Literature DB >> 29580237

Assessment of population coverage of hypertension screening in Thailand based on the effective coverage framework.

Kulpimol Charoendee1, Jiruth Sriratanaban1, Wichai Aekplakorn2, Piya Hanvoravongchai3.   

Abstract

BACKGROUND: Hypertension (HT) is a major risk factor, and accessible and effective HT screening services are necessary. The effective coverage framework is an assessment tool that can be used to assess health service performance by considering target population who need and receive quality service. The aim of this study is to measure effective coverage of hypertension screening services at the provincial level in Thailand.
METHODS: Over 40 million individual health service records in 2013 were acquired. Data on blood pressure measurement, risk assessment, HT diagnosis and follow up were analyzed. The effectiveness of the services was assessed based on a set of quality criteria for pre-HT, suspected HT, and confirmed HT cases. Effective coverage of HT services for all non-HT Thai population aged 15 or over was estimated for each province and for all Thailand.
RESULTS: Population coverage of HT screening is 54.6%, varying significantly across provinces. Among those screened, 28.9% were considered pre-HT, and another 6.0% were suspected HT cases. The average provincial effective coverage was at 49.9%. Around four-fifths (82.6%) of the pre-HT group received HT and Cardiovascular diseases (CVD) risk assessment. Among the suspected HT cases, less than half (38.0%) got a follow-up blood pressure measurement within 60 days from the screening date. Around 9.2% of the suspected cases were diagnosed as having HT, and only one-third of them (36.5%) received treatment within 6 months. Within this group, 21.8% obtained CVD risk assessment, and half of them had their blood pressure under control (50.8%) with less than 1 % (0.7%) of them managed to get the CVD risk reduced.
CONCLUSIONS: Our findings suggest that hypertension screening coverage, post-screening service quality, and effective coverage of HT screening in Thailand were still low and they vary greatly across provinces. It is imperative that service coverage and its effectiveness are assessed, and both need improvement. Despite some limitations, measurement of effective coverage could be done with existing data, and it can serve as a useful tool for performance measurement of public health services.

Entities:  

Keywords:  Access; Effective coverage; Hypertension; Measure; NCDs; Screening; Thailand

Mesh:

Year:  2018        PMID: 29580237      PMCID: PMC5869783          DOI: 10.1186/s12913-018-2996-y

Source DB:  PubMed          Journal:  BMC Health Serv Res        ISSN: 1472-6963            Impact factor:   2.655


Background

Hypertension is a major health problem facing many countries around the world including Thailand. It is a major risk factor leading to illnesses and deaths from cardiovascular diseases [1]. Approximately one-third of the world’s population has high blood pressure, and the number tends to increase more rapidly. It was estimated that in 2025 the number of people with hypertension would rise by 60% to about 1.56 billion [2]. The Global Burden of Disease Study 2013 put hypertension as a major risk factor for premature deaths globally [3]. An earlier survey in Thailand found an increased prevalence of hypertension among those aged 15 years and over during the last 5 years from 21.4% to 24.7%. Among them, 40% were unaware of having hypertension [4]. The Thai Burden of Disease Study 2009 reported hypertension as the second and third risk factors for DALYs for male and female, respectively [5]. Prevention or delay of the new HT cases is a key strategy under the Global Action Plan for the Prevention and Control of Non-Communicable Diseases (NCDs) with the goal to reduce illnesses and premature deaths from cardiovascular diseases [6]. HT screening is thus an important initial step leading to further adequate management. Actual health benefits can be achieved when effective hypertension screening is supported by adequate and continuous care for those in need [7]. A previous study revealed that hypertension screening in population age 65 year or older contributed to reduced rates of annual hospitalization due to cardiovascular diseases [8]. Systematic reviews by the U.S. Preventive Services Task Force reported that substantial indirect evidence continues to support the net benefit of screening for high blood pressure in adults aged 18 years or older [9]. In Thailand, HT screening is a basic healthcare service that has been widely available with the screening mostly performed in the community. Previously, HT screening performance was measured only by assessing service coverage. However, earlier studies showed that high rate of service coverage did not necessarily imply good health outcome. A significant proportion of those found during screening to be at risk from the disease did not get adequate care or follow up treatment. Hence, it is important to take into consideration not only HT service coverage but also its screening quality and effectiveness [10]. Health system can contribute to health improvement of the people by means of delivering high-quality service to those who will benefit from them. It is therefore important for policymakers and those involved in health service system governance to have accurate information especially in relation to the existing service gaps, both in term of population coverage and its effectiveness. In 2003 the World Health Organization (WHO) introduced effective coverage “framework” [11, 12] as a tool for health system performance assessment. Effective coverage is defined as “the fraction of potential health gain that is actually delivered to the population through the health system.” It is a significant advancement over the usual approach of measuring crude coverage. The effective coverage framework proposes to measure three components, which include health need, utilization, and service effectiveness and aggregates them into a single metric. It can be used in an assessment of individual or population level, and it allows for tracking changes and benchmarking of the health system performance. Over the years, the concept of effective coverage has been adopted to measure and assess a wide range of health services [11, 13, 14]. The objective of this study is to measure the effective coverage of hypertension screening services at the provincial level in Thailand, using an applied effective coverage framework.

