annex 3 finance workstream · agree npv inputs ... what are the transition costs (e.g., relocating...

Annex 3 – Finance workstream

Scarborough ASR | 21 January 2019

2

Scarborough acute services review – problem statement worksheet

Perspective/context

Acute services at Scarborough hospital have for a number of years been subject to growing clinical, financial and workforce pressures, in line with most other smaller acute hospitals around the country.

In 2012, York and Scarborough hospitals merged, with a view to addressing these challenges through greater collaboration across the two sites.

While this has delivered some benefits, the distance between the two sites has made it difficult to fully realise the intended benefits.

Constraints within solution space

▪ Ingoing hypothesis that there will continue to be an Emergency Department on the Scarborough Hospital site with associated core service elements

▪ Any solution needs to be consistent with broader strategies and developments across the region, including the Humber Acute Services Review

1 4

Stakeholders

▪ Local population served by Scarborough hospital▪ Staff at Scarborough & York hospitals▪ Local primary care, community and ambulance service providers▪ Neighbouring acute hospitals, in particular Hull and East Yorkshire

Hospitals NHS Trust▪ Regulators▪ Commissioners

Criteria for success

An aligned view on how best to deliver high quality, sustainable acute services for the population served by Scarborough Hospital, which:▪ Is based on a consensus, evidenced-based view of underlying

needs of the population and the challenges of continuing to meet those needs without change

▪ Provides both a short and long-term solution▪ Is aligned with broader strategies and developments across the

region▪ Is developed in a way that builds trust, confidence and stronger

relationships across staff on both YTH sites

2

5

Key sources of Insight

▪ Previous reviews and business cases, including: Independent Review of Health Services in North Yorkshire and York (2011 & 2013); YTH merger business case; Tariff local modification application; CQC reports

▪ National and local data on clinical, operational and financial performance (including workforce data)

▪ Staff interviews▪ External experts and reports, including reports on best practice

models for smaller hospitals from the NHS and overseas

Scope of Solution Space

▪ The emphasis is on how best to provide sustainable acute services to the population of Scarborough

▪ But this will include consideration of wider health and care services required by the local population to ensure a joined-up solution

3

6

3

The review is aimed at determining how best to meet the needs of the local population

Objective of the programme

▪ To develop an aligned view on how best to deliver high quality, sustainable acute services for the population served by Scarborough Hospital, which:

a. Is based on a consensus, evidenced-based view of underlying needs of the population and the challenges of continuing to meet those needs without change

b. Provides both a short and long-term solution

c. Is aligned with broader strategies and developments across the region

d. Is developed in a way that builds trust, confidence and stronger relationshipsacross staff on both YTH sites

4

Through the course of the review we are focusing on answering five questions

1. What is the case for change from a clinical, workforce and financial perspective, and which services are most impacted?

2. What evaluation criteria should be used to assess clinical models?

3. What are the range of clinical models that could underpin any future configurations?

4. What is the shortlist of service configuration models that we should assess against the evaluation criteria?

5. How do those options stack up against the evaluation criteria?

1

2

3

4

5

5

Programme governance is being managed through a series of working groups

Roles and responsibilities

▪ The Steering Group – with cross organisational representation – is responsible for providing oversight of the programme, debating key issues, and making final recommendations

▪ Any recommended service changes would need to be endorsed by CCG Governing Bodies and YTH board

▪ The Partnership Executive Group will provide direction to the overall programme and ensure coordination with other Partnership programmes and reviews

▪ The Clinical and Finance Groups are responsible for debating and agreeing key issues and assumptions to inform Steering Group discussions

▪ The Communications and Engagement Group will support the review by coordinating engagement and communication with local communities, staff and other stakeholders

Finance Reference Group

Communications and Engagement

Group

Clinical Reference Group

Scarborough Acute Services Review Steering Group

CCG Governing Bodies

Task and finish groups

(as required)

All activities supported by the Review Working

Group

YTH BoardPartnership

Executive Group

6

Finance Reference Group agendas and timings Focus for today

1. Agree ways of working and modelling approach

3. Review reconfiguration modelling assumptions

4. Review short list of models and implications for evaluation

2. Finalise baseline and review approach to travel time analysis

5. Review updated complete financial evaluation

Thurs 13th Sept Thurs 27th Sept Thurs 11th Oct Mon 22nd Oct Mon 29th Oct

▪ Sign off revisions in baseline assumptions (e.g., non-demographic activity growth, demand management)

▪ Agree updated ‘do nothing’ baseline

▪ Review and agree approach to travel time analysis

▪ Sign off revisions in baseline (e.g., demand management)

▪ Discuss approach to modelling and core assumptions– Review activity

shift assumptions

– Review capital expenditure assumptions

– Review NPV assumptions

▪ Review shortlist of models and high level descriptions

▪ Review and agree – activity shifts– capacity shifts– capital costs– I&E outputs

▪ Discuss transition cost assumptions and high level plan

▪ Agree sensitivity analysis to run

Discussion agenda

▪ Play back models and evaluation

▪ Agree any revisions to model outputs– I&E– Capital

requirement– Transition cost

▪ Agree NPV outputs and all sensitivities

▪ Finalise and agree provider baseline assumptions and outputs

▪ Finalise and agree revised provider baseline assumptions and outputs

▪ Agree activity shift assumptions

▪ Agree capital expenditure assumptions

▪ Agree NPV inputs

▪ Agree activity shift▪ Agree capacity shifts▪ Agree I&E and capital

cost components of evaluation

▪ Agree financial implications of shortlist to take back to CRG

▪ Agree transition cost assumptions

Outputs

▪ Finalise all remaining assumptions

▪ Finalise modelling outputs for– I&E– Capital cost– Transition cost– NPV

▪ Agree modelling approach and initial models

▪ Agree key baseline assumptions

▪ Agree financial evaluation criteria

▪ Agree ways of working, participants and meeting schedule

▪ Review financial evaluation criteria

▪ Review approach to modelling and key assumptions to be agreed

▪ Review key assumptions and preliminary output for ‘do nothing’ model

7

The following criteria will be used to evaluate models

Defined asEvaluation criteria

1.1 Clinical effectiveness

1.2 Patient and carer experience

1.3 Safety

Quality of Care1

2.1 Impact on patient choice

2.2 Distance, cost and time to access services

2.3 Service operating hours

2.4 Ability for clinicians to access specialist input

Access to care2

3.1 Scale of impact

3.2 Impact on recruitment, retention, skills

3.3 Sustainability

Workforce3

Deliverability

5.1 Expected time to deliver

5.2 Co-dependencies with other strategies/strategic fit5

4.1 Forecast income and expenditure at system and organisation level

4.2 Capital cost to the system

4.3 Transition costs required

4.4 Net present value (30 years)

Value for money4

Detailed on the following page

8

Finance/value for money sub-criteria

▪ What are the implications on income and expenditure for each acute Trust within the system?

▪ Will this model reduce the requirement for additional provider subsidy?

▪ What are the implications for total acute spend across the health and care system?

▪ What are the opportunities for investing in more appropriate / alternative settings of care?

▪ What would the capital costs be to the system of each model, including refurbishing or rebuilding capacity in other locations?

▪ Can the required capital be accessed and will the system be able to afford the necessary financing costs?

▪ What is the 30 year NPV (net present value) of each model, taking into account capital costs, transition costs and operating costs?

▪ What are the transition costs (e.g., relocating staff, training and education costs)?

Questions to test

Costs & income

Capital cost to the system

Net present value

Transition costs

Evaluation criteria

9

Analysis will focus on modelling the impact of acute clinical modles for a range of service lines

Areas we will cover Areas not addressed by this analysis

▪ 5 and 10 year projection of financials (I&E), activity and bed capacity for Scarborough Hospital

▪ Service lines in scope:– A&E (major, standard, minor)– Day case medicine– Elective medicine– Non elective medicine– Day case surgery– Elective surgery

– Non elective surgery– Critical care– Inpatient paeds– Maternity (births)– Outpatient (F2F and other)

▪ 30 year NPV for each option

▪ Acute patient activity, I&E and capacity for providers other than Scarborough Hospital

▪ Commissioning and contracting approach with other providers to support the clinical models

▪ Impact on diagnostic activity▪ Impact on social care

10

The financial modelling is driven by changes in population, changes to cost and price and shifts in activity between sites

Current slide 19Current slide 14 ?

Compare changes to baseline with different models

Apply the drivers to current position and forecast future position

Understand the drivers of changes in income and expenditure

Activity drivers

Non-demographic growth

Demand management/QIPP

Demographic growth

Income drivers Cost drivers

Price changes

4

# of new commissions

2010/11, WTE

% of total

2010/11

New nursing & midwifery commissions1

11

9

9

9

9

8

6

24

15

NHS London trains ~30% more nurses and midwives per qualified

workforce than the national average

Note: Data for North West SHA not readily available through public sources

1 Including pre-registration and post-registration nursing and midwifery training places

0.4

0.4

0.4

0.3

0.3

0.4

0.4

0.4

0.5

0.6

+40%

62.2

+32%

51.6

66.0

47.9

45.0

67.2

63.6

61.3

75.0

82.4

2,089National average

North East 1,135

South Central 1,555

South West 1,655

Yorkshire & Humber 1,697

South East Coast 1,609

East Midlands 1,733

East of England 1,991

West Midlands 2,851

London 4,572

NHS ACTIVITY COMPARISON

Source: SHA MPET investment plans and annual reports; SHA websites; NHS Information Centre Workforce Data, 2010; NHSL

internal data submissions; DH Exposition Book 2011; analysis

New nursing & midwifery

commissions per 1000

nursing workforce1

2010/11, #



weighted population1

2010/11, #

A

100

Forecast of future position

Comparison of different modles

6SOURCE: Team analysis

Savings

2014/152013/142012/132011/122010/11

Demographic change, residual demand growth and unit cost

changes, if left unmanaged, would together increase spendNominal

Forecast ‘do

nothing’ spend

Forecast actual

spend after savings

Savings measured

relative to the ‘do-

nothing’ spend

NOTE: See appendix for actual assumptions used

DUMMY NUMBERS –

FOR ILLUSTRATIVE

PURPOSES ONLY

Changes in the unit cost of activity

Changes to service standards

4

# of new commissions

2010/11, WTE

% of total

2010/11

New nursing & midwifery commissions1

11

9

9

9

9

8

6

24

15

NHS London trains ~30% more nurses and midwives per qualified

workforce than the national average

Note: Data for North West SHA not readily available through public sources

1 Including pre-registration and post-registration nursing and midwifery training places

0.4

0.4

0.4

0.3

0.3

0.4

0.4

0.4

0.5

0.6

+40%

62.2

+32%

51.6

66.0

47.9

45.0

67.2

63.6

61.3

75.0

82.4

2,089National average

North East 1,135

South Central 1,555

South West 1,655

Yorkshire & Humber 1,697

South East Coast 1,609

East Midlands 1,733

East of England 1,991

West Midlands 2,851

London 4,572

NHS ACTIVITY COMPARISON

Source: SHA MPET investment plans and annual reports; SHA websites; NHS Information Centre Workforce Data, 2010; NHSL

internal data submissions; DH Exposition Book 2011; analysis



nursing workforce1

2010/11, #



weighted population1

2010/11, #

A

100

Current slide 25

Baseline of current position (e.g., remove non-recur.)

Changes with activity shifts and new clinical models

7SOURCE: Summary analysis, 13 April full position.xls

Contract baselines versus agreed SLAs for all 7 in-sector NWL contracts

1 Planned procedures with thresholds, outpatient ratio adjustments, planned procedures not carried out, day case/outpatient procedure ratios

2011/12, £m

19.3

25.9

6.4 5.1

4.9

3.6

6.0

7.0

3.0

6.8

PCT

pro-

vision of

25%

readmis-

sion

funding

Total PCT

cash

envelope

requirement

-0.5

1,265.7

Market

share

change

Coding

and

counting

charges

Service

develop-

ments

Other

changes

NEL

marginal

rate

thres-

hold

Latest

SLA

position

1,255.9

Full-year

effects

Total

financial

cost

2011/12

1,229.3

Other

(typically

local

sch-

emes)

Growth

9.3

Other

contract

levers1

Demand

manage-

ment

2011/12

baseline

prices

and

grouper

1,271.6

Total value of demand

management and 4 main

contract levers are £45m

or 3.5% of 2011/12

baselines, details by acute

contract on the following

page

2010/11

outturn

1,219

Alternative total to consider

PCT total commitments is

SLA plus NEL, ie a total of

£1,258.9m

Overall increase

of 4.3% between

2010/11 outturn

and 11/12

baseline

Demand

management

and QIPP

contract levers

are critical

Growth

is very

low -

<1%

Significant growth in spending for variety of

reasons, many of which are agreed

changes to commissioning (eg

centralisation of stroke and trauma) or

reflect prior commitments or investments

11

The FRG will oversee the development of 5 modelsModel built

Status of …

Input dataDescription of outputs

Agreement with FRGData required

13th Sept

Population growth model

▪ Age-weighted population growth over the next ten years and past three years, shown by age band and by POD

▪ Population projections by 5y age bands (ONS or CCG)

▪ Activity data by POD and 5y age bands (HES 16/17)

1

27th Sept

Financial baseline model

▪ Bridge analysis to project the normalisedposition from 2018 through 2025

▪ Broken down to show the impact of activity changes, price and cost change and CIP

▪ Hospital financial plan (e.g., SLR) for 17/18

2

11th Oct

Activity & capacity baseline model

▪ Multiple small bridge analyses (one for each service line) to show the changes in numbers of patients in the base case

▪ Bed bridge incl. target lengthof stay

▪ Patient level activity data for base year (e.g. PLICs data from SLR 17/18)

3

22nd OctActivity shift / reconfigure-tion model

▪ Show the impact of different clinical models/potential service configuration models on activity, income, variable cost and fixed cost

▪ Patient level activity data for base year (e.g. PLICs data from SLR 17/18)

5

Travel time analysis

411th Oct▪ Public, private and blue light

transport data▪ Impact on travel times and population

flows

12

All assumptions required for the modelling have been agreed

Financial baseline model

Population growth model

2

1

Assumptions required

▪ CIP / service standards

▪ Economic assumptions (price change, inflation)

▪ Application of QIPP to service lines

▪ Fixed cost assumptions

▪ Cost breakdown by service line

▪ Service lines to model

▪ QIPP / demand management

▪ None – assuming no adjustments to population projections and local HES data represents an accurate profile of activity by age group

▪ Non-demographic growth

▪ Length of stay reduction target; bed occupancy targets

Source/ supporting data

▪ Trust

▪ NHSI

▪ FRG

▪ Trust

▪ Trust

▪ CRG

▪ CCG

▪ ONS / Trust

▪ Trust

▪ Trust / FRG

13th Sept

13th Sept

27th Sept

13th Sept

27th Sept

Date agreed

13th Sept

11th Oct

13th Sept

27th Sept


4▪ Impact on travel times and population flows ▪ FRG 11th Oct

11th OctActivity & capacity baseline model

3

Activity shift / reconfiguration model

5

▪ Workforce and variable cost shift assumptions

▪ Fixed cost shift assumptions

▪ Transition cost assumptions

▪ Capital cost assumptions

▪ Activity shifts under potential clinical models

▪ FRG

▪ FRG

▪ FRG

▪ FRG

▪ CRG

22nd Oct

29th Oct

22nd Oct

22nd Oct

22nd Oct

13

The models will require aligned activity, income and expenditure data

PLICs data from the SLR system is the right dataset to work with because:

✓ It’s at the right level of granularity (patient-level)

✓ Data is at the right unit (e.g., attendances for A&E, spells for IP, births for maternity etc.)

