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Ginah Nightingale, Pharm.D., BCOP
Assistant Professor, Department of Pharmacy Practice
Jefferson School of Pharmacy, Thomas Jefferson University
Philadelphia, Pennsylvania, USA
October 24, 2014
Evaluation of a Pharmacist-led Medication
Assessment to Identify the
Prevalence of Polypharmacy and
Potentially Inappropriate Medication (PIM)
Use Among Ambulatory Seniors with Cancer
Jefferson In the News!
Study Investigators� Ginah Nightingale, Pharm.D., BCOP1, Principal Investigator
Assistant Professor, Department of Pharmacy Practice
� Emily Hajjar, Pharm.D., BCPS, BCACP, CGP1
Associate Professor, Department of Pharmacy Practice
� Kristine Swartz, MD2
Assistant Professor, Division of Community and Family Medicine,
Department of Geriatrics and Palliative Care
� Jocelyn Andrel-Sendecki, MSPH3
Biostatistician, Division of Biostatistics, Department of Pharmacology and
Experimental Therapeutics
� Andrew Chapman, DO2
Clinical Associate Professor, Department of Medical Oncology, Co-Director
of the Jefferson Senior Adult Oncology Center 1Jefferson School of Pharmacy, Thomas Jefferson University, Philadelphia, PA
2Thomas Jefferson University Hospital, Philadelphia, PA 3Thomas Jefferson University, Philadelphia, PA
Faculty Disclosures
� This study was supported by the American Association of Colleges of
Pharmacy (AACP) 2013 New Investigator Award Grant Program
� Study investigators and key personnel do not have any disclosures
Background
� The American Cancer Society estimates that by 2030 70% of all
cancers in the U.S. will be diagnosed in senior adults1
� The elders are coming!
� Excessive medication consumption and potentially inappropriate
medication (PIM) use in the elderly is recognized as a significant
public health problem linked to billions in health expenditures2
� Cancer-related treatment and supportive care therapies escalate its
prevalence and complexity and can increase the risk for adverse
drug events, drug-drug interactions, non-adherence3-7
1Smith BD, et al. J Clin Oncol 2009; 27:2758–652Fu FZ, et al. Med Care 2007; 45:472-476
3Riechelmann T, et al. J Natl Cancer Inst. 2007; 99: 592-6004Riechelmann T, et al. J Pain Symptom Manage. 2008; 35:535-43
5Riechelmann T, et al. Cancer Chemother Pharmacol. 2005; 56: 286-906Puts M, et al. Drugs Aging 2009; 26: 519-36
7Scripture C, et al. Nat Rev Cancer 2006; 6: 546-558
Background� Literature and guidelines for senior adult oncology (SAO)
management recommend medication evaluations as a standard
component of the geriatric oncology assessment8-9
� A comprehensive medication assessment includes:– Prescription medications
– Non-prescription medications
– Complementary and alternative medications
� Conventional studies that previously examined prevalence of
polypharmacy (PP) and PIM use in the SAO population10-12 were
limited by:– Inherent pitfalls of patient self-report/chart extraction
– Use of antiquated definitions and screening criteria
– Lack of evaluation of excessive polypharmacy8Extermann M, et al. J Clin Oncol 2007; 25:1824–31
9The NCCN Clinical Practice Guidelines in Oncology Senior Adult Oncology (version 2.2014) 10Lichtman SM, et al. J Clin Oncol 2009 ;27:Abstract 9507
11Maggiore RJ, et al. J Clin Oncol 2011; 29:Abstract 1950112Prithviraj GK, et al. J Geriatr Oncol 2012; 3:228–37
Objectives and Design
Primary:• To identify the prevalence of PP, excessive polypharmacy (EPP),
and PIM use among SAO patients
Secondary:• To identify characteristics associated with PP and PIM use
Study Design:• Prospective patient-pharmacist session (comprehensive medication assessment)
• Retrospective data collection (Physicians/Pharmacists’ e-notes)
– Patients brought in all medications from home for review
Methods� Inclusion criteria:
– Geriatric-oncology multidisciplinary assessment (1/2011 - 6/2013)
– Cancer diagnosis (new diagnosis, recurrence, progression)
� Data collection included the following:– Age, gender, race, tumor type, stage
– Medications (prescription, non-prescription, complementary/herbals)
– Medical comorbidities (number and type)
– Eastern Cooperative Oncology Group (ECOG) status13
