Untreated Psychiatric and Substance Use Disorders Among Caregivers With Children Reported to Child Protective Services.

Importance: Mental and substance use disorders can interfere with parents' ability to care for their children and are associated with a greater likelihood of child protective services involvement to address child maltreatment. Parent engagement in psychiatric and substance use disorder treatment can prevent child maltreatment and family separations. Objective: To determine whether caregivers with psychiatric or substance use disorders whose children were referred to child protective services received Medicaid-funded psychiatric or substance use disorder treatment. Design, Setting, and Participants: Caregivers listed on child welfare records were linked with their Medicaid records using 2017 to 2020 Medicaid and child welfare data from Florida and Kentucky. Medicaid claims were analyzed to determine if caregivers had a psychiatric or substance use disorder diagnosis and whether those caregivers received counseling or medications. The analysis was conducted in 2023. Exposure: Diagnosis of a psychiatric or substance use disorder in 2020. Main Outcome and Measure: Receipt of psychiatric or substance use disorder counseling or medications. Results: Of the 58 551 caregivers, 65% were aged between 26 and 40 years; 69% were female and 31% were male. Overall, 78% identified as White, 20% identified as Black/African American, and less than 1% identified as American Indian/Alaska Native, Asian, or Native Hawaiian/Other Pacific Islander. In 2020, 59% of caregivers with Medicaid and children referred to child protective services had a mental health or substance use disorder diagnosis, compared with 33% of age- and sex-matched Medicaid beneficiaries without children referred to child protective services (P < .001). Among caregivers with a psychiatric disorder, 38% received counseling and 67% received psychiatric medication. Among those with a substance use disorder, 40% received counseling and 38% received a substance use disorder medication. Conclusions and Relevance: In this case-control study, despite Medicaid coverage of an array of effective behavioral health treatments, large portions of caregivers with Medicaid coverage, who need treatment and whose children were referred to child protective services, were not receiving treatment. Medicaid and child welfare agencies should make a greater effort to connect caregivers to behavioral health services.

Linked Child Welfare and Medicaid Data in Kentucky and Florida Highlights Racial Disparities in Access to Care.

Parents with serious mental health (MH) and substance use disorders (SUD) can face profound challenges caring for their children. MH/SUD treatment can improve outcomes for both parents and their children. This study evaluated whether parents with Medicaid with MH/SUD conditions whose children had child protective services (CPS) involvement were receiving MH/SUD treatment and whether receipt differed by race. We analyzed the 2020 Child and Caregiver Outcomes Using Linked Data (CCOULD) which contains Medicaid and child welfare records from Kentucky and Florida on 58,551 CPS-involved caregivers. Among caregivers with an MH diagnosis, White individuals were more likely than Black individuals to have received counseling (42% vs. 20%) or an MH medication (69% vs. 52%). Among caregivers with an SUD, White individuals were more likely than Black individuals to have received counseling (43% vs. 20%) or an SUD medication (43% vs. 11%). More effort is needed to connect parents with CPS involvement to MH/SUD treatment, particularly Black parents.

Comparing Patient and Provider Priorities Around Amputation Level Outcomes Using Multiple Criteria Decision Analysis.

BACKGROUND: Patients with chronic limb threatening ischemia may require a transmetatarsal amputation (TMA) or a transtibial amputation. When making an amputation-level decision, these patients face a tradeoff-a TMA preserves more limb and may provide better mobility but has a lower probability of primary wound healing and may therefore result in additional same or higher level amputation surgeries with an associated negative impact on function. Understanding differences in how patients and providers prioritize these tradeoffs and other outcomes may enhance shared decision-making. OBJECTIVES: Compare patient priorities with provider perceptions of patient priorities using Multiple Criteria Decision Analysis (MCDA). METHODS: The MCDA Analytic Hierarchy Process was chosen due to its low cognitive burden and ease of implementation. We included 5 criteria (outcomes): ability to walk, healing after amputation surgery, rehabilitation program intensity, limb length, and ease of use of prosthetic/orthotic device. A national sample of dysvascular lower-limb amputees and providers were recruited from the Veterans Health Administration with the MCDA administered online to providers and telephonically to patients. RESULTS: Twenty-six dysvascular amputees and 38 providers participated. Fifty percent of patients had undergone a TMA; 50%, a transtibial amputation. When compared to providers, patients placed higher value on TMA (72% vs. 63%). Patient versus provider priorities were ability to walk (47% vs. 42%), healing (18% vs. 28%), ease of prosthesis use (17% vs. 13%), limb length (11% vs. 13%), and then rehabilitation intensity (7% vs. 6%). LIMITATIONS: Our sample may not generalize to other populations. CONCLUSIONS: Provider perceptions aligned with patient values on amputation level but varied around the importance of each outcome. IMPLICATIONS: These findings illuminate some differences between patients' values and provider perceptions of patient values, suggesting a role for shared decision-making. Embedding this MCDA framework into a future decision aid may facilitate these discussions.

