Kristine Swartz

Evaluation of a Pharmacist-Led Medication Assessment Used to Identify Prevalence of and Associations With Polypharmacy and Potentially Inappropriate Medication Use Among Ambulatory Senior Adults With Cancer

PURPOSE The use of multiple and/or inappropriate medications in seniors is a significant public health problem, and cancer treatment escalates its prevalence and complexity. Existing studies are limited by patient self-report and medical record extraction compared with a pharmacist-led comprehensive medication assessment. PATIENTS AND METHODS We retrospectively examined medication use in ambulatory senior adults with cancer to determine the prevalence of polypharmacy (PP) and potentially inappropriate medication (PIM) use and associated factors. PP was defined as concurrent use of five or more and less than 10 medications, and excessive polypharmacy (EPP) was defined as 10 or more medications. PIMs were categorized by 2012 Beers Criteria, Screening Tool of Older Persons Prescriptions (STOPP), and the Healthcare Effectiveness Data and Information Set (HEDIS). RESULTS A total of 248 patients received a geriatric oncology assessment between January 2011 and June 2013 (mean age was 79.9 years, 64% were women, 74% were white, and 87% had solid tumors). Only 234 patients (evaluated by pharmacists) were included in the final analysis. Mean number of medications used was 9.23. The prevalence of PP, EPP, and PIM use was 41% (n = 96), 43% (n = 101), and 51% (n = 119), respectively. 2012 Beers, STOPP, and HEDIS criteria classified 173 occurrences of PIMs, which were present in 40%, 38%, and 21% of patients, respectively. Associations with PIM use were PP (P < .001) and increased comorbidities (P = .005). CONCLUSION A pharmacist-led comprehensive medication assessment demonstrated a high prevalence of PP, EPP, and PIM use. Medication assessments that integrate both 2012 Beers and STOPP criteria and consider cancer diagnosis, prognosis, and cancer-related therapy are needed to optimize medication use in this population.

Development of a comprehensive multidisciplinary geriatric oncology center, the Thomas Jefferson University Experience.

BACKGROUND The proportion of older patients with cancer is expected to grow exponentially in the next two decades. This population has large heterogeneity and it is well known that chronologic age is a poor predictor of outcomes. Research has shown that these patients are best served with a Comprehensive Geriatric Assessment (CGA) to formulate individualized treatment plans for better outcomes. However, the best model for CGA has yet to be determined. MATERIALS AND METHODS Our objective was to develop a highly functional model for the establishment of a comprehensive multidisciplinary geriatric oncology center in the setting of a university based NCI-designated cancer center. Each patient is evaluated by medical oncology, geriatric medicine, pharmacy, social work and nutrition. Expert navigation is provided to enhance the patient experience. At the conclusion, the inter-professional team meets to review each case and formulate a comprehensive treatment plan. The patient is classified as Fit, Vulnerable, or Frail based on the complete CGA. RESULTS The average age of patients seen was 80.7 with the most common diagnoses being breast, colorectal and lung cancers. Twenty four percent of patients were determined to be Fit, 47% Vulnerable, and 29% Frail. Twenty one percent of patients determined to be Frail by CGA received an ECOG score of 0-1 by the oncologist. Our pharmacists made specific recommendations in over 75% of patients and social work provided assistance in over 50% of patients. CONCLUSIONS We were able to observe some interesting trends such as potential discordance with ECOG score and assessment of Fit/Vulnerable/Frail but due to limitations in the data, this paper is not able to illustrate definitive correlations. Several challenges with the development of the clinic include 1) patient related issues, 2) navigation, 3) financial reimbursement, 4) referral patterns, and 5) coordination of care during office hours. We feel that we have been able to establish a model for a comprehensive multidisciplinary geriatric oncology evaluation center in the setting of a university based cancer center.

