Literature DB >> 35760540

Cost of primary care approaches for hypertension management and risk-based cardiovascular disease prevention in Bangladesh: a HEARTS costing tool application.

Muhammad Jami Husain1, Mohammad Sabbir Haider2, Renesa Tarannum3, Shamim Jubayer3, Mahfuzur Rahman Bhuiyan3, Deliana Kostova4, Andrew E Moran5, Sohel Reza Choudhury3.   

Abstract

OBJECTIVE: To estimate the costs of scaling up the HEARTS pilot project for hypertension management and risk-based cardiovascular disease (CVD) prevention at the full population level in the four subdistricts (upazilas) in Bangladesh. SETTINGS: Two intervention scenarios in subdistrict health complexes: hypertension management only, and risk-based integrated hypertension, diabetes, and cholesterol management.
DESIGN: Data obtained during July-August 2020 from subdistrict health complexes on the cost of medications, diagnostic materials, staff salaries and other programme components.
METHODS: Programme costs were assessed using the HEARTS costing tool, an Excel-based instrument to collect, track and evaluate the incremental annual costs of implementing the HEARTS programme from the health system perspective. PRIMARY AND SECONDARY OUTCOME MEASURES: Programme cost, provider time.
RESULTS: The total annual cost for the hypertension control programme was estimated at US$3.2 million, equivalent to US$2.8 per capita or US$8.9 per eligible patient. The largest cost share (US$1.35 million; 43%) was attributed to the cost of medications, followed by the cost of provider time to administer treatment (38%). The total annual cost of the risk-based integrated management programme was projected at US$14.4 million, entailing US$12.9 per capita or US$40.2 per eligible patient. The estimated annual costs per patient treated with medications for hypertension, diabetes and cholesterol were US$18, US$29 and US$37, respectively.
CONCLUSION: Expanding the HEARTS hypertension management and CVD prevention programme to provide services to the entire eligible population in the catchment area may face constraints in physician capacity. A task-sharing model involving shifting of select tasks from doctors to nurses and local community health workers would be essential for the eventual scale-up of primary care services to prevent CVD in Bangladesh. © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Entities:  

Keywords:  bangladesh; hearts hypertension management and cvd prevention program; program cost; scale-up of primary care services

Mesh:

Year:  2022        PMID: 35760540      PMCID: PMC9237880          DOI: 10.1136/bmjopen-2022-061467

Source DB:  PubMed          Journal:  BMJ Open        ISSN: 2044-6055            Impact factor:   3.006


This study uses the HEARTS costing tool to assess the expected cost of scaling up the programme to all eligible adults in the participating subdistricts (upazila). The study assesses two programme scenarios: a hypertension management programme and an integrated risk-based hypertension, diabetes and cholesterol management programme. The study disaggregates costs by function, identifying areas for efficiency improvements, such as task-sharing and bridging programme delivery from the upazila level to more localised community facilities. Due to lack of data at a local level, the cost projections rely on assumptions regarding population coverage, risk factor prevalence, primary care attendance rate, distribution of cardiovascular disease (CVD) risk among the population, distribution of patients by treatment protocols and frequency of patient visits by CVD risk. The study uses average medicine prices, unit costs of supplies, wages and provider time, which may vary across subdistricts depending on the procurement arrangements and operational efficiency.

Background

Hypertension is a major and preventable risk factor for cardiovascular disease (CVD). An estimated 1.13 billion people (1 in 4 men and 1 in 5 women) worldwide have hypertension.1 Among people with hypertension worldwide, fewer than one in five have it under control.1 High blood pressure (BP) is a leading global risk factor for premature death and disability, accounting for about 10 million (or 1 in 6) deaths worldwide each year.2 3 Uncontrolled hypertension significantly increases the risk of stroke, myocardial infarction, heart failure, dementia, renal failure, retinopathy and other diseases.4–7 Almost half of all CVD events are attributable to uncontrolled hypertension.2 3 Reducing the prevalence of hypertension is a standing global health objective.8–11 This objective complements the 2030 Sustainable Development Goal of reducing premature deaths from non-communicable diseases (NCDs) by 25%.12 Low-income and middle-income countries (LMICs), where two-thirds of all hypertension cases reside, are increasingly cognizant of the long-term benefits of addressing hypertension in their populations. However, implementing population-level measures targeting hypertension may present challenges for many LMICs where health systems have traditionally focused on infectious diseases and where the capacity for NCD care may be limited. Bangladesh is among lower-middle-income countries with a high burden of hypertension. In 2018, the prevalence of elevated BP (SBP and/or DBP ≥ 140/90 mm Hg) among adults in Bangladesh was 21%.13–15 According to the 2011 Bangladesh National Demographic and Health Survey, of 14.4 million hypertensive people (adults aged 35 and above), only 7.3 million (51%) were aware of their condition, 41% were treated and 18% had their BP levels under control.16 The burden of hypertension in Bangladesh is expected to grow alongside increased population ageing, rapid urbanisation with commensurate increases in sedentary lifestyle and processed food consumption, and other socioeconomic and lifestyle changes. However, only less than 5% of the health sector programme budget is allocated for NCDs control.16 This demonstrates the need for an effective, low-cost and efficient population-level approach in addressing hypertension. In 2016, WHO introduced the HEARTS technical package as a framework for CVD prevention at the primary care level.17 The HEARTS technical package consists of guidelines for implementing a primary care approach to CVD management, focusing on screening and management of CVD risk factors, including lifestyle modification and pharmacological treatment of metabolic risk factors such as hypertension, diabetes and hyperlipidaemia. In this paper, we describe the local budgetary impact of implementing the HEARTS programme at the population level for four subdistricts in Bangladesh, based on programme cost data obtained from a representative healthcare facility in each subdistrict. Although the initial focus of the programme in the four subdistricts is presently limited to hypertension control, scaling-up of the initiative may include screening, diagnosis and treatment of diabetes and high cholesterol. Understanding the cost drivers of CVD prevention approaches in the Bangladesh primary care system can support budgeting, procurement, evaluation and planning for scale-up.

Methods

Setting

In 2018, the Directorate General of Health Services and the National Heart Foundation of Bangladesh collaborated with Resolve to Save Lives (an initiative of Vital Strategies, a non-profit global public health organisation) to implement a pilot programme to strengthen the detection, treatment and follow-up management of hypertension in primary care. The programme was introduced in four health complexes in four subdistricts (upazilas) in the Sylhet district: Golapganj, Fenchuganj, Beanibazar and Bishwanath. In Bangladesh, hospitals and health facilities that are in the subdistrict (upazila) level or below are termed as primary health complexes. A typical upazila health complex is a 50-bed hospital with service coverage in the range of 100 000–400 000 population and plays a pivotal role in the provision of primary healthcare through a three-tier system consisting of the ward level, union level and upazila level. The upazila health complex performs a wide range of functions that includes prevention, promotion, treatment (inpatient, outpatient, limited diagnostic services), management, technical support, training, coordination and patient referral services. The outpatient service is usually staffed with five outpatient general practitioners including one resident medical officer, two medical officers and two medical assistants. An ‘NCD corner’ was set up in the outpatient with necessary logistics and personnel for screening and treatment. We project programme costs under two intervention scenarios: a hypertension-focused programme, and a risk-based integrated hypertension, diabetes and cholesterol management programme.

Patient and public involvement

Patients or the public were not involved in the design, conduct, reporting or dissemination plans of this research.

Hypertension management program

The HEARTS Technical Package for CVD prevention in primary care is organised around six modules: H–Healthy-lifestyle counselling, E—Evidence-based treatment protocols, A—Access to essential medicines and technology, R—Risk-based CVD management, T—Team-based Care and S—Systems for monitoring.18 Components of these modules are described in figure 1. In the four upazila primary care complexes in Bangladesh, programmed activities included: training of staff in following a standard treatment protocol, record keeping and reporting; ensuring adequate supply of necessary drugs; community outreach to increase awareness of the need for hypertension screening; introduction of patient monitoring tools and a monthly reporting system; and establishing a mechanism for patient referral from primary care to secondary care and tertiary care at MAG Osmani Medical College. The clinical management protocol for adults with hypertension (defined as systolic blood pressure (SBP)/diastolic blood pressure (DBP)≥140/90 mm Hg, or SBP/DBP≥130/80 mm Hg with comorbidity or high CVD-risk) entailed a first line of treatment with amlodipine 5 mg daily; a second line of treatment using amlodipine 5 mg plus losartan 50 mg daily; and a third line of treatment using amlodipine 5 mg plus losartan 50 mg plus hydrochlorothiazide 12.5 mg daily. Online supplemental appendix 1 depicts the hypertension treatment protocol. The prescribed medicines are typically obtained by public health facilities, generic, domestically manufactured and provided free of charge to patients. The national drug policy recommends that 70% of the public sector medicines be purchased from the state-owned Essential Drug Company Limited (EDCL), 25% from the Central Medical Stores Depot (CMSD) and 5% from local sources.19 20 In order to provide continuous care more sustainably and to reduce burden on physicians, a team-based care strategy was implemented. The healthcare providers were trained to acquire the necessary skills to provide brief interventions to record patients’ medical history, measuring BP, point-of-care testing to assess fasting blood glucose and cholesterol levels and urine dipstick for proteinuria, encourage behaviour change, assess CVD risk or initiate treatment protocol. The training sessions were conducted in one setup with a pool of selected doctors, nurses and community health workers (CHWs) trained with relevant modules. In this approach, CHWs were trained to provide counselling and some screening services along with the doctors and nurses. For the costing estimate, equal burden sharing in terms of provider time was assumed.
Figure 1

Cost components of the HEARTS programme in Bangladesh.

Cost components of the HEARTS programme in Bangladesh.

