The Effectiveness of a Computer Reminder System for Laboratory Monitoring of Metabolic Syndrome in Schizophrenic Outpatients Using Second-generation Antipsychotics

INTRODUCTION: The Metabolic Syndrome is a set of diverse clinical situations such as diabetes mellitus, hypertension and dyslipidemia. Patients with mental illnesses such as schizophrenia or bipolar disorder have a higher mortality than the general population attributable in 60% to somatic diseases and metabolic syndrome, where second generation antipsychotics increase the risk of weight gain and insulin resistance. Objectives. Correlate the treatment with second generation antipsychotics (SGAs) as a possible predictor for Metabolic Syndrome according to the NCEP ATP III (a) classification. METHODS: Descriptive, cross-sectional correlational study. The sample was of 92 patients, applying an open and convenience sampling due to the mental state of the patients in order to determine their degree of acceptance to the study (Informed Assent) and consent to the legal guardian as the main inclusion criterion. For the analysis, the following variables were considered: blood pressure, weight, height, abdominal circumference, serum levels of triglycerides, glucose and high density lipoproteins. The SPSS 20.0 ® program was used logistic regression analysis with a p-value <0.05 and a confidence level of 95%. RESULTS: SGAs most used was clozapine (54.3%). The correlation analysis showed that sociodemographic aspects such as personal history, habits, physical activity and paraclinical and anthropometric records correlated with the possible diagnosis of metabolic syndrome (p <0.05), but not with SGAs (p> 0.05). ). CONCLUSION: No correlation was found between the presence of the metabolic syndrome and the type of antipsychotic treatment.

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Overcoming barriers to monitoring patients taking second-generation antipsychotics

Mental Health Clinician ◽

10.9740/mhc.2018.03.049 ◽

2018 ◽

Vol 8 (2) ◽

pp. 49-55 ◽

Cited By ~ 1

Author(s):

Anita Peña ◽

Beth DeJongh ◽

Matthew Haas ◽

Michelle Harms

Keyword(s):

Metabolic Syndrome ◽

Second Generation ◽

Vital Signs ◽

Baseline Monitoring ◽

Metabolic Monitoring ◽

Increased Risk ◽

Second Generation Antipsychotics ◽

Awareness Information ◽

Before And After ◽

Patient Referrals

Abstract Introduction: Patients taking second-generation antipsychotics (SGAs) are at increased risk of developing metabolic syndrome because of the side effect profiles of these medications. A medication use evaluation (MUE) was conducted and showed that baseline monitoring rates of metabolic parameters in patients taking SGAs are low. A pharmacist-run metabolic syndrome monitoring clinic (MSMC) is available to mental health (MH) outpatients; however, the clinic is underused by providers. The purpose of this project was to increase baseline metabolic syndrome monitoring rates in patients taking SGAs by implementing interventions to overcome barriers to monitoring and to accessing the MSMC. Methods: Appropriate tools to improve monitoring were obtained, and an electronic consult for the MSMC was created. A presentation and pamphlet were developed to improve awareness. Information about free patient transportation was obtained and distributed. Efficacy was assessed by evaluating patient referrals to the clinic before and after intervention, comparing baseline monitoring rates after implementation with the MUE data, and administering an anonymous survey to outpatient MH providers. Results: There was a 37.5% increase in overall referral rates to the MSMC after intervention, but only 51.5% of patients attended appointments as scheduled. Monitoring of vital signs increased, but monitoring of laboratory parameters decreased. A total of 60% (9 of 15) of providers completed a survey, of which one third indicated they still forget to refer patients to the MSMC. Discussion: Overall, baseline metabolic monitoring rates remained low despite implementing several interventions. Patient and provider outreach is crucial for initiating and maintaining a successful metabolic monitoring system for patients taking SGAs.

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