Government-Expert Joint Intervention with Treatment Algorithm and Improved Hypertension Management and Reduced Stroke Mortality in a Primary-Care Setting.
Mulalibieke HeizhatiNan-Fang LiDelian ZhangSuofeiya AbulikemuGuijuan ChangJing HongNuerguli MaimaitiJunli HuLei WangGulinuer DuiyimuhanPublished in: International journal of hypertension (2021)
Hypertension management is suboptimal in the primary-care setting of developing countries, where the burden of both hypertension and cardiovascular disease is huge. Therefore, we conducted a government-expert joint intervention in a resource-constrained primary setting of Emin, China, between 2014 and 2016, to improve hypertension management and reduce hypertension-related hospitalization and mortality. Primary-care providers were trained on treatment algorithm and physicians for specialized management. Public education was delivered by various ways including door-to-door screening. Program effectiveness was evaluated using screening data by comparing hypertension awareness, treatment, and control rates and by comparing hypertension-related hospitalization and total cardiovascular disease (CVD) and stroke mortality at each phase. As results, 313 primary-health providers were trained to use the algorithm and 3 physicians attended specialist training. 1/3 of locals (49490 of 133376) were screened. Compared to the early phase, hypertension awareness improved by 9.3% (58% vs. 64%), treatment by 11.4% (39% vs. 44%), and control rates by 33% (10% vs. 15%). The proportion of case/all-cause hospitalization was reduced by 35% (4.02% vs. 2.60%) for CVD and by 17% (3.72% vs. 3.10%) for stroke. The proportion of stroke/all-cause death was reduced by 46% (21.9% in 2011-2013 vs. 15.0% in 2014-2016). At the control area, the proportion of case/all-cause mortality showed no reduction. In conclusion, government-expert joint intervention with introducing treatment algorithm may improve hypertension control and decrease related hospitalization and stroke mortality in underresourced settings.
Keyphrases
- blood pressure
- primary care
- cardiovascular disease
- randomized controlled trial
- atrial fibrillation
- machine learning
- cardiovascular events
- healthcare
- risk factors
- public health
- type diabetes
- mental health
- palliative care
- deep learning
- systematic review
- coronary artery disease
- metabolic syndrome
- climate change
- body composition
- high intensity
- health information