Cathy Michel

Improving health information systems for decision making across five sub-Saharan African countries: Implementation strategies from the African Health Initiative

BackgroundWeak health information systems (HIS) are a critical challenge to reaching the health-related Millennium Development Goals because health systems performance cannot be adequately assessed or monitored where HIS data are incomplete, inaccurate, or untimely. The Population Health Implementation and Training (PHIT) Partnerships were established in five sub-Saharan African countries (Ghana, Mozambique, Rwanda, Tanzania, and Zambia) to catalyze advances in strengthening district health systems. Interventions were tailored to the setting in which activities were planned.Comparisons across strategiesAll five PHIT Partnerships share a common feature in their goal of enhancing HIS and linking data with improved decision-making, specific strategies varied. Mozambique, Ghana, and Tanzania all focus on improving the quality and use of the existing Ministry of Health HIS, while the Zambia and Rwanda partnerships have introduced new information and communication technology systems or tools. All partnerships have adopted a flexible, iterative approach in designing and refining the development of new tools and approaches for HIS enhancement (such as routine data quality audits and automated troubleshooting), as well as improving decision making through timely feedback on health system performance (such as through summary data dashboards or routine data review meetings). The most striking differences between partnership approaches can be found in the level of emphasis of data collection (patient versus health facility), and consequently the level of decision making enhancement (community, facility, district, or provincial leadership).DiscussionDesign differences across PHIT Partnerships reflect differing theories of change, particularly regarding what information is needed, who will use the information to affect change, and how this change is expected to manifest. The iterative process of data use to monitor and assess the health system has been heavily communication dependent, with challenges due to poor feedback loops. Implementation to date has highlighted the importance of engaging frontline staff and managers in improving data collection and its use for informing system improvement. Through rigorous process and impact evaluation, the experience of the PHIT teams hope to contribute to the evidence base in the areas of HIS strengthening, linking HIS with decision making, and its impact on measures of health system outputs and impact.

Strengthening integrated primary health care in Sofala, Mozambique

BackgroundLarge increases in health sector investment and policies favoring upgrading and expanding the public sector health network have prioritized maternal and child health in Mozambique and, over the past decade, Mozambique has achieved substantial improvements in maternal and child health indicators. Over this same period, the government of Mozambique has continued to decentralize the management of public sector resources to the district level, including in the health sector, with the aim of bringing decision-making and resources closer to service beneficiaries. Weak district level management capacity has hindered the decentralization process, and building this capacity is an important link to ensure that resources translate to improved service delivery and further improvements in population health. A consortium of the Ministry of Health, Health Alliance International, Eduardo Mondlane University, and the University of Washington are implementing a health systems strengthening model in Sofala Province, central Mozambique.Description of implementationThe Mozambique Population Health Implementation and Training (PHIT) Partnership focuses on improving the quality of routine data and its use through appropriate tools to facilitate decision making by health system managers; strengthening management and planning capacity and funding district health plans; and building capacity for operations research to guide system-strengthening efforts. This seven-year effort covers all 13 districts and 146 health facilities in Sofala Province.Evaluation designA quasi-experimental controlled time-series design will be used to assess the overall impact of the partnership strategy on under-5 mortality by examining changes in mortality pre- and post-implementation in Sofala Province compared with neighboring Manica Province. The evaluation will compare a broad range of input, process, output, and outcome variables to strengthen the plausibility that the partnership strategy led to health system improvements and subsequent population health impact.DiscussionThe Mozambique PHIT Partnership expects to provide evidence on the effect of efforts to improve data quality coupled with the introduction of tools, training, and supervision to improve evidence-based decision making. This contribution to the knowledge base on what works to enhance health systems is highly replicable for rapid scale-up to other provinces in Mozambique, as well as other sub-Saharan African countries with limited resources and a commitment to comprehensive primary health care.

Stock-outs of essential health products in Mozambique-longitudinal analyses from 2011 to 2013

To assess the relationship between health system factors and facility‐level EHP stock‐outs in Mozambique.

