Newark Beth Israel Medical Center to Automate Scanning and Coding of Patient Records with Artificial Medical Intelligences’ EMscribe DX

System to Decrease DNFB by 3-5 Days, Increase Revenues and Efficiencies; Dolbey to Demo Fusion CAC Powered by EMscribe at AHIMA

 

SEATTLE– (BUSINESS WIRE) — Artificial Medical Intelligence (AMI) today announced that Newark Beth Israel Medical Center, part of the Saint Barnabas Health Care System, is implementing its EMscribeTM DX computer assisted coding (CAC) solution to automate the coding of its inpatient and outpatient records for streamlined billing and coding efficiencies.

Interested parties can see demonstrations of Fusion CAC Powered by EMscribeTM on the AHIMA trade show floor at Dolbey booth #413. Dolbey markets AMIs EMscribe under the Fusion CAC name.

EMscribe DX is a comprehensive CAC technology that scans the entire patient record for appropriate ICD9-CM diagnostic and procedure codes and CPT codes using innovative language processing technology. Its patent-pending algorithmic software electronically analyzes entire medical charts to pre-code with both CPT procedure and ICD9 diagnostic nomenclatures. Manual coders, enhanced with the results of EMscribe can easily approve or amend the automatic results and increase efficiencies by as much as 80%.

Newark Beth Israel Medical Center is using the EMscribe system to replace its manual coding process which requires staff to physically retrieve medical documents and enter code information into the system redundantly. Medical coding is the means of translating a patients medical chart into numeric codes so that providers can receive reimbursement appropriately. Presently, this manual process requires skilled practitioners, already in high demand, to manually read documents and laboriously key in the medical billing codes.

After implementing EMscribe, the hospitals medial coding process will significantly change because the AMI solution will automatically suggest appropriate ICD9 or procedure codes to staff coders. Coders will then approve the suitable codes and send the patient charts to the billing system. The hospital expects the system to significantly improve the efficiency and consistency of human coders while reducing the amount of time between when a patient is discharged and when billing is completealso known as the discharged not final billed (DNFB) window by 3-5 days. It also expects to save considerable costs from reducing its dependency on outsourced coding.

A proficient revenue cycle scheduling, quality coding, billing and a good denial management program is vital to the operational success of any hospital, said Mitch Blume, administrative director patient financial services at Newark Beth Israel Medical Center. “The technology behind EMscribe is helping us to dramatically improve the efficiency and quality of our medical coding process. This in turn reduces billing cycle time and ultimately contributes real savings to our bottom line. We want to do everything right the first time around so that we can produce clean claims and secure positive cash flow for the hospital on an ongoing basis.

Hospitals like Newark Beth Israel Medical Center are beginning to recognize that an effective claims management program can counter the continuing effects of declining payments and increasing cost pressures, said Stuart Covit, executive vice president of Artificial Medical Intelligence. Inadequate information technology and changes in billing and coding guidelines can all contribute to a high rate of claim denials. The EMscribe technology is the answer for hospitals like Newark Beth Israel that require a more efficient medical record coding process so that they can provide better service to patients, doctors and providers and improve billing and claim management.

Newark Beth Israel Medical Center will be implementing EMscribe throughout all departments that can utilize the improved coding system.

About Dolbey

Dolbey is a leader in providing dictation, transcription, speech recognition and coding solutions for healthcare in the United States and Canada. Together, Dolbey and Company, Inc. and Dolbey Systems, Inc. offer the award winning Fusion Suite of integrated products which is backed by the industrys largest organization of certified professionals who assist in design, implementation and support.

About AMI

Founded in 2002, Artificial Medical Intelligence http://www.artificialmed.com) is a healthcare informatics software developer, focusing on increasing efficiency within Health Information Management. Its patented core solution, EMscribeTM Dx, provides suggested ICD9-CM and CPT codes for both the inpatient and outpatient encounter. The innovative solution also functions as an information abstraction engine, automating such values as Present On Admission, (POA), and drug abstractions, as well as a new Recovery Re-submission module plus other customized data abstractions, thus making it the most comprehensive hospital tested HIM-Coding solution available. AMIs solutions are targeted at hospital healthcare facilities, communicating seamlessly with all hospital systems, as well as larger clinics and physician practices that are looking to automate process management and improve the processing of medical documents. AMI can also help customers achieve the goal of creating a complete electronic medical record. The company is headquartered in Eatontown, New Jersey.

