Dataset Information

Evaluating implementation of International Health Regulations core capacities: using the Electronic States Parties Self-Assessment Annual Reporting Tool (e-SPAR) to monitor progress with Joint External Evaluation indicators.

ABSTRACT:

Background

The International Health Regulations (IHR) are a legally binding instrument designed to improve Global Health Security by limiting the cross boarder spread of health risks. All 196 signatories to the IHR (2005) are required to report progress towards IHR core capacity implementation through an annual multi-sectoral self-assessment process known as the State Parties Self-Assessment Annual Reporting (SPAR). This mandatory process sits alongside the voluntary, external, peer-reviewed Joint External Evaluations (JEE) as two core components of the IHR monitoring and evaluation framework. JEEs are intended to occur once every 4-5 years following a voluntary request from the member state. This means that interim monitoring of IHR core capacity compliance, can be challenging and additional data sources are required. The outputs of the SPAR process represent one such source. Although the JEE and SPAR tools are intended to be complimentary, there has been no publicly available mapping of JEE indicators to SPAR indicators in order to inform progress on IHR compliance.

Results

This paper mapped JEE indicators to SPAR indicators and found a high level of correlation suggesting the SPAR process offers a method for countries and technical assistance programmes to monitor progress on IHR compliance and identify gaps in between JEE visits. However, coverage was not complete, and several gaps were identified most notably in antimicrobial resistance (AMR) and vaccinations.

Conclusion

Enhancing alignment between JEE and SPAR could offer a more consistent and complete way of assessing compliance with IHR.

SUBMITTER: Razavi A

PROVIDER: S-EPMC8243291 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundPublic health measures to prevent, detect, and respond to events are essential to control public health risks, including infectious disease outbreaks, as highlighted in the International Health Regulations (IHR). In light of the outbreak of 2019 novel coronavirus disease (COVID-19), we aimed to review existing health security capacities against public health risks and events.MethodsWe used 18 indicators from the IHR State Party Annual Reporting (SPAR) tool and associated data from national SPAR reports to develop five indices: (1) prevent, (2) detect, (3) respond, (4) enabling function, and (5) operational readiness. We used SPAR 2018 data for all of the indicators and categorised countries into five levels across the indices, in which level 1 indicated the lowest level of national capacity and level 5 the highest. We also analysed data at the regional level (using the six geographical WHO regions).FindingsOf 182 countries, 52 (28%) had prevent capacities at levels 1 or 2, and 60 (33%) had response capacities at levels 1 or 2. 81 (45%) countries had prevent capacities and 78 (43%) had response capacities at levels 4 or 5, indicating that these countries were operationally ready. 138 (76%) countries scored more highly in the detect index than in the other indices. 44 (24%) countries did not have an effective enabling function for public health risks and events, including infectious disease outbreaks (7 [4%] at level 1 and 37 [20%] at level 2). 102 (56%) countries had level 4 or level 5 enabling function capacities in place. 32 (18%) countries had low readiness (2 [1%] at level 1 and 30 [17%] at level 2), and 104 (57%) countries were operationally ready to prevent, detect, and control an outbreak of a novel infectious disease (66 [36%] at level 4 and 38 [21%] at level 5).InterpretationCountries vary widely in terms of their capacity to prevent, detect, and respond to outbreaks. Half of all countries analysed have strong operational readiness capacities in place, which suggests that an effective response to potential health emergencies could be enabled, including to COVID-19. Findings from local risk assessments are needed to fully understand national readiness capacities in relation to COVID-19. Capacity building and collaboration between countries are needed to strengthen global readiness for outbreak control.FundingNone.

Project description:BackgroundScientific research has provided evidence on benefits of well developed primary care systems. The relevance of some of this research for the European situation is limited.There is currently a lack of up to date comprehensive and comparable information on variation in development of primary care, and a lack of knowledge of structures and strategies conducive to strengthening primary care in Europe. The EC funded project Primary Health Care Activity Monitor for Europe (PHAMEU) aims to fill this gap by developing a Primary Care Monitoring System (PC Monitor) for application in 31 European countries. This article describes the development of the indicators of the PC Monitor, which will make it possible to create an alternative model for holistic analyses of primary care.MethodsA systematic review of the primary care literature published between 2003 and July 2008 was carried out. This resulted in an overview of: (1) the dimensions of primary care and their relevance to outcomes at (primary) health system level; (2) essential features per dimension; (3) applied indicators to measure the features of primary care dimensions. The indicators were evaluated by the project team against criteria of relevance, precision, flexibility, and discriminating power. The resulting indicator set was evaluated on its suitability for Europe-wide comparison of primary care systems by a panel of primary care experts from various European countries (representing a variety of primary care systems).ResultsThe developed PC Monitor approaches primary care in Europe as a multidimensional concept. It describes the key dimensions of primary care systems at three levels: structure, process, and outcome level. On structure level, it includes indicators for governance, economic conditions, and workforce development. On process level, indicators describe access, comprehensiveness, continuity, and coordination of primary care services. On outcome level, indicators reflect the quality, and efficiency of primary care.ConclusionsA standardized instrument for describing and comparing primary care systems has been developed based on scientific evidence and consensus among an international panel of experts, which will be tested to all configurations of primary care in Europe, intended for producing comparable information. Widespread use of the instrument has the potential to improve the understanding of primary care delivery in different national contexts and thus to create opportunities for better decision making.

Project description:PurposeA newly developed brief measure of nursing facility (NF) resident self-reported quality of life (QOL) has been proposed for inclusion in a modified version of the minimum data set (MDS). There is considerable interest in determining whether it is possible to develop indicators of QOL that are more convenient and less expensive than direct, in-person interviews with residents.Design and methodsQOL interview data from 2,829 residents living in 101 NFs using a 14-item version of a longer instrument were merged with data from the MDS and the Online Survey and Certification Automated Record (OSCAR). Bivariate and multivariate hierarchical linear modeling were used to assess the association of QOL with potential resident and facility level indicators.ResultsResident and facility level indicators were associated with self-reported QOL in the expected direction. At the individual resident level, QOL is negatively associated with physical function, visual acuity, continence, being bedfast, depression, conflict in relationships, and positively associated with social engagement. At the facility level, QOL is negatively associated with citations for failing to accommodate resident needs or providing a clean, safe environment. The ratio of activities staff to residents is positively associated with QOL. This study did not find an association between QOL and either use of restraints or nurse staff levels. Approximately 9 percent of the total variance in self-reported QOL can be attributed to differences among facilities; 91 percent can be attributed to differences among residents. Resident level indicators explained about 4 percent of the variance attributable to differences among residents, and facility factors explained 49 percent of the variance attributable to differences among NFs. However, the different variables explained only 10 percent of the variance in self-reported QOL.ImplicationsA brief self-report measure of NF resident QOL is consistently associated with measures that can be constructed from extant data sources. However, the level of prediction possible from these data sources does not justify reliance on external indicators of resident QOL for policy purposes.