Development and Reliability Testing of the Clinical Pharmacist Recommendation Taxonomy

Hoth, Angela; Carter, Barry L.; Ness, J. Mark Van; Bhattacharyya, Anjan; Shorr, Ronald I.; Rosenthal, Gary E.; Kaboli, Peter J.

doi:10.1592/phco.27.5.639

Cited by 22 publications

(34 citation statements)

References 20 publications

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“…The PCMs recorded all drug therapy, recommendations to physicians, and care plans within the study electronic database. The PCMs also classified each recommendation by type (Appendix ) and problem category (Appendix ) using a modification of a validated taxonomy . The PCMs could categorize each recommendation into more than one type or problem category, so the number of these classifications exceeded the overall number of individual recommendations.…”

Section: Methodsmentioning

confidence: 99%

Acceptance of Recommendations by Inpatient Pharmacy Case Managers: Unintended Consequences of Hospitalist and Specialist Care

et al. 2013

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Study Objective To determine if recommendations made by pharmacists and accepted by hospital physicians resulted in fewer post-discharge readmissions and urgent care visits compared to recommendations that were not implemented. Design Prospective review of pharmacist recommendations. Setting Patients admitted to a tertiary hospital and discharged to private community-based care. Patients A total of 192 subjects age 18 years or older who were a subsample of a randomized, prospective study, admitted with one of 10 cardiovascular or pulmonary disease or diabetes and utilized private community physicians and community pharmacies. Measurements and Main Results Pharmacy Case Managers (PCMs) performed evaluations for subjects and made recommendations to inpatient physicians. Subjects received medication counseling, a medication list and wallet card at discharge. Data from subjects and private physicians for 90 days post-discharge were collected. PCMs made 546 recommendations to inpatient physicians for 187 (97%) subjects. Overall, 48% of the recommendations were accepted. The acceptance rate was lower for those who ended up with an urgent care visit compared to other subjects (33.6% vs. 52.2%, p=0.033). There were high acceptance rates for medication reconciliation (78%, n=36) and when there was an actual allergy (100%, n=2) or medication error (100%, n=2). Physicians were less likely to accept recommendations related to medication indication (p<0.001), efficacy (p=0.041), and therapeutic disease monitoring (p=0.011). Recommendations made for subjects with a greater number of medications were also less likely to be accepted (p=0.003). Conclusion Recommendations to reconcile medications or address actual allergies or medication errors were frequently accepted. However, only 48% of all recommendations were accepted by inpatient physicians and there was no impact on healthcare utilization 90 days after discharge. This study suggests that recommendations by PCMs were underutilized and the low acceptance rate may have reduced the potential to avoid readmissions.

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Section: Methodsmentioning

confidence: 99%

Acceptance of Recommendations by Inpatient Pharmacy Case Managers: Unintended Consequences of Hospitalist and Specialist Care

et al. 2013

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“…Toward the end of the visit, a physician with expertise in prescribing for elders conferred with the pharmacist and patient, after which the physician-pharmacist team generated a consensus list of recommendations which was delivered to the patient’s primary care physician. The physician-pharmacist team identified problems using implicit review and then categorized the problems and recommended responses using a process with substantial to excellent inter-rater reliability (kappa 0.64 to 0.85) 19. These recommendations included suggestions about drugs that should be discontinued, substituted with a different drug, or prescribed at different doses, as well as suggestions about initiating new drugs that may benefit the patient.…”

Section: Methodsmentioning

confidence: 99%

“…In another case, an older patient taking a highly anticholinergic drug may have reported no adverse effects and good effectiveness of the drug, in which case the team did not recommend a change in therapy. All recommendations were recorded and categorized in the study database and assigned a priority level of high, medium, or low 19. Of note, the expert reviewers did not explicitly consult the Beers criteria or other such lists in making their recommendations.…”

Section: Methodsmentioning

confidence: 99%

Agreement Between Drugs-to-Avoid Criteria and Expert Assessments of Problematic Prescribing

