The Benefits of Clinical Dashboards

Clinical Dashboards are intended to provide a mechanism to harness local existing data and bring it together in a way that facilitates effective clinical decision making by clinicians. This capability enables clinicians to improve the performance and quality of their service, and the quality of care they provide to patients. In summary:

• Better information for clinical teams, presented in an easy to understand format with high visual impact
• Utilisation of multiple sources of existing data, providing clinical information, relevant across a multidisciplinary team
• Information provided in 'real time', facilitating immediate targeted decisions to improve patient care and avoiding delays by data cleansing processes
• Improved data quality through immediate, day-to-day visualisation of data - reinforces 'capture once, use many times' behaviours

The benefits of Clinical Dashboards have begun to emerge from the experiences of clinical teams that have implemented clinical dashboards. The confirmation of these benefits has helped to develop the following Benefits Framework.

The common benefits of Clinical Dashboards (see Stage 1 and Stage 2 benefits in the framework) have been assessed by direct interviews and surveys with clinicians who have been involved in Clinical Dashboard projects over the last 12-18 months. Some of these results are included below.

Benefits Framework

Stage one: Project Benefits Dashboard

• Selecting metrics allows Clinicians to define the performance drivers of their service
• Identifying data gaps highlight potential functional requirements / areas for improvement in local information provision
• Existing data is converted to high-value information presented in without delay, and defined by clinicians

Stage two: Team, Staff and Quick Wins (monitor)

• Immediate, and timely information available to assist decision making
• Improved local peer engagement and cooperation, raising the quality of care
• Increased staff awareness and engagement with local issues and improvement plans
• Local awareness of data quality issues leading to improved data capture and accuracy
• Provision of greater local information to patients which informs expectations and improves satisfaction

Stage three: Experience, Quality, and Effectiveness (improve)

• Improved quality of interactions with patients
• Improved integrated care from information sharing across organisational boundaries
• Streamlining of patient care to appropriate services (e.g. 'touch points' per episode, LOS, day case rate)
• Improved compliance (e.g. reduced 'mixed gender' breaches, screening rates, assessment rates)
• Improved efficiency and resource utilisation (e.g. Theatre utilisation, ambulance utilisation)

Overall, clinicians strongly agree that Clinical Dashboards are a useful tool that facilitates improved decision making which can lead to Productivity and Quality improvements for their clinical services.

The following benefits and examples (case studies) are non-exhaustive and have been identified across a variety of care settings (Primary, Secondary, Mental Health and Ambulance).

• Improved outcomes and quality of interactions with patients
• Reduced untoward/serious incident rates (e.g. reduced falls)
• Improved patient load tracking and management
• Improved infection rate management
• Improved patient satisfaction

Case Study: Improving patient experience through transparency and monitoring satisfaction

Background:

Clinical Dashboards create a mechanism to share information within clinical teams and wider stakeholders' such as patients (e.g. wall mounted dashboard screen in patient waiting areas/clinics).

To monitor patient experience, the three dimensions of Dignity/Respect, Care/Treatment, Administration/Timeliness are being recorded and displayed on the dashboard (along with other key performance data) within a surgical unit in an Acute trust

Outcome:

• Improved ability to assess the effectiveness of the Patient Experience Committee and Quality and Safety Board, which also focus on these themes
• The visual presentation of performance serves as a constant reminder to staff of the importance of the fundamental components of a good experience for patients, and hence, will assist with the reinforcement of positive behaviours among staff
• By providing transparency of key clinical information, patients feel better informed and understand the constraints and challenges of their service provider

• Streamlining of patient care and pathways (e.g. to appropriate services)
• Improved Day Case surgery rate
• Reduced delayed discharges / optimised Length of Stay
• Reduced readmission rates
• Reduced Acute admissions from GPs
• Reduced unnecessary attendances

Case Study: Reduced average Length of Stay by 10% through monitoring in real-time to identify outliers and avoiding delayed discharges

Background:

The average Length of Stay within a clinical department is often strongly affected by outliers (where the length of stay is significantly higher than expected). By focussing the entire team on proactively identifying these cases and avoiding delayed discharges, the average Length of Stay can be reduced by 10%.

Calculation Drivers:

• Average Length of Stay  = 50 days (current)
• Length of Stay reduced by 10% results in Length of Stay reduction of 5 days per admission
• Total patient admissions per year = 225
• Bed day cost of £320 of which 50% is considered 'direct costs'

Outcome:

• Length of Stay reduction of 5 days per patient for 225 patients results in 1125 bed days saved per year
• The efficiency savings relating to this benefit is 1125 x £320 x 50% (direct costs only) = £180K pa

• Improved integrated care from information sharing across organisational boundaries
• GP's informed about patient attendances at Secondary care in real time
• Ambulance Trust data integrated with Secondary to join up the end to end pathway

Case Study: Reduced non elective admissions from GPs where they are above the peer group average

Background:

A Clinical Dashboard solution has successfully integrated secondary care attendance data with GP patient lists in real-time. This has allowed practices to monitor and identify frequent attendances for both non elective admissions and A&E attendances.

By actively managing patients who are attending frequently, it is anticipated that 15% of acute admissions can be avoided where practices where admission rates are higher than the peer group average.

Calculation Drivers:

• Total number of admissions that are above the peer group average across PCT = 1,400 pa
• 15% reduction in these admissions = 210 admissions avoided per year
• Average admission cost per admission = £1,300

Outcome:

• 210 acute admissions avoided (releasing this capacity to the LHC)
• The efficiency savings relating to this benefit is 210 x £1,300 = £270K pa (across the LHC)

• Improved compliance
• Improved screening/assessment rates (e.g. MRSA)
• Improved compliance rates (e.g. cancer treatment start dates, discharge summary)

Case Study: Cervical screening rates improved from 45% to 72% in six months

Background:

Practice A is a small practice in the centre of a North of England city with high levels of deprivation and a multi-ethnic population - mainly Southern Asian and Gurjurati-speaking. The cervical screening rate has historically been very low - 45% in 2008. The GP considered this a reflection of the challenges of his practice population.

Outcome:

 The performance of the practice was viewed on the dashboard, by the whole team, at a regular clinical meeting. The clinicians were shocked to realise that the practice was such an 'outlier' in relation to cervical screening, both in relation the whole PCT and their 'peer group' practices.

The practice immediately developed an action plan to address their low cervical screening rate and have now achieved a rate of 72%

• Improved efficiency and resource utilisation
• Reduced ambulance turn-a-round time at hospital
• Reduced inter-hospital patient transfers
• Reduced cancelled operations
• Reduced DNA appointments

Case Study: Improved ambulance utilisation by actively monitoring hospital turn-a-round times

Background:

An Ambulance Trust is using their Clinical Dashboard solution to help monitor and actively manage ambulance ulitisation by reducing the number of turn-a-round times that are greater than 30minutes (overruns). The dashboard is a contributor to a wider initiate to improve ambulance efficiency. The initiative has set a goal to reduce turn-a-round overruns by 50%.

Calculation Drivers:

1. Monthly hours of ambulance utilisation lost to overruns = 1850 hrs / month à 22,200 hrs pa
2. 50% reduction of overruns = 11,000 hrs of ambulance utilisation released
3. Average cost per hour for Ambulance = £100
4. The dashboard is a contributor to the improved utilisation = 25% allocated to dashboard

Outcome:

• 11,000 hrs of ambulance time released per year
• The efficiency savings relating to this benefit is 11,000 x £100 = £1.1M pa
• As the dashboard is a contributor to the overall benefit 25% of the total is attributable = £275K pa