Relevant Health Indicators Research Articles

Identification of relevant mental health indicators for European community-based health enhancing physical activity initiatives: An adapted Delphi study

Health enhancing physical activity (HEPA) initiatives can improve mental health; however there is a lack of standardised measures to evaluate mental health impact. This study aimed to identify the relevant indicators of mental health and well-being in community-based HEPA initiatives in Europe as determined by specialists and practitioners in the field, and understand assessment methods commonly used.An adapted, two round, Delphi method was conducted with N = 20 specialists (practitioners and academics) in the field of mental health and physical activity from Denmark, the Netherlands, the UK, and Ireland. Specialists selected the most important indicators and agreed consensus on definitions and operationalisation, where consensus ≥50% signified important indicators.Specialists compiled 66 (n = 21 outcome, n = 45 determinant) indicators. Top rated indicators for the evaluation of HEPA initiatives were self-rated mental health (69.2%), physical activity (69.2%) life satisfaction (53.8%), stress (53.8%), loneliness (53.8%), social participation, network, connection and support (53.8%). Consensus on definition and application of the nine indicators varied (44.4%–100%), with no consensus on a standardised measurement tool reached, although specialists pointed to the need for culturally sensitive measurement tools.While this study highlights a lack of conformity for evaluating mental health and wellbeing outcomes, it suggests utility in an agreed definition and application of nine indicators for the evaluation of HEPA initiatives, with social determinants of particularly high importance across the relevant contexts. Further research is recommended to develop guidance on pragmatic measurement tools that can be utilised across other (European) countries and their implementation tested.

Improved Deep Extreme Learning Machine for State of Health Estimation of Lithium-Ion Battery

Prediction of state of health (SOH), a crucial aspect of battery management systems, necessitates accurate and reliable estimations for lithium-ion batteries. However, achieving high-precision SOH estimation using the deep extreme learning machine (DELM) in complex environments is challenging due to the instability caused by its random key parameters. To address this, we propose a novel approach that combines the improved bald eagle search (IBES) algorithm with DELM. By utilizing the IBES algorithm, we can extract highly relevant health indicators from the battery’s parameter curve during charging and discharging, as well as the incremental capacity curve. These indicators serve as inputs to the constructed estimation model, which predicts SOH under different working conditions. The proposed method has been validated using publicly available experimental data, with an overall error in SOH estimation of less than 1%. In comparison to the existing model, the proposed method achieves RMSE, MAE, and MAPE values lower than 0.35%, 0.26%, and 0.21%, respectively. These findings demonstrate that the proposed method excels in terms of both the speed and accuracy of SOH estimation, showcasing its enhanced robustness and reliability.

Dietary diversity and healthy weight management in the population: a data-driven analytical approach

Cardiovascular and cerebrovascular diseases (CVDs), diabetes mellitus, malignant tumours and chronic obstructive pulmonary disease (COPD), as typical chronic non-communicable diseases (NCDs), have increasingly become the major factors threatening the health of Chinese residents. In view of this, this study aimed to deeply analyse the key indicators and their interrelationships affecting the health status of the population, using the eight dietary balance criteria proposed in the newly revised Dietary Guidelines for Chinese Residents of the Chinese Society of Nutrition to screen and process the relevant health indicators. By constructing a comprehensive evaluation model and visualising the data, this study reveals the irrational factors in residents' dietary habits, such as high-fat diet and excessive alcohol consumption, which pose potential risks to residents' health. In addition, this paper explores the relationship between residents' dietary habits, exercise frequency and healthy body weight, aiming to provide a scientific basis and practical guidance for improving public health.

Protect the Children, Body and Soul

This paper critically examines American schooling systems, challenges their subtractive nature, and juxtaposes it with the culturally sustaining potential of education. We problematize the current tools for evaluating trauma and stress in young people of color and emphasize the need for a comprehensive understanding of indigenous medicines as a remedy. Drawing on interdisciplinary theories, we elucidate the pervasive and evolving nature of anti-blackness, reinforcing the sociohistorical structure of inequity within schools. As a response, this study presents a unique wellness survey (comprising two newly validated wellness scales) developed from a previous four-year longitudinal study investigating the relationship between culturally relevant teaching practices and improved health outcomes for children. We found a strong correlation between exposure to our culturally relevant intervention and several health indicators. Particularly, sustained telomere growth (protection of cells) was observed in over 90% of the participants in the intervention group, indicating a potential biological mechanism through which culturally informed interventions might contribute to improved health outcomes. We use these findings to argue that proactive measures centered on cultural and community contexts can serve as crucial protective factors, thereby potentially mitigating negative health outcomes related to racialized stress.