Computer Assisted Coding: Is the Future Here?

Vol. 15 •Issue 5 • Page 22
Computer Assisted Coding: Is the Future Here?

We’re already coding with encoders and handheld charge capture devices. When we get to computer assisted coding (CAC), will we need coders?

Take a look at the North Star in a telescope, a mere 430 light years from earth. Maybe it makes you consider events that can happen in the space of time, and how far advanced we are technologically (some fields more so than others). On a much smaller scale, HIM has seen significant innovations within the past 20 years. Many HIM departments use encoders to help coders assign codes. Clinics and hospitals are seeing physicians use mobile charge capture devices that help them document and code at the point of care. Now take a look through HIM’s telescope. Is computer assisted coding (CAC) that far off? There’s already talk of using artificial intelligence (AI) to automatically assign codes. If this is the future, what role do coders play in it?

 

Stardate 2005: Encoders

It’s not uncommon today to encounter automation within the coding process. Consider the logic or rules-based encoders in hospital HIM departments today. While not automatically assigning codes, “The encoder is a tool you would use, just as a code book is a tool,” said Mary Stanfill, RHIA, CCS, CCS-P, professional practice manger, HIM products and services for the American Health Information Management Association (AHIMA). “It just so happens to be a much more slick, computerized tool.”

In fact, it’s a code book and a whole lot more.

“We have a team of nosologists or coding experts whose primary job is to incorporate clinical content in our encoder product,” explained Ann Frischkorn, MBA, RHIA, product line manager, coding and classification solutions, 3M Health Information Services in Salt Lake City. “Once the coder enters a diagnosis or procedure description, Frischkorn explained, he/she is prompted with a series of questions to answer to derive the best code. For example, “A coder might put in a diagnosis of pneumonia and the system will offer a list of specific pneumonia related diagnoses.”

The encoder is stocked with information from the American Hospital Association’s Coding Clinic, the American Medical Association’s CPT Assistant, Centers for Medicare and Medicaid Services (CMS) publications and information from 3M’s “nosology hotline,” which clients can call when they come across something new.

But if it can’t code for you, can it at least supplement coders’ knowledge?

“Even within an HIM department there are coders with varying levels of experience who can get value out of using encoder software,” said Frischkorn. “The key to successful coding is more than just the tool. Coding is an art and a science, the science of using the software product, but also the art of understanding what a physician is trying to say in the documentation. It’s almost like you’re a detective when you’re coding.”

Surely we can automate away such mysteries, right?

 

Stardate 2005: Charge Capture

Charge capture is talked about in relation to the revenue cycle, the idea being that the quicker documentation is captured and coded, the faster the provider gets paid, according to David Delaney, MD, vice president of business development for Boston-based MedAptus Inc.

“What our product does is provide a tool for clinicians to have an easy means of capturing the information to generate a charge at the point of service,” Dr. Delaney explained. “Another thing it does is check charges against correct coding initiative rules and LMRPs at the time of entry, flagging any issues for providers to correct, real-time.”

But charge capture also impacts coding, as demonstrated at the Lahey Clinic in Burlington, MA, where some 3,000 patients a day are treated on an outpatient basis by 600 providers, of whom 225 are using the MedAptus system.

“We have 48 coders located out in the clinical areas very close to where the physicians do the outpatient visits. They work elbow to elbow with the physicians, provide education and feedback, and do audits to measure for compliance,” said Cynthia A. Trapp, CHFP, CMPE, CPC, CCS-P, director of professional coding at Lahey. Her coders are using the MedAptus system alongside the physicians. “Physicians will code with the MedAptus software, and then coders will review any edits they find. They have a PC companion that mirrors pretty closely what the physician is doing.”

