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How Clinical Decision Support Tools Can Be Used to Support Modern Care Delivery

Vinita Mujumdar, JD, and Haley Jeffcoat, MPH

September 1, 2022

How Clinical Decision Support Tools Can Be Used to Support Modern Care Delivery

Highlights

  • Identifies CDS tools that help surgeons and patients collaboratively develop a healthcare plan
  • Outlines methods for providing CDS, including tools with the potential to incorporate AI and ML technology
  • Describes challenges related to digital health tool implementation
  • Summarizes the role of the ACS and other societies in validating this technology

Surgeons are dedicated to providing optimal care for and working with their patients to achieve that goal. Fortunately, technology is making it more possible for surgeons and patients to partner in the decision-making process.

Hypothetical example: A 77-year-old patient visits a surgeon after cancerous polyps were identified during a routine colonoscopy. The patient has been nervous about the visit, especially because she witnessed her father lose his battle with colon cancer 20 years earlier. However, in recent decades new approaches to clinical decision-making and advances in care have emerged since her father died.

This patient wants to better understand her treatment and the risks involved. In addition to advancements in cancer care, innovations in healthcare information systems, clinical decision support (CDS), and other digital health tools allow physicians more access to patient information, resulting in more informed decision-making, better tracking, and improved communication with patients and across the care team. 

The surgeon enters the patient’s exam room, with a tablet in hand and accesses the patient’s electronic health record (EHR), showing her personal medical history, comorbidities, family history, and all of the recent physician notes, scans, and lab results related to her diagnosis. As the surgeon discusses potential diagnoses and treatment plans with her, the patient begins to ask many questions about the proposed surgical intervention, noticeably becoming increasingly nervous about the risk of a major operation at her age.

Aware of the patient’s discomfort, the surgeon opens an application on the tablet that calculates a patient’s personalized risk for surgical complications. The application or web service asks for permission to upload the patient’s information, such as name, date of birth, patient identification number, comorbidity parameters, and the Current Procedural Terminology (CPT)* code for the planned procedure.

With this information, the application auto-populates the required fields in the calculator from data in her medical record and quickly displays projections of the patient’s specific 30-day risks and outcomes of the procedure. The report reveals the patient’s risk for complications and shows that she has low-to-moderate risks. The surgeon shares the outputs from the risk calculator with the patient, engaging her in reaching an informed decision regarding the recommended care. 

Armed with clear information about potential risks for surgery, the patient can better appreciate data-driven decisions about her care and leaves the visit feeling comfortable with the treatment plan. 

Patients are increasingly more aware of their options and anticipated outcomes and expect to be more informed so they can participate in their healthcare decisions. In this instance, the patient is appreciative and finds her surgeon more trustworthy after having had a detailed discussion about her risks. This scenario describes just one of many in which CDS tools can be used to support patients and physicians as they navigate the complexities of receiving and delivering high-quality care.

This article describes CDS tools, explains why hospitals should consider making CDS tools more accessible to healthcare professionals, and outlines potential barriers regarding digital health tools. It also looks at the role the American College of Surgeons (ACS) and other professional societies could play in verifying the utility of this technology. 

Evolution of CDS 

CDS initially was limited to medication reminders and drug interactions found in the pharmacy sections of the EHR. Although these functionalities have proven to be important to both primary care and medical specialties, further expansion of CDS extends beyond these basic functions. CDS can better facilitate order sets, facilitate documentation, display relevant knowledge from expert analysis, lay out practice guidelines, and track patient conformance with protocols. These digital tools could also assist with assessing criteria for inclusion in clinical trials or other types of research. 

Healthcare delivery often is a complex journey, involving multiple data points and care teams that add to decisions about diagnosis, treatment, and the care plans. Digital tools such as platform-based web services and knowledge-enabled capabilities in a patient, nurse, or physician workflow hold great promise to support managing the various aspects of contemporary healthcare delivery.* Modern-day healthcare involves understanding the disease and clinical pathophysiological process of the individual patient and applying clinical knowledge across the lifecycle of a condition as well as the appropriate treatment or management regimen.

It is possible to think of medical conditions with the lifecycle beginning with disease prevention, early detection, timely diagnosis, treatment, management of those conditions, and survivorship with long-term surveillance. Across the various phases of the lifecycle are large swaths of knowledge that are best co-managed by the patient and the entire care team. Keeping all the clinical team members informed is critical to success, which might be defined by meeting patient goals for care or achieving positive patient outcomes, but this also can be challenging due to the complexities of modern care. Digital web services, such as apps using CDS tools, already address many of the complexities of today’s healthcare system and will continue to grow in applicability. These tools are limited in scope only by developers’ and users’ imaginations. 

