{"subscriber":false,"subscribedOffers":{}} Service Readiness For Noncommunicable Diseases Was Low In Five Countries In 2013–15 | Health Affairs

Research Article

Global Health Policy

Service Readiness For Noncommunicable Diseases Was Low In Five Countries In 2013–15

Affiliations
  1. Corrina Moucheraud ([email protected]) is an assistant professor in the Department of Health Policy and Management, Jonathan and Karin Fielding School of Public Health, at the University of California Los Angeles.
PUBLISHED:Free Accesshttps://doi.org/10.1377/hlthaff.2018.0151

Abstract

The growing burden of noncommunicable diseases (NCDs) may pose challenges for resource-limited health systems. This study used standardized, nationally representative data from Service Provision Assessments conducted in 2013–15 and the Service Availability and Readiness Assessment methodology to examine NCD service availability and readiness in Bangladesh, Haiti, Malawi, Nepal, and Tanzania. Both service availability and readiness were found to be very low: Very few facilities were fully “ready” to provide any one NCD service. Shortages of trained health workers and essential medicines were critical limitations to readiness. Rural and free facilities had lower availability and readiness, which may present access barriers. Policy makers should draw on decades of experience with global health initiatives to close these service gaps through the training of health workers on NCD screening and treatment, engaging the private sector on NCDs, and ensuring access to NCD medicines. Such efforts must be attentive to distributional equity and the multiple dimensions of care quality.

TOPICS

It is estimated that over 70 percent of all deaths worldwide are caused by noncommunicable diseases (NCDs)1—chiefly cardiovascular diseases, cancers, chronic respiratory diseases, and diabetes. These deaths, many of which are classified as premature because they occur before age seventy, disproportionately occur in low- and middle-income countries.2 NCDs also cause substantial economic burden by way of direct illness-related costs and indirect costs due to lost productivity.3

Policy makers at the global and national levels have demonstrated their commitment to addressing NCDs. For example, in 2013 the World Health Assembly endorsed the World Health Organization’s Global Action Plan for the Prevention and Control of NCDs 2013–2020, which provides specific policy and program recommendations for addressing the rising NCD burden.4 But NCD diagnosis and treatment require a well-functioning health system, which may be challenging for the low- and middle-income countries that bear the greatest NCD-related burden.5 Health system constraints on delivering NCD care have been recognized as a key global challenge and a priority area for investment and improvement.6,7 It is therefore essential to understand service availability and readiness for delivering NCD care in high-burden, system-constrained countries to identify areas for further investment and opportunities for service strengthening.

Recent analyses have identified low NCD service availability in low- and middle-income countries, based on proxy measures composed of general inputs (such as numbers of health workers and hospital beds)8 and single-country studies of NCD screening and treatment services.915 However, the literature has so far lacked an empirically driven generalizable analysis of NCD service availability and quality in low-resource settings. This study used nationally representative, standardized, comparable, and publicly available data to analyze the availability and readiness of selected NCD services (diagnosis and management of diabetes, cardiovascular disease, and chronic respiratory disease) in five low- and lower-middle-income countries: Bangladesh, Haiti, Malawi, Nepal, and Tanzania. (These diseases were selected because they are the focus of new NCD-specific questions on standardized service provision questionnaires implemented by the World Health Organization, described in more detail below.) The study also assessed the degree of access to these services, with a particular focus on geographic distribution (accessibility) and differences between facilities that offer services for free versus those that charge a fee (affordability).

Study Data And Methods

Data Source

This study used data from Service Provision Assessments (SPAs), which are surveys administered by the Demographic and Health Surveys Program.16 SPAs entail the collection of health facility data about service delivery inputs, outputs, and quality. The current survey tool includes indicators that correspond to the Service Availability and Readiness Assessment methodology of the World Health Organization and the US Agency for International Development.17 SPA data and this methodology can be used to generate valid, reliable, and standardized estimates of access to specific types of health services (availability) and inputs that are critical for the provision of high-quality health services (readiness).

SPA surveys include standardized facility inventory and health provider interview instruments. For the facility inventory, interviewers speak to the most knowledgeable person available about service readiness—namely, the availability of amenities, equipment, supplies, laboratory tests, and medicines—both generally and for specific services including diabetes, cardiovascular disease, and chronic respiratory disease. Additionally, health provider interviews are conducted with a random sample of approximately eight clinical personnel per facility. (See online appendix 1 for further details on the data sets.)18

This analysis included all publicly available cross-sectional Demographic and Health Surveys Program SPA data sets that included questions about NCDs: those for Bangladesh in 2014, Haiti in 2013, Malawi in 2013–14, Nepal in 2015, and Tanzania in 2014–15.1923

Study Setting

Exhibit 1 presents background information on the study countries and the SPA data sets. The low- and lower-middle-income countries are in three geographic regions (Latin America and the Caribbean, South Asia, and sub-Saharan Africa).24 Haiti is the smallest country studied, with a population of approximately 11 million people, and Bangladesh is the largest, with over 164 million people.25 Most of the countries have majority rural-dwelling populations (with the exception of Haiti, where over 60 percent of the population lives in urban areas).25 All of the countries have high prevalences of NCDs. According to recent surveillance and survey data, over 25 percent of adults in these countries have hypertension (except in Bangladesh, where the prevalence is only approximately 18 percent), and 4–10 percent have diabetes.2632

