When this measure comes back for maintenance, the committee would like to see:
- Explore potential updates to the numerator criteria (e.g., follow-up window, relapse patients, patients <18 years of age, and pharmacotherapy/prescription at the time of discharge); and
- Explore the usability of the measure with the accountable entity (i.e., demonstrating how states can use the measure to improve patient experience of continuity) and expanding the logic model to illustrate areas of improvement.
The Continuity of Care After Inpatient or Residential Treatment for Substance Use Disorder measure evaluates the percentage of discharges from inpatient or residential treatment for diagnoses of substance use disorders (SUD) among Medicaid or Medicare-Medicaid beneficiaries, aged 18 years and older, which were followed by a treatment service for SUD.
Measure Specs
- General Information(active tab)
- Numerator
- Denominator
- Exclusions
- Measure Calculation
- Supplemental Attachment
- Point of Contact
General Information
Continuity of care is related to improve health and life outcomes, therefore a quality measure to target extra efforts to engage individuals less likely to have continuity of care is expected to yield better care for beneficiaries with SUD. Continuity after inpatient or residential treatment has been found to be generally low and the variation in continuity rates suggests that there is substantial opportunity for improvement.
While other measures evaluate continuity of care after inpatient or residential substance use treatment, CBE #3453 varies in timing of continuity of care, diagnoses in the continuity of care visit, and the type of practitioners providing follow-up services. In addition, there are typically fewer quality measures for Medicaid and high rates of substance use for this population.
CBE #3453 uses administrative claims or encounter data. For measure testing the data source is the Transformed Medicaid Statistical Information System (T-MSIS), which contains beneficiaries, service utilization, administrative claims, and expenditure data for the Medicaid population, including those covered through both fee-for-service and managed care payers.
Numerator
Discharges from inpatient or residential treatment settings that were followed by:
- An outpatient visit, intensive outpatient encounter, or partial hospitalization with a primary or secondary SUD diagnosis on the day after discharge through day 7 or 14;
- A telehealth encounter for SUD on the day after discharge through day 7 or 14;
- Pharmacotherapy (filling a prescription or being administered or dispensed a medication) on day of discharge through day 7 or 14; or
- Residential admissions on day 3 through day 7 or day 14 (for inpatient discharges only).
CBE #3453 calculates the percentage of discharges from inpatient or residential treatment for substance use disorder (SUD) for Medicaid beneficiaries, ages 18 and older, which were followed by a treatment service for SUD. The numerator is the number of discharges from inpatient or residential treatment settings that were followed by an outpatient visit, intensive outpatient encounter, or partial hospitalization with a primary or secondary SUD diagnosis on the day after discharge through day 7 or 14; telehealth encounter for SUD on the day after discharge through day 7 or 14; pharmacotherapy (filling a prescription or being administered or dispensed a medication) on day of discharge through day 7 or 14; or residential admissions (for inpatient discharges only) on day 3 through day 7 or day 14. The measure will report two rates, continuity of care within 7 days and within 14 days after discharge. If an overdose diagnosis code appears on the same outpatient or inpatient claim that is being viewed as follow-up, that claim does not qualify as follow up.
Denominator
Discharges from inpatient or residential treatment settings with a primary diagnosis of SUD by Medicaid or Medicare-Medicaid beneficiaries, aged 18 years and older, that occurred between January 1 and December 15 of the measurement year. Beneficiaries must be enrolled in Medicaid during the month of discharge from inpatient or residential treatment and the following month.
The CBE #3453 measure data is reported annually across 12 months. The denominator is discharges from inpatient or residential treatment settings with a primary diagnosis of SUD by Medicaid or Medicare-Medicaid beneficiaries, aged 18 years and older, that occurred between January 1 and December 15 of the measurement year. Beneficiaries must be enrolled in Medicaid during the month of discharge from inpatient or residential treatment and the following month.
Exclusions
Denominator exclusions include discharges with hospice services during the measurement year and both the initial discharge and the admission/direct transfer discharge if the admission/direct transfer discharge occurs after December 15 of the measurement year. Discharges followed by admission or direct transfer to any inpatient (regardless of diagnosis) or SUD residential treatment setting within 7- or 14-day continuity of care period are also excluded. Transfer, hospitalization, or admission to inpatient or SUD residential treatment within 7 or 14 days after discharge may prevent a continuity of care visit from taking place. An exception is admission to residential treatment following discharge from inpatient treatment; these admissions are not excluded, because continuity into residential treatment after inpatient treatment is considered appropriate treatment.