✓ The activity, income and expenditure are already aligned and reconciled, which avoids resource intensive reconciliation that results from using financial and activity data from different datasets

✓ This data-set already has a reconciled cost breakdown (fixed, semi-fixed and variable) which we will need to model service configuration options

14

Contents

1. Population growth model

2. Financial baseline model

3. Activity and capacity baseline model

4. Travel time analysis

5. Activity shift model

Appendix – summary of financial impact of base model

15

Revised population growth model

Population growth model1▪ Population growth and impact on activity

growth, incl. non-demographic factors

Model part Description

▪ Baseline income and expenditure projected forward until 2030Financial baseline model2

▪ Impact of shifting services on activity, capacity, income, expenditure, NPV


5

▪ Impact on travel times and population flows Travel time analysis4

▪ Baseline activity and capacity by site by service line

Activity and capacity baseline model

3

16

Scarborough supports a catchment area covering ~180K people, 34 electoral wards and 25 GP surgeries

Source: HES 2016/17

Catchment for Scarborough Hospital1

East Riding of Yorkshire

▪ Bridlington Central and Old Town

▪ Bridlington North

▪ Bridlington South

▪ Driffield and Rural

Ryedale

▪ Cropton

▪ Kirkbymoorside

▪ Pickering East

▪ Pickering West

▪ Rillington

▪ Sherburn

▪ Thornton Dale

▪ Wolds

Scarborough

▪ Castle

▪ Cayton

▪ Central

▪ Derwent Valley

▪ Eastfield

▪ Esk Valley

▪ Falsgrave Park

▪ Filey

▪ Fylingdales

▪ Hertford

▪ Lindhead

▪ Mayfield

▪ Newby

▪ North Bay

▪ Northstead

▪ Ramshill

▪ Scalby, Hackness and Staintondale

▪ Seamer

▪ Stepney

▪ Streonshalh

▪ Weaponness

▪ Whitby West Cliff

▪ Woodlands

Proposed catchment GP Practice Hospital

Electoral wards in Scarborough catchment, by local authority

1 Catchment defined by electoral wards where more than 40% of non-elective inpatients were treated at Scarborough Hospital. All GP surgeries in the catchment also met these criteria -no GP surgeries outside of catchment meet this criteria

10 km

1POPULATION GROWTH MODEL

17

ONS population projection methodology

ONS population projections take into account:

▪ Fertility (births)

▪ Net migration e.g. people moving into and out of the area (the fertility estimate takes into account fertility from new migrants)

▪ Life expectancy (e.g. ONS models how life expectancy is expected to evolve and uses this to predict deaths)

▪ Stated plans from councils for the next few years including agreed new builds


18

Source: ONS 2016-based Sub National Population Projections; catchment are defined as the following wards: Stepney; Central; Weaponness; Eastfield; Woodlands; North Bay; Newby; Filey; Falsgrave; Northstead; Cayton; Scalby; Hackness and Staintondale; Lindhead; Hertford; Castle, Derwent Valley; Ramshill; Bridlington South; BridlingtonNorth; Seamer; Bridlington Central and Old Town; Thornton Dale; Sherburn; Fylingdales; Pickering East; Streonshalh; Whitby West Cliff; Pickering West; Rillington; Mayfield; Wolds; Cropton; Driffield and Rural; Kirkbymoorside; Esk Valley) accessed online in September 2018 [http://www.localhealth.org.uk]

The population across the catchment area is set to increase by ~ 0.2% p.a. by 2025 with higher increases in people aged over 70 years of age

35 36

53 49

53 54

34 39

3

2018

2

2025

70-89

90+

50-69

20-49

<20

181178

+0.2% p.a.

2.0%

0.1%

-1.0%

0.1%

2.2%

2018-25 CAGR, %Population projection by age, area in scope, ‘000

2.4

2.3

0.7

-0.2

0.6

All EnglandScarborough


19

Demographic-related activity growth rates

SOURCE: ONS 2016-based Sub National Population Projections over subsequent years; HES 2015/16; Trust activity data

Percent

2021 2023 2025 2026 2027 2028 20292019 20302020 2022 2024

Demo-graphic growth of activity

Time period of financial projection modelling

ELDC

ELIP

A&E

OP

NEL

Growth of underlying population

-6.4%

10.7%

11.3%

7.4%

8.6%

10.4%

2.2%

Maternity

Total2019-20302018

(0.5%)

1.0%

1.3%

0.1%

0.8%

0.4%

0.0%

(1.0%)

1.3%

1.0%

0.4%

1.0%

0.6%

0.2%

(1.2%)

1.1%

1.2%

0.3%

0.7%

0.4%

0.2%

(0.4%)

1.2%

0.8%

1.0%

1.0%

1.3%

0.4%

(0.6%)

1.1%

1.0%

0.8%

0.9%

1.0%

0.3%

(0.3%)

0.8%

0.8%

0.5%

0.6%

0.7%

0.2%

(0.9%)

0.6%

1.1%

0.6%

0.6%

0.9%

0.1%

(0.0%)

0.9%

0.6%

1.0%

0.9%

1.3%

0.3%

(0.5%)

0.5%

0.8%

0.5%

0.5%

0.8%

0.0%

0.7%

0.8%

0.6%

0.9%

0.8%

1.3%

0.4%

(0.4%)

1.0%

1.1%

0.6%

0.9%

0.8%

0.3%

(1.3%)

1.3%

1.1%

0.6%

0.8%

0.8%

0.1%

(1.6%)

0.8%

1.2%

0.4%

0.5%

0.6%

0.0%


20

Non-demographic-related activity growth ratesA&E

1715 16

+1.7% p.a.

Day case Elective inpatient

15 16 17

-3.2% p.a.

Non-elective inpatient

1615 17

+2.6% p.a.

Maternity

1615 17

+0.1% p.a.

1715 16

+3.5% p.a.

1615 17

+3.3% p.a.

1.1% p.a. 2.4% p.a. -4.2% p.a. 1.6% p.a. -0.3% p.a. 2.3% p.a.

OutpatientTrusts

England

Patients from regional CCGs1

attendingScarborough Hospital

Implied non-demographic growth1

0.6% p.a. 1.1% p.a. 1.1% p.a. 1.0% p.a. 0.4% p.a. 1.0% p.a.Est. Underlying demographic growth

2.6% p.a. 0.5% p.a. -4.3 p.a. 5.7% p.a. -1.1% p.a. 0.4% p.a.Implied non-demographic growth

1.0% p.a. 1.1% p.a. 1.3% p.a. 0.6% p.a. -0.5% p.a. 1.0% p.a.Est. Underlying demographic growth

14 1615 17 18

+3.6% p.a.

171514 16 18

-3.0% p.a.

14 15 16 17 18

+6.4% p.a.

1514 1716 18

-1.6% p.a.

1514 16 17 18

+1.6% p.a.

1614 15 1817

+1.4% p.a.

SOURCE: Hospital Episode Statistics, NHS Digital, Trust activity data

1 NHS Scarborough and Ryedale CCG, NHS East Riding of Yorkshire CCG 2 Activity rate data only until 2015/16

Chosen non-demographic growth2

2.6% p.a. 0.5% p.a. -4.3% p.a. 3.0% p.a. -1.1% p.a. 0.4%pa

Revised down to remove A&E admissions growth which could be distorting overall NEL growth due to changes in coding and counting


21

Contents







22

Revised financial baseline model


growth, incl. non-demographic factors





5




3

2FINANCIAL BASELINE MODEL

23

Baseline has been built with two models for activity growth

model Description

Demand management grounded in historically achieved levels

▪ Assumes historically achieved demand management influences future non-demographic-related activity growth rates (therefore historic levels of demand management are included in the non-demographic projections)

▪ Future demand management bears in mind historically achieved levels and relates to specific initiatives planned / plausibly implemented which are above and beyond historic initiatives

Demand management achieves commissioner balance position

B

▪ Assumes levels of demand management required to keep commissioners in balance

▪ Activity shift model is built using the commissioner balance baseline as the input

A


24

Activity growth projections with historically achieveddemand management levels

1 Baseline to include demand management projections from Scarborough and Ryedale CCG but not East Riding CCG

RTT wait time / activity backlog

▪ Not included as the Trust’s current position is to maintain the waiting list

Demand management: historically achieved levels

Activity change 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

NEL

Demographic 0.6% 0.8% 0.4% 0.8% 1.3% 0.6% 1.0% 0.7% 0.9% 1.3% 0.8% 1.3%

Non-demographic 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0%

Demand management 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

Total activity change 3.6% 3.8% 3.4% 3.8% 4.3% 3.6% 4.0% 3.7% 3.9% 4.3% 3.8% 4.3%

Births

Demographic -1.0% -0.4% -1.2% -1.3% -0.4% -1.6% -0.6% -0.3% -0.9% 0.0% -0.5% 0.7%

Non-demographic -1.1% -1.1% -1.1% -1.1% -1.1% -1.1% -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%


Total activity change -2.2% -1.6% -2.3% -2.4% -1.6% -2.7% -1.8% -1.5% -2.0% -1.2% -1.7% -0.4%

ELDC

Demographic 1.3% 1.0% 1.1% 1.3% 1.2% 0.8% 1.1% 0.8% 0.6% 0.9% 0.5% 0.8%

Non-demographic 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5%



ELIP

Demographic 1.3% 1.0% 1.1% 1.2% 1.1% 0.8% 1.2% 1.0% 0.8% 1.1% 0.6% 0.8%

Non-demographic -4.2% -4.2% -4.2% -4.2% -4.2% -4.2% -4.2% -4.2% -4.2% -4.2% -4.2% -4.2%



A&E

Demographic 0.4% 0.6% 0.3% 0.6% 1.0% 0.4% 0.8% 0.5% 0.6% 1.0% 0.5% 0.9%

Non-demographic 2.6% 2.6% 2.6% 2.6% 2.6% 2.6% 2.6% 2.6% 2.6% 2.6% 2.6% 2.6%

Demand management 0.0% -0.5% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%


OP

Demographic 1.0% 0.9% 0.7% 0.8% 1.0% 0.5% 0.9% 0.6% 0.6% 0.9% 0.5% 0.8%

Non-demographic 0.4% 0.4% 0.4% 0.4% 0.4% 0.4% 0.4% 0.4% 0.4% 0.4% 0.4% 0.4%

Demand management 0.0% -0.5% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%


Activity change projections1

Non-demographic related activity growth is higher than typically seen in other parts of the country but is based on hospital data for activity from patients living in Scarborough & Ryedale CCG and East Riding CCG

2AFINANCIAL BASELINE MODEL

25

Activity growth projections to achieve commissioner balance position

1 Baseline to include demand management projections from Scarborough and Ryedale CCG but not East Riding CCG

Demand management: commissioner’s balance position

Activity change 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

NEL

Demographic 0.6% 0.8% 0.4% 0.8% 1.3% 0.6% 1.0% 0.7% 0.9% 1.3% 0.8% 1.3%

Non-demographic 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0%

Demand management -3.1% -3.3% -2.9% -3.3% -3.8% -3.1% -3.5% -3.2% -3.4% -3.8% -3.3% -3.8%


Births

Demographic -1.0% -0.4% -1.2% -1.3% -0.4% -1.6% -0.6% -0.3% -0.9% 0.0% -0.5% 0.7%

Non-demographic -1.1% -1.1% -1.1% -1.1% -1.1% -1.1% -1.1% -1.1% -1.1% -1.1% -1.1% -1.1%



ELDC

Demographic 1.3% 1.0% 1.1% 1.3% 1.2% 0.8% 1.1% 0.8% 0.6% 0.9% 0.5% 0.8%

Non-demographic 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5%



ELIP

Demographic 1.3% 1.0% 1.1% 1.2% 1.1% 0.8% 1.2% 1.0% 0.8% 1.1% 0.6% 0.8%

Non-demographic -4.2% -4.2% -4.2% -4.2% -4.2% -4.2% -4.2% -4.2% -4.2% -4.2% -4.2% -4.2%



A&E

Demographic 0.4% 0.6% 0.3% 0.6% 1.0% 0.4% 0.8% 0.5% 0.6% 1.0% 0.5% 0.9%

Non-demographic 2.6% 2.6% 2.6% 2.6% 2.6% 2.6% 2.6% 2.6% 2.6% 2.6% 2.6% 2.6%



OP

Demographic 1.0% 0.9% 0.7% 0.8% 1.0% 0.5% 0.9% 0.6% 0.6% 0.9% 0.5% 0.8%

Non-demographic 0.4% 0.4% 0.4% 0.4% 0.4% 0.4% 0.4% 0.4% 0.4% 0.4% 0.4% 0.4%



RTT wait time / activity backlog

▪ Not included as the Trust’s current position is to maintain the waiting list

Activity change projections1

Non-demographic related activity growth is higher than typically seen in other parts of the country but is based on hospital data for activity from patients living in Scarborough & Ryedale CCG and East Riding CCG

2BFINANCIAL BASELINE MODEL

26

Recurrent starting position

"Do nothing" position

Pricechange2

Costinflation2

Activity change1 Change in service standard3

-29.0

12.9

Demand management

Trust CIP initiatives4

Projected surplus /

deficit in 2025

-23.2

2.6

-6.5 -43.2 0

18.1

-25.1

Scarborough’s deficit is projected to increase to ~£25m by 2025 but issensitive to productivity improvements being delivered

External factors on "do nothing" Levers available to the health economy

SOURCE: Scarborough 17/18 SLR data, Financial Baseline Forecasting Model

1 Activity change from demographic, non-demographic and demand management. Assumptions from historical activity, ONS population projections and CCG assumptions, with new activity adding cost using a varying scaling factor

2 Assumption from NHSI economic planning guidance3 Assumed growth of 1% per year on permanent staff costs as per national assumptions 4 Trust CIP is -2% p.a.