Prognostic and Health Management of Critical Aircraft Systems and Components: An Overview.

Prognostic and health management (PHM) plays a vital role in ensuring the safety and reliability of aircraft systems. The process entails the proactive surveillance and evaluation of the state and functional effectiveness of crucial subsystems. The principal aim of PHM is to predict the remaining useful life (RUL) of subsystems and proactively mitigate future breakdowns in order to minimize consequences. The achievement of this objective is helped by employing predictive modeling techniques and doing real-time data analysis. The incorporation of prognostic methodologies is of utmost importance in the execution of condition-based maintenance (CBM), a strategic approach that emphasizes the prioritization of repairing components that have experienced quantifiable damage. Multiple methodologies are employed to support the advancement of prognostics for aviation systems, encompassing physics-based modeling, data-driven techniques, and hybrid prognosis. These methodologies enable the prediction and mitigation of failures by identifying relevant health indicators. Despite the promising outcomes in the aviation sector pertaining to the implementation of PHM, there exists a deficiency in the research concerning the efficient integration of hybrid PHM applications. The primary aim of this paper is to provide a thorough analysis of the current state of research advancements in prognostics for aircraft systems, with a specific focus on prominent algorithms and their practical applications and challenges. The paper concludes by providing a detailed analysis of prospective directions for future research within the field.

A roadmap for using DHIS2 data to track progress in key health indicators in the Global South: experience from sub-saharan Africa

High quality health data as collected by health management information systems (HMIS) is an important building block of national health systems. District Health Information System 2 (DHIS2) software is an innovation in data management and monitoring for strengthening HMIS that has been widely implemented in low and middle-income countries in the last decade. However, analysts and decision-makers still face significant challenges in fully utilizing the capabilities of DHIS2 data to pursue national and international health agendas. We aimed to (i) identify the most relevant health indicators captured by DHIS2 for tracking progress towards the Sustainable Development goals in sub-Saharan African countries and (ii) present a clear roadmap for improving DHIS2 data quality and consistency, with a special focus on immediately actionable solutions. We identified that key indicators in child and maternal health (e.g. vaccine coverage, maternal deaths) are currently being tracked in the DHIS2 of most countries, while other indicators (e.g. HIV/AIDS) would benefit from streamlining the number of indicators collected and standardizing case definitions. Common data issues included unreliable denominators for calculation of incidence, differences in reporting among health facilities, and programmatic differences in data quality. We proposed solutions for many common data pitfalls at the analysis level, including standardized data cleaning pipelines, k-means clustering to identify high performing health facilities in terms of data quality, and imputation methods. While we focus on immediately actionable solutions for DHIS2 analysts, improvements at the point of data collection are the most rigorous. By investing in improving data quality and monitoring, countries can leverage the current global attention on health data to strengthen HMIS and progress towards national and international health priorities.

Management of health information of nepalese labour migrants

IntroductionThe monitoring and improvement of the health of labour migrants (LMs) require sufficient health data to be recorded and managed. In this context, this study was conducted to explore the management of health information of Nepalese labour migrants (NLMs).MethodsThis is an explorative qualitative study. Stakeholders involved directly or indirectly in maintaining the health profile of NLMs were first mapped, physically visited, and any documents or information were collected. Then, sixteen key informant interviews were conducted among these stakeholders related to labour migrants’ health information management and challenges. A checklist extracted information from the interviews, and a thematic analysis was carried out to summarize the challenges.ResultsGovernment agencies, non-governmental organizations, and government approved private medical centers are involved in generating and maintaining the health data of NLMs. The Foreign Employment Board (FEB) records deaths and disabilities of NLMs while at work abroad and these health records are also maintained in an online portal called Foreign Employment Information Management System (FEIMS) under the Department of Foreign Employment (DoFE). Health assessment of NLMs is a mandatory procedure before departure, which is done through the government-approved pre-departure private medical assessment centers. The health records from these assessment centers are first recorded in paper-based form and then entered into an online electronic form to be stored by the DoFE. The filled-up paper forms are sent to District Health Offices, which further report the data to the Department of Health Services (DoHS), Ministry of Health and Population (MoHP) and associated governmental infectious diseases centers. However, there is no formal health assessment of NLMs upon arrival to Nepal. Key informants raised various issues and concerns in maintaining health records of NLMs, which were grouped into three themes: lack of interest to develop a unified online system; need of competent human resources and equipment; and developing a set of health indicators for migrant health assessment.ConclusionThe FEB and government-approved private assessment centers are the main stakeholders in keeping the health records of outgoing NLMs. The current migrant health record keeping procedure in Nepal is fragmented. The national Health Information Management Systems does not effectively capture and categorize the health record of NLMs. There is a need to effectively link national health information system with premigration health assessment centers; and potentially develop a migrant health information management system by systematically keeping health records electronically with relevant health indicators on departing and arriving NLMs.

