Welcome and Introductions to the Yorkshire & Humber Liaison - - PowerPoint PPT Presentation

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Yorkshire and the Humber Mental Health Network

Welcome and Introductions to the Yorkshire & Humber Liaison Mental Health Network

Dr Katie Martin,Clinical Lead, Yorkshire and the Humber Clinical Networks

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Agenda

13.30 Welcome and Introductions to the Yorkshire & Humber Liaison Mental Health Network Dr Katie Martin Clinical Lead Yorkshire and the Humber Clinical Networks 13.35 IAPT Long Term Conditions Programme and the Fit with Liaison Mental Health Group discussion Ursula James IAPT Programme Manager NHS England 14.20 TEWV Evaluation, Demonstrating the Savings Group discussion re. impact on Wave 2 applications Aimee Fox & Sebastian Hinde, Research Fellows University of York 15.05 Assessment Paperwork – Group session Led by Katie 15.30 Close

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Yorkshire and the Humber Mental Health Network

The IAPT Long Term Conditions Programme Ursula James IAPT Programme Lead NHS England

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IAPT Programme

Expanding IAPT services to deliver successful interventions for long term conditions

Integrating IAPT with physical health pathways IAPT-LTC

Ursula James – National IAPT Programme Manager

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• At least 50% of people completing treatment should move to recovery.
• 16.8% of people with depression and anxiety disorders should access treatment in 17/18 rising

to 25% by 2020/21.

• 75% of people should start treatment within 6 weeks of referral, and 98% within 18 weeks.
• NHS Operational Planning and Commissioning Guidance 2017-19
• CCGs should commission additional IAPT services, in line with the trajectory to meet

25% of local prevalence in 2020/21.

• Ensure local workforce planning includes the number of therapists needed and

mechanisms are in place to fund trainees.

• From 2018/19, commission IAPT services integrated with physical healthcare and

supporting people with physical and mental health problems – IAPT-LTC (Long Term Conditions)

• Transformed treatment of anxiety & depression
• Stepped care psychological therapy services established

in every area of England. Self-referral.

• 15.8% of local prevalence (956,000 people) seen in services in 16/17
• Around 69% have course of treatment (over 565,000 per year)
• Outcomes recorded in 98% of cases (pre-IAPT 38%)
• Very strict (depression & anxiety) recovery criteria
• Nationally 51% recover and further 16% improve.
• 6 of every 10 CCGs have recovery > 50%, some > 60%.

IAPT programme- general overview IAPT programme- current standards

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FYFV Commitments

70,000 more children will access evidence based mental health care interventions Intensive home treatment will be available in every part of England as an alternative to hospital. No acute hospital is without all- age mental health liaison services, and at least 50% are meeting the ‘core 24’ service standard At least 30,000 more women each year can access evidence- based specialist perinatal mental health care 10% reduction in suicide and all areas to have multi-agency suicide prevention plans in place by 2017 Increase access to evidence-based psychological therapies to reach 25% of need, helping 600,000 more people per year The number of people with SMI who can access evidence based Individual Placement and Support (IPS) will have doubled 280,000 people with SMI will have access to evidence based physical health checks and interventions 60% people experiencing a first episode of psychosis will access NICE concordant care within 2 weeks including children Inappropriate out of area placements (OAPs) will have been eliminated for adult acute mental health care New models of care for tertiary MH will deliver quality care close to home reduced inpatient spend, increased community provision including for children and young people There will be the right number of CAMHS T4 beds in the right place reducing the number of inappropriate out of area placements for children and young people

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FYFV Commitments: Increase access to 1.5m people a year

15.58% 15.80% 16.80% 19% 22% 25% 953 960 1,020 1,160 1,370 1,500 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 0% 5% 10% 15% 20% 25% 2015/16 2016/17 2017/18 2018/19 2019/20 2020/21 Number of people accessing treatment, thousands

Access

Projected access rate People accessing treatment (thousands)

NEXT STEPS ON THE NHS FIVE YEAR FORWARD VIEW

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• CCGs should commission additional IAPT services, in line with the

trajectory to meet 25% of local prevalence in 2020/21.

• To meet the increase in access (66%), providers will need an additional

increase in staff of at least 50%.

• Overall planning of workforce should include increasing the number of

trainees to meet 4,500 commitment by 2020/21, this has been disseminated via regional teams with numbers at CCG level.

• Overall planning of workforce should include increasing the numbers
• f therapists co-located in general practice by 3,000 by 2020/21.
• From 2018/19, commission IAPT services integrated with physical

healthcare and supporting people with physical and mental health problems – IAPT-LTC

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What will this mean for CCGs and Providers?

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Aim:

• To implement integrated psychological therapies at scale – improving care

and outcomes for people with mental health problems and long term physical health problems, and distressing and persistent medically unexplained symptoms.

• To learn how best to implement integrated psychological therapies at scale in

an NHS context – moving from trials and pilots to business as usual.

• To build the return on investment case for integrated psychological therapies

– demonstrating savings in physical health care.

• To build capacity in the IAPT workforce, starting the expansion of the

workforce needed to meet 600,000 extra people entering treatment by 2020/21.

