Jing Sheng Quek, Jeremy Kaiwei Lew, Eng Sing Lee, Helen Elizabeth Smith, Sabrina Kay Wye Wong
{"title":"Prevalence of complexity in primary care and its associated factors: A Singapore experience.","authors":"Jing Sheng Quek, Jeremy Kaiwei Lew, Eng Sing Lee, Helen Elizabeth Smith, Sabrina Kay Wye Wong","doi":"10.47102/annals-acadmedsg.2024312","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>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.</p><p><strong>Method: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":502093,"journal":{"name":"Annals of the Academy of Medicine, Singapore","volume":"54 2","pages":"87-100"},"PeriodicalIF":2.5000,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of the Academy of Medicine, Singapore","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47102/annals-acadmedsg.2024312","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0
Abstract
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.