The American Health Information Management Association (AHIMA) announced today that Kona Community Hospital in Kealakekua, Hawai’i, has chosen to use the AHIMA library of physician query templates available in the mobile query platform from Artifact Health, an Iodine solution.
Originally published on Fierce Healthcare
Healthcare system survival pivots on many metrics, but the ability to generate revenue and to evidence high quality of care are two of the most essential.
At the center of both metrics is the clinical documentation process, where an accurate representation of every patient’s clinical experience while in a provider’s care must be recorded.
As simple as it may sound, achieving that accurate reflection of diagnoses, interventions and the clinical picture is anything but simple. Medicine is as much science as it is art, and complex definitions, levels of specificity and complex medical terminology mean that most hospitals struggle to document everything properly, leading to significant lost revenues and under-reporting on quality metrics.
Health systems have answered this challenge by standing up clinical documentation integrity (CDI) programs, staffed with clinicians. As more healthcare revenue is tied to achieving specific quality metrics, the role of CDI has become even more critical.
However, ensuring integrity and completeness of documentation would require health systems to staff CDI teams with an incredible amount of highly trained clinicians to review and correct documentation on every record, every day. The cost and complexity of such an operation is unimaginable, and no healthcare system has the resources to either employ that many people or even find a supply of that many highly specialized staff.
As a result, many health systems are turning to software to support CDI with technology that scales clinical staff abilities and provides intelligent automation. Unfortunately, the challenge that many have run into is how to identify the right technology for their operation.
All the work CDI specialists perform requires clinical knowledge—the sort of knowledge that is gained only after decades of academic study and real work experience. Automating that work means that the technology must mirror the same level of clinical thinking that any one of these specialists employs every day.
The challenge is immense. Emulating clinical thinking with software is among the loftiest goals of artificial intelligence in healthcare and requires the most sophisticated, cutting-edge technologies available—not to mention years of training. Even with the most advanced technology, AI has sometimes failed to impress the critics, as we’ve seen multiple reports call out the stumbles of larger ambitioned (but similarly conceptualized) efforts like IBM Watson.
But, while there are still areas for improvement, the truth is that AI still is making a significant impact across the healthcare landscape—and especially within CDI, where success is well documented.
While CDI is an excellent and proven use case for AI in healthcare, providers should understand that not all AI is the same. In fact, many legacy systems that deploy “the wrong type” of AI to CDI are unable to see all the gains possible with the correct deployment.
The key to leveraging AI in CDI is to utilize technology that can truly emulate the way clinicians think. It must read, digest, understand and make statistical predictions on the entirety of the clinical record similarly to how physicians look at all the evidence to assess and diagnose to appropriately provide patient care.
That’s where machine learning holds the key. Machine-learning is, at its heart, a pattern-recognition engine that can digest a plethora of individual pieces of data, recognize patterns and then use those patterns to make statistical predictions. If properly applied to clinical information, it is a very powerful technology. Fed over time with millions of patient encounters, machine learning begins to emulate the way clinicians think, automating numerous tasks or challenges that otherwise would only be solvable by a human. While it does not replace clinicians, it does reduce clinical staff burden, providing more time to be spent on patient care.
Additionally, by automatically the review of every patient record in real-time every day, cases can be prioritized so a CDI specialist knows what to look at—versus wasting time on those with no documentation irregularities. This type of machine learning interprets the clinical evidence, compares it to the existing documentation and highlights and prioritizes which cases have discrepancies automatically.
Many legacy applications attempt to use another AI technology, natural language processing (NLP), to automate complex clinical tasks. While NLP has some useful applications for tasks like clinical narration—where the dictionary-like “look up” function of NLP suggests a better or more accurate word—NLP is only a partial solution for CDI.
For example, NLP can translate the narrative documentation from the clinician into text understood by a computer. However, unless it’s paired with a machine learning solution that simultaneously reads and emulates clinical decision-making (thus enabling a comparison between what was written and what the clinical evidence says), it’s an inadequate solution to solving the core challenges in CDI.
