Improving Hospital Efficiency Through Data-Driven Management

Abstract

This article presents a case study of how one health system—Health First, in Brevard County, Florida—addressed resource challenges by using Lean thinking enabled by information technology. Examining Health First provides an opportunity to learn about how one hospital system addressed these challenges by making fundamental changes in their operations, in advance of the shift toward accountable care. Three years after Health First embarked on an effort to streamline patient flow and improve throughput, adult transfers within the system have increased by more than 300 percent and emergency department times between admission and inpatient bed occupancy decreased by 37 percent.

In the United States, 31 cents out of every health care dollar—about $750 billion per year—is spent on hospital care (Martin et al., 2012). To constrain further growth in health care spending, the Center for Medicare and Medicaid Services (CMS) and other third-party payers are experimenting with bundled payments, Accountable Care Organizations, and other alternatives to change how hospitals are paid (Hussey et al., 2012). As these efforts grow, hospitals will face increasing challenges in providing better care at lower cost (Hussey et al., 2012; Hsia, Kellermann, and Shen, 2011).

While CMS and other payers are trying to find ways to constrain payments, hospitals must contend with the steadily rising cost of pharmaceuticals, supplies, medical technology, and personnel. Until now, most hospitals have been able to leverage their power in local markets to negotiate favorable rates (Hussey et al., 2012). As a result, the growth of operating income in hospitals has offset declining revenue from investments and charitable contributions (Health Leaders Media, 2013). However, as payment reform gathers steam, this strategy will become increasingly difficult to pursue.

Operational issues in hospitals add to these challenges. Aggregate national and state-level occupancy rates in hospitals mask the fact that occupancy tends to be high in large urban community and teaching hospitals (Health Leaders Media, 2013; National Center for Health Statistics, 2012, 2013; Institute of Medicine, 2006). More than ten years ago, a Lewin Group survey (2002) for the American Hospital Association reported that 90 percent of Level I Trauma Centers and hospitals with more than 300 beds were operating “at or above” full capacity, and high occupancy continues to plague hospitals today (Institute of Medicine, 2006; Pitts et al., 2012; US Government Accountability Office, 2009). Hospitals that operate at full capacity operate less efficiently, something that affects patient flow with spillover effects throughout the system, prolonging emergency department (ED) lengths of stay for admitted patients who then have to “board” in ED exam rooms or hallways (Institute of Medicine, 2006; Pitts et al., 2012; U.S. Government Accountability Office, 2009; Kellermann, 2010; Rabin et al., 2012). When ED crowding becomes unmanageable, many hospitals divert inbound ambulances (Burt, McCaig, and Valverde, 2006), and private providers choose to send elective admissions to other facilities, resulting in a loss of potential revenue, delays in care, and worse health outcomes (Henneman et al., 2009; Morganti et al., 2013; Shen and Hsia, 2015; Sun et al., 2013).

In the coming years, the fiscal and operational challenges U.S. hospitals face are expected to become more acute from a confluence of factors: the aging population (Strunk, Ginsburg, and Banker, 2006), the growing prevalence of chronic diseases (Thorpe and Howard, 2006), and expanded coverage but less generous payments (Kellermann et al., 2012; Litvak and Bisognano, 2011). Hospitals will not be able to respond as they once did by building larger facilities and charging higher fees. To address these changes, hospitals will need to operate more efficiently, while at the same time maintaining or improving quality of care and health outcomes (Kellermann et al., 2012; Litvak and Bisognano, 2011; California Healthcare Foundation, 2011).

In this article, we present a case study of how one health system—Health First, in Brevard County, Florida—addressed these challenges by using Lean thinking enabled by information technology (IT). Examining Health First provides an opportunity to learn about how one hospital system addressed these challenges by making fundamental changes in its operations in advance of the shift toward accountable care. Health First's experience may provide lessons and insights for all hospitals looking to improve operational efficiency.

To conduct our assessment, we reviewed relevant published literature, documents and videos, and performance metrics provided by Health First's leadership. During a one-day site visit to Health First in May 2015, we conducted semi-structured interviews with seven key leaders in Health First's administration. Leaders were identified in consultation with hospital management based on key domains chosen by the research team. Because our study did not involve personal health information or an experimental intervention, it was exempt from human subjects review.

This study was funded by TeleTracking Technologies, Inc., the company that developed the IT solution used by Health First. TeleTracking sought an objective, independent assessment of the effect of its software on efforts to increase hospital efficiency in one setting and selected Health First as the site of the study. RAND conducted this study after securing an agreement with TeleTracking that it would publish study findings regardless of whether they were positive or negative.

What Is Lean Process Improvement?

To improve quality and efficiency while constraining costs, some hospitals have adopted quality improvement methodologies from industries outside of health care (Mason, Nicolay, and Darzi, 2015; Niemeijer et al., 2012). One such approach is Lean methodology. Initially developed by Toyota, Lean focuses on process improvement, affecting both structural components (e.g., technology, staffing, physical setup) and operational processes (Mason, Nicolay, and Darzi, 2015; Niemeijer et al., 2012).

The key goal of Lean is to deliver value to the consumer—in this case, the patient (Joosten, Bongers, and Janssen, 2009; Bowerman and Fillingham, 2007). Value is added by eliminating waste and duplicative elements of a system (Joosten, Bongers, and Janssen, 2009; Bowerman and Fillingham, 2007; Brandao de Souza, 2009). Instead of departments acting as individual units, departments are coordinated with streamlined operations (Bowerman and Fillingham, 2007). Lean is often combined with Six Sigma, an approach created by Motorola, which seeks to standardize processes to reduce errors (Joosten, Bongers, and Janssen, 2009). (Six Sigma is a data-driven approach and methodology for eliminating defects [driving toward six standard deviations between the mean and the nearest specification limit] in any process—from manufacturing to transactional and from product to service.)

Lean implementation occurs in a stepwise approach. First, a given organization must assess current operations and determine what is considered valuable to the patient as a consumer (Radnor, Holweg, and Waring, 2012). Next, the organization must take steps to implement improvement-oriented measures in a rapid cycle approach by bringing associates together to brainstorm and redesign various processes (Radnor, Holweg, and Waring, 2012). Finally, such changes are reassessed by reviewing performance data to ensure that the revised approach offers benefits (Radnor, Holweg, and Waring, 2012). The process is repeated multiple times as needed to address multiple aspects of a system performance.

A critical enabler of implementing Lean process improvement is access to data (Hsieh, Lin, and Manduca, 2007). In Lean, data are used at all levels of an organization and at every step in process improvement. IT can play a critical role in enabling the collection and use of data to assist with real-time daily operations and for review by managers to modify processes and improve efficiency (Hsieh, Lin, and Manduca, 2007).

Key Findings

• Metrics provided by Health First and staff interviews suggest that patient-flow initiatives substantially streamlined hospital operations and produced enormous gains in efficiency. Three years after Health First embarked on an effort to streamline patient flow and improve throughput, adult transfers have increased by more than 300 percent and emergency department times between admission and inpatient bed occupancy decreased by 37 percent.

• One key to initiative success was that the health care system's executive management articulated clear strategic goals and supported efforts to implement process improvement initiatives that focused on streamlining patient flow.

• The bed-tracking and hospital operation software used in our case study generates actionable, real-time data. It is used routinely by Health First associates to inform and execute operational decisions and allows system managers to spot bottlenecks, hold individual units and employees accountable, and track the health system's overall performance.

• Health First managers focus on continual process improvement, listen to suggestions from their associates, and create an environment of accountability and friendly competition with incentives for improved performances.