Multimorbidity and Complexity Among Patients with Cancer in Ontario: A Retrospective Cohort Study Exploring the Clustering of 17 Chronic Conditions with Cancer.

BACKGROUND: Multimorbidity is a concern for people living with cancer, as over 90% have at least one other condition. Multimorbidity complicates care coming from multiple providers who work within separate, siloed systems. Information describing high-risk and high-cost disease combinations has potential to improve the experience, outcome, and overall cost of care by informing comprehensive care management frameworks. This study aimed to identify disease combinations among people with cancer and other conditions, and to assess the health burden associated with those combinations to help healthcare providers more effectively prioritize and coordinate care. METHODS: We used a population-based retrospective cohort design including adults with a cancer diagnosis between March-2003 and April-2013, followed-up until March 2018. We used observed disease combinations defined by level of multimorbidity and partitive (k-means) clusters, ie groupings of similar diseases based on the prevalence of each condition. We assessed disease combination-associated health burden through health service utilization, including emergency department visits, primary care visits and hospital admissions during the follow-up period. RESULTS: 549,248 adults were included in the study. Anxiety, diabetes mellitus, hypertension, and osteoarthritis co-occurred with cancer 1.1 to 5.3 times more often than expected by chance. Disease combinations varied by cancer type and age but were similar between sexes. The largest partitive cluster included cancer and anxiety, with at least 25% of individuals also having osteoarthritis. Cancer also tended to co-occur with hypertension (8.0%) or osteoarthritis (6.2%). There were differences between clusters in healthcare utilization, regardless of the number of disease combinations or clustering approach used. CONCLUSION: Researchers, clinicians, policymakers, and other stakeholders can use the clustering information presented here to improve the healthcare system for people with cancer multimorbidity by developing cluster-specific care management and clinical guidelines for common disease combinations.

Structural Components of Integrated Behavioral Health Care: A Comparison of National Programs.

Initiatives that support and incentivize the integration of behavioral health and general medical care have become a focus of government strategies to achieve the triple aim of improved health, better patient experience, and reduced costs. The authors describe the components of four large-scale national initiatives aimed at integrating care for a wide range of behavioral health needs. Commonalities across these national initiatives highlight health care and social services needs that must be addressed to improve care for people with co-occurring behavioral health and general medical conditions. These findings can inform how to design, test, select, and align the most promising strategies for integrated care in a variety of settings.

Circadian misalignment and weekend alcohol use in late adolescent drinkers: preliminary evidence.

Alcohol use accelerates during late adolescence, predicting the development of alcohol use disorders (AUDs) and other negative outcomes. Identifying modifiable risk factors for alcohol use during this time could lead to novel prevention approaches. Burgeoning evidence suggests that sleep and circadian factors are cross-sectionally and longitudinally linked to alcohol use and problems, but more proximal relationships have been understudied. Circadian misalignment, in particular, is hypothesized to increase the risk for AUDs, but almost no published studies have included a biological measure of misalignment. In the present study, we aimed to extend existing research by assessing the relationship between adolescent circadian misalignment and alcohol use on a proximal timeframe (over two weeks) and by including three complementary measures of circadian alignment. We studied 36 healthy late (18-22 years old, 22 females) alcohol drinkers (reporting ≥1, standard drink per week over the past 30 days) over 14 days. Throughout the study, participants reported prior day's alcohol use and prior night's sleep each morning via smartphone and a secure, browser-based interface. Circadian phase was assessed via the dim light melatonin onset (DLMO) in the laboratory on two occasions (Thursday and Sunday nights) in counterbalanced order. The three measures of circadian alignment included DLMO-midsleep interval, "classic" social jet lag (weekday-weekend difference in midsleep), and "objective" social jet lag (weekday-weekend difference in DLMO). Multivariate imputation by chained equations was used to impute missing data, and Poisson regression models were used to assess associations between circadian alignment variables and weekend alcohol use. Covariates included sex, age, Thursday alcohol use, and Thursday sleep characteristics. As predicted, greater misalignment was associated with greater weekend alcohol use for two of the three alignment measures (shorter DLMO-midsleep intervals and larger weekday-weekend differences in midsleep), while larger weekday-weekend differences in DLMO were associated with less alcohol use. Notably, in contrast to expectations, the distribution of weekday-weekend differences in DLMO was nearly equally distributed between individuals advancing over the weekend and those delaying over the weekend. This unexpected finding plausibly reflects the fact that college students are not subject to the same systematically earlier weekday schedules observed in high school students and working adults. These preliminary findings support the need for larger, more definitive studies investigating the proximal relationships between circadian alignment and alcohol use among late adolescents.

