Assignment 2: Project Planning

Assignment 2: Project Planning

Assignment 2: Project Planning

A guide to quality improvement tools

December 2020


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Introduction 3
Purpose 3
Definition of ‘quality’ 3
Definition of healthcare quality improvement 3
Involving people in quality improvement 4
Quality improvement collaboratives 5
Directory of tools for quality improvement 6
Clinical audit 7
Statistical process control 9
Performance benchmarking 11
Process mapping 13
Root cause analysis 15
Model for improvement 17
Plan do study act 19
Lean/Six sigma 21
Technological innovations 23
Decision trees 25
Communication tools 27
Further reading list and references 29-30

Update 2020:
Ian Woolhouse, HQIP Kim Rezel, HQIP

First published: June 2015

Sally Fereday
Nicola Malbon

The National Quality Improvement Clinical Audit Network (NQICAN) and the HQIP Service User Network (SUN) for consultation on this document


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ISBN NO 978-1-907561-05-4

© 2020 Healthcare Quality Improvement Partnership Ltd (HQIP) Design: Pad Creative
The purpose of this guidance is to signpost those working within, leading, commissioning and using healthcare services to a broad range of quality improvement tools. It should be especially useful to those putting together quality improvement programmes.

This guidance introduces a variety of quality improvement tools used in healthcare and presents case examples and associated tools available to assist with implementation.

Definition of ‘quality’
Much of the current thinking that defines quality in the NHS was set out in ‘High quality care for all: NHS next stage review’,1 led by Lord Darzi.

It set out the following three dimensions (figure 1) which must all be present to provide a high quality service:
Clinical effectiveness: quality care is care which is delivered according to the best evidence as to what is clinically effective in improving an individual’s health outcomes
• Patient safety: quality care is care which is delivered so as to avoid all avoidable harm and risks to the individual’s safety
• Patient experience: quality care is care which looks to give the individual as positive an experience of receiving and recovering from the care as possible, including being treated according to what that individual wants or needs and with compassion, dignity and respect

Definition of healthcare quality improvement
There is no single definition of quality improvement within healthcare. In general, the term ‘quality improvement’ refers to the systematic use of methods and tools to try to continuously improve quality of care and outcomes for patients.

Key components include:

• Understanding the complex healthcare environment
• Applying a systematic approach
• Designing, testing and implementing changes using real time
• Measurement for improvement
There is no clear evidence that one approach is superior to others. Rather, it is the process of having a systematic approach to quality improvement and applying this consistently that is important.

Figure 1. Definition of quality

1. Department of Health, 2008. High quality care for all: NHS next stage review

Involving people in quality improvement
Those experiencing healthcare systems first hand can provide insightful feedback on the quality of services and how they might be improved. They can also provide useful personal perspectives which should be captured.

People’s input into service design is essential as only they have experience as service users. The involvement of people and communities in healthcare quality improvement can take many forms, for example:
• Representation at organisational quality committees
• Shadowing their journey to identify quality shortfalls
• Leading assessments of the health and care environment
• Completion of satisfaction surveys
• Involvement of people and communities to review the information materials that are provided to them
• Networking to share self-care strategies
• Analysis of complaints, concerns and claims
• People and community involvement in quality improvement focus groups

Figure 2. Capturing people and community experiences for insight and perspective

Quality improvement collaboratives
Quality improvement collaboratives involve groups of professionals coming together, either from within an organisation or across multiple organisations, to learn from and motivate each other to improve the quality of health services. Collaboratives often use a structured approach, such as setting targets and undertaking rapid cycles
of change.

The most common model for improvement collaboratives is the Breakthrough Series approach developed by the US
Institute of Healthcare Improvement. A Breakthrough Series is a short term (6 to 15months) learning system that brings together teams from hospitals or clinics to seek improvement in a focused topic area. The driving vision behind the Breakthrough Series is that sound science exists on the
basis of which the costs and outcomes of current healthcare practices can be greatly improved.
Key elements of an improvement collaborative include:

• Topic selection
• Faculty recruitment
• Enrolment of participating organisations and teams
• Learning sessions
• Action periods
• The model for improvement
• Summative workshops
• Measurement and evaluation

The quality improvement tools employed within improvement collaboratives are described in more detail in the next section.

