Data-Informed Platform for Health (DIPH)

NCT05310682 | Unknown

• 1 other identifier: INV-007644
• Study Type: interventional
• Target: 24
• Locations: 1 country
• Sites: 1

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).

Conditions

Behavior

Keywords

Health Information Systems; Organizational Decision Making; District level health administration; Data use; Health System Research; District level

Outcome Measures

Primary Outcomes (2)

• 'Health Information System performance' Index

  Conceptually: It refers to Behavioural (e.g. skills, attitudes, values, and motivation of the people who use data) and Technical (e.g. data collection processes, systems, and methods) determinants of the health information system at the district level. It is a survey-based assessment developed by Performance of Routine Information System Management (PRISM) Toolkit ( https://www.measureevaluation.org/resources/publications/tl-18-13/index.html). Operationally: the summary measures are created of the constructs 1) essential infrastructure for data management, 2) data diversity, 3)reporting timelines, 4) data-quality assessment mechanisms, and 5) data use motivation, i.e. summating the survey item's responses and converting scores to fall on a standardized scale of 0-100. Statistically, the difference-in-differences technique will be employed to compare the change in the outcome in the DIPH intervention arm versus the change occurring in the control arm to assess the net effect.

  From the randomization of districts to implementation of the DIPH intervention for 16 months (i.e immediately after completing the 4th DIPH cycle).

• 'Governance of data-driven decision-making' Index

  Conceptually: it refers to the Organizational determinants of health information system at the district level (i.e., information culture, structure, resources, and roles and responsibilities of key people who use data). It a survey-based assessment developed by Performance of Routine Information System Management (PRISM) Toolkit ( https://www.measureevaluation.org/resources/publications/tl-18-13/index.html). Operationally: the summary measures are created of the constructs 1) evidence-based decision-making, 2) participatory decision-making, 3) understanding value of data, 4) health system support for data-use/data-driven decision-making, and 5) accountability, i.e. by summating the survey item's responses and converting scores to fall on a standardized scale of 0-100. Statistically, the difference-in-differences technique will be employed to compare the change in the outcome in the DIPH intervention arm versus the change occurring in the control arm to assess the net effect.

  From the randomization of districts to implementation of the DIPH intervention for 16 months (i.e. immediately after completing the 4th DIPH cycle).

Study Arms (2)

DIPH-intervention districts

EXPERIMENTAL

Twelve districts were randomly selected from the North Shewa Zone of the Amhara region, Ethiopia. These districts were matched with the comparison arm based on health system performance and distance. The DIPH intervention is implemented at the district health administration office level.

Other: Data informed Platfrom for health

Non-intervention districts

NO INTERVENTION

Twelve districts were randomly selected from the North Shewa Zone of the Amhara region, Ethiopia. These districts were matched with the DIPH intervention arm based on health system performance and distance.

Interventions

Data informed Platfrom for health OTHER

The DIPH promotes local data use for decision-making, priority-setting, planning and course correction at the district level by introducing a structured and collaborative process within the administration cadre. The DIPH is delivered as a package of job aids and guidelines. It involves grouping stakeholders who are brought together to deliberate on issues in a virtual platform facilitated by regular meetings. The package facilitates stakeholders' meetings in five steps: Assessment, Engagement, Definition, Planning and Follow-up. Together, these steps make up one whole cycle of the DIPH completed over four months. Each cycle looks at a specific health theme, identified in the early stages of the cycle itself. The package also includes a digital interface where everyone can regularly review data and check on progress. Note: LSHTM has exempted this study from having a sponsor, as DIPH is implemented at the health system administration level.

Also known as: DIPH

DIPH-intervention districts

Eligibility Criteria

• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

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

You may not qualify if:

• Study participants who do not consent will be excluded.

Sponsors & Collaborators

• London School of Hygiene and Tropical Medicine: lead
• Ethiopian Public Health Institute: collaborator

Study Sites (1)

London School of Hygiene & Tropical Medicine

London, United Kingdom

Location

Related Publications (6)

• 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.

  PMID: 27591202 BACKGROUND

• 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.

  PMID: 27591204 BACKGROUND

• 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.

  PMID: 27591203 BACKGROUND

• 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.

  PMID: 27591205 BACKGROUND

• Zeleke GT, Avan BI, Dubale MA, Schellenberg J. Effect of the data-informed platform for health intervention on the culture of data use for decision-making among district health office staff in North Shewa Zone, Ethiopia: a cluster-randomised controlled trial. BMC Med Inform Decis Mak. 2024 Jul 5;24(1):190. doi: 10.1186/s12911-024-02597-x.

  PMID: 38970070 DERIVED

• Avan BI, Dubale M, Taye G, Marchant T, Persson LA, Schellenberg J. Data-driven decision-making for district health management: a cluster-randomised study in 24 districts of Ethiopia. BMJ Glob Health. 2024 Feb 29;9(2):e014140. doi: 10.1136/bmjgh-2023-014140.

  PMID: 38423549 DERIVED

Related Links

• DIPH training handbook

MeSH Terms

Conditions

Behavior

Interventions

Health

Intervention Hierarchy (Ancestors)

Population Characteristics

Study Officials

• Tanya Marchant, PhD

  London School of Hygiene and Tropical Medicine

  STUDY CHAIR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: HEALTH SERVICES RESEARCH
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate Professor

Study Record Dates

• First Submitted: February 10, 2022
• First Posted: April 5, 2022
• Study Start: September 1, 2020
• Primary Completion: April 30, 2022
• Study Completion: June 30, 2022
• Last Updated: April 5, 2022

Record last verified: 2022-03

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL
• Time Frame: Study datasets for the Data-Informed Platform for Health (DIPH) will be made available on LSHTM Data Compass, a research data repository operated by the London School of Hygiene and Tropical Medicine.
• Access Criteria: To protect participant confidentiality, the de-identified datasets are made available through a controlled access approach. Researchers wishing to access datasets will be asked to apply for access via the repository's data request form, providing information on the variables they wish to access and details of their analysis plan. The request will be sent to the study team (that performed the research and have greatest understanding of the data) and the LSHTM Research Data Manager (who acts as an independent advisor). If the data analysis can be performed in compliance with the study's ethical and legal requirements, the study team will produce a derived dataset that contains the requested variables and work with the applicant to help them to understand the data. If there remains a recognisable risk that the derived dataset contains potentially identifiable information, the applicant will be asked to sign a Data Sharing Agreement before being provided with the dataset.

Locations

GB (1)