Healthy Data for Better Healthcare

Cassidy Littleton | Address Verification, Article, Clinical Data Quality, Duplicate Elimination, Healthcare Data Management, Web API | , ,

Evaluating and maintaining data quality is complex in any industry. However, the uniquely complex and non-stop aspects of healthcare data management complicate the process significantly. Characterized by a steady stream of patient records and evolving contact points, information must be managed effectively within a deep well of legacy data. Coding and filing claims, and constant updating of medical records, are prime examples of routine data-entry points that can very quickly degrade the quality and resulting effectiveness of an organization’s database. Administrators and overall health networks are further challenged by socioeconomic changes in healthcare plans and federal requirements for compliance with data security and privacy.

Preventive medicine is often the best approach, and it’s no different in sustaining healthy data. Long-term success requires implementing a data-quality firewall that provides instantaneous, point-of-entry data-cleaning tools that prevent bad data from entering the database in the first place. From there, a healthy regimen of ongoing data-quality processes is advised, as even good data changes and degrades over time. Data simply isn’t stagnant, and providers must manage clinical and business processes effectively with the right on-site data-quality tools.

Nonstop data requires nonstop data quality

“Assuming the data is ‘just fine’ is not a sufficient data-quality program for a vibrant healthcare system. In fact, committing to data quality is an essential initiative, as administrators and practitioners alike rely heavily on the constant flow and high volume of shared information,” says Andy Hayler, CEO of analyst firm The Information Difference. “Clinicians may be primarily concerned with providing top-notch care, but today that is driven significantly by telemedicine and electronic communications. Recognizing the value of accurate data in this process is helping to improve treatment, diagnosis and overall patient health.”

On-site data-quality solutions enable effective maintenance of patient data, while allowing providers to meet privacy and compliance guidelines securely, thoroughly and automatically.

Achieving a single view of the customer (the patient, in this case) requires clean, standardized data that effectively matches, links and purges records. Simple problems arise, such as “householding,” in which residents of the same home may share the same surnames, be a party to divorce or even have changed names. Solving these basic issues at the point of data entry is optimal.

The flux of data is staggering, with more than 43 million Americans (one in six) moving annually and as many as 33 percent skipping the step of updating their address records. These basic challenges represent data that degrades very quickly, especially for healthcare facilities attempting to provide patient care to a moving target. Has marriage or divorce resulted in a name change? Are data fields combining or separating first and last names? Does the patient reside on 12th Avenue or Twelfth Street? Published research from The Data Warehousing Institute indicates that these types of common inaccuracies account for nearly 76 percent of data-quality errors. The wave of bad data can grow quickly, especially when you factor in daily changes in U.S. carrier routes and the more than 100,000 changes monthly to the USPS address data file such as additions, deletions and modifications.

Because a patient’s well-being relies in part on data integrity, healthcare organizations are moving to develop policies of routine updating and verification of information. Ongoing data hygiene is reflected in accurate patient records and is achieved with incremental as well as batch prevention of new duplicate records. Simple mistakes such as typos or improper formatting (Are we last name first? Do we ever combine data fields?) can be eliminated, preventing duplicate records entirely. When providers implement the correct data tool, they streamline and fine-tune data operations by reducing excessive rules-based matching and replacing it with state-of-the-art matching algorithms. This sophisticated level of data hygiene has business value far beyond patient care, consolidating master data into individual and unique customer records, reducing printing and mailing costs for providers.

Taking an enterprise approach to healthcare data management

Healthcare providers are meeting these data goals by integrating dedicated servers to house contact-data verification and enrichment programs. Standard data fields such as name and address can be associated with customized information determined to be of specific value to the provider. Verifying this information (name, old and new addresses, phone, e-mail, name parsing, geocoding and more) can result in managing millions of records hourly. Such high-level data demands are ideally handled with dedicated computer power that enables enterprise-level speed and processing.

Bad data can result in duplicate records, returned mail and costly errors in patient communications. Melissa’s Data Quality Suite is a toolkit of APIs that works to standardize, verify and correct addresses, telephone numbers, e-mail addresses and names so practitioners have clean, usable patient contact data on an ongoing basis.

These same systems that handle data processing so efficiently also allow providers to cluster operations with other systems and devices, increasing scalability, throughput and redundancy. Processes can be automated by implementing “smart scripts,” automatically collecting and installing the most current contact datasets on a predetermined weekly, monthly or quarterly basis.

Further, privacy and compliance needs can be met and any real-time failover can be addressed quickly by hosting a data-quality server on-site. “While managing patient data for the most effective treatment and care, healthcare providers must also meet security and compliance guidelines established by HIPAA, Sarbanes-Oxley and other regulations,” says Hayler. “These are significant drivers that have providers embracing data quality as a business necessity, made easier by the ability to enrich, scrub and validate data entirely within their own operational network.”

Keeping data fit for the long term

Healthcare systems are rising to place greater value on the power of data by identifying patients properly, channeling communications effectively and integrating patient information from a range of varied sources. These functions may seem like the basics for major healthcare organizations, but they’ve never been more important as providers are facing ongoing shifts in technology, a focus on accommodating an aging population and healthcare costs that are increasing steadily. On-site data-quality operations are helping medical professionals manage data quality automatically and securely — complementing privacy and compliance requirements and keeping clinicians focused on delivering excellent patient care.

This article was originally published in Healthcare Innovation here.