Methods

This study focuses on the assessment of HT prevention coverage at the individual level using providers’ perspective. It applied the effective coverage framework to measure comprehensive HT screening services including after screening activities in three specific groups: those with pre-HT; suspected HT; and confirmed HT. We obtained a secondary dataset from the administrative databases of the National Health Security Office (NHSO). This dataset derived from the outpatient service database for health promotion and disease prevention which covered over 40 million Thais in 76 provinces. NHSO collected data on individual health care service utilization at the outpatient department of health care providers under the Ministry of Public Health into 21 standard dataset files. We used 6 files from 2013 which contain information on population characteristics, HT screening, health care utilization, HT registry, HT patients follow up. The study samples were all Thai population aged 15 years and older whose information was available in the NHSO database. We included all Thais who registered in the national civil registration system and lived in the 76 study provinces. Those having been previously diagnosed with HT were excluded because they were not considered in the HT screening target group. Measurement of effective coverage of hypertension screening was based on the method originally proposed by Shengelia et al. It is based on the following formula [11, 12]:where Q is the quality, or health gain ratio, i.e., the gain provided to a person by intervention in relation to the maximum possible health gain; this study measured by the proportion of effectiveness of service in relation to the benefits received from the service; U is the utilization of health service and refers to the probability that the individual with a need will receive the intervention; this study measured by the proportion of service received by an individual; and. N is need indicator which refers to individuals who will gain actual benefits from receiving or true need; if N = 1 is the true need for receiving healthcare services, N = 0, then the individual does not have a need for coverage. Our operational definition of the population in need of HT screening follows the official criteria for the target population of HT screening as identified by the Ministry of Public Health in 2013. It included all Thai individuals aged 15 and older who live in the 76 provinces outside Bangkok. Bangkok was not included in the study because it has its own service delivery system governance with a separate information management system. Note that for Shengelia, quality is synonymous with effectiveness. In this study, we identified the effectiveness of HT screening based on a set of effectiveness criteria, which were constructed by the findings from a systematic literature review and a consultation with six national experts. The HT screening service in this study includes HT screening activities and subsequent post-screening health care needs such as risk assessment, disease detection, and monitoring to control blood pressure and prevention of complication from cardiovascular diseases. The effectiveness criteria (Q) of HT screening depended on the quality and completeness of a set of activities provided to the target groups. They ranged from blood pressure screening for non-HT population, to delivery of interventions to reduce HT risks, and to blood pressure management among the population at risk and newly diagnosed HT cases. The quality or effectiveness criteria were set up to assess these population subgroups, classified at the time of the initial screening by their blood pressure level. The ranges were SBP < 120 and DBP < 80 mmHg for normotension, SBP 120–139 and/or DBP 80–89 mmHg for pre-HT, and SBP ≥ 140 and/or DBP ≥ 90 mmHg for suspected HT. Table 1 shows the set of interventions and effectiveness criteria for these population subgroups. For example, in addition to blood pressure (BP) screening, anyone with BP in a pre-HT level must also obtain CVD risk assessment. Based on the measurements of effective coverage of each particular service at the individual level, aggregate summary statistics of effective coverage at the province and national levels were calculated.
Table 1

Criteria for measuring effective coverage of hypertension screening and prevention services

Target population subgroupsIntervention setsEffectiveness criteria (Q)
NormotensionBP measurementReceiving at least one BP measurement in a year
Pre HTHT& CVD risk assessmentaReceiving HT & CVD risk assessment
Suspected HTDiagnosis confirmationReceiving repeated BP measurement within 2 months after initial screening
Newly diagnosed HTCVD risk assessmentbReceiving CVD risk assessment
Timely treatmentReceiving early treatment
Controlling BP & risk factorsBlood pressure lower than the initial level or under control (Systolic BP < 140 mmHg and Diastolic BP < 90 mmHg) with serum lipid level better than the initial test.

aHT&CVD risk assessment for the pre-HT group includes history taking on age, sex, diabetic, smoking, and alcohol drinking history, and physical check-up for weight, height, waist circumference, and blood pressure measurement

bCVD risk assessment for newly diagnosed HT case includes blood test for total cholesterol, low-density lipoprotein, and high-density lipoprotein level

Criteria for measuring effective coverage of hypertension screening and prevention services aHT&CVD risk assessment for the pre-HT group includes history taking on age, sex, diabetic, smoking, and alcohol drinking history, and physical check-up for weight, height, waist circumference, and blood pressure measurement bCVD risk assessment for newly diagnosed HT case includes blood test for total cholesterol, low-density lipoprotein, and high-density lipoprotein level The study protocol was approved by the Institutional Review Board, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand on 4 April 2015 (Reference number 117/57). The 2013 dataset was used with the permission of NHSO.

