12 research outputs found

    A Narrative Synthesis of the Health Systems Factors Influencing Optimal Hypertension Control in Sub-Saharan Africa

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    <div><p>Introduction</p><p>In sub-Saharan Africa (SSA), an estimated 74.7 million individuals are hypertensive. Reducing the growing burden of hypertension in sub-Saharan Africa will require a variety of strategies one of which is identifying the extent to which actions originating at the health systems level improves optimal management and control.</p><p>Methods and Results</p><p>We conducted a narrative synthesis of available papers examining health systems factors influencing optimal hypertension in SSA. Eligible studies included those that analyzed the impact of health systems on hypertension awareness, treatment, control and medication adherence. Twenty-five articles met the inclusion criteria and the narrative synthesis identified the following themes: 1) how physical resources influence mechanisms supportive of optimal hypertension control; 2) the role of human resources with enabling and/or inhibiting hypertension control goals; 3) the availability and/or use of intellectual resources; 4) how health systems financing facilitate and/or compromise access to products necessary for optimal hypertension control.</p><p>Conclusion</p><p>The findings highlight the need for further research on the health systems factors that influence management and control of hypertension in the region.</p></div

    Impact of self-monitoring of BP on clinic sBP according to level of co-intervention support at 12 months (15 studies).

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    <p>Change in sBP adjusted for age, sex, baseline clinic BP, and history of diabetes. The trials are grouped into the 4 levels of intervention, and <i>I</i><sup>2</sup> and <i>P</i> values are shown for each level of intervention and for the overall analysis. Effect of self-monitoring on clinic sBP at 6 and 18 months are shown in <a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002389#pmed.1002389.s010" target="_blank">S3</a> and <a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002389#pmed.1002389.s013" target="_blank">S6</a> Figs, respectively. Wakefield’s study participants self-monitored for 6 months; follow-up continued to 12 months. Abbreviations: BP, blood pressure; sBP, systolic blood pressure.</p

    Impact of self-monitoring of BP on clinic and ambulatory dBP at 12 months (4 studies).

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    <p>These 4 studies used both clinic and ambulatory BP as endpoints and so are presented in addition to the overall results in <a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002389#pmed.1002389.g001" target="_blank">Fig 1</a>, which are for clinic BP alone (including these studies). Change in dBP adjusted for age, sex, baseline clinic BP, history of diabetes, and level of intervention. Effect of self-monitoring on diastolic clinic and ambulatory BP at 6 months is in <a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002389#pmed.1002389.s017" target="_blank">S10 Fig</a>. Abbreviations: BP, blood pressure; dBP, diastolic blood pressure.</p

    Impact of self-monitoring of BP on the RR of uncontrolled BP at 12 months according to level of co-intervention support (15 studies).

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    <p>RR of uncontrolled BP adjusted for age, sex, baseline clinic BP, and history of diabetes. The trials are grouped into the 4 levels of intervention, and <i>I</i><sup>2</sup> and <i>P</i> values are shown for each level of intervention and for the overall analysis. The effect of self-monitoring on the RR of BP at 6 and 18 months are displayed in <a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002389#pmed.1002389.s012" target="_blank">S5</a> and <a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002389#pmed.1002389.s015" target="_blank">S8</a> Figs, respectively. Wakefield study participants self-monitored for 6 months; follow-up continued to 12 months. Abbreviations: BP, blood pressure; RR, relative risk.</p
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