Melissa Unlocks Insight and Revenue with Breakthrough AI Tools for Clinics and Research Centers

Author | Clinical Data Quality, Healthcare Data Management, Machine Learning, Machine Reasoning, Melissa Informatics, News & Events, Press Release, Product Launch | , , , , , , , , , , , ,

Cutting Edge Data Quality Transforms Real-World Clinical Data into a Future-Proofed, Research-Ready Data Goldmine for Better Patient Care

Melissa, a leading provider of global contact data quality and identity verification solutions, today announced advanced artificial intelligence (AI) solutions that combine machine reasoning, natural language processing, and machine learning to tackle one of healthcare’s biggest problems: the time and cost of data harmonization and integration.

Hospitals, clinical care, and clinical research organizations are sitting on a veritable data goldmine, based on data gathered for years from electronic medical records (EMR), electronic health records (EHR), and laboratory information management systems (LIMS). While this real-world clinical data is unusually valuable, it is also unusually complex and diverse. Melissa Informatics’ Sentient (MIS) solution is a new and unique set of clinical data quality and integration tools that quickly and easily turn diverse, dirty, and disconnected data into a clean, research-ready data resource. Melissa Informatics has laid out the company’s easy-to-follow steps to turn clinical data into a future-proofed, AI-enabled “knowledgebase” in its newest paper, “The Six-Step Guide to Turn Clinical Data into Gold,” downloadable here.

“Too often, clinical data is expensively gathered and under-valued,” said Bob Stanley, senior director, customer projects, Melissa Informatics. “When you apply machine learning and machine reasoning to access, curate, and integrate this data, it becomes ready for rewarding new uses in patient care, precision medicine research, intellectual property, and unexpected new revenue.”

Melissa Informatics further demonstrates the value of AI-enabled data quality by providing real-world use cases from world-renowned clinics including Parkinson’s Institute and Clinical Center (PICC) and PROOF Centre.

Using Melissa Informatics MIS technology, PICC transformed data such as unstructured text, XML, tables, tsv, image content and other data formats into a research quality, well-managed data resource. This helped the organization meet its technical goals including creating a new, unified “Parkinson’s Insight” data resource – as well as its business goals, including researching and publishing discoveries from that data, and engaging in revenue-generating partnerships based on the new data resource. Access the full case study here.

PROOF Centre used MIS tools to better understand and model connections between desired data sources, working under PIPEDA, HIPAA, Safe Harbor and EMEA requirements for handling of confidential patient data. MIS enabled a global platform for integrated search and reporting, analytics, and knowledge creation and sharing. This project integrated diseases, treatments, outcomes, tissue bank information, laboratory data, molecular data from blood (gene expression, proteins, metabolites), and published data. Access the full case study here.

Melissa Informatics Advances Big Data Promise with Semantics and Machine Reasoning

Melissa Team | Big Data, Clinical Data Quality, Data Cleansing, Data Enhancement, Data Enrichment, Data Management, Data Quality, Healthcare Data Management

Free Webinar Features Enterprise Data Curation and Integration to Extract Value from Complex Data Lakes

Melissa, a leading provider of global contact data quality and identity verification solutions, today announced its informatics division, Melissa Informatics, is advancing the promise of big data using semantic technologies and machine reasoning. These tools help break through enterprise bottlenecks by enabling targeted data curation, integration, and interoperability of complex data. Melissa Informatics will introduce semantic technologies and demonstrate their role in improving data quality, integration, and enrichment in complex data environments in a new webinar titled “Make Your Data Lake Great Again.” Register here for this interactive online discussion, slated for Wednesday, June 27, 2018, at 11:00 a.m. Pacific/2:00 p.m. Eastern.

Attendees will gain a better understanding of challenges and costs associated with traditional data cleansing and integration methods, as well as how to use advanced NoSQL databases, ontology-enabled machine reasoning, and global semantics standards for data interoperability. Industry takeaways include:

  • How to define semantic technology and its applications
  • How to clean, connect, and access mission-critical data more effectively
  • A look at the World Wide Web Consortium, exploring standards and shared goals for global data, interoperability among applications, and strategies for addressing enterprise bottlenecks
  • How, why, and when to use advanced ontology-enabled machine reasoning, illustrated with a live demo

“As industries such as health sciences face complex, changing data requirements, semantics and machine reasoning is becoming critical to realizing research and business goals,” said Bob Stanley, senior director, customer projects, Melissa Informatics. “The right enterprise data strategies not only reduce risk, time, and cost, but also reveal much greater value by creating interoperability with existing data that is underused and hidden in applications, files, and databases.”

Click here to register for this free webinar. To connect with members of Melissa’s informatics or global intelligence team, visit or call 1-800-MELISSA.

 About Melissa

Since 1985, Melissa has specialized in global intelligence solutions to help organizations unlock accurate data for a more compelling customer view. More than 10,000 clients worldwide in arenas such as retail, education, healthcare, insurance, finance, and government, rely on Melissa for full spectrum data quality and ID verification software, including data matching, validation, and enhancement services to gain critical insight and drive meaningful customer relationships. For more information or free product trials, visit or call 1-800-MELISSA (635-4772).

About Melissa Informatics

Melissa Informatics extends the capabilities of Melissa’s global intelligence software and services to support world leaders in life sciences, biotechnology, pharmaceutical, and medical industries by harnessing the entire data lifecycle for business, pharmaceutical and clinical data. Our software and services bring data quality and machine reasoning together for insight and discovery by intelligently cleaning, connecting, and harmonizing multiple sources to offer interoperable data. Melissa Informatics reduces time and cost to benefit from clean, richly connected data. Revealing deeper data relationships from complex, dynamic data through machine reasoning operations, Melissa Informatics ensures the most reliable information in mission critical financial services, healthcare, and life science informatics. For more information or free product trials, visit or call 1-800-MELISSA (635-4772).