population health

Designing systems for multi morbidity

Multi Morbidity – Its all about population management blended with a personalised approach – two sides of the same coin

I’ve blogged plenty on the importance of multi morbidity.

The below graph is, I have often recently contended, the second most important chart in contemporary health care policy.

Multi morbidity is more common than uni morbidity. It matters.

However one of my team recently said to me – “but at some point you’ll need to say what needs to be DONE”. He’s right, I’ve had various gos at this all a bit bitty across many blogs.

Here’s an effort to write it into one space. Obvious areas some specific “topics”, some more general ways of working.

1) Clinical Target interventions

what the Rx / intervention responses to MM should be

Must focus on where the win’s are. Over diagnosis / treatment,

• Person centred care. Critical. More than critical. Essential. What’s the matter with you Mrs Smith vs what matters to you Mrs Smith. I MUST write the blog on this as I haven’t done it justice here

• geriatric assessments

• personalised care planning.

• Exercise / muscle mass / CV fitness / frailty link up

• poly pharmacy, over diagnosis agenda etc

• falls prevention

See here from David Oliver A manifesto for multimorbidity1 training needs to focus far more on coordinated, planned care of individuals

2 research priorities, prestige, and funding need to rebalance

3 embrace and promote skilled medical generalism

4 focus much more on tackling inappropriate polypharmacy

5 redesign healthcare delivery to fit the reality of patients’ needs now

A colleague of mine later added an ask around turning round NHS professionals expectations to deliver specialist if not super-specialist care in and out of hours. A job for the Academy of Royal Colleges to usefully emphasise the fact that current and increasingly super-specialist training and careers are unaffordable and less relevant to the health and care system of the future.

Beswick is a well evidenced source for all that, it shows where to expect most benefit. Requires careful consideration and contextualisation. Complex interventions to improve physical function and maintain independent living in elderly people: a systematic review and meta-analysis

NICE NG56 is excellent. Weakness is that it covers a lot of ground without indicating what’s likely to be of most impact. NICE CG56  – Multimorbidity: clinical assessment and management

2) ask of services, models and configurations

• home support / home care. Get people out of hospital as fast as possible so minimise decompensation.

• Adopting the why not home today, home as default mentality.

• Nuanced models of blended specialist / generalist… bespoke risk management for the most complex. The Commonwealth Fund are consistently publishing excellent material on models of care for high need cohorts.

Don’t neglect prevention – ignored at your peril. Wanless told us this 15 years ago. Disease incidence matters. It’s the number of cases rather than the average cost per case that is really driving costs. Illness and wellness approaches are needed. We know we usually neglect one in favour of the other, for all sorts of reasons. In a similar mould don’t ignore “healthy ageing” (in the broadest possible – not just a medical paradigm – construct at our peril. Most problems caused by lost fitness, preventable disease & attitude

Thinking in a prevention frame…. not just primary prevention. what’s the most likely LTC to develop first – presumably diabetes. If you have diabetes what’s the next likely LTC you’ll get? – presumably CHD. How do you prevent that (we know the answer). If you develop COPD first what’s the next thing you are going to get? – probably heart failure. How do we prevent that? Answer blood pressure. If you get CKD first … etc etc. But we don’t do that do we. If you have COPD we manage the COPD. We don’t manage the next worst disease risk. Somebody with diabetes plus CKD is probably next at risk of a stroke. How do we mitigate that risk? Answer blood pressure. Do we manage BP as a primary Mx aim? No we bloody don’t – we manage their HbA1c (which doesn’t correlate with any target outcome whatever). Only a third of those with DM + CKD have their BP managed to target – but guess what their HBA1C is managed to target – a stroke risk…….This seems the sort of prevention mindset we need to have in relation to MM.

• Don’t, really don’t, neglect mental health. We know it’s a massive deal. See here

See the Salisbury editorial on Karen Barnet’s seminal epi article. Well worth a read.  Multimorbidity: redesigning health care for people who use it

don’t over focus on risk stratification data driven models

See this cautionary tale from Guthrie and Mercer. Divided we fall: the commodification of primary medical careAllowing segmentation of general practice is a risky strategy with largely unknown consequences. It is Part of the case against one of the fundamental building blocks of population health. Tricky territory.

