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Summary The Health Care Quality Book Essay

Chapter 1: science and knowledge foundation

Two notable contributions to the industry from the Journal of American Medical Association: 1. Assessment of the state of quality  serious and widespread quality problems 2. Categorization of three defects:

a. Underuse: many scientifically sound practices are not used as often as they should be b. Overuse: can be seen in areas such as imaging studies for diagnosis in acute asymptomatic low back pain or prescription of antibiotics when not indicated for infections. c. Misuse: when the proper clinical care process is not executed appropriately, such as giving the wrong drug to a patients.

To Err Is Human: publication that shows the severity of the quality problems in a way that captured the attention of all key stakeholders for the first time  this report spoke about the negative, not how it should be improved. Crossing the quality chasm: provided a blueprint for the future that classified and unified the components of quality through six aims for improvement, chain of effect and simple rules for redesign of health care.

Six dimensions of quality (Berwick):
Outcome measures and goals (IOM) = Institute of Medicine’s Safe
Percentage of overall mortality rates/patients experiencing adverse events or harm Effective: science and evidence should be applied and serve as the standard for delivery of care. How well are evidence based practices followed? Percentage of time diabetic patients receive all recommended care at each doctor visit.. Efficient: Care and service should be cost effective, and waste should be removed. Analyzing the costs of care by patient, organization, provider or community Timely: no waits or delays in receiving care

Measured by waits and delays in receiving needed care, service, and test results. Patient centered: system should revolve around the patient, respect
its preferences and put the patient in control Patient or family satisfaction with care and service

Equitable: Disparities should be eradicated.
Examining differences in quality measures by race, gender, income or other factors.

The underlying framework for achieving these aims depicts the health care system in four levels: Level A: what happens with the patient
Level B: the micro system where care is delivered by small provider teams Level C: organizational level: the macro system or aggregation of the Microsystems and supporting functions. Level D: external environment where payment mechanisms, policy and regulatory factors reside (verblijven)

Chapter 2: Basic concepts of health care quality

The following attributes relevant to the definition of quality of care are important: Technical performance  refers to how well current scientific medical knowledge and technology are applied in a given situation (it is usually assessed in terms of timeliness and accuracy of the diagnosis, appropriateness in of therapy) Management of the interpersonal relationship  refers to how well the clinician relates to the patient on a human level.

The quality of this relationship is important because: By establishing a good relationship with the patient the clinician is able to fully address the patient’s concerns, reassure the patient and relieve the patient’s suffering It can affect technical performance: the clinician is better able to elicit from that patient are more complete and accurate medical history, which can result in a better diagnosis Amenities (voorzieningen)  refers to the characteristics of the setting in which the encounter between patient and clinician takes place, such as comfort, convenience and privacy. Amenities are valued both in their own right and for their effect on the technical and interpersonal aspects of care. Amenities can yield (opleveren) benefits that are more indirect.

Access  refers to the degree to which individuals and groups are able to obtain needed services. Responsiveness to patient preferences  respect for patients’ values, preferences and expressed needs affects quality of care as a factor in its own right. Equity  the amount, type or quality of health care provided can be related systematically to an individual’s characteristics, particularly race and ethnicity, rather than to the individual’s need for care or healthcare preferences, have heightened concern about equity in health care. Medicine does not fulfill its function adequately until the same perfection is within the reach of all individuals. Efficiency  refers to how well resources are used in achieving a given result. Cost-effectiveness  how much benefit, typically measured in terms of improvement in health status, the intervention yields for a particular level of expenditure.

For each stakeholder in health care, quality can be differently defined: page 30 + 31. These definitions have a great deal in common: Each definition emphasizes different aspects of care Definitions conflict only in relation to cost-effectiveness

All evaluations of quality of care can be classified in terms of one of the three aspects of caregiving they measure: Structure: when quality is measured in terms of structure, the focus is on the relatively static characteristics of the individuals who provide care and of the settings where the care is delivered. These characteristics include the education, training and certification of professionals. Process: refers to what takes place during the delivery of care, also can be the basis for evaluating quality of care. Outcomes: Outcome measures, which capture whether healthcare goals were achieved, are another way of assessment of quality of care. Outcome measures have to include the costs of care as well as patients’ satisfaction with care. Which one is better to use?  none of them, all depends on the circumstances.

