Scaling up noncommunicable disease care in a resource-limited context: lessons learned and implications for policy

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We report the results of a four-year, Ethiopian project to expand this model of NCD care to 15 primary hospitals and 45 health centres encompassing a wide geographical spread and serving a population of approximately 7.5 million people. Methods: Following baseline assessment of the 60 sites, 30 master trainers were used to cascade train a total of 621 health workers in the diagnosis, management and health education of the major common NCDs identified in a scoping review (hypertension, diabetes, chronic respiratory disease and epilepsy). Pre- and post-training assessments and regular mentoring visits were carried out to assess progress and remedy supply or equipment shortages and establish reporting systems. The project was accompanied by a series of community engagement activities to raise awareness and improve health seeking behaviour. Results: A total of 643,296 people were screened for hypertension and diabetes leading to a new diagnosis in 24,313 who were started on treatment. Significant numbers of new cases of respiratory disease (3,986) and epilepsy (1,925) were also started on treatment. Mortality rates were low except for hypertension in the rural health centres where 311 (10.2%) died during the course of the project. Loss to follow up (LTFU), defined as failure to attend clinic for >6 months despite reminders, was low in the hospitals but represented a significant problem in the urban and rural health centres with up to 20 to 30 % of patients with hypertension or diabetes absenting from treatment by the end of the project. Estimates of the population disease burden enrolled within the project, however, were disappointing; asthma (0.49%), hypertension (1.7%), epilepsy (3.3%) and diabetes (3.4%). Conclusion: This project demonstrates the feasibility of scaling up integrated NCD services in a variety of locations, with modest cost and methodology that is replicable and highly sustainable. However, the relatively small gain in the detection and treatment of common NCDs highlights the huge challenge in making NCD services available to all. Figures Figure 1 Summary Points There is a large body of literature recommending decentralisation of noncommunicable disease (NCD) care, but extremely few “real-world” examples at scale. Those that do are largely examples of NCD care limited to single diseases and in similar geographical or cultural settings. This project provides screening, enrolment and clinical outcomes data for fully integrated, multi-level NCD clinics across a wide geographical area in Africa’s second most populous nation. It is one of the first examples of scaled-up comprehensive care for all-comers with chronic noninfectious disease in rural and urban Ethiopia. It’s major limitation is that it is a “real-world” intervention and observational cohort, studied over a period constrained by a global pandemic and internal civil conflict. It uses routinely collected clinical data, limiting the ability to fully evaluate all relevant clinical outcomes. Introduction Non-communicable diseases (NCDs) are fast becoming the major cause of death and disability in many resource-limited countries especially in sub-Saharan Africa. In Ethiopia, NCDs together with injuries currently account for 44% of the total annual mortality [ 1 ] with cardiovascular/respiratory disease and diabetes being the major causes [ 2 ]. Yet the country remains among the world’s lowest income countries with a per capita gross national income of $ 960 and 24% of the population living below the poverty line (US $ 1.90 per day) with correspondingly low per capita health expenditure [ 3 ]. In addressing this problem the World Health Organization (WHO) has emphasized the importance of strengthening primary care systems and integrating cost-effective NCD interventions [ 4 ]. However, in Ethiopia as with many other resource-limited countries in sub-Saharan Africa, these systems remain poorly developed, particularly in the rural areas where most of the population live. Primary care in Ethiopia is delivered through a system of small primary (district) hospitals, health centres and health posts. Although the primary hospitals and health centres are generously staffed [ 1 ], a focus on acute care delivery (vaccinations, communicable diseases, and maternal and child health) together with the lack of expertise has limited their ability to provide effective NCD services. As a result, NCD care has been restricted to the secondary or tertiary hospitals found in the larger towns and cities. Over 20 years ago we developed a decentralized model for NCD care in Ethiopia, concentrating on locally prevalent conditions [ 5 ]. This was based on a group of 17 rural health centres situated around the University Hospitals of Gondar and Jimma, 750km northwest and 330km southwest of the capital, Addis Ababa, respectively. Nurses in the health centres through in-service training and support were enabled to effectively diagnose and initiate treatment in uncomplicated cases [ 6 , 7 ]. In 2014 the Ethiopian Ministry of Health (MoH) adopted this model and turned to partners to help scale up NCD care as part of its national strategic action plan, which emphasizes the need to strengthen and reorientate health systems to address prevention and control of NCDs through people-centred primary care and universal health coverage [ 8 ]. We report the results of a four-year project to expand this model of NCD care to primary hospitals and health centres in a variety of different locations with a wide geographical spread within Ethiopia. Methods/Description of project Organizational context Two NGOs, The Tropical Health Education Trust (THET) and Health Poverty Action (HPA), with extensive experience in decentralizing NCD care and primary health care interventions including community development, respectively, partnered with the Ethiopian MoH in a Novartis Social Business-funded project in 15 hospitals and 45 health centres (Figure 1) with the aim of increasing access to services for NCDs in six Ethiopian regions (Amhara, Tigray, Oromia, SNNPR, Benshangul-Gumuz and Afar) and one city administration (Addis Ababa, the capital city). Because of the outbreak of civil conflict, the eight original project sites in Tigray became inaccessible and were replaced with new sites in Benshangul and Afar. Of the 15 hospitals, three were general hospitals in Addis Ababa and 12 primary hospitals across the selected regions, while among the 45 health centres, 14 were urban and 31 rural. Essential NCD medicines were supplied through the MoH and dispensed at low cost or free for those on very low incomes. Figure one here. Baseline evaluation Comprehensive assessments were carried out in all 60 project sites using a modified version of the WHO Service Availability and Readiness Assessment (SARA) tool [9]. Structured interviews of hospital or health centre staff, reviews of medical records and general observation of the resources available provided information on the human resources available, the current patient throughput, laboratory facilities and pharmaceutical supplies relevant to NCDs. The hospitals and health centres were generally well-staffed (Table 1) although at project commencement there were no doctors below the primary hospital level. All the urban centres and almost all the health centres had access to water and power supplies although periodic interruptions were common in each region. All had some form of power back up. The urban hospitals served large populations with their catchment area overlapping somewhat with other providers. In contrast, there was enormous variation in the population covered by the health centres which ranged from as little as 2,000 to 92,000 in some locations depending on the area and population density. Services and facilities for NCD patients were sparse and patchy and, apart from the medical staff, none of the nurses and health officers had been specifically trained in NCD patient care. Table 1 here. Project design Training A system of cascade training was developed for the project. Initially, 30 general practitioner Master Trainers (MTs) were recruited from the 15 hospitals in the project with the aim that they would be leaders of change in improving NCD services in their respective hospitals and satellite health centres. During a 10-day residential course, training was delivered to cover the major common NCDs identified in a scoping review (hypertension, diabetes, chronic respiratory diseases and epilepsy) [1], the use of the Practical Approach to Care Kit (PACK) algorithms [10], together with instruction on training methods, particularly adult teaching and mentoring skills. Pre- and post-test evaluations were carried out before and after each topic. The MTs subsequently delivered a four-day training course to their respective catchment health centre staff using both didactic and interactive teaching methods. Again, daily pre- and post-training assessments were used to evaluate the knowledge and skills developed. A total of 621 health workers were trained to be responsible for patient screening, diagnosis, treatment and health education, including training for Health Extension Workers (HEWs). In the second year an additional ‘gap-filling’ training was arranged for health workers to fill vacancies created by health workers who had been trained but left their institutions or changed their job role. Following their return to their health facility, they were encouraged to start seeing and managing patients with NCDs, seeking advice from senior staff in the health centres or primary hospitals if necessary. Diagnostic criteria and management protocols for NCDs together with their risk factors, e.g. smoking, alcohol and obesity, were according to PACK guidelines. Supplementary Table 1 lists the drug treatments which were available in the health centres and hospitals. Patients were usually prescribed one month’s supply of medicines which cost approximately 2-4 US$ /month, although a waiver system in Ethiopia permits access to free health care for those most impoverished. NCD equipment and data collection As many of the health centres did not have access to the equipment required for the diagnosis and management of NCDs, basic equipment including weighing scales, sphygmomanometers and glucometers were provided. Both the health centres and hospitals received the MoH data collection tools which included patient registers, tally sheets, intake forms and follow-up forms with reporting formats for each NCD covered by the project training. Data from the clinics were reported on a quarterly basis on paper-based recording sheets. Mentoring and supervision Regular visits to both hospitals and health centres were carried out by a team consisting of members of the project team, MTs and local health office staff to discuss overall progress and identify any problems, for example drug supplies or equipment shortages. The MTs also visited the health centres regularly to give them in-service training using available cases or PACK in order to remedy gaps in diagnostic or patient communication skills. In addition, there were regular catchment area meetings involving local staff and annual stakeholder meetings in Addis Ababa for MoH NCD directorate staff, project staff, local health office staff, medical directors and facility heads. This involved a total of 458 mentoring visits, equivalent to 1,374 days over the 4½years of the project. Community engagement During the implementation of the project, a series of community engagement activities were held to raise awareness about NCDs aimed at improving health-seeking behaviour. A total of 1,045,302 people were reached through events such as