Additionally, rules-based technology solutions that utilize “rules” or “markers” to automate clinical tasks fail entirely to emulate the way that clinicians think. As a result, they cannot reflect the many permutations of the way clinical conditions are presented.
Robotic process automation (RPA) is another buzzword in healthcare that has been cited as a tool for handling repeatable basic tasks. However, within the mid-revenue cycle (and thus CDI), nearly all tasks have a clinical element, requiring clinical understanding to complete. That means RPA definitionally is not suited for more complex tasks that require higher-level thinking.
Instead, intelligent process automation (IPA) is the right solution, as IPA applies machine learning to RPA to automate complex tasks that require human judgment (much like the work of CDI). Thus, to apply IPA in the revenue cycle, not only is machine learning critical, it also is the only technology available today that specifically emulates clinical thinking and judgment.
As technology gets better at emulating a clinician’s mind, increasingly powerful AI engines will soon be able to capture documentation and coding instantaneously. By accurately automating clinical condition documentation directly into EMRs and identifying the final code set, the process will become even more efficient and will have fewer translation errors.
Ultimately, that means smaller teams will be able to support the entire documentation process, which reduces costs for providers and stress on clinicians.
There is no doubt that managing a health system has become increasingly complex, and that’s especially true for CDI teams that must capture data accurately and efficiently. However, AI has become a critical tool that is truly making an impact in the mid-revenue cycle, and there is much more innovation to come in the next few years. But, while we wait for that larger revolution, it’s important that health systems implement a stable and efficient CDI program now, powered by the right technology.
By Cheryl Ericson, MS, RN, CCDS, CDIP
Let me start by saying I’m a proponent of organizational definitions. I have long advocated them as a Clinical Documentation Integrity (CDI) best practice, but I do think their purpose is frequently misunderstood. Although we like to think organizational definitions are a tool to minimize denials, they are really just an organization-wide strategy to promote consistency and have little to no bearing outside your organization.
Contrary to popular beliefs, Centers for Medicare & Medicaid Services (CMS) does not “define” conditions like sepsis or malnutrition or morbid obesity. CMS provides guidance around when a particular condition is considered medically necessary so it will be covered by Medicare through National Coverage Determinations (NCDs) (e.g., gastric bypass defining morbid obesity as a BMI of 35 with the presence of complications due to morbid obesity) or Local Coverage Determinations (LCDs). But these NCDs and LCDs do not necessarily “define” the referenced conditions when it comes to publicly reported data. The same is true for quality measures adopted by CMS.
The CMS Quality Measure titled “Severe Sepsis and Septic Shock: Management Bundle” supports best practice for the treatment of severe sepsis and septic shock which includes processes associated with Sequential Organ Failure Assessment (SOFA); however, the population eligible for this measure is defined by the assignment of either a sepsis or severe sepsis code. If you need evidence of a lack of CMS guidance defining a particular condition, look no further than the recent Office of the Inspector General (OIG) findings related to severe malnutrition where the OIG audited cases to “determine whether providers are complying with Medicare billing requirements when assigning diagnosis codes for the treatment of severe types of malnutrition on inpatient hospital claims” (https://oig.hhs.gov/reports-and-publications/workplan/summary/wp-summary-0000258.asp). It is even hard to pin down commercial payers other than CMS when it comes to defining conditions. Often organizations receive information informing them a diagnosis was removed with little, if any explanation, of the criteria used to make that determination.