Exhibit 1 Selected characteristics of the study countries

CharacteristicBangladeshHaitiMalawiNepalTanzania
Overview
Geographic regionaSouth AsiaLatin America and the CaribbeanSub-Saharan AfricaSouth AsiaSub-Saharan Africa
Income classificationaLower middleLowLowLowLow
Population in 2017b164,669,75110,981,22918,622,10429,304,99857,310,019
GDP per capita in 2011 PPPc$3,319$1,654$1,084$2,298$2,583
Poverty headcount ratio at national poverty linec24.3% (2016)58.5% (2012)50.7% (2010)25.2% (2010)28.2% (2011)
Urban populationd35.860.916.619.433.0
Health indicators
Life expectancy at birth in 2015 (years)b73.063.763.870.866.7
Prevalence of NCDs among adults
Hypertensionel17.9%34.4%32.9%25.7%25.9%
 Ever measured previouslyf,jl67.1m25.357.331.6
Diabetesjp5.55.65.63.69.1
 Ever measured previouslyjl,o17.0m1.910.88.9
Data-set information
Year(s) of SPA datapu201420132013–1420152014–15
Surveyed facilities included in analysis1,3378539349341,147
Level
 Primary95.8%98.5%97.1%90.2%97.6%
 Secondary or tertiary4.21.52.99.82.4
Location
 Urban7.237.730.913.626.9
 Rural92.862.369.186.473.1%
Managing authority
 Public93.838.048.292.572.0
 Private6.262.051.87.528.0

SOURCE Author’s compilation. Except where noted, complete sources are in online appendix 2 (see note 18 in text). NOTES GDP is gross domestic product. PPP is purchasing power parity. NCD is noncommunicable disease. SPA is Service Provision Assessment.

aWorld Bank Country and Lending Groups (note 24 in text).

bUN Population Division, World population prospects: 2017 revision (note 25 in text).

cPercent of population at or below the poverty line in a particular country. World Bank, World Development Indicators, 2017.

dUN Population Division, World Urbanization Prospects, 2014 revision.

eSystolic blood pressure 140 or diastolic blood pressure 90mmHg, or on medication for hypertension.

fBangladesh Society of Medicine et al., Non-Communicable Disease Risk Factor Survey Bangladesh 2010.

gMalawi Ministry of Health et al., Malawi National STEPS Survey for Chronic Non-Communicable Diseases and Their Risk Factors (note 26 in text).

hTanzania Ministry of Health and Social Welfare et al., Tanzania STEPS Survey report (note 27 in text).

iNepal Ministry of Health and Population et al., Non communicable diseases risk factors (note 28 in text).

jZaman MM et al., Blood glucose and cholesterol levels in adult population of Bangladesh (note 29 in text).

kJiao J et al., Hypertension prevalence (note 30 in text).

lPolsinelli V et al., Hypertension and aging in rural Haiti (note 31 in text).

mNot available.

nPlasma venous value 126mg/dl, or on medication for diabetes.

oPierce L et al., Hypertension prevalence and knowledge assessment in rural Haiti (note 32 in text).

pOgurtsova K et al., IDF Diabetes Atlas.

qMalawi Ministry of Health et al., Malawi Service Provision Assessment 2013–14 (note 21 in text).

rInstitut Haïtien de l’Enfance et al., Évaluation de prestation des services de soins de santé (note 20 in text).

sTanzania Ministry of Health and Social Welfare et al., Tanzania Service Provision Assessment Survey 2014–2015 (note 23 in text).

tNational Institute of Population Research and Training et al., Bangladesh Health Facility Survey 2014 (note 19 in text).

uNepal Ministry of Health et al., Nepal Health Facility Survey 2015 (note 22 in text).

The SPA data sets for these countries contain results from assessments of approximately 800–1,300 health facilities, most of which are at the primary care level and in rural areas. The data sets include both public and private health facilities, but the split between public and private sectors varied substantially across countries.

In all of the study countries, national health policies have specified that NCD screening and treatment services should be provided across the health system, including at the primary care level.3337

Dependent Variables

Service availability and readiness were defined according to the Service Availability and Readiness Assessment approach.38 In that approach, availability is defined as the proportion of facilities offering each service and is presented as a dichotomous variable based on a yes/no question answered by the survey respondent: “Providers in the facility diagnose, prescribe treatment for, or manage patients with [condition X].”

Readiness is defined as whether specific people or items were available on the day of the survey: staff (at least one staff member trained in the diagnosis and management of the specific disease during the preceding two years), guidelines (national guidelines, visible in the service area), equipment (for disease-specific diagnosis or care, available and functional in the service area), diagnostics (on-site test capability, functional equipment, and supplies such as reagents), and medicines or commodities (in stock). A facility was classified as “ready” to provide services for a specific NCD if all of these components were present. Additionally, a readiness score was calculated, with one point for each of the following: guidelines, at least one provider, each piece of equipment, each diagnostic supply, and each medicine or commodity. Scores are reported only for those facilities with complete data on all score parameters. For ease of interpretation, these scores were standardized to a 0–100 scale. (See appendix 3 for additional details on all availability and readiness metrics.)18 A summary NCD service readiness score was also created by summing all of the disease-specific scores, with 0 assigned for facilities that did not have NCD services available, and standardizing the scores to a 0–100 scale.

Independent Variables

This analysis used Roy Penchansky and J. William Thomas’s “access framework” to analyze variability in NCD service availability and readiness.39 This framework posits that a patient’s ability to access the health care system is shaped by five factors: acceptability (whether services match the patient’s values and norms), accessibility (geographic and physical location), accommodation (presence of services when they are needed), affordability, and availability. Other scholars have added factors, including appropriateness, architecture (organizational structures), adequacy, and awareness.4042 For this analysis, the factors of accessibility and affordability were selected as key independent variables because of their correspondence with data collected in the SPA; the robust evidence base indicating their role in shaping service use;4347 and their salience for these lower-income, largely rural populations. Accessibility was operationalized as whether the facility was located in an urban or a rural area, as was already done in all of the data sets except the one for Nepal. In that case, this classification was made based on each facility’s GPS location and definitions of urban areas in the Global Rural-Urban Mapping Project Urban Extents data set.48Affordability was represented by a dichotomous variable for whether the facility offered services for free. Facilities that charged a flat fee and those that charged for a health card, consultation, medications, or registration were considered not free.