To assess quality using structure, process or outcome measures, we need to know what constitutes good structure, good process and good outcomes. We need criteria and standards we can apply to those measures of care: Criteria = specific attributes that are the basis for assessing quality Standards = express quantitatively what level the attributes must reach to satisfy preexisting expectations about quality. For example  type of measure:
structure and focus on primary care group practice: Criterion: percentage of board-certified physicians in internal or family medicine – Standard: 100% of physicians in the practice must be board certified in internal or family medicine.

Optimal standards: denote the level of quality that can be reached under the best conditions, typically conditions similar to those under which efficacy is determined  useful as reference point.

Structural measures are well suited to detecting lack of capacity to deliver care of acceptable quality. They are also only as good and useful as strength of their relation to desired processes and outcomes. To evaluate structure, process and outcome measures criteria and standards are essential. Whereas the formulation of criteria is expected to be evidence driven (efficacy). The setting of standards is not similarly tied to scientific literature. The decision to set standards at a minimal, ideal or achievable level is most meaningful if driven by the goals behind the specific quality of care evaluation for which the standards are to be used.

Chapter 3: Variation in medical practice and implications for quality

Variation  the difference between an observed event and a standard or norm. Without this standard, or best practice, measurement of variation offers little beyond (biedt niet meer dan) a description of the observations. Random variation = physical attribute of the event or process, adheres to the laws of probability and cannot be traced to a root cause. (houdt zich aan de wetten van waarschijnlijkheid en kan niet worden herleid tot een oorzaak). It is not worth to study it in detail.

Assignable variation = arises from a single or small set of causes that are not part of the event or process and therefore can be traced, identified, and implemented and eliminated  subject to potential misunderstanding because of complexity of design and interpretation. 1. Process variation = the difference in procedure throughout an organization (use of various screening methods for colorectal cancer) Technique  multitude of ways in which a procedure can be performed within the realm of acceptable medical practice. 2. Outcome variation = difference in the result of a single process (mostly focus on this measure) – the process yielding optimal results  outcomes research 3. Performance variation = the difference between any given result and the optimal ideal result. This threshold or best practice is the standard against which all other measurements of variation are compared. Performance variation tells us where we are and how far we are from where we want to be, and suggests ways to achieve the desired goal.

Variation can be desirable?  a successful procedure that differs from other, less successful procedures is by definition variation. The objective then for quality improvement is not simply to identify variation but to determine its value. How can the variation be eliminated or reduced in the ways that focus on the variation rather than on the people involved? So, understanding the implications for quality of variation in medical practice is not simply learning how eliminate variation but learning how to improve performance by identifying and accommodating good or suboptimal variation from a predefined best practice.

Variability plays a role in identifying, measuring and reporting quality indicators (effective, efficient, equitable..) and process-of-care improvements.

Some hospitals are reluctant to use quality improvement measures (they perceive them as biased towards academic medical research centers or large health care organization)  untrue! Quality improvements efforts can be and have been successfully applied to small organization and practices.

The size of an organization also effects the ability to disseminate (verspreiden) best practices. Large organization tend to have rigid frameworks or bureaucracies; change is slow and requires perseverance (doorzettingsvermogen) and the ability to make clear to skeptics and enthusiasts the value of the new procedure in their group and across the system.

An organization ‘s commitment to paying for quality improvement studies and
implementation is equally affected by its size and infrastructure, but there are some minimum standard levels of quality and linked reimbursement schemes to achieving goals established by the Joint Commission, CMS and Medicare  all organizations obligated to meet these standards.

Quality improvement effort must consider organizational mind-set, administrative and physician worldviews, and patient knowledge and expectations. Physician buy-in is critical to reducing undesired variation or creating new and succesfull preventive systems of clinical care, therefore: training physician champions and inciting (aanzetten) them to serve as models, mentors and motivators and it reduces the risk of alienating (vervreemden) the key participants in quality improvement efforts.

Patient education in quality of care is equally subject to variation; patients are aware of the status of health care providers in terms of national rankings, public news of quality successes and so on. Educating patients about a health care organization and its commitment to quality makes variation and process-of-care measures available to the public.

Organizational mind set  organizational infrastructure is an essential component in minimizing variation, disseminating best practices and supporting a research agenda associated with quality improvements. Economic incentives may be effective in addressing variation in health care by awarding financial bonuses to physicians and administrators who meet quality targets or withholding bonuses from those who do not. Goals of incentives: to help people understand that their organization is serious about implementing quality changes and minimizing unwanted variation to ensure alignment with national standards an directions in quality of care and to encourage them to use the resources of the organization to achieve this alignment .