So why bother with organizational definitions? To promote consistency across physicians, CDI professionals and Coding professionals. Often organizational definitions are a great way to engage physician leadership so they can become CDI advocates and to train CDIs. The reality is that making a diagnosis is a complex process and there is often disagreement across providers treating the same patient. Something else to consider is whether or not organizational definitions are too stringent and promote under-coding within an organization which can negatively impact financial goals. Just think about the debates that are occurring within the CDI profession over the use of Systemic Inflammatory Response Syndrome (SIRS) criteria vs. SOFA criteria for sepsis. Many organizations made the shift to SOFA criteria when it was first released only to return to SIRS criteria after the volume of sepsis cases decreased within their organization due to the stricter criteria. And what about those diagnoses that don’t have an organizational definition? What criteria should be used? Are we getting too bogged down in discussions about how to define a condition that we can’t see the forest from the trees? In fact, the whole concept of clinical criteria was such an issue within the CDI and Coding professions that the Official Coding Guidelines added the Coding Assignment and Clinical Criteria guideline a couple of years ago:
“The assignment of a diagnosis code is based on the provider’s diagnostic statement that the condition exists. The provider’s statement that the patient has a particular condition is sufficient. Code assignment is not based on clinical criteria used by the provider to establish the diagnosis.” (ICD-10-CM Official Guidelines for Coding and Reporting (FY 2021), Page 12 of 126).
Although this guideline was intended to provide clarity, I really think it just added another layer of confusion as some organizations mistook this advice as an excuse to stop clinically validating documented diagnoses. Really, this guideline only separated the coding function from the medical necessity function because those lines were getting blurred; however, the medical necessity requirement is still alive and well as demonstrated by OIG audits.
It was once believed that organizational definitions could be helpful from a compliance standpoint, but that only occurs when the definitions are consistently used across all payers and for all situations. Unfortunately, what I’ve seen over the years is that CDI professionals often have one rigorous set of criteria they use before querying for a potentially missing diagnosis and a different threshold for clinical validation e.g., if the provider documents a diagnosis based on limited criteria. I get it, most CFOs view CDI departments through a financial lens and few CDI departments want to be responsible for removing a diagnosis complication/comorbidity (CC) or major complication/comorbidity (MCC), but this inconsistency is confusing and increases compliance risk.
So that begs the question, “Have organizational definitions outlived their usefulness?” Perhaps it is time to re-evaluate the purpose of organizational definitions. Are they resulting in more harm than good? In particular, perform an analysis to determine if organizational definitions are yielding the desired impact, which is typically fewer denials. In addition, determine if organizational definitions have actually become a liability due to inconsistent application, or potentially leading to under-coding of valid diagnoses. Organizational definitions can be a great educational tool for CDI professionals, Coding professionals and providers, but they often have limited practical application outside of your organization, so be sure to evaluate their usefulness on a regular basis.
Wakefield, RI – (October 28, 2020) – ChartWise has unveiled NotePath, its latest innovation for the Clinical Documentation Integrity (CDI) market, bringing Natural Language Processing (NLP) and Artificial Intelligence (AI) together with the company’s flagship ChartWise CDI workflow application to improve accuracy, efficiency, and quality in the medical records of client hospitals, all powered by Microsoft Azure.
NotePath Smart Chart Review automatically finds, indexes, and presents clinical evidence and advice regarding initial working diagnoses, query suggestions, HCCs, patient safety indicators, co-morbidities, and other information. It also provides alerts to improve both the efficiency and accuracy of patient clinical documentation.
NotePath integrates with core ChartWise CDI software, allowing clinical documentation specialists to quickly and comprehensively review and identify critical clinical findings, medications, and lab results discovered through real-time, advanced NLP of all clinical documents in the EHR.
“The launch of NotePath and its Smart Chart Review functionality brings a new level of documentation integrity to our clients,” said Steven Mason, Jr., ChartWise President and CEO. “By identifying the clinical findings and alerting the CDI staff to the need for appropriate documentation, not only will hospitals obtain their appropriate reimbursements, but claims denials can also be prevented and quality scores improved. It’s a game-changer in the CDI market.”
