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ASSOCIATION BETWEEN COUNTRY PREPAREDNESS INDICATORS AND QUALITY CLINICAL CARE FOR CARDIOVASCULAR DISEASE RISK FACTORS IN 44 LOWER- AND MIDDLE-INCOME COUNTRIES: A MULTICOUNTRY ANALYSIS OF SURVEY DATA

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dc.contributor.author Davies, Justine I.
dc.contributor.author Reddiar, Sumithra Krishnamurthy
dc.contributor.author Hirschhorn, Lisa R.
dc.contributor.author Ebert, Cara
dc.contributor.author Marcus, Maja-Emilia
dc.contributor.author Seiglie, Jacqueline A.
dc.contributor.author Zhumadilov, Zhaxybay
dc.contributor.author Supiyev, Adil
dc.contributor.author Sturua, Lela
dc.contributor.author Silver, Bahendeka K.
dc.contributor.author Sibai, Abla M.
dc.contributor.author Quesnel-Crooks, Sarah
dc.contributor.author Norov, Bolormaa
dc.contributor.author Mwangi, Joseph K.
dc.contributor.author Omar, Omar Mwalim
dc.contributor.author Wong-McClure, Roy
dc.contributor.author Mayige, Mary T.
dc.contributor.author Martins, Joao S.
dc.contributor.author Lunet, Nuno
dc.contributor.author Labadarios, Demetre
dc.contributor.author Karki, Khem B.
dc.contributor.author Kagaruki, Gibson B.
dc.contributor.author Jorgensen, Jutta M. A.
dc.contributor.author Hwalla, Nahla C.
dc.contributor.author Houinato, Dismand
dc.contributor.author Houehanou, Corine
dc.contributor.author Guwatudde, David
dc.contributor.author Gurung, Mongal S.
dc.contributor.author Bovet, Pascal
dc.contributor.author Bicaba, Brice W.
dc.contributor.author Aryal, Krishna K.
dc.contributor.author Msaidie, Mohamed
dc.contributor.author Andall-Brereton, Glennis
dc.contributor.author Brian, Garry
dc.contributor.author Stokes, Andrew
dc.contributor.author Vollmer, Sebastian
dc.contributor.author Ba¨rnighausen, Till
dc.contributor.author Atun, Rifat
dc.contributor.author Geldsetzer, Pascal
dc.contributor.author Manne-Goehler, Jennifer
dc.contributor.author Jaacks, Lindsay M.
dc.date.accessioned 2021-02-09T11:17:45Z
dc.date.available 2021-02-09T11:17:45Z
dc.date.issued 2020-11-10
dc.identifier.citation Davies, J. I., Reddiar, S. K., Hirschhorn, L. R., Ebert, C., Marcus, M.-E., Seiglie, J. A., Zhumadilov, Z., Supiyev, A., Sturua, L., Silver, B. K., Sibai, A. M., Quesnel-Crooks, S., Norov, B., Mwangi, J. K., Omar, O. M., Wong-McClure, R., Mayige, M. T., Martins, J. S., Lunet, N., … Jaacks, L. M. (2020). Association between country preparedness indicators and quality clinical care for cardiovascular disease risk factors in 44 lower- and middle-income countries: A multicountry analysis of survey data. PLOS Medicine, 17(11), e1003268. https://doi.org/10.1371/journal.pmed.1003268 en_US
dc.identifier.issn 1549-1277
dc.identifier.issn 1549-1676
dc.identifier.uri https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1003268
dc.identifier.uri https://doi.org/10.1371/journal.pmed.1003268
dc.identifier.uri http://nur.nu.edu.kz/handle/123456789/5292
dc.description.abstract Abstract Background Cardiovascular diseases are leading causes of death, globally, and health systems that deliver quality clinical care are needed to manage an increasing number of people with risk factors for these diseases. Indicators of preparedness of countries to manage cardiovascular disease risk factors (CVDRFs) are regularly collected by ministries of health and global health agencies. We aimed to assess whether these indicators are associated with patient receipt of quality clinical care. Methods and findings We did a secondary analysis of cross-sectional, nationally representative, individual-patient data from 187,552 people with hypertension (mean age 48.1 years, 53.5% female) living in 43 low- and middle-income countries (LMICs) and 40,795 people with diabetes (mean age 52.2 years, 57.7% female) living in 28 LMICs on progress through cascades of care (condition diagnosed, treated, or controlled) for diabetes or hypertension, to indicate outcomes of provision of quality clinical care. Data were extracted from national-level World Health Organization (WHO) Stepwise Approach to Surveillance (STEPS), or other similar household surveys, conducted