Ideally, HealthCare Policies and Claims are building upon sequential data which acts as the Wealth of Information. Such wealth leverages its real potential with the existence of advanced claim management processes. These processes are derived using valuable insights from the Data Analytics concept and its intelligent tools. As a result, Data Analytics and Intelligence has become the widely accepted tool in the Healthcare industry and is giving an immense boost to the overall Healthtech environment. However, the idea of HealthCare Claim Analytics has taken the complete industry by storm with its extended utilities. So let’s find out what the idea of HealthCare Claim Analytics talks about?
What is HealthCare Claim Analytics?
HealthCare Claim Analytics is supremely backed by Claims Data and this data is also known as administrative data which are recorded and used on a bigger scale. Such a Claim database is a collection of information fetched from doctors’ appointments, bills, healthcare service providers, insurance agencies, patients, etc. The existence of a large sample size of Claims data acts useful in identifying and analyzing the severity of the situation and placing required measures in place.
Once the complete Claim data is derived it is articulated into insightful information using Advanced Data Analytics. Hence, the term refers to the “HealthCare Claim Analytics”, which is defined as the process for analyzing facts and offering useful Claim insights at both macro and micro levels. Moreover, the studies show that HealthCare Claim Analytics focuses on 80% preparation and 20% Analytics due to the complex nature of HealthCare data. Furthermore, the Health Care Analytics software facilitates filtration of claim data into segments and helps in analyzing the trends and drills in the industry.
Use cases of HealthCare Claim Analytics
Over the decades’ the insurance sector has seen several ebbs and flows due to improper claim management practices and assumption games. As a result, the need for precise and full-fledged databases has grown over time. According to studies 91% of Americans were recorded to have insurance coverage and due to poor claim practices, insurers faced nightmares where even around $100000 was paid for minor injuries like a broken finger. Hence, AI-driven Healthcare Claim Analytics has proved immensely beneficial in bridging the claim management gaps in the Healthcare Industry.
|Detecting Fraud||Undoubtedly, fraud plots in the Health insurance sector are becoming more complex. As a result, the field experts incorporate data analytics and its intelligent tools to identify suspicious events and claims. As a result, the early fraud detection potential of the Healthcare insurer helps to avoid hefty payouts. Using the data mining and modeling algorithms the reporting, visualizing, and analyzing processes become seamless.|
|Facilitating Payment Recovery||Oftentimes, the subrogation cases are neglected by Insurers due to the existence of voluminous data. Hence, the application of text analysis and Machine Learning algorithms allows insurers to identify key events and codes in the subrogation cases. Furthermore, it allows insurers to improve their recovery of payments from such cases.|
|Optimizing Payouts||Isn’t it true that insurers always focus on settling claims faster without much cost involvement? To enable this fast- process while addressing transparency it is important to analyze the claim histories and forecast the cost involvement. Based on this the healthcare insurance companies estimate and set the bar on instant payouts leading to accurate calculation of loss reserve and future claims.|
|Preventing Litigation||In most cases, disputed claims lead to increased expenses for the insurers. Hence, using data analytics such companies can spot and calculate the precise possibility for litigation. Based on such forecasts and analyses the insurers are not just able to prevent litigation but ensure faster claim settlement.|
|Building Product Efficiency||Data Analytics software solutions have emerged as the answer to faster, precise, and well-conditioned claim settlement processes. As a result, such analytics improves the pricing feature along with building great transparency. Hence, the insurers are able to stand by patients’ expectations with automated tools and stay ahead of the competitors.|
Metrics used for HealthCare Claim Analytics
Amongst the several Healthcare Maintenance KPIs, there are some impactful and crucial metrics that are responsible for bringing the claim cycle and processes in sync. Hence, some of the commonly known HealthCare Claim Analytics are mentioned below.
|Net Promoter Score||It is the prime standard for measuring customer loyalty in the HealthCare industry. This is calculated based on the survey conducted by policyholders where the score ranges from 0 to 10. After calculating the NPS score the detractors are subtracted from the percentage of promoters.|
|Cost Per Claim||The cost involved in claim processing impact the profitability scenario of the insurers. Therefore, it becomes crucial to settle and pay legitimate claims much faster. Further, it is calculated by dividing the total cost by the number of total claims where the cost of intake, technology, adjustments, etc are included in the claim processing costs.|
|Claim First Pass Resolution Rate||It is quite evident that claims are generally not resolved at first go but reworking on the claim proceedings is certainly required. To facilitate the healthy reworking structure total number of claims resolved at first go are divided by the total number of claims that were adjudicated (as a percentage). This way claims are resolved either through full or partial payment, what so ever is determined by the nature of the first pass claim count.|
|Claim Settlement Cycle Time||If the claim settlement process takes longer, the insurers tend to lose their customer base. Hence, lengthy cycle time is the troubled insurer invites itself as it leads to increased cost involvement, lower productivity, and unhealthy relationship with the clients. It is calculated by dividing the sum of claim settlement times by the total frequency of claims settled (resubmitted claims are not considered for this calculation).|
|Claim Denial Rate||It refers to the number of events where insurers refuse to make payment to the other party due to some legitimate reasons. Hence, the denial rate is calculated by dividing the number of denied claims by total processed claims. The calculation of Denial Rate includes claims that cannot be reversed and require additional information to settle.|
Tools used for HealthCare Claim Analytics
To make HealthCare Claim Analytics a more refined solution to the claim management process following tools and techniques are used. As a result, the adoption of such tools makes it evident that Data Analytics is certainly shaping the HealthCare Industry towards a progressive route.
