Impact of Noncommunicable Disease Multimorbidity on Healthcare Utilisation and Out-Of-Pocket Expenditures in Middle-Income Countries: Cross Sectional Analysis
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{"title"=>"Impact of noncommunicable disease multimorbidity on healthcare utilisation and out-of-pocket expenditures in middle-income countries: Cross sectional analysis", "type"=>"journal", "authors"=>[{"first_name"=>"John Tayu", "last_name"=>"Lee", "scopus_author_id"=>"37102143600"}, {"first_name"=>"Fozia", "last_name"=>"Hamid", "scopus_author_id"=>"56835358200"}, {"first_name"=>"Sanghamitra", "last_name"=>"Pati", "scopus_author_id"=>"55441302100"}, {"first_name"=>"Rifat", "last_name"=>"Atun", "scopus_author_id"=>"6602245046"}, {"first_name"=>"Christopher", "last_name"=>"Millett", "scopus_author_id"=>"8610765600"}], "year"=>2015, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84941344807", "doi"=>"10.1371/journal.pone.0127199", "pui"=>"605952454", "pmid"=>"26154083", "scopus"=>"2-s2.0-84941344807", "issn"=>"19326203", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)"}, "id"=>"d19e4849-7f2e-3aab-ac38-e9f2fd4ba6b2", "abstract"=>"BACKGROUND: The burden of non-communicable disease (NCDs) has grown rapidly in low- and middle-income countries (LMICs), where populations are ageing, with rising prevalence of multimorbidity (more than two co-existing chronic conditions) that will significantly increase pressure on already stretched health systems. We assess the impact of NCD multimorbidity on healthcare utilisation and out-of-pocket expenditures in six middle-income countries: China, Ghana, India, Mexico, Russia and South Africa.\\n\\nMETHODS: Secondary analyses of cross-sectional data from adult participants (>18 years) in the WHO Study on Global Ageing and Adult Health (SAGE) 2007-2010. We used multiple logistic regression to determine socio-demographic correlates of multimorbidity. Association between the number of NCDs and healthcare utilisation as well as out-of-pocket spending was assessed using logistic, negative binominal and log-linear models.\\n\\nRESULTS: The prevalence of multimorbidity in the adult population varied from 3.9% in Ghana to 33.6% in Russia. Number of visits to doctors in primary and secondary care rose substantially for persons with increasing numbers of co-existing NCDs. Multimorbidity was associated with more outpatient visits in China (coefficient for number of NCD = 0.56, 95% CI = 0.46, 0.66), a higher likelihood of being hospitalised in India (AOR = 1.59, 95% CI = 1.45, 1.75), higher out-of-pocket expenditures for outpatient visits in India and China, and higher expenditures for hospital visits in Russia. Medicines constituted the largest proportion of out-of-pocket expenditures in persons with multimorbidity (88.3% for outpatient, 55.9% for inpatient visit in China) in most countries.\\n\\nCONCLUSION: Multimorbidity is associated with higher levels of healthcare utilisation and greater financial burden for individuals in middle-income countries. Our study supports the WHO call for universal health insurance and health service coverage in LMICs, particularly for vulnerable groups such as the elderly with multimorbidity.", "link"=>"http://www.mendeley.com/research/impact-noncommunicable-disease-multimorbidity-healthcare-utilisation-outofpocket-expenditures-middle", "reader_count"=>78, "reader_count_by_academic_status"=>{"Unspecified"=>5, "Professor > Associate Professor"=>2, "Librarian"=>3, "Researcher"=>9, "Student > Doctoral Student"=>7, "Student > Ph. D. Student"=>19, "Student > Postgraduate"=>9, "Student > Master"=>15, "Other"=>2, "Student > Bachelor"=>2, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>2, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>5, "Professor > Associate Professor"=>2, "Librarian"=>3, "Researcher"=>9, "Student > Doctoral Student"=>7, "Student > Ph. D. Student"=>19, "Student > Postgraduate"=>9, "Student > Master"=>15, "Other"=>2, "Student > Bachelor"=>2, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>2, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>10, "Engineering"=>2, "Nursing and Health Professions"=>4, "Medicine and Dentistry"=>35, "Agricultural and Biological Sciences"=>2, "Sports and Recreations"=>1, "Business, Management and Accounting"=>4, "Social Sciences"=>17, "Economics, Econometrics and Finance"=>2, "Biochemistry, Genetics and Molecular Biology"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>2}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>35}, "Social Sciences"=>{"Social Sciences"=>17}, "Sports and Recreations"=>{"Sports and Recreations"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>2}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>4}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>4}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Unspecified"=>{"Unspecified"=>10}}, "reader_count_by_country"=>{"Bangladesh"=>1, "United States"=>1, "Malaysia"=>1, "Nigeria"=>1}, "group_count"=>8}

