Defining and measuring multimorbidity in primary care in Singapore: Results of an online Delphi study

Cross-sectional study assessing health outcome priorities of older adults with multimorbidity at a primary care setting in Singapore

OBJECTIVES

Managing older adults with multimorbidity may be challenging due to the conflicting benefits and harms of multiple treatments. Thus, it is important to identify patients' health outcome priorities to align treatment goals with their health preferences. This study aimed to use the Outcome Prioritisation Tool (OPT) to describe the health outcome priorities of older adults with multimorbidity and determine the factors associated with these priorities. Additionally, it aimed to assess the ease of completing the OPT in Singapore's primary care population.

DESIGN

Cross-sectional study conducted from January to March 2022.

SETTING

A public primary care centre in Singapore.

PARTICIPANTS

65 years and older with multimorbidity.

OUTCOME MEASURES

Primary outcome measure was the most important health outcome priorities on the OPT. Secondary outcome measures were factors affecting these priorities and ease of completing the OPT.

RESULTS

We enrolled 180 participants (mean age: 73.2±6.1 years). Slightly more than half (54.4%) prioritised 'staying alive', while the remainder (45.6%) prioritised 'maintaining independence' (25.6%), 'relieving pain' (10.6%) and 'relieving other symptoms' (9.4%). Participants with six or more chronic conditions were three times (OR 3.03 (95% CI1.09 to 8.42)) more likely to prioritise 'staying alive' compared with participants with three conditions. Most participants (69.4%) agreed that the OPT was easy to complete, and the mean time taken to complete the OPT was 3.8±1.6 minutes.

CONCLUSION

'Staying alive' was the most important health outcome priority, especially for older adults with six or more chronic conditions. The OPT was easily completed among older adults with multimorbidity in primary care. Further qualitative studies can be conducted to understand the factors influencing patients' priorities and explore the relevance of the OPT in guiding treatment decisions.

Differences in healthcare service utilization in patients with polypharmacy according to their risk level by adjusted morbidity groups: a population-based cross-sectional study

BACKGROUND

Patients with polypharmacy suffer from complex medical conditions involving a large healthcare burden. This study aimed to describe the characteristics and utilization of primary care (PC) and hospital care (HC) and factors associated in chronic patients with polypharmacy, stratifying by adjusted morbidity groups (AMG) risk level, sex and age, and comparing with non-polypharmacy.

METHODS

Cross-sectional study conducted in a Spanish basic healthcare area. Studied patients were those over 18 years with chronic diseases identified by the AMG tool from Madrid electronic clinical record, which was the data source. Sociodemographic, sociofunctional, clinical and healthcare utilization variables were described and compared by risk level, sex, age and having or not polypharmacy. Factors associated with healthcare utilization in polypharmacy patients were determined by a negative binomial regression model.

RESULTS

In the area studied, 61.3% patients had chronic diseases, of which 16.9% had polypharmacy vs. 83.1% without polypharmacy. Patients with polypharmacy (vs. non-polypharmacy) mean age was 82.7 (vs. 52.7), 68.9% (vs. 60.7%) were women, and 22.0% (vs. 1.2%) high risk. Their average number of chronic diseases was 4.8 (vs. 2.2), and 95.6% (vs. 56.9%) had multimorbidity. Their mean number of annual healthcare contacts was 30.3 (vs. 10.5), 25.9 (vs. 8.8) with PC and 4.4 (vs. 1.7) with HC. Factors associated with a greater PC utilization in patients with polypharmacy were elevated complexity, high risk level and dysrhythmia. Variables associated with a higher HC utilization were also increased complexity and high risk, in addition to male sex, being in palliative care, having a primary caregiver, suffering from neoplasia (specifically lymphoma or leukaemia) and arthritis, whereas older age and immobilization were negatively associated.

CONCLUSIONS

Polypharmacy population compared to non-polypharmacy was characterized by a more advanced age, predominance of women, high-risk, complexity, numerous comorbidities, dependency and remarkable healthcare utilization. These findings could help healthcare policy makers to optimize the distribution of resources and professionals within PC and HC systems, aiming for the improvement of polypharmacy management and rational use of medicines while reducing costs attributed to healthcare utilization by these patients.

A scoping review on the factors associated with the lost to follow-up (LTFU) amongst patients with chronic disease in ambulatory care of high-income countries (HIC)

BACKGROUND

Despite the importance of long term follow-up care for patients with chronic disease, many patients fail to adhere to their follow-ups, which increase their risk of further health complications. Therefore, the purpose of this scoping review was to find out the factors associated with lost to follow-up (LTFU) amongst patients with chronic disease in the ambulatory care setting of high-income countries (HICs) to gain insights for better quality of care. Understanding the definition of LTFU is imperative in informing patients, health professionals and researchers for clinical and research purposes. This review also provided an overview of the terms and definitions used to describe LTFU.

METHODS

The following databases: CINAHL, EMBASE, Medline, PsycINFO and Web of Science were searched for studies investigating the factors associated to LTFU from the date of inception until 07 January 2022.

RESULTS

Five thousand one hundred and seven records were obtained across the databases and 3,416 articles were screened after removing the duplicates. 25 articles met the inclusion criteria, of which 17 were cohort studies, five were cross-sectional studies and three were case-control studies. A total of 32 factors were found to be associated with LTFU and they were categorised into patient factors, clinical factors and healthcare provider factors.

CONCLUSION

Overall, the factors associated with LTFU were generally inconsistent across studies. However, some factors such as financial factors (i.e., no insurance coverage) and low accessibility of care were consistently associated with LTFU for both mental and physical chronic conditions. The operational definitions of LTFU also varied greatly across studies. Given the mixed findings, future research using qualitative aproaches would be pivotal in understanding LTFU for specific chronic diseases and the development of targeted interventions. Additionally, there is a need to standardise the operational definition of LTFU for research as well as clinical practice purposes.