A systematic literature review of methodologies used to assess medication adherence in patients with diabetes.

Current Medical Research & Opinion 0300-7995 doi:10.1185/03007995.2014.884491

Vol. 30, No. 6, 2014, 1071–1085

Article ST-0326.R1/884491 All rights reserved: reproduction in whole or part not permitted

Curr Med Res Opin Downloaded from informahealthcare.com by Ryerson University on 12/02/14 For personal use only.

Review A systematic literature review of methodologies used to assess medication adherence in patients with diabetes

Sarah Clifford

Abstract

Evidera, Bethesda, MD, USA

Magaly Perez-Nieves Eli Lilly and Company, Indianapolis, IN, USA

Anne M. Skalicky Evidera, Bethesda, MD, USA

Matthew Reaney Eli Lilly and Company, Surrey, UK

Objective: Adhering to prescribed medication is often a problem for patients with diabetes yet there is no consensus on how best to measure adherence in this patient population. This systematic literature review critically reviewed and summarized the methods used to measure medication adherence in patients with diabetes (on oral hypoglycemic agents [OHAs] and/or insulin) in original research published between 2007–2013. Study design: Literature review.

Karin S. Coyne Evidera, Bethesda, MD, USA Address for correspondence: Karin Coyne PhD, Senior Research Leader, Evidera, 7101 Wisconsin Ave, Suite 600, Bethesda, MD 20814, USA. Tel: +1 513-943-7604; Fax: +1 301-654-9864; [email protected] Keywords: Diabetes mellitus – Literature review – Medication adherence Accepted: 9 January 2014; published online: 11 February 2014 Citation: Curr Med Res Opin 2014; 30:1071–85

Methods: A systematic search for methods to assess medication adherence in patients with type I or type II diabetes was conducted using PubMed, EMBASE, PsychInfo, and Cochrane databases. Two researchers independently screened abstracts for initial eligibility and then applied the inclusion/exclusion criteria to the relevant full-text articles. Results: Fifty-nine articles met the criteria for inclusion. Subjective assessment (observer-reported and patientreported), pill counts, Medication Event Monitoring System (MEMS), cell-phone real-time assessment, and logbooks were used in prospective studies. In pharmacy claims databases, medication possession ratios (MPRs), or some derivation thereof, were utilized. Each method has strengths and weaknesses, but few approaches specifically addressed issues unique to assessing insulin adherence. Three novel approaches (using cell-phone real-time assessment, computerized logbooks, and a questionnaire about different dosing irregularities) provided insight on timing and dosing issues that could be useful for highlighting interventions to improve insulin adherence. Conclusion: No gold standard exists for measuring medication adherence in patients with diabetes. The plethora of adherence methods precludes the comparison of adherence rates across studies. Greater consistency is therefore needed in adherence measurement, including question content, recall period, and response options for self-report measures. Novel methods for understanding adherence to variable-dosed insulin require further research. Researchers should select a methodology that best fits their research question, study design, patient population and resources.

Introduction Diabetes is a complex chronic condition that requires patients to adhere to a range of self-care activities including diet, exercise, blood glucose monitoring,

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and medication. Maintaining appropriate adherence to these self-care behaviors is a problem commonly experienced by individuals with diabetes1,2. Medication adherence has been defined by the World Health Organization (WHO) as ‘‘the extent to which a person’s behaviour. . .corresponds with agreed recommendations from a health care provider’’3 and has been identified as being problematic for patients with diabetes4. The WHO emphasized that medication adherence is ‘‘the primary reason for suboptimal clinical benefit of therapy’’; therefore, it is not surprising that medication adherence has been the focus of considerable research3. Several literature reviews have been conducted previously to summarize research conducted in the area of medication adherence and diabetes4–6. A comprehensive review by Cramer (2004) focused on reviewing the extent of medication non-adherence in patients with diabetes; estimates from this review showed that reported non-adherence rates vary from 36 to 93%4. Subsequently, Odegard and Capoccia’s (2007) review presented evidence that illustrates the barriers to medication taking for those with diabetes mellitus and highlighted the limited availability of effective interventions that exist to improve adherence in this patient population6. Other terms used in relation to medication-taking are compliance and persistence. Compliance is often used interchangeably with the term adherence; it refers to the same behavior, but the term has been criticized for having negative connotations (i.e., implying that the patient is passive and has no choice in his/her treatment). Persistence has been defined by researchers, including Cramer and colleagues as ‘‘the duration of time from initiation to discontinuation of therapy’’7,8. Although they are related concepts, there is a crucial conceptual distinction between persistence and adherence, i.e., a patient can be persistent to a medication (remain on the prescribed therapy), but be non-adherent (e.g., forgetting doses or not always taking the medication as prescribed). A variety of medications are available for treating type I (T1DM) and type II (T2DM) diabetes mellitus, each with different efficacy and side-effect profiles, and often with different modes and frequencies of administration. Treatment is selected and individualized based on specific patient requirements for glycemic control, and patient preferences, characteristics, and susceptibilities to side effects9. Almost all patients with T1DM require the exogenous administration of subcutaneous insulin therapy to maintain glycemic control. Furthermore, as it is a progressive disease with decline of pancreatic beta-cell function over time, most patients with T2DM will also eventually require insulin therapy10,11. The latest American Diabetes Association guidelines recommend early initiation of insulin in patients with T2DM diabetes who are not meeting treatment goals12. However, hurdles such as developmental behaviors and perceived social 1072


pressures13 in T1DM and psychological insulin/injection resistance14 in T2DM make adherence to subcutaneous insulin particularly poor. Sub-optimal adherence can lead to increased use of health care services and costs, reduced patient health-related quality of life (HRQL), poor clinical outcomes, and increased burden of diabetes15–22. A recent narrative review by Gonzalez and Schneider (2011)5 highlighted the range of methodological issues in the assessment of diabetes treatment adherence and the apparent lack of a gold standard. Medication adherence can be assessed via blood/urine drug concentrations, use of a biological marker, self-report (asking patients if they are taking their medications as prescribed), electronic monitoring, pill counts, patient diaries, or pharmacy claims analyses; however, each method has its limitations. Non-adherence is a problem in both adult and pediatric diabetes populations4,23 although the differences in selfmanagement requirements between the groups need to be considered when thinking about measuring adherence in each group. For example, children are most likely to have their diabetes regimen managed by a patient or care-giver, and therefore an adherence measure may have to include the parent or care-giver’s perspective, as well as the child’s. In contrast, older children, adolescents and adults typically self-manage their own diabetes, and therefore their perspective can be sought directly. The purpose of this systematic literature review was to critically review and summarize the methods used to measure medication adherence in patients with diabetes (on oral hypoglycemic agents and/or insulin regimens). Furthermore, assessing adherence to insulin treatment presents unique challenges due to the importance of timing and correct dosing and the continual variation in insulin regimens and methods of administration available; yet there appears to be a dearth of literature which addresses the issue of variable dosing. Therefore, this review also sought to identify methods that are particularly relevant when assessing adherence to insulin regimens.

Methods Search strategy A systematic search for measures to assess medication adherence in patients with diabetes was conducted in the following databases: PubMed, EMBASE, PsychInfo and Cochrane Collaborative Databases (from January 1, 2007 to November 21, 2013). The last seven years were selected to focus on current medication adherence strategies. Figure 1 presents the keywords used in the search strategy. www.cmrojournal.com ! 2014 Informa UK Ltd


(diabetes OR hyperglycemic OR hyperglycaemic OR "glycemic control" OR "glycaemic control" OR insulin OR "diabetic control" OR antidiabetic)

AND

(“Medication Adherence" OR "Guideline Adherence" OR "Patient Compliance" OR "Treatment Refusal" OR "Refusal of Treatment" OR compliance OR complier OR adherence OR persistence OR persistency OR cooperation OR noncompliance OR nonadherence OR "non adherence" OR "non compliance”)


AND

(Dose OR doses OR dosage* OR inject* OR "Infusion Pumps" OR regimen OR "multiple daily injections" OR "insulin therapy" OR oral OR therapy OR "medication use" OR treatment OR "drug therapy")

AND ("monitoring device" OR "electronic device" OR "self monitor" OR "self monitoring" OR "Drug Monitoring" OR "Blood Glucose Self-Monitoring" OR "Self Administration" OR "Reminders" OR "management" OR "process outcomes" OR managing OR administration OR "Drug Administration Schedule" OR "medication possession ratios" OR self-report)

Figure 1. Search strategy for PubMed, EMBASE, PsychInfo, and Cochrane Databases.