Other covariates included the level of care offered at the facility (primary versus secondary or higher), which was classified based on health system information in the SPA report, patient volume (the number of outpatient visits during the last complete month, except in the case of Nepal—where the recall period was the last complete year), and location based on geospatial data.

Analysis

All facilities in each country’s SPA data set were included, except those that provided only inpatient services. Also, in Nepal stand-alone HIV testing and counseling sites were excluded (following methodology in that country’s SPA report section on NCD services).

Differences between proportions were tested for statistical difference using chi-square tests. Multivariable analyses were conducted, using ordinary least squares estimation for the continuous NCD readiness score and logistic regression for binary availability (yes/no) variables. Robust standard errors were used for all multivariable models, and district fixed effects were included. Survey sample weights at the facility level were used for all descriptive statistics. Analyses were conducted using Stata, version 14.2.

Limitations

The study had several limitations. First, only three NCDs were measured in these five countries’ surveys, and availability of care for other NCDs may differ. Notably, despite their high prevalence, mental and neurological conditions were not included.

Second, although the five nationally representative surveys included here represent an advance in the ability to analyze NCD services in low- and middle-income countries, the results are not generalizable to all such settings.

Third, operationalizing affordability as the presence of free care is a coarse measure. It overlooks important variations across people’s experiences and opinions. However, this definition was as detailed as the SPA data allowed.

Fourth, although the Service Availability and Readiness Assessment methodology includes many important inputs to service delivery, it might not be comprehensive, and its cross-national standardized metric might not capture locally relevant differences, such as varying treatment guidelines. Additionally, SPA surveys use a cross-sectional design, which might not be an accurate reflection of usual service readiness. For example, high availability of supplies could indicate that these supplies are not being used.

Lastly, although several important characteristics were included in the multivariable models, it is possible that salient variables remained unobserved or omitted.

Study Results

In all but one country, most surveyed facilities offered diagnosis, management, or both of at least one noncommunicable disease (exhibit 2). In Bangladesh, fewer than 20 percent of facilities offered any NCD care. Among the three study NCDs (diabetes, cardiovascular disease, and chronic respiratory disease), diabetes care was the least prevalent in all of the countries.

Exhibit 2 Proportion of facilities that diagnose noncommunicable diseases (NCDs), manage them, or both in each study country, by NCD, and types and locations of facilities with comprehensive NCD services available (all three services)

BangladeshHaitiMalawiNepalTanzania
Diagnose, manage, or both:
At least one of the study’s NCDsa18.7%93.8%90.3%95.0%68.3%
Diabetes15.784.747.221.252.6
Cardiovascular disease16.492.787.373.465.2
Chronic respiratory diseasea89.076.094.361.6
All of the study’s NCDsa13.479.941.420.748.2
Comprehensive service availability, by level
Primary10.7%80.0%37.7%12.6%47.3%
Secondary or tertiary74.992.396.395.285.9
Comprehensive service availability, by location
Urban49.7%83.5%61.2%49.6%57.3%
Rural10.578.232.616.244.9

SOURCE Author’s analysis of data from the Service Provision Assessment surveys. NOTES Years of SPA data and numbers of facilities for the countries are shown in exhibit 1. For p values for difference, based on chi-square test, all differences in level and location were significant (p<0.001) except for level in Haiti (p=0.27) and location in Haiti (p=0.06).

aBangladesh collected data on only two of the study’s three NCDs.

There was substantial variation in the share of facilities having comprehensive NCD service availability (that is, care was available for all of the study NCDs), from below 25 percent in the Asian countries (Bangladesh and Nepal) to almost 80 percent in Haiti (exhibit 2). Across the study countries, comprehensive NCD service availability was lower at primary care facilities and at facilities in rural areas. And in all of the countries except Haiti, these differences were large and highly significant.

Fewer than five of the facilities in each country were classified as fully ready to provide care for each of the three NCDs (see appendix 4).18 Only one facility (in Tanzania) was fully ready to provide care for chronic respiratory disease.

Among facilities that offered each type of NCD service, the average readiness score was generally highest for diabetes care (45–50 points on a 0–100 scale), and next-highest for cardiovascular disease (32–50 points) (exhibit 3). Chronic respiratory disease had the lowest score (23–36 points). Among all facilities, with those without each NCD service available receiving a readiness score of 0, readiness was highest for cardiovascular disease and lowest for diabetes. This reflects the overall higher availability of the former and low availability of the latter.

Exhibit 3 Facility readiness by study country and type of care for noncommunicable diseases

