south yorkshire gpstp june 2013

Self Management, Multimorbidity, Shared Decision Making and Care Planning with People who have

Long Term Conditions

Nigel Mathers

Professor of Primary Medical Care, University of SheffieldVice Chair, Royal College of General Practitioners

South Yorkshire GPSTP

June 2013

Academic Unit of Primary

Medical Care

2

Long Term Conditions and Personalisation of Care

Background

”the ageing population and the increased prevalence of chronic diseases require a strong reorientation away from the current emphasis

on acute and episodic care towards prevention, self care, and care that is well-coordinated and

integrated.”

The King’s Fund, 2011

3

Shared Decision Making, Care Planning and the use of Patient Decision Aids

1. Long Term Conditions:

• 15.4m people in England have one or more long term conditions (LTCs) • Utilisation of health services is high amongst the LTC group – they account for 30% of the population, but 70% of NHS spending (c. £70bn)• The number of people with multiple conditions is projected to increase and this will put pressure on NHS budgets • LTCs are strongly linked to health and economic inequalities• While the majority of people with LTCs are elderly by no means all

The person who lives with an LTC:

Day to day management is self management

Our grossly underutilized workforce: [people who live with LTCs]

2. Self management; many tasks, many challenges

The domains of self management:

My condition (Biological)

What I do(Social / Behavioural)

The way I feel (Psychological)

3. Patient Activation = knowledge, skills and confidence to manage one’s own health and healthcare

Knowledge(Biological)

Skills(Social / Behavioural)

Confidence(Psychological)

Strategies to support people on their ‘journey of activation’

Public services face unprecedented challenges

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0% 20% 40% 60% 80% 100%

Depression

Schizophrenia/bipolar

Anxiety

Dementia

Asthma

Epilepsy

Cancer

Hypertension

COPD

Diabetes

Painful condition

Coronary heart disease

Atrial fibrillation

Stroke/TIA

Heart failure

Percentage of patients with each condition who have other conditionsThis condition only This condition + 1 other + 2 others + 3 or more others

The commonest long term condition is:

Multiple long term conditions

11


4. Multimorbidity and Long Term Conditions:

The Picture in Scotland• Clinical data from 310 Scottish general practices for 1,754,133 registered patients was provided by the Primary Care Clinical Informatics Unit (“PCCIU data”)

• Clinical data from 40 Scottish general practices linked to hospital admissions data (“ISD and PCCIU data”)

•Stewart Mercer, Professor of Primary Care Research, University of Glasgow: SSPC National Lead for Multimorbidity Research [email protected]•Bruce Guthrie, Professor of Primary Care Medicine, University of Dundee: Living Well with Multimorbidity Epidemiology work-stream lead [email protected] •Sally Wyke, Professor of Interdisciplinary Research, University of Glasgow: [email protected]

mailto:[email protected]



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Multimorbidity and Long Term Conditions


How they relate

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Multimorbidity and Hospital Admissions

3 59 14 21

3447

6485

100

151

20

3151

74

115

151

200

242

318

342

479

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100

200

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400

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600

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per

100

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tien

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No of conditions

Potentially preventable admission

Other emergency admissions

15


5. Shared Decision Making

Shared decision Making is ‘a process in which clinicians and patients work together to select tests, treatments, management or support packages, based on clinical evidence and the patient’s informed preferences.

It involves the provision of evidence-based information about options, outcomes and uncertainties, together with decision support counselling and a system for recording and implementing patients’ informed preferences.’

Coulter A and Collins A. 2011. Making shared decision-making a reality: no decision about me, without me [pdf] London. The Kings Fund. Available at http://www.kingsfund.org.uk/publications/nhs_decisionmaking.html [Accessed 25 April 2012]

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Shared Decision Making

NHS patient Surveys (2002-9)

46-49% patients want more involvement in treatmentdecisions

20101 in 3 patients in Primary Care1 in 2 patients in Hospital

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Benefits of Shared Decision Making

Better ConsultationsClearer Risk CommunicationImproved Health LiteracyMore Appropriate DecisionsFewer Unwanted TreatmentsHealthier LifestylesImproved Confidence and Self-efficacySafer CareReduced CostsBetter Health Outcomes

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6. What are Patient Decision Aids (PDAs)?

