Ultimate Guide On Medical claims data

Healthcare organizations use medical claims data to improve population health planning. Here are the benefits of using this data and how to get started.

If you've ever undergone surgery, been in a car accident, or needed to see a doctor for any other reason, you know that medical bills can quickly add up. Even if you have health insurance, you may still be responsible for a large portion of the costs. Thankfully, there are ways to reduce your out-of-pocket expenses.

Familiarize yourself with medical claims data by understanding how this data works. You can make more informed decisions about your healthcare and hopefully save some money in the process. So whether you're an individual looking for ways to cut back on your medical care.

Medical Claim Data

A medical claim is a request for payment sent to an insurance company by a healthcare provider through electronic health records. The claim includes a description of the services provided, the date of service, and the amount charged. For a definitive healthcare provider to be reimbursed by an insurance company, they must submit a claim form. This form includes information about the patient, the services provided, and the insurance company.

Medical claim data, also known as administrative data can be used to track spending patterns, identify areas where costs are rising, and evaluate the performance of healthcare providers. It can also be used to develop strategies for reducing healthcare costs.

What To Consider When Analyzing Claims Data?

When analyzing medical claim data or other medical records, there are a few things to keep in mind. First, it's important to remember that not all claims are created equal. Some claims may be for more expensive procedures, while others may be for routine check-ups.

There are a few things to remember when analyzing medical claims data:

  • Not all claims are created equal - some claims may be for more expensive procedures, while others may be for routine check-ups.
  • Keep in mind that data can take some time to compile - claims can often take up to three months (in some cases longer) to adjudicate after a service has been rendered.
  • The data is cumulative, meaning it includes all the claims that have been submitted to an insurance company, regardless of when they were submitted.
  • When you receive data from a payer, you'll want to make sure that the files you receive have clean data, are formatted correctly, and follow consistent standards. This will help ensure that the data is easy to read and interpret.
  • Understand what is and isn't included in claims data. Claims data will (likely) not contain lab results or any clinical data that isn't tied to services billed to insurance. This data only includes information about services that have been billed to an insurance company. As a result, it can be used to track spending patterns, but it can't be used to evaluate the quality of care.

Ways To Use Claims Data To Inform Population Health Initiatives

Healthcare organizations are using claims data to achieve several important population health goals. Some key ways that claim data can help organizations advance their financial and population health goals include:

Medication Adherence Tracking

One way that healthcare organizations can use claims data is to track medication adherence. This can be done by identifying which medications have been prescribed to a patient and then tracking whether or not the patient has filled and refilled the prescriptions. This data can help organizations identify patients who may be struggling with medication adherence and provide them with targeted interventions.

Patient History Reporting

Medical claims data is a valuable resource for healthcare organizations because it includes a breadth of information from across multiple healthcare organizations. This data can help providers get a better picture of what's in a patient's history, including past procedures and diagnoses. This information can help providers make more informed decisions about care.

Tracking Of Preventative Services

The breadth of data that is available in medical claims also allows your organization to track the preventive services that patients have had in the past. This can be used to target outreach to patients who may need these services.

Aligning With Payers’ View Of Quality

Healthcare organizations can use medical claims data to track medication adherence, patient history, and preventive services. This data can help providers make more informed decisions about care and measure the impact of preventive services on patients' health. Additionally, this data can help healthcare organizations align their quality measurements with those of their payers.

Utilization & Resource Reporting

Another key way that healthcare organizations can use claims data is to track the expenses and use of their health care system. This information can help organizations identify areas where they may be overspending and identify opportunities to save money. Additionally, this data can help healthcare organizations understand how their patients are utilizing their services.

Tools For Healthcare Predictive Analytics

There are many software programs and applications that healthcare organizations can use to help them analyze their healthcare claims data. These tools allow you to visualize the data in different ways, identify patterns, and make predictions about future trends. Using these tools can help you better understand your claims data and how it can be used to improve population health.

HCC Models

Healthcare Cost Containment (HCC) coding is a broadly used technique, especially in risk-scoring algorithms. Risk-scoring models assign a single number to an individual describing their risk. This number is used to determine the number of services that the individual should receive. HCC coding can help organizations improve their population health by using claims data to identify high-risk individuals.

Event Groupers

Event groupers are a valuable tool for healthcare organizations because they allow you to see the relationships between different events. This information can help you understand how different events are related and identify patterns. Event groupers can also help you understand the impact of certain events on patients' health.

There are some different event groupers available, and each has its strengths and weaknesses. It is important to select an event group that will best meet the needs of your organization.

Clinical-Based Models

Domain knowledge is a critical component of being able to use healthcare claims data for predictive analytics. This knowledge includes an understanding of the different types of data that are available, how to analyze the data, and what the data means. A significant amount of domain knowledge is necessary to make full use of claims data but here the domain knowledge is usually gained over time through working with the data.

Once an organization has a good understanding of its claims data, it can start to build clinical-based models. Clinical-based models are models that are based on an organization's clinical knowledge. These models use information about patients' health and the treatments that they have received to make predictions about future events. Building these models can be a time-consuming process, but it is often worth the effort.

Benefits Of Healthcare Claims Data

There are many benefits to using healthcare claims data for predictive analytics. Some of these benefits include:

Assessing Medication Compliance

Using healthcare claims data for predictive analytics can help organizations assess medication compliance. This is because claims data include important details about medications. Every fill/refill of a prescription, complete with the date of that event, shows up. By analyzing this data, organizations can identify patients who are not taking their medications as prescribed and take steps to address this.

Good Reflection Of Tests, Procedures, And Services Provided

This means that any services provided by a provider who is not using electronic medical records (EMR) will fail to be reflected in the EMR data. The claims data, however, will contain evidence of them because all of these services need to be reimbursed. This is important to keep in mind when using claims data for predictive analytics because it can bias the results.

Conclusion

The use of medical claim data has become increasingly important in the field of population health. By analyzing and understanding this data, healthcare professionals can develop targeted interventions and improve the overall health of their patients. Check our Enter.Health to get different ways to utilize medical claims data and vast benefits. For more information on how to use healthcare claims data for predictive analytics, please contact our team to help you get started!

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