Journal of Gerontological Nursing

Evidence-Based Practice Guideline 

Quality Improvement in Nursing Homes

Mary J. Dyck, PhD, RN, LNHA; Theresa Schwindenhammer, MSN, RN; Howard K. Butcher, RN, PhD

Abstract

Dr. Dyck is Associate Professor, and Ms. Schwindenhammer is PhD candidate, Mennonite College of Nursing at Illinois State University, Normal, Illinois. Ms. Schwindenhammer is also Assistant Professor, Methodist College, Peoria, Illinois.

The authors have disclosed no potential conflicts of interest, financial or otherwise. Copyright © 2012 The University of Iowa John A. Hartford Foundation Center for Geriatric Nursing Excellence.

Quality may be defined as an attribute of a product or service (Spath, 2013). Several features of quality include: (a) achieving or surpassing customer expectations; (b) changing definitions of the expectations over time; and (c) improving the product or service as expectations change (Spath, 2013). Quality measurement is needed by researchers to measure costs and outcomes, and consumers need a guide to help them choose a nursing home. Clinical data are often used to measure nursing home quality. An example of a data source is the Minimum Data Set (MDS) (Gruneir & Mor, 2008). Many agree that nursing home quality is multidimensional, which makes identification and measurement more complex (Dellefield, 2007; Dosa, Bowers, & Gifford, 2006; Gruneir & Mor, 2008; Rantz et al., 1999).

This article is derived from the evidence-based practice guideline Quality Improvement in Nursing Homes (Dyck & Schwindenhammer, 2012), which can be purchased from the University of Iowa Hartford Center of Geriatric Nursing Excellence at http://www.nursing.uiowa.edu/excellence/evidence-based-practice-guidelines. The purpose of this evidence-based administrative guideline is to provide quality improvement knowledge and strategies for nursing homes. Nursing homes, including all departments (i.e., administration, nursing, social services, dietary, activities, housekeeping, laundry, finance, maintenance, and any others), can use this administrative guideline as a team to develop, define, implement, and evaluate their own quality improvement program. Interdisciplinary collaboration is part of a good quality improvement program and needs to incorporate not only nursing home providers, but also patients and their families (Gold, 2000; Gruneir & Mor, 2008; Harrington, 2005).

Nursing home quality is influenced by federal and state regulations, with the history of nursing home quality woven throughout federal and state programs (Castle & Ferguson, 2010; Rantz et al., 2001). Quality improvement processes are mandated by law and are used as a means to improve quality of care in nursing homes (Rosen et al., 2005). Legally, nursing homes are required to use the research-based Resident Assessment Instrument (RAI; U.S. Department of Health and Human Services, Health Care Financing Administration, 1997) for assessment and care planning purposes (Morris et al., 1990). Quality measures have been developed based on the RAI assessment data (Zimmerman et al., 1995). Because nursing homes are required to use these instruments, this administrative guideline is built on these requirements. Individuals using this administrative guideline need to acquaint themselves with the RAI; the most recent version of the MDS 3.0 User’s Manual (Centers for Medicare & Medicaid Services [CMS], 2013a), which details use of the RAI; and the Five Elements of Quality Assurance and Performance Improvement (QAPI).

Nursing homes with clinical consultation from advanced practice nurses (APNs) show significantly higher levels of quality than nursing homes without clinical consultants (Krichbaum, Pearson, & Hanscom, 2000; Rantz et al., 2001, 2009; Rantz, Vogelsmeier, et al., 2003; Ryden, Gross, et al., 2000; Smith, Mitchell, & Buckwalter, 1995). This administrative guideline is based on the premise that nursing homes will use a clinical consultant to enhance their quality of care and their quality improvement program. Improving quality of care in nursing homes has improved resident outcomes when using APNs either on-site or in consultation where they could effect change in clinical practice (Rantz et al., 2001; Russell, Madsen, Flesner, & Rantz, 2010).

Quality improvement is based on standards. Standards are statements that communicate expectations…

Dr. Dyck is Associate Professor, and Ms. Schwindenhammer is PhD candidate, Mennonite College of Nursing at Illinois State University, Normal, Illinois. Ms. Schwindenhammer is also Assistant Professor, Methodist College, Peoria, Illinois.

The authors have disclosed no potential conflicts of interest, financial or otherwise. Copyright © 2012 The University of Iowa John A. Hartford Foundation Center for Geriatric Nursing Excellence.

Address correspondence to Mary J. Dyck, PhD, RN, LNHA, Associate Professor, Mennonite College of Nursing at Illinois State University, Campus Box 5810, Normal, IL 61790-5810; e-mail: mjdyck@ilstu.edu.

Quality may be defined as an attribute of a product or service (Spath, 2013). Several features of quality include: (a) achieving or surpassing customer expectations; (b) changing definitions of the expectations over time; and (c) improving the product or service as expectations change (Spath, 2013). Quality measurement is needed by researchers to measure costs and outcomes, and consumers need a guide to help them choose a nursing home. Clinical data are often used to measure nursing home quality. An example of a data source is the Minimum Data Set (MDS) (Gruneir & Mor, 2008). Many agree that nursing home quality is multidimensional, which makes identification and measurement more complex (Dellefield, 2007; Dosa, Bowers, & Gifford, 2006; Gruneir & Mor, 2008; Rantz et al., 1999).

Purpose

This article is derived from the evidence-based practice guideline Quality Improvement in Nursing Homes (Dyck & Schwindenhammer, 2012), which can be purchased from the University of Iowa Hartford Center of Geriatric Nursing Excellence at http://www.nursing.uiowa.edu/excellence/evidence-based-practice-guidelines. The purpose of this evidence-based administrative guideline is to provide quality improvement knowledge and strategies for nursing homes. Nursing homes, including all departments (i.e., administration, nursing, social services, dietary, activities, housekeeping, laundry, finance, maintenance, and any others), can use this administrative guideline as a team to develop, define, implement, and evaluate their own quality improvement program. Interdisciplinary collaboration is part of a good quality improvement program and needs to incorporate not only nursing home providers, but also patients and their families (Gold, 2000; Gruneir & Mor, 2008; Harrington, 2005).

Essential Nursing Home Requirements

Nursing home quality is influenced by federal and state regulations, with the history of nursing home quality woven throughout federal and state programs (Castle & Ferguson, 2010; Rantz et al., 2001). Quality improvement processes are mandated by law and are used as a means to improve quality of care in nursing homes (Rosen et al., 2005). Legally, nursing homes are required to use the research-based Resident Assessment Instrument (RAI; U.S. Department of Health and Human Services, Health Care Financing Administration, 1997) for assessment and care planning purposes (Morris et al., 1990). Quality measures have been developed based on the RAI assessment data (Zimmerman et al., 1995). Because nursing homes are required to use these instruments, this administrative guideline is built on these requirements. Individuals using this administrative guideline need to acquaint themselves with the RAI; the most recent version of the MDS 3.0 User’s Manual (Centers for Medicare & Medicaid Services [CMS], 2013a), which details use of the RAI; and the Five Elements of Quality Assurance and Performance Improvement (QAPI).

