Readthedocs femhealth

cds_docs_femhealth/.readthedocs.yaml

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+version: 2
+build:
+  os: ubuntu-24.04
+  tools:
+    python: "3.12"
+sphinx:
+  configuration: cds_docs_femhealth/conf.py
+  fail_on_warning: true
+python:
+  install:
+    - requirements: cds_docs_femhealth/requirements.txt

cds_docs_femhealth/about_the_data.md

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+# About the Data
+
+## Where does the data in this dashboard come from?
+
+Data for this dashboard was extracted from public sources:
+
+* Procurement data from the Assam Government e-Procurement portal. CDL compiled and cleaned Assam's tender data using the Open Contracting Data Standard (OCDS), enabling a structured analysis of health-related procurement across departments and schemes from 2020 to 2023. Procurement data relevant for MCH was identified and tagged using Natural Language Processing (NLP) methods such as topic modelling.
+* Health outcome data from the Health Management Information System (HMIS) reports, including district-level indicators such as reported live births and infant deaths.
+
+## What time period does the dashboard cover?
+
+The dashboard covers two sets of data with overlapping time periods:
+
+* Procurement data: 2019 to 2025 (112 MCH-related tenders, ₹3.27 billion total value). The study describes procurement data covering 2020 to 2023.
+* Health outcome data (IMR): 2018-19 to 2022-23, five financial years of district-level infant mortality rates across 26 districts.
+
+The overlapping coverage allows procurement patterns and health outcome trends to be examined alongside each other, while recognising that the two datasets may not cover identical time periods.
+
+## What are the known limitations of the procurement data used in this dashboard?
+
+The study highlights systemic challenges that limit the effectiveness of procurement-based monitoring:
+
+* **Limited data coverage:** Only about 20% of Assam's tenders are published, creating significant data gaps. The 112 MCH-related tenders shown on the dashboard represent the published subset, not the full picture of government procurement.
+* **Delayed disclosure:** Contract award information is often delayed by an average of 250 days, far beyond the mandated 30-day disclosure timeline, hindering timely oversight.
+* **Inconsistencies in data fields:** Inconsistencies in location fields, scheme names, and work categories further complicate efforts to link spending with specific MCH interventions.
+
+Addressing these issues through complete, timely, and standardised procurement data publication would strengthen transparency and enable more robust analysis of government spending patterns.

cds_docs_femhealth/conf.py

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+project = "FemHealth Data Collaborative"
+author = "CivicDataLab"
+extensions = ["myst_parser"]
+source_suffix = {".rst": "restructuredtext", ".md": "markdown"}
+exclude_patterns = ["_build", ".DS_Store"]
+html_theme = "sphinx_rtd_theme"

cds_docs_femhealth/exploring_a_use_case/index.rst

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+Exploring a Use Case
+======================
+
+This section walks through one of the six use cases in the FemHealth Data Collaborative - Using Data Analysis to Spot Gaps in Maternal and Child Healthcare Service Delivery - showing what you can learn from it and how to navigate the dashboard yourself.
+
+.. image:: ../images/use_case_page_layout.png
+   :alt: Navigating the Use Case Page
+
+*Figure 1.1: Navigating the Use Case Page*
+
+.. image:: ../images/use_case_datasets_dashboards.png
+   :alt: Scroll to explore data and dashboards associated with a use case
+
+*Figure 1.2: Scroll to explore data and dashboards associated with a use case*
+
+The usage scenarios below help you explore how real-life questions can be answered using this data.
+
+.. toctree::
+   :maxdepth: 2
+
+   usage_scenarios_procurement
+   usage_scenarios_health_outcomes
+   where_to_go_from_here