• Evidence base for treatment options• Clarification of people’s values• Systematic guidance to inform decisions


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The PANDAs decision aid:• For doctors and nurses in General Practice• For people with Type 2 diabetes (T2DM) who are making treatment choices

Purpose of the study:To determine the clinical effectiveness of the PANDAs decision aid.

Primary Research Question:

“Does the use of the PANDAs decision aid improve decision quality in patients with T2DM who are making decisions whether or not to start insulin in General Practice?”

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METHODS [1]

Design: A cluster randomised controlled trial

Intervention:• Brief training of clinicians• Pre-consultation familiarisation with the PDA • Use of PDA by patients and clinicians in the consultation

Control: • Usual care (no PDA)

Participants:175 people with T2DM from 49 General Practices randomised into intervention (n=25) and control (n=24) groups.

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METHODS [2]

Inclusion criteria:

Practices:• >4 partners• List size >7,000• T2DM > 1% of Practice population

Patients:• People with T2DM (age >21) taking at least 2 oral glucose-lowering drugs at maximum tolerated dose• Most recent HbA1c >7.4% (>57 mmols/mol) or • Advised in preceding 6 months to add or consider changing to insulin

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METHODS [3]Outcome measures and follow-up:

Primary outcome measure: • Decisional conflict based on the Decisional Conflict Scale score (indicator of decision quality)

Secondary outcome measures• Knowledge: which treatment option most effective in reducing blood glucose and diabetic complications?• Realistic expectations: self-report of chances of experiencing hypoglycaemia, gaining weight and developing complications• Preference option: preferred treatment of initiating insulin, adhering more to diabetes advice, or making no change• Participation in decision making (Control Preference Scale)• Regret: for decision made (Regret Scale)

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Intervention Control

Number of Practices 25 24

List Size 7,510 (3,129-20,900) 7,325 (1,974-13,500)

People with diabetes 350(96-912) 356 (143-634)

No of partners 5 (1-13) 5 (2-10)

No of practice nurses 3 (1-6) 3 (1-5)

IMD* score 30.35 (range 8.9 - 59.5) 30.20 (range 6.5 - 55)

Study practice profile (mean and range)

*Index of Multiple Deprivation

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Make No Change

Follow the diabetes

advice more regularly

Start insulin I am not sure

Total

Control 33 (42.3%) 29 (37.1%) 9 (11.5%) 7 (9%) 78

Intervention 32 (34.7%) 38 (41.3 %) 17 (18.4%) 5 (5.4%) 92

Total 65 67 26 12 170

(X23=2.88, p =0.410 )

Preferred choices of patients in intervention and control groups post-consultation

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Intervention Control Mean difference in

HbA1cunadjusted

Mean difference in

HbA1cadjusted*

95% CI

8.64 (SD 1.37) 8.40 (SD 1.31) 0.244 0.351 -0.088 to 0.789

* adjusted for age, education, gender, baseline HbA1c, insulin status and clustering. P=0.117

The effect of the PANDAs decision aid on HbA1c at 6 months

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How did you make your decision about your diabetes treatment?(n = 169)

Passive Collaborative Autonomous Total

Control 16 (21%) 28 (36%) 33 (43%) 77 (100%)

Intervention 8 (9%) 25 (27%) 59 (64%) 92 (100%)

(X2=8.9, df=2, p=0.012)

Decision making roles of patients in the intervention and control groups, post consultation with their doctor/nurse

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CONCLUSIONS

In people with diabetes who are making treatment choices in General Practice, use of the PANDAs decision aid:

• Reduces decisional conflict• Improves knowledge• Promotes realistic expectations• Promotes autonomy

without prolonging consultation time

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The Richmond Group of Charities

Principles:

1. Co-ordinated care

Desired outcomes: people feel that the care they receive is seamless because it is organised around them and their needs.

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Principles:

2. Patients engaged in decisions about their care

Desired outcomes: all patients and carers can take anactive role in decisions about their care and treatmentbecause they are given the right opportunities, information and support.

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Principles:

3. Supported self-management

Desired outcomes: people with long term conditions canmanage their condition appropriately because they havethe right opportunities, resources and support.

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7. What is Care Planning?