Results

Table 2 shows general characteristic for the 76 provinces in 2013. The information was gathered from various databases, mostly from national surveys and Ministry of Public Health statistics. There were huge differences between province. For example, the mid-year population in a province ranges from 0.2 to 2.6 million with an average number of 0.8 million.
Table 2

Characteristics for 76 provinces in Thailand in 2013 (n = 76)

MeanSDMinMax
Midyear population (million)0.80.470.22.6
Age group (%)
 1–14 year19.02.8313.327.6
 60 year and over13.42.158.918.6
Education
 Literacy (%)95.35.7272.199.6
Economics
 Gross Provincial Product (100,000) per Capita1.41.400.410.3
Living area (%)
 Urban34.415.0311.374.5
Public health resources
 Density of primary care unit per sq.km.51.327.838.2178.6
 Population (1000) per primary care unit6.12.743.317.9
 Population (1000) per physician4.21.411.812.0
 Population (1000) per nurse0.60.210.31.4
 Population (1000) per public health personnel1.60.570.73.8
Characteristics for 76 provinces in Thailand in 2013 (n = 76) There were approximately 42 million Thai population aged 15 or older without a prior diagnosis of hypertension, our target population for HT screening. There are equal numbers of males and females with almost 38% of them in the 15 to 34 years old age group (Fig. 1). A little over half of the target population (54.6%) have had an HT screening during the study period. The proportion getting screening is slightly bigger among female. Among those who received HT screening, the proportions of each population subgroup (normotension, pre-HT, or suspected HT) are quite similar for males and females (Fig. 2). Those aged between 15 and 34 years have a higher proportion of normotension while population aged 35 years and older have a higher proportion of suspected HT or pre-HT individuals (Fig. 3).
Fig. 1

Age groups of Thai population 15 years old and over without established hypertension, 2013

Fig. 2

Proportion of Thai people with and without HT screening and proportion of HT screened individuals with normal blood pressure, pre HT, and suspected HT, by gender, 2013

Fig. 3

Proportion of Thai people with and without HT screening and proportion of HT screened individuals with normal blood pressure, pre HT, and suspected HT, by age group, 2013

Age groups of Thai population 15 years old and over without established hypertension, 2013 Proportion of Thai people with and without HT screening and proportion of HT screened individuals with normal blood pressure, pre HT, and suspected HT, by gender, 2013 Proportion of Thai people with and without HT screening and proportion of HT screened individuals with normal blood pressure, pre HT, and suspected HT, by age group, 2013 The diagram in Fig. 4 shows the share of different subpopulation across all age group and the proportions of each subgroup who received HT prevention interventions. Around four-fifths (82.6%) of the pre-HT group received HT and CVD risk assessment. Among the suspected HT cases, less than half (38.0%) got a follow-up blood pressure measurement within 60 days from the HT screening date. Around 9.2% of the suspected cases were diagnosed as having HT, and only one-third of them (36.5%) received treatment within 6 months. In this confirmed group, 21.8% obtained CVD risk assessment, and half of them had their blood pressure under control (50.8%) with less than 1% (0.7%) of them managed to get the CVD risk reduced.
Fig. 4

Pathway of HT screening and prevention and control service coverage, showing proportion of population in each subgroup and the services they received

Pathway of HT screening and prevention and control service coverage, showing proportion of population in each subgroup and the services they received Considerable differences across provinces were observed. Our analyses revealed that the average provincial effective coverage of HT screening for the target population is at 49.9%. It varies greatly across provinces, from 6.9% to 80.5%. Effective coverage level was considerably lower than crude coverage for all provinces. The difference between effective coverage and coverage of HT screening also varies across provinces, from to 1.3% to 14.2%. The effective coverage at the province level correlates well with the population coverage measure, with a strong linear relationship between the two (r = 0.99, p < 0.001). There is no clear relationship between the effective coverage and the province size (population size) as shown in Fig. 5. However, there is a weak but significant correlation between the level of coverage of a province and its quality/effectiveness of the screening coverage for the population age 15 years and over as shown in Fig. 6. The results show no clear pattern in the distribution of coverage and effective coverage across key provincial statistics including the proportion of urban population, Gross Provincial Product (GPP), the density of primary care unit per area (square kilometer), the ratio of population to primary care unit, and the ratio of population to healthcare personnel as shown in Fig. 7.
Fig. 5

Distribution of coverage and effective coverage of HT screening per 100,000 population in each of the 76 provinces, ranked from lowest to highest number of target population in the province

Fig. 6

Distribution of effective coverage and coverage level in 76 provinces of Thailand in relation to key development and public health indicators in the year 2013

Fig. 7

Two-way scatter plot between the percentage of HT screening coverage and proportion of prevention and control service effectiveness in each of 76 provinces