screening sessions, car-free days, market days and other gatherings in the intervention areas. In addition, a total of 6,714 religious and community leaders were engaged in a series of dialogues to help address the social norms and taboos which hinder people from accessing health services. Finally, specially designed radio messaging was broadcast to reach an estimated audience of more than one million people, providing information on NCDs, their risk factors and available treatment in nearly health centres. Screening for NCDs The local health staff in the project areas were encouraged to screen people opportunistically for NCDs (hypertension and diabetes) in triage/outpatient rooms in health centres. Screening for hypertension was carried out in all patients over 18 years and for diabetes in >40 year olds or those with hypertension. Other strategies used included carrying out open-air campaigns on car-free days, at marketplaces and the entrance to government offices. For the open-air events a small tent was erected with loudspeakers broadcasting music and announcements together with the distribution of leaflets. People with raised blood pressure or blood sugar were given a referral slip for further tests at primary hospitals or health centres. HEWs were trained to recognize symptoms of epilepsy or asthma and arrange appropriate referral. Results Project activity Between November 2018 and March 2023, 643,296 people were screened for hypertension and diabetes leading to a new diagnosis in 24,313 who were started on treatment. Table 2 shows the total numbers of new NCD cases registered during the project according to diagnosis and type of health facility. Large numbers were screened for hypertension in all locations with the highest detection rate in Addis Ababa (7.3%) and among the primary hospitals (5.1%). Detection rates in the health centres were much lower (1.6 % and 2.5% in the urban and rural health centres respectively). Because of the age restriction fewer people were screened for diabetes, nevertheless significant numbers of new cases were detected. Highest detection rates were reported in the Addis Ababa and primary hospitals (59.6% and 14.9% respectively) with much lower rates in the health centres (3.4% and 1.1% in urban and rural health centres respectively). For respiratory disease and epilepsy there were no specific efforts to find patients, yet significant numbers were enrolled in all types of facility. Reported mortality rates were low with the exception of hypertension in the rural health centres where 311 (10.2%) died over the course of the project. Loss to follow up (LTFU), defined as failure to attend clinic for >6 months despite reminders, was low in the hospitals but represented a significant problem in the urban and rural health centres with up to 20 to 30 % of patients with hypertension or diabetes absenting from treatment by the end of the project. Table 2 here Project impact To evaluate the project’s impact on the overall burden of disease in the population, we compared the numbers of patients enrolled with estimates of the potential total numbers of cases for each NCD, derived from published population prevalence data, according to the type of health facility (Table 3). For all NCDs only a small proportion of the potential number of cases in the population had been enrolled within the project. Asthma and hypertension had the lowest overall detection rates (0.49% and 1.7% respectively) while epilepsy (3.3%) and diabetes (3.4%) had the highest. However, there was wide variability between different types of facility. Detection rates were highest in the Addis Ababa hospitals and were lowest in the primary hospitals while urban health centres achieved higher rates than the rural health centres. The reported levels of control after 6 months treatment for hypertension (defined as achieved blood pressure <140/90 mmHg) or diabetes (random blood sugar <180mg% or fasting blood sugar <130mg%) in the quarterly returns were consistently greater than 85%. Table 3 here Finance Table 4 shows the estimated annual costs of the project (provided by the donor) together with an estimate of the cost per patient enrolled. Salaries for the Addis Ababa-based staff were a major component as were travel costs given the widely dispersed location of many of the project sites. However, community engagement proved to be the most expensive overall cost. Table 4 here Staff turnover Rapid turnover of staff was a major problem. Of the original 30 mentors trained, only 10 were still in place by the end of the project. To replace these a further 17 new mentors were trained. At health centre level almost 80% had moved on by the end of the project and we needed to re-train mentors for almost all sites. HEWs were least affected by turnover and all 610 trained remained in place for the duration of the project. Drug and equipment availability Essential medicines for hypertension, diabetes, asthma and epilepsy were available in almost all hospitals at the start of the project although sustaining adequate supplies proved to be a major problem because of difficulties with the national supply chain system. The situation was different in the health centres. At the start of the project NCD medicines and diagnostic equipment were patchily available in some of the centres. Midway through the project 32 of the health centres answered a short questionnaire asking about availability of essential NCD medicines. Hypertensives were available in all but four centres (23 had diuretics, 22 ACE inhibitors and 28 calcium channel blockers); diabetes medications in 25 (biguanides in 19 and sulphonylureas in 22); anticonvulsants in 20 and asthma inhalers in just 14. At the end of the project glucometers and sphygmomanometers/stethoscopes were present in all the NCD clinics (at least two of each). However, supplying enough test strips for glucometers proved to be difficult. Discussion We report the outcome of a large-scale intervention to deliver NCD services for major common diseases at the community-level where hitherto there was little or no provision. The intervention was embedded within the existing Ethiopian health service, using the existing staff and infrastructure. The project sites included large hospitals in the capital city, Addis Ababa, primary hospitals and both urban and rural health centres and for reasons of equality had a wide geographical coverage (Fig. 1 ) encompassing a population of approximately 7.5 million people (allowing for overlap of the catchment between large hospitals and between primary hospitals and their satellite health centres). The project was underpinned by close relationships with the MoH at national, regional and district (woreda) level and co-designed with the MoH, and the core activities were delivered by their personnel. Every aspect of set-up was tested and refined through processes of feedback, reflection, and re-design. The tools and methods jointly developed continue to be used and are part of the legacy of the project. Although a number of primary health care models of NCD care have been developed in sub-Saharan Africa, few have described an integrated, decentralized approach at the community level. A recent review of NCD and mental health interventions identified 188 studies of which only 29 were conducted in low-income countries [ 11 ]. Of these, just 11 were at the community or health centre level, and most focussed on a single disease or were small-scale pilot studies. Of the four comparable studies two were from Malawi [ 12 , 13 ], one from the Cameroon[ 14 ] and data from our previous work in Ethiopia [ 5 ]. Assessing the impact of the project on NCD services and the burden of disease in the community is more difficult. The data from the health centres suggests that a large number of nurses and health officers had been successfully trained and that the availability of basic equipment had substantially increased as a result of the project. The screening process was particularly successful with large numbers being assessed for hypertension or diabetes. Table 2 also shows that the screening process for hypertension had a higher yield in the hospital-based projects (7.3% and 5.1%) than in the health centres (1.6% and 2.5%) which probably reflects the higher prevalence rates in the screened populations. In a similar way, diabetes was much more likely to be detected among the hospitals than the health centres. The very high prevalence recorded in the Addis Abba hospitals may be unreliable or merely reflect the higher prevalence of diabetes attending those facilities. Epilepsy and respiratory disease were not part of the screening programme and the numbers of patients registered during the project were correspondingly much lower but with significant numbers enrolled for treatment in both urban and rural locations. Most people attending clinics were adequately controlled although our data is not complete enough to make definitive statements and follow-up will be needed to see whether this is maintained over the longer term. We have previously shown that staff in rural clinics in Ethiopia are well able to manage hypertension using simple regimes [ 6 ]. However, despite intensive outreach and engagement, uptake was low and retention on treatment somewhat disappointing (Table 3 ) although the duration of the project may have been too short to build up the level of community engagement and trust in the clinics and forms of NCD management required to make a substantial impact on the disease burden. Previous work in Ethiopia has demonstrated the numerous barriers to treatment, including access/distance, consistency of drug availability, cost (out-of-pocket expense and time) and cultural beliefs and practices related to health and healing [ 15 ]. One problem that became evident during the project was competition with other vertical health programmes. This was particularly evident in the more remote, lower-level care settings, where the NCD project was introduced alongside other, often better-resourced programmes (e.g. antenatal care; water, sanitation and hygiene (WASH); under-fives, tuberculosis (TB), HIV/AIDS, mental health). Despite the expansion of all cadres of health staff in Ethiopia, multiple programmes are delivered by the same, hard-pressed and resource-constrained staff in rural areas. Related to this was the problems many patients reported in navigating the NCD care system resulting in confusion, mixed messaging, duplication of tests and an inefficient use of resources. It is clear that more attention needs to be given to developing the continuum of care for NCDs at all levels: supporting patients throughout their care journey from health promotion, prevention, diagnosis, treatment, to rehabilitation, and/or palliative care. Integrating NCD services with other services such as HIV/AIDS, TB etc. should be considered, as has been the case in Kenya, Uganda, Zambia, Malawi and elsewhere [ 16 – 18 ]. Few, if any studies report the financial implications of projects such as the one we describe. While project funding is complex and dependent on the scale and geographic reach as well as the economic environment, our data (Table 4 ) suggest that while the per-patient costs are fairly low, the costs are likely to be considerable especially if the ongoing costs of medicines are included. NCD patients tend to be multiply disadvantaged compared to those needing episodic treatment for acute illnesses or who are within funded programmes such as HIV/AIDs and TB. Their need for continuous treatment and the concept of a disease that cannot be cured and needs lifelong medication places a long-term financial burden on the family, is counter-cultural and is a message at variance with those coming from other traditional systems of healing praxis. Although community-based insurance schemes