Quality Measures for Managing Prescription of Antipsychotic Medication Among Youths: Factors Associated With Health Plan Performance

Over the past decade, studies have documented the increase of antipsychotic prescribing for children and adolescents, raising public alarm and calls for increased efforts to monitor the use of these powerful agents (1–4). Little is known about the long-term effectiveness and safety profile of antipsychotic medications among youths (3, 5), and their use can result in serious health consequences, particularly weight gain and lipid and glucose abnormalities.

Among youths, most of these antipsychotic medications are prescribed for nonpsychotic conditions, such as attention-deficit hyperactivity disorder, aggression, and disruptive behaviors, and are prescribed disproportionately among vulnerable youths, including those covered by Medicaid or in foster care and those in minority populations (2, 6–9). This practice of prescribing antipsychotics for conditions for which no clear evidence supports their use, combined with the well-established health risks associated with their use, has led to calls for increased oversight of antipsychotic prescribing in vulnerable populations, especially those covered by Medicaid and the Children’s Health Insurance Program (7, 10–13). To address concerns, 31 states have instituted prior-authorization policies for prescription of second-generation antipsychotic medications for young children or adolescents or both through multiple strategies involving dissemination of best-practice guidelines, provider feedback, and psychiatric consultation services (13–15). In particular, peer review policies regarding antipsychotic prescribing appear to be associated with decreased prescribing to younger children (16).

Until recently, quality measures for pediatric antipsychotic prescribing did not exist, challenging efforts to systematically monitor appropriate antipsychotic prescribing practices and treatment management for youths taking these medications. In response to public health concerns, the Agency for Healthcare Research and Quality (AHRQ) and the Centers for Medicare and Medicaid Services (CMS) funded the National Collaborative for Innovation in Quality Measurement to develop a suite of pediatric measures focused on the safe and judicious use of antipsychotics by youths. Through this effort, the National Committee for Quality Assurance (NCQA) tested and implemented three measures related to antipsychotic prescribing in the Healthcare Effectiveness Data and Information Set (HEDIS) for commercial and Medicaid plan reporting, starting in 2015. These include the use of multiple concurrent antipsychotics among children and adolescents, provision of psychosocial care as first-line treatment among youths prescribed antipsychotics without a primary indication, and metabolic monitoring (lipid and glucose screening) among youths prescribed antipsychotics. The pediatric antipsychotic quality measures follow treatment guidelines (3) and address key concerns related to inappropriate prescribing and proper treatment management for youths prescribed antipsychotics. Legislation passed in January 2018 to extend the Children’s Health Insurance Program requires states to report the Medicaid Child Core Set by 2024, which includes the psychosocial care measure as a state-level measure, highlighting the public health significance of this quality measure.

In this study, we focused on two pediatric antipsychotic quality measures: provision of psychosocial care as first-line treatment among youths prescribed antipsychotics without a primary indication and metabolic monitoring (lipid and glucose screening) among youths prescribed antipsychotics. We were particularly interested in examining health plan characteristics and other contextual factors that may influence health plan performance on quality measures. Because of the low variability in health plan performance rates on the quality measure regarding use of multiple concurrent antipsychotics (2.7%±1.9% and 2.4%±1.7% across commercial and Medicaid plans, respectively), we excluded this measure from our study.

In this study, we selected independent variables that are available in the HEDIS data set and focused on those previously shown to be related to the quality of care provided by health plans. These included geographic region, for-profit status, and plan model type (17–20). We also examined the plan’s eligible population size and whether the plan operated in a state with prior-authorization policies for antipsychotic prescribing. Because youths prescribed antipsychotics typically represent a small proportion of a health plan’s overall enrollment, we hypothesized that plans with very small eligible populations would have limited incentives for allocating resources to improve care quality for this vulnerable population without additional external oversight. We were thus particularly interested in whether state policy efforts to focus attention on this small and vulnerable population through prior-authorization policies may be associated with plan performance on these quality measures.

Methods

Study Population

The study population included health plans that had at least 30 eligible patients and that reported either the HEDIS measure on metabolic monitoring or the first-line psychosocial care measure for youths ages 1–17 who received care in 2016.

Data Source

Plans used administrative claims data to calculate the antipsychotic measures and submit their performance rates to the NCQA on an annual basis. Administrative data include claims, enrollment files, and other transactional data.

Dependent Variables

Metabolic monitoring.

The study used the reported plan performance, defined as the percentage of youths ages 1–17 with ongoing antipsychotic use who had metabolic testing including both a glucose and a cholesterol test during the year.

First-line psychosocial care.

The study used the reported plan performance, defined as the percentage of youths ages 1–17 with a new prescription for an antipsychotic for a nonindicated use who received psychosocial care before or just after starting an antipsychotic.

Independent Variables

Plan characteristics.

