The effect of a computerized best practice alert system in an outpatient setting on metabolic monitoring in patients on second‐generation antipsychotics

2020 ◽  
Vol 45 (6) ◽  
pp. 1398-1404
Author(s):  
Sydnee Cohen ◽  
Jolene R. Bostwick ◽  
Vincent D. Marshall ◽  
Kathleen Kruse ◽  
Gregory W. Dalack ◽  
...  
2018 ◽  
Vol 8 (2) ◽  
pp. 49-55 ◽  
Author(s):  
Anita Peña ◽  
Beth DeJongh ◽  
Matthew Haas ◽  
Michelle Harms

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.


2018 ◽  
Vol 63 (4) ◽  
pp. 240-249 ◽  
Author(s):  
Mary Coughlin ◽  
Catherine Lindsay Goldie ◽  
Joan Tranmer ◽  
Sarosh Khalid-Khan ◽  
Deborah Tregunno

Objective: Children and adolescents with a range of psychiatric disorders are increasingly being prescribed atypical or second-generation antipsychotics (SGAs). While SGAs are effective at treating conduct and behavioural symptoms, they infer significant cardiometabolic risk. This study aims to explore what patient, treatment, and health care utilization variables are associated with adherence to Canadian Alliance for Monitoring Effectiveness and Safety of Antipsychotics in Children (CAMESA) metabolic monitoring guidelines. Method: A retrospective chart review of 294 children and adolescents accessing a large outpatient psychiatry setting within a 2-year study period (2014-2016) was conducted. Baseline and follow-up metabolic monitoring, demographic, treatment, and health care utilization variables were then assessed over a 1-year period of interest. Results: Metabolic monitoring practices did not adhere to CAMESA guidelines and were very poor over the 1-year observation period. There were significant differences between children (ages 4-12 years, n = 99) and adolescents (ages 13-18 years, n = 195). In adolescents, factors associated with any baseline metabolic monitoring were a higher number of psychiatry visits (odds ratio [OR], 1.2; 95% confidence interval [CI], 1.10 to 1.41), longer duration of contact (OR, 14; 95% CI, 2.31 to 82.4), and use of other non-SGA medications (OR, 3.2; 95% CI, 1.17 to 8.94). Among children, having an emergency room visit (OR, 3.4; 95% CI, 1.01 to 11.71) and taking aripiprazole (OR, 7.4; 95% CI, 2.02 to 27.45) increased the odds of receiving baseline metabolic monitoring. Conclusion: Findings from this study highlight the need for better metabolic monitoring for children and adolescents taking SGAs. Enhanced focus on opportunities for multidisciplinary collaboration is needed to improve the quality of care offered to this population.


2017 ◽  
Vol 27 (3) ◽  
pp. 1188-1198 ◽  
Author(s):  
Mary Coughlin ◽  
Catherine L. Goldie ◽  
Deborah Tregunno ◽  
Joan Tranmer ◽  
Marina Kanellos-Sutton ◽  
...  

2008 ◽  
Vol 7 (S1) ◽  
Author(s):  
Maria Markopoulou ◽  
Olga Georgiadou ◽  
Keranio Tsiftsoglou ◽  
Konstantinos Bobotas

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S140-S140
Author(s):  
Justine Abella Ross ◽  
Bernard Tegtmeier ◽  
Deron Johnson ◽  
Deepa Nanayakkara ◽  
Alfredo Puing ◽  
...  

Abstract Background In patients (pts) with cancer, the risk of Pneumocystis jirovecii pneumonia (PJP) is a function of dose and duration of corticosteroids (CS), underlying immunodeficiency, and immunosuppressive drugs. Trimethoprim/sulfamethoxazole (TMP/SMX) and atovaquone (ATO) are effective prophylaxis (ppx) agents against PJP. Guidelines recommend PJP ppx for pts on > 20 mg /day of prednisone or its equivalent for ≥ 1 month. A best practice alert (BPA) to identify pts receiving CS may assist with improving PJP ppx prescribing in cancer pts. Methods PJP BPA was created to identify pts on CS (excluding hydrocortisone) with no active prescription for TMP/SMX or ATO ppx in EMR. Dapsone and pentamidine excluded since not preferred agents at our institution. PJP case: positive PJP polymerase chain reaction (PCR) from bronchoalveolar lavage (BAL) > 84 copies or positive PJP direct fluorescent antibody (DFA) or cytology with clinical and radiographic suspicion. PJP PCR from BAL < 84 copies/ml with negative DFA and cytology excluded. Preventable PJP (P-PJP): pts after CS > = 30 days without PJP ppx. Non-preventable PJP (NP-PJP) : pts after CS < 30 consecutive days, or on PJP ppx (non-compliance, failure), or day +1 to +30 post hematopoietic cell transplant (HCT). Pre-intervention (pre-i) PJP pts 3/1/2018 to 7/31/19 (17 months), post-intervention (post-i) PJP pts 8/1/19 to 2/1/20 (18 months) evaluated to assess BPA impact on PJP inpatient (inpt) admissions. Results In the post-i, the BPA fired 3,588 times in 1,302 pts. Pre-i: 20 P-PJP, 13 NP-PJP out of 33 pts. Post-i: 6 P-PJP, 25 NP-PJP out of 31 pts. The BPA fired in 4/31 PJP pts in the post-i period: 2/6 of P-PJP, 2/25 NP-PJP. The number of P-PJP decreased from 20 to 6 in the post-i period (p=0.0097). Conclusion Implementation of a decision support tool significantly decreased the number of P-PJP. The BPA was limited by identifying pts after CS were prescribed after the initial visit leading to periods of CS use without ppx and inability to calculate CS dosing and length of prescription. BPA provided passive education in the outpatient setting and future opportunities include refining the EMR to better identify pts at risk for developing PJP. Disclosures All Authors: No reported disclosures