Chapter 4: Quality improvement: the foundation, processes, tools and knowledge transfer techniques

Different leaders of quality improvement systems: page 63 – 67

Quality improvement approaches (derivatives and models of the ideas and theories developed by thought leaders): PDCA/PDSA, Associates for Process Improvement’s Model for Improvement, FOCUS PDCA, Baldrige criteria, ISO 9000, Lean, Six Sigma.

PDCA/PDSA cycle
Basis for planning and directing performance improvement efforts. 1 Plan:
Objective: what are you trying to accomplish? What is the goal? Questions and predictions: What do you think will happen?
Plan to carry out the cycle: Who? What? When? Where?
2 Do
Educate and train staff
Carry out the plan (try out the change on a small scale)
Document the problems and unexpected observations?
Begin analysis of the data
3 Study/Check
Assess the effect of the change and determine the level of success as compared to the goal/objective Compare results to predictions
Determine what changes need to be made and what actions will be taken next 4 Act
Act on what you have learned
Determine whether the plan should be repeated with modifications or a new plan should be created Perform necessary changes
Identify remaining gaps in process or performance
Carry out additional PDCA/PDSA cycles until the agreed-upon goal or objective is met

API improvement model
Simple model for improvement based on Deming’s PDSA cycle. The model contains three fundamental questions that form the basis of improvement: What are we trying to accomplish?
How will we know that a change is an improvement?
What change can we make that will results in improvement?

FOCUS/PDCA model
Building on de PDCA cycle the FOCUS PDCA model is created: more specific and defined approach to process improvement. The key feature of this model is the preexistence of a process that needs improvement. The intent of this model is to maximize the performance of a preexisting process, although the inclusion of PDCA provides the option of using this model for new or redesign process. F: FIND a process to improve

O: ORGANIZE a team that knows the process
C: CLARIFY current knowledge of the existing or redesigned process U: UNDERSTAND the variables and causes of process variation within the chosen process S: SELECT the process improvement and identify the potential action for improvement Baldrige criteria

The criteria can be used to assess performance on a wide range of key indicators: health care outcomes; patient satisfaction; and operational, staff and financial indicators. The Baldrige healthcare criteria are built on the following set of interrelated core values and concepts (page 70). The criteria are organized into seven interdependent categories: Leadership

Strategic planning
Focus on patients, other customers, and markets
Measurement, analysis and knowledge management
Staff focus
Process management
Organizational performance results

Baldrige’s scoring system is based on a 1000 point scale. Each of the seven criteria is assigned a maximum value ranging from 85 to 450 maximum points. The most heavily weighted criterion is the results category (450). The weight of this category is based on an emphasis Baldrige places on results and an organization’s ability to demonstrate performance and improvement in the following areas: Product and service outcomes, customer-focused outcomes, financial and market outcomes, workforce-focused outcomes, process effectiveness outcomes, leadership outcomes.

ISO 9000
The international Organization for Standardization (ISO) issued the original 9000 series of voluntary technical standards in 1987 to facilitate the development and maintenance of quality control programs in the manufacturing industry. In 2000, ISO made major changes to the standards to make them more relevant to service and health care settings. Focused more on quality management systems, process approach, and the role of top management, the most recent standards include eight common quality management principles: Customer-focused organization

Leadership
Involvement of people
Process approach
System approach to management
Continual improvement
Factual approach to decision making
Mutually beneficial supplier relationships

Lean thinking
Lean  to describe production methods and product development that, when compared to traditional mass production processes, produce more products, with fewer defects, in a shorter time. The focus of Lean methodology is a ‘back to basics’ approach that places the needs of the customer first through the following five steps: 1. Define value as determined by the customer, identified by the provider’s ability to deliver the right product or service at an appropriate price. 2. Identify the value stream: the set of specific actions required to bring a specific product or service from concept to completion 3. Make value added steps flow from beginning to end

4. Let the customer pull the product from the supplier, rather than push products 5. Pursue perfection of the process

Six sigma
The aim of six sigma is to reduce variation (eliminate defects) in key business processes. By using a set of statistical tools to understand the fluctuation of a process, management can predict the expected outcome of that process. Six sigma incluses five steps, commonly known as DMAIC: Define: Identify the customers and their problems. Determine the key characteristics important to the customer along with the processes that support those key characteristics. Identify existing output conditions along with process elements. Measure: Categorize key characteristics, verify measurement systems and collect data Analyze: Convert raw data into information that provides insights into the process.