Baseline I&E projection for Scarborough Hospital from 2018 to 2025, £m

2025 position – Sensitivity to CIP (£M)

-2.5% -2.0% -1.5% -1.0% -0.5%-3.0% -0.0%

Annual cost improvement

-£17.7m -£23.0m -£28.4m -£34.0m -£39.8m-£12.6m -£45.7m

-£18.6m -£23.7m -£29.0m -£34.5m -£40.1m-£13.6m -£45.9m

-£19.4m -£24.4m -£29.6m -£35.0m -£40.4m-£14.5m -£46.1m

-£20.2m -£25.1m -£30.2m -£35.4m -£40.7m-£15.4m -£46.2m

-£20.9m -£25.7m -£30.7m -£35.7m -£41.0m-£16.3m -£46.3m

-£21.6m -£26.3m -£31.1m -£36.1m -£41.2m-£17.1m -£46.4m

Demand management

1.5% less

1.0% less

0.5% less

“As is”

0.5% more

1.0% more

1.5% more -£22.3m -£26.8m -£31.5m -£36.4m -£41.4m-£17.8m -£46.5m



SCARBOROUGH

27

Demand management

Costinflation2


Activity change1Recurrent starting position

Change in service standard3

17.012.1

Pricechange2

Trust CIP initiatives4

Projected surplus /

deficit in 2025

-2.0

-23.2

2.0

-27.3-6.1 -42.5

-27.5

Scarborough’s deficit is projected to increase to ~£27m by 2025 but issensitive to productivity improvements being delivered

External factors on "do nothing" Levers available to the health economy



2 Assumption from NHSI economic planning guidance3 Assumed growth of 1% per year on permanent staff costs as per national assumptions 4 Trust CIP is -2% p.a.

Baseline I&E projection for Scarborough Hospital from 2018 to 2025, £m

-2.5% -2.0% -1.5% -1.0% -0.5%-3.0% -0.0%

-£21.3m -£26.0m -£30.9m -£35.9m -£57.5m-£16.7m -£46.4m

-£21.9m -£26.6m -£31.3m -£36.2m -£57.3m-£17.5m -£46.4m

-£22.6m -£27.1m -£31.7m -£36.5m -£57.1m-£18.2m -£46.5m

-£23.1m -£27.5m -£32.1m -£36.7m -£56.8m-£18.9m -£46.5m

-£23.7m -£28.0m -£32.4m -£37.0m -£56.6m-£19.5m -£46.5m

-£24.2m -£28.4m -£32.7m -£37.2m -£56.3m-£20.1m -£46.4m

Demand management

1.5% less

1.0% less

0.5% less

“As is”

0.5% more

1.0% more

1.5% more -£24.7m -£28.8m -£33.0m -£37.3m -£56.0m-£20.7m -£46.4m




Annual CIP of 4.9% puts Scarborough and CCGs in balance

SCARBOROUGH2BFINANCIAL BASELINE MODEL

28

Breakdown of key financial metrics for Scarborough hospital

Breakdown of key financial metrics by service line

25.6%

80.0%

52.3%

80.2%

65.4%

77.7%

74.0%

87.7%

84.0%

68.6%

74.6%

69.6%

92.0%

74.6%

62.6%

41.7%

25.4%

24.9%

6.1%

4.2%

13.8%

10.3%9.7%

7.8%

2.7%

33.2%

12.0%

6.0%

16.0%

9.2%

8.5%

17.0%9.0%

6.2%

6.7%9.3%

5.7%

9.1%

9.4%

5.5%

5.4%

16.3%

Fixed Semi-variable Variable

SOURCE: Trust 17/18 SLR data, Financial Baseline Forecasting Model

-4.9

-0.1

-7.4

-2.4

-0.5

-1.8

0.7

-0.6

-0.5

-4.6

-0.1

-1.0

-23.2

0.1

SCARBOROUGH

-6.1

0.3

-7.7

-2.7

-0.8

-1.6

1.3

-0.8

-0.8

-5.3

-0.2

-0.9

-25.1

0

5.7

7.0

1.7

27.6

5.3

3.0

10.6

4.1

3.9

17.0

3.2

0.6

0.8

10.6

7.1

1.6

34.9

7.7

3.6

12.4

3.3

4.4

21.6

3.8

0.8

1.8

8.0

8.9

1.5

40.5

6.7

2.8

15.5

6.0

3.8

20.9

3.7

0.8

0.8

14.0

8.6

1.5

48.2

9.4

3.6

17.1

4.6

4.6

26.2

4.5

1.0

1.7

Outpatients

Day case medicine

Elective medicine

Non elective medicine

Day case surgery

Elective surgery

Non elective surgery

Critical Care

Inpatient paeds

Maternity - births

Other outpatients

Neonatal critical care

Breakdown of cost, % Total costs MarginTotal Income Total costsService

A&E

MarginTotal Income

TOTAL 90.5 113.7 119.9 145.0

2018, m£ 2025, m£



29

Breakdown of key financial metrics for Scarborough hospital

Breakdown of key financial metrics by service lineVariableFixed Semi-variable


SCARBOROUGH

5.7

7.0

1.7

27.6

5.3

3.0

10.6

4.1

3.9

17.0

3.2

0.6

0.8

10.6

7.1

1.6

34.9

7.7

3.6

12.4

3.3

4.4

21.6

3.8

0.8

1.8

6.4

7.9

1.5

32.4

6.0

2.8

12.4

4.8

3.8

19.3

3.7

0.7

0.8

12.2

7.8

1.5

41.2

8.7

3.6

14.6

4.0

4.6

24.8

4.5

0.9

1.7

Outpatients

Day case medicine

Elective medicine


Day case surgery

Elective surgery


Critical Care

Inpatient paeds

Maternity - births

Other outpatients


Breakdown of cost, % Total costs MarginTotal Income Total costsService

A&E

MarginTotal Income

TOTAL 90.5 113.7 102.5 130.1

2018, m£ 2025, m£


25.6%

80.0%

52.3%

80.2%

65.4%

77.7%

74.0%

87.7%

84.0%

68.6%

74.6%

69.6%

92.0%

74.6%

62.6%

41.7%

25.4%

24.9%

2.7%

12.0%

9.2%

10.3%

7.8%

9.7%

4.2%33.2%

8.5%

6.0%

16.3%

13.8%

17.0%9.0%

6.1%6.2%

6.7%9.3%

5.7%

16.0%9.4%

5.5%

5.4%

9.1%

-4.9

-0.1

-7.4

-2.4

-0.5

-1.8

0.7

-0.6

-0.5

-4.6

-0.1

-1.0

-23.2

0.1

-5.7

-8.9

-2.7

-0.8

-2.2

0.8

-0.8

-0.8

-5.5

-0.2

-0.9

-27.5

0.1

0

2BFINANCIAL BASELINE MODEL

30

Additional context on Scarborough financial baseline SCARBOROUGH

Sparsity payments

▪ Included within income

OP margins

▪ The loss is spread across all services apart from Maternity/Obstetrics:

– £0.5m loss on deliveries; False labour/premature rupture of membranes £100k loss; Ante natal observations £274k loss; Ante-natal complex or major disorders £423k loss; Total other loss is £900k

Maternity margins

▪ Reflects activity from births only

▪ Non-birth related maternity (e.g., midwife appointments, antenatal care etc.) is largely within OP


31



Activity change1

Pricechange2

Demand management

Costinflation2

-1.0

Change in service

standards3

-2.1

Trust CIP initiatives

Projected surplus /

deficit in 2025

-2.1

0

-5.3-5.6 0

3.42.8

Bridlington’s deficit is projected to be ~£2m by 2025 but is sensitive to productivity improvements being delivered

External factors on "do nothing"

Levers available to the health economy



2 Assumption from NHSI economic planning guidance 3 Assumed growth of 1% per year on permanent staff costs as per national assumptions 4 Trust CIP is -2% p.a.

Baseline I&E projection for Bridlington Hospital from 2018 to 2025, £m


Demand management -3.0% -2.5% -2.0% -1.5% -1.0% -0.5% -0.0%


£.4m -£.6m -£1.5m -£2.5m -£3.5m -£4.6m -£5.7m1.5% less

£.1m -£.8m -£1.7m -£2.7m -£3.7m -£4.7m -£5.8m1.0% less

-£.1m -£1.0m -£2.0m -£2.9m -£3.9m -£4.9m -£5.9m0.5% less

-£.4m -£1.3m -£2.1m -£3.1m -£4.0m -£5.0m -£6.0m“As is”

-£.6m -£1.5m -£2.3m -£3.2m -£4.2m -£5.1m -£6.1m0.5% more

-£.8m -£1.7m -£2.5m -£3.4m -£4.3m -£5.2m -£6.2m1.0% more

-£1.0m -£1.8m -£2.7m -£3.5m -£4.4m -£5.3m -£6.2m1.5% more


BRIDLINGTON2AFINANCIAL BASELINE MODEL

32

Change in service

standards3


-0.9

Demand management

Activity change1


Pricechange2

Costinflation2

Trust CIP initiatives

Projected surplus /

deficit in 2025

-0.3

-2.1 -2.50

1.9

-4.4

3.2

-5.4

Bridlington’s deficit is projected to be ~£2m by 2025 but is sensitive to productivity improvements being delivered

External factors on "do nothing"



2 Assumption from NHSI economic planning guidance 3 Assumed growth of 1% per year on permanent staff costs as per national assumptions 4 Trust CIP is -2% p.a.

Baseline I&E projection for Bridlington Hospital from 2018 to 2025, £m


Demand management -3.0% -2.5% -2.0% -1.5% -1.0% -0.5% -0.0%


-£.2m -£1.1m -£1.9m -£2.8m -£3.8m -£4.7m -£5.7m1.5% less

-£.4m -£1.3m -£2.1m -£3.0m -£3.9m -£4.9m -£5.8m1.0% less

-£.7m -£1.5m -£2.3m -£3.2m -£4.0m -£5.0m -£5.9m0.5% less

-£.9m -£1.6m -£2.5m -£3.3m -£4.2m -£5.1m -£6.0m“As is”

-£1.1m -£1.8m -£2.6m -£3.4m -£4.3m -£5.2m -£6.0m0.5% more

-£1.2m -£2.0m -£2.8m -£3.6m -£4.4m -£5.2m -£6.1m1.0% more

-£1.4m -£2.2m -£2.9m -£3.7m -£4.5m -£5.3m -£6.2m1.5% more


BRIDLINGTON2BFINANCIAL BASELINE MODEL

33

Breakdown of key financial metrics by service lineFixed Semi-variable Variable


0.9

0.2

1.9

3.5

5.1

9.0

0.7

0.1

3.6

4.5

5.4

8.4

1.2

0.1

2.7

4.5

4.7

11.0

0.8

0.1

5.0

5.4

5.1

10.0

Breakdown of key financial metrics for Bridlington hospital

2018, m£ 2025, m£

Breakdown of cost, % Total costs MarginTotal Income Total costsService MarginTotal Income

Outpatients

Day case medicine

Elective medicine


Day case surgery

Elective surgery


Critical Care

Inpatient paeds

Maternity - births

Other outpatients


A&E

Total 9.0 22.6 24.2 26.420.6


50.4%

78.6%

79.4%

54.8%

48.9%

47.3%

55.4%

32.0%

25.8%

39.5%

44.3%

31.8%

17.6%

19.5%

14.0%

6.6%

6.6%

14.8%

11.6%

8.4%

12.7%

0.3

0.1

-1.8

-1.0

-0.2

0.6

-2.1

0.4

0.1

-2.3

-0.9

-0.4

1.0

-2.1

BRIDLINGTON2AFINANCIAL BASELINE MODEL

34

Breakdown of key financial metrics by service line


0.9

0.2

1.9

3.5

5.1

9.0

0.7

0.1

3.6

4.5

5.4

8.4

1.0

0.1

2.1

3.9

4.5

9.8

0.7

0.1

4.1

4.9

5.0

9.2

Breakdown of key financial metrics for Bridlington hospital

2018, m£ 2025, m£

Breakdown of cost, % Total costs MarginTotal Income Total costsService MarginTotal Income

Outpatients

Day case medicine

Elective medicine


Day case surgery

Elective surgery


Critical Care

Inpatient paeds

Maternity - births

Other outpatients


A&E

Total 9.0 22.6 21.5 23.920.6


50.4%

78.6%

79.4%

54.8%

48.9%

47.3%

55.4%

32.0%

25.8%

39.5%

44.3%

31.8%

17.6%

6.6%

14.8% 6.6%

14.0%

19.5%

11.6%

8.4%

12.7%

0.3

0.1

-1.8

-1.0

-0.2

0.6

-2.1

0.3

0.1

-2.0

-1.0

-0.5

0.7

-2.5

BRIDLINGTON2BFINANCIAL BASELINE MODEL

VariableFixed Semi-variable

35

Additional context on Bridlington financial baseline

▪ The profit at Bridlington was broadly because of the tariff received in 2014/15 for Trauma and Orthopaedics, which resulted in a profit of approximately £2m on T&O, and an overall profit of £1m

▪ In 2017/18, the tariff for T&O and specifically complex joint replacements, has fallen significantly, resulting in an overall loss on the site

Bridlington margins

BRIDLINGTON2FINANCIAL BASELINE MODEL

36

Current Trust level income and expenditure

-23.0

-0.5

0.5

-23.0

Scarborough York Other1 Trust

£M 2017/2018I&E margin

1 Pathology and Radiology Direct Access cost and income are included in the “other” category as they are not site-specific

