Attempting to traverse through the ever-changing, quagmire of provider data can be a resource-intensive, tiresome task. As it is a crucial aspect of the health plan and workers compensation internal operations, it is imperative that provider data be managed efficiently so as not to burden those who rely on its accuracy, such as internal and external stakeholders, regulators, and consumers.
Provider data management solutions ensure the accessibility and accuracy of network data, so that those who need access to information can dodge the obstacles for an effortless, efficient experience. These four components of managing provider data are essential for a seamless and accurate stockpile of network data: 1. Secure Data Hosting 2. Data Scoring 3. Data Cleansing 4. Roster Management
Enlist secure cloud-based data hosting On premise has “lost the battle” to cloud-hosted solutions. The workload and cost associated with hosting internal provider data is not worth its inefficiency. External data hosting is much safer, simpler, and more cost effective (from a true total cost of ownership), to keep provider information consistent, clean, and up to date. Through a cloud-based master index, provider data can be securely transported across an organization, improving access and accountability with a “single-source of truth” By outsourcing provider data management to a trusted partner, healthcare organizations increase data accuracy, while reducing spending and frustration. The return on investment of an external data management solution is significant and compelling, making it essential to efficient PDM.
Benchmark and score your data The dynamic state of provider data often results in the need for continuous validation and correction. To gain clarity on the state of provider directory data, a data scoring solution helps organization benchmark their data and know where to focus their efforts. A data scoring solution provides insight into what needs to be scrubbed, standardized, and validated. Ideally, it should leverage Artificial Intelligence (AI) and Machine Learning (ML) to compare data against diverse, proven sources of accurate provider data, such as a master data index and third-party sources for validation. By first evaluating data, organizations can take the next step in provider data management - data cleansing. Using artificial intelligence to scrub provider data to the single attribute level enables a better outcome vs. traditional data cleansing approaches.
Cleanse data at the single attribute level Inaccurate provider data poses complications to consumers, providers, health plans, and partner experience. For this information to be reliable, it is imperative that the data be cleansed of errors and inaccuracies. This too, can be a labor-intensive process, and requires a detailed cleanse of every single aspect of data. A smart analytics solution benchmarks the current state of provider information, which helps pinpoint what needs to be scrubbed. AI-enabled data profiling then automates the identification of metadata and matches data down to the single-attribute level for more reliable provider data cleansing. Most groups abandon cleansing data down to the single attribute level, because it is extremely challenging to do so given that usually the ideal source for one data attribute is separate from another attribute. This process requires a complex understanding of hundreds of potential data sources, and which to prioritize. But the juice is worth the squeeze, which is why Perspecta has chosen to go the extra mile for our customers and incorporate over 700 different databases to get the ideal source for each data attribute. Being a vital part of your business, brand, and customer experience, provider data needs to be cleansed and checked frequently to include quality checks of the information to oversee errors that may be faced during processing. Optimize Provider Roster Management Managing a provider roster is very labor intensive. With stakeholders across your organization working off their own data sources and making updates to a spreadsheet, system, or even paper documents, errors and inconsistencies are more certain to happen. In addition, the process requires follow-up with providers to provide data changes and validate accuracy. Is there a better way? Enlisting a trusted provider roster management partner can more effectively manage the process, freeing up internal staff for other important aspects of their work queue. AI and Machine Learning (ML) can be a significant value-add for the provider roster management process. An experienced partner can better manage multiple provider data rosters by accessing their own master database, 3rd party sources, and validation process. This results in happier consumers, more efficient internal stakeholders, and a reduction in compliance risks. Don't be burdened by provider data management. Let us take care of your provider network data hosting, benchmarking, cleansing, and roster management.