Medication Adherence in Elders Essay
Medical adherence has been defined by Osterberg amp. Blaschke, (2005) as the extent to which patients take medications as prescribed by their health care providers. It has been reported as a crucial factor determining the health and well being of elderly population by the World Health Organization (Chung et al., 2008). The issue has been reported to have high prevalence varying from 8-71%, 13-93% during various studies. It has been estimated to result in huge economic burden as well as high mortality (Unni, 2008). Recent evidences indicate that only 50% of the prescribed doses are actually taken by individuals diagnosed with chronic diseases. Of these patients approximately 22% take medication in quantities lesser than the amount recommended, 12% do not fill their prescription and 12% buy the medication but forego them entirely. Though race, ethnicity and age have not been reported to be a risk factor for medication non-adherence, the issue is rendered critical among elderly patients due to the high vulnerability of this age group to chronic illnesses (Kocureck, 2009). In the light of above discussion the importance of research investigating the various aspects of the medication adherence in elderly population is highlighted. Medication Adherence in Elders Essay. The current research aims to examine the prevalence rates of medication adherence in elderly population. Literature Review High prevalence and large economic burden of medical non adherence has led to extensive studies and investigations enabling an understanding of the issue and devising adherence strategies. However despite the prolific research conducted during the last three decades an optimal strategy is lacking and hence the prevalence rates for non adherence are still on a rise. An estimated 100 billion dollar remains the annual cost of dealing with complications such as hospitalization, disability, disease aggravation mortality etc resulting as a consequence of non adherence (Wertheimer amp. Santella, 2003). On the basis of causes of non-adherence two types of medication non-adherence have been identified: intentional and unintentional. While the latter has been attributed to forgetfulness or incidental causes. the former is usually reported in patients who have been taking medications but discontinue upon feeling better or worse. However later research has shown that patient’s belief is an important contributor to forgetfulness in taking medication rendering ‘forgetting to take medication’ not a purely unintentional type of non-adherence (Unni, 2008). The major obstacles to medication resulting in non-adherence include forgetfulness, different priorities, deliberate omission of doses, information deficit and certain psychological factors. While the aforementioned factors are at least partially under the control of patients, certain factors such as cost, patient lifestyle inconsistent with medication timing and complex medication regime are important contributing factors attributed to the health care provider (Osterberg amp. Blaschke, 2005). Six patterns of medication adherence have been identified in patients with chronic diseases. First group adheres to the prescribed doses and timings fully, second is characterized by delays but with complete doses, third miss a single doses occasionally and also are inconsistent with
We searched multiple electronic databases for studies reporting reasons for non‐adherence to medication regimens in patients aged 75 years and over. Our results were not limited to specific diseases, health‐care settings, or geographical locations. The quality of eligible studies was assessed using the Newcastle‐Ottawa Scale. A narrative synthesis of findings was performed.
A total of 25 publications were included, all of which were in community settings. Frequent medication review and knowledge regarding the purpose of the medication were positively associated with adherence. Factors associated with poor adherence were multimorbidity, cognitive impairment, complex regimens with multiple prescribing physicians, and problems with drug storage or formulation.
These findings suggest that interventions to improve adherence could focus on medication review aimed at simplifying regimens and educating patients about their treatment. Groups with poor adherence that may benefit most from such a model include patients with multiple comorbidities and cognitive impairment.Medication Adherence in Elders Essay.
Multiple factors at the drug, patient, provider, and institutional levels may explain non‐adherence in the specific population of older people, including: (a) increased vulnerability to drug‐related problems through pharmacodynamic and pharmacokinetic changes9; (b) high prevalence of comorbidity with subsequent polypharmacy and functional impairment10-12; (c) elevated risk of drug interactions with increasing medication burden13, 14; and (d) high rates of service use across settings, leading to multiple providers and regimen complexity.15These problems rarely occur in isolation and can be both the cause and effect of non‐adherence, leading to a cycle of escalating adversity. Despite this, studies that explicitly consider this older population appear to be under‐represented, and those that do tend to focus on a single disease. We set out to quantify the factors potentially associated with adherence by undertaking a systematic review of studies addressing these issues specifically in persons aged ≥75 years, enabling synthesis of results across different diseases and health‐care settings. Medication Adherence in Elders Essay.
