Barriers to Screening
Barriers to screening exist at the level of the individual patient and provider as well as at the clinic and larger systems levels. Lack of provider awareness of evidence-based guidelines for metabolic monitoring despite the presence of the 2004 ADA/APA guidelines has been cited by researchers as an impediment to screening. In a survey of primary care clinicians in San Francisco, Mangurian et al found that 40% of primary care providers did not know about the ADA/APA consensus guidelines for metabolic monitoring. The same survey of primary care providers identified additional impediments to screening, including obstacles to collaboration with psychiatric providers and to scheduling patients for psychiatric follow-up [39]. Another clinician survey conducted by Parameswaran et al found that psychiatrists viewed psychiatric illness severity, lack of staff time, and lack of clinician time as significant barriers to metabolic screening. In addition, clinicians identified factors related to the complexity of coordinating care across systems as obstacles; these included barriers to coordinating follow-up with medical providers, long wait times for patients to see medical providers, and difficulty collaborating with medical providers [40].
Other systems-level barriers include lack of a population-based approach to screening (eg, registries) and lack of electronic record integration, which impedes the ability of primary care and psychiatry providers to share information related to the ordering of metabolic screening tests and prescribing of medications [41]. Mangurian calls for integration of electronic medical record systems between primary care and psychiatry, a population-based approach to metabolic monitoring utilizing registries and other elements of collaborative care models, and primary care consultation to aid in the treatment of metabolic abnormalities [41]. Amiel et al point to systems-level factors “including but not limited to … poor access to general medical services, inadequate medical record-keeping infrastructure, lack of in-system compliance incentives and lack of centralized oversight” [26].
Based on their experience implementing a computer-based intervention for metabolic monitoring, Lai et al propose that the following factors may influence providers’ engagement in metabolic monitoring: lack of apparent symptoms to suggest metabolic syndrome, patients’ lack of engagement in care, and poor access to care. They identify additional factors at the clinician level to include under-recognition of the need for metabolic monitoring, lack of familiarity with screening guidelines, lack of agreement with guidelines, and the potential for individual clinicians to forget to order tests [42]. At the systems-level, they identify the absence of ongoing training as a potential reason why sustained testing was not observed in their intervention [42].
In a 2011 survey of providers prescribing antipsychotic medication to Medicaid beneficiaries in Missouri, Morrato and colleagues found that factors limiting frequency of health care utilization were closely linked to lack of metabolic testing. They also noted disparities in screening guidelines may lead to lack of routine metabolic monitoring; providers may screen based on prescribed medication, diagnosis, or other risk factor based stratification depending on the guidelines followed [34].
Current Unmet Needs
Vulnerable Populations
Though rates of metabolic screening remain low for all groups prescribed antipsychotic medications, studies have consistently shown low rates of screening among children and adolescents [35,36]. Edelsohn and colleagues hypothesize that the cause of these low rates is multifactorial, including that guardians may be reluctant to have young people undergo blood draws [35]. Morrato and colleagues suggest that policymakers should focus initiatives on younger, healthier adults, who they found to have lower rates of screening [37].
Racial and ethnic minorities with SMI constitute another particularly vulnerable population, with some studies showing an increased risk of metabolic sequelae and lower likelihood of treatment for diabetes and other metabolic derangements among African American and Latino populations with SMI [14,43,44].
Integration of Care
Lack of widespread integration of care between mental health and primary care remains another unmet need [41]. Hasnain and colleagues recommend improved communication between mental health and primary care clinicians to coordinate care to improve rates of monitoring, facilitate early follow-up of metabolic abnormalities, and avoid duplication of monitoring efforts [45]. Morrato and colleagues recommend that efforts to increase rates of metabolic monitoring be targeted not only to providers practicing in community mental health centers, but also to other practice settings including primary care. They found that for 75% of people prescribed antipsychotic medications, the prescriptions were started by prescribing providers who practiced outside of a community mental health center [34] and recommend that educational initiatives and performance improvement interventions broaden to include primary care and other care settings [34].
Potential Interventions for Improvement
Early interventions to improve metabolic screening rates have included educational initiatives to teach providers about consensus guidelines. However, initiatives to educate clinicians on metabolic monitoring have shown to be inadequate to significantly improve rates of screening [33]. Therefore, subsequent initiatives have sought to influence screening rates by targeting behavior of individual clinicians with point-of-care tools, electronic reminders, or through systems-level reorganization towards population-based care [27,42,46].