Risk-based integrated hypertension, diabetes and hyperlipidaemia management programme

To further strengthen CVD prevention, the HEARTS programme in Bangladesh also planned to integrate diabetes and hyperlipidaemia management in addition to hypertension management in primary care patients. The programme entails assessment of target population by total CVD risk estimation to categorise their risk for CVD. The risk stratification is based on WHO and International Society of Hypertension cardiovascular risk prediction charts and expressed as the probability of developing CVD over 10 years: low CVD risk (0 to <10%); medium CVD risk (10% to 20%) and high CVD risk (≥20%).21 The treatment protocol for patients with uncomplicated type two diabetes (defined as fasting plasma glucose ≥ 7.0 mmol/L or routine plasma glucose ≥ 11.1 mmol/L or HbA1C ≥ 6.5%) managed at the primary care level included metformin (500 mg), metformin (1000 mg), then metformin (1000 mg) and gliclazide (80 mg) as the first, second and third lines of treatments, respectively. The protocol is based on the WHO guidance on diagnosis, classification and management of diabetes (HEARTS - D), which is aligned with the WHO Package of Essential Noncommunicable Disease Interventions in Primary Healthcare.22 For managing plasma lipid levels (ie, high cholesterol), the use of statins as the primary therapy is widely recommended, however, the WHO is yet to offer any specific guidance.23 For costing, the local consultants and experts proposed a statin-based treatment protocol for hyperlipidaemia including simvastatin (10 mg) as first, atorvastatin (20 mg) as second and atorvastatin (40 mg) as the third line of treatment. Costs associated with implementing integrated hypertension, diabetes and hyperlipidaemia treatment protocols include provider time spent on estimating CVD risk using risk charts during an annual primary care visit; training in CVD risk estimation, in addition to time spent collecting patient history; medication costs and diagnostic test costs including provider (technician) time, complete blood count panel, fasting blood glucose and blood lipid panel tests.

HEARTS costing tool

Programme costs were assessed using the HEARTS costing tool, an Excel-based instrument to collect, track and evaluate the incremental annual cost of implementing the HEARTS programme from the health system perspective. The tool is organised by HEARTS modules.24 In July–August 2020, we obtained unit costs from four upazila complexes and used these to project annual resource needs for implementing the CVD prevention programme at the subdistrict population level. The researchers completed in-person collection of data from the four facilities on human resource and time costs, diagnostic prices, time-motion on laboratory diagnostics, market price of medicines and others. Figure 1 shows major cost categories within HEARTS modules. Once programme costs and other inputs such as population coverage, risk factor prevalence and planned provider numbers were entered into the costing tool, the cost calculations were allocated across different HEARTS modules. The cost elements in the Healthy-lifestyle counselling module ‘H’ included costs of training providers in lifestyle counselling and costs of community awareness programmes and training. Counselling is based on the Assess, Advise, Agree, Assist, Arrange model, which is an evidence-based approach for promoting healthy behavioural changes to prevent NCD risk factors.25 26 Total provider time to administer brief counselling was equal to the average time that the health provider spends to counsel a patient to change behaviour multiplied by the total number of patients who would receive counselling. The cost of total provider time was calculated as the total provider time, multiplied by the weighted average salary of the health providers who have been trained to provide counselling. The cost elements in module ‘E’ included provider time devoted to assessing patient history, conducting physical exams and diagnostic tests, and return visits. The costs of diagnostic tests (complete blood count panel, blood lipid panel, fasting blood glucose), medications (hypertension, diabetes and cholesterol) and on-site diagnostic technologies and supplies were assessed under module ‘A’. Module ‘R’ reports the costs of training providers in conducting risk-based management and the cost of provider time for estimating patient CVD risk using risk charts. Module ‘T’ reports cost savings from task-sharing by comparing the cost that could have been incurred if the tasks were performed solely by the physicians with costs incurred through task-sharing among physicians, nurses and CHW. Therefore, in the baseline scenario (ie, in the absence of task-sharing allocation), the costing tool assumes a physician-led programme. In our cost projections, we assumed that doctors, nurses and CHWs will equally share the tasks (ie, provider time) when applicable. For instance, CHWs would only provide behavioural counselling and screening service, but they would not assess CVD risk (using risk-cart), or prescribe patients with pharmacologic treatments. Accordingly, the provider time allocated for behaviour counselling and screening will be shared equally among doctors, nurses and CHWs. Nurses will be trained to do major tasks (ie, counselling, screening and assessing CVD risk, and treating according to CVD risk), therefore, providers’ time for performing hypertension/CVD risk-assessment, prescribing suitable treatment and return-visits were allocated equally between doctors and nurses. While the ‘T’ module reports the cost savings from team-based care, the accrued cost of provider time (inclusive of doctors, nurses and CHWs) spent on various tasks is included in the corresponding ‘H’, ‘E’ and ‘R’ modules. Module ‘S’ reports costs related to human resources, technology (software and hardware), supplies and training for patient monitoring.

Data

Data on salaries of government healthcare providers and programme staff were collected from in-person interviews and/or records. Total salary was calculated according to the Government of Bangladesh National pay scale. Size of the population in the examined subdistricts was obtained from census and imputed based on Bangladesh Bureau of Statistics estimates. Other population parameters (eg, primary care attendance rate and risk factor prevalence) were obtained from the nationally representative NCD Risk Factor Survey 2018.15 Medicine prices were collected from the medicine outlets in the public hospitals. The unit prices represent the average price of domestically manufactured generic medicines procured by health facilities from EDCL or CMSD. Prices of laboratory diagnostics were collected from diagnostic labs at the district (Sylhet district) and subdistrict (upazila) levels. Data on time needed to conduct laboratory tests were collected from in-person interviews of laboratory personnel. Training data, including number of training and participants, per-diem costs of staff, costs related to rent, transport, refreshments and other logistics, were collected from the respective project records. Table 1 presents the prevalence of CVD risk factors as well as cost inputs used to populate the HEARTS costing tool. Fifteen per cent of the adult population was estimated to be at medium and high risk for CVD. The leading risk factors were tobacco use (43.7%), hyperlipidaemia (28.4%) and hypertension (21%), followed by physical inactivity (12.3%), diabetes (8.3%) and alcohol consumption (4.4%); The primary care attendance rate was assumed to be 47.9% in each upazila.15 The distributions of patients by CVD risks and for the pharmacological treatment of hypertension, diabetes and cholesterol by different treatment lines were adopted from the literature and/or based on local physician consensus.27–30 Local currency was converted to US dollars using the Bangladesh Bank official conversion rate in June 2020.
Table 1

