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Winter 2022

Health IT Happenings: Automated Data Collection Can Improve Information Sharing
By Mike Taylor
For The Record
Vol. 34 No. 1 P. 30

Before the advent of EHRs, health care data were largely confined to file folders and banker’s boxes. Now with the industry adopting e-health systems, anchored by EHRs, health care professionals are exploring the new frontier of data analytics. When implementing an e-health application, regardless of size, a systemic approach is necessary to account for the technical factors that impact the system's success.

The biggest technical challenge is creating connectivity between a new system and the existing environment. Lack of plug-and-play interoperability can result in an incomplete picture of the patient’s health status and could be detrimental to patient care. Any information deficit can dramatically affect a patient’s safety and often increases the overall cost of care. When attempting to gather a more complete understanding of the patient’s conditions, health care organizations often struggle with manual interoperability challenges.

In this manual world, even insignificant errors can have a major downstream impact. For example, should a piece of information be indexed to the wrong patient in the EHR, there will be obvious implications for patient care in addition to liability concerns. Treatment decisions may be made based on that document, triggering a string of potential adverse events involving health outcomes, the organization’s reputation, and more. In addition, the error may be compounded if that record is shared with other parties outside of the organization.

Don’t Hurt Yourself
Data quality problems can sometimes be traced to manual processes. For example, many organizations continue to scan paper records, an approach that can turn routine tasks such as postdischarge procedures into a hassle. If a patient who was in the hospital for a couple of days requires special instructions, tests, and treatments, it may take several days before his or her records are scanned and available.

Inside the organization, manual processes can make information sharing cumbersome. For example, a radiologist with a need to access a patient’s file may be forced to walk to the nurses’ station on the patient’s floor.

In the face of this dilemma, some organizations decide to bypass the HIM department and process documents throughout the organization. However, once HIM professionals are removed from the equation, the opportunities for error multiply quickly.

The situation may devolve into chaos with staff out on the floors scouring other departments in an attempt to keep records current and available while trying to follow a bunch of unfamiliar rules to find the right document type, deal with patient labels, and so on. The idea that someone whose main job is to deliver health care is going to spend significant time on a set of manual tasks that have no apparent connection to the care of their patient is a recipe for poor patient care. Error rates skyrocket and, in many cases, organizations just abandon the experiment.

Enter Technology
The good news for HIM leaders is technology exists to tackle the issue of incomplete information due to data system interoperability challenges. Software solutions can act as a universal conduit for patient information, helping providers gather and organize data across the health system. Select applications can receive health information from numerous sources, in many formats, using provider-specific rules to help automate the information collection process. During the process of ingesting data, the information is stored according to prescribed rules and placed in the “right” areas in the medical record, usually the EHR.

Although many health systems made a significant investment in state-of-the-art EHR systems such as Epic and Cerner, there are data that are difficult for these systems to collect and organize. Often, patient data are provided in paper form or via fax. Now technology captures these data, applies prescribed rules for organizing purposes, and automates much of the information processing.

Applications can accept electronic data and route them to the appropriate area of the EHR. Some information, whether in paper, fax, or electronic form, is routed to a queue where HIM professionals can review it before incorporating it into the record.

With these technologically enabled processes, HIM professionals can organize patient information more quickly. After the initial rules are agreed upon, technology eliminates the need to undertake the labor-intensive task of classifying information gathered manually from several sources.

Leading applications use natural language processing and optical character recognition to convert and organize patient data. In some cases, artificial intelligence and machine learning also are incorporated to streamline workflows based on the rules and guidelines of that particular health system.

By leveraging these technologies, the cost of information processing is significantly reduced, eliminating delays caused by manual data classification while improving data quality.

Implementation of this technology can also provide a boost to EHR usability, a topic drawing a lot of attention throughout the industry. One of the great things about the major EHR packages is that they can be customized to meet a health system’s unique workflow. The downside, however, is that this often results in the same piece of information being treated differently across health care systems—even if they use the same EHR. As a result, it’s difficult for each organization to map that information to line it up with their internal nomenclature. It may all be in the same domain, but that doesn’t necessarily translate to it being straightforward. Even if organizations use the same terminology, there may be complex nuances when it comes to which data are captured, who gets notified, etc.

Most health care leaders understand the value of reliable, quality data and their impact across the care continuum. Astute CFOs know it has been an issue in the HIM department for many years. When true data interoperability is added to their initial understanding of data integrity and accuracy, the value proposition becomes even more apparent.

There are numerous success stories of health systems that have implemented technology to automate the collection and categorization of patient records. As the complexity of health information increases, more health systems can benefit from this approach and reap the rewards of reduced operational costs, higher-quality patient records, and improved physician satisfaction.

— Mike Taylor is vice president of marketing at Solarity.