Oncology Nursing Society Putting Evidence into Practice PEP

Oncology Nursing Society Putting Evidence into Practice (PEP) Assessment and Measurement of Medication Adherence: Oral Anti-Cancer Agents Sandra L. Spoelstra, Ph. D, RN Oncology Nursing Society Congress April 20, 2015 Orlando, FL

Objectives I. To define medication adherence. § In relation to oral anti-cancer agents (OAC). II. To describe the methods available to assess and measure medication adherence.

The Problem • Despite efforts to encourage adherence to oral agents for cancer (OAC), rates are sub-optimal. (Bassan, 2014) • OAC adherence is a problem which may impact treatment success. (Puts, 2013) • There is need to assess and measure OAC adherence.

Definition Adherence: “The degree or extent of conformity to the recommendations about day-to-day treatment by the provider with respect to the timing, dosage, and frequency for the duration of time from initiation to discontinuation of therapy. ” (Cramer, 2007) – Timing (e. g. time of day – 9: 00 AM) – Dosage (e. g. 200 mg) – Frequency (e. g. daily, BID, TID) • Examines: – Taking < than prescribed – Taking > than prescribed – Doses taken too close together

Therapeutic Dosing • FDA Guidelines OACs (U. S. Food & Drug Administration, 2014) • Inadequate dosing can occur: – Due to toxicities from side effects of treatment – Dose reductions or stoppages – Problems with obtaining the medication (Bozic, 2013; Gebbia, 2012; Puts, 2013). • Tumor response or survival dosing is not known: – Whether 80% of the dosage is adequate – Or if 90% may be effective (Alberto, 1994)

Relative Dose Intensity (RDI) • Ratio of dose taken over time compared to the ordered dose. (Amgen, 2008) • Maintaining RDI reduces survival of resistant clones, increases percent of cells killed per dose, and decreases intervals between treatment cycles. • Results in greater treatment efficacy. • Most oncologists prefer 100% OAC adherence to assure RDI.

Complexities of OACs • Simple: – Once daily dosing • Complex: – More than daily dosing – On-and-off cycling – Two or more drugs (Spoelstra et al. , 2013)

The Process • PEP Team Project: Literature search to identify ways to assess and measure medication adherence – – – Oncology Nursing Society: Margaret Irwin Ph. D, RN, MN Cynthia Rittenberg, MN RN FAAN, AOCN Lee Ann Johnson, RN, PHDc Carol Blecher, MS, APNC, OACN, CBPN-C, CBCN Peggy Burhenn, MS, CNS, AOCNS Larissa Day, MSN, RN, CONC Diana Mc. Mahon, MSN, RN, OCN; AOCN Theresa Rudnitzki, MS, RN, ACNS-BC, AOCNS Josephine Smudde, MS, RN, BC, OCN Holly Sansoucie, RN, MSN, DNP, AOCN, CBCN Sandra Spoelstra, Ph. D, RN Janelle Tipton, MSN, RN, AOCN

Results • Measures: – 3 -Direct measures were identified – 4 -Indirect measures were identified • 7 -Tools were identified in the literature – Tools were divided into two categories: 1. Ability to assess risk of non-adherence 2. Ability to measure adherence rates

Direct & Indirect MEASURES

Direct Measures • Drug assays of serum or urine – not available for OACs • Drug markers – do not exist for OACs • Direct observation of medication ingestion 6 • COSTLY AND IMPRACTICAL

Indirect Measures • Self-report – Overestimates adherence due to questions not being specific, desire to please providers, and decreased cognitive ability to recall. Unreliable • Pill counts – Overestimate. Time consuming • Electronic monitoring systems – No way to know if ingested. Expensive and unrealistic for clinical setting • Pharmacy records and claims – Proportion of days covered (PDC): summing # days in a time period “covered” by the medication divided by # days in the period. Unrealistic for clinical setting as doctors do not have this access

To Assess TOOLS

Morisky Medication Adherence Scale (MMAS) • Evaluates past medication use patterns • Four “yes” or “no” questions (Moriskey, 1986) – Scored with a 1 for “yes” and a 0 for “no”; summed – Score of 0 is high adherence, 1 -2 is medium, and 3 -4 is low • Psychometrics: – Predictive validity 0. 75 adherence; 0. 47 nonadherence – Sensitivity 0. 81; Specificity 0. 44 • Floor/ceiling effects likely, due to the nature of questions – Makes tool unreliable to measure adherence • May be effective at predicting risk of nonadherence

Adherence Estimator • • Three-item tool (Mc. Horney, 2009) Screens likelihood of nonadherence Placed in categories: low, medium, high scores Psychometrics: – Sensitivity high: Cronbachs alpha at 0. 88 – Specificity acceptable at 59% • Does not assess adherence rate • May accurately predict risk of nonadherence.