Although it’s not uncommon for physicians to code their own documentation in this setting, Trapp explained, the movement to this automation has streamlined the coders’ work. “Before we had this automated process, everything was done on paper. The physicians would have an encounter form or billing ticket they would check off with a finite list of [procedure and diagnosis] codes that would get batched up at the end of the day.” The coders would review the batches as necessary and the batches would get sent off to billing, Trapp added.

While the clinic hasn’t eliminated coders with the automated process, “We have been able to eliminate the charge entry function in these areas, thus allowing us to redeploy charge entry staff into other roles,” said Trapp. But it has reduced some of the coders’ remedial tasks. In addition, “We’ve seen an increase in communication and collaboration between the physician and the coder to be much more accurate and compliant. It has been a tool for both parties, to ensure accurate coding,” she observed.

According to Dr. Delaney, the MedAptus solution is used in inpatient settings as well. In addition, his company has numerous vendor partnerships, enabling end-users to benefit from integrated clinical applications such as e-prescribing and dictation.

But while this is integrated, automated workflow that helps coders, it’s not quite CAC.

 

AI: Is the Future Now?

AHIMA’s Stanfill thinks CAC is just a matter of time—the question is how much time. Given AHIMA’s recent workgroup study on the topic (see Journal of AHIMA/Nov-Dec 2004), she begins by explaining why the association prefers the CAC acronym to “automated or “automatic” coding.

“Automatic implies there’s no human intervention,” said Stanfill. Based on conclusions from volunteers including vendors, users, informaticists, physicians and individuals in the field of natural language processing (NLP), “They agreed that today there is no fully automated system to assign codes,” said Stanfill. “Even when you talk to the vendors developing software applications that can automatically suggest codes, they all recommend you get the codes reviewed and edited by a person.”

That said, there have been inroads on the AI end. Just talk to Andrew B. Covit, MD, CEO of Artificial Medical Intelligence Inc. in Eatontown, NJ. Discussing his EMscribe Dx product, he explained, “It scans a document, identifies key words or phrases that define a given coding opportunity and matches them to appropriate ICD-9 codes. In addition, EMscribe effectively avoids overcoding by applying the product’s built-in rules that effectively block the code match in certain key situations.”

By employing a variation of NLP, “We capture how physicians speak, their medical ’slanguage’” said Dr. Covit. For example, “The standard dictionary has many different terms for ‘acute heart attack’ or ‘myocardial infarction,’ however most doctors do not speak using the official terminology. They may say that the patient is suffering from an ‘acute MI’ or a ‘new infarct’ but they are slang terms that are not listed in the ICD-9 terminology.” With AMI’s EMscribe product, “We’ve augmented the dictionary to be able to recognize those slang terms to make the solution realistic and useful in the real world,” Dr. Covit said.

“It’s taken us 3 years’ worth of development to get to the point where we are now capable of automating the coding process,” added Stuart Covit, executive vice president for marketing and administration for AMI. “We’re now confident about the reliability and computing powers this product offers.”

AMI says their technology is ripe for either the physician office setting or an acute care hospital. EMscribe DX is currently in beta testing at Robert Wood Johnson University Hospital in Brunswick, NJ, and the product was officially launched at the Healthcare Information and Management Systems Society conference in Dallas Feb. 13-17.

Of course, NLP-like solutions aren’t the only ones to hit the showroom floor.

 

Is the Future Structured?

Known as structured input or codified input, AHIMA’s Stanfill explained, “Structure doesn’t use NLP at all. With a structured input type of system, it’s driven by the health care provider who is documenting care.” These systems work on the same concept as macros,” she explained. For example, Stanfill offered, “Anybody who codes colonoscopies can tell you that doctors always do certain steps and in certain orders.” With preset menus for things such as anesthesia, prepping and draping, and insertion of scope, “The structured input approach capitalizes on that routine.”

The AHIMA workgroup found some structured input systems being utilized in specialty physicians groups such as gastroenterology. “They focused on CPT coding in this system because the procedures are very defined, fairly predictable steps,” said Stanfill.

