Electronic Health Management Information System Research Articles

The changes in health service utilisation in Malawi during the COVID-19 pandemic.

The COVID-19 pandemic and the restriction policies implemented by the Government of Malawi may have disrupted routine health service utilisation. We aimed to find evidence for such disruptions and quantify any changes by service type and level of health care. We extracted nationwide routine health service usage data for 2015-2021 from the electronic health information management systems in Malawi. Two datasets were prepared: unadjusted and adjusted; for the latter, unreported monthly data entries for a facility were filled in through systematic rules based on reported mean values of that facility or facility type and considering both reporting rates and comparability with published data. Using statistical descriptive methods, we first described the patterns of service utilisation in pre-pandemic years (2015-2019). We then tested for evidence of departures from this routine pattern, i.e., service volume delivered being below recent average by more than two standard deviations was viewed as a substantial reduction, and calculated the cumulative net differences of service volume during the pandemic period (2020-2021), in aggregate and within each specific facility. Evidence of disruptions were found: from April 2020 to December 2021, services delivered of several types were reduced across primary and secondary levels of care-including inpatient care (-20.03% less total interactions in that period compared to the recent average), immunisation (-17.61%), malnutrition treatment (-34.5%), accidents and emergency services (-16.03%), HIV (human immunodeficiency viruses) tests (-27.34%), antiretroviral therapy (ART) initiations for adults (-33.52%), and ART treatment for paediatrics (-41.32%). Reductions of service volume were greatest in the first wave of the pandemic during April-August 2020, and whereas some service types rebounded quickly (e.g., outpatient visits from -17.7% to +3.23%), many others persisted at lower level through 2021 (e.g., under-five malnutrition treatment from -15.24% to -42.23%). The total reduced service volume between April 2020 and December 2021 was 8 066 956 (-10.23%), equating to 444 units per 1000 persons. We have found substantial evidence for reductions in health service delivered in Malawi during the COVID-19 pandemic which may have potential health consequences, the effect of which should inform how decisions are taken in the future to maximise the resilience of healthcare system during similar events.

Uptake of reproductive, maternal and child health services during the first year of the COVID-19 pandemic in Uganda: A mixed methods study.

Use of reproductive health (RH), maternal, newborn and child health (MNCH) services in Uganda is suboptimal. Reasons for this are complex; however, service-delivery factors such as availability, quality, staffing, and supplies, contribute substantially to low uptake. The COVID-19 pandemic threatened to exacerbate existing challenges to delivery and use of high-quality RH and MNCH services. We conducted a mixed methods study, combining secondary analysis of routine electronic health management information system (eHMIS) data with exploratory key informant interviews (KII) to examine changes in health service uptake over the course of the pandemic and to understand service delivery adaptations implemented in response. We analyzed eHMIS data for four services (family planning, facility-based deliveries, antenatal visits, and immunization for children by one year), comparing them across four time periods: pre-COVID-19, partial lockdown, total lockdown and post lockdown. Additionally, KIIs were used to document adaptations made for continuity of health services. Use of services declined substantially during total lockdown; however, rebounded quickly to earlier observed levels, during the post lockdown for all four services, especially for immunization for children by one year. KIIs identified several health services delivery adaptations. At the community level, these included: community outreaches, training some mothers as community liaisons to encourage others to seek health services, and support from local leaders to create call centers to facilitate clients transport during travel restrictions. Health facilities creatively used space to accommodate social distancing and shifted providers' roles. District leadership reassigned health workers to facilities closest to their homes, provided vehicle passes to staff, and ambulances to transport pregnant women in critical need. WhatsApp groups facilitated communication at district level and enabled redistribution of supplies. Ministry of Health produced critical guidelines for continuity of health services. Implementing partners provided and redistributed commodities and personal protective equipment, and provided technical support, training and transport.

