Hospitals are generating a lot of documents. It starts with medical records, administrative documents like DNRs, consents or informative documents, but along with this there is a whole bunch of medical billing records getting generated with every step in the patient’s treatment.
Can these documents be of any use apart from their vital use in claim amount generation? Yes, these medical billings are helping us to corelate the medical treatment course. If any treatment records are missing it is easy to understand by looking at the medical billing records and matching them to original documents. And the missing records can be retrieved.
Billing records also provide us more details about the treatment including the ICD and CPT codes which direct us to exact diagnosis and treatment. Dates in the billing help navigate through the course of treatment and help understand “missed treatment” dates, total dates required for completion of the treatment.
If these data to be use further for treatment efficacy analytics or analysis of the worsening diagnosis by tracking the records. The dates, the data against dates, billing codes and the charges really provides a good ground to come up with analytical outcomes.
So, when we know these medical billing records are of great value for claim purpose, investigative data purpose and in the analytics as well, why not make sure that these documents are managed very carefully. How about having a billing summary?
However, seems very new concept, but it is a very best and handy tool heling litigation services, insurance companies and also the medical analytics. Billing summary includes the date wise gathering of all the charges generated during treatment. It also has ICD and CPD codes to give more precision to the details against charges. It also provides a brief analytical presentation of the medical bill amounts per year. The dates are arranged in the chronological way based on requirements.
ITCube sets up a virtual team for the billing summary, which works as a legislative support team or extended team to help extract valuable data from enormous numbers generated with a load of billing pages for any treatment.