Powerful analysis, influencing decisions 16 April, 2015 Commissioning Analysis and Intelligence Team...

Powerful analysis, influencing decisions18 April 2023

Commissioning Analysis and Intelligence Team

Kate Manton and Roger Halliday

Shared Decision MakingThe Evidence

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Powerful analysis, influencing decisions 218 April 2023

The aim of this paper is as a resource in making the evidence based case for shared decision making to the NHS. It outlines current expectations and performance, benefits of patient activation & interventions that drive this

1 Shared decision making: Expectations and current performance

2 Benefits of patient activation

3 Patient decision aids: costs and benefits

4 Giving information to patients: costs and benefits

5 Personalised care planning: costs and benefits

6 Support for self care: costs and benefits

7 Access to own health records: costs and benefits

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Put another way, the aim of this work is to help to overcome barriers to implementing shared decision making

“Shared decision making will never be widely practiced unless clinicians embrace the idea”1

Shared decision making will take time I haven’t got

Shared decision making isn’t appropriate for my patients

Shared decision making isn’t appropriate to my specialty

Barriers to clinician engagement1

There is no indication that using shared decision making takes more time. Indeed,

it can reduce demand for services

The vast majority of people want more involvement in decision making. Giving this tends to improve their quality of life, health, satisfaction with care that is safer

Studies consistently find benefits of shared decision making covering a wide

range of specialties, though not all covered yet

Source: (1) Implementing shared decision making in the UK, Coulter (2009), Health Foundation

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Before exploring the evidence, it is important to be clear that shared decision making is about a balanced approach to care decisions

Source: Systematic review of the effects of SDM on patient satisfaction, treatment adherance and Health status, April 2008, Psychotherapy and Psychosomatics

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Patient expectation about involvement in decisions

Patient sole decision maker

5%

Patient decides after consultation

18%

Doctor decides after consultation

16%

Doctor sole decision maker10%

Shared decision51%

While there are a range of views, half of people are looking to share decision making with clinicians and a quarter looking to be the lead decision maker

Source: Coulter & Jenkinson “European patients’ views on the responsiveness of health systems and healthcare providers” (2005) European Journal of Public Health, Vol. 15, No. 4, 355–360Note: Figures based on international study. As UK was similar to international average, this is likely to be close to England position

26% say doctor shouldhave primary decisionrole

23% say patient shouldhave primary decisionrole

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A substantial number of patients feel they are not encouraged to play an active role in their care. People report practice nurses are significantly better than other professions in involving patients in this way.

Were you encouraged to self care or play an more active role in caring for your long-term condition when you approached or looked at……

16

24

27

36

38

35

34

39

46

38

33

23

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Practice nurse

GP

Hospital doctor

Local Pharmacist

No Yes, a bit Yes, a lotSource: Self care for people with long-term conditions, Department of Health, 2009

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However, there has been an apparent lack of progress in engaging hospital inpatients in decision making in recent years

Were you involved as much as you wanted to be in decisions about your care and treatment?

53% 52% 51% 52% 52%

37% 37% 38% 37% 37%

10% 11% 11% 10% 11%

0%

10%

20%

30%

40%

50%

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70%

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2005 2006 2007 2008 2009

% a

ll re

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Yes, definitely Yes, to some extent NoSource: CQC inpatient surveys 2005-2009

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And while the UK performs quite well in most international health comparisons, it is worst out of seven comparator countries when it comes to delivering patient-centred care

% people saying the "Doctor always tells you about treatment options and involves you in decisions about the best treatment for you"

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Australia Canada Germany Netherlands New Zealand UK USA

% r

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Source: Davis, K., Schoen, C., & Stremikis, K. 2010, Mirror, mirror on the wall: how the performance of the US health care system compares internationally, Commonwealth Fund, New York.

% people saying the "regular doctor always or often tells you about care, treatment choices and asks opinions"

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% people saying the "Regular doctor always or often encouraged you to ask questions"

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% people saying the "Regular doctor always or often gives clear instructions about symptoms, when to seek further care"

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Patients want involvement in decisions

When asked whether they had been sufficiently involved in decisions about their care, nearly half of hospital inpatients and 30% of outpatients said they were not involved as much as they wanted to be1.

A survey on patient involvement found that over 50% of people wanted a model where doctors and patients made joint decisions about treatment decision. It also found that a higher proportion of younger people preferred this model, suggesting greater demand in the future for joint decision-making2.

Source: (1) National Patient Surveys, 2009, Care Quality CommissionSource: (2) A. Coulter in Shared Decision-Making in Health Care, Adrian Edwards and Glyn Elwyn, 2009, page 159-160

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6%

3%

10%

40%

41%

37%

55%

56%

53%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Family doctor/GP*

Practice nurse*

Hospital Doctor#

Poor Good Very good

There is little difference between GPs, practice nurses and hospital doctors in making their patients feel involved in decisions. A small group of people feel their clinician is poor at involving them in decisions

Q: How would you rate your practice nurse/GP/hospital doctor at involving you in decisions about your health care…?