Effects of cannabis regulation in Switzerland: Study protocol of a randomized controlled trial.

Cannabis is the most widely used illicit substance. Various countries have legalized cannabis for recreational use. Evidence on the health effects of cannabis regulation remains unclear and is mainly based on observational studies. To date, there is no randomized controlled study evaluating the impact of cannabis regulation for recreational use compared to the illicit market on relevant health indicators. The present study ("Weed Care") is the first to evaluate the impact of regulated cannabis access in pharmacies versus a waiting list control group representing the illicit market on problematic cannabis use as well as on mental and physical health. The study is divided into two parts-a randomized controlled study of 6 months followed by an observational study of 2 years. Participants (N = 374) are randomly assigned to either the experimental group with access to legal cannabis in pharmacies or to the waiting list control group representing the current legal framework in Switzerland, namely the illicit market. After 6 months, all participants will have access to legal cannabis for the following 2 years (observational study). The primary outcome is problematic cannabis use as measured with the Cannabis Use Disorders Identification Test-Revised (CUDIT-R). Secondary outcomes are cannabis use patterns, mental disorders (e.g., depression, anxiety, and psychosis) and physical health (e.g., respiratory symptoms). Primary and secondary outcomes will be assessed online every 6 months. The study is approved by the responsible ethics committee as well as by the Swiss Federal Office of Public Health. Findings from this study may provide a scientific basis for future discussions about addiction medicine and cannabis policy in Switzerland. ClinicalTrials.gov (NCT05522205). https://clinicaltrials.gov/ct2/show/NCT05522205.

The Right to Urban Happiness and Indexes of Happy Cities

The purpose of the article is to show the importance of urban happiness as a right of social welfare and what are the indicators of international measures that countries must comply with. The research question is: How to achieve happier cities? To answer the question, from the inductive method, a bibliographic search will be made of the concept of urban happiness and of the most relevant health, education and governance indicators proposed since 1979 by the different countries and research centers. Similarly, a contemporary count of the countries with the best indicators of urban happiness and their reasons will be made. Finally, some exemplifying cases of countries with better inter-subjective happiness indexes will be given. The article concludes with the importance of developing countries for achieving more social economies, capable of integrating growth in production (Economic growth) with general welfare and the enjoyment of public values.

The Role of Model Personalization for Sleep Stage and Sleep Quality Recognition Using Wearables

Personal informatics systems can help people promote their health and well-being. Recent studies have shown that such systems can be used to infer relevant health indicators such as, e.g., stress, anxiety, and sleeping habits. While automatic detection of sleep has been studied extensively, there is a lack of studies exploring how population and personalized models influence the performance of sleep detection. In this article, we address this challenge by investigating the recognition of sleep/wake stages and high/low sleep quality with a focus on the impact of personalized models. To evaluate our approach, we collect a dataset of physiological signals and self-reports about sleep/wake times and sleep quality score. The dataset contains 6557 hours of sensor data collected using wristbands from 16 participants over one month. Our results show that personalized models perform significantly better than population models for sleep quality recognition, and are comparably good for sleep stage detection. The balanced accuracy for sleep/wake and high/low sleep quality are 92.2% and 61.51%, which are significantly higher than baseline classifiers.

A qualitative study to explore the acceptability and usefulness of personalized biofeedback to motivate physical activity in cancer survivors

