Interventions to improve medication adherence in adults with mental–physical multimorbidity in primary care: a systematic review

Elena Lammila-Escalera; Geva Greenfield; Ziyang Pan; Dasha Nicholls; Azeem Majeed; Benedict Hayhoe

doi:10.3399/BJGP.2023.0406

Abstract

Background Medication non-adherence is a notable contributor to healthcare inefficiency, resulting in poor medication management, impaired patient outcomes, and ineffective symptom control.

Aim To summarise interventions targeting medication adherence for adults with mental–physical multimorbidity in primary healthcare settings.

Design and setting A systematic review of the literature — published in any language and with any country of origin — was conducted.

Method MEDLINE, EMBASE, PsycInfo, Web of Science, Cochrane Library, and the Cumulated Index to Nursing and Allied Health Literature — more commonly known as CINAHL — were searched for relevant studies. Data were extracted and synthesised using narrative synthesis. The Effective Practice and Organisation of Care (EPOC) taxonomy was used to classify intervention types. Risk of bias was assessed using the National Heart, Lung, and Blood Institute’s quality assessment tool for controlled intervention studies.

Results Eleven studies, representing 2279 patients, were included. All interventions examined were classified into one EPOC domain, namely ‘delivery arrangements’. All included studies examined patients who had a physical condition and depression. Seven studies examining interventions focused on coordination of care and management of care processes reported statistically significant improvements in medication adherence that were attributed to the intervention. Four studies considering the use of information and communication technology observed no changes in medication adherence.

Conclusion Interventions that coordinate and manage healthcare processes may help improve patients’ adherence to medication regimes in those with mental–physical multimorbidity. However, it is still necessary to better understand how digital health technology can support patients in following their medication regimes. As the growing challenges of treating multimorbidity are faced, everyone involved in health services — from providers to policymakers — must be receptive to a more integrated approach to healthcare delivery.

Introduction

Medication adherence¹^,² is ‘the degree to which the person’s behaviour corresponds with the agreed recommendations from a healthcare provider’.¹ This description encompasses several behaviours, from seeking medical attention to consuming medication as prescribed.²^,³ Non-adherence, therefore, presents health systems with a multifaceted challenge, imposing a significant economic burden globally.⁴ Five interacting dimensions are recognised to affect the ability to adhere to medication, namely:

social and economic factors;
healthcare provider-related factors;
condition-related factors;
therapy-related factors; and
patient-related factors.³^,⁵^,⁶

Socioeconomic status is one of the most frequently explored contributors to poor medication adherence, because of illness severity and primary care accessibility.²^,⁷

Medication non-adherence is particularly challenging for individuals with multimorbidity.⁸^–¹⁰ Multimorbidity is the coexistence of at least two long-term conditions;¹¹^,¹² it poses unique clinical challenges as patients have coexisting, and potentially interacting, diseases, which may amplify symptoms and discomfort.¹³^,¹⁴ Managing multimorbidity is complex and interventions to improve outcomes must be multifaceted.¹⁵ Consequently, individuals living with multimorbidity often require multiple medications to achieve optimal treatment.¹⁶^,¹⁷ This may result in a considerable burden on these individuals — for example, those with five or more chronic conditions could spend 5–8 hours a day managing these, which could contribute to treatment burden and reduce medication adherence.¹⁸^,¹⁹ Patients may also prioritise certain medications over others, according to disease progression and severity, acceptability or tolerability, and perceived importance.²^,⁷^,¹⁴ Ultimately, this can compromise drug safety, and lead to inappropriate prescriptions, adverse drug reactions, and unnecessary medication interactions.²⁰^–²² Additionally, psychiatric treatments have a lower adherence rate than those for physical conditions.²³ Mental–physical multimorbidity, which includes common mental disorder (CMD), can reduce adherence rates further.²³^–²⁶

This research builds on existing knowledge by addressing the uncertainty surrounding the effectiveness of interventions targeting medication adherence in adults with mental–physical multimorbidity in primary care. Prior to this review, the landscape lacked a systematic exploration of such interventions for this complex patient population. The findings offer a comprehensive synthesis of the literature, addressing a crucial evidential gap. Clinicians will benefit from a clearer understanding of those interventions that improve medication adherence in adults with mental–physical multimorbidity, which will help to enhance their ability to tailor care to patients and improve patient outcomes.

How this fits in

Previous studies¹⁶^,²⁷^,²⁸ have proposed many approaches to improving medication non-adherence. However, it is unclear which of these interventions address this issue, and to what extent they do so effectively, to inform best practice and service delivery. To date, no systematic review has assessed the evidence on interventions targeting medication adherence in individuals with mental–physical multimorbidity. This systematic review aimed to answer the following research question: what type of interventions are designed to improve medication adherence for adults with multimorbidity, including CMD, in primary care, and how effective are they?

Method

This review was conducted in line with recommendations in the Cochrane Handbook for Systematic Reviews of Interventions²⁹ and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Guidelines.³⁰ The protocol for this systematic review was preregistered on PROSPERO (registration number: CRD42022332974).

Eligibility criteria

The population, intervention, comparison, outcome, and study design — often referred to as PICOS — framework³¹ was used to formulate eligibility criteria. Studies were not excluded based on published language or country of origin. Studies with a quantitative randomised controlled trial design were eligible for inclusion if they considered adult populations with multimorbidity, including at least one chronic condition and at least one CMD comorbidity, presenting to primary care. Results from pilot studies were also eligible. Individuals with major depression — namely, a severe mental illness — were included in this systematic review for comprehensiveness. Studies were required to compare interventions targeting medication adherence in primary care with usual or standard care, or care without therapeutic components, and had to consider patient medication/treatment/therapy adherence rate as a primary or secondary outcome. Measures of effect included:

self-reported questionnaires or structured interviews;
therapeutic drug monitoring;
electronic devices; and
prescription pick-up/refill rates.

Search strategy

Information sources

Articles were identified through searches of the electronic databases MEDLINE, EMBASE, PsycInfo, Web of Science, Cochrane Library, and Cumulated Index to Nursing and Allied Health Literature — more commonly known as CINAHL — from January 2000 until May 2022. The search strategy was initially constructed for MEDLINE (Supplementary Table S1), but was later appropriately adapted for use with the other databases searched.

Selection process

After deduplication, the titles and abstracts of the eligible articles were independently screened against the inclusion and exclusion criteria by two reviewers. Conflicts were resolved by discussion. This process was repeated for full-text examination.

Data collection process

Data relevant to the study question were independently extracted from each qualified study by one of the reviewers who had conducted the screening and validated by the other. These data were summarised in a tabular format. Data extracted included the intervention under investigation, sociodemographic factors, and intervention effectiveness.

Study risk of bias assessment

The same two reviewers independently assessed the included studies for risk of bias using the National Heart, Lung, and Blood Institute’s study quality assessment tool for controlled intervention studies.³² Studies were not excluded based on quality assessment.

