Second-generation antipsychotics (SGAs) are commonly associated with metabolic side effects (i.e., weight gain, dyslipidemia, glucose intolerance) (1), which can develop into metabolic syndrome, a cluster of findings (including hypertension, insulin resistance, abdominal obesity, and atherogenic dyslipedemia) associated with increased risk of developing type 2 diabetes and cardiovascular disease (2). In recognition of the urgent need to reduce iatrogenic morbidity and improve the physical health monitoring of patients who are receiving SGAs, several guidelines have been proposed (3–5). Despite psychiatrists' awareness of the metabolic adverse effects of antipsychotic medications (6), widespread adoption of the guidelines has been lacking, and only a minority of patients prescribed antipsychotics are screened according to best-practice recommendations (7–9).
We created a quality improvement (QI) intervention in an academic hospital psychiatry resident outpatient clinic with the aim of increasing documented screening for metabolic abnormalities in patients being prescribed antipsychotic medications. We hypothesized that baseline rates of documented screening would be low (less than 20%), in keeping with previously published evidence (7–9) and that rates of documented screening would increase after the intervention.
Institutional review board (IRB) approval and waiver of informed consent was obtained from the Partners Health Care IRB. The study period was October 1, 2008 to October 1, 2009.
Quality-Improvement (QI) Intervention
The core components of our QI intervention included input from resident focus groups, resident education, and the creation of a Metabolic Screening Bundle template (a standardized, provider-populated form embedded in the psychiatry progress-note section of the electronic medical record [EMR]). Three 1-hour educational sessions for residents were conducted (by authors IRW, OF, and APW) to review antipsychotic medication-associated metabolic abnormalities, and residents and their supervisors were provided with literature on the current standards-and-practice guidelines (3–5). The first education session (October 2008) was directed at all residents seeing patients in outpatient clinic (Post-Graduate Year [PGY] 2, PGY3, PGY4); the second (March 2009) targeted residents beginning their clinic experience (PGY2), and was repeated for incoming PGY2 clinic residents (July 2009). Approximately 45 residents took part in the education sessions.
The standard we recommended in our clinic was at least annual metabolic screening of all patients prescribed any dose of any antipsychotic medication. We recommended screening with any dose, given that there are limited data available on dose-response of metabolic side effects, and published guidelines make no dose-specific recommendations. We included all antipsychotic medications, given the association with weight gain and first-generation antipsychotics, especially low-potency agents. Consistent with guidelines (4), residents were taught to monitor more frequently upon first initiating antipsychotic medications; however, for the purposes of this study, we viewed annual screening as an easily-measured and important first step.
We developed a standardized template for documenting the four components of the “Metabolic Screening Bundle,” (including body mass index [BMI]; blood pressure [BP]; fasting glucose; and fasting lipid panel, including total cholesterol, high-density lipoprotein, low-density lipoprotein, and triglycerides), which was integrated into psychiatry progress-note templates in the EMR. “Bundling,” the process of performing together interventions to improve clinical outcomes, has been successfully used in other areas of medicine, such as ventilator care (10). Also, we implemented a fasting laboratory test instruction sheet to be distributed to patients. Residents participated in a focus group mid-way through the intervention to help identify ongoing barriers to implementation. As a result of the resident feedback, we displayed a BMI table near the main clinic scale to facilitate point-of-care calculation of BMI.
Defining the Clinic Population
The study population was identified by individual clinic rosters maintained by each resident at baseline (10/01/2008) and each quarterly audit period thereafter (1/01/2009, 4/01/2009, 7/01/2009, 10/01/2009). All patients age 18 and over who received psychopharmacology management by psychiatry residents and were prescribed any antipsychotic medication during the study period were included in the study. Given the fluid nature of the outpatient clinic (i.e., new patient intakes, termination, or loss to follow-up), the population at each audit period was slightly different. Individual provider information was not tracked because of resident provider transitions at the change in academic year.
Audits of the EMR were completed at baseline and each quarter for the following year (by authors IRW, MJV, and JBS). Audits assessed whether a patient was currently being prescribed antipsychotics and whether individual elements of the Metabolic Screening Bundle had been documented at any point in the 12 months before the audit date, as determined by review of psychiatry progress notes in the EMR. Elements of the bundle were counted as being completed if a value or a reference to a value was documented in a psychiatry progress-note (e.g., “Fasting lipids completed and found to be normal.”). Data gathered at the time of patient entry into the study included: age, race, gender, primary-care provider, and diagnoses according to criteria from the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR). Data collected from progress-notes for each audit period included names and dosage of all standing and prn antipsychotic medications and components of the Metabolic Screening Bundle.
Data were analyzed with Microsoft Excel and SPSS 17.0. Frequencies were used to determine rates of screening at baseline and each quarterly audit. Further statistical analysis, using McNemar's test, compared frequencies at baseline and Quarter 4 for patients who were persistent users of antipsychotic medications (i.e., throughout the entire study period).