Clinical Consultation

Nursing homes with clinical consultation from advanced practice nurses (APNs) show significantly higher levels of quality than nursing homes without clinical consultants (Krichbaum, Pearson, & Hanscom, 2000; Rantz et al., 2001, 2009; Rantz, Vogelsmeier, et al., 2003; Ryden, Gross, et al., 2000; Smith, Mitchell, & Buckwalter, 1995). This administrative guideline is based on the premise that nursing homes will use a clinical consultant to enhance their quality of care and their quality improvement program. Improving quality of care in nursing homes has improved resident outcomes when using APNs either on-site or in consultation where they could effect change in clinical practice (Rantz et al., 2001; Russell, Madsen, Flesner, & Rantz, 2010).

Overview

Quality improvement is based on standards. Standards are statements that communicate expectations for quality performance and improvement. Institutional standards can be manifested as clinical guidelines, statements of expected outcomes of care treatment protocols, critical pathways (Watson, Brink, Zimmer, & Mayer, 2003), or the new QAPI standards. These standards are meant to serve as a framework for the development of institutional standards of care, competency-based educational programs, performance appraisals, job descriptions, and assessments of quality (Dozier, 1998; Morris, 2001).

Rates of adverse events, such as mortality, falls, or urinary tract infections, are useful to providers and consumers as measures of quality of care. Quality report cards have become an incentive to enhance the quality of the health care system, especially in nursing homes. Published report cards enhance accessibility of nursing home quality information to the consumer. This increases the sensitivity of demand for quality and generates incentives for providers to invest in quality improvement (Mukamel, Weimer, Spector, Ladd, & Zinn, 2008; Zinn, Weimer, Spector, & Mukamel, 2010).

Quality report cards and other rating programs have been developed to enhance the quality of the health care system (Mantone, 2005). Nursing Home Compare, which is available online (access http://www.medicare.gov/nursinghomecompare/search.html), is one such quality rating program. These ratings are in the form of a star and are based on measurements from health inspections, nursing home staffing levels, and MDS quality measures (Baier, Butterfield, Patry, Harris, & Gravenstein, 2009).

Regulatory History

Both nursing home staff and the lay public have been and continue to be concerned about the quality of care in nursing homes (Moxey, O’Connor, White, Turk, & Nash, 2002). A regulatory outgrowth of this concern resulted in federal nursing home reform legislation, known as the Omnibus Budget Reconciliation Act of 1989 (OBRA) (McGuiness, 1989). Although this legislation resulted in many reforms that have increased the quality of care in nursing homes, shortfalls exist in the current approach to quality improvement (Werner & Konetzka, 2010).

The Affordable Care Act (ACA) provided additional legislation to support quality and performance improvement in nursing homes (Dellefield, Kelly, & Schnelle, 2013). Previously, nursing homes were required to have a Quality Assessment and Assurance (QAA) committee (McGuiness, 1989). ACA required CMS to broaden QAPI activities in nursing homes (CMS, n.d.). CMS (2011) is now required to:

  • Establish QAPI standards and provide technical assistance to nursing homes on the development of best practices to meet the standards.
  • Test a nursing home QAPI prototype in a small nursing home demonstration project.
  • Promulgate a new QAPI regulation, in addition to the existing QAA regulation.

These new provisions in the law significantly expand the required nursing home QAPI activities. It is the intent of the law that nursing homes will continuously detect and correct quality deficiencies and sustain performance improvement (CMS, 2011). As part of the new QAPI regulation, nursing homes will be required to submit a facility plan to meet QAPI standards and implement QAPI best practices. The plan needs to include the coordination of the new QAPI plan with the previous QAA activities already required under current regulations (CMS, 2011).

Although the purpose of quality improvement programs is to provide high-quality care to consumers, the purpose of quality improvement activities is to evaluate and correct the care provided to residents in nursing homes (Barhyte, 1989; CMS, 2011). These activities can be identified by a variety of names, including quality improvement, quality assurance, continuous quality improvement, and total quality management. Although each term has slight nuances that differentiates it from the other terms, the basic purpose is to provide an organized process for the evaluation of practice/care delivery and improvement in the quality of care (Compas, Hopkins, & Townsley, 2008; Werner & Konetzka, 2010).

Quality Knowledge

Donabedian’s (1980) model is often used as a framework to define quality concepts. The model has three major components: structure, process, and outcome (Donabedian, 1980). Although these components can be individually described and evaluated, they are interrelated and affect each other (Harrington, 2005).

Structure describes the characteristics of organizations in which work occurs (Donabedian, 1980, 1986, 1992). Although reviewing structures provides information regarding the presence of key elements of high-quality care, it is only an indirect measure of quality (Schirm, Albanese, & Garland, 1999). Examples of structure may include staffing levels, number of beds or size of facility, management and leadership structures, ownership, and the physical building.

The process of care refers to the activities that occur within and among practitioners and residents, or the manner in which care is delivered (Spector & Mukamel, 1998). Process, which includes the appropriateness of care, timeliness of care, and technical proficiency (Noelker & Harel, 2001), is a direct measure of quality of care delivery within the context of established standards (Schirm et al., 1999). Examples include resident assessment and caregiving.

Outcome is defined as a change in a resident’s health status or the health status of a group of residents that can be ascribed to previous health care (Donabedian, 1980, 1986; Lang & Marek, 1992). Outcomes studied in the nursing home setting include mortality, hospitalization, facility-acquired pressure ulcers, functional status changes, injuries, urinary incontinence, weight loss, and infectious disease (Dellefield, 2000). Outcome evaluation assesses and disseminates the measurable changes in residents’ health statuses and satisfaction with their care (Barhyte, 1989; Berg et al., 1999; Schirm et al., 1999).

These three components—structure, process, and outcome—are interrelated. Although outcomes are monitored, they do not directly assess the quality of care performance. Outcomes only allow inferences regarding the process and structures of care. Even if outcomes are good, care still may not have been good. The potency of the inference depends on the strength of the causal relationships between process and outcome and between structure and process. Although outcomes are more easily understood by the lay public, they are also open to misinterpretation, due to multiple factors that can impact the outcomes. People often find this aspect difficult to understand (Donabedian, 1995).

Quality Improvement Data

To identify issues requiring quality activities in a nursing home, data from the facility need to be collected. Structural, process, and outcome data are available and can be useful. Structural data include nurse staffing schedules, which can assist in determining nurse staffing numbers and ratios per resident and by shift. Process data may include the prevalence of tube feedings, presence of Foley catheters, or use of nine or more different medications. Outcome data may include new fractures, falls, incident reports (Silver, 1999; Silver & Burack, 2000), and mortality rates. Clinical data in all three areas (i.e., structure, process, and outcome) are often already tracked as previously noted. Administrative data, which are often structural in nature, are collected to monitor compliance with state and federal regulations. Examples include physicians’ visits, admission, discharges, and transfers. Human resources’ data might include workers’ compensation files, turnover, and staffing. Depending on the use, these could be structure, process, or outcome data (Rantz & Popejoy, 1998). As an example, staffing patterns are a structural component, whereas turnover rates for the year are related to outcome data.

