Update README.md

README.md

@@ -24,8 +24,9 @@ Develop a simulation model for ‘’Geo-optimization of distribution and connec
 
 Background:
 - Sudden cardiac death is one of the most frequent causes of death in Germany (70-80K/yr.)
+- About 25-30% of sudden cardiac arrest patients are able to be treated by AED when paramedics arrive at the scene
 - Only 35% of affected patients arrive at the hospital alive (only 12% discharged from hospital alive)
-- Early CPR and defibrillation plays a key role in the chain of survival (time critical - should be done in <10 mins of event)
+- Early Cardio pulmonary resuscitation (CPR) and defibrillation plays a key role in the chain of survival (time critical - should be done in <10 mins of event)
 
 
 
@@ -36,8 +37,8 @@ We developed a multi-parametric simulation model for determining the most approp
 various environmental parameters of a city/ region [considering mobile (e.g. taxis) and fixed (e.g. EMS stations)] to bring early resuscitation
 to sudden cardiac arrest patients.
 
-The impact of the model could be determined by the perceived reduction in response time for responders (volunteers and first responders) to reach 
-sudden cardiac arrest patients to start treatment (CPR+AED use) thereby improving survival rates.
+The impact of the model could be determined by the perceived reduction in response time for responders (volunteers/ first responders/ mobile responders)
+to reach sudden cardiac arrest patients to start treatment (CPR+AED use) thereby improving survival rates.
 
 The model also includes simulation of drone AED transport to cardiac arrest locations for rural/ countryside settings.
 
@@ -46,10 +47,11 @@ The model also includes simulation of drone AED transport to cardiac arrest loca
 
 ## Nutzen für den Anwender (Applicability / Usability)
 
-The model will help city officials in performing detailed assessment and determining appropriate placements of AEDs for maximum 
+The model will help emergency services and dispatch centers in performing detailed assessment and determining appropriate placements of AEDs for maximum 
 impact during sudden cardiac arrest situations.
 
 The output of the model could be fed on to smart phone apps like Meine Stadt rettet/ first responder app to minimize response time for resuscitation.
+
 It will help in improving survival rates of sudden cardiac arrests through early intervention.
 
 Patients are benefited through early treatment and better outcomes during sudden cardiac arrest events. They also have a better quality of life 
@@ -61,10 +63,10 @@ It will help taxi service companies to improve revenues through 'health taxis' (
 
 ## Geschäftspotential (Business Potential / Feasibility)
 
-Sudden cardiac arrest is a major healthcare problem resulting in thousands of deaths every year. Cities/ Govts. are determined to improve cardiac health
-of population due to high mortality and associated economic impact.
+Sudden cardiac arrest is a major healthcare problem resulting in thousands of deaths every year. Cities, Govts., and insurance companies are determined to 
+improve cardiac health of population due to high mortality and associated economic impact.
 
-As our model takes in to account multiple modes of response (volunteer responders, taxis with AEDs and drone AEDs) the most 
+As our model takes in to account multiple modes of response (volunteer responders, taxis/police cars with AEDs and drone AEDs) the most 
 cost effective and efficient solution could be offered based on the region (cities vs rural).
 
 It provides opportunities for new business models for faster adoption and expansion (e.g. 'health taxi' service - customers could pay an