Also here on cyclical churn of people through different strata. A well known issue for those in the know. Predictive risk modelling under different data access scenarios: who is identified as high risk and for how long?

Simple ecological fallacy

This type of functionality is also important if we want to get our clinical teams focused on segmented risk management we need the analysis.

We over focus on using predictive model tools to try to identify risk in individuals and manage individuals. They aren’t very good there (predictive value not much more than coin toss). Ecological fallacy.

Risk strat and risk management is a population thing. Once you’ve got your strata, manage the cohort with interventions. When individual have needs meet those needs, but ensure good coverage of high value interventions across a cohort.

3) two approaches

a) Person centred care.

As well as clinical level, build it into the woodwork system wise. Training, expectations of system, incentives? As per above I must write the blog, it’s sooooooo important. Maybe Alf will do it for me. Maybe he already has.

I don’t think it’s at odds with a population approach, see here.

see the appendices of this excellent Richmond Group document for some thoughts on practical tools. NESTA are also writing amazing stuff in this space, most recently on good / bad help

b) population health management

• Models need to be population focused not service or organisation focused

• One decision point is weather the population health system is about managing risk and improving outcomes in those that are receiving health & care services (ie those who are poorly) or about the above and preventing illness in the first place (i e a whole population including care service users and citizens). Obviously both are important and necessary and the question is therefore about balance and focus. don’t ignore population risk management. Hyper actute stroke outcomes vs prevention of stroke

• Aim is to design models of service to manage risk,prevent or delay complications and improve outcomes in each of those segments. Move towards system to enable and interventions that manage population level risk (rather than refined pathways for xxxxxx), risk that is agnostic of the specific conditions. The default should be generalist, anticipatory care but supported by rest of system. There are 4 times as many complex patients in the community as there are in hospital beds. These are largely invisible in data and planning terms. But GP is looking after these.

WHOLE population.

Focusing only on high risk, top of triangle populations is a bit futile. In a health care context see Roland & Abel for the reason why. A focus on high risk is warranted, but don’t take eye off ball and neglect the low risk – as that is where the volume is. If you want to reduce the overal event rate by say 30% if you only focus on those at highest risk you need to reduce the event rate in that population by 160% – clearly mathematically and clinically impossible. Thus you need to aim to shift the event rate in the whole population by a small amount as well. Reducing risk in a small number of patient, even if at high individual relative and absolute risk of event, will have limited pop benefit

intervention matched to stages of change etc. consider stages of change (see for eg Lewis), impactability (see Lewis, Steventon & Billings) and Patient Activation

• The use of predictive / stratification tools is a given Segmentation is needed – see here revisiting segmentation. Primer on tools and methods, why and how.

Population medicine. What would a population healthcare approach look like for big targets – Heart, lungs, neuro, cancer. For example renal has been successful in the face of an inability to meet an ever increasing demand for dialysis capacity. The response was a sustained focus in on transplant, aggressive population management BP, CKD, CKD 3 to 4 transition, ditto 4 to 5 with a view to prevent and delay. What does this look like in the context of multi morbidity. It’s basically called “population heath management”

The population management of MM would benefit from more intelligent predictive risk analytics / risk stratification. The model we currently use does have ‘impactful’ LTCs as a predictor variable but doesn’t take account of LTCs in combination.

My sum up blog on population health is here

The Richmond Group document also has some excellent ideas re segments in there, though you have to get to the appendix to see them. See appendix c on clusters….i was struck by the warning at the bottom of appendix c

Appendix C: Multimorbidity clusters

Although there are limitations in the data that are currently collected,67 researchers are beginning to identify clinically relevant clusters. An early study carried out in the US,68 identified six multimorbidity clusters:

• A metabolic cluster including diabetes, hypertension, hyperlipidemia and coronary heart disease.

• An obesity cluster including osteoarthritis, low back pain, enlarged prostate, gastroesophageal reflux disease and obesity.

• A mixed anxiety-depression cluster with depression, PTSD and other anxiety disorders.