Costing inputs and unit costs

Input descriptionUnitsValue
Eligible population (adult population, age 18+)
 GolapganjPersons261 098
 FenchuganjPersons86 503
 BeanibazarPersons209 454
 BishwanathPersons192 075
 Primary healthcare attendance rate (annual)Per cent47.9%
Adult population with risk factors 
 Use of tobacco productsPer cent43.7%
 Hazardous or harmful use of alcoholPer cent4.4%
 Physical inactivityPer cent12.3%
 Hypertension (≥140/90 mm Hg)Per cent21.0%
 Diabetes (≥7.0 mmol/L or 126 mg/dL)Per cent8.3%
 Hyperlipidaemia (≥6 mmol/L or 190 mg/dL)Per cent28.4%
 Low CVD risk (0 to <10%)Per cent85.1%
 Medium CVD risk (10 to <20%)Per cent14.4%
 High CVD risk (≥20%)Per cent0.5%
Annual wage (in LCU (BDT) and USD, including benefits)
 DoctorsBDT (USD)/year1 399 452 (16 484)
 NursesBDT (USD)/year726 360 (8555)
 CHWsBDT (USD)/year486 568 (5731)
 Lab techniciansBDT (USD)/year576 720 (6793)
 AccountantBDT (USD)/year576 720 (6793)
 Administrative assistantBDT (USD)/year446 242 (5256)
 Clerical officerBDT (USD)/year446 242 (5256)
 CustodianBDT (USD)/year446 242 (5256)
 IT personnelBDT (USD)/year446 242 (5256)
 Programme directorBDT (USD)/year1 399 452 (16 484)
 Programme managerBDT (USD)/year726 300 (8555)
 SecretaryBDT (USD)/year446 242 (5256)
 Security officerBDT (USD)/year400 196 (4714)
 Pharmacist/chemistBDT (USD)/year576 720 (6,793)
 StatisticianBDT (USD)/year576 720 (6793)
 Supplies managerBDT (USD)/year486 568 (5731)
Purchasing price (in LCU (BDT) and USD) of pharmaceutical drugs 
Hypertension medicine
 Amlodipine 5 mgBDT (USD)/tablet1 (0.012)
 Losartan 50 mgBDT (USD)/tablet8 (0.094)
 HydrochlorothiazideBDT (USD)/tablet0.35 (0.004)
Diabetes medicine
 Metformin 500 mgBDT (USD)/tablet4 (0.047)
 Metformin 1000 mgBDT (USD)/tablet9 (0.106)
 GliclazideBDT (USD)/tablet3.5 (0.041)
Cholesteror medicine
 Simvastatin 10 mgBDT (USD)/tablet7 (0.082)
 Atorvastatin 20 mgBDT (USD)/tablet10 (0.118)
 Atorvastatin 40 mgBDT (USD)/tablet28 (0.330)
Purchasing price (in LCU) of diagnostic tests 
 Diabetes (complete blood count panel)BDT (USD)/test400 (4.71)
 Diabetes (fasting blood glucose)BDT (USD)/test120 (1.41)
 Diabetes and cholesterol (blood lipid panel)BDT (USD)/test800 (9.42)
Counselling patients to change behaviour 
 Time to counsel a patient to change behaviourMinutes10
 # of 'How to quit' informational materials disseminated per person, annually (print)Print5
 Cost of 'How to quit' informational materials, per unit (print materials)BDT (USD)/print20 (0.24)
 LCU to USD exchange rateBDT/USD84.9
 ‘Safety stock’ required to be on hand for medicinesPercent3.0
No of health providers in need of training 
 Counsel patients to change behaviourPersons30
 Assess patients' total CVD riskPersons10
Training to counsel patients to change behaviour (5A’s)*
 Classroom sizePersons30
 Hours of training neededPersons16
Training to screen/diagnosis/treat patients hypertension/CVD patients 
 Classroom sizePersons30
 Hours of training neededPersons8
No of trainers
 Professional trainer(s)Persons2
 Administrative staffPersons1
Input costs for training 
Hourly wage
 Professional trainerBDT (USD)/hour500 (5.89)
 Administrative staffBDT (USD)/hour250 (2.94)
Per unit cost of materials
 Instructive handbooksBDT (USD)/book1000 (11.8)
 Facility rental for training (1 day)BDT (USD)/day9000 (106)
 RefreshmentsBDT (USD)/day6000 (70.7)
 Per diem for staffBDT (USD)/day3500 (41.2)
 Per diem and/or salary of traineesBDT (USD)/day5000 (58.9)
 Transportation stipend for staffBDT (USD)/training3165 (37.3)
CVD risk screening and diagnosis 
Time (in minutes) a health provider spends to:
 Screen patients for total CVD riskMinutes5
 Provide a physical exam to assess patients' total CVD riskMinutes5
 Assess patient risk using a CVD risk chartMinutes5
Time (in minutes) a lab technician spends to:
 Administer and analyse a blood testMinutes10
 Administer and analyse a urine testMinutes10
Treatment for high CVD risk 
# follow-up visits for a person annually with the following levels of CVD risk annually 
 Low CVD risk (≥0% to <10%)Visits2
 Medium CVD risk (≥10% to <20%)Visits3
 High CVD risk (≥20%)Visits4
Time health providers spend with a patient during a visit?
 Generalists/primary care doctorsMinutes5
 NursesMinutes5
Screen for CVD risk: Diagnostics cost in LCU (BDT) and USD
 Diabetes (compete blood count panel)BDT (USD)/test400 (4.7)
 Diabetes (fasting blood glucose)BDT (USD)/test120 (1.4)
 Diabetes and cholesterol (blood lipid panel)BDT (USD)/test80 (0.9)
Pharmacological treatment for hypertension 
Hypertension Protocol Step #1 (Amlodipine 5 mg, 1 per day, 365 days)
 % of all individuals with high blood pressure who receive this treatment regimenPercent62%
Hypertension protocol step #2 (Amlodipine 5 mg+Losartan 50 mg)
 % of all individuals with high blood pressure who receive this treatment regimenPercent34%
Hypertension protocol step #3 (Amlodipine +Losartan+ Hydrochlorothiazide)
 % of all individuals with high blood pressure who receive this treatment regimenPercent4%
 Unit price of amlodipine 5 mg in LCU (Taka or BDT) and USDBDT (USD)/tablet1 (0.012)
 Unit price of losartan 50 mg in LCU (Taka or BDT) and USDBDT (USD)/tablet8 (0.094)
 Unit price of hydrochlorothiazide in LCU (Taka or BDT) and USDBDT (USD)/tablet0.35 (0.004)
Pharmacological treatment for diabetes 
Diabetes protocol step #1 (metformin 500 mg)
 % of all individuals with diabetes who receive this treatment regimenPercent75%
Diabetes protocol step #2 (metformin 1000 mg)
 % of all individuals with diabetes who receive this treatment regimenPercent15%
Diabetes protocol step #3 (metformin 1000 mg+gliclazide 8 mg)
 % of all individuals with diabetes who receive this treatment regimenPercent10%
 Unit price of metformin 500 mg in LCU (Taka or BDT) and USDBDT (USD)/tablet4 (0.047)
 Unit price of metformin 1000 mg in LCU (Taka or BDT) and USDBDT (USD)/tablet9 (0.106)
 Unit price of gliclazide 80 mg in LCU (Taka or BDT) and USDBDT (USD)/tablet3.5 (0.041)
Pharmacological treatment for high cholesterol (default regimens)
High cholesterol protocol step #1 (low intensity, simvastatin 10 mg)
 Percent of all individuals with high cholesterol who receive this treatmentPercent85%
High cholesterol protocol step #2 (moderate intensity, atorvastatin 20 mg)
 Percent of all individuals with high cholesterol who receive this treatmentPercent10%
High cholesterol protocol step #3 (high intensity, atorvastatin 40 mg)
 Percent of all individuals with high cholesterol who receive this treatmentPercent5%
 Unit price of simvastatin 10 mg in LCU (Taka or BDT) and USDBDT (USD)/tablet7 (0.082)
 Unit price of simvastatin 20 mg in LCU (Taka or BDT) and USDBDT (USD)/tablet10 (0.118)
 Unit price of atorvastatin 40 mg in LCU (Taka or BDT) and USDBDT (USD)/tablet28 (0.330)

*The ‘5A’ model is an evidence-based approach entailing health behaviour change counselling to prevent NCD risk factors in primary care setting.25 26

5A’s, Assess, Advise, Agree, Assist, Arrange; BDT, Bangladesh Taka; CHWs, community health workers; CVD, cardiovascular disease; LCU, Local currency unit; NCD, non-communicable disease.

Costing inputs and unit costs *The ‘5A’ model is an evidence-based approach entailing health behaviour change counselling to prevent NCD risk factors in primary care setting.25 26 5A’s, Assess, Advise, Agree, Assist, Arrange; BDT, Bangladesh Taka; CHWs, community health workers; CVD, cardiovascular disease; LCU, Local currency unit; NCD, non-communicable disease.

Results

Population coverage

The total population in the four subdistricts was 1.12 million, of which 749 000 were adults aged 18 and above (table 2). The total number of people eligible to receive counselling, screening, diagnosis and treatment under the two types of HEARTS intervention packages (ie, hypertension control and risk-based integrated approach) in the four subdistricts was determined by the primary care attendance rate, the prevalence of low-CVD, medium-CVD and high-CVD risk in the population, the prevalence of hypertension, diabetes and high cholesterol. The estimated number of eligible persons in the catchment area of the four subdistricts was 359 000, of which 305 000, 52 000 and 1800 were projected to be low-CVD, medium-CVD and high-CVD risk patients. The estimated number of persons undergoing treatment for hypertension, diabetes and high cholesterol was 75 000, 30 000 and 102 000, respectively (table 2). Unit costs and other cost inputs were applied to these population parameters to project total programme costs.
Table 2

Population coverage: care cascade for counselling, screening, diagnosis and treatment

GolapganjFenchuganjBeanibazarBishwanathTotal
Total population390 688129 436313 412287 4041 120 940
Adult population in need (18+ years)261 09886 503209 454192 075749 130
Adults who present at the health centre125 06641 435100 32892 004358 833
Providing brief counselling
 Eligible to receive brief advice125 06641 435100 32892 004358 833
 Tobacco user54 65418 10743 84440 206156 810
 Harmful alcohol550318234414404815 789
 Physical inactivity15 383509612 34011 31644 136
Screening and diagnosis of 10 year CVD risk
 Low CVD risk106 43135 26185 38078 295305 367
 Medium CVD risk18 009596714 44713 24951 672
 High CVD risk6252075024601794
Treatment of 10-year CVD risk
 Low CVD risk106 43135 26185 38078 295305 367
 Hypertension22 351740517 93016 44264 127
 Diabetes883429277087649925 345
 Cholesterol30 22610 01424 24822 23686 724
 Medium CVD risk18 009596714 44713 24951 672
 Hypertension378212533034278210 851
 Diabetes1495495119911004289
 Cholesterol511516954103376314 675
 High CVD risk6252075024601794
 Hypertension1314410597377
 Diabetes52174238149
 Cholesterol17859142131510

Risk factors and disease prevalence rates were assumed uniform across subdistricts.

CVD, cardiovascular disease.

Population coverage: care cascade for counselling, screening, diagnosis and treatment Risk factors and disease prevalence rates were assumed uniform across subdistricts. CVD, cardiovascular disease.

Hypertension management programme cost

Table 3 reports the estimated annual costs, in 2020 USD and Bangladesh Taka (BDT), of implementing the HEARTS hypertension management programme in four upazilas at the population level (adults aged 18 and above). Figure 2 presents the distribution of costs by HEARTS components and subcomponents. The total annual cost was estimated at US$3.2 million, equivalent to US$2.8 per capita, US$4.3 per adult and US$8.9 per eligible participant. Module ‘A’ (Access to medicines and technology) constitutes the largest cost share (US$1.36 million; 43%), followed by module ‘E’ (Evidence-based treatment protocols; US$1.22 million; 38%). The projected medication expenditure per patient treated with medications for hypertension was US$18.
Table 3