have been introduced in the country (in 2011), for poor rural patients even a co-payment system is likely to be a prohibitive drain on household finances in the long-term. Furthermore, enthusiasm to take part will be dampened for those not incurring healthcare costs, and the scheme will be unable to generate significant funds if only those with NCDs contribute in the long term. One of the major problems encountered in the project was ensuring accurate and consistent completion of the paper-based record system which depended on patient registers, tally sheets and intake forms for each NCD. The overly detailed registration forms were burdensome and led to incomplete and inaccurate recording which will have affected data quality in this report which, consequently, are likely to have underestimated the throughput of patients and loss to follow-up. Although during the four years of the project a number of improvements and revisions were made at central level, improved record keeping is still needed. One solution may the introduction of electronic medical records and linked IT systems which can facilitate clinical decision-making and enhance the ability to monitor outcomes, as has been shown in Malawi and elsewhere [ 19 ]. However, a cultural shift will be needed to promote the value of data in understanding what is being achieved and in driving up the quality and effectiveness of services. The availability of affordable medicines is essential for the running of NCD clinics and patient compliance [ 15 ] and, although essential medicines were provided by the MoH, at the local level supplies were not always available. In a survey of 32 health centres, while the majority had available antihypertensive and diabetes medicines a significant minority did not. Even fewer centres reported the availability of medicines for epilepsy or inhalers for asthma. Most of the health centres reported that the main reason for the poor availability was a slow-to-respond supply chain mechanism which lacked efficient and effective communications between its various levels and components. Staff turnover also proved to be a problem and required the identification of replacement trainers and mentors for almost for all sites. Loss of staff was most evident at the hospital and health centres level. By contrast all the HEWs trained during the project were retained for its duration. The likely reasons for this are the greater alternative job opportunities and financial advancement for urban-based staff coupled with the high workload and poor working environments. Finally, the arrival of Covid-19 in Ethiopia and the outbreak of civil conflict in Tigray had a significant effect on the project as travel was restricted, and it became more difficult for patients to attend hospital or health centre clinics. Despite this, mentoring and supervision of the clinics continued utilising IT solutions while clinic staff used mobile phones to keep in contact and ensure the follow-up of NCD patients. In summary, this project has demonstrated the feasibility of scaling up integrated NCD services in a variety of different locations, with modest costs, and a methodology that is replicable and is highly sustainable. While taking advantage of existing staff and infrastructure is important, the extra costs and effort involved in staff training, mentoring and community engagement are not inconsiderable for a modest gain in the detection and treatment of common NCDs. In addition, given that there are over 3,500 health centres in Ethiopia, the process of making NCD services available to all represents a huge challenge. This will need to be carried out in an evidence-based way, addressing known challenges and adapting to new ones. For the effort and investment to have the greatest impact, improving the uptake and reducing the numbers lost to treatment must be a key focus. This may include the use of IT technologies and telecare systems if these can be operated cheaply and at scale, together with further decentralisation of care so that HEWs and communities play a much greater part in health education, recognition, control and management of NCDs. Abbreviations ACE Angiotensin converting enzyme HEW Health extension workers IT Information technology LTFU lost to follow up NCD noncommunicable disease MT Master Trainers MoH Ministry of Health PACK Practical approach to care kit SARA Service availability and assessment tool SNNPR Southern Nations, Nationalities, and Peoples' Region THET Tropical Health Education Trust WHO World Health Organisation Declarations Ethics approval and consent to participate: Ethical approval with the University Faculty of Medicine Ethics Committee pending. No individuals were approached for this analysis which was based on aggregated clinic data. Consent for publication: N/A Availability of data and materials: The summary data used to generate the tables are available upon request to the corresponding author. Competing interests; The authors declare that they have no competing interests. Funding: The project was supported by a grant from Novartis Social Business to the Tropical Health Education Trust (London). Authors' contributions. YM, MM, DIWP and AM designed the project. YM and MM supervised and were involved in its execution, YM, DIWP and AM analysed the data and wrote the manuscript. All authors read and approved the final manuscript. Acknowledgements: We acknowledge advice and help in planning the project from Dr Addisu Worku, Dr Musie Gabremichael and the NCD team at the Federal Ministry of Health. We are also grateful for the help of Temesgen Degefa, Frehiwot Kebede, Abere Desie, Wesen Tilahun and Amleset Gebrehiwot without whose devotion to the project it would have not come to a successful end. We would also like to acknowledge THET deputy CEO Louise McGrath and country programme director Katharina Brassington for their unreserved commitment to the project. References Memirie ST, Dagnaw WW, Habtemariam MK, Bekele A, Yadeta D, Bekele A, Bekele W, Gedefaw M, Assefa M, Tolla MT et al : Addressing the Impact of Noncommunicable Diseases and Injuries (NCDIs) in Ethiopia: Findings and Recommendations from the Ethiopia NCDI Commission . Ethiop J Health Sci 2022, 32 (1):161-180. Tesfay FH, Zorbas C, Alston L, Backholer K, Bowe SJ, Bennett CM: Prevalence of chronic non-communicable diseases in Ethiopia: A systematic review and meta-analysis of evidence . Front Public Health 2022, 10 :936482. Bank W: The World Bank in Ethiopia . In . ; 2022. 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Manjomo RC, Mwagomba B, Ade S, Ali E, Ben-Smith A, Khomani P, Bondwe P, Nkhoma D, Douglas GP, Tayler-Smith K et al : Managing and monitoring chronic non-communicable diseases in a primary health care clinic, Lilongwe, Malawi . Public Health Action 2016, 6 (2):60-65. Abebe Bekele TG, Kassahun Amenu, Theodros Getachew, Atkure Defar, Habtamu Teklie,, Tefera Taddele GT, Misrak Getnet, Geremew Gonfa, Alemayehu Bekele, Tedla Kebede,, Yeweyenhareg Feleke DY, Mussie G/Michael, Mulugeta Guta, Fassil Shiferaw, Feyissa Challa,, Yabetse Girma KM, Yewondwossen Tadesse, Yibeltal Assefa, Amha Kebede, Kebede Worku: The hidden magnitude of raised blood pressure and elevated blood glucose in Ethiopia: A call for initiating community based NCDs risk factors screening program . Ethiopian Journal of Health Development 2017, 31 :362-369. Mulugeta T, Ayele T, Zeleke G, Tesfay G: Asthma control and its predictors in Ethiopia: Systematic review and meta-analysis . PloS one 2022, 17 (1):e0262566. Tekle-Haimanot R, Forsgren L, Ekstedt J: Incidence of epilepsy in rural central Ethiopia . Epilepsia 1997, 38 (5):541-546. Tables Table 1: Baseline data from the project hospitals and health centres. Nature of health facility Addis Ababa hospitals Primary hospitals Urban health centres Rural health centres Total No. 3 12 14 31 No. of linked health posts NA 360 20 178 Catchment population* 900,000 6,576,423 628,504 981,179 Total Staff 1,230 870 692 569 Doctors 141 127 0 0 Nurses 953 569 380 308 Health Officers 44 24 159 69 Pharmacists 89 118 110 70 IT staff 3 32 43 36 Distance to nearest referral hospital (mean in km) 5 171 6 43 *In some instances, the catchment populations of hospitals overlap with the catchment populations of health centres. Table 2: Numbers screened for hypertension and diabetes together with numbers of NCD cases enrolled to care during the project according to diagnosis and type of health facility. Reported mortality and loss to follow up (LTFU) over the duration of the study are also shown. Type of health facility Addis Ababa hospitals Primary hospitals Urban health centres Rural health centres Number of facilities 3 12 14 31 Hypertension Screened 66,880 55,467 293,235 123,212 Enrolled (%) 4,894(7.3) 2,813(5.1) 4,815(1.6) 3,045(2.5) Died 0 8 5 311 LTFU 3 88 837 251 Diabetes Screened 7,447 14,008 58,288 24,759 Enrolled (%) 4,441 (59.6) 2,083(14.8) 1953(3.4) 269(1.1) Died 0 5 7 6 LTFU 39 46 439 77 Respiratory Enrolled 881 360 1,950 795 Died 8 0 15 2 LTFU 0 52 3 49 Epilepsy Enrolled 480 639 499 307 Died 0 32 0 15 LTFU 0 2 1 15 Table 3: Numbers of patients diagnosed as a proportion of the total estimated caseload or each of the major diagnoses, according to the type of health facility. Nature of health facility Addis Ababa hospitals Primary Hospitals Urban health centres Rural health centres Number 3 12 14 31 Catchment population 900,000 6,576,423 628,504 981,179 Hypertension Estimated prevalence 1 (%) 15 15 15 7 Predicted caseload3 67,500 493,232 47,138 34,341 Case detection (%) 4,894 (7.3) 2,813(0.6) 4,815(10.2) 3,045(8.9) Diabetes Estimated prevalence 1 (%) 6 6 6 3 Predicted caseload 27,000 197,293 18,855 14,718 Case detection (%) 4,441 (16.4) 2,083(1.1) 1,953(10.4) 269(1.8) Asthma Estimated prevalence 2 (%) 9 9 9 9 Predicted caseload 81,000 591,878 56,565 88,306 Case detection (%) 881(1.1) 360(0.06) 1,950(3.4) 795(0.9) Epilepsy Estimated prevalence 3 (%) 0.64 0.64 0.64 0.64 Predicted caseload 5,760 42,089 4,022 6,280 Case detection (%) 480(8.3) 639(1.5) 499(12.4) 307(4.9) 1 ref [20] 2 ref[21] 3 ref [22] Predicted caseload based on estimated adult populations for hypertension and diabetes and total populations for asthma and epilepsy. Table 4: Project costs. Project cost per year (US$) Addis-based project staff 50,469 Travel and training* 75,407 Equipment* 16,099 Community engagement 86.702 Total cost 228,677 Cost per patient enrolled 10.5 *Annualised costs Additional Declarations No competing interests reported. Supplementary Files SupplementaryTable1.docx Cite Share Download PDF Status: Published Journal Publication published 24 Jul, 2024 Read the published version in BMC Health Services Research → Version 1 posted Editorial decision: Revision requested 14 Mar, 2024 Submission checks completed at journal 14 Mar, 2024 Editor assigned by journal 14 Mar, 2024 First submitted to journal 13 Feb, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3953489","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":279702016,"identity":"c86bf42b-b4a6-4c6a-b777-6f82f8bfc60c","order_by":0,"name":"Yoseph Mamo","email":"","orcid":"","institution":"Tropical Health Education Trust","correspondingAuthor":false,"prefix":"","firstName":"Yoseph","middleName":"","lastName":"Mamo","suffix":""},{"id":279702017,"identity":"856e397a-7a4e-47fb-950b-36bf5ec4c451","order_by":1,"name":"Mirchaye Mekoro","email":"","orcid":"","institution":"Health Poverty Action","correspondingAuthor":false,"prefix":"","firstName":"Mirchaye","middleName":"","lastName":"Mekoro","suffix":""},{"id":279702018,"identity":"0751884d-87a5-4182-9a60-9326b184cfd7","order_by":2,"name":"David Phillips","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYDCCw0D8AU2MmaAWxhkQJmMDcVoOAFXwkKSF7ziP2WPbnHvyDPyHjz/4uINBnr+Bx9gAnxbJwzzmxrnbig0bJNISG2eeYTCccYDHOAGfFoPDvNukc7clJDBI8Bg287YxMG5g4DE+QFCLJUgL/xmwFnvitDCCtDDkgLUkgrTgdZjkYf7vhr3bEgzbgH6ZObNNInnGYbZivN7nO38s7cHPbQny/PyHD3z42GZj29/evFkCnxYgYEMiGSQIRiSS4lEwCkbBKBgFuAAALNdBBei73nAAAAAASUVORK5CYII=","orcid":"","institution":"University of Southampton","correspondingAuthor":true,"prefix":"","firstName":"David","middleName":"","lastName":"Phillips","suffix":""},{"id":279702019,"identity":"1aecc8b2-7456-4021-815c-e5fee5968e46","order_by":3,"name":"Andrew Mortimore","email":"","orcid":"","institution":"University of Southampton","correspondingAuthor":false,"prefix":"","firstName":"Andrew","middleName":"","lastName":"Mortimore","suffix":""}],"badges":[],"createdAt":"2024-02-13 12:19:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3953489/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3953489/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12913-024-11328-x","type":"published","date":"2024-07-25T00:25:44+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":53007309,"identity":"6f9d2169-2434-48d6-a0ee-0314fec574d4","added_by":"auto","created_at":"2024-03-19 15:13:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":304561,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of initial project sites.