Desafios da implementação da rede cegonha: reflexões sobre planejamento e avaliação dos serviços de acolhimento com classificação de risco obstétrico / Challenges of the implementation of the Stork Network: reflections on planning and evaluation of reception services with obstetric risk classification / Desafíos de la implementación de la Red Cigüeña: reflexiones sobre la planificación y evaluación de servicios de acogida con clasificación de riesgo obstétrico

Considerando o ciclo das Políticas públicas, o planejamento e a avaliação são elementos cruciais, favorecendo organização e julgamento de valor a respeito de uma intervenção ou sobre qualquer um dos seus componentes, envolvendo tanto quem faz uso dos serviços como quem produz os mesmos. Na perspectiva da melhoria da assistência prestada à mulher e ao recém-nascido na porta de entrada dos serviços de atenção materno-infantis, é realizado o Acolhimento com Classificação de Risco Obstétrico que cursa como uma ferramenta de apoio à tomada de decisão clínica que tem como intuito a identificação da paciente crítica ou mais grave, permitindo um atendimento de maneira rápida e segura de acordo com o potencial de risco, com base nas evidências científicas existentes. Objetivo: Realizar uma reflexão teórica acerca dos avanços e limitações relacionados aoplanejamento e avaliação dos serviços deAcolhimento com Classificação de RiscoObstétrico.Metodologia:Trata-se de um estudo de caráter descritivo, em formato de artigo de reflexão, em que foram definidas duas dimensões categóricas que retratam o contexto do planejamento e avaliação dos serviços de Acolhimento com Classificação de RiscoObstétrico.Resultados:Percebemos que ainda é possível identificar muitas arestas no planejamento e na qualidade da prestação deste tipo de serviço, principalmente no que diz respeito à garantia da integralidade e do cuidado de acordo com as necessidades da mulher.Conclusões:Para que uma articulação entre os diferentes atores seja alcançada são necessárias estratégias de planejamento que tornem viável buscar a qualidade assistencial e que deem condições de avaliar essa assistência prestada (AU).

Considering the cycle of Public Policies, planning and evaluation are crucial elements, favoring organization and judgment of valuesregarding an intervention or any of its components, involving both those who use the services and those who produce them. With a view toimproving the care provided to women and newborns at the entranceto maternal and child care services, the Reception with Obstetric Risk Classification iscarried out as a tool to support clinical decision-making which aims to identify critical or more severe patients, allowing a quick and safe care according to the risk potential, based on existing scientific evidence.Objective:To carry out a theoretical reflection on the advances and limitations related to the planning and evaluation of Reception serviceswith Obstetric Risk Classification.Methodology:This is a descriptive study, in the form of a reflection article, in which two categorical dimensions were defined and that portray the context of planning and evaluation of Reception serviceswith Obstetric Risk Classification.Results:We realized that it is still possible to identify many edges in the planning and quality of the provision of this type of service, especially with regard to ensuring comprehensiveness and care according to the needs of women.Conclusions:In order to achieved thearticulation between the different actors, it is necessary to plan strategies that make it feasible to seek care quality and that provide conditions for evaluating this assistance provided (AU).

Considerando el ciclo de las Políticas Públicas, la planificación y la evaluación son elementos cruciales, favoreciendo la organización y el juicio de valor sobre una intervención o cualquiera de sus componentes, involucrando tanto a quienes utilizan los servicios como a quienes los producen. Con el objetivode mejorar la asistenciabrindadaa lasmujeresy recién nacidosen elingresoa los servicios de atención materno-infantil, se realiza laAcogidacon Clasificación de Riesgo Obstétrico como una herramienta de apoyo a la toma de decisiones clínicas que tiene como objetivo identificar las pacientes más graves, permitiendo una atención rápida y segura de acuerdo al potencial de riesgo, segúnla evidencia científica existente.Objetivo: Realizar una reflexión teórica sobre los avances y limitaciones relacionados con la planificación y evaluación de los servicios de Acogida con Clasificación de Riesgo Obstétrico.Metodología:Se trata de un estudio descriptivo, en forma de artículo de reflexión, en el que se definieron dos dimensiones categóricas que retratan el contexto de planificación y evaluación de los servicios de Acogida con Clasificación de Riesgo Obstétrico. Resultados: Percibimos que aún es posible identificar muchas asperezasen la planificación y calidad de la prestación de este tipo de servicio, especialmente en lo que se respectaa garantizar la integralidad y la atención acorde a las necesidades de las mujeres. Conclusiones: Para que se logre una articulación entre los diferentes actores, son necesarias estrategias de planificación que viabilicen la búsqueda de la calidad de la atención y que proporcionen condiciones para evaluar esta asistencia brindada (AU).

