The impact of preexisting psychiatric disorders and antidepressant use on COVID-19 related outcomes: a multicenter study.

Pre-existing mental disorders are linked to COVID-19-related outcomes. However, the findings are inconsistent and a thorough analysis of a broader spectrum of outcomes such as COVID-19 infection severity, morbidity, and mortality is required. We investigated whether the presence of psychiatric diagnoses and/or the use of antidepressants influenced the severity of the outcome of COVID-19. This retrospective cohort study evaluated electronic health records from the INSIGHT Clinical Research Network in 116,498 individuals who were diagnosed with COVID-19 between March 1, 2020, and February 23, 2021. We examined hospitalization, intubation/mechanical ventilation, acute kidney failure, severe sepsis, and death as COVID-19-related outcomes. After using propensity score matching to control for demographics and medical comorbidities, we used contingency tables to assess whether patients with (1) a history of psychiatric disorders were at higher risk of more severe COVID-19-related outcomes and (2) if use of antidepressants decreased the risk of more severe COVID-19 infection. Pre-existing psychiatric disorders were associated with an increased risk for hospitalization, and subsequent outcomes such as acute kidney failure and severe sepsis, including an increased risk of death in patients with schizophrenia spectrum disorders or bipolar disorders. The use of antidepressants was associated with significantly reduced risk of sepsis (p = 0.033), death (p = 0.026). Psychiatric disorder diagnosis prior to a COVID-19-related healthcare encounter increased the risk of more severe COVID-19-related outcomes as well as subsequent health complications. However, there are indications that the use of antidepressants might decrease this risk. This may have significant implications for the treatment and prognosis of patients with COVID-19.

Racial differences in COVID-19 severity associated with history of substance use disorders and overdose: Findings from multi-site electronic health records in New York City.

Substance use disorders (SUD) are associated with increased risk of worse COVID-19 outcomes. Likewise, racial/ethnic minority patients experience greater risk of severe COVID-19 disease compared to white patients. Providers should understand the role of race and ethnicity as an effect modifier on COVID-19 severity among individuals with SUD. This retrospective cohort study assessed patient race/ethnicity as an effect modifier of the risk of severe COVID-19 disease among patients with histories of SUD and overdose. We used merged electronic health record data from 116,471 adult patients with a COVID-19 encounter between March 2020 and February 2021 across five healthcare systems in New York City. Exposures were patient histories of SUD and overdose. Outcomes were risk of COVID-19 hospitalization and subsequent COVID-19-related ventilation, acute kidney failure, sepsis, and mortality. Risk factors included patient age, sex, and race/ethnicity, as well as medical comorbidities associated with COVID-19 severity. We tested for interaction between SUD and patient race/ethnicity on COVID-19 outcomes. Findings showed that Non-Hispanic Black, Hispanic/Latino, and Asian/Pacific Islander patients experienced a higher prevalence of all adverse COVID-19 outcomes compared to non-Hispanic white patients. Past-year alcohol (OR 1.24 [1.01-1.53]) and opioid use disorders (OR 1.91 [1.46-2.49]), as well as overdose history (OR 4.45 [3.62-5.46]), were predictive of COVID-19 mortality, as well as other adverse COVID-19 outcomes. Among patients with SUD, significant differences in outcome risk were detected between patients of different race/ethnicity groups. Findings indicate that providers should consider multiple dimensions of vulnerability to adequately manage COVID-19 disease among populations with SUDs.

ICD-11: A catalyst for advancing patient safety surveillance globally.

