MAKING HEALTH CARE AFFORDABLE: PRESERVING ACCESS AND IMPROVING VALUE DETERMINING PATTERNS OF CARE AND CHARACTERISTICS OF YOUTH WITH HIGHEST MENTAL HEALTH EXPENSE Summary of Key Findings March 2013 Katherine E. Grimes, MD, MPH Benjamin Lê Cook, PhD, MPH Children’s Health Initiative

Executive Summary Massachusetts residents, having been in the forefront with regard to access to health insurance, are soon to feel the impact of health care reimbursement changes related to Patient Protection and Affordable Care Act (ACA) of 2010 implementation. The ACA follows years of escalating health care costs in the US, with few evident gains in quality. A national debate ensued regarding ways to improve health care value; the goal being for costs to be managed, and for quality to be improved. In MA, policy leaders are seeking to achieve better value, while maintaining the access gains seen from their own health care legislation in 2006. The hope is that better quality for a larger group will, ultimately, lead to even greater cost-efficiency as the population grows healthier. National health care reform is promoting the use of Accountable Care Organizations (ACO’s), which are expected to manage cost and quality for populations under a global payment system. But, in order for the transition to global payments to be feasible, payors and providers need to better understand the distribution of needs, morbidity and expenditures among their shared patient populations; particularly among expensive sub-populations. This chartpack presents an analysis of medical expense for children with mental health needs, an understudied aspect of the insured population but one with a growing share of the health dollar. We include overall and per child mean expense and service use trends and discuss implications for policy. We also consider key elements in the development of interventions for this group for whom usual care processes do not seem to be effective. Our study sample is children 3-18 years old, covered by MassHealth. We divided them into two groups, with and without psychiatric diagnoses, to examine the impact of co-morbidities on medical expense. In addition, we have analyzed those whose mental health expenditures are in the upper tenth of all mental health expenditures, in order to identify characteristics of these “super-users”. Our findings indicate that the presence of any psychiatric diagnosis vastly increases expenditures for non- psychiatric services, even after controlling for other variables, such as age, race/ethnicity, language and gender. For those with co- morbid conditions, such as asthma, obesity or diabetes, this effect on medical expense is magnified. Mental health needs in children or parents complicates treatment of other health conditions; addressing those mental health conditions has been shown to improve physical health status and reduce overall cost of care. Possible policy implications of our results include the necessity for designers of accountable care elements, such as medical homes or global payment, to consider the major (3-10 fold) impact of children with psychiatric diagnoses on overall pediatric expense. Likewise, it will be important to build-in monitoring of how well the new delivery system models serve the needs of these children, so as to effectively intercept the increasing slope of medical expense. A related policy focus important for ACO system design is that of psychiatric medication use among children and adolescents. In our study, the likelihood of psychiatric medication use is tripled among child mental health “super-users”. Many of these medications have been found, in other studies, to be associated with increased physical health risks, thus raising the specter of a cycle of ever increasing morbidity and expense for children beginning as young as 3 and 4 years old. Trends in our study, where usage does not correlate with diagnostic distribution (but does correlate with being male) suggest poor health care quality and are deserving of greater oversight. The complexity of covariate patterns, where we found white, teenage males disproportionately represented among “super-users”, for example, suggests that recognized service access barriers, along with possible variations by Medicaid category (i.e. SSI vs. TANF) need to be studied in greater depth, looking at trends over time, before final intervention recommendations can be made. However, drawing upon earlier work in MA, we suggest that individualized clinical intervention approaches be built around particular “super-users” and their families, using flexible benefits and highly integrated health care delivery within an ecological model. Examples of this approach could include active care management, respite, and transportation support for families of children with complex health needs. Based on our data, outreach and active health status monitoring is also needed to reach those youth with early indicators of need, in order to reduce the risk of higher morbidity; bringing both poor outcomes and high cost.