The power of these tools comes from the potential to draw upon a variety of data sources and incorporation of evidence-based guidelines or advanced algorithms and deliver them within a workflow that is aligned to the surgeon’s mental models and supports their cognitive process. 

CDS tools also have the potential to support surgeons’ delivery of high-quality care and reduce physician burden, and, therefore, physician burnout. Specifically, CDS tools can decrease administrative and documentation burden, relieve cognitive burdens, synthesize and share treatment options, provide input from clinical guidelines, and employ artificial intelligence (AI), machine learning (ML), and predictive analytics for patient outcomes and price transparency. 

Importantly, CDS should never replace a physician’s clinical judgment; rather, the goal of these and other digital health tools is to enhance physicians’ knowledge and augment their cognitive efforts. Care is highly personalized and requires a physician-patient interface where the medical knowledge is contextualized and personalized in a trusted manner for each patient. This point cannot be overemphasized. It is important for physicians to leverage the content and use it within the context of applied surgical science with their patient. 

Types of CDS Tools and Methods of Providing CDS  

CDS is defined as a process for enhancing health-related decisions and actions with pertinent, organized clinical knowledge and patient information to improve the delivery of healthcare services. A variety of CDS tools and mechanisms are available, and these options continue to expand with the advancement of new technology and increased interoperability. Some CDS tools already are embedded in EHR systems, so surgeons already could be using elements of CDS in their practice without knowing it. 

Table 1 offers ways to provide CDS for care of the surgical patient. Many of the CDS methods listed in the table also could incorporate AI and ML technology, including computable models of clinical guidelines and pathways, further enabling the capability of these technologies. In addition, many CDS methods can be applied across different types of platforms beyond the EHR. 

Table 1. Methods of Providing CDS and Cognitive Support

Type

Description

Medication dosing support

Inform clinician about medication dose adjustment, formulary checking, dose checking, default doses, indication-based ordering

Order facilitator

Includes order sentences, subsequent or corollary orders, consultant-recommended orders, indication-based ordering, and rule-based order sets

Point-of-care alerts/reminders

Prompts clinicians about how prescription medications interact with other drugs, the patient’s medical condition, and allergies; reminds clinicians to assess specific care items; notifies clinicians about critical laboratory values or high-risk states

Relevant information display

Ensures that clinicians have up-to-date and necessary patient data to make decisions in providing care to the patient, such as showing recent lab values when ordering medication

Expert systems

Apply advanced logic or computational methods to assist clinicians in ordering, diagnosing, treating, and interpreting data elements; may be applied across CDS mechanisms

Workflow support

Includes order routing, registry functions, medication reconciliation, automatic order termination, order approvals, free-text order parsing, documentation aids, and activity-based summary views

Summary views

Includes a composition of all the pertinent or relevant patient-level information such as the conditions, complications, procedures, labs, findings, diagnostics, risk/severity scores, active orders, clinical activities, potential next steps (for example, orders) and compliance with/adherence to guideline recommendations, and more that are then filtered, sorted, and/or oriented to a given condition, procedure, or workflow activity (for example, rounding)

Smart forms and documentation templates

Can facilitate documentation-based CDS by enabling a multi-problem visit note while capturing coded information and providing sophisticated decision support

Timeline views

Shows a chronological display of the patient’s clinical events and can compare with other patients

Interaction models

Information can be displayed similarly to a site map for a web page to support the conceptual models of its target users. Used in apps to align the user interface to clinician mental models and in-app workflows to cognitive processes and clinical activities

Benefits of Using CDS in Surgical Practice 

As the capabilities of CDS continue to expand and more practices adopt CDS tools, surgeons likely will experience the benefits of these tools if they are implemented thoughtfully. Implementation of CDS tools has been associated with more efficient care processes, facilitation of shared decision-making with patients, improvements in patient outcomes, cost savings, and more.§ The surgeon can leverage CDS at the point of care and during postoperative care assessments to evaluate performance improvements and facilitate communication with patients. In this article, the focus is on improvements in care processes, improved clinical outcomes, reduced cognitive burden, reduced administrative burden, and cost/resource savings that are possible with the use of CDS tools. 

