The prevalence of multimorbidity in primary care: a comparison of two definitions of multimorbidity with two different lists of chronic conditions in Singapore

How family physicians in Singapore recognise complexity during consultations: a qualitative study

BACKGROUND

The prevalence of persons with complex needs in Singapore is rising. Poor understanding of what constitutes complexity impedes the identification of care gaps and development of interventions to improve care for these individuals. We aim to identify the characteristics contributing to complexity in primary care, from the Family Physicians' (FP) perspectives.

METHODS

Focus group discussions (FGDs) were conducted from January to September 2021 with experienced FPs across 14 study sites, employing a qualitative descriptive approach based on a complexity framework. Data were coded independently and categorised using thematic analysis by two independent investigators.

RESULTS

Five FGDs were conducted with 18 FPs aged 32 to 57 years old working in different primary care settings, with a mean of 13.5 years of primary care experience. Participants emphasised the need for a unified definition of complexity. Complexity is characterised by the presence of issues spanning across two or more domains (medical, psychological, social or behavioural) that adversely impact medical care and outcomes. Persons with complex needs contrast with persons with medically difficult issues. Medical domain issues include the number of active medical problems, poor chronic disease control, treatment interactions, ill-defined symptoms, management of end-of-life conditions and functional impairment. Psychological domain issues include the presence of mental health conditions or cognitive impairment. Social domain issues include the lack of social support, competing social responsibilities and financial issues, while behavioural domain issues include a lack of trust in healthcare workers, fixed health beliefs and poor health literacy.

CONCLUSION

Recognising the medical, psychological, social and behavioural factors that contribute to complexity aids in discerning the diverse needs of individuals with complex needs. This underscores the need for additional support in these pertinent areas.

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.

How do older adults with multimorbidity navigate healthcare?: a qualitative study in Singapore

BACKGROUND

Patients living with multimorbidity may require frequent visits to multiple healthcare institutions and to follow diverse medical regimens and advice. Older adults with multimorbidity could face additional challenges because of declining cognitive capability, frailty, increased complexity of diseases, as well as limited social and economic resources. Research on how this population navigates the healthcare system in Singapore also remains unknown. This study investigates the challenges older adults with multimorbidity face in navigating healthcare in Singapore.

METHODS

Twenty older adults with multimorbidity from a public primary care setting were purposively sampled. Interviews conducted inquired into their experiences of navigating the healthcare system with multiple conditions. Inductive thematic analysis was performed by independent coders who resolved differences through discussion.

RESULTS

Older adults with multimorbidity form a population with specific characteristics and challenges. Their ability to navigate the healthcare system well was influenced by these themes including patient-related factors (autonomy and physical mobility, literacy and technological literacy, social support network), healthcare system-related factors (communication and personal rapport, fragmented system, healthcare staff as advocate) and strategies for navigation (fitting in, asking for help, negotiating to achieve goals, managing the logistics of multimorbidity).

DISCUSSION

Older adults with multimorbidity should not be treated as a homogenous group but can be stratified according to those with less serious or disruptive conditions (less burden of illness and burden of treatment) and those with more severe conditions (more burden of illness and burden of treatment). Among the latter, some became navigational experts while others struggled to obtain the resources needed. The variations of navigational experiences of the healthcare system show the need for further study of the differential needs of older adults with multimorbidity. To be truly patient-centred, healthcare providers should consider factors such as the existence of family support networks, literacy, technological literacy and the age-related challenges older adults face as they interact with the healthcare system, as well as finding ways to improve healthcare systems through personal rapport and strategies for reducing unnecessary burden of treatment for patients with multimorbidity.

Multimorbidity patterns in the working age population with the top 10% medical cost from exhaustive insurance claims data of Japan Health Insurance Association

Although the economic burden of multimorbidity is a growing global challenge, the contribution of multimorbidity in patients with high medical expenses remains unclear. We aimed to clarify multimorbidity patterns that have a large impact on medical costs in the Japanese population. We conducted a cross-sectional study using health insurance claims data provided by the Japan Health Insurance Association. Latent class analysis (LCA) was used to identify multimorbidity patterns in 1,698,902 patients who had the top 10% of total medical costs in 2015. The present parameters of the LCA model included 68 disease labels that were frequent among this population. Moreover, subgroup analysis was performed using a generalized linear model (GLM) to assess the factors influencing annual medical cost and 5-year mortality. As a result of obtaining 30 latent classes, the kidney disease class required the most expensive cost per capita, while the highest portion (28.6%) of the total medical cost was spent on metabolic syndrome (MetS) classes, which were characterized by hypertension, dyslipidemia, and type 2 diabetes. GLM applied to patients with MetS classes showed that cardiovascular diseases or complex conditions, including malignancies, were powerful determinants of medical cost and mortality. MetS was classified into 7 classes based on real-world data and accounts for a large portion of the total medical costs. MetS classes with cardiovascular diseases or complex conditions, including malignancies, have a significant impact on medical costs and mortality.

