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

被引:19
作者
Davies, Justine I. [1 ,2 ,3 ,4 ]
Reddiar, Sumithra Krishnamurthy [5 ]
Hirschhorn, Lisa R. [6 ]
Ebert, Cara [7 ]
Marcus, Maja-Emilia [8 ,9 ]
Seiglie, Jacqueline A. [10 ]
Zhumadilov, Zhaxybay [11 ]
Supiyev, Adil [12 ]
Sturua, Lela [13 ]
Silver, Bahendeka K. [14 ]
Sibai, Abla M. [15 ]
Quesnel-Crooks, Sarah [16 ]
Norov, Bolormaa [17 ]
Mwangi, Joseph K. [18 ]
Omar, Omar Mwalim [19 ]
Wong-McClure, Roy [20 ]
Mayige, Mary T. [21 ]
Martins, Joao S. [22 ]
Lunet, Nuno [23 ]
Labadarios, Demetre [24 ]
Karki, Khem B. [25 ]
Kagaruki, Gibson B. [21 ]
Jorgensen, Jutta M. A. [19 ]
Hwalla, Nahla C. [26 ]
Houinato, Dismand [27 ]
Houehanou, Corine [27 ]
Guwatudde, David [28 ]
Gurung, Mongal S. [29 ]
Bovet, Pascal [30 ,31 ]
Bicaba, Brice W. [32 ]
Aryal, Krishna K. [33 ]
Msaidie, Mohamed [34 ]
Andall-Brereton, Glennis [16 ]
Brian, Garry [35 ]
Stokes, Andrew [36 ]
Vollmer, Sebastian [8 ,9 ]
Barnighausen, Till [37 ,38 ,39 ]
Atun, Rifat [5 ,40 ]
Geldsetzer, Pascal [41 ]
Manne-Goehler, Jennifer [42 ,43 ]
Jaacks, Lindsay M. [5 ,44 ,45 ]
机构
[1] Univ Birmingham, Inst Appl Hlth Res, Birmingham, W Midlands, England
[2] Univ Witwatersrand, Sch Publ Hlth, MRC Wits Rural Publ Hlth & Hlth Transit Res Unit, Johannesburg, South Africa
[3] Kings Coll London, Kings Ctr Global Hlth, London, England
[4] Stellenbosch Univ, Dept Global Hlth, Ctr Global Surg, Stellenbosch, South Africa
[5] Harvard TH Chan Sch Publ Hlth, Dept Global Hlth & Populat, Boston, MA USA
[6] Northwestern Univ, Feinberg Sch Med, Med Social Sci, Chicago, IL 60611 USA
[7] RWI Leibniz Inst Econ Res, Berlin Off, Berlin, Germany
[8] Univ Goettingen, Dept Econ, Gottingen, Germany
[9] Univ Goettingen, Ctr Modern Indian Studies, Gottingen, Germany
[10] Harvard Med Sch, Massachusetts Gen Hosp, Diabet Unit, Boston, MA 02115 USA
[11] Nazarbayev Univ, Univ Med Ctr, Natl Lab Astana, Nur Sultan, Kazakhstan
[12] Nazarbayev Univ, Ctr Life Sci, Lab Epidemiol & Publ Hlth, Natl Lab Astana, Nur Sultan, Kazakhstan
[13] Natl Ctr Dis Control & Publ Hlth, Noncommunicable Dis Dept, Tbilisi, Georgia
[14] St Francis Hosp, Kampala, Uganda
[15] Amer Univ Beirut, Dept Epidemiol & Populat Hlth, Fac Hlth Sci, Beirut, Lebanon
[16] Caribbean Publ Hlth Agcy, Port Of Spain, Trinidad Tobago
[17] Natl Ctr Publ Hlth, Ulaanbaatar, Mongolia
[18] Kenya Minist Hlth, Div Noncommunicable Dis, Nairobi, Kenya
[19] Minist Hlth, Zanzibar, Tanzania
[20] Caja Costarricense Seguro Social, Epidemiol Off & Surveillance, San Jose, Costa Rica
[21] Natl Inst Med Res, Dar Es Salaam, Tanzania
[22] Univ Nacl Timor Lorosae, Postgrad Program Off, Dili, Timor-Leste
[23] Univ Porto, Dept Ciencias Saude Publ & Forenses & Educ Med, Fac Med, Porto, Portugal
[24] Stellenbosch Univ, Fac Med & Hlth Sci, Stellenbosch, South Africa
[25] Univ Kathmandu, Inst Med, Tribuvan, Nepal
[26] Amer Univ Beirut, Fac Agr & Food Sci, Beirut, Lebanon
[27] Univ Abomey Calavi, Lab Epidemiol Chron & Neurol Dis, Fac Hlth Sci, Cotonou, Benin