Total annual cost of HEARTS hypertension control programme in four subdistricts

GolapganjFenchuganjBeanibazarBishwanathTotal
BDTUSDBDTUSDBDTUSDBDTUSDBDTUSD
H: Healthy lifestyles13 335 339157 0714 765 10756 12610 800 324127 2129 947 252117 16438 848 022457 574
H1: Training costs418 9904935418 9904935418 9904935418 99049351 675 96019 740
 H1.1: Facility rental (% of H1)18 00021218 00021218 00021218 00021272 000848
 H1.2: Human resources20 00023620 00023620 00023620 00023680 000942
 H1.3: Instructive handbooks35 00041235 00041235 00041235 000412140 0001649
 H1.4: Per diem/transportation339 9904005339 9904005339 9904005339 99040051 359 96016 018
 H1.5: Refreshments60007160007160007160007124 000283
H2: Brief counselling costs12 816 349150 9584 246 11750 01310 281 334121 0999 428 262111 05136 772 062433 122
 H2.1: Tobacco9 272 756109 2203 072 10836 1857 438 64787 6176 821 44180 34726 604 952313 368
  Provider time to administer 5A’s3 807 37444 8451 261 40114 8573 054 29335 9752 800 87032 99010 923 938128 668
  Informational materials (print)5 465 38264 3741 810 70721 3284 384 35451 6414 020 57247 35715 681 014184 700
 H2.2: Alcohol933 64110 997309 3203643748 9718822686 82780902 678 75931 552
  Provider time to administer 5A’s383 3514515127 0061496307 5263622282 01033221 099 89312 955
  Informational materials (print)550 2906482182 3142147441 4455200404 81747681 578 86618 597
 H2.3: Physical inactivity2 609 95230 741864 68910 1852 093 71524 6611 919 99422 6157 488 35088 202
  Provider time to administer 5A’s1 071 64112 622355 0404182859 67510 126788 34592863 074 70136 216
  Informational materials (print)1 538 31118 119509 65060031 234 04014 5351 131 64813 3294 413 64951 986
H3: Other programme costs100 0001178100 0001178100 0001178100 0001178400 0004711
   Community awareness meetings50 00058950 00058950 000589 50 000 589200 0002356
   Community health workers training50 00058950 00058950 000589 50 000 589200 0002356
E: Evidence-based treatment protocols35 959 415423 55011 913 524140 32428 846 806339 77426 453 304311 582103 173 0491 215 230
E1: Ask about patient history - provider time5 317 33462 6311 761 65820 7504 265 58950 2433 911 66146 07415 256 241179 697
E2: Assess via physical exam and diagnostic tests - provider time5 317 33462 6311 761 65820 7504 265 58950 2433 911 66146 07415 256 241179 697
E3: Return visits - Counsel and treat per protocol - provider time25 324 748298 2898 390 20998 82520 315 628239 28918 629 982219 43472 660 567855 837
A: Access to Essential Medicines and Technologies40 197 017473 46313 429 971158 18632 279 509380 20629 615 146348 824115 521 6431 360 679
A1: Hypertension medications40 028 765471 48113 261 719156 20432 111 257378 22429 446 893346 842114 848 6331 352 752
   Amlodipine 5 mg9 873 894116 3003 271 26838 5317 920 88293 2977 263 66485 55628 329 707333 683
   Losartan 50 mg30 016 637353 5539 944 653117 13424 079 482283 62222 081 538260 08986 122 3101 014 397
   Hydrochlorothiazide 12.5 mg138 235162845 798539110 8921306101 6911198396 6164672
A2: Diagnostic technologies, machines and supplies168 2531982168 2531982168 2531982168 253 1982673 0107927
R: Risk-based management172 3342030172 3342030172 3342030172 3342030689 3368119
R1: Training costs172 3342030172 3342030172 3342030172 3342030689 3368119
T: Team-based care Savings from training nurses and CHWs to do tasks customarily performed by doctors13 815 043162 7214 576 98953 91011 082 490130 53610 162 944119 70539 637 467466 872
T1: Savings from training nurses11 976 134141 0623 967 75046 7349 607 309113 1608 810 163103 77134 361 355404 727
 Savings from counselling to change behaviour1 355 87315 970449 20752911 087 68812 811997 43911 7483 890 20845 821
 Savings from screening for--and assess--CVD risk3 367 23539 6611 115 58113 1402 701 21231 8162 477 08429 1769 661 112113 794
 Savings from treating CVD risk7 253 02585 4302 402 96128 3035 818 41068 5335 335 63962 84620 810 036245 112
T2: Savings from training CHWs1 838 90921 660609 23971761 475 18117 3761 352 78115 9345 276 11262 145
 Savings from counselling to change behaviour1 838 90921 660609 23971761 475 18117 3761 352 78115 9345 276 11262 145
S: Systems for monitoring3 114 63636 6863 114 63636 6863 114 63636 6863 114 63636 68612 458 546146 744
S1: Human resources2 969 63634 9782 969 63634 9782 969 63634 9782 969 63634 97811 878 546139 912
S2: Technology110 0001296110 0001296110 0001296110 0001296440 0005183
S3: Supplies10 00011810 00011810 00011810 00011840 000471
S4: Training25 00029425 00029425 00029425 000294100 0001178
Total Programme Cost (H+E+A+R+T+S)92 778 7421 092 80033 395 573393 35275 213 609885 90869 302 672816 286270 690 5963 188 346

BDT, Bangladesh Taka; CHWs, community health worker; CVD, cardiovascular disease.

Figure 2

Distribution of annual cost by HEARTS components.

Total annual cost of HEARTS hypertension control programme in four subdistricts BDT, Bangladesh Taka; CHWs, community health worker; CVD, cardiovascular disease. Distribution of annual cost by HEARTS components. Most of the projected annual cost (95%) of implementing module ‘H’ (Healthy-lifestyles counselling) was attributable to the cost of provider time and information materials for counselling patients (US$433 000). The estimated cost for module ‘E’ (Evidence-based treatment protocols) was attributable to provider time across three major activities: asking patient history (US$180 000; 15%), patient assessment via physical exam and diagnostic tests (US$180 000; 15%), and conducting return visits (US$856 000, 70%). The projected cost to implement module ‘S’ (Systems for monitoring) was US$147 000, primarily attributed to administration staff labour costs (95%), with the remaining cost allocated to technology (software/hardware). Table 4 highlights an important programmatic aspect by describing health providers’ time needed to implement the hypertension control programme. Implementing the programme at the full population level in all four subdistricts was estimated to require the full-time equivalent of 51 doctors, 51 nurses and 6 CHWs. The largest time requirement activities included providing initial screening and diagnosis and conducting return visits.
Table 4

Hypertension control programme: estimated health provider time for counselling, screening, diagnosis and treatment

ActivityGolapganjFenchugonjBeanibazarBishwanathTotal
WorkdaysFTEWorkdaysFTEWorkdaysFTEWorkdaysFTEFTE
Counselling to change behaviour
 Doctor524 days, 7 hours2.0173 days, 6 hours0.7420 days, 2 hours1.6385 days, 2 hours1.55.8
 Nurses524 days, 7 hours2.0173 days, 6 hours0.7420 days, 2 hours1.6385 days, 2 hours1.55.8
 CHW524 days, 7 hours2.0173 days, 6 hours0.7420 days, 2 hours1.6385 days, 2 hours1.55.8
Screening and diagnosis
 Doctor1302 days, 1 hours5.0431 days, 6 hours1.71045 days, 2 hours4.0958 days, 3 hours3.714.4
 Nurses1302 days, 1 hours5.0431 days, 6 hours1.71045 days, 2 hours4.0958 days, 3 hours3.714.4
Return visits - counsel and treat per protocol
 Doctor2806 days, 0 hours10.8929 days, 6 hours3.62251 days, 1 hours8.72064 days, 2 hours7.931.0
 Nurses2806 days, 0 hours10.8929 days, 6 hours3.62251 days, 1 hours8.72064 days, 2 hours7.931.0

Annual: total minutes/124 800.

CHW, community health worker; FTE, full-time equivalent.

Hypertension control programme: estimated health provider time for counselling, screening, diagnosis and treatment Annual: total minutes/124 800. CHW, community health worker; FTE, full-time equivalent.

Risk-based integrated hypertension, diabetes and high cholesterol management programme cost

Table 5 reports the estimated costs of implementing the risk-based hypertension, diabetes and high cholesterol management programme in four upazilas at the population level (adults aged 18 and above). Figure 2 presents the distribution of costs by HEARTS components. The total annual cost was estimated at US$14.4 million, equivalent to US$12.9 per capita, US$19.3 per adult and US$40.2 per eligible participant. Module ‘A’ (Access to medicines and technology) constitutes the largest cost share (US$11.7 million; 81%), followed by module ‘E’ (Evidence-based treatment protocols, US$1.9 million; 13%). Within module ‘A’, the projected costs of diagnostic tests, hypertension medications, diabetes medications and cholesterol medications were US$5.7 million (49% of module costs), US$1.4 million (12%), US$0.9 million (7%) and US$3.8 million (32%), respectively. The projected medication expenditure per patient treated with medications for hypertension, diabetes and cholesterol was US$18, US$29 and US$37, respectively.
Table 5

Annual cost of implementing risk-based hypertension, diabetes and high cholesterol management programme in four subdistricts