Distribution of coverage and effective coverage of HT screening per 100,000 population in each of the 76 provinces, ranked from lowest to highest number of target population in the province Distribution of effective coverage and coverage level in 76 provinces of Thailand in relation to key development and public health indicators in the year 2013 Two-way scatter plot between the percentage of HT screening coverage and proportion of prevention and control service effectiveness in each of 76 provinces

Discussion

Our study is the first implementation of the effective coverage framework proposed by the World Health Organization for health service assessment in Thailand. It measured a comprehensive set of services related to HT screening from pre-diagnosis interventions to treatment new diagnosed HT within the first six months. All of the components were assessed and summarized into a single metric. The coverage of HT screening at 55% indicates that during the study period, just over half of the Thai population aged 15 years and above, who have never been diagnosed with hypertension before, received hypertension screening services. This is despite HT screening being a major health campaign by the government. This is not surprising. An earlier population sample survey also showed that around 40% of the hypertensive individuals were not aware that they are hypertensive [4]. The gap in screening coverage demonstrates that the service still does not reach all those in need which is a missed opportunity for disease prevention and control. The barriers to service access could stem from any of the three dimensions as described in Evans et al. [15] namely, physical accessibility, financial affordability, and acceptability. In the Thai context, financial affordability should not be a major issue given HT screening is part of the benefit package of the Universal Health Coverage program that has been in place nationwide since 2002. Physical accessibility and acceptability could be more important. Even though most healthcare facilities offer outreach community HT screening services, the identified gap demonstrates that a significant proportion of the target population could not be reached. Effective coverage of HT screening in Thailand (excluding Bangkok) was found to be only half of its full potential. A major portion of the effective coverage gap was due to incomplete screening coverage as discussed above. But there was also a big portion of those who were screened and considered as HT suspects but did not have access to a timely confirmation visit. The variation in effective coverage of HT screening service across province deserves further deliberation. Huge difference in provincial level stats may indicate the differences in policies, procedures, and other factors. These include human resources (both quantity and quality), budget, technology and local environment. Existing literature shows that several factors can affect patient access and the decision of the patient to receive service. These include education level, awareness of information related to health and healthcare alternatives, location and distance of the service unit, convenience, travel cost and awareness of service quality [12, 16]. They can be classified into personnel factors (such as knowledge and skills, intention on reducing risk factors, social collaboration) and healthcare service system factors (including access, sufficiency and appropriateness of the service, acceptance in receiving service) [17]. In Thailand, both personnel factor and system factor could be key determinants. Further study is needed to understand these determinants to help improve the HT screening and related services in the country. Our findings also reveal that there are relatively small differences between crude coverage and effective coverage statistics at the province level (range from 1.3% to 14.2% with an average difference of 4.2%). This can simply be interpreted as the gap in service effectiveness is small, and the gap in overall coverage is more important. However, there are three other possible explanations for such findings. First, the choice of the target population in Thailand to all people age 15 years and over resulted in a bigger population to screen and more of them in the normotension group. Both factors contributed to lower relative importance of the effectiveness component in the effective coverage assessment. Second, limited data availability in the secondary healthcare service dataset made it more difficult to assess service effectiveness. Third, the choice of effectiveness criteria used in this study where quality weight is set to either zero or one made the assessment not sensitive to the change in program effectiveness. Further studies are required to improve the tool as well as data availability for better assessment. Such improvement especially in the evaluation of NCDs service quality and effectiveness will provide additional insights into the performance of hypertension screening services in Thailand. A number of limitations exist in this study. The measurement of comprehensive effectiveness was not possible with limited data. Hence, some components of quality or effectiveness measures were left out while others cannot be measured. The study relies on relatively concrete effectiveness or quality scores that may not fully reflect the potential benefit from obtaining a specific component of HT services. It requires further studies to assess the intervention effectiveness to fine tune the weights adhered to each quality or effectiveness component. The administrative data used in this study was limited by the completeness in itself and by the lack of data from health care providers outside the Ministry of Public Health, including the private sector. All these limitations should be overcome in further studies for the measurement to be more accurate. A few recommendations are provided here for future studies. Determinants of provincial differences should be further investigated to identify relevant factors that influence HT screening and prevention coverage and their effective coverage. The tool for effective coverage measurement in HT screening can be refined with better design of effectiveness criteria. Future analyses may focus on specific groups such as the urban, non-urban, and vulnerable population groups. Nevertheless, our analyses show a significant gap in hypertension screening services in the country, which implies that improvement in primary care systems is required. For other health care interventions or services, effective coverage framework can be used to improve their performance assessment. It will be particularly useful for those programs that already have good service coverage to include the quality component in their assessment.

Conclusion

Our findings suggest that hypertension screening coverage, post-screening service quality, and effective coverage of HT screening in Thailand were still low and they vary greatly across provinces. It is imperative that service coverage and its effectiveness are assessed, and both need improvement. Despite some limitations, the exercise in Thailand shows that the measurement of effective coverage could be done with existing data, and it can serve as a useful tool for performance measurement of public health services. The findings shed light for global universal health coverage monitoring effort where measurement of effective service coverage is a core component a health target of the Sustainable Development Goals.
  12 in total

1.  Access, utilization, quality, and effective coverage: an integrated conceptual framework and measurement strategy.

Authors:  Bakhuti Shengelia; Ajay Tandon; Orvill B Adams; Christopher J L Murray
Journal:  Soc Sci Med       Date:  2005-07       Impact factor: 4.634

Review 2.  Benchmarking of performance of Mexican states with effective coverage.