Inclusion and exclusion criteria Articles were included in the review if they met the following inclusion criteria: The study abstract was available The study design and methods were described The article assessed adherence to at least one type of diabetes medication as either a primary or secondary outcome The rates of medication adherence or persistence were reported The article included details of the methods used to calculate adherence level or proportion of adherers/ non-adherers The article was published from 2007 to the time of the review Articles were excluded if they met any of the following criteria: The article only focused on adherence to diet or exercise and did not assess adherence to medication The article did not report medication adherence rates The article was a letter, case report, commentary, or review The article was an animal or in vitro study The article was a duplicate ! 2014 Informa UK Ltd www.cmrojournal.com

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Review process Two members of the project team independently screened the titles and abstracts identified from the search strategy for eligibility in the review. For all abstracts classified by the researchers as eligible, the full published article was obtained. The full-text articles were reviewed by two members of the project team to confirm whether the article met the inclusion criteria. Any articles meeting the exclusion criteria were removed. Data from the articles were then extracted, including: study design, medical population, sample size, study population, study methods (including adherence measures used), and results from the medication adherence assessment.

Results As shown in Figure 2, 628 abstracts were screened and 130 were selected for full-text review. Two additional articles were identified via expert recommendation. A total of 59 articles that assessed adherence to medication in patients with diabetes met the eligibility criteria. Results are summarized in Table 1. The majority of studies reviewed were conducted in North America alone (n ¼ 47, 80%). Forty-six studies used a cross-sectional, randomized controlled, or prospective cohort study design, and thirteen studies used a retrospective study design. Thirty-four studies were with T2DM patients only; 14 were with T1DM patients only; six were with both T1DM and T2DM patients; and five studies did not report the diabetes type.

Cross-sectional, prospective and RCT studies For the cross-sectional, prospective and randomized controlled studies, the majority (37 of 46; 80%) used at least one self-report measure to assess medication adherence24–57, four used pharmacy claims databases or pharmacy/medical records to calculate medication possession ratios (MPR) or some derivation of the MPR formula31,55,58,59, three used prescription refill60–62, two studies used pill/medication counts63,64, one used clinician-reported measures44, one used the Medication Event Monitoring System (MEMS)65, one used a cell phone Ecological Momentary Assessment (EMA)66 and one used a database of logbooks from T1DM patients attending summer camps67. Several studies used more than one adherence measurement methodology25,31,44,55,56,66. Table 2 summarizes the strengths and weaknesses of the different general approaches observed in this review to assessing medication adherence. Of the 37 studies that used self-report to measure medication adherence, a wide range of approaches were used, including questionnaires, interviews, or individual Systematic review of diabetes medication adherence measures Clifford et al.

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Search Steps

Excluded

639 records identified through database search

628 of records remained after duplications were removed


628 abstracts were screened

Total record excluded: 484 Reasons: 1. 2. 3. 4. 5.

Animal or in vitro n = 1 Case report, n = 2 Clinical guidelines, n = 3 Commentary, n = 23 Diabetes medication adherence not assessed, n = 462 6. Qualitative study, n = 9

130 abstracts eligible for full text review Total articles excluded: 73 2 articles recommended by expert in the field

59 articles met eligibility requirement

Reasons: 1. Conference proceedingsonly abstract available, n =15 2. Diabetes medication adherence not assessed, n = 17 3. Diabetes adherence measure not described, n = 5 4. No rates of diabetes adherence reported, n = 24 5. Commentary, guidelines or literature review, n = 12

Figure 2. Search strategy to identify articles relevant to assessing adherence to diabetes medication (from 2007 to 2013).

questions. The length of the self-report measures varied considerably (from one to 90 items); ranging from simple single items to extensive questionnaires which assessed adherence to the whole range of diabetes self-care behaviors. Furthermore, a range of recall periods were used when asking patients to report their medication adherence. Of the articles which reported a recall period, the majority used the past week/7 days as the recall period (n ¼ 11), followed by the past month (n ¼ 4), past 30 days (n ¼ 1), past 2 weeks (n ¼ 2), past 3 months (n ¼ 2), past 12 months (n ¼ 1), and a ‘typical week’ (n ¼ 1). Four articles asked participants to think about their medication taking ‘in general’, and the recall period was not reported in the remaining articles (n ¼ 11). The difference in style and content of the self-report measures and the wide range of recall periods used, in addition to the large number of studies where recall period was not reported, makes it difficult to compare adherence 1074


levels across these studies. Some studies that used selfreport measures only reported a mean total score which gives an indication of the extent of adherence in relation to the total possible score, whereas others used a cut-point to dichotomize participants into adherent/non-adherent categories. When rates of medication adherence/nonadherence were reported in the articles using self-report measures, adherence rates varied from 26%39 to 96%32. The Morisky Medication Adherence Scale (MMAS68,69) was the most frequently used self-report measure (n ¼ 7)26,28,31,42,55,56,70; both the 4-item and 8-item format were used. The 4-item MMAS was originally developed for use in hypertension69 but has been used extensively in other conditions. The 8-item version was developed more recently68 and has not yet been as widely used. The MMAS items were developed in generic terms, i.e., ‘Do you ever forget to take your medicine?’ and ‘When you feel better do you sometimes stop taking your www.cmrojournal.com ! 2014 Informa UK Ltd


T2DM

T1DM

T1DM & T2DM

Wolever et al., 201056

Wysocki et al., 200757

Zhang et al., 201059

Walker et al., 201155

T2DM T2DM T1DM T1DM & T2DM T2DM

T1DM

T1DM & T2DM T1DM & T2DM T1DM & T2DM T2DM

T2DM

Phumipamorn et al., 200864 Rubak et al., 201162 Snoek et al., 200851 Tan et al., 201154

Markowitz et al., 2012

Lingvay et al., 200963

Lin et al., 201261

Heisler et al., 201039

43

37

Gialamas et al., 2009

French et al., 201370

Bogner et al., 2012 Cohen et al., 201031

T2DM T2DM

T2DM

Babamoto et al., 200926

65

T1DM

Diabetes Mellitus Type

Randomized, controlled trials Amsberg et al., 200925

Citation

Oral

Insulin

Oral & Insulin

Oral Oral Insulin Oral & Insulin Oral

Oral & Insulin Oral & Insulin Insulin

Oral & Insulin

Insulin

Oral

Oral Oral

Oral & Insulin

Insulin

Medication Type

Clinical Indicator

HbA1c

HbA1c

HbA1c

Blood glucose & HbA1c HbA1c HbA1c HbA1c HbA1c

HbA1c, glucose, BMI and BP HbA1c

HbA1c

HbA1c HbA1c

HbA1c

HbA1c

Table 1. Summary table of adherence measures used in review articles.