ChartWise delivers software for the healthcare industry built on Azure to provide scalability and high performance while maintaining uptime availability. Chartwise uses Azure SQL for data architecture, and data analytics are driven by Microsoft Power BI to provide clients with the reports and insights they need to optimize their programs. A dedicated team of ChartWise experts helps ensure data security and integrity with HIPAA-compliant applications and databases.
“We are pleased to see how ChartWise has added value to their customers by integrating their solutions with Microsoft Azure. Hospitals operate on slim margins, and having revenue-impacting applications reliably available is critical to their success,” said Kevin Dolan, US Chief Alliance Officer, Microsoft Health and Life Sciences, Microsoft. “ChartWise applications allow its customers to take advantage of the flexibility and enterprise-grade reliability that Azure provides.”
ChartWise Medical Systems, Inc., based in Wakefield, R.I., is a premier, three-time KLAS award-winning CDI software provider of clinical documentation solutions for hospitals worldwide. Award-winning workflow and prioritization software, consulting, education services, and support provide outstanding return on investment, while improving quality. To learn more, contact us at sales@ChartWisemed.com or visit www.ChartWisemed.com.
MOBILE, Ala. (September 23, 2020) — CPSI (NASDAQ: CPSI), a healthcare solutions company, and ChartWise Medical Systems Inc. (ChartWise), a three-time best in KLAS award-winning computer-assisted clinical document improvement (CDI) company, today announced a partnership that will help healthcare organizations of all sizes improve clinical documentation accuracy and overall medical reimbursement.
To strategically manage costs, while also requiring improvements in the quality of patient care, payers continue to shift from fee-for-service to fee-for-value reimbursement models. However, providers struggle with incomplete or inaccurate documentation that often results in incorrect billing, reimbursement and quality reporting. By leveraging the ChartWise computer-assisted CDI software, physicians and clinical documentation specialists (CDS) have the tools and guidance necessary to improve documentation quality, resulting in reduced claim denials and more accurate reimbursement.
Dr. Jon Elion, founder of ChartWise, said, “We have spent the last 25 years focusing on technology innovations that help healthcare providers work smarter, not harder. ChartWise enables patient care to be delivered in a more efficient and effective manner, while empowering the clinicians and staff with the tools they need every day.”
“TruBridge provides end-to-end revenue cycle management products and services to healthcare organizations of all sizes,” said Chris Fowler, president of TruBridge. “Through this partnership with ChartWise, we will enhance our existing CDI service with the software and technology that will ultimately improve reimbursement for clients. With this electronic health record (EHR)-agnostic offering, we believe there will be real interest in the added value to the bottom line of many healthcare organizations – especially considering the current financial dynamics being experienced during the COVID-19 pandemic.”
Steven Mason, president and chief executive officer of ChartWise, said, “We are proud and excited to have a mutually beneficial partnership that will improve the value proposition of the TruBridge CDI offering. Our award-winning solution with built-in intelligent expertise guides physicians and CDS toward a complete diagnostic picture, automatically analyzing lab data, medications and procedures to help identify complications and additional diagnoses that have not been specified completely in the notes. The result is improved patient acuity determination, quality scores and revenue capture.”
About CPSI
CPSI is a leading provider of healthcare solutions and services for community hospitals, their clinics and post-acute care facilities. Founded in 1979, CPSI is the parent of four companies – Evident, LLC, American HealthTech, Inc., TruBridge, LLC, and iNetXperts, Corp. d/b/a Get Real Health. Our combined companies are focused on helping improve the health of the communities we serve, connecting communities for a better patient care experience, and improving the financial operations of our clients. Evident provides comprehensive EHR solutions for community hospitals and their affiliated clinics. American HealthTech is one of the nation’s largest providers of EHR solutions and services for post-acute care facilities. TruBridge focuses on providing business, consulting and managed IT services, along with its complete RCM solution, for all care settings. Get Real Health focuses on solutions aimed at improving patient engagement for individuals and healthcare providers. For more information, visit www.cpsi.com.