1.Prepared pro-active Practice team

2.Informed engagement by people in their own care

3.Partnership working between Doctors/Nurses [HCPs] and people with Long Term Conditions [LTCs]

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‘The House’ IT: Clinical record of care planning

& able to feed data into commissioning

Consultation skills/attitude

Integrated, multi-disciplinary team &

expertise

Senior buy-in & local champions to

support & role model

Emotional & psychological

support

Information/ structured education

‘Prepared’ for consultation

Identify and fulfill needs

Procured time for consultations, training and IT

Quality assure and measure

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Care Planning: the Sheffield experience (Stephenson, 2013)

Care fragmentation

R3


RCGP Care Planning Programme:

The Vision:

A joint strategic approach to health improvement based on the concerted implementation of care planning in general practice, within the context of multimorbidity,

and in partnership with a range of disease specific organisations; covering, for example, cardiovascular

conditions, respiratory and musculo-skeletal conditions and cancer.

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The RCGP Care Planning Programme

Aims:

• To embed care planning into the ‘core business’ of General Practice

• To incorporate the development of care planning skills into the GP training curriculum and facilitate other educational initiatives for established GPs.

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Long Term Conditions and Personalisation of CareThe RCGP Care Planning Programme:

Objectives:

• Communities of Practice ‘Natural Laboratories’Leadership facilitationActive Championing (“diffusion of innovation”)Primary Healthcare Team involvement

Service redesign/delivery models

• Learning and training resources (GP curriculum)

• Improvement research (evaluation)

• Development of IT/Metrics

• Communication strategy

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8. Practice Variation

Understanding variation: the bad and the good. Mulley, 2011

Bad Variation (care not evidence-based)

•Poor research professional uncertainty

•Poor knowledge professional ignorance

JAMA, 1988

Good Variation (care is patient-centered)

•Clinical differences among patients

•Personal differences among patients

If all variation were bad, it would be easy to stop it. What is difficult is reducing the bad variation while keeping the good.


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Practice variation: when there is little or no evidence

• When to order a diagnostic test…?

• How often to see a patient with chronic disease…?

• When to admit a patient to a hospital…?

• When to admit a patient to intensive care…?

• How long a patient should stay in the hospital…?


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Variation: decreasing the bad and increasing the goodMulley, 2011

Decreasing bad variation (making care evidence-based)

•Improve knowledge management

•Improve communication

•No avoidable ignoranceIncreasing good variation (making care patient-centered)

•Recognize clinical differences among patients

•Honor personal differences among patients

The only efficient way to reduce overuse, underuse, and misuse of care

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Patient ‘Empowerment’ [Personalisation of Care]

Long Term Conditions and Multimorbidity

Shared Decision Making (Patient Activation)

Use of Patient Decision Aids

Care Planning

Practice Variation

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It’s time for change!

Thank You

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Questions?

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Clinical Practice variation

J Allison Glover, 1874-1963

1938:

•10-fold variation in tonsillectomy

•8-fold risk of death with surgical treatment

•The response:•“…these strange bare facts of incidence…”•“… tendency for the operation to be performed for no particular reason and no particular result.”•“…sad to reflect that many of the anesthetic deaths… were due to unnecessary operations.”


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John E. Wennberg, 1973


•17-fold variation in tonsillectomy

•6-fold variation in hysterectomy

•4-fold variation in prostatectomy

•“The need for assessing outcome of common medical practices”

•“Professional uncertainty and the problem of supplier-induced demand”

Clinical practice variation: it’s rediscovery by Wennberg

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The PANDAs Decision Aid contains the following information in line with the International Patient Decision Aid Standards criteria:

1. Information about insulin and other treatment optionsReasons for starting insulinThe procedure for insulin injectionCommon concerns about insulinTreatment options: Make no change; lifestyle

modification; insulin therapy

2. Presents probabilities of outcomesThe advantages and disadvantages of each option

are described in words, numbers and pictures (‘smiley faces’)

3. Patient value clarificationsA list of patients’ values about the advantages and

disadvantages of insulin therapy

4. Structured guidance

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Content of the PANDAs decision aid


METHODS [7]