Figure 3: Collaboration for quality improvement

Collaborative quality improvement

Tools to measure care against agreed standards Page
Clinical audit Checks clinical care meets defined quality standards 7
Statistical process control Measures quality within predefined parameters 9
Performance benchmarking Measures quality against peers or national targets 11
Tools to understand the cause of the problem Page

Process mapping Maps the patient journey for quality improvement opportunities

Root cause analysis Systematically uncovers the causes of events affecting quality
Tools to plan and test improvement projects Page
Model for improvement Decides upon, test and refines quality improvements 17

Plan do study act Introduces and tests potential quality improvements on a small scale

Lean six sigma Eliminates waste and redirects resources for quality and efficiency
Tools to promote change in practice Page

Technological innovations Automates processes and systems for care quality improvement

Decision trees Improves the quality and consistency of processes in healthcare

Communication tools Improves quality of care through structured information exchange

Clinical audit

Most effective:



How to use it:

For ensuring compliance with specific clinical standards and driving clinical care improvement.

Evidence based clinical standards drawn from best practice and an audit proforma comprised of measures derived from the standards. A clearly defined population of patients (or a sample from the population) whose care will be measured using the pro forma.

Clinical audit can be described as a quality improvement cycle that involves measurement of the effectiveness of healthcare against agreed and proven standards for high quality, and taking action to bring practice in line with these standards so as to improve the quality of care and health outcomes.2

To check clinical care provided against specific desired standards, clinical audit typically involves the design of a clinical audit pro forma comprising those standards, and the subsequent review of a defined sample
of healthcare data, such as health records, using this pro forma, collecting data over a specified timeframe. Data is analysed and where shortfalls against the standards are identified, action planning follows, to drive improvement, with repeated cycles of data collection and analysis at appropriate intervals to monitor change. Each full audit cycle is not complete until there is evidence that changes made have been effective (see Fig.4). Clinical audits can be carried out retrospectively, though are increasingly prospective, with clinicians completing proformas during or immediately after care delivery, or through automated electronic healthcare record ongoing real time data collection. Where clinical audits are designed and carried out by clinicians,
desired standards are embedded and awareness is raised amongst those delivering care. Findings and required actions for quality improvement should be shared with the entire relevant workforce to foster learning

2. Burgess, R. (ed), 2011. New Principles of Best Practice in Clinical Audit. 2nd ed. Radcliffe Publishing Limited


Figure 4: The clinical audit cycle
Stage 1 –
Preparation and planning (including for re-audit)

Stage 2 –
Measuring performance

4 3

Stage 4 –
Sustaining improvement (including re-audit)

Stage 3 – Implementing change

3. Barlow, J. and Krassas, G. (2013). Improving management of type 2 diabetes – findings of the Type 2 care clinical audit. Australian Family Physician

Statistical process control

Most effective:

When a process requires monitoring and control to maximise its full potential for optimum quality of care.


Statistical process control (SPC) is a method of quality improvement using statistics to monitor and control a process, ensuring that it operates at its full potential. At full potential, required quality is maintained and
waste is minimised. SPC can be applied to any process within which outputs can be measured. SPC involves:
• Control charts
• A focus on continuous improvement
• The design of experiments

SPC highlights the degree of variation from required outputs and enables the measurement of the impact of any experimental process change made for improvement.


Figure 5: Statistical process control chart4

Consecutive points
Case example:
Healthcare quality issue
Variation in improvement among practices participating in the Saskatchewan chronic disease management collaborative (CDMC), which set out to improve the quality of care through clinical processes for patients living with diabetes and coronary artery disease.5

Method selection
Statistical process control was applied to monitor the variation in improvement among practices participating in the CDMC and to explore the variation to identify remedial actions required.