Synthesis methods

A meta-analysis was considered impractical, because of the anticipated heterogeneity of interventions. Consequently, a narrative synthesis approach was conducted, utilising the Effective Practice and Organisation of Care (EPOC) taxonomy³³ to classify the interventions reported. There are four categories:

delivery arrangements;
financial arrangements;
governance arrangements; and
implementation strategies.

Results

Study selection

Figure 1 outlines the review process. Searches identified 6941 studies; of 39 selected for full-text screening, a total of 28 were excluded because of outcomes, patient population, study design, or that the record could not be accessed. As a result, 11 randomised controlled trials³⁴^–⁴⁴ were included in this review.

Figure 1.

Systematic review flow chart.

Study characteristics

Of the 11 trials (Supplementary Table S2), nine³⁴^–³⁶^,³⁸^–⁴²^,⁴⁴ were conducted in the US, one³⁷ in Australia, and one⁴³ in South Africa. Six articles³⁴^–³⁶^,³⁸^,⁴³^,⁴⁴ targeted medication adherence as a primary outcome. These 11 studies recruited 2279 adults with multimorbidity and CMD. Disease combinations included hypertension, diabetes, HIV/AIDS, and coronary heart disease, all in combination with depression.

Three studies⁴⁰^,⁴²^,⁴⁴ were deemed as being of good quality, five studies³⁶^,³⁷^,³⁹^,⁴¹^,⁴³ were considered to be of fair quality, and three studies³⁴^,³⁵^,³⁸ were assessed as being of poor quality (Supplementary Table S3). Reasons for the poorer ratings included a failure to meet an adequate randomisation requirement, not specifying the randomisation method, not specifying the treatment allocation concealment, or not reporting the blinding of the researchers.

Intervention classification

All 11 trials³⁴^–⁴⁴ assessed interventions that could be classified as delivery arrangement interventions, according to the EPOC taxonomy. Of the interventions reported, the most frequent EPOC subcategories of the delivery arrangement domain that were explored were the:

coordination of care and management of care processes; and
use of information and communication technology (ICT).

Interventions focused on coordination of care and management of care processes

Seven studies³⁴^–³⁶^,⁴⁰^,⁴¹^,⁴³^,⁴⁴ examined interventions that targeted the coordination of care and the management of care processes. These interventions were multifaceted, with several components spanning EPOC subcategories. These components included:

case management;
integration;
shared care;
shared decision making; and
teams.

For instance, three studies³⁴^–³⁶ assessed an integrated depression and chronic-disease treatment intervention by utilising an integrated care manager as a liaison between the physician and patient. The role of this intermediary case management was to work with the patient to address the factors of adherence and effectively communicate the rationale behind antidepressant and antihypertension medication use. Similarly, the multicondition collaborative care management intervention proposed by Lin et al⁴¹ aimed to coordinate care using a care manager.

The nurse-led intervention detailed by Safren et al⁴³^,⁴⁴ integrated adherence counselling with traditional cognitive behavioural therapy (CBT) techniques for treating depression and antiretroviral therapy adherence. This programme commenced with problem solving, employing case studies (Life-Steps) to prepare participants for subsequent CBT sessions. Additional resources offered to participants included reminders, graphic aids, and self-care and physical-activity techniques.

Katon et al⁴⁰ focused on shared care, decision making, and team collaboration. Nurses collaborated with other health professionals, such as psychiatrists, who would co-review medication use, provide recommendations, and work closely with patients to establish patient-centred goals. A stepped-care algorithm was also employed, whereby participants who did not initially meet goals had to choose their next treatment plan during a second phase of the intervention.

ICT interventions

Four studies³⁷^–³⁹^,⁴² utilised ICT and telemedicine to deliver care. Clarke et al³⁷ assessed the delivery of their self-management CBT programme through a web-based platform. Targeting the improvement of social and occupational functioning, participants were required to complete a minimum set of CBT modules. Moreover, the platform offered self-monitoring reminders, home practice activities, and motivational statements. This intervention was entirely self-guided; the other ICT interventions were guided by health professionals.

Both Himelhoch et al³⁹ and Piette et al⁴² examined the impact of CBT-based interventions delivered via telephone. In contrast, the trial by Cohen et al³⁸ assessed an intervention comprising electronic-device monitoring and consultation; this pharmacist-led telehealth management programme involved the deployment of an electronic device (Health Buddy^®) to facilitate communication — it sent individualised daily reminders to patients to take their medications.

Reported outcomes

All 11 studies collated reported medication adherence as an outcome, with eight³⁴^–³⁹^,⁴²^,⁴⁴ also reporting mental health outcomes and five³⁴^–³⁷^,⁴² reporting physical health outcomes (Box 1). Of the seven studies assessing interventions based on coordination of care and management of care processes, six³⁴^–³⁶^,⁴⁰^,⁴³^,⁴⁴ reported improved medication adherence, four³⁴^–³⁶^,⁴⁴ reported improvements in mental health outcomes, and three³⁴^–³⁶ reported improvements in physical health outcomes. Of the four studies examining ICT interventions, two³⁸^,³⁹ reported maintained medication adherence, and two³⁷^,⁴² reported improved mental health outcomes only.

Intervention focus	Medication adherence	Mental health outcomes	Physical health outcomes
Coordination of care and management of care processes	Three studies³⁴^–³⁶ reported that, for their respective outcome assessments, the intervention group exhibited a higher proportion of patients who had ≥80% adherence to medication, compared with their control participants. Three studies⁴⁰^,⁴³^,⁴⁴ reported that intervention participants had significantly greater medication adherence than the control group. One of these studies⁴⁴ recorded that adherence gains were not maintained at 8 months. A further study⁴¹ reported that, although there were no differences observed for medication adherence, adjustment rates were higher among the intervention group, relative to the control	Four studies³⁴^–³⁶^,⁴⁴ reported significant reductions in depression status and depressive symptoms, compared with their control participants	Three studies³⁴^–³⁶ reported better physical chronic-disease indices compared with their control participants
ICT	Two studies³⁸^,³⁹ observed that medication adherence was maintained in the intervention participants, in comparison with the controls. Two studies³⁷^,⁴⁰ reported no differences in medication adherence between intervention and control participants	Two studies³⁷^,⁴² reported significant reductions in depressive symptoms. In contrast, one study³⁹ observed that both intervention and control group participants experienced significant reductions in depressive symptoms. One study³⁸ reported that there were no significant changes for both groups in terms of depression scores	One study³⁷ observed that intervention participants experienced no differences in blood glucose monitoring. Another study⁴² reported no differences in Hba1c levels between the intervention and control groups

EPOC = Effective Practice and Organisation of Care. Hba1c = glycated haemoglobin. ICT = information and communication technology.