Instruments

• Decisional Conflict Scale (DCS)16 item scale with 5 subscales: uncertainty, informed, values

clarity, support, effective decision

• Control Preference Scale (CPS)5 item scale: 2 items active role, 1 item shared role, 2 Items passive

role

• Regret Scale5 item scale: measures distress or remorse after a healthcare

decision

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METHODS [8]

Statistical Analysis

• Using total DCS score as primary outcome: total number of participants 86 and total cluster size 17• Outcome variables treated as continuous• Multiple regressions with generalised estimating equations (GEE) and exchangeable correlation to allow for clustering• Multiple logistic regression with GEE was used for binary outcomes in the secondary analysis• Analysis according to intention to treat principle

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Subscore Intervention Control Mean differenceunadjusted

Mean difference adjusted*

95% CIp value

Uncertainty 20.1 (16.6) 29.4 (20.8)

-9.29 -8.72 -14.9 to -2.53 p=0.006

Informed 18.1 (13.3) 26.0 (16.6)

-7.65 -8.69 -13.3 to -4.10 p<0.001

Values Clarity 16.7 (13.9) 26.7 (18.2)

-9.74 -9.84 -14.8 to -4.84p<0.001

Support 17.4 (13.1) 20.8 (15.3)

-3.41 -3.66 -8.58 to 1.25p=0.144

Effective Decision

16.1 (14.4) 23.3 (15.2)

-9.70 -9.80 -16.8 to 2.75p=0.006

Total Score 17.4 (12.6) 25.2 (14.9)

-7.67 -7.72 -12.5 to –2.97p<0.001

* adjusted for age, education and gender

Comparison of decisional conflict scores between the intervention and control groups (0=no decisional conflict, 100=maximum decisional conflict).

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Intervention Decision Aid

ControlUsual Care

UnadjustedOdds Ratio

Adjusted+ Odds Ratio (95% CI)

ICC p value

Knowledge

Number 95 80

Which choice has the greatest chance of lowering your blood sugar?

49(51.6%)

23(28.8%)

2.63 1.31 (1.14 to 1.50)

0.071 <0.001

Which choice has the greatest chance of lowering your complications?

29(30.5%)

23(28.8%)

1.09 1.20 (0.07 to 19.05) 0.202 0.90

Realistic expectations

If you take insulin, about how many times might you experience ‘hypos’ in a year?

77/95(81.0%)

4/75(5.2%)

77 ^ - <0.001*

If you take insulin, about how much more weight might you gain in a year?

67/95 (70.5%) 4/75 (5.3%) 42.5 - <0.001*

Out of 100 people like you who take insulin, how many may get complications in five years?

25/95 (26.3%) 4/80 (5%) ^ - <0.001*

+ adjusted for clustering, insulin initiation, age, gender and education level ^ Numbers answering correctly in the control group were too few to control for clustering.* Chi-squared p value

Secondary outcomes: Knowledge and realistic expectations (Questions answered correctly)

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Intervention Control Mean difference unadjusted

Mean difference adjusted*

p value

Regret Score 44.63 44.57 0.06 0.22(-2.48 to

2.93)

0.872

Persistence with chosen option

68.1% 56.3% 1.65† 1.17^

(1.00 to 1.36)

0.041

* adjusted for age, education, gender, baseline HbA1c, insulin status and clustering†Crude odds ratio ^Adjusted odds ratio

Comparison of the decision Regret Score and persistence with chosen option between the intervention and usual care groups after six months

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Acknowledgements:

Funding body: National Institute for Health Research (NIHR), Research for Patient Benefit Programme UK [PB-PG-0906-11248]

NIHR National Trials Register: 14842077

Sheffield Health and Social Care NHS Foundation Trust

Ethics permission: North Sheffield Research Ethics Committee (07/Q2308/53)

Expert specialist advice: Professor Simon Heller

Members of the PANDAs Advisory Group

Members of the Sheffield Diabetes UK Group

ALL DOCTORS, NURSES AND PEOPLE WITH DIABETES WHO PARTICIPATED IN THE PANDAs TRIAL

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SINGLE DISEASE SPECIFIC SOLUTIONS WILL NOT WORK

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Decision plane showing the distribution of simple consent, informed consent, and shared decision making within 4 types of medical decisions