Although much data may already be collected by the facility, the data probably are not in a useful format. When data are analyzed, they develop into information and eventually become knowledge, which is usable in decision making. Staff are able to use the data more effectively if they are displayed in meaningful reports (Rantz et al., 1997, 2000). The key component of successful problem solving and decision making is the ability to effectively use available data and information. Without effective use of data and information, poor and ill-informed decisions are made. A good quality improvement program will provide data, information, and knowledge to the administrator and director of nursing for effective decision making (Bradley & Thompson, 2000; Dyck, 2002).

Nursing Home Quality

OBRA mandated the development of a standardized assessment tool known as the RAI. The RAI is composed of three components: MDS, care area triggers, and utilization guidelines. The new MDS 3.0 was implemented October 1, 2010. Quality measures (QMs) based on the data from the MDS 3.0 were endorsed by the National Quality Forum in June 2011 (CMS, 2012b) and are now available at http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/NHQIQualityMeasures.html.

The QMs have four purposes (CMS, 2012b):

  • To provide information about the quality of care in nursing homes that may be chosen for oneself or one’s family member.
  • To provide information about the quality of care in nursing homes where a family member already lives.
  • To facilitate conversation with nursing home staff about the quality of care in a facility.
  • To provide data to the nursing home to assist staff in its quality management program.

Systematic use of QMs can assist in the identification of quality problems and determination of other problems for both facility staff and regulatory surveyors. QMs are used at both a resident and a facility level. At the resident level, QMs represent either the presence or absence of a condition (Karon & Zimmerman, 1996). A facility-level QM is the aggregation of all resident scores for a QM divided by either the total number of residents or the total number of possible residents.

QMs derived from the MDS data differentiate nursing homes of good quality and poorer quality and provide feedback for nursing homes (Rantz et al., 1996, 2001; Rantz, Vogelsmeier, et al., 2003). Interpreting performance is essential for nursing homes to determine the action needed to improve their quality of care (Rantz et al., 2006).

With the passage of the ACA in March 2010, nursing homes must further develop their quality improvement program to include both QAPI elements (Dellefield et al., 2013). Discussion of each QAPI element is integrated into the protocol.

Description of the Practice

A quality improvement administrative guideline is a complex, multi-faceted tool for the management of quality in a nursing home. As such, it has many parts. Each part will be addressed in a separate section.

Quality Improvement Program Structure

An overall plan for program structure and information flow is necessary for the success of the program. Program structure legitimizes the QM findings and establishes accountability for follow up on findings. Therefore, formal organizational structures must be established (Dellefield, 2007; Gruneir & Mor, 2008). Tasks to be completed for the quality improvement structure include:

Quality Improvement Program Process Overview

Many data are available in the health care field. Data refer to the facts, figures, and numbers routinely collected in the functioning of the nursing home. Typically, the problem is not a lack of data, rather it is a lack of usable information. Data that have been processed and analyzed become information that can be useful in operating and managing the nursing home. Data become information after someone has asked questions that place the data within its proper context (Carey & Lloyd, 2001).

Quality improvement studies the typical behavior and output of a process to gain knowledge about possible causes of variation in the process. One common model for studying quality improvement problems is the Plan, Do, Study, and Act (PDSA) cycle shown in the Figure. The PDSA cycle provides the process for an overall quality improvement plan and for evaluating specific target problems (Bradley & Thompson, 2000; Lighter & Fair, 2000; McLaughlin & Kaluzny, 1999; Nelson & Batalden, 1993). One tool to use in the evaluation process is root cause analysis (RCA).

Plan-Do-Study-Act (PDSA) cycle.Note. Adapted from Bradley and Thompson (2000); Lighter and Fair (2000); and McLaughlin and Kaluzny (1999).

Figure.

Plan-Do-Study-Act (PDSA) cycle.

Note. Adapted from Bradley and Thompson (2000); Lighter and Fair (2000); and McLaughlin and Kaluzny (1999).

Benchmarking

Benchmarking is similar to the quality improvement process. A quality improvement process is an internal benchmarking process of comparing data with facility standards, yet is distinct from other approaches to quality improvement because it emphasizes review and shared planning among practitioners, residents, and other service users (Davies & Goodman-Cripacc, 2008). When a facility compares itself to other organizations, external benchmarking occurs (Camp & Tweet, 1994).

Improvement/Benchmarking Plan Implementation. Watson, Mobarak, and Stimson (1999) have outlined the steps as follows:

  • Plan for quality improvement/benchmarking, both internal and external.
  • Collect and analyze data: (a) use RCA to determine causes of quality issues; (b) analyze data.
  • Study data.
  • Improve the process.

Consumer Satisfaction

Although many residents in nursing homes have long lengths of stay, they are often considered unable to respond to surveys, questionnaires, or interviews (Mor, 2001). One study showed that 30% of residents would not have been interviewed if staff had used their judgment rather than an interview protocol (van Maris, Soberman, Murray, & Norton, 1996). Although family members have opinions regarding the quality of care and quality of life of their relative, research has shown that surrogates cannot accurately express the resident’s opinion regarding care (Lavizzo-Mourey, Zinn, & Taylor, 1992; Meister & Boyle, 1996). Resident satisfaction is an indicator of the quality of care provided by the facility (Grau, Chandler, & Saunders, 1995; Kleinsorge & Koenig, 1991; Rantz et al., 1999; Ryden, Gross, et al., 2000; Uman & Urman, 1997). A variety of tools are available for measuring consumer satisfaction. Ryden, Gross, et al. (2000) developed the Satisfaction with Nursing Home instrument, which is publicly available. Another example is The Preferences for Everyday Living Inventory, which facilitates the identification of the most commonly held preferences for person-centered care delivery (Van Haitsma et al., 2012).

Implementation of Consumer Satisfaction Process.

  • Identify a committee to implement a consumer satisfaction process with both residents and families (Ejaz, 2000). The committee should report to the QAA committee (Rantz et al., 1998).
  • Obtain administrative support for the consumer satisfaction process (Parker et al., 1999).
  • Prepare staff, as satisfaction surveys may be viewed as a threat by staff (van Maris et al., 1996).
  • Decide on the tool to be used. Use of previously developed and tested tools is recommended due to the resources and time required for tool development and testing (McDaniel & Nash, 1990).
  • Add facility-specific questions as desired (Ejaz, 2000).
  • Determine administration frequency, if not specifically recommended by authors of chosen tool (Ejaz, 2000).
  • Identify interviewers. Interviewers who are not staff members are preferred, as residents may try to give answers that they believe staff members want to hear.
  • Select residents to complete the resident survey/interview. The use of a protocol that requires interviewers to approach residents three times on three separate occasions is recommended prior to determining that residents are unable to participate (van Maris et al., 1996).
  • Develop a family survey, if the above family survey is not useful for the facility.
  • Select family members or significant others to complete a family survey (Mayo & Wallhagen, 2009).
  • Print tool using Courier 14- to 16-point font for older adults (Bailey, Boyd, Boyd, & Clark, 1987; Fine & Peli, 1996; Mansfield, Legge, & Bane, 1996).
  • Conduct survey (Ejaz, 2000).
  • Analyze data, including comments from surveys.
  • Disseminate findings.