The World Health Organization's (WHO) international classification of disease version 11 (ICD-11) contains several features which enable improved classification of patient safety events. We have identified three suggestions to facilitate adoption of ICD-11 from the patient safety perspective. One, health system leaders at national, regional, and local levels should incorporate ICD-11 into all approaches to monitor patient safety. This will allow them to take advantage of the innovative patient safety classification methods embedded in ICD-11 to overcome several limitations related to existing patient safety surveillance methods. Two, application developers should incorporate ICD-11 into software solutions. This will accelerate adoption and utility of software-enabled clinical and administrative workflows relevant to patient safety management. This is enabled as a result of the ICD-11 application programming interface (or API) developed by the WHO. Third, health system leaders should adopt the ICD-11 using a continuous improvement framework. This will help leaders at national, regional and local levels to take advantage of specific existing initiatives which will be strengthened by ICD-11, including peer review comparisons, clinician engagement, and alignment of front-line safety efforts with post marketing surveillance of medical technologies. While the investment to adopt ICD-11 will be considerable, these will be offset by reducing the ongoing costs related to a lack of accurate routine information.

Coding mechanisms for diagnosis timing in the International Classification of Diseases, Version 11.

BACKGROUND: Diagnoses that arise after admission are of interest because they can represent complications of health care, acute conditions arising de novo, or acute decompensation of a chronic comorbidity occurring during the hospital stay. Three countries in the world have adopted diagnosis timing codes for a number of years. Their experience demonstrates the feasibility and utility of associating an International Classification of Diseases, Version 9 or International Classification of Diseases, Version 10 diagnostic code with information on diagnosis timing, either as part of a diagnostic field or as a separate field. However, diagnosis timing is not an integrated feature of these two classifications as it will be for International Classification of Diseases, Version 11. METHODS: We examine the different types of diagnosis timing that can be used to describe complex patients and present examples of how the new International Classification of Diseases, Version 11 codes may be used. RESULTS: Extension codes are one of the important new features of International Classification of Diseases, Version 11 and allow more specificity in diagnosis timing. CONCLUSION: Imbedded and standardized diagnosis timing information is possible within the International Classification of Diseases, Version 11 classification system.

The three-part model for coding causes and mechanisms of healthcare-related adverse events.

ICD-11 provides a promising new way to capture healthcare-related harm or injury. In this paper, we elaborate on the framework for describing healthcare-related events where there is a presumed causal link between an event and underlying healthcare-related factors. The three-part model for describing healthcare-related harm or injury in ICD-11 consists of (1) a healthcare-related activity that is the cause of injury or other harm (selected from Chapter 23 of ICD-11); (2) a mode or mechanism of injury or harm, related to the underlying cause (also from Chapter 23 of ICD-11); and (3) the harmful consequences of the event to the patient, selected from any of Chapters 1 through 22 of ICD-11 (most importantly, the injury or harm experienced by the patient). Concepts from these three elements are linked/clustered through postcoordination to reflect the three-part model in a single coded expression. ICD-11 contains many novel features, and the three-part model described here for healthcare-related adverse events is a notable example.

Opioid use disorder Cascade of care framework design: A roadmap.

Unintentional overdose deaths, most involving opioids, have eclipsed all other causes of US deaths for individuals less than 50 years of age. An estimated 2.4 to 5 million individuals have opioid use disorder (OUD) yet a minority receive treatment in a given year. Medications for OUD (MOUD) are the gold standard treatment for OUD however early dropout remains a major challenge for improving clinical outcomes. A Cascade of Care (CoC) framework, first popularized as a public health accountability strategy to stem the spread of HIV, has been adapted specifically for OUD. The CoC framework has been promoted by the NIH and several states and jurisdictions for organizing quality improvement efforts through clinical, policy, and administrative levers to improve OUD treatment initiation and retention. This roadmap details CoC design domains based on available data and potential linkages as individual state agencies and health systems typically rely on limited datasets subject to diverse legal and regulatory requirements constraining options for evaluations. Both graphical decision trees and catalogued studies are provided to help guide efforts by state agencies and health systems to improve data collection and monitoring efforts under the OUD CoC framework.

Implementation of Behavioral Health Integration in Small Primary Care Settings: Lessons Learned and Future Directions.