Box 1.

Reported outcomes, by EPOC taxonomy intervention category³³

Discussion

Summary

Current interventions show a potential to improve medication adherence in adults with mental–physical multimorbidity in primary care, despite substantial heterogeneity in participant and intervention characteristics. Trials that assessed interventions focused on the coordination of care and care processes showed improvements across all outcomes, supporting the implementation of this intervention type for this complex patient population. In contrast, studies examining the efficacy of ICT interventions reported conflicting findings.

Strengths and limitations

To the authors’ knowledge, this is the first systematic review to examine the effectiveness of interventions to improve medication adherence for adults with multimorbidity including CMD. This review addresses a crucial evidential gap for this group, presenting valuable insight to improve service delivery. Moreover, the focus on RCTs ensured that the evidence generated was of high quality, as RCTs are recommended when establishing a causal relationship.⁴⁵

Despite an extensive search, only 11 articles were included because of strict eligibility criteria. Only depression plus a limited number of physical comorbidities were trialled in the studies eligible, restricting applicability across other chronic diseases and mental disorders. Few countries were represented, with all trials conducted in countries with English as their primary language; however, it is important to note that variation in terminology and intervention description, due to differences in language or culture, may have led to some studies being overlooked in the search. This review is also vulnerable to the limitations of the various methods used to quantify adherence, such as self-report measures.⁴⁶

There are recognised limitations in employing the EPOC taxonomy as a guide in synthesis,³³ and interventions to improve outcomes for individuals with multimorbidity are often multifaceted and have a potential for overlap in categorisation. Furthermore, the interventions demonstrated a broad range of characteristics, varying from marked structural changes in the healthcare team to patient-level amendments; consequently, causality on any outcome cannot be attributed to a specific intervention component. Finally, no studies from the UK were identified. This may have an impact on the contextual adaptability of the interventions proposed, limiting generalisability for widespread implementation in UK settings.

Comparison with existing literature

This review reaffirms previous conclusions that, despite successes with care coordination and care management processes, evidence for widespread implementation of these interventions remains undeveloped.⁴⁷^–⁵⁰ However, unlike previous work,⁴⁷^–⁵⁰ this review investigates the efficacy of interventions to improve medication adherence for this unique patient population.

Some of the interventions examined that were reported as successful at improving medication adherence have also been successful when assessed for suitability in other contexts across a variety of outcomes—for example, team care has been used in the treatment and management of other conditions, such as depression and anxiety, fostering improved outcomes in participants, and contributing to the potential usefulness of the intervention throughout the healthcare system.⁵¹ Previous research⁵²^,⁵³ has explored the relationship between care coordination and medication adherence; although the exact mechanism of association is not fully understood, it is likely influenced by fostering a robust relationship between the patient and the professional.⁵⁴^,⁵⁵ In addition, evidence indicates that an ongoing partnership may improve patient satisfaction, trust, and communication.⁵⁶

Implications for research and practice

This systematic review identified that the dominant intervention type assessed targeted service delivery arrangements. Trials assessing coordination of care interventions reported improvements in medication adherence as well as mental and physical health outcomes. In contrast, ICT interventions failed, overall, to improve outcomes for trial participants. Additional resources must, consequently, be allocated to foster the creation, testing, and implementation of interventions that aim to integrate care to improve outcomes for this complex group of patients.

To mitigate the impending challenges associated with multimorbidity, health services, providers, and policymakers must be receptive to adopting alternative approaches to care. National guidelines and policies should be reviewed to ensure alignment with best practices for this complex patient population and to support the implementation of novel ideas for change. This review presents several interventions that could be utilised to improve medication adherence, either as a reference for care delivery or as a foundational basis for additional development. Primary care providers should embrace the evidence presented in this review to reinforce care management processes and coordinate efforts to improve outcomes. The patient–provider relationship should also be prioritised when formulating strategies to enhance medication adherence for this complex patient population. The benefit of investment in medication non-adherence strategies could markedly outweigh any associated short-term expenses associated with staffing, cost, and capacity constraints.⁴

Decision makers should also grasp the opportunity to use digital health technologies and integrate them into usual service delivery. Despite conflicting evidence, the MyCompass³⁷ platform and the Health Buddy^®³⁸ device represent how digital health technologies may improve outcomes and alleviate associated burdens for the provider. However, comprehensive training, acceptance, communication, and organisational stability must be given special consideration to support the successful implementation of digital health technologies and ensure optimal outcomes.⁵⁷

There is a lack of evidence concerning which existing interventions improve medication adherence for adults with mental–physical multimorbidity in primary care and to what extent they do so. Further research is urgently required to expand the sparse evidence base for interventions supporting the care of this complex group of patients. Most of the studies collated in this review focused solely on a specific combination of chronic disease and CMD; subsequently, more trials should actively include participants with various comorbidity combinations. This would provide greater insight into the viability of widespread implementation, whereby adults with multimorbidity present to primary care with varied combinations of chronic disease. Future research should also conduct sub-group analyses to assess how variables associated with adults with multimorbidity affect the efficacy of these interventions. As an example, only one study in this review recruited African American participants. Special focus should be given to age, ethnicity, and socioeconomic status, as the literature on these factors is limited. By neglecting to incorporate these variables into the analysis, appropriate evidence will not be generated, potentially resulting in inadequate care.

Furthermore, the interventions trialled in this review may not be suitable for implementation across all global contexts. It would be advantageous if trials examined efficacy in other contexts and countries to ensure the interventions’ contextual adaptability. Economic evaluations to determine cost-effectiveness would also be beneficial by providing decision makers with additional operational information for reaching a consensus on feasibility.

Notes

Funding

This article presents independent research supported by the National Institute for Health and Care Research (NIHR) under the Applied Health Research programme for North West London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care.

Ethical approval

Not applicable.

Provenance

Freely submitted; externally peer reviewed.

Competing interests

The authors have declared no competing interests.

Discuss this article:

bjgp.org/letters

Received August 15, 2023.
Revision requested November 28, 2023.
Accepted February 26, 2024.

http://creativecommons.org/licenses/by/4.0/

This article is Open Access: CC BY 4.0 licence (http://creativecommons.org/licences/by/4.0/).