Study participants were primary care practices from across the province, involving more than 25% of Saskatchewan family

physicians, all 13 regional health authorities and more than 15,000 patients with diabetes and coronary artery disease. SPC charts were used to record variation in CDMC process compliance between practices over time. The SPC charts set out to query whether all practices improved against the CDMC measures and if not, whether there were groups of practices that appeared to have different levels or rates of improvement and then to explore why.

Impact on quality
Once the variation in process compliance was charted it informed a further qualitative study to better understand why any differences occurred, exploring additional data on factors such as context (culture, team efficiency, leadership) and facilitation (collaborative facilitator roles and skills), to shed more light upon why differences between practices (and groups of practices) occurred and enable remedial action plans.

4. NHS Institute for Innovation and Improvement, 2008. Statistical process control
5. Timmerman, T. and Verrall, T. et al, 2010. Taking a closer look: using statistical process control to identify patterns of improvement in a quality-improvement collaborative. Quality and Safety in Health Care

Performance benchmarking
Most effective:

When local and national performance targets are established and given organisational importance as drivers for quality improvement.


How to use it:

Performance indicators are used as part of a benchmarking process to raise awareness of required standards and act as drivers for quality improvement. Healthcare organisations and their departments strive to meet standards imposed, and those performing well demonstrate models of best practice which can be shared, becoming the benchmark against which performance is compared.

Performance may be monitored through provision of data, or evidence of compliance with standards, to an external agency publishing league tables, which can also drive quality improvement as organisations aim for lead positions. Performance indicators should be carefully devised and are most powerful if they are active, for example, focused upon quality improvement initiatives met through evidence of positive outcomes achieved. The communication of organisational performance against national benchmarks for context raises awareness of shortfalls and stimulates further subsequent quality improvement.

Key performance indicators (KPIs) and benchmarking are also used within healthcare organisations to compare activity across different departments or units, unearthing and sharing best practice locally to drive quality improvement. Formal, routine and regular systems of data collection and review help define
quality improvement targets, provide a clear picture of progress towards goals and indicate trends, including emerging quality issues requiring resolution. Balanced scorecards are useful to translate organisational vision and strategy into tangible objective measures to help create KPIs, enabling measurement of progress towards defined targets, such as length of stay parameters, and mortality and readmission rates and may ultimately take any shape or form (see fig.6).


Figure 6: Producing a balanced scorecard

6. Schechter, M.S., 2012. Benchmarking to improve the quality of cystic fibrosis care. Current Opinion in Pulmonary Medicine

Process mapping

Most effective:

When the ‘patient’ journey is complex with associated inefficiencies.


Reviewing and mapping the whole ‘patient’ journey or diagnostic pathway with all parties involved enables the identification of inefficiencies and opportunities for improvement. It illustrates unnecessary steps, duplication, discrepancies, and variation and stimulates ideas for quality improvement to help create failsafe systems (see fig.7).


Figure 7: Process mapping7

The anticoagulant blood testing process

Effect on patient

Case example:
Healthcare quality issue
Evidence suggested that primary care physicians were not satisfied with communication at transition points between inpatient and ambulatory care and that information was often not provided in a timely manner, omitted essential information or contained ambiguities that put patients at risk.8

Method selection
Safe patient transitions depend upon effective and co-ordinated processes and the patient journey was therefore reviewed using process mapping.

Process mapping illustrated handover practices in place between ambulatory and inpatient care settings, identifying existing barriers and effective transitions of care and highlighting

potential areas for quality improvement. Focus group interviews were conducted to facilitate a process mapping exercise with clinical teams in six academic health centres in the USA, Poland, Sweden, Italy, Spain and the Netherlands. High level processes for patient admission to hospital through the emergency department, inpatient care and discharge back in the community were found to be comparable across sites.

Impact on quality
The process mapping exercise highlighted barriers to providing information to primary care physicians, inaccurate or incomplete information on referral and discharge, a lack of time and priority to collaborate with counterpart colleagues, and a lack of feedback to clinicians involved in handovers. Process mapping was effective in bringing together key stakeholders to make explicit current and required processes, exploring the barriers to and changes necessary for safe and reliable patient transitions, for quality improvement, through process revision.