• Challenging the Mind/Body split

2016/17 and 2017/18 - IAPT Early Implementer Programme

London

Key

IAPT Wave 1 and 2 CCGs

Wave 1 Wave 2

• 68 CCGs
• 62% of all STP’s have at

least 1 CCG within commissioning IAPT-LTC

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IAPT-LTC Definition

What defines an Integrated IAPT service?

An integrated service will expand access to psychological therapies for people with long term health conditions or MUS by providing care genuinely integrated into physical health pathways working as part of a multidisciplinary team, with therapists, who have trained in IAPT LTC/MUS top up training, providing evidence based treatments collocated with physical health colleagues.

What defines an Integrated IAPT service? An integrated service will expand access to psychological therapies for people with long term health conditions or MUS by providing care genuinely integrated into physical health pathways working as part of a multidisciplinary team, with therapists, who have trained in IAPT LTC/MUS top up training, providing evidence based treatments collocated with physical health colleagues. It is important to keep this definition in mind when setting up your integrated service. It may be that in the beginning all these requirements are not met however you should be aiming for a service model which satisfies all 3 of the criteria above.

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How?

• Co-located physical and mental healthcare
• NICE-recommended therapies, adapted for people with LTCs

and delivered by properly trained therapists. Hence the need for CPD courses for IAPT Hi & PWPs

• IT systems support outcome monitoring for all (mental health

symptoms, disability, perception of physical health problems).

• All IAPT’s existing quality standards.
• Closely linked to, and managed with core IAPT (don’t try to

reinvent the wheel)

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What is available to support implementation?

CPD for therapists in psychological therapy for people with long term conditions and/or medically unexplained symptoms Service design: implementation guidance available Extra core trainees to backfill experienced staff moving into IAPT-LTC Suite of guidance including: accessible “how to” guide; Building the business case document; IAPT-LTC data handbook; IAPT-LTC data quality guide; IAPT-LTC FAQ’s

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Which LTC’s? Summary of Wave 1 and 2 sites

The most common LTCs that are likely to be seen in new integrated IAPT services:-

• Diabetes
• Chronic obstructive pulmonary disease (COPD)
• Cardiovascular disease (CHD)
• Musculoskeletal problems, Chronic pain.
• MUS

Colocation for the Early Implementers:-

• GP Practices/Primary Care
• Acute Hospitals and Secondary Care
• Community Teams

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Commissioners

• There is enthusiasm in providers and CCGs to develop integrated

services, and there are examples of services that are already providing psychological therapies in this way

• Start early! Engagement, relationships and development of

pathways does take time

• Develop a good implementation plan which is co-produced, has

both physical and mental health input along with service user collaboration

• When developing pathways, carefully consider local nuance –

where lends itself to integrated working? What do the Right Care packs show?

• Mapping exercise to prevent duplicate commissioning- what is

commissioned from the physical care envelope

• Can this work across the STP/ vanguard

Learning from process so far

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Providers

• Start early- Engagement, relationships and development of pathways does

take time

• Ensure there is clarity re the distinctions between IAPT LTC, Liaison

Psychiatry and health psychology, and that the pathways between all three are clear and collaborative

• Make links top down and bottom up
• Don’t underestimate the important of publicity and marketing- start this

early too

• How should you brand your service to appeal to the target audience –

think about language, stigma, visual design..

• Training and engagement of Physical Health Care staff
• Can you dual train practitioners?
• Undergoing significant service developments at pace can have an impact
• n staff wellbeing - ensure steps are taken to support the team

Learning from process so far

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Allocation to Core IAPT vs Integrated IAPT

• IAPT clients with a co-morbid LTC that is not a significant problem –

treated in Core IAPT

• IAPT clients with a co-morbid LTC that significantly impacts on

wellbeing, for which IAPT treatment will need to be adapted – Integrated IAPT

• Referrals through –
• Usual route (Self/GP Referral)
• Directly from specialist physical health teams/workers (e.g.

Diabetes Service)

• Generic community physical health workers (e.g. District

Nurses/Matrons, Practice Nurses)

• Psychiatric Liaison services

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Pathway Example

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Leaflet Example

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• Initial information from Early Implementer sites indicates a

significant amount of referrals have come from physical health care colleagues who are new referrers into IAPT services

• Early indication of a significantly higher proportion of older

adults ( compared to the core IAPT services)

• Early indication of a more balanced gender split (currently

2/3 female to 1/3 male in core IAPT)

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Impact of integration on referral source

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• Early Implementer sites report recovery rates of >50% for

patients in IAPT-LTC pathways

• Results of local evaluations from wave 1 early implementer

sites demonstrate reductions in healthcare utilisation for patients seen in IAPT-LTC

• Table below is taken from initial site evaluation following

446 patients in IAPT-LTC with pre and post CSRI (Client Services Receipt Inventory)

21

Early Implementer Initial Outcomes

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• Sites who have shared their initial local evaluation data

report:- I. Reduction in GP appointments post treatment II. Reduction in doctor/consultant appointments post treatment

• III. Reductions in medical investigations post

treatment

• IV. Reductions in hospital admissions and A & E

attendances

• Some sites reported increases in specialist nurse use –

indicating better use of healthcare and condition management

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Initial CSRI Data

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Impact of IAPT-LTC CPD training

“the specialist training helped to highlight the varied ways that ill health can have a negative impact on a person’s experience of life” “…encouraged me to incorporate

• ther relevant approaches…”

“…feel more confident …” “…felt helpless, but now.. I don’t feel quite as lost!...” “…easily be able to liaise with the nurses and physiotherapists to ask questions relating to my clients” “….get these questions answered by the professional involved….” “….now I am more at ease with making contact with physical health professionals about a client because it does feel like our business. “

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Feedback from patients

• ‘I am joining in with life again, I am noticing things around me. I am

able to make more effort and can do so much now without experiencing any stress at all’.