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-3953489/v1/66c250c253ae6ac0f6d1c989.png"},{"id":61197033,"identity":"11d4c2a6-327c-4f6a-85ce-24796a16fadb","added_by":"auto","created_at":"2024-07-27 00:25:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1300307,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3953489/v1/84a74578-3843-4089-aa04-cb2df9078c9a.pdf"},{"id":53007293,"identity":"cac42103-6696-4331-baa7-89d0444b8c74","added_by":"auto","created_at":"2024-03-19 15:13:39","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":13788,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-3953489/v1/67a596ae2044907972cdcf4e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Scaling up noncommunicable disease care in a resource-limited context: lessons learned and implications for policy","fulltext":[{"header":"Summary Points","content":"\u003cul\u003e\n \u003cli\u003eThere is a large body of literature recommending decentralisation of noncommunicable disease (NCD) care, but extremely few “real-world” examples at scale. Those that do are largely examples of NCD care limited to single diseases and in similar geographical or cultural settings. This project provides screening, enrolment and clinical outcomes data for fully integrated, multi-level NCD clinics across a wide geographical area in Africa’s second most populous nation.\u003c/li\u003e\n \u003cli\u003eIt is one of the first examples of scaled-up comprehensive care for all-comers with chronic noninfectious disease in rural and urban Ethiopia.\u003c/li\u003e\n \u003cli\u003eIt’s major limitation is that it is a “real-world” intervention and observational cohort, studied over a period constrained by a global pandemic and internal civil conflict. It uses routinely collected clinical data, limiting the ability to fully evaluate all relevant clinical outcomes.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Introduction","content":"\u003cp\u003e Non-communicable diseases (NCDs) are fast becoming the major cause of death and disability in many resource-limited countries especially in sub-Saharan Africa. In Ethiopia, NCDs together with injuries currently account for 44% of the total annual mortality [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] with cardiovascular/respiratory disease and diabetes being the major causes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Yet the country remains among the world\u0026rsquo;s lowest income countries with a \u003cem\u003eper capita\u003c/em\u003e gross national income of \u003cspan\u003e$\u003c/span\u003e960 and 24% of the population living below the poverty line (US\u003cspan\u003e$\u003c/span\u003e 1.90 per day) with correspondingly low \u003cem\u003eper capita\u003c/em\u003e health expenditure [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In addressing this problem the World Health Organization (WHO) has emphasized the importance of strengthening primary care systems and integrating cost-effective NCD interventions [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, in Ethiopia as with many other resource-limited countries in sub-Saharan Africa, these systems remain poorly developed, particularly in the rural areas where most of the population live.\u003c/p\u003e \u003cp\u003ePrimary care in Ethiopia is delivered through a system of small primary (district) hospitals, health centres and health posts. Although the primary hospitals and health centres are generously staffed [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], a focus on acute care delivery (vaccinations, communicable diseases, and maternal and child health) together with the lack of expertise has limited their ability to provide effective NCD services. As a result, NCD care has been restricted to the secondary or tertiary hospitals found in the larger towns and cities. Over 20 years ago we developed a decentralized model for NCD care in Ethiopia, concentrating on locally prevalent conditions [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This was based on a group of 17 rural health centres situated around the University Hospitals of Gondar and Jimma, 750km northwest and 330km southwest of the capital, Addis Ababa, respectively. Nurses in the health centres through in-service training and support were enabled to effectively diagnose and initiate treatment in uncomplicated cases [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn 2014 the Ethiopian Ministry of Health (MoH) adopted this model and turned to partners to help scale up NCD care as part of its national strategic action plan, which emphasizes the need to strengthen and reorientate health systems to address prevention and control of NCDs through people-centred primary care and universal health coverage [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. We report the results of a four-year project to expand this model of NCD care to primary hospitals and health centres in a variety of different locations with a wide geographical spread within Ethiopia.\u003c/p\u003e"},{"header":"Methods/Description of project","content":"\u003cp\u003e\u003cem\u003eOrganizational context\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTwo NGOs, The Tropical Health Education Trust (THET) and Health Poverty Action (HPA), with extensive experience in decentralizing NCD care and primary health care interventions including community development, respectively, partnered with the Ethiopian MoH in a Novartis Social Business-funded project in 15 hospitals and 45 health centres (Figure 1) with the aim of increasing access to services for NCDs in six Ethiopian regions (Amhara, Tigray, Oromia, SNNPR, Benshangul-Gumuz and Afar) and one city administration (Addis Ababa, the capital city). Because of the outbreak of civil conflict, the eight original project sites in Tigray became inaccessible and were replaced with new sites in Benshangul and Afar. Of the 15 hospitals, three were general hospitals in Addis Ababa and 12 primary hospitals across the selected regions, while among the 45 health centres, 14 were urban and 31 rural. Essential NCD medicines were supplied through the MoH and dispensed at low cost or free for those on very low incomes.\u003c/p\u003e\n\u003cp\u003eFigure one here.\u003c/p\u003e\n\u003cp\u003eBaseline evaluation\u003c/p\u003e\n\u003cp\u003eComprehensive assessments were carried out in all 60 project sites using a modified version of the WHO Service Availability and Readiness Assessment (SARA) tool\u0026nbsp;[9]. Structured interviews of hospital or health centre staff, reviews of medical records and general observation of the resources available provided information on the human resources available, the current patient throughput, laboratory facilities and pharmaceutical supplies relevant to NCDs.\u003c/p\u003e\n\u003cp\u003eThe hospitals and health centres were generally well-staffed (Table 1) although at project commencement there were no doctors below the primary hospital level. All the urban centres and almost all the health centres had access to water and power supplies although periodic interruptions were common in each region. All had some form of power back up. The urban hospitals served large populations with their catchment area overlapping somewhat with other providers. In contrast, there was enormous variation in the population covered by the health centres which ranged from as little as 2,000 to 92,000 in some locations depending on the area and population density. Services and facilities for NCD patients were sparse and patchy and, apart from the medical staff, none of the nurses and health officers had been specifically trained in NCD patient care.\u003c/p\u003e\n\u003cp\u003eTable 1 here.\u003c/p\u003e\n\u003cp\u003eProject design\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTraining\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA system of cascade training was developed for the project. Initially, 30 general practitioner Master Trainers (MTs) were recruited from the 15 hospitals in the project with the aim that they would be leaders of change in improving NCD services in their respective hospitals and satellite health centres. During a 10-day residential course, training was delivered to cover the major common NCDs identified in a scoping review (hypertension, diabetes, \u0026nbsp;chronic respiratory diseases and epilepsy) \u0026nbsp;[1], the use of the Practical Approach to Care Kit (PACK) algorithms\u0026nbsp;[10], together with instruction on training methods, particularly adult teaching and mentoring skills. Pre- and post-test evaluations were carried out before and after each topic. The MTs subsequently delivered a four-day training course to their respective catchment health centre staff using both didactic and interactive teaching methods. Again, daily pre- and post-training assessments were used to evaluate the knowledge and skills developed. A total of 621 health workers were trained to be responsible for patient screening, diagnosis, treatment and health education, including training for Health Extension Workers (HEWs). In the second year an additional ‘gap-filling’ training was arranged for health workers to fill vacancies created by health workers who had been trained but left their institutions or changed their job role. Following their return to their health facility, they were encouraged to start seeing and managing patients with NCDs, seeking advice from senior staff in the health centres or primary hospitals if necessary. Diagnostic criteria and management protocols for NCDs together with their risk factors, e.g. smoking, alcohol and obesity, were according to PACK guidelines. Supplementary Table 1 lists the drug treatments which were available in the health centres and hospitals. Patients were usually prescribed one month’s supply of medicines which cost approximately 2-4 US$ /month, although a waiver system in Ethiopia permits access to free health care for those most impoverished.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNCD equipment and data collection\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAs many of the health centres did not have access to the equipment required for the diagnosis and management of NCDs, basic equipment including weighing scales, sphygmomanometers and glucometers were provided. Both the health centres and hospitals received the MoH data collection tools which included patient registers, tally sheets, intake forms and follow-up forms with reporting formats for each NCD covered by the project training. Data from the clinics were reported on a quarterly basis on paper-based recording sheets.