Effects of a health information system data quality intervention on concordance in Mozambique: time-series analyses from 2009–2012

BackgroundWe assessed the effects of a three-year national-level, ministry-led health information system (HIS) data quality intervention and identified associated health facility factors.MethodsMonthly summary HIS data concordance between a gold standard data quality audit and routine HIS data was assessed in 26 health facilities in Sofala Province, Mozambique across four indicators (outpatient consults, institutional births, first antenatal care visits, and third dose of diphtheria, pertussis, and tetanus vaccination) and five levels of health system data aggregation (daily facility paper registers, monthly paper facility reports, monthly paper district reports, monthly electronic district reports, and monthly electronic provincial reports) through retrospective yearly audits conducted July-August 2010–2013. We used mixed-effects linear models to quantify changes in data quality over time and associated health system determinants.ResultsMedian concordance increased from 56.3% during the baseline period (2009–2010) to 87.5% during 2012–2013. Concordance improved by 1.0% (confidence interval [CI]: 0.60, 1.5) per month during the intervention period of 2010–2011 and 1.6% (CI: 0.89, 2.2) per month from 2011–2012. No significant improvements were observed from 2009–2010 (during baseline period) or 2012–2013. Facilities with more technical staff (aβ: 0.71; CI: 0.14, 1.3), more first antenatal care visits (aβ: 3.3; CI: 0.43, 6.2), and fewer clinic beds (aβ: -0.94; CI: −1.7, −0.20) showed more improvements. Compared to facilities with no stock-outs, facilities with five essential drugs stocked out had 51.7% (CI: −64.8 -38.6) lower data concordance.ConclusionsA data quality intervention was associated with significant improvements in health information system data concordance across public-sector health facilities in rural and urban Mozambique. Concordance was higher at those facilities with more human resources for health and was associated with fewer clinic-level stock-outs of essential medicines. Increased investments should be made in data audit and feedback activities alongside targeted efforts to improve HIS data in low- and middle-income countries.

Option B+ in Mozambique: Formative Research Findings for the Design of a Facility-Level Clustered Randomized Controlled Trial to Improve ART Retention in Antenatal Care.

Introduction:With the rollout of “Option B+” in Mozambique in 2013, initial data indicated major challenges to early retention in antiretroviral therapy (ART) among HIV-positive pregnant women. We sought to develop and test a pilot intervention in 6 large public clinics in central Mozambique to improve retention of mothers starting ART in antenatal care. The results from the formative research from this study described here were used to design the intervention. Methods:The research was initiated in early 2013 and completed in early 2014 in each of the 6 study clinics and consisted of (1) patient flow mapping and measurement of retention through collection of health systems data from antenatal care registries, pharmacy registries, ART clinic databases, (2) workforce assessment and measurement of patient waiting times, and (3) patient and worker individual interviews and focus groups. Results:Coverage of HIV testing and ART initiation were over 90% at all sites, but retention at 30-, 60-, and 90-day pharmacy refill visits was very low ranging from only 5% at 1 site to 30% returning at 90 days. These data revealed major systemic bottlenecks that contributed to poor adherence and retention in the first month after ART initiation. Long wait times, short consultations, and poor counseling were identified as barriers. Conclusions:Based on these findings, we designed an intervention with these components: (1) workflow modification to redefine nurse tasks, shift tasks to community health workers, and enhance patient tracking and (2) an adherence and retention package to systematize active patient follow-up, ensure home visits by community health workers, use text messaging, and intensify counseling by health staff. This intervention is currently under evaluation using a stepped wedge design.

Implementing rapid testing for tuberculosis in Mozambique

Abstract Problem In Mozambique, pulmonary tuberculosis is primarily diagnosed with sputum smear microscopy. However this method has low sensitivity, especially in people infected with human immunodeficiency virus (HIV). Patients are seldom tested for drug-resistant tuberculosis. Approach The national tuberculosis programme and Health Alliance International introduced rapid testing of smear-negative sputum samples. Samples were tested using a polymerase-chain-reaction-based assay that detects Mycobacterium tuberculosis deoxyribonucleic acid and a mutation indicating rifampicin resistance; Xpert® MTB/RIF (Xpert®). Four machines were deployed in four public hospitals along with a sputum transportation system to transfer samples from selected health centres. Laboratory technicians were trained to operate the machines and clinicians taught to interpret the results. Local setting In 2012, Mozambique had an estimated 140 000 new tuberculosis cases, only 34% of which were diagnosed and treated. Of tuberculosis patients, 58% are HIV-infected. Relevant changes From 2012–2013, 1558 people were newly diagnosed with tuberculosis using sputum smears at intervention sites. Xpert® detected M. tuberculosis in an additional 1081 sputum smear-negative individuals, an increase of 69%. Rifampicin resistance was detected in 58/1081 (5%) of the samples. However, treatment was started in only 82% of patients diagnosed by microscopy and 67% of patients diagnosed with the rapid test. Twelve of 16 Xpert® modules failed calibration within 15 months of implementation. Lessons learnt Using rapid tests to diagnose tuberculosis is promising but logistically challenging. More affordable and durable platforms are needed. All patients diagnosed with tuberculosis need to start and complete treatment, including those who have drug resistant strains.

