Healthcare Accessibility Diagnostic - Nouvelle-Aquitaine

I. Geographic Footprint: Where are healthcare professionals today?

The first step of our diagnostic maps the current (2022) state of healthcare supply for five key professions: General Practitioners (GPs), Physiotherapists, Dentists, Nurses, and Midwives.

This interactive mapping reveals a clear divide between the coast and the hinterland. The Atlantic coast and the “urban corridor” (Poitiers-Angoulême-Bordeaux) appear as high-supply zones (Green). Conversely, the north-eastern region shows significant gaps (Yellow/Red), particularly for specialized care like dentistry.

Methodological Note: Areas in black correspond to zones where APL data is unavailable.

While these maps show where professionals are, they do not tell us the magnitude of the gap between the best and worst-served municipalities. To measure the statistical severity of these inequalities, we must examine the distribution range.

II. Quantifying Regional Disparities: Is inequality marginal or systemic?

By using boxplots, we can visualize the statistical dispersion of healthcare supply. This allows us to compare “average” municipalities with some of the “outliers” (the black dots on the graph).

Methodological Rigor: The Challenge of Units
To ensure a scientifically rigorous comparison, significant data processing was required. One cannot directly compare professions on a single scale without precaution:
- GPs are measured in consultations per year/inhabitant.
- Other professions are measured in FTE per 100,000 inhabitants.

To obtain a coherent visualization, the analysis was structured so that each profession has its own reference frame (independent vertical axes). Without this separation, the critical variations of GPs would have been flattened and invisible compared to the higher numbers of nurses.

The data reveals contrasting realities across professions:
- Nurses and Physiotherapists: They show the widest dispersion. Some municipalities benefit from a supply more than five times higher than the regional average, while others remain at zero. This high volatility indicates a very unequal distribution across the territory.
- General Practitioners: The findings are more alarming. The “box” (containing 50% of municipalities) is situated at a dangerously low level. The median is close to alert thresholds, meaning the “medical desert” is no longer a statistical exception but is becoming the norm for a majority of municipalities in Nouvelle-Aquitaine.
- Dentists and Midwives: There is a very strong concentration at the bottom with numerous isolated points at the top, illustrating a hyper-concentration of supply in a few major urban hubs.

A snapshot of 2022 is informative, but health policy requires foresight. Is this GP deficit a recent accident or a long-term trend?

III. Temporal Divergence (2016–2022): How has accessibility evolved?

This longitudinal analysis tracks the average APL in the region from 2016 to 2022.

A striking “Scissor Effect” is visible:
- The Decline: General Practitioners (GPs) show a steady and alarming decline.
- The Rise: Paramedical professions (nurses, midwives, physios) are on an upward trajectory.

Methodological Note: This analysis could not be performed for dentists as data is only available for 2021 and 2022.

This suggests a mutation of the healthcare system: the “entry gate” (the doctor) is shrinking, while support care is growing, creating a bottleneck in the patient’s care pathway.

IV. The Healthcare Fragility Score (SFS): Which territories are globally vulnerable?

To move beyond profession-by-profession analysis, we developed the SFS (Score de Fragilité Sanitaire). This composite index aggregates data from the five healthcare professions to identify zones where the shortage is systemic.

1. Weighting: Why these coefficients?
   The absence of a GP impacts public health more heavily than the absence of a secondary specialty. We applied clinical weighting:
   • General Practitioners (Coeff. 3): The pivot of the care system. A deficiency here weakens the entire territorial diagnostic.
   • Nurses (Coeff. 2): Essential for home care and chronic pathology monitoring, especially in rural areas.
   • Physiotherapists and Dentists (Coeff. 1.5): Key for autonomy and oral health.
   • Midwives (Coeff. 1): Targeted toward a specific population segment (perinatal health).

The final score is normalized (Z-score) to situate each municipality relative to the regional average.

2. Reading the “Master Map” of Vulnerability
   • Deep Red Zones: Territories of cumulative fragility. These are critical areas where multiple pillars (GP, Nurses, etc.) are simultaneously in deficit.
   • Deep Blue Zones: Territories of high attractiveness with a complete care ecosystem.
   • Black Zones (NA): Sectors where APL data is unavailable.
3. A Decision-Making Tool
   This map could allow Regional Health Agencies (ARS) and local officials to precisely identify sectors where building a Multi-professional Health House (MSP) is an absolute priority.

V. The Population-Vulnerability Matrix: Where is the human risk highest?

This final visualization plots the SFS score (y-axis) against the total population of each municipality (x-axis). The objective is to distinguish geographic fragility from demographic criticality.

1. Why use a logarithmic scale for the population?
   For this analysis, using a standard linear scale would have rendered the graph unreadable. In Nouvelle-Aquitaine, the population disparity is immense: ranging from villages with fewer than 50 inhabitants to metropolises like Bordeaux (over 250,000 inhabitants).
   • The problem with the linear scale: All small and medium-sized municipalities (90% of the sample) would have been “crushed” into a thin strip on the left side of the graph, making their analysis impossible.
   • The advantage of the logarithm: The logarithmic scale allows us to expand the gaps between small municipalities while compressing those of large cities. This enables us to observe, on a single plane, the distribution of care in both a small rural village and a mid-sized city, offering a democratic and exhaustive view of the territory.
2. The “Quadrant of Anxiety”: Identifying Urgency
   We have defined a priority high-alert zone (highlighted in yellow on the graph, bottom right) which we call the “Quadrant of Anxiety”. It allows us to distinguish between two types of realities:

   • Rural Deserts (bottom left): Here, vulnerability is real but often “anticipated” by public policies due to the very low density. The challenge here is structural.

   • Urban Fragility (bottom right): This is the critical zone this report aims to highlight. It concerns municipalities with over 5,000 inhabitants that have a negative SFS score.

3. The Concept of the “Invisible Desert”
   These towns appear in red on our matrix. We label them “invisible deserts” because, unlike isolated rural areas, they appear on the surface to have services. However, relative to their population size, the healthcare supply is dramatically insufficient.
   In these territories, it is not merely a few dozen, but thousands of citizens who simultaneously lose seamless access to care. This situation triggers a chain reaction: saturation of the few available medical offices, a massive shift of patients toward local hospital emergency services, and, ultimately, a rapid degradation of urban public health.