cds_docs_femhealth/exploring_a_use_case/usage_scenarios_health_outcomes.md

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+# Usage scenarios to link procurement spending with health outcomes
+
+## 1. How does MCH-related procurement spending compare with infant mortality rates across districts?
+
+**Why This Matters, and to Whom:** Given that a majority of Assam's population relies on public health infrastructure, analysing procurement information becomes crucial for assessing how effectively the state supports women, children, and other vulnerable groups. This is useful for public health practitioners and researchers assessing whether spending is reaching the districts that need it most.
+
+**Where to look:** In the District Analysis tab, see the MCH Tenders vs Infant Mortality Rate map. The bivariate choropleth map overlays district-level Infant Mortality Rate (IMR) data with MCH-related tender values, aggregated over the study period.
+
+<img width="1567" height="711" alt="MCH Tenders vs Infant Mortality Rate choropleth map" src="https://github.com/user-attachments/assets/35a9a808-820b-4e33-889c-9f74c5f06267" />
+
+*Figure: MCH Tenders vs Infant Mortality Rate choropleth map.*
+
+**What the dashboard shows:** This revealed substantial disparities. Districts such as Dibrugarh, Jorhat, and Kamrup Metro continue to exhibit higher IMR levels, even though Kamrup Metro accounts for some of the state's highest procurement spending, driven largely by a few major infrastructure projects. Conversely, districts like Bongaigaon and Dhemaji, despite receiving comparatively modest tender values, show significantly better IMR outcomes.
+
+**What to notice:** This suggests that higher spending alone does not guarantee improvements in health indicators; efficiency, relevance of spending, and local service delivery capacity play vital roles. The analysis underscores that procurement data can reveal gaps between investments and outcomes, helping identify districts where health needs remain unmet or where spending may not be translating into measurable improvements.
+
+## 2. Are there districts where high procurement spending has not translated into improved infant mortality outcomes?
+
+**Why This Matters, and to Whom:** This kind of district-level accountability check is useful for civil society organizations and public health practitioners tracking whether investment is translating into results on the ground.
+
+**Where to look:** Two tabs: District Analysis + Health Indicators. To investigate this further, navigate to MCH Tenders vs Infant Mortality Rate map and cross-reference with District-wise Infant Mortality Trends.
+
+<img width="788" height="355.5" alt="MCH Tenders vs Infant Mortality Rate choropleth map" src="https://github.com/user-attachments/assets/35a9a808-820b-4e33-889c-9f74c5f06267" />
+<img width="788" height="332.5" alt="cross referenced with District-wise Infant Mortality Trends" src="https://github.com/user-attachments/assets/822ac2c6-6089-48ea-8870-4430f6616e7d" />
+
+*Figure: MCH tenders vs. IMR map cross referenced with District-wise Infant Mortality Trends.*
+
+**What the dashboard shows:** Kamrup Metro accounts for some of the state's highest procurement spending, including the single largest MCH tender (₹2.14 billion for the 500-bedded Mother and Child Hospital at GMCH, as seen in the Top 10 table). Yet IMR in Kamrup Metro has remained elevated:
+
+| | 2018-19 | 2019-20 | 2020-21 | 2021-22 | 2022-23 |
+|---|---|---|---|---|---|
+| Kamrup Metro | 39.04 | 46.36 | 11.67 | 33.65 | 39.42 |
+
+
+Dibrugarh received MCH-related infrastructure investment including a Central Gas Pipeline installation at Assam Medical College and Hospital (listed in the Top 10 table). Its IMR shows a spike in 2021-22:
+
+| | 2018-19 | 2019-20 | 2020-21 | 2021-22 | 2022-23 |
+|---|---|---|---|---|---|
+| Dibrugarh | 25.38 | 22.12 | 20.46 | 33.41 | 25.91 |
+
+Jorhat has persistently high IMR, remaining above 32 across all five years, despite being one of the districts identified in the choropleth as exhibiting higher IMR:
