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Home » Crisis In The CDI Space: Workforce Shortages & How AI Can Help

Crisis In The CDI Space: Workforce Shortages & How AI Can Help

    The CDI Space Is a Hotbed of Activity, but It’s not Without its Challenges.

    One of the biggest issues facing this sector is a lack of qualified workers to fill jobs. This can be attributed to several factors: an ageing workforce that’s leaving their positions and retiring; a lack of training programs for new hires; and high turnover rates among younger employees who don’t want to commit long-term because they feel like there are better opportunities out there (which there might be).

    The shortage of qualified CDI professionals is something many healthcare organizations are struggling to keep up with the demand for–CDI services. In fact, some hospitals have resorted to outsourcing their documentation needs to third-party vendors. However, this can be costly and inefficient since it requires them to share sensitive patient information with external parties who may not have adequate security measures in place.

    A recent survey conducted by HIMSS Analytics found that more than half of healthcare organizations reported having difficulty hiring CDIs due to a lack of qualified candidates. The same survey also found that 36 percent of CDIs leave their jobs within six months because they don’t feel supported or challenged by their employers

    In this article, we’ll explore how these technologies can be used to identify opportunities for improvement in charting quality and performance; uncovering critical information from patient records; improving physician efficiency; facilitating provider collaboration; driving better decision-making across an organization; improving patient care coordination through real-time access to data at point-of-care locations throughout hospitals or clinics.

    Artificial Intelligence Can Help Reduce the Burden on the Workforce

    The good news is that AI technology offers an alternative solution: it allows providers access to powerful tools that facilitate collaboration between clinicians and improve decision-making around clinical documentation improvement efforts (CDIs).

    One way they’re doing this is by leveraging Clinical Natural Language Processing (cNLP), machine learning (ML), and deep learning technologies to revolutionize how they uncover critical information from patient records.

    Today, AI can analyze information in a patient record to uncover critical data that may not be readily apparent to humans. For example, AI can help identify gaps in care across a patient’s entire life, uncovering opportunities for improvement that could impact the quality of care and health outcomes.

    Building Trust between Physicians, CDI Staff & Technology is Paramount

    When it comes to implementing AI in clinical documentation, the relationship between CDI staff and physicians becomes even more important. AI can help automate some of the low-hanging fruit which is repetitive and doesn’t require the critical thinking skills of a nurse or physician conducting CDI. Resources can be reduced by 25% if the budget requires, or deploying CDI Staff to focus on more complex cases, quality metrics capture and improvement, SOI and mortality reviews, denials management and following up on concurrent query responses and non-responses to provide more targeted guidance to physicians.

    To build trust with physicians, organizations must ensure that they have access to their own data and can use it without restriction. In addition, they should invest in ongoing education around how AI works so physicians feel comfortable using it as a tool for improving quality care.

    However, to successfully use AI in clinical documentation, physicians must be able to understand that with more timely notification of queries, they need to respond sooner and tolerate some noise. The technology is never perfect but helps the usability of responding within workflow while the patient’s case details are still top of mind. Within days of use the technology becomes more accurate and reliable, learning from physician responses. CDI staff can play a key role in building this trust by working with physicians at the point of care to ensure accurate clinical documentation is achieved. 

    Ultimately, the relationship between CDI staff and physicians is critical to ensuring that the medical record is an accurate reflection of the care provided to the patient, so that appropriate quality decision support and revenue-sensitive guidance reflects the services rendered. The advanced, embedded note editor feature for physicians is delivered as they are typing in Notereader CDI within Epic’s latest November 2022 version, powered by HITEKS. Learn more about how we are helping Epic hospitals and clinics achieve automation to boost US News and World Report rankings, and achieve the top 20% of Medicine CMI nationally, all without compromising care.


    Revolutionizing the Way Healthcare Providers Uncover Critical Information from Patient Records

    The good news is that AI technology offers an alternative solution: it allows providers access to powerful tools that facilitate collaboration between clinicians and improve decision-making around CDIs efforts. This results in better care delivery outcomes while also reducing costs associated with hiring additional staff members or contracting out work externally.

    Artificial Intelligence can help reduce the burden on the workforce. AI has been used to automate non-critical and repetitive tasks, allowing human reviewers to focus on complex cases that require their expertise. This allows for more efficient use of resources and reduces reliance on human review.

    Perceived Challenges of AI-Powered CDI

    While AI-powered CDI can help solve many of the problems facing the industry, it also comes with its own unique set of challenges.

    A potential issue with using AI for this purpose is accuracy: while these programs aren’t exactly known for making mistakes very often (at least not more than humans), they’re still susceptible to errors from time to time–and since these types of errors could potentially cause serious harm if left unchecked by human intervention (such as misdiagnosing an illness), there’s definitely reason enough here why we need some kind of oversight mechanism built into the algorithms.

    Lack of control: The most common fear among those considering AI for their team is losing control over their business processes and operations. In some cases this fear has been justified — companies who have implemented AI without proper planning have experienced significant losses due to unexpected outcomes from machine learning algorithms and automation processes that were not fully thought through by management teams.

    What if we could take advantage of technology in order to make this situation better?

    Isn’t it Time That We Turn Toward the Future?

    The CDI workforce shortage is a major concern for healthcare providers today that are facing increasing regulations and revenue pressures. An acute lack of resources is limiting the ability of these professionals to do their job efficiently and effectively. Essentially, there aren’t enough people to do all the work.

    As EHRs like Epic continue to evolve, so too must the processes for managing and supporting these solutions. Appropriate documentation is just as much a part of delivering quality healthcare as the clinical decisions that physicians make throughout the day. It requires a great deal of time, effort, and engagement from clinicians.

    With the adoption of artificial intelligence, EHR-enabled clinical documentation processes can benefit from the best attributes of both humans and machines. Technologies like CAPD360 have the potential to improve clinician collaboration and decision-making, enhance patient care coordination, reduce errors, and improve overall workflow among healthcare providers.