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  • {"files"=>["https://ndownloader.figshare.com/files/2167597"], "description"=>"<div><p>Background</p><p>The burden of non-communicable disease (NCDs) has grown rapidly in low- and middle-income countries (LMICs), where populations are ageing, with rising prevalence of multimorbidity (more than two co-existing chronic conditions) that will significantly increase pressure on already stretched health systems. We assess the impact of NCD multimorbidity on healthcare utilisation and out-of-pocket expenditures in six middle-income countries: China, Ghana, India, Mexico, Russia and South Africa.</p><p>Methods</p><p>Secondary analyses of cross-sectional data from adult participants (>18 years) in the WHO Study on Global Ageing and Adult Health (SAGE) 2007–2010. We used multiple logistic regression to determine socio-demographic correlates of multimorbidity. Association between the number of NCDs and healthcare utilisation as well as out-of-pocket spending was assessed using logistic, negative binominal and log-linear models.</p><p>Results</p><p>The prevalence of multimorbidity in the adult population varied from 3∙9% in Ghana to 33∙6% in Russia. Number of visits to doctors in primary and secondary care rose substantially for persons with increasing numbers of co-existing NCDs. Multimorbidity was associated with more outpatient visits in China (coefficient for number of NCD = 0∙56, 95% CI = 0∙46, 0∙66), a higher likelihood of being hospitalised in India (AOR = 1∙59, 95% CI = 1∙45, 1∙75), higher out-of-pocket expenditures for outpatient visits in India and China, and higher expenditures for hospital visits in Russia. Medicines constituted the largest proportion of out-of-pocket expenditures in persons with multimorbidity (88∙3% for outpatient, 55∙9% for inpatient visit in China) in most countries.</p><p>Conclusion</p><p>Multimorbidity is associated with higher levels of healthcare utilisation and greater financial burden for individuals in middle-income countries. Our study supports the WHO call for universal health insurance and health service coverage in LMICs, particularly for vulnerable groups such as the elderly with multimorbidity.</p></div>", "links"=>[], "tags"=>["sage", "health service coverage", "Noncommunicable Disease Multimorbidity", "LMIC", "outpatient visits", "multimorbidity", "aor", "ci", "expenditure", "Cross Sectional Analysis BackgroundThe burden", "healthcare utilisation", "South Africa.MethodsSecondary analyses", "ncd"], "article_id"=>1477357, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["John Tayu Lee", "Fozia Hamid", "Sanghamitra Pati", "Rifat Atun", "Christopher Millett"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0127199", "stats"=>{"downloads"=>0, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Impact_of_Noncommunicable_Disease_Multimorbidity_on_Healthcare_Utilisation_and_Out_Of_Pocket_Expenditures_in_Middle_Income_Countries_Cross_Sectional_Analysis_/1477357", "title"=>"Impact of Noncommunicable Disease Multimorbidity on Healthcare Utilisation and Out-Of-Pocket Expenditures in Middle-Income Countries: Cross Sectional Analysis", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-07-08 03:18:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/2167596"], "description"=>"<p><b>Notes:</b> Figures in the last column are regression coefficients and 95% CI for the variable “number of NCD” from regression models adjusting for all covariates. Log-linear models is used to estimate both outpatient and inpatient out-of-pocket spending outcomes.</p><p>Association between number of NCDs and out-of-pocket spending.