We used the following search terms in PubMed, adapting them for EMBASE and Web of Science: (Complia*/Non‐complia*) (Adher*/Non‐adher*) (Concordan*/Non‐concordan*) (Elder*/Old*/Geriatr*/Aged/Senior). References for included articles and relevant literature reviews were also hand‐searched for additional relevant publications. The search was completed in November 2017.
After screening title and abstract, the full text was reviewed. The majority of screening was carried out by A.S., with a sample independently carried out by a second reviewer (R.R.) and cross‐checked to ensure validity and reproducibility. Any uncertainty was resolved following discussion with a third reviewer (D.D.). Screening and full‐text review was undertaken using Covidence.16
We used the following inclusion criteria:
We applied the following exclusion criteria: non‐English publications; articles that had not undergone full peer review, such as conference abstracts/posters; publications relating solely to the cost of medicines or cost analysis; and studies published prior to 2000 due to evolutions in prescribing practice over the last two decades. Medication Adherence in Elders Essay.
Data were extracted and entered into a custom template made by the first author. Data were extracted twice by two independent reviewers (A.S. and M.W.C.). Any inconsistencies were resolved by a third reviewer (D.D.). Extracted data included basic information about the study (timing, design, location/setting, sample size, and demographics of the participants), method of data collection, definition of adherence, and any measured associations (if any). Study quality was assessed by the same independent reviewers using the Newcastle‐Ottawa Scale17 rating: selection, comparability, and outcome (maximum score = 9 points).
Of the 6346 publications identified, 540 were eligible for full‐text review and 25 met the criteria for inclusion (Figure 1). The majority of those eligible for inclusion were observational studies (one randomized controlled trial, 11 cohort, and 13 cross‐sectional) based in Europe or North America. Participants were community dwelling (range n = 27 to n = 140 000), although some studies assessed specific groups within the community, such as those post‐hospitalization or memory clinic users (Table 118-42). Operational definitions of non‐adherence varied, even when the method of data collection was the same. Methods for ascertaining adherence included: (a) data collected from electronic monitoring systems; (b) information from medical records, such as prescription fill data and insurance claims; and (c) data from interviews or self‐report questionnaires. These differences were considered when drawing broader conclusions.
Citation | Study design | Sample | Setting | Data collection | Adherence assessments | Covariates | Summary findings | Quality | Comments |
---|---|---|---|---|---|---|---|---|---|
Barat et al 200118 | Cross‐sectional
Random sample from population register |
Patients aged 75 prescribed medication by GP
Size = 348 Mean age = 75 M:F = 43:57 |
Denmark
Patients living in own homes |
Structured interview with medical, cognitive and functional assessment | Drug score,
dose score and regimen score calculated Self‐report for missed doses |
Dementia*
Depression Sex Alcohol consumption Knowledge* Years of schooling Living alone Number of prescribing physicians* Number of drugs* Number of OTC drugs Use of compliance aids |
Positive association:
Not having dementia, Knowledge of purpose of treatment and consequences of omission, Living with spouse Negative association: Increasing number of prescribers, Increasing number of drugs |
Random sample from population register Structured interview with verification from GP record
N‐O score = 6 |
|
Borah et al 201019 | Cohort
All eligible members of health plan included |
All new initiators of Alzheimer’s disease medication
Size = 3091 Mean age = 80 M:F = 36:64 |
USA
Members of large health plan |
Baseline information from electronic health record
1‐year follow‐up of pharmacy fill data |
MPR calculated for dementia medication
Non‐adherent if MPR < 80% |
Charlson Comorbidity Index*
Age* Sex* Pill burden* |
Positive association:
Younger age Male sex Higher pill burden Negative association: Higher comorbidity score |
All eligible patients included from large register
Retrospective cohort therefore no dropouts N‐O score = 8 |
For every one under increase in pill burden, likelihood of adherence if increased by 19%. Did not control for caregiver support |
Bourcier et al 201720 | Cross‐sectional
All eligible patients within geographical area invited |
Patients aged > 75 with a GP prescription
Size = 1206 Mean age = 82 M:F = 35:65 |
France
Community pharmacy in Greater Paris |
Structured interview and access to pharmacy record | Girerd score