Among facilities with each service available
Among all facilities
DiabetesCardiovascular diseaseChronic respiratory diseaseDiabetesCardiovascular diseaseChronic respiratory disease
Bangladesh
Average overall readiness score44.533.6a2.45.2a
Meeting readiness in:
 Staff and training24.3%16.1%a12.7%9.4%a
 Guidelines20.018.5a20.018.5a
 Equipment95.196.4a95.896.8a
 Diagnostics77.3ba76.8ba
 Medicines and commodities14.430.3a3.640.2a
Haiti
Average overall readiness score46.449.623.037.746.120.5
Meeting readiness in:
 Staff and training29.2%33.1%29.7%27.3%32.9%28.2%
 Guidelines4.46.27.14.46.27.1
 Equipment97.999.897.497.999.697.5
 Diagnostics70.0bb66.1bb
 Medicines and commodities59.684.357.253.784.556.2
Malawi
Average overall readiness score48.141.135.721.435.927.1
Meeting readiness in:
 Staff and training18.0%15.3%13.2%11.0%14.1%11.8%
 Guidelines25.530.031.725.530.031.7
 Equipment95.698.592.795.798.492.5
 Diagnostics53.7bb30.4bb
 Medicines and commodities91.667.597.083.567.697.1
Nepal
Average overall readiness score49.031.622.57.023.121.2
Meeting readiness in:
 Staff and training3.8%2.0%9.2%1.4%1.6%8.7%
 Guidelines5.83.07.35.83.07.3
 Equipment98.199.799.099.599.599.0
 Diagnostics81.4bb51.8bb
 Medicines and commodities64.428.082.031.625.182.2
Tanzania
Average overall readiness score47.135.328.619.322.817.5
Meeting readiness in:
 Staff and training11.9%10.8%9.3%7.7%7.9%6.5%
 Guidelines20.422.022.420.422.022.4
 Equipment96.697.893.595.397.793.8
 Diagnostics78.8bb64.5bb
 Medicines and commodities34.140.287.022.741.988.7

SOURCE Author’s analysis of data from the Service Provision Assessment surveys. NOTE Readiness score and readiness in specific areas are explained in the text.

aBangladesh collected data on only two of the study’s three NCDs.

bRelevant only for diabetes.

In Malawi, Nepal, and Tanzania, the presence of at least one recently trained health worker was the lowest of the readiness components across all three NCDs (exhibit 3): This level of staffing was found at only approximately 13–18 percent of facilities in Malawi, 2–10 percent in Nepal, and 9–12 percent in Tanzania. National guidelines for NCD diagnosis or management were present at fewer than one-third of facilities in any country for any of the three diseases. Equipment was widely available (over 90 percent of facilities that offered each type of NCD service met the readiness criteria), and diabetes diagnostics were relatively common (over 70 percent of such facilities in all countries except Malawi met the criteria).

The availability of essential NCD medicines varied widely across diseases and countries (exhibit 3). In Bangladesh and Tanzania, fewer than 40 percent of facilities had at least one diabetes or CVD medicine, whereas in Malawi, at least one diabetes medicine was found in over 90 percent of facilities. (Appendix 5 contains details on the availability of specific medicines.)18

In Haiti, Malawi, and Tanzania, urban facilities were more likely to have comprehensive NCD services available, compared to rural facilities (even after service volume, care level, and district were controlled for), and had higher NCD service readiness scores (exhibit 4). In Haiti and Malawi, these differences were substantial and significant: The odds of comprehensive NCD service availability at urban facilities were approximately twice those at rural facilities, and service availability scores were on average approximately 6–7 percentage points higher at urban facilities. The Asian countries—Bangladesh and Nepal—did not exhibit significant urban-rural differences in NCD service availability or readiness.

Exhibit 4 Availability of comprehensive services for noncommunicable diseases (NCDs) and readiness in facilities in the study countries

BangladeshHaitiMalawiNepalTanzania
Comprehensive NCD services availablea (odds ratios)
Urban (ref: rural)1.032.02**1.89**0.941.19*
 Standard error0.270.580.520.270.13
Free care (ref: for-fee care)0.22****0.11****0.43****0.29****0.54*
 Standard error0.070.040.060.080.18
Overall readiness scoreb (percentage-point difference)
Urban (ref: rural)0.726.09****7.07**0.634.69*
 Standard error2.252.223.461.482.52
Free care (ref: for-fee care)−19.16****−20.63****−8.70****−8.93****−13.04****
 Standard error2.851.451.191.802.52

SOURCE Author’s analysis of data from the Service Provision Assessment surveys. NOTE Covariates include patient volume (total outpatient visits in the last complete month [or year, for Nepal]), primary care facility (yes or no), and district-level fixed effects.

aAll of the study’s NCDs can be diagnosed, managed, or both.

bReadiness score is explained in the text.

*p<0.1

**p<0.05

****p<0.001

Significant differences were seen between free facilities and those that charged a fee (exhibit 4). Facilities offering free care were much less likely to have comprehensive NCD services available (adjusted odds ratios: 0.11–0.43)—except in Tanzania, where this difference was less strong and not significant. The NCD service readiness scores were also much lower at free facilities compared to for-fee facilities, by 20 percentage points in Bangladesh and Haiti and 9–13 percentage points in Malawi, Nepal, and Tanzania.

Discussion

Like many low- and middle-income countries, the countries in this study are experiencing a rising burden of noncommunicable diseases, and this study indicates that these countries’ health systems are not well equipped to address this burden.

Availability of services is far from universal: In all countries except Haiti, fewer than half of surveyed facilities offered diagnosis, management, or both of the three NCDs. Service readiness—that is, the availability of requisite care inputs—was extremely weak, particularly because of shortages of trained health workers; guidelines; and, in some countries, essential medicines. Free and rural facilities in all countries had low NCD service availability and readiness. This finding is particularly salient because it may indicate the presence of access barriers for vulnerable patients. These results are consistent with findings from earlier descriptions of NCD services in these countries.14,4954

Although all of the study countries have government policies to provide NCD care throughout the health system, these results suggest that there may be challenges in policy implementation. In some countries, such NCD-related policies are relatively recent, so low service availability may reflect a ramp-up implementation period. However, a recent multicountry analysis using SPA data found similarly low service availability and readiness for a broad indicator of primary care readiness, including infrastructure and inputs (medicines, laboratory services, and equipment) for managing prevalent communicable diseases and providing reproductive/maternal health care.55 This suggests that these limitations might not be due to recent policy changes or in-progress implementation.