A pharmacist-led medication assessment used to determine a more precise estimation of the prevalence of complementary and alternative medication (CAM) use among ambulatory senior adults with cancer

OBJECTIVES The prevalence of complementary and alternative medication (CAM) use in senior adult oncology (SAO) patients is widely variable and little is known about whether polypharmacy (PP) and potentially inappropriate medication (PIM) use influences CAM use given the increased number of comorbidities and polypharmacy. One approach to optimize medication management is through utilization of pharmacists as part of a team-based, healthcare model. MATERIALS AND METHODS Prevalence of CAM and factors influencing CAM use was examined in a secondary analysis of 248 patients who received an initial comprehensive geriatric oncology assessment between January 2011 and June 2013. Data was collected from electronic medical records. CAM was defined as herbal medications, minerals, or other dietary supplements, excluding vitamins. Patient characteristics influencing CAM use (e.g. comorbidities, PP and PIM use) were analyzed. RESULTS Only 234 patients (evaluated by pharmacists) were included in the final analysis. Mean age was 79.9 years [range 61-98]; 64% women, 74% Caucasian, 87% with a solid tumor, mean comorbidities, 7.69. CAM prevalence was 26.5% (n=62) and median CAM use was 0 (range 0-10). The proportion of CAM use (1, 2, and 3) was 19.2%, 6.4%, and 0.4%, respectively. Associations with CAM use (versus no-CAM) were polypharmacy (P=0.045), vision impairment (P=0.048) and urologic comorbidities (P=0.021). CONCLUSIONS A pharmacist-led comprehensive medication assessment demonstrated a more precise estimation of CAM prevalence in the ambulatory SAO population. CAM use was associated with polypharmacy, ophthalmic and urologic medical conditions. Integrating pharmacists into team-based (geriatric and oncology) care models is an underutilized yet viable solution to optimize medication use.

Telemedicine and Palliative Care: an Increasing Role in Supportive Oncology

With the emergence of telemedicine as a routine form of care in various venues, the opportunities to use technology to care for the most vulnerable, most ill cancer patients are extremely appealing. Increasingly, evidence supports early integration of palliative care with standard oncologic care, supported by recent NCCN guidelines to increase and improve access to palliative care. This review looks at the use of telemedicine to expand access to palliative care as well as provide better care for patients and families where travel is difficult, if not impossible. When telemedicine has been used, often in Europe, for palliative care, the results show improvements in symptom management, comfort with care as well as patient and family satisfaction. One barrier to use of telemedicine is the concerns with technology and technology-related complications in population that is often elderly, frail and not always comfortable with non-face-to-face physician care. There remain significant opportunities to explore this intersection of supportive care and telemedicine.

Implementing a pharmacist-led, individualized medication assessment and planning (iMAP) intervention to reduce medication related problems among older adults with cancer.

OBJECTIVES Medication-related problems (MRP) affecting older adults are a significant healthcare concern and account for billions in medication-related morbidity. Cancer therapies can increase the prevalence of MRP. The objective of this study was to test the feasibility and effectiveness of implementing a pharmacist-led individualized medication assessment and planning (iMAP) intervention on the number and prevalence of MRP. MATERIALS AND METHODS This prospective pilot study enrolled oncology outpatients aged ≥65years. Intervention feasibility encompassed recommendation acceptance rate and intervention delivery time. The intervention was facilitated by pharmacists where patients received comprehensive medication management at baseline and at the 30- and 60-day follow-up. RESULTS Forty-eight eligible patients enrolled and 41 patients (85.4%) were included in the analysis. Mean age was 79.1years [range 65-101]; 66% women, 83% Caucasian, mean comorbidity count was 7.76. Forty-six percent of the pharmacist recommendations were accepted and the prevalence of MRP at baseline versus 60-day follow-up decreased by 20.5%. The average time to conduct the initial session was 22min versus 15min for the follow-up sessions. Resources needed included a tracking system for scheduling follow-up calls and a database for tracking acceptance of recommendations. A total of 123 MRP were identified in 95% of patients (N=39) with a mean of 3 MRP per patient. The mean reduction in number of MRP (3 at baseline versus 1.6 at 60-day follow-up) was 45.5%. CONCLUSIONS The pharmacist-led iMAP intervention was feasible and effective at reducing MRP. Additional inter-professional medication safety based interventions measuring patient-reported outcomes are still needed.