Sociotechnical factors of sustainable digital health systems: A system dynamics model

BackgroundThe introduction of digital health technology in a healthcare facility results in emergent and recursive interactions between new technology and existing social systems, technologies, and operating environments. ObjectivesThe study aims at developing a sociotechnical system dynamics model of digital health systems to assess the influence of sociotechnical factors on the sustainable use of an electronic Health Information Management System (eHMIS). MethodsA total of 40 face-to-face interviews in 18 healthcare facilities and two separate sessions of focus group discussions were conducted to study eHMIS implementation in Ethiopia. A system dynamics modelling of digital health systems implementation is developed, tested and verified with a case of eHMIS implementation in Ethiopia. ResultsThe long-term sustainability of the digital health system requires acceptance of technology, improved information quality to make appropriate decisions and better end-user satisfaction. The ‘individuals’ intention to use’ drives technology acceptance in the early years of the eHMIS use and social factors in the later stage. Besides, the role of technology to improve work performance determines the level of users’ satisfaction. The effort of improving ‘information quality’ is strongly influenced by the quality systems, i.e., reliable, easy to use, and capable to meet end-user requirements. ConclusionsThe system's acceptance was improved through effective training and communication, whereas the ‘information quality’ was enhanced through ‘system quality’ and users’ satisfaction. The ability of technology to improve work performance and reduce the burden on end-users has increased the satisfaction of end-users.

The quality of health data before and after the implementation of the electronic health management information system for the fistula program in Tanzania

AbstractThis study assessed the quality and challenges of health data before and after the implementation of the Hospital Information System (HIS) for the fistula program at the Comprehensive Community‐based Rehabilitation Hospital in Tanzania. This was a mixed methods study. Data were collected at baseline and end‐line (before and after the implementation of the HIS) study using quantitative Data Quality Assessment (DQA) checklists and individual interviews. At the baseline, the DQA checklists were assessed using files registered from 2017 to May 2019. At the end‐line, the DQA checklists used data for a patient registered at the established HIS from June 2019 to December 2020. Interviews with clinical and non‐clinical staff were conducted at both baseline and end‐line studies. The study found that data quality improved after the implementation of the HIS. At baseline, data completeness declined from 85% in 2017 to 44.9% in 2019 while accuracy declined from 44% in 2017 to 31% in 2019. At the end‐line, data completeness and accuracy were >80% and 100% annually respectively. Data preciseness increased from 0% at baseline to 100% at the end‐line. Both data completeness and accuracy had inconsistent tend over months, although preciseness could not be evaluated at baseline as no breakdown of indicators was reported. The major challenges related to data quality included language barrier, incompleteness of data, incorrect data entry, use of both manual and electronic systems, as well as unreliable electricity and network. In general, the HIS had improved rates of data quality in terms of completeness, accuracy, and preciseness of data as compared to the manual system. Policy‐makers and hospital administrators should ensure that the HIS are integrated into national hospital information systems, build staff capacity, ensure reliable sources of electrical power, and regular training on data collection.

Effects of Demographic Characteristics on the Electronic Health Management Information System (eHMIS) Functions in Tanzania

We assessed the use of Electronic Health Management Information – eHMIS – and the influence of demographic characteristics on the eHMIS functions. In particular, we explore changes in the usage of eHMIS among health workers. We also determined the effects of demographic characteristics on the usage of eHMIS and assessed any improvement in the ability to use eHMIS after its development. A mixed research design approach was adopted. The respondents were the clinical and non-clinical staff. Data was collected using interviews and questionnaires in three phases: baseline, midline, and final survey. The findings revealed an increase in the frequency of use of the eHMIS for entering and searching data entry from the midline to the final review. Apart from entering data, browsing, and retrieving previously recorded data, other eHMIS functions were not affected by demographic characteristics. On self-efficacy, there was an increase in health workers who felt comfortable using the system in the final survey compared to the baseline survey. In conclusion, enough training, user experience, and support from the management are very important in effective eHMIS implementation.

