INTRODUCTION: As the population ages, patient complexity is increasing, intensifying the demand for well-resourced, coordinated care. A deeper understanding of the factors contributing to this complexity is essential for optimising resource allocation. This study evaluates the prevalence of complex care needs in Singapore's primary care settings and identifies the factors associated with these needs. METHOD: Using a qualitative study design, we developed a patient complexity questionnaire to assess how Singapore family physicians recognise patient complexity. Sixty-nine experienced primary care physicians applied this tool to assess patient encounters, categorising each as "routine care" (RC), "medically challenging" (MC), or "complex care" (CC). We compared the care needs across these categories and used mixed-effects multinomial logistic regression to determine the independent predictors of complexity. RESULTS: Of the 4327 encounters evaluated, 15.0% were classified as CC, 18.5% as MC, and 66.4% as RC. In both CC and MC encounters, the most common medical challenges were polypharmacy (66.2% in CC, 44.9% in MC); poorly controlled chronic conditions (41.3% in CC, 24.5% in MC); and treatment interactions (34.4% in CC, 26.0% in MC). Non-medical issues frequently identified included low health literacy (32.6% in CC, 20.8% in MC); limited motivation for healthy lifestyle behaviours (27.2% in CC, 16.6% in MC); and the need for coordinated care with hospital specialists (24.7% in CC, 17.1% in MC). The top 3 independent predictors of complexity included mobility limitations requiring assistance (odds ratio [OR] for requiring wheelchair/trolley: 7.14 for CC vs RC, 95% confidence interval [CI] 4.74-10.74); longer consultation times with physicians (OR for taking >20 minutes for doctor's consultation: 3.96 for CC vs RC, 95% CI 2.86-5.48); and low socioeconomic status (OR for living in 1- or 2-room HDB flats: 2.98 for CC vs RC, 95% CI 1.74-5.13). CONCLUSION High care needs, encompassing both CC and MC encounters, were prevalent in primary care interactions. These findings highlight that relying solely on chronic disease count is insufficient to capture the full spectrum of patient complexity.
Singapore/epidemiology* ; Humans ; Primary Health Care/statistics & numerical data* ; Male ; Female ; Middle Aged ; Aged ; Adult ; Surveys and Questionnaires ; Prevalence ; Polypharmacy ; Qualitative Research ; Chronic Disease/therapy* ; Logistic Models

INTRODUCTION: Studies of concordance between patients' self-report of diseases and a criterion standard (e.g. chart review) are usually conducted in epidemiological studies to evaluate the agreement of self-reported data for use in public health research. To our knowledge, there are no published studies on concordance for highly prevalent chronic diseases such as diabetes and pre-diabetes. The aims of this study were to evaluate the concordance between patients' self-report and their medical records of diabetes and pre-diabetes diagnoses, and to identify factors associated with diabetes concordance. METHOD: A cross-sectional, interviewer-administered survey was conducted on patients with chronic diseases after obtaining written consent to assess their medical notes. Interviewers were blinded to the participants' profiles. Concordance was evaluated using Cohen's kappa (κ). A multivariable logistic regression model was used to identify factors associated with diabetes concordance. RESULTS: There was substantial agreement between self-reported and medical records of diabetes diagnoses (κ=0.76) and fair agreement for pre-diabetes diagnoses (κ=0.36). The logistic regression model suggested that non-Chinese patients had higher odds of diabetes concordance than Chinese patients (odds ratio [OR]=4.10, 95% confidence interval [CI] 1.19-14.13, P=0.03). Patients with 3 or more chronic diseases (i.e. multimorbidity) had lower odds of diabetes concordance than patients without multimorbidity (OR=0.21, 95% CI 0.09-0.48, P<0.001). CONCLUSION Diabetes concordance was substantial, supporting the use of self-report of diabetes by patients with chronic diseases in the primary care setting for future research. Pre-diabetes concordance was fair and may have important clinical implications. Further studies to explore and improve health literacy and patient-physician communication are needed.
Humans ; Prediabetic State ; Singapore/epidemiology* ; Cross-Sectional Studies ; Diabetes Mellitus/epidemiology* ; Medical Records ; Self Report

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.
Chronic Disease ; Comorbidity ; Cross-Sectional Studies ; Female ; Health Care Costs ; Humans ; Prevalence ; Primary Health Care ; Retrospective Studies ; Singapore/epidemiology*