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Evaluation of Practice at the Population Level

Barbara A. Niedz

Early in their careers, nurses often have an enthusiasm and energy for caring for one patient at a time. Over the years that focus broadens as the more experienced nurse embraces a role that is more expansive and addresses issues at a population level. As administrators, leaders, educators, and managers, the advanced practice registered nurse’s (APRN’s) scope of practice widens even further. Quality nurse professionals expand their view to the entire organization and across departments. Nurses have, over the years, moved in many diverse directions. We not only care for patients at the bedside, but in their homes, businesses, schools, prisons, rehabilitation settings, as well as in outpatient and mental health facilities. Nurses also serve in settings that may be considered more “nontraditional”: for example, working for managed care organizations (MCOs) by providing utilization management, and designing and implementing case and disease management programs. Another critical responsibility of APRNs is the oversight of clinical outcomes at the population level.

The advancement of many educational opportunities for nurses has moved our profession into new and exciting places. The advent of the advanced practice licensure designation has opened doors for nurses that did not exist 20 years ago. Nursing has become proactive and more responsive to the needs of the healthcare environment and to the needs of our patients. APRN status and licensure expand the nursing role to include status as primary care providers, and APRNs are recognized in many preferred provider networks across the country, receiving appropriate reimbursement. Our potential to influence the health of patient populations has expanded accordingly.

This chapter describes ways to evaluate population outcomes, systems’ changes, as well as effectiveness, efficiency, and trends in care delivery across the continuum. Strategies to monitor healthcare quality are addressed, as well as factors that lead to success. Most important, these concepts are explored within the role and competencies of the APRN.

MONITORING HEATHCARE QUALITY

Nash, Reifsnyder, Fabius, and Pracilio (2011) explain that the concept of population health includes an integrated system of care across the continuum. The population health model “seeks to eliminate healthcare disparities, increase safety, and promote effective, equitable, ethical and accessible care” (p. 4). They explain that quality is defined in terms of clinical data and outcomes, both economic and patient centered. In their view, “quality is founded on evidence based medicine” (p. 5) and describes the relationship between quality of care and the cost of care; if the quality of care improves, the cost of care is reduced (Nash et al., 2011). Nash et al. (2011) describe the importance of prevention, screening, and patient self-care management. They describe the importance of identifying risk factors to the development of chronic illness and the influence of the community, the availability of and access to various programmatic elements that can help manage and reduce the cost of care. The incidence of diabetes mellitus could potentially be reduced by getting control of the rampant obesity problem across the United States. As an example of a prevention indicator of quality for health plans, monitoring the patient’s body mass index (BMI) is an important Healthcare Effectiveness Data and Information Set (HEDIS) measure and is also included in the Centers for Medicare & Medicaid Services Five-Star Quality Rating System (CMS STARs) measures. Preventing the incidence of diabetes mellitus can potentially result in reducing its short- and long-term complications, which could subsequently save thousands, perhaps hundreds of thousands, of healthcare dollars. As an example, consider the impact of preventing the incidence of type 2 diabetes mellitus on end-stage renal disease (ESRD), and the cost of dialysis alone. In 2012, Medicare expenditures for outpatient dialysis were $10.7 billion (Medicare Payment Advisory Committee, 2014).

The Institute for Healthcare Improvement (IHI) puts the ideas of Nash et al. (2011) into action in the Triple Aim initiative. The goals of the Triple Aim are (a) better health, (b) better experience of care, and (c) lower cost. The Triple Aim framework serves as the model for many organizations and communities (Bisognano & Kenny, 2012). The Triple Aim site can be accessed at www.ihi.org/Topics/TripleAim/Pages/default.aspx.

Juran (DeFeo, 2014; DeFeo & Juran, 2010) offers a definition of quality that is both parsimonious and applicable across disciplines. He defines quality in terms of the customer and explains that a product or service has quality if it is “fit for use” in the eyes of the customer. Goonan (1995) and Dienemann (1992) have applied Juran’s definition to healthcare scenarios. Patients, as consumers of healthcare products and services, fit the definition of customers, regardless of the payment source. Juran (DeFeo, 2014; DeFeo & Juran, 2010) explains that for a product or service to meet the needs of the customer, it must have the right features and must be free from deficiencies.