An Assessment of State-Level Planning for Physical Activity Promotion in the United States.

The prevalence and attributable risk of disease due to physical inactivity require it to be made a public health priority. Public health planning allows for prioritization and resource allocation, particularly at the state and local levels. The extent to which state planning efforts for physical activity exist in the United States is unknown. The purpose of this paper is to describe the scope in which physical activity is incorporated in state-level public health plans in the United States, with an emphasis on alignment with the national guidelines and the National Physical Activity Plan. A standardized internet search audit was developed and conducted for each of 50 US states and the District of Columbia between May 2017 and January 2018 to determine the prevalence and characteristics of health planning documents that include physical activity. Data abstracted for analysis used a standardized search protocol that included the components of the Physical Activity Guidelines for Americans and the US National Physical Activity Plan. Results found that most states had between 4 and 6 chronic disease prevention and control plans that mention physical activity; however, it was inconsistently aligned with recommendations from both the Guidelines and the National Plan. Only 2 states had stand-alone public health planning documents explicitly dedicated to physical activity promotion. No state planning documents addressed children and adolescents, adults, and older adults simultaneously. To be maximally effective, state public health planning for physical activity should be made a priority and these efforts should align as much as possible with current guidance from the Physical Activity Guidelines for Americans and the US National Physical Activity Plan.

Using modeling and scenario analysis to support evidence-based health workforce strategic planning in Malawi.

BACKGROUND: A well-trained and equitably distributed workforce is critical to a functioning health system. As workforce interventions are costly and time-intensive, investing appropriately in strengthening the health workforce requires an evidence-based approach to target efforts to increase the number of health workers, deploy health workers where they are most needed, and optimize the use of existing health workers. This paper describes the Malawi Ministry of Health (MoH) and collaborators' data-driven approach to designing strategies in the Human Resources for Health Strategic Plan (HRH SP) 2018-2022. METHODS: Three modelling exercises were completed using available data in Malawi. Staff data from districts, central hospitals, and headquarters, and enrollment data from all health training institutions were collected between October 2017 and February 2018. A vacancy analysis was conducted to compare current staffing levels against established posts (the targeted number of positions to be filled, by cadre and work location). A training pipeline model was developed to project the future available workforce, and a demand-based Workforce Optimization Model was used to estimate optimal staffing to meet current levels of service utilization. RESULTS: As of 2017, 55% of established posts were filled, with an average of 1.49 health professional staff per 1000 population, and with substantial variation in the number of staff per population by district. With current levels of health worker training, Malawi is projected to meet its establishment targets in 2030 but will not meet the WHO standard of 4.45 health workers per 1000 population by 2040. A combined intervention reducing attrition, increasing absorption, and doubling training enrollments would allow the establishment to be met by 2023 and the WHO target to be met by 2036. The Workforce Optimization Model shows a gap of 7374 health workers to optimally deliver services at current utilization rates, with the largest gaps among nursing and midwifery officers and pharmacists. CONCLUSIONS: Given the time and significant financial investment required to train and deploy health workers, evidence needs to be carefully considered in designing a national HRH SP. The results of these analyses directly informed Malawi's HRH SP 2018-2022 and have subsequently been used in numerous planning processes and investment cases in Malawi. This paper provides a practical methodology for evidence-based HRH strategic planning and highlights the importance of strengthening HRH data systems for improved workforce decision-making.

Understanding the role of village fund and administrative capacity in stunting reduction: Empirical evidence from Indonesia.

