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Effect of patient app use on quality of care in rheumatic disease
Yomei Shaw
Friday, Feb. 1, 2019 · 3:16 p.m. · 16m 33s
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for the introduction uh so i uh thank you to the organised
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for inviting me to present today about uh the effects of
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a disease management apps on quality of care in rheumatic diseases
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it's okay
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so the the research that i'm going to talk to you about today
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uh the uh main goal was to uh investigate
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twenty stand whether disease monitoring apps uh in a remote taller g.
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can improve quality of care and by disease monitoring apps
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uh i mean uh mobile apps for patience uh
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the that to allow the patience to um
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uh oh allow patients to import a data about their symptoms
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and allow them to and uh that they it's mobile so they can do this uh anytime that they want um
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and uh then based on their inputs uh that the uh it can uh a score of
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the disease status the hell status can be calculated and tracked over time
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uh so these kind of apps are really exciting in theory
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ah uh the for improving the quality of care uh in we think that they can improve quality
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of care in two ways you think that um such apps can make air more effective
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my allowing doctors to see how the patient is doing a remotely
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and also by generating more data to inform treatment decisions
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we also think that these kinds of apps can uh make care more patient centred
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by empowering patience to get more involved in their own care and
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also by promoting a better communication between patients and physicians
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but the reality is that using apps comes with some costs you have
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to invest time and money into cleaning the apt you also
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have to invest a lot of time and effort into learning how to use a nap and to making making on data entries
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so this is why it's important to um understand
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can apps do the things that we hope they will too and
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um by finding the answers this question uh in a while
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you'll useful information for people who are deciding whether they want
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to use uh this kind of apps and also um
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uh some useful information for for people who are involved in designing apps and i
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thinking about how to optimise design of apps and um and and they use
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so the setting for study is the swiss clinical quality management rheumatic diseases registry
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s. e. q. um which follows i think about sixteen thousand patients
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um uh it since uh going from two thousand
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fifteen to the end of two thousand eighteen
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yes you can um offered it's patience to more while apps for a documenting
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their symptoms over time when using patient reported outcome measures are validated
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um and so there were two apps uh called i
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dialogue encompass uh oh yeah and uh one of
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them asked yeah one of them is used every month and the other one is used every week
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um and both of these apps allow patients to
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review their pass measurements um and physicians
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to access the patients input measures and i should i should say also that um
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in in this analysis i'm presenting we didn't uh and rise the two apps
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uh use separately we combine the the data from both
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and analysts together so here's a um a view of what uh the
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patient might see when they're using one of the apps i dialogue
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on the left you can see uh the patient is asked to answer a
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question about their fatigue symptoms and on the right you you see um
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uh and uh a chart of the patients disease activity status over time and so
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that's created based calculate based on uh the patients inputs answers to the questions
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uh_huh and here you see a a a view of what
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a fit uh and as you can physician sees when they log
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into the database uh that it's a it's a chart with
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with many many different measures thought it over time um and uh and you also see
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at the bottom uh uh the patients medications are also listed uh so uh_huh
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i'll show you here um is circled in red those are the points in time at which
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uh this patient had clinic visits and um all of the other points that
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are coming between those uh the the those where the red circles are
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our contributed there's a data point contribute by the patients at entries
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so you can see that's actually adding a lot of
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uh information uh for the decision to see how they patients doing overtime
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so we evaluated uh the apps using data for two sources the first was
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a survey uh administer to the patients uh going from a february to
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uh december of last year and this survey had some questions about
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the patient doctor relationship uh satisfaction with apps familiarity with technology
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uh and then the second is was was uh was the data that's collected regularly by the s. a. can database
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on a on a patient characteristics disease activity annotations
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um the outcomes that we were assessing
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well we're uh these five outcomes all of them are binary and so uh
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uh these are all desirable outcomes and the presence of them is what we were hoping to
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to to see um two of them are for a related to the patient physician relationship
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um uh the first one is uh uh a
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measure of satisfaction which shared decision making
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which uh was it's calculated um based on
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patients responses to um uh the survey questions asking them to assess how
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satisfied they were with the effort there is she is putting into
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uh understanding the health issues listening to them and and taking
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those um those issues in incorporating them into decisions
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then the next measure was um uh the satisfaction with falling evolution of
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the disease and um and that's also based on survey question
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then we have disease manager now comes which were low disease activity at the last visit reduction of disease
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activity in the last year of follow up and treatment intensification in the last six months awful
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well we divided the uh the patients into
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three treatment groups um those who
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uh did not we observe did not use any up those whom we observed two
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use a nap but whom did not uh discuss the update of with their position