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMentoring and supervision\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eRegular visits to both hospitals and health centres were carried out by a team consisting of members of the project team, MTs and local health office staff to discuss overall progress and identify any problems, for example drug supplies or equipment shortages. The MTs also visited the health centres regularly to give them in-service training using available cases or PACK in order to remedy gaps in diagnostic or patient communication skills. In addition, there were regular catchment area meetings involving local staff and annual stakeholder meetings in Addis Ababa for MoH NCD directorate staff, project staff, local health office staff, medical directors and facility heads. This involved a total of 458 mentoring visits, equivalent to 1,374 days over the 4½years of the project.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCommunity engagement\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDuring the implementation of the project, a series of community engagement activities were held to raise awareness about NCDs aimed at improving health-seeking behaviour. A total of 1,045,302 people were reached through events such as screening sessions, car-free days, market days and other gatherings in the intervention areas. In addition, a total of 6,714 religious and community leaders were engaged in a series of dialogues to help address the social norms and taboos which hinder people from accessing health services. Finally, specially designed radio messaging was broadcast to reach an estimated audience of more than one million people, providing information on NCDs, their risk factors and available treatment in nearly health centres.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eScreening for NCDs\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe local health staff in the project areas were encouraged to screen people opportunistically for NCDs (hypertension and diabetes) in triage/outpatient rooms in health centres. Screening for hypertension was carried out in all patients over 18 years \u0026nbsp;and for diabetes in \u0026gt;40 year olds or those with hypertension. Other strategies used included carrying out open-air campaigns on car-free days, at marketplaces and the entrance to government offices. For the open-air events a small tent was erected with loudspeakers broadcasting music and announcements together with the distribution of leaflets. People with raised blood pressure or blood sugar were given a referral slip for further tests at primary hospitals or health centres. HEWs were trained to recognize symptoms of epilepsy or asthma and arrange appropriate referral.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eProject activity\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBetween November 2018 and March 2023, 643,296 people were screened for hypertension and diabetes leading to a new diagnosis in 24,313 who were started on treatment. Table 2 shows the total numbers of new NCD cases registered during the project according to diagnosis and type of health facility. Large numbers were screened for hypertension in all locations with the highest detection rate in Addis Ababa (7.3%) and among the primary hospitals (5.1%). Detection rates in the health centres were much lower (1.6 % and 2.5% in the urban and rural health centres respectively). Because of the age restriction fewer people were screened for diabetes, nevertheless significant numbers of new cases were detected. Highest detection rates were reported in the Addis Ababa and primary hospitals (59.6% and 14.9% respectively) with much lower rates in the health centres (3.4% and 1.1% in urban and rural health centres respectively). For respiratory disease and epilepsy there were no specific efforts to find patients, yet significant numbers were enrolled in all types of facility. Reported mortality rates were low with the exception of hypertension in the rural health centres where 311 (10.2%) died over the course of the project. Loss to follow up (LTFU), defined as failure to attend clinic for \u0026gt;6 months despite reminders, was low in the hospitals but represented a significant problem in the urban and rural health centres with up to 20 to 30 % of patients with hypertension or diabetes absenting from treatment by the end of the project.\u003c/p\u003e\n\u003cp\u003eTable 2 here\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eProject impact\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo evaluate the project’s impact on the overall burden of disease in the population, we compared the numbers of patients enrolled with estimates of the potential total numbers of cases for each NCD, derived from published population prevalence data, according to the type of health facility (Table 3). For all NCDs only a small proportion of the potential number of cases in the population had been enrolled within the project. Asthma and hypertension had the lowest overall detection rates (0.49% and 1.7% respectively) while epilepsy (3.3%) and diabetes (3.4%) had the highest. \u0026nbsp;However, there was wide variability between different types of facility. Detection rates were highest in the Addis Ababa hospitals and were lowest in the primary hospitals while urban health centres achieved higher rates than the rural health centres. The reported levels of control after 6 months treatment for hypertension (defined as achieved blood pressure \u0026lt;140/90 mmHg) or diabetes (random blood sugar \u0026lt;180mg% or fasting blood sugar \u0026lt;130mg%) in the quarterly returns were consistently greater than 85%.\u003c/p\u003e\n\u003cp\u003eTable 3 here\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFinance\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTable 4 shows the estimated annual costs of the project (provided by the donor) together with an estimate of the cost per patient enrolled. Salaries for the Addis Ababa-based staff were a major component as were travel costs given the widely dispersed location of many of the project sites. However, community engagement proved to be the most expensive overall cost.\u003c/p\u003e\n\u003cp\u003eTable 4 here\u003c/p\u003e\n\u003cp\u003eStaff turnover\u003c/p\u003e\n\u003cp\u003eRapid turnover of staff was a major problem. Of the original 30 mentors trained, only 10 were still in place by the end of the project. To replace these a further 17 new mentors were trained. At health centre level almost 80% had moved on by the end of the project and we needed to re-train mentors for almost all sites. HEWs were least affected by turnover and all 610 trained remained in place for the duration of the project.\u003c/p\u003e\n\u003cp\u003eDrug and equipment availability\u003c/p\u003e\n\u003cp\u003eEssential medicines for hypertension, diabetes, asthma and epilepsy were available in almost all hospitals at the start of the project although sustaining adequate supplies proved to be a major problem because of difficulties with the national supply chain system. The situation was different in the health centres. At the start of the project NCD medicines and diagnostic equipment were patchily available in some of the centres. Midway through the project 32 of the health centres answered a short questionnaire asking about availability of essential NCD medicines. Hypertensives were available in all but four centres (23 had diuretics, 22 ACE inhibitors and 28 calcium channel blockers); diabetes medications in 25 (biguanides in 19 and sulphonylureas in 22); anticonvulsants in 20 and asthma inhalers in just 14. At the end of the project glucometers and sphygmomanometers/stethoscopes were present in all the NCD clinics (at least two of each). However, supplying enough test strips for glucometers proved to be difficult.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe report the outcome of a large-scale intervention to deliver NCD services for major common diseases at the community-level where hitherto there was little or no provision. The intervention was embedded within the existing Ethiopian health service, using the existing staff and infrastructure. The project sites included large hospitals in the capital city, Addis Ababa, primary hospitals and both urban and rural health centres and for reasons of equality had a wide geographical coverage (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) encompassing a population of approximately 7.5\u0026nbsp;million people (allowing for overlap of the catchment between large hospitals and between primary hospitals and their satellite health centres). The project was underpinned by close relationships with the MoH at national, regional and district (woreda) level and co-designed with the MoH, and the core activities were delivered by their personnel. Every aspect of set-up was tested and refined through processes of feedback, reflection, and re-design. The tools and methods jointly developed continue to be used and are part of the legacy of the project. Although a number of primary health care models of NCD care have been developed in sub-Saharan Africa, few have described an integrated, decentralized approach at the community level. A recent review of NCD and mental health interventions identified 188 studies of which only 29 were conducted in low-income countries [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Of these, just 11 were at the community or health centre level, and most focussed on a single disease or were small-scale pilot studies. Of the four comparable studies two were from Malawi [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], one from the Cameroon[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and data from our previous work in Ethiopia [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAssessing the impact of the project on NCD services and the burden of disease in the community is more difficult. The data from the health centres suggests that a large number of nurses and health officers had been successfully trained and that the availability of basic equipment had substantially increased as a result of the project. The screening process was particularly successful with large numbers being assessed for hypertension or diabetes. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e also shows that the screening process for hypertension had a higher yield in the hospital-based projects (7.3% and 5.1%) than in the health centres (1.6% and 2.5%) which probably reflects the higher prevalence rates in the screened populations. In a similar way, diabetes was much more likely to be detected among the hospitals than the health centres. The very high prevalence recorded in the Addis Abba hospitals may be unreliable or merely reflect the higher prevalence of diabetes attending those facilities. Epilepsy and respiratory disease were not part of the screening programme and the numbers of patients registered during the project were correspondingly much lower but with significant numbers enrolled for treatment in both urban and rural locations.