</p>", "links"=>[], "tags"=>["sage", "health service coverage", "Noncommunicable Disease Multimorbidity", "LMIC", "outpatient visits", "multimorbidity", "aor", "ci", "expenditure", "Cross Sectional Analysis BackgroundThe burden", "healthcare utilisation", "South Africa.MethodsSecondary analyses", "ncd"], "article_id"=>1477356, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["John Tayu Lee", "Fozia Hamid", "Sanghamitra Pati", "Rifat Atun", "Christopher Millett"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0127199.t003", "stats"=>{"downloads"=>7, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Association_between_number_of_NCDs_and_out_of_pocket_spending_/1477356", "title"=>"Association between number of NCDs and out-of-pocket spending.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-07-08 03:18:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/2167593"], "description"=>"<p>Estimates presented here are based on respondent’s healthcare visit that was not free of charge.</p>", "links"=>[], "tags"=>["sage", "health service coverage", "Noncommunicable Disease Multimorbidity", "LMIC", "outpatient visits", "multimorbidity", "aor", "ci", "expenditure", "Cross Sectional Analysis BackgroundThe burden", "healthcare utilisation", "South Africa.MethodsSecondary analyses", "ncd"], "article_id"=>1477353, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["John Tayu Lee", "Fozia Hamid", "Sanghamitra Pati", "Rifat Atun", "Christopher Millett"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0127199.g005", "stats"=>{"downloads"=>16, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Percentage_of_out_of_pocket_spending_for_each_type_of_outpatient_service_in_persons_with_multimorbidity_Fig_5a_Percentage_of_out_of_pocket_spending_for_each_type_of_inpatient_service_in_persons_with_multimorbidity_Fig_5b_/1477353", "title"=>"Percentage of out-of-pocket spending for each type of outpatient service in persons with multimorbidity (Fig 5a); Percentage of out-of-pocket spending for each type of inpatient service in persons with multimorbidity (Fig 5b).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-07-08 03:18:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/2167591"], "description"=>"<p>Figures in the last column are coefficients and 95% CI for the variable “number of NCD” from regression models adjusting for all covariates. Logistic model is used to estimate any visit for outpatient/inpatient service, and negative binomial model is used for number of visit/ hospitalisation days outcome.</p>", "links"=>[], "tags"=>["sage", "health service coverage", "Noncommunicable Disease Multimorbidity", "LMIC", "outpatient visits", "multimorbidity", "aor", "ci", "expenditure", "Cross Sectional Analysis BackgroundThe burden", "healthcare utilisation", "South Africa.MethodsSecondary analyses", "ncd"], "article_id"=>1477351, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["John Tayu Lee", "Fozia Hamid", "Sanghamitra Pati", "Rifat Atun", "Christopher Millett"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0127199.g003", "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Association_between_number_of_NCDs_and_healthcare_utilisation_any_inpatient_utilisation_Fig_3a_Association_between_number_of_NCDs_and_healthcare_utilisation_number_of_inpatient_visits_Fig_3b_/1477351", "title"=>"Association between number of NCDs and healthcare utilisation- any inpatient utilisation (Fig 3a); Association between number of NCDs and healthcare utilisation- number of inpatient visits (Fig 3b).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-07-08 03:18:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/2167592"], "description"=>"<p>Data source World Health Organization (WHO) Study on Global Ageing and Adult Health (SAGE) survey, wave 1.</p>", "links"=>[], "tags"=>["sage", "health service coverage", "Noncommunicable Disease Multimorbidity", "LMIC", "outpatient visits", "multimorbidity", "aor", "ci", "expenditure", "Cross Sectional Analysis BackgroundThe burden", "healthcare utilisation", "South Africa.MethodsSecondary analyses", "ncd"], "article_id"=>1477352, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["John Tayu Lee", "Fozia Hamid", "Sanghamitra Pati", "Rifat Atun", "Christopher Millett"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0127199.g004", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Proportion_of_respondents_reporting_that_their_last_outpatient_visit_was_free_of_charge_Fig_4a_Proportion_of_respondents_reporting_that_their_last_inpatient_visit_was_free_of_charge_Fig_4b_/1477352", "title"=>"Proportion of respondents reporting that their last outpatient visit was free of charge (Fig 4a); Proportion of respondents reporting that their last inpatient visit was free of charge (Fig 4b).