Policy Implications

These findings suggest opportunities for improving service availability and readiness for diagnosing and managing noncommunicable diseases. First, it is important to increase the capacity of the workforce to manage NCDs. This might be accomplished through expanding training opportunities for clinicians or shifting tasks to other providers—although recent systematic reviews have found weak evidence to support the latter approach.56,57 There are limits to what trained providers can accomplish, however, if other inputs are lacking.

Second, global access to medicines and universal health coverage initiatives have important implications for NCD care.58 Many NCD treatments are on essential medicines lists but remain expensive and inaccessible in many countries.59 Policies to ensure availability and affordability—including securing adequate financing; monitoring access (availability, use, and prices); improving efficiency and quality in medicine selection, procurement, and use through regulatory mechanisms and clinical guidelines; and strengthening supply chains at global and national levels—will be essential to ensure NCD care within universal health coverage.7,60

Third, policy makers should seek ways to constructively engage the private sector in addressing NCDs.7,61,62 Examples from other areas—such as the Affordable Medicines Facility–malaria,63 the GAVI Alliance for vaccine-preventable diseases,64 or approaches to delivering sexual and reproductive health services65—may offer insights across a range of policy entry points including medicines’ procurement, regulation, and supply; financing and marketing of services; and contracting with and training of providers.

There are two important caveats to these policy recommendations. First, the ingredients of service readiness—supplies, infrastructure, medicines, and trained personnel—do not necessarily equate to high-quality care. A recent analysis of SPA data found that such inputs are weakly correlated with care quality,66 which reinforces the need to focus on metrics beyond easy-to-count health service inputs or utilization rates.67 It is thus imperative for policy makers and clinical communities to develop and implement robust approaches to measuring quality of care,68 and these should be attentive to the chronic life-course trajectory of patients managing NCDs.

Equity and access should be central to policy and system changes intended to strengthen the delivery of NCD services.

Second, the vast and growing burden of NCDs has bolstered interest in broad-based health system strengthening.69 The results of this study highlight existing access barriers to NCD care. Equity and access should therefore be central to policy and system changes intended to strengthen the delivery of NCD services. For example, in closing the observed gap of health workers trained in NCDs, attention should be paid to how these trained workers are distributed both geographically and across health system levels and sectors (private and public).

Conclusion

There is global and national commitment to addressing the burden of noncommunicable diseases, but services remain inadequate in these low- and middle-income countries. This analysis is the first to present cross-national findings about standardized service availability and readiness for NCDs in selected low- and middle-income countries. The lack of methodologies to assess NCD care has previously been noted,70 so these data offer an important new resource. Analyses such as this one can inform decisions about allocating resources to where they are most needed and suggest policy and program priorities for countries facing a substantial noncommunicable disease burden.

ACKNOWLEDGMENTS

The author thanks Veronika Wirtz and James Macinko for their valuable comments on previous versions of this article.

