Defining Multimorbidity in Singapore's Primary Care Setting
Multimorbidity is often described as the co-occurrence of multiple conditions. It is common in the primary care setting, with significant implications for both the patient and the healthcare system. These patients often have complex needs, report reduced quality of life, and have a significant treatment burden. It is also associated with increased healthcare visits and costs. With an ageing population, the burden of multimorbidity is likely to increase.
MOHT has partnered with the three polyclinic clusters to define and measure multimorbidity in primary care settings to form the foundation for identifying, testing and evaluating potential interventions to prevent multimorbidity, improve patient outcomes and reduce healthcare costs.
The concept of multimorbidity has been around for years, but there is no universally accepted definition.
For instance, how many conditions should we include in our list to count under multimorbidity? How should we define a condition as ‘chronic’ to be eligible to be considered in the list of conditions? Which data sources (e.g., patient self-reports, medical records or claims records, etc.) should be used to determine the prevalence of chronic conditions? Should we use a cut-off of two or three in our local context as internationally, both cut-offs have been used in different settings? What should be our reference population as the prevalence of multimorbidity varies across different settings (e.g., primary care, hospital, etc.)? One review identified more than one hundred ways of defining multimorbidity. Internationally, the reported prevalence of multimorbidity can range from less than 5% to more than 95%, depending on how it is defined. Within Singapore, this prevalence can vary from 16% to 89%.
To unify efforts addressing multimorbidity within the local setting, we must come to a collective understanding of how we define and measure it.
MOHT conducted an online Delphi study to gain consensus on the definition of multimorbidity and the list of chronic conditions used to define multimorbidity within Singapore’s primary care setting. The Delphi method is a “group facilitation technique, which is an iterative multistage process, designed to transform opinions into group consensus.” Experts are chosen to form the panel who anonymously participate in multiple rounds of providing opinions and getting controlled feedback on these opinions until consensus is achieved.
Family physicians practicing in an ambulatory primary care setting in Singapore at the time of the study and regularly encountered patients with multiple chronic conditions were invited to participate in our study. Family physicians from both public and private settings formed the panel. Our study comprised three rounds of online voting by the panel. While Delphi Round One was qualitative for idea generation, the subsequent two rounds were quantitative to gain consensus based on pre-defined criteria following an iterative feedback process.
The response rates for the three rounds were 62%, 87% and 94%, respectively. Among 40 panellists who responded, 46% were 31-40 years old, 65% were male and 73% were from public primary healthcare.
A condition can be considered chronic if it lasts for six months or more, is recurrent or persistent, impacts the patient across multiple domains and requires long-term management. A list of 23 chronic conditions for defining multimorbidity was finalised (Table 1). The panel concluded that multimorbidity should be defined as the presence of three or more chronic conditions from this finalized list of 23 categories of chronic conditions. For example, a patient visiting primary care who has diabetes, high blood pressure and arthritis will be categorized as having multimorbidity based on our study findings (having three chronic conditions from the list of conditions).
Our findings will help define multimorbidity nationally and standardise its measurement across different primary care clusters in Singapore. Moving forward, we are taking a deep dive into data analytics to gain insights into multimorbidity related healthcare use and associated costs. Check back here for future updates!
Dr Shilpa Tyagi is Senior Data Analyst, Future Primary Care. This post was co-authored with Victoria Koh, Senior Executive, Future Primary Care; Prof Gerald Koh, Clinical Director and Head, Future Primary Care and Dr Lee Eng Sing, Fellow, Future Primary Care.