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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

Evaluation of a Pharmacist-led Medication Assessment to ... · high prevalence of PP, EP and PIM use among ambulatory SAO patients High pill burden (increased use of medication) was

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Page 1: Evaluation of a Pharmacist-led Medication Assessment to ... · high prevalence of PP, EP and PIM use among ambulatory SAO patients High pill burden (increased use of medication) was

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

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Jefferson In the News!

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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

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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

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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

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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

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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

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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

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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

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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

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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)

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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)

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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

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37 (16%)

96 (41%)

96 (95%)

5 (5%)

101 (43%)

No Polypharmacy Polypharmacy Excessive Polypharmacy Extreme Polypharmacy

*Sample size (N=234)

Results

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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

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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.

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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

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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

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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

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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

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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

Page 22: Evaluation of a Pharmacist-led Medication Assessment to ... · high prevalence of PP, EP and PIM use among ambulatory SAO patients High pill burden (increased use of medication) was

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

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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

Page 24: Evaluation of a Pharmacist-led Medication Assessment to ... · high prevalence of PP, EP and PIM use among ambulatory SAO patients High pill burden (increased use of medication) was

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