greater quantity than needed for the expected duration of pain severe enough to require opioids. This guideline recommendation, and the IOP-LD measure’s threshold of a 7 days’ supply, is supported by extensive epidemiological evidence. To highlight, a 2018 study by Shah et al. found that the probability of long-term opioid use increased with each additional day supplied past the third day when initiating opioid therapy; the probability of long-term use was more than twice as high for individuals who received greater than 7 days’ supply. (1)
Using the IOP-LD measure, health plans can identify early opportunities to decrease initial opioid prescriptions for long duration that may place patients at increased risk for negative outcomes. The measure fills a continued, critical need in opioid measurement and seeks to uncover actionable opportunities to reduce conversion to chronic opioid use and misuse before it occurs.
Because the IOP-LD measure only captures initial opioid prescriptions in individuals with no prescription claims for opioids in the preceding 90 days, and does not penalize subsequent prescriptions for ongoing pain, it is not anticipated to result in unintended consequences related to access, discontinuation, or abrupt tapering in patients currently undergoing long-term opioid therapy. Additionally, the measure excludes individuals in hospice and those with cancer, sickle cell disease, or receiving cancer-related pain treatment.
Initial Opioid Prescribing for Long Duration is a feasible, actionable, and evidence-based measure that can improve patient safety.
Initial Opioid Prescribing for Long Duration
see attached for commnets
IOP-LD Public Comment Steward Response
PQA appreciates the American Medical Association’s (AMA) comments on the Initial Opioid Prescribing for Long Duration (IOP-LD) measure.
IOP-LD is a health plan quality measure intended for population level use and is not intended to guide individual care decisions. The expected rate for the measure is not 0%, as clinical situations may arise, albeit uncommonly, in which greater than 7 days’ supply for an initial prescription is warranted. The IOP-LD measure does not penalize health plans for subsequent opioid prescriptions following the opioid initiation period. Instead, for patients with no opioids during the lookback period whose pain is severe enough to require more than seven days’ supply of opioids, the measure encourages appropriate evaluation and follow-up care.
Below, we provide additional clarity on various elements of the measure highlighted in the AMA’s comments.
PQA notes that the AMA’s comments include statements connecting the IOP-LD measure to opioid prescriptions broadly, as well as statements connecting the IOP-LD measure to opioid dosage and quantity.
PQA clarifies that the IOP-LD measure focuses on initial opioid prescriptions and does not evaluate the quality of non-initial opioid prescriptions, including chronic opioid therapy. Additionally, the IOP-LD measure focuses on the days’ supply of initial opioid prescriptions and does not evaluate opioid dosage in any way.
The AMA suggests that the seven days’ supply threshold used in the IOP-LD measure is based on “arbitrary, low-quality evidence”. This statement stands in stark contrast to the evaluation completed the National Quality Forum Patient Safety Standing Committee, whose review of the IOP-LD measure during original endorsement resulted in unanimous passing votes on the “Evidence” criterion.
PQA notes that Battelle staff have reached a similar conclusion in their Preliminary Analysis, noting that the IOP-LD measure is “supported by a comprehensive literature review including a systematic review with high evidence quality and 13 high quality empirical studies, demonstrating a clear net benefit in terms of reducing initial opioid prescriptions with >7 days’ supply.”
A broad body of evidence from many researchers over a significant amount of time has demonstrated the relationship between the duration of initial opioid prescriptions and subsequent risks for patients. This body of evidence and the design of this measure were carefully reviewed by a technical expert panel during development of the measure, including a variety of pain medicine and opioid experts, accountable entities, persons with lived experience, and other stakeholders. Measure maintenance follows a similar evidence- and consensus-based approach.
PQA disagrees with the AMA’s comments that the IOP-LD measure is misaligned with CDC guidelines. Instead, PQA clarifies that the IOP-LD measure is well-supported by the 2022 CDC Guideline. The 2022 CDC Guideline states:
While a specific threshold is not included, the body of evidence provided in the measure submission (much of which is cited in the 2022 CDC Guideline itself) strongly supports the relationship between initial prescriptions for greater than 7 days’ supply and subsequent risks for patients. The 2022 CDC Guideline Implementation Considerations provide additional clarifications supporting the design of the IOP-LD measure (all statements verbatim):
When the diagnosis and severity of acute pain warrant use of opioids, clinicians should prescribe no greater quantity than needed for the expected duration of pain severe enough to require opioids. For many common causes of nontraumatic, nonsurgical pain, when opioids are needed, a few days or less are often sufficient, and shorter courses can minimize the need to taper opioids to prevent withdrawal symptoms at the end of a course of opioids. However, durations should be individualized to the patient’s clinical circumstances.