In Juran’s view (DeFeo & Juran, 2010), new features (such as new cardiac surgical equipment or the capacity to provide outpatient dialysis) may require capital and operating expenses. Deficiencies or defects in our healthcare products or services always contribute to the cost of poor quality. The cost of one hospital-acquired infection has been estimated at $15,000 by McCaughey (2006) and may range from as low as $500 to as much as $50,000 (Hassan, Tuckman, Patrick, Kountz, & Kohn, 2010). Hospitals are no longer reimbursed for the cost associated with the development of a third- or fourth-degree pressure ulcer in a patient if that ulcer was hospital acquired and not present on admission. The Centers for Medicare & Medicaid Services (CMS), which functions under the aegis of the U.S. Department of Health and Human Services (HHS), promulgated rules to this effect in 2008 (see www.cms.gov/HospitalAcqCond). The development of a hospital-acquired third- or fourth-degree pressure ulcer is also included in the National Quality Forum’s list of “never events” (“The Power of Safety,” 2010). In recent years, CMS has dictated by law and regulation that hospitals will not be reimbursed for care related to 14 of these never-event conditions that occur during an inpatient admission (CMS, 2014a). Other preventable outcomes that contribute to the cost of poor quality have consequences that go beyond dollars and cents. Deficiencies that result in complications and even death arise from poor systems and human failures. These have gotten significant and appropriate attention through the patient safety movement (Institute of Medicine [IOM], 1999, 2001). Through TJC and the National Patient Safety Goals, attention to hospital and other healthcare organizations has resulted in significant strides toward reducing deficiencies. The importance of improving quality by avoiding the “never events” and reducing deficiencies has reinforced the necessity of accurate and thorough documentation and medical decision making by all healthcare providers.

Although Juran’s definition of quality does have merit and application in healthcare (Kaplan, Bisgaard, Truesdell & Zetterholm, 2009; Muerer, McGartland-Rubio, Counte, & Burroughs, 2002), capturing ways and means to measure both outcome and process indicators of quality have emerged from an evidence-based approach. For example, research literature has shown that in order to decrease the incidence of congestive heart failure (CHF) hospital readmission rates, inpatient discharge instructions should capture key components, including (a) discharge medications, (b) the importance of weight tracking and documenting daily, (c) diet control, (d) what to do if symptoms worsen, (e) activity level restrictions, and (f) follow-up care instructions (Agency for Healthcare Research and Quality [AHRQ], 2014). Lack of any of these components is clearly seen as a “deficiency” and should be captured across aggregate data sets in hospitals (see http://www.jointcommission.org/). Thus, measurement mechanisms emerge from Juran’s definition of quality (2010), which also fit with Donabedian’s (1980) framework of structure, process, and outcome and Nash et al.’s (2011) view of population health.

Organizational Models for Excellence

Nurses provide the backbone of healthcare organizations, whether inpatient, outpatient, rehabilitation, home care, community health, or in an MCO. Services can be provided in person or sometimes via the telephone. In certain circumstances, nurses provide support by developing and monitoring telehealth programs. As such, understanding the organizational framework that can maximize positive outcomes and minimize deficiencies through the role of the nurse has value. The APRN, in particular, adds value, particularly through oversight and development of these newly emerging models of care.