Sources: *GP patient survey, Department of Health, Q3/Q4 2009-10 #NHS Inpatient Survey, 2009, Care Quality Commission

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Study found GPs to be receptive to SDM, although practical barriers such as time need to be addressed

Results• Attitudes and confidence ratings showed positive changes• Time constraints remained important as barrier

Method

• Study carried out in South Wales in 2000 • Randomised trial looking at GPs attitudes to involving patients in SDM• 20 GPs received training in SDM skills• GPs consulted with up to 48 patients each for study• Questionnaire assessments before and after each training stage

Conclusion• Professionals receptive to patient involvement and willing to acquire relevant skills• Time should be addressed as priority

Source: Involving patients in decision making and communicating risk: a longitudinal evaluation of doctor ’s attitudes and confidence during a randomised trial, March 2004, Journal of Evaluation in Clinical Practice

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Virtually all clinicians are supportive of the principle of shared decision making and patient decision aids, though some key practicalities get in the way of this being a reality.

Source: (1) “Findings from a national survey of physicians”, Foundation for Informed Medical Decision Making (2009)Source: (2) Hibbard et al “Measuring clinician beliefs about patient self-management” (2010)

45%

38%

6%

4%

7%

Not enough time

Patient has difficulty

understanding

No trusted information

sourceP

atients rely on my

recomm

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Oth

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Biggest clinician barrier to shared decision making 1

Clinicians support idea of shared decision making

•93% clinicians report shared decision making as a positive process. 1

•96% clinicians say they would use decision aids if they met clinical standards (48% say much more comfortable with this).1

•No significant differences in attitude to and delivery of shared decision making by characteristic of clinician2

•However, 43% say shared decision making could lead to unnecessary tests or screenings.

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The aim of this paper is as a resource in making the evidence based case for shared decision making to the NHS. It outlines current expectations and performance, benefits of patient activation and interventions that drive this








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The evidence shows that more “activated”* patients are ….

Service use• admitted to hospital 17% less2, though more likely to use more out of hospital healthcare resource1

• Much less likely to be readmitted to hospital in 30 days2

Quality of life• More satisfied with their life1

• More control of their life1

Evidence covers many different dimensions of patient care and outcomes

Safer care• less likely to have an adverse incident as result of poor care coordination2

• less likely to suffer as result of medical error2

Clinical indicators• more likely to stick to treatment regimes3

• 18% more likely to have good glycemic control2

• better clinical outcomes for conditions where researched

Patient experience

• 1% of patients involved in decision making are dissatisfied with their experience of care, compared to 39% who are not involved4

•1% increase in patient involvement associated with 0.4% rise in satisfaction4

Source: (1) Department of Health analysis of “Self care survey”, Department of Health/Ipsos-MORI, 2009Source: (2) Carol Remmers. The Relationship Between the Patient Activation Measure, Future Health Outcomes, and Health Care Utilization Among Patients with Diabetes. Kaiser Care Management Institute, PhD Dissertation.Source: (3) The impact of patient participation on adherence and clinical outcome in primary care of depression. Loh et al. Patient education and counselling 65(2007) 69-78Source: (4) GP patient survey, Department of Health/Ipsos-MORI 2009-10,Note: (*) “Activated” patients are those who have the necessary knowledge, skill, and confidence to play a significant role in decisions and management of their health

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Activating patients is likely to mean they get safer care and have greater confidence in health system

Source: Carol Remmers. The Relationship Between the Patient Activation Measure, Future Health Outcomes, and Health Care Utilization Among Patients with Diabetes. Kaiser Care Management Institute, PhD Dissertation.

0 10 20 30 40 50 60 70

% readmission to hospital in 30 days

% experienced a medical error

% reporting poor care coordination

% suffering health consequences due to poorcare coordination

% reporting lost confidence in healthcare system

Highly active patients Less activated patients

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A study of people with depression found patient participation greatly influenced treatment adherence and improved clinical outcomes

Source: Loh et al. “The impact of patient participation on adherence and clinical outcome in primary care of depression”. Patient education and counselling 65(2007) 69-78

Patient participation in shared decision making

The study measured six aspects of patient participation following initial appointment:

• patient helped to understand information• Doctor felt to understand what was important to the patient• Doctor answers questions well• Feeling of adequate involvement in decisions• Extent decisions were made jointly by patient and clinician•Satisfaction with decision making process

Better treatment adherence

Separately assessed separately by GPs and patients after eight weeks on the

programme

Reductions in severity of depression related complaints

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Allowing for socio-demographic factors, more active patients in England are more likely to be satisfied with and in control of their life, and use more out of hospital health services. Activation isn’t linked to change in health status

