The number of hip and knee replacements required is increasing due to ageing populations, and as governments seek to meet demand and contain costs, there is a need to take a fresh look at how costs can be reduced whilst improving patient care. Currently clinicians make treatment decisions on hip and knee replacement patients based on their physical activity and pain levels but without having good visibility of those two indicators of patient well-being. If clinicians are given remote and time aggregated access to that information along with clinical analysis of it, decisions all along the care pathway can be better informed with the result that patient outcomes are improved and cost savings are realised.
by D. Heaton, Dr I. Revie and Dr M. Slomczykowski
Clinical need
Each year there are approximately one million primary hip and knee replacements carried out in Europe, with the number growing at over 4% annually. North America, the Middle East and Pacific Rim also have a significant and growing number of replacements. With an ageing world population, it is likely that the demand for hip and knee replacements will continue to grow while the funds to resource them become more scarce.
With this in mind, Activ4Life Healthcare Technologies Ltd, initiated discussions with clinicians to determine where there were areas for improvement. What they found was that the two key reasons for carrying out hip and knee replacements were to increase patients’ mobility and reduce their pain, both parameters that are not currently economically measurable over time. In addition to being a key reason for joint replacement, activity is a vital part of the recovery and rehabilitation process, but again, this is currently not effectively measured in patients.
As the ability to walk is a frequent discharge criterion, it is important to ensure that this is maintained in the period early after discharge when hospital staff are no longer available to provide support. It is important to ensure that patients continue to increase activity over several weeks to re-establish mobility. If patients do not show a clearly increasing trend in activity levels post-operatively there may be additional complications which warrant attention. Without sufficient exercise muscles will weaken leading to a poor outcome and the real possibly of a negative effect on the stability of an operated joint. However, over- exercising a joint early post-operatively can also be a significant risk to recovery, potentially damaging the integrity of the joint, in which case the life of the joint will be compromised, and a revision will probably be required.
Compliance with the prescribed exercise regime is important for patient outcomes and for reducing the costs associated with poor outcomes and/or revisions. Currently the only method of measuring compliance is by asking patients how much exercise they are taking. This is time consuming and unreliable, as it is subjective and reliant on the patient’s memory. Furthermore, patients who are not complying for whatever reason are unlikely to be detected until the damage is irreversible.
At present, clinicians have to make treatment decisions using minimal information based on ’snapshots’ of subjective measures of activity and pain provided by the patient from time to time, often at intervals of many weeks. What is considered very active by one patient may be considered inactive by another. Established scoring systems such as the Oxford Knee Score, Harris Hip Score and SF-12 are widely used and have some merit but they cannot provide quantitative trends that would show the rate at which a patient is declining pre-operatively, or if recovery is on track post-operatively. Moreover, there are very few published data on the activity characteristics of patients according to their different physical characteristics. For instance, what does the decline in mobility of a regular tennis player look like compared to the decline of someone who leads a more sedentary life, but is still in pain and frustrated by declining mobility? Obviously, there will be a broad spectrum of activity profiles for different patients. These need to be known and presented as a baseline for comparison as recovery progresses. Absolute measures of activity alone would be a step forward, but would not yield the ‘whole picture’ or maximum benefits. Clearly, more is needed.
If data on patients’ activity and pain levels were made visible to clinicians, and referenced to norms, treatment decisions would be better informed. This would improve many stages of overall patient care including triage of those presenting with joint pain; determination of optimal time for intervention; recovery prediction, appropriate exercise regime planning, exercise compliance monitoring, hospital planning and early detection of complications. Enhanced well as improved efficiency and cost savings.