These insights include identify the fundamental and most important causes of the defects or problems. Improve: Develop solutions to the problem, and make changes to the process. Measure process changes and judge whether the changes are beneficial or another set of changes is necessary. Control: If the process is performing at a desired and predictable level, monitor the process to ensure that no unexpected changes occur. The primary tool of six sigma is that focus on variation reduction will lead to more uniform process output. Secondary effects include less waste, less throughput time and less inventory.

Quality tools: three categories (also six categories distinguishing on page 74) Basic quality tools
Control chart: upper and lower control boundaries that define the limits of common cause variation. It is used to monitor and analyze variation from a process to determine whether that process is stable and predictable or unstable and not predictable Histogram

Cause-and-Effect/Fishbone diagram: the problem is stated on the right side of the cart, and likely causes are listed around major headings that lead to the effect. It can help organize the causes contributing to a complex problem. Pareto chart: 80% of the variation of any characteristic is caused by only 20% of the possible variables. Management and planning tools (75)

Affinity diagram: a list of ideas is created, and then individual ideas are written on small note cards. Team members study the cards and group the ideas into common categories. The affinity diagram is a way to create order of a brainstorm session. Matrix diagram: helps us to answer two important
questions when sets of data are compared: Are the data related? How strong is the relationship? Priorities matrix: uses a series of planning tools built around the matrix chart. Other quality tools

Benchmarking: compares the processes and successes of you competitor of similar top-performing organizations to your current processes to define, through gap analysis, process variation and organizational opportunities for improvement. Benchmarking defines not only organizations that perform better but also how they perform better. Failure mode and effect analysis: examines potential problems and their causes and predicts undesired results. FMEA normally is used to predict product failure form past part failure, but it also can be used to analyze future system failures  both in patient safety toolbox. 5S: is a systematic program that helps workers take control of their workspace so that is actually works for them instead of being a neutral or, as is quite common, competing factor. Sort: means to keep only necessary items

Straighten: means to arrange and identify items so they can be easily retrieved when needed. Shine: means to keep items and workspaces clean and in working order Standardize: means to use best practices consistently

Sustain: means to maintain the gains and make a commitment to continue the first four S.

Theory of Transfer of Learning  page 77

Rapid cycle testing/improvement
Developed by IHI, rapid cycle testing/improvement was designed to create various small tests involving small sample sizes and using multiple PDSA cycles that build on the lessons learned in short period while gaining buy-in from staff involved in the change. It is designed to reduce the cycle time of new process implementation from months to days.

Read 78/79/80/81

Chapter 5: Milestones in the quality measurement journey

Many health care providers struggle to address the measurement mandate proactively, which leads organizations to assume a defensive posture when external organizations release the data. In such cases, the provider usually responds in one of the following ways: data are old, data are not stratified and do not represent appropriate comparisons, our patients are sicker than those in other hospitals. A more proactive posture would be to develop an organization-wide approach to quality measurement that meets both internal and external demands. This approach is not a task, but a journey that has many potential pitfalls and detours. Key milestones exist that mark your progress and chart your direction.

Milestone 1: Develop a measurement philosophy (strategic step): What is/should be the role of performance measurement in the organization? Should it be done periodically or a day-to-day function? The first step toward this milestone should be the creation of an organizational statement on the role of measurement. Three simply questions should be explored when developing a measurement philosophy: 1. Do we know our data better than anyone else does?

2. Do we have a balanced set of measures that encompasses clinical, operational, customer service and resource allocations? 3. Do we have a plan for using the data to make improvements?

Milestone 2: Identify the concepts to be measured (types and categories of measures) (strategic and operational step)
The second milestone consists of deciding which concepts the organization wishes to monitor. There are three basic categories of measures: structure (s): represents the physical and organizational aspects of the organization processes (p): every activity, every job, is part of a process. outcomes (o): structure combine with processes to produce outcomes. The relationship between these categories usually is shown as follows: s + p = o Another categorization that can be made is (more specific) according to the six aims for improvement: 1 Safe, 2 Effective, 3 Patient centered, 4 Timely, 5 Efficient, 6 Equitable Regardless of the method used, an organization must decide which concepts, types, or categories of measures it wishes to track.

Milestone 3: Select specific measures
What aspect of (patient safety) do we want to measure?
What specific measures could we track?
Choose a specific indicator
In this step you need to specifying what aspect of for example patient safety you intend to measure and the actual measures. Within the patient safety, you could focus on medication errors, patient falls, wrong site surgeries etc. Within the medication error you can measure different things: number of medication orders that had an error, total number of errors caught each day, percentage of orders with an error etc.