7. NHS Institute for Innovation and Improvement, 2008. A conventional model of process mapping
8. Johnson, J.K., and Farnan, J.M., et al., 2012. Searching for the missing pieces between the hospital and primary care: mapping the patient process during care transitions. British Medical Journal Quality & Safety

Root cause analysis

Most effective:

When events affecting quality, are noted and analysis is required to identify the root causes of events, for improvement.


Root cause analysis (RCA) is a structured process, often used as a reactive method, to identify causes after an adverse event has occurred, or as an investigative tool to identify causes after clinical audit findings demonstrate shortfalls in the quality of care. However, RCA also affords insights which make it useful as a pro-active method to forecast or predict possible events before they occur, at system or process design or review stage. RCA enables the source of an issue or problem to be identified, so that resources for quality improvement can be appropriately directed towards the true cause of the issue or problem, rather than towards the symptoms.
Patient safety RCA investigations should be conducted at a level appropriate and proportionate to the adverse event under review, and should involve all associated stakeholders by way of relevant multidisciplinary
team involvement, with remedial action planning and associated audit and re-audit to prevent adverse event recurrence. Where adverse events are significant, affected patients/carers should be invited to take part for their valuable perspective and insight, as appropriate.


Figure 8: Fishbone cause and effect diagram9

Patient factors
Clinical condition Physical factors Social factors
Psychological/mental factors
Interpersonal relationships

Individual (staff) factors
Physical issues Psychology Social issues Personality Cognitive factors Domestic issues

Task factors
Guidelines Procedures Protocols Decision aids Task design

Communication factors
Verbal Written Non verbal

Team factors
Role congruence Leadership Support
Cultural factors

Problem or issue (CDP/SDP)

Education & training factors
Competence Supervision Availability Accessibility Appropriateness

Equipment & resource factors
Displays Integrity Positioning Usability

Working condition factors
Administrative Physical environment Staffing Workload/hours Time

Organisational & strategic factors
Organisational structure Priorities
Externally imported risks Safety culture

Case example:
Healthcare quality issue
Fluctuation in overdue medication dose rates in an acute teaching hospital.10

Method selection
Root cause analysis meetings were an essential component of a wider review to identify and investigate the causes of changes in overdue medication dose rates.

To investigate the changes in overdue medication dose rates over a four year period in an acute teaching hospital, retrospective time-series analysis of weekly dose administration data was

reviewed. Prescription data was extracted from the locally developed electronic prescribing and administration system, with an audit database containing details on every drug prescription and dose administration. Four interventions were implemented at the hospital: (1) the ability for doctors to pause medication doses; (2) clinical dashboards; (3) visual indicators for overdue doses and (4) executive-led overdue doses RCA meetings, at which findings were evaluated for cause and effect, and plans for remedial action were drawn up.

Impact on quality
Missed medication doses decreased significantly upon the introduction of these interventions coupled with overdue doses RCA meetings to drive improvement.

9. American Society for Quality, 2014. Fishbone cause and effect tool
10. Coleman, J.J. and Hodson, J. et al., 2013. Missed medication doses in hospitalised patients: a descriptive account of quality improvement measures and time series analysis. International Journal of Quality in Health Care

Model for improvement
Most effective:

When a procedure, process or system needs changing, or a new procedure, process or system is to be introduced, for measurable quality improvement.


