Patients' Medication-Related Experience of Care Is Associated with Adherence to Cardiometabolic Disease Therapy in Real-World Clinical Practice

Abstract

Adherence to cardiometabolic disease (CMD) medications is typically suboptimal. This study sought to evaluate the relationship between patients' medication-related experiences of care and adherence to CMD therapy. This study was conducted using electronic health records and administrative data from an ambulatory care setting. It included adult managed care beneficiaries with a prescription for CMD medications (antihyperlipidemic, antihypertensive, or antihyperglycemic agents) between 2010 and 2014, written ±14 days of an office encounter linked to a completed patient experience survey. Outcomes were primary and overall adherence. Primary adherence was defined as ever filling a CMD medication and overall adherence as ≥80% days covered over 365 days among those with an initial fill. Survey items (“inclusion in treatment decisions” and “information about medications”) are measured on a scale from 1 (very poor) to 5 (very good). Logistic regression was used to assess associations between ratings on each item (5 vs. <5) and primary or overall adherence. Eligibility criteria were met by 7368 patients; 5865 had ≥1 fill. After adjusting for confounders, better patient experiences with “inclusion in treatment decisions” (adjusted odds ratio [OR]:1.16; P = 0.049) and “information about medications” (OR:1.22; P = 0.009) were associated with greater odds of overall adherence to therapy. No significant associations were found between patient experience and primary adherence. Better patient medication-related experience of care is associated with improved adherence to CMD therapy. Efforts to include patients in treatment decision making and to provide better education on medications are simple, modifiable solutions to improve adherence and resultant outcomes of CMD treatment.

Introduction

Medications used to reduce cardiometabolic disease (CMD) risk, including antihyperlipidemic, antihypertensive, and antihyperglycemic agents, are among the most commonly prescribed drugs in the United States.¹ However, adherence to these medications is typically suboptimal. In individuals with dyslipidemia, 50% discontinue statin therapy within a year of treatment initiation^2,3 and for those who remain on therapy, adherence declines over time.^3,4 Among individuals with hypertension, up to 56% report nonadherence to treatment.^5,6 Adherence to oral diabetes medications varies widely based on the type of regimen (36% to 96%), with rates particularly low for twice-daily (52%) or polytherapy (36%) regimens.⁷ For these conditions, lower rates of adherence lead to poor disease control and an increased risk of disease-related hospitalizations and mortality.^8

–13 Overall, poor adherence to chronic disease medications costs the US health care system $100 to $289 billion per year.^14
–16

Multiple factors contribute to medication adherence, including sociodemographic, psychological, disease condition, and therapy-related attributes, such as cost and dosing frequency.¹⁷ Patients' experiences with their health care providers also can influence how they take medications. For conditions such as pain, inflammatory bowel disease, asthma, and cancer, a positive association has been demonstrated between adherence to medications and patients' ratings of experience of care, including patient–provider communication,^{18

–27} shared decision making,^20,22,28 and overall satisfaction.²⁹ Although several studies have evaluated the role of patients' rating of care experience and their adherence to CMD medications,^{19,20,26,27,29} few have used objective measures of adherence.^20,27 We are unaware of any studies that have examined patients' ratings of medication-related experience in relationship to primary versus overall adherence. Herein, primary adherence is defined as patients ever filling their prescribed medications and overall adherence as patients filling medications as directed.

This study aimed to investigate the relationship between patients' medication-related experiences of care with their health care provider and objective measures of primary and overall adherence to CMD therapy among adult managed care beneficiaries in real-world clinical practice.

Methods

Study design and setting

This retrospective, observational cohort study was conducted using electronic health records (EHRs), pharmacy claims, and patient-reported experience of care survey data from a multispecialty ambulatory health care delivery system in northern California. The system serves approximately 1 million patients annually and contracts with the majority of health plans in the region, including commercial payers, Medicare, and Medicaid. The system does not have a single, fixed drug formulary and, thus, health care providers can prescribe mostly as they choose, restricted only by patients' prescription drug plans or preferences. In terms of payer mix and drug prescribing, the organization operates like the majority of health care systems and independent physician practices in the United States. This study was approved by the organization's Institutional Review Board and was conducted in accordance with Health Insurance Portability and Accountability Act standards.