MMAS – 8-item Single item ‘‘Have you missed a medication dose in the past week?’’ Diabetes Self-Management Profile (DSMP)

SDSCA DSCI Revised Diabetes Self-care Activities (R-SDSCA)73 MMAS – 4-item Single medication adherence item from SDSCA scale

Self-report questionnaire adapted from Lu et al.72

Self-report assessment71

Medication Adherence Report Scale (MARS-5) MARS-5

MMAS SDSCA

Diabetes Self-Care Inventory (DSCI) Summary of Diabetes Self-Care Activities (SDSCA) Morisky Medication Adherence Scale (MMAS)

Self-Report

MPR (80%)

Pharmacy claims data from a health care worker union (MPR change defined as 20% [e.g. going from 60 to 80% adherence])

MPR: used as a continuous variable and tertiles: 542% 42–65% 465%

Pharmacy/Medical/Registry Records Databases (and cut-points used)

Medication Adherence Measures


(continued )

Pill count Prescription refill

Pill count

Prescription refill

MEMS caps

Other Measures

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T1DM

T1DM

Drew et al., 201034

Ellis et al., 200735

T2DM

T2DM

Nicklett and Liang, 201047

Miller and Drotar, 200744

Nau et al., 200746

T1DM

Lewin et al., 201041 Mann et al., 200942

T1DM

T1DM T2DM

Kindmalm et al., 200760 Kreyenbuhl et al., 201140

Mulvaney et al., 201245

T1DM & T2DM T2DM T2DM

Gimenes et al., 200938

Fernandes et al., 2011

T1DM

T2DM T2DM

Daly et al., 200932 Delahanty et al., 200733

36

T2DM T1DM

Brod et al., 2012 Butler et al., 200730

75

Oral & Insulin

Oral

Insulin

Insulin

Insulin Oral & Insulin

Oral & Insulin Oral & Insulin

Oral & Insulin

Insulin

Insulin

Insulin

Oral & Insulin Oral & Insulin

Insulin Insulin

Insulin Oral & Insulin Oral & Insulin

T1DM T2DM T2DM

Bagner et al., 200727 Bailey et al., 201228 Billimek and Sorkin, 201229

Medication Type

Oral & Insulin Oral

Diabetes Mellitus Type

Cross-sectional and prospective cohort studies T2DM Aikens and Piette, 2013103 T2DM Alvarez Guisasola et al., 200824

Citation

Table 1. Continued.

Hb1Ac & glucose HbA1c

HbA1c

HbA1c HbA1c

HbA1c

HbA1c

HbA1c

HbA1c HbA1c & glucose

HbA1c

HbA1c HbA1c

Clinical Indicator

Self-report questionnaire: 4item scale adapted from the MARS Self-developed self-report questions

Diabetes Behavior Rating Scale (DBRS)

Brief Medication Questionnaire (BMQ)81 DSMP MMAS – modified 4-item version DSCI

MMAS – 4-item Patient administered, selfreported adherence questionnaires74 DSMP MMAS – 8-item Patient administered selfreported questionnaire 90-item patient questionnaire 14-item Diabetes Self-Care Inventory76 2-item self-report questionnaire SDSCA Two additional adherence items 16-item DSCI (adapted from La Greca et al.77 Diabetes Management Scale (DMS)78 Chronic Disease Compliance Instrument–Diabetes (CDCIdiabetes)79 Treatment Adherence Measure (TAM)80

Self-Report




Health Care Provider Rating Questionnaire Cell phone – Ecological Momentary Assessment (EMA) – www.telesage.com

Prescription refill

Diabetes registry – medication regimens

Other Measures


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T2DM

T2DM

T2DM

T2DM

T2DM

T2DM

T2DM

T2DM

Cobden et al., 200786

Colombi et al., 200887

Donnelly et al., 200788

Egede et al., 201289

Grant et al., 200790

Kalsekar et al., 200791

Kleinman et al., 200892

Krass et al., 201193

T1DM or T2DM

Williams et al., 200958

T2DM

T1DM

Toussi et al., 200867

Retrospective studies Adams et al., 200885

T1DM & T2DM

Tan and Magarey, 200853

T1DM

T2DM

Rothman et al., 200850

Stewart et al., 2009

T2DM

Rhee et al., 200849

52

T2DM

Odegard and Gray, 200848

Table 1. Continued.

Oral & Insulin

Oral & Insulin

Oral

Oral

Oral & Insulin

Insulin

Oral & Insulin

Insulin

Oral

Oral

Insulin

Oral & Insulin

Insulin

Oral & Insulin

Oral & Insulin

Oral & Insulin

HbA1c

HbA1c

HbA1c

HbA1c & glucose & SMBG

Hb1Ac & glucose

Capillary blood glucose (CBG)

Fasting Blood Glucose (FBG)

HbA1c

HbA1c, Random Blood Glucose (RBG) HbA1c

Hb1Ac

Telephone and mail survey; Treatment self-regulation questionnaire84

Brief Medication Questionnaire (BMQ) Two additional adherence items Patient self-report questionnaire82 Telephone survey that includes a domain on medication usage Patient self-report & parent report83 Interviewer-administered: 75item ‘Self-care Activity’ Survey53

Prescribing & dispensing data (No cut-point reported) PharMetrics database of medical & pharmaceutical claims (MPR 80%) PPG Industries pharmacy and prescription claims (MPR 80%) Medical records and dispensed prescribing databases (MPR 80%) Veterans’ Health Administration National Patient Care and Pharmacy Benefits Management databases (MPR 80%) Harvard Vanguard pharmacy and medical records data 490% ¼ excellent 50–90% ¼ moderate 550% ¼ poor State Medicaid medical and prescription claims data (No cutpoint reported) Human Capital Management Services Research Reference Database (MPR 80%) Dispensing history from proportional community pharmacies (MPR 90%)

Continuous, multiple-interval measure of medication gaps (CMG): (80%)


(continued )

Database of logbooks recording insulin dosages



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medicine?’ Response options are yes (0) or no (1). Item responses are summed to create an adherence score range from 0 to 4 for the 4-item scale and 0 to 8 for the 8-item scale with higher scores indicating better adherence. In this review, non-adherence cut-points were usually 2 using the 4-item scale and 6 for the 8-item scale. The MMAS wording can be amended so it is disease-specific (e.g., ‘Do you ever forget to take your diabetes medicine?’), but only one of the six articles using the MMAS reported that they used the diabetes-specific wording27. Diabetes-specific self-report measures were also identified and used in several studies each, e.g., Diabetes SelfCare Inventory (DSCI, n ¼ 5)25,30,34,44,51, Summary of Diabetes Self-Care Activities (SDSCA, n ¼ 4)25,31,33,55, and the Diabetes Self-Management Profile (DSMP, n ¼ 3)27,41,57. The DSCI97,98 (14 items) and SDSCA99 (16 items) are both self-report questionnaires with items assessing adherence to diabetes-related self-care activities. The DSMP100–102 (both 23- and 24-item versions) also assesses adherence to the range of diabetes self-care activities but is interviewer administered. The Diabetes Behavior Rating Scale45 and Diabetes Management Scale35 were other diabetes-related self-report questionnaires used in just one study each. Generic self-report questionnaires used were: the Brief Medication Questionnaire40, Chronic Disease Compliance Instrument36, Medication Adherence Report Scale37,103, Medication Adherence Report Scale – adaptation46, and the Treatment Adherence Measure38. Eleven studies29,32,39,43,47–50,52,53,56 did not use a selfreport scale to measure adherence, but used a more simple, direct approach, often asking just one or two questions, e.g., asking patients when they last missed a dose of their medication39,48,56, or asking patients to rate the percentage of time they were adherent in the last month32,43. Only three of these articles reported that their measurement approach had been previously validated39,48,52. Three distinctive methods from the prospective studies are notable as they attempted to understand the unique issues in assessing adherence to insulin: the Ecological Momentary Assessment (EMA) approach66, computerized logbooks67, and a 90-item patient questionnaire which evaluates a range of different dosing irregularities75. The EMA approach was novel as it provided insight into the timing and dosing of insulin which has not been captured by other adherence measures66. These researchers measured behaviors and experiences in real time using mobile phone devices and a commercially available interactive telephone response system. Adolescents with T1DM were called twice a day for 10 days and asked about their diabetes self-care behaviors. On average, adolescents reported missing 20% of their insulin doses, with the majority (74% of all missed doses) of injections reported to be in the morning. This information may be useful when planning future interventions for this patient



VA National Psychosis Registry (MPR 80%) Electronic medical records from Veterans’ Health Information System Technology Architecture (VistA) database (MPR 80%) VA National Psychosis Registry (MPR 80%) Providence Primary Care Research Network in Oregon (MPR 80%)


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Oral T2DM

Oral T2DM Piette et al., 200796

Rozenfeld et al., 2008

19

Oral & Insulin T1DM Neugaard et al., 2011

Oral T2DM Kreyenbuhl et al., 201094

95

Diabetes Mellitus Type Citation

Table 1. Continued.