• ‘People have been telling me I look so much happier in myself, my

daughter is amazed as I am offering to look after the babies. It made me realise how much I had been ignoring the family around, my health is in control and I have my life back’.

• “My diabetes has also changed- my mood has changed because I have

control of my sugar better than I ever had done. I’ve got the depressed attitude out of the way and I can manage the diabetes better.” “Anxiety was more disabling to me than my heart attack or the surgery” “After my heart attack I was feeling chest pain and I kept going to A & E and hospital but they said I was fine. Then I saw the Heart2Heart therapist and realised I was

• depressed. I’ve got a long way to go but I

can get out of the house now and I am thinking of returning to work”

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Feedback from professionals

• “Just wanted to let you know that I saw LJ last week and it was

like having a completely different person sat in front of me.”

• “X is absolutely thrilled with the work you have been doing with

him and reports you have finally helped him to understand why he has struggled for years with his health management behaviours.”

• “Patients report your help has impacted their whole life - work,

relationships & diabetes.”

• Thanks - your input is certainly making my job with patients much

easier!”

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Thank you for listening Contact me on ujames@nhs.net

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Yorkshire and the Humber Mental Health Network

The IAPT Long Term Conditions Programme and the fit with Liaison Mental Health Questions and Discussion

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Yorkshire and the Humber Mental Health Network

The TEWV Evaluation, Demonstrating the Savings Aimee Fox & Sebastian Hinde, Research Fellows University of York

Evaluation of Core24

Crisis and Liaison Network 7th March 2018

Aimée Fox Laura Bojke Gerry Richardson Sebastian Hinde

Executive Summary

• Assess the cost-effectiveness of the Core24 mental health liaison service in York

compared to the pre Core24 service.

• Individual level, anonymised, administrative data from the Vale of York

Commissioning Group and York Teaching Hospital Foundation Trust.

• Interrupted Time Series Analysis to assess impact of Core24 on identified key metrics

and associated costs.

• Within the study period, Core24 significantly begins to reduce A&E attendances and

associated costs along with significantly reducing length of hospital stay and subsequent costs.

• Despite evaluating an incomplete service with limited data post-intervention, a

significant effect of Core24 is reported.

National Evidence

• Previous evidence suggests an effective liaison psychiatry service can

promote positive cost-savings

– RAID model in Birmingham : £4-£6 million potential cost-savings per annum – LSE evaluation of RAID model in Birmingham: £3.55 million – Acute Hospital Liaison Service evaluation in Durham and Darlington: £3.1 per annum

• Cost-savings

– Reduced LOS – Admission avoidance – Reduced re-admissions

• Differences in evaluations

– Follow-up period – Full service evaluation – Methodology

Context

• Impact of Core 24 on admissions performance (ED attendances, ED

attendances admitted to hospital, ED attendances who re-attended 2+ times)

– Calculate cost-savings realised from reduced admissions

• Impact of Core 24 on reduced length of stay

– Calculate cost-savings realised in reduced bed days

• Return to usual place of residence

– Identify reduced number of patients admitted from hospital into care home settings or from residential to nursing care

Data

• ED attendance and inpatient admissions data for

patients with a MH diagnosis between April 2015 and October 2017

• ED attendances
• ED attendances admitted to

hospital

• Hospital admissions
• Length of stay
• Return to usual place of

residence

• ED re-attenders
• Hospital re-admissions

• Data cleaning
• Separated data into 3 distinct datasets:
• 1. ED attendances only: contains ED attendances. Patients treated in ED and subsequently

discharged

• 2. IP admissions only: contains patients who were admitted to hospital through another pathway
• ther than through the ED
• 3. ED + IP: includes ED attenders who were subsequently admitted to hospital
• Analysis so far……

– Impact of Core24 on ED attendances and subsequent costs – Impact of Core24 on IP admissions, Length of Stay (LOS) and subsequent cost – Impact of Core24 on ED attenders being admitted to hospital

• Next analysis…….

– Impact of Core24 on cost of ED attenders being admitted to hospital – Impact of Core24 on return to usual place of residence

Work to date………

• ED attendances (1st April 2015 – 26th September 2017)
• 8104 observations
• IP admissions (1st April 2015 to 30th October 2017)
• 1803 observations
• ED + IP (1st April 2015 – 26th September 2017)
• 472 observations

Dataset description

(Sample size and dates)

Methods

• Interrupted Time Series Analysis was used to assess the impact of Core24 on identified outcomes. In an ITSA, an
• utcome is observed over multiple equally spaced time-points before and after the introduction of an intervention

that is expected to interrupt its level or trend.

• ITSA Example (Linden and Arbor, 2015)
• To assess the impact of an increase in

cigarette tax per pack and anti-smoking campaigns in 1989.

