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FACTORS AFFECTING COMPLIANCE WITH MEDICATION REGIMES

Patient-Related Factors

With regard to patient-related factors, demographics such as age, gender, race, intelligence, level of education, marital status, and social status generally have not been found to relate to medication compliance (APhA, 2003). However, in the review by the APhA, the following demographic variables have been found to correlate with compliance: limited access to health care, financial problems, communication barriers, and lack of social support. While it may be surprising that older age has not been associated with poorer compliance, compliance-related problems associated with older people are attributed to characteristics of the medication regime as opposed to age (e.g., older people take more medications and are more susceptible to adverse drug events).

Compliance with medications is also low when patients are in denial regarding the nature/severity of their condition; when medications are prescribed for preventative reasons for conditions that are symptomless; when patients feel no benefit for taking the medication; when patients do not believe that the medication will affect their condition; when there are no immediate consequences for not taking the medication; and when patients feel that the short-term disadvantages to the medication (such as side effects) outweigh the long-term benefits (APhA, 2003). As pointed out by Treharne, Lons, and Kitas (2004), it appears that perceptions are stronger predictors of adherence that demographic factors, in the group of patient-related factors.

In a study by Kaplan et al. (2004) study, unmarried status, feelings of sadness or depression for more than two weeks of the prior year, lack of insurance, and children in the household were independently associated with poorer compliance with lipid-lowering medication. Their subjects consisted of 510 patients treated in the cardiology practices of three hospitals located in the Bronx, NY. The mean age was 64.4, and ranged from 33 to 94. Hispanics (37%), Black (33%), and White non-Hispanic individuals (25%) comprised the sample. Educational attainment and household income were low, with 47 percent holding less than a high school diploma, and 78 percent reporting an annual household income of less than $20,000. More than 60 percent of subjects were covered solely by public health insurance, with 11 percent having no insurance. Approximately half had monthly out-of-pocket expenses for prescription medications, and 25 percent reported difficulty paying for medications.

In a study of 496 patients treated for hypertension, the majority of whom were 65 or older, Wang et al. (2002) found that only 29 percent of the sample had enough medication to cover at least 80 percent of the days during the 1-year study period (based on prescription refill records). Thirty-five percent of the sample had enough medication to cover between 50 and 79 percent of the days in the study period, and 36 percent had less than 50 percent of the days in the study period covered. After controlling for the potential confounding effects of demographic variables (age, gender, race, education, and employment status), use of thiazide diuretics, the presence of comorbid conditions (coronary artery disease, cerebrovascular disease, and renal failure), and locus of control, Wang et al. (2002) found that an increase in depressive symptom severity was significantly associated with a lower odds of compliance. There was no association between compliance and knowledge of hypertension, health beliefs and behaviors, social supports, or satisfaction with care. There was a trend toward compliance for patients perceiving that their health is controlled by external factors.

Dunbar-Jacob et al. (2003) analyzed sociodemographic factors to identify predictors of medication compliance for the three measures of compliance. With regard to the percentage of prescribed doses taken, only race (White versus Black) was significant. Black subjects were more likely to be compliant than White subjects (98% versus 88% adherence, respectively). With regard to the percentage of days with correct dosing, only total household income predicted adherence. Adherence increased with increases in income, from 68 percent for those with incomes less than $20,000, to 87 percent for those with incomes between $20,000 and $29,999, to 86 percent for those with incomes over $30,000. With regard to the percentage of expected doses with correct timing, only income and number in household were significant. Subjects with lower incomes were less likely to be compliant to correct dose timing. As the number of people living in the household increased, adherence to correct timing decreased. Subjects living alone had an average adherence rate of 70 percent. Those living with one other person had an average adherence rate of 62 percent. Individuals living with at least two other people had an average adherence rate of 59 percent. Neither age, gender, marital status, education, employment status, nor insurance coverage significantly predicted medication compliance in the Dunbar-Jacob et al. (2003) study.

 

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