Poorly adherent if score ≥ 3 |
Age
Social isolation* Satisfaction with formulation* Use of generic name* Complete written regimen Need to split tablets Use of MCA |
Positive association:
Satisfaction with formulation Negative association: Social isolation Use of generic name |
Reports “adjusted odds ratios” but does not state which variables were controlled for
N‐O score = 3 |
|
Choudhry et al 200821 | Cohort
All eligible members from health plan included |
All patients discharged from hospital following first myocardial infarction
Size = 33 646 Mean age = 81 M:F = 25:75 |
USA
Members of large health plan |
Medicare PACE and PAAD records | PDC calculated | COPD*
Hospitalization in previous year Age Male* Ethnicity* Nursing home* Pill burden |
Positive association:
White race Nursing home resident Negative association: COPD Male sex |
Large retrospective cohort study Odds ratios adjusted for several important factors
N‐O score = 8 |
Many diseases were assessed; COPD was the only one to have a statistically significant association with adherence |
Cooper et al 200522 | Cross‐sectional
Participants of AdHOC study. Medication Adherence in Elders Essay. |
Participants invited from a “representative area” judged by national lead
Size = 3881 Mean age = 82 M:F = 25:75 |
Europe (11 countries) | Structured interview | Self‐reported adherence plus comparison with available prescriptions | Cognitive impairment*
Dementia diagnosis Psychiatric diagnosis Depression Impaired vision/hearing Age Sex Being unmarried* Alcohol screen positive* Abusive Socially inappropriate Resisting care* Wandering Living situation Living alone/in care Resident caregiver ADLs/iADLs Medications Number of medications No medication review in last 6 months* |
Positive association:
Cognitive impairment Being unmarried Medication review Negative association: Alcohol overuse Resisting care |
Each sample judged to be representative of that country
Participants derived from other study so perhaps represent motivated individuals N‐O score = 6 |
Cohort identified from participants of the AdHOC study |
Fallis et al 201323 | Cohort
Consecutive discharges from hospital |
All discharges who were prescribed a new medication
Size = 232 Mean age = 78 M:F = 49:51 |
Canada
Consecutive discharges from hospital followed into the community |
Review of electronic pharmacy record and discharge summary | Failure to fill prescription (non‐initiation) | Age
Sex Discharge to long‐term care* Number of medications Inclusion of primary care physician’s name on script |
Negative association:
Discharge to long‐term care |
Representative cohort
Data sourced from electronic health record N‐O score = 8 |
|
Foebel et al 201224 | Cross‐sectional
Patients assessed under RAI‐HC |
Patients with heart failure assessed for care needs
Size = 140 822 All aged >75 M:F not stated |
Canada
Community based |
Review of RAI‐HC validated against medical records | Medication use in past 7 days Deemed non‐adherent if use <100% | Caregiver stress level*
Caregiver residence* |
Negative association:
Stressed caregiver Caregiver does not live with client |
Very large sample size with multivariate regression
N‐O score = 6 |
Highest impact on adherence if caregiver is stressed and does not live with client |
Garcia‐Sempere et al 201725 | Cohort
Patients discharged from hospital |
Patients admitted with hip fracture and prescribed bone protection
Size = 4856 84% aged ≥ 75 M:F = 13:87 |
Spain
Cohort identified from hospital discharges followed into the community |
Review of electronic health record | PDC for bone protection medication at 1 year and 4 years | Comorbidity*
Emergency attendance History of stroke* History of diabetes Age* Sex* Sedatives* Polypharmacy |
Negative association:
Charlson score > 2 History of stroke Increasing age Male sex Sedatives |
Representative cohort of this population
4‐year follow‐up period Attrition rate not stated N‐O score = 7 |
Only considered adherence to bone protection. As age increased, risk of non‐adherence also increased. |
Hayes et al 200926 | Cross‐sectional
Retirement village residents given additional vitamin C tablet |
Recruited from 2 retirement villages
Size = 38 Mean age = 82 M:F = 32:68 |
USA
Community based All residents invited from the 2 villages |
Electronic pill box measurement for additional tablet | Dose count and timing of dose measured
Non‐adherent if < 80% |
Cognitive function* | Positive association:
Higher cognitive function |
Very small study
Only controlled for number of drugs N‐O score = 4 |
Effect of cognitive function persisted after adjustment for number of medications |
Jerant et al 201127 | Cohort
Pill count every 6 months |
Sample derived from Ginkgo biloba trial
Size = 771 Mean age = 78 M:F = 58:42 |
USA.
