Pharmacist medication reviews to improve safety monitoring in primary care patients.
Keywords: primary care behavioral health model, pharmacists, psychotropic medications, population-based care, quality improvement
The Institute of Medicine (IOM) has highlighted a gap between health care people receive and ideal health care, and has identified six
"Aims for Improvement" intended to close this gap. These aims include provision of safe, effective, patient-centered, timely, efficient, and equitable care (Committee on Quality of Health Care in America, Institute of Medicine, 2001). In today's health care landscape, patients prescribed psychotropic medications within primary care are a group at risk for suboptimal care related to medication use. Frequency of psychotropic prescription by primary care providers (PCPs) and challenges these medications present in terms of monitoring are barriers to care that is safe.
Although PCPs are responsible for prescribing 60% to 70% of psychotropic medications, compliance with recommended safety monitoring is often suboptimal within primary care (Pirl, Beck, Safren, & Kim, 2001). A study across 10 health maintenance organizations uncovered over 50% of prescriptions for carbamazepine, divalproex, and lithium were dispensed without completion of all recommended laboratory tests (Raebel et al., 2005). Compliance with guideline-recommended monitoring for movement disorders and adverse metabolic effects with antipsychotic medication also remains low. A meta-analysis of 290,534 patients across 48 studies evaluating baseline metabolic screening practices with antipsychotic prescription revealed that less than 50% of patients received glucose, weight, and lipid monitoring, and less than 25% had glycosylated hemoglobin (HbA1c) monitoring (Mitchell, Delation, Vancampfort, Correll, & De Hert, 2012). A separate analysis of 109,451 Medicaid patients revealed even lower numbers, with 27% receiving glucose and 10% receiving lipid monitoring following antipsychotic initiation (Morrato et al., 2010). Psychotropic medications have additional safety concerns, including potential to interact with other medications via pharmacodynamic and pharmacokinetic mechanisms. This is of particular concern given the high prevalence of medical comorbidities requiring medication management in patients with mental health conditions (English, Dortch, Ereshefsky, & Jhee, 2012).
As medication experts, pharmacists may be uniquely positioned to participate on integrated care teams to facilitate safer psychotropic medication use. The involvement of pharmacists within this capacity in inpatient, mental health specialty, and primary care has already been described. Within inpatient settings, pharmacists facilitate safe medication use via collaborative drug therapy management (CDTM), protocol directed laboratory monitoring, drug utilization review, consultation, and provider education (Finley, Crismon, & Rush, 2003; Hazra et al., 2011; Jenkins & Bond, 1996; Suehs, Mican, & Campbell, 2011). In outpatient mental health specialty and primary care settings, pharmacists most commonly participate in medication safety through comprehensive services provided to individual patients. This includes CDTM, comprehensive medication therapy management (MTM), care management, and provider and patient education (Adler et al., 2004; Finley, Rens, et al., 2002, 2003; Gallimore & Kushner, 2013; McKee, Lee, & Cobb, 2013; Moczygemba et al., 2011; Rubio-Valera et al., 2011). Outcomes related to safety have been favorable, with pharmacist intervention associated with increases in adherence and follow-up rates, and reductions in medication-related problems, polypharmacy, hospital admissions, and adverse effects (Finley, Crimson, et al., 2003; Jenkins & Bond, 1996; McKee et al., 2013).
What has not yet been established is the impact pharmacists have on psychotropic medication safety monitoring at the population level. Can pharmacists improve medication safety by providing targeted monitoring services within an integrated care team for patients at risk of suboptimal safety monitoring?
The Primacy Care Behavioral Health (PCBH) Model is an integrated and embedded model of care in which PCPs and behavioral health consultants (BHCs) work together to provide comprehensive biopsychosocial care (Robinson & Reiter, 2007). The PCBH model aims to improve overall population health while decreasing burden of demand for mental health care on the primary care system. It emphasizes a population-based approach, which focuses on meeting a limited, but vital, number of health care needs for a defined population versus providing comprehensive services to a small number of individual patients within that population (Robinson & Reiter, 2007; Rychnovsky, 2003; Weiss, 1998).