As with NLP, Stanfill added, “Neither of these technologies are totally futuristic ‘Star Trek’ kinds of things, but their use is limited in health care,” said Stanfill, who added that one prerequisite to either technology is fully electronic text.

Beyond that is, of course, the electronic health record (EHR), something that both Stanfill and Frischkorn agree will move CAC forward.

Frischkorn sees it pushing structured coding. “I think with the movement toward EHRs, you’ll see more structured text output. Right now I’m seeing more NLP than structured text, but that will shift as we move forward.”

If the technology could go either way, one might question where this leaves the coders.

 

Domo Arigato, Coder Roboto

Technological innovations do change jobs. Trapp recalls when she introduced automated charge capture to her coding staff back in 2001. “At first the coders were afraid,” said Trapp. “They wanted to know: What is going to happen to our jobs?” Their roles have changed, but certainly they haven’t been eliminated. Nor does Trapp see a day when that would happen.

“I think because the intensity and complexity of coding is growing so much that, even with an automated system, you have to have skilled people who are going to review what is being [generated] in the system before it’s billed out.”

And after working with NLP, even AMI’s Covit doesn’t discount the role of the coder. “We believe there should always be some form of human intervention, be it at an administrator level or whatever. The fact of the matter is, there needs to be human intervention in this process at some point,” he said.

“I’ve seen NLP more in the professional setting as opposed to the inpatient setting,” commented 3M’s Frischkorn. “Depending on who you talk to, errors can range from 10 percent to 50 percent.” She compares NLP to speech recognition technology and the impact it has had on the job of MTs.

“Many MTs have gone from typing to becoming editors/experts on what is deemed a good transcribed report. The same thing will happen with coders. But I don’t see the validation role ever going away. Whether it’s structured or unstructured, I think the skill sets of the coders will need to expand even more than what they are now.” From Frischkorn’s perspective, “The computer will take care of coding standard mammograms and other repetitive procedures, but the coder will need to audit the coding and work with the physician, probably even more so than what’s required today.”

Nonetheless, “It will probably be a while before we see these systems in the inpatient environment,” said Stanfill. “We need electronic text and systems designed to be able to handle multiple inputs from multiple health care providers. Now we’re seeing them in specific pockets of outpatient reporting.”

Trapp added, “I haven’t seen a [CAC] system that’s gotten it perfect. The language might lead you to use one code, but to use codes you really have to understand that language.”

Stanfill agreed, but added, “We’ll get there. It’s not if, but when. I don’t know that I can say when that will be, but when we do, it’s going to be awesome.”

Linda Gross is an associate editor at ADVANCE.

Gaining a Coded Edge

Radiology Group, PC, SC, is a practice of 13 radiologists in Davenport, Iowa. The practice owns the Radiology Group Imaging Center, one of the most comprehensive imaging facilities in Iowa and Western Illinois.

To maximize growth, Radiology Group decided in 2000 to spin off its billing function into a separate company, P2P Medical Management, now Radiology Billing and Coding Specialists, LLC (RBCS).

RBCS independently provides services to radiology practices and physician groups, processing nearly 320,000 reports annually for clients across numerous hospitals and outpatient sites. As it grew, a paper-based coding process and chronic coder shortage created a bottleneck, limiting the operation’s ability to grow further.

“We received all reports on paper, with codes handwritten on them by our coders,” says Melissa Wagler, RBCS’ billing office manager. “We were always about four weeks behind in coding. If one of our coders took any time off, we fell even further behind.” 

The reverberations of the coding backlog extended to other operational areas. Redirecting resources to handle the backlog meant other billing staff had less time to devote to denials, quality assurance, and other account activities.

A Coder’s Perspective on Computer-Assisted Coding Software

A Coder’s Perspective on Computer-Assisted Coding Software
By Greg Schnitzer, RN, CCS, CCS-P, CPC, CPC-H, RCC, CHC
Radiology Today
Vol. 9 No. 9 P. 34

For nearly a decade, computed-assisted coding (CAC) software has been available to help coders. So what is this software all about, and how does it help?

