There is a direct link between quality of your company's data and its business performance. High Quality data keeps your company competitive in a volatile and turbulent economic challenges. To operate at a peak level of its efficiency, comply with the growing number of regulations and better manage risks, your company should have a high quality data content not in just one department but throughout the entire organization, both inside and outside of your company's firewalls. Our Data Quality Services can help by leveraging powerful technology stacks that deliver the full range of data quality capabilities for your 340B data.
To achieve a higher level data quality, one must to perform seven different steps methodology such as:
- Data Profiling
- Data Quality Measurement
- Defining Data Definition Rules
- 360 Degree Data Integration
- 340B Data Review for Exceptions
- Data standardization & Enrichment
- Data Monitoring and Delivery
During Data Profiling:-
You identify the data anamolies in the data sources such as Payer, Fee, Claims data, Prescriber, Patients, Covered Entities and Controls because identifying the data fields is a critical step to the success of your business applications. You must investigate each data attributes to uncover its metadata. Metadata uncovers the Data Anomalies, Data Sources, Data Transformation and Data Clarity. Metadata is nothing but "Data About Data" and its essential for performing impact analysis. Having an accurate data content helps Data Scientist or Data Stewards to optimally perform their job function.
Data Quality Measurement:-
Next you must need to measure the metrics of the quality of the data within your application. As I mentioned in my earlier blog about data quality, quality of the data must be measured based on the six metrics such as:
- Completeness - What data is missin or unusable?
- Confirmity - What data is stored in a non-standard format?
- Consistency - What data values give conflicting information?
- Duplication - What data records or attributes are repeated?
- Integrity - What data is missing or not referenced?
- Accuracy - What data is incorrect or out of date?
In addition to the above, you can also include your own data quality metrics or dimensions that are most important for your business. Delivering such awesome data quality reports helps to improve the business and IT collaboration for better delivery.
Defining Data Definition Rules:- During this step, we must analyze the data quality report and define the rules to perform data cleansing & parsing the data for better usability. Data Manager or Data Stewards can easily define the data quality rules for master data such Prescriber, Provider, Patients, Drugs for Inventory Management and financial data. During this course you need to make sure that the data definition rules are reused on daily basis and eliminate the data redundancy, using data quality matching rules. Depending upon the business needs, these rules must be enabled for both batch and realtime basis.
360 Degree Data Integration:-
For a broader or 360 degree Data integration process, all of the above three steps help to accelerate. Once Data Stewards build the data quality rules, IT can able to run these rules by integrating in a website, data loading process on both realtime or near realtime.
340B Data Review for Exceptions:-
As we review the data quality processes, most cleansed data meet the data quality standards or business requirements that has been set. But inevitably the quality of some data is so poor that must be identified and corrected. There should be an automation process that helps to build an effective exception management solutions. With RCTECH Data quality assistance, Data stewards can be able to view and filter the low quality data before they are loaded into the target. They can review exceptions, duplications, null records, incorrect patient details, incorrect drug strengths, expired or invalidated prescriber contract with the contract pharmacies. These are the essential steps that one must follow to bring the cost down and in fact proactively identify the potential loss to the speciality pharmacy.
Data Monitoring and Delivery:-
Finally 'customer' which includes both IT and Business should be able to view the completeness of data, daily invoices, expenses by any given period, inventory details, back order details, purchase order summary, commission and sales earned by certain time period. Data Quality reports should accurately report six quality dimensions. These reports will clearly identify if the quality of data is increased or decreased. Also reports should be directly linked to your companies KPI (Key Performance Indicator). With our dynamic reporting and monitoring capabilities, IT or business personnel can monitor the quality of the data across the enterprise.
Data Quality must be owned by IT and Business for the successful business functions. RCTECH Solutions Inc helps our customers to bring the technology available in the market for effective business and IT colloboration. Also our tailored solutions helps to access, discover, cleanse, integrate and deliver the quality data regardless of where it resides. If you wish to extend the data quality solutions for your IT or just 340B data, RCTECH can help.