Socio-demographics

Socio-demographics

Service deliveryService delivery

Patient activationPatient

activation

•Older people•In good health

•Older people•In good health

Sex, deprivation income, rurality, Sex, deprivation income, rurality,

x

Satisfaction and control of life and

health

Satisfaction and control of life and

health

•Prep to see doc•Healthy lifestyle•Active self care•Own care ability

•Prep to see doc•Healthy lifestyle•Active self care•Own care ability

Satisfaction with services

Satisfaction with services

x

Key health drivers of life control and satisfaction1

Source: (1) Department of Health analysis of “Self care survey”, Department of Health/Ipsos-MORI, 2009Source: (2) Carol Remmers. The Relationship Between the Patient Activation Measure, Future Health Outcomes, and Health Care Utilization Among Patients with Diabetes. Kaiser Care Management Institute, PhD Dissertation.

Use of health care services

•Evidence from the USA is that active patients are admitted to hospital 17% less, and much less likely to be readmitted to hospital in 30 days2

• Taking account of socio-demographic characteristics, more active people more likely to use out of hospital services1

Health Status•Taking account of socio-demographic characteristics, there is no relationship between patient activation and their health status1

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People who are involved in decisions are more satisfied

•Out of the patients who answered good or very good to their rating of their GP involving them in decisions, 96% are satisfied with the care they received.

•Whereas, of those who answered poor or very poor, only 37% are satisfied care.

Source: GP patient survey, Department of Health, Q3/Q4 200910

Doctor is poor at involving patient in decisions

37%

24%

39%

Doctor is good at involving patient in decisions

96%

3%

1%

Satisfied

Neither satisfied or dissatisfied

Dissatisfied

How satisfied are you with the care you received at your GP surgery?

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Hospital patients are more likely to rate their care good to excellent when they feel they are involved in decisions

Patient didn't feel involved in decisions

64%

20%

15%

Source: NHS Inpatient Survey, 2009, Care Quality Commission

Patient felt involved in decisions

96%

3%

1%

Good to Excellent care

Fair care

Poor care

Overall, how would you rate the care you received?

• Out of the patients who felt involved in decisions, 96% of them rated the care they received as good to excellent

• Out of those who didn’t feel involved in decisions, 64% rated the care they received as good to excellent.

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Source: Analysis of the GP Patient Survey Q3 + Q4 2009/10

A regression was carried out to see how significant aspects such as: Involvement in decisions; confidence and trust in GPs; and explanations of tests and treatments were in determining a patient’s satisfaction with care.

Other factors that were included to try to isolate the effect of patient involvement issues included socio-demographics (like age, health status), practice characteristics (like deprivation, rurality and prevalence of conditions) and service factors (like time since last GP visit). There is a full list in annex.

FINDINGSConfidence and trust in the GP, and patients feeling their GPs listened to them were most significant in explaining satisfaction with care. These are aspects of shared decision making.A 10% increase in patients…..

•….who felt more involved in decisions is linked to a 1% increase in satisfaction•….who had confidence and trust in their GP is linked to a 4.9% increase in satisfaction•….who felt listened to is linked to increased satisfaction of 2.4%•….who felt their GP was good at explaining tests and treatments is linked to a 0.5% increase

•77% of the variability in satisfaction can be accounted for by the variables mentioned above

When taking other factors into account, involvement in decisions with the GP and explanations of treatments is still key to satisfaction

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Feeling listened to and having trust in your GP, is directly linked to higher satisfaction with primary medical care

1.0%

4.9%

2.4%

0.5%

0% 1% 2% 3% 4% 5% 6%

...felt more involved indecisions

...had confidence and trustin GP

...felt listened to

...felt their GP was good atexplaining tests and

treatments

A 10% increase in patients who….

Associated increase in satisfaction

Source: GP patient survey, Department of Health, Q3/Q4 200910

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Powerful analysis, influencing decisions 2218 April 2023 Source: Department of Health analysis of the NHS Inpatient Survey 2009

FINDINGSInvolvement in decisions about discharge, confidence and trust in doctor/nurse and involvement in decisions about care and treatment were significant in determining rating of care

A 1 point increase in….

• …Confidence and Trust in their Doctor is linked to 0.5 point increase in rating of care

• …Confidence and Trust in their Nurse is linked to a 0.4 point increase in rating of care

•…Involvement in decisions about care and treatment is linked to a 0.4 point increase in rating of care

•...Involvement in decisions about their discharge in linked to a 0.1 point increase in rating of care

87% of the variability in the rating of care can be explained by this model

Shared decision making is important to improving patient satisfaction in hospitals as well as GP practices

METHODThe NHS Inpatient survey includes a question on how the patient would rate the care they received. Each trust receives a mean score for each question. This ranges from 0 to 100, 100 being the most positive score

A regression was carried out to see whether the following variables influenced the rating of care:-•Confidence and Trust in Doctor/Nurse•Involvement in Decisions about care and treatment•Good explanations of risks and benefits of treatments•Involvement in decisions about dischargeAgain, socio-demographic and other trust factors were included in the regression.