Medication Type

HbA1c

Clinical Indicator

Self-Report



Other Measures

Abbreviations: BMI, body mass index; BMQ, Brief Medication Questionnaire; BP, blood pressure; CDCI-diabetes, Chronic Disease Compliance Instrument-Diabetes; CMG, Continuous Glucose Monitoring; DBRS, Diabetes Behavior Rating Scale; DSCI, diabetes self-care inventory; DSMP, Diabetes Self-Management Program; EMA, Ecological Momentary Assessment; HbA1c, glycated hemoglobin; MARS-5, Medication Adherence Report Scale; MMAS, Morisky Medication Adherence Scale; MPR, Medication Possession Ratios; SDSCA, summary of diabetes self-care activities; SMBG, self-monitoring of blood glucose; T1DM, type 1 diabetes mellitus; T2DM, type 2 diabetes mellitus; TAM, treatment adherence measure; VA, Veterans Affairs.



Electronic or paper-based medical record review

Patient prescription refill count. Medication Possession Ratio (MPR) is typically defined as the sum of the days’ supply of medication, divided by the number of days between refills

Pills counted to assess number of pills remaining in relation to number of pills prescribed

Measures medication bottle opening during a defined period of time

Details the dose, frequency and number of missed doses

Patient-report of adherence-related behaviors; can be self or interviewer-administered formats

Observer report of frequency of adherence/ non-adherence

Definition

Device provides real-time measurements of glucose levels Biochemical marker of blood glucose control over the preceding 2–4 months

Continuous Glucose Monitoring

HbA1c levels

Biochemical Measurement as Proxies to Adherence Glucose Monitoring An indicator of short-term glycemic control

Record review

Retrospective Pharmacy refill claims

Remaining dosage units or pill count

Other Measures Medication Event Monitoring System

Medication diary

Patient-reported Questionnaires: Questionnaires

Subjective Ratings of Adherence Observer-reported Questionnaires: Physician reports

Adherence Measurement

Table 2. Summary of strengths and weaknesses of methods to evaluate medication adherence.

Objective measure, signal of longer-term glycemic control

Real-time measurement; may enable better glucose control

Simple; less expensive; easy to use

Provides accurate prescribing and dosing information

Inexpensive; reliable measure of adherence

Inexpensive; widespread use possible

Precise, tracks patterns of taking medication; records time and date medication bottle opened

Simple; easy to administer, various forms of administration (phone, mail, ePRO, inperson), widespread use possible, can focus on generic adherence to medication or a range of self-care adherence behaviors; can be inexpensive Only self-report method providing regimen data

Physician perception of patient adherence to prescribed treatment

Strength


Findings can be misleading; influenced by diet, activity, or absorption Expense prevents widespread use; not as accurate and reliable as standard blood glucose meters Expense prevents widespread use, not well correlated with adherence measures, requires blood collection and laboratory testing

Prescription refill is not equivalent to medication ingestion; requires a closed pharmacy system; difficult to differentiate patient overuse and early refills or appropriate behaviors such as changes in drug regimens, combination therapies, or multiple dispensings to achieve a specific dose; cannot accurately account for variable dosing requirements of insulin Time intensive; requires a closed medical care system; documentation of prescribing and dosing is not equivalent to medication ingestion

Expense prevents widespread use; data easily altered; bottle opening is not the same as medication ingestion; dosage patterns not captured; cannot be used with insulin administration Patient must bring in pills; can over-estimate medication adherence; data easily altered by the patient (e.g., pill dumping); timing and dosage patterns not captured

Time consuming; may over-estimate adherence; patient must complete and return diary (thus, potential for low response rate)

Data are questionnaire dependent; may overestimate adherence; may not correlate well with clinically objective measures

Opportunity for observation of whether patient behavior is limited or unrealistic; overestimates adherence

Weakness



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group. In terms of insulin dosing, the average rate of reported incorrect insulin doses was quite low (4.6%). Toussi et al.67 presented another innovative approach to assessing adherence as the authors argued that existing adherence measures are not applicable for the evaluation of adherence to insulin adjustment guidelines because the guidelines do not specify correct insulin doses in advance as patients have control over determining the correct dose that is needed. Therefore, Toussi and colleagues developed an indicator-based measure of adherence where T1DM adolescents had their self-calculated injected insulin doses entered into a computerized logbook while they were at summer camp in France. This logbook was then compared against the recommended dose (using a clinical guideline) and level of agreement between the self-calculated and recommended doses was calculated. Adolescents had been taught to use the official national guideline (Aide aux Jeunes Diabe´tiques – AJD; the English language translation of the clinical guideline is available in a zip file from the authors’ original paper67) consisting of two pages of simple recommendations for how to adjust insulin dose in a basal–bolus schema of insulin therapy which included one injection of insulin lispro or insulin aspart before each meal, and one injection of insulin glargine before bed. The level of agreement between the computer-generated recommended dose adjustments and the patient self-administered doses was categorized as follows: Absolute agreement: injected dose and recommended dose were the same Relative agreement: slight difference between injected and recommended dose Extreme disagreement: extreme difference between injected and recommended dose, defined as such if patient dose adjustment was in an opposite direction (i.e., increase vs. decrease). The authors argue that this corresponds to ‘potentially dangerous’ cases Under-treatment: the injected dose was smaller compared to the recommended dose Over-treatment: the injected dose was greater compared to the recommended dose Results showed that there was absolute agreement for 45% of insulin doses, relative agreement for 30%, extreme disagreement for 2%, under-treatment for 26% and overtreatment for 30%. This study was only conducted on a small sample (n ¼ 28) but as data were collected over the 3 week camp, the authors had data on 1656 insulin doses. This approach is unique as it provides a detailed insight into daily patterns of medication taking over an extended period of time and was the only study that addressed the issue of ‘over-adherence’ (i.e., over-treatment with insulin). Another innovative approach was taken in the article by Brod et al. (2012)75. The authors conducted an online, multinational cross-sectional study of patients with T2DM treated with basal insulin. They evaluated patterns of 1080


adherence according to three types of dosing irregularity over the last 30 days: missed, mistimed ( 2 hours from prescribed time), and reduced dose. This study involved 3042 patients from six countries (US, Japan, UK, Germany, Canada, and Denmark). The questionnaire was developed using an international steering committee of clinical diabetes experts, literature, and focus groups/ interviews with diabetes patients, in order to ensure high survey content validity. Results showed that more than a third of patients reported some type of basal insulin dosing irregularity in the last 30 days (22% missed; 24% mistimed; 14% reduced dose). The authors argue that these three dosing irregularities are unique behavioral entities and should therefore be measured separately. This study provides great insight in to the extent and type of insulin dosing irregularities performed by patients with T2DM.

