Join the live webinar from
on
Get free access to Accorded and Out of Pocket's course.
Join the live webinar from
DHNY Summit 2024
on the
Sept 18
Time-consuming query runs and onerous SQL/SAS/Python/R and Excel calculations drain your team’s agility and resources.
Healthcare analytics are tedious and slow
Manual upload & data warehouses (1-4 days)
Data Review & QA (1-2 days)
Custom SQL queries & Excel (4-10 days)
Excel / BI Tool for Data Visualization (1-3 days)
Model modifications require repeat of steps 3 & 4.
Your team’s analyses take seconds, not hours or days. Ready-to-go actuarially rigorous data insights directly in your existing tech stack.
Need to implement a new logic or assumptions? Just reconfigure the feature instead of overhauling your entire model. Now, your team can focus on what’s important.
1 Inbound Data Transfer
Input schema design prior to transfer and ensure only the necessary inputs are transferred.
Transfer via SFTP or Box is also available
2 Accorded’s Magic Touch
Translate business and analytical logics into reusable features that transform data in real time.
3 Outbound Data Transfer
Customizable output schema design ensures the enriched data is relevant.
All of the same mechanisms listed for inbound data transfer apply.
.png)
.png)
.png)
Step 1
Prior to data transfer, input data schema is designed to ensure only the necessary inputs are transferred.
There is no need to overhaul your data infrastructure.
Step 2
Accorded Platform enriches, pre-queries, and groups your data using actuarial and med econ logic.
Step 3
Actuarially transformed data tables are transferred to your data warehouse
Now your whole team has access to standardized and actuarially-rigorous VBC data assets.
Calculates retrospective savings per person for the impact of a clinical solution
Identifies claims with ED utilization that could have been prevented
Calculates relative risk of high spend for each person
Calculates the number of monthly IBNR claims per member
Calculates a person’s total allowed cost of care per month, using a payer claims dataset
Identifies claims with ED utilization that could have been prevented
Indicates whether a person has had an annual wellness visit
Calculates a person’s total allowed cost of care per month, using a reference dataset
Calculates relative risk of high spend for each person
Indicates a person’s “core condition” based on primary and secondary diagnosis category
For a given disease, indicates whether a person has had the disease
Indicates whether a person has been readmitted
Identifies which provider a member is attributed to
Calculates the number of monthly incurred claims per person
Identifies claims that should be assigned to one or more distinct episodes
Calculates patient encounters with a service or treatment (utilization rate)
Identifies people with ED utilization that could have been prevented
Calculates the unit cost of a service or treatment provided (reimbursement rate)
Accorded supports inbound and outbound mechanisms for HIPAA-compliant data transfer. Talk to an expert for more details.
Integrations
Transfer via SFTP or Box is also available.
Medicare risk score for each patient in the database.
Predictive risk score for substance use disorder at the member level. 429.92
Episode of care cost and utilization metrics for maternity episodes
voidable ED claims list backed on NYU avoidable ED definition.
Medicare risk score for each patient in the database.
Predictive risk score for substance use disorder at the member level. 429.92
Episode of care cost and utilization metrics for maternity episodes
voidable ED claims list backed on NYU avoidable ED definition.
Medicare risk score for each patient in the database.
Shared savings performance based on contract stipulations
Shared savings performance measures based on specialty related costs.
Inpatient readmission rate and description data on readmission.
HIPAA Compliant | SOC 2 Certified
Keeping customer data safe is top priority for us. Accorded is committed to protecting the security, confidentiality, integrity, availability, and privacy of its information resources including PHI.