The Development and Pilot Study of a Multiple Criteria Decision Analysis (MCDA) to Compare Patient and Provider Priorities around Amputation-Level Outcomes.

Background. Patients with chronic limb-threatening ischemia who are facing a lower-limb amputation often require a transmetatarsal amputation (TMA) or a transtibial amputation (TTA). A TMA preserves more of the patient's limb and may provide better mobility but has a lower probability of primary wound healing relative to a TTA and may result in additional amputation surgeries. Understanding the differences in how patients and providers prioritize key outcomes may enhance the amputation decisional process. Purpose. To develop and pilot test a multiple criteria decision analysis (MCDA) tool to elicit patient values around amputation-level selection and compare those with provider perceptions of patient values. Methods. We conducted literature reviews to identify and measure the performance of criteria important to patients. Because the quantitative literature was sparse, we developed a Sheffield elicitation framework exercise to elicit criteria performance from subject matter experts. We piloted our MCDA among patients and providers to understand tool acceptability and preliminarily assess differences in patient and provider priorities. Results. Five criteria of importance were identified: ability to walk, healing after amputation surgery, rehabilitation intensity, limb length, and prosthetic/orthotic device ease. Patients and providers successfully completed the MCDA and identified challenges in doing so. We propose potential solutions to these challenges. The results of the pilot test suggest differences in patient and provider outcome priorities. Limitations. The pilot test study enrolled a small sample of providers and patients. Conclusions. We successfully implemented the pilot study to patients and providers, received helpful feedback, and identified solutions to improve the tool. Implications. Once modified, our MCDA tool will be suitable for wider rollout. Highlights: Patients and providers have successfully completed our MCDA, and patients feel the MCDA may be useful in clinical practice.We encountered several methodologic challenges and identified approaches to ease participant burden.When data are sparse, using the Sheffield elicitation framework is helpful in creating a performance matrix, although patients relied largely on their amputation experiences to complete the exercise. Blinding the alternatives may help patients better understand the process.

Estimating State-Level Health Burden of Diabetes: Diabetes-Attributable Fractions for Diabetes Complications.

INTRODUCTION: Limited information is available on the health burden of diabetes at the state level. This study estimated state-specific attributable fractions and the number of cases attributable to diabetes for diabetes-related complications. METHODS: For each state, diabetes-attributable fractions for nine diabetes complications were estimated: three self-reported complications from the 2013 Behavioral Risk Factor Surveillance System, hospitalizations with three complications from 2011 to 2014 State Inpatient Databases, and three complications from 2013 Medicare data. Attributable fractions were calculated using RR and diabetes prevalence and the total number of cases using attributable fractions and total number of complications. Adjusted RR of each complication for people with and without diabetes by age and sex was estimated using a generalized linear model. Analyses were conducted in 2015-2016. RESULTS: Median state-level diabetes-attributable fractions for self-reported complications were 0.14 (range, 0.10-0.19) for mobility limitations; 0.13 (range, 0.04-0.21) for limitations in instrumental activities of daily living; and 0.12 (range, 0.06-0.20) for severe visual impairment or blindness. Median state-level diabetes-attributable fractions for diabetes-associated hospitalizations were 0.19 (range, 0.08-0.24) for congestive heart failure; 0.08 (range, 0.02-0.16) for myocardial infarction; and 0.62 (range, 0.46-0.73) for lower extremity amputations. Median state-level diabetes-attributable fractions for complications among Medicare beneficiaries were 0.17 (range, 0.14-0.23) for coronary heart disease; 0.28 (range, 0.24-0.33) for chronic kidney disease; and 0.22 (range, 0.08-0.32) for peripheral vascular disease. CONCLUSIONS: Diabetes carries a significant health burden, and results vary across states. Efforts to prevent or delay diabetes or to improve diabetes management could reduce the health burden because of diabetes.

