By Shelley Davis, MSN, RNC, CCM
June 2021– Healthcare pioneer Florence Nightingale may be best known for her reforms of the shockingly unsanitary conditions in the Barrack Hospital during the Crimean War in 1854. A lesser-known achievement, however, is that she also is a pioneer of what we know today as data-driven population health management. Following the war, Nightingale conducted a mortality analysis of British soldiers and concluded that 16,000 of 18,000 deaths were not due to battle wounds, but rather preventable diseases caused by poor sanitation. Nightingale even presented her findings using sophisticated data visualization techniques that would not look out of place today in a PowerPoint presentation.
Long since Nightingale’s innovative use of what we now call data analytics, health systems and accountable care organizations have embarked on data-driven care management initiatives. Even with the vastly more sophisticated healthcare technology we have today, organizations still encounter five common pitfalls that slow progress. These pitfalls, however, are largely strategic and operational and can be solved through re-assessing and redefining the organization’s care management goals and properly leveraging resources.
Pitfall No. 1: The Short Model
When organizations launch care management programs with an investment of time, staffing and technology, they often see some quick wins. But the highest risk, highest cost, most complex patients also are the most difficult to manage.
To achieve results, these entities require care managers to deliver health literacy education and help overcome external restraining forces or social determinants of health (SDOH) that impact care plan adherence. All of this requires time, patience, and an interdisciplinary team approach to overcome obstacles.
Too often, however, organizations abruptly shift direction without allowing enough time to achieve desired results. That is where re-assessing goals and setting more realistic and measurable targets may be needed.
Pitfall No. 2: The Narrow Model
Similarly, healthcare organizations eager to see rapid improvement among their highest-cost conditions may focus their care management resources on specific conditions, such as depression, diabetes or heart failure. This siloed approach, however, can create redundancies where multiple clinicians contact patients about similar matters or to close the same gaps, which can be confusing to the patient and reduce engagement. It is also a more costly strategy for the organization.
A better approach would be to focus on individual patients with the care manager taking the lead. The rest of the patient’s care team can be informed and engaged through means like an integrated population health management platform. This more efficient approach can help establish a strong relationship with the care manager, building a patient’s trust and engagement.
Pitfall No. 3: The Eyes Too Big for Stomach Model
On the opposite end of the spectrum, some organizations want to move the needle on cost and quality outcomes through care management and may enroll too large of a population without dedicating an adequate number of care managers. The optimal care-manager-to-patient ratio will depend greatly on patient complexity and will need to be determined over time but starting with a focused population early in the program is a better approach.
A population health management platform can also help organizations arrive at their ideal ratio sooner through continuous analysis of care management data as patients enroll and ultimately graduate from the program.
Pitfall No. 4: The Never Graduates Model
Some complex patients, however, can fall into the “never graduates” category. These patients may deeply engage with their care managers and claim they are committed to treatment plan adherence, but for various reasons, are not making meaningful progress toward self-management.
In some of these cases, the patient becomes dependent on the care manager instead of themselves, which may require calling on an interdisciplinary team to help patients overcome these attachments. A different clinician may be able to offer alternative motivational techniques to encourage adherence and reinforce education initiated by the original care manager.
Pitfall No. 5: The Missed the Mark/Window Model
These models are closely related because they are both attributable to the quality and timeliness of patient data. Effective care management is driven by risk stratification, which is dependent on the accuracy and timeliness of data used to create the models. If care managers are not focused on the highest-risk patients because the organization does not have the proper risk management or risk modeling solutions in place, then more avoidable emergency department (ED) visits or hospitalizations could result.
Likewise, care manager interventions are more effective closer to the point of an ED visit, hospitalization, or similar encounter. Knowing when these events occur requires timely data so the care manager can impact the patient at the time of greatest need for care coordination and education. An untoward or unexpected event may also be the impetus for behavioral change, and it is critical for a care manager to engage when the event is still fresh in the patient’s mind.
Every data point matters. A population health management platform can ensure care managers always have access to the most accurate risk stratification models so that these valuable care management resources are dedicated to the appropriate patients. Additionally, solutions that provide alerts related to patient admissions, discharges, and transfers keep care management teams informed, in real-time, about changes to a patient’s overall health.
Begin at the End
While analysis of high-quality and timely data is crucial to support care management success, such factors are only relevant once the organization has established clear, concise goals that align with overarching objectives and the needs of the community. Once those goals are established, the organization can empower care managers with a platform that ingests real-time encounter data, provides accurate risk stratification, and deploys ongoing analysis of performance and outcomes.
Using these goals and tools, an interdisciplinary care management team comprised of experienced professionals operating at the top of their licensure can effectively manage an organizations’ highest-need patients and place them on a sustainable path toward self-management and optimal outcomes.
About the Author
Shelley is the Clinical Engagement Manager at Lightbeam Health Solutions. She is an educator and leader with experience in population health management, clinical advisory and analytics, business, economics, case management, pediatric critical care, trauma, and cardiac care.
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