Community based |
Pill count | Non‐adherent if < 80% | Cognitive function*
Comorbidity BMI Self‐rated health* Age* Sex Ethnicity Income Personality trait* Smoking Years of schooling Social visits |
Positive association:
High self‐rated health Negative association: Cognitive impairment Age Neuroticism |
Median follow‐up 6.1 years Cohort predominantly well‐educated white males
N‐O score = 8 |
1 standard deviation in 3MSE score increases non‐adherence by 3%. 5‐year increment in age increased non‐adherence by 1.3%. |
Lee et al 201328 | Cohort
Interviews via social work outreach team |
Sample recruited via social workers
Size = 86 Mean age = 81 M:F = 37:63 |
Hong Kong
Community based |
Structured interview with MMAS score | Non‐adherent if MMAS score ≥ 2 | Comorbidity
Sex* Health‐related knowledge Adverse drug reaction Polypharmacy* Drug storage problems* |
Negative association:
Female sex Polypharmacy Accumulation of drugs Scattered storage Any storage problem |
Small sample of specific group
Does not control for other variables N‐O score = 6 |
Defined polypharmacy as ≥ 9 drugs |
Li et al 200829 | Cross‐sectional
Questionnaire given to sample of Mandarin speakers |
Convenience sample from Asian health clinic
Size = 144 Mean age = 75 M:F = 52:48 |
USA
Community based via Asian health clinic |
Self‐report questionnaire
With MMAS score |
Non‐adherent if ≤80% | Sex*
Perceived susceptibility to disease Belief about medicines Social support Length of time since immigration* |
Positive association:
Female sex Longer time since immigration |
Small sample of very specific group
Self‐report with no verification N‐O score = 4 |
Beliefs regarding Western and Chinese medicine were not significant |
Lindquist et al 201230 | Cross‐sectional
Interview following admission to hospital. Medication Adherence in Elders Essay. |
Recruited from acute admissions ward
Size = 254 Mean age = 79 M:F = 47:53 |
USA
Community following recruitment on acute admissions ward |
Interview | Comparison of self‐report with discharge summary | Cognitive impairment
Age Sex Health literacy* Marital status |
Poor health literacy increases risk of unintentional non‐adherence
Good health literacy increases risk of intentional non‐adherence |
Relies on self‐report during interview
N‐O score = 5 |
Mini‐Mental State Examination cutoff for cognitive impairment determined by level of education |
Mansur et al 200831 | Cohort
Follow‐up of discharges from hospital |
Recruited from acute geriatric ward
Size = 198 Mean age = 81 M:F = 38:62 |
Israel
Follow‐up acute geriatric admissions |
Telephone interview ± verification with GP | Self‐report | Contact with GP*
Polypharmacy* Medication regimen changes* |
Negative association:
No contact with GP Polypharmacy High number of regimen changes |
Verification of self‐report with GP
N‐O score = 8 |
Polypharmacy defined as ≥7 drug types |
Marcum et al 201332 | Cross‐sectional
Questionnaire with subset of large population cohort. |
Participants of Health, Ageing and Body Composition Study with HTN ± DM ± CHD
Size = 897 Mean age = 82 M:F = 47:53 |
USA
Community |
Self‐report questionnaire | MMAS‐4 and Cost‐Related Nonadherence‐2 | Comorbidity*
Physical function Falls* Sleep disturbance* Flu vaccination Hospitalization* Age Sex Race* Education/literacy Marital status |
Positive association:
3 of DM/CHD/HTN Cancer Negative association: 2 of DM/CHD/HTN Sleep disturbance Hospitalization in previous 6 months Black race |
Representative sample from large population cohort
Outcome assessed by self‐report N‐O score = 4 |
All patients had at least one of DM/CHD/HTN. With reference to 1 of 3,
2 of 3 worsened adherence and 3 of 3 improved adherence. |
Márquez‐Contreras et al 201633 | Cohort
Primary care patients |
Patients taking NOAC in primary care
Size = 370 Mean age = 75 M:F = 47:53 |
Spain
Patients recruited via primary care and specialized researchers |
Electronic pill counts and structured interviews | Compliance percentage from pill count
Adherent if ≥80% |
Comorbidity*
Bodyweight* Polypharmacy* |
Negative association:
Increasing number of current diseases Bodyweight Polypharmacy |
1‐year follow‐up period
N‐O score = 7 |
Definitions of current diseases, bodyweight and polypharmacy not given. |
Moisan et al 200234 | Cross‐sectional
Interviews with patients recruited via ambulatory care |
Cohort recruited via ambulatory care