SOURCE: Trust data


37

Other assumptions for baseline projection

1 Change in Service Standards

SOURCE: Financial Baseline Forecasting Model

CIP All 10.4% 2.0%2.0% 21.9%

Non-staff - lab 10.4% 2.0%2.0% 21.9%

Non staff –patient

15.9% 3.0%3.0% 34.4%

Non staff –buildings etc

10.4% 2.0%2.0% 21.9%

10.4% 2.0%2.0% 21.9%

Non staff -transport

10.4% 2.0%2.0% 21.9%

Non staff –other

10.4% 2.0%2.0% 21.9%

CISS1 Perm. staff 5.1% 1.0%1% 10.5

4.0% 8.7%0.8% 0.8%

Births -4.3% -7.6%-0.9% -0.8%

A&E 2.9% 6.3%0.6% 0.6%

15.9% 34.4%3.0% 3.0%

ELDC 6.0% 10.6%1.2% 1.0%

ELIP 5.9% 11.2%1.1% 1.1%

Births -5.5% -10.8%-1.1% -1.1%

ELIP -19.5% -35.2%-4.2% -4.2%

OP 4.4% 8.2%0.9% 0.8%

ELDC 2.5% 5.0%0.5% 0.5%

NEL

OP 2.0% 4.1%0.4% 0.4%

A&E 13.7% 29.3%2.6% 2.6%

Demo-graphic growth

AllPrice change

4.6% 0.9%0.9% 9.5%

NEL

Non-demo-graphic growth

5Y impact,%

10Y CAGR,%

5Y CAGR,%

10Y impact,% CostsIncome

5Y impact,%

10Y CAGR,%

5Y CAGR,%

10Y impact,%

Non staff

Cost inflation

Non staff -hotel

10.4% 2.0%2.0% 21.9%

Staff costs 20.4% 3.3%3.8% 38.9%

Non staff -imaging

10.4% 2.0%2.0% 21.9%


38

Contents







39



growth, incl non-demographic factors





5




3

3ACTIVITY AND CAPACITY BASELINE MODEL

40SOURCE: Patient level (PLICs) data from SLR system 2017/18

Baseline activity projections by service line SCARBOROUGH

CAGR, %Unit Activity Projection 2018 to 2025Service line Rationale

13.711.1

6.9 8.5

8.47.5

0.3 0.3

24.9 32.3

10.09.0

1.3 1.0

5.5 7.1

0.60.5

3.43.3

18.2 22.6

1.4 1.2

152.9 165.7

9.28.5

0.20.2

-3.1%

1.6%

3.8%

3.8%

0.3%

3.1%

1.6%

3.8%

-3.1%

-2.1%

1.2%

1.2%

-2.1%

Decrease in non-demographic growth trend

Rises in line with non-elective trend

Assumed growth in-line with average of EL and NELs demo and non-demo trend

Driven by demo trend (elderly population)

Increase in non-demographic growth trend


Driven primarily by non-demo trend

Driven by demo and non-demo trends

Modest non-demo trend

Driven by non-demo trends

Assumed to decrease in line with births


251.5 279.4 1.5%

Attendances, KA&E Standard

Attendances, KA&E Minor

FCEs, KDay case medicine

FCEs, KElective medicine

FCEs, KNon elective medicine

FCEs, KDay case surgery

FCEs, KElective surgery

FCEs, KNon elective surgery

FCEs, KCritical Care

FCEs, KInpatient paeds

Births, KMaternity - births

Attendances, KOutpatients

Attendances, KOther outpatients

FCEs, KNeonatal critical care

Total

Attendances, KA&E Major


A&E primarily driven by non-demo trend and increases in elderly population

3AACTIVITY AND CAPACITY BASELINE MODEL


Baseline activity projections by service line SCARBOROUGH


11.1 11.1

6.9 6.9

7.5 7.5

0.3 0.3

24.9 25.8

9.0 9.0

1.3 1.0

5.5 5.7

0.50.5

3.43.3

18.2 18.2

1.4 1.2

152.9152.9

8.5 8.5

0.2 0.2

-3.1%

0.0%

0.5%

0.5%

0.3%

0.0%

0.0%

0.5%

-3.1%

-2.1%

0.0%

0.0%

-2.1%

A&E primarily driven by non-demo trend and increases in elderly population – offset by demand management


Rises in line with non-elective trend

Assumed growth in-line with average of EL and NELs demo and non-demo trend

Held steady by demand management

Increase in non-demographic growth trend, offset

by demand management

Held steady by demand management


Driven by demo and non-demo trends

Modest non-demo trend, held steady by demand management

Driven by non-demo trends, held steady by

demand management

Assumed to decrease in line with births

Increase in non-demographic growth trend, offset by demand management

251.5 252.1 0.0%















Total



3BACTIVITY AND CAPACITY BASELINE MODEL

42

Target ALOS reduction is 15% which would take Scarborough to mediancasemix adjusted ALOS; top quartile would require a 21% reduction

40 21 73 5 6 8 9 10

Ø 5.3

-12%

-15%

-24.4%

-21.0%

Median – 5.2 days (12% reduction)

Top quartile – 4.7 days (21% reduction)

Top decile – 4.5 days (24% reduction)

Scarborough – 5.9 days2

1 For acute trusts only 2 Case mix adjusted to Scarborough’s activity mix

SOURCE: HES 2016/17 IP 2017/17 APC dataset M13, c/o NHS Digital

Case-mix adjusted non-elective1 average length of stay, for Scarborough General Hospital, against all non-specialist acute Trusts in England, 2016/17, Days

▪ Case-mix adjustment separates Trust performance from the complexity of the case-mix

▪ The ALoS for all other Trusts is calculated in the model in which all other Trusts had the same case-mix of HRGs as Scarborough hospital (HRG provides more consistency across trusts than specialty)

▪ Excludes daycases but includes zero bed days for NEL and ELIP

▪ ITU days included to be comparable across trusts

▪ Scarborough would need a ~12% reduction in ALOS to achieve current median for peer set

▪ Target ALOS reduction for 2025 is -15%

5.0 days (15% reduction)


SCARBOROUGH

43

Segmentation of bed days

1 Excluding RA (regular attenders) and Other (not recorded type), Paediatrics patients are defined by age 0 – 18 years old; 2 Figures calculated assuming that all patients in this category currently stay for 31 days, will go down to trust average LOS for NEL patients, and each reduction of a 20 bed unit saves a hospital £2 million

SOURCE: HES 2016/17

Non-elective aged 65+

9%

4%

32%

Other non-elective

2%

2%

8%

1

0

1%

6%

PaedsElective

2%17%

Maternity

18%

31 10 3 1

100%= (in ‘000s)

= 46,000bed days

Patients with LOS of 0-7 days and days 0-7 of patients with LOS >7 days

8-30 days 31+ days

2016/17 bed days by LOS band and POD1

Total bed days and % of POD

65% of bed days at Scarborough hospital are occupied by stranded patients with length of stay 8 days or longer (majority aged over 65)


44SOURCE: Trust 17/18 SLR activity data, Trust Operational Performance data

Capacity baseline

SpecialtyBed numbers required at Scarborough hospital to support 17/18 activity1, beds2

1 Bed requirement to support 17/18 activity levels calculated from FCE activity and length of stay data and may differ from Trust’s bed allocation to specialties

2 Includes overnight inpatient beds only – this excludes ED, OP, community, and mental health beds. Also excludes critical care and neonatal critical care

3 Includes elective and non-elective medicine but excludes day case medicine4 includes elective and non-elective surgery but excludes day case surgery5 Excludes SCBU6 Captures activity from births only – excludes antenatal pathways etc.7 Based on occupancy rate of 88%, which includes beds that are unoccupied due to intentional

bed closure



55

11

9

39

Medicine3

Surgery4

Paeds5

Maternity - births6

Unoccupied7

Total

214

328

SCARBOROUGH

3A/BACTIVITY AND CAPACITY BASELINE MODEL

45

Capacity projection

289

328 340

429 429

365

39

89 64

2025 number of beds

2018 occupied of beds

Un-occupied beds2

Move to target utilisation

Activity increase by 2025

2018 total beds

2025 number of beds

12

2018 number of beds

0

Change in activity due to demand mgmt. initiatives

Average length of stay reduction

2025 required number of beds

+37

Projected change in inpatient activity by 2025 and impact on Scarborough hospital’s bed requirement, beds1

1. Beds include only overnight inpatient beds. This excludes all daycase beds, ED beds, critical care beds, SCBU, community and mental health beds

2. Target utilisation 85% for all service lines – currently running at 88% utilisation overall3

3. Assume change in activity due to demographic and non-demographic factors as per “do nothing” baseline4. Assumes demand management5. Assumes 15% inpatient average length of stay reduction

Assumptions

SOURCE: Trust 17/18 SLR activity data, Trust Operational Performance data


2 Based on 82% occupancy rate3 This includes beds at are unoccupied due to intentional bed closure


SCARBOROUGH3AACTIVITY AND CAPACITY BASELINE MODEL

46

Capacity projection

289

328 340

420

346

29439

80 74

52

Move to target utilisation

2025 number of beds

2018 occupied of beds

Un-occupied beds2

Activity increase by 2025

2018 number of beds

12

2018 total beds

2025 number of beds

Change in activity due to demand mgmt. initiatives

Average length of stay reduction

2025 required number of beds

-34

1. Beds include only overnight inpatient beds. This excludes all daycase beds, ED beds, critical care beds, SCBU, community and mental health beds

2. Target utilisation 85% for all service lines – currently running at 88% utilisation overall3

3. Assume change in activity due to demographic and non-demographic factors as per “do nothing” baseline4. Assumes demand management5. Assumes 15% inpatient average length of stay reduction

Assumptions

SOURCE: Trust 17/18 SLR activity data, Trust Operational Performance data


2 Based on 82% occupancy rate3 This includes beds at are unoccupied due to intentional bed closure


Projected change in inpatient activity by 2025 and impact on Scarborough hospital’s bed requirement, beds1

SCARBOROUGH3BACTIVITY AND CAPACITY BASELINE MODEL


Baseline activity projections by service line BRIDLINGTON

-3.1%

1.8%

3.8%

1.6%

3.8%

-3.1%

1.2%















N/A


N/A

N/A





N/A

Modest non-demo trend

N/A

N/A


1.7 1.9

0.0 0.0

0.9 1.2

3.22.8

1.1 0.9

0 0

45.942.3

Total 53.048.9 1.2%




3AACTIVITY AND CAPACITY BASELINE MODEL


Baseline activity projections by service line BRIDLINGTON

-3.1%

0.0%

0.5%

0.0%

0.5%

-3.1%

0.0%















N/A


N/A

N/A

Driven by demo trend (elderly population), offset by demand management

Driven primarily by non-demo trend, offset by demand management

Driven by demo trend (elderly population), held steady by demand management


N/A

Modest non-demo trend, held steady by demand management

N/A

N/A

Increase in non-demographic growth trend, offset by demand management

1.7 1.7

0.0 0.0

0.9 0.9

2.8 2.8

1.1 0.9

0 0

42.3 42.3

Total 48.9 48.7 -0.1%




3BACTIVITY AND CAPACITY BASELINE MODEL

49

Contents





– Scarborough drive times

– Scarborough public transport travel times

– York drive times



50








5




3

4TRAVEL TIME ANALYSIS

51

Contents










52

▪ Travel times analysis is used to answer 2 primary questions against each model

▪ What is the impact on patient access? informs evaluation of “access to care”

▪ What is the impact of service change on patient flows? informs financial modelling

1Application

Methodology

▪ Geospatial data (from TomTom) used to measure travel times from each postcode in Scarborough’s catchment area to each nearby acute hospital (York, James Cook, Hull)

▪ Three different travel times measured (peak, off-peak, night)

▪ Night is proxy for blue-light / ambulance

2

Approach to travel time analysis (drive times)4TRAVEL TIME ANALYSIS

53

Share of population1 by closest alternative site – peak time journeys

Source: ONS 2016-based population data, ONS 2011 lower super output areas mapping to 2017 wards, Tom Tom 2017

James Cook

Hull

York

58%=102K

30%= 54K

12%=21K

1 2016 population size; based on catchment wards mapped to lower super output areas

100%=177K1

Scarborough: York is the closest alternative hospital for 58% of the catchment area population


54

Travel time for Scarborough catchment area for a service delivered at Scarborough hospital

Travel time for Scarborough catchment area to the nearest site for a service provided at an alternative site

Cumulative share of population1 by drivetime, by option

SOURCE: ONS 2016-based population data, ONS 2011 lower super output areas mapping to 2017 wards, Tom Tom 2017


Peak time

Share of population in catchment area, cumulative, %

Off-peak time

Drive time, minutes Drive time, minutes


Travel times for the Scarborough hospital catchment area4TRAVEL TIME ANALYSIS

55SOURCE: ONS 2016-based population data, ONS 2011 lower super output areas

mapping to 2017 wards, Tom Tom 2017

Scarborough hospital

Minimum drive time to the nearest acute hospital – average of peak, off-peak, and night-time journeys1

Minimum drive time if service is at Scarborough hospital Minimum drive time to the nearest site for a service provided at an alternative site

Average of peak, off-peak and nightAverage: 22 mins

Average of peak, off-peak and nightAverage: 53 mins

1 note that night journeys are also a proxy measure for "blue light" ambulance journeys

Average travel time to an acute hospital4TRAVEL TIME ANALYSIS



PeakAverage: 26 mins


Minimum drive time to the nearest acute hospital – average of peak-time journeys


Average travel time during peak-time journeys Scarborough hospital4TRAVEL TIME ANALYSIS



Minimum drive time to the nearest acute hospital – average of off-peak journeys

Off-peakAverage: 22 mins



Average travel time during off-peak journeys Scarborough hospital4TRAVEL TIME ANALYSIS

58Source: ONS 2016-based population data, ONS 2011 lower super output areas



Average travel time during night-time journeys

Minimum drive time to the nearest acute hospital – average of night-time journeys1

Night-timeAverage: 19 mins



Scarborough hospital4TRAVEL TIME ANALYSIS

59

Contents










60

Approach to travel time analysis (public transport)

▪ Geospatial data (from HERE) used to measure public transport travel times from each postcode in Scarborough’s catchment area to each nearby acute hospital (York, James Cook, Hull)

▪ Two different travel times measured (peak and off-peak), adjusting specific hours to be in line with actual average travel times

▪ Public transport travel times include overall time from a relevant postcode to a hospital, including walking, to account for the overall travel time it would take to reach a hospital

61

Travel times for the Scarborough hospital catchment area

Travel time for Scarborough catchment area for a service delivered at Scarborough hospital

Travel time for Scarborough catchment area to the nearest hospital for a service at the closest alternative site

Cumulative share of population1 by public transport travel time, by option

SOURCE: ONS 2016-based population data, ONS 2011 lower super output areas mapping to 2017 wards


Peak time


Off-peak time




62

Average public transport travel time to an acute hospital



Minimum travel time to the nearest acute hospital – average of peak and off-peak

Minimum travel time if service is at Scarborough hospital

Minimum travel time to the nearest site for a service provided at an alternative site

Average of peak and off-peakAverage: 194 mins

Average of peak and off-peakAverage: 134 mins


63

Average public transport travel time during peak-time journeys




Minimum travel time to the nearest acute hospital – average of peak-time journeys




64

Average public transport travel time during off-peak journeys


Minimum travel time to the nearest acute hospital – average of off-peak journeys






65

Contents










66

Approach to York travel time analyses

Application

Methodology

▪ Steering Group has recommended to conduct travel time analysis for York to see whether any potential service reconfiguration would result in increase in demand for services in Scarborough purely coming from travel times