The Indonesian government launched various programs to handle stunting cases, including village funds. This paper examined the effects of village fund programs and village apparatuses' capacities to combat stunting based on aggregate data at the district level in Indonesia. Using descriptive data analysis and fixed effect panel regression, we observed that village fund programs could significantly reduce Indonesia's stunting prevalence, especially outside Java. It also revealed that the increasing education of regional leaders does not necessarily positively impact leaders' skills in handling stunting. At the same time, the number of village officials has a statistically significant influence on reducing stunting prevalence. It advised that the village budget fund can support national priorities in tackling the prevalence of stunting. Furthermore, it is essential to build the capacity of the village head for increasing awareness of health activities, especially early prevention of stunting, in addition to an adequate number of officials.

Role of geospatial mapping in the planning of HIV programs: A case study from Southern India.

ABSTRACT: Geographic information systems (GIS) tools can be used to understand the spatial distribution of local HIV epidemics but are often underutilized, especially in low-middle income countries. We present characteristics of an HIV epidemic within Hyderabad, a large city in southern India, as a case study to highlight the utility of such data in program planning.Cross-sectional sample recruited using respondent-driven sampling in a cluster-randomized trial.We analyzed data from 2 cross-sectional respondent-driven sampling surveys of MSM in Hyderabad, which were conducted as part of a cluster-randomized trial. All participants were tested for HIV and those positive underwent viral load quantification. ArcGIS was used to create heat maps of MSM distribution using self-reported postal code of residence and combined into larger zones containing at least 200 MSM.Postal code data was available for 661 MSM (66.2%) in the baseline and 978 MSM (97.8%) in the follow-up survey. The proportion of HIV-positive MSM (12.7-15.7%) and prevalence of virally suppressed persons (2.6-8.2%) increased between the 2 surveys. The distribution of all MSM, HIV-positive MSM, and HIV-viremic MSM differed significantly by geographic zone with several zones having higher numbers of HIV-positive and viremic individuals than would be expected based on the distribution of all MSM.The prevalence of HIV and HIV viremia among MSM differed by geographic zones within a city and evolved over time. Such data could be critical to improving program implementation efficiency by accurately targeting resources to population characteristics.

Toward a New Strategic Public Health Science for Policy, Practice, Impact, and Health Equity.

The COVID-19 pandemic and its social and health impact have underscored the need for a new strategic science agenda for public health. To optimize public health impact, high-quality strategic science addresses scientific gaps that inform policy and guide practice. At least 6 scientific gaps emerge from the US experience with COVID-19: health equity science, data science and modernization, communication science, policy analysis and translation, scientific collaboration, and climate science. Addressing these areas within a strategic public health science agenda will accelerate achievement of public health goals. Public health leadership and scientists have an unprecedented opportunity to use strategic science to guide a new era of improved and equitable public health.

Scenario modelling as planning evidence to improve access to emergency obstetric care in eastern Indonesia.

The rate of maternal deaths in remote areas in eastern Indonesia-where geographic conditions are difficult and the standard of infrastructure is poor-is high. Long travel times needed to reach emergency obstetric care (EMOC) is one cause of maternal death. District governments in eastern Indonesia need effective planning to improve access to EMOC. The aim of this study was to develop a scenario modelling tool to be used in planning to improve access to EMOC in eastern Indonesia. The scenario model was developed using the geographic information system tool in NetLogo. This model has two inputs: the location of the EMOC facility (PONED) and the travel cost of moving across geographical features in the rainy and dry seasons. We added a cost-benefit analysis to the model: cost is the budget for building the infrastructure; benefit is the number of people who can travel to the EMOC in less than 1 hour if the planned infrastructure is built. We introduced the tool to representative midwives from all districts of Nusa Tenggara Timur province and to staff of Kupang district planning agency. We found that the tool can model accessibility to EMOC based on weather conditions; compare alternative infrastructure planning scenarios based on cost-benefit analysis; enable users to identify and mark poor infrastructure; and model travel across the ocean. Lay people can easily use the tool through interactive scenario modelling: midwives can use it for evidence to support planning proposals to improve access to EMOC in their district; district planning agencies can use it to choose the best plan to improve access to EMOC. Scenario modelling has potential for use in evidence-based planning to improve access to EMOC in low-income and lower-middle-income countries with poor infrastructure, difficult geography conditions, limited budgets and lack of trained personnel.