between July 2005 and November 2016. We used mixed-effects logistic regression to estimate associations between each quality clinical care outcome and indicators of country development (gross domestic product [GDP] per capita or Human Development Index [HDI]); national capacity for the prevention and control of noncommunicable diseases (‘NCD readiness indicators’ from surveys done by WHO); health system finance (domestic government expenditure on health [as percentage of GDP], private, and out-of-pocket expenditure on health [both as percentage of current]); and health service readiness (number of physicians, nurses, or hospital beds per 1,000 people) and performance (neonatal mortality rate). All models were adjusted for individual-level predictors including age, sex, and education. In an exploratory analysis, we tested whether national-level data on facility preparedness for diabetes were positively associated with outcomes. Associations were inconsistent between indicators and quality clinical care outcomes. For hypertension, GDP and HDI were both positively associated with each outcome. Of the 33 relationships tested between NCD readiness indicators and outcomes, only two showed a significant positive association: presence of guidelines with being diagnosed (odds ratio [OR], 1.86 [95% CI 1.08–3.21], p = 0.03) and availability of funding with being controlled (OR, 2.26 [95% CI 1.09–4.69], p = 0.03). Hospital beds (OR, 1.14 [95% CI 1.02–1.27], p = 0.02), nurses/midwives (OR, 1.24 [95% CI 1.06–1.44], p = 0.006), and physicians (OR, 1.21 [95% CI 1.11–1.32], p < 0.001) per 1,000 people were positively associated with being diagnosed and, similarly, with being treated; and the number of physicians was additionally associated with being controlled (OR, 1.12 [95% CI 1.01–1.23], p = 0.03). For diabetes, no positive associations were seen between NCD readiness indicators and outcomes. There was no association between country development, health service finance, or health service performance and readiness indicators and any outcome, apart from GDP (OR, 1.70 [95% CI 1.12–2.59], p = 0.01), HDI (OR, 1.21 [95% CI 1.01–1.44], p = 0.04), and number of physicians per 1,000 people (OR, 1.28 [95% CI 1.09–1.51], p = 0.003), which were associated with being diagnosed. Six countries had data on cascades of care and nationwide-level data on facility preparedness. Of the 27 associations tested between facility preparedness indicators and outcomes, the only association that was significant was having metformin available, which was positively associated with treatment (OR, 1.35 [95% CI 1.01–1.81], p = 0.04). The main limitation was use of blood pressure measurement on a single occasion to diagnose hypertension and a single blood glucose measurement to diagnose diabetes. Conclusion In this study, we observed that indicators of country preparedness to deal with CVDRFs are poor proxies for quality clinical care received by patients for hypertension and diabetes. The major implication is that assessments of countries’ preparedness to manage CVDRFs should not rely on proxies; rather, it should involve direct assessment of quality clinical care. en_US
dc.language.iso en en_US
dc.publisher Public Library of Science en_US
dc.relation.ispartofseries PLOS Medicine;17(11), e1003268
dc.rights Attribution-NonCommercial-ShareAlike 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/3.0/us/ *
dc.subject Diabetes mellitus en_US
dc.subject Health economics en_US
dc.subject Noncommunicable diseases en_US
dc.subject Hypertension en_US
dc.subject Health care policy en_US
dc.subject Health services administration and management en_US
dc.subject Global health en_US
dc.subject Diabetes diagnosis and management en_US
dc.subject Research Subject Categories::MEDICINE en_US
dc.title ASSOCIATION BETWEEN COUNTRY PREPAREDNESS INDICATORS AND QUALITY CLINICAL CARE FOR CARDIOVASCULAR DISEASE RISK FACTORS IN 44 LOWER- AND MIDDLE-INCOME COUNTRIES: A MULTICOUNTRY ANALYSIS OF SURVEY DATA en_US
dc.type Article en_US
workflow.import.source science


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