Clinicians should generally avoid prescribing additional opioids to patients just in case pain continues longer than expected.
For postoperative pain related to major surgery, procedure-specific opioid prescribing recommendations are available with ranges for amounts of opioids needed (on the basis of actual use and refills and on consensus).
In particular, PQA calls attention to statement (4). One of the core facets of the IOP-LD measure is a focus on care coordination and timely follow-up. Follow-up opioid prescriptions after the initiation period do not count towards the numerator of the measure. The measure does not penalize subsequent opioid prescriptions that occur following the opioid initiation period. Instead, it promotes appropriate follow-up for patients with pain severe enough to require greater than 7 days’ supply for an opioid in an initial prescription. For these individuals, high-quality care means having their pain properly assessed and a care plan in place (which may or may not involve continued opioid therapy), rather than providing patients with an extensive days’ supply in the first place, which evidence demonstrates is associated with substantial risks.
With respect to (3), the literature does not suggest that post-surgical patients are immune to the risks associated with initial opioid prescribing for greater than 7 days. In a 2022 retrospective cohort study, Young et al. (Young JC, Dasgupta N, Chidgey BA, et al. Impacts of Initial Prescription Length and Prescribing Limits on Risk of Prolonged Postsurgical Opioid Use. Med Care. Jan 1 2022;60(1):75-82.) showed that the risk of prolonged opioid use increased monotonically with the length of initial opioid prescriptions in a population of 1,060,596 opioid naïve adults undergoing invasive surgery. Additionally, in a 2018 retrospective cohort study, Brat et al. (Brat GA, Agniel D, Beam A, et al. Postsurgical prescriptions for opioid naive patients and association with overdose and misuse: retrospective cohort study. BMJ. 2018;360:j5790) found that duration of use was mostly strongly associated with opioid misuse in an analysis of 568,612 surgical claims.
The duration of 7 days used by the IOP-LD measure is consistent with numerous guidelines and resources for post-surgical opioid prescribing, such as the evidence-based Michigan OPEN Adult Opioid Prescribing Guidelines (https://michigan-open.org/) and the Johns Hopkins expert consensus-based Opioid-Prescribing Guidelines for Common Surgical Procedures (Overton HN, et. al. Opioid-Prescribing Guidelines for Common Surgical Procedures: An Expert Panel Consensus. J Am Coll Surg. 2018 Oct;227(4):411-418). Especially important, the Johns Hopkins guidelines note that “Overall, patients who had the procedures voted for lower opioid amounts than surgeons who performed them.”
PQA welcomes additional evidence on this subject for review and evaluation.
PQA agrees that the application of rigid opioid prescribing limits can result in patient access concerns and other intended consequences. However, PQA emphasizes that IOP-LD is a retrospective, population-level quality measure and does not represent an absolute prescribing limit.
The IOP-LD measure is also designed specifically to minimize patient access concerns and other unintended consequences. For patients with no opioids during the lookback period whose pain is severe enough to require more intensive or longer duration of pain management with opioids, the measure encourages appropriate evaluation and follow-up care.
PQA monitors for unintended consequences carefully across multiple channels. For example, PQA receives annual reports from entities that license and use PQA measures on an annual basis, which provides the opportunity for measure users to provide feedback. PQA plans to refine this reporting for the next cycle to more explicitly request information on any unintended consequences.
PQA also maintains a close collaborative relationship with quality programs that use the IOP-LD measure. For example, PQA regularly meets with the team responsible for implementation of the IOP-LD measure in the Medicare Part D to discuss operationalization of the measure and feedback from both the program administrators and measure users.
Across these channels, PQA has not received comments indicating observed unintended consequences. However, PQA remains committed to ongoing monitoring to ensure its measures function as intended.
The AMA cites concerns that populations that are excluded from the measure may face unintended consequences, noting that “Nearly all inappropriate prescribing restriction laws and policies, however, use similar language, but all generally fail to ensure protection for all in these vulnerable populations.”
PQA reiterates that the IOP-LD measure is not a restrictive law or policy, but rather a population-level retrospective quality measure. The calculation of the IOP-LD measure is clearly defined by the measure specifications, which ensures that excluded populations (including individuals with cancer, cancer-related pain, sickle cell disease, receiving palliative care, or in hospice) are not included in the measure rate.
