Case Analysis: Systems Acquisition

Chapter 4 Information Systems to Support Population Health Management Learning Objectives To be able to understand the data and information needs of health systems in managing population health effectively under value-based payment models. To be able to discuss key health IT tools and strategies for population health management including EHRs, registries, risk stratification, patient engagement, and outreach, care coordination and management, analytics, health information exchange, and telemedicine and telehealth. To be able to discuss the application and use of data analytics to monitor, predict, and improve performance. The enactment of the Affordable Care Act (ACA) brought about sweeping legislation intended to reduce the numbers of uninsured and make health care accessible to all Americans. It also ushered in an era in which changing reimbursement and care delivery models are driving providers from the current fragmented system focused on volume-based services to an outcomes orientation. As a result, the health care system now taking shape is one in which value-based payment models financially reward patient-centered, coordinated, accountable care. Against this backdrop, providers' increasing use of evidence-based medicine and growing capabilities in managing volumes of clinical evidence through sophisticated health IT systems will mean that treatments can be tailored for the individual and interventions can be made earlier to keep patients well. Furthermore, patient engagement is fast becoming a critical component in the care process, particularly in the area of population health management (PHM). Health care providers' interest in improving population health appears to be increasing because of the sudden ubiquity of the phrase, because many are participating in accountable care organizations (ACOs), and because even hospitals not participating in an ACO increasingly have incentives to reduce their number of potentially unavoidable admissions, readmissions, and emergency department visits (Casalino, Erb, Joshi, & Shortell, 2015). In this chapter we'll not only seek a common understanding of PHM but also explore how the advent of shared accountability financial arrangements between providers and purchasers of care has created significant focus on PHM. We'll also review the core processes associated with accountable care and examine the strategic IT investments and data management capabilities required to support population health management and enable a successful transition from volume-based to value-based care. PHM: Key to Success Although the ACO model is still new and evolving, approximately 750 ACOs are in operation today, covering some 23.5 million lives under Medicare, Medicaid, and private insurers. Although not all ACOs have demonstrated success in delivering better health outcomes at a lower cost, many have achieved promising results (Houston & McGinnis, 2016). As such, significant ACO growth is expected. In fact, it is predicted that upward of 105 million people will be covered by an ACO by 2020 (Leavitt Partners, 2015). Similarly, although the industry's move to value-based payment is also in its early stages, value-based contracts are expected to substantially increase throughout the next decade. CMS has a stated goal that 50 percent of Medicare payments will be tied to alternative payment models by the end of 2018 (US DHHS, 2015). In fact, the projected impact of MACRA, which we discussed in Chapter One, on the adoption of value-based payment models is expected to rival the impact of Meaningful Use on adoption of EHRs. In addition, the substantial payment reform activity at the federal level is paralleled by private insurers' efforts to support value-based payment and new models of care. For example, Aetna expects that 75 percent of its contracts will be value-based by 2020 (Jaspen, 2015). These trends will accelerate the demand for services and technology that enable health systems and other organizations (health plans, Medicaid, community-based organizations, employers, and so forth) to jointly manage the health and care of populations—either as an ACO or in an ACO-like fashion. Although diverse, these organizations will all have a common need to improve operational efficiency, drive better patient outcomes while reducing the overall cost of care, and effectively engage consumers in managing their health and care. Although the new reimbursement system is still taking shape, it's clear that population health management will become a required core competency for provider organizations in a post fee-for-service payment environment (Institute for Health Technology Transformation, 2012). Understanding Population Health Management Population health as a concept first appeared in 2003 when David Kindig and Greg Stoddart (2003) defined it as “the health outcomes of a group of individuals, including the distribution of such outcomes within the group” (p. 380). It is important to note that medical care is only one of many factors that affect those outcomes. Other factors include public health interventions; aspects of the social environment (income, education, employment, social support, and culture); the physical environment (urban design, clean air and water); genetics; and individual behavior (Institute for Health Technology Transformation, 2012). “Improving the health of populations” was later identified as one element in the Institute for Healthcare Improvement's triple aim for improving the US health care system, along with improving the individual experience of care and reducing the per capita cost of care (Berwick, Nolan & Whittington, 2008, p. 759). Today, population health management comprises the proactive application of strategies and interventions to defined groups of individuals (e.g., diabetics, cancer patients with tumor regrowth, the elderly with multiple comorbidities) to improve the health of individuals within the group at the lowest cost. PHM interventions are designed to maintain and improve people's health across

Chapter 6 System Implementation and Support

Learning Objectives

· To be able to discuss the process that a health care organization typically goes through in implementing a health care information system.

