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Article: How to Scale Healthcare Improvement Without Increasing Headcount

Value-Based Care and bundled payments requires your health system to get better, faster. Historically that has meant hiring more analyst and running more reports. This solution does not scale in the new healthcare economy, and new solutions are required to successfully make this change. Value-Based Performance Management applications solve the scale issue of healthcare.

A few months ago, while we were meeting with healthcare executives and analysts, the following observation was made: every industry has used automation and technology to replace headcount except healthcare. In other industries, new IT systems generally represent efforts to achieve greater efficiency, lower cost, and increased revenue. In healthcare, IT systems have been introduced to track programs and report on the explosion of data being collected, but efficiency and cost reduction have not been points of emphasis.

While healthcare providers can’t transform the system without good data, data alone is not enough. To transform healthcare, providers need understanding. The current model requires analysts to provide the insight necessary to facilitate change, but analysts can’t scale at the same rate as data – there simply aren’t enough people to answer all the questions being asked. The new healthcare economy needs a focus on automation.

To effect change, healthcare systems need to transform, aggregate, and present data in such a way to be actionable. The traditional approach to this process generally resembles the following: define the project and outcomes; outline the budget, timeline and headcount required; estimate ongoing maintenance costs and headcount; and staff the project, either by taking resources off existing projects, hiring new resources, or waiting for resources to become available.

Although this process has been employed successfully in the past, it is not a sustainable solution. The road to failure is paved with good intentions, and IT projects are no exception. Projects regularly go over budget, scope creeps, people get pulled off to work on other projects, and the expected returns are rarely realized.

Aside from the speedbumps inherent in new projects, there is the issue of focus. If your business is healthcare, building in-house technology itself does not give you a competitive advantage. The value of that technology lies in its ability to help you transform healthcare delivery. Reducing risk by deploying healthcare-specific, ready-built applications allows you to focus on the important part of your business: patient care.

Historically, the next step of “what to do with the data” has been a manual process, staffed with teams of analysts and consultants. Some software vendors package consultants and analysts together with their technology to make it work. The tools of the analyst include spreadsheets, email and modules tacked onto EMRs. This strategy is slow, expensive, and doesn’t resolve the headcount issue. In the next couple of years, studies estimate that the United States will have a shortage of 2 million analysts with the required knowledge and expertise in data analysis and data management. Shifting the burden from your organization to a consultant doesn’t address the fundamental shortage of skilled workers. The solution is a fundamental shift in the approach to decision support.

Analysts are not decision makers. The key to transformation is to provide insights directly to the decision maker without the analyst layer in between. So how do you automate what an analyst does to get the insights to the end user? Tools or modules are not the answer. They require FTEs to create, configure, and populate, which exacerbates the shortage problem. Configuring report and dashboard tools frequently takes more time than originally planned. If a prebuilt application can answer the same question, the solution would be to deploy the application and save the teams for important tasks that would not have been completed otherwise.

Value-Based Performance Management applications that deliver personalized, role-based metrics to each member of the health system can answer 80% of the common questions, and IT teams can allocate their skilled and expensive analyst resources to critical, clinical and financial problems.

So you have decided to get the data directly to the decision maker and bypass the analyst. How do you do that? The answer is not to simply automate the generation and delivery of reports to the user. That ignores a very important factor: the workflow of the decision-making process. Workflow is the missing link between tools and applications: tools are functionality without workflow.

Performance has historically been measured using a formula of Volume X Price. However, there are many more dimensions – quality, cost, timeliness, satisfaction – with performance at the center of them all. Tools are unable to provide the transparency and the situational awareness to produce the right decision.

Automated workflows must marry personalization, standardization, and guided navigation with data analysis and reports.

Personalization means showing data relevant to each user and changing the data displayed based on the user, such as metrics specific to a provider based on their role and specialty. If one plan is created that can be personalized to everyone in the organization, each showing different metrics, targets, and weighting, goals can be aligned and visible across the organization.

Standardization includes a metrics engine that automatically calculates metrics based on new data, and is kept current with the updated metrics definitions as well as newly adopted metrics. It needs to include automatic error checking and validation – code matching, data harmonization, missing/invalid/duplicate data, etc. – tasks that an analyst has historically performed.

Guided navigation leads the decision maker on the path to the right answer – anticipating the next question the user will ask and showing them the appropriate information.

Data volume has been increasing at an exponential rate for many years, and, with the mass adoption of EMR systems, data collection will continue to outpace the ability to analyze it. The solution requires a fundamental shift to automated decision support so the shortage of analysts doesn’t hamper improvements in patient care, and so irrational variation and waste in the healthcare system can be reduced. Tools are not the answer – they merely shift the headcount problem, because tools inherently fail to address the value that analysts add to the decision support process. The new healthcare economy needs Value-Based Performance Management applications that can marry high quality analysis, intuitive workflow, personalization, and outcome based planning and execution.

Author: Tim Ramey