The healthcare industry’s migration from reporting to business intelligence use has not been transformative. Providers have tended to adhere to traditional key performance indicators (KPIs), and emerging architecture for analysis tends to be disparate and promote a silo mentality. Meanwhile, key information for realistic modeling and trending lacks sufficient detail and organization.
The limitations of current approaches can be likened to a car dashboard. These dashboards are critical for making active decisions: We look at the gas gauge to determine when to stop for gas, and at the speedometer to determine whether we are going too fast or too slow. However, an owner of a car on the road cannot determine by looking at the gauges whether he or she is on the right road, whether it’s time to buy or trade in for a new car, or what conditions may cause damage requiring maintenance or repair.
Likewise, in health care, a dashboard is a grouping of gauges for snapshot readings and cannot provide executives with specific insight for targeted strategic decision making, with prioritization, for addressing operational issues. Gauges are effective at the operational level for monitoring supplies, ensuring necessary inventory, and complying with regulations such as correct temperatures and shelf life for implant storage. But when it comes to executive action, these kinds of dashboards are only snapshots that provide insufficient information for strategic action.
When migrating to business intelligence tools, the common practice among healthcare organizations has been to create dashboard gauges using KPIs historically used in reporting, such as case mix index (CMI) and length of stay (LOS). Information from these gauges is useful at low, operational levels, but the numbers are static and not well correlated for a tactical overview. When looking at just CMI and LOS numbers, for example, it’s impossible to tell whether value-based payment levels are sufficient to cover costs, or to see how the numbers relate to increased acuity in relation to comorbidities, charges, patient engagement, and quality outcomes.
U.S. health systems are expanding their business models with myriad issues including top-down cost allocation, business intelligence tools that do not provide adequate information for decision making, and a lack of integrated proactive planning at the ground level of operations. This issue is important to address given the ongoing focus on expanding the capitation payment model. The assumption of executives looking to maintain operating margin under capitation is that volumes will decrease, reducing FTEs, overtime, and LOS. Historically, however, organization margins have been affected along with quality, because organizations remained top-heavy, without integrated modeling of contracted payer mix and acuity of patients at the department level and proper alignment of the workforce.
Recently, an accounting executive wrote to me, “Nurses are the most important part of health care.” Unfortunately, when modeling operational plans, budgeting, and trending strategies, healthcare providers do not view the nursing workforce in their models as both the greatest asset and greatest expense in relation to all strategies, and do not take into account cost details that are needed across continuums at the departmental level.
Under capitation, the assumption is that care will shift from acute to outpatient and home care. Without proper modeling of a detailed, integrated workforce as well as efficiency and quality associated with strategies, costs simply shift rather than go down, and surprise costs and outcomes surface when acuity or volumes do not decrease under covered lives.
When the standard healthcare business model migrates to a top-down cost allocation with covered lives (and shared risk value models), the focus turns to saving money by reducing LOS, overtime, and FTEs. When executives use only these KPIs, the savings often are elusive when patient acuity remains high, necessitating more staff and leading to rising cost with increased and expensive agency nursing coverage; or quality is impacted, such as through a rise in hospital-acquired infections.
It’s time to design a better paradigm, including lighter overhead with top-down strategy, bottom-up modeling using detailed workload instead of focusing solely on volume, and workforce design based on strategies and aligned with payment contracting. What is needed is an approach that involves amalgamated financial and operational reviews at the executive level allowing tactical issues that must be addressed to be rapidly prioritized, and that includes comprehensive, integrated analysis at the operational and departmental levels using real-time dashboards.
The healthcare hierarchy should be streamlined with lower overhead, and executive data correlations should expand, moving away from the traditional focus on static gauges and toward ensuring that workload, workflow, workforce, quality, efficiency, cost, and operating margin are integrated for the various service lines. Such an approach will ensure that leadership can set clear targets and priorities among strategic actions that are directed to achieving those targets.