+
+| | 2018-19 | 2019-20 | 2020-21 | 2021-22 | 2022-23 |
+|---|---|---|---|---|---|
+| Jorhat | 34.18 | 37.50 | 34.68 | 38.16 | 32.83 |
+
+**What to notice:** Higher spending alone does not guarantee improvements in health indicators. Efficiency, relevance of spending, and local service delivery capacity play vital roles.
+
+## 3. Which districts show a sharp spike or anomaly in infant mortality in a particular year?
+
+**Why This Matters, and to Whom:** A sharp spike in IMR in a single year may reflect localised disruptions or specific events affecting health service delivery. The dashboard highlights a visible peak for Karbi Anglong in 2020-21. Spotting these anomalies is useful for public health practitioners and researchers investigating specific events or service disruptions.
+
+**Where to look:** To investigate a spike, hover on the bar in question to see the exact IMR value for that district and year.
+
+<img width="1576" height="665" alt="District-wise Infant Mortality Trends" src="https://github.com/user-attachments/assets/822ac2c6-6089-48ea-8870-4430f6616e7d" />
+
+*Figure: District-wise Infant Mortality Trends showing spikes in Kamrup Rural and Dibrugarh.*
+
+
+**What the dashboard shows:** From the data, notable spikes include:
+
+| District | Spike year | IMR in spike year | Previous year | Following year |
+|---|---|---|---|---|
+| Kamrup Rural | 2020-21 | 44.35 | 13.88 | 8.19 |
+| Dibrugarh | 2021-22 | 33.41 | 20.46 | 25.91 |
+| Kamrup Metro | 2019-20 | 46.36 | 39.04 | 11.67 |
+| Karbi Anglong | 2021-22 | 18.38 | 12.07 | 8.84 |
+| Morigaon | 2020-21 | 17.61 | 15.98 | 5.08 |
+
+**What to notice:** These spikes can be cross-referenced with the procurement data. For example, Dibrugarh's IMR spike in 2021-22 (33.41) can be checked against its presence in the Top 10 tenders table, where it received a gas pipeline installation at Assam Medical College. Despite this investment, IMR spiked, suggesting the investment may not have been aligned with the factors driving infant mortality in that period.
+
+## 4. Has there been a shift in MCH-related procurement priorities after COVID-19?
+
+**Why This Matters, and to Whom:** The team examined how procurement patterns evolved over time, noting a significant shift from programme-driven purchases led by the National Health Mission (NHM) in 2021 towards more infrastructure-oriented procurement by departments such as Public Works (Building & NH) and Health & Family Welfare in 2022-23. This trend is useful for policymakers and researchers evaluating how priorities shifted in response to a major disruption.
+
+**Where to look:** Two tabs: Department and Scheme Analysis + Health Indicators. This shift can be examined across two dashboard elements: The Sankey diagram shows the current distribution of spending across schemes and departments, with SOPD and infrastructure-related departments dominating. The District-wise Infant Mortality Trends chart shows year-on-year changes around 2020-21, where districts such as Karbi Anglong show a visible peak.
+
+<img width="788" height="332.5" alt="cross referenced with District-wise Infant Mortality Trends" src="https://github.com/user-attachments/assets/822ac2c6-6089-48ea-8870-4430f6616e7d" />
+<img width="801.5" height="398.5" alt="Cross referencing distribution of spending across departments and schemes with district-wise IMR trends" src="https://github.com/user-attachments/assets/680882cc-487b-4172-bfc6-96fd58068db8" />
+
+*Figure: Cross referencing distribution of spending across departments and schemes with district-wise IMR trends.*
+
+
+**What the dashboard shows:** From the Top 10 tenders, COVID-related procurement is visible:
+
+* Morigaon: ₹10 million for Oxygen generation plant at COVID Care Hospital (2022)
+* Kamrup Metro: ₹7.24 million for COVID-19 GMCH MCH Building (2022)
+
+**What to notice:** The dashboard description notes the goal of identifying "emerging hotspots and post-COVID shifts in priorities, supporting more targeted planning, prioritisation, and course correction."