The model for improvement accelerates improvements in the quality of healthcare processes and outcomes, via two phases:

1. Three fundamental questions, asked and addressed in any order, to define required changes and measures of improvement

2. The plan, do, study, act (PDSA) cycle (see next entry) to test changes in live settings and determine improvements

How to use it:

With an understanding of the current situation, where problems lie in a process, and what needs to change, quality improvements are designed, tested, measured and refined. For successful quality improvement it
is vital that an appropriate stakeholder team is formed as ideas for change arise from the insight of those who work in the system.
Three fundamental questions are answered by the team (see fig.9):

1. What are we trying to accomplish? The required quality improvements and specific group of patients that will be affected are defined
2. How will we know that a change is an improvement? Time-specific, measurable improvement aims are set

3. What changes can we make that will result in improvement? For each change to be tested, specific quantitative measures are established to determine whether or not the changes lead to improvement

Changes are tested using a PDSA cycle on a small scale, in the live setting: planning the change, testing it out, evaluating and acting upon results. After testing, learning and refining through several PDSA cycles, the change is implemented on a wider scale, for example, for an entire pilot population or hospital.



Figure 9: The Model for Improvement11

11. Institute for Healthcare Improvement, 2012. Model for Improvement
12. Brilli, R.J., and McClead, R.E.Jr., et al., 2013. A comprehensive patient safety program can significantly reduce preventable harm, associated costs, and hospital mortality. Journal of Pediatrics

Plan do study act

Most effective:

When a procedure, process or system needs changing, or a new procedure, process or system is to be introduced.


How to use it:

Plan, do, study, act (PDSA) cycles test changes to assess their impact, ensuring new ideas improve quality before implementation on a wider scale. Making changes to processes can give unexpected results, so it is safer and more efficient to test quality improvements on a small scale before wholesale implementation, allowing a sample of stakeholders involved to assess the proposed changes in action. Such small scale change introduction also enables interactions with other systems to be tested without causing large scale disruption to service quality, for example, completing a new patient assessment proforma with a limited group of patients before using the proforma for all patients.

A procedure, process or system which needs changing, or a new procedure, process or system to be introduced is developed (plan), implemented for a specific timeframe on a small scale with a minimal cohort of stakeholders (do), evaluated (study) and adjusted (act), with repeated PDSA cycles, until it is fit for purpose and wholesale implementation. Involving stakeholders in all four stages of the PDSA cycle fosters engagement with changes proposed and enables input for adjustment where potential users are aware of barriers to change (see fig.10).


Figure 10: The four stages of the plan, do, study, act quality improvement cycle

13. Boyd, S., and Aggarwal, I., et al., 2011. Peripheral intravenous catheters: the road to quality improvement and safer patient care. Journal of Hospital Infection

Lean/Six sigma

Most effective:

When healthcare systems are inefficient, wasteful and inconsistent in quality of care.


How to use it:

Lean seeks to improve flow in the value stream and eliminate waste. Six sigma uses the framework Define, measure, analyse, improve and control (DMAIC), with statistical tools, to uncover and understand root causes of variation and reduce them. Repeatability and reduced variation in healthcare services helps ensure a consistently high quality experience for patients, whilst waste reduction enables resources to be used where they are most effective. A combination of Lean and Six sigma provides a structured approach to quality improvement with effective problem-solving tools. Rapid transformational improvement results, with cost savings.

Lean uses process mapping with associated stakeholders to identify inefficiencies affecting the quality of care, enabling action planning for improvement (see fig.11). Process mapping with Lean adjustment
eliminates activity carried out ‘just-in-case’ or in a batch, holding excess inventory, waiting patients, excess transportation, defects, unnecessary staff movement, and unnecessary processing. In Six sigma, DMAIC and control charts are used to study adjusted processes over time. DMAIC is comprised of:

• Define: state the problem, specify the patient group, identify goals and outline the target process
• Measure: decide the parameters to be quantified and the best way to measure them, collect the necessary baseline data and measure after changes have been made
• Analyse: identify gaps between actual performance and goals, determine the causes of those gaps, determine how process inputs affect outputs, and rank improvement opportunities

• Improve: devise potential solutions, identify solutions that are easiest to implement, test hypothetical solutions and implement required improvements
• Control: share a detailed solution monitoring plan, observe implemented improvements for success, update on a regular basis and maintain a
training routine

Statistical process control charts are combined with DMAIC, whereby data are plotted chronologically, with a central line for the average, an upper line for the upper control limit and a lower line for the lower control limit, determined from historical data. By comparing current data with these lines after adjusted processes, conclusions are drawn about process variation. Such studies identify areas for improvement to ensure consistency of quality in health care, ultimately improving the patient experience.