\u003c/p\u003e \u003cp\u003eMost people attending clinics were adequately controlled although our data is not complete enough to make definitive statements and follow-up will be needed to see whether this is maintained over the longer term. We have previously shown that staff in rural clinics in Ethiopia are well able to manage hypertension using simple regimes [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. However, despite intensive outreach and engagement, uptake was low and retention on treatment somewhat disappointing (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) although the duration of the project may have been too short to build up the level of community engagement and trust in the clinics and forms of NCD management required to make a substantial impact on the disease burden. Previous work in Ethiopia has demonstrated the numerous barriers to treatment, including access/distance, consistency of drug availability, cost (out-of-pocket expense and time) and cultural beliefs and practices related to health and healing [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOne problem that became evident during the project was competition with other vertical health programmes. This was particularly evident in the more remote, lower-level care settings, where the NCD project was introduced alongside other, often better-resourced programmes (e.g. antenatal care; water, sanitation and hygiene (WASH); under-fives, tuberculosis (TB), HIV/AIDS, mental health). Despite the expansion of all cadres of health staff in Ethiopia, multiple programmes are delivered by the same, hard-pressed and resource-constrained staff in rural areas. Related to this was the problems many patients reported in navigating the NCD care system resulting in confusion, mixed messaging, duplication of tests and an inefficient use of resources. It is clear that more attention needs to be given to developing the continuum of care for NCDs at all levels: supporting patients throughout their care journey from health promotion, prevention, diagnosis, treatment, to rehabilitation, and/or palliative care. Integrating NCD services with other services such as HIV/AIDS, TB etc. should be considered, as has been the case in Kenya, Uganda, Zambia, Malawi and elsewhere [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFew, if any studies report the financial implications of projects such as the one we describe. While project funding is complex and dependent on the scale and geographic reach as well as the economic environment, our data (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) suggest that while the per-patient costs are fairly low, the costs are likely to be considerable especially if the ongoing costs of medicines are included. NCD patients tend to be multiply disadvantaged compared to those needing episodic treatment for acute illnesses or who are within funded programmes such as HIV/AIDs and TB. Their need for continuous treatment and the concept of a disease that cannot be cured and needs lifelong medication places a long-term financial burden on the family, is counter-cultural and is a message at variance with those coming from other traditional systems of healing praxis. Although community-based insurance schemes have been introduced in the country (in 2011), for poor rural patients even a co-payment system is likely to be a prohibitive drain on household finances in the long-term. Furthermore, enthusiasm to take part will be dampened for those not incurring healthcare costs, and the scheme will be unable to generate significant funds if only those with NCDs contribute in the long term.\u003c/p\u003e \u003cp\u003eOne of the major problems encountered in the project was ensuring accurate and consistent completion of the paper-based record system which depended on patient registers, tally sheets and intake forms for each NCD. The overly detailed registration forms were burdensome and led to incomplete and inaccurate recording which will have affected data quality in this report which, consequently, are likely to have underestimated the throughput of patients and loss to follow-up. Although during the four years of the project a number of improvements and revisions were made at central level, improved record keeping is still needed. One solution may the introduction of electronic medical records and linked IT systems which can facilitate clinical decision-making and enhance the ability to monitor outcomes, as has been shown in Malawi and elsewhere [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. However, a cultural shift will be needed to promote the value of data in understanding what is being achieved and in driving up the quality and effectiveness of services.\u003c/p\u003e \u003cp\u003eThe availability of affordable medicines is essential for the running of NCD clinics and patient compliance [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and, although essential medicines were provided by the MoH, at the local level supplies were not always available. In a survey of 32 health centres, while the majority had available antihypertensive and diabetes medicines a significant minority did not. Even fewer centres reported the availability of medicines for epilepsy or inhalers for asthma. Most of the health centres reported that the main reason for the poor availability was a slow-to-respond supply chain mechanism which lacked efficient and effective communications between its various levels and components.\u003c/p\u003e \u003cp\u003eStaff turnover also proved to be a problem and required the identification of replacement trainers and mentors for almost for all sites. Loss of staff was most evident at the hospital and health centres level. By contrast all the HEWs trained during the project were retained for its duration. The likely reasons for this are the greater alternative job opportunities and financial advancement for urban-based staff coupled with the high workload and poor working environments.\u003c/p\u003e \u003cp\u003eFinally, the arrival of Covid-19 in Ethiopia and the outbreak of civil conflict in Tigray had a significant effect on the project as travel was restricted, and it became more difficult for patients to attend hospital or health centre clinics. Despite this, mentoring and supervision of the clinics continued utilising IT solutions while clinic staff used mobile phones to keep in contact and ensure the follow-up of NCD patients.\u003c/p\u003e \u003cp\u003eIn summary, this project has demonstrated the feasibility of scaling up integrated NCD services in a variety of different locations, with modest costs, and a methodology that is replicable and is highly sustainable. While taking advantage of existing staff and infrastructure is important, the extra costs and effort involved in staff training, mentoring and community engagement are not inconsiderable for a modest gain in the detection and treatment of common NCDs. In addition, given that there are over 3,500 health centres in Ethiopia, the process of making NCD services available to all represents a huge challenge. This will need to be carried out in an evidence-based way, addressing known challenges and adapting to new ones. For the effort and investment to have the greatest impact, improving the uptake and reducing the numbers lost to treatment must be a key focus. This may include the use of IT technologies and telecare systems if these can be operated cheaply and at scale, together with further decentralisation of care so that HEWs and communities play a much greater part in health education, recognition, control and management of NCDs.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eACE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAngiotensin converting enzyme\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHEW\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHealth extension workers\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInformation technology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLTFU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elost to follow up\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNCD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enoncommunicable disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMaster Trainers\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMoH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMinistry of Health\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePACK\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePractical approach to care kit\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSARA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eService availability and assessment tool\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSNNPR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSouthern Nations, Nationalities, and Peoples' Region\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTHET\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTropical Health Education Trust\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWHO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWorld Health Organisation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate: \u0026nbsp;Ethical approval with the University Faculty of Medicine Ethics Committee pending. No individuals were approached for this analysis which was based on aggregated clinic data.\u003c/p\u003e\n\u003cp\u003eConsent for publication: N/A\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials: The summary data used to generate the tables are available upon request to the corresponding author. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompeting interests; The authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding: \u0026nbsp; The project was supported by a grant from Novartis Social Business to the Tropical Health Education Trust (London).\u003c/p\u003e\n\u003cp\u003eAuthors' contributions. YM, MM, DIWP and AM designed the project. YM and MM supervised and were involved in its execution, YM, DIWP and AM analysed the data and wrote the manuscript. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcknowledgements: We acknowledge advice and help in planning the project from Dr\u0026nbsp;Addisu Worku, Dr Musie Gabremichael and the NCD team at the Federal Ministry of Health.\u0026nbsp;We are also grateful for the help of Temesgen Degefa, Frehiwot Kebede, Abere Desie, Wesen Tilahun and Amleset Gebrehiwot without whose devotion to the project it would have not come to a successful end. We would also like to acknowledge THET deputy CEO Louise McGrath and country programme director Katharina Brassington for their unreserved commitment to the project.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMemirie ST, Dagnaw WW, Habtemariam MK, Bekele A, Yadeta D, Bekele A, Bekele W, Gedefaw M, Assefa M, Tolla MT\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eAddressing the Impact of Noncommunicable Diseases and Injuries (NCDIs) in Ethiopia: Findings and Recommendations from the Ethiopia NCDI Commission\u003c/strong\u003e. \u003cem\u003eEthiop J Health Sci \u003c/em\u003e2022, \u003cstrong\u003e32\u003c/strong\u003e(1):161-180.\u003c/li\u003e\n\u003cli\u003eTesfay FH, Zorbas C, Alston L, Backholer K, Bowe SJ, Bennett CM: \u003cstrong\u003ePrevalence of chronic non-communicable diseases in Ethiopia: A systematic review and meta-analysis of evidence\u003c/strong\u003e. \u003cem\u003eFront Public Health \u003c/em\u003e2022, \u003cstrong\u003e10\u003c/strong\u003e:936482.\u003c/li\u003e\n\u003cli\u003eBank W: \u003cstrong\u003eThe World Bank in Ethiopia\u003c/strong\u003e. 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\u003cem\u003eBMJ Glob Health \u003c/em\u003e2021, \u003cstrong\u003e6\u003c/strong\u003e(5).\u003c/li\u003e\n\u003cli\u003eFoo C, Shrestha P, Wang L, Du Q, Garcia-Basteiro AL, Abdullah AS, Legido-Quigley H: \u003cstrong\u003eIntegrating tuberculosis and noncommunicable diseases care in low- and middle-income countries (LMICs): A systematic review\u003c/strong\u003e. \u003cem\u003ePLoS medicine \u003c/em\u003e2022, \u003cstrong\u003e19\u003c/strong\u003e(1):e1003899.\u003c/li\u003e\n\u003cli\u003eWroe EB, Kalanga N, Dunbar EL, Nazimera L, Price NF, Shah A, Dullie L, Mailosi B, Gonani G, Ndarama EPL\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eExpanding access to non-communicable disease care in rural Malawi: outcomes from a retrospective cohort in an integrated NCD-HIV model\u003c/strong\u003e. \u003cem\u003eBmj Open \u003c/em\u003e2020, \u003cstrong\u003e10\u003c/strong\u003e(10):e036836.