FAIR Equivalency with Regulatory Framework for Digital Health in Uganda

Abstract This study explores the possibility of opening a policy window for the adoption of the FAIR Guidelines— that data be Findable, Accessible, Interoperable, and Reusable (FAIR)—in Uganda's eHealth sector. Although the FAIR Guidelines were not mentioned in any of the policy documents relevant to Uganda's eHealth sector, the study found that 83% of the documents mentioned FAIR Equivalent efforts, such as the adoption of the National Identification Number (NIN) as a unique identifier in Uganda's national Electronic Health Management Information System (eHMIS) (findability), the planned/ongoing integration of various information systems (interoperability), and the alignment of various projects with international best practices/standards (reusability). A FAIR Equivalency Score (FE-Score), devised in this study as an aggregate score of the mention of the equivalent of FAIR facets in the policy documents, showed that the documents at the core of Uganda's digital health/eHealth policy have the highest score of all the documents analysed, indicating that there is a degree of alignment between Uganda's National eHealth Vision and the FAIR Guidelines. Therefore, it can be concluded that favourable conditions exist for the adoption and implementation of the FAIR Guidelines in Uganda's eHealth sector. Hence, it is recommended that the FAIR community adopt a capacity building strategy through organisations with a worldwide mandate, such as the World Health Organization, to promote the adoption of the FAIR Guidelines as part of international best practices.

MODELING DIABETES PATIENTS' ATTENDANCE AT BAGAMOYO DISTRICT HOSPITAL USING AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) MODELS.

This study presented the use of Autoregressive Integrated Moving Average (ARIMA) technique to modeling the diabetes patients' attendance at Bagamoyo district hospital using monthly time series data. The data used in the analysis of this study are monthly reading of diabetes patients data covered the period from January 2014 to December 2021. The data were retrieved from the hospital electronic health management information system. The Autoregressive Integrated Moving Average (ARIMA) approach was applied to the diabetes patients' data through the model identication, estimation, diagnostic checking, stationary and forecasting in R statistical software. The study identied Autoregressive Integrated Moving Average ARIMA (0, 1, 1) model to be the best one to t for the monthly total number of diabetes patients' attendance hospital outpatient department for seven years of monthly data. This was veried by Akaike's Information Criterion (AIC) and Bayesian Information Criterion (BIC) of the model selection criteria, Autoregressive Integrated Moving Average ARIMA (0, 1, 1) model shown the smallest values, hence this was selected as an adequate model to represent the Bagamoyo district hospital diabetes patients data. The forecast values indicate clearly that diabetes patients' attendance at Bagamoyo district hospital would be on an increase rate per month during the year 2022. Therefore, the government needs to put in place more and to engage necessary requirements for a satisfying healthcare system by increasing the medical supplies to the Bagamoyo district hospital.

Trends of Road Traffic Injury in Ethiopia, 2015 to 2017: National eHMI data analysis.

Background: Road traffic injury (RTI) is one of the leading causes of mortality and morbidity globally. It accounts for more than 1.35 million deaths per year. Low and middle-income countries are affected severely, thus, Ethiopia is among the most affected countries. This paper aims to analyze three years of Electronic Health Management Information System (eHMIS) surveillance data of Road traffic injuries in Ethiopia. Methods: eHMIS Road traffic injury data were reviewed for three years period ( 2015 to 2017) and Analysis was done by Microsoft Excel and SPSS. Result: The trend of injury in Ethiopia increased from 69882 to 100,628 from 2015 to 2017, which was more than a 30 % increase in three years, and inpatient death increased from 125 to 265. Males were affected more than females. Means of monthly reported injuries were computed for each year and one-way ANOVA was employed to test the difference of means of injuries, and all three means were significantly different with P < 0.05 at 95% CI. Linear regression was used to evaluate the trend per a year; the slope of the trend was estimated to be B = 22033, with 95% CI (17536 -26529), P< 0.05, which indicated a significant increase of the trend. Conclusion: This analysis revealed that in Ethiopia the burden of Road Traffic Injury (RTI) was increasing. Being male has a greater risk of RTI. High-level political commitment and actions are needed to halt the problem.