To calculate denominator exclusions:
- Exclude discharges for patients who receive hospice services during the measurement year.
- Exclude discharges after December 15 of the measurement year.
- Exclude discharges followed by admission or direct transfer to an inpatient or SUD residential treatment setting within the 7- or 14-day continuity of care period regardless of the primary diagnosis (with exception of admission to residential treatment following discharge from inpatient treatment).
- Exclude episodes that do not include at least one claim with primary diagnosis of SUD.
The denominator for the 7- and 14-day continuity of care rates will differ because of the different exclusions based on transfer or admission to a hospital or residential treatment for 7 versus 14 days. For example, a beneficiary admitted to a residential setting on day 10 after discharge will be excluded from the 7-day rate but not from the 14-day rate.
Measure Calculation
Please see measure score calculation diagram attachment.
States have the option to stratify by location of the inpatient or residential discharge. To do this stratification:
- Calculate the inpatient continuity of care rate by dividing the number of discharges with evidence of a qualifying continuity of care visit or pharmacotherapy event by the denominator (after exclusions), only including discharges with a treatment location assigned as residential. Calculate the inpatient continuity rates separately for 7 and 14 days after discharge.
- Calculate the residential continuity of care rate by dividing the number of discharges with evidence of a qualifying continuity of care visit or pharmacotherapy event by the denominator (after exclusions), only including discharges with a treatment location assigned as residential. Calculate the residential continuity rates separately for 7 and 14 days after discharge.
- For episodes assigned to a mix of both settings, for the purposes of stratification, assign the episode to one setting based on the last setting of the episode.
Not applicable. CBE #3453 measure does not involve sampling.
Supplemental Attachment
Point of Contact
Not applicable.
United States
Importance
Evidence
Continuity of care helps to sustain the gains attained in initial treatment and to prevent relapses. Individuals who are at an increased risk of relapse, either due to low social support or motivation, may particularly benefit from continuing care following discharge (McKay, 2021). Half of the individuals who complete SUD treatment relapse within a year of discharge and are not connected to aftercare services (Stanojlovic & Davidson, 2021). Low treatment rates are associated with increased relapse, treatment readmission, and mortality (Stanojlovic & Davidson, 2021). In contrast, continuity of care after discharge from inpatient or residential SUD treatment is linked to reduced substance use (McKay, 2021), fewer readmissions (Kinard, Brennan-Cook, Johnson, Long, Yeatts, & Halpern, 2024), less criminal justice involvement (RTI International & National Governors Association, 2021), lower mortality (Stanojlovic & Davidson, 2021), improved housing and employment (Stanojlovic & Davidson, 2021), and a decrease in mental health symptoms (Stanojlovic & Davidson, 2021). Use of a performance measure to identify patients who are less likely to have continuity of care or have shorter stays in follow-up care is critical in targeting extra efforts in engaging these patients (Harris, McKellar, Moos, Schaefer, & Cronkite, 2006).