Retrospective database studies Thirteen retrospective studies were also identified which assessed medication adherence in patients with diabetes19,85–89,91–96. All of these used Medication Possession Ratios (MPR) or some derivation of the MPR formula (defined as the sum of the days’ supply of medication divided by the number of days between refills). The majority of studies used pharmacy/medical claims data, except for one study in Scotland which used a local diabetes registry88 and two in the United States which used a Department of Veterans Affairs (VA) clinical registry89,96. In general, adherence was defined as MPR 0.8 (i.e., the patient had a supply of prescribed medication for at least 80% of the days for which he or she was prescribed medication; referred to as 80% or greater adherence). Many studies reported average MPRs for the sample or the proportion of patients classified as adherent/nonadherent based on the 0.8 cut-point. Only three studies reported MPRs that exceeded 1.0 (or 100% adherence): Cobden et al.86 adjusted MPRs greater than 1 to 1; Kreyenbuhl et al.94 excluded patients with MPRs exceeding 1.2 from the analysis as the authors thought the higher rate was likely related to an excess supply of medication resulting from a change in medication dosage or from the patient obtaining a refill early; and Donnelly et al.88 reported that if subsequent prescriptions were dispensed before the end of a previous prescription, then the previous prescription was censored at the start of the new prescription. For OHA-only studies, average MPR rates ranged from 70% to 90%19,75,87,91. Colombi et al.87 reported MPRs stratified according to age group (65 vs. 565) and co-pay categories (low, medium or high) and found the lowest rates of adherence in the high co-pay category (average MPR of 70% in both age groups) compared to the low co-pay category (82% and 78%, for the 65 vs. www.cmrojournal.com ! 2014 Informa UK Ltd



565 age groups respectively). The rates for the low co-pay category patients were similar to the mean MPRs of 81%, 80%, and 78% reported by Rozenfeld et al.19, Grant et al.90, and Egede et al.89, respectively. The highest average MPRs were found by Kalsekar et al.91 who stratified average MPR according to whether patients used an independent or chain pharmacy (90% and 88%, respectively). Rates may have been higher in this study as the sample consisted exclusively of patients newly started on OHAs. Grant et al.90 also reported adherence rates according to MPR tertiles: less than 10% were classified as having poor adherence (MPR 550%), 48% were categorized as having moderate adherence (MPR between 50–90%), and 42% of patients were deemed to have excellent adherence (MPR 490%). For studies that reported average MPRs across all types of diabetes medication (OHAs and insulin), Krass et al.93 used a cut-point of 0.9 to define adherence/non-adherence and 70% of patients were defined as adherent. Piette et al.96 used a cut-point of 0.8 and found 71% were categorized as adherent. For studies reporting insulin-only MPRs, average MPR ranged from 59%86 and 61%92 to 71%88. Kleinman et al.92 reported that only 36.5% of insulin users were deemed adherent based on an MPR 0.8. The differences in MPRs here may have been due to differences in sample characteristics among the studies. There was a higher mean age in the sample from Donnelly et al.88 compared to the samples from Cobden et al.86 and Kleinman et al.92 (62 yrs vs. 45.1 yrs and 46.5 yrs respectively). Countryspecific differences may also be an explanatory factor; the sample in the Donnelly study was from Scotland, UK where there are zero or minimal costs for filling prescriptions, compared to the US samples in Cobden et al.86 and Kleinman et al.92 where prescription costs are higher. Another method of describing medication use from retrospective database studies included the calculation of persistence to OHAs which was calculated as the proportion of days covered, and defined as the total number of days’ supply for the study year divided by the number of days between first fill and the end of the year95. However, Neugaard et al.95 excluded patients on insulin when evaluating their persistence calculation. Another study by Kalsekar et al.91 compared patients who used chain vs. private pharmacies for refilling their prescription medications and explored differences in OHA medication adherence and four other patterns of medication use between patients in these two groups: discontinuation, augmentation, switching, and non-modification. They found the difference in rates of adherence (using MPR) between chain and private pharmacy patients was statistically significant, although the magnitude of difference was small (88% vs. 90%, respectively, p50.009). Patients using a chain pharmacy were significantly (1.3 times) more likely to augment therapy compared to ! 2014 Informa UK Ltd www.cmrojournal.com

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patients using an independent pharmacy. No other significant differences in utilization patterns were reported. Kleinman et al.92 used claims databases to evaluate medication adherence to insulin regimens in more detail than the others and compared insulin adherence between insulin glargine and other insulin types. The authors argued that days’ supply information in pharmacy claims data is not as accurate for injectable medications as for those in pill form, thus they devised a method to adjust days’ supply for insulin to reflect a more likely average time between insulin prescriptions. The authors found that individuals receiving a 30 day supply of insulin did not fill another prescription until an average of 45 days after the initial fill. Therefore, in their analysis they adjusted the original days supplied by a factor of 1.5 (or 45/30) to provide a more accurate reflection of the fact that insulin dosages change over time and vary day to day. They used the adjusted days supplied value with the date the prescription was filled to determine the time period for which a supply was available to the patient and also determined the number of days the patient had a supply of insulin during the 12 month study period. The MPR was then defined as usual as the number of days in the year with a supply available divided by the total number of days in the year. They found that patients on a once daily dose of insulin glargine had a significantly higher average MPR compared to patients on short-acting insulin which required multiple injections (66% vs. 54%, p50.0001).

Discussion This review summarized the methods used to measure medication adherence in patients with diabetes (on OHAs and/or insulin) in original research published from 2007 to 2013, and highlighted novel methods that have been used to assess the issues specific to measuring adherence to the variable dosing involved in insulin regimens. Fifty-nine articles assessing adherence to medication in patients with diabetes were identified. The most frequently used method of assessing adherence was self-report, followed by use of pharmacy claims databases to calculate MPRs or some derivation of the MPR formula. Several other methods were used much less frequently, including pill count, MEMS, and clinician-reported adherence. The diverse approaches for assessing adherence preclude comparison of adherence rates across studies. Even where a similar approach was taken (e.g., self-report was used in 37 studies), it was used inconsistently, with various selfreport measures used, and with no standard recall period, different question content, and different response options. Relatively few studies explicitly addressed the unique methodological issues inherent in measuring adherence to Systematic review of diabetes medication adherence measures Clifford et al.

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a variable dose regimen like insulin. Kleinman et al.92 addressed the methodological problems in calculating MPRs from pharmacy claims databases for patients on insulin, and proposed a useful method of adjusting the days’ supply value by a factor of 1.5 to reflect the fact that insulin dosages often change over time. The Mulvaney et al.66, Brod et al.75, and Toussi et al.67 studies were small but they utilized relatively innovative approaches to capture timing and dosing issues and offer useful insights into ideal intervention for providing adherence-related support to diabetes patients on insulin regimens. The Toussi et al.67 study was also important as it highlighted the little-discussed issue of over-adherence in patients taking insulin. However, the disadvantages of the approaches used in these two studies are that they are time-consuming for both the researcher and participant and are also resource intensive. When choosing a methodology for assessing adherence in patients with diabetes, researchers should consider the purpose and scope of their study and their target patient population and select an approach that best fits their needs and available resources. For example, many studies have used MPRs as a useful way of measuring adherence, particularly in retrospective studies of T2DM patients taking OHA. However, this approach may only be relevant for researchers who seek a quantitative indication of the extent of adherence/non-adherence and it would not be suitable for studies where researchers also want to measure and understand patients’ reasons for non-adherence or type of non-adherence, i.e., whether it is intentional (the patient makes an active decision to not take the medication) or unintentional (the patient may forget to take the medication or not realize he/she is not taking it as prescribed). The advantages of using MPR are that it is usually derived from a reliable and extensive source of patient medical and prescription information and it is relatively inexpensive. Alternatively, self-report measures can be used in studies where researchers want to assess both the extent of non-adherence and patients’ reasons for non-adherence. Some self-report measures have been developed with generic items related to medication taking (e.g., MMAS, MARS), and which have been used in a range of chronic conditions to assess medication adherence; whereas others were developed specifically for use in the diabetes patient population (e.g., DSCA, DSCI, DSMP). Choice of selfreport measure should reflect the specific needs of the researchers. For example, the diabetes-specific measures would be most relevant for researchers interested in assessing adherence to the range of diabetes self-care behaviors (e.g., diet, exercise, blood glucose monitoring, medication). However, researchers who want to focus solely on medication adherence may find the general medication adherence measures more appropriate due to their shorter length and specific focus on items related to 1082