PQA clarifies that the IOP-LD measure does not include any definition for the term “opioid naïve.”
The IOP-LD measure uses a 90-day lookback period to establish a negative medication history used to identify subsequent initial opioid prescriptions. PQA agrees that lookback periods to define initial opioid prescriptions are variably defined in the literature, with some studies using 60-days to as long as twelve months. Notably, for the related health plan safety edits in Medicare Part D, lookback periods typically range from 60 to 120 days.
PQA tested 30, 45, 90, and 120-day lookbacks in the measure and discussed this extensively with subject matter experts and our technical expert panels. Ultimately, the technical expert panel agreed that a 30-day interval was too conservative and oversensitive in identifying prescriptions as initial, and there were inherently tradeoffs between sensitivity and specificity at each of the other lookback periods. The effects on measure rates of using various thresholds were generally minor (1%-2%).
PQA clarifies that the IOP-LD measure does NOT include medications prescribed to treat opioid use disorder (OUD). Although the measure includes methadone prescribed for pain identified using outpatient prescription claims, methadone used for treating OUD is, by law, only dispensed through a federally certified opioid treatment program and is not included in the measure. Additionally, no buprenorphine products are included in the measure.
The inclusion or exclusion of methadone was discussed during the development process. Ultimately, stakeholders preferred to err on the side of patient safety by including initial prescriptions for methadone (identified via prescription claims and thus used for pain) in the measure, as opposed to excluding due to theoretical concerns about methadone used for opioid use disorder (which would not be paid under a prescription drug benefit and thus would not be captured in the measure). Additionally, historical PQA analyses demonstrated that outpatient prescription claims for methadone made up less than 1% of opioid claims included in the IOP-LD measure.
As noted in the scientific acceptability section of the measure submission and within Battelle’s preliminary assessment, IOP-LD measure reliability exceeded the threshold of 0.6 for every MAPD contract and at least 90% of PDP contracts for every year tested, which represents exceptional reliability.
With respect to a case minimum, the PQA provides guidance in the PQA Measure Manual stating, “If the denominator used to calculate a measure is <30, the organization should note in performance reports an insufficient sample size for measurement purposes on that particular measure and should not report the rate.” Consistent with this guidance, reliability testing only included entities with at least 30 patients in the denominator as noted in the measure submission.
PQA welcomes the opportunity to better understand the AMA’s concerns related to IOP-LD measure reliability.
Initial Opioid Prescribing for Long Duration (IOP-LD)
UnitedHealthcare (UHC) remains deeply concerned that the Initial Opioid Prescribing for Long Duration (IOP-LD) measure will fail to effectively control opioid overutilization. Instead, it risks creating unintended consequences. The PQM Pre-Rulemaking Measure Review 2023 Recommendations Report echoes many of UHC’s concerns specifically regarding the adequacy of evidence, alignment with current clinical guidelines for opioid prescribing, whether additional exclusions are needed, and unintended consequences of using the measure in quality performance measurement. For example, the current measure specification does not support critical exclusions, such as major surgery and trauma, and may not be appropriate for Special Needs Plan (SNP) populations.
Additionally, any measure aimed at minimizing opioid misuse must be carefully structured to avoid restricting access to medically necessary prescriptions. IOP-LD, in its current iteration, does not adequately safeguard against this risk. Specifically:
It lacks robust clinical exclusions through medical diagnosis for exclusion criteria and instead refers to the Common Working File which can be incomplete.
Its lookback period of only 90 days prior or during the measurement year may be too short to fully account for the clinical history necessary to evaluate a new opioid prescription appropriately.
It is unclear how the negative lookback of 90 days will apply to beneficiaries new to a plan to ensure appropriate targeting for the measure.
Lastly, to eliminate biases in measurement, IOP-LD should exclude beneficiaries from the denominator when it is determined more than seven days of therapy is medically necessary through pharmacist point-of-sale edit overrides or a provider supporting statement. These allowances are currently permitted by CMS, and CMS has indicated that safety edits such as the 7-day supply limit should not be implemented as prescribing limits. CMS could use Part D reporting data to determine beneficiaries who should be excluded from the measure on this basis.
IOP-LD Public Comment Steward Response
PQA appreciates UnitedHealthcare’s comments on the IOP-LD measure.