• A neurovascular cluster including peripheral vascular disease, stroke, transient ischaemic attack, Alzheimer’s disease and seizures.

• A liver cluster including Hepatitis B, Hepatitis C, chronic liver disease and HIV.

• A dual diagnosis cluster including substance abuse, alcohol dependence, schizophrenia and bipolar disease.

A more recent German study69 identified three overlapping multimorbidity patterns among older patients (aged 65 and over):

1 Cardiovascular/metabolic disorders including hypertension and diabetes mellitus (30 per cent of women; 39 per cent of men).

2 Anxiety/depression/somatoform disorders and pain including depression and osteoporosis (34 per cent of women; 22 per cent of men).

3 Neuropsychiatric disorders including chronic stroke and dementias (6 per cent of women; 0.8 per cent of men).

Almost half of the men (48 per cent) and women (50 per cent) in the German sample could be assigned to at least one of the three clusters, but there were also considerable differences between the male and female sample in terms of the conditions involved.

There are risks with this approach, such as over-focusing on conditions within a cluster to the point of ignoring conditions that are more likely to belong to other clusters. However, as the quality of research in this area improves, it could provide opportunities to design and implement better condition management programmes, improved clinical guidelines and other benefits for people living with multimorbidity.68

The other warning that isn’t picked up is whilst focusing on clusters is helpful from a planning type of perspective…. Again it may run the risk of upsetting the delicate balance between population based approaches to MM, not person centred… and all that stuff….. tricky…….

4). structural stuff

Don’t over focus on structure. We all know culture eats structure for breakfast. We all know we over focus on structure (form) at the expense of function. Make structure work for you and do the right thing

There’s deeply nhanced thinking that solution = structural integration. Solution is NOT the current model, nor is it structural. Danger of constant regression back to the 1) hospital model, 2) structural solutions to problems

Supply led care. Attention is needed to supply side considerations and ensuring we don’t neglect demand side (i.e. Primary care and social care). An approach focused on supply side and managing illness will likely end in bigger hospitals. Not many of the demand side interventions are showing much promise in short term time horizon. Should aim for 20% of NHS £ being primary care.

PRIMARY CARE – investment is critical, especially at the deep end

See my past blog on this. Esp see the recent paper by Mercer et al on consultation length.

RESULTS In affluent areas, patients with multimorbidity received longer consultations than patients without multimorbidity (mean 12.8 minutes vs 9.3, respectively; P = .015), but this was not so in deprived areas (mean 9.9 minutes vs 10.0 respectively; P = .774). In affluent areas, patients with multimorbidity perceived their GP as more empathic (P = .009) than patients without multimorbidity; this difference was not found in deprived areas (P = .344). Video analysis showed that GPs in affluent areas were more attentive to the disease and illness experience in patients with multimorbidity (P < .031) compared with patients without multimorbidity. This was not the case in deprived areas (P = .727).

CONCLUSIONS In deprived areas, the greater need of patients with multimorbidity is not reflected in the longer consultation length, higher GP patient centeredness, and higher perceived GP empathy found in affluent areas. Action is required to redress this mismatch of need and service provision for patients with multimorbidity if health inequalities are to be narrowed rather than widened by primary care.

5). How’s it all organised

For Example Key questions around frailty as an organizing concept. HT @muirgray

In the local population, who has overall responsibility for:

• Promoting frailty as a condition for which targeted interventions must be planned and delivered?

• Identifying individuals living with frailty?

• Planning care models to address key stages of frailty (pre/early, moderate or severe)?

• Identifying and reporting on measurable positive and negative frailty associated outcomes?

• Quality assurance and value for money of frailty care?

• Getting best value for money from the investment by caring agencies re frailty?

• How do we do the right thing for the patient and at the same time recognise that costs shift from health to social care?

Only thoughts what are yours

The ask

“The centre” (whatever that means) is full of metrics, measures, fear and fury about system focused priorities and targets (RTT, A&E 4 hr etc), and single illness specific areas of focus (CVD, cancer).

These are important things.

However there’s little to no focus of expectation from the centre on the central challenge in Health and Social Care.this needs to change

3 replies on “Designing systems for multi morbidity”

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