Prioritizing quality measure concepts at the interface of behavioral and physical healthcare.

OBJECTIVE: Integrated healthcare models can increase access to care, improve healthcare quality, and reduce cost for individuals with behavioral and general medical healthcare needs, yet there are few instruments for measuring the quality of integrated care. In this study, we identified and prioritized concepts that can represent the quality of integrated behavioral health and general medical care. DESIGN: We conducted a literature review to identify candidate measure concepts. Experts then participated in a modified Delphi process to prioritize the concepts for development into specific quality measures. SETTING: United States. PARTICIPANTS: Expert behavioral health and general medical clinicians, decision-makers (policy, regulatory and administrative professionals) and patient advocates. MAIN OUTCOME MEASURES: Panelists rated measure concepts on importance, validity and feasibility. RESULTS: The literature review identified 734 measures of behavioral or general medical care, which were then distilled into 43 measure concepts. Thirty-three measure concepts (including a segmentation strategy) reached a predetermined consensus threshold of importance, while 11 concepts did not. Two measure concepts were 'ready for further development' ('General medical screening and follow-up in behavioral health settings' and 'Mental health screening at general medical healthcare settings'). Among the 31 additional measure concepts that were rated as important, 7 were rated as valid (but not feasible), while the remaining 24 concepts were rated as neither valid nor feasible. CONCLUSIONS: This study identified quality measure concepts that capture important aspects of integrated care. Researchers can use the prioritization process described in this study to guide healthcare quality measures development work.

Enrollment of Specialty Mental Health Clinics in a State Medicaid Program to Promote General Medical Services.

OBJECTIVE: To promote integrated general medical care for individuals with serious mental illness, the New York State Office of Mental Health (OMH) established regulations allowing specialty mental health clinics to provide Medicaid-reimbursable health monitoring (HM) and health physicals (HP). This study examined clinics' enrollment in this program to understand its potential to reach individuals with serious mental illness. METHODS: Information on enrollment and characteristics of clinics (N=500) was obtained from OMH administrative databases. Clinic enrollment in the HM/HP program was examined for the program's first five years (2010-2015). Logistic regression models accounting for the clustering of multiple clinics within agencies were used to examine characteristics associated with enrollment. RESULTS: A total of 291 of 500 (58%) licensed clinics in New York State in 2015 enrolled in the HM/HP program, potentially reaching 62% of all Medicaid enrollees with serious mental illness seen in specialty mental health clinics in the state. State-operated clinics were required to participate, and had 91% enrollment. Over half of hospital-affiliated and freestanding mental health clinics elected to enroll (53% and 54%, respectively). In adjusted models, enrollment was higher among freestanding clinics compared with hospital-affiliated clinics, higher in larger than smaller clinics, and higher in county-operated than in private nonprofit clinics. CONCLUSIONS: The high level of enrollment in the HM/HP program indicates strong interest among mental health clinics in providing general medical care services. However, supplemental policies may be needed to extend the program to areas of the mental health system where barriers to general medical care services are highest.

General Medical Outcomes From the Primary and Behavioral Health Care Integration Grant Program.