Validation of patient- and GP-reported core sets of quality indicators for older adults with multimorbidity in primary care: results of the cross-sectional observational MULTIqual validation study

BACKGROUND

Older adults with multimorbidity represent a growing segment of the population. Metrics to assess quality, safety and effectiveness of care can support policy makers and healthcare providers in addressing patient needs. However, there is a lack of valid measures of quality of care for this population. In the MULTIqual project, 24 general practitioner (GP)-reported and 14 patient-reported quality indicators for the healthcare of older adults with multimorbidity were developed in Germany in a systematic approach. This study aimed to select, validate and pilot core sets of these indicators.

METHODS

In a cross-sectional observational study, we collected data in general practices (n = 35) and patients aged 65 years and older with three or more chronic conditions (n = 346). One-dimensional core sets for both perspectives were selected by stepwise backward selection based on corrected item-total correlations. We established structural validity, discriminative capacity, feasibility and patient-professional agreement for the selected indicators. Multilevel multivariable linear regression models adjusted for random effects at practice level were calculated to examine construct validity.

RESULTS

Twelve GP-reported and seven patient-reported indicators were selected, with item-total correlations ranging from 0.332 to 0.576. Fulfilment rates ranged from 24.6 to 89.0%. Between 0 and 12.7% of the values were missing. Seventeen indicators had agreement rates between patients and professionals of 24.1% to 75.9% and one had 90.7% positive and 5.1% negative agreement. Patients who were born abroad (- 1.04, 95% CI =  - 2.00/ - 0.08, p = 0.033) and had higher health-related quality of life (- 1.37, 95% CI =  - 2.39/ - 0.36, p = 0.008), fewer contacts with their GP (0.14, 95% CI = 0.04/0.23, p = 0.007) and lower willingness to use their GPs as coordinators of their care (0.13, 95% CI = 0.06/0.20, p < 0.001) were more likely to have lower GP-reported healthcare quality scores. Patients who had fewer GP contacts (0.12, 95% CI = 0.04/0.20, p = 0.002) and were less willing to use their GP to coordinate their care (0.16, 95% CI = 0.10/0.21, p < 0.001) were more likely to have lower patient-reported healthcare quality scores.

CONCLUSIONS

The quality indicator core sets are the first brief measurement tools specifically designed to assess quality of care for patients with multimorbidity. The indicators can facilitate implementation of treatment standards and offer viable alternatives to the current practice of combining disease-related metrics with poor applicability to patients with multimorbidity.

Multimorbidity and statin prescription for primary prevention of cardiovascular diseases: A cross-sectional study in general practice in France

Background

Statins are a first line, evidence-based yet underprescribed treatment for cardiovascular primary prevention. In primary care settings, multimorbidity is a complex situation which makes it difficult to apply prevention guidelines.

Aim

To assess the associations between multimorbidity and prescription of statins in accordance with the 2016 ESC recommendations ("appropriate prescription"), and to identify the factors and conditions associated with these prescriptions.

Design and setting

Cross-sectional prospective study in the French region of Rhône-Alpes among 40 general practitioners and their patients.

Methods

We examined the association between appropriate statin prescription and several patient characteristics, including multimorbidity, using multivariate logistic regression models.

Results

Between August 2017 and February 2019, 327 patients were included in the study. Seventy-four (22.6%) were on statin medication and 199 (60.9%) exhibited multimorbidity, defined as ≥2 diseases. Only 22.5% of eligible patients were prescribed statins for primary prevention. Diabetes was most strongly associated with appropriate statin prescription (aOR 8.10, CI 95: 3.81-17.80). Multimorbidity was not associated with appropriate statin prescription (aOR 1.31, CI 95: 0.54-3.26), except in the presence of diabetes which defined diabetic multimorbidity (aOR 10.46, CI 95: 4.87-23.35). Conversely, non-diabetic multimorbidity was associated with lower odds of being appropriately prescribed a statin (aOR 0.26, CI 95: 0.12-0.56).

