Prescribing for patients with multimorbidity: aiming to tailor to patient-set goals

Cahill, Patricia

doi:10.3399/bjgp15x683857

Cited by 4 publications

(4 citation statements)

References 10 publications

(14 reference statements)

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“…There is a paucity of scientific evidence and guidelines for this group of patients, given that older patients are often excluded from clinical trials, and most of the recommendations from various clinical guidelines often only focus on the treatment of single disease rather than considering multiple diseases holistically. 56,57 Consequently, some patients may be over-prescribed with inappropriate medications when drug-drug and drug-disease relationships are not carefully considered. 43 At the same time, when patients have higher number of comorbidities, it may also be easier for physicians to miss out the prescribing of appropriate medications even in the presence of clinical indication, which may inadvertently result in PPO.…”

Section: Discussionmentioning

confidence: 99%

“…55 In the presence of multimorbidity, older patients often have to take multiple medications to treat the respective diseases. 56 Yet, it may not be an easy task for physicians to make therapeutic decisions in the presence of multimorbidity. There is a paucity of scientific evidence and guidelines for this group of patients, given that older patients are often excluded from clinical trials, and most of the recommendations from various clinical guidelines often only focus on the treatment of single disease rather than considering multiple diseases holistically.…”

Section: Comparison With Existing Literaturementioning

confidence: 99%

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Factors associated with potentially inappropriate prescribing among older persons in primary care settings: Systematic review

Lee

Tan

Goh

et al. 2023

Proceedings of Singapore Healthcare

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Background Potentially inappropriate prescribing (PIP) is common in primary care and is associated with adverse outcomes. Knowledge of the risk factors of PIP can be critical in designing PIP interventions, especially in guiding our understanding on how PIP occurs in primary care. Objective This systematic review examined factors associated with PIP, specific to primary care. Methods We searched PubMed, Embase, CINAHL, Web of Science, Scopus and PsycINFO for studies related to ‘older persons’, ‘primary care’ and ‘inappropriate prescribing’. Two reviewers conducted study selection, data extraction and quality appraisal. Factors associated with PIP were narratively synthesized. Results Of the 1017 articles identified, we included 25 articles and a total of 2,893,925 participants, with average age of 70.4–84.0 years. Risk factors of PIP could be classified into patient, physician and system factors. Patient factors were related to patient demographics (advanced age, lower education level and lower socioeconomic status), medical comorbidities (polypharmacy and multimorbidity) and lifestyle factors (unhealthy habits and use of over-the-counter medications). Physician and system factors included older, male, solo general practitioner (GP), higher number of visits of pharmaceutical sales representatives to GP, centrally located GP practice, and smaller number of older patients following up with GP, and medication source from public health system. Conclusions The findings provide contextual information to guide our understanding of PIP in primary care. Factors identified in this review can inform the design of complex interventions for PIP, as well as be used to develop risk prediction tools to identify high-risk groups who may require further interventions related to PIP.

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Section: Discussionmentioning

confidence: 99%

Section: Comparison With Existing Literaturementioning

confidence: 99%

Factors associated with potentially inappropriate prescribing among older persons in primary care settings: Systematic review

Lee

Tan

Goh

et al. 2023

Proceedings of Singapore Healthcare

View full text Add to dashboard Cite

show abstract

“…improving quality of life). 33 However, the needs of patients do not always coincide with those perceived by health professionals. This causes discrepancies between the expectations of the health professional and those of the patient.…”

Section: Introductionmentioning

confidence: 99%

“…30 , 34 – 40 Managing MM therefore represents a major challenge for PC health professionals, and is complicated by disorganization and fragmentation of the health system; the lack of institutional recognition of the leadership of the PC provider in comprehensive patient care; ineffective communication with other healthcare levels; limited time per consultation; traditional teaching methods based on specific diseases; inadequate clinical practice guidelines focused on individual diseases without considering combinations thereof; and difficulties implementing shared decision-making with patients and patient-centered care. 6 – 38 , 40 – 43 There is a need to identify, evaluate, and implement interventions that facilitate MM management using a comprehensive, community-supported approach and thereby improve the quality of life of these patients and reduce treatment burden, adverse events, and fragmented care, all of which are associated with increased healthcare utilization and costs. 6 , 38 , 44 – 47 …”

Section: Introductionmentioning

confidence: 99%

Identification of the multimorbidity training needs of primary care professionals: Protocol of a survey

Leiva-Fernández

González-Hevilla

Prados-Torres

et al. 2021

Journal of Multimorbidity and Comorbidity

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Background: Current epidemiological situation has prompted the consideration of multimorbility (MM) as a prevalent condition, influenced by age, educational level and social support, related to unfavorable social and health determinants. Primary Care (PC) has a key role in its approach but further training of professionals in MM is required. The evidence on the effectiveness of training interventions in MM is still limited. Knowing the experiences, opinions and training needs of professionals is essential to enhance training interventions. Objectives: Identify perceived training needs by PC health professionals (doctors and nurses) in MM and polypharmacy. Methods: Design: Cross-sectional study based on an online survey (anonymous-ad hoc questionnaire). Participants and recruitment: 384 doctors and nurses working in healthcare centers and out-of-hospital emergencies of the Spanish National Health System. Non-probabilistic convenience sampling via email addressed to Health Institutions, and social networks. Data: Demographic characteristics and professional profile data (close-ended and multiple-choice questions) will be collected. Open-ended questions will be used to identify training needs, difficulties and resources about MM; required skills to care patients with MM will be assessed using a 4-item ordinal scale. Analysis: Coding of data prior to analysis. Descriptive statistical analysis, participation and completion rates of the questionnaire and estimation of absolute and relative frequencies and 95% confidence intervals in close-ended questions. Content analysis with inductive methodology in open-ended questions. Ethics: Ethical approval, Online informed consent. Conclusions: The identification of training needs of health professionals who care for patients with MM will be necessary data for developing highly effective training activities.

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Social Determinants of Health and Comorbidities Among Individuals with Atherosclerotic Cardiovascular Disease: The Behavioral Risk Factor Surveillance System Survey

Rifai

Jia

Pickett

et al. 2022

Population Health Management

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Prescribing for patients with multimorbidity: aiming to tailor to patient-set goals

Cited by 4 publications

References 10 publications

Factors associated with potentially inappropriate prescribing among older persons in primary care settings: Systematic review

Factors associated with potentially inappropriate prescribing among older persons in primary care settings: Systematic review

Identification of the multimorbidity training needs of primary care professionals: Protocol of a survey

Social Determinants of Health and Comorbidities Among Individuals with Atherosclerotic Cardiovascular Disease: The Behavioral Risk Factor Surveillance System Survey

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