What information might you include in an analytical model identifying “frequent fliers” or “high utilizers,” patients that have the most repeat visits and consume the most resources?

Please read your peer discussion and give your feedback.
1 st discussion
Is the decision to provide intensive therapy for this high-risk population evidence based? In your opinion how does it relate to clinical judgment?
I feel the data provides vast amounts of data in order to point towards the need for intensive therapy and enough data (evidence) is provided to be considered “evidence based.” Within the last decade, medical forecasting literature has seen significant attempt to revisit the role of clinician/physician judgment in medical decision making which enables and compliments the collaboration of clinical judgement. Despite the successful application of these traditional statistical models in healthcare, the complexity of the human body, the multidimensional and nonlinear nature of biological systems, and clinical characteristics limits their predictive ability. According to our readings with the emergence of data mining, Artificial Neural Networks has been experimented to support evidence based medicine in assessing and predicting more complex biological systems and medical scenarios with greater degree of accuracy over the conventional statistical models (Brown, 2019). There are still weaknesses of course yet it seems hourly we are reaching significantly better ways of translating data into clinical applicable judgment.
In your opinion what are the implications of, and potential for, aligning the strategies and corporate interests of Central Medical and Health First for better serving patients?
I believe we can all agree that healthcare is at the forefront of every political debate, reinvention and new fad, for obvious reasons. Healthcare leaders and policy makers have tried countless incremental fixes such as attacking fraud, reducing errors, enforcing practice guidelines, making patients more informed consumers and of course as we are studying endlessly, implementing electronic medical records, according to but according to WHO none have had much impact. It’s time for a fundamental new strategy. Which at its core can maximize value for patients which means achieving the best outcomes at the lowest cost. We must move away from a supply-driven health care system organized around providers and toward a patient-centered system organized around what patients need. Of course there has to be a shift from the volume and profitability of services provided to the patient outcomes achieved. Of course value-based care has attempted that but its success is questionable at best.
“The strategy for moving to a high-value health care delivery system comprises six interdependent components: organizing around patients’ medical conditions rather than physicians’ medical specialties, measuring costs and outcomes for each patient, developing bundled prices for the full care cycle, integrating care across separate facilities, expanding geographic reach, and building an enabling IT platform (Chang, 2018).”

2nd discussion
What information might you include in an analytical model identifying “frequent fliers” or “high utilizers,” patients that have the most repeat visits and consume the most resources? Where would you access this information?
I would want to know the demographic data of my patient population and match that with a generic patient profile of all our patients that have similar comorbidities as my “frequent fliers”. The demographic data would come from my patient records. The generic patient profile information would come from various databases that already exist of de-identified patient records. Once I have built my patient profiles, I would start modeling outcomes of the generic patients using evidence based medicine in order to begin to create patient profiles and the suggested treatments so I can start screening the patients that are coming in the door. I think this will allow me to better triage the high utilizers when they come in and get them into the correct treatments sooner.
What challenges do you think health care leaders face when they apply modeling to guide transformation of the health system?
The main challenge is that the idea of modeling treatments is still relatively new and the fact that there are not a lot of outcomes based evidence based guidelines for patients makes the idea of modeling their treatments that much harder. It’s good to try it now and focus on areas that are a little more robust in terms of outcomes data but it is still very early in the process.

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