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Pharmacist medication reviews to improve safety monitoring in primary care patients.

Objective: Patients prescribed psychotropic medications within primary care are at risk of suboptimal monitoring. It is unknown whether pharmacists can improve medication safety through targeted monitoring of at risk populations. Access Community Health Centers implemented a quality improvement pilot project that included pharmacists on an integrated care team to provide medication reviews for patients. Aims were to determine whether inclusion of a pharmacist performing medication reviews within a primary care behavioral health (PCBH) practice is feasible and facilitates safe medication use. Method: Pharmacists performed medication reviews of the electronic health record for patients referred for psychiatry consultation. Reviews were performed 1-3 months following consultation and focused on medications with known suboptimal monitoring rates. Reviews were documented within the EHR and routed to the primary care provider. Primary outcome measures were change in percentage up-to-date on monitoring and AIMS assessment, and at risk of experiencing drug interaction(s) between baseline and 3 months postreview. Secondary outcome was provider opinion of medication reviews collected via electronic survey. Results: Reviews were performed for 144 patients. Three months postreview, percentage up-to-date on recommended monitoring increased 18% (p = .0001), at risk for drug interaction decreased 20% (p < .0001), and up-to-date on AIMS decreased 12% (p = .2113). The majority of surveyed providers wanted medication reviews to continue. Conclusion: Pharmacist population-level monitoring within an integrated care team is feasible and associated with improved safety monitoring of psychotropic medications. Results identify key areas for improvement that other clinics considering integration of similar pharmacy services should consider.

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.

Target Population

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.

Establishing Measures

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).

Monitoring Parameters

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.

AIMS Assessment

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.

Drug Interaction

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.

Provider Survey

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:


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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

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 (%)

  Female                                                 89 (62)
  Mean                                                    42.6
  Range                                                   11-51
  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% []
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

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)
                                        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)

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

* 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

Note. AIMS = Abnormal Involuntary Movement Scale;
BHC = behavioral health consultant.
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Author:Gallimore, Casey E.; Sokhal, Dimmy; Schreiter, Elizabeth Zeidler; Margolis, Amanda R.
Publication:Families, Systems & Health
Date:Jun 1, 2016
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