How New Mexico Leveraged a COVID-19 Case Forecasting Model to Preemptively Address the Health Care Needs of the State: Quantitative Analysis.

BACKGROUND: Prior to the COVID-19 pandemic, US hospitals relied on static projections of future trends for long-term planning and were only beginning to consider forecasting methods for short-term planning of staffing and other resources. With the overwhelming burden imposed by COVID-19 on the health care system, an emergent need exists to accurately forecast hospitalization needs within an actionable timeframe. OBJECTIVE: Our goal was to leverage an existing COVID-19 case and death forecasting tool to generate the expected number of concurrent hospitalizations, occupied intensive care unit (ICU) beds, and in-use ventilators 1 day to 4 weeks in the future for New Mexico and each of its five health regions. METHODS: We developed a probabilistic model that took as input the number of new COVID-19 cases for New Mexico from Los Alamos National Laboratory's COVID-19 Forecasts Using Fast Evaluations and Estimation tool, and we used the model to estimate the number of new daily hospital admissions 4 weeks into the future based on current statewide hospitalization rates. The model estimated the number of new admissions that would require an ICU bed or use of a ventilator and then projected the individual lengths of hospital stays based on the resource need. By tracking the lengths of stay through time, we captured the projected simultaneous need for inpatient beds, ICU beds, and ventilators. We used a postprocessing method to adjust the forecasts based on the differences between prior forecasts and the subsequent observed data. Thus, we ensured that our forecasts could reflect a dynamically changing situation on the ground. RESULTS: Forecasts made between September 1 and December 9, 2020, showed variable accuracy across time, health care resource needs, and forecast horizon. Forecasts made in October, when new COVID-19 cases were steadily increasing, had an average accuracy error of 20.0%, while the error in forecasts made in September, a month with low COVID-19 activity, was 39.7%. Across health care use categories, state-level forecasts were more accurate than those at the regional level. Although the accuracy declined as the forecast was projected further into the future, the stated uncertainty of the prediction improved. Forecasts were within 5% of their stated uncertainty at the 50% and 90% prediction intervals at the 3- to 4-week forecast horizon for state-level inpatient and ICU needs. However, uncertainty intervals were too narrow for forecasts of state-level ventilator need and all regional health care resource needs. CONCLUSIONS: Real-time forecasting of the burden imposed by a spreading infectious disease is a crucial component of decision support during a public health emergency. Our proposed methodology demonstrated utility in providing near-term forecasts, particularly at the state level. This tool can aid other stakeholders as they face COVID-19 population impacts now and in the future.

Development of COVIDVax Model to Estimate the Risk of SARS-CoV-2-Related Death Among 7.6 Million US Veterans for Use in Vaccination Prioritization.

Importance: A strategy that prioritizes individuals for SARS-CoV-2 vaccination according to their risk of SARS-CoV-2-related mortality would help minimize deaths during vaccine rollout. Objective: To develop a model that estimates the risk of SARS-CoV-2-related mortality among all enrollees of the US Department of Veterans Affairs (VA) health care system. Design, Setting, and Participants: This prognostic study used data from 7 635 064 individuals enrolled in the VA health care system as of May 21, 2020, to develop and internally validate a logistic regression model (COVIDVax) that predicted SARS-CoV-2-related death (n = 2422) during the observation period (May 21 to November 2, 2020) using baseline characteristics known to be associated with SARS-CoV-2-related mortality, extracted from the VA electronic health records (EHRs). The cohort was split into a training period (May 21 to September 30) and testing period (October 1 to November 2). Main Outcomes and Measures: SARS-CoV-2-related death, defined as death within 30 days of testing positive for SARS-CoV-2. VA EHR data streams were imported on a data integration platform to demonstrate that the model could be executed in real-time to produce dashboards with risk scores for all current VA enrollees. Results: Of 7 635 064 individuals, the mean (SD) age was 66.2 (13.8) years, and most were men (7 051 912 [92.4%]) and White individuals (4 887 338 [64.0%]), with 1 116 435 (14.6%) Black individuals and 399 634 (5.2%) Hispanic individuals. From a starting pool of 16 potential predictors, 10 were included in the final COVIDVax model, as follows: sex, age, race, ethnicity, body mass index, Charlson Comorbidity Index, diabetes, chronic kidney disease, congestive heart failure, and Care Assessment Need score. The model exhibited excellent discrimination with area under the receiver operating characteristic curve (AUROC) of 85.3% (95% CI, 84.6%-86.1%), superior to the AUROC of using age alone to stratify risk (72.6%; 95% CI, 71.6%-73.6%). Assuming vaccination is 90% effective at preventing SARS-CoV-2-related death, using this model to prioritize vaccination was estimated to prevent 63.5% of deaths that would occur by the time 50% of VA enrollees are vaccinated, significantly higher than the estimate for prioritizing vaccination based on age (45.6%) or the US Centers for Disease Control and Prevention phases of vaccine allocation (41.1%). Conclusions and Relevance: In this prognostic study of all VA enrollees, prioritizing vaccination based on the COVIDVax model was estimated to prevent a large proportion of deaths expected to occur during vaccine rollout before sufficient herd immunity is achieved.