Economic Costs Attributable to Diabetes in Each U.S. State.

OBJECTIVE: To estimate direct medical and indirect costs attributable to diabetes in each U.S. state in total and per person with diabetes. RESEARCH DESIGN AND METHODS: We used an attributable fraction approach to estimate direct medical costs using data from the 2013 State Health Expenditure Accounts, 2013 Behavioral Risk Factor Surveillance System, and the Centers for Medicare & Medicaid Services' 2013-2014 Minimum Data Set. We used a human capital approach to estimate indirect costs measured by lost productivity from morbidity (absenteeism, presenteeism, lost household productivity, and inability to work) and premature mortality, using the 2008-2013 National Health Interview Survey, 2013 daily housework value data, 2013 mortality data from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research, and mean wages from the 2014 Bureau of Labor Statistics. Costs were adjusted to 2017 U.S. dollars. RESULTS: The estimated median state economic cost was $5.9 billion, ranging from $694 million to $55.5 billion, in total and $18,248, ranging from $15,418 to $30,915, per person with diabetes. The corresponding estimates for direct medical costs were $2.8 billion (range $0.3-22.9) and $8,544 (range $6,591-12,953) and for indirect costs were $3.0 billion (range $0.4-32.6) and $9,672 (range $7,133-17,962). In general, the estimated state median indirect costs resulting from morbidity were larger than costs from mortality both in total and per person with diabetes. CONCLUSIONS: Economic costs attributable to diabetes were large and varied widely across states. Our comprehensive state-specific estimates provide essential information needed by state policymakers to monitor the economic burden of the disease and to better plan and evaluate interventions for preventing type 2 diabetes and managing diabetes in their states.

Diabetes-Attributable Nursing Home Costs for Each U.S. State.

OBJECTIVE: To estimate the diabetes-attributable nursing home costs for each state. RESEARCH DESIGN AND METHODS: We used a diabetes-attributable fraction (AF) approach to estimate nursing home costs attributable to diabetes (in 2013 dollars) in aggregate and per person with diabetes in each state. We calculated the AFs as the difference in diabetes prevalence between nursing homes and the community. We used the Centers for Medicare & Medicaid Services 2013-2015 Minimum Data Set to estimate the prevalence of diabetes in nursing homes and to adjust for the intensity of care among people with diabetes in nursing homes. Community prevalence was estimated using the Behavioral Risk Factor Surveillance System (BRFSS). State nursing home expenditures were from the 2013 State Health Expenditure Accounts. RESULTS: The fraction of total nursing home expenditures attributable to diabetes ranged from 12.3% (Illinois) to 22.5% (Washington, DC; median AF of 15.6%, New Jersey). The median AF was highest in the 19-64 years age-group and lowest in the 85 years or older age-group. Nationally, diabetes-attributable nursing home costs were $18.6 billion. State-level diabetes-attributable costs ranged from $21 million in Alaska to $2.0 billion in California. Diabetes-attributable nursing home costs per person ranged from $374 in New Mexico to $1,610 in Washington, DC (median of $799 in Maine). CONCLUSIONS: Our estimates provide state policymakers with an improved understanding of the economic burden of diabetes in each state's nursing homes. These estimates could serve as critical inputs for planning and evaluating diabetes prevention and management interventions that can keep people healthier and living longer in their communities.

Projected Costs of Informal Caregiving for Cardiovascular Disease: 2015 to 2035: A Policy Statement From the American Heart Association.