At study baseline, 140 patients of 390 total patients in the clinic met inclusion criteria; at Quarter 1, 154 of 419; at Quarter 2, 146 of 425; at Quarter 3, 138 of 437; and at Quarter 4, 131 of 436 (representing 30%–36% of the total clinic sample). In sum, 206 adult patients were prescribed an antipsychotic medication for at least one audit during the entire study period, thus meeting inclusion criteria. A total of 39 different psychiatry residents provided care for these patients throughout the study period.
Among these 206 patients, the mean age was 41 years (SD: 1 year), and 51% were women. Race was predominantly white (83%), with a small proportion of black (7%), Hispanic (5%), and Asian (4%) patients. Patients' insurance coverage was two-thirds public insurance (e.g., Medicare, state Medicaid) and one-third private insurance. All patients had an identified primary-care provider (PCP), with two-thirds having a PCP affiliated with the same academic medical center as the psychiatry clinic. The most prevalent diagnoses were affective disorders (e.g., major depressive disorder [32%], bipolar disorder [23%], mood disorder not otherwise specified [17%]), anxiety disorders (e.g., anxiety disorder not otherwise specified [19%], posttraumatic stress disorder [12%], obsessive-compulsive disorder [11%], generalized anxiety disorder [10%]), and psychotic disorders (e.g., psychosis not otherwise specified [12%], schizophrenia [11%]).
Rates of resident documentation of the component parts of the Metabolic Screening Bundle in the preceding 12 months increased from baseline audit through the Quarter 4 audit. Documentation increased from 5% at baseline to 44% at Quarter 4 for BMI; 4% to 39% for BP; 15% to 55% for fasting glucose; and 14% to 55% for fasting lipid panel.
Additional subgroup analysis was conducted on the 90 patients who were continuing users of antipsychotic medications (i.e., met inclusion criteria from the baseline audit through Quarter 4). Documentation increased from 7% at baseline to 49% at Quarter 4 for BMI; 4% to 43% for BP; 17% to 59% for fasting glucose; 18% to 62% for fasting lipid panel; and 1% to 31% for the full Metabolic Screening Bundle. All changes were statistically significant (p<0.0001).
The QI project interventions were successful in increasing rates of documented metabolic screening in an outpatient population prescribed antipsychotic medications by psychiatry residents. The low rates of glucose and lipid screening at the start of this intervention were similar to screening rates following the American Diabetes Association and American Psychiatric Association Consensus Statement observed in recent studies of large commercial managed-care and Medicaid administrative claims databases, which showed rates of lipid screening around 10% and glucose screening from 20% to 30% (8, 9). Improvement in documentation rates were similarly observed by Barnes et al. in their 2008 study of a quality-improvement program that included a provider-education component in an effort to improve screening for the metabolic syndrome in a sample of psychiatric outpatients cared for by assertive outreach teams in the United Kingdom (7).
Although significant gains in screening rates were observed, from 45% to 65% of patients remained unscreened for various components of the Metabolic Screening Bundle. Of the components of the bundle, blood pressure was the least documented at both beginning and end of the study. The low documentation rate of blood pressure may be related to several barriers to implementation, including the lack of appropriately-sized cuffs for larger patients, the limited availability of blood-pressure cuffs, and provider discomfort with physical contact with patients. Automatic blood-pressure cuffs with wide availability in the clinic may help overcome these barriers.
Several additional barriers to monitoring were noted by residents in their focus-group session, including: problems with the physical plant of the clinic; workflow and time constraints; information-technology limitations; and communication challenges, because one-third of our clinic population had non-affiliated primary-care providers. The addition of individualized feedback about monitoring rates to providers, as seen in the Barnes study, may assist with further increasing rates of monitoring.
Study strengths included the ability to look at individual patient and provider interactions regarding implementation of screening guidelines and determining whether screening data were documented by psychiatric providers, thus signifying provider awareness of the data.
This study has several limitations. Mainly, this intervention was implemented without a control group; thus, it is difficult to know what changes in rates of screening may have occurred naturally regardless of our QI project interventions. Limitations of the chart audit include inability to capture undocumented results or results documented places other than psychiatry notes that may have been reviewed by the resident but not remarked on in the progress-note. Thus, documentation rates may underrepresent the actual metabolic monitoring that has been considered. It is also unclear whether the gains made with this intervention and this cohort of residents can be sustained without a dedicated group of residents championing change.
No financial support was received for this study.
Dr. Henderson: research grant support from Takeda Pharmaceuticals and Johnson and Johnson/Ortho McNeil, honoraria for CME lectures from Pfizer and Reed Medical Education, honorarium for Advisory board from Merck; consultant for Novartis, Alkermes, and NuPathe; Dr. Freudenreich: research grant support from Pfizer, consultant for Beacon Health Strategies, honoraria for CME lectures from Reed Medical Education. The remaining authors have no competing interests to disclose.