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Putting Telehealth to the TestThe Lothian RandomisedControlled Trials
Brian McKinstry (lead), Martin Egan (NHS Lothian), Janet Hanley (Qualitative), Paul Padfield (HBP), Hilary Pinnock (COPD), John McKnight (diabetes), Cathie Sudlow (stroke) Sarah Wild (epidemiology), Steff Lewis (statistics), Marjon van der Pol (economics), Claudia Pagliari (e-health), Lucy McCloughan (programme manager), Aziz Sheikh (primary care), Bill MacNee (respiratory), Sandra Auld (telecare). Collaborators: Wisia Wedzicha (COPD), J Roca (telemetry), Martin Dennis (stroke), Martin Denvir (CCF), Colin Fischbacher (ISD), John Steyn (GP IT), Angela Lindsay (physiotherapy), Chris Burton.
• Brief exploration of the background to Telehealth
• Overview of our research programme
• What patients and clinicians think of telehealth
• Discussion about what is useful to measure and how to interpret such measures
Rise in Long Term Conditions
• 17.5 million UK adults are living with a chronic disease
• By 2030 the prevalence of chronic disease will double
So how do we cope?
•Policy drive towards self-monitoring and self-care
•Is self-monitoring effective?
Why does self-monitoring fail?
• Difficulty in maintaining motivation
• Infrequent feedback from clinical staff
• Therapeutic inertia
Remote server
Record of readings and symptom scores
Internet or SMS
Urgent referral if required
Constant monitoring of potentially unstable conditions (e.g. COPD)
Call centre
Relatively stable conditions (e.g. diabetes, BP) checked intermittently (normally by practice nurse
GP practicePatient takes readings and enters symptom score
Home
Call to check situation
Reminders to self monitorAutomated feedback
Links to online information
Models of telemetric supported self monitoring
Consultation arranged as appropriate
Telephone or videolink
Does it work?
• Do patients and doctors like it?
• Are outcomes improved?
• Does it actually save time and resources?
TeleScot Randomised Controlled Trials
– Hypertension • A common largely asymptomatic condition (n=400)
– Stroke/HBP • Affecting older frailer group with challenging targets
(n=400)
– Diabetes • A condition requiring multiple measurements, blood
pressure, blood glucose and weight (n=270)
– COPD • A symptomatic potentially unstable progressive condition
(n=300)
COPD monitoring
Each day, please record any WORSENING of symptoms from your usual daily level.
I am more breathless than usual
My sputum has increased in colour
My sputum has increased in amount
I have a cold (such as runny or blocked nose)
I have increased wheeze or chest tightness
I have a fever
I have an increased cough
I have a sore throat
<3 is OK
3-4 watch next day
5+ take action
Do the patients like it?
“I’ve never felt so well looked after in my life. I think it’s a godsend like.” (Patient aged 58)
“I don’t worry about him the same as I used tae. It’s all taken care of before it can get tae that level. That machine can tell Alec he’s ill even before he kens it hisself” (Spouse of patient aged 75)
“There’s some times you phone them up for an appointment ye cannae get one. . . So I feel if I’ve got that (telehealth device) I’ve got a chance of a doctor anyway.” (Patient age 75)”
What do the clinicians think?
Some concerns about workload
Worries about medicalisation
Concerns about false positives
Worries about the utility of physiological measurements
Some medicolegal worries
Workload
• Doubling of prescriptions of antibiotics, prednisolone
• Doubling of the number of times the record is opened
• But• Probably reflects previously undiagnosed
exacerbations
• Partly reflects non-optimised care
• Important to have a good existing infrastructure for management of exacerbations
Making sense of the symptom and telemetry data
• Some patients have difficulty distinguishing ‘bad days’ from exacerbations
• How do physiological measures relate to symptoms and exacerbations?
• What types of measure are likely to be helpful
• Is individual variation too great to allow setting parameters
Variation in events and dataSymptom Score
days
0 20 40 60
02
46
8
FEV1
days
0 20 40 60
0.6
0.8
1.0
1.2
1.4
Variation in FEV1
days
0 20 40 60
0.0
00.0
40.0
8
Symptom Score
days
0 20 40 60
02
46
8
Pulse rate
days
0 20 40 60
40
60
80
100
120
Variation in Pulse rate
days
0 20 40 60
02
46
810
Symptom Score
FEV1
Pulse
A sensible relationship!
Symptom score according to whether taking antibiotics
0.112065 0.112066 0.112068 0.112073
02
46
8
Antibiotics vs Symptom Score by individual
Antibiotics
0 1
02
46
8
Antibiotics vs Symptom Score by individual
Antibiotics
Sym
pto
m s
core
---
---
No Yes
Currently taking antibiotics?
Clinician Concerns
• “Spirometry..which I can’t imagine anybody would do properly. I mean how can they do that properly (at home).”
• “Scores are only part of the picture. You need to see the person as well”
• “You really need a sort of second layer (VC) to make sense of the scores, and decide if they need a visit. M’s scores are OK but I know.because I spoke to her that she’s really bad. Others score high and they’re fine”
• “I think anything that gives better information more quickly is a good thing. But that’s the thing with information, if it’s not passed on to somebody then it’s NOT a good idea, so there have to be good procedures in place for making sure that the information goes to whoever needs it”
Conclusions
• Patients like Telehealth
• It encourages evidence based practice and quality care
• Telehealth systems need robust underpinning structures to observe and manage the data provided
• They may not save time/resources in primary care
• We need rigorous research to discover where and how the systems are best applied and which physiological measures are best employed