INTRODUCTION: In a recent report, the American Heart Association estimated that medical costs and productivity losses of cardiovascular disease (CVD) are expected to grow from $555 billion in 2015 to $1.1 trillion in 2035. Although the burden is significant, the estimate does not include the costs of family, informal, or unpaid caregiving provided to patients with CVD. In this analysis, we estimated projections of costs of informal caregiving attributable to CVD for 2015 to 2035. METHODS: We used data from the 2014 Health and Retirement Survey to estimate hours of informal caregiving for individuals with CVD by age/sex/race using a zero-inflated binomial model and controlling for sociodemographic factors and health conditions. Costs of informal caregiving were estimated separately for hypertension, coronary heart disease, heart failure, stroke, and other heart disease. We analyzed data from a nationally representative sample of 16 731 noninstitutionalized adults ≥54 years of age. The value of caregiving hours was monetized by the use of home health aide workers' wages. The per-person costs were multiplied by census population counts to estimate nation-level costs and to be consistent with other American Heart Association analyses of burden of CVD, and the costs were projected from 2015 through 2035, assuming that within each age/sex/racial group, CVD prevalence and caregiving hours remain constant. RESULTS: The costs of informal caregiving for patients with CVD were estimated to be $61 billion in 2015 and are projected to increase to $128 billion in 2035. Costs of informal caregiving of patients with stroke constitute more than half of the total costs of CVD informal caregiving ($31 billion in 2015 and $66 billion in 2035). By age, costs are the highest among those 65 to 79 years of age in 2015 but are expected to be surpassed by costs among those ≥80 years of age by 2035. Costs of informal caregiving for patients with CVD represent an additional 11% of medical and productivity costs attributable to CVD. CONCLUSIONS: The burden of informal caregiving for patients with CVD is significant; accounting for these costs increases total CVD costs to $616 billion in 2015 and $1.2 trillion in 2035. These estimates have important research and policy implications, and they may be used to guide policy development to reduce the burden of CVD on patients and their caregivers.

Estimation of Breast Cancer Incident Cases and Medical Care Costs Attributable to Alcohol Consumption Among Insured Women Aged <45 Years in the U.S.

INTRODUCTION: This study estimated the percentage of breast cancer cases, total number of incident cases, and total annual medical care costs attributable to alcohol consumption among insured younger women (aged 18-44 years) by type of insurance and stage at diagnosis. METHODS: The study used the 2012-2013 National Survey on Drug Use and Health, cancer incidence data from two national registry programs, and published relative risk measures to estimate the: (1) alcohol-attributable fraction of breast cancer cases among younger women by insurance type; (2) total number of breast cancer incident cases attributable to alcohol consumption by stage at diagnosis and insurance type among younger women; and (3) total annual medical care costs of treating breast cancer incident cases attributable to alcohol consumption among younger women. Analyses were conducted in 2016; costs were expressed in 2014 U.S. dollars. RESULTS: Among younger women enrolled in Medicaid, private insurance, and both groups, 8.7% (95% CI=7.4%, 10.0%), 13.8% (95% CI=13.3%, 14.4%), and 12.3% (95% CI=11.4%, 13.1%) of all breast cancer cases, respectively, were attributable to alcohol consumption. Localized stage was the largest proportion of estimated attributable incident cases. The estimated total number of breast cancer incident alcohol-attributable cases was 1,636 (95% CI=1,570, 1,703) and accounted for estimated total annual medical care costs of $148.4 million (95% CI=$140.6 million, $156.1 million). CONCLUSIONS: Alcohol-attributable breast cancer has estimated medical care costs of nearly $150 million per year. The current findings could be used to support evidence-based interventions to reduce alcohol consumption in younger women.

Medical costs of treating breast cancer among younger Medicaid beneficiaries by stage at diagnosis.