▪ The analyses in the following pages shows that for York catchment area, which is defined as electoral wards with the shortest travel times, closest alternative hospital is Harrogate District Hospital (50%)

▪ Scarborough would be the closest hospital for 6% of York catchment population

▪ Geospatial data (from TomTom) used to measure travel times from each postcode in Scarborough’s catchment area to each nearby acute hospital (York, James Cook, Hull)

▪ Three different travel times measured (peak, off-peak, night)

▪ Night is proxy for blue-light / ambulance


67

York: Harrogate is the closest alternative hospital for 50% of the catchment area population

SOURCE: ONS 2016-based population data, ONS 2011 lower super output areas mapping to 2017 wards, HERE 2018


Share of population1 by nearest acute hospital other than York (closest alternative) –peak time journeys

FriarageHospital

Hull Hospital

St James’s Hospital

24%=78K 6%=

18K

5%=16K

100%=319K1

50%=160K

Harrogate District hospital

Pinderfields Hospital

7%=23K

Doncaster Royal Infirmary

1%= 4K

6%=19K



68

Travel times for the York hospital catchment area

Travel time for York catchment area for a service delivered at York hospital

Travel time for York catchment area to the nearest hospital for a service at the closest alternative site

Cumulative share of population1 by drivetime, by option



Peak time


Off-peak time




69

Average York travel time to an acute hospital


York hospital

Minimum drive time to the nearest acute hospital – average of peak, off-peak, and night-time journeys1

Minimum drive time if service is at York hospital Minimum drive time to the nearest site for a service provided at an alternative site

Average of peak, off-peak, and nightAverage: 35 mins


Average of peak, off-peak, and nightAverage: 16 mins


70

Average York travel time during peak-time journeys




Minimum drive time to the nearest acute hospital – average of peak-time journeys


York hospital4TRAVEL TIME ANALYSIS

71

Average York travel time during off-peak journeys


Minimum drive time to the nearest acute hospital – average of off-peak journeys





72

Average York travel time during night-time journeys



Minimum drive time to the nearest acute hospital – average of night-time journeys1





73

Contents






– Approach to clinical models

– Activity shift assumptions

– Approach to shift model

– Summary financial evaluation

– I&E impact

– Capital costs

– Transition costs

– Systemwide NPV impact

– Sensitivity analyses

– Next steps


74

Activity shift model







5




3

5ACTIVITY SHIFT MODEL

75

Contents










– I&E impact

– Capital costs




– Next steps


76

Conceptual approach: filtering process narrowed down from a long list of potential models to a shorter list plus the status quo

Conceptual approach to clinical model development

Consider interdependencies to develop specialty combinations

Narrow clinical models based on high level criteria and keeping meaningfully different models only

Describe clinical models shortlist for full quality of care assessment

Long list of all combination of service line models for key service areas

Modelsviable from a clinical interdependency perspective

Models to be modelled

1 2 3 4

Identify possible range of service line models for key service areas:

▪ A&E

▪ Acute medicine

▪ Emergency surgery

▪ Critical care

▪ Elective surgery

▪ Maternity

▪ Paediatrics


77

Standardised care pathways

Common approaches (integration) across whole system

Easy access to senior decision makers – on site or remotely

Remote access to specialist opinion

Mental health crisis teams available, ideally in ED/UTC

Stabilisation and rapid transfer for patients needing escalation

Transfer back from specialist centres to local units

Greater use of hot clinics

Incentivisation of recruitment & retention by developing a USP

Enhanced use of IT/technology (e.g. telemedicine, virtual clinics)

Easy step-down or transfer to community / social settings

Common enablers to all models5ACTIVITY SHIFT MODEL

78

A range of clinical models exist for each service

Service Range of models explored

Frailty Frailty unit/hub included in all configurations

Emergency surgery

OOH gen. surgery registrar (with cons support from York)

Surgery hot clinics (SAU + recovery beds)

24/7 emergency general surgery

Ambulatory emergency surgery only

Critical care L2 critical care+/- eICU No enhanced careL3 critical care +/- eICUL1 care plus critical care service

Elective surgeryModerate perioperative risk elective surgery

Day cases only High perioperative risk elective surgery

Low perioperative risk elective surgery

PaediatricsPaediatric assessment unit (all walk-ins & referrals) UTC onlyInpatient

MDT led care at Front door (no paediatrician)

MaternityLower risk obstetric service with limited neonates (L1)

On-call midwife-led unit

High risk obstetric service24/7 on-site midwife-led unit

Acute medicine Selective acute take with AAU Step up/Step down beds24/7acute medical take with AAU

Ambulatory Assessment unit (AAU) only – no beds

A&EFront door assessment model A&E UTC only24/7 A&E

“Medical only” A&E + UTC

Service models can be combined to form thousands of combinations of whole-hospital clinical models

5

79

Eight potential models

1 Includes imaging modalities which do not require direct radiology supervision (e.g. can be interpreted by the referring clinician or reported remotely). Does not assume provision of interventional radiology procedures

Model 3C Model 11D Model 15DModel 4A Model 4CModel 1A Model 1C Model 17D

Paediatrics

Paeds assessment unit



Inpatient paediatrics


Inpatient paediatrics



Maternity

Lower risk consultant led obstetrics

Midwife led unit

Midwife led unit

High risk obstetrics


High risk obstetrics


Midwife led unit

Critical care

Level 3 Level 2 Level 1 plus critical care service

Level 3 Level 3 Level 3 Level 3 Level 1 plus critical care service

A&E

Front door assessment model

Medical only A&E

Medical only A&E



24/7 A&E 24/7 A&E UTC only

Emergency surgery

24x7 emergency general surgery

OOH reg on site (cons support at York)







Acute medicine

Full medical take + AAU

Selective medical take + AAU







Elective surgery

Cases with high peri-operative risk


Cases with moderate perioperative risk





Cases with moderate perioperative risk

▪ Frailty unit / hub included in all configurations▪ Assumes diagnostic imaging1 and pathology services exist in all models


80

Contents










– I&E impact

– Capital costs




– Next steps


81

Approach to activity shift assumptions

▪ Clinically-led judgement

▪ Based on 15+ interviews with CDs and lead clinicians for key service lines impacted across Scarborough and York

▪ Generally good alignment in perspectives between clinicians within service lines

▪ Assumptions selectively supported / informed by activity data e.g., proportion of “low risk” obstetrics patients

▪ Forms basis for more detailed bottom-up / prospective analysis of activity shifts in a later phase of work

Application

Methodology

▪ Clinical activity requires bed capacity and brings income and expenditure with it

▪ Shifts in clinical activity are used to model shifts in bed capacity, income and expenditure between hospitals


82

Clinical activity shift assumptions by modelX % of current activity in Scarborough which stays in Scarborough

SOURCE: Interviews with Clinical Directors and lead clinicians

1 OP likely to increase due to increased referrals to fracture clinic in UTC model

Model 15DModel 3C Model 11D Model 17DModel 4A Model 4CModel 1A Model 1C

100 95 95 100 95 70 240

100 100 100 100 100 100 100100

100 97 97 100 95 65 140

100 100 100 100 100 100 100100

100 100 100 100 100 92.5 4545

100 100 100 100 100 100 100100

100 100 100 100 100 100 100100

100 100 100 100 100 100 100100

100 95 95 90 85 40 3030

100 100 100 100 100 100 6565

100 100 100 100 100 100 10095

100 100 100 100 100 100 100100

100 95 95 100 100 40 3030

100 100 100 100 100 100 9595

100 100 100 100 100 100 13011301

100 100 100 90 90 20 020

100 100 100 100 100 100 100100

100 40 40 100 40 25 2525

100 100 100 100 100 75 3030

100 100 100 100 100 100 100100

100 100 100 75 75 50 5050

100 95 95 100 95 95 9595

100 100 100 100 100 100 100100

100 60 60 90 60 60 00

Crit. care

Paedia-

trics

Obs and

Gynae

A&E

Emerg-

ency gen.

surgery

Acute

medicine

Trauma &

ortho-

paedics

Majors

Minors

Resus

Daycase

Non-elective

Elective

Outpatient

Daycase

Non-elective

Elective

Outpatient

Daycase

Non-elective

Elective

Outpatient

Outpatient

Births

Elective gynae

Day case gynae

Nonelective gynae

Antenatal care

Outpatient gynae

Inpatient

Neonates 100 25 25 100 25 0 00


83

Model 15DModel 3C Model 11D Model 17DModel 4A Model 4CModel 1A Model 1C

100% 100% 100% 100% 100% 100% 100% 100%

100% 95% 95% 100% 95% 70% 40% 2%

100% 97% 97% 100% 95% 65% 40% 1%

100% 100% 100% 100% 100% 100% 80% 80%

100% 100% 100% 100% 100% 100% 80% 80%

100% 100% 100% 100% 100% 93% 45% 45%

100% 100% 100% 100% 100% 99% 98% 98%

100% 100% 100% 100% 100% 95% 71% 71%

100% 96% 96% 91% 89% 49% 40% 40%

100% 100% 100% 90% 90% 20% 20% 0%

100% 60% 60% 100% 60% 60% 0% 0%

100% 40% 40% 100% 40% 25% 25% 25%

100% 100% 100% 100% 100% 100% 102% 102%

100% 100% 100% 100% 100% 100% 100% 100%

100% 25% 25% 100% 25% 0% 0% 0%

1 Clinical service line activity shift assumptions are translated to financial service lines by weighting contributing clinical service line activity shift assumptions by proportion of activity contributed to each service line within financial model

2 Increased activity related to likely increase in fracture clinic referrals in UTC only model

A&E Standard

Day case medicine

Elective medicine


Day case surgery

Elective surgery


A&E Major

A&E Minor

Critical Care

Inpatient paeds

Maternity - births

Outpatients

Other outpatients


Financial model service line1

SOURCE: Clinical activity shift assumptions derived from interviews with clinical directors and lead clinicians; Activity data from Performance and Information team at York Teaching Hospital NHS Foundation Trust

Activity shifts have been mapped to financial model service lines 5ACTIVITY SHIFT MODEL

84

Projected activity numbers in 2025 by clinical model (1/2)5ACTIVITY SHIFT MODEL

Model 1A Model 1C Model 3C Model 4A

011.1 11.1

18.218.2 0

6.9 0 6.9

7.507.5

00.3 0.3

025.8 25.8

9.0 0 9.0

01.0 1.0

05.7 5.7

0.500.5

3.4 0 3.4

01.2 1.2

0152.9 152.9

08.5 8.5

00.2 0.2

0.310.8 11.1

18.20.917.3

06.9 6.9

07.5 7.5

0.3 0 0.3

025.8 25.8

9.009.0

01.0 1.0

0.25.5 5.7

0 0.50.5

1.32.0 3.4

0.7 1.20.5

0152.9 152.9

8.508.5

0.1 0.20

11.10.310.8

0.917.3 18.2

6.906.9

7.5 0 7.5

0 0.30.3

025.8 25.8

09.0 9.0

01.0 1.0

0.25.5 5.7

0.5 0 0.5

1.32.0 3.4

0.70.5 1.2

0152.9 152.9

08.5 8.5

0 0.1 0.2

011.1 11.1

018.2 18.2

6.90 6.9

7.5 0 7.5

00.3 0.3

25.81.324.5

09.0 9.0

01.0 1.0

0.35.3 5.7

0.50.10.5

3.40.23.2

1.201.2

0 152.9152.9

08.5 8.5

0.2 0 0.2

Unit

Attendances, K

Attendances, K

FCEs, K

FCEs, K

FCEs, K

FCEs, K

FCEs, K

FCEs, K

FCEs, K

FCEs, K

Births, K

Attendances, K

Attendances, K

FCEs, K


A&E Standard

A&E Minor

Day case medicine

Elective medicine


Day case surgery

Elective surgery


Critical Care

Inpatient paeds

Maternity - births

Outpatients

Other outpatients


Service line

Retained at Scarborough

Delivered at alternative site

In thousands

85

Projected activity numbers in 2025 by clinical model (2/2)5ACTIVITY SHIFT MODEL

Model 4C Model 11D Model 15D Model 17D

0.610.5 11.1

Retained at Scarborough

Delivered at alternative site

0.9 18.217.3

06.9 6.9

07.5 7.5

0.300.3

1.324.5 25.8

09.0 9.0

01.0 1.0

0.65.1 5.7

0.10.5 0.5

3.42.0 1.3

0.70.5 1.2

0 152.9152.9

08.5 8.5

0.0 0.2

11.13.97.2

5.512.8 18.2

0 6.96.9

7.507.5

0.3 0 0.3

23.2 2.6 25.8

8.9 9.00.1

1.0 0.1 1.0

5.73.02.7

0.20.4 0.5

2.0 1.3 3.4

0.9 1.20.3

152.9 0 152.9

8.58.5 0

0.2 0.20

6.74.4 11.1

10.97.3 18.2

06.9 6.9

0.76.7 7.5

0 0.30.2

14.211.6 25.8

9.00.18.9

0.30.8 1.0

3.4 5.72.3

0.50.1 0.5

1.32.0 3.4

1.20.90.3

-3.1 156.0 152.9

8.508.5

0.20 0.2

11.0 11.10.1

17.90.4 18.2

06.9 6.9

6.7 0.7 7.5

0 0.30.2

25.814.211.6

0.18.9 9.0

0.30.8 1.0

3.42.3 5.7

0.1 0.5 0.5

1.32.0 3.4

0.3 0.9 1.2

156.0-3.1 152.9

08.5 8.5

0.20 0.2

A&E Major

A&E Standard

A&E Minor

Day case medicine

Elective medicine


Day case surgery

Elective surgery


Critical Care

Inpatient paeds

Maternity - births

Outpatients

Other outpatients


Service line Unit

Attendances, K

Attendances, K

FCEs, K

FCEs, K

FCEs, K

FCEs, K

FCEs, K

FCEs, K

FCEs, K

FCEs, K

Births, K

Attendances, K

Attendances, K

FCEs, K

Attendances, K

In thousands

86

Contents










– I&E impact

– Capital costs




– Next steps


87

We model income, activity and beds movements across the system using two semi-fixed cost scaling assumptions

1 Changes in capacity drive changes in fixed costs 2 Changes in income drive movements of costs 3 Informed by Trust analysis

4 Based on average maintenance backlog 2016-2018 5 Assumed that CIP related efficiencies do not overlap with ALOS reduction 6 Based on costs per bed for Lilac ward