The IOP-LD measure is not designed to prevent prescribing of opioids, but rather to ensure that when they are prescribed, the patient is placed at the lowest risk possible. The IOP-LD measure does not penalize health plans for subsequent opioid prescriptions following the opioid initiation period. Instead, for patients with no opioids during the lookback period whose pain is severe enough to require more than seven days’ supply of opioids, the measure encourages appropriate evaluation and follow-up care.
Regarding a potential exclusion for major surgery, the literature does not suggest that post-surgical patients are immune to the risks associated with initial opioid prescribing for greater than 7 days. In a 2022 retrospective cohort study, Young et al. (Young JC, Dasgupta N, Chidgey BA, et al. Impacts of Initial Prescription Length and Prescribing Limits on Risk of Prolonged Postsurgical Opioid Use. Med Care. Jan 1 2022;60(1):75-82.) showed that the risk of prolonged opioid use increased monotonically with the length of initial opioid prescriptions in a population of 1,060,596 opioid naïve adults undergoing invasive surgery. Additionally, in a 2018 retrospective cohort study, Brat et al. (Brat GA, Agniel D, Beam A, et al. Postsurgical prescriptions for opioid naive patients and association with overdose and misuse: retrospective cohort study. BMJ. 2018;360:j5790) found that duration of use was mostly strongly associated with opioid misuse in an analysis of 568,612 surgical claims.
The duration of 7 days used by the IOP-LD measure is consistent with numerous guidelines and resources for post-surgical opioid prescribing, such as the evidence-based Michigan OPEN Adult Opioid Prescribing Guidelines (https://michigan-open.org/) and the Johns Hopkins expert consensus-based Opioid-Prescribing Guidelines for Common Surgical Procedures (Overton HN, et. al. Opioids After Surgery Workgroup. Opioid-Prescribing Guidelines for Common Surgical Procedures: An Expert Panel Consensus. J Am Coll Surg. 2018 Oct;227(4):411-418). Especially important, the Johns Hopkins guidelines note that “Overall, patients who had the procedures voted for lower opioid amounts than surgeons who performed them.” However, PQA welcomes additional evidence on this subject for review and evaluation.
Regarding Special Needs Plans (SNP) populations, PQA is currently exploring the feasibility and appropriateness of excluding individuals in long-term care, which would potentially apply to individuals enrolled in an Institutional Special Needs Plan (I-SNP). That potential change would be considered through PQA’s systematic, transparent, and consensus-based process involving several multistakeholder panels composed of clinical and measurement science experts.
The IOP-LD measure includes several exclusions which are captured using ICD-10 codes present on medical claims. PQA specifications do not include program-specific guidance on the specific files that should be queried for applicable ICD-10 codes.
The IOP-LD measure uses a 90-day lookback period to establish a negative medication history used to identify subsequent initial opioid prescriptions. PQA agrees that lookback periods to define initial opioid prescriptions are variably defined in the literature, with some studies using 60-days to as long as twelve months. Notably, for the related health plan opioid safety edits in Medicare Part D, lookback periods typically range from 60 to 120 days.
PQA tested 30, 45, 90, and 120-day lookbacks in the measure and discussed this extensively with subject matter experts and our technical expert panels. Ultimately, group agreed that a 30-day interval was too conservative and oversensitive in identifying prescriptions as initial, and there were inherently tradeoffs between sensitivity and specificity at each of the other lookback periods. The effects on measure rates of using various thresholds were generally minor (1%-2%).
Regarding beneficiaries that are new to a plan, the IOP-LD measure requires that an individual be continuously enrolled in a plan for the entire measurement year (January 1 through December 31) and the 90 days prior to the index prescription start date (IPSD), defined as the earliest date of service for an opioid medication during the measurement year, for inclusion in the measure denominator. If an individual is not continuously enrolled in the 90 days prior to the IPSD, it is not possible to determine if they are initiating opioid therapy. Therefore, individuals without available lookback data, e.g., those who are newly enrolled in plans who receive an index opioid prescription without available data for the preceding 90 days, are not included in the IOP-LD measure.
IOP-LD is a quality measure intended for population level use and is not intended to guide individual care decisions. The expected rate for the measure is not 0%, as clinical situations may arise, albeit uncommonly, in which greater than 7 days’ supply for an initial prescription is warranted. The IOP-LD measure does not represent a 7-day supply prescribing limit.
As UHC notes, the safety edits in place via Part D allow health plans, pharmacies, and prescribers to override 7-day limits in clinically appropriate situations. This quality measure is separate from the safety edits and serves as a valuable, complementary tool to continue to monitor the quality of initial opioid prescribing.