Figure 11: Lean elimination of waste

14. Al-Hakim, L. and Gong, X.Y., 2012. On the day of surgery: how long does preventable disruption prolong the patient journey? International Journal of Health Care Quality Assurance

Technological innovations
Most effective:

When processes and systems require automation for reliability, ultimately saving resources.


Technological innovations automate processes and systems, offer reliability, reduce human error, and variation in care, and thus drive quality improvement. Life expectancy has increased and the healthcare system faces future crises with elderly care provision, a predicted rise in dementia diagnoses, obesity and associated conditions such as diabetes and cardiovascular disease and the need for wise use of limited resources. Efficiencies through technology are therefore vital to the sustainability of high quality healthcare provision.

How to use it:

Growth in the telehealth, telemedicine and telecare sectors, whereby technologies and related services concerned with health and wellbeing are accessed by people remotely, or provided for them at a distance, reduces time absorbed through routine appointments. It also enables patients to move from a state of dependency towards more flexible and empowered self-care arrangements, improving quality of life and healthcare experience.15 Technological innovations can incorporate alarms and early warning alerts where deterioration in patient health occurs, preventing serious decline.

Technological innovations and interventions have the power to improve and streamline the quality of care for patients of all ages and demographics, affording convenience and accessibility, and enabling patients to normalise and prevent medical conditions.

The move towards integrated electronic healthcare records affords shared real time data retrieval, active safety warnings and mandatory searchable fields, and sets the platform for further technological innovations to efficiently and effectively improve the quality of healthcare (see fig.12).

15. TeleSCoPE, 2014. Telehealth services code of practice for europe


Figure 12: Remote technologies for healthcare quality improvement

Case example:
Healthcare quality issue
The quality, timeliness and cost of outpatient surgical processes in hospitals were found to be adversely affected by problems in locating supplies and equipment and by post- operative infections.16

Method selection
Radio Frequency Identification (RFID) technology, the wireless use of electromagnetic fields to track data and equipment, automates identification systems to increase reliability and reduce human error and variation in care, for quality, timeliness and cost improvement.

A study was designed to research the benefits of implementing RFID, limiting scope to outpatient surgical processes in hospitals. The study used the Define, measure, analyse, improve, control (DMAIC) approach (see previous Lean/Six sigma entry), work flow

diagrams, value stream mapping and discrete event simulation, to examine the impact of implementing RFID equipment tracking on improving the effectiveness (quality and timeliness) and efficiency (cost reduction), of outpatient surgical processes.

Impact on quality
The study analysis showed significant estimated annual cost and time savings in carrying out surgical procedures with RFID technology implementation, largely due to the elimination of non-value added activities: locating supplies and equipment, and the elimination of the “return” loop created by preventable post-operative infections. Several fail-safes developed using RFID technology improved patient safety, the cost effectiveness of operations and the success of outpatient surgical procedures.
Many stakeholders in the hospital environment were positively affected by the use of RFID technology, including patients, physicians, nurses, technicians and administrators. Computations of costs and savings helped decision makers understand the benefits of the technology.

16. Southard, P.B. and Chandra, C. et al., 2012. RFID in healthcare: a Six sigma DMAIC and simulation case study. International journal of health care quality assurance

Decision trees

Most effective:

When decisions around healthcare options require consistency of approach.


A decision tree is a flowchart whereby each intersection represents a test and each branch represents the outcome of the test, designed by stakeholders of a multidisciplinary team to improve quality and consistency of decisions taken throughout a process.


