Constructing a resident practice profile requires three steps: compiling a roster of patients the resident treats, extracting pertinent data from patient records, and analyzing and comparing the residents’ practice profile with other peers’ (1–3). Developing a resident practice profile can be challenging for educators because compiling a patient roster and extracting pertinent practice data are frequently very time consuming and can raise issues of patient confidentiality. Consequently, the practice profile is often limited to a small sample of the resident’s practice rather than a comprehensive overview. Data on the cost of resident practice interventions are often particularly difficult to determine (2). Because of the difficulties associated with constructing a resident practice profile, most reports of practice-based learning in psychiatry focus on learning evidence-based medicine principles or other techniques that do not require collecting a representative sample of resident practice data (4).
Although electronic medical record information technology (IT) is often cited as a methodology to facilitate developing practice-based learning interventions, a recent review of the impact of IT on education did not note any published reports utilizing pharmacy IT to improve resident competency in practice-based learning (5).
In this report we describe a methodology using U.S. Department of Veterans Affairs (VA) pharmacy IT that overcomes many of the difficulties associated with developing a resident practice profile. We also describe how psychiatric educators might use these resident prescription profiles to improve the education of residents in the clinic setting, including the development of practice-based learning interventions.
Nationwide, VA prescriptions are ordered through a computerized pharmacy system, which can generate reports describing the prescribing practices of residents in the following manner. VA pharmacy staff enter the Veterans Health Information Systems and Technology Architecture (VISTA) “Provider by Drug Costs” report to generate individual provider prescribing profiles for specific time periods. This report option is part of the Outpatient Pharmacy package and is available to all VA pharmacy managers. It can be found by selecting “Output Reports,” then “Cost Analysis Reports,” and finally “Provider by Drug Costs.”
This produces an individual provider report that includes the medication name and, by medication, the number of original and refill prescriptions written, the total cost of the medication to the VA, and the average cost of those prescriptions. The total number of original and refill prescriptions filled, the total cost of all fills, and the average cost of all fills for the specified time period for that provider are also provided. Individual patient data are not included in the report, ensuring patient confidentiality. The report details the number of times a resident writes a new prescription or refills an existing prescription for each dosage strength of a medication. For example, a separate line in the report is generated for aripiprazole in 5 mg, 10 mg, and 20 mg tablets.
To demonstrate the utility of these prescription practice profiles, we report on antipsychotic medication prescription profiles of four postgraduate year 3 (PGY-3) and five PGY-4 university-affiliated residents working in a VA psychotic disorders outpatient clinic. Data are reported on prescriptions written from July 2005 through May 15, 2006.
We calculated prescribing practices and costs for each resident using the computer generated individual reports. To determine the total number of prescriptions and total cost for each antipsychotic medication, the data for each dosage strength was summed. Calculations included the total number of prescriptions for each antipsychotic medication, the ratio of each atypical prescribed to total atypical prescriptions, the range of typical agents prescribed, and the ratio of total typical to total atypical prescriptions. Costs of atypical and typical agents and percentage of each medication’s cost to total individual resident prescribing costs were also calculated. Aggregate prescription frequency and cost for each antipsychotic medication for all residents in the clinic were calculated as well. To protect resident confidentiality, only aggregate data for two or more residents are included here. As a result, our institution does not require Institutional Review Board approval for this report.
Veterans Affairs pharmacy IT facilitated the development of resident prescribing profiles in an efficient and confidential manner. Generating individual reports on antipsychotic medication utilization and cost for all nine residents required 1.5 hours of pharmacist time. Aggregating and analyzing the data using a computer spreadsheet program required an additional 3.5 hours. No individual patient records or identifying information were communicated to the pharmacy staff, educators, or education administrative staff developing the prescription profiles.
Aggregate Resident Prescription Practices in the Clinic
Residents on average wrote 65 new prescriptions (range=38 to 97) and 65 follow-up prescriptions (range=27 to 101) during their 46 weeks in the clinic. An average of 81.6% of the prescriptions were written for atypical agents, while 18.4% were for typical antipsychotic medication. There was a wide range of atypical/total prescriptions among the residents: 67.1% to 95.6%.
Within the atypical antipsychotic medication group, risperidone was most frequently prescribed (accounting for 33.2% of all atypical prescriptions), followed by quetiapine (29.1%), olanzapine (20.7%), aripiprazole (10.7%), and ziprasidone (6.2%). Seven residents had prescribed each of the five atypical antipsychotic medications. Of the two residents who had not prescribed each of the five atypical agents, neither had prescribed ziprasidone.