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10 point increase in trust score of patients who….

5

4

4

1

- 1 2 3 4 5 6

had confidence and trust in hospitaldoctor

had confidence and trust in hospitalnurse

felt involved in decisions aboutcare and treatment

felt involved in decisions aboutdischarge

Increase in rating of care

Source: Department of Health analysis of the NHS Inpatient Survey 2009

Feeling involved in decisions and having trust in your hospital doctor or nurse, is directly linked to higher satisfaction with hospital care

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Analysis of the GP Patient Survey Q3 + Q4 2009/10, Hospital Episode Statistics 2008-09, Exeter Payments System 2009-10

RESULTS

• Involvement in decisions and the explanation of tests and treatments were not significant in number of ACS referrals. This could mean that patients who are involved in decisions are not referred more or less than people who are not.

• Every 1% increase in patients who felt they had confidence and trust in their GP, leads to 6.8 less ACS referrals per 1000

•Every 1% increase in patients who felt their GP listened to them, leads to 5.7 more ACS referrals per 1000

• 43% of the variability in ACS referrals could be explained by this model

METHODAmbulatory Care Sensitive conditions are illnesses – mainly chronic diseases, where adequate care can safely be provided in primary care. These conditions contribute most to avoidable emergency hospital admissions which are expensive. The same variables, as in the previous slide, were used to determine whether they affect ACS referrals.

No link between involvement in decisions and admissions for ambulatory care sensitive conditions

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There is room for improvement for hospital Trusts : after standardisation for patient type there are 18 percentage points from highest to lowest in involving patients in decisions

Relationship between Decisions and Rating of Care

50

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65

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60 65 70 75 80 85 90 95Rating of Care

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Correlation Coefficient = 0.88

Specialist trusts feature a lot among those rated highest

There is a strong the relationship is between the

rating of care and Inpatients involvement in decisions

Source: Analysis of the NHS Inpatient Survey 2009

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10 Hospital trusts with highest rating% people feeling involved in decisions – highest/lowest hospital trusts

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Young, non-white people with no LTC feel less involved in decisions as they want to be

Decision making by Age Group

65% 65%69%

72%75%

79% 79% 77%

0%

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Decision making by Ethnicity

72% 71%68%

66% 66%

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71%76%

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•Older people, white people and people who had an LTC are more involved in decisions

•Those in poorer health feel more involved in decisions although not significantly different from healthier people

•Targeting these groups that feel less involved in decisions they want to be involved in could help to narrow the gap

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However, there is a slightly different profile for activated patients, who tend to be younger, more educated and in better health.

Current inequalities in patient activation

0

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Source:How engaged are people in their health care? Findings of a national telephone survey, Picker Institute Europe, 2005

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Patient decision aids have been shown to often improve patient activation and reduce healthcare costs

There is no evidence on the direct impact of patient decision aids on satisfaction with care, quality of life or life expectancy. However, this may come by being a more active patient

Service use• reduce discretionary surgery rates by around 25%1 • reduce decisions to have screening by up to 20%1 • reduce overall healthcare costs for some but not all treatment choices2-4

Patient knowledge significantly improved knowledge of condition and treatment choices1

International and UK evidence suggests that implementing patient decision aids would…

Patient decision making

• Reduce perception that choice made was ineffective (though no effect on satisfaction with decision)1

• Reduce indecision and give greater feeling of control in decision making1

Source: (1) O'Connor et al. Decision aids for patients facing health treatment or screening decisions (review). Cochrane Library, 2009 volume 2.Source: (2) Kennedy et al. “Effects of decision aids for menorrhagia on treatment choices, health outcomes, and costs JAMA2002; 288: 2701-2708Source: (3) Murray et al. Randomised controlled trial of an interactive multimedia decision aid on hormone replacement therapy in primary care. British Medical Journal 2001; 323: 490-3, Source: (4) Murray et al. Randomised controlled trial of an interactive multimedia decision aid on benign prostatic hypertrophy in primary care. British Medical Journal 2001; 323: 493-6.

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The evidence suggests using patient decision aids makes little difference to the length of consultations

Choice of statin• 3.8 minutes extra outpatient consultation when using decision aid, but not statistically significant6

Breast cancer screening

• One study found consultations using decision aids took 8 minutes less than regular consultations2. Another found no difference in consultation length3.

Evidence is available covering five different situations

Cancer treatment • No difference in consultation length whether using decision aid or not4.

Pre-natal down syndrome screening

• Consultation using patient decision aids took 6 minutes longer than regular consultations5.