Both Defeo and Juran (2010) and Donabedian (1980) put the concept of quality into the framework of an organization. Care of a patient across the wellness–illness continuum requires consistent and cogent processes and systems. Accordingly, Donabedian’s view is that healthcare organizations require appropriate structure and key processes. Taken together, the structure and processes assist the organization in producing desired outcomes for their patients (Donabedian, 1980). Juran characterizes organizations as high functioning and marked by positive outcomes if features are maximized and deficiencies are minimized. In order to accomplish this, organizations plan for, control, and continuously improve quality. Both clinical and service quality characteristics are defined in terms of customers’ needs and expectations. Others have made similar observations in applying Juran’s organizational model in healthcare organizations (Best & Neuhauser, 2006; Goonan & Scarrow, 2010; Maddox, 1992). In 1987, the federal government instituted the Malcolm Baldridge Award, which recognizes those organizations that demonstrate principles characteristic of high performance and achieve significant business results through quality-improvement techniques. This award is based on seven key guiding principles and embodies the theoretical model of quality that Juran honed throughout his career (DeFeo & Juran, 2010; National Institute of Standards and Technology [NIST], 2015). In the late 1990s, this award was opened to healthcare organizations. Between 2002 and 2014, there were 17 winners of the Baldridge Award in the healthcare division (NIST, 2015).

W. Edwards Deming (Moen & Norman, 2010) developed similar theories of quality and consistently modeled the theme of reducing variation, and building quality into a product or system so that there is less need to depend on inspection (after the fact). Deming’s model was also influenced by the work of other quality giants, like Shewhart and Feigenbaum (“Guru Guide,” 2010). Ishikawa (“Guru Guide,” 2010) paved the way for Japan’s economic turnaround after World War II, largely based on the work of both Juran and Deming, who were sent by the U.S. government to support Japan after the war. These models rely heavily on the theory that all of quality is measurable and that reducing variation in processes holds a vital role in reducing the incidence of defects and, ultimately, assuring better outcomes.

Deming (Moen & Norman, 2010), Juran (2010), Crosby (“Guru Guide,” 2010), and others explain that reducing variation is a continuous task, even when a given product or service is exceeding the needs of customers and especially when a given product or service is not competitive in the marketplace. The Six Sigma movement (DeFeo & Barnard, 2004; Pyzdek & Keller, 2009) emerged from a quality-improvement initiative at General Electric in the 1980s and set out to reduce defects or deficiencies to fewer than 3.4 defects per 1,000,000 opportunities. In essence, this model for quality improvement and planning is built on the work of Juran, Deming, Crosby, Ishikawa, Feigenbaum, and others (“Guru Guide,” 2010). Although it is clear that Donabedian’s work is theoretically sound, it also resonates with this thinking. In designing an influenza vaccination process for employees using the Six Sigma approach, Kaplan, Bisgaard, Truesdaell, and Zetterholm (2009) applied the model to a population health issue. Many others have applied the Six Sigma theoretical model to various healthcare processes. This model has significant application for process improvement across the spectrum of healthcare processes (Corn, 2009). To illustrate the application of process improvement theory and the use of Six Sigma models, consider the studies presented in Table 8.1.

Developing a Six Sigma approach works best when it is done broadly, across the entire organization. When a Six Sigma approach is well defined for a given organization, the impetus and funding source for the program comes directly from governance and cascades from the senior leadership team throughout, to the frontline employees, who use the systems and processes within them on a day-to-day basis. Deciding which projects are convened and which are not is also a governance process, and would likely emerge out of the quality infrastructure. Governance provides for an educational process to learn and apply the use of the many tools in the Six Sigma tool chest, many of which have a heavy statistical process control overlay. Six Sigma leadership uses an educational process in the form of various “belts” for certification. For example, a master black belt possesses the skills to oversee multiple Six Sigma projects simultaneously. The black belt is typically the project facilitator; green belts are often process business owners and may serve as the team lead in a Six Sigma team. The yellow belt is the team member who will also be schooled in the use of many of the tools (Pyzdek & Keller, 2009).

The patient safety movement in healthcare has given rise to a wider application of the Six Sigma model. In addition, the language of defects and deficiencies, though developed out of manufacturing and other type of product development, has resulted in consistent thinking that complications heretofore considered risks of procedure or hospitalization are now considered preventable (Courtney, Ruppman, & Cooper, 2006). The patient safety movement in the United States emerged largely due to the TJC and their attention to sentinel events (Joint Commission Resources, 2003). In addition, the consensus report of the Institute of Medicine “To Err Is Human,” published by the IOM in December 1999, provides a focus on the potential for preventable error. One of the most telling comments early in the book explains that there are between 44,000 and 98,000 preventable medical errors annually in the United States that lead to patient deaths (IOM, 1999). The variability in the range is significant. Measurement mechanisms that would provide accurate descriptions of these sentinel events did not exist at that time. In the language of the process improvement gurus, these are defects and deficiencies. Applying these theoretical models to healthcare has tremendous potential in accurately describing quality of care by improving outcomes through attention to process.