Patient eligibility criteria

We included managed care beneficiaries at least 18 years of age on the date of a prescription for a CMD medication (antihyperglycemic, antihyperlipidemic, and antihypertensive agents) between January 1, 2010, and December 31, 2014. We focused the analysis on the managed care population within the health system because of the availability of comprehensive pharmacy claims for these patients. Pharmacy claims data are received by Sutter Health from the individual health plans. Generic Product Identifier codes were used to classify each drug product within a given class. Oral drug products across therapeutic classes of interest were included in the analysis, as well as antihyperglycemic, non-insulin injectable agents. Insulin was excluded from this study because its dosing is not fixed and, therefore, calculations of adherence would not be reliable. Within each class, we chose the first medication prescribed to a patient within 14 days of an office encounter linked to a completed patient experience survey as will be described. The first medication prescribed during the study period was defined as the “index medication,” the medication start date as the “index date,” and the 365-day period from the index date as the “medication window.”

Within each therapeutic class, patients contributed 1 medication to the analysis but were permitted to have multiple drugs across classes. Thus, patients may have up to 3 observations. Patients were required to have EHR activity in the 12 months prior to the index date to collect sufficient medication and disease history and EHR activity up to 12 months after the medication window to confirm continuity of care in the health system.

Outcome measures

Main outcomes of interest were primary and overall adherence. Both prescribing data and pharmacy data were used to assess adherence. Primary adherence was defined as evidence of ever filling a prescribed CMD medication (operationalized as a pharmacy claim on or after the index date through the expected end date of the prescription).³⁰ Of those who fill an initial prescription, overall adherence was defined as filling a CMD medication as directed (operationalized as the proportion of days covered [PDC]). PDC was calculated as the sum of days' supply of pharmacy claims identified during the 365-day medication window and the traditional cut point of PDC ≥80% was used to characterize adherence.³⁰ This definition is consistent with that endorsed by the National Quality Forum (NQF), and used by the Centers for Medicare & Medicaid Services (CMS) and other insurance payers for performance-based reimbursment.^31
–33 Within the medication window, we measured nonoverlapping days' supply for drugs within each class, allowing for switching between drugs after the index medication.

Main predictor variables

Main predictors of interest were patients' ratings of medication-related experience of care items from the Press-Ganey Medical Practice survey. Survey items of interest asked patients to rate services received during their visit for a “care provider's effort to include you in decisions about your treatment” and “information the care provider gave you about medications (if any).” Responses are scored on a 5-point scale: 1 = very poor, 2 = poor, 3 = fair, 4 = good, and 5 = very good. For these analyses, we dichotomized responses to survey items as 5 versus <5, as the distribution of responses is typically left skewed (a majority choosing very good).

The survey was conducted by an independent organization, Press-Ganey (www.pressganey.com). Surveys were mailed to patients after randomly selected clinic visits, with no more than 1 survey sent to a patient within 90 days. The organization sought 30 responses per physician per 6-month period, or roughly 5 per month. The survey references, and is therefore linked, to a specific office encounter. The response rate for this voluntary survey is approximately 20%. There is evidence of response bias such that older and non-Hispanic white (NHW) individuals are more likely to respond to the survey (data not shown). For research purposes, survey responses were joined to patients' medical records at the encounter level and all data were analyzed in a de-identified manner.