Steinman¹,

Rosenthal²,

Landefeld³

et al. 2009

Arch Intern Med

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Background Drugs-to-avoid criteria are commonly used to evaluate prescribing quality in elders. However, few studies have evaluated the concordance between these criteria and individualized patient assessments as measures of problem prescribing. Methods We used data on 256 outpatients from the Iowa City VA Medical Center who were age 65 and older and taking 5 or more medications. After a comprehensive patient interview, a physician/pharmacist study team recommended that certain drugs be discontinued, substituted, or reduced in dose. We evaluated the degree to which drugs considered potentially inappropriate by the drugs-to-avoid criteria of Beers and Zhan were also considered problematic by the study team, and vice versa. Results In the study cohort, 256 patients were using 3678 medications. The physician/pharmacist team identified 563 drugs (15%) as problematic, the Beers criteria flagged 214 drugs (6%) as potentially inappropriate, and the Zhan criteria flagged 91 drugs (2.5%). Kappa statistics for concordance between drugs-to-avoid criteria and expert assessments were 0.10–0.14, indicating “slight” agreement between these measures. Sixty-one percent of drugs identified as potentially inappropriate by the Beers criteria and 49% of drugs flagged by the Zhan criteria were not judged problematic by the expert reviewers. Correspondence between drugs-to-avoid criteria and expert assessment varied widely across different types of drugs. Conclusions Drugs-to-avoid criteria have limited power to differentiate between drugs and patients with and without prescribing problems identified on individualized expert review. While these criteria are useful as guides for initial prescribing decisions, they are insufficiently accurate to use as stand-alone measures of prescribing quality.

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“…The intervention might reduce the number of unnecessary medications but it might increase total medications if there are untreated indications as we have observed in several other studies 15, 56, 57. It will be important to categorize the total number of medications and their association with the primary outcome variables (mMAI score, MEs, ADEs and visits to health care facilities).…”

Section: Secondary Measuresmentioning

confidence: 91%

The Iowa Continuity of Care study: Background and methods

Carter

Farris²,

Abramowitz

et al. 2008

American Journal of Health-System Pharmacy

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Purpose We describe an ongoing study of enhanced continuity of pharmacy care following hospital discharge to assess its impact on quality and patient safety. Methods The Iowa Continuity of Care (COC) study is a randomized, prospective trial enrolling 1,000 patients with selected medical conditions admitted to one large Midwest hospital. All patients must agree to obtain medications from one community pharmacy of their choice for 90 days post-discharge. Patients will be randomized to a control group, minimal intervention, or an enhanced intervention. Patients in the control group will receive usual care. Patients in the minimal and enhanced intervention groups will receive admission medication verification with the patients’ community pharmacists, medication teaching, and discharge counseling from a pharmacist case manager (PCM). In addition, patients in the enhanced intervention group will have a discharge care plan faxed to their outpatient physician and community pharmacist and will receive a follow-up phone call from the PCM 3–5 days post-discharge. The PCM will continue to resolve medication problems and facilitate communication between the community providers for patients in the enhanced intervention group. A blinded research nurse will collect data, including adverse drug events (ADEs), at admission, 30 days post-discharge and 90 days post-discharge. Outcome Measurements The primary outcome measures include medication appropriateness, ADEs, emergency department visits, unscheduled office visits and re-hospitalizations. Data will be collected from the inpatient electronic medical record, outpatient physician medical records, community pharmacist records and directly from patients. A cost-effectiveness analysis will be performed. Conclusion The Iowa COC study will examine the effects of increased communication with a PCM on the incidence of serious ADE, hospitalizations, and unscheduled office visits in patients with cardiovascular disease, pulmonary disease, or diabetes. The study will address the value of a PCM to improve communication of care plans between the inpatient and community settings.

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Development and Reliability Testing of the Clinical Pharmacist Recommendation Taxonomy

Abstract: The CPR taxonomy provides a reliable method to systematically evaluate clinical pharmacy recommendations based on the therapeutic problem identified and specific action recommended to resolve the problem.

Cited by 22 publications

References 20 publications

Acceptance of Recommendations by Inpatient Pharmacy Case Managers: Unintended Consequences of Hospitalist and Specialist Care

Acceptance of Recommendations by Inpatient Pharmacy Case Managers: Unintended Consequences of Hospitalist and Specialist Care

Agreement Between Drugs-to-Avoid Criteria and Expert Assessments of Problematic Prescribing

The Iowa Continuity of Care study: Background and methods

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