References

1.↵
1. Jimmy B,
2. Jose J
(2011) Patient medication adherence: measures in daily practice. Oman Med J 26, 3, 155–159.
OpenUrl CrossRef PubMed
2.↵
1. Sabaté E
(2003) Adherence to long-term therapies: evidence for action (World Health Organization, Geneva).
3.↵
1. Alvi Y,
2. Khalique N,
3. Ahmad A,
4. et al.
(2019) World Health Organization dimensions of adherence to antiretroviral therapy: a study at Antiretroviral Therapy Centre, Aligarh. Indian J Community Med 44, 2, 118–124.
OpenUrl
4.↵
1. Cutler RL,
2. Fernandez-Llimos F,
3. Frommer M,
4. et al.
(2018) Economic impact of medication non-adherence by disease groups: a systematic review. BMJ Open 8, 1, e016982.
OpenUrl Abstract/FREE Full Text
5.↵
1. Payne RA,
2. Avery AJ,
3. Duerden M,
4. et al.
(2014) Prevalence of polypharmacy in a Scottish primary care population. Eur J Clin Pharmacol 70, 5, 575–581.
OpenUrl CrossRef PubMed
6.↵
1. Peh KQE,
2. Kwan YH,
3. Goh H,
4. et al.
(2021) An adaptable framework for factors contributing to medication adherence: results from a systematic review of 102 conceptual frameworks. J Gen Intern Med 36, 9, 2784–2795.
OpenUrl
7.↵
1. Bratzke LC,
2. Muehrer RJ,
3. Kehl KA,
4. et al.
(2015) Self-management priority setting and decision-making in adults with multimorbidity: a narrative review of literature. Int J Nurs Stud 52, 3, 744–755.
OpenUrl CrossRef PubMed
8.↵
1. Fabbri E,
2. Zoli M,
3. Gonzalez-Freire M,
4. et al.
(2015) Aging and multimorbidity: new tasks, priorities, and frontiers for integrated gerontological and clinical research. J Am Med Dir Assoc 16, 8, 640–647.
OpenUrl CrossRef PubMed
9.
1. Guisado-Clavero M,
2. Violán C,
3. López-Jimenez T,
4. et al.
(2019) Medication patterns in older adults with multimorbidity: a cluster analysis of primary care patients. BMC Fam Pract 20, 1, 82.
OpenUrl
10.↵
1. Wehling M
(2009) Multimorbidity and polypharmacy: how to reduce the harmful drug load and yet add needed drugs in the elderly? Proposal of a new drug classification: fit for the aged. J Am Geriatr Soc 57, 3, 560–561.
OpenUrl CrossRef PubMed
11.↵
1. Pereira Nunes B,
2. Rodrigues Batista SR,
3. Bof de Andrade F,
4. et al.
(2018) Multimorbidity: the Brazilian Longitudinal Study of Aging (ELSI–Brazil). Rev Saude Publica 52, Suppl 2, 10s.
OpenUrl
12.↵
1. Barnett K,
2. Mercer SW,
3. Norbury M,
4. et al.
(2012) Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet 380, 9836, 37–43.
OpenUrl CrossRef PubMed
13.↵
1. Bayliss EA,
2. Ellis JL,
3. Steiner JF
(2007) Barriers to self-management and quality-of-life outcomes in seniors with multimorbidities. Ann Fam Med 5, 5, 395–402.
OpenUrl Abstract/FREE Full Text
14.↵
1. Foley L,
2. Larkin J,
3. Lombard-Vance R,
4. et al.
(2021) Prevalence and predictors of medication non-adherence among people living with multimorbidity: a systematic review and meta-analysis. BMJ Open 11, 9, e044987.
OpenUrl Abstract/FREE Full Text
15.↵
1. Lee JT,
2. Hamid F,
3. Pati S,
4. et al.
(2015) Impact of noncommunicable disease multimorbidity on healthcare utilisation and out-of-pocket expenditures in middle-income countries: cross sectional analysis. PLoS One 10, 7, e0127199.
OpenUrl CrossRef PubMed
16.↵
1. Patton DE,
2. Cadogan CA,
3. Ryan C,
4. et al.
(2018) Improving adherence to multiple medications in older people in primary care: selecting intervention components to address patient-reported barriers and facilitators. Health Expect 21, 1, 138–148.
OpenUrl PubMed
17.↵
1. Molokhia M,
2. Majeed A
(2017) Current and future perspectives on the management of polypharmacy. BMC Fam Pract 18, 1, 70.
OpenUrl PubMed
18.↵
1. Harris MF,
2. Dennis S,
3. Pillay M
(2013) Multimorbidity: negotiating priorities and making progress. Aust Fam Physician 42, 12, 850–854.
OpenUrl PubMed
19.↵
1. Jowsey T,
2. McRae IS,
3. Valderas JM,
4. et al.
(2013) Time’s up. Descriptive epidemiology of multi-morbidity and time spent on health related activity by older Australians: a time use survey. PLoS One 8, 4, e59379.
OpenUrl CrossRef PubMed
20.↵
1. Sánchez-Fidalgo S,
2. Guzmán-Ramos MI,
3. Galván-Banqueri M,
4. et al.
(2017) Prevalence of drug interactions in elderly patients with multimorbidity in primary care. Int J Clin Pharm 39, 2, 343–353.
OpenUrl
21.
1. Millar E,
2. Gurney J,
3. Stanley J,
4. et al.
(2019) Pill for this and a pill for that: a cross-sectional survey of use and understanding of medication among adults with multimorbidity. Australas J Ageing 38, 2, 91–97.
OpenUrl
22.↵
1. Bower P
(2014) Better management of multimorbidity: a critical look at the ‘Ariadne principles’ BMC Med 12, 222.
OpenUrl PubMed
23.↵
1. Cramer JA,
2. Rosenheck R
(1998) Compliance with medication regimens for mental and physical disorders. Psychiatr Serv 49, 2, 196–201.
OpenUrl CrossRef PubMed
24.
1. Ciechanowski PS,
2. Katon WJ,
3. Russo JE
(2000) Depression and diabetes: impact of depressive symptoms on adherence, function, and costs. Arch Intern Med 160, 21, 3278–3285.
OpenUrl CrossRef PubMed
25.
1. Piette JD,
2. Heisler M,
3. Ganoczy D,
4. et al.
(2007) Differential medication adherence among patients with schizophrenia and comorbid diabetes and hypertension. Psychiatr Serv 58, 2, 207–212.
OpenUrl CrossRef PubMed
26.↵
1. Domino ME,
2. Beadles CA,
3. Lichstein JC,
4. et al.
(2014) Heterogeneity in the quality of care for patients with multiple chronic conditions by psychiatric comorbidity. Med Care 52, Suppl 3, S101–S109.
OpenUrl
27.↵
1. Garfield S,
2. Judah G
(2022) Learning from successes: designing medication adherence intervention research so that we can learn what works and why. BMJ Qual Saf 31, 2, 83–85.
OpenUrl FREE Full Text
28.↵
1. Kini V,
2. Ho PM
(2018) Interventions to Improve medication adherence: a review. JAMA 320, 23, 2461–2473.
OpenUrl PubMed
29.↵
1. Higgins JPT,
2. Thomas J,
3. Chandler J,
4. et al.
(2019) Cochrane handbook for systematic reviews of interventions (John Wiley & Sons, Chichester).
30.↵
1. Moher D,
2. Liberati A,
3. Tetzlaff J,
4. Altman DG
(2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement. Open Med 3, 3, e123–130.
OpenUrl CrossRef PubMed
31.↵
1. Methley AM,
2. Campbell S,
3. Chew-Graham C,
4. et al.
(2014) PICO, PICOS and SPIDER: a comparison study of specificity and sensitivity in three search tools for qualitative systematic reviews. BMC Health Serv Res 14, 579.