Research capacity building integrated into PHIT projects: leveraging research and research funding to build national capacity

BackgroundInadequate research capacity impedes the development of evidence-based health programming in sub-Saharan Africa. However, funding for research capacity building (RCB) is often insufficient and restricted, limiting institutions’ ability to address current RCB needs. The Doris Duke Charitable Foundation’s African Health Initiative (AHI) funded Population Health Implementation and Training (PHIT) partnership projects in five African countries (Ghana, Mozambique, Rwanda, Tanzania and Zambia) to implement health systems strengthening initiatives inclusive of RCB.MethodsUsing Cooke’s framework for RCB, RCB activity leaders from each country reported on RCB priorities, activities, program metrics, ongoing challenges and solutions. These were synthesized by the authorship team, identifying common challenges and lessons learned.ResultsFor most countries, each of the RCB domains from Cooke’s framework was a high priority. In about half of the countries, domain specific activities happened prior to PHIT. During PHIT, specific RCB activities varied across countries. However, all five countries used AHI funding to improve research administrative support and infrastructure, implement research trainings and support mentorship activities and research dissemination. While outcomes data were not systematically collected, countries reported holding 54 research trainings, forming 56 mentor-mentee relationships, training 201 individuals and awarding 22 PhD and Masters-level scholarships. Over the 5 years, 116 manuscripts were developed. Of the 59 manuscripts published in peer-reviewed journals, 29 had national first authors and 18 had national senior authors. Trainees participated in 99 conferences and projects held 37 forums with policy makers to facilitate research translation into policy.ConclusionAll five PHIT projects strongly reported an increase in RCB activities and commended the Doris Duke Charitable Foundation for prioritizing RCB, funding RCB at adequate levels and time frames and for allowing flexibility in funding so that each project could implement activities according to their trainees’ needs. As a result, many common challenges for RCB, such as adequate resources and local and international institutional support, were not identified as major challenges for these projects. Overall recommendations are for funders to provide adequate and flexible funding for RCB activities and for institutions to offer a spectrum of RCB activities to enable continued growth, provide adequate mentorship for trainees and systematically monitor RCB activities.

Wait and consult times for primary healthcare services in central Mozambique: a time-motion study

Background We describe wait and consult times across public-sector clinics and identify health facility determinants of wait and consult times. Design We observed 8,102 patient arrivals and departures from clinical service areas across 12 public-sector clinics in Sofala and Manica Provinces between January and April 2011. Negative binomial generalized estimating equations were used to model associated health facility factors. Results Mean wait times (in minutes) were: 26.1 for reception; 43.5 for outpatient consults; 58.8 for antenatal visits; 16.2 for well-child visits; 8.0 for pharmacy; and 15.6 for laboratory. Mean consultation times (in minutes) were: 5.3 for outpatient consults; 9.4 for antenatal visits; and 2.3 for well-child visits. Over 70% (884/1,248) of patients arrived at the clinic to begin queuing for general reception prior to 10:30 am. Facilities with more institutional births had significantly longer wait times for general reception, antenatal visits, and well-child visits. Clinics in rural areas had especially shorter wait times for well-child visits. Outpatient consultations were significantly longer at the smallest health facilities, followed by rural hospitals, tertiary/quaternary facilities, compared with Type 1 rural health centers. Discussion The average outpatient consult in Central Mozambique lasts 5 min, following over 40 min of waiting, not including time to register at most clinics. Wait times for first antenatal visits are even longer at almost 1 h. Urgent investments in public-sector human resources for health alongside innovative operational research are needed to increase consult times, decrease wait times, and improve health system responsiveness.Background We describe wait and consult times across public-sector clinics and identify health facility determinants of wait and consult times. Design We observed 8,102 patient arrivals and departures from clinical service areas across 12 public-sector clinics in Sofala and Manica Provinces between January and April 2011. Negative binomial generalized estimating equations were used to model associated health facility factors. Results Mean wait times (in minutes) were: 26.1 for reception; 43.5 for outpatient consults; 58.8 for antenatal visits; 16.2 for well-child visits; 8.0 for pharmacy; and 15.6 for laboratory. Mean consultation times (in minutes) were: 5.3 for outpatient consults; 9.4 for antenatal visits; and 2.3 for well-child visits. Over 70% (884/1,248) of patients arrived at the clinic to begin queuing for general reception prior to 10:30 am. Facilities with more institutional births had significantly longer wait times for general reception, antenatal visits, and well-child visits. Clinics in rural areas had especially shorter wait times for well-child visits. Outpatient consultations were significantly longer at the smallest health facilities, followed by rural hospitals, tertiary/quaternary facilities, compared with Type 1 rural health centers. Discussion The average outpatient consult in Central Mozambique lasts 5 min, following over 40 min of waiting, not including time to register at most clinics. Wait times for first antenatal visits are even longer at almost 1 h. Urgent investments in public-sector human resources for health alongside innovative operational research are needed to increase consult times, decrease wait times, and improve health system responsiveness.

