Healthcare needs, experiences and treatment burden in primary care patients with multimorbidity: An evaluation of process of care from patients&apos; perspectives

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Abstract

Background

Patients with multimorbidity often experience treatment burden as a result of fragmented, specialist‐driven healthcare. The ‘family doctor team' is an emerging service model in China to address the increasing need for high‐quality routine primary care.

Objective

This study aimed to explore the extent to which treatment burden was associated with healthcare needs and patients' experiences.

Methods

Multisite surveys were conducted in primary care facilities in Guangdong province, southern China. Interviewer‐administered questionnaires were used to collect data from patients ( N = 2160) who had ≥2 clinically diagnosed long‐term conditions (multimorbidity) and had ≥1 clinical encounter in the past 12 months since enrolment registration with the family doctor team. Patients' experiences and treatment burden were measured using a previously validated Chinese version of the Primary Care Assessment Tool (PCAT) and the Treatment Burden Questionnaire, respectively.

Results

The mean age of the patients was 61.4 years, and slightly over half were females. Patients who had a family doctor team as the primary source of care reported significantly higher PCAT scores (mean difference 7.2 points, p < .001) and lower treatment burden scores (mean difference −6.4 points, p < .001) when compared to those who often bypassed primary care. Greater healthcare needs were significantly correlated with increased treatment burden ( β‐coefficient 1.965, p < .001), whilst better patients' experiences were associated with lower treatment burden ( β‐coefficient −0.252, p < .001) after adjusting for confounders.

Conclusion

The inverse association between patients' experiences and treatment burden supports the importance of primary care in managing patients with multimorbidity.

Patient Contribution

Primary care service users were involved in the instrument development and data collection.

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Most cited references 46

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Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study.

Karen Barnett, Stewart Mercer, Michael Norbury … (2012)

Long-term disorders are the main challenge facing health-care systems worldwide, but health systems are largely configured for individual diseases rather than multimorbidity. We examined the distribution of multimorbidity, and of comorbidity of physical and mental health disorders, in relation to age and socioeconomic deprivation. In a cross-sectional study we extracted data on 40 morbidities from a database of 1,751,841 people registered with 314 medical practices in Scotland as of March, 2007. We analysed the data according to the number of morbidities, disorder type (physical or mental), sex, age, and socioeconomic status. We defined multimorbidity as the presence of two or more disorders. 42·2% (95% CI 42·1-42·3) of all patients had one or more morbidities, and 23·2% (23·08-23·21) were multimorbid. Although the prevalence of multimorbidity increased substantially with age and was present in most people aged 65 years and older, the absolute number of people with multimorbidity was higher in those younger than 65 years (210,500 vs 194,996). Onset of multimorbidity occurred 10-15 years earlier in people living in the most deprived areas compared with the most affluent, with socioeconomic deprivation particularly associated with multimorbidity that included mental health disorders (prevalence of both physical and mental health disorder 11·0%, 95% CI 10·9-11·2% in most deprived area vs 5·9%, 5·8%-6·0% in least deprived). The presence of a mental health disorder increased as the number of physical morbidities increased (adjusted odds ratio 6·74, 95% CI 6·59-6·90 for five or more disorders vs 1·95, 1·93-1·98 for one disorder), and was much greater in more deprived than in less deprived people (2·28, 2·21-2·32 vs 1·08, 1·05-1·11). Our findings challenge the single-disease framework by which most health care, medical research, and medical education is configured. A complementary strategy is needed, supporting generalist clinicians to provide personalised, comprehensive continuity of care, especially in socioeconomically deprived areas. Scottish Government Chief Scientist Office. Copyright © 2012 Elsevier Ltd. All rights reserved.

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Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modelling study

Andrew Clark, Mark Jit, Charlotte Warren-Gash … (2020)

Summary Background The risk of severe COVID-19 if an individual becomes infected is known to be higher in older individuals and those with underlying health conditions. Understanding the number of individuals at increased risk of severe COVID-19 and how this varies between countries should inform the design of possible strategies to shield or vaccinate those at highest risk. Methods We estimated the number of individuals at increased risk of severe disease (defined as those with at least one condition listed as “at increased risk of severe COVID-19” in current guidelines) by age (5-year age groups), sex, and country for 188 countries using prevalence data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 and UN population estimates for 2020. The list of underlying conditions relevant to COVID-19 was determined by mapping the conditions listed in GBD 2017 to those listed in guidelines published by WHO and public health agencies in the UK and the USA. We analysed data from two large multimorbidity studies to determine appropriate adjustment factors for clustering and multimorbidity. To help interpretation of the degree of risk among those at increased risk, we also estimated the number of individuals at high risk (defined as those that would require hospital admission if infected) using age-specific infection–hospitalisation ratios for COVID-19 estimated for mainland China and making adjustments to reflect country-specific differences in the prevalence of underlying conditions and frailty. We assumed males were twice at likely as females to be at high risk. We also calculated the number of individuals without an underlying condition that could be considered at increased risk because of their age, using minimum ages from 50 to 70 years. We generated uncertainty intervals (UIs) for our estimates by running low and high scenarios using the lower and upper 95% confidence limits for country population size, disease prevalences, multimorbidity fractions, and infection–hospitalisation ratios, and plausible low and high estimates for the degree of clustering, informed by multimorbidity studies. Findings We estimated that 1·7 billion (UI 1·0–2·4) people, comprising 22% (UI 15–28) of the global population, have at least one underlying condition that puts them at increased risk of severe COVID-19 if infected (ranging from 66% of those aged 70 years or older). We estimated that 349 million (186–787) people (4% [3–9] of the global population) are at high risk of severe COVID-19 and would require hospital admission if infected (ranging from <1% of those younger than 20 years to approximately 20% of those aged 70 years or older). We estimated 6% (3–12) of males to be at high risk compared with 3% (2–7) of females. The share of the population at increased risk was highest in countries with older populations, African countries with high HIV/AIDS prevalence, and small island nations with high diabetes prevalence. Estimates of the number of individuals at increased risk were most sensitive to the prevalence of chronic kidney disease, diabetes, cardiovascular disease, and chronic respiratory disease. Interpretation About one in five individuals worldwide could be at increased risk of severe COVID-19, should they become infected, due to underlying health conditions, but this risk varies considerably by age. Our estimates are uncertain, and focus on underlying conditions rather than other risk factors such as ethnicity, socioeconomic deprivation, and obesity, but provide a starting point for considering the number of individuals that might need to be shielded or vaccinated as the global pandemic unfolds. Funding UK Department for International Development, Wellcome Trust, Health Data Research UK, Medical Research Council, and National Institute for Health Research.