Change in semi-variable cost

Change in fixed cost

Net present value

Income & expenditure

Capital cost

Transition cost

Change in income from baseline2

Change in cost from baseline

Change in capacity1

Unit capacity cost

Asset sales

Double running cost

Change in variable cost

Potential capex avoidance

Project mgmt. cost

Time value

Assumption

Cost transferred (%)

Cost stranded at divesting site when activity reduced (%)

Scaling factor where capacity reducing (%)

Scaling factor on capex where capacity increasing (%)

Cost per one bed moved per day (£)

Net land receipts per site (£)

Scaling factor applied to bed cost (%)

Cost per bed below threshold (£)

Backlog maintenance cost per site (£)

PMO cost (£)

ALOS reduction target (%)

Discount rate (%)

Duration (# days)

Occupancy target (%)

Baseline capacity (# beds)

Min number of beds for fixed cost change

Cost above threshold (£)

Bed threshold

Cost transferred (%)

Value

Depends on service line

30% or 52% of semi-variable cost depending on A and B

75%

10% of CapEx

£250

1,950,000

75%

£204,0006

1,260,0004

£100K

15%5

3.5%

90 days

85%

322

30

£408,000

60

70% of semi-variable cost3 (which varies by service line)

Sensitivity analysis applied to this assumption


88

Variable and semi-variable costs move to different extents with activity, while fixed cost scales with capacity changes

1 Includes 3.5% PDC (public dividend capital), 4% operating costs, and 2.5% depreciation (assuming 40 year average life span of fixed asset)

SourceAssumption/description

Variable cost▪ Scale in proportion with income (i.e. 10% increase in income leads

to a 10% increase in variable costs)▪ Modelling

assumption

Semi-fixed cost

▪ Where service lines at sites are reduced/increased, but not removed, scaling factor implies proportional change in income

– 70% scaling factor implies that a 10% decrease in income reduces overall semi-fixed costs by 10%*70%=7.0%

– This models the effect of stranded cost retention

▪ Modelling assumption

Fixed cost

▪ For sites with increasing capacity, fixed cost impact estimated at 10% of capex1

▪ For sites with decreasing capacity, fixed cost is reduced in line with beds with 75% scaling factor

▪ Modelling assumption


89

The following has been agreed for capital and capacity

Assumption/description

Potential capital expenditure avoidance

▪ When capacity is reduced at a site the amount of annual maintenance backlog is reduced in proportion with bed reduction

Net capital receipts

▪ When beds/capacity are reduced by more than 60 beds at a site, then some land can be sold for a return

▪ This is calculated as 75% of the reduction in land value in proportion with bed reduction

– 75% net land receipts scaling factor

Capital cost of new capacity

▪ Capital cost is calculated on a per-bed basis using assumptions agreed

▪ When beds are over 60, we apply a step function and apply a higher cost per bed (£408k)

▪ If we add fewer than 60 beds, we apply a smaller cost per bed (£204k)


90

The following step function approach is used to calculate fixed costs

SOURCE: Currie & Brown review of Capital Expenditure Costs, Department of Health In-patient care Health building note, NHS England data,

1 Based on costs per bed for Lilac ward

Assumptions

Output

Removed fixed costs, £

Added fixed costs, £

Scaling factor, %

10%

Capital cost for extra beds, £

Removed standard overnight beds, #beds

Cost estimate per standard overnight bed, £

£204K1 for all beds under 60

Average fixed cost per bed, £

If we remove over 30 beds

Added standard overnight beds, #beds

Method for calculating removed fixed cost

Method for calculating added fixed costs and capital costs

Scaling factor, %

75%

£408k for all beds over 60


91

We estimate net capital receipts in line with overnight bed reductions using estimated present land values

Net land receipts, £

Net land receipt scaling factor, %

Estimated net land present value, £

Beds remaining in Scarborough1, %

75%

1,950,000

Only if over 60 beds removed

Method for calculating net land receipts

1 Change in beds (%) includes change in beds due to activity shift, demand management, ALOS and target occupancy rate


92

Beds remaining in Scarborough1, %

Capital cost for extra beds , £

Cost estimate per standard overnight bed, £

£204K for all beds under 60

Beds added2, #beds

£408k for all beds over 60

Maintenance backlog, £

Current maintenance backlog, £

Net land receipts, £

Additionally, we estimate system capital costs using capital costs, maintenance backlog and net land receipts Assumptions

Output

=System capital costs, £

Method for calculating system capital costs

1 Applies only to beds removed due to activity shift. If there are 60 beds removed out of 300 due to activity shift, remaining bed percentage is 80%

2 Includes beds added to Scarborough and other sites

£1,260,000

If more than 30 beds are removed


93

FRG has agreed to run the following sensitivity analyses Sensitivities being modelled

FRG decided to run sensitivities to see the impact of:

B. CCG only achieving historical levels of demand management

C. Semi-fixed cost factor being 48% (to reflect internal work done to identify proportion of semi-fixed costs which may actually move)

D. ALOS reduction allowing Scarborough to reach current top quartile of average length of stay

E. Assuming synergies in semi-fixed cost transfer – assume only 80% of shifted semi-fixed cost would transfer to receiving site1

F. Cost of adding new beds being £100k for under 60 beds and £200k for over 60 beds

F

1 56% consolidation factor means that out of 70% of transferred semi-fixed cost 80% gets consolidated (70%*80%=56%)

Modelled alternative “Base case”

B C D E

15%15% 15% 15% 21% 15%2025 target ALOS reduction

Required to keep Commissioners in balance

Demand management levels assumed


Based on levels historically achieved




70% removal factor70% consolidation factor





Semi-fixed costs transferred with activity

70% removal factor56% consolidation factor1

Bed costs

£100k – under 60 beds£200k – over 60 beds







94

Contents










– I&E impact

– Capital costs




– Next steps


95

The following criteria was used to evaluate models

Defined asEvaluation criteria

1.1 Clinical effectiveness

1.2 Patient and carer experience

1.3 Safety

2.1 Impact on patient choice

2.2 Distance, cost and time to access services

2.3 Service operating hours

2.4 Ability for clinicians to access specialist input

3.1 Scale of impact

3.2 Impact on recruitment, retention, skills

3.3 Sustainability

4.1 Forecast income and expenditure at system and organisation level

4.2 Capital cost to the system

4.3 Transition costs required

4.4 Net present value (30 years)

Quality of Care

Access to care

Workforce

Value for money

Deliverability

5.1 Expected time to deliver

5.2 Co-dependencies with other strategies/strategic fit

1

2

3

4

5

Detailed on the following page


96

Finance/value for money sub-criteria

Costs & income

▪ What are the implications on income and expenditure for each acute hospital within the system?

▪ Will this model reduce the requirement for additional subsidy for Scarborough?



Capital cost to the system




Net present value

▪ What are the transition costs (e.g., relocating staff, training and education costs)?Transition costs

Questions to testEvaluation criteria


97

+ Slightly better than status quo

Slightly worse than status quo

-Similar to status quo+ Significantly better than status quo

+ Significantly worse than status quo

--

Evaluation of models: Value for MoneyDemand management: commissioner’s balance position

1 York, Hull, James Cook

Models

Evaluation criteria Rationale behind the scores 11D4A 4C1C 3C 15D1A1 17D

NP

V

30 year NPV improves with models 1C, 3C, 4A, 4C, and 11D but remains negative throughoutNPV changes for models 1C to 11D over 30 year time horizon are small enough to be considered similar to status quo


30 year model NPV vs baseline (£m)-6.3 10.2 10.2 10.9 9.9 -35.3

-

-36.3

-

6.0

Tran

siti

on

co

sts


Models 1C to 4C require transition costs of less than £1M. Model 11D requires transition costs of more than £1M, and model 15D and 17D require significantly higher transition costsTransition costs (£m)

0.0 0.3 0.3 0.2 0.4 3.9

- -

3.91.3

-

- -

Fore

cast

I&

E at

sys

tem

an

d h

osp

ital

le

vel


I&E change vs baseline

(£m)

Other hospitals1

Scarborough

System level

Outside York Trust

Within York Trust

Hospital level

Trust level


Total acute spend across the system is less than £1M across all models


Small magnitude of !&E change across models is not likely to allow significant additional investment in more appropriate / alternative settings of care

▪ Does this model reduce the requirement for additional subsidy for Scarborough?

Most models change Scarborough’s 2025 I&E position by less than £1M and are therefore similar to the baseline. Net I&E change for model 15D and 17D is worse than status quo by greater than £1M

0.8

0.0

0.8

0.8

0.0

0.1

0.6

0.8

0.5

0.3

0.1

0.6

0.8

0.6

0.1

0.6

0.2

0.8

0.4

0.4

-0.1

0.9

0.8

-0.1

0.9

-1.6

1.8

0.2

-1.1

1.2

-1.0

1.2

0.2

-1.0

1.1

-0.7

1.6

0.9

-0.2

1.1

- - - -

- -Cap

ital

co

sts


Capital costs required for models 1C to 4C are higher than £1M. Capital costs (~£40m) required to build capacity at other trusts in models 15D and 17D are significant


Implied capital cost required (£m)

Additional beds required (beds)

System will likely struggle with capital cost >£10M

1.3

0

3.5

11

3.5

11

2.1

4

4.2

15

- - -

42.1

170

- -

42.1

170

11.4

53

- -

- -


98

Key messages to steering group alongside the financial baseline and value for money evaluation

Next steps for

modelling

▪ Incorporate transport costs▪ Develop detailed bottom-up costing of new workforce models for narrowed down list of clinical model options▪ Develop detailed perspective on SFC shifts by service line▪ Establish capacity at receiving hospitals and potential for synergies / scaling benefits

Context for the financial baseline

▪ This baseline is a "do nothing" position as far as potential reconfiguration options are concerned but is not a "do nothing" position for the hospital and CCGs in terms of performance improvement initiatives

▪ The current baseline makes ambitious assumptions about demand management, CIP and ALOS improvements

– It assumes that in order to keep commissioners in balance, the system is able to neutralise the majority of demographic and non-demographic related activity growth in non-elective, A&E, and outpatients through demand management – which will require Scarborough to save 74 beds between now and 2025

– On top of this it assumes the hospital can continue to deliver 2% annual CIP savings

– On top of, an independent to the CIP, it also assumes a 15% reduction in ALOS by 2025 which equates to a reduction of52 beds

▪ Despite these initiatives, Scarborough's financial baseline shows a worsening deficit, from -£23M in 2018 to -£27.5M in 2025

Risks /

uncertainties

in the

modelling

▪ The biggest risk / uncertainty of the modelling is how semi-fixed costs (SFC) will shift. There are two parts to this:

– How SFCs are allocated between Scarborough and the receiving site▫ The base case assumes that 30% of semi-fixed costs stay at Scarborough and 70% transfer to the receiving hospital▫ York Trust Finance has done preliminary work to show that more than 30% of the semi-fixed costs could stay at Scarborough▫ We have conducted a sensitivity to reflect this (52% of SFC stay at Scarborough, 48% go to receiving hospital) which shows that each model

has a worse NPV than the base case

– The total amount of SFC in the system▫ The base case assumes this stays at 100% (i.e. no synergies or dissynergies from reconfiguration) which makes models with more

substantial reconfigurations appear worse than others as they attract higher capital costs but no scale benefits▫ We have conducted a sensitivity to show the effect of scale benefits where the receiving hospital only receives 80% of the shifted SFC. This

makes models with more substantial reconfigurations appear better than others because of the synergies from reconfiguring▫ However it is also possible there will be some dys-synergies from reconfiguring because SFC remain at Scarborough but are also incurred at

the receiving hospital▫ This is an important assumption which the modelling is sensitive to so will be important to develop in more detail in the next phase of work

Considerations not accounted for at this stage

▪ Transport costs, either from additional YAS conveyances or internal transfers, are yet to be incorporated into the modelling and will naturally be higher for the models with more substantial reconfigurations


99

Contents










– I&E impact

– Capital costs




– Next steps


100

Change in 2025 Scarborough I&E across all models compared to baseline

1C

3C

4A

4C

11D

15D

Income lost to other hospitals,m£Model

Change in I&E comparing to baseline,m£

SOURCE: Trust baseline data, Activity shift model

17D

2025 Scar-borough I&E

Change in Scarborough semi-variable cost vs baseline

Change in Scarborough fixed cost vs baseline

2025 Scar-borough income

2025 Scar-borough cost

Change in Scarborough variable cost vs baseline

-£0.8m£0.0m

-£1.0m-£0.4m

-£1.0m-£0.4m

-£0.9m-£0.2m

-£1.1m-£0.5m

-£2.0m-£2.1m

-£4.6m-£5.6m

Baseline --

-£4.6m

£102.5m

£97.5m

£97.5m

£101.0m

£96.0m

£82.7m

£60.1m

£102.5m

£57.0m -£5.9m


1A1

1 Current Commissioned Model

-5.1

-5.1

-42.4

-1.6

-6.5

-45.6

-19.9

£0.0m

-£3.9m

-£3.9m

-£1.0m

-£4.8m

-£14.1m

-£30.3m

-£33.3m

-

£129.3m

£124.9m

£124.9m

£128.1m

£123.7m

£112.0m

£89.6m

£86.2m

£130.1m

-£26.8m

-£27.4m

-£27.4m

-£27.1m

-£27.7m

-£29.3m

-£29.4m

-£29.3m

-£27.5m

0.8

-1.7

0

0.1

0.1

-1.9

0.4

-0.1

-1.8


101

Net change to I&E for other hospitals

Additional income to hospital

Net impact of reconfig. on I&E on other hospitals

Impact of change in fixed cost on hospital I&EModel

Impact of change in variable cost on hospital I&E

Impact of change in semi-fixed cost on hospital I&E


1.5

0

0.9

5.1

2.9

00

0.5

2.9

1.50.6

0.6

0.2

2.4

3.8

5.5

11.5

0.82.0

6.0

24.6

12.7

26.4

13.7

0.1

000

0.4

0.2

0.40.10.2

0.200.1

0.50.1

0.3

1.50.3

0.8

0.80.3

0.8

0.70.3

0.8

York James Cook Hull

000

0.200.1

0.2

0.3

0

1.7

0.1

0.100.1

0.10.2

3.2

1.20.3

3.4

0.6

0.7

0.71.8

0.5

4.2

000

2.2

4.0

1.2

2.20.51.2

0.60.10.3

1.4

2.80.6

8.21.7

17.83.7

9.2

19.5

10.1

0

0

00

0

0.1

0.1

0.1

0.4

0.1

0.100

0.20

0.1

0.1

0.6

0.3

0.4

2.8

1.0

2.8

1.0

1C

3C

4A

4C

11D

15D

17D


1A1



102

Net change to I&E for the system

0

-0.1

0.8

-0.7

0.1

-1.6

0.1

0.6

-1.0

Baseline -£27.5m -£27.5m

0.9

0.2

1.6

0

0

0.6

0.6

1.8

1.2

0.8

0

0.8

0.8

0.8

0.8

0.9

0.2

0.2

Net impact on I&E to Scarborough,m£

Net impact on I&E to other hospitals, m£

Net impact on I&E to the system, comparing to baseline, m£Model

Baseline Scarborough I&E

2025 Scarborough I&E plus impact on system


-£26.8m

1C

3C

4C

11D

15D

4A

-£26.8m

-£26.8m

-£26.7m

-£26.6m

-£27.3m

-£26.8m

-£27.3m17D


1A1



103

Trust-level changes in 2025 across all Models compared to baseline



1 Current Commissioned Model 2 James Cook and Hull hospitals

1C

3C

4A

4C

11D

15D

Model Other Trusts

17D

1A1 0.8

0.5

-1.0

0.5

0.6

-0.2

0.4

-1.1

0.4

0.3

0.3

0

1.1

0.1

1.1

1.2

-33

-37

-37

-35

-39

-55

-104

-104

5

5

2

6

22

71

71

0

1.8

2.5

2.5

27.5

27.5

2.9

6.9

14.5

1.3

0.9

0

0.9

0.4

4.5

14.5

I&E change, m£ Change in beds, # of beds Change in capital cost, m£

Other Trusts Other Trusts


104

Evaluation criteria





--

Evaluating models against: I&E impact

1 York, Hull, James Cook

- -

Fore

cast

I&E

at s

yste

m a

nd

ho

spit

al l

eve

l


I&E change vs baseline

(£m)

Other hospitals1

Scarborough

System level

Outside York Trust

Within York Trust

Hospital level

Trust level


Total acute spend across the system is less than £1M across all models


Small magnitude of !&E change across models is not likely to allow significant additional investment in more appropriate / alternative settings of care

▪ Does this model reduce the requirement for additional subsidy for Scarborough?