Primary care practices are in great need of practical guidance on the steps they can take to build behavioral health integration (BHI) capacities, particularly for smaller practice settings with fewer resources. 11 small primary care sites (≤ 5 providers) throughout New York State utilized a continuum framework of core components of BHI in combination with technical assistance. Surveys were collected at baseline, 6-months, and 12-months. Semi-structured interviews and focus groups were conducted during site visits, and a stakeholder roundtable was facilitated to address broader themes. Data were analyzed using qualitative thematic analysis. Practices reported successful engagement with the framework and actively participated in planning and advancing BHI operations. Greater success was observed in practices with existing on-site BHI services, identified champions for BHI, early and sustained training and involvement of providers and administrators, use of collaborative agreements with external behavioral health providers, and capacity to successfully receive reimbursements for BHI services. Advancing health information technologies was a challenge across sites. Financing and policy factors were viewed as critically important to advance integration efforts. The pilot of a continuum framework offers lessons for primary care practices and policymakers to advance integrated BH care.

Empirically identified networks of healthcare providers for adults with mental illness.

BACKGROUND: Policies target networks of providers who treat people with mental illnesses, but little is known about the empirical structures of these networks and related variation in patient care. The goal of this paper is to describe networks of providers who treat adults with mental illness in a multi-payer database based medical claims data in a U.S. state. METHODS: Provider networks were identified and characterized using paid inpatient, outpatient and pharmacy claims related to care for people with a mental health diagnosis from an all-payer claims dataset that covers both public and private payers. RESULTS: Three nested levels of network structures were identified: an overall network, which included 21% of providers (N = 8256) and 97% of patients (N = 476,802), five communities and 24 sub-communities. Sub-communities were characterized by size, provider composition, continuity-of-care (CoC), and network structure measures including mean number of connections per provider (degree) and average number of connections who were connected to each other (transitivity). Sub-community size was positively associated with number of connections (r = .37) and the proportion of psychiatrists (r = .41) and uncorrelated with network transitivity (r = -.02) and continuity of care (r = .00). Network transitivity was not associated with CoC after adjustment for provider type, number of patients, and average connection CoC (p = .85). CONCLUSIONS: These exploratory analyses suggest that network analysis can provide information about the networks of providers that treat people with mental illness that is not captured in traditional measures and may be useful in designing, implementing, and studying interventions to improve systems of care. Though initial results are promising, additional empirical work is needed to develop network-based measures and tools for policymakers.

Bridging the Behavioral Health Gap in Serious Illness Care: Challenges and Strategies for Workforce Development.

Comorbidity with behavioral health conditions is highly prevalent among those experiencing serious medical illnesses and is associated with poor outcomes. Siloed provision of behavioral and physical healthcare has contributed to a workforce ill-equipped to address the often complex needs of these clinical populations. Trained specialist behavioral health providers are scarce and there are gaps in core behavioral health competencies among serious illness care providers. Core competency frameworks to close behavioral health training gaps in primary care exist, but these have not extended to some of the distinct skills and roles required in serious illness care settings. This paper seeks to address this issue by describing a common framework of training competencies across the full spectrum of clinical responsibility and behavioral health expertise for those working at the interface of behavioral health and serious illness care. The authors used a mixed-method approach to develop a model of behavioral health and serious illness care and to delineate seven core skill domains necessary for practitioners working at this interface. Existing opportunities for scaling-up the workforce as well as priority policy recommendation to address barriers to implementation are discussed.

Rates and Impact of Adherence to Recommended Care for Unhealthy Alcohol Use.