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Managing patients with multimorbidity in primary care.

Emma Wallace, Chris Salisbury, Bruce Guthrie … (2015)

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Author and article information

Contributors

Xiu‐Jing Hu: Role: Research Postgraduate

Harry H. X. Wang:

ORCID: http://orcid.org/0000-0002-0361-6527

Role: Associate Professorwanghx27@mail.sysu.edu.cn , haoxiangwang@cuhk.edu.hk

Yu‐Ting Li: Role: Research Manager

Xiao‐Ya Wu: Role: Public Health Practitioner

Yi Wang: Role: Research Postgraduate

Jia‐Heng Chen: Role: Undergraduate

Jia‐Ji Wang: Role: Professor

Samuel Y. S. Wong:

ORCID: https://orcid.org/0000-0003-0934-6385

Role: Professor

Stewart W. Mercer:

ORCID: https://orcid.org/0000-0002-1703-3664

Role: Professor

Journal

Journal ID (nlm-ta): Health Expect

Journal ID (iso-abbrev): Health Expect

Journal ID (doi): 10.1111/(ISSN)1369-7625

Journal ID (publisher-id): HEX

Title: Health Expectations : An International Journal of Public Participation in Health Care and Health Policy

Publisher: John Wiley and Sons Inc. (Hoboken )

ISSN (Print): 1369-6513

ISSN (Electronic): 1369-7625

Publication date (Electronic): 28 September 2021

Publication date (Print): February 2022

Volume: 25

Issue: 1 ( doiID: 10.1111/hex.v25.1 )

Pages: 203-213

Affiliations

[ ¹ ] School of Public Health Sun Yat‐Sen University Guangzhou China

[ ² ] JC School of Public Health and Primary Care, Faculty of Medicine The Chinese University of Hong Kong Shatin Hong Kong SAR

[ ³ ] State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center Sun Yat‐Sen University Guangzhou China

[ ⁴ ] Guangdong‐provincial Primary Healthcare Association Guangdong China

[ ⁵ ] School of Public Health Guangzhou Medical University Guangzhou China

[ ⁶ ] Centre for Population Health Sciences, Usher Institute University of Edinburgh Scotland UK

Author notes

[*] [* ] Correspondence Harry H. X. Wang, School of Public Health, Sun Yat‐Sen University, No. 74 Zhongshan Rd 2, Guangzhou 510080, China.

Email: wanghx27@ 123456mail.sysu.edu.cn and haoxiangwang@ 123456cuhk.edu.hk

Author information

Harry H. X. Wang http://orcid.org/0000-0002-0361-6527

Samuel Y. S. Wong https://orcid.org/0000-0003-0934-6385

Stewart W. Mercer https://orcid.org/0000-0002-1703-3664

Article

Publisher ID: HEX13363

DOI: 10.1111/hex.13363

PMC ID: 8849236

PubMed ID: 34585465

SO-VID: 665bf3d0-99bc-4fa9-a969-2e63295aa5a8

License:

This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

History

Date revision received : 15 August 2021

Date received : 27 January 2021

Date accepted : 06 September 2021

Page count

Figures: 3, Tables: 3, Pages: 11, Words: 7387

Funding

Funded by: National Natural Science Foundation of China

Award ID: 71904212

Award ID: 71673309

Funded by: Science and Technology Development Fund of Guangdong Province

Award ID: 2016A020216006

Funded by: Special Support Program of Guangdong Province

Award ID: 2017TQ04R749

Funded by: Basic and Applied Basic Research Foundation of Guangdong Province

Award ID: 2019A1515011381

Funded by: Higher Education Reform Project of Guangdong Province

Award ID: 20191206–20

Funded by: National Natural Science Foundation of China in collaboration with UK Research and Innovation (UKRI) — the Economic and Social Research Council (ESRC)

Award ID: 72061137002

Funded by: Medical Research Council (MRC), UK

Award ID: ES/T014164/1

Custom metadata

source-schema-version-number 2.0

cover-date February 2022

details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:6.1.1 mode:remove_FC converted:16.02.2022

ScienceOpen disciplines: Health & Social care

Keywords: health services evaluation,multimorbidity,patients' experiences,primary care assessment tool (pcat),process of care,treatment burden questionnaire (tbq)

Data availability:

ScienceOpen disciplines: Health & Social care

Keywords: health services evaluation, multimorbidity, patients' experiences, primary care assessment tool (pcat), process of care, treatment burden questionnaire (tbq)

Healthcare needs, experiences and treatment burden in primary care patients with multimorbidity: An evaluation of process of care from patients' perspectives

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Abstract

Background

Objective

Methods

Results

Conclusion

Patient Contribution

Related collections

Irish Journal of Paramedicine

Most cited references 46

Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study.

Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modelling study

Managing patients with multimorbidity in primary care.

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