Milestone 4: Develop operational definitions for each measure An operational definition is a description, in quantifiable terms, of what to measure and the specific steps needed to measure it consistently. A good operational definition: Gives communicable meaning to a concept or an idea

Is clear and unambiguous
Specifies the measurement method, procedures and equipment
Provides decision-making criteria when necessary and
Enables consistency in data collection
The problem created by poor operational definitions should be obvious: if you do not use the same operational definition each time you record and plot data on a chart, you will either miss a true change in the data or think a change has occurred when in fact one has not. Using the same operational definition becomes even more critical if you are trying to compare several hospitals or clinics in a system.

Milestone 5: Develop a data collection plan and gather data (giving special consideration to stratification and sampling) Direct start with data collection may cause teams to collect the wrong data in the wrong amounts. The data collection phase consists of two parts:

Planning for data collection: what process will be monitored? What specific measures will be collected? What are the operational definitions of measures?.. The actual data gathering: how will you collect the data? Will you conduct a pilot study? Who will collect the data?… (page 94) Once you have resolved these issues, the data collection should go smoothly. Sometimes improvement teams do not spend enough time on data collection plans. This can lead to the following problems: (1) collect too much, or too little data (2) collect the wrong data (3) become frustrated with the entire measurement journey. Consequences can be: the team tends to (1) distort (verdraaien) the data (2) distort the process that is produced the data or (3) kill the messenger.

Two key data collection skills – stratification and sampling enhance any data collection effort. Stratification = the separation and classification of data into reasonably homogeneous categories. The objective of stratification is to create strata, or categories, within the data that are mutually exclusive and facilitate discovery of patterns that would not be observed if the data were aggregated. Stratification allows understanding of differences in the data caused by different factors (page 95). If you do not think about how these factors could influence your data you run the risk of making incorrect conclusions and having to filter out the stratification effect manually after you have collected the data. Sampling (steekproef)  the most important thing you can do to reduce the amount of time and resources spent on data collection. There are four conditions for developing a sampling plan: accuracy, reliability, speed and economy. Sampling consists of a series of compromises and trade-offs. The basic purpose of sampling is to be able to draw a limited number of observations and be reasonably confident that they represent the larger population from which they were drawn.

There are two basic approach to sampling: Probability sampling techniques: based on statistical probability (systematic sampling, simple random sampling, stratified random sampling, stratified proportional random sampling) Non-probability sampling techniques: should be used when estimating the reliability of the selected sample or generally applying the results of the sample to larger population is not the principal concern. The basic objective is of this type of sampling is to select a sample that the researchers believe is typical of the larger population. (convenience
sampling, quota sampling and judgement sampling) 99-102

Milestone 6: Analyze the data using statistical process control methods (especially run and control charts) Translate data into information.

Milestone 7: Use the analytic results to take action (implement cycles of change, test theories and make improvements)

Chapter 6: Data collection

Quality measurements can be grouped into four categories:
Clinical quality
Financial performance
Patient satisfaction
Functional status
To report on each of these categories, several spate data sources may be required. The challenge is to collect as much data as possible from the fewest sources with the objectives of consistency and continuity in mind.

Retro prospective data collection: involves identification and selection of a patient’s medical record or group of records after the patient has been discharged. Prospective data collection: relies on medical record review, but it is completed during a patient’s hospitalization or visit rather than retrospectively. Disadvantage: time consuming and can distract nurse from their direct patient care responsibilities, expensive method, mostly full time data analyst needed.

Source for data for quality improvements:
Administrative databases: are information collected, processed and stored in automated information systems. Excellent source of data for reporting on clinical quality, financial performance, and certain patient outcomes.

Advantages: less expensive source of data, they incorporate transaction systems, moest of the code sets embedded are standardized, the database are staffed by individuals who are skilled, the volume is great, data reporting tools are available.. Disadvantages: some argue that these data is less reliable than data gathered by chart review. Patient surveys: especially when teams are interested in the perceptions of patients, either in terms of the quality of care or the quality of service provided. A team can design the survey itself, hire an expert to design a survey, or purchase an existing survey/survey service. Functional status surveys: usually measured before and at several points following the treatment or procedure. (for example a baseline before the knee procedure and then assessments are made at regular intervals after the surgery) Health plan databases: excellent source of data for quality improvement projects, particularly projects that have a population health management focus.