The ProV3.8 monitoring system
Recognising these needs, the ProV3.8 system was developed to deliver effective reporting of patient activity and pain. Designed to be used on each patient for several months pre- and post-operatively, the system comprises three separate components:
• Patient hardware: a very user-friendly activity monitor and associated dock with a pain reporting facility
• Analysis against clinical “personas”: a comparison against a specific activity profile matched to the user
• Reporting: regular reports to the user and clinicians responsible for that user’s care
Patient hardware
At the start of each day the patient fixes the activity monitor to the waist, under clothing, using a double-sided medical grade adhesive patch. The activity monitor, about the size of a wrist watch and weighing only 15g, is unobtrusive and discreet. A 3-axis accelerometer and onboard processor are utilised to count steps and record each one against time. At the end of the day the patient removes the activity monitor and inserts it into the dock. This incorporates an integral mobile phone module that transmits the data to a secure server. At this point the patient is given the opportunity to record pain level for the day on a scale of 1 - 10 simply by pushing one of two buttons. There is no requirement for the patient to have an internet connection or any other equipment such as PC, PDA or mobile phone. The patient does not have to be familiar with modern communication technology demands on the user. All that is required is to wear the activity monitor during the day and place it in the dock overnight. Pain recording involves only the push of a single button.
Analysis against personas
Each patient’s data is compared against an assigned “persona”: a researched activity norm based on BMI, age, gender, operative state and lifestyle. This persona thus fits the patient’s characteristics, and is displayed with the patient’s activity data in the weekly reports. This persona profile is also used in setting patient activity targets, both pre- and post-operatively.
Reporting
Reports are generated from the analysis and show activity performance and trend lines against expected activity. These reports are delivered both to the decision-making clinicians and to the patient. Additionally, should activity levels fall outside predetermined boundaries, alerts can be generated to the clinician. Such alerts would allow an instruction to the patient to change their exercise behaviour appropriately. In the case of under-exercise this would improve outcomes; in the case of over-exercise a revision could be avoided in some patients.
How the reports feed into the decision-making process along the care pathway can be illustrated by considering the different phases of the patient’s care in Figure 2. The green line shows a typical long-term activity profile for a patient having a primary hip replacement.
• Throughout the period of care, remote monitoring and visibility of the patient’s well-being can reduce the number of visits to clinicians: primary care doctors, surgeons and physiotherapists.
• It is well documented that delaying intervention for too long can result in a sub-optimal recovery; the patient takes longer to recover and the eventual plateau of activity level reached is lower than for earlier interventions. The red line illustrates the benefits of operating at the optimal time; a sustained higher level of activity more quickly. Conversely, an intervention before the optimal time is inefficient as it increases the likelihood of a revision later in life. In addition, the benefits, as perceived by the patient, are less. Enabling an informed decision on when to operate will, in some cases, allow the use of conservative, lower cost treatment options in the short term, thus allowing those with a more urgent need to be referred to secondary care earlier.
• Limited healthcare resources means that patients’ activity cannot be monitored as closely as would be ideal and thus discharge planning is often conservative. The instant availability of activity trends during the hospital post-operation period, together with increased patient confidence from knowing monitoring will continue at home, allows an earlier discharge from hospital with associated cost benefits.
• If activity levels are much lower than expected, or pain levels consistently higher, alerts that there may be a complication are generated to the clinicians. Such alerts also notify patients and their surgeons of inappropriate post-operative activity such as excessive or too demanding or too early exercise.
• Once patients are discharged from hospital and are back at home, monitoring and reporting results in increased se|f-awareness, encouraging self-management of care. In the longer term studies have shown that people who are able to quantify their activity levels tend to take more exercise, the obvious resulting health benefits.
Summary
The implementation of this system allows better clinical decision-making for hip and knee replacement patients, leading to improved outcomes and cost savings from:
• Triage of patients presenting with joint pain
• A reduction in incorrect referrals from primary to secondary care
• A reduction in unnecessary procedures
• Quicker discharge from hospital
• Fewer post-operative visits to clinicians
• Quicker recovery post-operatively
• Informed patient self management
• Recovery to a higher level of activity
• Early detection of complications allowing more conservative treatment options and less remedial work.
• Compliance with common government policies of patient self-management, improved quality at lower cost, measurement of quality, better use of ICT and data management.
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