Plans reported the size of their eligible population for the quality measure, the plan’s profit status (not for profit or for profit), and the plan’s model type (independent practice association or network, mixed model, staff or group, unknown).

Prior authorization and region.

We examined whether the plan reported operating in a state requiring that providers obtain prior authorization before prescribing antipsychotic medications to youths. We followed Schmid et al. (13) to identify states that had instituted prior authorization by 2014, the year before HEDIS reporting on these measures was adopted. We determined the U.S. Department of Health and Human Services region to which each plan is assigned on the basis of CMS regional offices, which regulate and monitor implementation of CMS policies and regulations.

Statistical Analysis

We analyzed and report our data by insurance program type (Medicaid versus commercial) because of expected differences in patient demographic characteristics and because of specific interest in Medicaid enrollees, who are disproportionately prescribed antipsychotics.

Bivariate associations between each plan characteristic (size of eligible population, region, profit status, model type, and state legislation on prior authorization) and each performance measure were assessed with Spearman correlations, the two-sample t test, and linear regression. Main-effects multivariable linear regression models were used to examine the combined association of these plan characteristics with each performance measure by insurance program type. Size of the eligible population and region are likely to be important confounders with the other plan characteristics and thus were retained in the model regardless of statistical significance. For all other plan characteristics, only those that were significantly associated with the performance measure at p<.05, after adjustment for other plan characteristics, were retained in the final regression model. The regression results are summarized by using adjusted means and standard errors. For both performance measures, higher scores indicate better plan performance.

Results

Plans Reporting Performance Measures

In 2016, 565 commercial plans and 459 Medicaid plans voluntarily submitted data to the NCQA.

Commercial plans.

Of the 565 commercial plans, 406 submitted data on the metabolic monitoring measure, and 279 of the 406 plans (69%) met minimum denominator requirements (at least 30 eligible members) for the measure. Of the 405 plans that submitted data on the first-line psychosocial care measure, 160 (40%) met minimum denominator requirements.

Medicaid plans.

Of the 459 plans that submitted data, only 200 Medicaid plans provided data on the metabolic monitoring measure, and 164 of the 200 plans (82%) met minimum denominator requirements. Of the 170 plans that submitted data for the first-line psychosocial care measure, 134 (79%) met minimum denominator requirements.

Metabolic Monitoring Performance Measure

Table 1 summarizes plan characteristics for the 279 commercial plans and 164 Medicaid plans with reportable metabolic monitoring data. Among youths who had ongoing antipsychotic use, on average, 33.8%±10.0% of those in commercial plans and 33.3%±10.9% of those in Medicaid plans received metabolic monitoring (data not shown).

Associations Between Plan Characteristics and Metabolic Monitoring

Commercial plan characteristics related to region, profit status, and model type were significantly associated with the metabolic monitoring measure in unadjusted analyses (Table 2). After adjustment for plan characteristics, commercial plans in the North performed about 11 percentage points higher, on average, compared with the other three regions (p<.001). Not-for-profit commercial plans also had better metabolic monitoring performance than for-profit commercial plans (36.8% versus 32.5%, p<.001). The five commercial plans with a staff or group model type had significantly better metabolic monitoring performance (13 to 15 percentage points higher, on average), compared with the other three model types (p<.001). In adjusted analyses, commercial plans operating in states requiring prior authorization for antipsychotic medications had significantly better metabolic monitoring performance, compared with commercial plans in states without such policies (34.8% versus 31.8%, p=.006).

Medicaid plan characteristics related to region and profit status were significantly associated with the metabolic monitoring measure in unadjusted analyses (Table 2). After adjustment for plan characteristics, Medicaid plans in the North performed 8 to 11 percentage points higher, compared with Medicaid plans in the other regions (p<.001). After adjustment for plan characteristics, profit status was no longer significantly associated with metabolic monitoring performance. In addition, Medicaid plans operating in states requiring prior authorization for antipsychotic medications had significantly higher metabolic monitoring performance, compared with plans operating in states without this requirement (34.1% versus 29.8%, p=.011).

First-Line Psychosocial Care Performance Measure

Table 3 summarizes plan characteristics for 160 commercial plans and 134 Medicaid plans that reported the first-line psychosocial care measure and had an eligible population of sufficient size. Among youths who had a new prescription for an antipsychotic medication for a nonindicated use, on average, 57.7%±10.7% of those in commercial plans and 60.2%±13.3% of those in Medicaid plans received psychosocial care before or just after starting an antipsychotic medication (data not shown).

