| | December 20209UTLOOKHealthcare Tech based on what is documented in the charts, but if the documentation more accurately depicted how sick their population truly was, their spending would appear to be in line with expectations. Providers need tools to identify the HCC codes used last year, identify conditions were never coded but are obvious based on their medication history, and NLP tools to find the little gems of wisdom hiding in the text documents of our charts.· Pharmacy cost management: Patients and providers will work together to lower the out of pocket spend on medications if they both understand the costs involved. At the time of prescribing, a patient would make an informed decision about using a generic versus a name brand if they could. However most providers cannot tell you the cost of the medication to the patient when they arrive at the pharmacy due to the complexity of pharmacy benefits. Price transparency software that provides guidance towards lowering prescription costs at the point of care (not at the pharmacy) are essential. Real time prescription benefits across a full range of your population is critical to pharmacy cost containment.· Utilization Review software: Providers will hate it, but there is a lot of waste in healthcare and utilization review is one tool in the toolbox to control costs. A better option is clinical decision support tools at the time of ordering to steer providers away from unnecessary tests or to alert them that a similar test was done at another facility recently. The software is only one part of the expense and there are usually teams of clinicians needed to support the use of these tools effectively. · Risk stratification algorithms: We all have limited resources and need to focus on the right people in our population. Predictive algorithms for readmissions, progression to palliative care models, and risk for progression to severe chronic disease (kidney failure, diabetes, coronary artery disease), requires configuration, testing, and then implementation into the provider workflow (which is the hard part). Some healthcare systems are hiring data scientists to create their own algorithms which will produce a more accurate tool for your particular needs compared to a generic model purchased from a national vendor. The decision to build versus buy must be undertaken thoughtfully because data scientists are in high demand and therefore costly. · Provider network management: Providers need to know who are the low cost, high value providers in their market and have the ability to suggest these providers preferentially over high cost, low quality providers. Referral management software and analytics around leakage and referral patterns is necessary to control costs. Figuring out who is a low cost/high value provider can be challenging without broad access to data from multiple hospitals or claims data from Medicare.· Analytic tools that evaluate access, supply, and demand: If demand outstrips supply for primary care, access becomes horrible and patients will use the emergency room as their primary care provider. This is expensive and inefficient. Most systems develop and maintain their own dashboards to monitor metrics like 3rd next available appointment, average wait time for a new patient, schedule utilization, and provider productivity. · Remote patient monitoring and telehealth: These tools are frequently touted as solutions for readmission reduction and chronic disease management, although the data is somewhat mixed concerning the success of the initiatives. There is nothing wrong with the tools. The challenge is developing effective interventions and using predictive tools to focus on patients that can actually be helped. The tools today are not perfect, but when combined with dedicated nurses it can be effective.· Effective communication software: This includes provider to patient, provider to provider, and across the care team communication. The current disjointed processes for moving a patient from ambulatory to inpatient and then to Mark Weisman
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