medication-taking. Alternatively, specific subscales of the diabetes-specific measures could be used instead of the entire scale, if acceptable and valid according to the original scale developer’s guidelines. Recall period should also be carefully considered, as recall bias is more likely to occur if the timeframe for recalling adherence behavior is not recent enough for patients to accurately remember how and when they have been taking their medication. Self-report is a simple and relatively low-cost approach, but it can over-estimate adherence. A previous review indicated that less than half of self-report measures correlated with non-self-report measures of adherence104. However, the authors found that agreement between measures varied substantially between type of self-report measure. Diaries and questionnaires were highly concordant with the non-self-report measures (71% [10 of 14] and 55% [12 of 22] of comparisons, respectively), whereas interviews were highly concordant with non-self-report measures in relatively few of the comparisons (31%; 15 of 49). Other strengths and weaknesses are outlined in Table 2. An alternative to the self-report questionnaires/scales is a simplified approach of asking patients to report when they last missed a dose of their medication or to rate the extent to which they have taken their medications as prescribed. The advantage of this approach over other selfreport methods is that the questions are concise and quick to administer. However, little information was provided on the validity and reliability of these questions in the papers identified in this review. There is clearly a need for further research and debate in the area of assessing adherence to medication in patients with diabetes. Many self-report questionnaires have been used to assess medication adherence in this patient population, but there needs to be greater consensus on which measures are most appropriate for use in different research scenarios. Methodological studies are needed that compare self-report options and recall periods in assessing adherence in patients with diabetes, e.g., the approach taken by Lu et al.72 in a methodological paper regarding assessment of medication adherence in patients with HIV. Lu and colleagues72 evaluated three different self-report response formats (frequency, percentage, and rating responses) and three different recall periods (3 days, 7 days, and a month) for assessing medication adherence. They then compared those results with MEMS adherence taken during the same time period. They found less overestimation of self-reported adherence with a 1 month recall period than with a 3 or 7 day recall period and that the rating response was the most accurate response format. Interestingly, the percentage and frequency items had a greater tendency to under-report poor adherence and over-report good adherence. However, at present, this methodological approach could only be used with patients www.cmrojournal.com ! 2014 Informa UK Ltd


taking OHAs as there is no electronic monitoring for insulin. Another area for further research is to explore the impact that new and upcoming diabetes therapies have on adherence and/or persistency levels – e.g. extended release insulin preparations.


Conclusion Adhering to prescribed medication (OHAs and/or insulin) is a problem for many patients with diabetes. Researchers, clinicians and policy-makers need to understand how best to assess medication adherence in this patient population and they need a measure which accurately captures details specific to the diabetes medication regimens. The wide range of methodologies used to assess medication adherence in patients with diabetes illustrates that although there has been substantial research in this area, there is a lack of consensus on the best method to measure adherence. Self-report and MPRs have been most widely used. Researchers should select a methodology that best fits their research question, study design, target patient population, timeline, and resources. Further research and consideration also needs to be given to address the issue of variable dosing when measuring medication adherence in patients with diabetes on an insulin regimen. Novel measures (e.g., EMA and computerized logbook databases) could be evaluated in larger samples of patients taking insulin to get a better understanding of patterns of medication adherence and dosing issues over time.

Transparency Declaration of funding Funding for this work was provided by Eli Lilly and Company. Declaration of financial/other relationships S.C., A.S. and K.S.C. are employed by Evidera, which provides consulting and other research services to pharmaceutical, device, government and non-government organizations. As Evidera employees, they work with a variety of companies and organizations and are expressly prohibited from receiving any payment or honoraria directly from these organizations for services rendered. M.P.-N. and M.R. are employees of Eli Lilly and Company. CMRO peer reviewers may have received honoraria for their review work. The peer reviewers on this manuscript have disclosed that they have no relevant financial relationships. Acknowledgements The authors would like to thank colleagues who helped with the retrieval and tabling of articles for this literature review: Zaneta Balantac, Katherine Kim, Laurie Smith and Hafiz Oko-Osi.


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References 1. Kurtz SM. Adherence to diabetes regimens: empirical status and clinical applications. Diabetes Educ 1990;16:50-9 2. Peyrot M, Rubin RR, Lauritzen T, et al. Psychosocial problems and barriers to improved diabetes management: results of the Cross-National Diabetes Attitudes, Wishes and Needs (DAWN) Study. Diabetic Med 2005;22:1379-85 3. World Health Organization. Adherence to long-term therapies: evidence for action. 2003; Available from: http://apps.who.int/medicinedocs/en/d/ Js4883e/ [Last accessed 6 December 2012] 4. Cramer JA. A systematic review of adherence with medications for diabetes. Diabetes Care 2004;27:1218-24 5. Gonzalez JS, Schneider HE. Methodological issues in the assessment of diabetes treatment adherence. Curr Diabetes Rep 2011;11:472-9 6. Odegard PS, Capoccia K. Medication taking and diabetes: a systematic review of the literature. Diabetes Educ 2007;33:1014-29 7. Cramer JA, Roy A, Burrell A, et al. Medication compliance and persistence: terminology and definitions. Value Health 2008; 11:44-7 8. Peterson AM, Nau DP, Cramer JA, et al. A checklist for medication compliance and persistence studies using retrospective databases. Value Health 2007;10:3-12 9. Inzucchi SE, Bergenstal RM, Buse JB, et al. Management of hyperglycaemia in type 2 diabetes: a patient-centered approach. Position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetologia 2012;55:1577-96 10. NICE. Type 2 diabetes: The management of type 2 diabetes. 2009. Available at: http://www.nice.org.uk/nicemedia/live/12165/44320/44320.pdf [Last accessed 6 December 2012] 11. UKPDS. Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). UK Prospective Diabetes Study (UKPDS) Group. Lancet 1998;352:837-53 12. Nathan DM, Buse JB, Davidson MB, et al. Medical management of hyperglycemia in type 2 diabetes: a consensus algorithm for the initiation and adjustment of therapy: a consensus statement of the American Diabetes Association and the European Association for the Study of Diabetes. Diabetes Care 2009;32:193-203 13. Borus JS, Laffel L. Adherence challenges in the management of type 1 diabetes in adolescents: prevention and intervention. Curr Opin Pediatr 2010;22:405-11 14. Polonsky WH, Fisher L, Guzman S, et al. Psychological insulin resistance in patients with type 2 diabetes: the scope of the problem. Diabetes Care 2005;28:2543-5 15. Ho PM, Rumsfeld JS, Masoudi FA, et al. Effect of medication nonadherence on hospitalization and mortality among patients with diabetes mellitus. Arch Intern Med 2006;166:1836-41 16. Lau DT, Nau DP. Oral antihyperglycemic medication nonadherence and subsequent hospitalization among individuals with type 2 diabetes. Diabetes Care 2004;27:2149-53 17. Lee WC, Balu S, Cobden D, et al. Medication adherence and the associated health-economic impact among patients with type 2 diabetes mellitus converting to insulin pen therapy: an analysis of third-party managed care claims data. Clinical Therapeutics 2006;28:1712-25; discussion 10-1 18. Pladevall M, Williams LK, Potts LA, et al. Clinical outcomes and adherence to medications measured by claims data in patients with diabetes. Diabetes Care 2004;27:2800-5 19. Rozenfeld Y, Hunt JS, Plauschinat C, et al. Oral antidiabetic medication adherence and glycemic control in managed care. Am J Manag Care 2008;14:71-5 20. Salas M, Hughes D, Zuluaga A, et al. Costs of medication nonadherence in patients with diabetes mellitus: a systematic review and critical analysis of the literature. Value Health 2009;12:915-22 21. Sokol MC, McGuigan KA, Verbrugge RR, Epstein RS. Impact of medication adherence on hospitalization risk and healthcare cost. Med Care 2005;43:521-30