2020 ◽  
pp. 070674372097484
Author(s):  
Sarra Jazi ◽  
Leila Ben-Amor ◽  
Pascale Abadie ◽  
Marie-Line Menard ◽  
Rachel Choquette ◽  
...  

Objective: The potential metabolic adverse effects of second-generation antipsychotics (SGA) need to be monitored. The Canadian Alliance for Monitoring Effectiveness and Safety of Antipsychotics (CAMESA) offers guidelines for this purpose. We aimed to evaluate the long-term rates of youths receiving monitoring in mental health clinics and document the factors that may influence them. Method: The charts of 180 patients (13.3 ± 3.1 years, 54.4% males) receiving SGA treatment for the first time between January 2016 and June 2018 were reviewed. Monitoring was divided into baseline and 1- to 6-month and 9- to 24-month periods. Population under study was stratified into children (4 to 12 years) and adolescents (13 to 18 years). Sociodemographic characteristics, psychiatric diagnosis and comorbidities, prescribed SGAs and comedications, anthropometric measures (AM), blood pressure (BP), blood tests (BT), electrocardiogram, and the psychiatrist’s years of practice were collected. Cross tables were used to present the monitoring rates. Categories were compared by covariate analysis. Rates of patients monitored across categories were compared using Fisher exact test. Results: Monitoring rates for AM, BT, and BP were 55%, 47.8%, and 46.7% at baseline; 50%, 41.7%, and 45.2% at 1 to 6 months; and 47.2%, 41.5%, and 40.6% at 9 to 24 months, respectively. Higher monitoring rates were significantly associated with adolescent status (baseline, 1 to 6 months), a diagnosis of psychotic and/or affective disorder (baseline, 1 to 6 months, 9 to 24 months), having ≤1 psychiatric comorbidities (1 to 6 months), high SGA dose (baseline, 1 to 6 months), and clinician’s experience (baseline, 9 to 24 months). Significantly lower monitoring rates were associated with the psychostimulant/atomoxetine comedication (baseline, 1 to 6 months, 9 to 24 months). Conclusion: Five years after publication of the CAMESA guidelines, metabolic monitoring is conducted for less than half of patients. In our sample, age, diagnostic category, psychiatric comorbidities, SGA dose, clinician’s experience, and comedications influenced the monitoring rates. Major progress still needs to be made before reaching a satisfactory level of monitoring.


2019 ◽  
Vol 152 (Supplement_1) ◽  
pp. S124-S124
Author(s):  
Gregory Pomper ◽  
Matt Hunt ◽  
Erica Van Dyke ◽  
Johanna Waldron ◽  
Brian Hiestand ◽  
...  

Abstract Objectives The laboratory received a request to report abnormal troponin (ab-TnI) as critical values (CVs) for ED patients. The laboratory information system (LIS) was programmed to identify only ED patients presenting with an ab-TnI. Only the first ab-TnI on presentation was critical. Unnecessary laboratory CV communications could impair overall turnaround time. Methods Mean troponin, ab-TnI test volumes, and ab-TnI from ED patients with suspected acute coronary syndrome were determined. The LIS team constructed a best practice alert in the Beaker module (EPIC, Verona, WI). The ab-TnI CV build filtered patients based on ab-TnI values and ED location. Based on pilot data, the build was adjusted to limit ab-TnI alerts to only the first ab-TnI result. The amended build logic was to trigger the alert if an ED location TnI was abnormal. At trigger, if the lowest TnI result in the last 24 hours is ≤0.040, the return “true.” If true, then no TnI >0.040 in the last 24 hours, call the ED because they currently have a result >0.040. If the answer is “false,” then do not call the ED. If the patient had no TnI in the last 24 hours, then the alert would be triggered as well. The system was piloted after education to the ED and laboratory teams. Results The mean TnI per day was 150; the mean ab-TnI was 63 (42%), of which 1.1 ab-TnI originated from the ED. After pilot go-live, the actual number of ab-TnI/day was 14.3. The alert logic was amended to limit the trigger to the first ab-TnI result, reducing the CV volume to 9.6/day. Conclusion The LIS can be leveraged to develop a clinically valuable and operationally manageable critical value alert system. Clinical and laboratory teams must be open to amending the process as needed to achieve success.


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