Data Collection and Management

Decisions in a quality improvement program are driven by data and the ability to manage and process them. Without accurate data, neither accurate analysis nor changes can be made (Bradley & Thompson, 2000; Dyck, 2002; Katz, 1992; Tracy, 1999). Sound decisions result in accurate and correct change plans. The purposes of data collection are: validation of the current process; rationale for making changes in care; rationale for increasing, decreasing, or maintenance of organizational resources; and determination of reliable thresholds for evaluation (Katz, 1992). Typically, data management for quality improvement purposes is a decentralized process in that both managers and front-line employees are involved in data analysis, management, and dissemination.

MDS 3.0 QMs are available to assist in quality evaluation. Because all staff, not just nursing staff, may impact the required QMs, a team approach to meeting quality improvement standards is essential.

In addition to the CMS-required QMs, each nursing home department needs to determine its core quality indicators (QIs). These core QIs will likely be based on regulatory requirements. As core QIs are consistently being met, other indicators may be developed, with the facility choosing to move to higher standards. Examples of some possible QIs for each department are given in the Table. Managers need to involve their staff in the development of the department’s core QIs. Following development of the core department QIs, staff can assist in data analysis, management, and dissemination. Due to the significant number of required QMs that affect the nursing department, it is recommended that they focus on only the required MDS 3.0 QMs at the initiation of the quality improvement program.

Sample Quality Indicators

Table:

Sample Quality Indicators

Implementation of Data Collection and Management.

  • Implement QAPI Element 3: Feedback, Data Systems, and Monitoring.
  • Implement QAPI Element 4: Performance Improvement Projects (PIPs). The purpose of PIPs is to evaluate and improve care and/or services in an area that needs attention (CMS, 2012a).
  • Educate all who will be collecting and managing data (Landi et al., 1999).
  • Determine core QIs for each department.
  • Choose data elements that will access the requisite data for the core QIs using current sources of readily accessible data as part of the quality improvement program, if possible.
  • Review current data collection tools to determine if they provide the necessary data for the QI (Katz, 1992).
  • Determine volume and frequency of data to be collected.
  • Identify an individual to be accountable for data management (Katz, 1992).
  • Use a computer for data management to ensure the quality of results and to meet regulatory guidelines (Humbertson, 2001).

Data Analysis (Statistical Process Control)

At the core of quality improvement is a scientific approach to data analysis. Although facilities have much data, they also have opinions and anecdotes without a basis in fact. With the use of a scientific approach, data can be evaluated and analyzed, processes improved, and progress tracked (Katz, 1992; Kelly, Johnson, & Sollecito, 2013; Zimmerman, Jewell, & Karon, 1998). Essentially, statistical process control identifies variation in the system. Variation, or variance, is defined as the extent to which a process differs from the standard. All processes have variations and always will (Kelly et al., 2013). The goal is to reduce the variability in the process to decrease uncertainty (Katz, 1992; Kelly et al., 2013) and to increase the quality of care.

A major challenge becomes understanding the process that requires improvement. RCA has been mandated by CMS as the analytic method used to determine the fundamental cause of the problem in PIPs (Dellefield et al., 2013). A sentinel or adverse event triggers the implementation of RCA. The RCA process follows the PDSA cycle shown in the Figure. The RCA steps that occur in relationship to the PDSA cycle are:

Plan

  • Recognize the event.
  • Identify root causes.
  • Develop interventions to prevent recurrence of events.

Do

  • Implement and test interventions.

Study

  • Evaluate whether the interventions achieved the preferred results.

Act

  • Implement interventions permanently or review and retest interventions (Spath, 2013).

Implementation of Data Analysis.

  • Educate all who will be analyzing data.
  • Access facility QIs on a regular basis, at least monthly.
  • Implement QAPI Element 5: Systematic Analysis and Systemic Action (CMS, 2012a).
  • Use RCA in analysis of PIPs.
  • Use quality improvement tools to assist in the analysis as needed (Schwab, DelSorbo, Cunningham, Craven, & Watson, 1999).
  • Review facility QMs, at least monthly (Popejoy et al., 2000).
  • Review facility systems for resident care for common resident problems (e.g., falls, pressure ulcers, weight loss, incontinence) (Rantz et al., 2001).
  • Review the results of data collection and compare with current standards of care, including but not limited to, QMs, consumer satisfaction data, and adverse event data (Rantz et al., 1998).
  • Discuss the changes that will be necessary to solve problems associated with the problem/situation under review in the interdisciplinary QAA committee (Rantz et al., 1998).
  • Develop an improvement plan (Rantz et al., 1998).
  • Implement the improvement plan (Rantz et al., 1998).

Results Dissemination

Following data analysis, reports must be disseminated in a timely manner. The reports must be written in a manner that the recipient can understand (Greer, 1988). Interactive dissemination, which occurs throughout the project rather than just at the end, is most important to maintain interest. Different methods of dissemination are appropriate for different individuals and groups. Although the methods of dissemination vary with the population receiving the information, principles of dissemination remain the same despite the methods. These principles include multiple methods of feedback dissemination, repetition of message, and in-person transmission of information (Tasa, Baker, & Murray, 1996).

Dissemination Process.

  • Disseminate quality improvement study results, revised policy/policies, revised procedure(s), and revised protocol(s) to supervisory and direct care staff (Rantz & Popejoy, 1998).
  • Revise orientation materials to include policy, procedure, and protocol changes (Rantz et al., 1998).
  • Evaluate the changes shortly after implementation of the improvement plan (Compas et al., 2008).
  • Determine times to monitor the problem at routine intervals to ensure that changes continue to be practiced and are effective (Rantz et al., 1998).

Evaluation of Administrative Guideline Implementation

Throughout this quality improvement administrative guideline, the terms process and outcome have been used to refer to indicators for the evaluation of quality of resident care. In this section, these terms will be used to evaluate the implementation process and outcomes of this administrative guideline. The purpose of this section is to guide the facility in evaluating the implementation and outcomes of a nursing home quality improvement program, using this administrative guideline.

Process Indicators

Process indicators are interpersonal and environmental factors that can facilitate the use of an administrative guideline. Process quality indicators may help improve quality of care (Castle & Ferguson, 2010). One process factor that can be assessed with a sample of professional and nonprofessional staff is knowledge about quality improvement. A facility-wide process indicator that should be monitored over time is the continued use of a gerontological nurse consultant either on-site or via telephone (Rantz et al., 2009).