ObjectiveMany cancer survivors do not meet recommended levels of exercise, despite the benefits physical activity offers. This study aimed to understand experiences of insufficiently active overweight/obese breast or colorectal cancer survivors, in efforts to (1) examine regular physical activity barriers, and (2) determine perceptions and acceptability of a remotely delivered physical activity intervention utilizing wearable sensors and personalized feedback messages.MethodsIn-person and virtual small group interviews were conducted engaging overweight/obese cancer survivors (n = 16, 94% female, 94% breast cancer survivors) in discussions resulting in 314 pages of transcribed data analyzed by multiple coders.ResultsAll participants expressed needing to increase physical activity, identifying lack of motivation centering on survivorship experiences and symptom management as the most salient barrier. They indicated familiarity with activity trackers (i.e., Fitbit) and expressed interest in biosensors (i.e., continuous glucose monitors [CGMs]) as CGMs show biological metrics in real-time. Participants reported (1) personalized feedback messages can improve motivation and accountability; (2) CGM acceptability is high given survivors’ medical history; and (3) glucose data is a relevant health indicator and they appreciated integrated messages (between Fitbit and CGM) in demonstrating how behaviors immediately affect one's body.ConclusionsThis study supports the use of wearable biosensors and m-health interventions to promote physical activity in cancer survivors. Glucose-based biofeedback provides relevant and motivating information for cancer survivors regarding their daily activity levels by demonstrating the immediate effects of physical activity. Integrating biofeedback into physical activity interventions could be an effective behavioral change strategy to promote a healthy lifestyle in cancer survivors.

Establishing a Mental Health Surveillance in Germany: Development of a framework concept and indicator set.

In the course of the recognition of mental health as an essential component of population health, the Robert Koch Institute has begun developing a Mental Health Surveillance (MHS) system for Germany. MHS aims to continuously report data for relevant mental health indicators, thus creating a basis for evidence-based planning and evaluation of public health measures. In order to develop a set of indicators for the adult population, potential indicators were identified through a systematic literature review and selected in a consensus process by international and national experts and stakeholders. The final set comprises 60 indicators which, together, represent a multidimensional public health framework for mental health across four fields of action. For the fifth field of action ‘Mental health promotion and prevention’ indicators still need to be developed. The methodology piloted proved to be practicable. Strengths and limitations will be discussed regarding the search and definition of indicators, the scope of the indicator set as well as the participatory decision-making process. Next steps in setting up the MHS will be the operationalisation of the single indicators and their extension to also cover children and adolescents. Given assured data availability, the MHS will contribute to broadening our knowledge on population mental health, supporting a targeted promotion of mental health and reducing the disease burden in persons with mental disorders.

Behavioral Monitoring Tool for Pig Farmers: Ear Tag Sensors, Machine Intelligence, and Technology Adoption Roadmap.

Simple SummaryIn a pig farm, it is challenging for the farm caretaker to monitor the health and well-being status of all animals in a continuous manner throughout the day. Automated tools are needed to remotely monitor all the pigs on the farm and provide early alerts to the farm caretaker for situations that need immediate attention. With this goal, we developed a sensor board that can be mounted on the ears of individual pigs to generate data on the animal’s activity, vocalization, and temperature. The generated data will be used to develop machine learning models to classify the behavioral traits associated with each animal over a testing period. A number of factors influencing the technology adoption by farm caretakers are also discussed.Precision swine production can benefit from autonomous, noninvasive, and affordable devices that conduct frequent checks on the well-being status of pigs. Here, we present a remote monitoring tool for the objective measurement of some behavioral indicators that may help in assessing the health and welfare status—namely, posture, gait, vocalization, and external temperature. The multiparameter electronic sensor board is characterized by laboratory measurements and by animal tests. Relevant behavioral health indicators are discussed for implementing machine learning algorithms and decision support tools to detect animal lameness, lethargy, pain, injury, and distress. The roadmap for technology adoption is also discussed, along with challenges and the path forward. The presented technology can potentially lead to efficient management of farm animals, targeted focus on sick animals, medical cost savings, and less use of antibiotics.

Staying Ahead of the Epidemiologic Curve: Evaluation of the British Columbia Asthma Prediction System (BCAPS) During the Unprecedented 2018 Wildfire Season.