The current article described a quality improvement (QI) pilot project that integrated a pharmacist onto a PCBH team to provide population-based monitoring of psychotropic medication regimens. We sought to determine whether inclusion of a pharmacist performing medication reviews within a PCBH practice is feasible and whether it facilitates safer medication use through improved rates of safety monitoring.
The QI process was conducted between June 2013 and July 2014 for a pilot group of patients at Access Community Health Centers (hereafter "Access") in Madison, Wisconsin. The model for improvement was used as a framework for the QI project (Langley, Nolan, Nolan, Norman, & Provost 2009). The project qualified for exemption status under the University of Wisconsin Institutional Review Board.
Team Members and Setting
Access is a Federally Qualified Health Center comprised of three clinics that provide dental, medical, and pharmacy services in addition to behavioral health services utilizing the PCBH model (Robinson & Reiter. 2007). Clinicians across the three sites include PCPs (17 family and internal medicine physicians, 12 resident physicians, four pediatricians, four physician assistants, and one nurse practitioner), a consulting psychiatrist, and BHCs (eight psychologists and social workers, and varying levels of trainees from practicum students to postdoctoral fellows). A clinical pharmacist with 0.2 fulltime equivalent supported through the University of Wisconsin-Madison School of Pharmacy and a full-time pharmacy resident practice at two of the three sites.
Access also has a psychiatric consultation service that follows an integrated care model in which a psychiatrist provides consultation services with a population-based focus (Zeidler Schreiter, Pandhi, Fondow, & Fahey, 2013; Zeidler Schreiter, 2014; Zeidler Schreiter et al., 2013). Access PCPs refer patients for a one-time face-to-face or verbal/written consultation. Patients are triaged for consultation through BHCs, who see the patients prior to determine appropriateness of referral. Through consultation, the psychiatrist provides opinions regarding diagnostic clarification and medication management options; however, prescriptive authority is retained by PCPs.
The chief behavioral health officer, clinical pharmacist, and pharmacy resident collaborated on design of the QI pilot project, including selection of target population, design of the intervention (medication reviews), and establishment of outcome measures. Informal input on design of the intervention was also obtained from other BHCs and PCPs during provider meetings.
The population selected for intervention was patients who had a face-to-face consultation with Access's psychiatrist. This population was selected for several reasons. Given the referral to psychiatry, this was a group of patients with a high likelihood of psychotropic medication prescription and suboptimal treatment outcome. Additionally, this was a group already preidentified within normal clinic workflow, and therefore did not place additional burden on the system or its providers in identifying patients. This was thought to increase feasibility and likelihood of sustainability in the busy clinic environment. Lastly, there was no preexisting mechanism in place to ensure follow up with the PCP after the consulting psychiatry visit. Therefore, there were internal concerns within the PCBH team regarding consistency of monitoring for this particular group of patients.
The intervention selected was medication reviews performed by the clinical pharmacist and pharmacy resident (hereafter "pharmacy"). Reviews focused on medications with known suboptimal safety monitoring in primary care settings (carbamazepine, divalproex, lithium and antipsychotic medications; Mitchell et al., 2012; Morrato et al.. 2010; Raebel et al., 2005). Reviews also assessed for the presence of drug interactions, given the interaction potential of psychotropic medications. Pharmacy was selected to perform medication reviews based on a high degree of medication knowledge and favorable safety outcomes observed in the literature (Finley, Crimson, et al., 2003; Jenkins & Bond, 1996; McKee et al., 2013).
At four time points over the course of the year (June, September, December, and March), the BHC team member responsible for managing psychiatry consultation referral and scheduling compiled a list of patients who had a face-to-face visit with the consulting psychiatrist in the previous 3-month period. This was the list of patients for medication review. The timing of the reviews was 1 to 3 months post-psychiatry-consultation visit.
