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A BSTRACTS
B49
Prevalence and Correlates of Self-Reported Medication Non-
Adherence among Older Adults with Diabetes Mellitus, Coronary
Heart Disease, and/or Hypertension.
Z. A. Marcum, 1 Y. Zheng, 1 S. Perera, 1 E. Strotmeyer, 1 A. Newman, 1
E. Simonsick, 2 R. Shorr, 3 D. C. Bauer, 4 J. M. Donohue, 1 J. T. Hanlon. 1
1. University of Pittsburgh, Pittsburgh, PA; 2. NIA Intramural
Research Program, Baltimore, MD; 3. VA GRECC, Gainesville, FL; 4.
UCSF, San Francisco, CA.
Supported By: Supported in part by National Institute on Aging
grants and contracts (R56AG 0207017, P30AG024827, T32 AG021885,
K07AG033174, R01AG034056, 3U01 AG012553, N01-AG-6-2101,
N01-AG-6-2103, and N01-AG-6-2106), a National Institute of Mental
Health grant (R34 MH082682), a National Institute of Nursing
Research grant (R01 NR010135), Agency for Healthcare Research
and Quality grants (R01 HS017695, K12 HS019461, R01HS018721),
and a VA Health Services Research grant (IIR-06-062). This research
was also supported in part by the Intramural Research program of the
NIH, National Institute on Aging.
Background: Medication non-adherence is common among
older adults with chronic co-morbidity, but the underlying factors are
largely unexplored. This study examines the prevalence and correlates
of self-reported medication non-adherence among communitydwelling
older adults with chronic cardiovascular conditions (i.e., diabetes
mellitus [DM], coronary heart disease [CHD], and/or
hypertension [HTN]).
Methods: The study sample (mean [SD] age 82.1 [2.8], 52.5% female,
37.0% black) included 897 members from the Health Aging
and Body Composition cohort (n=3075) with any DM (n=338;
37.7%), CHD (n=381; 42.5%), or HTN (684; 76.3%) at year 10. Selfreported
medication non-adherence was measured by the 4-item
Morisky Medication Adherence Scale (MMAS) and 2-item Cost-Related
Non-Adherence scale (CRN) at year 11; these scales separately
assess different reasons for medication non-adherence. We used multivariable
logistic regression models with backward selection to identify
correlates (i.e., demographic, health status, and access to care factors)
of non-adherence for each measure.
Results: Non-adherence by MMAS and CRN was reported by
40.7% and 7.7%, respectively. Non-adherence by MMAS was associated
with black race (adjusted odds ratio=AOR=1.85, 95% interval=1.25-2.74)
and hospitalization in the previous 6 months
(AOR=1.97, 95% interval=1.22-3.17). Non-adherence by CRN was
associated with marital status (married vs. unmarried; AOR=0.47,
95% interval=0.23-0.98) and money-related delay in medical care
(AOR=6.94, 95% interval=2.41-19.97). Age, gender, and the total
number of regularly scheduled medications were not associated with
non-adherence by either MMAS or CRN.
Conclusions: Self-reported medication non-adherence is common
in older adults with chronic cardiovascular conditions, and nonadherence
measured by CRN is less prevalent than MMAS. No correlates
for non-adherence were detected consistently across both
measures. Future studies should evaluate targeted interventions
based on patient-specific modifiable barriers to improve medication
adherence.
B50
Health Care Proxy Involvement and Satisfaction in Decision-
Making for the Treatment of Infections in Nursing Home Residents
with Advanced Dementia.
C. K. Ankuda, 1 J. L. Givens, 2,3 S. L. Mitchell. 2,3 1. University of
Vermont College of Medicine, Burlington, VT; 2. Division of
Gerontology, Beth Israel Deaconess Medical Center, Boston, MA; 3.
Hebrew SeniorLife Institute for Aging Research, Boston, MA.
Supported By: National Institutes of Health (NIH)
Background: Infections are common in advanced dementia, and
health care proxies (HCPs) are often called upon to make treatment
decisions. This study describes the awareness, involvement, and satisfaction
of HCPs in decision making regarding infectious episodes for
a cohort of nursing home (NH) residents with advanced dementia.
Methods: From 2010-2011, data were prospectively collected
from 135 NH residents with advanced dementia and their HCPs at 22
Boston area facilities. For each infectious episode, information was
obtained on whether the HCP: 1. could be contacted by study staff; 2.
was aware of the infection; and 3. was involved in decision making.
Multivariable logistic regression was used to determine resident,
HCP and episode characteristics associated with HCP awareness of
the infectious episode.
Results: Residents experienced 287 infectious episodes (82 respiratory,
114 urinary tract infection, 37 skin and 53 fever). HCPs were
able to be contacted by study staff for 217/287 episodes. Once contacted,
HCPs were aware of 94/217 (43%) of episodes, and of these,
were involved in decision-making for 57/94 (61%). HCP awareness of
the episode was associated with the HCP being the child of the resident
(vs. other relationship) [adjusted odds ratio (AOR) 2.34, 95% CI
1.19 – 4.59], female (AOR 2.79, 1.37-5.66), and the episode being
treated with antibiotics (AOR 3.68, 1.56-8.66).
Conclusions: The majority of infectious episodes in NH residents
with advanced dementia do not involve HCPs in decision-making.
Awareness of infections among HCPs is more likely for episodes
treated with antibiotics, and when the HCP is the resident’s child and
is female. These factors may help target infectious episodes that require
greater attention with respect to better informing HCPs of their
loved one’s health status.
B51
Can a patient navigator get older patients and their oncologists on
the same page?
E. Vig, 1,2 C. Clark, 2 R. Engelberg. 2 1. Geriatrics, VAPSHCS, Seattle,
WA; 2. Medicine, University of Washington, Seattle, WA.
Supported By: American Cancer Society
Background Older patients may approach cancer management
decisions differently than younger patients. Although older patients
may be more concerned about quality of life than cure, oncologists do
not routinely elicit patients’ quality of life concerns. As a result, older
patients and their oncologist may not be on the same page during office
visits.
We undertook a two phase pilot study to test whether a patient
navigator intervention could facilitate shared decision-making between
older patients with cancer and their oncologists.
Methods In the study’s first phase, we interviewed oncologists,
older cancer patients, and their family members about their decisionmaking,
and whether/how a patient navigator might help. Interviews
were recorded, transcribed, and analyzed using grounded theory
methods.
In the second phase, the patient navigator met with an older patient
prior to an oncology appointment to identify his/her quality of
life and other concerns. The navigator then accompanied the patient
to the oncology appointment and debriefed afterwards. Several days
later, an investigator debriefed separately with the oncologist and the
patient/family. Content analysis and descriptive statistics were used to
analyze study data.
Results In the first phase, we recruited 9 oncologists from 2 clinics,
12 of their patients, and 3 of their family members. Oncologists
and patients thought navigators could be helpful by clarifying understanding,
taking notes, and helping patients ask questions.
In the second phase, the 9 oncologists identified 9 additional patients.
Prior to the navigated visits, patients identified their main concerns
(mean 3 concerns, range 1-5). During the visits, the navigator reminded
the patient of concerns in 4 visits, facilitated discussion about
referral to a pain specialist in 1 visit, clarified referral to a cardiologist
in 1 visit, and clarified the follow up plan with the oncologist in 2 visits.
Patients described the navigator as helpful, reported that all their
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AGS 2012 ANNUAL MEETING