Beliefs about Medication Questionnaire (BMQ) • 17 -item two-section, self-report tool (Horne, 1999) 1. BMQ-Specific assesses medications prescribed for personal use • Two 5 -item factors assess beliefs about necessity of medication and concerns based on beliefs about the danger of dependence and long-term toxicity and the disruptive effects 2. BMQ-General assesses beliefs about medicines in general. • Two 4 -item factors assessing beliefs about medicine overuse and safety • Score: – – 1 -point strongly disagree; 2 -disagree, 3 -uncertain, 4 -agree, 5 -strongly agree Higher scores (range 10— 50) indicate better adherence Cronbachs Alpha each sub-scales >0. 80 Sensitivity and specificity lacking to measure adherence • Can possibly predict nonadherence • Tedious process for clinical setting.

Adherence Starts with ® Knowledge (ASK-20 ) • ASK-20® (Hahn et al. , 2008) – 20 clinically actionable items • Whether medication was taken >, < than prescribed, skipped, or stopped. • During past week, month, 3 -months, >3 -months, never – Cronbachs alpha 0. 85 – Convergent reliability with self-reported adherence is good – Tool is not scored – Cannot assess adherence rates. • May be useful to assess risk of nonadherence

Adherence Starts with ® Knowledge (ASK-12 ) • Shorter version of ASK-20 (Matza et al. , 2009) • Three subscales that are scored: – Adherence behavior – Health beliefs – Inconvenience or forgetfulness • Psychometrics: – – Internal consistency reliability (α=0. 75) Test-retest reliability (Intraclass Correlation 0. 79) Convergent validity correlations with MMAS p<0. 001 Proportion days covered pharmacy claims data p=0. 06. • Can possibly be adequate in predicting risk of nonadherence and measuring adherence rates

Medication Adherence Report Scale (MARS) • Ten “yes” or “no” questions – Scores 0 -10; 10 represents high likelihood of adherence • Developed from 30 -item Drug Attitudes Inventory (DAI) and 4 -item Medication Adherence Questionnaire (MAQ) • Create more reliable and valid tool (Fialko, 2008) • Good internal consistency (α=0. 75) • Insufficient sensitivity (53%), specificity (57%), positive predictive value (42% to 57%) to detect nonadherence • Receiver operating curve 0. 56 (95% CI 0. 521 to 0. 616; p=0. 01), does not accurately predict risk of nonadherence • Does not accurately predict risk of non-adherence or rates of adherence

Brief Adherence Rating Scale (BARS) • 4 -items: 3 -questions plus visual analog scale to assess the proportion of doses taken in past month (Byerly, 2008) – # prescribed doses taken per day – # days, over the past month, the patient did not take the prescribed doses – # of days over the past month, the patient took less than the prescribed doses • Psychometrics: – – – BARS and MEMS® medication adherence significant p<0. 0001 Cronbachs very high internal reliability (α=0. 92) A moderate/strong test–retest reliability 0. 53 to 0. 92 Concurrent validity significant to PANSS p=0. 002 Good sensitivity (73%) and specificity (74%) • Sufficient validity, reliability, sensitive and specific to estimate risk of nonadherence and adherence rates

Assessing and Measuring Medication Adherence STATE OF THE SCIENCE

• Ability to assess and/or measure OAC medication adherence is poor. – Most measures are indirect, and include a form of self-report that cannot truly capture if the medication was taken. – A few tools are able to assess risk of nonadherence – Lack specificity to determine adherence – Nor can both OAC underadherence and overadherence can be examined.

Tools that may be useful for measuring adherence rates: • ASK-12® • BARS Tools that may assess risk of non-adherence: • • Adherence Estimator Morisky ASK-12® BARS

Implications for Research • Need for practice-based tools • Technology – Including timing, dose, frequency, & duration

Implications for Nursing Practice • Adherence needs to be defined, assessed, and documented.

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