Quadrant A: high risk, high certaintyConsent type: InformedShared decision making: absentInteraction: intermediate, enough for an adequately informed decisionExample: laparotomy for gunshot wound of abdomen

Quadrant B: high risk, low certaintyConsent type: InformedShared decision making: presentInteraction: extensive, including discussion of patient values, preferences, hopes and fearsExample: mastectomy or lumpectomy plus radiation for early breast cancer

Quadrant C: low risk, high certaintyConsent type: simpleShared decision making: absentInteraction: minimal or noneExample: lower diruetic dose for patient with low serum potassium level

Quadrant D: low risk, low certaintyConsent type: simpleShared decision making: presentInteraction: intermediateExample: lifestyle changes vs. medication for lyperlipidemia

Zone of informed consent

Zone of shared decision making

Combined zone

Certain(1 clear best choice)

Certainty Uncertain>2 alternatives

Ris

kH

Igh

Lo

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RCGP Care Planning Programme

Communities of Practice – Tasks

• Redesign the condition-specific pathway• Contribute to evaluation• Collect feedback and use agreed metrics• Develop local systems of project management• Medical ‘musts’ in multimorbidity• Determine resource use within/between Practices• Use agreed IT• Participate in learning sets• Develop and share local commissioning mechanisms

Shared decision making, care planning and the use of patient decision aids

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Context

• 15.4m people in England have one or more long term conditions (LTCs) • Utilisation of health services is high amongst the LTC group – they account for 30% of the population, but 70% of NHS spending (c. £70bn)• The number of people with multiple conditions is projected to increase and this will put pressure on NHS budgets • LTCs are strongly linked to health and economic inequalities• While the majority are elderly by no means all

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The Picture in Scotland• Clinical data from 310 Scottish general practices for 1,754,133 registered patients was provided by the Primary Care Clinical Informatics Unit (“PCCIU data”)

• Or clinical data from 40 Scottish general practices linked to hospital admissions data (“ISD and PCCIU data”)

•Stewart Mercer, Professor of Primary Care Research, University of Glasgow: SSPC National Lead for Multimorbidity Research [email protected]•Bruce Guthrie, Professor of Primary Care Medicine, University of Dundee: Living Well with Multimorbidity Epidemiology work-stream lead [email protected] •Sally Wyke, Professor of Interdisciplinary Research, University of Glasgow: [email protected]




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Multimorbidity and Hospital Admissions

3 59 14 21

3447

6485

100

151

20

3151

74

115

151

200

242

318

342

479

0

100

200

300

400

500

600

0 1 2 3 4 5 6 7 8 9 10+

Ann

ual a

dmis

sion

rate

per

100

0 pa

tien

ts

No of conditions

Potentially preventable admission

Other emergency admissions

72


Wagner, 2004

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‘The House’ IT: Clinical record of care planning

& able to feed data into commissioning

Consultation skills/attitude

Integrated, multi-disciplinary team &

expertise

Senior buy-in & local champions to

support & role model

Emotional & psychological

support

Information/ structured education

‘Prepared’ for consultation

Identify and fulfill needs

Procured time for consultations, training and IT

Quality assure and measure

74


Care Planning: the Sheffield experience (Stephenson, 2013)

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NHS Funding

arctic’ scenario: real funding cuts (-2 per cent for first three years, -1 per cent for second three years) ‘cold’ scenario: 0 per cent real growth in six years ‘tepid’ scenario: real increase (+2 per cent for first 3 years, then +3 per cent for the next three years).

Appleby J, Crawford R, Emmerson C. (2009) How cold will it be? http://www.kingsfund.org.uk/research/publications/ how_cold_will_it_be_html (Last accessed on 11 October 2009).

http://http/www.kingsfund.org.uk/research/publications/%20how_cold_will_it_be_html

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National QIPP Programme for LTC Personalisation

Risk profiling and stratification of risk Integrated community teams with single lead professional contact for Care Planning Transferring knowledge and control back to the patient

Enabled by Change in tariff moving to “A Year of Care”

Supported by Futures Forum report on Integration

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Principles:

1. Co-ordinated care

Desired outcomes: people feel that the care they receive is seamless because it is organised around them and their needs.