[28] Makerere Univ, Sch Publ Hlth, Dept Epidemiol & Biostat, Kampala, Uganda
[29] Minist Hlth, Hlth Res & Epidemiol Unit, Thimphu, Bhutan
[30] Univ Ctr Primary Care & Hlth Serv Unisante, Lausanne, Switzerland
[31] Minist Hlth, Victoria, Seychelles
[32] Inst Africain Sante Publ IASP, Ouagadougou, Burkina Faso
[33] Abt Associates Inc, Monitoring Evaluat & Operat Res Project, Kathmandu, Nepal
[34] Govt Union Comoros, Minist Hlth Solidar Social Cohes & Gender, Moroni, Comoros
[35] Fred Hollows Fdn New Zealand, Auckland, New Zealand
[36] Boston Univ, Sch Publ Hlth, Dept Global Hlth, Boston, MA USA
[37] Heidelberg Univ, Heidelberg Inst Global Hlth HIGH, Heidelberg, Germany
[38] Africa Hlth Res Inst AHRI, Somkhele, South Africa
[39] Africa Hlth Res Inst AHRI, Durban, South Africa
[40] Harvard Univ, Harvard Med Sch, Dept Global Hlth & Social Med, Boston, MA 02115 USA
[41] Stanford Univ, Dept Med, Div Primary Care & Populat Hlth, Palo Alto, CA 94304 USA
[42] Harvard Med Sch, Brigham & Womens Hosp, Div Infect Dis, Boston, MA 02115 USA
[43] Massachusetts Gen Hosp, Med Practice Evaluat Ctr, Boston, MA 02114 USA
[44] Publ Hlth Fdn India, Delhi, India
[45] Univ Edinburgh, Global Acad Agr & Food Secur, Edinburgh, Midlothian, Scotland
基金
美国国家卫生研究院;
关键词
SUB-SAHARAN AFRICA; HEALTH SYSTEMS;
D O I
10.1371/journal.pmed.1003268
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
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. Author summary Why was the study done? Diseases such as high blood pressure and diabetes are becoming increasingly common in low- and middle-income countries (LMICs). Treatment for these conditions is simple and cheap. However, without treatment, sufferers are at high risk of adverse consequences, such as heart attacks and strokes. It is important therefore to be able to measure whether patients who need treatment are getting it. Currently, LMICs' progress towards being able to treat patients with hypertension and diabetes is measured using proxies, for example, whether policies, guidelines, funding, structures, or human resources are in place. What did the researchers find? We measured whether 187,552 people with hypertension living in 43 LMICs and 40,795 people with diabetes living in 28 LMICs had their high blood pressure or diabetes treated well; i.e., they had these conditions diagnosed, treated, or controlled. We found that most proxy measures were not reflective of whether patients had their condition treated well. What do these findings mean? To judge countries' progress towards ability to treat hypertension and diabetes requires directly assessing whether people with these diseases are getting the treatment that they need. The main limitation of the study was that a one-time measurement of blood pressure or blood glucose was used to define whether participants had high blood pressure or diabetes. To make a concrete clinical diagnosis requires more detailed investigation.
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页数:25
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