Medication reviews were conducted by reviewing the electronic health record (EHR) of each patient to collect relevant subjective/ objective information. This included a current medication list and most recent date/value of applicable monitoring parameters (fasting lipid panel, glucose, electrolytes, renal function, liver function tests, thyroid stimulating hormone, complete blood count, blood pressure, heart rate, weight, height, electrocardiogram, serum drug level, and abnormal involuntary movement scale (AIMS) score). Monitoring parameters and timeframe for monitoring were based on recommendations from the American Psychiatric Association Practice Guidelines, Mount Sinai Conference Consensus recommendations, the Development Conference on Antipsychotic Drugs and Obesity and Diabetes, and individual medication monographs (American Diabetes Association, American Psychiatric Association, American Association of Clinical Endocrinologists, & North American Association for the Study of Obesity, 2004; Hirschfeld RMA, 2005; Marder et al., 2004; Rush, 2000). Pharmacy used these guidelines, along with information collected from the EHR, to assess appropriateness of monitoring for each psychotropic medication. Medications were also inserted into a drug interaction database to screen for presence of interactions.
Subject/objective information, along with pharmacy's assessment of monitoring, was documented as an informational note within each patient's EHR and routed to their PCP. The PCPs were also informed of missing monitoring and drug interaction concerns via EHR messaging and reminders placed on upcoming appointment notes. If pharmacy felt a patient would benefit from an outreach call or another psychiatry consult a request was sent to BHC team via the EHR.
At baseline (time of medication review), demographic information and the three outcome variables were extracted from the EHR of each patient and recorded in a deidentified database. Outcomes variables were whether patient was (a) up-to-date on recommended psychotropic monitoring parameters ("yes" or "no"), (b) up-to-date on AIMS assessment ("yes" or "no"), and (c) at risk for drug interaction(s) ("yes" or "no"). The definition of what constituted a "yes" or "no" for each variable is described in Table 1. The same outcome variables were reevaluated 3 months postmedication review through a retrospective EHR review and recorded in the database. Pharmacy was responsible for extracting and recording all variables.
Primary outcome measures were change in percentage of patients up-to-date on recommended psychotropic monitoring parameters, up-to-date on AIMS assessment, and at risk for drug interaction(s) between baseline and 3 months postmedication review. A secondary outcome measure was PCP opinion of the medication reviews. Following three quarters of medication reviews, an anonymous electronic survey was e-mailed to all PCPs to collect feedback. They were asked to respond to statements evaluating quality and continuation of the medication reviews using a 5-point Likert scale (strongly agree to strongly disagree), and statements evaluating achievement of the QI project's aims on a 4-point Likert scale (very helpful to not at all helpful). Strongly agree and agree responses, and very and somewhat helpful responses were collapsed on analysis to simplify interpretation of results. Feedback pertaining to suggestions for future improvement of medication reviews was also solicited as open-ended responses.
Descriptive statistics were used to describe baseline characteristics, primary outcome results, and PCP survey responses. The McNemar test was performed on the primary outcomes comparing the proportion of participants up-todate on recommended psychotropic monitoring, up-to-date on AIMS assessment, and experiencing clinically significant drug interaction(s) prior to the review and 3 months postreview with an a priori alpha 0.05. The 95% confidence intervals (CIs) were determined for the portion of participants positive for each primary outcome on prechart review and postchart review. Only patients prescribed carbamazepine, divaloproex, lithium, or antipsychotic at both time points (baseline and postreview) were included in the recommended psychotropic monitoring outcome, and only patients prescribed an anti-psychotic medication at both time points were included in the AIMS assessment outcome. An exploratory post hoc analysis was also conducted using the t test, chi-squared test, and logistic regression to determine whether any baseline characteristics influenced the primary outcomes. Data analysis was completed with R version 2.15.1 and Stata version 14.0.