Improved Care Processes and Patient Experience

CDS systems can contribute to improvements in care processes, such as reduction in the variation in care delivery, duplication of tests and services, and timely and reliable ordering of necessary tests and preventive services, thereby enabling physicians to offer more targeted information to patients and caregivers based on their needs and what they value. By layering evidence-based best practices on top of unique patient information found in EHRs, CDS tools can present the clinician with knowledge that is tailored to the patient to inform more personalized care decisions to engage patients and caregivers throughout their care journey. The tools also can help close gaps across the care model by guiding the physician through clinical pathways and recommending evidence-based processes to allow for more reliable, valid, and timely quality measurement, and drive more impactful and rapid quality improvement (QI) cycles. With the greater availability of more reliable and valid digital data, registries can interoperate with clinical information systems and integrate more advanced capabilities (data collection, real-time comparison, AI/ML).

As CDS tools continue to advance, opportunities to move toward a learning health system arise. In a learning health system, clinicians can learn from each other and from the data. The data can be applied to inform clinical pathways and practice, which all can be facilitated by CDS tools. In addition, the advanced capabilities will allow traditional evidence-based medicine guidelines to integrate customized medical recommendations and advanced analytics, such as AI and ML, to give physicians a real-world view of a specific patient. By streamlining how the information is presented to physicians and putting the right information in their hands at the right time throughout the care cycle, physicians’ time can shift back to the patient and away from their workstations.

Improved Patient Outcomes 

CDS tools can help drive improvement in patient outcomes in several ways. As clinicians move through their clinical workflow, CDS software can integrate alerts and notifications to keep the clinical team informed on the latest clinical guidelines, avoid negative drug interactions, unnecessary tests, medication errors, and other adverse clinical events. By implementing CDS, physicians and healthcare institutions may notice shorter length of stays following procedures, reduced complication and morbidity from complications, improved recovery time, and more. With the increase in data and personalized patient information offered by the CDS tools, clinicians will be able to identify potential complications and intervene earlier. The ability to track patient data, compliance with standards of care, and the status of quality control metrics in one system strengthens QI cycles. 

CDS tools also can provide additional pathways of communication between the patient and the care team. This could include functionalities that prompt patients to provide feedback and facilitate how the clinical team provides resources to patients. By capturing patients’ experiences and maintaining open lines of communication, patients are empowered to stay engaged in their care and physicians can better understand how to provide value and meet patients’ goals. Shared decision-making is critical to delivering high-quality patient-centered care. 

Reduced Cognitive Burden

Physicians are responsible for an increasing number of cognitive and administrative tasks. Physicians now have access to large amounts of data from many sources. While powerful, this influx of data and tasks also can contribute to cognitive burden and physician burnout. By enabling physicians to easily access the relevant information or knowledge at specific decision points within the care cycle, their cognitive load and administrative burden will decrease. By aligning CDS algorithms with mental models (for example, clinicians’ existing knowledge about diseases, procedures, organ systems, and more) and clinical workflows informed by up-to-date clinical best practices and guidelines, CDS systems can help physicians organize activities and tasks and provide specific information and inferences needed to optimally complete each task. 

Reduced Costs, Waste, and Administrative Burden 

Duplicative services, unnecessary testing, adverse patient outcomes, and variations and gaps in the physician workflow can pose significant financial strain on healthcare institutions and take time away from direct patient care. Although a practice’s initial investment in CDS integration may be significant, proper use of the tool can contribute to fewer costly adverse events, redundant services, and more.

Some CDS tools also can assist with burdensome and timely documentation tasks. For example, based on the data the physician enters into the EHR, the tool can present billing codes and modifiers for surgeons as they work through the care cycle, resulting in more accurate and appropriate billing. To support registry and QI program efforts, both the clinical team and nurse abstractors can use CDS to better facilitate and accelerate data abstraction and documentation. By decreasing adverse clinical events and shortening the time physician and their extenders spend on administrative activities, physician practices and health systems could experience reduced costs. 

Challenges Associated with CDS Implementation 

Introducing advanced technology into care delivery is presenting a paradigm shift. Although CDS implementation has many benefits, challenges and disruptions do occur when undergoing a major change. Barriers to CDS implementation span from the need for physician trust in the tools to alignment of workflows with current EHR systems, regulation and governance of data and knowledge, liability concerns, and more. 

Physician Trust 

When exploring the use of any new technology, a common barrier can be users’ lack of trust in the tool. Physicians are likely to have concerns about implications for patient safety, and it can take time for users to become comfortable applying the CDS outputs to inform patient care. To enhance trust in using the tool, the following considerations are essential: transparency, ease of use, proof of validation, reliability, data quality, opportunities for feedback, and adequate regulation. 