Within the typical group, perphenazine was most frequently prescribed (46.5% of all typical agents), followed by haloperidol (17.7%), fluphenazine (14.9%), thioridazine (8.8%), chlorpromazine and loxepine (both at 5.5%), and trifluoperazine (1%). Compared with prescribing practices for the atypical agents, residents were less likely to have prescribed a wide range of typical antipsychotic medications: two residents (22%) had prescribed only one typical agent, and the majority (67%) had experience with only two or three typical agents.
The total cost of antipsychotic medication prescribed by the nine residents over the 46 weeks was $128,869. Although typical agents comprised 18.4% of all prescriptions written, their cost was only 1.2% of the total antipsychotic medication cost.
Within the atypical antipsychotic medication group, olanzapine contributed 34.5% of all prescription costs but comprised only 20.7% of all prescriptions. Quetiapine contributed only 17.9% to total costs while comprising 29.1% of all prescriptions. Risperidone also contributed less to percentage of total cost than to percentage of total prescriptions (27.6% of cost, 33.2% of prescriptions). Both ziprasidone and aripiprazole had nearly equivalent contributions to percentage cost and to percentage of total prescriptions written (7.7% of cost, 6.2% of prescriptions; 12.2% of cost, 10.7% of prescriptions, respectively).
Veterans Affiars pharmacy IT facilitated development of prescription profiles from a comprehensive sample of all antipsychotic medication prescriptions written by the residents. Because no individual patient information was included in the report, concerns about breeches of patient confidentiality were minimal. This complete prescribing data set for nine residents was collected and analyzed in 5 hours, rather than the many hours usually involved in collecting and analyzing a sample of data through a chart audit. Lastly, comprehensive pharmacy cost data, usually particularly difficult to obtain, was collected.
This methodology for developing resident prescription profiles has several advantages and disadvantages. As new prescriptions are separated from renewal prescriptions, it is possible to determine whether new prescription patterns changed after an educational intervention. This is an important feature, because new prescriptions may be more sensitive to change as practitioners may be less likely to change medications on patients considered clinically stable. This methodology does not provide data on the appropriateness of medication prescription, which must account for concurrent patient illness, patient preferences, prior experience with the medication, and other relevant clinical issues.
This report is limited to describing the methodology for creating a resident prescription profile and does not describe how this information was received or utilized by residents or faculty. However, we believe resident prescription profiles are especially useful for faculty supervising residents in medication clinic settings. With this feedback, faculty can help ensure that residents have experiences prescribing a wide variety of antipsychotic medications, as clinically indicated. Faculty can utilize this data to inform individual supervisory discussions about antipsychotic choice, side effect profile, and cost. These profiles also provide an opportunity to discuss the merits of physician report cards, linking practices like prescription of medications to outcomes and cost. Although patients treated in the VA make the same copayment no matter which medication is prescribed, individual resident prescription cost profiles may promote resident-faculty discussions about the importance of comparing medication costs when caring for patients who pay for their own medication. Lastly, knowledge of aggregated medication costs in a resident’s own practice may facilitate discussions of why formulary restrictions are often a component of cost-containment strategies for managed care systems like the VA.
Significant opportunities for improving resident competency in practice-based learning are present in this dataset. For example, recent reports question whether atypical agents offer an advantage over the typical antipsychotic medications (6). Yet atypical antipsychotic medications accounted for over 80% of resident prescriptions. Side effects like weight gain and metabolic syndrome are of significant concern (6, 7), yet a medication like aripiprazole, which may cause those side effects less frequently (6), was infrequently prescribed. Future reports utilizing the prescription profiles could compare resident prescribing practices among institutions or determine whether resident prescribing practices changed after a practice-based educational intervention.
Approximately 45% of the 181 U.S. general psychiatric residency training programs report having a “major participating institution” affiliation with a VA hospital (8). Where these affiliations exist, we believe psychiatric educators should develop relationships with VA pharmacy IT staff. These collaborative relationships between academic medical centers and the VA could improve resident education and ensure high quality, cost-effective clinical care for veterans.
Manuscripts authored by an editor of Academic Psychiatry or a member of its editorial or advisory board undergo the same editorial review process, including blinded peer review, applied to all manuscripts. Additionally, the editor is recused from any editorial decision making.
At the time of submission, the authors disclosed no competing interests.