• Vertical line at 1989 represents time of

intervention.

• Extrapolate the slope pre-intervention

(Counterfactual)

Methods

• ITSA allows us to:

– specify the outcome variable, – Identify the time period in which the intervention was introduced, – produce a line plot of the predicted outcome variable combined with a scatter plot of the actual values of the

• utcome variable over time

– provide post-treatment trend estimates. – account for trends in seasonality

• Given the nature of our data, we conducted separate analyses on the impact of Core24 on ED attendance, IP

admission, LOS and associated costs

• Data is in weeks

– ED: 130 weeks in total: pre-Core24 105 weeks, Core24 1 week (week 106), post Core24 24 weeks. – IP: 134 weeks in total: pre-Core24 105 weeks, Core24 1 week (week 106), post-Core24 28 weeks.

• Costs

– HRG codes – NHS reference costs – Core24 costs (Monthly staff costs from April 2017 to October 2017)

• Total cost over this period = £455,794
• Average monthly cost = £65,113

ED attendance description n = 8104

4611 57% 3490 43%

Age category <15 16 to 24 25 to 39 40 to 64 >65 ED attendances 606 (7%) 2704 (33%) 2112 (26%) 2201 (27%) 481 (6%)

Patient type 1st time attenders: 7717 (95%) Follow-up (planned): 48 (1%) Follow-up (unplanned: 339 (4%) Source of referral Emergency service: 4541 (56%) Self-referral: 2263 (28%) Average age = 34 years ED attenders by age category

ED attendance description n = 8104

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+ Psychiatric condition 3030 (100.00) 184 (6.07%) 1016 (33.53%) 798 (26.34%) 823 (27.16%) 209 (6.90%) Poisoning 1458 (100.00%) 147 (10.08%) 434 (29.77%) 411 (28.19%) 361 (24.76%) 105 (7.20%) Poisoning, other incl. alcohol 1167 (100.00%) 44 (3.77%) 499 (42.76%) 237 (20.31%) 323 (27.68%) 64 (5.48%) Poisoning w/ proprietary drug 1146 (100.00%) 181 (15.79%) 474 (41.36%) 256 (22.34%) 201 (17.54%) 34 (2.97%) Poisoning w/ prescription drugs 484 (100.00%) 35 (7.23%) 187 (38.64%) 134 (27.69%) 116 (23.97%) 12 (2.48%) ED attenders’ primary diagnosis by age category

ED attendance description n = 8104

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+ Psychiatric condition 3030 (100.00) 184 (6.07%) 1016 (33.53%) 798 (26.34%) 823 (27.16%) 209 (6.90%) Poisoning 1458 (100.00%) 147 (10.08%) 434 (29.77%) 411 (28.19%) 361 (24.76%) 105 (7.20%) Poisoning, other incl. alcohol 1167 (100.00%) 44 (3.77%) 499 (42.76%) 237 (20.31%) 323 (27.68%) 64 (5.48%) Poisoning w/ proprietary drug 1146 (100.00%) 181 (15.79%) 474 (41.36%) 256 (22.34%) 201 (17.54%) 34 (2.97%) Poisoning w/ prescription drugs 484 (100.00%) 35 (7.23%) 187 (38.64%) 134 (27.69%) 116 (23.97%) 12 (2.48%) ED attenders’ primary diagnosis by age category

ED attendance description n = 8104

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+ Psychiatric condition 3030 (100.00) 184 (6.07%) 1016 (33.53%) 798 (26.34%) 823 (27.16%) 209 (6.90%) Poisoning 1458 (100.00%) 147 (10.08%) 434 (29.77%) 411 (28.19%) 361 (24.76%) 105 (7.20%) Poisoning, other incl. alcohol 1167 (100.00%) 44 (3.77%) 499 (42.76%) 237 (20.31%) 323 (27.68%) 64 (5.48%) Poisoning w/ proprietary drug 1146 (100.00%) 181 (15.79%) 474 (41.36%) 256 (22.34%) 201 (17.54%) 34 (2.97%) Poisoning w/ prescription drugs 484 (100.00%) 35 (7.23%) 187 (38.64%) 134 (27.69%) 116 (23.97%) 12 (2.48%) ED attenders’ primary diagnosis by age category

ED attendance description n = 8104

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+ Psychiatric condition 3030 (100.00) 184 (6.07%) 1016 (33.53%) 798 (26.34%) 823 (27.16%) 209 (6.90%) Poisoning 1458 (100.00%) 147 (10.08%) 434 (29.77%) 411 (28.19%) 361 (24.76%) 105 (7.20%) Poisoning, other incl. alcohol 1167 (100.00%) 44 (3.77%) 499 (42.76%) 237 (20.31%) 323 (27.68%) 64 (5.48%) Poisoning w/ proprietary drug 1146 (100.00%) 181 (15.79%) 474 (41.36%) 256 (22.34%) 201 (17.54%) 34 (2.97%) Poisoning w/ prescription drugs 484 (100.00%) 35 (7.23%) 187 (38.64%) 134 (27.69%) 116 (23.97%) 12 (2.48%) ED attenders’ primary diagnosis by age category