Associations Between Plan Characteristics and First-Line Psychosocial Care

Commercial plan characteristics related to region, profit status, and prior authorization were significantly associated with the first-line psychosocial care measure in unadjusted analyses (Table 4). After adjustment for plan characteristics, commercial plans in the South performed worse on average by 7 to 12 percentage points on the first-line psychosocial care measure, compared with the other three regions (p<.001). Not-for-profit commercial plans had significantly better performance than for-profit commercial plans (62.5% versus 55.9% of youths received first-line psychosocial care, p<.001). Although plans operating in states that did not require prior authorization had significantly higher first-line psychosocial care performance in unadjusted analyses, this association was no longer statistically significant after adjustment for plan characteristics.

Medicaid plan characteristics related to eligible population size, region, profit status, and prior authorization were significantly associated with the first-line psychosocial care measure performance in unadjusted analyses (Table 4). After adjustment for plan characteristics, there was a positive association between eligible population size and first-line psychosocial care performance, whereby Medicaid plans with a larger eligible population had better performance, compared with Medicaid plans with a smaller eligible population. In the adjusted analyses, performance of the five Medicaid plans in the West was 17 to 23 percentage points worse, compared with the other three regions (p<.001). Not-for-profit Medicaid plans had significantly better performance, compared with for-profit Medicaid plans (62.4% versus 57.7% of youths received first-line psychosocial care, p=.045). After adjustment for other plan characteristics, the association between prior authorization and first-line psychosocial care was no longer statistically significant, largely because of the high correlation between region and prior authorization.

Discussion

Consistent with the literature on antipsychotic prescribing practices, we found that the proportion of plans that met minimum eligibility requirements for monitoring youths was smaller in commercial plans, compared with Medicaid plans, for both quality measures. Health plan performance rates for the antipsychotic measures were quite comparable across commercial and Medicaid plans, despite likely differences in enrollee characteristics. Approximately one-third of youths prescribed antipsychotics in these plans received metabolic monitoring, and about three-fifths received first-line psychosocial care in conjunction with antipsychotic use.

Consistent with prior findings of delivery of lower-quality care by for-profit plans (18, 20), the study found that across both commercial and Medicaid programs, not-for-profit plans had significantly higher rates of metabolic monitoring and provision of first-line psychosocial care, compared with for-profit plans, suggesting that profit status may be related to care quality for these pediatric measures. As in prior work that showed geographic variation in care quality (19), we also found broad regional differences in how plans performed on both these measures. For Medicaid plans, eligible population size was also associated with better performance on the measure of first-line psychosocial care. Further research to understand various factors, such as practice variations, market forces, and individual factors, that may account for such regional variations is needed to develop targeted strategies for addressing these regional disparities in care quality.

Of note, we found that state legislation requiring prior authorization for antipsychotic medications was a key factor associated with higher performance on the measure of metabolic monitoring in both Medicaid and commercial plans, suggesting a potentially important role of state legislation, in conjunction with quality measurement, in driving care quality for this measure. States varied in how they implemented prior-authorization policies for the use of antipsychotics by youths, with differences in application by age and drug type and by whether, or how, a clinical review process was implemented as part of the overall process (16). In all but one state (Virginia), prior authorization did not address alternative nonpharmacologic treatments or metabolic monitoring (13), which may explain why state legislation on prior authorization for antipsychotic prescribing was found to have less of an impact on the measure of first-line psychosocial care.

Findings from this study were limited in several ways. First, reporting of health plan performance on these quality measures is currently voluntary (some states require reporting by Medicaid plans); 24 states reported data on the provision of first-line psychosocial care in 2017 (21). Although most health plans submitted data for at least one of the two measures, reportable rates for each measure were lower. Commercial plans were primarily challenged by small eligible populations, especially for the psychosocial care measure. Although small denominators were less of an issue for Medicaid plans, they were more likely to not report data for the psychosocial care measure because they did not provide a mental health benefit or were not required to report these rates. Second, we could not adjust for key population differences that might have affected our findings (e.g., socioeconomic status, foster care status, diagnosis, and access to psychosocial services); however, stratified reporting by plan category (commercial versus Medicaid) may have mitigated some of these differences. Third, we had very limited information on plan characteristics or the context in which they were operating. Although we used a published report to identify states that had instituted prior-authorization policies on antipsychotic prescribing for youths, there was variation in how and when these policies were implemented. Thus we were not able to understand how such variation and other unmeasured plan characteristics might have influenced performance rates on these measures. Given the significant national attention to this issue, several state and local efforts have been developed at various points to improve care quality with regard to antipsychotic prescribing (13–15). We were unable to account for those efforts in the study.

Conclusions

These limitations notwithstanding, this study is the first to examine health plan performance on national quality measures for managing antipsychotic prescribing for youths. Our findings highlight the potential relevance of eligible population size, plan profit status, and geographic variation in health plan performance on these measures. State legislation on prior authorization for antipsychotic prescribing for youths appears to be a key factor associated with better management practices, particularly for monitoring of metabolic results. Use of measures in conjunction with policies such as prior authorization could be particularly helpful in encouraging better care delivery to small and highly vulnerable populations.