Direct financial assistance for improved maternal and child health data: a pilot study supporting the health management information system in Malawi

BackgroundThe health management information system (HMIS) is an integral component of a strong health care system. Despite its importance for decision-making, the quality of HMIS data remains of concern in low- and middle-income countries. To address challenges with the quality of maternal and child health (MCH) data gathered within Malawi’s HMIS, we conducted a pilot study evaluating different support modalities to district-level HMIS offices. We hypothesized that providing regular, direct financial assistance to HMIS offices would enable staff to establish strategies and priorities based on local context, resulting in more accurate, timely, and complete MCH data.MethodsThe pilot intervention was implemented in Mwanza district, while Chikwawa, Neno, and Ntchisi districts served as control sites given support received from other institutions. The intervention consisted of providing direct financial assistance to Mwanza’s HMIS office following the submission of detailed budgets and lists of planned activities. In the control districts, we performed interviews with the HMIS officers to track the HMIS-related activities. We evaluated the intervention by comparing data quality between the post- and pre-intervention periods in the intervention and control districts. Additionally, we conducted interviews with Mwanza’s HMIS office staff to determine the acceptability and appropriateness of the intervention.ResultsFollowing the 10-month intervention period, we observed improvements in MCH data quality in Mwanza. The availability and completeness of MCH data collected in the registers increased by 22 and 18 percentage points, respectively. The consistency of MCH data between summary reports and electronic HMIS also improved. In contrast, 2/3 control districts noted minimal changes or reductions in data quality after 10 months. The qualitative interviews confirmed that, despite some challenges, the intervention was well received by the participating HMIS office. HMIS staff preferred our strategy to other conventional strategies that fail to give them the independence to make decisions.ConclusionsThis pilot intervention demonstrated an alternative approach to support HMIS offices in their daily efforts to improve data quality. Given the Ministry of Health’s (MoH) interest in strengthening its HMIS, our intervention provides a strategy that the MoH and local and international partners could consider to rapidly improve HMIS data with minimal oversight.

Predictors of electronic health management information system for improving the quality of care for women and people with disabilities

The electronic Hospital management Information System (eHMIS) can improve care for vulnerable patients, help collect important disability and maternal health data, and improve the hospital’s overall data management. This study assessed the use of HMIS and factors influencing the usage and behavioral intentions to use the eHMIS at the Comprehensive Community Based Rehabilitation in Tanzania (CCBRT). We investigated both clinical and non-clinical staff (n=69) using tablets and online surveys, with a rate of return of 71.9%. The ICT staff were also interviewed to supplement data from the survey. The survey questionnaire was guided by the updated Information System Success (ISS) model. Most health workers (81.2%) used the eHMIS several times a day to support different decision-making activities. The better educated personnel were more likely to enter data more effectively into eHMIS as compared to their counterparts. Among six predictors, self-efficacy positively influenced self-reported use and user satisfaction of HMIS, while service quality negatively affected self-reported use of eHMIS. The system quality positively influenced health workers to be satisfied with the eHMIS, and user satisfaction positively influenced continued usage intention of the eHMIS. Both user satisfaction and continued usage intention were positively related to individual impact of eHMIS. Individual impact had positive effects on organizational impact of eHMIS. This is a comprehensive study conducted in Tanzania regarding the implementation of eHMIS, and factors influencing post-adoptive use of HMIS to improve quality of care of women and people with disabilities.