About TruBridge
TruBridge, a member of the CPSI family of companies, provides business and consulting services, and an end-to-end Revenue Cycle Management (RCM) solution. With our arsenal of RCM offerings that include a HFMA Peer Reviewed® product and an HMFA Peer Reviewed® complete outsourcing service, TruBridge helps hospitals, physician clinics, and skilled nursing organizations of all sizes become more efficient at serving their communities. For further information visit www.trubridge.com.
About ChartWise
ChartWise Medical Systems, Inc., based in Wakefield, RI, is a healthcare software firm and the developer of ChartWise CDI, a web-based solution for Computer-Assisted Clinical Documentation Improvement. ChartWise CDI’s built-in clinical intelligence and efficient workflow assists physicians and clinical documentation specialists with increased completeness and accuracy of documentation, risk-adjustment, reimbursement and quality scores. Developed by renowned physician Jon Elion, M.D., ChartWise CDI is the only clinical documentation software that translates clinical language used by physicians into accurate diagnostic language required for documentation and reimbursement. ChartWise CDI has provided a positive ROI between five (5) to eighteen (18) times the cost of the software for every client who has used ChartWise CDI. ChartWise was recognized in the 2016 and 2017 Inc. 5000 List as one of America’s fastest-growing private companies, placing first among all Rhode Island-based businesses on the list each year. ChartWise has also been a KLAS award winner for the CDI software category for three (3) consecutive years. For more information, visit www.chartwisemed.com.
Forward-Looking Statements
This press release contains forward-looking statements within the meaning of the “safe harbor” provisions of the Private Securities Litigation Reform Act of 1995. These forward-looking statements can be identified generally by the use of forward-looking terminology and words such as “expects,” “anticipates,” “estimates,” “believes,” “projects,” “targets,” “predicts,” “intends,” “plans,” “potential,” “may,” “continue,” “should,” “will” and words of comparable meaning. Without limiting the generality of the preceding statement, all statements in this press release relating to the prospects of CPSI’s partnership with ChartWise are forward-looking statements. We caution investors that any such forward-looking statements are only predictions and are not guarantees of future performance. Certain risks, uncertainties and other factors may cause actual results to differ materially from those projected in the forward-looking statements. Such factors may include: risks related to TruBridge’s ability to successfully leverage ChartWise’s computer-assisted CDI software to improve reimbursement for, and add value to, healthcare organizations; the impact of COVID-19 and related economic disruptions which have materially affected the Company’s revenue and could materially affect the Company’s gross margin and income, as well as the Company’s financial position and/or liquidity; actions to be taken by the Company in response to the pandemic; the legal, regulatory and administrative developments that occur at the federal, state and local levels; potential disruptions, breaches, or other incidents affecting the proper operation, availability, or security of the Company’s or its partners’ information systems, including unauthorized access to or theft of patient, business associate, or other sensitive information or inability to provide patient care because of system unavailability; changes in revenues due to declining hospital demand and deteriorating macroeconomic conditions (including increases in uninsured and underinsured patients); potential increased expenses related to labor or other expenditures; and the impact of our substantial indebtedness and the ability to refinance such indebtedness on acceptable terms or at all, as well as risks associated with disruptions in the financial markets and the business of financial institutions as the result of the COVID-19 pandemic which could impact us from a financial perspective. Numerous other risks, uncertainties and other factors may cause actual results to differ materially from those expressed in any forward-looking statements. Such factors include risk factors described from time to time in CPSI’s public releases and reports filed with the Securities and Exchange Commission, including but not limited to, CPSI’s most recent Annual Report on Form 10-K and Quarterly Reports on Form 10 Q. We also caution investors that the forward-looking information described herein represents CPSI’s outlook only as of this date, and CPSI undertakes no obligation to update or revise any forward-looking statements to reflect events or development after the date of this press release.