Physicians also may have concerns about the data and algorithms used in tools that incorporate AI and ML capabilities. With these advanced tools, the need for trusted and complete data sources is even more important, and ensuring the algorithms and data are properly validated is crucial. If the tool is not developed and trained with data that are representative of the patient population the physicians serve, the data outputs could be inaccurate or biased. To lower the risk of bias, the use of trusted and complete data sources in development and testing stages is extremely important. 

Alignment with Existing Workflows and Information Systems 

Aligning new technology with existing systems, such as EHRs, and accessing data within these systems can be difficult and costly, which can contribute to slow uptake of tools like CDS. To minimize these barriers, it will be necessary to apply components of systems engineering to effectively incorporate CDS methods and tools into clinicians’ workflows and demonstrate the value of the tool. This process should include evaluations of existing processes before taking steps to automate them with CDS or other knowledge-based digital health tools.

Automating a poor process will only exacerbate gaps in care, inefficiencies, and risk of error. By completing these assessments, institutions can identify problems or inefficiencies in their systems and implement CDS tools to update and redesign workflows that support and augment optimal care. Allotting time for user training is crucial to optimize the tool’s functionalities and reduce user errors and disruptions in workflow. Properly training users so they are comfortable with the technology and feel confident about the outputs will go a long way toward building provider trust.  

Regulation and Liability 

Healthcare institutions should have their own governance and structure for CDS and digital health tools, including pathways for user feedback and timely responses to feedback as physicians have concerns or encounter issues. Liability risks and uncertainty about who is responsible for issues with CDS algorithms, outputs, or user errors can hinder implementation of CDS systems. Before implementing these systems, institutions should be confident in the quality of the tool and its capabilities and thoroughly understand vendor contracts. Contracts with hold harmless clauses, in which vendors require that purchasers shift responsibility to the user, pose high liability risks for physicians; such provisions should be removed. 

Key Takeaways to Support and Advance the Use of CDS 

CDS tools should be integrated in the clinician’s workflow to decrease burden, not add to it. The following describe important components regarding CDS implementation:

  • CDS can support delivering value to patients through improvements in shared decision-making and patient goal identification 
  • CDS should be tailored to the particular clinical environment 
  • CDS should support physician decision-making and reduce cognitive load 
  • CDS tools should be properly integrated with existing clinical information systems
  • Healthcare systems can help promote the use of CDS and build trust in new technologies
  • The cost savings from CDS integration can offset the initial investment to implement these systems

The ACS’s Role 

The ACS and other specialty societies have several important functions with regard to web services and CDS. Primarily, surgeons and their patients must evaluate the technology to ensure it represents the evidence and the clinical algorithms used in CDS. For example, the risk calculator mentioned earlier in this article must have governance over maintenance of the risk formula and remain up to date. The technology used to implement the algorithm must faithfully aggregate the right data elements for the risk calculation. Finally, the implementation at the point of care must be affordable and sustainable so that cloud implementations or platforms do not create a costly barrier to entry for digital web services by charging exorbitant user fees (known as “toll-gating the applications”).

Algorithms, applied medical science, and knowledge artifacts must be accurate and meaningful to physicians. Specialty societies can help ensure that the clinical pathways, data, and guidance are up to date and align with clinical best practices. If the ACS and other professional societies review and validate a tool, users can be more confident that it is a safe investment. 

Acknowledgment

The authors would like to recognize Matthew Burton, MD, principal clinical informatician and knowledge architect, Holistic Healthcare Solutions, Phoenix, AZ, for his contribution to this article.


Vinita Mujumdar is Chief of Regulatory Affairs, ACS Division of Advocacy and Health Policy, Washington, DC. 


All specific references to CPT codes and descriptions are © 2021 American Medical Association. All rights reserved. CPT is a registered trade-mark of the American Medical Association.

*Mujumdar JD, Jeffcoat H. Leveraging knowledge management for better quality surgical care: An introduction. Bull Am Coll Surg. March 4, 2021. Available at: https://bulletin.facs.org/2021/03/leveraging-knowledge-management-for-better-quality-surgical-care-an-introduction. Accessed August 3, 2022. 

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McCoy AB, Melton GB, Wright A, Sittig DF. Clinical decision support for colon and rectal surgery: An overview. Clin Colon Rectal Surg. 2013 Mar;26(1):23-30. 

§Tcheng JE, Bakken S, Bates DW, Bonner III H, Gandhi TK, Josephs M, K. Kawamoto K, Lomotan EA, Mackay E, Middleton B, Teich JM, Weingarten S, Hamilton Lopez M, editors. Optimizing Strategies for Clinical Decision Support: Summary of a Meeting Series. Washington, DC: National Academy of Medicine; 2017.