Background: The modular British Columbia Asthma Prediction System (BCAPS) is designed to reduce information burden during wildfire smoke events by automatically gathering, integrating, generating, and visualizing data for public health users. The BCAPS framework comprises five flexible and geographically scalable modules: (1) historic data on fine particulate matter (PM2.5) concentrations; (2) historic data on relevant health indicator counts; (3) PM2.5 forecasts for the upcoming days; (4) a health forecasting model that uses the relationship between (1) and (2) to predict the impacts of (3); and (5) a reporting mechanism.Methods: The 2018 wildfire season was the most extreme in British Columbia history. Every morning BCAPS generated forecasts of salbutamol sulfate (e.g., Ventolin) inhaler dispensations for the upcoming days in 16 Health Service Delivery Areas (HSDAs) using random forest machine learning. These forecasts were compared with observations over a 63-day study period using different methods including the index of agreement (IOA), which ranges from 0 (no agreement) to 1 (perfect agreement). Some observations were compared with the same period in the milder wildfire season of 2016 for context.Results: The mean province-wide population-weighted PM2.5 concentration over the study period was 22.0 μg/m3, compared with 4.2 μg/m3 during the milder wildfire season of 2016. The PM2.5 forecasts underpredicted the severe smoke impacts, but the IOA was relatively strong with a population-weighted average of 0.85, ranging from 0.65 to 0.95 among the HSDAs. Inhaler dispensations increased by 30% over 2016 values. Forecasted dispensations were within 20% of the observed value in 71% of cases, and the IOA was strong with a population-weighted average of 0.95, ranging from 0.92 to 0.98. All measures of agreement were correlated with HSDA population, where BCAPS performance was better in the larger populations with more moderate smoke impacts. The accuracy of the health forecasts was partially dependent on the accuracy of the PM2.5 forecasts, but they were robust to over- and underpredictions of PM2.5 exposure.Conclusions: Daily reports from the BCAPS framework provided timely and reasonable insight into the population health impacts of predicted smoke exposures, though more work is necessary to improve the PM2.5 and health indicator forecasts.

Wearable Based Calibration of Contactless In-home Motion Sensors for Physical Activity Monitoring in Community-Dwelling Older Adults.

Passive infrared motion sensors are commonly used in telemonitoring applications to monitor older community-dwelling adults at risk. One possible use case is quantification of in-home physical activity, a key factor and potential digital biomarker for healthy and independent aging. A major disadvantage of passive infrared sensors is their lack of performance and comparability in physical activity quantification. In this work, we calibrate passive infrared motion sensors for in-home physical activity quantification with simultaneously acquired data from wearable accelerometers and use the data to find a suitable correlation between in-home and out-of-home physical activity. We use data from 20 community-dwelling older adults that were simultaneously provided with wireless passive infrared motion sensors in their homes, and a wearable accelerometer for at least 60 days. We applied multiple calibration algorithms and evaluated results based on several statistical and clinical metrics. We found that using even relatively small amounts of wearable based ground-truth data over 7–14 days, passive infrared based wireless sensor systems can be calibrated to give largely better estimates of older adults' daily physical activity. This increase in performance translates directly to stronger correlations of measured physical activity levels with a variety of age relevant health indicators and outcomes known to be associated with physical activity.

When everyone agrees: human rights norms on women and children and their effects on health

ABSTRACT What are the effects of international human rights norms? This paper links the creation of two human rights treaties, the Convention on the Elimination of All Forms of Discrimination Against Women (CEDAW) and the Convention on the Rights of the Child (CRC) to health indicators that signal whether well-being for women and children is improving. These two conventions are of particular interest because nearly all countries in the world are parties to both treaties, which attests to their strength as international norms. Using two new methodologies – ITSA and Joinpoint analysis, we show that both CRC and CEDAW have demonstrable and significant effects across a variety of relevant health indicators and have had effects in countries regardless of region, level of development, and regime type. Thus, our paper is one of the first to link the existence of norms with cross-national effects on the ground within countries not as rules to be enforced, but rules that have effects outside of courts or political offices that create changes for individual well-being beyond the treaties and law themselves.

No effects of pilot performance-based intervention implementation and withdrawal on the coverage of maternal and child health services in the Koulikoro region, Mali: an interrupted time series analysis.

Performance-based financing (PBF) has been promoted and increasingly implemented across low- and middle-income countries to increase the utilization and quality of primary health care. However, the evidence of the impact of PBF is mixed and varies substantially across settings. Thus, further rigorous investigation is needed to be able to draw broader conclusions about the effects of this health financing reform. We examined the effects of the implementation and subsequent withdrawal of the PBF pilot programme in the Koulikoro region of Mali on a range of relevant maternal and child health indicators targeted by the programme. We relied on a control interrupted time series design to examine the trend in maternal and child health service utilization rates prior to the PBF intervention, during its implementation and after its withdrawal in 26 intervention health centres. The results for these 26 intervention centres were compared with those for 95 control health centres, with an observation window that covered 27 quarters. Using a mixed-effects negative binomial model combined with a linear spline regression model and covariates adjustment, we found that neither the introduction nor the withdrawal of the pilot PBF programme bore a significant impact in the trend of maternal and child health service use indicators in the Koulikoro region of Mali. The absence of significant effects in the health facilities could be explained by the context, by the weaknesses in the intervention design and by the causal hypothesis and implementation. Further inquiry is required in order to provide policymakers and practitioners with vital information about the lack of effects detected by our quantitative analysis.