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and finally those who uh both used in ah and also reported discussing the updated with a physician
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and um and to to determine whether they discuss the active their
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decision that was based on uh on another survey question
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and we hypothesise that um basically the non that users would have the worst outcomes
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and um the up only users would have a slightly better outcomes and
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and that the best group would be the hapless discussion group
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uh so to assess the impact of the uh tap use on the outcomes we use small time
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variant logistic regressions on and since this was not a a randomised study was observation all
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uh the different treatment groups were were not the same they had the patience in those groups have different characteristics
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so uh to account for that we um we use propensity score waiting
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uh and um these id you you can see the some of
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the uh factors that were included in the propensity score models
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uh age gender diagnose is we also included a
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factors such as clinic type and physician gender
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okay so the results um uh we hear the by the baseline
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characteristics of of the included patients uh we had about uh
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about two thousand patients um and uh i was about sixteen hundred did not use any out
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and uh one hundred twenty uh it you only use an up
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and then an hour plus discussion group one hundred fifty eight
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and uh uh one of the important differences was in h. and there was some other differences
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to not shown on the slide in um in terms of a medication use for example
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and here the on adjusted out can rates among the treatment groups
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so uh first i'm looking at the
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um the uh patient the the patient physician relationship analyses
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uh well i uh there's a higher rate a high
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rates of satisfaction among the hapless discussion group
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compared to non up users
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and uh we also find that there's a higher rates
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of uh apologise the they are wrong the wrong one a circle should actually be
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it should actually be this wanna apologise um there were high rates of trick an
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intensification among the um among the up only use compared to non up users
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here the uh results of the regressions
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um yeah so shown our odds ratios well comparing be
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up use groups to non at users and uh
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uh so the results are actually kind of similar to
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uh to the um to the uh to the wrong rates so uh
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the applet discussion group was more likely
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to be satisfied with your decision making and falling evolution of the disease compared to non at users
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and uh and all got apologetic and this is the wrong
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the wrong one circled a treatment in transcription a a higher uh
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more higher likelihood of people intensification on long up only group
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and for the uh a disease management outcomes
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uh they were they were not significant for the hapless discussion group but uh
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you can see that the the adjusted rates are are higher than one and that uh
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for uh if it's wrong it and apologise it should be this one circle
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they are higher uh the uh the it was close to being significant
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this result for improved disease activity among the hapless discussion group
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so so we found that the use of the apps without
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discussing updated with the decision tended to lower satisfaction
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uh this could be because maybe uh people who use taps um
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had high had higher expectations today physicians and when they
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ended up not discussing update with the physician
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uh that that made them less satisfied with with um
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with uh that mansion and of other disease um
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and i mean i think this is this is very interesting because uh it's sort of confirms
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some physicians worries about the introduce introduction of patient
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apps um some physicians are worried that
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uh and they and they about apps and they say if i don't really want to use somewhere i don't want them to be to use because
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if you send me this extra info from the patient then i have to do
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something with it and then if i don't i'll be playing so it's it's
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um it's if it's if you that you'll at that i've heard uh many times
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expressed by doctors and this is kind of supporting the food here um
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and and so if you're trying to convince decisions to be on board with such apps
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you you i it's probably not going to sell it to them if you just say well here's
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a cool that and it gives you lots of cool information you also have to say
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and i'm going to teach you how to use the information here's how to talk to talk about it with your patient
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um okay and and and so we also found that uh apt use
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plus discussion had positive impacts on satisfaction with the
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patient doctor relationship and improvement in disease activity
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uh so to summarise um uh the message that i think the state is
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telling telling us is that apps can improve the quality of care
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but they need to be integrated into care prostheses for all t. optimal impact
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um the needs to be more guidance to patients and physicians about how do you how
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to interpret information and then how to use it in consultations and in daily life
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uh so thank you for your attention and i'm happy to answer any questions or
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your comments are interesting greater covering the question for your show
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to your information uh uh why people choose not to use yes
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the ops yes the uh yes we do so um
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uh uh this is interesting too because the number one reason uh that people said that they
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they didn't use they chose not to use zap was that the physician did not inform
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and actually we we did have a uh uh some uh that some
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people who started to use zap after we given the survey
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so yeah so so that indicates to me that you really in the importance of getting physicians
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on board with with these kinds of things you it has to be uh something bad
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both physicians and patients see as as beneficial to him tighter
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so um i remain you've got the uh should be free tickets for ever lose
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room on the people over um it's no time for coffee break um
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uh_huh yeah okay so we stopped relaxation at four o'clock three started it
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yeah
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