CAC software is used to “read” dictated and transcribed documents that are in an electronic format, much the same way a spell-checking program reads a document. The software recognizes words and phrases, as well as the regions of the document in which those words and phrases appear, and the contexts of those words and phrases. It then “predicts” through intricate statistical analysis, elaborate algorithms and rules, or a combination of the two what the proper CPT and ICD-9-CM codes should be for the procedures and conditions it finds.

Using CAC
A radiology group or a billing company, for example, contracts with a CAC software coding companies and arranges for its dictated and transcribed radiology reports to be sent electronically to the CAC company via the Internet. The CAC company then submits the reports to its coding software server. The coded reports will either be sent back to the provider where they can be reviewed by a coder with a Web browser or straight to the provider’s billing system, if the organization is comfortable with certain types of reports bypassing a coder for review.

Typically, the interface that a coder uses displays the note on one side of the screen and the automatically assigned codes on the other. The coder uses this interface to review the notes, look at the codes assigned by the software, make any necessary coding changes, and then approve the report to go into the billing system. Afterward, the coder is instantly provided with the next note for review.

Because this is generally done via the Internet, the coding process can be decentralized, and the coder could be working from anywhere. This opens up new possibilities for organizations looking for top talent, enabling them to hire from any location. At the same time, it frees coders to live and work wherever they prefer.

Additionally, sophisticated natural language processing systems modernize compliance efforts and internal audits, both concurrently and retroactively examining the flow of information for correct codes, poor dictation, and other issues that can muddle the process.

How Does It Work
Sophisticated CAC software is not based solely on key words appearing in a document. To be a valuable tool for the coder, it must be more advanced than that. It must be able to determine when a procedure or condition appears in a context that allows it to be coded vs. where it should not be coded.

For example, consider the following sentences that would appear in a typical radiology note:

1. I see a coin lesion on the patient’s left lung.

2. The patient’s father has a coin lesion on the left lung.

3. I have confirmed that the coin lesion is now absent in the patient’s left lung.

4. I have ruled out the presence of a coin lesion on the patient’s left lung.

5. There is a questionable coin lesion on the patient’s left lung.

Few coders would have trouble determining that while the coin lesion is codable in the first example, it would not be codable in the other examples. Clearly, recognizing the mere presence of the words “coin lesion” is insufficient to code the note correctly. While coding a condition is relatively easy, CAC software must be sophisticated enough to recognize myriad contexts where a phrase like coin lesion may not actually be a codable condition.

How can software recognize and know when the condition appears in a codable context or noncodable context? The short answer is that there are different computational approaches. Books could be (and have been) written about computational linguistics and natural language processing, as well as how software can be taught to “understand” language patterns and make predictions based on similar documents it has seen in the past. In essence, CAC software, supported by natural language processing, coaches computers to understand the English language and read physicians’ dictated reports to assign appropriate codes for patient encounters. Sophisticated software algorithms are written and millions of coded notes are analyzed by a computer to see how human coders coded the notes. Based on all the coding humans did, the software statistically predicts and learns to emulate a team of coders.

So what does this all mean for a coder? In its first decade of actual use for coding physicians’ notes, the magic that CAC software performs has become more elaborate. Early on, CAC software involved the simplest of notes such as routine mammograms, chest x-rays, and x-rays of a limb to evaluate a fracture. The technology could accurately assign those codes without a coder’s review. Using CAC can reduce the demands on human coders by removing their involvement in simple and repetitive coding tasks.

Candidly, most coders—including me—would be glad to be rid of these radiology reports. Not only are these notes the low hanging fruit of coding, they’re also the drudgery of coding. For a coder, working with a CAC software tool can mean the difference between coding their 200th screening mammography report of the day or spending their time with the more interesting and complex reports.

CAC software has become a valuable coding tool, just as encoders became valuable tools 20 years ago. But be forewarned, like virtually every other industry, technology is changing how people work. Keeping up with the changes such as CAC helps coders continue to succeed and do their jobs even better. CAC elevates coders professionally, focusing on advanced coding work and offering experience in auditing and quality control, ultimately making coders more competitive in the market.