Screening and linkage to care for hepatitis C among inpatients in Georgia's national hospital screening program

The country of Georgia initiated an ambitious national hepatitis C elimination program. To facilitate elimination, a national hospital hepatitis C screening program was launched in November 2016, offering all inpatients screening for HCV infection. This analysis assesses the effectiveness of the first year of the screening program to identify HCV-infected persons and link them to care. Data from Georgia's electronic Health Management Information System and ELIMINATION-C treatment database were analyzed for patients aged ≥18 years hospitalized from November 1, 2016 to October 31, 2017. We described patient characteristics and screening results and compared linked-to-care patients to those not linked to care, defined as having a test for viremia following an HCV antibody (anti-HCV) positive hospital screening. Of 291,975 adult inpatients, 252,848 (86.6%) were screened. Of them, 4.9% tested positive, with a high of 17.4% among males aged 40–49. Overall, 19.8% of anti-HCV+ patients were linked to care, which differed by sex (20.6% for males vs. 18.4% for females; p = .019), age (23.9% for age 50–59 years vs. 10.7% for age ≥ 70 years; p < .0001), and length of hospitalization (21.8% among patients hospitalized for 1 day vs. 16.1% for those hospitalized 11+ days; p = .023). Redundant screening is a challenge; 15.6% of patients were screened multiple times and 27.6% of anti-HCV+ patients had a prior viremia test. This evaluation demonstrates that hospital-based screening programs can identify large numbers of anti-HCV+ persons, supporting hepatitis C elimination. However, low linkage-to-care rates underscore the need for screening programs to be coupled with effective linkage strategies.

SAT-131 EVALUATION OF RENAL DATA QUALITY: A PREPARATORY STEP FOR A RENAL REGISTRY IN AN ISN/SRC CENTER, IN PORT HARCOURT, NIGERIA

The impact of renal registries that promote service planning, disease management, quality improvement, and research is dependent on the quality of baseline data. Inadequate baseline data collection tools and the low utilization of electronic Health Information Management Systems (eHIMs) are key challenges to the development of renal registries in Africa as stated by the African Regional Association of Nephrology (AFRAN). This state of affairs prompted the baseline assessment of renal data quality and the development of a structured data collection tool as a prerequisite for the commencement of a community-level primary care renal service and the establishment of the local renal registry at an ISN/SRC center, at the University Port Harcourt Teaching Hospital, Nigeria, Patients' data were extracted from physical records for the period 2015 to 2018 and entered on renal registry template based on a modified WHO Steps instrument proposed by the South Africa Medical Research Council. CKD Africa Collaboration. The tool had 10 domains of Demographic and general information (DGI), Behavioural measurements (BM), Cardiovascular risk, CKD Risk and Past medical history (CVCKRisk), Physical measurements (Anthropometric and metabolic) (PM), Measures of kidney function (MKF), Measures of chronic kidney disease impact (CKDI), Renal Imaging (RI), CKD Course and outcome (CKDCO), Renal Histology (RH) and Renal Replacement Therapy (RRT) with a total of 67 items. Three domains and 20 items were excluded in the analysis which focused on the data quality dimension of completeness. There were 1099 patient entries, with an overall data completeness range of 14.16 – 99.42%. The range and mean of data completeness in percentages (%) for 7 domains were DGI: 76.50 – 99.42, 87.92±13.18, BM: 95.18 - 96.79, 96.01±0.81, CVCKRisk: 16.93 - 93.43, 81.26±24.78, PM: 35.62 -94.74, 76.94±24.02, MKF: 31.97 - 77.52, 54.33 ±23.66, CKDI: 14.16 - 77.52, 48.06 ±24.93, RI: 33.58 - 38.98, 36.5840 ±2.66 respectively. There were significant differences in the mean completeness within and across the domains. The BM Domains had the highest mean completion rate of 96.01±0.81%, while the highest item completion rate of 99.42% and 99.27% was attained in demographic information items such as gender and age respectively. The lowest rates of 31.97%, 14.16% and 33.58% respectively were recorded in MKF, CKDI and RI items such as urine albumin, mineral bone disease parameters, and renal imaging measurements. There are significant gaps in data completeness with the current data tools used in the facility. The poor data quality limits the integrative capacity of the renal data from this center to other sub-regional and national registries. The lack of a structured data tool also limits the implementation of standardized community based renal care service. In response to this assessment, a structured data collection and patient assessment tool were developed to improve data quality and make the establishment of a local registry achievable. It is advocated that the assessment of facility data quality and the development of structured data tools are important perquisites in promoting standardized community based renal care, renal data quality, and successful registry development in technologically challenged environments.