Conclusion

Multimorbidity, in itself, does not seem to be a determinant factor for appropriate statin prescription. The latter appears to be determined by a patient's type of multimorbidity, especially the presence or not of diabetes. Differentiating between diabetic and non-diabetic multimorbidity may be a pragmatic way for GPs to improve primary prevention in a patient-centered and shared decision-making approach.

Describing a complex primary health care population to support future decision support initiatives

Introduction

Developing decision support tools using data from a health care organization, to support care within that organization, is a promising paradigm to improve care delivery and population health. Descriptive epidemiology may be a valuable supplement to stakeholder input towards selection of potential initiatives and to inform methodological decisions throughout tool development. We additionally propose that to properly characterize complex populations in large-scale descriptive studies, both simple statistical and machine learning techniques can be useful.

Objective

To describe sociodemographic, clinical, and health care use characteristics of primary care clients served by the Alliance for Healthier Communities, which provides team-based primary health care through Community Health Centres (CHCs) across Ontario, Canada.

Methods

We used electronic health record data from adult ongoing primary care clients served by CHCs in 2009-2019. We performed traditional table-based summaries for each characteristic; and applied three unsupervised learning techniques to explore patterns of common condition co-occurrence, care provider teams, and care frequency.

Results

There were 221,047 eligible clients. Sociodemographics: We described 13 characteristics, stratified by CHC type and client multimorbidity status. Clinical characteristics: Eleven-year prevalence of 24 investigated conditions ranged from 1% (Hepatitis C) to 63% (chronic musculoskeletal problem) with non-uniform risk across the care history; multimorbidity was common (81%) with variable co-occurrence patterns. Health care use characteristics: Most care was provided by physician and nursing providers, with heterogeneous combinations of other provider types. A subset of clients had many issues addressed within single-visits and there was within- and between-client variability in care frequency. In addition to substantive findings, we discuss methodological considerations for future decision support initiatives.

Conclusions

We demonstrated the use of methods from statistics and machine learning, applied with an epidemiological lens, to provide an overview of a complex primary care population and lay a foundation for stakeholder engagement and decision support tool development.

Sociodemographic and Health-Related Factors Influencing Drug Intake among the Elderly Population

Excessive drugs intake among the elderly population, including self-medication, constitutes an important public health problem. Polypharmacy may lead to numerous adverse health effects, which become more prevalent when combined with biological changes in seniors. In this cross-sectional study, 500 Polish adults aged ≥60 years (M = 67.9 ± 4.2) were asked to complete a questionnaire via telephone calls, allowing us to identify sociodemographic and health-related factors influencing the daily medications consumption. Our findings revealed that all of the participants were receiving medications; 60.2% of them receive at least 1 to 3 drugs per day (301/500). The most commonly used medications included antihypertensive drugs and analgesics (51.0% and 46.0%, respectively). Taking into account clinical conditions, independent predictors of receiving over 3 medications per day turned out to be (1) coronary artery disease (OR = 6.77; CI 95%, 2.86–16.1), (2) diabetes (OR = 3.23, CI 95%, 1.75–5.95), (3) asthma (OR = 4.87, CI 95%, 2.13–11.1), (4) heart failure (OR = 3.38, CI 95%, 1.59–7.19) and (5) gastroesophageal reflux disease (OR = 1.93, CI 95%, 1.03–3.62). Participants suffering from depression were more likely to take drugs for hypertension (OR = 1.70, CI 95%, 1.04–2.78), while those with anxiety and social loneliness took more painkillers (OR = 2.59, CI 95%, 1.58–4.26 and OR = 2.08, CI 95%, 1.38–3.13, respectively). The most significant sociodemographic factors increasing the drugs intake among the population included in our study were high body mass and subsequent increased BMI values (OR = 2.68, CI 95%, 1.50–4.77). Furthermore, living in a city with over 400,000 inhabitants increased the likelihood of taking antidepressants (OR = 2.18, CI 95%, 1.20–3.94). Our study revealed factors increasing the risk of excessive medications intake and hence, increased susceptibility to some iatrogenic diseases among the elderly population. These factors should be considered by primary care physicians while prescribing appropriate drugs to elderly patients.

Patterns and predictors of oral antipsychotic prescribing in adult patients with schizophrenia

Background

Objective

Methods

Results

Conclusions

Transitions between versions of the International Classification of Diseases and chronic disease prevalence estimates from administrative health data: a population-based study

Background

Diagnosis codes in administrative health data are routinely used to monitor trends in disease prevalence and incidence. The International Classification of Diseases (ICD), which is used to record these diagnoses, have been updated multiple times to reflect advances in health and medical research. Our objective was to examine the impact of transitions between ICD versions on the prevalence of chronic health conditions estimated from administrative health data.