References:
Harris, A. H., McKellar, J. D., Moos, R. H., Schaefer, J. A., & Cronkite, R. C. (2006). Predictors of engagement in continuing care following residential substance use disorder treatment. Drug Alcohol Depend, 84(1), 93-101. doi: 10.1016/j.drugalcdep.2005.12.010
Kinard, T., Brennan-Cook, J., Johnson, S., Long, A., Yeatts, J., & Halpern, D. (2024). Effective Care Transitions: Reducing Readmissions to Improve Patient Care and Outcomes. Professional case management, 29(2), 54–62. https://doi.org/10.1097/NCM.0000000000000687
McKay J. R. (2021). Impact of Continuing Care on Recovery From Substance Use Disorder. Alcohol research : current reviews, 41(1), 01. https://doi.org/10.35946/arcr.v41.1.01
RTI International & National Governors Association. (2021). Community Supervision and Treatment of Individuals With Substance Use Disorder - Challenges and Opportunities for Governors and State Officials. Bureau of Justice Assistance Comprehensive Opioid, Stimulant, and Substance Abuse Program. Retrieved from: https://www.nga.org/wp-content/uploads/2021/06/RTI_Community_Supervision_and_Treatment_of_Individuals_With_Substance_Use_Disorder.pdf
Stanojlović, M., & Davidson, L. (2021). Targeting the Barriers in the Substance Use Disorder Continuum of Care With Peer Recovery Support. Substance abuse : research and treatment, 15, 1178221820976988. https://doi.org/10.1177/1178221820976988
Measure Impact
Forty to sixty percent of individuals who complete inpatient or residential substance use treatment experience relapse (National Institute on Drug Abuse, 2020). Continuing care is an important part of treating SUDs and individuals at high risk of relapse may benefit more from continuing care compared to individuals at low risk (McKay, 2021). Benefits of continuity of care for substance use include improved mental health, improved housing and employment, and less criminal justice involvement (Stanojlovic & Davidson, 2021; RTI International & National Governors Association, 2021).
References:
McKay J. R. (2021). Impact of Continuing Care on Recovery From Substance Use Disorder. Alcohol research: Current reviews, 41(1), 01. https://doi.org/10.35946/arcr.v41.1.01
National Institute on Drug Abuse. (2020). Treatment and Recovery. Drugs, brains, and behavior: the science of addiction. Retrieved from Treatment and Recovery | National Institute on Drug Abuse (NIDA).
RTI International & National Governors Association. (2021). Community Supervision and Treatment of Individuals With Substance Use Disorder - Challenges and Opportunities for Governors and State Officials. Bureau of Justice Assistance Comprehensive Opioid, Stimulant, and Substance Abuse Program. Retrieved from https://www.nga.org/wp-content/uploads/2021/06/RTI_Community_Supervision_and_Treatment_of_Individuals_With_Substance_Use_Disorder.pdf
Stanojlović, M., & Davidson, L. (2021). Targeting the Barriers in the Substance Use Disorder Continuum of Care With Peer Recovery Support. Substance Abuse: Research and treatment, 15, 1178221820976988. https://doi.org/10.1177/1178221820976988
Performance Gap
The distribution of performance scores for CBE #3453 are presented in Exhibit 1, within the performance-gap attachment. Scores demonstrate room for improvement with median scores of 30.8 percent for the 7-day rate and 37.9 percent for the 14-day rate.
Exhibit 2, within the performance-gap attachment, examines performance scores by several beneficiary characteristics, including age, sex, race, ethnicity, education level, language and living arrangement (lives alone or with someone else). Chi-square and probability were calculated to determine whether differences in performance scores based on these characteristics were statistically significant.
Performance score differences in all categories except for sex (age, race and dual eligibility status) were statistically significant demonstrating disparities in treatment based on these traits. Performance scores were lowest for beneficiaries aged 65 and older (7-day rate of 16.7 percent and 14-day rate of 20.1 percent) and those who were dually-eligible for Medicaid and Medicare benefits (7-day rate of 23.6 percent versus 39.1 percent for Medicaid-only beneficiaries and 14-day rate of 27.0 percent versus 42.7 percent for Medicaid-only beneficiaries).
Equity
Equity
As shown in Exhibit 2, within the performance-gap attachment, some potential social risk factors were examined to identify performance gaps. These factors include biological sex, race, age band, and dual eligibility status. Statistically significant differences in performance have been identified which demonstrate an opportunity for improving health equity based on these risk factors.
Feasibility
Feasibility
CBE #3453 was assessed via qualitative survey of a multi-stakeholder panel. Results of the feasibility assessment, as captured in two survey questions, indicate that CBE #3453 does not have any data collection challenges and the measure is minimally burdensome to report.
In general, there are no concerns with capturing data for this measure using data elements defined in the specifications. All respondents indicated No or Not Sure/Do Not Know when asked about challenges associated with data collection and reporting. These findings indicate general support for data collection feasibility. Burden of reporting was also not identified as a concern for use of CBE #3453, with all respondents stating either Yes or Not Sure/Do Not Know when asked about undue burden associated with implementation. These findings suggest that the measure is likely minimally burdensome to report, and feasibility is not a concern.
