Clinical trial NCT05310682: Data-Informed Platform for Health (DIPH)
Official title: Data-Informed Platform for Health (DIPH)
Study type: INTERVENTIONAL
Overall status: UNKNOWN
Phase: NA
Conditions: Behavior
Keywords: Health Information Systems
Organizational Decision Making
District level health administration
Data use
Health System Research
District level
Lead sponsor: London School of Hygiene and Tropical Medicine
Sponsor class: OTHER
Collaborators: name: Ethiopian Public Health Institute
First posted: 2022-04-05
Enrollment: 24
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: HEALTH_SERVICES_RESEARCH

Brief summary: The overall aim of the Data-Informed Platform for Health (DIPH) is to improve Maternal, Newborn and Child Health (MNCH) programmes and services at the district level. The DIPH strategy does this by bringing together data on inputs and processes to promote the use of local data for decision-making, priority-setting, and planning by introducing a structured decision-making process at the district level.

The DIPH is embedded in the existing district decision-making forum- e.g., performance review teams meetings - adding a structured coordination process between different departments and formal data-sharing for evidence-based decision-making, planning, and resource allocation according to local health priorities. Conceptually, the DIPH strategy uses a structured set of processes involving five pre-defined steps and standardised job-aids corresponding to each step to facilitate linking data from health and associated departments and stakeholders. A typical DIPH cycle has five steps around a health theme, which take about four months to complete. Technical assistance is provided by the district stakeholders' induction, orientation, and handholding during the implementation of the initial cycles.

The DIPH job-aids - a set of standardised job-aids (paper forms or web-based interface) - are designed to help organise and interpret data from multiple sectors involved in delivering services around the chosen theme using a common data-sharing platform. They are aimed at district leadership and management teams systematically using, inputting and processing data for decision-making, planning and progress monitoring of the theme.

In Ethiopia, the DIPH intervention research will be employed for four cycles in the North Shoa zone (12 intervention and 12 comparison districts), coupled with process evaluation to understand and improve ongoing implementation issues. In addition, for the impact evaluation of DIPH implementation, a before-and-after comparison of the study outcomes between intervention and comparison study arms will be carried out via district health administration surveys.

This study is a collaboration between the Ethiopian Public Health Institute (EPHI) and the London School of Hygiene and Tropical Medicine (LSHTM).

Detailed description: The overall purpose of the Data-Informed Platform for Health - or DIPH - is to improve MNCH programmes and services through data-driven decision-making at the district level. It is a strategy for strengthening health systems. The DIPH does this by bringing together various stakeholders into a single platform and facilitating their understanding and use of key district-level data.

Our focus is MNCH, although the DIPH concept has broad applicability. The primary objectives of the DIPH are to promote the use of local data from programmatic activities for 1) decision-making, priority-setting and planning at the district health administration level; and 2) appraisal of health services and programmes. The DIPH approach will regularly bring governmental and non-governmental service providers to a common forum to share data according to an agreed plan and use the resulting information as a tool in priority-setting for resource allocation and needs assessment for further acquiring funds.

A district is considered an operating unit for the DIPH based on the assumption that this is the lowest administrative level of decision-making in a health system in Ethiopia. The DIPH concept has its roots in the 'District Evaluation Platform approach.' The DIPH does not try to reinvent the wheel - it is embedded in decision-making procedures that already exist at the district level. DIPH adds a structured coordination process between the government and private stakeholders of formal data-sharing for evidence-based decision-making, planning and resource allocation. Moreover, the DIPH is conducted in accordance with local health priorities.

The DIPH is delivered as a package of job aids and guidelines. Structurally, the box is made up of three main elements: Firstly, it involves the grouping of stakeholders who are brought together to deliberate on issues in a virtual platform facilitated by regular meetings. The membership of this virtual platform is flexible and responds to the needs of the problems in focus. Secondly, the DIPH package facilitates these stakeholder meetings in five steps: Assessment, Engagement, Definition, Planning and Follow-up. These five steps together makeup one whole cycle of the DIPH and, in practice, take 3-4 months to complete. Each cycle looks at a specific health theme, identified in the early stages of the cycle itself. Thirdly, the DIPH package also includes a digital interface where everyone involved in the process can regularly review data and check on progress.

Overall aim:

To enhance interaction among district-level health personnel and linkage of databases to improve coordinated decision-making and planning by strengthening health systems through capacity-building and effective use of data for decision-making.

