feat: add Pathway Cost Effectiveness lollipop chart (Task 9.4)

- Create create_cost_effectiveness_figure() in plotly_generator.py
  Horizontal lollipop chart with dot size by patient count,
  colour gradient green→amber→red by cost, retention annotations
- Fix calculate_retention_rate() to accept both 'value' and 'patients' keys
- Add _render_cost_effectiveness() dispatch in chart.py callbacks
- Wire into tab switching for active_tab='cost-effectiveness'

dash_app/callbacks/chart.py

@@ -108,6 +108,33 @@ def _render_market_share(app_state, title):
     return create_market_share_figure(data, title)
 
 
+def _render_cost_effectiveness(app_state, chart_data, title):
+    """Build the cost effectiveness lollipop figure from current filter state."""
+    from dash_app.data.queries import get_pathway_costs
+    from data_processing.parsing import calculate_retention_rate
+    from visualization.plotly_generator import create_cost_effectiveness_figure
+
+    filter_id = (app_state or {}).get("date_filter_id", "all_6mo")
+    chart_type = (app_state or {}).get("chart_type", "directory")
+
+    selected_dirs = (app_state or {}).get("selected_directorates") or []
+    selected_trusts = (app_state or {}).get("selected_trusts") or []
+    directory = selected_dirs[0] if len(selected_dirs) == 1 else None
+    trust = selected_trusts[0] if len(selected_trusts) == 1 else None
+
+    try:
+        data = get_pathway_costs(filter_id, chart_type, directory, trust)
+    except Exception:
+        log.exception("Failed to load pathway cost data")
+        return _empty_figure("Failed to load pathway cost data.")
+
+    if not data:
+        return _empty_figure("No pathway cost data available.\nTry adjusting your filters.")
+
+    retention = calculate_retention_rate(data)
+    return create_cost_effectiveness_figure(data, retention, title)
+
+
 def register_chart_callbacks(app):
     """Register tab switching, pathway data loading, and chart rendering callbacks."""
 
@@ -224,6 +251,9 @@ def register_chart_callbacks(app):
         elif active_tab == "market-share":
             fig = _render_market_share(app_state, title)
 
+        elif active_tab == "cost-effectiveness":
+            fig = _render_cost_effectiveness(app_state, chart_data, title)
+
         else:
             # Placeholder for charts not yet implemented
             tab_label = dict(TAB_DEFINITIONS).get(active_tab, active_tab)