OpenUrl CrossRef PubMed
32.↵
1. National Heart, Lung, and Blood Institute
Study quality assessment tools: quality assessment of controlled intervention studies, https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools (accessed 22 Mar 2024).
33.↵
1. Effective Practice and Organisation of Care
(2015) EPOC Taxonomy. epoc.cochrane.org/epoc-taxonomy (accessed 15 June 2023).
34.↵
1. Bogner HR,
2. de Vries HF
(2008) Integration of depression and hypertension treatment: a pilot, randomized controlled trial. Ann Fam Med 6, 4, 295–301.
OpenUrl Abstract/FREE Full Text
35.↵
1. Bogner HR,
2. de Vries HF
(2010) Integrating type 2 diabetes mellitus and depression treatment among African Americans: a randomized controlled pilot trial. Diabetes Educ 36, 2, 284–292.
OpenUrl CrossRef PubMed
36.↵
1. Bogner HR,
2. Morales KH,
3. de Vries HF,
4. Cappola AR
(2012) Integrated management of type 2 diabetes mellitus and depression treatment to improve medication adherence: a randomized controlled trial. Ann Fam Med 10, 1, 15–22.
OpenUrl Abstract/FREE Full Text
37.↵
1. Clarke J,
2. Sanatkar S,
3. Baldwin PA,
4. et al.
(2019) A web-based cognitive behavior therapy intervention to improve social and occupational functioning in adults with type 2 diabetes (the SpringboarD trial): randomized controlled trial. J Med Internet Res 21, 5, e12246.
OpenUrl
38.↵
1. Cohen LB,
2. Taveira TH,
3. Wu W-C,
4. Pirraglia PA
(2020) Pharmacist-led telehealth disease management program for patients with diabetes and depression. J Telemed Telecare 26, 5, 294–302.
OpenUrl
39.↵
1. Himelhoch S,
2. Medoff D,
3. Maxfield J,
4. et al.
(2013) Telephone based cognitive behavioral therapy targeting major depression among urban dwelling, low income people living with HIV/AIDS: results of a randomized controlled trial. AIDS Behav 17, 8, 2756–2764.
OpenUrl
40.↵
1. Katon WJ,
2. Von Korff M,
3. Lin EHB,
4. et al.
(2004) The Pathways Study: a randomized trial of collaborative care in patients with diabetes and depression. Arch Gen Psychiatry 61, 10, 1042–1049.
OpenUrl CrossRef PubMed
41.↵
1. Lin EHB,
2. Von Korff M,
3. Ciechanowski P,
4. et al.
(2012) Treatment adjustment and medication adherence for complex patients with diabetes, heart disease, and depression: a randomized controlled trial. Ann Fam Med 10, 1, 6–14.
OpenUrl Abstract/FREE Full Text
42.↵
1. Piette JD,
2. Richardson C,
3. Himle J,
4. et al.
(2011) A randomized trial of telephonic counseling plus walking for depressed diabetes patients. Med Care 49, 7, 641–648.
OpenUrl CrossRef PubMed
43.↵
1. Safren SA,
2. O’Cleirigh C,
3. Andersen LS,
4. et al.
(2021) Treating depression and improving adherence in HIV care with task-shared cognitive behavioural therapy in Khayelitsha, South Africa: a randomized controlled trial. J Int AIDS Soc 24, 10, e25823.
OpenUrl CrossRef PubMed
44.↵
1. Safren SA,
2. O’Cleirigh CM,
3. Bullis JR,
4. et al.
(2012) Cognitive behavioral therapy for adherence and depression (CBT-AD) in HIV-infected injection drug users: a randomized controlled trial. J Consult Clin Psychol 80, 3, 404–415.
OpenUrl CrossRef PubMed
45.↵
1. Hariton E,
2. Locascio JJ
(2018) Randomised controlled trials — the gold standard for effectiveness research: study design: randomised controlled trials. BJOG 125, 13, 1716.
OpenUrl PubMed
46.↵
1. Stirratt MJ,
2. Dunbar-Jacob J,
3. Crane HM,
4. et al.
(2015) Self-report measures of medication adherence behavior: recommendations on optimal use. Transl Behav Med 5, 4, 470–482.
OpenUrl CrossRef PubMed
47.↵
1. Smith SM,
2. Wallace E,
3. O’Dowd T,
4. Fortin M
(2021) Interventions for improving outcomes in patients with multimorbidity in primary care and community settings. Cochrane Database Syst Rev 1, 1, CD006560.
OpenUrl CrossRef PubMed
48.
1. Smith SM,
2. Soubhi H,
3. Fortin M,
4. et al.
(2012) Managing patients with multimorbidity: systematic review of interventions in primary care and community settings. BMJ 345, e5205.
OpenUrl Abstract/FREE Full Text
49.
1. Wallace E,
2. Salisbury C,
3. Guthrie B,
4. et al.
(2015) Managing patients with multimorbidity in primary care. BMJ 350, h176.
OpenUrl FREE Full Text
50.↵
1. Yang C,
2. Zhu S,
3. Tze Fan Lee D,
4. Chair SY
(2022) Interventions for improving medication adherence in community-dwelling older people with multimorbidity: a systematic review and meta-analysis. Int J Nurs Stud 126, 104154.
OpenUrl
51.↵
1. Eghaneyan BH,
2. Sanchez K,
3. Mitschke DB
(2014) Implementation of a collaborative care model for the treatment of depression and anxiety in a community health center: results from a qualitative case study. J Multidiscip Healthc 7, 503–513.
OpenUrl PubMed
52.↵
1. Robles S,
2. Anderson GF
(2011) Continuity of care and its effect on prescription drug use among Medicare beneficiaries with hypertension. Med Care 49, 5, 516–521.
OpenUrl PubMed
53.↵
1. Kerse N,
2. Buetow S,
3. Mainous AG,
4. et al.
(2004) Physician–patient relationship and medication compliance: a primary care investigation. Ann Fam Med 2, 5, 455–461.
OpenUrl Abstract/FREE Full Text
54.↵
1. Bauer AM,
2. Parker MM,
3. Schillinger D,
4. et al.
(2014) Associations between antidepressant adherence and shared decision-making, patient-provider trust, and communication among adults with diabetes: diabetes study of Northern California (DISTANCE). J Gen Intern Med 29, 8, 1139–1147.
OpenUrl CrossRef PubMed
55.↵
1. Hall JA,
2. Gulbrandsen P,
3. Dahl FA
(2014) Physician gender, physician patient-centered behavior, and patient satisfaction: a study in three practice settings within a hospital. Patient Educ Couns 95, 3, 313–318.
OpenUrl CrossRef PubMed
56.↵
1. Haggerty JL,
2. Reid RJ,
3. Freeman GK,
4. et al.
(2003) Continuity of care: a multidisciplinary review. BMJ 327, 7425, 1219–1221.
OpenUrl FREE Full Text
58.↵
1. Cresswell KM,
2. Bates DW,
3. Sheikh A
(2013) Ten key considerations for the successful implementation and adoption of large-scale health information technology. J Am Med Inform Assoc 20, e1, e9–e13.
OpenUrl CrossRef PubMed

In this issue

Download PDF

Download PowerPoint

Email Article

Citation Tools

Keywords

More in this TOC Section

Show more Research

Cited By...