Medication reviews were performed for 144 patients and resulted in 90 recommendations sent to PCPs, of which 61% were accepted. The most common reason for nonacceptance was patient not returning for follow-up visit to initiate recommendation.
Demographics of the target population at baseline are presented in Table 2. Ninety percent had comorbid mental health diagnoses, and 94% had comorbid mental health and medical diagnoses. Antipsychotics and mood stabilizers were each prescribed in 40% of the population, and 73% were prescribed two or more psychotropic medications. The population had significant metabolic risk, with roughly half within the obese category and a quarter meeting criteria for metabolic syndrome. Upon post hoc analysis, the only associations found to be statistically significant at baseline were that older patients were more likely to have a drug interaction present (p = .009), and patients who had comorbid medical diagnoses were more likely to be up-to-date on lab monitoring (p = .038).
Primary outcome measures are displayed in Table 3. At baseline, 111 patients were prescribed a psychotropic medication requiring periodic laboratory or diagnostic monitoring. Among those patients, the percentage that was up-to-date on recommended monitoring parameters was significantly improved by 18% (p = .0001) on the postchart review, with 43% (95% CI [29.35, 57.75]) of those requiring additional monitoring at baseline (n = 51) now up-to-date on those parameters. Parameters most frequently overdue included fasting lipid panel (35%), complete blood count (20%), serum drug level (15%), electrocardiogram (14%), serum glucose (10%), and renal function (6%). Only two of 60 patients who were up-to-date on monitoring parameters at baseline became overdue for lab monitoring upon postchart review.
A total of 52 patients were prescribed an antipsychotic at baseline and remained on anti-psychotic at postchart review. Patients who received an AIMS assessment within the recommended time frame decreased by approximately 12% from baseline to postchart review, although this decline was not statistically significant (p = .2113). Of the patients not up-to-date at baseline (n = 13), 38% (95% CI [13.86, 68.42]) received an AIMS assessment and became up-to-date between baseline and postchart review. Of the 39 that were up-to-date at baseline, 28% (95% CI [15.0, 44.87]) did not remain up-to-date and were overdue for a repeat AIMS on postchart review.
The percentage of patients at risk of experiencing an adverse effect from a drug interaction was significantly decreased by approximately 20% between the baseline and postchart reviews (p < .0001). The most commonly identified drug interaction was increased risk of QT prolongation (53%). At the postchart review, 46% (95% [CI 33.39, 59.06]) of patients at risk for a drug interaction at baseline (n = 63) no longer remained at risk. Only one patient originally not at risk for drug interaction at baseline became at risk upon postchart review.
Results of the provider survey are listed in Table 4. Fourteen of 38 PCPs (37%) completed the survey, all of whom had a pharmacist-initiated psychotropic medication review performed for one or more of their patients. The majority of PCPs agreed that the medication review by pharmacy should continue and that reviews were helpful in facilitating appropriate lab monitoring, identification, and management of drug interactions, and provision of AIMS. Only 43% agreed that reviews allowed them to spend less time reviewing medications themselves, and 57% felt reviews were helpful in facilitating the scheduling of follow-up visits. Six PCPs provided open-ended feedback comments, which are presented in Table 5.
Through the QI pilot project, we found that population-level monitoring by pharmacists within a PCBH practice is feasible and associated with improved safety monitoring. Medication reviews required approximately 10 hr per week of pharmacist time. Participation of the pharmacy resident increased project feasibility by sharing workload and allowing the clinical pharmacist to also allocate time to preexisting clinic responsibilities. Medication reviews were associated with a significant increase in patients receiving guideline-recommended monitoring and reduction in patients at risk for drug interactions. In general, PCP feedback was supportive of pharmacists performing population-based monitoring, with the majority surveyed wanting the medication reviews to continue.