– Functional status14 based on geriatrician assessment• Fit (Minimal co-morbidity and no functional dependence)
• Vulnerable (Some dependence IADLs, controlled co-morbidities, geriatric syndrome)
• Frail (3+ co-morbidities, dependence in 1+ ADLs, significant geriatric syndrome)
13Oken MM, et al. Am J Clin Oncol. 1982; 5:649-65514Balducci L, et al. The Oncologist. 2000; 5:224-237
Study terms and definitions
Polypharmacy (PP) and excessive polypharmacy (EPP)15-17
� PP - concurrent use of ≥ 5 and < 10 medications
� EPP - concurrent use of ≥10 medications
Potentially inappropriate medication use (3 indices)18-20
� 2012 Beers criteria
� Screening tool of older persons’ potentially inappropriate
prescriptions (STOPP)
� Healthcare and data information set (HEDIS)15Montamat SC, et al. Clin Geriatr Med. 1992;8:143-58
16Hajjar ER, et al. Am J Geriatr Pharmacother. 2007;5:345-5117Hovstadium B, et al. Clin Geriatr Med. 2012;28(2):159-172
18American Geriatrics Society Updated Beers Criteria for Potentially Inappropriate Medication Use in Older Adults. J Am Geriatr Soc 201219O’Mahony D, et al. European Geriatric Medicine 2010;1: 45–51
20National Committee on Quality Assurance. Drugs to be avoided in the elderly. March 2014
Baseline demographics and characteristics, n=248
Age, mean (SD) 79.9 (6.84) years
Female gender, n (%) 159 (64%)
Race, n (%)• Caucasian
• African American
184 (74%)
48 (19%)
Solid malignancies, n (%)• Colorectal
• Breast
• Lung
• Urinary tract (bladder, renal, urethral, urothelial)
• Upper Gastrointestinal (pancreatic, bile duct, gall bladder)
• Esophageal
• Neuroendocrine
• Gastric
• Prostate
216 (87%)
46 (19%)
45 (18%)
39 (16%)
18 (7.3%)
15 (6%)
9 (3.6%)
8 (3.2%)
7 (2.8%)
7 (2.8%)
Hematologic malignancies, n (%)• Lymphoma
32 (13%)
13 (5%)
Results
ResultsBaseline demographics and characteristics, n=248
Cancer stage, n (%)• Stage I
• Stage II
• Stage III
• Stage IV
• Recurrence (local and metastatic)
• Staging not applicable
31 (13%)
59 (24%)
46 (19%)
65 (26%)
34 (14%)
8 (3.2%)
*ECOG performance status, n (%)• 0
• 1
• 2
• 3
71 (29%)
108 (44%)
58 (23%)
9 (4%)
**Functional status, n (%)• Fit
• Vulnerable
• Frail
57 (23%)
120 (49%)
68 (28%)
Number of comorbidities (excluding cancer diagnosis), mean (SD) 7.69 (3.47)
*ECOG performance status (N=247); ECOG 4 = 1 (0.4%)
**Functional status (N=245)
Results
230 (93%)
117 (47%)
88 (36%)
108 (44%)
43 (17%)
89 (36%) 91 (37%)
68 (27%)
162 (65%)
68 (27%)
82 (33%)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Comorbidity prevalence*, n (%)
*Sample size (N=248)
Results
Medication Use, n=234
Total medications
• Total medications, mean (SD), [range] 2163, 9.23 (4.79), [1–30]
Prescription medications
• Total medications, mean (SD), [range] 1430, 6.1 (3.58), [0–20]
Non-prescription medications
• Total medications, mean (SD), [range] 647, 2.76 (2.11), [0–10]
Complementary medications
• Total medications, mean (SD), [range] 86, 0.38 (0.88), [0-10]
*Sample size based on number of patients evaluated by a pharmacist
37 (16%)
96 (41%)
96 (95%)
5 (5%)
101 (43%)
No Polypharmacy Polypharmacy Excessive Polypharmacy Extreme Polypharmacy
*Sample size (N=234)
Results
Prescription Medication Use, n=234
Prescription category N %
Cardiovascular (Alpha-adrenergic agonists/antagonists, antiarrhythmics, beta-adrenergic
antagonist, calcium channel antagonists, renin-angiotensin aldosterone antagonists, vasodilators)180 76.9
Dislipidemics (Statins, ezetimibe, niacin, fenofibrate) 124 53
Gastrointestinal (Antiemetics, constipation/diarrhea, histamine-2 antagonist, PPIs) 96 41
Diuretic 94 40.2
Endocrine (Antidiabetic orals/injectable, thyroid replacement, antithyroid agents) 87 37.2
Analgesic (Non-steroidal anti-inflammatory drugs, opioids/non-opioids, neuropathic pain drugs) 69 29.5
Antiplatelet/anticoagulant 53 22.7
Neuropsychiatric (Antidepressants, antiparkinson agents, antipsychotics, anticonvulsants) 51 21.8
Vitamin/minerals 45 19.2
Pulmonary/respiratory (Inhalers, oral tablets) 44 18.8
Potentially inappropriate medication use
prevalence**, n (%)
2012 Beers, STOPP criteria and HEDIS collectively identified 173 PIM occurrences
which was present in 40% (n=94), 38% (n=88), 21% (n=49) of patients, respectively.