Intended for Healthcare Professionals

Tweets by @BJGPjournal

[1] 1.↵
Jimmy B,
Jose J
(2011) Patient medication adherence: measures in daily practice. Oman Med J 26, 3, 155–159.
OpenUrl CrossRef PubMed

[2] Jimmy B,

[3] Jose J

[4] 2.↵
Sabaté E
(2003) Adherence to long-term therapies: evidence for action (World Health Organization, Geneva).

[5] Sabaté E

[6] 3.↵
Alvi Y,
Khalique N,
Ahmad A,
et al.
(2019) World Health Organization dimensions of adherence to antiretroviral therapy: a study at Antiretroviral Therapy Centre, Aligarh. Indian J Community Med 44, 2, 118–124.
OpenUrl

[7] Alvi Y,

[8] Khalique N,

[9] Ahmad A,

[10] et al.

[11] 4.↵
Cutler RL,
Fernandez-Llimos F,
Frommer M,
et al.
(2018) Economic impact of medication non-adherence by disease groups: a systematic review. BMJ Open 8, 1, e016982.
OpenUrl Abstract/FREE Full Text

[12] Cutler RL,

[13] Fernandez-Llimos F,

[14] Frommer M,

[15] et al.

[16] 5.↵
Payne RA,
Avery AJ,
Duerden M,
et al.
(2014) Prevalence of polypharmacy in a Scottish primary care population. Eur J Clin Pharmacol 70, 5, 575–581.
OpenUrl CrossRef PubMed

[17] Payne RA,

[18] Avery AJ,

[19] Duerden M,

[20] et al.

[21] 6.↵
Peh KQE,
Kwan YH,
Goh H,
et al.
(2021) An adaptable framework for factors contributing to medication adherence: results from a systematic review of 102 conceptual frameworks. J Gen Intern Med 36, 9, 2784–2795.
OpenUrl

[22] Peh KQE,

[23] Kwan YH,

[24] Goh H,

[25] et al.

[26] 7.↵
Bratzke LC,
Muehrer RJ,
Kehl KA,
et al.
(2015) Self-management priority setting and decision-making in adults with multimorbidity: a narrative review of literature. Int J Nurs Stud 52, 3, 744–755.
OpenUrl CrossRef PubMed

[27] Bratzke LC,

[28] Muehrer RJ,

[29] Kehl KA,

[30] et al.

[31] 8.↵
Fabbri E,
Zoli M,
Gonzalez-Freire M,
et al.
(2015) Aging and multimorbidity: new tasks, priorities, and frontiers for integrated gerontological and clinical research. J Am Med Dir Assoc 16, 8, 640–647.
OpenUrl CrossRef PubMed

[32] Fabbri E,

[33] Zoli M,

[34] Gonzalez-Freire M,

[35] et al.

[36] 9.
Guisado-Clavero M,
Violán C,
López-Jimenez T,
et al.
(2019) Medication patterns in older adults with multimorbidity: a cluster analysis of primary care patients. BMC Fam Pract 20, 1, 82.
OpenUrl

[37] Guisado-Clavero M,

[38] Violán C,

[39] López-Jimenez T,

[40] et al.

[41] 10.↵
Wehling M
(2009) Multimorbidity and polypharmacy: how to reduce the harmful drug load and yet add needed drugs in the elderly? Proposal of a new drug classification: fit for the aged. J Am Geriatr Soc 57, 3, 560–561.
OpenUrl CrossRef PubMed

[42] Wehling M

[43] 11.↵
Pereira Nunes B,
Rodrigues Batista SR,
Bof de Andrade F,
et al.
(2018) Multimorbidity: the Brazilian Longitudinal Study of Aging (ELSI–Brazil). Rev Saude Publica 52, Suppl 2, 10s.
OpenUrl

[44] Pereira Nunes B,

[45] Rodrigues Batista SR,

[46] Bof de Andrade F,

[47] et al.

[48] 12.↵
Barnett K,
Mercer SW,
Norbury M,
et al.
(2012) Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet 380, 9836, 37–43.
OpenUrl CrossRef PubMed

[49] Barnett K,

[50] Mercer SW,

[51] Norbury M,

[52] et al.

[53] 13.↵
Bayliss EA,
Ellis JL,
Steiner JF
(2007) Barriers to self-management and quality-of-life outcomes in seniors with multimorbidities. Ann Fam Med 5, 5, 395–402.
OpenUrl Abstract/FREE Full Text

[54] Bayliss EA,

[55] Ellis JL,

[56] Steiner JF

[57] 14.↵
Foley L,
Larkin J,
Lombard-Vance R,
et al.
(2021) Prevalence and predictors of medication non-adherence among people living with multimorbidity: a systematic review and meta-analysis. BMJ Open 11, 9, e044987.
OpenUrl Abstract/FREE Full Text

[58] Foley L,

[59] Larkin J,

[60] Lombard-Vance R,

[61] et al.

[62] 15.↵
Lee JT,
Hamid F,
Pati S,
et al.
(2015) Impact of noncommunicable disease multimorbidity on healthcare utilisation and out-of-pocket expenditures in middle-income countries: cross sectional analysis. PLoS One 10, 7, e0127199.
OpenUrl CrossRef PubMed

[63] Lee JT,

[64] Hamid F,

[65] Pati S,

[66] et al.

[67] 16.↵
Patton DE,
Cadogan CA,
Ryan C,
et al.
(2018) Improving adherence to multiple medications in older people in primary care: selecting intervention components to address patient-reported barriers and facilitators. Health Expect 21, 1, 138–148.
OpenUrl PubMed

[68] Patton DE,

[69] Cadogan CA,

[70] Ryan C,

[71] et al.