Figure 13: Decision tree17

Unexplained syncope

Non-traumatic first faint with Holter in patient history or recurrent faints < 1 months apart

Mobile cardiac telemetry system

Patients history included > 1 faints more than one month apart and previous holter/mobile cardiac telemetry system

Traumatic faint/fall even if 1st event

Reveal insertable cardiac monitoring at day 31 if Mobile cardiac telemetry system is (-)

Reveal insertable cardiac monitoring

Case example:
Healthcare quality issue
It was noted that among patients who were discharged from a hospital emergency department (ED), about 3% returned within 30 days.18

Method selection
A decision tree was chosen to guide decisions around healthcare options on discharge, with consistency of approach.

A decision tree based model with electronic medical record features was developed and validated, estimating the ED 30-day revisit risk for all patients approaching discharge from ED. A retrospective cohort of 293,461 ED encounters was assembled, with the associated patients’ demographic information and one-

year clinical histories as the inputs. To validate, a prospective cohort of 193,886 encounters was constructed. Cluster analysis of high-risk patients identified discrete sub-populations with distinctive demographic, clinical and resource utilisation patterns, which were incorporated into the ED discharge decision tree.

Impact on quality
Revisits were found to relate to the nature of the disease, medical errors, and/or inadequate diagnoses and treatment during
the patient initial ED visit. Identification of high-risk patients using the decision tree enabled new strategies for improved ED care with reduced ED resource utilisation. The ED 30-day revisit decision tree model was incorporated into the electronic health record, and uncovered opportunities for targeted care
intervention to reduce resource burden, and most importantly to improve the quality of care and patient health outcomes.

17. Medtronics, 2014. Decision Tree: Syncope
18. Hao, S. and Jin, B., et al, 2014. Risk prediction of emergency department revisit 30 days post discharge: a prospective study. PLOS ONE Journal

Communication tools
Most effective:

When essential information requires rapid transfer.


Clear communication in healthcare is essential and carefully designed tools can help ensure comprehensive, complete and consistent communication to improve the quality of care


Figure 14: Situation, background, assessment, recommendation (SBAR)

19. Macmillan Cancer Support, 2010. Treatment summary: a tool to improve communication between cancer services and primary care

Further reading list

Involving people in quality improvement: Page 4
i. HQIP, 2020. Patient and public involvement in clinical audit
ii. HQIP, 2020. A guide to developing a patient panel in clinical audit
iii. NHS Improvement, Patient experience framework, June 2018iii
iv. NHS Institute for Innovation and Improvement: The experience based design (EBD) approach, July 2017
v. NHS England, 2019. Patient led assessments of the care environment

Quality improvement collaboratives: Page 5
i. IHI Breakthrough collaborative series
ii. NHS Improving Quality, 2008. Patient safety collaboratives

Clinical audit: Page 7
i. HQIP, 2015. Clinical audit: a guide for NHS boards and partners
ii. HQIP, 2015. Good governance handbook
iii. National Institute for Health and Care Excellence (NICE), 2014. Clinical audit tools

Statistical process control: Page 9
i. NHS Improvement making data count

Performance benchmarking: Page 11
i. NHS Improvement, 2008. Balanced scorecard

Process mapping: Page 13
i. NHS Improvement, A conventional model of process mapping

Root cause analysis: Page 15
i. NHS Improvement, 2008. Root cause analysis using five whys
Model for improvement: Page 17
i. Institute for Healthcare Improvement, 2012. Model for improvement

Plan do study act: Page 19
i. NHS Improvement, 2008. Plan do study act
ii. Institute for Healthcare Improvement, 2013. Plan do study act work sheet

Lean & Six sigma: Page 21
i. NHS Improvement, Vital signs: an improvement practice
ii. NHS Improvement, Lean Six Sigma: some basic concepts

Technological innovations: Page 23
i. NHS Institute Improvement, Digitilisation
ii. NHS Digital, NHS interoperability toolkit

Communication tools: Page 27
i. NHS Improvement, SBAR communication tool

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December 2020

Criteria Excellent Good Needs Improvement Below Expectations Points Earned
State the purpose of the project and current state baselines and identify key project stakeholders.