Most models change Scarborough’s 2025 I&E position by less than £1M and are therefore similar to the baseline. Net I&E change for model 15D and 17D is worse than status quo by greater than £1M

0.8

0.0

0.8

0.8

0.0

0.1

0.6

0.8

0.5

0.3

0.1

0.6

0.8

0.6

0.1

0.6

0.2

0.8

0.4

0.4

-0.1

0.9

0.8

-0.1

0.9

-1.6

1.8

0.2

-1.1

1.2

-1.0

1.2

0.2

-1.0

1.1

-0.7

1.6

0.9

-0.2

1.1

Models

Rationale behind the scores 11D4A 4C1C 3C 15D1A1 17D


105

Contents










– I&E impact

– Capital costs




– Next steps


106

Bed shifts under different models

SOURCE: Activity shift model

1 Includes overnight inpatient beds, i.e., elective and non-elective adult beds (excluding critical care, maternity, neonatal cots, day case beds etc); Beds are rounded to the nearest integer

2 Fixed activity share split for all models 3 Current Commissioned Model


295

284

284

291

280

243

126

126

328

6

6

3

9

30

98

98

0

Incremental impact on other hospitals2 beds Beds required at Scarborough in 2025 beds1Model

Current number of beds1:

1

1

1

2

6

20

20

0

3

3

1

4

16

51

51

0

James Cook Hull York


1A3

1C

3C

4A

4C

11D

15D

17D


107

Implied capital costs modelling under different models

System

Adding new Scarborough capacity1

Clearing backlog maint.2

Net land receipts

Scar-borough Δ bedsbeds

New beds at

other hospitals,beds

6

6

3

9

30

98

98

1

1

1

2

6

20

20

3

3

1

4

16

51

51

000

4.2

3.2

0.3

0

0.7

00

1.30.3

0.7

1.3

0.5

0.30.1

1.80.40.9

6.21.3

27.9

10.4

27.94.2

10.4

Scar-borough net costm£

Other hospitals net cost3

m£

0.7

1.2

1.2

1.3

1.2

-0.4

1.2

-0.4

2.3

42.5

0

2.3

0.9

3.0

10.7

42.5


SOURCE: Activity data from SLAM 17/18, Activity shift model

Model



Capital cost of new capacity at other hospitals,m£

1A1 £1.3m£1.3m(33) £0.0m £0.0m

1C £3.5m£1.2m(44) £0.0m £0.0m

3C £3.5m£1.2m(44) £0.0m £0.0m

4A £2.1m£1.2m(37) £0.0m £0.0m

4C £4.2m£1.2m(48) £0.0m £0.0m

11D £11.4m£1.0m(85) £0.0m -£0.4m

15D £42.1m£0.5m(202) £0.0m -£0.9m

17D £42.1m£0.5m(202) £0.0m -£0.9m

Costs shown as positive


108

Trust-level changes in 2025 across all models compared to baseline



1 Current Commissioned Model 2 James Cook and Hull hospitals

1C

3C

4A

4C

11D

15D

Model Other Trusts

17D

1A1

0.6

0.5

0.5

0.4

-0.2

-1.1

-1.0

0.3

1.2

0.1

0

0.3

0.4

1.1

1.1

-33

-37

-37

-35

-39

-55

-104

-104

5

5

2

6

22

71

71

0

6.9

2.5

27.5

27.5

2.5

2.9

1.8

4.5

1.3

0

0.9

14.5

0.9

14.5

0.4

I&E change, m£ Change in beds, # of beds Change in capital cost, m£

Other Trusts Other Trusts


109

Suggested evaluation of models: Capital

Key questions

▪ Does the group agree with the ratings and rationale for the capital costs evaluation?

Evaluation criteria





--

- - - -

- -

Cap

ital

co

sts


Capital costs required for models 1C to 4C are higher than £1M. Capital costs (~£40m) required to build capacity at other trusts in models 15D and 17D are significant


Implied capital cost required (£m)

Additional beds required (beds)

System will likely struggle with capital cost >£10M

1.3

0

3.5

11

3.5

11

2.1

4

4.2

15

- - -

42.1

170

- -

42.1

170

11.4

53

Models


- -

- -


110

Contents










– I&E impact

– Capital costs




– Next steps


111

Transition costs associated with the movement of beds

Model Total transition cost# of beds moved by 2025

15D

1C

3C

4A

4C

11D

17D

SOURCE: Activity shift model

▪ Assumes £250 per bed day for the disruption

▪ Assumes 90 days of disruption

▪ Assumes that there is a fixed PMO cost of £100k for the duration of transition

£3.9m

£0.4m

£0m

£0.3m

£0.3m

£0.2m

£3.9m

£1.3m

11

11

4

15

53

170

170

0


1A1

1 Current Model


112

Key questions

▪ Does the group agree with the ratings and rationale for the transition costs evaluation?

Evaluating models against: Transition costs

Evaluation criteria





--

Tran

siti

on

co

sts


Models 1C to 4C require transition costs of less than £1M. Model 11D requires transition costs of more than £1M, and model 15D and 17D require significantly higher transition costsTransition costs (£m)

0.0 0.3 0.3 0.2 0.4 3.9

- -

3.91.3

-

Models


- -


113

Contents










– I&E impact

– Capital costs




– Next steps


114

30 year NPV, m£

SOURCE: Reconfiguration model; Trust baseline data

1 System capital costs shown here 2 System NPV relative to base case over 30 years, with 3.5% discount rate (as per Green Book) not including the terminal value of any assets, and assuming all assets are maintained in line with depreciation 3 Current Model

System NPV analysis with current assumptionsDemand management: commissioner’s balance position

Baseline

Total system net capital costs1 m£

Transition costsModel

Net impact on 30 year NPV to the system, compared to baseline

1C

3C

4C

11D

15D

Net impact on discounted I&E to other hospitals

30 year Net Present Value2 (£m)

4A

17D -34.2

-1.0

-3.4

-2.8

-1.7

-34.2

-9.3

-2.8

0

-0.3

-0.3

-3.9

-0.4

-0.2

-1.3

-3.9

-6.3

10.2

10.2

-36.3

10.9

9.9

6.0

-35.3

7.7

-22.8

-5.3

-14.0

-17.4

3.6

3.6

-0.8

39.3

5.2

0

20.2

9.8

9.8

14.5

15.9

1A3

-504.5

-510.8

-498.5

-493.6

-494.3

-494.3

-539.9

-494.6

-540.8

Net impact on discounted I&E to Scarborough System 30 year NPV


115

Evaluating models against: NPV

Key questions

▪ Does the group agree with the ratings and rationale for the NPV evaluation?

Evaluation criteria





--

NP

V

30 year NPV improves with models 1C, 3C, 4A, 4C, and 11D but remains negative throughoutNPV changes for models 1C to 11D over 30 year time horizon are small enough to be considered similar to status quo


30 year model NPV vs baseline (£m)-6.3 10.2 10.2 10.9 9.9 -35.3 -36.36.0

models


- -


116

Contents










– I&E impact

– Capital costs




– Next steps


117

FRG has agreed to run the following sensitivity analyses Sensitivities being modelled

FRG decided to run sensitivities to see the impact of:

B. CCG only achieving historical levels of demand management

C. Semi-fixed cost factor being 48% (to reflect internal work done to identify proportion of semi-fixed costs which would actually move)

D. ALOS reduction allowing Scarborough to reach current top quartile of average length of stay

E. Assuming synergies in semi-fixed cost transfer – assume only 80% of shifted semi-fixed cost would transfer to receiving site1

F. Cost of adding new beds being £100k for under 60 beds and £200k for over 60 beds

F

1 56% consolidation factor means that out of 70% of transferred semi-fixed cost 80% gets consolidated (70%*80%=56%)

Modelled alternative “Base case”

B C D E

15%15% 15% 15% 21% 15%2025 target ALOS reduction


Demand management levels assumed


Based on levels historically achieved









Semi-fixed costs transferred with activity

70% removal factor56% consolidation factor1

Bed costs








118

m£


Sensitivity analysis: net impact on I&E

1 Current state 2 York, Hull, James Cook

Net impact on I&E

B C D E F

SensitivitiesHistorical demand management

48% of semi-fixed costs transferred“Base case”

Top quartile ALOS reduction

Semi-fixed cost consolidation factor 56%

Bed costs £100k and £200k

1C

3C

4C

11D

15D

4A

17D

1A1

A

0.8

-1.7

-1.9

-1.8

0.9

2.6

2.0

1.9

0.1

0.8

0.4

0.7

0.7

-0.1

0.1

0.4

0.8

0.8

0.8

0.8

0.9

0.1

0.1

Scarborough

Other hospitals1

-5.2

-5.7

-5.8

3.9

3.8

3.9

1.1

0.5

-0.7

-0.7

-0.7

0.7

-1.4

0.7

-1.2

-1.4

-1.8

-0.7

-0.7

-0.7

-1.3

-1.9

-1.9

-6.1

-11.4

-12.2

7.0

11.6

12.4

0.8

0.1

1.9

-1.1

0.7

1.9

-1.1

2.4

0.2

-1.6

0.8

0.8

0.8

0.8

0.8

0.9

0.2

1.2

0.9

-1.3

-1.7

-1.6

0.7

0.7

1.0

2.7

2.4

2.3

1.2

1.30.6

0.6

0.3

1.2

0.3

1.3

1.3

1.4

0.7

0.7

1.8

5.4

8.1

8.6-1.7

0.1

-1.8

1.6

0.8

1.00.6

1.5

0.1

1.5

6.3

0.4

-0.1

-1.7

0.8

1.6

1.7

3.7

6.9

-1.7

-1.9

-1.8

1.0

3.1

4.2

4.0

2.3

0.4

0.1

0.8

0.4

0.8

0.8

0.1

-0.1

0.8

0.9

0.9

0.8

0.9

1.4

2.2

Total = system net I&E impact55ACTIVITY SHIFT MODEL

119SOURCE: Reconfiguration model; Trust baseline data

Sensitivity analysis: net impact on I&E for the Trust

1 Current state

Net impact on I&E

B C D E F

SensitivitiesHistorical demand management

48% of semi-fixed costs transferred“Base case”


Semi-fixed cost consolidation factor 56%


1C

3C

4C

11D

15D

4A

17D

1A1

A

0.8

0.5

0.5

0.6

0.4

-1.1

-1.0

0.4

1.1

1.2

1.1

0.8

0.8

-0.2

0.1

0.3

0.3

0.9

0.8

0.7

0.8

0.1

0.1

York Trust

Out of Trust

-2.9

-4.0

-4.0

1.6

2.1

2.1

0.3

-0.7

-0.7

-1.0

-0.9

-1.0

0.3

0.5

0.2

-1.2

-0.7

-0.7

-0.7

-0.7

-1.3

-1.9

-1.9

-5.0

-5.4

3.0

5.2

5.5

0.3

-2.1

0.8

0.8

0.8

0.8-0.2

0.5

0.2

0.9

1.0

0.8

0.8

0.8

0.8

0.1

1.2

1.0

1.0

1.1

0.9

-0.6

-0.5

0.3

0.3

0.4

1.1

1.3

1.2

1.3

0.7

1.30.2

0.1

1.2

1.3

1.2

1.3

0.7

1.4

2.6

2.9

2.3

3.7

3.9

0.8

0.8

0.6

0.2

1.0

0.7

1.0

0.6

1.0

0.8

1.6

1.6

0.9

1.8

3.7

6.3

6.8

0.8

0.6

0.6

0.7

0.5

0.4

0.4

0.5

1.3

1.9

1.8

0.9

0.3

0.3

0.8

0.2

0.1

0.9

0.9

1.0

1.4

2.3

2.2

Total = system net I&E impact


m£


Sensitivity analysis: change in number of beds and capital costs

1 Current state 2 York, Hull, James Cook

1.31.3

Beds change for

Scarborough, #beds35

C D E F

-44

-44

-48

-85

-202

-37

-202

-33

24

24

19

-28

-173

30

-173

35

-44

-44

-48

-85

-202

-37

-202

-33

-64

-64

-67

-102

-211

-58

-211

-54

-44

-44

-48

-85

-202

-37

-202

-33

-44

-44

-48

-85

-202

-37

-202

-33

Model

Sensiti-vities

1C

3C

4C

11D

15D

4A

17D

1A1

B

Historical demand management“Base case”