Authors:  Rafael Lozano; Patricia Soliz; Emmanuela Gakidou; Jesse Abbott-Klafter; Dennis M Feehan; Cecilia Vidal; Juan Pablo Ortiz; Christopher J L Murray
Journal:  Lancet       Date:  2006-11-11       Impact factor: 79.321

Review 3.  Evidence for the reaffirmation of the U.S. Preventive Services Task Force recommendation on screening for high blood pressure.

Authors:  Tracy Wolff; Therese Miller
Journal:  Ann Intern Med       Date:  2007-12-04       Impact factor: 25.391

4.  Global burden of hypertension: analysis of worldwide data.

Authors:  Patricia M Kearney; Megan Whelton; Kristi Reynolds; Paul Muntner; Paul K Whelton; Jiang He
Journal:  Lancet       Date:  2005 Jan 15-21       Impact factor: 79.321

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Journal:  Hypertension       Date:  2003-12-01       Impact factor: 10.190

6.  Evaluation of a diabetes care program using the effective coverage framework.

Authors:  Erika López-López; David Gutiérrez-Soria; Alvaro J Idrovo
Journal:  Int J Qual Health Care       Date:  2012-10-05       Impact factor: 2.038

7.  Improving cardiovascular health at population level: 39 community cluster randomised trial of Cardiovascular Health Awareness Program (CHAP).

Authors:  Janusz Kaczorowski; Larry W Chambers; Lisa Dolovich; J Michael Paterson; Tina Karwalajtys; Tracy Gierman; Barbara Farrell; Beatrice McDonough; Lehana Thabane; Karen Tu; Brandon Zagorski; Ron Goeree; Cheryl A Levitt; William Hogg; Stephanie Laryea; Megan Ann Carter; Dana Cross; Rolf J Sabaldt
Journal:  BMJ       Date:  2011-02-07

Review 8.  Patient and healthcare provider barriers to hypertension awareness, treatment and follow up: a systematic review and meta-analysis of qualitative and quantitative studies.

Authors:  Rasha Khatib; Jon-David Schwalm; Salim Yusuf; R Brian Haynes; Martin McKee; Maheer Khan; Robby Nieuwlaat
Journal:  PLoS One       Date:  2014-01-15       Impact factor: 3.240

