Value Analysis
Value Analysis for health care is the health care outcome per dollar of cost expended. Everyone recognizes that care cost is spiraling out of control. Reasons are numerous. But evidence points to the increasing price of drugs and an intent to increase the volume of services for nonessential treatments.
The Galen software suite provides several opportunities to decrease the costs of drugs and to generate savings for nephrology patients. Of further interest is to improve and streamline practitioner services such that a measure of excellence becomes quality rather than volume.
The measure and improvement of quality services requires the collections of historical data and applications of machine learning to identify changes in practices that increase value.
For example, a patient’s symptoms are recorded and inserted into the AI software. The results indicate the type of disease that exists within the patient. Many other types of analysis can be applied to either predict or classify a particular outcome.
Comorbidity
Comorbidity, which stresses the nature of treatments, denotes the existence of two or more diseases within a patient simultaneously. Arterial hypertension and cardiovascular diseases are accountable as major risk factors for developing renal disease. Other features such as peripheral vascular disease are also known to exist with kidney disorders.
Physician experience is instrumental in measuring and treating comorbidity, but artificial intelligence techniques can be used to supplement diagnoses.
Large databases are structured as input for the training of a neural net. Data types are obtained from previous comorbidity studies and from records that exist in various nephrology offices. A neural net predicts outcomes for various combinations of existing diseases. The results inspire treatment plans that will best produce patient improvements.
Situations for various conditions can be addressed:
- A medical condition existing simultaneously but independently with another condition in a patient.
- A medical condition in a patient that causes, is caused by, or is otherwise related to another condition in the same patient.
- Two or more medical conditions exist simultaneously regardless of their causal relationship.
A neural net continues to learn and to predict more accurate information as new comorbidity data are introduced.
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