Results from the qualitative survey related to measure feasibility for CBE #3453 appear in Exhibit 3 and Exhibit 4 (within the supplemental attachment).
No changes were made to the final measure specifications in response to the feasibility assessment. There was high agreement that the measure is likely minimally burdensome to report.
Proprietary Information
Scientific Acceptability
Testing Data
As described above, CBE #3453 uses administrative claims or encounter data and pharmacy claims. For measure testing, the data source is the Transformed Medicaid Statistical Information System (T-MSIS) which contains part beneficiary, service utilization, administrative claims, and expenditure data for the Medicaid population, including those covered through both fee-for-service and managed care payers. The measurement period for scientific acceptability testing was calendar year 2021.
The same data were used for all aspects of testing.
For 49 states (see note below Exhibit 5) and the District of Columbia, there were 764,497 episodes of inpatient or residential treatment for SUD among eligible Medicaid beneficiaries in the measurement year of 2021. As shown in Exhibit 5, within the supplemental attachment, denominator counts ranged from 66 to 97,231 with a median of 5,519.
More than half (59.8 percent) of the denominator were beneficiaries between 25 and 44 years of age, and approximately 67.8 percent of the denominator were male beneficiaries. White, non-Hispanic beneficiaries accounted for approximately 56.3 percent of the denominator, followed by other or multi-racial groups (approximately 18.1 percent), and Black, non-Hispanic beneficiaries (approximately 16.2 percent). About 9.4 percent of the denominator were beneficiaries who were Hispanic of any race. More information is presented in Exhibit 6 (within the supplemental attachment).
Reliability
Reliability was calculated in accordance with the methods described in The Reliability of Provider Profiling: A Tutorial (2009). This approach calculates the ability of the measure to distinguish between the performances of different measured entities. Specifically, the testing calculated the signal-to-noise ratio for each entity (in this case, state or district), with higher scores indicating greater reliability. The reliability score is estimated using a beta-binomial model and is a function of the entity’s sample size and score on the measure, as well as the variance across entities.
References:
Adams, J. (2009). The Reliability of Provider Profiling: A Tutorial. https://doi.org/10.7249/ tr653
Exhibit 7, within the reliability attachment, provides the distribution of reliability scores for CBE #3453. The average signal-to-noise reliability for the 7-day rate was 0.99785, and ranged from 0.98723 to 0.99996 across states. The average signal-to-noise reliability for the 14-day rate was 0.99782, and ranged from 0.98581 to 0.99996 across states.
The signal-to-noise analyses showed that the reliability of CBE #3453 is excellent. Although high signal-to-noise reliability is not indicative of high-quality healthcare, it does indicate that the measure may be used to distinguish between states with respect to healthcare quality.
High reliability for CBE #3453 is likely supported by large enough sample sizes at the state level. The median number of denominator episodes per state was 5,519 (ranging from 66 to 97,231).
Validity
Convergent Validity: To assess convergent validity, the team examined the correlations between CBE #3453 7-day and 14-day rates and HEDIS Initiation and Engagement of Alcohol and Other Drug Abuse or Dependence Treatment (IET) measure (measurement year 2021, 18 and older age stratification, “initiation” indicator). The HEDIS IET measure assesses the percentage of individuals with new episode of alcohol or other drug abuse or dependence who initiated treatment within 14 days and received ongoing treatment within 34 days after initiation.
The measure developer also examined the correlation between CBE #3453 and CBE #3400, which represents the percentage of Medicaid beneficiaries aged 18 or older with an OUD who filled a prescription for or were administered or dispensed an FDA-approved medication for OUD during the measurement year.
Face Validity: Results of the face-validity assessment, as captured in the TEP survey (for questions 4 through 14), showed a variety of opinions from the TEP respondents, with the majority of responses indicating some level of agreement with the face validity of CBE #3453.
Validity results are presented within the attachment.
Convergent validity results. Performance score data for the HEDIS® IET measure show moderate correlation with both reported scores for CBE #3453, as presented in Exhibit 8. For the 7-day continuity of care score, the Spearman correlation coefficient was 0.66 with the IET 14-day treatment initiation score and 0.65 with the IET 34-day treatment initiation score. For the 14-day continuity of care score, the Spearman coefficient was 0.68 for the IET 14-day treatment initiation score and 0.67 with the 34-day treatment initiation score. Correlations with the CBE #3400 measure were strong (Spearman correlation coefficients of 0.70 with the CBE #3453 7-day continuity of care score and 0.72 with the CBE #3453 14-day continuity of care score. All correlations were statistically significant with p<0.0001.