(40 pts)

Purpose of the project is clearly articulated, and current state of the issue is clearly and

completely described.  Baseline statistics are provided along with a detailed analysis of how they compare to benchmarks. Key


are clearly identified including a description of how the project impacts them and their

importance to

the project. (36-40)

Purpose ad current state of the issue is

Clearly described. Baselines are not statistically indicated or are incomplete. Analysis of what the baseline statistics represent are articulated along with benchmarks.  Key stakeholders are clearly identified but reason for inclusion is incomplete. (32-35 points)

Purpose and current state of

the issue is

described, but

may be incomplete. Baselines only generally described, or no benchmarks are provided.

Stakeholders are

identified, but

may be missing

some. (28-31 points)

Purpose and description of the

current state of

the issue is

incomplete or

unclear. Statistics and benchmarks are missing.

Stakeholders may be missing.

Overall description is

incomplete or not


clearly. (0-27)

Analysis of the problem is completed using one of the quality improvement tools found in Chapter 2 of the textbook or a quality analysis tool of your choice and state the results of the analysis. (25) Analysis is completed using at least one of the quality tools in the textbook or another tool the student describes. Analysis is completed correctly and explained clearly and concisely.  Based on the analysis, insights provided as to what contributing factors may have led to the current state of the problem. (23-25)


Analysis is completed using at least one of the

quality tools in

the textbook or

another tool the student describes.

Analysis is completed correctly. May be explained

less clearly or

completely. Contributing factors to the problem are not clear (20-22)

 Analysis is

completed by

using at least one

of the quality tools

in the textbook or

another tool the

student describes.

Clarification may

be needed for the

reader to interpret

the analysis. Insights into the contributing problems are vague or missing (15-19)

Analysis is


incorrectly, or an

inappropriate tool is used. Evidence that the student does not

understand how

to use the tools is

demonstrated. (0-14)

Explain the purpose of the quality improvement tool(s) chosen and the rationale for your choice. (15) The purpose of the selected quality tool(s) is described clearly and completely, and the rationale for the choice of tool is reasonable and concisely explained. (13-15) The purpose of the selected quality tool(s) is described less clearly or completely.  The rationale for the choice of tool is described and explained less clearly or completely, and needs further explanation. (10-12) The purpose of the selected quality tool(s) is not described completely and is lacking a clear rationale for the choice. (8-10) The purpose of the selected quality tool(s) is missing and rationale for is use is not presented. (0-7)  
Language, organization and use of references (10) Uses technical or scientific terminology appropriately and

correctly and applied at a doctorate level. No major grammatical or formatting errors.

Paper is organized with the use of headings.

Paper flows and information is presented clearly. References are used when indicated/appropriately. (9-10)

Uses technical or scientific terminology appropriately and

correctly at a graduate level. No more than 2 major grammatical or formatting errors and a few minor errors.

Paper is organized with the use of headings.

Some information may need clarifying. References provided in most situations where needed.  (7-8)

Ordinary word choice: use of scientific terminology avoided and/or not written at a graduate level. Some serious grammatical errors Paper may lack headings and may not flow very clearly. References are lacking throughout the paper. (3-6) Limited vocabulary: errors impair communication. Paper is not organized and lacks clear flow of information. References are missing throughout the paper. (0-2)  
DB: Paper posted by due date.  Responses to peers with helpful suggestions, additional information, expansion of ideas, or alternative views.  (10) Initial response posted by due date. At least two peer responses posted which contain helpful suggestions, provide specific additional insights or information, expands ideas, or provides an alternative viewpoint. (9-10)


Initial response posted by due date. At least two peer responses posted which contain suggestions, insights, or information, or provides an alternative viewpoint, but lack detail or substance (7-8) Initial response posted by due date. Only one peer response posted which contains minimal substance with suggestions, additional insights or information, ideas, or an and alternative viewpoint. (4-7) Initial response posted late.  Only one peer response posted which does not contain helpful suggestions, provide additional insights or information, expands ideas, or provides an alternative viewpoint. (0-3)  
        Total Points (100)  


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