TABLE 8.1    •    Examples of Process Improvement Theory and the Use of the Six Sigma Model

Kaplan and Norton (1996, 2001) take measurement in organizations a step further and link progress against the strategic planning cycle to organizational goals and objectives. Their “balanced scorecard” model lends itself to healthcare well, and has been applied internationally (Chu, Wang, & Dai, 2009; Moulin et al., 2007; Potthoff & Ryan, 2004; Yap, Siu, Baker, Brown, & Lowi-Young, 2005). In fact, the Malcolm Baldridge Award has several specific criteria (see www.nist.gov/baldrige/publications/hc_criteria.cfm), and one of the most important is the recognition of “results.” The results criteria require evidence of measurement and improvement of quality across organizations and systems. A well-defined scorecard at the enterprise level, which is balanced across several categories relating to the customer’s experience, is a useful and important tool for senior leadership and governance. As we move into a discussion about planning, controlling for and improving quality across the entire patient population, understanding theoretical models for process improvement and their application becomes not only useful and accepted, but necessary and, most important, leads to improved outcomes of care.

Process Improvement Models and Tools

The literature provides applied evidence of various process improvement models that have many commonalities. Deliberate and thoughtful use of applied evidence and the use of process improvement models can result in reduction of defects and deficiencies to levels that meet and exceed customers’ expectations, whether those expectations surround clinical quality, customer satisfaction, core business process, or utilization of healthcare resource expectations. The “plan, do, check, act” (PDCA) process improvement model (Moen & Norman, 2010); the Juran Six-Step Quality Improvement Process model (DeFeo & Juran, 2010); or Six Sigma’s define, measure, analyze, improve, and control (DMAIC) model all have common features and they are all problem-solving models that drive measurable improvement when used properly. They can facilitate a thought process and require a team initiative. They will work whether the problem is related to clinical quality, customer satisfaction, core business processes, or utilization of healthcare resources. They work inside and outside of healthcare, whether the problem is simple or complex and whether one is concerned about the care of patients or developing tangible products for retail sale. Table 8.2 describes characteristics that are commonly found in process improvement models.

TABLE 8.2    •    Characteristics and Commonalities of Process Improvement Models

Population-Based Models

On a continuum from health and wellness (H&W) products to complex care management, a variety of population-based models have emerged over recent years (Table 8.3). Patients move across a continuum from good health to the end of life and enter a variety of settings in doing so. Programs are designed to offer both telephone care and field-based approaches to prevention, disease management (DM), care coordination, case management (CM), and care integration. Patients are identified through predictive models and other stratification methods. The extent of outreach is determined by various levels of acuity, and the frequency of patient contact may depend on clinical assessment and care planning. Motivational interviewing and health education are primary strategies to engage patients into modifying their behaviors, but a hallmark of all of these programs is ultimately a change in health behaviors, which leads to desired outcomes. Preventive strategies such as smoking-cessation programs, as well as care coordination strategies such as identifying a medical home and assuring medical transportation to an outpatient facility, combined with condition-specific strategies in the presence of various chronic disease states, to reduce the incidence of ED usage for primary care and reduce inpatient admissions are all examples of ways to improve access to care in the hopes of ensuring overall quality of care (Fetterolf, Holt, Tucker, & Khan, 2010; Moreo & Urbano, 2014; O’Toole et al., 2010; Rice et al., 2010). Research has shown that disease and CM programs are effective in reducing the trajectory of chronic disease by providing less utilization of healthcare resources and providing enhanced patient satisfaction by improving the patient’s ability to perform activities of daily living and improving her or his ability to manage chronic diseases (self-efficacy) Baicker, Cutler, & Song, 2010; Bedell & Kaszkin-Bettag, 2010; Govil, Weidner, Merritt-Worden, & Ornish, 2009; Lamb, Toye, & Barker, 2008; Rantz et al., 2014).