Size = 325 Mean age = 78 M:F = 17:83 |
Canada
Community follow‐up of patients recruited via ambulatory care |
Interview with MMAS score | Non‐adherent if ≥1 “yes” on MMAS questionnaire. | Age
Sex Ability to read/understand script Belief* Perception of health Satisfaction Living alone Help to take medication Sufficient funds Treatment complexity Pill organizer |
Negative association:
Belief drugs have little/no effect |
Predominantly female sample
N‐O score = 5 |
Reports only crude odds ratios |
Ownby et al 200635 | Cross‐sectional
Interview with users of memory disorder clinic |
Convenience sample from memory clinic
Size = 63 Mean age = 76 M:F = 29:71 |
USA
Recruited via memory clinic |
Interview plus verification with carers and medical records | Park and Jones model used | Cognition
Age* Sex Memory strategy Knowledge* Seriousness of disease Education Side effects* Total number of drugs |
Positive association:
Knowledge of outcome of disease if not treated Age Negative association: Relies on self to remember doses Side‐effects |
Adherence based on self‐report with verification with carers
N‐O score = 5 |
P‐values given but no odds ratios |
Ownby et al 201236 | Randomized controlled trial. Medication Adherence in Elders Essay. | Cohort recruited via memory clinic
Size = 27 Mean = 79.9 M:F = 59:31 |
USA
Recruited via memory clinic |
Interview with cognitive testing and electronic pill monitoring | Continuous scale based on electronic monitoring
No cutoff for “non‐adherent” |
Cognition
Presence of caregiver* |
Positive association:
Presence of caregiver |
Very small sample
N‐O score = 7 |
Participants all have clinical diagnosis of memory problem and treated with cholinesterase inhibitor or memantine.
Poor adherence predicted cognitive decline, but cognition did not predict adherence. Effect of caregiver presence attenuated over time |
Pasina et al 201437 | Cohort
Interview with patients recruited from acute medical ward and followed into the community |
First 100 patients discharged from ward with polypharmacy
Size = 100 Mean age = 78 M:F = N/A |
Italy
Recruited via acute medical unit and followed into the community |
Structured interview | Medication level: mean adherence of each patient
Patient level: % of patients who are 100% adherent |
Age
Sex Marital status Presence of caregiver Number of medications* |
Non‐adherent had higher number of prescriptions than adherent (9.5 vs. 8.2, P = 0.043) | Length of study = 3 months
Does not control for other variables Odds ratios not given N‐O score = 5 |
|
Piper et al 201738 | Cross‐sectional
Random sample of Medicare beneficiaries |
5% sample of Medicare beneficiaries with epilepsy
Size = 36 912 Median age >75 M:F = 39:61 |
USA
Community |
Access to medical record | PDC from electronic health record Non‐adherent if PDC < 0.8 | Comorbidity*
Seeing specialist* Ethnicity* Sex* Age* Income* |
Positive association:
Being eligible for low‐income subsidy Negative association: Comorbid conditions: 1‐3 = OR 1.09, 4+ = OR 1.31 Seeing neurologist close to diagnosis African American/Hispanic/Asian ethnicity (ref. White) Female sex Age over 85 Below poverty line |
Random sample of largest US electronic health database Multivariate logistic regression
N‐O score = 6 |
Large well‐designed study specific to patients with epilepsy |
Salter et al 201439 | Cohort
Interviews in a subset of the MRC SCOOP trial over 18 months |
Geographical subset selected from SCOOP trial
Size = 30 Median age > 75 M:F = 0:100 |
UK
Community |
Structured interview | Self‐report during interview Non‐adherent if <80% doses taken | Medical history
History of falls Family history Response to screening Acceptance of risk |
No factors had significant association | Very small sample
Only female participants Does not control for other variables N‐O score = 5 |
As such a small sample size, the study may be under‐powered. |
Sheer et al 201640 | Cohort
Evaluation of pharmacy record of Medicare beneficiaries |
Patients in receipt of Medicare prescription for an intra‐ocular hypotensive agent
Size = 73 256 Mean age = 76 M:F = 42:58 |
USA
Community |
Access to electronic pharmacy record | PDC specifically for intra‐ocular agents
Non‐adherent if PDC <˜ 80% |
Sex*
Age* Income subsidy* New prescription* |
Positive association:
Increasing age Low income subsidy Negative association: Male sex New prescription |