The results add to existing evidence supporting pharmacy's role in facilitating safe medication use, and advance the literature by describing a novel role for pharmacists on PCBH teams providing targeted services to populations at risk for suboptimal safety monitoring (Finley, Crimson, et al., 2003; Jenkins & Bond. 1996; McKee et al., 2013). This is a contrast to the comprehensive medication services provided to a smaller group of individual patients (i.e., referred for a comprehensive MTM) that has been previously described. Facilitating safe medication use at the population level aligns with the IOM's aims for optimizing health care (Committee on Quality of Health Care in America, Institute of Medicine, 2001). The QI pilot project also identified changes that could improve future medication reviews at Access and offers important insight for other clinics or PCBH teams considering integration of similar pharmacy services.
Medication reviews were not effective in improving compliance with recommended AIMS monitoring. Challenges to consistently performing AIMS assessments in primary care could have contributed. As AIMS assessments have not been historically performed in primary care settings, PCPs may not be aware of how and when they should be conducted. In fact, most patients who were up-to-date on AIMS at baseline had it performed at the consulting psychiatry visit. Short visit times (15-20 min), high no-show rates, and low follow-up rates also complicate performance of AIMS in primary care. Therefore, simply informing a PCP that AIMS is due or facilitating scheduling of a PCP visit is unlikely to have a high impact. This was supported by PCP comments suggesting pharmacist provision of AIMs would have been a more effective approach.
Future efforts should focus on following patients prescribed antipsychotics longitudinally to facilitate baseline and repeat AIMs. QI initiatives could focus on databases to track when patients are due for a repeat AIMS, pharmacist provision of AIMS, targeted educational interventions for PCPs, and training additional clinic staff to conduct AIMS prior to or directly following office visits.
Provider feedback identified several additional areas for improvement. It was suggested that monitoring could have been better facilitated if pharmacists directly ordered recommended labs, and this is a useful avenue for consideration. Second, PCPs felt medication reviews would have been more useful had the pharmacist taken a holistic approach to the reviews by assessing medications related to medical conditions in addition to mental health diagnoses. The substantial degree of metabolic risk identified in the target population could be an area to target. At Access, future medication reviews will also include a metabolic assessment of arteriosclerotic cardiovascular disease 10-year risk, blood pressure, body mass index, blood glucose, and hemoglobin Ale levels, with corresponding medication management recommendations provided to PCPs.
Less than half of surveyed PCPs felt that medication reviews lightened workload. While this was not a direct aim of the reviews, it is part of the broader PCBH mission to improve care by reducing workload on the primary care system, including providers (Robinson & Reiter, 2007). This finding may be influenced by a PCP's professional relationship with pharmacists at Access. It has previously been identified that an established and trusting relationship between pharmacist and physician is necessary for pharmacy medication management to be accepted and considered beneficial (McGrath et al., 2010; Snella & Sachdev, 2003). At Access, pharmacists performed reviews for patient at all three clinics, but only had in-person interactions and established relationships with PCPs at two of the three sites. A PCP who was less familiar with the pharmacists may have low confidence in the reviews and recommendations. This further emphasizes the importance of face-to-face contact among all team members to establish professional relationships and rapport when integrating a new service.
Design of the QI pilot project had several limitations. Medication reviews were only one factor in patient care. Contribution of confounding factors to the observed changes in outcome measures cannot be ruled out in absence of a control group. Response rate on PCP survey was low and may not represent the entire PCP population at Access. Medication reviews were completed once, with no subsequent follow-up by the pharmacist. To ensure improved monitoring continues, a mechanism for repeating medication reviews at future time points should be implemented and evaluated. Use of a database or reminder system within the EHR could be considered. Finally, referral for psychiatric consultation was not a perfect method for identifying patients at high risk for suboptimal safety monitoring. Although a large number of patients were prescribed psychotropic medications requiring safety monitoring (40% antipsychotics and 40% mood stabilizers), some had medication regimens that did not require extensive monitoring (i.e., antidepressant or stimulant monotherapy). This was emphasized in open-ended survey comments by PCPs. Additionally, patients stable on psychotropic medication or reluctant to see a psychiatrist are unlikely to be referred to consulting psychiatry, but may be prescribed a medication regimen that requires regular safety monitoring. By selecting only patients referred to consulting psychiatry. those additional patients who could benefit from the service are missed. Future efforts should include identification and review of all patients with an active prescription for medications requiring the greatest degree of monitoring, such as carbamazepine, divaloproex, lithium, and antipsychotic (Mitchell et al.. 2012; Morrato et ah, 2010; Raebel et ah, 2005).