Potentially Inappropriate Medication
Use, n=234
Medication category N %
Benzodiazepine 38 16.2
Gastrointestinal (Antiemetics, anticholinergic/antispasmodics, constipation/diarrhea, PPIs) 22 9.4
Non-steroidal anti-inflammatory drugs 20 8.6
Antiplatelet 19 8.1
Antihistamine (First generation) 14 6
Beta-adrenergic antagonist 13 5.6
Sedative hypnotic 7 3
Neuropsychiatric (Antipsychotics) 6 2.6
Cardiovascular (Antiarrhythmics, calcium channel antagonists) 6 2.6
Endocrine (Sulfonylureas, sliding scale insulin, dessicated thyroid) 6 2.6
Results
Patient characteristics associated with polypharmacy
No PP (n=37)< 5 medications
Any PP (n=197)≥ 5 medications
P-value
Age, mean (SD) 79.03 (7.4) 79.93 (6.65) 0.491
Female gender, n (%) 27 (72.97) 123 (62.44) 0.265
Race, n (%)
• Caucasian
• African American 25 (67.57)
9 (24.32)
148 (75.13)
36 (18.27)
0.861
Number of comorbidities, mean
(SD) 4.59 (2.19) 8.6 (3.4) <0.001
PIM use, n (%) 7 (18.92) 112 (56.85) <0.001
ResultsPatient characteristics associated with PIM use
No PIM
(n=115)
PIM
(n=119)P-value
Age, mean (SD) 80.3 (7.2%) 79.3 (6.3%) 0.260
Female gender, n (%) 76 (66%) 74 (62%) 0.534
Race, n (%)
• Caucasian
• African American
80 (70%)
24 (21%)
93 (78%)
21 (18%)
0.437
Number of comorbidities, mean (SD) 7.3 (3.4) 8.7 (3.6) 0.005
Polypharmacy, n (%)
• No polypharmacy
• Polypharmacy (≥5 and < 10 meds)
• Excessive Polypharmacy (>10 meds)
30 (26.1%)
54 (47%)
31 (27%)
7 (5.9%)
42 (35.3%)
70 (58.8%)
<0.001
Summary
� A pharmacist-led comprehensive medication assessment demonstrated a
high prevalence of PP, EP and PIM use among ambulatory SAO patients
� High pill burden (increased use of medication) was associated with:
‾ Increased comorbidity count
‾ Increased PIM use
� STOPP and 2012 Beers criteria were most inclusive for identifying
PIMs
‾ 2012 Beers and the STOPP criteria mutually identified 66 (38%) PIM
occurrences supporting the fact both tools may be complementary
Limitations� Single-center study
� Small cohort
� Pharmacist recommendations were made but not
tracked to assess primary provider’s acceptance
‾ Our SAO functions as a consultative center
�Captured medication use at a single (initial) visit
‾ Most patients were not on anti-cancer treatment at initial visit
‾ Medication use in this population changes continuously
�Heterogeneous cancer types / cancer stages
What’s Next…Future Directions�Another funded research study!
‾ 2014 American Society of Health-System Pharmacists (ASHP) New Investigator Award
‾ A Pharmacist-led Intervention to Identify and Reduce Medication Related Problems (MRP) during SAO Transitions of Care
� Development of an easy to apply modified PIM screening tool (integrates 2012 Beers and STOPP criteria) and considers:
‾ Cancer diagnosis and prognosis
‾ Cancer treatment
‾ Supportive care therapies
Acknowledgements
I would like to acknowledge and thank the following individuals
who assisted with this research investigation:
� Laura Pizzi, Pharm.D., MPH
� Joshua Schoppe, MPH, CCRP
� Vittorio Maio, Pharm.D., MS, MSPH
� Krystal Guo, Pharm.D.
� Stephanie Komura, Pharm.D.
� Eric Urnoski, Pharm.D. Candidate 2015
Ginah Nightingale, Pharm.D., BCOP
Assistant Professor, Department of Pharmacy Practice
Jefferson School of Pharmacy, Thomas Jefferson University
Philadelphia, Pennsylvania, USA
October 24, 2014
Evaluation of a Pharmacist-led Medication
Assessment to Identify the
Prevalence of Polypharmacy and
Potentially Inappropriate Medication (PIM)
Use Among Ambulatory Seniors with Cancer