· To be able to assess the organizational and behavioral factors that can affect system acceptance and use and strategies for managing change.

· To be able to develop a sample system implementation plan for a health care information system project, including the types of individuals who should be involved.

· To gain insight into many of the things that can go wrong during system implementations and strategies that health care manager can employ to alleviate potential problems.

· To be able to discuss the importance of training, technical support, infrastructure, and ongoing maintenance and evaluation of any health care information system project.

Once a health care organization has finalized its contract with the vendor to acquire an information system, the system implementation process begins. Selecting the right system does not ensure user acceptance and success; the system must also be incorporated effectively into the day-to-day operations of the health care organization and adequately supported or maintained. Whether the system is built in-house, designed by an outside consultant, or leased or purchased from a vendor, it will take a substantial amount of planning and work to get the system up and running smoothly and integrated into operations.

This chapter focuses on the two final stages of the system development life cycle: implementation and then support and evaluation. It describes the planning and activities that should occur when implementing a new system. Our discussion focuses on a vendor-acquired system; however, many of the activities described also apply to systems designed in-house, by an outside developer, or acquired or leased through cloud-based computing services.

Implementing a new system (or replacing an old system) can be a massive undertaking for a health care organization. Not only are there workstations to install, databases to build, and networks to test but also there are processes to redesign, users to train, data to convert, and procedures to write. There are countless tasks and details that must be appropriately coordinated and completed if the system is to be implemented on time and within budget—and widely accepted by users. Essential to the process is ensuring that the introduction of any new health care information system or workflow change results in improved organizational performance, such as a reduction in medication errors, an improvement in care coordination, and more effective utilization of tests and procedures.

Concerns have been raised about the potential for EHRs to result in risk to patient safety. Health care information systems such as EHRs are enormously complex and involve not only the technology (hardware and software) but also people, processes, workflow, organizational culture, politics, and the external environment (licensure, accreditation, regulatory agencies). The Institute of Medicine published a report that offers health care organizations and vendors suggestions on how to work collaboratively to make health IT safer (IOM, 2011). Poor user-interface designs, ineffective workflow, and lack of interoperability are all considered threats to patient safety. Several of the suggested strategies for ensuring system safety are discussed in this chapter.

Along with attending to the many activities or tasks associated with system implementation, it is equally important to manage change effectively and address organizational and behavioral issues. Studies have shown that over half of all information system projects fail. Numerous political, cultural, behavioral, and ethical factors can affect the successful implementation and use of the new system (Ash, Anderson, & Tarczy-Hornoch, 2008; Ash, Sittig, Poon, Guappone, Campbell, & Dykstra, 2007; McAlearney, Hefner, Sieck, & Huerta, 2015; Sittig & Singh, 2011). We devote a section of this chapter to strategies for managing change and the organizational and behavioral issues that can arise during the system implementation process. The chapter concludes by describing the importance of supporting and maintaining information systems.

System Implementation Process

System implementation begins once the organization has acquired the system and continues through the early stages following the go-live date (the date when the system is put into general use for everyone). Similar to the system acquisition process, the system implementation process must have a high degree of support from the senior executive team and be viewed as an organizational priority. Sufficient staff, time, and resources must be devoted to the project. Individuals involved in rolling out the new system should have sufficient resources available to them to ensure a smooth transition.

The time and resources needed to implement a new health care information system can vary considerably depending on the scope of the project, the needs and complexity of the organization, the number of applications being installed, and the number of user groups involved. There are, however, some fundamental activities that should occur during any system implementation, regardless of its size or scope:

· Organize the implementation team and identify a system champion.

· Clearly define the project scope and goals.

· Identify accountability for the successful completion of the project.

· Establish and institute a project plan.

Failing to appropriately plan for and manage these activities can lead to cost overruns, dissatisfied users, project delays, and even system sabotage. In fact, during the industry rush to take advantage of CMS incentive dollars, a flurry of EHR stories hit the news—with everything from CIOs and CEOs losing their jobs as a result of “failed” EHR implementations, to hospital operations screeching to a halt, to significant financial problems arising from glitches in the revenue cycle. These high-profile cases brought national attention to the consequences of a failed implementation. During system implementation, facilities often see their days in accounts receivable and denials increase while cash flow slows. By organizations anticipating risks