BACKGROUND: Unhealthy alcohol use is a major worldwide health problem. Yet few studies have assessed provider adherence to the alcohol-related care recommended in clinical practice guidelines, nor links between adherence to recommended care and outcomes. OBJECTIVES: To describe quality of care for unhealthy alcohol use and its impacts on drinking behavior RESEARCH DESIGN: Prospective observational cohort study of quality of alcohol care for the population of patients screening positive for unhealthy alcohol use in a large Veterans Affairs health system. PARTICIPANTS: A total of 719 patients who screened positive for unhealthy alcohol use at one of 11 primary care practices and who completed baseline and 6-month telephone interviews. MAIN MEASURES: Using administrative encounter and medical record data, we assessed three composite and 21 individual process-based measures of care delivered across primary and specialty care settings. We assessed self-reported daily alcohol use using telephone interviews at baseline and 6-month follow-up. KEY RESULTS: The median proportion of patients who received recommended care across measures was 32.8% (range < 1% for initiating pharmacotherapy to 93% for depression screening). There was negligible change in drinking for the study population between baseline and 6 months. In covariate-adjusted analyses, no composites were significantly associated with changes in heavy drinking days or drinks per week, and just one of nine individual measures tested was significantly associated. In a subsample of patients drinking above recommended weekly limits prior to screening, two of nine individual measures were significantly associated. CONCLUSIONS: This study shows wide variability in receipt of recommended care for unhealthy alcohol use. Receipt of recommended interventions for reducing drinking was frequently not associated with decreased drinking. Results suggest deficits in provision of comprehensive alcohol care and in understanding how to improve population-based drinking outcomes.

Collaborative care: enough of the why; what about the how?

The clinical and cost-effectiveness of collaborative care for improving outcomes in people with mental and physical comorbidities is well established. However, translating these models into enduring change in routine care has proved difficult. In this editorial we outline how to shift the conversation on collaborative care from 'what are we supposed to do?' to 'how we can do this'.Declaration of interestP.P.R. has received honoraria from Publicis LifeBrands and the Institute for Healthcare Improvement outside of the submitted work. H.A.P. reports personal fees from the BIND Health Plan outside of the submitted work; and is a Member of the Council on Quality of Care of the American Psychiatric Association.

Evolving Models of Integrated Behavioral Health and Primary Care.

PURPOSE OF REVIEW: Mental and physical disorders commonly co-occur leading to higher morbidity and mortality in people with mental and substance use disorders (collectively called behavioral health disorders). Models to integrate primary and behavioral health care for this population have not yet been implemented widely across health systems, leading to efforts to adapt models for specific subpopulations and mechanisms to facilitate more widespread adoption. RECENT FINDINGS: Using examples from the UK and USA, we describe recent advances to integrate behavioral and primary care for new target populations including people with serious mental illness, people at the extremes of life, and for people with substance use disorders. We summarize mechanisms to incentivize integration efforts and to stimulate new integration between health and social services in primary care. We then present an outline of recent enablers for integration, concentrating on changes to funding mechanisms, developments in quality outcome measurements to promote collaborative working, and pragmatic guidance aimed at primary care providers wishing to enhance provision of behavioral care. Integrating care between primary care and behavioral health services is a complex process. Established models of integrated care are now being tailored to target specific patient populations and policy initiatives developed to encourage adoption in particular settings. Wholly novel approaches to integrate care are significantly less common. Future efforts to integrate care should allow for flexibility and innovation around implementation, payment models that support delivery of high value care, and the development of outcome measures that incentivize collaborative working practices.

Community Interventions to Promote Mental Health and Social Equity.

PURPOSE OF REVIEW: We review recent community interventions to promote mental health and social equity. We define community interventions as those that involve multi-sector partnerships, emphasize community members as integral to the intervention, and/or deliver services in community settings. We examine literature in seven topic areas: collaborative care, early psychosis, school-based interventions, homelessness, criminal justice, global mental health, and mental health promotion/prevention. We adapt the social-ecological model for health promotion and provide a framework for understanding the actions of community interventions. RECENT FINDINGS: There are recent examples of effective interventions in each topic area. The majority of interventions focus on individual, family/interpersonal, and program/institutional social-ecological levels, with few intervening on whole communities or involving multiple non-healthcare sectors. Findings from many studies reinforce the interplay among mental health, interpersonal relationships, and social determinants of health. There is evidence for the effectiveness of community interventions for improving mental health and some social outcomes across social-ecological levels. Studies indicate the importance of ongoing resources and training to maintain long-term outcomes, explicit attention to ethics and processes to foster equitable partnerships, and policy reform to support sustainable healthcare-community collaborations.