cds_docs_femhealth/exploring_a_use_case/usage_scenarios_procurement.md

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+# Usage scenarios to understand overall MCH procurement
+
+Enter the dashboard linked to this use case to analyse the data.
+
+## 1. How many MCH-related tenders have been issued in Assam, and what is the total value of MCH-related procurement?
+
+**Why This Matters, and to Whom:** Understanding the overall scale of MCH-related procurement provides a starting point for examining how public resources are being directed towards maternal and child health. This baseline figure is useful across the board, for government officials assessing overall investment, researchers scoping an analysis, and civil society organizations gauging the size of public commitment to MCH.
+
+**Where to look:** Navigate to the Overview tab at the top of the dashboard. The dashboard reports 112 MCH-related tenders with a total of ₹3,269,789,064 spent towards MCH outcome improvement over the period 2019 to 2025.
+
+<img width="1603" height="681" alt="Summary indicators showing total MCH-related tenders and procurement value" src="https://github.com/user-attachments/assets/76e63f80-e82d-4ce0-b5b4-f90da1c0fc4d" />
+
+*Figure: Summary indicators showing total MCH-related tenders and procurement value.*
+
+**What the dashboard shows:** Between 2019 and 2025, a total of 112 MCH-related tenders were issued in Assam, with a combined value of approximately ₹3.27 billion (INR 3,269,789,064) spent towards MCH outcome improvement.
+
+**What to notice:** These headline figures represent the published subset of MCH-related procurement. Given that only about 20% of Assam's tenders are published, the actual scale of MCH-related procurement is likely to be larger.
+
+## 2. Which schemes fund MCH-related procurement in Assam, and how does spending flow from schemes to implementing departments?
+
+**Why This Matters, and to Whom:** MCH-related procurement involves multiple schemes and departments. Knowing where spending is concentrated helps understand whether resources are directed towards infrastructure, service delivery, or both. This is particularly useful for government and policymakers working on budget allocation and scheme design.
+
+**Where to look:** Navigate to the Department and Scheme Analysis tab to view the Sankey diagram. This Sankey diagram maps the flow of MCH-related tenders from major schemes to their implementing departments.
+
+<img width="801.5" height="398.5" alt="Sankey diagram showing flow of MCH-related tenders from schemes to departments" src="https://github.com/user-attachments/assets/680882cc-487b-4172-bfc6-96fd58068db8" />
+
+*Figure: Sankey diagram showing flow of MCH-related tenders from schemes to departments.*
+
+**What the dashboard shows:** State-Owned Priority Development (SOPD) schemes account for the bulk of procurement, with approximately ₹2.19 billion routed through Public Works Building and NH Department and Chief Engineer (Buildings), largely for the building of hospitals and related infrastructure.
+
+Health-sector schemes account for comparatively smaller shares:
+
+| Scheme | Routed through | Approximate tender value |
+|---|---|---|
+| NHM (National Health Mission) | National Health Mission; State Programme Management Unit | ₹615 million |
+| RCH (Reproductive and Child Health) | Public Works Building and NH Department | ₹65 million |
+| LAQSHYA (Labour Room Quality Improvement Initiative) | State Programme Management Unit, NHM | ₹58.5 million |
+| MSDP (Multi-Sectoral Development Programme) | Bodoland Territorial Council; PWD-BTC | ₹14.5 million |
+| HFW / SOPD via BTC | Health and Family Welfare, BTC; Bodoland Territorial Council | ₹10 million |
+| CHD-SCHEME (Congenital Heart Disease Scheme) | Bodoland Territorial Council, PWD | ₹9.7 million |
+| UIP (Universal Immunisation Programme) | Public Works Building and NH Department | ₹9.3 million |
+
+**What to notice:** While multiple schemes and departments are formally linked to MCH, effective control over spending is concentrated in a few departments, and a large portion of "MCH-related" expenditure is tied up in civil works rather than direct service delivery.
+
+_**Data Note:** To contextualise these patterns, CDL also mapped all schemes relevant to maternal and child health, including Pradhan Mantri Matru Vandana Yojana (PMMVY), POSHAN Abhiyan, Integrated Child Development Services (ICDS), and tea garden welfare initiatives, helping to link procurement activity to key policy interventions._
+
+## 3. What proportion of MCH-related spending goes towards infrastructure (civil works) versus direct health service delivery?
+
+**Why This Matters, and to Whom:** The type of procurement matters. Infrastructure investments and programme or service-related investments support maternal and child health in different ways. This distinction is useful for policymakers and public health practitioners weighing infrastructure investment against direct service delivery needs.
+
+**Where to look:** Two tabs: Department and Scheme Analysis + District Analysis.
+
+<img width="801.5" height="398.5" alt="Sankey diagram showing flow of MCH-related tenders from schemes to departments" src="https://github.com/user-attachments/assets/680882cc-487b-4172-bfc6-96fd58068db8" />
+<img width="803.5" height="306" alt="Top 10 MCH Procurement by Value" src="https://github.com/user-attachments/assets/3b5cc6df-69e1-422f-b5f0-ff6a691f11b8" />
+
+*Figure: Sankey diagram (Department and Scheme Analysis tab) and the Top 10 MCH Procurement by Value table (District Analysis tab) explored together.*
+
+**What the dashboard shows:** State-owned priority schemes (SOPD) account for the bulk of procurement and are routed predominantly through Public Works and Chief Engineer (Buildings), largely for the building of hospitals and related infrastructure.
+
+In contrast, health-sector schemes such as NHM, RCH, and UIP account for a much smaller share of overall tender value and are routed mainly through the Health and Family Welfare Department, the National Health Mission, and the State Programme Implementation Unit.
+
+The Top 10 tenders confirm this pattern. The largest individual MCH investments are infrastructure projects:
+
+* ₹2.14 billion: Mother and Child Hospital (500 bedded) at GMCH, Guwahati
+* ₹123 million: 100 bedded Maternity Child Health wing at Dhubri Civil Hospital
+* ₹65 million: 100 bedded Maternity Child Health Wing at North Lakhimpur
+* ₹33.4 million: Repair/renovation of Mother and Child Hospital at Silchar
+* ₹30.8 million: Nutritional Rehabilitation Centre and Mother and Child ward at Bongaigaon
+
+**What to notice:** A large portion of "MCH-related" expenditure is tied up in civil works rather than direct service delivery. A few very large infrastructure projects account for a disproportionate share of the biggest individual MCH investments, especially in and around Guwahati, while most other districts see much smaller flagship contracts.