Improving data quality across 3 sub-Saharan African countries using the Consolidated Framework for Implementation Research (CFIR): results from the African Health Initiative

BackgroundHigh-quality data are critical to inform, monitor and manage health programs. Over the seven-year African Health Initiative of the Doris Duke Charitable Foundation, three of the five Population Health Implementation and Training (PHIT) partnership projects in Mozambique, Rwanda, and Zambia introduced strategies to improve the quality and evaluation of routinely-collected data at the primary health care level, and stimulate its use in evidence-based decision-making. Using the Consolidated Framework for Implementation Research (CFIR) as a guide, this paper: 1) describes and categorizes data quality assessment and improvement activities of the projects, and 2) identifies core intervention components and implementation strategy adaptations introduced to improve data quality in each setting.MethodsThe CFIR was adapted through a qualitative theme reduction process involving discussions with key informants from each project, who identified two domains and ten constructs most relevant to the study aim of describing and comparing each country’s data quality assessment approach and implementation process. Data were collected on each project’s data quality improvement strategies, activities implemented, and results via a semi-structured questionnaire with closed and open-ended items administered to health management information systems leads in each country, with complementary data abstraction from project reports.ResultsAcross the three projects, intervention components that aligned with user priorities and government systems were perceived to be relatively advantageous, and more readily adapted and adopted. Activities that both assessed and improved data quality (including data quality assessments, mentorship and supportive supervision, establishment and/or strengthening of electronic medical record systems), received higher ranking scores from respondents.ConclusionOur findings suggest that, at a minimum, successful data quality improvement efforts should include routine audits linked to ongoing, on-the-job mentoring at the point of service. This pairing of interventions engages health workers in data collection, cleaning, and analysis of real-world data, and thus provides important skills building with on-site mentoring. The effect of these core components is strengthened by performance review meetings that unify multiple health system levels (provincial, district, facility, and community) to assess data quality, highlight areas of weakness, and plan improvements.

Remote monitoring of Xpert® MTB/RIF testing in Mozambique: results of programmatic implementation of GxAlert.

SETTING Electronic diagnostic tests, such as the Xpert® MTB/RIF assay, are being implemented in low- and middle-income countries (LMICs). However, timely information from these tests available via remote monitoring is underutilized. The failure to transmit real-time, actionable data to key individuals such as clinicians, patients, and national monitoring and evaluation teams may negatively impact patient care. OBJECTIVE To describe recently developed applications that allow for real-time, remote monitoring of Xpert results, and initial implementation of one of these products in central Mozambique. DESIGN In partnership with the Mozambican National Tuberculosis Program, we compared three different remote monitoring tools for Xpert and selected one, GxAlert, to pilot and evaluate at five public health centers in Mozambique. RESULTS GxAlert software was successfully installed on all five Xpert computers, and test results are now uploaded daily via a USB internet modem to a secure online database. A password-protected web-based interface allows real-time analysis of test results, and 1200 positive tests for tuberculosis generated 8000 SMS result notifications to key individuals. CONCLUSION Remote monitoring of diagnostic platforms is feasible in LMICs. While promising, this effort needs to address issues around patient data ownership, confidentiality, interoperability, unique patient identifiers, and data security.