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Francisco A García-Guerra; Evariste Gasana; Johanna M Geleijnse; Bradford D Gessner; Pete Gething; Katherine B Gibney; Richard F Gillum; Ibrahim A M Ginawi; Maurice Giroud; Giorgia Giussani; Shifalika Goenka; Ketevan Goginashvili; Hector Gomez Dantes; Philimon Gona; Teresita Gonzalez de Cosio; Dinorah González-Castell; Carolyn C Gotay; Atsushi Goto; Hebe N Gouda; Richard L Guerrant; Harish C Gugnani; Francis Guillemin; David Gunnell; Rahul Gupta; Rajeev Gupta; Reyna A Gutiérrez; Nima Hafezi-Nejad; Holly Hagan; Maria Hagstromer; Yara A Halasa; Randah R Hamadeh; Mouhanad Hammami; Graeme J Hankey; Yuantao Hao; Hilda L Harb; Tilahun Nigatu Haregu; Josep Maria Haro; Rasmus Havmoeller; Simon I Hay; Mohammad T Hedayati; Ileana B Heredia-Pi; Lucia Hernandez; Kyle R Heuton; Pouria Heydarpour; Martha Hijar; Hans W Hoek; Howard J Hoffman; John C Hornberger; H Dean Hosgood; Damian G Hoy; Mohamed Hsairi; Guoqing Hu; Howard Hu; Cheng Huang; John J Huang; Bryan J Hubbell; Laetitia Huiart; Abdullatif Husseini; Marissa L Iannarone; Kim M Iburg; Bulat T Idrisov; Nayu Ikeda; Kaire Innos; Manami Inoue; Farhad Islami; Samaya Ismayilova; Kathryn H Jacobsen; Henrica A Jansen; Deborah L Jarvis; Simerjot K Jassal; Alejandra Jauregui; Sudha Jayaraman; Panniyammakal Jeemon; Paul N Jensen; Vivekanand Jha; Fan Jiang; Guohong Jiang; Ying Jiang; Jost B Jonas; Knud Juel; Haidong Kan; Sidibe S Kany Roseline; Nadim E Karam; André Karch; Corine K Karema; Ganesan Karthikeyan; Anil Kaul; Norito Kawakami; Dhruv S Kazi; Andrew H Kemp; Andre P Kengne; Andre Keren; Yousef S Khader; Shams Eldin Ali Hassan Khalifa; Ejaz A Khan; Young-Ho Khang; Shahab Khatibzadeh; Irma Khonelidze; Christian Kieling; Daniel Kim; Sungroul Kim; Yunjin Kim; Ruth W Kimokoti; Yohannes Kinfu; Jonas M Kinge; Brett M Kissela; Miia Kivipelto; Luke D Knibbs; Ann Kristin Knudsen; Yoshihiro Kokubo; M Rifat Kose; Soewarta Kosen; Alexander Kraemer; Michael Kravchenko; Sanjay Krishnaswami; Hans Kromhout; Tiffany Ku; Barthelemy Kuate Defo; Burcu Kucuk Bicer; Ernst J Kuipers; Chanda Kulkarni; Veena S Kulkarni; G Anil Kumar; Gene F Kwan; Taavi Lai; Arjun Lakshmana Balaji; Ratilal Lalloo; Tea Lallukka; Hilton Lam; Qing Lan; Van C Lansingh; Heidi J Larson; Anders Larsson; Dennis O Laryea; Pablo M Lavados; Alicia E Lawrynowicz; Janet L Leasher; Jong-Tae Lee; James Leigh; Ricky Leung; Miriam Levi; Yichong Li; Yongmei Li; Juan Liang; Xiaofeng Liang; Stephen S Lim; M Patrice Lindsay; Steven E Lipshultz; Shiwei Liu; Yang Liu; Belinda K Lloyd; Giancarlo Logroscino; Stephanie J London; Nancy Lopez; Joannie Lortet-Tieulent; Paulo A Lotufo; Rafael Lozano; Raimundas Lunevicius; Jixiang Ma; Stefan Ma; Vasco M P Machado; Michael F MacIntyre; Carlos Magis-Rodriguez; Abbas A Mahdi; Marek Majdan; Reza Malekzadeh; Srikanth Mangalam; Christopher C Mapoma; Marape Marape; Wagner Marcenes; David J Margolis; Christopher Margono; Guy B Marks; Randall V Martin; Melvin B Marzan; Mohammad T Mashal; Felix Masiye; Amanda J Mason-Jones; Kunihiro Matsushita; Richard Matzopoulos; Bongani M Mayosi; Tasara T Mazorodze; Abigail C McKay; Martin McKee; Abigail McLain; Peter A Meaney; Catalina Medina; Man Mohan Mehndiratta; Fabiola Mejia-Rodriguez; Wubegzier Mekonnen; Yohannes A Melaku; Michele Meltzer; Ziad A Memish; Walter Mendoza; George A Mensah; Atte Meretoja; Francis Apolinary Mhimbira; Renata Micha; Ted R Miller; Edward J Mills; Awoke Misganaw; Santosh Mishra; Norlinah Mohamed Ibrahim; Karzan A Mohammad; Ali H Mokdad; Glen L Mola; Lorenzo Monasta; Julio C Montañez Hernandez; Marcella Montico; Ami R Moore; Lidia Morawska; Rintaro Mori; Joanna Moschandreas; Wilkister N Moturi; Dariush Mozaffarian; Ulrich O Mueller; Mitsuru Mukaigawara; Erin C Mullany; Kinnari S Murthy; Mohsen Naghavi; Ziad Nahas; Aliya Naheed; Kovin S Naidoo; Luigi Naldi; Devina Nand; Vinay Nangia; K M Venkat Narayan; Denis Nash; Bruce Neal; Chakib Nejjari; Sudan P Neupane; Charles R Newton; Frida N Ngalesoni; Jean de Dieu Ngirabega; Grant Nguyen; Nhung T Nguyen; Mark J Nieuwenhuijsen; Muhammad I Nisar; José R Nogueira; Joan M Nolla; Sandra Nolte; Ole F Norheim; Rosana E Norman; Bo Norrving; Luke Nyakarahuka; In-Hwan Oh; Takayoshi Ohkubo; Bolajoko O Olusanya; Saad B Omer; John