The prevalence of major drug-drug interactions in older adults with cancer and the role of clinical decision support software

OBJECTIVES Drug-drug interactions (DDIs) represent an escalating concern for older adults attributed to polypharmacy, multi-morbidity and organ dysfunction. Few studies have evaluated the prevalence of major DDIs and the variability between DDI detection software which confuses management. MATERIALS AND METHODS Prevalence of major DDIs was examined as a secondary analysis of outpatients aged ≥65 years. Demographic and clinical information was collected from electronic health records including age, sex, race, cancer type, comorbidities, and medications. All DDIs were screened by a clinical pharmacist using Lexi-Interact® and Micromedex®. Major DDIs were defined as Lexi-Interact® category D or X and/or Micromedex® category major or contraindication. Summary statistics of patient characteristics and DDIs were computed. RESULTS Our cohort included 142 patients (mean age, 77.7 years; 56% women, 73% Caucasian). The mean medications was 9.8 including 6.7 prescriptions, 2.6 non-prescriptions, and 0.5 herbals. Lexi-Interact® identified 310 major DDIs in 69% of patients (n = 98) with an average of 2.2 DDIs per patient. Micromedex® identified 315 major DDIs in 61% of patients (n = 87) with an average of 2.2 DDIs per patient. DDIs mostly involved opioids, antiplatelets, electrolyte supplements, antiemetics, and antidepressants. Variability existed with the severity rating reporting of the clinical decision support software. CONCLUSIONS There was a high prevalence of major DDIs in older adults with cancer. Utilizing clinical decision support software was beneficial for detecting DDIs however, variability existed with severity reporting. Future studies need to identify the relevant DDIs with clinical implications in order to optimize medication safety in this population.

Reply to M.-E. Rougé Bugat et al.