A Model for an Electronic Health Information Management System with Structural Interoperability in Heterogeneous Environments for continued Health Care

Electronic Health Records (EHR) Systems have over the recent years become an integral part of any effective Health Care System. Volumes of data is kept in heterogeneous systems and though continued health care highly depends on knowledge acquired from medical history captured at various points, this information is usually not readily available. This is caused by lack of interoperability and use of standards. Usually, interoperability has been targeted at health systems communicating amongst themselves and not with other supporting systems such as administrative systems that may be directly affected by healthcare systems or may themselves affect healthcare systems.&#x0D; The University of Zambia (UNZA) Clinic EHR does not interoperate with administrative systems systems. This study proposes a model to improve the efficiency of healthcare at UNZA Clinic by introducing an EHR system that applies interoperability with the University’s Human Resource and Student Information Systems at as less a cost a possible. The study was guided by two (2) objectives. A baseline study was conducted to evaluate the performance of the currently implemented modules of the Electronic System at UNZA Clinic to address objective number (1). 200 questionnaires were distributed during clinic visits with 150 of them being used to collect data from within University community. Of these, 50 were given to members of staff that benefit from the health services, 75 to students and 50 to the healthcare providers. The remaining 25 questionnaires were shared amongst staff dependents and the community outside the University.&#x0D; Our results show that there is potential to improve on patient delay time. Many respondents suggested that automating the processes and securely sharing electronic records amongst the offices that attend to them would better the service. A model has been proposed to address objective 2 for the design of a prototype that adheres to HL7 EHR Standards. In order to achieve an interoperable eHealth Records System, we have investigated and proposed a Web Service architecture.

Quality assurance of health management information system in Kayunga district, Uganda

Background: An efficient health management information system (HMIS) improves health care delivery and outcomes. However, in most rural settings in Uganda, paper-based HMIS are widely used to monitor public health care services. Moreover, there are limited capabilities and capacity for quality HMIS in remote settings such as Kayunga district.Objectives: The quality assurance practices of HMIS in health centres (HCs) in Kayunga district were evaluated.Method: A cross-sectional descriptive study design was used to assess the quality of HMIS at 21 HCs in Kayunga district. Data were collected through in-depth interviews of HMIS focal persons as well as document analysis of HMIS records and guidelines between 15 June 2010 and 15 July 2010. The main outcomes were quality assurance practices, the HMIS programmatic challenges and opportunities. The practice of HMIS was assessed against a scale for good quality assurance practices. Qualitative data were coded and thematically analysed, whereas quantitative data were analysed by descriptive statistics using SPSS v22 software.Results: All the 21 HCs had manual paper-based HMIS. Less than 25% of HCs practised quality assurance measures during collection, compilation, analysis and dissemination of HMIS data. More than 50% of HCs were not practising any type of quality assurance during analysis and dissemination of data. The main challenges of the HMIS were the laborious and tedious manual system, the difficulty to archive and retrieve records, insufficient HMIS forms and difficulty in delivering hard copies of reports to relevant stakeholders influenced quality of data. Human resource challenges included understaffing where 43% of participating HCs did not have a designated HMIS staff.Conclusion: The HMIS quality assurance practices in Kayunga were suboptimal. Training and support supervision of HMIS focal persons is required to strengthen quality assurance of HMIS. Implementation of electronic HMIS dashboards with data quality checks should be integrated alongside the manual system.

