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Powerful analysis, influencing decisions 16 April, 2015 Commissioning Analysis and Intelligence Team Kate Manton and Roger Halliday Shared Decision Making.

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Presentation on theme: "Powerful analysis, influencing decisions 16 April, 2015 Commissioning Analysis and Intelligence Team Kate Manton and Roger Halliday Shared Decision Making."— Presentation transcript:

1 Powerful analysis, influencing decisions 16 April, 2015 Commissioning Analysis and Intelligence Team Kate Manton and Roger Halliday Shared Decision Making The Evidence

2 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 2 16 April, 2015 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

3 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 3 16 April, 2015 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 engagement 1 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

4 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 4 16 April, 2015 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

5 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 5 16 April, 2015 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, 355–360 Note: Figures based on international study. As UK was similar to international average, this is likely to be close to England position 26% say doctor should have primary decision role 23% say patient should have primary decision role

6 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 6 16 April, 2015 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.

7 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 7 16 April, 2015 However, there has been an apparent lack of progress in engaging hospital inpatients in decision making in recent years

8 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 8 16 April, 2015 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

9 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 9 16 April, 2015 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 be 1. 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-making 2. Source: (1) National Patient Surveys, 2009, Care Quality Commission Source: (2) A. Coulter in Shared Decision-Making in Health Care, Adrian Edwards and Glyn Elwyn, 2009, page 159-160

10 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 10 16 April, 2015 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

11 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 11 16 April, 2015 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

12 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 12 16 April, 2015 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) Not enough time Patient has difficulty understanding No trusted information source Patients rely on my recommendations Other 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 clinician 2 However, 43% say shared decision making could lead to unnecessary tests or screenings.

13 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 13 16 April, 2015 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 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

14 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 14 16 April, 2015 The evidence shows that more “activated”* patients are …. Service use admitted to hospital 17% less 2, though more likely to use more out of hospital healthcare resource 1 Much less likely to be readmitted to hospital in 30 days 2 Quality of life More satisfied with their life 1 More control of their life 1 Evidence covers many different dimensions of patient care and outcomes Safer care less likely to have an adverse incident as result of poor care coordination 2 less likely to suffer as result of medical error 2 Clinical indicators more likely to stick to treatment regimes 3 18% more likely to have good glycemic control 2 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 involved 4 1% increase in patient involvement associated with 0.4% rise in satisfaction 4 Source: (1) Department of Health analysis of “Self care survey”, Department of Health/Ipsos-MORI, 2009 Source: (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) 69-78 Source: (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

15 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 15 16 April, 2015 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.

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

17 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 17 16 April, 2015 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 Service delivery Patient activation Older people In good health Older people In good health Sex, deprivation income, rurality, x 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 x Key health drivers of life control and satisfaction 1 Source: (1) Department of Health analysis of “Self care survey”, Department of Health/Ipsos-MORI, 2009 Source: (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 days 2 Taking account of socio-demographic characteristics, more active people more likely to use out of hospital services 1 Health Status Taking account of socio-demographic characteristics, there is no relationship between patient activation and their health status 1

18 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 18 16 April, 2015 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

19 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 19 16 April, 2015 Hospital patients are more likely to rate their care good to excellent when they feel they are involved in decisions Source: NHS Inpatient Survey, 2009, Care Quality Commission 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.

20 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 20 16 April, 2015 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. FINDINGS Confidence 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

21 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 21 16 April, 2015 Feeling listened to and having trust in your GP, is directly linked to higher satisfaction with primary medical care Source: GP patient survey, Department of Health, Q3/Q4 200910

22 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 22 16 April, 2015 Source: Department of Health analysis of the NHS Inpatient Survey 2009 FINDINGS Involvement 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 METHOD The 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 discharge Again, socio-demographic and other trust factors were included in the regression.

23 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 23 16 April, 2015 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

24 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 24 16 April, 2015 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 METHOD Ambulatory 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

25 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 25 16 April, 2015 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 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 % people feeling involved in decisions – highest/lowest hospital trusts

26 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 26 16 April, 2015 Young, non-white people with no LTC feel less involved in decisions as they want to be 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

27 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 27 16 April, 2015 However, there is a slightly different profile for activated patients, who tend to be younger, more educated and in better health.