Elective referral from GP

• No difference in consultation length whether using decision aid or not1

Sources: (1,2,6 from Interventions for improving the adoption of shared decision making by healthcare professionals (Review) Légaré et al, 2010 (1) Stacey, 2006(2) Green 2004 (6) Nannenga 2009. 3-5 from O'Connor et al. Decision aids for patients facing health treatment or screening decisions (review). Cochrane Library, 2009 volume 2. (3) Whelan, 2003 (4)Butow 2004 (5) Bekker 2004

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Decision Aids tend to reduce rates of high volume discretionary surgery

Source: O'Connor et al. Decision aids for patients facing health treatment or screening decisions (review). Cochrane Library, 2009 volume 2.

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Decision Aids also affect rates of screening and other therapies

Source: O'Connor et al. Decision aids for patients facing health treatment or screening decisions (review). Cochrane Library, 2009 volume 2.

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£1,810

£1,030

£1,333

1.58

1.57

1.57

£0 £200 £400 £600 £800 £1,000 £1,200 £1,400 £1,600 £1,800 £2,000

Standard Care

PtDA video

PtDA video and nursecoaching

Average cost (£)

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8Average QALY gain

average cost (£) Average QALY gainSource: Kennedy et al. JAMA2002; 288: 2701-2708

As a result, overall costs for people using patient decision aids are usually below those who don’t, with no change in outcome

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People who got information on their long-term condition used more expensive services more often

People who got information on their long-term condition used more expensive services more often

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5F

amily

Doc

tor/

GP

/Nur

se

Loca

l pha

rmac

ist

Hos

pita

l Doc

or

Nur

se

Out

patie

nts

Hea

lthvi

sito

r/co

mm

unity

nurs

e

The

rapi

sts

Com

plem

enta

ryth

erap

y

A&

Ede

p/C

asua

lty/O

OH

serv

ice

NH

S d

irect

tele

phon

ehe

lplin

e

Men

tal H

ealth

serv

ice

Soc

ial w

orke

r

NH

S w

alk-

in c

entr

e

Sel

f car

e sk

ills

trai

ning

NH

S c

hoic

es

Av

era

ge

nu

mb

er o

f u

ses

pe

r p

ati

en

t p

er y

ea

r

Info users

Non Info users

Source: Department of Health/Ipsos-MORI, self care survey 2009

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Information forms part of feeling supported: receiving information at all is seen as basic requirement, but the quality of information significantly impacting on whether someone feels fully supported or not

69%

53%

65%

21%

33%16%

11% 14%19%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Info Sought - good Info Sought - poor No Info

Yes- received all support I require Yes - but not all support required No - not received any supportSource: Department of Health/Ipsos-MORI, self care survey 2009

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Patients who hadn’t sought information would look to their GP in the future

People who hadn't sought information would look to their GP for information in the future

0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%

Family Doc

Practice nurse

Local pharmacists/chemists

Hospital doc

NHS choices

Health websites

% of people who hadn't sought info

Source: Department of Health/Ipsos-MORI, self care survey 2009

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Lots of people use information to help manage their health or make choices, though this is much less so for people from minority ethnic groups and those living in the most deprived communities

0

10

20

30

40

50

60

All

peop

le

Men

Wom

en

16-2

4

25-3

4

35-4

4

45-5

4

55-6

4

65+

AB

C1

C2

DE

Whi

te-B

ritis

h

Oth

er

Has

lon

g-te

rm c

ondi

tion

No

long

-te

rm c

ond

ition

Ve

ry a

fflu

ent

afflu

ent

aver

age

depr

ive

d

very

de

priv

ed

% p

eo

ple

wh

o s

aid

....

Information helped manage health Used info, but not helpedSource: primary care tracker survey - Jan-Oct 2010

Gender Age Social class Health Status

DeprivationEthnic group

Inequalities in using information about health conditions

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There is evidence that personalised care planning can improve quality of life, satisfaction with care and reduce service use. This is a lever for activating patients, through joint decision making and information

Service use• 20% fewer hospital admissions and 28% few hospital bed days8

• No known change in other services8

Quality of lifeIncreased quality of life for diabetes patients (+5%) and asthma (+34%). No change for studies on COPD1-3