London 2017: Lessons learned in transfusion emergency planning.

BACKGROUND AND OBJECTIVES: Hospitals prepare for emergencies, but the impact on transfusion staff is rarely discussed. We describe the transfusion response to four major incidents (MIs) during a 6-month period. Three events were due to terrorist attacks, and the fourth was the Grenfell Tower fire. The aim of this paper was to share the practical lessons identified. METHODS: This was a retrospective review of four MIs in 2017 using patient administration systems, MI documentation and post-incident debriefs. Blood issue, usage and adverse events during the four activation periods were identified using the Laboratory Information Management System (TelePath). RESULTS: Thirty-four patients were admitted (18 P1, 4 P2, 11 P3 and 1 dead). Forty-five blood samples were received: 24 related to nine MI P1 patients. Four P1s received blood components, three with trauma and one with burns, and 35 components were issued. Total components used were six red blood cells (RBC), six fresh frozen plasma (FFP) and two cryoprecipitate pools. Early lessons identified included sample labelling errors (4/24). Errors resolved following the deployment of transfusion staff within the emergency department. Components were over-ordered, leading to time-expiry wastage of platelets. Careful staff management ensured continuity of transfusion services beyond the immediate response period. Debriefing sessions provided staff with support and enabled lessons to be shared. CONCLUSIONS: Transfusion teams were involved in repeated incidents. The demand for blood was minimal. Workload was related to sample handling rather than component issue. A shared situational awareness would improve stock management. A laboratory debriefing system offered valuable feedback for service improvement, staff training and support.

Geographic Coverage and Verification of Trauma Centers in a Rural State: Highlighting the Utility of Location Allocationfor Trauma System Planning.

BACKGROUND: Care at verified trauma centers has improved survival and functional outcomes, yet determining the appropriate location of potential trauma centers is often driven by factors other than optimizing system-level patient care. Given the importance of transport time in trauma, we analyzed trauma transport patterns in a rural state lacking an organized trauma system and implemented a geographic information system to inform potential future trauma center locations. STUDY DESIGN: Data were collected on trauma ground transport during a 3-year period (2014 through 2016) from the Statewide Incident Reporting Network database. Geographic information system mapping and location-allocation modeling of the best-fit facility for trauma center verification was computed using trauma transport patterns, population density, road network layout, and 60-minute emergency medical services transport time based on current transport protocols. RESULTS: Location-allocation modeling identified 2 regional facilities positioned to become the next verified trauma centers. The proportion of the Vermont population without access to trauma center care within 60 minutes would be reduced from the current 29.68% to 5.81% if the identified facilities become verified centers. CONCLUSIONS: Through geospatial mapping and location-allocation modeling, we were able to identify gaps and suggest optimal trauma center locations to maximize population coverage in a rural state lacking a formal, organized trauma system. These findings could inform future decision-making for targeted capacity improvement and system design that emphasizes more equitable access to trauma center care in Vermont.

Engaging Consumers in Medicaid Program Design: Strategies from the States.