Measuring Efficiency at the Interface of Behavioral and Physical Health Care.

BACKGROUND: Measures of efficiency in healthcare delivery, particularly between different parts of the healthcare system could potentially improve health resource utilization. We use a typology adapted from the Agency for Healthcare Research and Quality to characterize current measures described in the literature by stakeholder perspective (payer, provider, patient, policy-maker), type of output (reduced utilization or improved outcomes) and input (physical, financial or both). AIMS OF THE STUDY: To systematically describe measures of healthcare efficiency at the interface of behavioral and physical healthcare and identify gaps in the literature base that could form the basis for further measure development. METHODS: We searched the Medline database for studies published in English in the last ten years with the terms 'efficiency', 'inefficiency', 'productivity', 'cost' or 'QALY' and 'mental' or 'behavioral' in the title or abstract. Studies on healthcare resource utilization, costs of care, or broader healthcare benefits to society, related to the provision of behavioral health care in physical health care settings or to people with physical health conditions or vice versa were included. RESULTS: 85 of 6,454 studies met inclusion criteria. These 85 studies described 126 measures of efficiency. 100 of these measured efficiency according to the perspective of the purchaser or provider, whilst 13 each considered efficiency from the perspective of society or the consumer. Most measures counted physical resources (such as numbers of therapy sessions) rather than the costs of these resources as inputs. Three times as many measures (95) considered service outputs as did quality outcomes (31). DISCUSSION: Measuring efficiency at the interface of behavioral and physical care is particularly difficult due to the number of relevant stakeholders involved, ambiguity over the definition of efficiency and the complexity of providing care for people with multimorbidity. Current measures at this interface concentrate on a limited range of outcomes. LIMITATIONS: We only searched one database and did not review the gray literature, nor solicit a call for relevant but unpublished work. We did not assess the methodological quality of the studies identified. IMPLICATION FOR HEALTH CARE PROVISION AND USE: Most measures of healthcare efficiency are currently viewed from the perspective of payers and providers, with very few studies addressing the benefits of healthcare to society or the individual interest of the consumer. One way this imbalance could be addressed is through much stronger involvement of consumers in measurement-development, for example, by an expansion in patient-reported outcome measures in assessing quality of care. IMPLICATIONS FOR HEALTH POLICIES: Integrating behavioral and physical care is a major area of implementation as health systems in high income countries move from volume to value based care delivery. Measuring efficiency at this interface has the potential to incentivize and also evaluate integration efforts. IMPLICATIONS FOR FURTHER RESEARCH: There has been only one previous systematic review of efficiency measurement and none at the interface of behavioral and physical care. We identify gaps in the evidence base for efficiency measurement which could inform further research and measurement development.

Integrating Behavioral Health and Primary Care Services for People with Serious Mental Illness: A Qualitative Systems Analysis of Integration in New York.

People with co-occurring behavioral and physical conditions receive poorer care through traditional health care services. One solution has been to integrate behavioral and physical care services. This study assesses efforts to integrate behavioral health and primary care services in New York. Semi-structured interviews were conducted with 52 professionals in either group or individual settings. We aimed to identify factors which facilitate or hinder integration for people with serious mental illness and how these factors inter-relate. Content analysis identified structural, process, organizational ("internal") and contextual ("external") themes that were relevant to integration of care. Network analysis delineated the interactions between these. We show that effective integration does not advance along a single continuum from minimally to fully integrated care but along several, parallel pathways reliant upon consequential factors that aid or hinder one another.