Specific research objectives:

1. To systematically strengthen the district health system using the DIPH strategy by developing a coordinated decision-making and planning through the Data-Informed Platformfor Health strategy
2. To evaluate the effectiveness of embedding the Data-Informed Platform for Health within the district health system with respect to improvement in district health performance in terms of data management and data-driven decision-making as compared to Non-DIPH districts.

This is a health system intervention to adapt, implement and evaluate the DIPH approach in Ethiopia, in close collaboration with national and local institutions, and engage key government stakeholders.

Study Design: a randomised controlled study design will employ pre and post-comparisons to establish the effectiveness of DIPH intervention. A district will be considered as a study implementation unit and equal number will be allocated for the presence and absence of intervention arm.

Study area: the study will be implemented in North Shewa, one of the administrative zones in the Amhara region. The study will be conducted in all 24 districts of the Zone by allocating 12 of them in intervention and 12 in non-intervention arms. To reduce subjective allocation, matching will be done based on the district performance level based on HMIS indicators and distance.

The development phase has been successfully completed with formative research, field observations, consultative meetings with district administrations, co-creation workshops with the federal health ministry, and adaptation of the DIPH package according to the Ethiopian district health system.

Implementation phase: four-monthly cycles of DIPH each will be conducted in the 12ditricts of the North Shewa zone over the 16 months. Which will form the basis of formal evaluation of DIPH intervention (An additional 1 four-monthly cycle -Transition cycle -will be conducted to implement and evaluate exit strategy of the DIPH intervention)

Embedding: The Performance Review Team meetings of the district health administration, which is entrusted with integrating planning and facilitating data-driven and collaborative decision-making, will be used as a platform to introduce the DIPH. Activities will focus primarily on:

1. Strengthening the Performance Review Team forum for the engagement of all government and non-governmental stakeholders to identify challenges and solutions and assess resource allocation and responsibilities. These meetings will be convened to achieve consensus-building and collective decision-making to improve health systems and services in their areas.
2. Promoting the critical review and regular use of local data to understand health-system progress at the district level.

Training: Before initiating the first DIPH cycle, the district health management staff of DIPH districts will be provided with three days' intensive residential training based on the specifically-designed DIPH training handbook in their zonal city. The overall aim of this curriculum, which is the basis of a training handbook, is to provide tools and knowledge for improved decision-making at the district level, utilising available data. Its target audience is district health officers in administrative and managerial roles within health systems. The first half of the course will cover the four core skills of decision-making, stakeholder engagement, data-use, and monitoring health-system performance. Next, participants will be provided with an overview of district-level organisational structure, followed by an introduction to DIPH, steps in the DIPH cycle, primary and supplementary forms, roles and responsibilities, DIPH meetings, and, finally,, how to use the DIPH interface.

On average, the research team will train five to six staff members per district. Along with the district's health department head, programme officers and an HMIS focal person, experts from the zonal health department will be included in the training. The DIPH research investigators team will conduct the three-day residential training.

Overall, the field team will comprise one DIPH regional coordinator, four DIPH support supervisors and one data manager. Each support supervisor will be assigned three districts to provide overall technical support in implementing the DIPH strategy. This will consist of inducting, orientating and handholding district stakeholders during the implementation of the initial cycles, participating in districts' monthly performance-review meetings, and monitoring collected data. Data collection will be performed on tablets using appropriate software for electronic data collection. Data collected from the field will be sent to EPHI's server daily through the Internet File Streaming System, a technology for transferring data already installed at EPHI.

EVALUATION:

B. Process evaluation will be carried out to understand and address on-going implementation issues and will specially address the following questions:

To what extent is health data used for problem-solving and delivering health services in each DIPH cycle? What is the level of engagement of various health stakeholders? What are the key mechanisms for data-sharing and consensus-building among the range of health-service stakeholders at the district level? What are the facilitators of, and barriers to, sustaining the DIPH strategy?

Data will be collected on semi-structured forms for in-depth interviews by DIPH support supervisors for each cycle throughout the implementation of DIPH. Synthesised findings will be presented periodically to respective district staff so that learning can be used to improve the following DIPH cycle. Post-intervention, end of cycle four, in-depth interviews will be also be conducted with the health administration of 4 selected comparison districts to assess any comparable changes that happened in the decision making and data use culture in the control districts over time.