Outcome Indicators

Outcome indicators are those expected to change or improve from consistent use of this administrative guideline in nursing home quality improvement programs. The core QMs that should be monitored over time are the CMS-required QMs in addition to the QIs determined by each department.

Conclusions and Implications for Gerontological Nursing Practice

Quality of care is important in every health care setting. In nursing homes, individuals are often given care for a significant period of time. All staff, not just nursing staff, need to know what quality is and how to implement it in the nursing home. Because a QAPI program is now required in every U.S. nursing home that is Medicare and Medicaid certified, all staff need to be involved in the program, which may require new skills for many staff members.

Implementation of a QAPI program requires both knowledge and skill development at a variety of levels. A variety of resources are available to develop the program for the facility, including this evidence-based practice guideline and the Quality Improvement Organizations in every state (CMS, 2013b). To increase the quality of care, knowledge regarding evidence-based practices for care may also need to be investigated and implemented in the facility. A resource for evidence-based practices for individuals with dementia include a Nonpharmacological Toolkit for Senior Living Communities (Resnick, Kolanowski, & Van Haitsma, 2014). Other evidence-based practice resources may be found on Consult-GeriRN at http://consultgerirn.org/resources. In addition, the University of Iowa College of Nursing’s evidence-based practice guidelines on geriatric nursing can be found at http://www.nursing.uiowa.edu/excellence/evidence-based-practice-guidelines. Facilities’ clinical consultants will undoubtedly have other resources to recommend. All of the above could facilitate knowledge development.

A necessary skill might be the ability to use a Microsoft® Excel spreadsheet for data management. Both online and face-to-face classes are available for computer skill development.

All nursing home staff play a significant role in quality management, whether the involvement is through direct care or in program management. Everyone has a role. Residents deserve quality facilities and quality care.