TABLE 8.3    •    Population Health Models

One of the most interesting recent trends in population-based care management is care integration. Care integration is a concept that is well known to nurses, but may not be as familiar to other health professionals. Here’s an example: A patient is admitted to an inpatient acute care hospital with a significant drug overdose, subsequent to an attempted suicide. This long-standing behavioral health (BH) patient has been managed “on and off” by a variety of BH professionals, and has been receiving various psychotropic medications. In addition, the patient has a medical history that includes long-standing diabetes and CAD; other healthcare professionals have managed these aspects of the patient’s healthcare. In fact, the medical professionals have not been in touch with the BH professionals, at the patient’s request. In the ED, the BH professionals’ role is pre-empted as the patient’s overwhelming medical needs are the priority. When the patient is admitted to the intensive care unit (ICU), a host of consultants are brought to the case, and after being “cleared medically,” the patient is transferred to the inpatient BH unit. Care is sometimes fragmented and the BH needs are addressed separately and apart from the medical needs of the patient. The primary care physician may not be involved until after discharge and may not have a clear sense of the many issues that play a role in the complete care of this patient. Although there is no question about the prioritization of care, there is also no integration of care. The patient’s experience is divided into two distinctly different phases, in some ways compromising effective use of healthcare resources. This is where the importance of the medical home comes into play. Length of stay is clearly segmented into two sequential phases rather than managed in parallel. Although this inpatient example is a familiar one, lack of care integration is a common problem also on the outpatient side of the care continuum. Processes of care that appropriately integrate care have been somewhat problematic in the U.S. healthcare system in the past. In recent years, it has become apparent that care integration needs to improve, which would improve the quality of care, resolve access issues, and reduce overutilization of healthcare resources (Gill, Swarbrick, Murphy, Spagnolo, & Zechner, 2009; Godchaux, 1999; Santos, Henggeler, Burns, Arana, & Meisler, 1995; Weinstein, LaNoue, Collins, Henwood, & Drake, 2013).

Two recent initiatives bring these ideas into sharp perspective. The first is the concept of the patient-centered medical home (PCMH). Within this model, care integration services are well defined and the process of bringing care to the patients where, when, and how they need them becomes not only possible but practical. The NCQA promulgates standards that describe this initiative (see www.ncqa.org/tabid/1302/Default.aspx). Accountable care organizations (ACOs) provide another model that incorporates these ideas into organized systems of care with healthcare providers, PCMHs, and hospitals partnering together. This is a program furthered by the CMS (see www.cms.gov/PhysicianFeeSched/downloads/10-5-10ACO-WorkshopAMSessionTranscript.pdf and www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/ACO/index.html?redirect=/ACO).

Nurse-Sensitive Process and Outcome Indicators at the Population Level

Many authors have promulgated ways to organize measures, as taken together they represent a picture of quality. Kaplan and Norton (1996, 2001) suggest four generic categories that could work for any organization, including organizations that focus on healthcare. These perspectives include (a) internal business processes, (b) customer focus, (c) learning and growth, and (d) financing. The NCQA places the HEDIS measures into categories as well. The HEDIS categories include (a) effectiveness of care, (b) access/availability of care, (c) satisfaction with the experience of care, (d) use of services, and (e) cost of care (HEDIS, 2014).

Although the list of possible indicators used to measure population health and population health nursing may seem endless, four categories of measures, metrics, and indicators emerge. These broad categories are clinical quality, customer satisfaction, core business processes, and utilization of healthcare resources. Loosely based on Kaplan and Norton (1996, 2001) and the NCQA HEDIS frameworks, an organizing framework for evaluating population health nursing emerges. As these categories are of use in organizing our thinking regarding quality in the inpatient setting, they also have merit in outpatient settings, and as we consider care of the entire population with a given disease condition, these categories continue to add value to this discussion as an organizing framework. For the purpose of this discussion, the words “measures,” “metrics,” and “indicators” are used interchangeably. As we have put forward a definition of quality that is “measurable,” our measures are quantifiable, a set of metrics that indicate the presence or absence of quality, and degrees on that continuum.