GolapganjFenchuganjBeanibazarBishwanathTotal
BDTUSDBDTUSDBDTUSDBDTUSDBDTUSD
H: Healthy lifestyles counselling13 335 339157 0714 765 10756 12610 800 324127 2129 947 252117 16438 848 022457 574
H1: Training costs418 9904935418 9904935418 9904935418 99049351 675 96019 740
 H1.1: Facility rental (% of H1)18 00021218 00021218 00021218 00021272 000848
 H1.2: Human resources20 00023620 00023620 00023620 00023680 000942
 H1.3: Instructive handbooks35 00041235 00041235 00041235 000412140 0001649
 H1.4: Per diem/transportation339 9904005339 9904005339 9904005339 99040051 359 96016 018
 H1.5: Refreshments60007160007160007160007124 000283
H2: Brief counselling costs12 816 349150 9584 246 11750 01310 281 334121 0999 428 262111 05136 772 062433 122
 H2.1: Tobacco9 272 756109 2203 072 10836 1857 438 64787 6176 821 44180 34726 604 952313 368
  Provider time to administer 5A’s3 807 37444 8451 261 40114 8573 054 29335 9752 800 87032 99010 923 938128 668
  Informational materials (print)5 465 38264 3741 810 70721 3284 384 35451 6414 020 57247 3571,5681,014184 700
 H2.2: Alcohol933 64110 997309 3203643748 9718822686 82780902 678 75931 552
  Provider time to administer 5A’s383 3514515127 0061496307 5263622282 01033221 099 89312 955
  Informational materials (print)550 2906482182 3142147441 4455200404 81747681 578 86618 597
 H2.3: Physical inactivity2 609 95230 741864 68910 1852 093 71524 6611 919 99422 6157 488 35088 202
  Provider time to administer 5A’s1 071 64112 622355 0404182859 67510 126788 34592863 074 70136 216
  Informational materials (print)1 538 31118 119509 65060031 234 04014 5351 131 64813 3294 413 64951 986
H3: Other programme costs100 0001178100 0001178100 0001178100 0001178400 0004711
 Community awareness meetings50 00058950 00058950 00058950 000589200 0002356
 Community health workers training50 00058950 00058950 00058950 000589200 0002356
E: Evidence-based treatment protocols56 155 264661 42818 604 504219 13445 048 007530 60141 310 245486 575161 118 0201 897 739
E1: Ask about patient history—provider time5 317 33462 6311 761 65820 7504 265 58950 2433 911 66146 07415 256 241179 697
E2: Assess via physical exam and diagnostic tests——provider time25 513 182300 5098 452 63899 56020 466 790241 06918 768 602221 06773 201 212862 205
E3: Return visits - Counsel and treat per protocol—provider time25 324 748298 2898 390 20998 82520 315 628239 28918 629 982219 43472 660 567855 837
A: Access to Essential Medicines and tech.347 102 9434 088 374115 109 3531 355 823278 480 8353 280 104255 388 4403 008 109996 081 57111 732 410
A1: Diagnostic tests170 039 6552 002 82356 334 940663 545136 406 5821 606 674125 088 5361 473 363487 869 7145 746 404
 Complete blood count (panel)51 527 168606 91617 071 194201 07441 335 328486 87137 905 617446 474147 839 3071 741 335
 Blood lipid panel103 054 3361 213 83234 142 388402 14882 670 656973 74275 811 234892 947295 678 6143 482 669
 Fasting blood glucose15 458 150182 0755 121 35860 32212 400 598146 06111 371 685133 94244 351 792522 400
A2: Hypertension medications40 028 765471 48113 261 719156 20432 111 257378 22429 446 893346 842114 848 6331 352 752
 Amlodipine 5 mg9 873 894116 3003 271 26838 5317 920 88293 2977 263 66485 55628 329 707333 683
 Losartan 50 mg30 016 637353 5539 944 653117 13424 079 482283 62222 081 538260 08986 122 3101 014 397
 Hydrochlorothiazide 12.5 mg138 235162845 798539110 8921306101 6911198396 6164672
A3: Diabetes medications25 366 503298 7818 404 04298 98820 349 124239 68318 660 698219 79672 780 367857 248
 Metformin 500 mg11 707 617137 8993 878 78945 6879 391 903110 6238 612 630101 44433 590 939395 653
 Metformin 1000 mg12 292 998144 7944 072 72847 9719 861 498116 1549 043 262106 51735 270 486415 436
 Gliclazide1 365 88916 088452 52553301 095 72212 9061 004 80711 8353 918 94346 160
A4: Cholesterol medications111 499 7681 313 30736 940 399435 10589 445 6201 053 54182 024 060966 126319 909 8473 768 078
 Simvastatin 10 mg79 451 930935 83026 322 800310 04563 736 699750 72758 448 282688 437227 959 7112 685 038
 Atorvastatin 20 mg13 353 266157 2824 424 00052 10810 712 050126 1739 823 241115 70438 312 556451 267
 Atorvastatin 40 mg18 694 572220 1956 193 60072 95214 996 870176 64213 752 537161 98553 637 579631 774
A5: Diagnostic tech. machines and supplies168 2531982168 2531982168 2531982168 2531982673 0107927
R: Risk-based management5 489 66864 6601 933 99222 7804 437 92352 2724 083 99548 10415 945 577187 816
R1: Training costs172 3342030172 3342030172 3342030172 3342030689 3368119
R2: Estimate risk using risk charts5 317 33462 6311 761 65820 7504 265 58950 2433 911 66146 07415 256 241179 697
T: Team-based care: Savings from training nurses and CHWs to do tasks customarily performed by doctors25 600 367301 5368 481 52399 90020 536 731241 89318 832 739221 82373 451 360865 151
T1: Savings from training nurses23 761 458279 8767 872 28392 72419 061 549224 51817 479 958205 88968 175 248803 006
 Savings from counselling to change behaviour1 355 87315 970449 20752911 087 68812 811997 43911 7483 890 20845 821
 Savings from screening for—and assess—CVD risk15 152 559178 4755 020 11459 13012 155 452143 17411 146 879131 29443 475 005512 073
 Savings from treating CVD risk7 253 02585 4302 402 96128 3035 818 41068 5335 335 63962 84620 810 036245 112
T2: Savings from training CHWs1 838 90921 660609 23971761 475 18117 3761 352 78115 9345 276 11262 145
 Savings from counselling to change behaviour1 838 90921 660609 23971761 475 18117 3761 352 78115 9345 276 11262 145
S: Systems for monitoring3 114 63636 6863 114 63636 6863 114 63636 6863 114 63636 68612 458 546146 744
S1: Human resources2 969 63634 9782 969 63634 9782 969 63634 9782 969 63634 97811 878 546139 912
S2: Technology110 0001296110 0001296110 0001296110 0001296440 0005183
S3: Supplies10 00011810 00011810 00011810 00011840 000471
S4: Training25 00029425 00029425 00029425 000294100 0001178
Total programme cost (H+E+A+R+T+S)425 197 8505 008 220143 527 5921 690 549341 881 7254 026 875313 844 5683 696 6381,224,451,73514 422 282

5 A’s, Assess, Advise, Agree, Assist, Arrange; BDT, Bangladesh Taka; CHW, community health worker; CVD, cardiovascular disease.

Annual cost of implementing risk-based hypertension, diabetes and high cholesterol management programme in four subdistricts 5 A’s, Assess, Advise, Agree, Assist, Arrange; BDT, Bangladesh Taka; CHW, community health worker; CVD, cardiovascular disease. The adoption of task-sharing approach would save US$865 000, of which US$803 000 comes from using nurses to complete tasks customarily performed by doctors (ie, counselling, screening and assessing CVD risk, and treating according to CVD risk) and US$62 000 comes from using CHWs to provide counselling to change behaviour. Implementing the risk-based hypertension, diabetes and high cholesterol management programme at the full population level in all four subdistricts was estimated to require the full-time equivalent of 58 doctors, 58 nurses, 6 CHWs and 101 lab technicians (table 6). The largest time requirement activities included providing initial screening and diagnosis and conducting return visits.
Table 6

Integrated risk-based approach: estimated health provider time for counselling, screening, diagnosis and treatment

ActivityGolapganjFenchugonjBeanibazarBishwanathTotal
WorkdaysFTEWorkdaysFTEWorkdaysFTEWorkdaysFTEFTE
Counselling to change behaviour
 Doctor524 days, 7 hours2.0173 days, 6 hours0.7420 days, 2 hours1.6385 days, 2 hours1.55.8
 Nurses524 days, 7 hours2.0173 days, 6 hours0.7420 days, 2 hours1.6385 days, 2 hours1.55.8
 CHW524 days, 7 hours2.0173 days, 6 hours0.7420 days, 2 hours1.6385 days, 2 hours1.55.8
Screening and diagnosis
 Doctor1302 days, 1 hours5.0431 days, 6 hours1.71045 days, 2 hours4.0958 days, 3 hours3.714.4
 Nurses1302 days, 1 hours5.0431 days, 6 hours1.71045 days, 2 hours4.0958 days, 3 hours3.714.4
 Screening and diagnosis by Lab technicians9119 days, 3 hours35.13021 days, 6 hours11.67315 days, 0 hours28.16708 days, 1 hours25.8100.6
Estimating CVD risk using risk charts
 Doctor2 658 6672.5880 8290.82 132 7952.01 955 8301.87.2
 Nurses2 658 6672.5880 8290.82 132 7952.01 955 8301.87.2
Return visits—counsel and treat per protocol
 Doctor2806 days, 0 hours10.8929 days, 6 hours3.62251 days, 1 hours8.72064 days, 2 hours7.931.0
 Nurses2806 days, 0 hours10.8929 days, 6 hours3.62251 days, 1 hours8.72064 days, 2 hours7.931.0

CHW, community health worker; CVD, cardiovascular disease; FTE, full-time equivalent.

Integrated risk-based approach: estimated health provider time for counselling, screening, diagnosis and treatment CHW, community health worker; CVD, cardiovascular disease; FTE, full-time equivalent.