78


RCGP Care Planning Programme:

The Vision:

A joint strategic approach to health improvement based on the concerted implementation of care planning in general practice, within the context of multimorbidity,

and in partnership with a range of disease specific organisations; covering, for example, cardiovascular

conditions, respiratory and musculo-skeletal conditions and cancer.

79



Principles:

2. Patients engaged in decisions about their care

Desired outcomes: all patients and carers can take anactive role in decisions about their care and treatmentbecause they are given the right opportunities, information and support.

80



Principles:


Desired outcomes: people with long term conditions canmanage their condition appropriately because they havethe right opportunities, resources and support.

81


RCGP Care Planning Programme

Communities of Practice – Tasks

• Redesign the condition-specific pathway• Contribute to evaluation• Collect feedback and use agreed metrics• Develop local systems of project management• Medical ‘musts’ in multimorbidity• Determine resource use within/between Practices• Use agreed IT• Participate in learning sets• Develop and share local commissioning mechanisms

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RCGP Care Planning Consortium:

• British Heart Foundation• British Lung Foundation• Macmillan Cancer Support• Arthritis Research UK• King’s Fund• Health Foundation• Primary Care Rheumatology Society• Diabetes UK• RCGP

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SINGLE DISEASE SPECIFIC SOLUTIONS WILL NOT WORK

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How they relate

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Principles:

1.Co-ordinated Care

2.Patients engaged in decisions about their care


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Aims:

• To embed care planning into the ‘core business’ of General Practice

• To incorporate the development of care planning skills into the GP training curriculum and facilitate other educational initiatives for established GPs.

87



Objectives:

1. Build communities of Practice (‘Natural Laboratories’)• Leadership facilitation• Active Championing (“diffusion of innovation”)• Primary Healthcare Team involvement• Service redesign/delivery models

2. Develop a central reference (evaluation) group

• Learning and training resources (GP curriculum)• Improvement research (evaluation)• Development of IT/Metrics• Communication strategy

88


RCGP Care Planning Consortium:

• British Heart Foundation• British Lung Foundation• Macmillan Cancer Support• Arthritis Research UK• King’s Fund• Health Foundation• Primary Care Rheumatology Society• Diabetes UK• RCGP

Public services face unprecedented challenges

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0% 20% 40% 60% 80% 100%

Depression

Schizophrenia/bipolar

Anxiety

Dementia

Asthma

Epilepsy

Cancer

Hypertension

COPD

Diabetes

Painful condition

Coronary heart disease

Atrial fibrillation

Stroke/TIA

Heart failure

Percentage of patients with each condition who have other conditionsThis condition only This condition + 1 other + 2 others + 3 or more others

The commonest long term condition is:

Multiple long term conditions

Care fragmentation is the norm and waste is endemic

The person who lives with LTCs is the ultimate delivery mechanism:

Day to day management is self management

The development of the Patient Activation Measure

Other constructs • Locus of control• Self efficacy• Readiness to change

Tend to be used as predictors of individual behaviours and do not capture the broad range of knowledge, skills, beliefs and behaviours needed to manage LTCs

Patient Activation Measure: 22 items

Development of the PAM. Hibbard J et al. Health Services Research 2004; 39(4): 1009-1032

Impact of shared decision making: some examples

• Surgery for benign prostatic hyperplasia in the United States and United Kingdom

• Hysterectomy for benign uterine conditions in the United Kingdom

• Surgery and percutaneous intervention for coronary disease in Canada

• Surgery for back pain in the United States

• Surgery for hip and knee pain in Canada


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7% of population

14% of population


METHODS [3]

Intervention• Training of doctors and nurses (1-2 hours):• Principles of shared decision making• Importance and clinical effectiveness of decision aids• Evidence for treatment options in poorly controlled T2DM• Essential skills in risk communication

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METHODS [6]

Baseline data:• Practice and clinician profile• Patient sociodemography• Diabetes profile (duration, complications, prescription, glycaemic control)• Co-morbidities (hypertension, coronary artery disease, dyslipidaemia, chronic kidney disease)• Previous T2DM education

6 month follow-up data:• HbA1c• Regret score• Persistence with decision

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Shared Decision Making and Care Planning

Patient decision aids promote:

• Realistic expectations• Value decision concordance• Patient involvement in decision making

They also improve knowledge

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south yorkshire gpstp june 2013

Documents