In conclusion, pharmacist medication reviews are associated with improved monitoring rates and decreased interaction risk. Positive impact on outcome measures combined with PCP feedback suggests a novel population-based role for pharmacists on PCBFI teams facilitating safe psychotropic medication use. Overall, this is an important area that requires more thorough exploration and that should be a target for future research efforts.
Casey E. Gallimore, PharmD, MS and Dimmy Sokhal, PharmD
University of Wisconsin-Madison
Elizabeth Zeidler Schreiter, MA, PsyD
Access Community Health Centers, Madison, Wisconsin
Amanda R. Margolis, PharmD, MS
University of Wisconsin-Madison
This article was published Online First March 17, 2016.
Casey E. Gallimore, PharmD, MS and Dimmy Sokhal, PharmD, School of Pharmacy, University of WisconsinMadison; Elizabeth Zeidler Schreiter, MA, PsyD. Access Community Health Centers, Madison, Wisconsin; Amanda R. Margolis, PharmD, MS, School of Pharmacy, University of Wisconsin-Madison.
Correspondence concerning this article should be addressed to Casey E. Gallimore. PharmD. MS. Pharmacy Practice Department, School of Pharmacy, University of WisconsinMadison. 1015 Rennebohm Hall, 777 Highland Avenue. Madison, WI 53705. E-mail: firstname.lastname@example.org
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Received August 12, 2015
Revision received December 16, 2015
Accepted January 4, 2016
Table 1 Definition of Primary Outcome Variables Variable: Patient is ... Defining criteria for "yes" Up-to-date on monitoring Guideline (a) recommended laboratory/ parameters (yes/no) diagnostic parameters most recently checked within advised timeframe for antipsychotic, carbamazepine, lithium, and valproic acid (i.e., FLP. CBC, EKG). Up to date on AIMS AIMS last performed within previous 12 (yes/no) months for second-generation antipsychotic, 6 months for first- generation antipsychotic, 3 months for previous AIMS score [greater than or equal to] 3. At risk for drug Potential interaction between two or more interaction (yes/no) medications with moderate to high likelihood of resulting in an adverse patient outcome present. Considered resolved on postchart review if patient no longer taking that combination of medications or if appropriate patient education or monitoring has been implemented to validate safety of continuing to take that combination of medications (i.e., EKG performed to assess risk of QT prolongation or education provided on symptoms of serotonin syndrome). Note. FLP = fasting lipid panel; CBC = complete blood count; EKG = electrocardiogram; AIMS = Abnormal Involuntary Movement Scale. (a) American Psychiatric Association Practice Guidelines, Consensus Development Conference on Antipsychotic Drugs and Obesity and Diabetes, Mount Sinai Conference Consensus recommendations, and individual medication monographs. Table 2 Baseline Demographics of Target Population Characteristic n (%) Gender Female 89 (62) Age Mean 42.6 Range 11-51 Race White 93(65) African American 48(33) Others 3(2) Mental health diagnoses Depression/mood disorder 90(63) Anxiety disorder 64(44) Alcohol and other drug abuse 68 (47) Insomnia 18(13) Posttraumatic stress disorder 31 (22) Bipolar disorder 44(31) Psychotic disorder 34 (24) ADHD 21 (15) OCD 10(7) Tobacco use 57 (40) Other psychiatric disorders 13(9) Medical diagnoses Diabetes 22(15) Dyslipidemia 31 (22) Obesity 78 (54) Metabolic syndrome3 36 (25) Comorbid mental health diagnoses 130 (90) Comorbid mental health + medical diagnoses 135 (94) Diagnoses per patient (average) Mental health 3.2 Medical 5.1 Psychotropic medications Antidepressant 86 (60) Antipsychotic 58 (40) Mood stabilizer 57 (40) Benzodiazepine 30 (21) Stimulant 12(8) Sedative 30(21) Lithium 5(3) Others 61 (42) [greater than or equal to] 2 psychotropic medications 105 (73) Nonpsychotropic medications (average) 5.2 Prescription coverage Insured 126 (87) Medicare 41 (28) Medicaid 66 (46) Private 19(13) Uninsured 18(13) Note. ADHD = attention deficit hyperactivity disorder; OCD = obsessive compulsive disorder. (a) Metabolic syndrome-if two or more of the following criteria are met: blood pressure [greater than or equal to] 130/85; fasting blood glucose >135; high-density lipoprotein, <40 (males)/<50 (females); obesity; triglycerides [greater than or equal to] 150. Table 3 Primary Outcome Measures at Baseline and Post-Pharmacist- Initiated Psychotropic Medication Reviews Number of Baseline chart Outcome measures patients (n) review [95% CI] Up-to-date monitoring parameters 111 54.1% [220.127.116.11] At risk of drug interaction 144 43.8% [35.5,52.3] Up-to-date AIMS assessment 52 75.0% [61.1, 86.0] Postchart review Outcome measures [95% CI] p value Up-to-date monitoring parameters 72.1% [62.8, 80.2] .0001 At risk of drug interaction 24.3% [17.6,32.2] <.0001 Up-to-date AIMS assessment 63.5% [49.0, 76.4] .2113 Note. CI = confidence interval; AIMS = Abnormal Involuntary Movement Scale. Table 4 Primary Care Provider Perception of Medication Reviews Agreed/Strongly Evaluation statements agreed n (%) "Please indicate your level of agreement with the following statements ..." Pharmacists should continue to perform psychotropic medication reviews. 13(93) Other federally qualified community health centers would benefit from pharmacist- initiated psychotropic medication reviews. 12(86) The psychotropic medication chart reviews provided by the pharmacist are thorough. 13(93) Psychotropic medication reviews by a pharmacist allows me to spend less time reviewing medications. 6(43) The "in-basket" messages summarizing recommended monitoring or follow up are helpful. 11 (79) Very/Somewhat helpful n (%) "Please indicate how helpful reviews provided by pharmacist were in each of the following areas of psychotropic medication monitoring ..." Facilitating achievement of 12 (86) appropriate lab monitoring. Identifying and managing drug 12 (86) interaction. Facilitating provision of AIMS. 11 (79) Facilitating the scheduling of 8 (57) follow-up visits. Note. N = 14 clinicians. AIMS = Abnormal Involuntary Movement Scale. Table 5 Provider Feedback Comments Open-ended statements * Clarify process for AIMS assessments--who does them, provider? BHC? Publicize how charts are selected. * These haven't been helpful, primarily because they've been done on meds which don't need much review. I'd prefer they follow medications that require actual lab monitoring and either remind us to do so or just go ahead and order the monitoring. * It would be even more helpful if pharmacy called the patient to have them come in and do an AIMS or updated an upcoming visit's appointment notes with needed monitoring parameters. * Recent changes in state law allow a broad scope of potential delegations from physicians to pharmacists. It would be helpful to investigate how this could be used to have the pharmacist take a more active role in completing appropriate lab monitoring rather than simply sending the plan to the provider. The pharmacist could take an active role in making sure the monitoring studies were ordered and completed. This team-based approach to patient care could reduce the time that a provider would need to spend on insuring the monitoring was completed. * I felt these would have been more productive if the pharmacist new a little more about multi-morbidity. * Great idea, unsure how patients are selected for review or how to ask for a specific patient's chart to be reviewed. Note. AIMS = Abnormal Involuntary Movement Scale; BHC = behavioral health consultant.