Discussion

The HEARTS pilot project in four Bangladesh subdistricts launched a framework for hypertension management in primary care, with a potential for expanding into a comprehensive CVD prevention approach that incorporates hypertension, diabetes and cholesterol management. This study projects the expected cost of scaling up the programme to all eligible adults in the participating subdistricts. We assessed two programme scenarios: a hypertension management programme and an integrated risk-based hypertension, diabetes and cholesterol management programme. The total annual cost was estimated at US$3.2 and US$14.4 million for the hypertension and risk-based comprehensive approach, respectively. The overall per capita cost was approximately US$2.8 per capita for the hypertension control programme and US$12.9 per capita for the risk-based comprehensive approach. These estimates correspond to 0.14% and 0.7% of the 2020 gross domestic product per capita in Bangladesh, respectively. The main cost drivers for the hypertension control programme were medication expenditures (43%) and the cost of provider time for providing care during multiple visits (38%). In the risk-based integrated approach, the combined costs of hypertension, diabetes and cholesterol medications and diagnostic tests make up the largest share of the overall programme cost (81%). Although the main driver of projected programme costs for the integrated approach was expenditure on essential medicines and diagnostic tests, hypertension and diabetes medications contributed a relatively small portion (19%) to this expenditure (ie, module A), whereas cholesterol medications contributed nearly 32%. Hypertension treatment remains among the leading cost-effective ways to combat heart disease. In this study, the annual medication expenditure per patient treated with medications for hypertension, diabetes and cholesterol was US$18, US$29 and US$37, respectively. Though based on observations gathered in one district of Bangladesh, our results are consistent with those reported by past studies. A previous study on Bangladesh by Nugent et al31 estimated that hypertension treatment would cost about US$13 (BDT1070) per patient per year.31 WHO (2011) has estimated the average hypertension screening cost for LMICs at approximately US$4 for LMICs, not including treatment but including the cost of performing CVD risk assessment and BP measurement in primary care settings.32 Haque33 estimated the average cost of diabetes screening in Bangladesh at approximately US$5 (BDT411), including glucose screening in primary care, documentation, setting up referrals and organising screening events but excluding treatment.33 In this study, the cost elements in the Bangladesh HEARTS programme are wide-ranging including screening, diagnosis and treatment for multiple CVD risk conditions (hypertension, diabetes, hyperlipidaemia) and counselling for CVD risk factors (tobacco use, alcohol use and physical inactivity). The analysis revealed that scaling up the hypertension management programme within the four subdistricts would require an additional full-time equivalent of 51 doctors, 51 nurses and 6 CHWs. Population-level scale-up of the risk-based hypertension, diabetes and high cholesterol management programme in the four subdistricts was estimated to require the full-time equivalent of 58 doctors, 58 nurses, 6 CHWs and 101 lab technicians. To put this in context, a typical 50-bed subdistrict public health complex in Bangladesh employs 20 doctors, 16 nurses and 1 medical assistant. Oftentimes, not all health provider posts are filled. This gap in provider capacity poses a significant barrier to programme expansion. Team-based care using task-sharing among doctors, nurses and CHWs and volunteers can accomplish the activities required by the HEARTS package more affordably, including NCD-related health promotion, prevention, screening and patient navigation through the health system. A systematic review of intervention trials in LMICs by Joshi et al34 found that team-based care, including task sharing was effective in improving process outcomes (eg, hypertension and diabetes screening) and health outcomes (eg, hypertension and diabetes control) and achieving treatment concordance with doctors.16 34 Krishnan et al35 conducted a study on a community-based hypertension management programme of BP monitoring and lifestyle counselling intervention undertaken by female community health volunteers in Nepal, and assessed the intervention to be highly cost-effective.35 However, there are several barriers to team-based care with task sharing, including staff attrition and turnover, retention of training, patient perception and acceptance toward non-physician health workers, lack of delegation of work by physicians, legislation and policy etc.36 In Bangladesh, of the four entities (ie, the government, for-profit private sector, non-profit nongovernmental organisation and donor agencies) involved in the primary healthcare provision, the government plays the leading role, mainly in rural areas. There are six tiers of public healthcare infrastructure: national, divisional, district, upazila (subdistrict), union and ward levels. To tackle NCDs, the government of Bangladesh introduced ‘NCD Corners’ initiative in 2012 dedicated to providing prevention and care services for common NCDs and related conditions. The government has plans to expand ‘NCD corners’ at the upazila level, and the upazila primary care setting is well positioned to bridge the link the healthcare providers down to the union, ward (and community) levels by harnessing community support and delegating suitable activities under task-sharing principles.16 37 38 This will enhance healthcare access among disadvantaged populations and mitigate health disparities. Further, in Bangladesh, according to the 2016 Household Income Expenditure Survey and 2014 Health and Morbidity Status Survey, one in three patients received treatment from a pharmacy or medical shop, while about one in five received treatment from public health providers.39 40 This emphasises the need for partnerships with various types of public–private health providers. The models of care introduced in the Bangladesh national hypertension guidelines and NCD operational plan are encouraging; however, there are capacity challenges to the scaling-up of NCD care in Bangladesh.41 42 The fiscal year 2021 budget allocation to the health sector stands just above 5%, which is less than 1% of GDP. Further, less than 5% of public sector funding for health covers NCDs, despite NCDs being responsible for almost two-thirds (63% in 2016) of disability-adjusted life-years in Bangladesh.16 The per capita NCD allocation is only US$0.08.16 There is a need for better coordination of non-state stakeholders in NCD control with the public sector with a stronger focus of the public sector on NCD prevention and health promotion.16 The health sector in Bangladesh is financed 93% from domestic sources (74% out-of-pocket, 17% government health expenditure and 3% other private sources) and 7% from external health expenditures. Domestic general government health expenditure per capita is only US$7 (0.4% of GDP per capita).43 Due to insufficient public sector funding, out-of-pocket expenditure for NCD care is large in Bangladesh, contributing to the impoverishment of patients and their families. Moreover, a recent policy review by Biswas et al44 highlights the lack of proper planning, implementation and monitoring of NCD health initiatives.44 However, the Bangladesh Copenhagen Project assessed the benefits of managing hypertension through targeted investment and reported a high level of return on investment (BDT17 benefit for every BDT spent).31 This report has several limitations. Due to lack of data at a local level, the cost projections rely on assumptions regarding population coverage, risk factor prevalence, primary care attendance rate, distribution of CVD risk among the population, distribution of patients by treatment protocols, and frequency of patient visits by CVD risk, which were assumed to be uniform for the four subdistricts and across age or sex groups. Similarly, unit costs of supplies, wages and provider time allocations were assumed to be the same across subdistricts. Since the examined subdistricts are adjacent to each other, these unit costs may not be considerably different. While we used average medicine prices, they may vary in different subdistricts depending on the procurement arrangement and sources. However, in Bangladesh, the price variations are minimal or low in the public health facilities, given the medicines are procured mainly from EDCL and/or CMSD.19 20 The strength of the study lies in its ability to disaggregate costs by function, identifying areas for efficiency improvements, such as task-sharing and bridging programme delivery from the upazila level to more localised community facilities. In 2018, the Government of Bangladesh introduced a multisectoral action plan for NCD prevention and control, which emphasises NCD risk factors including tobacco use, unhealthy diet, physical inactivity and harmful use of alcohol.42 This study can inform approaches to scaling up this action plan nationally, with the goal of increasing population outreach for CVD prevention at the primary care level. Using the costs reported in this study for future cost-effectiveness analyses can further support evidence-based decision making for CVD prevention programmes in Bangladesh.

Conclusion

Expanding the HEARTS hypertension management and CVD prevention programme to provide services to the entire eligible population in the catchment area may face constraints in physician capacity. A task-sharing model involving shifting of select tasks from doctors to nurses and local CHWs would be essential for the eventual scale-up of primary care services to prevent CVD in Bangladesh.
  18 in total

Review 1.  Evaluating primary care behavioral counseling interventions: an evidence-based approach.

Authors:  Evelyn P Whitlock; C Tracy Orleans; Nola Pender; Janet Allan
Journal:  Am J Prev Med       Date:  2002-05       Impact factor: 5.043

2.  Cost-effectiveness and budget impact of the community-based management of hypertension in Nepal study (COBIN): a retrospective analysis.

Authors:  Anirudh Krishnan; Eric Andrew Finkelstein; Per Kallestrup; Arjun Karki; Michael Hecht Olsen; Dinesh Neupane
Journal:  Lancet Glob Health       Date:  2019-10       Impact factor: 26.763

3.  A cost-benefit analysis of a National Hypertension Treatment Program in Bangladesh.

Authors:  Rachel Nugent; Elizabeth Brower; Alejandro Cravioto; Tracey Koehlmoos
Journal:  Prev Med       Date:  2017-08-19       Impact factor: 4.018

4.  The correlation between blood pressure and kidney function decline in older people: a registry-based cohort study.

Authors:  Bert Vaes; Emilie Beke; Carla Truyers; Steven Elli; Frank Buntinx; Jan Y Verbakel; Geert Goderis; Gijs Van Pottelbergh
Journal:  BMJ Open       Date:  2015-06-30       Impact factor: 2.692

5.  Bangladesh policy on prevention and control of non-communicable diseases: a policy analysis.

Authors:  Tuhin Biswas; Sonia Pervin; Md Imtiaz Alam Tanim; Louis Niessen; Anwar Islam
Journal:  BMC Public Health       Date:  2017-06-19       Impact factor: 3.295

6.  Non-communicable disease (NCD) corners in public sector health facilities in Bangladesh: a qualitative study assessing challenges and opportunities for improving NCD services at the primary healthcare level.

Authors:  Lal B Rawal; Kie Kanda; Tuhin Biswas; Md Imtiaz Tanim; Prakash Poudel; Andre M N Renzaho; Abu S Abdullah; Sheikh Mohammed Shariful Islam; Syed Masud Ahmed
Journal:  BMJ Open       Date:  2019-10-07       Impact factor: 2.692

7.  Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.