NOTES

  • 1 Wang H, Naghavi M, Allen C, Barber RM, Bhutta ZA, Carter Aet al. Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388(10053):1459–544. Crossref, MedlineGoogle Scholar
  • 2 World Health Organization. Noncommunicable diseases: key facts [Internet]. Geneva: WHO; 2018 Jun 1 [cited 2018 Jun 5]. Available from: http://www.who.int/mediacentre/factsheets/fs355/en/ Google Scholar
  • 3 Bloom DE, Cafiero ET, Jané-Llopis E, Abrahams-Gessel S, Bloom LR, Fathima Set al. The global economic burden of non-communicable diseases [Internet]. Geneva: World Economic Forum; 2011 Sep [cited 2018 Jun 5]. Available from: http://www3.weforum.org/docs/WEF_Harvard_HE_GlobalEconomicBurdenNonCommunicableDiseases_2011.pdf Google Scholar
  • 4 World Health Organization. Global action plan for the prevention and control of noncommunicable diseases 2013–2020 [Internet]. Geneva: WHO; c 2013 [cited 2018 Jun 26]. Available from: http://apps.who.int/iris/bitstream/handle/10665/94384/9789241506236_eng.pdf Google Scholar
  • 5 Maher D, Harries AD, Zachariah R, Enarson D. A global framework for action to improve the primary care response to chronic non-communicable diseases: a solution to a neglected problem. BMC Public Health. 2009;9:355. Crossref, MedlineGoogle Scholar
  • 6 Daar AS, Singer PA, Persad DL, Pramming SK, Matthews DR, Beaglehole Ret al. Grand challenges in chronic non-communicable diseases. Nature. 2007;450(7169):494–6. Crossref, MedlineGoogle Scholar
  • 7 Hogerzeil HV, Liberman J, Wirtz VJ, Kishore SP, Selvaraj S, Kiddell-Monroe Ret al. Promotion of access to essential medicines for non-communicable diseases: practical implications of the UN political declaration. Lancet. 2013;381(9867):680–9. Crossref, MedlineGoogle Scholar
  • 8 Bollyky TJ, Templin T, Cohen M, Dieleman JL. Lower-income countries that face the most rapid shift in noncommunicable disease burden are also the least prepared. Health Aff (Millwood). 2017;36(11):1866–75. Go to the articleGoogle Scholar
  • 9 Elias MA, Pati MK, Aivalli P, Srinath B, Munegowda C, Shroff ZCet al. Preparedness for delivering non-communicable disease services in primary care: access to medicines for diabetes and hypertension in a district in south India. BMJ Glob Health. 2018;2(Suppl 3):e000519. Crossref, MedlineGoogle Scholar
  • 10 Gabert R, Ng M, Sogarwal R, Bryant M, Deepu RV, McNellan CRet al. Identifying gaps in the continuum of care for hypertension and diabetes in two Indian communities. BMC Health Serv Res. 2017;17(1):846. Crossref, MedlineGoogle Scholar
  • 11 Jacobs B, Hill P, Bigdeli M, Men C. Managing non-communicable diseases at health district level in Cambodia: a systems analysis and suggestions for improvement. BMC Health Serv Res. 2016;16(1):32. Crossref, MedlineGoogle Scholar
  • 12 Pakhare A, Kumar S, Goyal S, Joshi R. Assessment of primary care facilities for cardiovascular disease preparedness in Madhya Pradesh, India. BMC Health Serv Res. 2015;15(1):408. Crossref, MedlineGoogle Scholar
  • 13 Macinko J, Leventhal DGP, Lima-Costa MF. Primary care and the hypertension care continuum in Brazil. J Ambul Care Manage. 2018;41(1):34–46. Crossref, MedlineGoogle Scholar
  • 14 Bintabara D, Mpondo BCT. Preparedness of lower-level health facilities and the associated factors for the outpatient primary care of hypertension: evidence from Tanzanian national survey. PLoS One. 2018;13(2):e0192942. Crossref, MedlineGoogle Scholar
  • 15 Armstrong-Hough M, Kishore SP, Byakika S, Mutungi G, Nunez-Smith M, Schwartz JI. Disparities in availability of essential medicines to treat non-communicable diseases in Uganda: a Poisson analysis using the Service Availability and Readiness Assessment. PLoS One. 2018;13(2):e0192332. Crossref, MedlineGoogle Scholar
  • 16 Demographic and Health Surveys Program. SPA overview [Internet]. Rockville (MD): ICF; [cited 2018 Jun 5]. Available from: http://www.dhsprogram.com/What-We-Do/Survey-Types/SPA.cfm Google Scholar
  • 17 O’Neill K, Takane M, Sheffel A, Abou-Zahr C, Boerma T. Monitoring service delivery for universal health coverage: the Service Availability and Readiness Assessment. Bull World Health Organ. 2013;91(12):923–31. Crossref, MedlineGoogle Scholar
  • 18 To access the appendix, click on the Details tab of the article online.
  • 19 National Institute of Population Research and Training, Associates for Community and Population Research, ICF International. Bangladesh Health Facility Survey 2014: final report [Internet]. Rockville (MD): ICF International; 2016 Mar [cited 2018 Jun 5]. Available from: https://dhsprogram.com/pubs/pdf/SPA23/SPA23.pdf Google Scholar
  • 20 Institut Haïtien de l’Enfance, ICF International. Haïti: évaluation de prestation des services de soins de santé 2013 [Internet]. Rockville (MD): ICF International; 2014 Mar [cited 2018 Jun 5]. Available from: https://dhsprogram.com/pubs/pdf/SPA19/SPA19.pdf Google Scholar
  • 21 Malawi Ministry of Health, ICF International. Malawi Service Provision Assessment (SPA) 2013–14 [Internet]. Rockville (MD): ICF International; 2014 Nov [cited 2018 Jun 5]. Available from: https://dhsprogram.com/pubs/pdf/SPA20/SPA20%5BOct-7-2015%5D.pdf Google Scholar
  • 22 Nepal Ministry of Health, New ERA, NHSSP, ICF. Nepal Health Facility Survey 2015: final report [Internet]. Rockville (MD): ICF International; 2017 Jan [cited 2018 Jun 5]. Available from: https://dhsprogram.com/pubs/pdf/SPA24/SPA24.pdf Google Scholar
  • 23 Tanzania Ministry of Health and Social Welfare, Zanzibar Ministry of Health, Tanzania National Bureau of Statistics, Zanzibar Office of Chief Government Statistician, ICF International. Tanzania Service Provision Assessment Survey 2014–2015 [Internet]. Rockville (MD): ICF International; 2016 Feb [cited 2018 Jun 5]. Available from: https://dhsprogram.com/pubs/pdf/spa22/spa22.pdf Google Scholar