Local studies where care planning or person centred care has been tried show…

Satisfaction with care

• Better experience of communication with doctors and nurses8

• Better experience of treatment received8

• Reduced knowledge of condition compared to control group8

Clinical indicators• Higher BMI and blood pressure for diabetes patients7

• No change in other indicators (e.g HBA1C for diabetes patients)8

• No change in FEV1/FVC for people with asthma8

Source: (1) Kinmonth et al. 1998. “Randomised controlled trial of patient centred care of diabetes in general practice: impact on current wellbeing and future disease risk ”, BMJ Vol 317 pp1202-1208Source: (2) Martin et al. 2004. “Care plans for acutely deteriorating COPD: A randomized controlled trial”, Chronic Respiratory Disease Vol 1 pp191-195Source: (3) Lahdensuo et al. 1996. “Randomised comparison of guided self management and traditional treatment of asthma over one year”, BMJ Vol 312 pp748-752Source: (4) Ouwens et al. “Integrated care programmes for chronically ill patients: a review of systematic reviews” In J for Quality in Health Care 2005; Volume 17, Number 2: pp. 141–146Source: (5) Liu et al. 2003. “Cost-effectiveness of collaborative care for depression in a primary care veteran population”, Psychiatric Services Vol 54 698-704Source: (6) Katon et al. 1999. “Stepped collaborative care for primary care patients with persistent symptoms of depression”, Archives of General Psychiatry Vol 56 pp1109-1115Source: (7) Olivarius et al. 2001. “Randomised controlled trial of structured personal care of type 2 diabetes mellitus”, BMJ Vol 323(7319) p970Source: (8) Care planning impact assessment, Department of Health, Jan 2009

Mortality Improved mortality for stroke patients, but not for people with diabetes4,7

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If someone agrees a care plan, they are more likely to be aware of and take up options for self care support. However, awareness is still relatively low even when people have engaged in care planning

Awareness that self care support can improve condition management by engagement in care planning

0%

5%

10%

15%

20%

25%

30%

35%

40%

Information to manageconditon

Information for choice of care Skills training Support network Home equipment

% a

war

e th

at s

elf

care

su

pp

ort

can

imp

rove

co

nd

itio

n m

anag

eme

nt

No plan or discussion

had discussion, not plan

agreed care plan

Source: primary care tracker, wave 27 (Oct09)

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Given personalised care planning should be offered to all with a long-term condition, it has the potential to reduce inequalities in patient activation. However, current delivery reflects existing inequalities.

Inequalities in personalised care planning

0%

10%

20%

30%

40%

50%

60%

70%

80%

All

peop

le

Mal

e

Fem

ale

18 t

o 24

25 t

o 34

35 t

o 44

45 t

o 54

55 t

o 64

65 t

o 74

75 t

o 84

85 o

r ov

er

Brit

ish

Iris

h

Any

oth

er w

hite

Whi

te a

nd B

lack

Cai

bbea

n

Whi

te a

nd B

lack

Afr

ican

Whi

te a

nd A

sian

Any

oth

er m

ixed

Indi

an

Pak

ista

ni

Ban

glad

eshi

Any

oth

er A

sian

Car

ibbe

an

Afr

ican

Any

oth

er B

lack

Chi

nese

Oth

er

Exc

elle

nt

Ver

y go

od

Goo

d

Fai

r

Poo

r

Non

e

Bud

dhis

t

Chr

istia

n

Hin

du

Jew

ish

Mus

lim

Sik

h

Oth

er

I w

ould

pre

fer

not

to s

ay

Het

eros

exua

l/Str

aigh

t

Gay

/Les

bian

Bis

exua

l

Oth

er

I w

ould

pre

fer

not

to s

ay

% p

eop

le w

ith

a l

on

g-t

erm

co

nd

itio

n w

ho

ag

reed

a c

are

pla

n

Source: GP patient survey, 2010

Gender Age Health Status ReligionEthnic group Sexual orientation

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The case for self care support is well researched: self care skills training and education is likely to reduce service use and improve length & quality of life.

Service use• reduce number of GP visits6

• help to prevent unnecessary admissions to hospital6 • reduce length of stay of necessary hospital admissions6

Quality of life

• Increased life expectancy [+4 mths for people with diabetes]1,3

•Improve health status, self efficacy & control1-3

• Enable patients to remain in their homes and communities and halved days off work and improve feeling of control in their condition1-4

Evidence from studies round the world suggested that a supporting self care would…

Satisfaction with care

• increase choice for patients6 • improve end of life care6

• integrate all elements of care6

Clinical indicators• Reduce BMI, HbA1C & BP for people with diabetes1,3• lead to more smoking quitters, people who exercise and have good diet1-3• lead to reduced stress for people with mental health conditions

Self care support networks

• While some support networks have been shown to be modestly successful, a systematic review found there was limited patient benefit from these networks5

Source: (1) Jacobs-Van der Bruggen (2009); Cost-Effectiveness of Lifestyle Modification in Diabetic Patients; Diabetes Care 32:1453–1458, Source: (2) Kennedy et al. “The effectiveness and cost effectiveness of a national lay-led self care support programme for patients with LTCs: a pragmatic RCT” J Epidemiol. Community Health 2007;61;254-261Source: (3) A. Shearer et al Cost-effectiveness of flexible intensive insulin management to enable dietary freedom in people with Type 1 diabetes in the UK; Diabetic Medicine, 21, 460–467 Source: (4) Ipsos-MORI, primary care survey 2010Source: (5) Woolacott N, Orton L, Beynon S, Myers L, Forbes C Systematic review of the clinical effectiveness of self care support networks in health and social care. Health Technology Assessment database http://www.crd.york.ac.uk/CRDWeb/ShowRecord.asp?View=Full&ID=32006001556 Source: (6) Research evidence on the effectiveness of self care support, Department of Health (2007),

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If someone is supported to self care, they are much more likely to say they feel fully supported to manage their long-term condition

Extent people are supported to manage long-term condition by whether helped to self care

3

4

12

19

14

20

20

25

51

32

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Yes

No

Is s

om

eon

e h

elp

ed t

o s

elf

care

?