BACKGROUND: Younger women (aged 18-44 years) diagnosed with breast cancer often face more aggressive tumors, higher treatment intensity, and lower survival rates than older women. In this study, we estimated incident breast cancer costs by stage at diagnosis and by race for younger women enrolled in Medicaid. METHODS: We analyzed cancer registry data linked to Medicaid claims in North Carolina from 2003 to 2008. We used Surveillance, Epidemiology, and End Results (SEER) Summary 2000 definitions for cancer stage. We split breast cancer patients into two cohorts: a younger and older group aged 18-44 and 45-64 years, respectively. We conducted a many-to-one match between patients with and without breast cancer using age, county, race, and Charlson Comorbidity Index. We calculated mean excess total cost of care between breast cancer and non-breast cancer patients. RESULTS: At diagnosis, younger women had a higher proportion of regional cancers than older women (49 vs. 42%) and lower proportions of localized cancers (44 vs. 50%) and distant cancers (7 vs. 9%). The excess costs of breast cancer (all stages) for younger and older women at 6 months after diagnosis were $37,114 [95% confidence interval (CI) = $35,769-38,459] and $28,026 (95% CI = $27,223-28,829), respectively. In the 6 months after diagnosis, the estimated excess cost was significantly higher to treat localized and regional cancer among younger women than among older women. There were no statistically significant differences in excess costs of breast cancer by race, but differences in treatment modality were present among younger Medicaid beneficiaries. CONCLUSIONS: Younger breast cancer patients not only had a higher prevalence of late-stage cancer than older women, but also had higher within-stage excess costs.

A new methodological approach to adjust alcohol exposure distributions to improve the estimation of alcohol-attributable fractions.

BACKGROUND AND AIMS: To assess the burden of excessive alcohol use, researchers estimate alcohol-attributable fractions (AAFs) routinely. However, under-reporting in survey data can bias these estimates. We present an approach that adjusts for under-reporting in the estimation of AAFs, particularly within subgroups. This framework is a refinement of a previous method conducted by Rehm et al. METHODS: We use a measurement error model to derive the 'true' alcohol distribution from a 'reported' alcohol distribution. The 'true' distribution leverages per-capita sales data to identify the distribution average and then identifies the shape of the distribution with self-reported survey data. Data are from the National Alcohol Survey (NAS), the National Household Survey on Drug Abuse (NHSDA) and the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). We compared our approach with previous approaches by estimating the AAF of female breast cancer cases. RESULTS: Compared with Rehm et al.'s approach, our refinement performs similarly under a gamma assumption. For example, among females aged 18-25 years, the two approaches produce estimates from NHSDA that are within a percentage point. However, relaxing the gamma assumption generally produces more conservative evidence. For example, among females aged 18-25 years, estimates from NHSDA based on the best-fitting distribution are only 19.33% of breast cancer cases, which is a much smaller proportion than the gamma-based estimates of approximately 28%. CONCLUSIONS: A refinement of Rehm et al.'s approach to adjusting for underreporting in the estimation of alcohol-attributable fractions provides more flexibility. This flexibility can avoid biases associated with failing to account for the underlying differences in alcohol consumption patterns across different study populations. Comparisons of our refinement with Rehm et al.'s approach show that results are similar when a gamma distribution is assumed. However, results are appreciably lower when the best-fitting distribution is chosen versus gamma-based results.

Breast cancer treatment costs in younger, privately insured women.

PURPOSE: Younger women (under age 45 years) diagnosed with breast cancer often face more aggressive tumors, higher treatment intensity, lower survival rates, and greater financial hardship. The purpose of this study was to estimate breast cancer costs by stage at diagnosis during the first 18 months of treatment for privately insured younger women. METHODS: We analyzed North Carolina cancer registry data linked to claims data from private insurers from 2003 to 2010. Breast cancer patients were split into two cohorts: a younger and older group aged 21-44 and 45-64 years, respectively. We conducted a cohort study and matched women with and without breast cancer using age, ZIP, and Charlson Comorbidity Index. We calculated mean excess costs between breast cancer and non-breast cancer patients at 6, 12, and 18 months. RESULTS: For younger women, AJCC 6th edition stage II cancer was the most common at diagnosis (40%), followed by stage I (34%). On the other hand, older women had more stage I (46%) cancer followed by stage II (34%). The excess costs for younger and older women at 12 months were $97,486 (95% confidence interval [CI] $93,631-101,341) and $75,737 (95% CI $73,962-77,512), respectively. Younger breast cancer patients had both a higher prevalence of later-stage disease and higher within-stage costs. CONCLUSIONS: The study reports high costs of treatment for both younger and older women than a non-cancer comparison group; however, the estimated excess cost was significantly higher for younger women. The financial implications of breast cancer treatment costs for younger women need to be explored in future studies.