References

  • Baier, R., Butterfield, K., Patry, G., Harris, Y. & Gravenstein, S. (2009). Identifying star performers: The relationship between ambitious targets and nursing home quality improvement. Journal of the American Geriatrics Society, 57, 1498–1503. doi:10.1111/j.1532-5415.2009.02362.x [CrossRef]
  • Bailey, I.L., Boyd, L.H., Boyd, W.L. & Clark, M. (1987). Readability of computer display print enlarged for low vision. American Journal of Optometry and Physiological Optics, 64, 678–685. doi:10.1097/00006324-198709000-00006 [CrossRef]
  • Barhyte, D.Y. (1989). Quality assurance systems overview. In LeSage, J. & Barhyte, D.Y. (Eds.), Nursing quality assurance in long-term care. Rockville, MD: Aspen.
  • Berg, M.S., Dreher, M., Davenport, K.D., Greiner, J., Howell, R.E., Mutnick, A.H. & Titler, M.G. (1999). University of Iowa Hospital and Clinics: Outcomes management. Nursing Administration Quarterly, 24, 31–65. doi:10.1097/00006216-199910000-00005 [CrossRef]
  • Bradley, M.G. & Thompson, N.R. (2000). Quality management integration in long-term care: Guidelines for excellence. Baltimore, MD: Health Professions Press.
  • Butcher, A.H. (1994). Supervisors matter more than you think: Components of a mission-centered organizational climate. Hospital and Health Services Administration, 39, 505–520.
  • Camp, R.C. & Tweet, A.G. (1994). Benchmarking applied to health care. Journal on Quality Improvement, 5, 229–238.
  • Carey, R.G. & Lloyd, R.C. (2001). Measuring quality improvement in healthcare: A guide to statistical process control applications. Milwaukee, WI: Quality Press.
  • Castle, N.G. & Ferguson, J.C. (2010). What is nursing home quality and how is it measured?The Gerontologist, 50, 426–442. doi:10.1093/geront/gnq052 [CrossRef]
  • Centers for Medicare & Medicaid Services. (n.d.). Nursing home quality assurance and program improvement. Retrieved from https://www.cms.gov/Medicare/Provider-Enrollment-and-Certification/SurveyCertificationGenInfo/Downloads/nhqapibackground.pdf
  • Centers for Medicare & Medicaid Services. (2011). Quality assurance and performance improvement (QAPI) in nursing homes-activities related to QAPI implementation. Retrieved from https://www.cms.gov/Medicare/Provider-Enrollment-and-Certification/SurveyCertificationGenInfo/Downloads/Survey-and-Cert-Letter-12-38.pdf
  • Centers for Medicare & Medicaid Services. (2012a). Five elements of QAPI. Retrieved from http://www.cms.gov/Medicare/Provider-Enrollment-and-Certification/SurveyCertification-GenInfo/Downloads/fiveelementsqapi.pdf
  • Centers for Medicare & Medicaid Services. (2012b). Quality measures. Retrieved from http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQuality-Inits/NHQIQualityMeasures.html
  • Centers for Medicare & Medicaid Services. (2013a). MDS 3.0 RAI manual. Retrieved from http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQuality-Inits/MDS30RAIManual.html
  • Centers for Medicare & Medicaid Services. (2013b). Quality improvement organizations. Retrieved from http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityImprovementOrgs/index.html?redirect=/Quality-ImprovementOrgs
  • Compas, C., Hopkins, K.A. & Townsley, E. (2008). Best practices in implementing and sustaining quality of care: A review of the quality improvement literature. Research in Gerontological Nursing, 1, 209–216. doi:10.3928/00220124-20091301-07 [CrossRef]
  • Compas, L.B. (2004). Nurses’ working hours. Health Affairs, 23, 274–275. doi:10.1377/hlthaff.23.6.274 [CrossRef]
  • Davies, S. & Goodman-Cripacc, C. (2008). Supporting quality improvement in care homes for older people: The contribution of primary care nurses. Journal of Nursing Management, 16, 1115–1120. doi:10.1111/j.1365-2834.2007.00838.x [CrossRef]
  • Dellefield, M.E. (2000). The relationship between nurse staffing in nursing homes and quality indicators. Journal of Gerontological Nursing, 26(6), 14–28. doi:10.3928/0098-9134-20000601-05 [CrossRef]
  • Dellefield, M.E. (2007). Implementation of the resident assessment instrument/minimum data set in the nursing home as organization: Implications for quality improvement in RN clinical assessment. Geriatric Nursing, 28, 377–386. doi:10.1016/j.gerinurse.2007.03.002 [CrossRef]
  • Dellefield, M.E., Kelly, A. & Schnelle, J.F. (2013). Quality assurance and performance improvement in nursing homes: Using evidence-based protocols to observe nursing care processes in real-time. Journal of Nursing Care Quality, 28, 43–51. doi:10.1097/NCQ.0b013e31826b090b [CrossRef]
  • Donabedian, A. (1980). Definition of quality and approaches to its assessment: Explorations in quality assessment and monitoring (Vol. 1). Ann Arbor, MI: Health Administration Press.
  • Donabedian, A. (1986). Criteria and standards for quality assessment and monitoring. Quality Review Bulletin, 12, 99–108.
  • Donabedian, A. (1992). The role of outcomes in quality assessment and assurance. Quality Review Bulletin, 18, 356–360.
  • Donabedian, A. (1995). The role of outcomes in quality assessment and assurance. In Graham, N.O. (Ed.), Quality in health care: Theory, application, and evolution (pp. 32–46). Gaithersburg, MD: Aspen.
  • Dosa, D., Bowers, B. & Gifford, D.R. (2006). Critical review of resident assessment protocols. Journal of the American Geriatrics Society, 54, 659–666. doi:10.1111/j.1532-5415.2006.00654.x [CrossRef]
  • Dozier, A.M. (1998). Professional standards: Linking care, competence, and quality. Journal of Nursing Care Quality, 12(4), 22–29. doi:10.1097/00001786-199804000-00007 [CrossRef]
  • Dyck, M.J. (2002). Nursing informatics: Applications for long-term care. Journal of Gerontological Nursing, 28(10), 30–39. doi:10.3928/0098-9134-20021001-10 [CrossRef]
  • Dyck, M.J. & Schwindenhammer, T. (2012). Quality improvement in nursing homes. In Schoenfelder, D.P. (Series Ed.), Series on evidence-based practice guidelines. Iowa City, IA: The University of Iowa College of Nursing John A. Hartford Foundation Center of Geriatric Nursing Excellence.
  • Ejaz, F.K. (2000). An overview of the process of conducting consumer satisfaction surveys in nursing facilities. In Cohen-Mansfield, J., Ejaz, F.K. & Werner, P. (Eds.), Satisfaction surveys in long-term care (pp. 137–165). New York, NY: Springer.
  • Fine, E.M. & Peli, E. (1996). Visually impaired observers require a larger window than normally sighted observers to read from a scroll display. Journal of the American Optometric Association, 67, 390–396.
  • Gold, M.F. (2000). Reaching a new level in outcomes management. Provider, 26, 42–44.
  • Grau, L., Chandler, B. & Saunders, C. (1995). Nursing home residents’ perceptions of the quality of their care. Journal of Psychosocial Nursing and Mental Health Services, 33(5), 34–41.
  • Greer, A.L. (1988). The state of the art versus the state of the science: The diffusion of new medical technologies into practice. International Journal of Technology Assessment in Health Care, 4, 5–26. doi:10.1017/S0266462300003202 [CrossRef]
  • Gruneir, A. & Mor, V. (2008). Nursing home safety: Current issues and barriers to improvement. Annual Review of Public Health, 29, 369–382. doi:10.1146/annurev.publhealth.29.020907.090912 [CrossRef]
  • Harrington, C. (2005). Quality of care in nursing home organizations: Establishing a health services research agenda. Nursing Outlook, 53, 300–304. doi:10.1016/j.outlook.2005.10.002 [CrossRef]
  • Humbertson, S.K. (2001). Management of a point-of-care program: Organization, quality assurance, and data management. Clinics in Laboratory Medicine, 21, 255–268.