CBE #3453 is rated strongly for validity. The majority of TEP respondents indicated that the measure has face validity and is able to distinguish between good quality and poor quality of care. In addition, convergent validity analysis shows strong (or high moderate) correlation with performance measures expected to perform similarly to CBE #3453.
Face validity results. The results shown above in Exhibit 9, all respondents either strongly agreed or agreed that CBE #3453 assesses continuity of care for adult Medicaid beneficiaries after inpatient or residential treatment for SUD (i.e., 75 percent strongly agreed, and the remaining 25 percent of respondents agreed). These findings suggest that the measure concept, as specified, is meaningful in assessing what it intends to assess.
Exhibit 10 shows that all respondents either strongly agreed or agreed that seven and 14 days after discharge are reasonable timeframes to assess for continuity of care after inpatient or residential treatment for SUD (i.e., 50 percent of respondents strongly agreed, and 50 percent agreed). These findings suggest that the timeframes used to assess timely follow-up in this measure are supported by stakeholder consensus.
In Exhibit 11, all respondents either strongly agreed or agreed that comparing scores for this measure meaningfully differentiates good performance from poor performance (i.e., 75 percent of respondents strongly agreed, and the remaining 25 percent of respondents agreed). These findings suggest that the measure, as specified, is useful in understanding and comparing the quality of care between different entities measured.
The results in Exhibit 12 show that the majority of individuals responded Strongly Agree or Agree. One respondent (i.e., 25 percent) indicated Do Not Know or Not Applicable, as they were unsure if the codes adequately inform the measure. Overall, these findings suggest that the data elements defined in this measure for identifying the discharge episodes for the denominator are reasonable and useful in identifying the population of interest.
Exhibit 13 shows that the majority of individuals responded Strongly Agree or Agree. T One respondent (i.e., 25 percent) was undecided on the appropriateness of the exclusion, as they were unclear on the rationale behind it. Overall, these findings suggest general stakeholder support for the exclusion of denominator episodes that are followed by an inpatient admission within the continuity of care assessment period.
In Exhibit 14, all respondents either strongly agreed or agreed that admission to residential treatment following discharge from inpatient treatment should be considered appropriate treatment in the assessment of continuity of care (i.e., 50 percent strongly agreed, and 50 percent agreed). These findings reflect stakeholder support for the continued inclusion of residential treatment as an option for care continuity in the numerator criteria.
The findings presented in Exhibit 15 show that 75 percent of respondents either strongly agreed or agreed, that continuity of care visits can be identified using outpatient claims files or tables that contain diagnosis, procedure, revenue codes, procedure code modifiers, or place of service codes (i.e., 25 percent strongly agreed, and 50 percent agreed). One respondent (i.e., 25 percent) indicated Do Not Know or Not Applicable, as they were unsure of the various claims and coding systems that could be used to inform the measure. These results, as a whole, suggest that the data elements used to define the measure’s numerator criteria are reasonable and useful for capturing services indicative of care continuity.
In Exhibit 16, 75 percent of respondents strongly agreed that continuity of care visits with an SUD diagnosis in the primary or secondary position should be considered appropriate for the measure’s numerator (i.e., 25 percent strongly agreed, and an additional 50 percent of respondents agreed). One respondent (i.e., 25 percent) disagreed, stating that the SUD diagnosis should be in the primary position only. These results suggest that, while there may be slight disagreement on this topic, the majority of respondents supported the allowance of any diagnosis position for the SUD diagnosis on the continuity of care visit claim. Allowing any diagnosis position on the claim (i.e., primary or secondary), measured entities have a greater chance of satisfying the measure’s numerator criteria.
In Exhibit 17, 75 percent of respondents either strongly agreed or agreed that telehealth should be considered an appropriate continuity of care visit (i.e., 25 percent strongly agreed, and an additional 50 percent of respondents agreed). One respondent (i.e., 25 percent) was undecided on this topic. These findings suggest that the majority of stakeholders are supportive of the allowance of telehealth modalities in the measure’s numerator. Allowing telehealth services increases the ability of measured entities to satisfy the measure’s criteria for a continuity of care visit.