Trends in MD/PhD Graduates Entering Psychiatry: Assessing the Physician-Scientist Pipeline.

OBJECTIVE: The goal of this study was to identify trends in MD/PhD graduates entering psychiatry, to compare these trends with other specialties, and to review strategies for enhancing the physician-scientist pipeline. METHODS: Data on 226,588 medical students graduating from Liaison Committee on Medical Education accredited programs between 1999 and 2012 (6626 MD/PhDs) were used to evaluate the number, percentage, and proportion of MD/PhDs entering psychiatry in comparison with other specialties (neurology, neurosurgery, internal medicine, family medicine, and radiation oncology). Linear regression and multiple linear regression determined whether these values increased over time and varied by sex. RESULTS: Over 14 years, an average of 18 MD/PhDs (range 13-29) enrolled in psychiatry each year. The number of MD/PhDs going into psychiatry significantly increased, although these gains were modest (less than one additional MD/PhD per year). The proportion of students entering psychiatry who were MD/PhDs varied between 2.9 and 5.9 per 100 residents, with no significant change over time. There was also no change in the percentage of MD/PhDs entering psychiatry from among all MD/PhD graduates. The rate of increase in the number of MD/PhDs going into psychiatry did not differ significantly from other specialties except for family medicine, which is decreasing. The rate of MD/PhDs going into psychiatry was higher for women, suggesting closure of the sex gap in 17 years. CONCLUSIONS: Despite the increase in the number of MD/PhDs entering psychiatry, these numbers remain low. Expanding the cohort of physician-scientists dedicated to translational research in psychiatry will require a multipronged approach.

Impact of a Mental Health Based Primary Care Program on Quality of Physical Health Care.

We examine the impact of mental health based primary care on physical health treatment among community mental health center patients in New York State using propensity score adjusted difference in difference models. Outcomes are quality indicators related to outpatient medical visits, diabetes HbA1c monitoring, and metabolic monitoring of antipsychotic treatment. Results suggest the program improved metabolic monitoring for patients on antipsychotics in one of two waves, but did not impact other quality indicators. Ceiling effects may have limited program impacts. More structured clinical programs to may be required to achieve improvements in quality of physical health care for this population.

Deriving ICD-10 Codes for Patient Safety Indicators for Large-scale Surveillance Using Administrative Hospital Data.

BACKGROUND: Existing administrative data patient safety indicators (PSIs) have been limited by uncertainty around the timing of onset of included diagnoses. OBJECTIVE: We undertook de novo PSI development through a data-driven approach that drew upon "diagnosis timing" information available in some countries' administrative hospital data. RESEARCH DESIGN: Administrative database analysis and modified Delphi rating process. SUBJECTS: All hospitalized adults in Canada in 2009. MEASURES: We queried all hospitalizations for ICD-10-CA diagnosis codes arising during hospital stay. We then undertook a modified Delphi panel process to rate the extent to which each of the identified diagnoses has a potential link to suboptimal quality of care. We grouped the identified quality/safety-related diagnoses into relevant clinical categories. Lastly, we queried Alberta hospital discharge data to assess the frequency of the newly defined PSI events. RESULTS: Among 2,416,413 national hospitalizations, we found 2590 unique ICD-10-CA codes flagged as having arisen after admission. Seven panelists evaluated these in a 2-round review process, and identified a listing of 640 ICD-10-CA diagnosis codes judged to be linked to suboptimal quality of care and thus appropriate for inclusion in PSIs. These were then grouped by patient safety experts into 18 clinically relevant PSI categories. We then analyzed data on 2,381,652 Alberta hospital discharges from 2005 through 2012, and found that 134,299 (5.2%) hospitalizations had at least 1 PSI diagnosis. CONCLUSION: The resulting work creates a foundation for a new set of PSIs for routine large-scale surveillance of hospital and health system performance.