cds_docs_femhealth/exploring_a_use_case/where_to_go_from_here.md

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+# Where to Go From Here
+
+This dashboard is one of several use cases in the FemHealth Data Collaborative. The same navigation applies to the others: from the collaborative page, select any use case card to explore it and see associated datasets and dashboards. Alternatively, go to the Datasets section on the Collaborative page to browse and download the datasets directly.
+
+Here is a mapping demonstrating how the interoperable datasets and their use cases may be relevant to different stakeholders:
+
+| Stakeholder | Relevant use case(s) | Relevant dataset(s) |
+|---|---|---|
+| Government / Policymakers (finance, health departments) | Strengthening Financial Accountability towards Girl Education; Enhancing Gender Data Use in Assam: Gender Sensitive Budgeting in Focus | Gender Budget Statement Assam 2018-19 to 2025-26; HMIS MCH Assam 2022-23 |
+| Researchers / Analysts | Using Data Analysis to Spot Gaps in Maternal and Child Healthcare Service Delivery | Assam Maternal Health; Assam Health Indicators 2020; NFHS District Fact Sheet - Assam |
+| Public health practitioners | Using Data Analysis to Spot Gaps in Maternal and Child Healthcare Service Delivery | Women's Conditions in Assam 2025; HMIS child health report Assam 2018-20; Assam Health Indicators (October 2020) |
+| Civil society / Child rights organizations | An Analysis of Victim Compensation in POCSO Cases in Assam; Analysing the Implementation of Child Protection Laws in India | Data Privacy, Ethics & Security Framework for supporting Child Rights in the Akshara Ecosystem; State/UT-wise Complaints Received by NCPCR; State/UT-wise Children covered by Child Care; State/UTs-wise Juvenile Homes Under Child Care |