OBJECTIVE: Primary and Behavioral Health Care Integration (PBHCI) grants aim to improve the health of people with serious mental illness by integrating primary and preventive general medical services into behavioral health settings. This report describes the general medical outcomes of persons served by early cohorts of programs, funded in 2009 or 2010, that participated in this national demonstration project. METHODS: A quasi-experimental, difference-in-differences design was used to compare changes in general medical health among consumers served at three PBHCI clinics (N=322) and three clinics that were selected as matched control sites (N=469). Propensity-score weighting was used to adjust for baseline differences between PBHCI and control clinic populations. Baseline data were collected between 2010 and 2012; follow-up data were collected approximately one year later. General medical outcomes included blood pressure; body mass index; cholesterol, triglyceride, and blood glucose or HbA1c levels; and self-reported tobacco smoking. RESULTS: Compared with consumers served at control clinics, PBHCI consumers had better outcomes for cholesterol: mean reductions in total cholesterol were greater by 36 mg/dL (p<.01), mean reductions in low-density lipoprotein cholesterol were greater by 35 mg/dL (p<.001), and mean increases in high-density lipoprotein cholesterol were greater by 3 mg/dL (p<.05). No significant PBHCI effects were observed for the other health indicators. CONCLUSIONS: Approximately one year of PBHCI treatment resulted in statistically and potentially clinically significant improvements in cholesterol but not in other general medical outcomes examined. More rigorous implementation of integrated care in community behavioral health settings may be needed to further improve the health of adults with serious mental illness.

Integrating Primary Care Into Community Mental Health Centers: Impact on Utilization and Costs of Health Care.

OBJECTIVE: This evaluation was designed to assess the impact of providing integrated primary and mental health care on utilization and costs for outpatient medical, inpatient hospital, and emergency department treatment among persons with serious mental illness. METHODS: Two safety-net, community mental health centers that received a Substance Abuse and Mental Health Services Administration Primary and Behavioral Health Care Integration (PBHCI) grant were the focus of this study. Clinic 1 had a ten-year history of providing integrated services whereas clinic 2 began integrated services with the PBHCI grant. Difference-in-differences (DID) analyses were used to compare individuals enrolled in the PBHCI programs (N=373, clinic 1; N=389, clinic 2) with propensity score-matched comparison groups of equal size at each site by using data obtained from medical records. RESULTS: Relative to the comparison groups, a higher proportion of PBHCI clients used outpatient medical services at both sites following program enrollment (p<.003, clinic 1; p<.001, clinic 2). At clinic 1, PBHCI was also associated with a reduction in the proportion of clients with an inpatient hospital admission (p=.04) and a trend for a reduction in inpatient hospital costs per member per month of $217.68 (p=.06). Hospital-related cost savings were not observed for PBHCI clients at clinic 2 nor were there significant differences between emergency department use or costs for PBHCI and comparison groups at either clinic. CONCLUSIONS: Investments in PBHCI can improve access to outpatient medical care for persons with severe mental illness and may also curb hospitalizations and associated costs in more established programs.

Integrating primary care into community behavioral health settings: programs and early implementation experiences.

OBJECTIVE: This article describes the characteristics and early implementation experiences of community behavioral health agencies that received Primary and Behavioral Health Care Integration (PBHCI) grants from the Substance Abuse and Mental Health Services Administration to integrate primary care into programs for adults with serious mental illness. METHODS: Data were collected from 56 programs, across 26 states, that received PBHCI grants in 2009 (N=13) or 2010 (N=43). The authors systematically extracted quantitative and qualitative information about program characteristics from grantee proposals and semistructured telephone interviews with core program staff. Quarterly reports submitted by grantees were coded to identify barriers to implementing integrated care. RESULTS: Grantees shared core features required by the grant but varied widely in terms of characteristics of the organization, such as size and location, and in the way services were integrated, such as through partnerships with a primary care agency. Barriers to program implementation at start-up included difficulty recruiting and retaining qualified staff and issues related to data collection and use of electronic health records, licensing and approvals, and physical space. By the end of the first year, some problems, such as space issues, were largely resolved, but other issues, including problems with staffing and data collection, remained. New challenges, such as patient recruitment, had emerged. CONCLUSIONS: Early implementation experiences of PBHCI grantees may inform other programs that seek to integrate primary care into behavioral health settings as part of new, large-scale government initiatives, such as specialty mental health homes.