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The implementation of maternal health guidelines remains unsatisfactory, even for simple, well established interventions. In settings where most births occur in health facilities, as is the case in Kerala, India, preventing maternal mortality is linked to quality of care improvements.Evidence-informed quality standards (QS), including quality statements and measurable structure and process indicators, are one innovative way of tackling the guideline implementation gap. Having adopted a zero tolerance policy to maternal deaths, the Government of Kerala worked in partnership with the Kerala Federation of Obstetricians & Gynaecologists (KFOG) and NICE International to select the clinical topic, develop and initiate implementation of the first clinical QS for reducing maternal mortality in the state. Description of practice: The NICE QS development framework was adapted to the Kerala context, with local ownership being a key principle. Locally generated evidence identified post-partum haemorrhage as the leading cause of maternal death, and as the key priority for the QS. A multidisciplinary group (including policy-makers, gynaecologists and obstetricians, nurses and administrators) was established. Multi-stakeholder workshops convened by the group ensured that the statements, derived from global and local guidelines, and their corresponding indicators were relevant and acceptable to clinicians and policy-makers in Kerala. Furthermore, it helped identify practical methods for implementing the standards and monitoring outcomes.An independent evaluation of the project highlighted the equal importance of a strong evidence-base and an inclusive development process. There is no one-size-fits-all process for QS development; a principle-based approach might be a better guide for countries to adapt global evidence to their local context.

作者:Ioana, Vlad;V P, Paily;Rajeev, Sadanandan;Fran?oise, Cluzeau;M, Beena;Rajasekharan, Nair;Emma, Newbatt;Sujit, Ghosh;K, Sandeep;Kalipso, Chalkidou

来源:F1000Research 2016 年 5卷

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作者:
Ioana, Vlad;V P, Paily;Rajeev, Sadanandan;Fran?oise, Cluzeau;M, Beena;Rajasekharan, Nair;Emma, Newbatt;Sujit, Ghosh;K, Sandeep;Kalipso, Chalkidou
来源:
F1000Research 2016 年 5卷
标签:
evidence-informed policy-making maternal health quality improvement
The implementation of maternal health guidelines remains unsatisfactory, even for simple, well established interventions. In settings where most births occur in health facilities, as is the case in Kerala, India, preventing maternal mortality is linked to quality of care improvements.Evidence-informed quality standards (QS), including quality statements and measurable structure and process indicators, are one innovative way of tackling the guideline implementation gap. Having adopted a zero tolerance policy to maternal deaths, the Government of Kerala worked in partnership with the Kerala Federation of Obstetricians & Gynaecologists (KFOG) and NICE International to select the clinical topic, develop and initiate implementation of the first clinical QS for reducing maternal mortality in the state. Description of practice: The NICE QS development framework was adapted to the Kerala context, with local ownership being a key principle. Locally generated evidence identified post-partum haemorrhage as the leading cause of maternal death, and as the key priority for the QS. A multidisciplinary group (including policy-makers, gynaecologists and obstetricians, nurses and administrators) was established. Multi-stakeholder workshops convened by the group ensured that the statements, derived from global and local guidelines, and their corresponding indicators were relevant and acceptable to clinicians and policy-makers in Kerala. Furthermore, it helped identify practical methods for implementing the standards and monitoring outcomes.An independent evaluation of the project highlighted the equal importance of a strong evidence-base and an inclusive development process. There is no one-size-fits-all process for QS development; a principle-based approach might be a better guide for countries to adapt global evidence to their local context.