Why data-driven planning will work for healthcare — 4 takeaways

The COVID-19 pandemic highlighted challenges health systems face with financial planning in a highly dynamic environment. In many healthcare organizations, the pandemic has been a catalyst to reevaluate current planning tools and processes.

During a webinar hosted by Becker's Hospital Review and sponsored by Syntellis Performance Solutions, two leaders from Syntellis — Jay Spence, vice president for healthcare industry solutions, and Steve Wasson, executive vice president and general manager of data and intelligence solutions — discussed how a data-driven, unified approach can transform financial planning into a more effective and more agile process.

Four takeaways:

  1. Today's healthcare business challenges call for a new approach to financial planning. Syntellis, which offers healthcare financial planning and decision-support software that is used by more than 2,800 customers, surveyed healthcare finance leaders just before the pandemic's onset. The company found 95 percent of respondents agreed they needed to better leverage financial, operational and analytical data in planning and forecasting. The pandemic drove that point home: when finance teams were asked to quickly model what would happen with elective surgeries dropping off for months, it wasn't easy to forecast.

    Two key takeaways from the survey were: for many organizations traditional approaches lacked planning agility; and tools to better connect shifts in volume and mix of services to financial outcomes are needed.

  2. Integrated planning tools can dramatically improve the budgeting process. The evolution of integrated planning concepts progress from unified, to connected, to directed planning. Connected planning describes the ability to effectively structure how historical patient-level data from decision support solutions is used to model how changes in service line volume and mix impact financial forecasts and operational budgets. Directed planning extends those capabilities by incorporating predictive modeling to help inform the assumptions. These capabilities translate effectively to rolling forecasting: a process that evaluates how current business driver trends will translate and impact future periods.

    "Adoption of rolling forecasting has accelerated over the last couple of years and is enabling more dynamic data-driven and future-focused planning in the industry," Mr. Spence said.

  3. Examples from other industries show how data science can better inform planning. Walmart and Netflix examine patterns through vast databases to determine what's needed in stores or what should be recommended viewing. Healthcare is also using data science effectively in some areas. For example, Cedars-Sinai in Los Angeles used early COVID-19 data to predict needs such as PPE with 85 to 95 percent accuracy, according to research cited by presenters during the webinar.

  4. Data science and predictive analytics hold great promise in healthcare. Forward-looking information, to predict service-line or department needs, relies on access to broad sets of data such as that offered by Syntellis. When budgeting, "it's great to see what happened, but it's even better to see what is going to happen," Mr. Wasson said.

Disruption continues in healthcare, which can make more agile planning a business imperative. Syntellis Performance Solutions’ Axiom Healthcare Suite helps healthcare organizations achieve directed planning, bringing together financial forecasting, planning, operational budgeting, and data analytics to support more effective and strategic decision-making.

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