  • Karon, S.L. & Zimmerman, D.R. (1996). Using indicators to structure quality improvement initiatives in long-term care. Quality Management in Health Care, 4(3), 54–66. doi:10.1097/00019514-199604030-00008 [CrossRef]
  • Katz, J. (1992). Managing quality: A guide to monitoring and evaluating nursing services. St. Louis, MO: Mosby Year-book.
  • Kelly, D.L., Johnson, S.P. & Sollecito, W.A. (2013). Measurement, variation, and CQI tools. In Sollecito, W.A. & Johnson, J.K. (Eds.), McLaughlin & Kaluzny’s continuous quality improvement in health care (4th ed., pp. 77–116.). Burlington, MA: Jones & Bartlett Learning.
  • Kleinsorge, I.K. & Koenig, H.F. (1991). The silent customers: Measuring customer satisfaction in nursing homes. Journal of Health Care Marketing, 11(4), 2–13.
  • Krichbaum, K.E., Pearson, V. & Hanscom, J. (2000). Better care in nursing homes: Advanced practice nurses’ strategies for improving staff use of protocols. Clinical Nurse Specialist, 14, 40–46. doi:10.1097/00002800-200001000-00014 [CrossRef]
  • Landi, F., Sgadari, A., Zuccala, G., Pahor, M., Carbonin, P. & Bernabei, R. (1999). A brief training program on resident assessment instrument improves motivation of nursing home staff. Journal of Nutrition, Health, and Aging, 3, 24–28.
  • Lang, N. & Marek, K.D. (1992). Outcomes that reflect clinical practice. In Patient outcomes research: Examining the effectiveness of nursing practice: Proceedings of the State of the Science Conference. , September 11–13, 1991. (pp. 27–38). Rockville, MD: U.S. Department of Health and Human Services, Public Health Service, National Institutes of Health.
  • Lavizzo-Mourey, R.J., Zinn, J. & Taylor, L. (1992). Ability of surrogates to represent satisfaction of nursing home residents with quality of care. Journal of the American Geriatrics Society, 40, 39–47.
  • LeSage, J. & Barhyte, D.Y. (1989). Implementation of a quality assurance program. In LeSage, J. & Barhyte, D.Y. (Eds.), Nursing quality assurance in long-term care (pp. 101–142). Rockville, MD: Aspen.
  • Lighter, D.E. & Fair, D.C. (2000). Principles and methods of quality management in health care. Gaithersburg, MD: Aspen.
  • Mansfield, J.S., Legge, G.E. & Bane, M.C. (1996). Psychophysics of reading. XV: Font effects in normal and low vision. Investigative Ophthalmology & Visual Science, 37, 1492–1502.
  • Mantone, J. (2005). Public knowledge. Nursing homes improve quality-of-care scores. Modern Healthcare, 35, 12.
  • Mayo, A.M. & Wallhagen, M.I. (2009). Considerations of informed consent and decision-making competence in older adults with cognitive impairment. Research in Gerontological Nursing, 2, 103–111. doi:10.3928/19404921-20090401-08 [CrossRef]
  • McDaniel, C. & Nash, J.G. (1990). Compendium of instruments measuring patient satisfaction with nursing care. Quality Review Bulletin, 16, 182–188.
  • McGuiness, C. (Ed.). (1989). Congress and the nation VII, 1985–1988. Washington, DC: Congressional Quarterly.
  • McLaughlin, C.P. & Kaluzny, A.D. (1999). Defining quality improvement: Past, present, and future. In McLaughlin, C.P. & Kaluzny, A.D. (Eds.), Continuous quality improvement in health care (pp. 3–33). Gaithersburg, MD: Aspen.
  • Meister, C. & Boyle, C. (1996). Perceptions of quality in long-term care: A satisfaction survey. Journal of Nursing Care Quality, 10(4), 40–47. doi:10.1097/00001786-199607000-00007 [CrossRef]
  • Mor, V. (2001). Approaches to quality of care by regulatory and accreditation organizations. In Noelker, L.S. & Harel, Z. (Eds.), Linking quality of long-term care and quality of life (pp. 42–71). New York, NY: Springer.
  • Morris, J.N., Hawes, C., Fries, B.E., Phillips, C.D., Mor, V., Katz, S. & Friedlob, A.S. (1990). Designing the national resident assessment instrument for nursing homes. The Gerontologist, 30, 293–307. doi:10.1093/geront/30.3.293 [CrossRef]
  • Morris, K. (2001). Are professional nursing standards really important? How do they impact my practice?Ohio Nurses Review, 76(3), 20.
  • Moxey, E.D., O’Connor, J.P., White, E., Turk, B. & Nash, D.B. (2002). Developing a quality measurement tool and reporting format for long-term care. Joint Commission Journal on Quality Improvement, 28, 180–196.
  • Mukamel, D.B., Weimer, D.L., Spector, W.D., Ladd, H. & Zinn, J.S. (2008). Publication of quality report cards and trends in reported quality measures in nursing homes. Health Services Research, 43, 1244–1262. doi:10.1111/j.1475-6773.2007.00829.x [CrossRef]
  • Nelson, E.C. & Batalden, P.B. (1993). Patient-based quality measurement systems. Quality Management in Health Care, 2, 18–30. doi:10.1097/00019514-199302010-00006 [CrossRef]
  • Noelker, L.S. & Harel, Z. (2001). Humanizing long-term care: Forging a link between quality of care and quality of life. In Noelker, L.S. & Harel, Z. (Eds.), Linking quality of long-term care and quality of life (pp. 3–26). New York, NY: Springer.
  • Parker, V.A., Wubbenhorst, W.H., Young, G.J., Desai, K.R. & Charns, M.P. (1999). Implementing quality improvement in hospitals: The role of leadership and culture. American Journal of Medical Quality, 14, 64–69. doi:10.1177/106286069901400109 [CrossRef]
  • Popejoy, L.L., Rantz, M.J., Conn, V., Wipke-Tevis, D.D., Grando, V.T. & Porter, R. (2000). Improving quality of care in nursing facilities: Gerontological clinical nurse specialist as research nurse consultant. Journal of Gerontological Nursing, 26(4), 6–13. doi:10.3928/0098-9134-20000401-04 [CrossRef]
  • Rantz, M.J., Cheshire, D., Flesner, M., Petroski, G.F., Hicks, L., Alexander, G. & Thomas, S. (2009). Helping nursing homes “at risk” for quality problems: A statewide evaluation. Geriatric Nursing, 30, 238–249. doi:10.1016/j.gerinurse.2008.09.003 [CrossRef]
  • Rantz, M.J., Grando, V., Conn, V.S., Zwygart-Stauffacher, M., Hicks, L.L., Flesner, M. & Maas, M. (2003). Getting the basics right: Care delivery in nursing homes. Journal of Gerontological Nursing, 29(11), 15–25. doi:10.3928/0098-9134-20031101-07 [CrossRef]
  • Rantz, M.J., Hicks, L.L., Grando, V., Petroski, G.F., Madsen, R.W., Mehr, D.R. & Maas, M. (2004). Nursing home quality, cost, staffing, and staff mix. The Gerontologist, 44, 24–38. doi:10.1093/geront/44.1.24 [CrossRef]
  • Rantz, M.J., Mehr, D.R., Conn, V.S., Hicks, L.L., Porter, R., Madsen, R.W. & Maas, M. (1996). Assessing quality of nursing home care: The foundation for improving resident outcomes. Journal of Nursing Care Quality, 10(4), 1–9. doi:10.1097/00001786-199607000-00002 [CrossRef]
  • Rantz, M.J., Mehr, D.R., Hicks, L.L., Scott-Cawiezell, J., Petroski, G.F., Madsen, R.W. & Zwygart-Stauffacher, M. (2006). Entrepreneurial program of research and service to improve nursing home care. Western Journal of Nursing Research, 28, 918–934. doi:10.1177/0193945905284715 [CrossRef]
  • Rantz, M.J., Miller, T.V., Popejoy, L.L. & Zwygart-Stauffacher, M. (1998). Outcome-based quality improvement for long-term care. Gaithersburg, MD: Aspen.
  • Rantz, M.J., Petroski, G.F., Madsen, R.W., Mehr, D.R., Popejoy, L., Hicks, L.L. & Grando, V. (2000). Setting thresholds for quality indicators derived from MDS data for nursing home quality improvement reports: An update. Joint Commission Journal on Quality Improvement, 26, 101–110.
  • Rantz, M.J., Petroski, G.F., Madsen, R.W., Scott, J., Mehr, D.R., Popejoy, L. & Grando, V. (1997). Setting thresholds for MDS (minimum data set) quality indicators for nursing home quality improvement reports. Joint Commission Journal on Quality Improvement, 23, 602–611.
  • Rantz, M.J., Popejoy, L., Petroski, G.F., Madsen, R.W., Mehr, D.R., Zwygart-Stauffacher, M. & Maas, M. (2001). Randomized clinical trial of a quality improvement intervention in nursing homes. The Gerontologist, 41, 525–538. doi:10.1093/geront/41.4.525 [CrossRef]