Life Satisfaction and mobility: Their associations with career attitudes, and health-related factors among postgraduates having studied in universities intra EU and outside EU

BackgroundUniversity postgraduates’ mobility towards, and outside the EU is continuously increasing, creating a competitive context in which maintaining a high life satisfaction (LS) is a public health challenge. However, the relationship between LS and its determinants among this population are under-documented. Our aims were to measure LS indicators of mobile postgraduates (Intra EU: Who pursue part of their studies in Europe; Outside EU: Who study outside of Europe) versus non-mobile (pursue their studies in Luxembourg), and to analyze the associations between LS and career attitudes, socioeconomic characteristics, and health-related factors for each group.MethodSix hundred and sixty-four (644) students obtained financial aid from the Luxembourgish government independent of their family’s socioeconomic situation. Contacted by post, they completed an online questionnaire. Analyses included a multiple linear regression model in which only significant relationships (p < 0.05) were used.ResultsThree groups were created: Mobile intra EU (n = 381), mobile outside EU (n = 43) and non-mobile (n = 66) postgraduates. Health satisfaction was positively linked to LS, in all groups. Among the mobile outside EU group, majority (63.2%) were men and 57.9% did not live alone - health was the only determinant which contributed to their LS. Among the mobile intra EU, majority (57.8%) were women, and 64.3% not living alone. Autonomy and career adaptability attitudes were positively associated with their LS (b: 0.210 and 0.119, respectively), whereas the worry factor was negatively (b: − 0.153 and -0.159) associated. The non-mobile, were the oldest of the three groups. Majority (51.6%) were women, and 93.7% did not live alone. Career optimism and planning attitudes were positively correlated to their LS (regression parameter estimates (b: 0.400 and 0.212, respectively).ConclusionsAttention should be devoted to the LS of local and cosmopolitan students, as it seems to be a relevant health indicator. Overall, the farther the mobility was, the higher the postgraduates’ general LS (8.5/10) was; this indicator was higher than the LS indicator for the age group 25–34 years 7.53/10 (EU-28, in 2013). University’ services could promote the development of career projects and the promotion of health to enhance postgraduates’ LS. University policy makers need to ensure this for all students.

Widening the lens to childhood: relevance and lifetime risk of kidney failure.

Lifetime risk of outcomes is emerging as a highly relevant health indicator, even in the context of low absolute risk of disease progression in short time frames. Evidence to support this concept for kidney failure is increasing, with growing emphasis on the long-term impact of risk factors occurring early in life. Proteinuria and stage of chronic kidney disease (CKD) are now established predictors of CKD progression in children, and youth with type 2 diabetes are emerging as a group at significant risk. Recent population-based studies have also examined the lifetime risk of end-stage renal disease in individuals with any childhood CKD. A recent study found that even in the absence of biomarkers of renal injury, childhood CKD can increase the lifetime risk of end-stage renal disease four-fold, and up to 10-fold in adults less than 40 years of age. Children with CKD are at high lifetime risk of kidney failure and require follow-up. Identifying children at highest lifetime risk through the use of biomarkers and risk equations, and determining the optimal duration and intensity of follow-up requires further research.

Iceland and development aid in the era of the MDGs: a case study of an Alma Ata inspired primary healthcare project in southern Malawi

ABSTRACTThe monitoring of relevant health indicators is important in the examination of work that aims to improve health, not only globally, as for example, through the Millennium Development Goals 2000–2015, but also at the national, regional and/or sectoral, level. During the period 2000–2011, the Icelandic International Development Agency (ICEIDA) supported the strengthening of the primary healthcare system in the Monkey Bay area of Mangochi District, Malawi. Based on data collected through several evaluative approaches and the use of commonly used health indicators, we explore the overall performance and constraints of the services provided by ICEIDA during project implementation. Structural and diverse process indicators provided evidence that access to governmental services improved during the project period. The population expressed satisfaction with the ongoing improvement of the healthcare services they felt were of good value and quality. During the MDG era, Malawi succeeded in decreasing the under-5 mortality rate by 2/3 (MDG4 target), and maternal mortality by 66% by implementing evidence based interventions similar to those ICEIDA supported in the Monkey Bay area. Albeit small, ICEIDA's support was a relevant, effective, and efficient approach to strengthen primary healthcare services in the Monkey Bay area, resulting in tangible and sustainable benefits for the Monkey Bay communities, that may also be applicable in other settings.