48% of semi-fixed costs transferred Top quartile ALOS reduction

Semi-fixed cost con-solidation factor 56% Bed costs £100k and £200k

Scarborough capital costs

Other hospital capital costs2

1.2

2.3 3.5

3.52.3

1.2

2.1

0.9

1.2

3.0

1.2

4.2

11.410.70.7

42.1-0.4 42.5

42.5-0.4 42.1

8.4 8.4

2.46.1 8.4

2.46.1 8.4

1.17.3 8.4

3.35.1 8.4

12.91.3 14.1

55.055.2-0.2

55.2-0.2 55.0

1.3 1.3

2.3 3.5

1.2

2.3 3.5

1.2

0.9

1.2 2.1

4.23.0

1.2

10.70.7 11.4

42.5-0.4 42.1

42.5-0.4 42.1

1.31.3

2.1

0.9

3.0

3.0

0.9

2.1

2.1

0.8

1.2

2.8

0.9

3.7

10.510.00.6

38.238.6-0.4

38.6-0.4 38.2

1.31.3

2.3

1.2

3.5

2.3

1.2

3.5

0.9

1.2 2.1

3.0 4.2

1.2

10.70.7 11.4

-0.4 42.5 42.1

42.142.5-0.4

1.3 1.3

1.1

1.2 2.3

1.1

1.2 2.3

0.4

1.2 1.7

2.71.5

1.2

5.3

0.7

5.9

20.8

-0.4 20.4

20.4-0.4

20.8



Sensitivity analysis: change in number of beds and capital costs for the Trust

1 Current state

C D E F

Model

Sensiti-vities

B

Historical demand management“Base case”

48% of semi-fixed costs transferred Top quartile ALOS reduction

Semi-fixed cost con-solidation factor 56% Bed costs £100k and £200k

1C

3C

4C

11D

15D

4A

17D

1A1 1.31.3

Capital costs for York Teaching hospital NHS Foundation Trust

Other hospital capital costs

3.5

0.9

2.5

0.9

2.5 3.5

2.1

0.4

1.8

1.3

4.22.9

4.56.9 11.4

42.127.5 14.5

14.527.5 42.1

-33

-37

-37

-39

-55

-104

-35

-104

30

30

28

9

-52

33

-52

35

-37

-37

-39

-55

-104

-35

-104

-33

-58

-58

-59

-74

-120

-55

-120

-54

-37

-37

-39

-55

-104

-35

-104

-33

-37

-37

-39

-55

-104

-35

-104

-33

Beds change for York

Teaching hospital NHS

Foundation Trust, #beds

35

8.4 8.4

1.07.5 8.4

1.0 8.47.5

8.40.58.0

1.47.1 8.4

8.7 5.4 14.1

18.3 55.036.7

36.7 18.3 55.0

1.3 1.3

3.5

0.9

2.5

0.9

2.5 3.5

2.1

0.4

1.8

1.3

2.9 4.2

4.56.9 11.4

14.527.5 42.1

14.527.5 42.1

1.3 1.3

3.0

0.9

2.1

2.1

0.9

3.0

1.7 2.1

0.3

1.2

2.5 3.7

10.54.26.4

13.5

24.7 38.2

38.2

13.5

24.7

1.31.3

3.5

0.9

2.5

0.9

2.5 3.5

0.4

1.8 2.1

1.3

2.9 4.2

11.44.56.9

14.5 42.127.5

14.527.5 42.1

1.31.3

0.5

1.9 2.3

2.3

0.5

1.9

0.2

1.5 1.7

2.1

0.6

2.7

2.2

3.7 5.9

7.1

13.3 20.4

13.3

7.1

20.4



Sensitivity analysis: transition costs

1 Current state

Model

Sensitivities

Beds shifted, #beds

B C D

Historical demand manage-ment

48% of semi-fixed costs trans-ferred

“Base case”


B C D

Transition costs, £m

Historical demand manage-ment

“Base case”

48% of semi-fixed costs trans-ferred


E

Semi-fixed cost consoli-dationfactor 56%

F


E

Semi-fixed cost consoli-dationfactor 56%

F


1C

3C

4C

11D

15D

4A

17D

1A1

11.0

11.0

4.0

15.0

53.0

170.0

170.0

12.0

12.0

5.0

16.0

63.0

208.0

208.0

11.0

11.0

4.0

15.0

53.0

170.0

170.0

10.0

10.0

4.0

14.0

49.0

158.0

158.0

11.0

11.0

4.0

15.0

53.0

170.0

170.0

11.0

11.0

4.0

15.0

53.0

170.0

170.0

0.3

0.3

0.2

0.4

1.3

3.9

3.9

0.4

0.4

0.2

0.5

1.5

4.8

4.8

0.3

0.3

0.2

0.4

1.3

3.9

3.9

0.3

0.3

0.2

0.4

1.2

3.6

3.6

0.3

0.3

0.2

0.4

1.3

3.9

3.9

0.3

0.3

0.2

0.4

1.3

3.9

3.9


123

m£


Sensitivity analysis: system NPV

B C D

Model

Sensiti-vities

1 Current state

ACTIVITY SHIFT MODEL

Change NPV

vs baseline

30 year

NPV

Change NPV

vs baseline

30 year

NPV

Change NPV

vs baseline

30 year

NPV

Change NPV vs baseline

“Base case”

30 year NPV

Historical demand management

48% of semi-fixed costs transferred


Change NPV

vs baseline

30 year

NPV

Change NPV

vs baseline

30 year

NPV

Semi-fixed cost consolidation factor 56% Bed costs £100k and £200k

E F

1C -494 -481 -493 -486 -481 -491

3C -494 -481 -493 -486 -481 -491

4C -495 -481 -493 -486 -478 -491

11D -498 -493 -495 -490 -449 -485

15D -540 -539 -530 -526 -431 -485

4A -494 -481 -493 -486 -490 -492

17D -541 -540 -530 -527 -421 -486

1A1 -511 -497 -511 -503 -511 -511

Baseline -505 -462 -505 -505 -505 -505

-6.3

10.2

10.2

10.9

6.0

-35.3

-36.3

9.9

-34.9

-18.5

-18.5

-18.5

-30.8

-76.9

-77.6

-18.2

-6.3

11.2

11.2

11.2

9.9

-25.3

-25.2

11.2

1.8

18.4

18.4

18.8

14.6

-21.9

-22.8

18.2

-6.3

23.7

23.7

14.3

55.8

73.9

83.6

26.7

13.1

13.1

12.1

19.9

19.8

18.9

13.8

-6.3

5

124

Contents










– I&E impact

– Capital costs




– Next steps


125

Next steps

▪ Financial modelling in this initial phase is top-down. More detailed financial analysis, capacity planning, and costing will be required in any subsequent phases once a narrower set of clinical model models are being considered

▪ Examples of further work are:

‒ Transport costs

o For any model it will be necessary to identify in a more detailed way what additional capacity is required where, including for the ambulance trust, and what, if any, capital would be required to secure that capacity

o This should also include transfers between hospitals as well as activity taken directly to other hospitals

‒ Workforce impact

o Each model will require a more detailed assessment of impact on workforce

NOT EXHAUSTIVE

126

Contents







127

Summary of financial impact of base model (1/5)

Notes:Transport/ambulance costs of transfers is not includedCIP's will assume any savings for LOS reductions therefore there is a double count of fixed cost bed savings (52 beds at £1.2m)Demand management/QIPP not historicvally achieved, therefore a significant assumption and risk buit inNo allowance for double running costs should part of a service transfer. The shifts in some models cross speciaties.No allowance for co-dependency of obstetrics/gynaecology if births transferLow volumes may not save semi fixed, fixed costs but will lose income to York Trust, increasing the deficit.

Clinical model @ 2025

£mModel 1c,£m

Model 3c,£m

Model 4a,£m

Model 4c,£m

Model 11d,£m

Model 15d,£m

Model 1a,£m

2017/18 Baseline -23.0 -23.0 -23.0 -23.0 -23.0 -23.0 -23.0 -23.0 -23.0

Model 17d,£mSummary @ 2025

Bridge

Service costs -6.1 -6.1 -6.1 -6.1 -6.1 -6.1 -6.1 -6.1 -6.1

2% CIP (SF, VC ) 17.0 17.0 17.0 17.0 17.0 17.0 17.0 17.0 17.0

Cost Inflation -27.0 -27.0 -27.0 -27.0 -27.0 -27.0 -27.0 -27.0 -27.0

Growth cost (SF,V reduced by scaling factor 70%)

-13.0 -13.0 -13.0 -13.0 -13.0 -13.0 -13.0 -13.0 -13.0

Demand management cost savings (SF,V reduced by scaling factor 70%)

13.0 13.0 13.0 13.0 13.0 13.0 13.0 13.0 13.0

Price Inflation (Income) 12.0 12.0 12.0 12.0 12.0 12.0 12.0 12.0 12.0

Growth (Income at tariff est 100%) 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0

Demand management income savings (income at tariff est 100%)

-15.0 -15.0 -15.0 -15.0 -15.0 -15.0 -15.0 -15.0 -15.0

Deficit SGH 2024/25 -27.1 -27.1 -27.1 -27.1 -27.1 -27.1 -27.1 -27.1 -27.1

Deficit SGH 2024/25 -27.1 -27.1 -27.1 -27.1 -27.1 -27.1 -27.1 -27.1 -27.1

Current beds 2017/18 329.0 329.0 329.0 329.0 329.0 329.0 329.0 329.0 329.0

Additional beds required to achieve 85% Occupancy

12.0 12.0 12.0 12.0 12.0 12.0 12.0 12.0 12.0

128



Bed reductions due to demand management

Summary @ 2025

Bed reductiuons assumed due to 15% LOS improvement

Bed increases due to growth

Sub total baseline bed shift assumptions

Bed reductions due to model shifts out

Net beds on SGH Site

Beds transfering to York

Beds transfeting to Hull

Beds transfering to James Cook

Beds transferred to receiving sites


Revenue income change

Revenue cost change (SF)

Revenue cost change (VC)

-74.0

-52.0

80.0

-34.0

295.0

-74.0

-52.0

80.0

-34.0

295.0

0.0

0.0

0.0

-74.0

-52.0

80.0

-34.0

-10.0

285.0

6.0

3.0

1.0

10.0

-5.1

-3.9

-0.4

-74.0

-52.0

80.0

-34.0

-10.0

285.0

6.0

3.0

1.0

10.0

-5.1

-3.9

-0.4

-74.0

-52.0

80.0

-34.0

-3.0

292.0

3.0

1.0

1.0

5.0

-1.6

-1.0

-0.2

-74.0

-52.0

80.0

-34.0

-14.0

281.0

9.0

4.0

2.0

15.0

-6.5

-4.8

-0.5

-74.0

-52.0

80.0

-34.0

-51.0

244.0

30.0

16.0

6.0

52.0

-19.9

-14.1

-2.1

-74.0

-52.0

80.0

-34.0

-168.0

127.0

98.0

51.0

20.0

169.0

-42.4

-30.3

-5.6

-74.0

-52.0

80.0

-34.0

-168.0

127.0

98.0

51.0

20.0

169.0

-45.6

-33.3

-5.9


£mModel 1c,£m

Model 3c,£m

Model 4a,£m

Model 4c,£m

Model 11d,£m

Model 15d,£m

Model 1a,£m

Model 17d,£m

129



Revenue fixed cost change (Net impact bed change - Net beds on SGH site above @ £30k per bed x 75%)

Summary @ 2025

Revenue impact SGH (-) increases deficit

York hospital




Revenue fixed cost change (Net impact bed change - Net beds transfering in as above @ £xx per bed)

Revenue impact York Hospital

Summary York Trust





Summary Revenue impact York Trust

-0.8

0.8

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

-0.8

0.8

-1.0

0.2

2.9

2.2

0.2

0.1

0.4

-2.2

-1.7

-0.2

-0.9

0.6

-1.0

0.2

2.9

2.2

0.2

0.1

0.4

-2.2

-1.7

-0.2

-0.9

0.6

-0.8

0.4

0.9

0.6

0.1

0.1

0.1

-0.7

-0.4

-0.1

-0.7

0.5

-1.1

-0.1

3.8

2.8

0.3

0.2

0.5

-2.7

-2.0

-0.2

-0.9

0.4

-1.9

-1.8

11.5

8.2

1.2

0.6

1.5

-8.4

-5.9

-0.9

-1.3

-0.3

-4.5

-2.0

24.6

17.8

3.2

2.8

0.8

-17.8

-12.5

-2.4

-1.7

-1.2

-4.5

-1.9

26.4

19.5

3.4

2.8

0.7

-19.2

-13.8

-2.5

-1.7

-1.2


£mModel 1c,£m

Model 3c,£m

Model 4a,£m

Model 4c,£m

Model 11d,£m

Model 15d,£m

Model 1a,£m

Model 17d,£m

130



Hull/ James Cook

Summary @ 2025





Summary Revenue impact Hull/James Cook

Overall Impact on patch




Revenue fixed cost change (Net impact bed change - Net beds change as above @ £xx per bed)

Summary Revenue impact Overall patch

Baseline deficit B/F + Clinical Model impact

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

-0.8

0.8

-26.3

2.1

1.8

0.1

0.1

0.1

-0.1

0.1

-0.1

-0.8

0.7

-26.4

2.1

1.7

0.1

0.1

0.2

-0.1

0.0

-0.1

-0.8

0.8

-26.3

0.7

0.4

0.1

0.0

0.2

0.0

0.0

0.0

-0.7

0.7

-26.4

2.8

2.0

0.3

0.1

0.4

0.1

0.0

0.1

-0.8

0.8

-26.3

8.4

5.9

0.9

0.4

1.2

0.0

0.0

0.0

-0.9

0.9

-26.2

17.8

12.9

2.4

1.4

1.1

0.0

0.4

0.0

-0.3

-0.1

-27.2

19.2

14.1

2.5

1.4

1.2

0.0

0.3

0.0

-0.3

0.0

-27.1


£mModel 1c,£m

Model 3c,£m

Model 4a,£m

Model 4c,£m

Model 11d,£m

Model 15d,£m

Model 1a,£m

Model 17d,£m

131



Capital investment

Summary @ 2025

Capacity York

Capacity Hull/ James Cook

Net land receipts (Sale of land SGH)

Maintenance backlog savings SGH

Capital costs

Transitional costs

0.0

0.0

1.3

1.3

0.0

1.3

1.0

1.2

3.5

0.3

1.3

1.0

1.2

3.5

0.3

0.5

0.4

1.2

2.1

0.2

1.8

1.3

1.2

4.3

0.4

6.2

4.5

-0.4

1.0

11.3

1.3

27.9

14.6

-0.9

0.5

42.1

3.9

27.9

14.6

-0.9

0.5

42.1

3.9


£mModel 1c,£m

Model 3c,£m

Model 4a,£m

Model 4c,£m

Model 11d,£m

Model 15d,£m

Model 1a,£m

Model 17d,£m

annex 3 finance workstream · agree npv inputs ... what are the transition costs (e.g., relocating...

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