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-07-08 03:18:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/2167590"], "description"=>"<p>Figures in the last column are coefficients and 95% CI for the variable “number of NCD” from regression models adjusting for all covariates. Logistic model is used to estimate any visit for outpatient/inpatient service, and negative binomial model is used for number of visit/ hospitalisation days outcome.</p>", "links"=>[], "tags"=>["sage", "health service coverage", "Noncommunicable Disease Multimorbidity", "LMIC", "outpatient visits", "multimorbidity", "aor", "ci", "expenditure", "Cross Sectional Analysis BackgroundThe burden", "healthcare utilisation", "South Africa.MethodsSecondary analyses", "ncd"], "article_id"=>1477350, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["John Tayu Lee", "Fozia Hamid", "Sanghamitra Pati", "Rifat Atun", "Christopher Millett"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0127199.g002", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Association_between_number_of_NCDs_and_healthcare_utilisation_any_outpatient_utilisation_Fig_2a_Association_between_number_of_NCDs_and_healthcare_utilisation_number_of_outpatient_visits_Fig_2b_/1477350", "title"=>"Association between number of NCDs and healthcare utilisation- any outpatient utilisation (Fig 2a); Association between number of NCDs and healthcare utilisation- number of outpatient visits (Fig 2b).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-07-08 03:18:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/2167595"], "description"=>"<p>Association between number of NCDs and healthcare utilisation.</p>", "links"=>[], "tags"=>["sage", "health service coverage", "Noncommunicable Disease Multimorbidity", "LMIC", "outpatient visits", "multimorbidity", "aor", "ci", "expenditure", "Cross Sectional Analysis BackgroundThe burden", "healthcare utilisation", "South Africa.MethodsSecondary analyses", "ncd"], "article_id"=>1477355, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["John Tayu Lee", "Fozia Hamid", "Sanghamitra Pati", "Rifat Atun", "Christopher Millett"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0127199.t002", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Association_between_number_of_NCDs_and_healthcare_utilisation_/1477355", "title"=>"Association between number of NCDs and healthcare utilisation.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-07-08 03:18:20"}
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  • {"files"=>["https://ndownloader.figshare.com/files/2167589"], "description"=>"<p>Prevalence of multimorbidity by age groups in SAGE countries.</p>", "links"=>[], "tags"=>["sage", "health service coverage", "Noncommunicable Disease Multimorbidity", "LMIC", "outpatient visits", "multimorbidity", "aor", "ci", "expenditure", "Cross Sectional Analysis BackgroundThe burden", "healthcare utilisation", "South Africa.MethodsSecondary analyses", "ncd"], "article_id"=>1477349, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["John Tayu Lee", "Fozia Hamid", "Sanghamitra Pati", "Rifat Atun", "Christopher Millett"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0127199.g001", "stats"=>{"downloads"=>8, "page_views"=>86, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Prevalence_of_multimorbidity_by_age_groups_in_SAGE_countries_/1477349", "title"=>"Prevalence of multimorbidity by age groups in SAGE countries.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-07-08 03:18:20"}

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2019-04-06 02:38:24 UTC
Target URL
http://counter-101.soma.plos.org/api/v1.0/stats/doi/10.1371%2Fjournal.pone.0127199
Trace

/app/models/concerns/networkable.rb:21:in `get_result'
/app/models/source.rb:165:in `get_data'
/app/models/retrieval_status.rb:47:in `perform_get_data'
/app/jobs/source_job.rb:52:in `block (2 levels) in perform'
/app/jobs/source_job.rb:51:in `block in perform'
/app/jobs/source_job.rb:35:in `each'
/app/jobs/source_job.rb:35:in `perform'