Nelson Opio; Ricardo Orozco; Rodolfo S Pagcatipunan; Amanda W Pain; Jeyaraj D Pandian; Carlo Irwin A Panelo; Christina Papachristou; Eun-Kee Park; Charles D Parry; Angel J Paternina Caicedo; Scott B Patten; Vinod K Paul; Boris I Pavlin; Neil Pearce; Lilia S Pedraza; Andrea Pedroza; Ljiljana Pejin Stokic; Ayfer Pekericli; David M Pereira; Rogelio Perez-Padilla; Fernando Perez-Ruiz; Norberto Perico; Samuel A L Perry; Aslam Pervaiz; Konrad Pesudovs; Carrie B Peterson; Max Petzold; Michael R Phillips; Hwee Pin Phua; Dietrich Plass; Dan Poenaru; Guilherme V Polanczyk; Suzanne Polinder; Constance D Pond; C Arden Pope; Daniel Pope; Svetlana Popova; Farshad Pourmalek; John Powles; Dorairaj Prabhakaran; Noela M Prasad; Dima M Qato; Amado D Quezada; D Alex A Quistberg; Lionel Racapé; Anwar Rafay; Kazem Rahimi; Vafa Rahimi-Movaghar; Sajjad Ur Rahman; Murugesan Raju; Ivo Rakovac; Saleem M Rana; Mayuree Rao; Homie Razavi; K Srinath Reddy; Amany H Refaat; Jürgen Rehm; Giuseppe Remuzzi; Antonio L Ribeiro; Patricia M Riccio; Lee Richardson; Anne Riederer; Margaret Robinson; Anna Roca; Alina Rodriguez; David Rojas-Rueda; Isabelle Romieu; Luca Ronfani; Robin Room; Nobhojit Roy; George M Ruhago; Lesley Rushton; Nsanzimana Sabin; Ralph L Sacco; Sukanta Saha; Ramesh Sahathevan; Mohammad Ali Sahraian; Joshua A Salomon; Deborah Salvo; Uchechukwu K Sampson; Juan R Sanabria; Luz Maria Sanchez; Tania G Sánchez-Pimienta; Lidia Sanchez-Riera; Logan Sandar; Itamar S Santos; Amir Sapkota; Maheswar Satpathy; James E Saunders; Monika Sawhney; Mete I Saylan; Peter Scarborough; Jürgen C Schmidt; Ione J C Schneider; Ben Schöttker; David C Schwebel; James G Scott; Soraya Seedat; Sadaf G Sepanlou; Berrin Serdar; Edson E Servan-Mori; Gavin Shaddick; Saeid Shahraz; Teresa Shamah Levy; Siyi Shangguan; Jun She; Sara Sheikhbahaei; Kenji Shibuya; Hwashin H Shin; Yukito Shinohara; Rahman Shiri; Kawkab Shishani; Ivy Shiue; Inga D Sigfusdottir; Donald H Silberberg; Edgar P Simard; Shireen Sindi; Abhishek Singh; Gitanjali M Singh; Jasvinder A Singh; Vegard Skirbekk; Karen Sliwa; Michael Soljak; Samir Soneji; Kjetil Søreide; Sergey Soshnikov; Luciano A Sposato; Chandrashekhar T Sreeramareddy; Nicolas J C Stapelberg; Vasiliki Stathopoulou; Nadine Steckling; Dan J Stein; Murray B Stein; Natalie Stephens; Heidi Stöckl; Kurt Straif; Konstantinos Stroumpoulis; Lela Sturua; Bruno F Sunguya; Soumya Swaminathan; Mamta Swaroop; Bryan L Sykes; Karen M Tabb; Ken Takahashi; Roberto T Talongwa; Nikhil Tandon; David Tanne; Marcel Tanner; Mohammad Tavakkoli; Braden J Te Ao; Carolina M Teixeira; Martha M Téllez Rojo; Abdullah S Terkawi; José Luis Texcalac-Sangrador; Sarah V Thackway; Blake Thomson; Andrew L Thorne-Lyman; Amanda G Thrift; George D Thurston; Taavi Tillmann; Myriam Tobollik; Marcello Tonelli; Fotis Topouzis; Jeffrey A Towbin; Hideaki Toyoshima; Jefferson Traebert; Bach X Tran; Leonardo Trasande; Matias Trillini; Ulises Trujillo; Zacharie Tsala Dimbuene; Miltiadis Tsilimbaris; Emin Murat Tuzcu; Uche S Uchendu; Kingsley N Ukwaja; Selen B Uzun; Steven van de Vijver; Rita Van Dingenen; Coen H van Gool; Jim van Os; Yuri Y Varakin; Tommi J Vasankari; Ana Maria N Vasconcelos; Monica S Vavilala; Lennert J Veerman; Gustavo Velasquez-Melendez; N Venketasubramanian; Lakshmi Vijayakumar; Salvador Villalpando; Francesco S Violante; Vasiliy Victorovich Vlassov; Stein Emil Vollset; Gregory R Wagner; Stephen G Waller; Mitchell T Wallin; Xia Wan; Haidong Wang; JianLi Wang; Linhong Wang; Wenzhi Wang; Yanping Wang; Tati S Warouw; Charlotte H Watts; Scott Weichenthal; Elisabete Weiderpass; Robert G Weintraub; Andrea Werdecker; K Ryan Wessells; Ronny Westerman; Harvey A Whiteford; James D Wilkinson; Hywel C Williams; Thomas N Williams; Solomon M Woldeyohannes; Charles D A Wolfe; John Q Wong; Anthony D Woolf; Jonathan L Wright; Brittany Wurtz; Gelin Xu; Lijing L Yan; Gonghuan Yang; Yuichiro Yano; Pengpeng Ye; Muluken Yenesew; Gökalp K Yentür; Paul Yip; Naohiro Yonemoto; Seok-Jun Yoon; Mustafa Z Younis; Zourkaleini Younoussi; Chuanhua Yu; Maysaa E Zaki; Yong Zhao; Yingfeng Zheng; Maigeng Zhou; Jun Zhu; Shankuan Zhu; Xiaonong Zou; Joseph R Zunt; Alan D Lopez; Theo Vos; Christopher J Murray
Journal:  Lancet       Date:  2015-09-11       Impact factor: 79.321