Policy Points As Medicaid programs grow in scale and complexity, greater consumer input may guide successful program design, but little is known about the extent to which state agencies are engaging consumers in the design and implementation of programs and policies. Through 50 semistructured interviews with Medicaid leaders in 14 states, we found significant variation in consumer engagement approaches, with many common facilitators, including leadership commitment, flexible strategies for recruiting and supporting consumer participation, and robust community partnerships. We provide early evidence on how state Medicaid agencies are integrating consumers' experiences and perspectives into their program design and governance. CONTEXT: Consumer engagement early in the process of health care policymaking may improve the effectiveness of program planning and implementation, promote patient-centric care, enhance beneficiary protections, and offer opportunities to improve service delivery. As Medicaid programs grow in scale and complexity, greater consumer input may guide successful program design, but little is known about the extent to which state agencies are currently engaging consumers in the design and implementation of programs and policies, and how this is being done. METHODS: We conducted semistructured interviews with 50 Medicaid program leaders across 14 states, employing a stratified purposive sampling method to select state Medicaid programs based on US census region, rurality, Medicaid enrollment size, total population, ACA expansion status, and Medicaid managed care penetration. Interview data were audio-recorded, professionally transcribed, and underwent iterative coding with content and thematic analyses. FINDINGS: First, we found variation in consumer engagement approaches, ranging from limited and largely symbolic interactions to longer-term deliberative bodies, with some states tailoring their federally mandated standing committees to engage consumers. Second, most states were motivated by pragmatic considerations, such as identifying and overcoming implementation challenges for agency programs. Third, states reported several common facilitators of successful consumer engagement efforts, including leadership commitment, flexible strategies for recruiting and supporting consumers' participation, and robust community partnerships. All states faced barriers to authentic and sustained engagement. CONCLUSIONS: Sharing best practices across states could help strengthen programs' engagement efforts, identify opportunities for program improvement reflecting community needs, and increase participation among a population that has traditionally lacked a political voice.

Integrating the Built and Social Environment into Health Assessments for Maternal and Child Health: Creating a Planning-Friendly Index.

Environmental and community context earliest in the life course have a profound effect on life-long health outcomes. Yet, standard needs assessments for maternal and child health (MCH) programs often overlook the full range of influences affecting health in-utero and early childhood. To address this, we developed a methodology for assessing community risk in MCH based on six domains integrating 66 indicators across community, environment, socioeconomic indicators, and MCH outcomes. We pilot this methodology in Pennsylvania, and share examples of how local governments, planners, and public health officials across the geographic spectrum can integrate this data into community planning for improved maternal and child health.

Predicting mortality for Covid-19 in the US using the delayed elasticity method.

The evolution of the pandemic caused by COVID-19, its high reproductive number and the associated clinical needs, is overwhelming national health systems. We propose a method for predicting the number of deaths, and which will enable the health authorities of the countries involved to plan the resources needed to face the pandemic as many days in advance as possible. We employ OLS to perform the econometric estimation. Using RMSE, MSE, MAPE, and SMAPE forecast performance measures, we select the best lagged predictor of both dependent variables. Our objective is to estimate a leading indicator of clinical needs. Having a forecast model available several days in advance can enable governments to more effectively face the gap between needs and resources triggered by the outbreak and thus reduce the deaths caused by COVID-19.

The legacy of MeNZB and possible implications for COVID-19 vaccination.

It is now over a decade since the meningococcal B vaccine, MeNZB, was in routine use in New Zealand. From July 2004 until June 2008 it was administered in a three-dose schedule to over a million individuals, aged six weeks to 20 years, to provide protection against the epidemic strain of group B Meningococci. The cost of the campaign, including the development of the vaccine was substantial, in excess of $200M, but it contributed to a reduced incidence of meningococcal infections along with a reduction in morbidity and mortality. The campaign led to the development of a national immunisation register (NIR), which is still in existence today. As well as considering the legacies of the MeNZB vaccination programme, this paper examines whether there are any lessons to be learned, specifically concerning active vaccine safety monitoring, which may be important if, and when, a COVID-19 vaccine is developed and a national immunisation campaign instituted.