By: Fran Jurcak, MSN, RN, CCDS, CCDS-O, Chief Clinical Strategist
The goal of a quality Clinical Documentation Integrity program is to support documentation that identifies ALL of the conditions being monitored and treated during a patient encounter. Clear and simple. Yet many CDI Specialists (CDIS) in our profession spend significant time “shopping” for queries that only impact financial or quality outcomes (SOI/ROM). Not only does this waste significant and valuable CDI time, but the true goal of CD work is to ensure documentation integrity of the complete medical record.
If the clinical evidence supports a condition that is not clearly and consistently documented, best practice would dictate that communication with the provider should occur to ensure accuracy of the medical record. Period. For documentation integrity, the impact of the intervention shouldn’t matter. The need to accurately capture documentation of all the conditions that were assessed, evaluated and cared for in the medical record is essential to accurate coding of the care provided and results in accurate payment and reporting of quality metrics.
CDI Specialists spend countless precious minutes searching for queries with impact. Thinking that the only way to engage providers is to only “bother” them with queries that matter is short sighted and misses the bigger picture of the value of documentation integrity. In a world with diminishing resources and where integrity of the medical record is so important to capturing true acuity of every patients’ condition, every query opportunity to support documentation integrity is vital.
If the documentation does not reflect the clinical evidence in the medical record, any and all queries should be communicated with the provider. Picking and choosing the “right” query creates inconsistency that is not only confusing to providers but allows for inaccurate coding and reporting, which can lead to incorrect reimbursement and poor performance in quality metrics.
Let’s also talk about the time wasted on searching for the right query. Knowing that resources are limited and time is short (average length of stay is typically below 5 days) there isn’t time to spare for a search-and-seek mentality. CDI Specialists need to stay focused on the job at hand and not spend upwards of twenty minutes hunting for the query that drives a particular metric. All conditions being cared for and monitored should be appropriately documented in the medical record so they can be accurately coded and reported.
During the current COVID-19 pandemic, we discovered that across our clients, query rates on COVID-19 patients are 33-42% higher than on non-COVID-19 patients. It’s not likely that provider documentation is materially worse for these patients than others. Rather, this seems to point to the fact that due to the perceived need for greater scrutiny on these records to capture all appropriate comorbid conditions for accurate reimbursement and reporting, CDI staff are actually querying for every co-morbid condition. Why just these patient records and not all patient records?
Many CDI professionals spend additional time concurrently coding the record thinking this will assist them in identifying a query opportunity. While there may be other good reasons to concurrently code a record, doing so to specifically identify impactful query opportunities is often wasted effort as the impact of a query may change due to additional documentation that results later in the stay. For example, consider a CDIS that spends time searching for a condition that will impact the DRG, say a Major Comorbid Condition (MCC). So, the CDS searches for a condition that qualifies as an MCC and queries that condition based upon the clinical evidence but does not query other conditions that are also clinically supported but do not qualify as MCC. Then, later in the stay an additional MCC condition becomes accurately documented, which changes the impact of the query. The end result is wasted time concurrently coding, often leading to missed query opportunities on other conditions and subsequent negative impact to accurate documentation, coding and reporting. If a condition is being monitored and/or treated and not clearly and consistently documented, the documentation should be clarified regardless of the potential impact.
It’s important for CDI Specialists to utilize their clinical expertise and judgment to determine if there are documentation integrity concerns and communicate with providers to resolve those concerns. While basic knowledge of code language and coding guidelines is important to assist in accurately capturing documentation, CDI professionals should be assessing the clinical evidence in the medical record to identify missed or inaccurate documentation of conditions to support the integrity of medical record documentation. How the condition final codes should be driven by the documentation and completed by professional coders.
So the catch line is this: While it is important for CDI Specialists to understand coding language and be able to identify appropriate codes for conditions being monitored and treated, CDI Specialists need to focus their attention on supporting documentation integrity and query all documentation concerns, not just those that have financial impact.