  • 24 World Bank. World Bank Country and Lending Groups [Internet]. Washington (DC): World Bank; [cited 2018 Jun 5]. Available from: http://data.worldbank.org/about/country-and-lending-groups Google Scholar
  • 25 United Nations Population Division. World population prospects. New York (NY): UN; 2017. Google Scholar
  • 26 Malawi Ministry of Health, World Health Organization. Malawi National STEPS Survey for Chronic Non-Communicable Diseases and Their Risk Factors: final report [Internet]. Geneva: WHO; 2010 Jun [cited 2018 Jun 20]. Available from: http://www.who.int/ncds/surveillance/steps/Malawi_2009_STEPS_Report.pdf Google Scholar
  • 27 Tanzania Ministry of Health and Social Welfare, National Institute for Medical Research, World Health Organization. Tanzania STEPS Survey report [Internet]. Geneva: WHO; c 2013 [cited 2018 Jun 20]. Available from: http://www.who.int/ncds/surveillance/steps/UR_Tanzania_2012_STEPS_Report.pdf Google Scholar
  • 28 Nepal Ministry of Health and Population, Nepal Health Research Council, World Health Organization. Non communicable diseases risk factors: STEPS survey Nepal 2013 [Internet]. Kathmandu: Nepal Health Research Council; [cited 2018 Jun 5]. Available from: http://www.searo.who.int/nepal/mediacentre/non_communicable_diseases_risk_factors_steps_survey_nepal_2013.pdf Google Scholar
  • 29 Zaman MM, Choudhury SR, Ahmed J, Talukder MH, Rahman AH. Blood glucose and cholesterol levels in adult population of Bangladesh: results from STEPS 2006 survey. Indian Heart J. 2016;68(1):52–6. Crossref, MedlineGoogle Scholar
  • 30 Jiao J, Jacobsen AA, Birch SA, Hecht EM, DeGennaro V. Hypertension prevalence: an examination of urban and rural Haiti. Lancet Glob Health. 2014;2(Spec Iss):S25. CrossrefGoogle Scholar
  • 31 Polsinelli VB, Satchidanand N, Singh R, Holmes D, Izzo JL. Hypertension and aging in rural Haiti: results from a preliminary survey. J Hum Hypertens. 2017;31(2):138–44. Crossref, MedlineGoogle Scholar
  • 32 Pierce L, Shannon A, Sonnenfeld J, Pearlmutter M, Previl H, Forrester JE. Hypertension prevalence and knowledge assessment in rural Haiti. Ethn Dis. 2014;24(2):213–9. MedlineGoogle Scholar
  • 33 Malawi Ministry of Health. Malawi Health Sector Strategic Plan 2011–2016 [Internet]. Lilongwe: The Ministry; [cited 2018 Jun 5]. Available from: http://www.nationalplanningcycles.org/sites/default/files/country_docs/Malawi/2_malawi_hssp_2011_-2016_final_document_1.pdf Google Scholar
  • 34 Tanzania Ministry of Health and Social Welfare. National Noncommunicable Disease Strategy July 2008–June 2018 [Internet]. Dar es Salaam: The Ministry; 2008 Oct 6 [cited 2018 Jun 5]. Available from: http://www.iccp-portal.org/system/files/plans/Tanzania_National%20%20NCD%20strategy_2008-1.pdf Google Scholar
  • 35 Haiti Ministère de la Santé Publique et de la Population. Représentation du système de santé: le paquet minimum de services (PMS) cadre conceptuel [Internet]. Port-au-Prince: MSPP; [cited 2018 Jun 5]. Available from: https://mspp.gouv.ht/site/downloads/Paquet_minimum_de_services_1er%20niveau.pdf Google Scholar
  • 36 Bangladesh Directorate General of Health Services, Ministry of Health and Family Welfare. 4th Health, Population, and Nutrition Sector Programme: operational plan, non-communicable disease control 2017–2022. Dhaka: The Directorate General; 2017. Google Scholar
  • 37 Government of Nepal. Multisectoral action plan for the prevention and control of non communicable diseases (2014–2020) [Internet]. Kathmandu: Government of Nepal; [cited 2018 Jun 5]. Available from: http://www.searo.who.int/nepal/mediacentre/ncd_multisectoral_action_plan.pdf Google Scholar
  • 38 Health Statistics and Information Systems. Service Availability and Readiness Assessment (SARA): an annual monitoring system for service delivery: reference manual: version 2.2 [Internet]. Geneva: World Health Organization; [revised 2015 Jul; cited 2018 Jun 5]. Available from: http://apps.who.int/iris/bitstream/handle/10665/149025/WHO_HIS_HSI_2014.5_eng.pdf Google Scholar
  • 39 Penchansky R, Thomas JW. The concept of access: definition and relationship to consumer satisfaction. Med Care. 1981;19(2):127–40. Crossref, MedlineGoogle Scholar
  • 40 Saurman E. Improving access: modifying Penchansky and Thomas’s theory of access. J Health Serv Res Policy. 2016;21(1):36–9. Crossref, MedlineGoogle Scholar
  • 41 Levesque JF, Harris MF, Russell G. Patient-centred access to health care: conceptualising access at the interface of health systems and populations. Int J Equity Health. 2013;12:18. Crossref, MedlineGoogle Scholar
  • 42 Frost LJ, Reich MR. Access: how do good health technologies get to poor people in poor countries? Cambridge (MA): Harvard Center for Population and Development Studies; 2008. Google Scholar
  • 43 Ettaro L, Songer TJ, Zhang P, Engelgau MM. Cost-of-illness studies in diabetes mellitus. Pharmacoeconomics. 2004;22(3):149–64. Crossref, MedlineGoogle Scholar
  • 44 Atun R, Davies JI, Gale EAM, Bärnighausen T, Beran D, Kengne APet al. Diabetes in sub-Saharan Africa: from clinical care to health policy. Lancet Diabetes Endocrinol. 2017;5(8):622–67. Crossref, MedlineGoogle Scholar
  • 45 Karra M, Fink G, Canning D. Facility distance and child mortality: a multi-country study of health facility access, service utilization, and child health outcomes. Int J Epidemiol. 2017;46(3):817–26. MedlineGoogle Scholar
  • 46 Simkhada B, Teijlingen ER, Porter M, Simkhada P. Factors affecting the utilization of antenatal care in developing countries: systematic review of the literature. J Adv Nurs. 2008;61(3):244–60. Crossref, MedlineGoogle Scholar
  • 47 Moyer CA, Mustafa A. Drivers and deterrents of facility delivery in sub-Saharan Africa: a systematic review. Reprod Health. 2013;10(1):40. Crossref, MedlineGoogle Scholar