Don't know Don't need support Not received supportReceived some, not all support Received all support needed

Source: primary care tracker survey, Department of Health, 2009

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The aim of this paper is as a resource in making the evidence based case for shared decision making to the NHS. It outlines current expectations and performance, benefits of patient activation and interventions that can drive this








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Patients with access to their records feel more involved in their health care, have more confidence & understand appointment discussions better

9

5

76

62

54

25

26

21

21

34

43

36

65

74

3

4

3

39

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

I am more worried about a particularaspect of my health

I am confused about a particular aspectof my health

I feel more involved in my health care

I understand better what has previouslybeen discussed at my appointments

I feel more confident in my GP

I have decided to seek further informationabout a particular aspect of my health

Agreed or strongly agreed Neither agreed nor disagreed Disagreed or strongly disagreed

+ve

-ve

Source: How patients use access to their electronic GP record – a quantative study, Vanita Bhavnania, et al. Family Practice, Nov 2010 - link

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Annex

Coe fficientsa

.178 .017 10.447 .000 .144 .211

.000 .009 .000 .017 .987 -.018 .018

.136 .020 .067 6.670 .000 .096 .176

.138 .027 .051 5.161 .000 .085 .190

.058 .039 .011 1.478 .139 -.019 .135

.034 .015 .017 2.208 .027 .004 .064

-.089 .011 -.051 -7.727 .000 -.111 -.066

-.170 .015 -.110 -11.534 .000 -.199 -.141

-.227 .024 -.086 -9.615 .000 -.273 -.181

-.081 .010 -.082 -7.850 .000 -.101 -.061

.099 .013 .126 7.676 .000 .073 .124

.486 .019 .315 26.142 .000 .449 .522

.020 .007 .017 2.704 .007 .005 .034

.000 .000 .021 2.316 .021 .000 .000

-.001 .001 -.007 -1.180 .238 -.003 .001

.000 .000 .009 .714 .475 .000 .001

-1.22E-06 .000 -.070 -5.597 .000 .000 .000

-.046 .073 -.009 -.631 .528 -.189 .097

-.104 .130 -.010 -.800 .424 -.358 .151

-.154 .039 -.086 -3.969 .000 -.230 -.078

-.942 .054 -.172 -17.481 .000 -1.048 -.837

.205 .073 .025 2.817 .005 .062 .348

.640 .242 .022 2.645 .008 .166 1.114

-.057 .059 -.009 -.962 .336 -.173 .059

-.274 .111 -.024 -2.461 .014 -.492 -.056

-.714 .112 -.047 -6.368 .000 -.934 -.494

-.050 .050 -.012 -.987 .324 -.148 .049

-.151 .097 -.013 -1.556 .120 -.341 .039

.608 .274 .013 2.218 .027 .071 1.145

.139 .127 .008 1.101 .271 -.109 .388

.044 .010 .036 4.391 .000 .024 .064

.017 .028 .005 .620 .535 -.037 .071

-.352 .150 -.032 -2.354 .019 -.645 -.059

.176 .016 .084 10.944 .000 .145 .208

.364 .176 .013 2.064 .039 .018 .709

.232 .049 .185 4.773 .000 .137 .328

-.164 .085 -.011 -1.923 .054 -.330 .003

.048 .008 .039 5.923 .000 .032 .064

.243 .015 .257 16.343 .000 .214 .272

.045 .014 .054 3.250 .001 .018 .073

(Constant)

age18to24

age65to74

age75to84

age85plus

excellent

good

fair

poor

noltc

dec isions

confidence

tried6months

depriv

rural

noofgps

lists ize

chd

stroke

bp

dm

copd

epil

thy

cancer

mh

asthma

hflvd

pc

dem

dep

ckd

af

obes

ld

smoke

cvd

gp3months

listen

explain

Model1

B Std. Error

UnstandardizedCoefficients

Beta

StandardizedCoefficients

t Sig. Lower Bound Upper Bound

95% Confidence Interval for B

Dependent Variable: satisfieda.