28 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 28 16 April, 2015 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 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

29 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 29 16 April, 2015 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 choices 2-4 Patient knowledge significantly improved knowledge of condition and treatment choices 1 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 making 1 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: 2701-2708 Source: (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.

30 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 30 16 April, 2015 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 significant 6 Breast cancer screening One study found consultations using decision aids took 8 minutes less than regular consultations 2. Another found no difference in consultation length 3. Evidence is available covering five different situations Cancer treatment No difference in consultation length whether using decision aid or not 4. Pre-natal down syndrome screening Consultation using patient decision aids took 6 minutes longer than regular consultations 5. Elective referral from GP No difference in consultation length whether using decision aid or not 1 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

31 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 31 16 April, 2015 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.

32 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 32 16 April, 2015 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.

33 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 33 16 April, 2015 Source: 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

34 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 34 16 April, 2015 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 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

35 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 35 16 April, 2015 People who got information on their long-term condition used more expensive services more often

36 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 36 16 April, 2015 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

37 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 37 16 April, 2015 Patients who hadn’t sought information would look to their GP in the future

38 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 38 16 April, 2015 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 Inequalities in using information about health conditions

39 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 39 16 April, 2015 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 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

40 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 40 16 April, 2015 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 days 8 No known change in other services 8 Quality of life Increased quality of life for diabetes patients (+5%) and asthma (+34%). No change for studies on COPD 1-3 Local studies where care planning or person centred care has been tried show… Satisfaction with care Better experience of communication with doctors and nurses 8 Better experience of treatment received 8 Reduced knowledge of condition compared to control group 8 Clinical indicators Higher BMI and blood pressure for diabetes patients 7 No change in other indicators (e.g HBA1C for diabetes patients) 8 No change in FEV1/FVC for people with asthma 8 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 pp1202-1208 Source: (2) Martin et al. 2004. “Care plans for acutely deteriorating COPD: A randomized controlled trial”, Chronic Respiratory Disease Vol 1 pp191-195 Source: (3) Lahdensuo et al. 1996. “Randomised comparison of guided self management and traditional treatment of asthma over one year”, BMJ Vol 312 pp748-752 Source: (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. 141–146 Source: (5) Liu et al. 2003. “Cost-effectiveness of collaborative care for depression in a primary care veteran population”, Psychiatric Services Vol 54 698-704 Source: (6) Katon et al. 1999. “Stepped collaborative care for primary care patients with persistent symptoms of depression”, Archives of General Psychiatry Vol 56 pp1109-1115 Source: (7) Olivarius et al. 2001. “Randomised controlled trial of structured personal care of type 2 diabetes mellitus”, BMJ Vol 323(7319) p970 Source: (8) Care planning impact assessment, Department of Health, Jan 2009 Mortality Improved mortality for stroke patients, but not for people with diabetes 4,7

41 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 41 16 April, 2015 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

42 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 42 16 April, 2015 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

43 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 43 16 April, 2015 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 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

44 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 44 16 April, 2015 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 visits 6 help to prevent unnecessary admissions to hospital 6 reduce length of stay of necessary hospital admissions 6 Quality of life Increased life expectancy [+4 mths for people with diabetes] 1,3 Improve health status, self efficacy & control 1-3 Enable patients to remain in their homes and communities and halved days off work and improve feeling of control in their condition 1-4 Evidence from studies round the world suggested that a supporting self care would… Satisfaction with care increase choice for patients 6 improve end of life care 6 integrate all elements of care 6 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 networks 5 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;254-261 Source: (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 2010 Source: (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=32006001556http://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),

45 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 45 16 April, 2015 If someone is supported to self care, they are much more likely to say they feel fully supported to manage their long-term condition

46 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 46 16 April, 2015 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 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

47 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 47 16 April, 2015 Patients with access to their records feel more involved in their health care, have more confidence & understand appointment discussions better +ve -ve Source: How patients use access to their electronic GP record – a quantative study, Vanita Bhavnania, et al. Family Practice, Nov 2010 - linklink

48 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 48 16 April, 2015 Annex 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)

49 Commissioning Analysis and Intelligence Team Powerful analysis, influencing decisions 49 16 April, 2015 Annex R squared value = 87% From slides 21-22. Source: NHS Inpatient survey 2009. Regression analysis enter method. Trust level


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