ED attendance description n = 8104

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+ Psychiatric condition 3030 (100.00) 184 (6.07%) 1016 (33.53%) 798 (26.34%) 823 (27.16%) 209 (6.90%) Poisoning 1458 (100.00%) 147 (10.08%) 434 (29.77%) 411 (28.19%) 361 (24.76%) 105 (7.20%) Poisoning, other incl. alcohol 1167 (100.00%) 44 (3.77%) 499 (42.76%) 237 (20.31%) 323 (27.68%) 64 (5.48%) Poisoning w/ proprietary drug 1146 (100.00%) 181 (15.79%) 474 (41.36%) 256 (22.34%) 201 (17.54%) 34 (2.97%) Poisoning w/ prescription drugs 484 (100.00%) 35 (7.23%) 187 (38.64%) 134 (27.69%) 116 (23.97%) 12 (2.48%) ED attenders’ primary diagnosis by age category

IP admissions description n= 1803

Age Categories Total <15 16 to 24 25 to 39 40 to 64 65+ IP Admissions 1803 (100%) 94 (5.21%) 86 (4.77%) 144 (7.99%) 428 (23.74%) 1051 (58.29% )

Source of admission: Usual place of residence 1754 (97%) Discharge destination: Usual place of residence 1531 (85%) Average LOS: 10 days (min 1, max 223) Average age = 65 years IP admissions by age category

IP admissions description n= 1803

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+ Delirium unspecified 377 (100%) 4 (1.06%0 1 (0.27%) 2 (0.53%) 12 (3.18%) 358 (94.96) Alcohol, withdrawal state 263 (100%) 4 (1.52%) 51 (19.39%) 180 (68.44%) 28 (10.65%) Dementia unspecified 248 (100%) 1 (0.40%) 4 (1.61%) 243 (97.98%) Anxiety disorder, unspecified 128 (100%) 9 (7.03%) 9 (7.03%) 22 (17.19%) 37 (28.91%) 51 (39.84%) Vascular dementia 83 (100%) 1 (1.2%) 82 (98.80%) Inpatient primary diagnosis by age

IP admissions description n= 1803

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+ Delirium unspecified 377 (100%) 4 (1.06%0 1 (0.27%) 2 (0.53%) 12 (3.18%) 358 (94.96) Alcohol, withdrawal state 263 (100%) 4 (1.52%) 51 (19.39%) 180 (68.44%) 28 (10.65%) Dementia unspecified 248 (100%) 1 (0.40%) 4 (1.61%) 243 (97.98%) Anxiety disorder, unspecified 128 (100%) 9 (7.03%) 9 (7.03%) 22 (17.19%) 37 (28.91%) 51 (39.84%) Vascular dementia 83 (100%) 1 (1.2%) 82 (98.80%) Inpatient primary diagnosis by age

IP admissions description n= 1803

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+ Delirium unspecified 377 (100%) 4 (1.06%0 1 (0.27%) 2 (0.53%) 12 (3.18%) 358 (94.96) Alcohol, withdrawal state 263 (100%) 4 (1.52%) 51 (19.39%) 180 (68.44%) 28 (10.65%) Dementia unspecified 248 (100%) 1 (0.40%) 4 (1.61%) 243 (97.98%) Anxiety disorder, unspecified 128 (100%) 9 (7.03%) 9 (7.03%) 22 (17.19%) 37 (28.91%) 51 (39.84%) Vascular dementia 83 (100%) 1 (1.2%) 82 (98.80%) Inpatient primary diagnosis by age

IP admissions description n= 1803

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+ Delirium unspecified 377 (100%) 4 (1.06%0 1 (0.27%) 2 (0.53%) 12 (3.18%) 358 (94.96) Alcohol, withdrawal state 263 (100%) 4 (1.52%) 51 (19.39%) 180 (68.44%) 28 (10.65%) Dementia unspecified 248 (100%) 1 (0.40%) 4 (1.61%) 243 (97.98%) Anxiety disorder, unspecified 128 (100%) 9 (7.03%) 9 (7.03%) 22 (17.19%) 37 (28.91%) 51 (39.84%) Vascular dementia 83 (100%) 1 (1.2%) 82 (98.80%) Inpatient primary diagnosis by age

IP admissions description n= 1803

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+ Delirium unspecified 377 (100%) 4 (1.06%0 1 (0.27%) 2 (0.53%) 12 (3.18%) 358 (94.96) Alcohol, withdrawal state 263 (100%) 4 (1.52%) 51 (19.39%) 180 (68.44%) 28 (10.65%) Dementia unspecified 248 (100%) 1 (0.40%) 4 (1.61%) 243 (97.98%) Anxiety disorder, unspecified 128 (100%) 9 (7.03%) 9 (7.03%) 22 (17.19%) 37 (28.91%) 51 (39.84%) Vascular dementia 83 (100%) 1 (1.2%) 82 (98.80%) Inpatient primary diagnosis by age

IP admissions description n= 1803

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+ Delirium unspecified 377 (100%) 4 (1.06%0 1 (0.27%) 2 (0.53%) 12 (3.18%) 358 (94.96) Alcohol, withdrawal state 263 (100%) 4 (1.52%) 51 (19.39%) 180 (68.44%) 28 (10.65%) Dementia unspecified 248 (100%) 1 (0.40%) 4 (1.61%) 243 (97.98%) Anxiety disorder, unspecified 128 (100%) 9 (7.03%) 9 (7.03%) 22 (17.19%) 37 (28.91%) 51 (39.84%) Vascular dementia 83 (100%) 1 (1.2%) 82 (98.80%) Inpatient primary diagnosis by age

