Joseph J. Parks

Effects of Adopting a Smoke-Free Policy in State Psychiatric Hospitals

OBJECTIVE The aim of this study was to investigate how adopting a smoke-free policy in state psychiatric hospitals affected key factors, including adverse events, smoking cessation treatment options, and specialty training for clinical staff about smoking-related issues. METHODS Hospitals were surveyed in 2006 and 2008 about their smoking policies, smoking cessation aids, milieu management, smoking cessation treatment options, and aftercare planning and referrals for smoking education. Comparisons were made between hospitals that went smoke-free between the two time periods (N=28) and those that did not (N=42). RESULTS Among hospitals that changed to a smoke-free policy, the proportion that reported adverse events decreased by 75% or more in three areas: smoking or tobacco use as a precursor to incidents that led to seclusion or restraint, smoking-related health conditions, and coercion or threats among patients and staff. Hospitals that did not adopt a smoke-free policy cited several barriers, including resistance from staff, patients, and advocates. CONCLUSIONS Although staff were concerned that implementing a smoke-free policy would have negative effects, this was not borne out. Findings indicated that adopting a smoke-free policy was associated with a positive impact on hospitals, as evidenced by a reduction in negative events related to smoking. After adoption of a smoke-free policy, fewer hospitals reported seclusion or restraint related to smoking, coercion, and smoking-related health conditions, and there was no increase in reported elopements or fires. For hospitals adopting a smoke-free policy in 2008, there was no significant difference between 2006 and 2008 in the number offering nicotine replacement therapies or clinical staff specialty training. Results suggest that smoking cessation practices are not changing in the hospital as a result of a change in policy.

A Call for Improved Prevention and Reduction of Obesity Among Persons With Serious Mental Illness

The primary purpose of this Open Forum is to alert the psychiatric community to a recently published policy paper by the National Association of State Mental Health Program Directors (NASMHPD), Obesity Reduction and Prevention Strategies for Individuals With Serious Mental Illness. The report was developed through a comprehensive review of materials and extensive discussions in an expert panel meeting held August 9-10, 2007. The report indicates that psychiatrists who disregard the physical health of their patients and focus only on treating the patients psychiatric condition are not only neglectful but are also contributing to the epidemic of obesity among people with serious mental illness. The NASMHPD Medical Directors Council has concluded that psychiatrists in the public mental health system are doing far too little to prevent and reduce obesity among patients the system serves.

The Role of Clinical Setting and Management Approach in Metabolic Testing Among Youths and Adults Treated With Antipsychotics

OBJECTIVE This study compared metabolic screening among patients who received antipsychotic treatment at community mental health centers (CMHCs), with or without case management, and patients treated elsewhere. METHODS Rates of glucose and lipid testing among youths and adults in Missouri Medicaid (N=9,473) who received antipsychotic treatment at CMHCs, with and without case management, were evaluated. Multivariable logistic regressions determined which characteristics were independently associated with metabolic testing. RESULTS A total of 37.0% and 17.3% of youths and 68.7% and 34.9% of adults had glucose and lipid testing, respectively. Compared with treatment elsewhere, treatment at CMHCs, with or without case management, respectively, was associated with higher odds of glucose testing (youths, adjusted odds ratio [AOR]=1.68 and 1.89; adults, AOR=1.43 and 1.44) and lipid testing (youths, AOR=2.40 and 2.35; adults, AOR=1.97 and 1.48). CONCLUSIONS CMHCs had higher rates of metabolic testing, possibly reflecting Missouris efforts to promote testing in these settings.

Psychiatry’s Role in Improving the Physical Health of Patients With Serious Mental Illness: A Report From the American Psychiatric Association

The American Psychiatric Association Integrated Care Workgroup recently convened an expert panel charged with addressing the role of psychiatry in improving the physical health of persons with serious mental illness. The group reviewed the peer-reviewed and gray literature and developed a set of recommendations grounded in this review. This column summarizes the panels primary findings and recommendations to key stakeholders, including clinicians, health care organizations, researchers, and policy makers.

Performance Measures: From Proliferation to Implementation

Sunderji and colleagues have admirably undertaken the daunting task of examining and cataloguing, in detail, the vastly diverse universe of integration outcome performance measures published to date. The most sobering finding of their work is the extensive variability and complete lack of standardization in both what is being measured and how it is being measured. Of 1,255 implementation and outcome measures, the investigators identified 148 “unique” measures, yielding an average of 8.5 published variants of each unique measurement. Clearly, creating measures and publishing them is much easier and quicker than implementing them, let alone systematically using them. In fact, only 67% (841 of 1,255) of the published measures have been implemented. It is difficult to see the value of publishing ameasure that is never employed. Of the implemented measures, the authors identified 385 that they deem useful. If the previous average of 8.5 variants for each “unique” measure holds up for the subpopulation of measures, that still leaves a total of 45 potential performance measures for integrated care. I’ve seen very few organizations that can systematically measure and improve more than six to eight performance measures at once. We have become lost in a sea of highly variable minutia. It is like trying to apply performance measures to snowflake production. Everything is unique, and we have no consensus on what is optimal. We need to step back and find consensus on basic principles and then adhere to them aswe pursue the particulars. The first and most important goal of measuring performance is not to improve performance, but rather to determine the range of performance and where we, as individual practitioners or organizations, fall within that range. We were all taught that we have a duty to practice within the usual accepted community “standard of practice,” but how are we to know what the standard of practice is? We were commonly taught that it is a given truth derived from a textbook or lecture. More recently, numerous publications proclaim the consensus of various groups of experts on the standard of practice, in rather detailed terms. But surely, some part of the usual community standards of practice must include the range of current practices. There is very little published information on this, and as the Sunderji et al. article amply shows, there is a remarkable lack of uniformity or agreement on how to measure the range of practice. We can effectively undertake projects and interventions to improve our performance only after we learn what the range of outcomes is and where each of us falls within that range. Working on performance improvement without knowing the baseline of the range and one’s position in it is like measuring progress to a destination when you are lost. Standardization is the basis for continuous improvement and quality. It is not possible to improve things that are not standardized because without standardization, we cannot, for example, be sure that we’re giving the same treatment or program twice in a row, let alone whether the treatment or program from one clinician or organization is substantially the same as that from another. Ensuring uniformity of a treatment or program over time or across different treatment settings requires process measurement. Process performance must be defined before outcomes can be effectively measured across multiple providers, let alone improved. Setting uniform standards for a small, operationally manageable set of measures could be the responsibility of providers, payers, or government. In the case of health care, all three have failed to systematically push for standardization because it would mean accepting compromises and constraints on themselves and, more important, entail a great deal of painful work. The providers of health care— integrated, behavioral, or other—are so diverse and numerous that there is no hope of a push for standardization from their side. That leaves the payers and government. In most other mature industries, such as automotive, aviation, retail, and food, major purchasers are deeply involved in improving the quality of operations of their suppliers. The pay-for-performance implementation efforts of payers and government will never achieve substantial success by trying to improve dozens of “unique measures” of integrated care, each of which has multiple variants, in integrated behavioral health care or in any other area of health care.