These databases are valuable because they contain detailed information on all care received by health plan members. It provides a comprehensive record of patient activity and can be used to identify and select patients for enrollment in disease management programs. Used properly: rich source of data for population management, disease management and quality improvement projects. Health plan databases limitations: considerations include accuracy, detail and timeliness. Recoding may make some data inaccurate, they do not contain detailed information on outcomes of care . Patient registries: powerful source of quality improvement data. Advantages: rich source of information because they are customized, can collect all the data that the physician or health system determines are most important, can be used for quality improvements, they are not subject to the shortcomings of administrative or health plan databases, collection techniques can be combined to provide a complete picture of the patient experience. They are versatile and flexible. Example case study in clinical reporting: page 123-127

Conclusion: there are many sources and data collection approaches from which to choose. Rarely does one method serve purposes, so it is important to understand the advantages and disadvantages of all methods. A combination is also possible. Knowledge of different sources and techniques will help you to use data more effectively and efficiently in your clinical improvement effort.

Chapter 7: Statistical tools for quality improvement

Three fundamental purposes for performance measurement:
Assessment of current performance: identify strengths and weaknesses of current processes Demonstration and verification of performance improvement
And control of performance
Performance measurement benefits organizations in several ways: provides factual evidence of performance, promotes ongoing organization self-evaluation and improvement, illustrates improvement, facilitates cost-benefit analysis, helps to meet external requirements and demands for performance evaluation, may facilitate the establishment of long-term relationships with various external stakeholders. May differentiate the organization from competitors, may contribute to the awarding of business contacts and fosters organizational survival. ..

Chapter 13: Leadership for quality

Leadership = working with people and systems to produce needed change. Individual leadership = this set of leadership is about what people must be and what they must know how to do, if they are to influence others to bring about needed changes. Both being and doing are needed, especially when the changes required for quality improvement involve reframing core value or remaking professional teams. Many improvements in health care will require these kinds of deep changes in values. These changes are sometimes labeled as transformational changes to distinguish them from transactional changes, which do not require changes in values and patterns of behavior.

Organizational leadership = about creating a supportive organizational environment in which hundreds of capable individual leaders’ work can thrive (groeien). One way to view this level (system-of-leadership level) is as a complex set of interrelated activities in five broad categories: Set direction: every organization has a sense of direction, a future self-image. A leader should set that direction. Establish the foundation: leaders must prepare themselves and their leadership teams with the knowledge and skills necessary to improve systems and lead change (and reframe values) Build will: to initiate and sustain change takes will, which seem to be highly sensitive to discord and often grind to a halt because of one loud voice opposing change  therefore making logical and quantitative links should be made between improvement and key business goals. Generate ideas: quality challenges require innovation.

Page 313

Implementing quality as the core organizational strategy

Implementing a culture that has quality improvement at its core is an important goal for providers who want to serve patients better, gain the support of healthcare providers, stay ahead of government regulation, meet consumer’s demand for transparent information on quality and costs, an gain a competitive advantage in the marketplace. Recent history: many efforts have not resulted in the sustainable quality improvements that the leaders hoped to see.

Quality improvement strategy should start with leadership from the board of trustees, the CEO and the executive team, but it is a challenge for health care organizations because of the many internal competing agendas, the rapidly changing environment, employees and so on.

First step: to establish an organizational culture that will support the hospital on their journey to quality  starting point: leadership!

Kaplan & Norton: Balanced Scorecard  this approach includes the perspective of the patient and family, internal processes such as clinical pathways, learning and growth opportunities that focus on employees and financial performance. Role of leadership: leaders ask financial questions about market share, margins and quality implications. They raise questions related to the satisfaction of their internal and external customers and the way in which business processes must change to improve and sustain quality. Primary focus on creating a culture of quality.

Baldrige National Quality Program
Creating the change towards quality starts with leadership.
Road map for change
Eight stage change process, modified form Kotter’s seminal work (Leading Change 1996) serves as a realistic and viable framework to guide leaders who are managing a change to quality: 1. Unfreezing the old culture

This is the most difficult step because of culture’s influence on employee behavior and some employee’s to desire to resist change and impede progress. 2. Forming a powerful guiding coalition

3. Developing a vision and strategy
4. Communicating a vision and strategy
5. Empowering employees to act on the vision and strategy
6. Generating short-term wins
7. Consolidating gains and producing more change
8. Refreezing new approaches in the culture

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