Table Of Contents SLIDE 2 Executive Summary SLIDE 4 Data and Methods SLIDE 5 Demographics by Study Category SLIDES 6-11 Expense Comparisons SLIDES 12- 14 Psychiatric Diagnoses and Psychotropic Medication Distribution SLIDES 15-17 Characteristics and Significant Predictors of Being in the Top 10% of MH Expense SLIDE 18 Conclusions

Data And Methods DATA: Study sample = 9,230; continuously enrolled MassHealth youth, with any physical (Peds) or mental health (MH) claims between 2007-2012; Age range = 3-18 years (mean 9.3); 2846 out of 9230 (31%) of those with > 12 mos. enrollment had at least one mental health claim; top 10% of expenditures for mental health care = 285 children. METHODS: Summary statistics for population demographics, as well as expense calculations by child, age group, gender, race/ethnicity, diagnosis, and service use, including psychotropic medication use. Analyses using multivariate generalized linear models to estimate differences in total, physical health care and non-psychotropic pharmacy expenditures for Peds-only vs. MH service users; logistic regression models predicting membership in top 10% MH expense. Both analyses adjust for age, gender, race, language, and physical health diagnosis.

Demographic Distribution: by Study Category   Children With No Mental Health Services: n = 6384 Children With Any Mental Health Service; n= 2846 Children with MH Expenses in Top 10%; n = 285 3 – 5 yrs. 3058 (48%) 1182 (41%) 95 (33%) 6 – 12 yrs. 2023 (32%) 1015 (36%) 97 (34%) 13 – 18 yrs. 1303 (20%) 649 (23%) 93 (33%) Males 3117 (49%) 1590 (56%) 183 (64%) Females 3267 (51%) 1256 (44%) 102 (36%) Hispanic 1592 (25%) 774 (27%) 64 (22%) White 1236 (19%) 862 (30%) 111 (39%) Black 1271 (20%) 554 (19%) 57 (20%) Asian 630 (10%) 150 (5%) 17 (6%) Nat American 85 (1%) 7 (1%) 1 (1%) Other 950 (14%) 385 (14%) 27 (9%) Unk/Declined 700 (11%) 114 (4%) 8 (3%) Study sample: Continuously enrolled Massachusetts Medicaid Children age 3-18, between 2007-2012 (N=9230) Children with Mental Health Services were somewhat older and more often male than those with Physical Health Services only. Of those with known race/ethnicity, the proportion of youth identified as Black remained fairly stable across the study categories. The percentage of those identified as Hispanic went up among those with Mental Health diagnoses, but dropped Top 10% Mental Health expense. The proportion of White children rose steadily across study categories: with the percentage among the Top 10% more than double the percentage of White children in the No Mental Health Services group. 5

Percent of Dollars and Population for Children's Mental Health "Super-users"

Mean Annual Physical Health Expense: Comparing Children with and without Co-morbid Mental Health Conditions Youth with identified mental health needs (> 0 mental health claims) spend significantly more in physical health care (outpatient, pharmacy, and inpatient expenses) than those without mental health claims Total annual mean physical health expense for children with mental illness is $1704 compared to $937 for those with no mental illness “Super-users” (top 10%) of mental health care with a total annual mean physical health expense of $2793

Mean Annual Emergency Room Expense: Comparing Children with and without Co-morbid Mental Health Conditions Youth with mental health needs spent more than twice as much on ER services, as those with physical health service use only. “Super-users” spend more than 4 times as much on ER use as children with no mental health claims.

Mean Annual Mental Health Expense: Children with any Mental Health Claim vs. “Super-users” The majority of expenditures for both youth with any mental health claim and for mental health “Super-users” came from outpatient care. Children with any mental health claim spent just over $200 per year on inpatient psychiatric hospital use. “Super-users” spent over $2,000 per year on inpatient psychiatric hospital services.

Mean Annual Total Expense: Comparing Children with and without Co-morbid Mental Health Conditions 31% of study youth had at least one MH/SA claim or psychotropic medication prescription Children with mental health needs spend $3 in overall health expenditures for every $1 spent by those without mental health claims. “Super-users” spend over $10,000 per year on overall health care; almost ten times more than children without mental health needs.