IP admissions description n= 1803

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+ Delirium unspecified 377 (100%) 4 (1.06%0 1 (0.27%) 2 (0.53%) 12 (3.18%) 358 (94.96) Alcohol, withdrawal state 263 (100%) 4 (1.52%) 51 (19.39%) 180 (68.44%) 28 (10.65%) Dementia unspecified 248 (100%) 1 (0.40%) 4 (1.61%) 243 (97.98%) Anxiety disorder, unspecified 128 (100%) 9 (7.03%) 9 (7.03%) 22 (17.19%) 37 (28.91%) 51 (39.84%) Vascular dementia 83 (100%) 1 (1.2%) 82 (98.80%) Inpatient primary diagnosis by age

Admitted ED attendances description n = 472

255 54% 217 46%

Average age = 44 years

Age category <15 16 to 24 25 to 39 40 to 64 >65 ED attendances 16 (3.39%) 35 (7.42%) 130 (27.54%) 242 (51.27%) 49 (10.38%)

ED attenders by age category Patient type 1st time attenders: 458 (97%) Follow-up (unplanned: 14 (3%) Average LOS: 2 days (min 1, max 68)

Admitted ED attendances description n = 472

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+

Alcohol, withdrawal state 262 (100.00%) 3 (1.15%) 82 (31.30%) 165 (62.98%) 12 (4.58%) Acute intoxication 72 (100.00%) 6 (8.33%) 15 (20.83%) 16 (22.22%) 28 (38.89%) 7 (9.72%) Anxiety disorder, unspecified 23 (100.00%) 2 (8.70%) 4 (17.39%) 4 (17.39%) 4 (17.39%) 9 (39.13%) Depressive episode 14 (100.00%) 1 (7.14%) 4 (28.57%) 2 (14.2950 3 (21.43%) 4 (28.57%)

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+ Social problem including homelessness and alcohol 174 (100.00)

1 (0.57%) 48 (27.59%) 111 (63.79%) 14 (8.05%)

CNS condition, other than epilepsy 108 (100.00%) 2 (1.85) 32 (29.63%) 71 (65.74%) 3 (2.78%) Psychiatric condition 89 (100.00%) 9 (10.11%) 16 (17.98%) 20 (22.47%) 21 (23.60%) 23 (25.84%)

Poisoning, other including alcohol

73 (100.00%) 7 (9.59%) 12 (16.44%) 17 (23.29%) 31 (42.47%) 6 (8.22%) Poisoning 11 100.00%) 2 (18.18%) 3 (27.27%) 3 (27.27%) 3 (27.27%)

Primary Diagnosis for ED attendance by age category Primary Diagnosis for IP admissions by age category

Admitted ED attendances description n = 472

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+

Alcohol, withdrawal state 262 (100.00%) 3 (1.15%) 82 (31.30%) 165 (62.98%) 12 (4.58%) Acute intoxication 72 (100.00%) 6 (8.33%) 15 (20.83%) 16 (22.22%) 28 (38.89%) 7 (9.72%) Anxiety disorder, unspecified 23 (100.00%) 2 (8.70%) 4 (17.39%) 4 (17.39%) 4 (17.39%) 9 (39.13%) Depressive episode 14 (100.00%) 1 (7.14%) 4 (28.57%) 2 (14.2950 3 (21.43%) 4 (28.57%)

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+ Social problem including homelessness and alcohol 174 (100.00)

1 (0.57%) 48 (27.59%) 111 (63.79%) 14 (8.05%)

CNS condition, other than epilepsy 108 (100.00%) 2 (1.85) 32 (29.63%) 71 (65.74%) 3 (2.78%) Psychiatric condition 89 (100.00%) 9 (10.11%) 16 (17.98%) 20 (22.47%) 21 (23.60%) 23 (25.84%)

Poisoning, other including alcohol

73 (100.00%) 7 (9.59%) 12 (16.44%) 17 (23.29%) 31 (42.47%) 6 (8.22%) Poisoning 11 100.00%) 2 (18.18%) 3 (27.27%) 3 (27.27%) 3 (27.27%)

Primary Diagnosis for ED attendance by age category Primary Diagnosis for IP admissions by age category

Admitted ED attendances description n = 472

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+

Alcohol, withdrawal state 262 (100.00%) 3 (1.15%) 82 (31.30%) 165 (62.98%) 12 (4.58%) Acute intoxication 72 (100.00%) 6 (8.33%) 15 (20.83%) 16 (22.22%) 28 (38.89%) 7 (9.72%) Anxiety disorder, unspecified 23 (100.00%) 2 (8.70%) 4 (17.39%) 4 (17.39%) 4 (17.39%) 9 (39.13%) Depressive episode 14 (100.00%) 1 (7.14%) 4 (28.57%) 2 (14.2950 3 (21.43%) 4 (28.57%)

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+ Social problem including homelessness and alcohol 174 (100.00)