  • Rantz, M.J. & Popejoy, L.L. (1998). Using MDS quality indicators to improve outcomes. Gaithersburg, MD: Aspen.
  • Rantz, M.J., Vogelsmeier, A., Manion, P., Minner, D., Markway, B., Conn, V. & Mehr, D.R. (2003). Statewide strategy to improve quality of care in nursing facilities. The Gerontologist, 43, 248–258. doi:10.1093/geront/43.2.248 [CrossRef]
  • Rantz, M.J., Zwygart-Stauffacher, M., Popejoy, L., Grando, V.T., Mehr, D.R., Hicks, L.L. & Scott, J. (1999). Nursing home care quality: A multidimensional theoretical model integrating the views of consumers and providers. Journal of Nursing Care Quality, 14, 16–37. doi:10.1097/00001786-199910000-00004 [CrossRef]
  • Resnick, B., Kolanowski, A.M. & Van Haitsma, K. (2014). Promoting positive behavioral health: A nonpharmacological toolkit for senior living communities. Journal of Gerontological Nursing, 40(1), 2–3. doi:10.3928/00989134-20131206-01 [CrossRef]
  • Rosen, J., Mittal, V., Degenholtz, H., Castle, N., Mulsant, B., Rhee, Y.J. & Rubin, F. (2005). Organizational change and quality improvement in nursing homes: Approaching success. Journal of Healthcare Quality, 27(6), 6–14, 21, 44. doi:10.1111/j.1945-1474.2005.tb00583.x [CrossRef]
  • Russell, T.L., Madsen, R.W., Flesner, M. & Rantz, M.J. (2010). Pain management in nursing homes: What do quality measure scores tell us?Journal of Gerontological Nursing, 36(12), 49–56. doi:10.3928/00989134-20100504-07 [CrossRef]
  • Ryden, M.B., Gross, C.R., Savik, K., Snyder, M., Lee Oh, H., Jang, Y.P. & Krichbaum, K. (2000). Development of a measure of resident satisfaction with the nursing home. Research in Nursing and Health, 23, 237–245. doi:10.1002/1098-240X(200006)23:3<237::AID-NUR8>3.0.CO;2-I [CrossRef]
  • Ryden, M.B., Snyder, M., Gross, C.R., Savik, K., Pearson, V., Krichbaum, K. & Mueller, C. (2000). Value-added outcomes: The use of advanced practice nurses in long-term care facilities. The Gerontologist, 40, 654–662. doi:10.1093/geront/40.6.654 [CrossRef]
  • Schirm, V., Albanese, T. & Garland, T.N. (1999). Understanding nursing home quality of care: Incorporating caregivers’ perceptions through structure process, and outcome. Quality Management in Health Care, 8, 55–63. doi:10.1097/00019514-199908010-00007 [CrossRef]
  • Schwab, R.A., DelSorbo, S.M., Cunningham, M.R., Craven, K. & Watson, W.A. (1999). Using statistical process control to demonstrate the effect of operational interventions on quality indicators in the emergency department. Journal for Healthcare Quality, 21(4), 38–41. doi:10.1111/j.1945-1474.1999.tb00975.x [CrossRef]
  • Silver, M.S. (1999). Incident review management: A systemic approach to performance improvements. Journal for Healthcare Quality, 21(6), 21–27. doi:10.1111/j.1945-1474.1999.tb01000.x [CrossRef]
  • Silver, M.S. & Burack, O.R. (2000). Challenges to effective incident review management: Administrative and clinical factors. Journal for Healthcare Quality, 22(5), 6–12. doi:10.1111/j.1945-1474.2000.tb00146.x [CrossRef]
  • Smith, M., Mitchell, S. & Buckwalter, K.C. (1995). Nurses helping nurses: Development of internal specialists in long-term care. Journal of Psychosocial Nursing and Mental Health Services, 33(4), 38–42.
  • Spath, P.L. (2013). Introduction to health-care quality. Chicago, IL: Health Administration Press.
  • Spector, W.D. & Mukamel, D.B. (1998). Using outcomes to make inferences about nursing home quality. Evaluation and the Health Professions, 21, 291–315. doi:10.1177/016327879802100301 [CrossRef]
  • Tasa, K., Baker, G.R. & Murray, M. (1996). Using patient feedback for quality improvement. Quality Management in Health Care, 4(2), 55–67. doi:10.1097/00019514-199600420-00008 [CrossRef]
  • Tracy, K.B. (1999). Those old MDS files can be a gold mine. Nursing Homes/Long Term Care Management, 48(1), 48–51, 67–68.
  • Uman, G.C. & Urman, H.N. (1997). Measuring consumer satisfaction in nursing home residents. Nutrition, 13, 705–707. doi:10.1016/S0899-9007(97)83023-7 [CrossRef]
  • U.S. Department of Health and Human Services Health Care Financing Administration. (1997). 42 CFR Part 483. Medicare and Medicaid; Resident assessment in long term care facilities. Federal Register, 62(246), 67174–67212.
  • Van Haitsma, K., Curyto, K., Spector, A., Towsley, G., Kleban, M., Carpenter, B. & Koren, M.J. (2012). The preferences for everyday living inventory: Scale development and description of psychosocial preferences responses in community-dwelling elders. The Gerontologist, 53, 582–595. doi:10.1093/geront/gns102 [CrossRef].
  • van Maris, B., Soberman, L., Murray, M. & Norton, P.G. (1996). Satisfaction of residents and families in long-term care: II. Lessons learned. Quality Management in Health Care, 4(3), 47–53. doi:10.1097/00019514-199604030-00007 [CrossRef]
  • Watson, C.J., Mobarak, A.M. & Stimson, K. (1999). A collaborative effort to establish a long-term care benchmark process. Journal for Healthcare Quality, 21(2), 19–23. doi:10.1111/j.1945-1474.1999.tb00947.x [CrossRef]
  • Watson, N.M., Brink, C.A., Zimmer, J.G. & Mayer, R.D. (2003). Use of the Agency for Health Care Policy and Research Urinary Incontinence Guideline in nursing homes. Journal of the American Geriatrics Society, 51, 1779–1786. doi:10.1046/j.1532-5415.2003.51564.x [CrossRef]
  • Werner, R.M. & Konetzka, R.T. (2010). Advancing nursing home quality through quality improvement itself. Health Affairs, 29, 81–86. doi:10.1377/hlthaff.2009.0555 [CrossRef]
  • Zimmerman, D.R., Jewell, K.E. & Karon, S.L. (1998). Using resident assessment data to improve nutritional care in nursing homes: The power of information. Nutrition, 14, 410–415. doi:10.1016/S0899-9007(97)00461-9 [CrossRef]
  • Zimmerman, D.R., Karon, S.L., Arling, G., Clark, B.R., Collins, T., Ross, R. & Sainfort, F. (1995). Development and testing of nursing home quality indicators. Health Care Financing Review, 16, 107–127.
  • Zinn, J.S., Weimer, D.L., Spector, W. & Mukamel, D.B. (2010). Factors influencing nursing home response to quality measure publication: A resource dependence perspective. Health Care Management Review, 35, 256–265. doi:10.1097/HMR.0b013e3181e23d64 [CrossRef]

Sample Quality Indicators

DepartmentRegulation or Facility StandardQuality IndicatorType of Quality Indicator
MaintenanceFacility water temperatures are to be ≤110° F to prevent burns to residents.Water temperatures at ≤110° F on weekly checks.Process
No residents are burned while bathing.Outcome
Separate plumbing systems function for resident use and for dietary and laundry use.Structure
DietaryHot food temperatures are kept at requisite temperatures while serving to prevent food-borne illnesses.No food-borne illnesses will occur.Outcome
LaundryResidents’ clothing will be laundered to provide clean clothing for residents.Residents are wearing clean, dry clothing.Outcome
HousekeepingWet floor signs need to be placed at both ends of a hallway when mopping the floor to prevent falls.Two wet floor signs are present on either end of a hallway when the floor is or has been mopped.Process
No falls during mopping.Outcome
Social ServicesSocial Service assessments are completed within a timely manner.MDS social service assessments are signed and dated within 14 days of admission.Outcome
NursingNursing staffing schedules will be kept for 1 year.Any nursing schedule within the past year is available within minutes upon request.Structure
AdministrationPotential residents and family members will receive information regarding the facility in a timely manner.Admission packets will be mailed within 24 hours.Process

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