A. Before-and-after comparison of health-system outcomes employed difference-in-differences estimates in intervention- and comparison-district surveys to assess changes resulting from DIPH implementation, in terms of changes in health information system performance and governance of data-driven decision-making at the district level

Study participants: The survey respondents will be the head of the health department, all programme officers and data managers at the district level. All eligible district staff will be interviewed, except those working in their respective districts for less than six months. IT is anticipated that on average 6 -7 eligible staff would be available in each district and all of them will be included in the study.

The sample size estimations for the required number of districts required per study arm is based on the statistical formula recommended by Hayes et al i.e a minimum sample size of 72 health management staff per study arm (144 in total) would have 80% power to detect a difference of at least 25 percentage points as statistically significant.

Data-collection: After a detailed pilot testing, baseline survey data-collection will be carried out by DIPH field teams. For end-line survey data-collection, an independent team of four data-collectors and one supervisor will be recruited from the zone for one month. Data-collectors will be recruited by EPHI and will, as a minimum, have a Master's degree. Their classroom training on the survey instruments will be followed by a written assessment on the survey contents. Data collectors will be provided with a field manual for reference during fieldwork. Job descriptions - with the roles and responsibilities of each team member and expected day-to-day deliverables - will be provided. The survey will be piloted to test survey procedures and tools, and a detailed standard operating-procedures document for the survey will be provided to the data-collection team.

Data Analysis: For quantitative analysis, the summary measures/indices will be calculated for each of the 24 districts at baseline and endline, ranging from 0-100%. The indexes will also be categorized to create indicators to determine proportion change for before and after comparison to answer the extent to which the DIPH has changed Health Information System performance and data-driven decision-making.

For the qualitative data, a realist evaluation analysis approach principles will be employed to identify prevalent issues that influence the embedding of the DIPH in health facilities and determine the opportunities that can be leveraged to promote DIPH strategy at the district level.

All these findings will inform an additional outcome of the DIPH evaluation, i.e. revision of the DIPH programme theory for the Ethiopian context.

Eligibility criteria: Inclusion Criteria:

* All districts in the North Shewa zone will be included in the study.
* All managerial and administrative district staff.

Exclusion Criteria:

* Study participants who do not consent will be excluded.

Primary outcomes:
measure: 'Health Information System performance' Index
timeFrame: From the randomization of districts to implementation of the DIPH intervention for 16 months (i.e immediately after completing the 4th DIPH cycle).
measure: 'Governance of data-driven decision-making' Index
timeFrame: From the randomization of districts to implementation of the DIPH intervention for 16 months (i.e. immediately after completing the 4th DIPH cycle).
Secondary outcomes:
Other outcomes:
Locations:
city: London
country: United Kingdom
facility: London School of Hygiene & Tropical Medicine
Study officials:
affiliation: London School of Hygiene and Tropical Medicine
name: Tanya Marchant, PhD
role: STUDY_CHAIR
References:
citation: Wickremasinghe D, Hashmi IE, Schellenberg J, Avan BI. District decision-making for health in low-income settings: a systematic literature review. Health Policy Plan. 2016 Sep;31 Suppl 2(Suppl 2):ii12-ii24. doi: 10.1093/heapol/czv124.
citation: Avan BI, Berhanu D, Umar N, Wickremasinghe D, Schellenberg J. District decision-making for health in low-income settings: a feasibility study of a data-informed platform for health in India, Nigeria and Ethiopia. Health Policy Plan. 2016 Sep;31 Suppl 2(Suppl 2):ii3-ii11. doi: 10.1093/heapol/czw082.
citation: Bhattacharyya S, Berhanu D, Taddesse N, Srivastava A, Wickremasinghe D, Schellenberg J, Iqbal Avan B. District decision-making for health in low-income settings: a case study of the potential of public and private sector data in India and Ethiopia. Health Policy Plan. 2016 Sep;31 Suppl 2(Suppl 2):ii25-ii34. doi: 10.1093/heapol/czw017.
citation: Gautham M, Spicer N, Subharwal M, Gupta S, Srivastava A, Bhattacharyya S, Avan BI, Schellenberg J. District decision-making for health in low-income settings: a qualitative study in Uttar Pradesh, India, on engaging the private health sector in sharing health-related data. Health Policy Plan. 2016 Sep;31 Suppl 2(Suppl 2):ii35-ii46. doi: 10.1093/heapol/czv117.