How Nurse Advice Lines Can Help Hospitals and Providers Manage Population Health

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How will you ensure quality care for your patients, manage risk and reduce cost at the same time? Choosing proven, high-quality care management services that direct patients to the right care at the right time is a great way to start.

As a result of the June 28 Supreme Court Decision and President Obama's November re-election, much work — and uncertainty — still remains for those who administer and oversee benefits plans. As experts continue to debate the pros and cons of the Patient Protection and Affordable Care Act, payors, providers and hospitals are tasked with the real challenge of improving care while both managing risk and reducing cost. Their responsibilities are beginning to blur and overlap, and all healthcare professionals need more effective tools to help them rise to the challenge. Payors, providers and hospitals need advanced technology, effective disease management programs, better care coordination and increased patient accountability and involvement to improve health outcomes.

Nurse advice lines have an important role in this mix of strategies as well. NALs have emerged from being a check-the-box type program to become a proven tool for ensuring that patients receive the right level of care at the right time and place. This matters because the best NALs have the ability to accurately and appropriately redirect patients from unnecessary emergency room visits to other forms of care that effectively treat the medical issue while eliminating the wait time and cost of an unnecessary ER visit. Plus, an effective NAL call educates patients on self-care and healthier lifestyle choices and supports the patient and provider relationship.

Nurse advice line effectiveness: Algorithms versus guidelines

Algorithms are a sequence of instructions for systematically solving a specific problem or achieving a goal. Many of us use algorithms every day without realizing it. For example, if your car won’t start, you — or your mechanic — should apply an algorithmic approach to figure out what's not working. You'll work through a logical list of possible causes, starting with checking the battery cables, for example. If the battery cables aren't loose, corroded or damaged, you'll then check to see if the battery has a full charge. If the battery is dead, you'll replace it and test to see if your car will now start. If you instead find that the battery is working, you'll then test the ignition switch with a voltmeter. Depending on the result, you'll look at either the wiring connections on the starter or components on the gear shift lever. You'll rule out the most obvious causes first, getting more specific as you figure out what's not working. By using an algorithmic approach of asking a logical series of questions, you're able to get to a deep level of detail to identify the exact problem and determine the appropriate solution. Viewed in this manner, the car repair process is a sequence of steps that lead the mechanic through the process of troubleshooting and fixing the car.

Algorithms for an NAL operate the same way. They work much like a flow chart — you take a path through different questions based on the answers to previous questions and arrive at a recommendation. In a clinical algorithm approach, symptom assessments are phrased so the caller can respond yes or no. As with a flow chart, each yes or no response determines the next question in the algorithm, using branch-chain logic. This approach rules out serious conditions first and then determines the acuity level of the callers' symptoms and timing of the recommended intervention.

In contrast, guideline-based approaches are like a checklist — if the answer to a question is no, you keep going, and as soon as you hit a yes, you're done. Unfortunately, this approach doesn't allow sufficient detail to be gathered for the nurse to effectively triage the patient. The nurse asks a series of questions, sometimes in varying order. Once the patient answers yes to any assessment question, the session is over and the recommended intervention is delivered — often prematurely. Instead of being able to drill down and understand what is truly going on with the patient, the nurse must direct the patient to the highest level of care they might need, resulting in overtriage and unnecessary use of ER and urgent care services.

Some guideline-based NALs try to overcome this challenge by packing multiple symptoms into a single question. For example, they may ask if the caller has chest pain and difficulty breathing or nausea or radiation of the pain and no pain with palpation of the chest wall. However, this is a complicated question to ask or to answer, and makes it nearly impossible to modify or improve the guideline based on outcomes data.

Inconsistency in advice based on the guideline approach reduces an organization's ability to accurately trend outcomes across a population to determine the value and benefit of the NAL. Unfortunately, most NALs are based on this guideline approach.

Two approaches, different results

Waking up in the middle of the night, a man calls an NAL. Using the guideline approach, a nurse asks if he is experiencing chest pains. If he answers "yes," he is told to either call 911 or seek emergency department care, regardless of the etiology of the symptom.

On the other hand, an algorithm-based approach would take the conversation further to determine if the caller was truly in an emergency situation. The nurse would continue to ask questions and gather more information — resulting in a higher probability that the patient can seek care in a clinic setting for pain that might be only heartburn or some other non-emergent issue.

Algorithms are easy to use and require the fewest steps possible to reach a recommendation, allowing a registered nurse to quickly and accurately triage calls and direct patients to the care they need. Algorithmic logic is consistent, unlike guidelines which can leave room for interpretation and thus deliver inconsistent recommendations and results.