Cohort identified retrospectively therefore no dropouts
Large cohort Multivariate logistic regression N‐O score = 8 |
Study specific to intra‐ocular agents |
Turner et al 200941 | Cross‐sectional
Interviews with patients identified in primary care |
“Representative sample” from primary care record
Size = 202 Mean age = 77 M:F = 34:66 |
USA
Community |
Structured interview | Non‐adherent if any dose missed in the last 3 months | Mood disorder
Self‐rated health Age Ethnicity Checks blood pressure at home Trouble following advice Polypharmacy* Runs out of medication* |
Negative association:
≥4 antihypertensive medications Runs out of medication |
Adjustment made for demographics, treatment regimen, and sampling weights
N‐O score = 5 |
Primary focus of study was antihypertensive medications |
Ulfvarson et al 200742 | Cross‐sectional
Hospital discharges followed into the community |
All eligible admissions to the acute medical ward invited
Size = 200 Mean age = 79 M:F = 48:52 |
Sweden
Sample identified in hospital and assessed in the community |
Interview with medical record linkage | Self‐report verified against medical record | Self‐rated health
Sex Age Education/knowledge Marital status Experience of side‐effects Polypharmacy Use of OTC/herbal meds Sufficient information Sufficient time with doctor/nurse Use of compliance aid |
No factors had significant association | Multivariate logistic regression
N‐O score = 6 |
Relatively small sample. Perhaps the study was under‐powered |
Factors positively associated with adherence included being of European descent,21, 32, 38 and having high health literacy and information about the treatment purpose and consequences of omission.18, 30 With regard to specific diseases, only cancer was shown to have a positive association with adherence.32
Demographic factors negatively associated with adherence included older age19, 25, 27, 35, 38 and being male,21, 25, 28, 29, 40 although these associations were weak (Figure 2). Health behaviors negatively associated with adherence were excessive alcohol consumption.22 Other factors negatively associated with adherence included the neurotic personality trait (other personality traits did not have a significant impact),27 recent hospitalization, and lack of contact with a general practitioner.31, 32 Higher levels of comorbidity were also associated with poorer adherence (Figure 3).9, 25, 33, 38 Compared with people who did not have these diseases, stroke,25 falls,32 sleep disturbance,32 and chronic obstructive pulmonary disease21 were all found to have an independent negative effect on adherence due to their presence. There was a suggestion that cognitive impairment shares a negative association with adherence18, 22, 26, 27 (Figure 4), although these results contrasted findings from two smaller studies. Both of these studies not demonstrating any association featured small sample sizes, one of which recruited patients from a memory clinic (i.e., without a healthy control comparator).30, 35
General education did not appear to be associated with adherence,18, 27, 32, 35, 42 and nor were psychiatric diagnoses.18, 22, 41 The two studies reporting body mass index associations had discordant results.27, 33
The only medication factor positively associated with adherence was having had a medication review in the last 6 months, although this was only assessed in one study.22 Factors negatively associated with adherence included recently changed medication regimens31 and those regimens that had been formulated through involvement of greater numbers of prescribing physicians.18 Patient dissatisfaction with the drug formulation and difficulties with drug storage, such as accumulation of drugs and scattered drug storage, were also negatively associated with adherence.20, 28, 41
In general, adherence was negatively associated with larger numbers of prescribed drugs, but this was not consistent. Where reports defined polypharmacy with a higher cutoff (such as greater than seven or even nine drugs), polypharmacy was more likely to have a negative association with adherence.28, 31, 37 The studies that used a continuous scale of overall pill burden were less likely to find an association between polypharmacy and adherence.21, 22, 35 One study reported improved adherence with increasing pill burden.19. Medication Adherence in Elders Essay.