[72] 17.↵
Molokhia M,
Majeed A
(2017) Current and future perspectives on the management of polypharmacy. BMC Fam Pract 18, 1, 70.
OpenUrl PubMed

[73] Molokhia M,

[74] Majeed A

[75] 18.↵
Harris MF,
Dennis S,
Pillay M
(2013) Multimorbidity: negotiating priorities and making progress. Aust Fam Physician 42, 12, 850–854.
OpenUrl PubMed

[76] Harris MF,

[77] Dennis S,

[78] Pillay M

[79] 19.↵
Jowsey T,
McRae IS,
Valderas JM,
et al.
(2013) Time’s up. Descriptive epidemiology of multi-morbidity and time spent on health related activity by older Australians: a time use survey. PLoS One 8, 4, e59379.
OpenUrl CrossRef PubMed

[80] Jowsey T,

[81] McRae IS,

[82] Valderas JM,

[83] et al.

[84] 20.↵
Sánchez-Fidalgo S,
Guzmán-Ramos MI,
Galván-Banqueri M,
et al.
(2017) Prevalence of drug interactions in elderly patients with multimorbidity in primary care. Int J Clin Pharm 39, 2, 343–353.
OpenUrl

[85] Sánchez-Fidalgo S,

[86] Guzmán-Ramos MI,

[87] Galván-Banqueri M,

[88] et al.

[89] 21.
Millar E,
Gurney J,
Stanley J,
et al.
(2019) Pill for this and a pill for that: a cross-sectional survey of use and understanding of medication among adults with multimorbidity. Australas J Ageing 38, 2, 91–97.
OpenUrl

[90] Millar E,

[91] Gurney J,

[92] Stanley J,

[93] et al.

[94] 22.↵
Bower P
(2014) Better management of multimorbidity: a critical look at the ‘Ariadne principles’ BMC Med 12, 222.
OpenUrl PubMed

[95] Bower P

[96] 23.↵
Cramer JA,
Rosenheck R
(1998) Compliance with medication regimens for mental and physical disorders. Psychiatr Serv 49, 2, 196–201.
OpenUrl CrossRef PubMed

[97] Cramer JA,

[98] Rosenheck R

[99] 24.
Ciechanowski PS,
Katon WJ,
Russo JE
(2000) Depression and diabetes: impact of depressive symptoms on adherence, function, and costs. Arch Intern Med 160, 21, 3278–3285.
OpenUrl CrossRef PubMed

[100] Ciechanowski PS,

[101] Katon WJ,

[102] Russo JE

[103] 25.
Piette JD,
Heisler M,
Ganoczy D,
et al.
(2007) Differential medication adherence among patients with schizophrenia and comorbid diabetes and hypertension. Psychiatr Serv 58, 2, 207–212.
OpenUrl CrossRef PubMed

[104] Piette JD,

[105] Heisler M,

[106] Ganoczy D,

[107] et al.

[108] 26.↵
Domino ME,
Beadles CA,
Lichstein JC,
et al.
(2014) Heterogeneity in the quality of care for patients with multiple chronic conditions by psychiatric comorbidity. Med Care 52, Suppl 3, S101–S109.
OpenUrl

[109] Domino ME,

[110] Beadles CA,

[111] Lichstein JC,

[112] et al.

[113] 27.↵
Garfield S,
Judah G
(2022) Learning from successes: designing medication adherence intervention research so that we can learn what works and why. BMJ Qual Saf 31, 2, 83–85.
OpenUrl FREE Full Text

[114] Garfield S,

[115] Judah G

[116] 28.↵
Kini V,
Ho PM
(2018) Interventions to Improve medication adherence: a review. JAMA 320, 23, 2461–2473.
OpenUrl PubMed

[117] Kini V,

[118] Ho PM

[119] 29.↵
Higgins JPT,
Thomas J,
Chandler J,
et al.
(2019) Cochrane handbook for systematic reviews of interventions (John Wiley & Sons, Chichester).

[120] Higgins JPT,

[121] Thomas J,

[122] Chandler J,

[123] et al.

[124] 30.↵
Moher D,
Liberati A,
Tetzlaff J,
Altman DG
(2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement. Open Med 3, 3, e123–130.
OpenUrl CrossRef PubMed

[125] Moher D,

[126] Liberati A,

[127] Tetzlaff J,

[128] Altman DG

[129] 31.↵
Methley AM,
Campbell S,
Chew-Graham C,
et al.
(2014) PICO, PICOS and SPIDER: a comparison study of specificity and sensitivity in three search tools for qualitative systematic reviews. BMC Health Serv Res 14, 579.
OpenUrl CrossRef PubMed

[130] Methley AM,

[131] Campbell S,

[132] Chew-Graham C,

[133] et al.

[134] 32.↵
National Heart, Lung, and Blood Institute
Study quality assessment tools: quality assessment of controlled intervention studies, https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools (accessed 22 Mar 2024).

[135] National Heart, Lung, and Blood Institute

[136] 33.↵
Effective Practice and Organisation of Care
(2015) EPOC Taxonomy. epoc.cochrane.org/epoc-taxonomy (accessed 15 June 2023).

[137] Effective Practice and Organisation of Care

[138] 34.↵
Bogner HR,
de Vries HF
(2008) Integration of depression and hypertension treatment: a pilot, randomized controlled trial. Ann Fam Med 6, 4, 295–301.
OpenUrl Abstract/FREE Full Text

[139] Bogner HR,

[140] de Vries HF

[141] 35.↵
Bogner HR,
de Vries HF
(2010) Integrating type 2 diabetes mellitus and depression treatment among African Americans: a randomized controlled pilot trial. Diabetes Educ 36, 2, 284–292.
OpenUrl CrossRef PubMed

[142] Bogner HR,

[143] de Vries HF

[144] 36.↵
Bogner HR,
Morales KH,
de Vries HF,
Cappola AR
(2012) Integrated management of type 2 diabetes mellitus and depression treatment to improve medication adherence: a randomized controlled trial. Ann Fam Med 10, 1, 15–22.
OpenUrl Abstract/FREE Full Text

[145] Bogner HR,

[146] Morales KH,

[147] de Vries HF,

[148] Cappola AR

[149] 37.↵
Clarke J,
Sanatkar S,
Baldwin PA,
et al.
(2019) A web-based cognitive behavior therapy intervention to improve social and occupational functioning in adults with type 2 diabetes (the SpringboarD trial): randomized controlled trial. J Med Internet Res 21, 5, e12246.
OpenUrl

[150] Clarke J,

[151] Sanatkar S,

[152] Baldwin PA,

[153] et al.

[154] 38.↵
Cohen LB,
Taveira TH,
Wu W-C,
Pirraglia PA
(2020) Pharmacist-led telehealth disease management program for patients with diabetes and depression. J Telemed Telecare 26, 5, 294–302.
OpenUrl

[155] Cohen LB,

[156] Taveira TH,

[157] Wu W-C,

[158] Pirraglia PA

[159] 39.↵
Himelhoch S,
Medoff D,
Maxfield J,
et al.
(2013) Telephone based cognitive behavioral therapy targeting major depression among urban dwelling, low income people living with HIV/AIDS: results of a randomized controlled trial. AIDS Behav 17, 8, 2756–2764.
OpenUrl

[160] Himelhoch S,

[161] Medoff D,

[162] Maxfield J,

[163] et al.