1083



June 2014

22. Vervloet M, van Dijk L, Santen-Reestman J, et al. Improving medication adherence in diabetes type 2 patients through Real Time Medication Monitoring: a randomised controlled trial to evaluate the effect of monitoring patients’ medication use combined with short message service (SMS) reminders. BMC Health Serv Res 2011;11:5 23. Hood KK, Peterson CM, Rohan JM, Drotar D. Association between adherence and glycemic control in pediatric type 1 diabetes: a meta-analysis. Pediatrics 2009;124:e1171-9 24. Alvarez Guisasola F, Tofe Povedano S, Krishnarajah G, et al. Hypoglycaemic symptoms, treatment satisfaction, adherence and their associations with glycaemic goal in patients with type 2 diabetes mellitus: findings from the Real-Life Effectiveness and Care Patterns of Diabetes Management (RECAPDM) Study. Diabetes Obes Metabol 2008;10(Suppl 1):25-32 25. Amsberg S, Anderbro T, Wredling R, et al. A cognitive behavior therapy-based intervention among poorly controlled adult type 1 diabetes patients – a randomized controlled trial. Patient Educ Couns 2009;72-80 26. Babamoto KS, Sey KA, Camilleri AJ, et al. Improving diabetes care and health measures among hispanics using community health workers: results from a randomized controlled trial. Health Educ Behav 2009;113-26 27. Bagner DM, Williams LB, Geffken GR, et al. Type 1 diabetes in youth: The relationship between adherence and executive functioning. Child Health Care 2007;36:169-79 28. Bailey GR, Barner JC, Weems JK, et al. Assessing barriers to medication adherence in underserved patients with diabetes in Texas. Diabetes Educ 2012;38:271-79 29. Billimek J, Sorkin DH. Self-reported neighborhood safety and nonadherence to treatment regimens among patients with type 2 diabetes. J Gen Intern Med 2012;27:292-96 30. Butler JM, Skinner M, Gelfand D, et al. Maternal parenting style and adjustment in adolescents with type I diabetes. J Pediatr Psychol 2007;32:1227-37 31. Cohen HW, Shmukler C, Ullman R, et al. Measurements of medication adherence in diabetic patients with poorly controlled HbA(1c). Diabetic Med 2010; 210-6 32. Daly JM, Hartz AJ, Xu Y, et al. An assessment of attitudes, behaviors, and outcomes of patients with type 2 diabetes. Journal of the American Board of Family Medicine: JABFM 2009;22:280-90 33. Delahanty LM, Grant RW, Wittenberg E, et al. Association of diabetes-related emotional distress with diabetes treatment in primary care patients with Type 2 diabetes. Diabetic Med 2007;24:48-54 34. Drew LM, Berg C, Wiebe DJ. The mediating role of extreme peer orientation in the relationships between adolescent-parent relationship and diabetes management. J Fam Psych 2010;24:299-306 35. Ellis DA, Podolski C-L, Frey M, et al. The role of parental monitoring in adolescent health outcomes: Impact on regimen adherence in youth with type 1 diabetes. J Pediatr Psychol 2007;32:907-17 36. Fernandes R, Wales S, Crisp J, Kyngas H. Modification and testing of the Chronic Disease Compliance Instrument to measure treatment compliance in adolescents with diabetes. J Clin Nurs 2011;20:1273-81 37. Gialamas A, Yelland LN, Ryan P, et al. Does point-of-care testing lead to the same or better adherence to medication? A randomised controlled trial: the PoCT in General Practice Trial. Med J of Australia 2009;487-91 38. Gimenes HT, Zanetti ML, Haas VJ. Factors related to patient adherence to antidiabetic drug therapy. Rev Latino-Am Enfermagem 2009;17:46-51 39. Heisler M, Hofer TP, Klamerus ML, et al. Study protocol: the Adherence and Intensification of Medications (AIM) study – a cluster randomized controlled effectiveness study. Trials 2010;11:95 40. Kreyenbuhl J, Leith J, Medoff DR, et al. A comparison of adherence to hypoglycemic medications between Type 2 diabetes patients with and without serious mental illness. Psychiatry Res 2011;188:109-14 41. Lewin AB, Storch EA, Williams LB, et al. Brief report: Normative data on a structured interview for diabetes adherence in childhood. J Pediatr Psychol 2010;35:177-82 42. Mann DM, Ponieman D, Leventhal H, Halm EA. Predictors of adherence to diabetes medications: The role of disease and medication beliefs. J Behav Med 2009;32:278-84

1084


43. Markowitz SM, Carper MM, Gonzalez JS, et al. Cognitive-behavioral therapy for the treatment of depression and adherence in patients with type 1 diabetes: pilot data and feasibility. Prim Care Companion CNS Disord 2012;14 44. Miller VA, Drotar D. Decision-making competence and adherence to treatment in adolescents with diabetes. J Pediatr Psychol 2007;32:178-88 45. Mulvaney SA, Rothman RL, Dietrich MS, et al. Using mobile phones to measure adolescent diabetes adherence. Health Psychol 2012;31:43-50 46. Nau DP, Aikens JE, Pacholski AM. Effects of gender and depression on oral medication adherence in persons with type 2 diabetes mellitus. Gender Medicine 2007;4:205-13 47. Nicklett EJ, Liang J. Diabetes-related support, regimen adherence, and health decline among older adults. J Gerontol B Psychol Sci Soc Sci 2010;65B:390-99 48. Odegard PS, Gray SL. Barriers to medication adherence in poorly controlled diabetes mellitus. Diabetes Educ 2008;34:692-97 49. Rhee MK, Ziemer DC, Caudle J, et al. Use of a uniform treatment algorithm abolishes racial disparities in glycemic control. Diabetes Educ 2008;34:655-63 50. Rothman RL, Mulvaney S, Elasy TA, et al. Self-management behaviors, racial disparities, and glycemic control among adolescents with type 2 diabetes. Pediatrics 2008;121:e912-9 51. Snoek FJ, van der Ven NC, Twisk JW, et al. Cognitive behavioural therapy (CBT) compared with blood glucose awareness training (BGAT) in poorly controlled Type 1 diabetic patients: long-term effects on HbA moderated by depression. A randomized controlled trial. Diabetic Med 2008;25:1337-42 52. Stewart SM, Wang JT, Wang Y-C, White PC. Patient- versus parent-reported psychological symptoms as predictors of type 1 diabetes management in adolescents. Child Health Care 2009;38:200-12 53. Tan MY, Magarey J. Self-care practices of Malaysian adults with diabetes and sub-optimal glycaemic control. Patient Educ Couns 2008;72:252-67 54. Tan MY, Magarey JM, Chee SS, et al. A brief structured education programme enhances self-care practices and improves glycaemic control in Malaysians with poorly controlled diabetes. Health education research 2011;26:896-907 55. Walker EA, Shmukler C, Ullman R, et al. Results of a successful telephonic intervention to improve diabetes control in urban adults: a randomized trial. Diabetes Care 2011;34:2-7 56. Wolever RQ, Dreusicke M, Fikkan J, et al. Integrative health coaching for patients with type 2 diabetes: a randomized clinical trial. Diabetes Educ 2010;36:629-39 57. Wysocki T, Harris MA, Buckloh LM, et al. Randomized trial of behavioral family systems therapy for diabetes: maintenance of effects on diabetes outcomes in adolescents. Diabetes Care 2007;30:555-60 58. Williams GC, Patrick H, Niemiec CP, et al. Reducing the health risks of diabetes: How self-determination theory may help improve medication adherence and quality of life. Diabetes Educ 2009;35:484-92 59. Zhang Y, Lave JR, Donohue JM, et al. The impact of Medicare part D on medication adherence among older adults enrolled in Medicare-advantage products. Medical care 2010;48:409-17 60. Kindmalm L, Melander A, Nilsson JL. Refill adherence of antihyperglycaemic drugs related to glucose control (HbA1c) in patients with type 2 diabetes. Acta Diabetologica 2007;44:209-13 61. Lin EH, Von Korff M, Ciechanowski P, et al. Treatment adjustment and medication adherence for complex patients with diabetes, heart disease, and depression: a randomized controlled trial. Ann Fam Med 2012;10:6-14 62. Rubak S, Sandbaek A, Lauritzen T, et al. Effect of "motivational interviewing" on quality of care measures in screen detected type 2 diabetes patients: a one-year follow-up of an RCT, ADDITION Denmark. Scand J Prim Health Care 2011;29:92-98 63. Lingvay I, Legendre JL, Kaloyanova PF, et al. Insulin-based versus triple oral therapy for newly diagnosed type 2 diabetes: which is better? Diabetes Care 2009;1789-95 64. Phumipamorn S, Pongwecharak J, Soorapan S, et al. Effects of the pharmacist’s input on glycaemic control and cardiovascular risks in Muslim diabetes. Primary care diabetes 2008;2:31-7