\u003c/li\u003e\n\u003cli\u003eManjomo RC, Mwagomba B, Ade S, Ali E, Ben-Smith A, Khomani P, Bondwe P, Nkhoma D, Douglas GP, Tayler-Smith K\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eManaging and monitoring chronic non-communicable diseases in a primary health care clinic, Lilongwe, Malawi\u003c/strong\u003e. \u003cem\u003ePublic Health Action \u003c/em\u003e2016, \u003cstrong\u003e6\u003c/strong\u003e(2):60-65.\u003c/li\u003e\n\u003cli\u003eAbebe Bekele TG, Kassahun Amenu, Theodros Getachew, Atkure Defar, Habtamu Teklie,, Tefera Taddele GT, Misrak Getnet, Geremew Gonfa, Alemayehu Bekele, Tedla Kebede,, Yeweyenhareg Feleke DY, Mussie G/Michael, Mulugeta Guta, Fassil Shiferaw, Feyissa Challa,, Yabetse Girma KM, Yewondwossen Tadesse, Yibeltal Assefa, Amha Kebede, Kebede Worku: \u003cstrong\u003eThe hidden magnitude of raised blood pressure and elevated blood glucose in Ethiopia: A call for initiating community based NCDs risk factors screening program\u003c/strong\u003e. \u003cem\u003eEthiopian Journal of Health Development \u003c/em\u003e2017, \u003cstrong\u003e31\u003c/strong\u003e:362-369.\u003c/li\u003e\n\u003cli\u003eMulugeta T, Ayele T, Zeleke G, Tesfay G: \u003cstrong\u003eAsthma control and its predictors in Ethiopia: Systematic review and meta-analysis\u003c/strong\u003e. \u003cem\u003ePloS one \u003c/em\u003e2022, \u003cstrong\u003e17\u003c/strong\u003e(1):e0262566.\u003c/li\u003e\n\u003cli\u003eTekle-Haimanot R, Forsgren L, Ekstedt J: \u003cstrong\u003eIncidence of epilepsy in rural central Ethiopia\u003c/strong\u003e. \u003cem\u003eEpilepsia \u003c/em\u003e1997, \u003cstrong\u003e38\u003c/strong\u003e(5):541-546.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1: Baseline data from the project hospitals and health centres.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"614\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.781758957654723%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.21824104234528%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eNature of health facility\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.781758957654723%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003eAddis Ababa hospitals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.472312703583063%\" valign=\"top\"\u003e\n \u003cp\u003ePrimary hospitals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"top\"\u003e\n \u003cp\u003eUrban health centres\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"top\"\u003e\n \u003cp\u003eRural health centres\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.781758957654723%\" valign=\"top\"\u003e\n \u003cp\u003eTotal No.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.472312703583063%\" valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"top\"\u003e\n \u003cp\u003e31\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.781758957654723%\" valign=\"top\"\u003e\n \u003cp\u003eNo. of linked health posts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.472312703583063%\" valign=\"top\"\u003e\n \u003cp\u003e360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"top\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"bottom\"\u003e\n \u003cp\u003e178\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.781758957654723%\" valign=\"top\"\u003e\n \u003cp\u003eCatchment population*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"bottom\"\u003e\n \u003cp\u003e900,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.472312703583063%\"\u003e\n \u003cp\u003e6,576,423\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\"\u003e\n \u003cp\u003e628,504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\"\u003e\n \u003cp\u003e981,179\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.781758957654723%\" valign=\"top\"\u003e\n \u003cp\u003eTotal Staff\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e1,230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.472312703583063%\" valign=\"top\"\u003e\n \u003cp\u003e870\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"bottom\"\u003e\n \u003cp\u003e692\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"bottom\"\u003e\n \u003cp\u003e569\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.781758957654723%\" valign=\"top\"\u003e\n \u003cp\u003eDoctors\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.472312703583063%\" valign=\"bottom\"\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"bottom\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"bottom\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.781758957654723%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Nurses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e953\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.472312703583063%\" valign=\"bottom\"\u003e\n \u003cp\u003e569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"bottom\"\u003e\n \u003cp\u003e380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"bottom\"\u003e\n \u003cp\u003e308\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.781758957654723%\" valign=\"top\"\u003e\n \u003cp\u003eHealth Officers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.472312703583063%\" valign=\"bottom\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"bottom\"\u003e\n \u003cp\u003e159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"bottom\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.781758957654723%\" valign=\"top\"\u003e\n \u003cp\u003ePharmacists\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.472312703583063%\" valign=\"bottom\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"bottom\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"bottom\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.781758957654723%\" valign=\"top\"\u003e\n \u003cp\u003eIT staff\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.472312703583063%\" valign=\"bottom\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"bottom\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"bottom\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.781758957654723%\" valign=\"top\"\u003e\n \u003cp\u003eDistance to nearest referral hospital (mean in km)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.472312703583063%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"bottom\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;*In some instances, the catchment populations of hospitals overlap with the catchment populations of health centres.\u003c/p\u003e\n\u003cp\u003eTable 2: Numbers screened for hypertension and diabetes together with numbers of NCD cases enrolled to care during the project according to diagnosis and type of health facility. Reported mortality and loss to follow up (LTFU) over the duration of the study are also shown.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"538\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.881040892193308%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"72.11895910780669%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eType of health facility\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003eAddis Ababa hospitals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003ePrimary hospitals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003eUrban health centres\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003eRural health centres\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003eNumber of facilities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003eScreened\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003e66,880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003e55,467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e293,235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e123,212\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003eEnrolled (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003e4,894(7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003e2,813(5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e4,815(1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e3,045(2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003eDied\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e311\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003eLTFU\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e837\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e251\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003eDiabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003eScreened\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003e7,447\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003e14,008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e58,288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e24,759\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003eEnrolled (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003e4,441 (59.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003e2,083(14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e1953(3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e269(1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003eDied\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003eLTFU\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e439\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003eRespiratory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003eEnrolled\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003e881\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003e360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e1,950\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e795\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003eDied\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003eLTFU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003eEpilepsy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003eEnrolled\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003e480\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003e639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e307\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003eDied\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.932960893854748%\" valign=\"top\"\u003e\n \u003cp\u003eLTFU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.6219739292365%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.573556797020483%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.435754189944134%\" valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3: Numbers of patients diagnosed as a proportion of the total estimated caseload or each of the major diagnoses, according to the type of health facility.