Sensitivity and positive predictive value of the measles surveillance system in Uganda, 2012-2015

Introduction : disease surveillance is a critical component in the control and elimination of vaccine preventable diseases. The Uganda National Expanded Program on Immunization strives to have a sensitive surveillance system within the Integrated Disease Surveillance and Response (IDSR) framework. We analyzed measles surveillance data to determine the effectiveness of the measles case-based surveillance system and estimate its positive predictive value in order to inform policy and practice. Methods : an IDSR alert was defined as 1 suspected measles case reported by a district in a week, through the electronic Health Management Information System. We defined an alert in the measles case-based surveillance system (CBS) as 1 suspected measles case with a blood sample collected for confirmation during the corresponding week in a particular district. Effectiveness of CBS was defined as having 80% of IDSR alerts with a blood sample collected for laboratory confirmation. Positive predictive value was defined as the proportion of measles case-patients who also had a positive measles serological result (IgM +). We reviewed case-based surveillance data with laboratory confirmation and measles surveillance data from the electronic Health Management Information System from 2012-2015. Results : a total of 6,974 suspected measles case-persons were investigated by the measles case-based surveillance between 2012 and 2015. Of these, 943 (14%) were measles specific IgM positive. The median age of measles case-persons between 2013 and 2015 was 4.0 years. Between 2013 and 2015, 72% of the IDSR alerts reported in the electronic Health Management Information System, had blood samples collected for laboratory confirmation. This was however less than the WHO recommended standard of 80%. The PPV of CBS between 2013 and 2015 was 8.6%. Conclusion : effectiveness of measles case-based surveillance was sub-optimal, while the PPV showed that true measles cases have significantly reduced in Uganda. We recommended strengthening of case-based surveillance to ensure that all suspected measles cases have blood samples collected for laboratory confirmation to improve detection and ensure elimination by 2020.

The functionality status and challenges of electronic health management information system: The case of public health centres in Amhara Region, Ethiopia

Background: Although electronic health management information systems (eHMIS) have been applied in the Ethiopian healthcare system since 2006, the functionality status and challenges are not assess...

Positive predictive value and effectiveness of measles case-based surveillance in Uganda, 2012-2015.

IntroductionDisease surveillance is a critical component in the control and elimination of vaccine preventable diseases. The Uganda National Expanded Program on Immunization strives to have a sensitive surveillance system within the Integrated Disease Surveillance and Response (IDSR) framework. We analyzed measles surveillance data to determine the effectiveness of the measles case-based surveillance system and estimate its positive predictive value in order to inform policy and practice.MethodsAn IDSR alert was defined as ≥1 suspected measles case reported by a district in a week, through the electronic Health Management Information System. We defined an alert in the measles case-based surveillance system (CBS) as ≥1 suspected measles case with a blood sample collected for confirmation during the corresponding week in a particular district. Effectiveness of CBS was defined as having ≥80% of IDSR alerts with a blood sample collected for laboratory confirmation. Positive predictive value was defined as the proportion of measles case-patients who also had a positive measles serological result (IgM +). We reviewed case-based surveillance data with laboratory confirmation and measles surveillance data from the electronic Health Management Information System from 2012–2015.ResultsA total of 6,974 suspected measles case-persons were investigated by the measles case-based surveillance between 2012 and 2015. Of these, 943 (14%) were measles specific IgM positive. The median age of measles case-persons between 2013 and 2015 was 4.0 years. Between 2013 and 2015, 72% of the IDSR alerts reported in the electronic Health Management Information System, had blood samples collected for laboratory confirmation. This was however less than the WHO recommended standard of ≥80%. The PPV of CBS between 2013 and 2015 was 8.6%.ConclusionIn conclusion, the effectiveness of measles case-based surveillance was sub-optimal, while the PPV showed that true measles cases have significantly reduced in Uganda. We recommended strengthening of case-based surveillance to ensure that all suspected measles cases have blood samples collected for laboratory confirmation to improve detection and ensure elimination by 2020.