Data for children continuously enrolled in Medicaid for at least 12 months between 2007-2008. Mental health defined as presence of MH diagnosis, MH service claim or prescription of psychotropic medication.

Psychiatric Diagnosis Distribution for Children: Top 10% vs Psychiatric Diagnosis Distribution for Children: Top 10% vs. Remaining 90% of MH Expenditures Diagnoses are listed in order of frequency, not expense; Mood Disorders are most frequent Dx for Top 10%. Children in the Top 10% are 17 times more likely to have a diagnosis of psychosis than other children with MH/SA claims.

Distribution of Children Receiving Psychotropic Medication Overall, 21% of all children with a MH/SA diagnosis or service type were prescribed at least one psychotropic medication (N=2846) 54 % of children in the “super-user” category were prescribed psychotropic medications (N=285) 18 % of the remaining children with a mental health diagnosis were prescribed psychotropic medication (N=2561)

Psychotropic Medication Categories Frequency Distribution of Children Prescribed Psychotropic Medications, by Type of Drug Psychotropic Medication Categories Children on Psych Meds* Super-Users** Anti-ADHD meds 47% 53% Antidepressants 41% 63% Benzodiazepines and Sedatives 23% 18% Antipsychotics Atypical Typical 5% 0% 45% 3% Anticonvulsants and Mood Stabilizers 9% Other 7% *Lower 90% = 2561 out of 2846 children with MH/SA claim expense ** Top 10% = 285 out of 2846 children with MH/SA claim expense “Super-users” were 7 times more likely to be prescribed Atypical Antipsychotics than other children Atypical Anti- psychotics are not only the most expensive psychotropic medication type, they carry significant physical health risks “Super-users” averaged 2 or more psychotropic meds per child

“Super-user” Characteristics: Who are Youth in the top 10% of MH Expenditures Physical Health Co-morbidities Developmental Disorders 30%, Asthma 19%, Obesity 18%, Diabetes registry 1% Language English 72%, Other 10%, Haitian Creole 7%, Spanish 5% Race/Ethnicity - White 39%, Hispanic 22%, Black 20%, Other 9%, Asian 6%

Youth with a mental health claim spent more on physical health expenditures even after adjustment for covariates Regression models, adjusting for age, gender, race, language, and physical health diagnoses, showed: having a mental health claim was significantly associated with increased total health care expenditures but having a mental health claims was also significantly associated with increases in non-mental health care expenditures, including pediatric outpatient, inpatient, ER and pharmacy expense

Significant Predictors of Being in the Top 10% of MH Expense Among the full population Odds Ratio Male 1.61 Age 6-12 Age 13-18 1.47 2.64 Hispanic .54 Black .55 Asian .40 Obesity 1.02 Asthma 2.21 Diabetes 2.62 Among those with MH Claim Odds Ratio ADHD Referent Psychosis 7.1 Autism 4.3 Mood 4.1 PTSD 3.5 Anxiety 2.2 Other disorders .65

Conclusions Accountability for cost and quality will be key areas in Affordable Care across all populations. It will be important to monitor how well the new delivery system models serve the needs of children. Medical expense analyses have focused on adults; with children presumed to be healthy and inexpensive. Our study indicates clinical trends for children have changed dramatically. Chronic conditions, including mental illness, are now drivers of pediatric expense. ACO’s will need to address the major (3-10 fold) impact of MH/SA diagnoses in children on overall pediatric expense. Key to reducing that expense is improving poor quality (despite the rarity of psychosis, we found 47% of “super-users” were prescribed anti-psychotics, which have recently been shown to increase the risk of obesity and diabetes). Improved quality can be achieved through integrated primary and specialty care teams working, along with families and schools, to replace the emphasis on “management” of children (often via meds) with a new goal of diagnostic clarity and clinically appropriate treatment.