Whenever possible, standardized data definitions are essential. This sets up a level playing field for comparisons. Since the late 1990s, data sets, external comparisons, and guidance for standardized numerator and denominator have emerged across the patient continuum of care. As our industry has become more accountable to the public for outcomes, this kind of standardization has been essential, facilitating external comparisons on the basis of data sets. In addition, these numerators and denominators are described in detail, right down to the technical specifications. These technical specifications describe what types of codes are included in the numerator and which are included and excluded in the denominator. These codes have become widely accepted, the application of which results in fair and appropriate comparisons and rankings. Various groups (both governmental and private) have defined measures, specified the technical mechanics of counting and determining rates, and applied these measures across the industry. These include, but are not limited to, (a) CMS (www.cms.gov/center/quality.asp), (b) TJC (www.jointcommission.org), (c) the Agency for Healthcare Research and Quality, (d) NCQA (www.ncqa.org), (e) the National Quality Forum (NQF; www.qualityforum.org), and (f) the National Database of Nursing Quality Indicators (NDNQI; http://www.pressganey.com/ourSolutions/performance-and-advanced-analytics/clinical-business-performance/nursing-quality-ndnqi).

Measures have also emerged over time. As our foray into this area of accountability for outcomes has been heightened by legislators, policy makers, and the public at large, the connection between the cost of poor quality in healthcare and healthcare reform has become more explicit. Although it might require capital and operational outlay of funding to develop a specific product or service with the right features within the healthcare industry, the cost of poor quality adds a substantial burden to the cost of healthcare. For example, when a patient in a hospital setting experiences a delay in obtaining a diagnostic procedure that is essential to the appropriate management of his or her disease state, this core business process can delay decision making, causing a longer length of stay for the patient in the hospital. This delay may also lead to disease progression and result in complications that otherwise might have been prevented. Another question that should be addressed is whether these types of delays are due to the type of insurance, underinsurance, or lack of insurance. As discussed in Chapter 2, an important component of APRN practice is the need to recognize and address issues related to healthcare disparities.

When patient safety is compromised in hospitals, the result can be substantial. The example of delayed diagnostic testing may not only hinder the determination of a patient’s diagnosis but may lead to patients receiving inaccurate medications or treatments or errors, such as a patient identification mix-up, that can result in loss of life. Over time, we are better able to identify the impact of the cost of poor quality by capturing and quantifying these indicators of quality in the aggregate. Sorting out “what counts and what doesn’t” helps to provide clarity and a clearer view of quality across the board.

Clinical Quality

Nurse-sensitive indicators of population health that relate to clinical quality can be seen in a number of the metrics recognized by external organizations with available external benchmarks. In the HEDIS (NCQA, 2014a) data set created and maintained by the NCQA, there are several benchmarks that relate to chronic disease conditions. Nurses, who are in the field or on the phone in telephone call centers, reach out to patients with the intention of helping them wade through the various resources made available to them through private and public means to manage their overall health, given the presence of various disease states. The most common disease states managed by DM programs include (a) diabetes mellitus, (b) persistent asthma, (c) COPD, (d) CAD, and (e) CHF. Other chronic disease conditions also may be of interest. In CM programs, the complexity of care is heightened by the number and acuity of the chronic conditions coexisting in a patient’s profile. Social problems, housing, transportation, and pharmacy costs often emerge in CM programs. Similarly, the emphasis from a clinical quality perspective in H&W programs is on preventive care, early recognition of emerging disease, and use of appropriately placed screening tools.

Table 8.4 lists several examples of clinical quality measures that are sensitive to the APRN role at the population health level in DM, CM, and lifestyle management or H&W programs, whether their intervention is on the telephone, in person in any setting, or via a telehealth program. APRNs who have responsibilities regardless of the setting can strengthen a program design by assuring that outcomes measures are used in evaluating program effectiveness and incorporating a blend of process and outcome measures in quality program development.

TABLE 8.4

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