Exhibit 18 shows that the majority of respondents stated Strongly Agree or Agree when asked if pharmacotherapy should be considered an appropriate continuity of care option. The findings from these results indicate that pharmacotherapy should be allowed as an appropriate continuity of care option in the numerator. A response of Not Sure/Do Not Know may be a byproduct of this stakeholder having a different understanding of the measure’s intent, and thus, how the measure should define continuity of care.
The findings in Exhibit 19 show that all respondents strongly agreed, agreed, or did not know if indications of pharmacotherapy can be identified in outpatient or pharmacy files, or tables that contain the specified procedure codes or NDCs (i.e., 25 percent strongly agreed, and 25 percent agreed). These findings suggest that the numerator criteria for pharmacotherapy, as specified, is reasonable and useful for identifying OUD pharmacotherapy events.
Risk Adjustment
Use & Usability
Use
Purpose: The goal of IAP was to improve the health and health care of Medicaid beneficiaries and to reduce costs by supporting states’ ongoing payment and delivery system reforms. Medicaid IAP supported state Medicaid agencies to build capacity in key program and functional areas by offering targeted technical support, tool development, and cross-state learning opportunities. The goal of the Medicaid IAP Reducing SUD area was to support states to introduce policy, program, and payment reforms to better identify individuals with SUD, expand coverage for effective treatment, enhance care and practices delivered to beneficiaries, and develop payment mechanisms for SUD services that will provide better outcomes.
Geographic area and percentage of accountable entities and patients included: The IAP covered all 50 states.
Level of analysis and care setting: The measure is included in the IAP for optional reporting at the state level.
Purpose: Shatterproof is a nonprofit organization focused on the ongoing addiction crisis in the United States. The organization promotes treatment through advocacy and partnerships, and developed the Addiction Treatment Locator, Assessment, and Standards platform (ATLAS)—a website and mobile application that provides information on treatment facilities, including types of services offered, insurances accepted, quality measures, consumer experience responses, and provider survey responses.
Geographic area and percentage of accountable entities and patients included: Shatterproof confirmed that CBE #3453 is reported in the following four states: Delaware, Massachusetts, New York, and West Virginia.
Level of analysis and care setting: This measure is reported at the state level.
Usability
Usability of the measure was assessed via qualitative survey of a multi-stakeholder group. The results indicate that respondents had mixed opinions on the usability of the measure in determining care quality. While the majority of respondents agreed that the measure is useful, one respondent did not believe that a claims-based process measure is a sufficient assessment for understanding and determining health care quality. The team notes that CBE #3453 may be bundled with other process (and outcome, as available) measures for the SUD population to establish a more comprehensive evaluation of quality.
Furthermore, 75 percent of respondents to the measure developer’s survey of usability either strongly agreed or agreed that the CBE #3453 measure assesses the quality of care (i.e., continuity of care) provided to Medicaid beneficiaries who are at high risk due to their recent inpatient or residential treatment event for SUD (i.e., 50 percent strongly agreed, and another 25 percent agreed). One respondent (i.e., 25 percent) strongly disagreed, stating that quality cannot be measured using claims data alone. These findings suggest mixed feedback on whether this claims-based measure is sufficient in determining the quality of care provided by different Medicaid agencies on this care process.
Similarly, 75 percent of respondents either strongly agreed or agreed that results from the CBE #3453 measure can be used by state Medicaid agencies and other entities to guide decision-making and improve healthcare quality and health outcomes (i.e., 50 percent strongly agreed, and another 25 percent agreed). One respondent (i.e., 25 percent) disagreed, stating that CBE #3453 is a process measure lacking meaningful outcome components, and quality cannot be measured using only claims data. These findings suggest general support for the CBE #3453 measure as a sufficient tool for guiding care and improving health care quality.
Fifty percent of respondents strongly agreed, and an additional 25 percent of respondents agreed, that assessing for continuity of care after inpatient or residential treatment for SUD is important because the measure’s results can supply meaningful information to the individuals or entities that use the measure’s data (e.g., Medicaid beneficiaries, healthcare providers, states, health plans, and other entities). One respondent (i.e., 25 percent) was undecided on this assertion.