Authors:  Mohammad H Forouzanfar; Lily Alexander; H Ross Anderson; Victoria F Bachman; Stan Biryukov; Michael Brauer; Richard Burnett; Daniel Casey; Matthew M Coates; Aaron Cohen; Kristen Delwiche; Kara Estep; Joseph J Frostad; K C Astha; Hmwe H Kyu; Maziar Moradi-Lakeh; Marie Ng; Erica Leigh Slepak; Bernadette A Thomas; Joseph Wagner; Gunn Marit Aasvang; Cristiana Abbafati; Ayse Abbasoglu Ozgoren; Foad Abd-Allah; Semaw F Abera; Victor Aboyans; Biju Abraham; Jerry Puthenpurakal Abraham; Ibrahim Abubakar; Niveen M E Abu-Rmeileh; Tania C Aburto; Tom Achoki; Ademola Adelekan; Koranteng Adofo; Arsène K Adou; José C Adsuar; Ashkan Afshin; Emilie E Agardh; Mazin J Al Khabouri; Faris H Al Lami; Sayed Saidul Alam; Deena Alasfoor; Mohammed I Albittar; Miguel A Alegretti; Alicia V Aleman; Zewdie A Alemu; Rafael Alfonso-Cristancho; Samia Alhabib; Raghib Ali; Mohammed K Ali; François Alla; Peter Allebeck; Peter J Allen; Ubai Alsharif; Elena Alvarez; Nelson Alvis-Guzman; Adansi A Amankwaa; Azmeraw T Amare; Emmanuel A Ameh; Omid Ameli; Heresh Amini; Walid Ammar; Benjamin O Anderson; Carl Abelardo T Antonio; Palwasha Anwari; Solveig Argeseanu Cunningham; Johan Arnlöv; Valentina S Arsic Arsenijevic; Al Artaman; Rana J Asghar; Reza Assadi; Lydia S Atkins; Charles Atkinson; Marco A Avila; Baffour Awuah; Alaa Badawi; Maria C Bahit; Talal Bakfalouni; Kalpana Balakrishnan; Shivanthi Balalla; Ravi Kumar Balu; Amitava Banerjee; Ryan M Barber; Suzanne L Barker-Collo; Simon Barquera; Lars Barregard; Lope H Barrero; Tonatiuh Barrientos-Gutierrez; Ana C Basto-Abreu; Arindam Basu; Sanjay Basu; Mohammed O Basulaiman; Carolina Batis Ruvalcaba; Justin Beardsley; Neeraj Bedi; Tolesa Bekele; Michelle L Bell; Corina Benjet; Derrick A Bennett; Habib Benzian; Eduardo Bernabé; Tariku J Beyene; Neeraj Bhala; Ashish Bhalla; Zulfiqar A Bhutta; Boris Bikbov; Aref A Bin Abdulhak; Jed D Blore; Fiona M Blyth; Megan A Bohensky; Berrak Bora Başara; Guilherme Borges; Natan M Bornstein; Dipan Bose; Soufiane Boufous; Rupert R Bourne; Michael Brainin; Alexandra Brazinova; Nicholas J Breitborde; Hermann Brenner; Adam D M Briggs; David M Broday; Peter M Brooks; Nigel G Bruce; Traolach S Brugha; Bert Brunekreef; Rachelle Buchbinder; Linh N Bui; Gene Bukhman; Andrew G Bulloch; Michael Burch; Peter G J Burney; Ismael R Campos-Nonato; Julio C Campuzano; Alejandra J Cantoral; Jack Caravanos; Rosario Cárdenas; Elisabeth Cardis; David O Carpenter; Valeria Caso; Carlos A Castañeda-Orjuela; Ruben E Castro; Ferrán Catalá-López; Fiorella Cavalleri; Alanur Çavlin; Vineet K Chadha; Jung-Chen Chang; Fiona J Charlson; Honglei Chen; Wanqing Chen; Zhengming Chen; Peggy P Chiang; Odgerel Chimed-Ochir; Rajiv Chowdhury; Costas A Christophi; Ting-Wu Chuang; Sumeet S Chugh; Massimo Cirillo; Thomas K D Claßen; Valentina Colistro; Mercedes Colomar; Samantha M Colquhoun; Alejandra G Contreras; Cyrus Cooper; Kimberly Cooperrider; Leslie T Cooper; Josef Coresh; Karen J Courville; Michael H Criqui; Lucia Cuevas-Nasu; James Damsere-Derry; Hadi Danawi; Lalit Dandona; Rakhi Dandona; Paul I Dargan; Adrian Davis; Dragos V Davitoiu; Anand Dayama; E Filipa de Castro; Vanessa De la Cruz-Góngora; Diego De Leo; Graça de Lima; Louisa Degenhardt; Borja del Pozo-Cruz; Robert P Dellavalle; Kebede Deribe; Sarah Derrett; Don C Des Jarlais; Muluken Dessalegn; Gabrielle A deVeber; Karen M Devries; Samath D Dharmaratne; Mukesh K Dherani; Daniel Dicker; Eric L Ding; Klara Dokova; E Ray Dorsey; Tim R Driscoll; Leilei Duan; Adnan M Durrani; Beth E Ebel; Richard G Ellenbogen; Yousef M Elshrek; Matthias Endres; Sergey P Ermakov; Holly E Erskine; Babak Eshrati; Alireza Esteghamati; Saman Fahimi; Emerito Jose A Faraon; Farshad Farzadfar; Derek F J Fay; Valery L Feigin; Andrea B Feigl; Seyed-Mohammad Fereshtehnejad; Alize J Ferrari; Cleusa P Ferri; Abraham D Flaxman; Thomas D Fleming; Nataliya Foigt; Kyle J Foreman; Urbano Fra Paleo; Richard C Franklin; Belinda Gabbe; Lynne Gaffikin; Emmanuela Gakidou; Amiran Gamkrelidze; Fortuné G Gankpé; Ron T Gansevoort; Francisco A García-Guerra; Evariste Gasana; Johanna M Geleijnse; Bradford D Gessner; Pete Gething; Katherine B Gibney; Richard F Gillum; Ibrahim A M Ginawi; Maurice Giroud; Giorgia Giussani; Shifalika Goenka; Ketevan Goginashvili; Hector Gomez Dantes; Philimon Gona; Teresita Gonzalez de Cosio; Dinorah González-Castell; Carolyn C Gotay; Atsushi Goto; Hebe N Gouda; Richard L Guerrant; Harish C Gugnani; Francis Guillemin; David Gunnell; Rahul Gupta; Rajeev Gupta; Reyna A Gutiérrez; Nima Hafezi-Nejad; Holly Hagan; Maria Hagstromer; Yara A Halasa; Randah R Hamadeh; Mouhanad Hammami; Graeme J Hankey; Yuantao Hao; Hilda L Harb; Tilahun Nigatu Haregu; Josep Maria Haro; Rasmus Havmoeller; Simon I Hay; Mohammad T Hedayati; Ileana B Heredia-Pi; Lucia Hernandez; Kyle R Heuton; Pouria Heydarpour; Martha Hijar; Hans W Hoek; Howard J Hoffman; John C Hornberger; H Dean Hosgood; Damian G Hoy; Mohamed Hsairi; Guoqing Hu; Howard Hu; Cheng Huang; John J Huang; Bryan J Hubbell; Laetitia Huiart; Abdullatif Husseini; Marissa L Iannarone; Kim M Iburg; Bulat T Idrisov; Nayu Ikeda; Kaire Innos; Manami Inoue; Farhad Islami; Samaya Ismayilova; Kathryn H Jacobsen; Henrica A Jansen; Deborah L Jarvis; Simerjot K Jassal; Alejandra Jauregui; Sudha Jayaraman; Panniyammakal Jeemon; Paul N Jensen; Vivekanand Jha; Fan Jiang; Guohong Jiang; Ying Jiang; Jost B Jonas; Knud Juel; Haidong Kan; Sidibe S Kany Roseline; Nadim E Karam; André Karch; Corine K Karema; Ganesan Karthikeyan; Anil Kaul; Norito Kawakami; Dhruv S Kazi; Andrew H Kemp; Andre P Kengne; Andre Keren; Yousef S Khader; Shams Eldin Ali Hassan Khalifa; Ejaz A Khan; Young-Ho Khang; Shahab Khatibzadeh; Irma Khonelidze; Christian Kieling; Daniel Kim; Sungroul Kim; Yunjin Kim; Ruth W Kimokoti; Yohannes Kinfu; Jonas M Kinge; Brett M Kissela; Miia Kivipelto; Luke D Knibbs; Ann Kristin Knudsen; Yoshihiro Kokubo; M Rifat Kose; Soewarta Kosen; Alexander Kraemer; Michael Kravchenko; Sanjay Krishnaswami; Hans Kromhout; Tiffany Ku; Barthelemy Kuate Defo; Burcu Kucuk Bicer; Ernst J Kuipers; Chanda Kulkarni; Veena S Kulkarni; G Anil Kumar; Gene F Kwan; Taavi Lai; Arjun Lakshmana Balaji; Ratilal Lalloo; Tea Lallukka; Hilton Lam; Qing Lan; Van C Lansingh; Heidi J Larson; Anders Larsson; Dennis O Laryea; Pablo M Lavados; Alicia E Lawrynowicz; Janet L Leasher; Jong-Tae Lee; James Leigh; Ricky Leung; Miriam Levi; Yichong Li; Yongmei Li; Juan Liang; Xiaofeng Liang; Stephen S Lim; M Patrice Lindsay; Steven E Lipshultz; Shiwei Liu; Yang Liu; Belinda K Lloyd; Giancarlo Logroscino; Stephanie J London; Nancy Lopez; Joannie Lortet-Tieulent; Paulo A Lotufo; Rafael Lozano; Raimundas Lunevicius; Jixiang Ma; Stefan Ma; Vasco M P Machado; Michael F MacIntyre; Carlos Magis-Rodriguez; Abbas A Mahdi; Marek Majdan; Reza Malekzadeh; Srikanth Mangalam; Christopher C Mapoma; Marape Marape; Wagner Marcenes; David J Margolis; Christopher Margono; Guy B Marks; Randall V Martin; Melvin B Marzan; Mohammad T Mashal; Felix Masiye; Amanda J Mason-Jones; Kunihiro Matsushita; Richard Matzopoulos; Bongani M Mayosi; Tasara T Mazorodze; Abigail C McKay; Martin McKee; Abigail McLain; Peter A Meaney; Catalina Medina; Man Mohan Mehndiratta; Fabiola Mejia-Rodriguez; Wubegzier Mekonnen; Yohannes A Melaku; Michele Meltzer; Ziad A Memish; Walter Mendoza; George A Mensah; Atte Meretoja; Francis Apolinary Mhimbira; Renata Micha; Ted R Miller; Edward J Mills; Awoke Misganaw; Santosh Mishra; Norlinah Mohamed Ibrahim; Karzan A Mohammad; Ali H Mokdad; Glen L Mola; Lorenzo Monasta; Julio C Montañez Hernandez; Marcella Montico; Ami R Moore; Lidia Morawska; Rintaro Mori; Joanna Moschandreas; Wilkister N Moturi; Dariush Mozaffarian; Ulrich O Mueller; Mitsuru Mukaigawara; Erin C Mullany; Kinnari S Murthy; Mohsen Naghavi; Ziad Nahas; Aliya Naheed; Kovin S Naidoo; Luigi Naldi; Devina Nand; Vinay Nangia; K M Venkat Narayan; Denis Nash; Bruce Neal; Chakib Nejjari; Sudan P Neupane; Charles R Newton; Frida N Ngalesoni; Jean de Dieu Ngirabega; Grant Nguyen; Nhung T Nguyen; Mark J Nieuwenhuijsen; Muhammad I Nisar; José R Nogueira; Joan M Nolla; Sandra Nolte; Ole F Norheim; Rosana E Norman; Bo Norrving; Luke Nyakarahuka; In-Hwan Oh; Takayoshi Ohkubo; Bolajoko O Olusanya; Saad B Omer; John Nelson Opio; Ricardo Orozco; Rodolfo S Pagcatipunan; Amanda W Pain; Jeyaraj D Pandian; Carlo Irwin A Panelo; Christina Papachristou; Eun-Kee Park; Charles D Parry; Angel J Paternina Caicedo; Scott B Patten; Vinod K Paul; Boris I Pavlin; Neil Pearce; Lilia S Pedraza; Andrea Pedroza; Ljiljana Pejin Stokic; Ayfer Pekericli; David M Pereira; Rogelio Perez-Padilla; Fernando Perez-Ruiz; Norberto Perico; Samuel A L Perry; Aslam Pervaiz; Konrad Pesudovs; Carrie B Peterson; Max Petzold; Michael R Phillips; Hwee Pin Phua; Dietrich Plass; Dan Poenaru; Guilherme V Polanczyk; Suzanne Polinder; Constance D Pond; C Arden Pope; Daniel Pope; Svetlana Popova; Farshad Pourmalek; John Powles; Dorairaj Prabhakaran; Noela M Prasad; Dima M Qato; Amado D Quezada; D Alex A Quistberg; Lionel Racapé; Anwar Rafay; Kazem Rahimi; Vafa Rahimi-Movaghar; Sajjad Ur Rahman; Murugesan Raju; Ivo Rakovac; Saleem M Rana; Mayuree Rao; Homie Razavi; K Srinath Reddy; Amany H Refaat; Jürgen Rehm; Giuseppe Remuzzi; Antonio L Ribeiro; Patricia M Riccio; Lee Richardson; Anne Riederer; Margaret Robinson; Anna Roca; Alina Rodriguez; David Rojas-Rueda; Isabelle Romieu; Luca Ronfani; Robin Room; Nobhojit Roy; George M Ruhago; Lesley Rushton; Nsanzimana Sabin; Ralph L Sacco; Sukanta Saha; Ramesh Sahathevan; Mohammad Ali Sahraian; Joshua A Salomon; Deborah Salvo; Uchechukwu K Sampson; Juan R Sanabria; Luz Maria Sanchez; Tania G Sánchez-Pimienta; Lidia Sanchez-Riera; Logan Sandar; Itamar S Santos; Amir Sapkota; Maheswar Satpathy; James E Saunders; Monika Sawhney; Mete I Saylan; Peter Scarborough; Jürgen C Schmidt; Ione J C Schneider; Ben Schöttker; David C Schwebel; James G Scott; Soraya Seedat; Sadaf G Sepanlou; Berrin Serdar; Edson E Servan-Mori; Gavin Shaddick; Saeid Shahraz; Teresa Shamah Levy; Siyi Shangguan; Jun She; Sara Sheikhbahaei; Kenji Shibuya; Hwashin H Shin; Yukito Shinohara; Rahman Shiri; Kawkab Shishani; Ivy Shiue; Inga D Sigfusdottir; Donald H Silberberg; Edgar P Simard; Shireen Sindi; Abhishek Singh; Gitanjali M Singh; Jasvinder A Singh; Vegard Skirbekk; Karen Sliwa; Michael Soljak; Samir Soneji; Kjetil Søreide; Sergey Soshnikov; Luciano A Sposato; Chandrashekhar T Sreeramareddy; Nicolas J C Stapelberg; Vasiliki Stathopoulou; Nadine Steckling; Dan J Stein; Murray B Stein; Natalie Stephens; Heidi Stöckl; Kurt Straif; Konstantinos Stroumpoulis; Lela Sturua; Bruno F Sunguya; Soumya Swaminathan; Mamta Swaroop; Bryan L Sykes; Karen M Tabb; Ken Takahashi; Roberto T Talongwa; Nikhil Tandon; David Tanne; Marcel Tanner; Mohammad Tavakkoli; Braden J Te Ao; Carolina M Teixeira; Martha M Téllez Rojo; Abdullah S Terkawi; José Luis Texcalac-Sangrador; Sarah V Thackway; Blake Thomson; Andrew L Thorne-Lyman; Amanda G Thrift; George D Thurston; Taavi Tillmann; Myriam Tobollik; Marcello Tonelli; Fotis Topouzis; Jeffrey A Towbin; Hideaki Toyoshima; Jefferson Traebert; Bach X Tran; Leonardo Trasande; Matias Trillini; Ulises Trujillo; Zacharie Tsala Dimbuene; Miltiadis Tsilimbaris; Emin Murat Tuzcu; Uche S Uchendu; Kingsley N Ukwaja; Selen B Uzun; Steven van de Vijver; Rita Van Dingenen; Coen H van Gool; Jim van Os; Yuri Y Varakin; Tommi J Vasankari; Ana Maria N Vasconcelos; Monica S Vavilala; Lennert J Veerman; Gustavo Velasquez-Melendez; N Venketasubramanian; Lakshmi Vijayakumar; Salvador Villalpando; Francesco S Violante; Vasiliy Victorovich Vlassov; Stein Emil Vollset; Gregory R Wagner; Stephen G Waller; Mitchell T Wallin; Xia Wan; Haidong Wang; JianLi Wang; Linhong Wang; Wenzhi Wang; Yanping Wang; Tati S Warouw; Charlotte H Watts; Scott Weichenthal; Elisabete Weiderpass; Robert G Weintraub; Andrea Werdecker; K Ryan Wessells; Ronny Westerman; Harvey A Whiteford; James D Wilkinson; Hywel C Williams; Thomas N Williams; Solomon M Woldeyohannes; Charles D A Wolfe; John Q Wong; Anthony D Woolf; Jonathan L Wright; Brittany Wurtz; Gelin Xu; Lijing L Yan; Gonghuan Yang; Yuichiro Yano; Pengpeng Ye; Muluken Yenesew; Gökalp K Yentür; Paul Yip; Naohiro Yonemoto; Seok-Jun Yoon; Mustafa Z Younis; Zourkaleini Younoussi; Chuanhua Yu; Maysaa E Zaki; Yong Zhao; Yingfeng Zheng; Maigeng Zhou; Jun Zhu; Shankuan Zhu; Xiaonong Zou; Joseph R Zunt; Alan D Lopez; Theo Vos; Christopher J Murray
Journal:  Lancet       Date:  2015-09-11       Impact factor: 79.321