Compliance aids were not consistently associated with adherence (Figure 5).18, 20, 34, 42 One study found that compliance aids were associated with medications being taken on a given day but not improved adherence to the correct dosage or regimen.18
Six studies reported on the presence of a caregiver, five of which found no association with adherence.22, 27, 29, 34, 37 One study found that a resident caregiver improved adherence focused on patients with mild cognitive impairment.34 There was no consensus between studies that reported the setting in which the patient lived, and similarly whether the patient lived alone or with someone else.18, 20-23, 34
Factors most consistently negatively associated with adherence in this older population were related to complex regimens with multiple prescribing physicians, and problems with medication storage and formulation. Multimorbidity and cognitive impairment were also negatively associated with adherence. In contrast, recent medication review and knowledge about the purpose of the treatment and consequences of omission were positively associated with adherence. However, the use of medication compliance aids and, in the absence of cognitive impairment, the presence of a caregiver did not appear to be associated with adherence. Although we sought to examine this question specifically in older populations, we found only a weak negative association with adherence at these ages. Taken together, our findings suggest that interventions for improving adherence should be aimed at patients with multimorbidity and cognitive impairment, with the goal of improving knowledge about the treatment and simplifying regimens.
This review goes beyond the findings of an earlier systematic review by considering studies conducted outside of the USA and focusing solely on patients aged over 75 years.43 Previous work found it difficult to draw broad conclusions due to differences in the definition and measurement of adherence and the limited number of publications that were included.Medication Adherence in Elders Essay. Our findings support the conclusions that health‐related knowledge, cognitive impairment, and polypharmacy have an impact on adherence. However, our analysis adds uncertainty to the notion that medication compliance aids are effective. This suggests that future investigations into other forms of adherence support are merited. The utility of compliance aids has been debated in a recent European Medicines Agency Reflection Paper, in which problems relating to the recognition of medicines due to removal from their original packaging were specifically highlighted.44 We found that external reminders (such as caregivers and phone call reminders) were more effective in older adults with cognitive impairment.45
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Our results should be treated with caution. As with previous research in this area,43 the primary limitation relates to the quantity of available research. Though we used broad inclusion criteria, we only identified 25 eligible publications. Most of these were observational, with very few randomized controlled trials having been undertaken. A further limitation concerns the lack of a clear consensus definition of adherence and polypharmacy. As such, studies relating to the administration of medications are heterogenous, both in the populations studied and in their outcome definition. Nonetheless, the strongest associations hold despite these operational differences. The major strengths of our approach have been our specific focus on older populations, a previously unexplored group with a high prevalence of adherence issues, and inclusion of studies across a range of English‐language health‐care systems.
The mechanisms underlying factors with an impact on adherence are strongly interlinked. An individual with multiple medical problems is likely to see several health‐care practitioners, all of whom may make changes to their regimen. This is likely to be confusing, thereby leading to poor adherence. Cognitive impairment across domains such as episodic memory and executive function will have consequences that include both intentional and unintentional non‐adherence. The prevalence of multimorbidity and cognitive impairment increases with age, and appears to become more important for adherence than age per se. As such, medication review with the opportunity to clarify and simplify prescription regimens and for the patient to ask questions might be most effective in this group.Medication Adherence in Elders Essay. This is consistent with having fewer prescribing physicians and knowledge about the treatment being positively associated with adherence, and should be considered in light of our finding that neither the presence of a carer (in the absence of cognitive impairment) nor compliance aids showed any association with adherence. A recent case report discussed the potential utility of knowing a patient’s medication schedule so that the pill burden is not unnecessarily increased when changes need to be made, something that could be achieved with this single‐point‐of‐care model.46 Ultimately, it may be that the most effective interventions focus on patient empowerment rather than the influence of external factors, even if individuals are living with cognitive impairment or dementia.47
Overall, this review supports our understanding that non‐adherence is prevalent amongst older patients and is multifactorial in origin. We suggest that interventions to improve adherence in this population might be most effective if delivered in the form of a medication review, with the aim of simplifying prescription regimens and providing patient education on the indications of individual therapies. If provided from a single point of care, this would reduce the number of prescribing physicians and monitor the frequency of regimen changes. In addition, switching formulation to that preferred by the patient and screening for drug storage problems could also be effective in optimizing adherence. In particular, it would seem that specific targeting of those with cognitive impairment and multimorbidity would address an at‐risk group with unmet needs. Medication Adherence in Elders Essay.