Taken as a whole, these findings suggest general support for the measure’s importance. One TEP respondent provided an additional comment, stating that CBE #3453 is an “important measure for reporting and quality improvement.”
CBE #3453 has been discussed with the measure developer’s technical expert panel to solicit input from a multidisciplinary body with perspectives related to the measure’s construct and implementation. To date, other than feedback from one TEP member to express this measure using a data source other than claims, no additional feedback on the technical specifications has been received.
No feedback has been received for CBE #3453.
Data from the Shatterproof ATLAS are not yet available. Trends in performance will be provided as part of future endorsement maintenance review.
No positive or negative findings have been identified for CBE #3453.
Comments
Staff Preliminary Assessment
CBE #3453 Staff Assessment
Importance
Strengths:
- Evidence suggests that the use of this process measure will identify patients that may require additional engagement in order to reduce readmissions and provide a continuity of care essential for successful outcomes. The developer cites evidence related to discharge and readmission rates for substance use disorder (SUD). Denominator counts and performance gap tables indicate an existing gap in care, as recent as 2021.
Limitations:
- The logic model shows the process from SUD treatment to remission. However, no thorough description of the logic model is provided beyond the four simple components (i.e., treatment --> discharge --> follow-up --> remission).
Rationale:
- Overall, the process and data involved in the measure are straightforward and present an opportunity to enhance care for people who are treated for SUD.
Feasibility Acceptance
Strengths:
- Data is comprised of administrative claims or encounter data. Data collection does not involve sampling. The developer employs the Transformed Medicaid Statistical Information System (T-MSIS) as the data source.
- The qualitative survey conducted indicated that there are minimal challenges for data collection and minimal burden to report. No changes were suggested nor made in response to panel feedback.
Limitations:
- None identified.
Rationale:
- Data is comprised of administrative claims or encounter data. Data collection does not involve sampling. The qualitative survey conducted indicated that there are minimal challenges for data collection and minimal burden to report. No changes were suggested nor made in response to panel feedback.
Scientific Acceptability
Strengths:
- The measure is clear and well defined.
- State-level reliability is conducted on 2021 7-day and 14-day data using the beta-binomial method (the measure is not risk-adjusted). Average state-level reliability is >0.6 for all reliability deciles for the 7- and 14-day data across 50 states. (The estimated reliability for the first decile is 0.995 for both datasets.)
Limitations:
- Reliability is estimated on a state level, and does not address entity level reliability. The developer does state that the measure can be used to distinguish between states.
Rationale:
- The measure is well defined. Reliability is assessed at the state level. Reliability statistics are above the established thresholds.
Strengths:
- The 7- and 14-day rates provide insight into duration and likelihood of remission
Limitations:
- None identified.
Rationale:
- The developer employs the Transformed Medicaid Statistical Information System (T-MSIS) as the data source. In addition, the 7- and 14-day rates provide insight into duration and likelihood of remission.
Equity
Strengths:
- The developer describes risk factors examined to identify performance gaps (e.g., race). Statistically significant differences in the measure rates were found across age, race, and dual eligibility status.
Limitations:
- The measure simply highlights the gaps but does not provide description of how gaps will be addressed or improved.
Rationale:
- In sum, the developer described meaningful differences in measure rates for patients of different ages, races, and dual eligibility status.
Use and Usability
Strengths:
- The measure is currently in use.
- The developer reports discussing the measure's implementation with an expert panel; however, only one expert provided feedback related to data source considerations.
Limitations:
- The developer reports discussing the measure's implementation with an expert panel; however, only one expert provided feedback related to data source considerations.
- Public comments regarding usability were not received nor reported. The developer does not provide rationale as to why no comments were made. Based on the submission, it is not known if the developer sought input on barriers.
- Trend data was not provided.
- The developer noted that performance will be provided for a future maintenance review cycle.
Rationale:
- The current use of the measure is documented; however, usability feedback was inconclusive and additional data is needed to understand barriers to use.
Committee Independent Review
No further comments
Importance
Given the growing SUD events occurring and the potential to achieve positive patient outcomes, particularly in a population that often struggles w/ social determinants such as transportation, this measure can help offer insights surrounding why therapy is inconsistent.