Coe fficientsa

7.353 1.826 4.026 .000 3.773 10.933

-.309 .992 -.003 -.312 .755 -2.253 1.635

-1.680 2.187 -.012 -.768 .442 -5.968 2.607

1.916 2.866 .010 .668 .504 -3.703 7.534

1.016 4.204 .003 .242 .809 -7.225 9.258

-3.223 1.640 -.024 -1.965 .049 -6.439 -.008

5.721 1.232 .049 4.642 .000 3.306 8.137

12.624 1.588 .121 7.949 .000 9.511 15.738

16.531 2.538 .093 6.513 .000 11.556 21.507

-6.987 1.109 -.104 -6.300 .000 -9.161 -4.813

-1.083 1.381 -.020 -.784 .433 -3.791 1.625

-6.770 1.996 -.065 -3.392 .001 -10.682 -2.857

2.558 .790 .032 3.238 .001 1.009 4.107

.061 .005 .170 11.510 .000 .051 .072

-.434 .115 -.037 -3.782 .000 -.659 -.209

.002 .040 .001 .062 .951 -.076 .081

-5.61E-05 .000 -.048 -2.388 .017 .000 .000

73.516 7.825 .202 9.395 .000 58.176 88.855

14.052 13.945 .021 1.008 .314 -13.284 41.389

8.459 4.175 .070 2.026 .043 .274 16.644

20.556 5.793 .056 3.548 .000 9.200 31.912

84.910 7.826 .155 10.849 .000 69.568 100.251

155.016 25.989 .081 5.965 .000 104.070 205.961

-11.299 6.367 -.026 -1.775 .076 -23.780 1.182

-74.539 11.951 -.096 -6.237 .000 -97.966 -51.112

68.821 12.054 .067 5.709 .000 45.192 92.450

27.320 5.407 .099 5.053 .000 16.721 37.920

-42.935 10.409 -.055 -4.125 .000 -63.339 -22.532

-18.577 29.446 -.006 -.631 .528 -76.298 39.144

109.237 13.620 .087 8.020 .000 82.538 135.935

3.487 1.079 .042 3.231 .001 1.371 5.602

-1.225 2.968 -.005 -.413 .680 -7.042 4.593

56.168 16.072 .075 3.495 .000 24.663 87.673

-4.424 1.730 -.031 -2.557 .011 -7.816 -1.032

20.011 18.936 .011 1.057 .291 -17.109 57.131

-28.769 5.228 -.339 -5.503 .000 -39.017 -18.521

-11.125 9.139 -.011 -1.217 .224 -29.040 6.790

1.043 .879 .012 1.187 .235 -.680 2.765

5.694 1.599 .089 3.562 .000 2.561 8.828

2.580 1.498 .046 1.722 .085 -.356 5.516

(Constant)

age18to24

age65to74

age75to84

age85plus

excellent

good

fair

poor

noltc

dec isions

confidence

tried6months

depriv

rural

noofgps

lists ize

chd

stroke

bp

dm

copd

epil

thy

cancer

mh

asthma

hflvd

pc

dem

dep

ckd

af

obes

ld

smoke

cvd

gp3months

listen

explain

Model1

B Std. Error


Beta




Dependent Variable: acsa.

R squared value = 77% R squared value = 43%

Regression output SPSS. Satisfied with care and ACS admissions per 1000 head. Enter method: Leaving insignificants in. GPPS y4q4 Practice level weighted.

(a) Satisfaction with care (slides 19-20) (a) Admissions for ACS conditions (slide 23)

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Annex

Coefficientsa

-23.022 7.776 -2.961 .004 -38.389 -7.655

.484 .093 .302 5.176 .000 .299 .668

.354 .078 .263 4.571 .000 .201 .508

.388 .074 .371 5.231 .000 .242 .535

-.081 .087 -.041 -.935 .351 -.252 .090

.114 .057 .120 2.013 .046 .002 .226

-.039 .026 -.063 -1.520 .131 -.090 .012

.011 .056 .009 .201 .841 -.100 .122

.008 .050 .008 .159 .874 -.091 .107

.057 .041 .051 1.384 .169 -.024 .137

.261 .301 .047 .868 .387 -.334 .857

-.004 .054 -.003 -.069 .945 -.110 .102

-.080 .065 -.069 -1.247 .214 -.208 .047

.289 .384 .034 .753 .453 -.470 1.048

.092 .065 .060 1.410 .161 -.037 .221

(Constant)

Q32_mean

Q36_mean

Q41_mean

Q51_mean

Q58_mean

female_tpc

age1_tpc

age2_tpc

age3_tpc

eth2_tpc

eth3_tpc

eth4_tpc

eth5_tpc

eth6_tpc

Model1

B Std. Error


Beta




Dependent Variable: Q74_meana.

R squared value = 87%

From slides 21-22. Source: NHS Inpatient survey 2009. Regression analysis enter method. Trust level

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Powerful analysis, influencing decisions 16 April, 2015 Commissioning Analysis and Intelligence Team...

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