Ensuring high clinical quality

A randomized, controlled trial published in the Archives of Pediatrics & Adolescent Medicine looked at the recommendations given by an algorithm-based NAL, and compared those recommendations with those given by on-call physicians. The study found a high degree of concordance between the physicians' recommendations and the algorithm recommendations.[1] It is this high level of clinical integrity and consistency in reproducible outcomes that make algorithm-based NALs superior.

Ensuring algorithms are always at the highest level of clinical quality requires a review process with frequent and regular updates. Most effective is a three-step process: prospective review, concurrent review and retrospective review.

In the prospective review, algorithms should be reviewed annually by an existing panel of credentialed physicians, and those physicians should recommend changes based on advances in medical knowledge and clinical practice.

Throughout the year, in the concurrent review, a team of quality specialists should listen to actual NAL calls and ensure that the algorithm questions are being asked and answered as expected. If the callers or nurses consistently have difficulty with specific questions, the clinical team should modify those questions to make them clearer and the answers more consistent and reliable.

Finally, during the retrospective review, an NAL vendor should validate algorithm performance over time. Algorithms should be validated by evidence-based research, which includes a review of sorting and/or risk issues identified by nurses, clients, callers and others. When a risk issue is identified, the case should be presented to a clinical quality committee to recommend changes to the algorithm.

Nurse advice lines and population health management

As the healthcare industry moves to toward patient-centered medical home and accountable care models, providers and hospitals must find ways to manage risk and improve the health outcomes of patients. Managing these patient populations requires providers and hospitals to transform from episodic to holistic approaches to care. Providing access to a robust nurse advice line is an easy but important step in making this transformation.

NALs serve as an extension of a provider or hospital's staff, giving patients access to reliable, quality medical advice beyond office or staff hours. And as we've discussed, the most effective NALs — those that are based on algorithms — are able to accurately assess a patient's condition and then direct that person to the most appropriate level of care. This helps reduce unnecessary ER visits and inpatient readmissions, identify cases for referral to care management services, decrease variability in recommendations, provide patient support, lower medical costs, improve profit margins and manage risk.

As providers and hospitals look to implement an NAL, there are two approaches: You can build it yourself, or you can outsource to a vendor. There is a tremendous amount of work involved in developing, staffing, marketing and reporting on an in-house NAL. Partnering with an experienced NAL vendor dramatically simplifies that process, enabling a provider or hospital to ramp up quickly without having to change their current care delivery systems or learn how to deliver care management programs.

While telephonic NAL programs can be an effective way to move to population health management, there are some very specific questions providers and hospitals should ask when evaluating NAL vendors.

The first consideration is whether a vendor uses algorithms or guidelines, and the rigor and speed with which those algorithms or guidelines are evaluated, updated and deployed. Providers and hospitals must also ask vendors to demonstrate that they are able to effectively redirect patients to the most appropriate, and often less acute level of care, reducing unnecessary ER visits and at the same time making sure that patients who need emergency services are directed to them. User satisfaction rates, clinical and financial performance metrics and URAC and NCQA accreditation should also be taken into consideration. NALs that operate 24 hours per day, seven days per week are key in meeting NCQA's care accessibility requirement for designation as a PCMH.

An algorithm-based, 24/7 nurse advice line can give providers, hospitals and payors a boost in cost savings and risk management, as well as help ensure better outcomes for patients. Proven, reliable managed care solutions will continue to go the distance — regardless and/or in support of changing healthcare systems and regulations.

Footnotes:
[1] Archives of Pediatrics & Adolescent Medicine, July 2003; 157(7)

Steve Silverstein, MD, FACEP is vice president and chief clinical architect for McKesson Health Solutions. He focuses on the development of decision management and clinical decision support tools, chronic condition management programs, patient triage and consumer health education content, and is responsible for the clinical integrity of McKesson's decision management products. Earlier in his career, Dr. Silverstein was a senior editor at Micromedex and practiced emergency medicine for over 20 years. He is also the author of numerous publications, and is residency trained and board certified in both emergency medicine and internal medicine.

Holly Toomey, RN, BSHM is the associate vice president for care management strategy at McKesson Health Solutions. Leveraging her extensive payor and provider experience, she is responsible for developing and maintaining the care management product portfolio strategy across McKesson and ensuring creation of synergistic care management offerings. Ms. Toomey has held leadership positions at companies including Cost Care (now Unicare), United Health Care of New England, Harvard Pilgrim Health Care and the Massachusetts Peer Review Organization.

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