65. Bogner HR, Morales KH, de Vries HF, Cappola AR. Integrated management of type 2 diabetes mellitus and depression treatment to improve medication adherence: a randomized controlled trial. Ann Fam Med 2012;15-22 66. Mulvaney SA, Rothman RL, Wallston KA, et al. An internet-based program to improve self-management in adolescents with type 1 diabetes. Diabetes Care 2010;33:602-4 67. Toussi M, Choleau C, Reach G, et al. A novel method for measuring patients’ adherence to insulin dosing guidelines: introducing indicators of adherence. BMC Med Inform Decis Mak 2008;8:55 68. Morisky DE, Ang A, Krousel-Wood M, Ward HJ. Predictive validity of a medication adherence measure in an outpatient setting. J Clin Hypertens (Greenwich) 2008;10:348-54 69. Morisky DE, Green LW, Levine DM. Concurrent and predictive validity of a self-reported measure of medication adherence. Med Care 1986;24:67-74 70. French DP, Wade AN, Farmer AJ. Predicting self-care behaviours of patients with type 2 diabetes: the importance of beliefs about behaviour, not just beliefs about illness. J Psychosom Res 2013;74:327-33 71. Heisler M, Faul JD, Hayward RA, et al. Mechanisms for racial and ethnic disparities in glycemic control in middle-aged and older Americans in the health and retirement study. Arch of InternMed 2007;167:1853-60 72. Lu M, Safren SA, Skolnik PR, et al. Optimal recall period and response task for self-reported HIV medication adherence. AIDS Behav 2008;12:86-94 73. Naicker AS, Ohnmar H, Choon SK, et al. A study of risk factors associated with diabetic foot, knowledge and practice of foot care among diabetic patients. Int Med J 2009;16:189-93 74. Grant RW, Devita NG, Singer DE, Meigs JB. Improving adherence and reducing medication discrepancies in patients with diabetes. Ann Pharmacother 2003;37:962-9 75. Brod M, Rana A, Barnett AH. Adherence patterns in patients with type 2 diabetes on basal insulin analogues: missed, mistimed and reduced doses. Curr Med Res Opin 2012;28:1933-46 76. La Greca A, Follansbee D, Skyler J. Developmental and behavioral aspects of diabetes management in youngsters. Child Health Care 1990;19:132-39 77. La Greca AM, Auslander WF, Greco P, et al. I get by with a little help from my family and friends: adolescents’ support for diabetes care. J Pediatr Psychol 1995;20:449-76 78. Frey MA, Ellis D, Naar-King S, Greger N. Diabetes management in adolescents in poor metabolic control. Diabetes Educ 2004;30:647-57 79. Kyngas HA, Skaar-Chandler CA, Duffy ME. The development of an instrument to measure the compliance of adolescents with a chronic disease. J Adv Nurs 2000;32:1499-506 80. Delgado AB, Lima ML. Contributo para a validacao concorrente de uma medida de adesao aos tratamentos. Psicologia, Saude & Doenc¸as 2001;2:81-100 81. Svarstad BL, Chewning BA, Sleath BL, Claesson C. The Brief Medication Questionnaire: a tool for screening patient adherence and barriers to adherence. Patient Educ Couns 1999;37:113-24 82. Rhee MK, Slocum W, Ziemer DC, et al. Patient adherence improves glycemic control. Diabetes Educ 2005;31:240-50 83. Littlefield CH, Craven JL, Rodin GM, et al. Relationship of self-efficacy and binging to adherence to diabetes regimen among adolescents. Diabetes Care 1992;15:90-4 84. Levesque CS, Williams GC, Elliot D, et al. Validating the theoretical structure of the Treatment Self-Regulation Questionnaire (TSRQ) across three different health behaviors. Health Educ Res 2007;22:691-702 85. Adams AS, Trinacty CM, Zhang F, et al. Medication adherence and racial differences in A1C control. Diabetes Care 2008;31:916-21


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86. Cobden D, Lee WC, Balu S, et al. Health outcomes and economic impact of therapy conversion to a biphasic insulin analog pen among privately insured patients with type 2 diabetes mellitus. Pharmacotherapy 2007;27:948-62 87. Colombi AM, Yu-Isenberg K, Priest J. The effects of health plan copayments on adherence to oral diabetes medication and health resource utilization. Journal of occupational and environmental medicine / American College of Occupational and Environmental Medicine 2008;50:535-41 88. Donnelly LA, Morris AD, Evans JM, collaboration DM. Adherence to insulin and its association with glycaemic control in patients with type 2 diabetes. QJM 2007;100:345-50 89. Egede LE, Gebregziabher M, Dismuke CE, et al. Medication nonadherence in diabetes: longitudinal effects on costs and potential cost savings from improvement. Diabetes Care 2012;35:2533-9 90. Grant R, Adams AS, Trinacty CM, et al. Relationship between patient medication adherence and subsequent clinical inertia in type 2 diabetes glycemic management. Diabetes Care 2007;30:807-12 91. Kalsekar I, Sheehan C, Peak A. Utilization patterns and medication adherence in patients with type 2 diabetes: Variations based on type of pharmacy (chain vs independent). Res Social Adm Pharm 2007;3:378-91 92. Kleinman NL, Schaneman JL, Lynch WD. The association of insulin medication possession ratio, use of insulin glargine, and health benefit costs in employees and spouses with type 2 diabetes. J Occup Environ Med 2008;50:1386-93 93. Krass I, Hebing R, Mitchell B, et al. Diabetes management in an Australian primary care population. J Clin Pharm Ther 2011;36:664-72 94. Kreyenbuhl J, Dixon LB, McCarthy JF, et al. Does adherence to medications for type 2 diabetes differ between individuals with vs without schizophrenia? Schizophr Bull 2010;36:428-35 95. Neugaard BI, Priest JL, Burch SP, et al. Quality of care for veterans with chronic diseases: Performance on quality indicators, medication use and adherence, and health care utilization. Popul Health Manag 2011;14:99-106 96. Piette JD, Heisler M, Ganoczy D, et al. Differential medication adherence among patients with schizophrenia and comorbid diabetes and hypertension. Psychiatr Serv 2007;58:207-12 97. Greco P, La Greca A, Ireland S, et al. Assessing adherence in IDDM: a comparison of two methods. Diabetes 1990;39:108A 98. La Greca AM, Swales T, Klemp S, Madigan S. Self care behaviors among adolescents with diabetes. 9th Annual Sessions of the Society of Behavioral Medicine. Baltimore, MD, 1988:A42. 99. Toobert DJ, Glasgow RE. Assessing diabetes self-management: the summary of diabetes self-care activities questionnaire. In: Bradley C, ed. Handbook of Psychology and Diabetes. Chur, Switzerland: Harwood Academic, 1994:351-75 100. Harris MA, Wysocki T, Sadler M, et al. Validation of a structured interview for the assessment of diabetes self-management. Diabetes Care 2000;23:1301-4 101. Wysocki T, Harris M, Buckloh L, et al. Randomized trial of behavioral family systems therapy for adolescents with diabetes: effects on diabetes outcomes. Diabetes Care 2004;53:441-6 102. Wysocki T, Harris MA, Wilkinson K, et al. Self-management competence as a predictor of outcomes of intensive therapy or usual care in youth with type 1 diabetes. Diabetes Care 2003;26:2043-7 103. Aikens JE, Piette JD. Longitudinal association between medication adherence and glycaemic control in Type 2 diabetes. Diabetic medicine : a journal of the British Diabetic Association 2013;30:338-44 104. Garber MC, Nau DP, Erickson SR, et al. The concordance of self-report with other measures of medication adherence: a summary of the literature. Medical care 2004;42:649-52


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