Feasibility Acceptance
Encounter data has most often seemed to be a highly reliable data source for binary measures such as this process measure.
Scientific Acceptability
The model depicted was clear and concise; however, I would urge caution with oversimplification to avoid missing potential process failures.
No further comments here.
Equity
Description of equity presented is appropriate and relevant to this population
Use and Usability
In and of itself, this binary process measure is limited; however, trending and subpopulation categorization may yield additional important information that could inform the process and strengthen the ability to facilitate compliance.
Summary
No further comments
Met - a strong new-to-the-system concept
Importance
Important, actively evolvement field. Given the recent waiver and Rx authorizations, providers will slowly become more comfortable with SUD tx and the needed access to care thereafter will become a well-trodden route.
Feasibility Acceptance
The ability to stand up an initiative is now supported through reimbursement. Keeping the overhead low will be important. A barrier I foresee will be no-shows.
Scientific Acceptability
This is a known area of need, which lacks robust medical/community service support funding. The ability to smoothly transition these patients will improve outcomes and prevent relapse due to lack of access.
Albeit further data is needed and ongoing.
Equity
Addessed and adequate.
Use and Usability
NB the notion of how to address no-shows. Telehealth will likely help with this concept. Transitional care billing seems to be the background business model, appropriately.
The ease of access with telehealth leads one to believe that this would be an attractive concept.
Happy to agree that this is "soon to be met" as the timeline goes on a further data and evidence backs this newer model.
Summary
I like that we lean on telehealth for this to improve access and likelihood of follow up.
Yes!
Importance
Agree with staff preliminary assessment. Addresses an important societal issue with a reasonable process measure.
Feasibility Acceptance
Agree with staff preliminary assessment. Very feasible.
Scientific Acceptability
Agree with staff preliminary assessment.
Agree with staff preliminary assessment.
Equity
I could not locate Exhibit 2 among the various tabs and documents. Based on what I did find and the information in the staff preliminary assessment, I concur with the staff preliminary assessment.
Use and Usability
agree with staff preliminary assessment
Summary
Very important measure for Medicaid. Very feasible and captures an important process. I like that it captures multiple types of followup with different types of providers.
Support
Importance
-
Feasibility Acceptance
-
Scientific Acceptability
-
-
Equity
-
Use and Usability
I resonate with the assessment found in the Limitations: "Public comments regarding usability were not received nor reported. The developer does not provide rationale as to why no comments were made. Based on the submission, it is not known if the developer sought input on barriers."
Summary
I also hope the developer can comment in more detail.
Helpful Measure Addressing SUD
Importance
This measure seems important and addresses an existing gap. The evidence provided is sufficient.
Feasibility Acceptance
The measure uses Medicaid claims.
Scientific Acceptability
Using the Adams reliability testing framework, the Measure Developer provides suitable evidence that the measures are reliable.
However, I would like to also see the Measure Developer conduct a split-half reliability test, where each state is randomly subdivided into two substates, the measures are recalculated by substate, and the intraclass correlation coefficient is calculated for each measure using the resulting dataset. The benefit of this test is that it does not rely on the beta-binomial parametric assumptions of the Adams test. These parametric assumptions can inflate reliability statistics.
The Measure Developer showed sufficient convergent and face validity evidence to suggest that the measures are valid.
Equity
Evidence reported exceeds what is required for this optional section.
Use and Usability
Could be met if trend data is provided to show that states are using these measures to improve quality. A more detailed logic model could help facilitate discussions with state administrators and providers on the mechanisms for improving quality.
Summary
Overall, I support this measure as specified. The two addressable items can be addressed under the current specification with current data.
Public Comments
Public Comment Shared During May 29 Listening Session
I'm thinking this would be an important measure because of the addictive uses of patients that are experiencing this. So once patients are discharged, that they're not just lost out there. That they will benefit from continuity of care after their experience in these units (inpatient or residential treatment units). That there is still follow-up because now that they're back in the environment, we want to know if they're still able to exist, what other issues that they may be having that they can capture that information to again continue them being free from substances that may cause them to relapse, or anything like that. So, I will support this as well too.