We appreciate the valuable comments by Rougé Bugat et al regarding our publication. We agree that senior adults with cancer are exposed to high pill burdens that require a thorough evaluation of polypharmacy and potentially inappropriate medication (PIM) use as part of the comprehensive geriatric assessment (CGA). This correspondence addresses the questions raised by Rougé Bugat et al, specifically the principle tools used in our CGA; the omission of a comorbidity scale and assessment of cognitive status; and the exclusion of the Screening Tool to Alert Doctors to the Right Treatment (START) criteria. The approach of the interprofessional health care team of our institution to the CGA is published in detail separately. In short, the geriatrician assesses activities of daily living and instrumental activities of daily living and incorporates several tools, such as the Vulnerable Elders Survey, the Mini-cog, the Geriatric Depression Screen, the Timed Up and Go, and a subjective assessment of life expectancy by using the Walter and Covinsky life expectancy tables. Our center has considered using the Charleston Comorbidity Index and the Cumulative Illness Rating Scale-Geriatrics to provide an objective measurement of comorbidity severity; however, we have found these scales difficult to implement in a busy clinic session to add real-time value to the clinical evaluation. We recognize that the lack of an objective measurement could be considered a weakness for research purposes, but we believe that it has not affected our ability to make sound clinical judgments. Rougé Bugat et al are correct in their commentary about the omission of the Mini-cog assessment in our publication; however, cognitive assessments were performed, documented, and discussed with the health care team at the time of each patient visit. This omission did not compromise the study findings, because the intent of the study was to assess the landscape of the medication use for the entire cohort regardless of a specific comorbidity or functional deficit. Medication assessments were comprehensive, accurate, and relevant, because all patients were instructed to bring in all medications (ie, prescription, nonprescription, herbals, and supplements) to objectively evaluate each medication with the patient and/or caregivers that were present at the consultation session. The pharmacist spoke directly to the patient and/or caregivers to confirm medication possession; to confirm the ability to self-administer, read medication label directions, and state medication indications; and to assess the ability of the patient or caregiver to manage medications in an organized manner. When the pharmacist identified medication-related problems (eg, cognitive impairment associated with medication nonadherence), this information was discussed with the patient and the interprofessional team, and a progress note was documented in the electronic health record. Medication recommendations (eg, patient requires caregiver assistance for medication management on the basis of cognitive status; consider discontinuing PIM because of increased risk of falls, given history of recent falls) were forwarded to the primary oncologist and/or medical provider for additional evaluation. As mentioned in our publication, acceptance of the pharmacists’ interventions was not part of this study, but it does represent an area that warrants exploration to assess associations with adverse drug events, health care use costs, and quality of life. Rougé Bugat et al raise an interesting point regarding exclusion of the START criteria. START was developed on the basis of community-dwelling elders admitted to a hospital with acute illness, which differs from our ambulatory oncology population. Initiation of medications on the basis of START (eg, statins for cardiovascular disease, bisphosphonates for bone health) may not be reasonable for patients with poor prognoses or terminal cancers. A comprehensive medication assessment would be warranted to reduce the use of unnecessary medications with a focus on prioritizing the goals of care of the patient (eg, relieving symptoms, maintaining functionality) through shared decision making between the patient and the health care team. Also, Rougé Bugat et al made reference to a publication by Cool et al that used multiple reference tools to identify a high proportion of PIM use in patients in nursing homes. We agree with the method, which is why our study used three of the most current evidence-based, clinically validated criteria in the literature. In our publication, we comment that these tools should be used in a complementary manner to guide clinician decision making about safe medication use, because there are notable differences among these screening tools. In conclusion, we believe that integration of pharmacists into team-based (geriatric and oncology) care models is an underused yet viable solution to optimize medication management. We agree that prospective studies are needed to evaluate medication use and associations with adverse events that compromise cancer management plans and negatively affect patient outcomes and quality of life.

Senior Adult Oncology: Three Cases of Advanced Cancer in Patients of Advanced Age

The American Cancer Society reports that more than 60% of all cancers and 80% of cancer-related deaths in the United States occur in patients older than age 65 (1,2). Epidemiologic data show that the likelihood of developing certain cancers in older age is higher than in younger individuals, and intuitively, this stands to reason, due to physiologic factors, time for the expression and development of genetically-related cancers, and a longer range of environmental exposures. However, many cancers may be more difficult to treat in older individuals due to higher incidence of medical co-morbidities, as well as the biology of certain tumors themselves. Heterogeneous behaviors of several cancers manifest as unique situations in elderly patients across a broad spectrum, including on average, more indolent estrogen-receptor-positive breast cancers, as well as more drug-resistant acute leukemias which may arise on a background of a long history of myelodysplasia. In addition, optimum dosing and prediction of treatment toxicity remains a difficult question, as older cancer patients are not well represented in clinical trials, for which often the inclusion criteria list a maximum age of 70. Furthermore, many cancers such as hematologic malignancies, may not be able to be treated with maximum aggressiveness such as high-dose chemotherapy followed by stem cell transplant or autologous stem cell rescue as would be tolerated by younger individuals (usually under the age to 60–65). In our quest as physicians to “first do no harm” (3,4), we wrestle with our best recommendations for our elderly patients, often in the face of frail physicality and potential for increased risk of infection and iatrogenically-induced side effects and morbidity. We present here 3 cases of advanced cancers in patients of advanced chronologic age, who also exhibit multiple medical co-morbidities. Their situations likely warrant specifically tailored treatment given their age, which would be markedly different if they presented in earlier decades of life. We pose the following clinical questions: (a) What treatments would you offer/feel comfortable offering these patients? (b) What factors are important in arriving at these decisions between and among the physician, patients, and families? (c) What modifications would you make to standard treatments if indicated for these particular patients?