|HCC Models||It is a widely used technique where risk-scoring algorithms are used to predict claim costs by assigning a single number to the individuals. Hence, it works by categorizing the conditions by assigning the ICD-10 diagnosis code based on which further weights are assigned. As a result, allows service providers to capture the breadth of data and make it analyzable and understandable.|
|Clinical Bond Models||Here, the clinically-defined algorithms are used to identify the patient’s health conditions and the claim possibility thereupon. Similarly, multiple outpatient events help to define the combination and quantity of the claims. With the help of this model, the general characteristics of the patient to risk and severity can be defined well in advance.|
|Event Groupers||It can be understood as the extension of HCC models where nuances are not recorded but are equally relevant to streamline the process and eliminate loss-making events. Hence, Event Groupers attempt to make correlations across data sets easier and more accessible. Moreover, amongst the array of complexities “episode groupers” allow designing well-formulated episodes and facilitate effective policy research.|
|HealthCare Insurance Software||By using the HealthCare Insurance Software automation of operations and conversion of the searchable database into useful insights becomes completely smooth. Furthermore, tailors solutions for HealthCare Claims using Patients’ Demographics. Such Data Analytics software is potent to address data privacy shortcomings with their Versatile frameworks and also consider aspects like payout optimization, fraud detection, risk assessment, etc.|
|Custom Claim Analytics Software||Custom Claim Analytics Software is developed to stay in line with the latest market trends. Such software uses a variety of tools to build comprehensive HealthCare Claim solutions. These tools make it easier to understand the severity level of the patients and the probability of the claim-based events. The tools supporting the Custom Claim Analytics are as follows: Patient Analysis Unstructured Data Analytics Predictive Modeling AI-driven tools ( CRMs, EHR systems, etc)|
HealthCare Claim Analytics Companies
The invasion of big players in the HealthCare Claim Analytics ecosystem has revolutionized the way service providers perceive the Claim Management process. Moreover, these companies have continuously brought required innovations at their door for allowing the ecosystem to grow flawlessly.
|IBM Watson||It is the leading technology company that develops healthcare applications that are powered by Artificial Intelligence and Machine Learning algorithms. As a result, helps to deliver precise solutions for use cases for Claim Management. Precisely, with specialization in Oncology Watson recommends the AI-driven healthcare systems for managing Oncology claims.|
|Digital Reasoning Systems||Synthesis. a digital reasoning system allows service providers to create advantageous positions. Furthermore, their partnership with Hospital Corporation of America (HCA) allows the entire collaboration to use natural language understanding and build holistic capabilities and understanding for the patient.|
|Health Fidelity||It is seen as the sizable solution for leading the Healthcare Natural Language Processing Engine and enabling the providers to determine the risk level. Here, data intelligence and analytics tools help to optimize risk and streamline claim management proceedings.|
|Linguamatics||This product is used by more than 85% of the companies due to its specialization in advanced natural language understanding. It facilitates timely drug discovery which helps to reduce the claim rate by decreasing risk severity and risk.|
|Flatiron Health||Flatiron Health is one of the significant players in the Data Analytics market which provides access to vast datasets for patients. It supports approximately 200 million active patient records and facilitates research which further helps to bridge the Claim Management Processes in the entire ecosystem.|
|Avasdi||This company serves as the pioneer HealthCare Analytics object for driving operational decisions in the HealthCare and Insurance industry. Hence, helps to support Population Health predictions, Clinical Variation and Denial Management.|
HealthCare Claim Analyst
A Claim Analyst is the field professional who is responsible for verifying and updating the claim-related information for the reviewing process and determining the reimbursement. Such professional helps to provide billing analyses of claims and enforce standard federal regulations. The key responsibility of the HealthCare Claim Analyst is to provide contract provisions for determining the claim payment structure. Moreover, such research also helps to frame the accurate status of medical claims and carefully review charges.
These professionals are expected to hold skill and expertise in matters like inpatient/outpatient billing, itemization of charges, and taking care of revenue codes. Furthermore, health information and auditing experience in the healthcare setting and system is preferred by organizations across the globe.
Evidently, the adoption rate of HealthCare Claim Analytics is growing in numbers across all the healthcare industries worldwide. As a result, Claim Analytics have made Insurance procuring, premium building, and claim to file proceeding more refined for both the parties involved in the insurance contract. However, the development of advanced Data Analytics infrastructure in the HealthCare Claim Management has benefitted the service providers at large by allowing them to facilitate research, predict claim structure, and make the proceedings secure and speedy.