Methods

Study data (i.e., physician billing claims, hospital records) were from the province of Manitoba, Canada, which has a universal healthcare system. ICDA-8 (with adaptations), ICD-9-CM (clinical modification), and ICD-10-CA (Canadian adaptation; hospital records only) codes are captured in the data. Annual study cohorts included all individuals 18 + years of age for 45 years from 1974 to 2018. Negative binomial regression was used to estimate annual age- and sex-adjusted prevalence and model parameters (i.e., slopes and intercepts) for 16 chronic health conditions. Statistical control charts were used to assess the impact of changes in ICD version on model parameter estimates. Hotelling’s T² statistic was used to combine the parameter estimates and provide an out-of-control signal when its value was above a pre-specified control limit.

Results

The annual cohort sizes ranged from 360,341 to 824,816. Hypertension and skin cancer were among the most and least diagnosed health conditions, respectively; their prevalence per 1,000 population increased from 40.5 to 223.6 and from 0.3 to 2.1, respectively, within the study period. The average annual rate of change in prevalence ranged from -1.6% (95% confidence interval [CI]: -1.8, -1.4) for acute myocardial infarction to 14.6% (95% CI: 13.9, 15.2) for hypertension. The control chart indicated out-of-control observations when transitioning from ICDA-8 to ICD-9-CM for 75% of the investigated chronic health conditions but no out-of-control observations when transitioning from ICD-9-CM to ICD-10-CA.

Conclusions

The prevalence of most of the investigated chronic health conditions changed significantly in the transition from ICDA-8 to ICD-9-CM. These results point to the importance of considering changes in ICD coding as a factor that may influence the interpretation of trend estimates for chronic health conditions derived from administrative health data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13118-8.

Measuring the quality of care for older adults with multimorbidity: Results of the MULTIqual project

Background and Objectives

Providing health care for older adults with multimorbidity is often complex, challenging, and prone to fragmentation. Although clinical decision making should take into account treatment interactions, individual burden, and resources, current approaches to assessing quality of care mostly rely on indicators for single conditions. The aim of this project was to develop a set of generic quality indicators for the management of patients aged 65 and older with multimorbidity that can be used in both health care research and clinical practice.

Research Design and Methods

Based on the findings of a systematic literature review and eight focus groups with patients with multimorbidity and their family members, we developed candidate indicators. Identified aspects of quality were mapped to core domains of health care to obtain a guiding framework for quality-of-care assessment. Using nominal group technique, indicators were rated by a multidisciplinary expert panel (n = 23) following standardized criteria.

Results

We derived 47 candidate quality indicators from the literature and 4 additional indicators from the results of the focus groups. The expert panel selected a set of 25 indicators, which can be assigned to the levels of patient factors, patient–provider communication, and context and organizational structures of the conceptual framework.

Discussion and Implications

We developed a comprehensive indicator set for the management of multimorbidity that can help to highlight areas with potential for improving the quality of care and support application of multimorbidity guidelines. Furthermore, this study may serve as a blueprint for participatory designs in the development of quality indicators.

Healthcare cost of patients with multiple chronic diseases in Singapore public primary care setting

INTRODUCTION

The rising prevalence of multiple chronic diseases is an important public health issue as it is associated with increased healthcare utilisation. This paper aimed to explore the annual per capita healthcare cost in primary care for patients with multiple chronic diseases (multimorbidity).

METHODS

This was a retrospective cohort study conducted in a cluster of public primary care clinics in Singapore. De-identified data from electronic medical records were extracted from July 2015 to June 2017. Only patients with at least 1 chronic disease were included in the study. Basic demographic data and healthcare cost were extracted. A list of 20 chronic diseases was considered for multimorbidity.

RESULTS

There were 254,377 patients in our study population, of whom 52.8% were female. The prevalence of multimorbidity was 62.4%. The median annual healthcare cost per capita for patients with multimorbidity was about twice the amount compared to those without multimorbidity (SGD683 versus SGD344). The greatest percentage increment in cost was when the number of chronic diseases increased from 2 to 3 (43.0%).

CONCLUSION

Multimorbidity is associated with higher healthcare cost in primary care. Since evidence for the optimal management of multimorbidity is still elusive, prevention or delay in the onset of multimorbidity in the general population is paramount.