Impact of a district-wide health center strengthening intervention on healthcare utilization in rural Rwanda: Use of interrupted time series analysis

BackgroundEvaluations of health systems strengthening (HSS) interventions using observational data are rarely used for causal inference due to limited data availability. Routinely collected national data allow use of quasi-experimental designs such as interrupted time series (ITS). Rwanda has invested in a robust electronic health management information system (HMIS) that captures monthly healthcare utilization data. We used ITS to evaluate impact of an HSS intervention to improve primary health care facility readiness on health service utilization in two rural districts of Rwanda.MethodsWe used controlled ITS analysis to compare changes in healthcare utilization at health centers (HC) that received the intervention (n = 13) to propensity score matched non-intervention health centers in Rwanda (n = 86) from January 2008 to December 2012. HC support included infrastructure renovation, salary support, medical equipment, referral network strengthening, and clinical training. Baseline quarterly mean outpatient visit rates and population density were used to model propensity scores. The intervention began in May 2010 and was implemented over a twelve-month period. We used monthly healthcare utilization data from the national Rwandan HMIS to study changes in the (1) number of facility deliveries per 10,000 women, (2) number of referrals for high risk pregnancy per 100,000 women, and (3) the number of outpatient visits performed per 1,000 catchment population.ResultsPHIT HC experienced significantly higher monthly delivery rates post-HSS during the April-June season than comparison (3.19/10,000, 95% CI: [0.27, 6.10]). In 2010, this represented a 13% relative increase, and in 2011, this represented a 23% relative increase. The post-HSS change in monthly rate of high-risk pregnancies referred increased slightly in intervention compared to control HC (0.03/10,000, 95% CI: [-0.007, 0.06]). There was a small immediate post-HSS increase in outpatient visit rates in intervention compared to control HC (6.64/1,000, 95% CI: [-13.52, 26.81]).ConclusionWe failed to find strong evidence of post-HSS increases in outpatient visit rates or referral rates at health centers, which could be explained by small sample size and high baseline nation-wide health service coverage. However, our findings demonstrate that high quality routinely collected health facility data combined with ITS can be used for rigorous policy evaluation in resource-limited settings.

Arranging blood for elective thyroid surgeries: dilemma continues in the developing world

BackgroundCross matched blood is frequently ordered based on a subjective anticipation of blood loss for a procedure. Excessive blood arrangement and wastage overburdens the blood bank in terms of work load and storage of blood, increases cost of medical care and results in injudicious use of a limited resource. The aim of this short report is to assess the current practice for arranging cross matched blood in elective thyroid surgeries by comparing cross match to blood transfused ratio.FindingsMedical records for all patients from January 2009 to December 2014 undergoing thyroid surgery were retrieved and reviewed through electronic health information management system (HIMS). A total of 91 patients were included in the study, out of which 18 (19.7%) were male and 73 (80.2%) were female. A total of 107 units of blood were arranged and only 9 were transfused. 47 patients underwent a total thyroidectomy, while 44 underwent a hemithyroidectomy. The cross match to transfusion ratio came out to be 11.88.ConclusionsRoutine arrangement of cross matched blood is not required in elective thyroid surgeries. All institutions should have a maximum blood ordering schedule planned for elective procedures, and blood products should be arranged accordingly to avoid unnecessary cross matching.

Some correlates of electronic health information management system success in nigerian teaching hospitals.

Nowadays, an electronic health information management system (EHIMS) is crucial for patient care in hospitals. This paper explores the aspects and elements that contribute to the success of EHIMS in Nigerian teaching hospitals. The study adopted a survey research design. The population of study comprised 442 health information management personnel in five teaching hospitals that had implemented EHIMS in Nigeria. A self-developed questionnaire was used as an instrument for data collection. The findings revealed that there is a positive, close relationship between all the identified factors and EHIMS’s success: technical factors (r = 0.564, P < 0.05); social factors (r = 0.616, P < 0.05); organizational factors (r = 0.621, P < 0.05); financial factors (r = 0.705, P < 0.05); and political factors (r = 0.589, P < 0.05). We conclude that consideration of all the identified factors was highly significant for the success of EHIMS in Nigerian teaching hospitals.