Telehealth to support referral management in a universal health system: a before-and-after study.

BACKGROUND: Management of patient flow within a healthcare network, allowing equitable and qualified access to healthcare, is a major challenge for universal health systems. Implementation of telehealth strategies to support referral management has been shown to increase primary care resolution and to promote coordination of care. The objective of this study was to assess the impact of telehealth strategies on waiting lists and waiting times for specialized care in Brazil. METHODS: Before-and-after study with measures obtained between January 2019 and February 2020. Baseline measurements of waiting lists were obtained immediately before the implementation of a remotely operated referral management system. Post-interventional measurements were obtained monthly, up to six months after the beginning of operation. Data was extracted from the database of the project. General linear models were applied to assess interaction of locality and time over number of cases on waiting lists and waiting times. RESULTS: At baseline, the median number of cases on waiting lists ranged from 2961 to 12,305 cases. Reductions of the number of cases on waiting lists after six months of operation were observed in all localities. The magnitude of the reduction ranged from 54.67 to 88.97 %. Interaction of time measurements was statistically significant from the second month onward. Median waiting times ranged from 159 to 241 days at baseline. After six months, there was a decrease of 100 and 114 waiting days in two localities, respectively, with reduction of waiting times only for high-risk cases in the third locality. CONCLUSIONS: Adoption of telehealth strategies resulted in the reduction of number of cases on waiting lists. Results were consistent across localities, suggesting that telehealth interventions are viable in diverse settings.

eSIP-Saúde: Mozambique's novel approach for a sustainable human resources for health information system.

INTRODUCTION: Over the past decade, governments and international partners have responded to calls for health workforce data with ambitious investments in human resources information systems (HRIS). However, documentation of country experiences in the use of HRIS to improve strategic planning and management has been lacking. The purpose of this case presentation is to document for the first time Mozambique's novel approach to HRIS, sharing key success factors and contributing to the scant global knowledge base on HRIS. CASE PRESENTATION: Core components of the system are a Government of Mozambique (GOM) registry covering all workers in the GOM payroll and a "health extension" which adds health-sector-specific data to the GOM registry. Separate databases for pre-service and in-service training are integrated through a business intelligence tool. The first aim of the HRIS was to identify the following: who and where are Mozambique's health workers? As of July 2015, 95 % of countrywide health workforce deployment information was populated in the HRIS, allowing the identification of health professionals' physical working location and their pay point. HRIS data are also used to quantify chronic issues affecting the Ministry of Health (MOH) health workforce. Examples include the following: HRIS information was used to examine the deployment of nurses trained in antiretroviral therapy (ART) vis-à-vis the health facilities where ART is being provided. Such results help the MOH align specialized skill sets with service provision. Twenty-five percent of the MOH health workforce had passed the 2-year probation period but had not been updated in the MOH information systems. For future monitoring of employee status, the MOH established a system of alerts in semi-monthly reports. As of August 2014, 1046 health workers were receiving their full salary but no longer working at the facilities. The MOH is now analyzing this situation to improve the retirement process and coordination with Social Security. CONCLUSION: The Mozambican system is an important example of an HRIS built on a local platform with local staff. Notable models of strategic data use demonstrate that the system is empowering the MOH to improve health services delivery, health workforce allocation, and management. Combined with committed country leadership and ownership of the program, this suggests strong chances of sustainability and real impact on public health equity and quality.

Roundtable on Urban Living Environment Research (RULER).

For 18 months in 2009-2010, the Rockefeller Foundation provided support to establish the Roundtable on Urban Living Environment Research (RULER). Composed of leading experts in population health measurement from a variety of disciplines, sectors, and continents, RULER met for the purpose of reviewing existing methods of measurement for urban health in the context of recent reports from UN agencies on health inequities in urban settings. The audience for this report was identified as international, national, and local governing bodies; civil society; and donor agencies. The goal of the report was to identify gaps in measurement that must be filled in order to assess and evaluate population health in urban settings, especially in informal settlements (or slums) in low- and middle-income countries. Care must be taken to integrate recommendations with existing platforms (e.g., Health Metrics Network, the Institute for Health Metrics and Evaluation) that could incorporate, mature, and sustain efforts to address these gaps and promote effective data for healthy urban management. RULER noted that these existing platforms focus primarily on health outcomes and systems, mainly at the national level. Although substantial reviews of health outcomes and health service measures had been conducted elsewhere, such reviews covered these in an aggregate and perhaps misleading way. For example, some spatial aspects of health inequities, such as those pointed to in the 2008 report from the WHO's Commission on the Social Determinants of Health, received limited attention. If RULER were to focus on health inequities in the urban environment, access to disaggregated data was a priority. RULER observed that some urban health metrics were already available, if not always appreciated and utilized in ongoing efforts (e.g., census data with granular data on households, water, and sanitation but with little attention paid to the spatial dimensions of these data). Other less obvious elements had not exploited the gains realized in spatial measurement technology and techniques (e.g., defining geographic and social urban informal settlement boundaries, classification of population-based amenities and hazards, and innovative spatial measurement of local governance for health). In summary, the RULER team identified three major areas for enhancing measurement to motivate action for urban health-namely, disaggregation of geographic areas for intra-urban risk assessment and action, measures for both social environment and governance, and measures for a better understanding of the implications of the physical (e.g., climate) and built environment for health. The challenge of addressing these elements in resource-poor settings was acknowledged, as was the intensely political nature of urban health metrics. The RULER team went further to identify existing global health metrics structures that could serve as platforms for more granular metrics specific for urban settings.