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"597\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.14572864321608%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"70.85427135678393%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eNature of health facility\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.14572864321608%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003eAddis Ababa hospitals\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.587939698492463%\" valign=\"top\"\u003e\n \u003cp\u003ePrimary\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eHospitals\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.08542713567839%\" valign=\"top\"\u003e\n \u003cp\u003eUrban health centres\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003eRural health centres\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.14572864321608%\" valign=\"top\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.587939698492463%\" valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.08542713567839%\" valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.14572864321608%\" valign=\"top\"\u003e\n \u003cp\u003eCatchment population \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e900,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.587939698492463%\" valign=\"top\"\u003e\n \u003cp\u003e6,576,423\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.08542713567839%\" valign=\"top\"\u003e\n \u003cp\u003e628,504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e981,179\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.14572864321608%\" valign=\"top\"\u003e\n \u003cp\u003eEstimated prevalence\u003csup\u003e1\u003c/sup\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.587939698492463%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.08542713567839%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.14572864321608%\" valign=\"top\"\u003e\n \u003cp\u003ePredicted caseload3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e67,500 \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.587939698492463%\" valign=\"top\"\u003e\n \u003cp\u003e493,232 \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.08542713567839%\" valign=\"top\"\u003e\n \u003cp\u003e47,138\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e34,341 \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.14572864321608%\" valign=\"top\"\u003e\n \u003cp\u003eCase detection (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e4,894 (7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.587939698492463%\" valign=\"top\"\u003e\n \u003cp\u003e2,813(0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.08542713567839%\" valign=\"top\"\u003e\n \u003cp\u003e4,815(10.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e3,045(8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eDiabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.14572864321608%\" valign=\"top\"\u003e\n \u003cp\u003eEstimated prevalence\u003csup\u003e1\u003c/sup\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.587939698492463%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.08542713567839%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.14572864321608%\" valign=\"top\"\u003e\n \u003cp\u003ePredicted caseload\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e27,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.587939698492463%\" valign=\"top\"\u003e\n \u003cp\u003e197,293\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.08542713567839%\" valign=\"top\"\u003e\n \u003cp\u003e18,855\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e14,718\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.14572864321608%\" valign=\"top\"\u003e\n \u003cp\u003eCase detection (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e4,441 (16.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.587939698492463%\" valign=\"top\"\u003e\n \u003cp\u003e2,083(1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.08542713567839%\" valign=\"top\"\u003e\n \u003cp\u003e1,953(10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e269(1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.14572864321608%\" valign=\"top\"\u003e\n \u003cp\u003eAsthma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.587939698492463%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.08542713567839%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.14572864321608%\" valign=\"top\"\u003e\n \u003cp\u003eEstimated prevalence\u003csup\u003e2\u003c/sup\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.587939698492463%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.08542713567839%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.14572864321608%\" valign=\"top\"\u003e\n \u003cp\u003ePredicted caseload\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e81,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.587939698492463%\" valign=\"top\"\u003e\n \u003cp\u003e591,878\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.08542713567839%\" valign=\"top\"\u003e\n \u003cp\u003e56,565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e88,306\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.14572864321608%\" valign=\"top\"\u003e\n \u003cp\u003eCase detection (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e881(1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.587939698492463%\" valign=\"top\"\u003e\n \u003cp\u003e360(0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.08542713567839%\" valign=\"top\"\u003e\n \u003cp\u003e1,950(3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e795(0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.14572864321608%\" valign=\"top\"\u003e\n \u003cp\u003eEpilepsy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.587939698492463%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.08542713567839%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.14572864321608%\" valign=\"top\"\u003e\n \u003cp\u003eEstimated prevalence\u003csup\u003e3\u003c/sup\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.587939698492463%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.08542713567839%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.14572864321608%\" valign=\"top\"\u003e\n \u003cp\u003ePredicted caseload\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e5,760\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.587939698492463%\" valign=\"top\"\u003e\n \u003cp\u003e42,089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.08542713567839%\" valign=\"top\"\u003e\n \u003cp\u003e4,022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e6,280\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.14572864321608%\" valign=\"top\"\u003e\n \u003cp\u003eCase detection (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e480(8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.587939698492463%\" valign=\"top\"\u003e\n \u003cp\u003e639(1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.08542713567839%\" valign=\"top\"\u003e\n \u003cp\u003e499(12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.09045226130653%\" valign=\"top\"\u003e\n \u003cp\u003e307(4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eref\u0026nbsp;[20]\u0026nbsp;\u003csup\u003e2\u003c/sup\u003eref[21]\u0026nbsp;\u003csup\u003e3\u003c/sup\u003eref\u0026nbsp;[22]\u003c/p\u003e\n\u003cp\u003ePredicted caseload based on estimated adult populations for hypertension and diabetes and total populations for asthma and epilepsy.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; Table 4: Project costs.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.92307692307692%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.07692307692308%\" valign=\"top\"\u003e\n \u003cp\u003eProject cost per year (US$)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.92307692307692%\" valign=\"top\"\u003e\n \u003cp\u003eAddis-based project staff\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.07692307692308%\" valign=\"top\"\u003e\n \u003cp\u003e50,469\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.92307692307692%\" valign=\"top\"\u003e\n \u003cp\u003eTravel and training*\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.07692307692308%\" valign=\"top\"\u003e\n \u003cp\u003e75,407\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.92307692307692%\" valign=\"top\"\u003e\n \u003cp\u003eEquipment*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.07692307692308%\" valign=\"top\"\u003e\n \u003cp\u003e16,099\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.92307692307692%\" valign=\"top\"\u003e\n \u003cp\u003eCommunity engagement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.07692307692308%\" valign=\"top\"\u003e\n \u003cp\u003e86.702\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.92307692307692%\" valign=\"top\"\u003e\n \u003cp\u003eTotal cost\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.07692307692308%\" valign=\"top\"\u003e\n \u003cp\u003e228,677\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.92307692307692%\" valign=\"top\"\u003e\n \u003cp\u003eCost per patient enrolled\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.07692307692308%\" valign=\"top\"\u003e\n \u003cp\u003e10.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Annualised costs\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3953489/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3953489/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Although primary care models for the care of common noncommunicable diseases (NCD) have been developed in sub-Saharan Africa, few have described an integrated, decentralized approach at the community level. We report the results of a four-year, Ethiopian project to expand this model of NCD care to 15 primary hospitals and 45 health centres encompassing a wide geographical spread and serving a population of approximately 7.5 million people.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Following baseline assessment of the 60 sites, 30 master trainers were used to cascade train a total of 621 health workers in the diagnosis, management and health education of the major common NCDs identified in a scoping review (hypertension, diabetes, chronic respiratory disease and epilepsy). Pre- and post-training assessments and regular mentoring visits were carried out to assess progress and remedy supply or equipment shortages and establish reporting systems. The project was accompanied by a series of community engagement activities to raise awareness and improve health seeking behaviour.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e A total of 643,296 people were screened for hypertension and diabetes leading to a new diagnosis in 24,313 who were started on treatment. Significant numbers of new cases of respiratory disease (3,986) and epilepsy (1,925) were also started on treatment. Mortality rates were low except for hypertension in the rural health centres where 311 (10.2%) died during the course of the project. Loss to follow up (LTFU), defined as failure to attend clinic for \u0026gt;6 months despite reminders, was low in the hospitals but represented a significant problem in the urban and rural health centres with up to 20 to 30 % of patients with hypertension or diabetes absenting from treatment by the end of the project. Estimates of the population disease burden enrolled within the project, however, were disappointing; asthma (0.49%), hypertension (1.7%), epilepsy (3.3%) and diabetes (3.4%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e This project demonstrates the feasibility of scaling up integrated NCD services in a variety of locations, with modest cost and methodology that is replicable and highly sustainable. However, the relatively small gain in the detection and treatment of common NCDs highlights the huge challenge in making NCD services available to all.\u003c/p\u003e","manuscriptTitle":"Scaling up noncommunicable disease care in a resource-limited context: lessons learned and implications for policy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-19 15:13:17","doi":"10.21203/rs.3.rs-3953489/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-03-14T16:45:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-14T12:46:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-14T12:46:45+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2024-02-13T11:56:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"24fe2b92-7398-4d4b-89dd-256b132b9069","owner":[],"postedDate":"March 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-07-27T00:25:44+00:00","versionOfRecord":{"articleIdentity":"rs-3953489","link":"https://doi.org/10.1186/s12913-024-11328-x","journal":{"identity":"bmc-health-services-research","isVorOnly":false,"title":"BMC Health Services Research"},"publishedOn":"2024-07-25 00:25:44","publishedOnDateReadable":"July 25th, 2024"},"versionCreatedAt":"2024-03-19 15:13:17","video":"","vorDoi":"10.1186/s12913-024-11328-x","vorDoiUrl":"https://doi.org/10.1186/s12913-024-11328-x","workflowStages":[]},"version":"v1","identity":"rs-3953489","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3953489","identity":"rs-3953489","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}