1 (0.57%) 48 (27.59%) 111 (63.79%) 14 (8.05%)

CNS condition, other than epilepsy 108 (100.00%) 2 (1.85) 32 (29.63%) 71 (65.74%) 3 (2.78%) Psychiatric condition 89 (100.00%) 9 (10.11%) 16 (17.98%) 20 (22.47%) 21 (23.60%) 23 (25.84%)

Poisoning, other including alcohol

73 (100.00%) 7 (9.59%) 12 (16.44%) 17 (23.29%) 31 (42.47%) 6 (8.22%) Poisoning 11 100.00%) 2 (18.18%) 3 (27.27%) 3 (27.27%) 3 (27.27%)

Primary Diagnosis for ED attendance by age category Primary Diagnosis for IP admissions by age category

Admitted ED attendances description n = 472

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+

Alcohol, withdrawal state 262 (100.00%) 3 (1.15%) 82 (31.30%) 165 (62.98%) 12 (4.58%) Acute intoxication 72 (100.00%) 6 (8.33%) 15 (20.83%) 16 (22.22%) 28 (38.89%) 7 (9.72%) Anxiety disorder, unspecified 23 (100.00%) 2 (8.70%) 4 (17.39%) 4 (17.39%) 4 (17.39%) 9 (39.13%) Depressive episode 14 (100.00%) 1 (7.14%) 4 (28.57%) 2 (14.2950 3 (21.43%) 4 (28.57%)

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+ Social problem including homelessness and alcohol 174 (100.00)

1 (0.57%) 48 (27.59%) 111 (63.79%) 14 (8.05%)

CNS condition, other than epilepsy 108 (100.00%) 2 (1.85) 32 (29.63%) 71 (65.74%) 3 (2.78%) Psychiatric condition 89 (100.00%) 9 (10.11%) 16 (17.98%) 20 (22.47%) 21 (23.60%) 23 (25.84%)

Poisoning, other including alcohol

73 (100.00%) 7 (9.59%) 12 (16.44%) 17 (23.29%) 31 (42.47%) 6 (8.22%) Poisoning 11 100.00%) 2 (18.18%) 3 (27.27%) 3 (27.27%) 3 (27.27%)

Primary Diagnosis for ED attendance by age category Primary Diagnosis for IP admissions by age category

Admitted ED attendances description n = 472

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+

Alcohol, withdrawal state 262 (100.00%) 3 (1.15%) 82 (31.30%) 165 (62.98%) 12 (4.58%) Acute intoxication 72 (100.00%) 6 (8.33%) 15 (20.83%) 16 (22.22%) 28 (38.89%) 7 (9.72%) Anxiety disorder, unspecified 23 (100.00%) 2 (8.70%) 4 (17.39%) 4 (17.39%) 4 (17.39%) 9 (39.13%) Depressive episode 14 (100.00%) 1 (7.14%) 4 (28.57%) 2 (14.2950 3 (21.43%) 4 (28.57%)

Primary Diagnosis Total <15 16 to 24 25 to 39 40 to 64 65+ Social problem including homelessness and alcohol 174 (100.00)

1 (0.57%) 48 (27.59%) 111 (63.79%) 14 (8.05%)

CNS condition, other than epilepsy 108 (100.00%) 2 (1.85) 32 (29.63%) 71 (65.74%) 3 (2.78%) Psychiatric condition 89 (100.00%) 9 (10.11%) 16 (17.98%) 20 (22.47%) 21 (23.60%) 23 (25.84%)

Poisoning, other including alcohol

73 (100.00%) 7 (9.59%) 12 (16.44%) 17 (23.29%) 31 (42.47%) 6 (8.22%) Poisoning 11 100.00%) 2 (18.18%) 3 (27.27%) 3 (27.27%) 3 (27.27%)

Primary Diagnosis for ED attendance by age category Primary Diagnosis for IP admissions by age category

Did Bootham have an impact on ED attendances?

Before presenting the results……

• There was discussion on whether the closure of Bootham in October

2015 impacted on the number of ED attendances in York.

• If we interrupt the time series at the point of Bootham closure, ITSA

reports NO significant impact on ED attendances

Results

• ITSA output reporting the impact of

Core24 on:

– Number of ED attendances and costs – Number of ED patients admitted to hospital – Number of IP admissions and costs – Average LOS and costs

Results (Impact of Core24 on total number of ED attendances)

Variable Coefficient Standard Error P value 95% CI Intercept (β0) 60.33 1.96 0.000 56.46 – 64.21 Baseline trend (β1) 0.03 0.03 0.380

• 0.03 – 0.09

Change in level after Core24 (β2) 12.49 3.87 0.002 4.82 – 20.15 Change in trend after Core24 (β3)

• 0.93

0.30 0.002

• 1.52 – -0.34

Post-trend output

• 0.91

0.30 0.003

• 1.49 – -0.32
• Significant increase in

ED attendances after the launch of Core24 (β2) coupled with a significant decrease in the slope of the regression (β3).

• Core24 is having a

significant impact on ED attendances

• Results predict that

CORE24 began to reduce ED attendances at week 120. (14 weeks after CORE24 funding was secured).