Review 10.  Effective coverage: a metric for monitoring Universal Health Coverage.

Authors:  Marie Ng; Nancy Fullman; Joseph L Dieleman; Abraham D Flaxman; Christopher J L Murray; Stephen S Lim
Journal:  PLoS Med       Date:  2014-09-22       Impact factor: 11.069

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  11 in total

1.  Evidence for an expanded hypertension care cascade in low- and middle-income countries: a scoping review.

Authors:  Michael A Peters; Caitlin M Noonan; Krishna D Rao; Anbrasi Edward; Olakunle O Alonge
Journal:  BMC Health Serv Res       Date:  2022-06-27       Impact factor: 2.908

2.  Effectiveness of a Multidisciplinary Approach Intervention to Improve Blood Pressure Control Among Elderly Hypertensive Patients in Rural Thailand: A Quasi-Experimental Study.

Authors:  Nanthakan Sungsuman Woodham; Surasak Taneepanichskul; Ratana Somrongthong; Apaporn Kitsanapun; Benjapan Sompakdee
Journal:  J Multidiscip Healthc       Date:  2020-07-03

3.  Prevalence of and factors associated with hypertension among the hill tribe population aged 35 years and over in northern Thailand: a cross-sectional study.

Authors:  Kanya Somprasong; Tawatchai Apidechkul; Niwed Kullawong; Panupong Upala; Ratipark Tamornpark; Chalitar Chomchoei; Fartima Yeemard; Siriyaporn Khunthason; Vivat Keawdounglek; Chanyanut Wongfu
Journal:  Am J Cardiovasc Dis       Date:  2020-04-15

4.  Health risk behaviors, musculoskeletal disorders and associated cultural adaptation, depression: a survey among Myanmar migrant workers in Chiangmai, Northern Thailand.

Authors:  Thin Nyein Nyein Aung; Yoshihisa Shirayama; Saiyud Moolphate; Myo Nyein Aung; Thaworn Lorga; Motoyuki Yuasa
Journal:  Int J Gen Med       Date:  2019-08-14

5.  Contribution of Four Polymorphisms in Renin-Angiotensin-Aldosterone-Related Genes to Hypertension in a Thai Population.

Authors:  Pimphen Charoen; Jakris Eu-Ahsunthornwattana; Nisakron Thongmung; Pedro A Jose; Piyamitr Sritara; Prin Vathesatogkit; Chagriya Kitiyakara
Journal:  Int J Hypertens       Date:  2019-08-14       Impact factor: 2.420

6.  Coverage and effectiveness of hypertension screening in different altitudes of Tibet autonomous region.

Authors:  Ci Song; Virasakdi Chongsuvivatwong; Suolang Wangdui; Danzeng Mima; Cuoji Zhuoma; D Ji; Ouzhu Luobu; Hutcha Sriplung
Journal:  BMC Public Health       Date:  2021-01-06       Impact factor: 3.295

7.  Lack of a bridge between screening and medical management for hypertension: health screening cohort in Japan.

Authors:  Shingo Fukuma; Tatsuyoshi Ikenoue; Yoshiyuki Saito; Yukari Yamada; Yusuke Saigusa; Toshihiro Misumi; Masataka Taguri
Journal:  BMC Public Health       Date:  2020-09-17       Impact factor: 3.295

8.  Geographical inequality in service utilization for primary aldosteronism screening: spatial epidemiological study in Southern Thailand.

Authors:  Onnicha Suntornlohanakul; Suporn Sakarin; Noppadol Kietsiriroje; Hutcha Sriplung
Journal:  BMC Health Serv Res       Date:  2022-04-07       Impact factor: 2.655

9.  Prevalence and Risk Factors for Hypertension among Myanmar Migrant Workers in Thailand.

Authors:  Thin Nyein Nyein Aung; Yoshihisa Shirayama; Saiyud Moolphate; Thaworn Lorga; Warunyou Jamnongprasatporn; Motoyuki Yuasa; Myo Nyein Aung
Journal:  Int J Environ Res Public Health       Date:  2022-03-16       Impact factor: 3.390

10.  Clinical audit of adherence to hypertension treatment guideline and control rates in hospitals of different sizes in Thailand.

Authors:  Chaisiri Angkurawaranon; Kanokporn Pinyopornpanish; Supattra Srivanichakorn; Pattara Sanchaisuriya; Bang-On Thepthien; Dusida Tooprakai; Elisha Ngetich; Albertino Damasceno; Michael Hecht Olsen; James E Sharman; Renu Garg
Journal:  J Clin Hypertens (Greenwich)       Date:  2021-01-27       Impact factor: 3.738

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