Review 8.  Hypertension, cognitive decline, and dementia: an epidemiological perspective.

Authors:  Christophe Tzourio
Journal:  Dialogues Clin Neurosci       Date:  2007       Impact factor: 5.986

9.  Blood pressure and incidence of twelve cardiovascular diseases: lifetime risks, healthy life-years lost, and age-specific associations in 1·25 million people.

Authors:  Eleni Rapsomaniki; Adam Timmis; Julie George; Mar Pujades-Rodriguez; Anoop D Shah; Spiros Denaxas; Ian R White; Mark J Caulfield; John E Deanfield; Liam Smeeth; Bryan Williams; Aroon Hingorani; Harry Hemingway
Journal:  Lancet       Date:  2014-05-31       Impact factor: 79.321

Review 10.  Task shifting for non-communicable disease management in low and middle income countries--a systematic review.

Authors:  Rohina Joshi; Mohammed Alim; Andre Pascal Kengne; Stephen Jan; Pallab K Maulik; David Peiris; Anushka A Patel
Journal:  PLoS One       Date:  2014-08-14       Impact factor: 3.240

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  2 in total

1.  Financial implications of protocol-based hypertension treatment: an insight into medication costs in public and private health sectors in India.

Authors:  Swagata Kumar Sahoo; Anupam Khungar Pathni; Ashish Krishna; Bhawna Sharma; Danielle Cazabon; Andrew E Moran; Dagmara Hering
Journal:  J Hum Hypertens       Date:  2022-10-21       Impact factor: 2.877

2.  Building the health-economic case for scaling up the WHO-HEARTS hypertension control package in low- and middle-income countries.

Authors:  Andrew E Moran; Margaret Farrell; Danielle Cazabon; Swagata Kumar Sahoo; Doris Mugrditchian; Anirudh Pidugu; Carlos Chivardi; Magdalena Walbaum; Senait Alemayehu; Wanrudee Isaranuwatchai; Chaisiri Ankurawaranon; Sohel R Choudhury; Sarah J Pickersgill; David A Watkins; Muhammad Jami Husain; Krishna D Rao; Kunihiro Matsushita; Matti Marklund; Brian Hutchinson; Rachel Nugent; Deliana Kostova; Renu Garg
Journal:  Rev Panam Salud Publica       Date:  2022-09-02
  2 in total

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