Results (Impact of Core24 on Total ED costs)

Variable Coefficient Standard Error P value 95% CI Intercept (β0) 8705.78 306.50 0.000 8099.22 – 9312.34 Baseline trend (β1) 9.42 4.76 0.050

• 0.00 – 18.83

Change in level after Core24 (β2) 2334.48 564.64 0.000 1217.07 – 3451.89 Change in trend after Core24 (β3)

• 153.08

42.48 0.000

• 237.14 - -69.01

Post-trend output

• 143.66

42.21 0.000

• 227.20 - -60.12
• Significant increase in

ED costs after the launch of Core24 (β2) followed by a significant decrease (β3) in the slope of the regression line.

• Core24 is having an
• verall significant

impact on total ED costs.

• Results predict that

CORE24 began to reduce total ED costs at week 122 (16 weeks after CORE24 funding was secured)

Results (Impact of Core24 on admitted ED attendances)

Variable Coefficient Standard Error P value 95% CI Intercept (β0) 4.20 0.42 0.000 3.37 – 5.03 Baseline trend (β1)

• 0.01

0.01 0.133

• 0.02 – 0.00

Change in level after Core24 (β2) 0.89 0.63 0.156

• 0.35 – 2.13

Change in trend after Core24 (β3) 0.00 0.04 0.990

• 0.08 – 0.81

Post-trend output

• 0.01

0.04 0.819

• 0.09 – 0.07
• No overall significant

impact of Core24 on number of ED attendances admitted to hospital.

Impact of Core24 on average ED costs

• ITSA to estimate impact of Core24 on average ED costs per week
• No significant findings
• Shows that the decrease in total ED costs is due to the Core24

service and not as a result of patient case-mix.

• ITSA graphics/output available on request.

Results (Impact of Core24 on IP admissions)

Variable Coefficient Standard Error P value 95% CI Intercept (β0) 12.77 0.72 0.000 11.34 – 14.19 Baseline trend (β1) 0.01 0.01 0.536

• 1.98 – 0.03

Change in level after Core24 (β2) 1.16 1.59 0.468

• 1.98 – 4.29

Change in trend after Core24 (β3) 0.01 0.10 0.905

• 0.19 – 0.21

Post-trend output 0.02 0.10 0.849

• 0.18 – 0.22
• No overall significant

impact of Core24 on number of IP admissions.

• Expected given type of

patient included in this analysis.

Results (Impact of Core24 on IP costs)

Variable Coefficient Standard Error P value 95% CI Intercept (β0) 37424.65 2354.59 0.000 32766.03 – 42083.27 Baseline trend (β1) 33.62 36.89 0.364

• 39.36 – 106.60

Change in level after Core24 (β2) 9540.84 5378.63 0.078

• 1100.92 – 20182.60

Change in trend after Core24 (β3)

• 98.17

316.92 0.757

• 725.21 – 528.87

Post-trend output

• 64.55

314.77 0.8378

• 687.33 – 558.23
• No overall significant

impact of Core24 on IP costs.

Results (Impact of Core24 on average LOS)

Variable Coefficient Standard Error P value 95% CI Intercept (β0) 12.42 1.40 0.000 9.64 – 15.19 Baseline trend (β1)

• 0.03

0.02 0.209

• 0.07 – 0.01

Change in level after Core24 (β2) 3.37 1.75 0.056

• 0.09 – 6.84

Change in trend after Core24 (β3)

• 0.18

0.08 0.021

• 0.32 – -0.03

Post-trend output

• 0.20

0.07 0.006

• 0.34 - -0.06
• Significant decrease in

average LOS after launch of Core24 (β3).

• Core24 is having a

significant impact on average LOS

• Results predict that

CORE24 began to reduce average LOS at week 124 (18 weeks after CORE24 funding was secured)

Results (Impact of Core24 on average LOS cost)

Variable Coefficient Standard Error P value 95% CI Intercept (β0) 2996.027 326.81 0.000 2349.42 – 3642.64 Baseline trend (β1)

• 4.45

4.78 0.333

• 14.10 – 4.81

Change in level after Core24 (β2) 699.73 417.31 0.096

• 125.92 –

1525.39 Change in trend after Core24 (β3)

• 42.88

17.47 0.015

• 77.44 - -8.32

Post-trend output

• 47.52

16.80 0.005

• 80.77 - -14.28
• Significant decrease

in average LOS costs following the launch of Core24 team (β3)

• Core24 has an overall

significant impact on average LOS costs

• Results predict that

CORE24 began to reduce average LOS costs at week 126 (20 weeks after CORE24 funding was secured)

Discussion

Limitations

– Evaluating an incomplete service – Lack of data post-intervention – Lack of comparator area – Relatively crude cost estimation – Selection of patients

Strengths

– Robust methodology – Repeatability of analysis – Speed of the evaluation of recent data

What’s next?

– Finalise ED + IP admissions dataset – Estimate the impact of Core24 on the cost ED +IP admissions – Return to usual place of residence – Additional data (+2 months post Core24) – Re-attenders (ED) and re-admissions (IP)

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Yorkshire and the Humber Mental Health Network

The TEWV Evaluation, Demonstrating the Savings Questions and Discussion

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Yorkshire and the Humber Mental Health Network

Group Work Session Assessment Paperwork

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Yorkshire and the Humber Mental Health Network

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