  • 48 Center for International Earth Science Information Network, CUNY Institute for Demographic Research, International Food Policy Research Institute, World Bank, Centro Internacional de Agricultura Tropical. Global Rural-Urban Mapping Project, version 1 (GRUMPv1): urban extent polygons, revision 01 [Internet]. Palisades (NY): NASA Socioeconomic Data and Applications Center; [cited 2018 Jun 5]. Available from: http://sedac.ciesin.columbia.edu/data/set/grump-v1-urban-ext-polygons-rev01 Google Scholar
  • 49 Wood R, Viljoen V, Van Der Merwe L, Mash R. Quality of care for patients with non-communicable diseases in the Dedza District, Malawi. Afr J Prim Health Care Fam Med. 2015;7(1):1–8. CrossrefGoogle Scholar
  • 50 Leung C, Aris E, Mhalu A, Siril H, Christian B, Koda Het al. Preparedness of HIV care and treatment clinics for the management of concomitant non-communicable diseases: a cross-sectional survey. BMC Public Health. 2016;16(1):1002. Crossref, MedlineGoogle Scholar
  • 51 Peck R, Mghamba J, Vanobberghen F, Kavishe B, Rugarabamu V, Smeeth Let al. Preparedness of Tanzanian health facilities for outpatient primary care of hypertension and diabetes: a cross-sectional survey. Lancet Glob Health. 2014;2(5):e285–92. Crossref, MedlineGoogle Scholar
  • 52 Shrestha R, Ghale A, Chapagain BR, Gyawali M, Acharya T. Survey on the availability, price, and affordability of selected essential medicines for non-communicable diseases in community pharmacies of Kathmandu valley. SAGE Open Med. 2017;5:2050312117738691. CrossrefGoogle Scholar
  • 53 Mendis S, Fukino K, Cameron A, Laing R, Filipe A, Khatib Oet al. The availability and affordability of selected essential medicines for chronic diseases in six low- and middle-income countries. Bull World Health Organ. 2007;85(4):279–88. Crossref, MedlineGoogle Scholar
  • 54 Mannava P, Abdullah A, James C, Dodd R, Annear PL. Health systems and noncommunicable diseases in the Asia-Pacific region: a review of the published literature. Asia Pac J Public Health. 2015;27(2):NP1–19. Crossref, MedlineGoogle Scholar
  • 55 Leslie HH, Spiegelman D, Zhou X, Kruk ME. Service readiness of health facilities in Bangladesh, Haiti, Kenya, Malawi, Namibia, Nepal, Rwanda, Senegal, Uganda, and the United Republic of Tanzania. Bull World Health Organ. 2017;95(11):738–48. Crossref, MedlineGoogle Scholar
  • 56 Joshi R, Alim M, Kengne AP, Jan S, Maulik PK, Peiris Det al. Task shifting for non-communicable disease management in low and middle income countries—a systematic review. PLoS One. 2014;9(8):e103754. Crossref, MedlineGoogle Scholar
  • 57 Ogedegbe G, Gyamfi J, Plange-Rhule J, Surkis A, Rosenthal DM, Airhihenbuwa Cet al. Task shifting interventions for cardiovascular risk reduction in low-income and middle-income countries: a systematic review of randomised controlled trials. BMJ Open. 2014;4(10):e005983. Crossref, MedlineGoogle Scholar
  • 58 Wirtz VJ, Hogerzeil HV, Gray AL, Bigdeli M, de Joncheere CP, Ewen MAet al. Essential medicines for universal health coverage. Lancet. 2017;389(10067):403–76. Crossref, MedlineGoogle Scholar
  • 59 Ewen M, Zweekhorst M, Regeer B, Laing R. Baseline assessment of WHO’s target for both availability and affordability of essential medicines to treat non-communicable diseases. PLoS One. 2017;12(2):e0171284. Crossref, MedlineGoogle Scholar
  • 60 Abegunde D. Background paper: essential medicines for non-communicable diseases (NCDs) [Internet]. Geneva: World Health Organization; [cited 2018 Jun 5]. Available from: http://www.who.int/medicines/areas/policy/access_noncommunicable/EssentialMedicinesforNCDs.pdf Google Scholar
  • 61 Hancock C, Kingo L, Raynaud O. The private sector, international development, and NCDs. Global Health. 2011;7(1):23. Crossref, MedlineGoogle Scholar
  • 62 Mills A. Health care systems in low- and middle-income countries. N Engl J Med. 2014;370(6):552–7. Crossref, MedlineGoogle Scholar
  • 63 Tougher S, Ye Y, Amuasi JH, Kourgueni IA, Thomson R, Goodman Cet al. Effect of the Affordable Medicines Facility—malaria (AMFm) on the availability, price, and market share of quality-assured artemisinin-based combination therapies in seven countries: a before-and-after analysis of outlet survey data. Lancet. 2012;380(9857):1916–26. Crossref, MedlineGoogle Scholar
  • 64 Lee LA, Franzel L, Atwell J, Datta SD, Friberg IK, Goldie SJet al. The estimated mortality impact of vaccinations forecast to be administered during 2011–2020 in 73 countries supported by the GAVI Alliance. Vaccine. 2013;31(Suppl 2):B61–72. Crossref, MedlineGoogle Scholar
  • 65 Peters DH, Mirchandani GG, Hansen PM. Strategies for engaging the private sector in sexual and reproductive health: how effective are they? Health Policy Plan. 2004;19(Suppl 1):i5–i21. Crossref, MedlineGoogle Scholar
  • 66 Leslie HH, Sun Z, Kruk ME. Association between infrastructure and observed quality of care in 4 healthcare services: a cross-sectional study of 4,300 facilities in 8 countries. PLoS Med. 2017;14(12):e1002464. Crossref, MedlineGoogle Scholar
  • 67 Kruk ME, Larson E, Twum-Danso NA. Time for a quality revolution in global health. Lancet Glob Health. 2016;4(9):e594–6. Crossref, MedlineGoogle Scholar
  • 68 Akachi Y, Kruk ME. Quality of care: measuring a neglected driver of improved health. Bull World Health Organ. 2017;95(6):465–72. Crossref, MedlineGoogle Scholar
  • 69 Samb B, Desai N, Nishtar S, Mendis S, Bekedam H, Wright Aet al. Prevention and management of chronic disease: a litmus test for health-systems strengthening in low-income and middle-income countries. Lancet. 2010;376(9754):1785–97. Crossref, MedlineGoogle Scholar
  • 70 Robertson J, Macé C, Forte G, de Joncheere K, Beran D. Medicines availability for non-communicable diseases: the case for standardized monitoring. Global Health. 2015;11(1):18. Crossref, MedlineGoogle Scholar
Loading Comments...