[164] 40.↵
Katon WJ,
Von Korff M,
Lin EHB,
et al.
(2004) The Pathways Study: a randomized trial of collaborative care in patients with diabetes and depression. Arch Gen Psychiatry 61, 10, 1042–1049.
OpenUrl CrossRef PubMed

[165] Katon WJ,

[166] Von Korff M,

[167] Lin EHB,

[168] et al.

[169] 41.↵
Lin EHB,
Von Korff M,
Ciechanowski P,
et al.
(2012) Treatment adjustment and medication adherence for complex patients with diabetes, heart disease, and depression: a randomized controlled trial. Ann Fam Med 10, 1, 6–14.
OpenUrl Abstract/FREE Full Text

[170] Lin EHB,

[171] Von Korff M,

[172] Ciechanowski P,

[173] et al.

[174] 42.↵
Piette JD,
Richardson C,
Himle J,
et al.
(2011) A randomized trial of telephonic counseling plus walking for depressed diabetes patients. Med Care 49, 7, 641–648.
OpenUrl CrossRef PubMed

[175] Piette JD,

[176] Richardson C,

[177] Himle J,

[178] et al.

[179] 43.↵
Safren SA,
O’Cleirigh C,
Andersen LS,
et al.
(2021) Treating depression and improving adherence in HIV care with task-shared cognitive behavioural therapy in Khayelitsha, South Africa: a randomized controlled trial. J Int AIDS Soc 24, 10, e25823.
OpenUrl CrossRef PubMed

[180] Safren SA,

[181] O’Cleirigh C,

[182] Andersen LS,

[183] et al.

[184] 44.↵
Safren SA,
O’Cleirigh CM,
Bullis JR,
et al.
(2012) Cognitive behavioral therapy for adherence and depression (CBT-AD) in HIV-infected injection drug users: a randomized controlled trial. J Consult Clin Psychol 80, 3, 404–415.
OpenUrl CrossRef PubMed

[185] Safren SA,

[186] O’Cleirigh CM,

[187] Bullis JR,

[188] et al.

[189] 45.↵
Hariton E,
Locascio JJ
(2018) Randomised controlled trials — the gold standard for effectiveness research: study design: randomised controlled trials. BJOG 125, 13, 1716.
OpenUrl PubMed

[190] Hariton E,

[191] Locascio JJ

[192] 46.↵
Stirratt MJ,
Dunbar-Jacob J,
Crane HM,
et al.
(2015) Self-report measures of medication adherence behavior: recommendations on optimal use. Transl Behav Med 5, 4, 470–482.
OpenUrl CrossRef PubMed

[193] Stirratt MJ,

[194] Dunbar-Jacob J,

[195] Crane HM,

[196] et al.

[197] 47.↵
Smith SM,
Wallace E,
O’Dowd T,
Fortin M
(2021) Interventions for improving outcomes in patients with multimorbidity in primary care and community settings. Cochrane Database Syst Rev 1, 1, CD006560.
OpenUrl CrossRef PubMed

[198] Smith SM,

[199] Wallace E,

[200] O’Dowd T,

[201] Fortin M

[202] 48.
Smith SM,
Soubhi H,
Fortin M,
et al.
(2012) Managing patients with multimorbidity: systematic review of interventions in primary care and community settings. BMJ 345, e5205.
OpenUrl Abstract/FREE Full Text

[203] Smith SM,

[204] Soubhi H,

[205] Fortin M,

[206] et al.

[207] 49.
Wallace E,
Salisbury C,
Guthrie B,
et al.
(2015) Managing patients with multimorbidity in primary care. BMJ 350, h176.
OpenUrl FREE Full Text

[208] Wallace E,

[209] Salisbury C,

[210] Guthrie B,

[211] et al.

[212] 50.↵
Yang C,
Zhu S,
Tze Fan Lee D,
Chair SY
(2022) Interventions for improving medication adherence in community-dwelling older people with multimorbidity: a systematic review and meta-analysis. Int J Nurs Stud 126, 104154.
OpenUrl

[213] Yang C,

[214] Zhu S,

[215] Tze Fan Lee D,

[216] Chair SY

[217] 51.↵
Eghaneyan BH,
Sanchez K,
Mitschke DB
(2014) Implementation of a collaborative care model for the treatment of depression and anxiety in a community health center: results from a qualitative case study. J Multidiscip Healthc 7, 503–513.
OpenUrl PubMed

[218] Eghaneyan BH,

[219] Sanchez K,

[220] Mitschke DB

[221] 52.↵
Robles S,
Anderson GF
(2011) Continuity of care and its effect on prescription drug use among Medicare beneficiaries with hypertension. Med Care 49, 5, 516–521.
OpenUrl PubMed

[222] Robles S,

[223] Anderson GF

[224] 53.↵
Kerse N,
Buetow S,
Mainous AG,
et al.
(2004) Physician–patient relationship and medication compliance: a primary care investigation. Ann Fam Med 2, 5, 455–461.
OpenUrl Abstract/FREE Full Text

[225] Kerse N,

[226] Buetow S,

[227] Mainous AG,

[228] et al.

[229] 54.↵
Bauer AM,
Parker MM,
Schillinger D,
et al.
(2014) Associations between antidepressant adherence and shared decision-making, patient-provider trust, and communication among adults with diabetes: diabetes study of Northern California (DISTANCE). J Gen Intern Med 29, 8, 1139–1147.
OpenUrl CrossRef PubMed

[230] Bauer AM,

[231] Parker MM,

[232] Schillinger D,

[233] et al.

[234] 55.↵
Hall JA,
Gulbrandsen P,
Dahl FA
(2014) Physician gender, physician patient-centered behavior, and patient satisfaction: a study in three practice settings within a hospital. Patient Educ Couns 95, 3, 313–318.
OpenUrl CrossRef PubMed

[235] Hall JA,

[236] Gulbrandsen P,

[237] Dahl FA

[238] 56.↵
Haggerty JL,
Reid RJ,
Freeman GK,
et al.
(2003) Continuity of care: a multidisciplinary review. BMJ 327, 7425, 1219–1221.
OpenUrl FREE Full Text

[239] Haggerty JL,

[240] Reid RJ,

[241] Freeman GK,

[242] et al.

[243] 58.↵
Cresswell KM,
Bates DW,
Sheikh A
(2013) Ten key considerations for the successful implementation and adoption of large-scale health information technology. J Am Med Inform Assoc 20, e1, e9–e13.
OpenUrl CrossRef PubMed

[244] Cresswell KM,

[245] Bates DW,

[246] Sheikh A

Main menu

User menu

Search