Covariates

We extracted information from the EHR on patient demographics, including age as of the index date, gender, race, ethnicity, and English proficiency. The health care system collects self-reported race, ethnicity, and preferred language during routine clinical encounters. We categorized patients as English proficient if their primary spoken language was documented as English. Race/ethnicity was categorized as NHW, black/African American, Asian, Hispanic, and other or unknown. Information was extracted on encounter and problem list diagnoses in the 12 months prior to the index date to calculate a measure of disease burden – the Charlson Comorbidity Index score.³⁴ We classified the index medication as belonging to one of 3 CMD classes (antihypertensive, antihyperglycemic, and antihyperlipidemic) and as incident if there was no evidence of a prescription for a medication within the therapeutic class in the prior 12 months. Prescription co-payments were quantified for patients with at least 1 pharmacy claim for the index medication. Information was extracted on the number of office visits that the patient had with the prescribing provider in the previous 24 months and the count of active medications as of the index date. US Census data were used to determine the median household income of the Census block in which the patient resides as a proxy for socioeconomic status. Information also was collected on the prescribing provider of the index medication, including gender, department (primary care, specialty, or unknown), and years of experience, defined as number of years since medical school graduation. An indicator of patient–provider race/ethnic concordance was also included.

Statistical methods

Descriptive statistics were used to summarize patient, prescription, and provider characteristics and the proportion of prescriptions for which patients had primary or overall adherence. Logistic regression was used to examine bivariate and multivariable associations between the outcome (primary or overall adherence) and the main predictor (ratings of each satisfaction item; ≤4 vs. 5). Multivariable models included fixed effects for patient, prescription, and provider covariates (Table 1) and random patient effects to account for multiple observations (ie, multiple prescriptions per patient across therapeutic classes). We examined potential multicollinearity between covariates and considered excluding a variable when it was highly correlated with another variable; we found no evidence of multicollinearity among covariates (data not shown).

Table 1.

Patient Demographics and Characteristics

Variables	All patients (N = 7368) N (%)	Patients with ≥1 pharmacy fill (N = 5865) N (%)
Patient Gender (Woman)	4064 (55.2)	3245 (55.3)
Patient Age, years
<40	181 (2.5)	102 (1.7)
40–65	2981 (40.5)	2157 (36.8)
>65	4206 (57.1)	3606 (61.5)
Patient Race/Ethnicity
Asian	985 (13.4)	722 (12.3)
Black/African American	132 (1.8)	105 (1.8)
Hispanic	587 (8.0)	451 (7.7)
Non-Hispanic White	4723 (64.1)	3866 (65.9)
Unknown	941 (0.13)	721 (0.1)
Race/Ethnic Concordance
Yes	3365 (45.7)	2727 (46.5)
No	3240 (44)	2547 (43.4)
Unknown	763 (10.4)	591 (10.1)
English Proficiency
Yes	6897 (93.6)	5517 (94.1)
No	302 (4.1)	224 (3.8)
Not reported	169 (2.3)	124 (2.1)
Charlson Comorbidity Index Score
0	3454 (46.9)	2671 (45.5)
1	1730 (23.5)	1369 (23.3)
≥2	2184 (29.6)	1825 (31.1)
Provider Visit Count
0	1649 (22.4)	1301 (22.2)
1–3	3122 (42.4)	2438 (41.6)
>3	2597 (35.3)	2126 (36.3)
Incident Drug	1682 (22.8)	1334 (22.8)
Visit Department
Primary care	3468 (47.1)	2686 (45.8)
Specialty	2882 (39.1)	2366 (40.3)
Other	1004 (13.8)	813 (13.9)
Concurrent Medication, Count
0	1530 (20.8)	1164 (19.9)
1–5	5274 (71.6)	4250 (72.5)
6+	564 (7.7)	451 (7.7)
Median Income
<$75,000	1567 (21.3)	1209 (20.6)
$75,000–$135,000	3602 (48.9)	2832 (48.3)
>$135,000	1768 (24)	1491 (25.4)
Unknown	431 (5.9)	333 (5.7)
Provider Gender (Woman)	3903 (53.0)	3072 (52.4)
Provider Experience (Years)
≤10 (ref)	881 (12.0)	674 (11.5)
11–30	4557 (61.9)	3614 (61.6)
>31	896 (12.2)	743 (12.7)
Unknown	1034 (14.0)	834 (14.2)
Cardiometabolic Drug Class^*
Antihyperglycemic	1043 (10.8)	827 (10.6)
Antihyperlipidemic	3244 (33.7)	2652 (34.1)
Antihypertensive	5350 (55.5)	4304 (55.3)
Co-pay for Fill of Index Medication^*
<$6	–	2092 (26.9)
$6–$15.99	–	3463 (44.5)
≥$16	–	2067 (26.6)
Unknown	–	161 (2.1)

Prescription level.

