Heath Care Analytics
06-06-2018 20:35 PM - last edited 10-22-2018 01:17 AM
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Heath Care Analytics
Health Care Analytics provide analysis of different disciplines of health care including financial analysis,staffing plans and clinical data analysis.It focusses on searching patterns in the healthcare data to provide meaningful insights and improve healthcare quality by limiting excessive funding.The idea is to increase the profits and quality by analysing the areas which impact the growth of the healthcare industry.
This is a brief description about insights provided by each report.
Hospital Patient Care Financial Margins by Payors-This report shows the surplus and deficit by payor in total and by inpatient and outpatient services.
Revenue Cycle Management
Revenue cycle management is the process used by healthcare systems in the United States to track the revenue from patients, from their initial appointment or encounter with the healthcare system to their final payment of balance. It is a cycle that describes and explains the life cycle of a patient (and subsequent revenue and payments) through a typical healthcare encounter from admission (registration) to final payment (or adjustment off of accounts receivables).
Proper revenue cycle management ensures that billing errors are reduced so that reimbursements from the insurance companies are maximized.
Executive Summary-Revenue Cycle Management
This report summarizes the important aspects of the revenue cycle management
- Manage the amount receivable, visits, charges, payments and adjustments monthly or yearly and compare the performance of same with previous year (YTD or MTD).
- Track the net collection rate.
- Determine Payer information.
Charges, Payments and Adjustments
- This is the detailed report for charges, payment and adjustments.
- It provides insights about the adjustment distribution according to charges (YTD or MTD) for Current Year and Previous Year.
- The evaluation of the distribution of charges, payments and adjustments for each provider and payor is clearly depicted in the report.
AR Management KPI
- According to AR aging bucket we are distributing the AR amount.
- Top 5 financial class according to AR.
- Determining the AR amount according to Account Balance Category.
Coding Distribution
- Track coding (CPT and ICD) distribution for old and new patients
- Determine the centers/clinics with highest visits w.r.t. CPT codes
- Determine the count of CPT code for each financial class
Denial Management
- Determine the reasons for the occurrence of each denial and decide which areas we can improve to decrease the denial rate.
Charge Liquidation
- Evaluate total no. of account and % of AR w.r.t the aging categories and account balance categories.
- Evaluate Monthly charge liquidation.
Glossary
AR |
Accounts Receivable |
Accounts receivable or A/R is a term used to denote money owed to your practice for services you have rendered and billed. Any payments due from patients, payers, or other guarantors are considered A/R. |
CPT |
Current Procedural Terminology |
Current Procedural Terminology (CPT) is a medical code set that is used to report medical, surgical, and diagnostic procedures and services to entities such as physicians, health insurance companies and accreditation organizations. CPT codes are used in conjunction with ICD-9-CM or ICD-10-CM numerical diagnostic coding during the electronic medical billing process. |
DAR |
Days of Accounts Receivable |
Days in Accounts Receivable (A/R). Days in A/R refers to the average number of days it takes a practice to collect payments due. The lower the number, the faster the practice is obtaining payment, on average. |
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Can you please share with me if pissible, avi081265@sagore.onmicrosoft.com
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Dear Mr/Ms Hardik
Your dashboard's wonderful, I like it.
And, about "Payer mix change from previous year", how do you create effective up/down a row?
Pls, I want to build my dashboard which sames that.
Thank you so much!
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Please
Thanks in advance
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How can i contact the developer or get this ?
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were you able to contact the developer?
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This is really impressive. My only critique is that the images in the background distract from the actual data and visualizations. Perhaps you can make them more transparent or not at all. Great work!
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Amazing Work...