Unadjusted and adjusted odds ratios with 95% confidence intervals were generated for fixed-effect covariates after simple and multiple regression, respectively. P < 0.05 was considered statistically significant. All analyses were conducted using SAS 9.3 (SAS Institute, Inc., Cary, NC).

Results

A total of 25,298 adult patients were identified who had a CMD medication prescribed within 14 days of the encounter linked to a completed experience of care survey between 2010 and 2014; 24,289 (96%) had sufficient EHR history and follow-up. Of these, 7368 patients (30%) with 9637 prescriptions were managed care beneficiaries meeting all study eligibility criteria; 5865 patients had an initial pharmacy fill.

The majority of patients were older than 65 years of age, NHW, women, and had at least 1 prior encounter with the health care provider who prescribed the index medication (Table 1). Additional patient demographics and characteristics are displayed in Table 1, as are provider demographics. Relative frequency distributions of prescriptions by therapeutic classes are shown in the Supplementary Data (Supplementary Data are available online at www.liebertpub.com/pop).

The rate of primary adherence was 79.1% and, among those with an initial fill, the rate of overall adherence was 58.4%. No associations were found between patients' ratings on “inclusion in treatment decisions” or “information about medications” and primary adherence to CMD therapy (Table 2). However, patients with better ratings of “inclusion in treatment decisions” and “information about medications” had 16% and 22% significantly greater odds of overall adherence to CMD therapy, respectively (P < 0.05, for each).

Table 2.

Relationship Between Adherence and Patient-Reported Ratings of Medication-Related Experience of Care Survey Items

	Primary adherence (N = 7368)		Overall adherence (N = 5865)
Survey item	Unadjusted OR (95% CI)	Adjusted OR (95% CI)	Unadjusted OR (95% CI)	Adjusted OR (95% CI)
Inclusion in treatment decisions	1.06 (0.94, 1.19)	1.16 (0.65, 2.05)	1.12 (1.00, 1.26)	1.16 (1.00, 1.25)
	P = 0.37	P = 0.61	P = 0.047	P = 0.049
Information about medications	1.06 (0.94, 1.20)	1.26 (0.71, 2.27)	1.16 (1.04, 1.31)	1.22 (1.05, 1.42)
	P = 0.32	P = 0.43	P = 0.01	P = 0.009

CI, confidence interval; OR, odds ratio.

Discussion

In this retrospective, observational study of adult managed care beneficiaries with prescriptions for CMD medications in an ambulatory care setting, better patient-reported ratings of medication-related experiences with their health care providers were associated with improved overall, but not primary, adherence. Despite controlling for a large number of potential confounders, unadjusted and adjusted estimates were similar (Table 1).

Several studies have reported positive associations between ratings of patients' experiences of care, particularly for patient–provider communication and adherence to treatments for diabetes and hypertension.^{19,20,26,27,29} Some of these studies, however, were conducted using self-reported measures of medication adherence,^19,26,29 which may overestimate adherence rates.³⁵ Self-reported measures of adherence also may be problematic when measured concurrently with experience of care, making it difficult to assess a temporal relationship. Moreover, most prior studies typically have been conducted in select groups—African Americans, low-income adults, or older adults—which may limit generalizability to other populations.

We are aware of 2 studies on the relationship between patient-reported experiences of care and adherence that are similar to the present study in terms of using objective measures of medication adherence among patients from a health care delivery system.^20,27 In a study of 9377 adult managed care beneficiaries with diabetes from the Diabetes Study of Northern California (DISTANCE) survey of Kaiser Permanente in northern California, Ratanawongsa et al found that higher ratings of “providers' involving patients in treatment decisions” and “understanding patients' problems with treatment” were associated with improved adherence to antihypertensive, antihyperlipidemic, and antihyperglycemic medications.²⁰ In another study of 2109 patients with diabetes from the Geisinger Health System in central and northern Pennsylvania, Shoenthaler et al found that patients' perceived satisfaction with their physicians' “ability to educate the patient during the medical encounter” was associated with better adherence to antihyperglycemic medications.²⁷

Overall, the present study findings further support the association between patients' positive medication-related experiences with their health care providers and improved adherence to medications to reduce CMD risk. A unique contribution of this study is the evaluation of the relationship between patients' ratings of medication-related experiences and primary adherence—that is, ever filling a prescribed medication. Primary adherence has received much attention in recent years, given studies reporting that 20% to 30% of patients do not ever fill their prescribed chronic disease medications.³⁶ This study's primary adherence rate of 79% is consistent with previous findings. That patients' ratings of medication-related experiences of care were associated with overall, but not primary, adherence, suggests that patients do not necessarily abandon their prescriptions if they have a less than optimal medication-related experience with their prescribing provider, but they may not actually consume or persist with treatment.

Health system interventions are warranted to ensure that patients are more involved in treatment decision making and that they receive comprehensive information about the medications they are prescribed, including reasons for taking these medications and potential side effects. Shared decision making between patients and providers is associated with better outcomes and, in recent years, has taken a prominent role in developing health care policy.^37,38 Shared decision making is endorsed by the American Diabetes Association, the American College of Cardiology, and American Heart Association in selecting appropriate medications and/or setting treatment goals to reduce cardiometabolic and cardiovascular disease risk.^39,40 However, it is unknown to what extent providers and patients engage in shared decision making in clinical practice.

There are several limitations to consider when interpreting the study findings. The retrospective, observational study design limits causal inferences. Because this study was restricted to a sample of patients who received and ultimately responded to the patient experience survey, it was limited to a relative small group of patients who were prevalent users of CMD medications. Ideally, we would have evaluated incident users of these medications, as we predict associations between patients' medication-related experiences and adherence would be stronger. Nevertheless, we observed a relationship between experiences of care and adherence among a cohort of patients who were largely prevalent users. Health plan pharmacy claims were used as a measure of medication adherence, but it is unknown if patients actually consumed medications. Pharmacy claims data may underestimate adherence for patients who for pay for prescriptions in cash (ie, without insurance) or those who received drug samples at the time the prescription was written. Although it is unknown from this study if clinical outcomes improved because of better adherence, there is a body of literature describing the relationship between CMD medication adherence and clinical outcomes.^8

–12 Lastly, the study population was from an ambulatory care setting in northern California. Although it is unknown if these findings are generalizable to other regions in the United States, the study setting is similar to many other health care delivery systems and independent physician practices in terms of provider reimbursement and formulary structure.

Despite limitations, this study has several strengths. Comprehensive patient, prescription, and provider data from the EHR were used and this information was linked to administrative pharmacy claims and patient-reported survey data to construct a cohort of patients within a large health care delivery system. The study's health care system collects patient experience survey data as a part of routine clinical care. Thus, results from this study may be more representative of patients in real-world clinical practice as opposed to those recruited for research and who self-report adherence. Furthermore, relatively strict criteria (±14 days) were used for the temporal relationship between the date the medication of interest was prescribed and the office encounter to which the survey was linked. This was important to mitigate issues related to recall bias and issues of other time-dependent factors that may influence patient ratings between the date of the prescription and when the survey was completed. An advantage of this study is that it was able to leverage both prescribing data and pharmacy claims data to measure both primary and overall adherence. Studies using only pharmacy claims may overestimate adherence in the absence of a prescription start date. Lastly, the measure of overall adherence is consistent with that endorsed by the NQF, and used by CMS and other insurance payers for performance-based reimbursement contracts.^31
–33

In summary, efforts to optimize patients' medication-related experiences with their health care provider, especially involving them in treatment decision making and better educating them on the need for medications and potential side effects, are simple, modifiable solutions to improve adherence and resultant outcomes of CMD treatment.

Footnotes

Author Disclosure Statement

The authors declare that there are no conflicts of interest. The Palo Alto Medical Foundation Research Institute of Sutter Health received research funding to conduct this study from Janssen Scientific Affairs.

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