Embracingthe Future

InnovatingHealthcare

September2018

From Diabetes Prevention 1.0 to Prevention 3.0The Case for Diabetes Prevention The rising global prevalence of type 2 diabeteshas placed acute strain on healthcare budgets,attracting the attention of US and UK policy-makers.The US National Diabetes Prevention Programestablished credible evidence linking lifestylechange with reducing risk of type 2 diabetesonset, leading policy-makers in the UK toestablish the NHS Healthier You DiabetesPrevention Programme. Prevention 1.0, wasgeared to helping those identified with elevatedblood sugar levels to create a lifestyle changeplan in face-to-face settings. Prevention 2.0 builton this by leveraging telehealth and nascentdigital-enablement to reinforce face-to-faceprovision with remote support.

Pushing the Boundaries of the PossibleHitachi’s diabetes prevention journey started in2010, when the company developed its firstdigitally-enabled service to support its employeesin meeting their wellness goals. Hitachi’sprogramme attempted to move provision towardstelehealth and digital-enablement (Prevention2.0). By bringing together a blend of telehealthcoaching and digital tools, Hitachi was able topersonalise the provision of care, whilst giving theiremployees the means to effectively self-manage

their lifestyle changes. Since 2010, the solutionhas been rolled-out to other Japanese corporatesand used as a foundation for Hitachi’s collaborationwith the NHS in England, aimed at leveragingclinical knowledge, remote telehealth and digitalsolutions to create a new model of provision, orprevention 3.0.

The Value of Data-Driven Insights Hitachi’s approach to digitising diabetesprevention established both data-driven insightsand dynamic intelligence at the centre of its digitalstrategy. Leveraging the latest in data technologyreinforced Hitachi’s collaborations with the NHS inEngland, by showing commissioners, providersand researchers its impact. Commissioners showeda quick willingness to engage with population-leveldata that could enable them to configure servicesfor hard-to-reach population cohorts. Providerswere equally as eager to engage with patient-leveldata in order to personalise pathways to maximiseoutcomes for their patients. Researchers saw thefuture potential that new data-points could bringfuture service studies.

Digitally EnabledPathway Personalisation:Data-Driven Insights,Dynamic Intelligence &Prevention 3.0

02

tion of smart diabetes prevention of smart diabetes prevenuuThe evolThe evoltion 3: tion 3: PrevenPreven

u lut t luun

T nt t

coachingthelehealTeleheal

Solutions

etailers

Digital

T

Provider

R

Community ugmenta

OSYSTEMCTH E

GETARTAR

LTH EHEAL

managementcondition Advanced

managementEarly condition

Prevention

ellnessW

outcomesSustainable improved

supportted Di�erentia

Augmenta

tientClient/PaearableW

taDa

Providers

coachingtheleheal

oolsToolsManagement

Teleheal

Self

tient

a

Client/Pa

en

earableW

ta

t

Da

.Vs

tient tient

th coachingeleheal Teleheal

Client/Pa

tion 2 0tion 2.0tion 1.0tion 1.0tion 0tion 0

YAYTODDigital Solutions

ProvisionLimited Prevention

outcomesSignifically improved

support

outcomesMarginal

all support

Client/Pa

supportNo

outcomestive

Personalized

tient

P

Client/Pa

Nega

One-size-fits

tion 3.0tion 3.0PrevenPrevenPreven Preven Preven

A

Preven Preven Preven

f2f Coaching f2f T

T

T

W

AI

Care

W

T

LAABLEABLE

tiontion ven ven

L L

n n nt

PeersNetwork

PeersamilyF

oolsToolsManagement

Self

tiona

OPDC

conditionsKidney

conditionsHeart

T2D

TEM

L EAM

t .0 0

d

TMa ent

YS SYSTEMSTEMSTEMSTEMYYYYTH ECOSTH ECOSTH ECOSTH ECOSLTH ECOST ABLED SCALABLED SCALY ENY ENLY ENY ENADIGITDIGITALLALL

VISIONVISIONVISIONVISIONOOOOPRPR HEALHEALHEALHEALPRPRLIMITED PREVENTION LIMITED PREVENTION

© 2017 Hitachi Consulting

tion. ormating digital transfor acceleratalyst ftor and a caT era business integra oT era business integratd., f Hitachi Ltion oganizaessional services orfoHitachi Consulting, the global solutions and pr

tionAugmenta

VVOOPO

YY MM S SYSSS SYYLT LT T Y N

H NA LY ENTTA A

OO NNRROVOVVVROROOO N

PN

P VISIONVISIONVISIONVISIONOOOOPRPRO PREVENTIVE O PREVENTIVE TA LLY ENNNNO N

PRPR E

OORROVOVOOD

HGAM-MSDS GEMENTGEMENTAA EMENTGEMENTMANMAN--MMSELFSELF

AL TOOLS FORAL TOOLS FORTAL TOOLS FORA TTA TA DIGITDIGITSELFSELF

RF- NANAGF A LTH ECOST

L P TTNN

AI n

is an Io

analysed at population-level, to inform assessmentof regional/local population needs, or at a patient-level, to drive service personalisation.

Progress DataThe second building block making-up a credibledata model provides a comprehensive log ofpatient activity data. This block is built up from self-reported patient datapoints automaticallyreported by smart IoT devices such as wearablesand scales. Data captured through IoT devices can,at first, be seen as providing more credible datathen manually self-reported patient data, however,a small number of patients who intentionally setout to ‘game’ the system are equally as likely tomanipulate data reported through such devices.This is one of the key reasons why digital toolsshould be regarded as enabling the interactionbetween health professionals and patients ratherthan replacing it altogether. Validating self-reporteddata becomes an important aspect of maintainingdata integrity.

Hitachi’s Smart Digital Diabetes Preventionsolution is designed to capture progress data,building-up a detailed picture of patient progressagainst ‘hard’ goals such as weight loss and bloodsugar levels (as measured by HbA1c indicators),as well as ‘soft’ goals such as agreed dietary andactivity goals. Progress data is used dynamicallyby Health Advisors to drive the support providedto patients during their time in service, focusingon the greatest areas of patient needs.

Engagement DataThe third building block making-up a credible datamodel provides information on how the patientengages with the digital service and its enablingtools. This includes a detailed log of digital usage –including the time and patterns of engagementwith the solution, usage of particular features, andany other patient interactions with the digital tools,including patient satisfaction/feedback loops. Thisdata, outside ‘hard’ clinical data, provides the bestproxy indicator for patient engagement with thedigital service.

The Role of Self-Reported DataThe global digitisation of healthcare has thepotential to provide vast volumes of data generatinginsights needed to personalise, enhance andoptimise healthcare services at a time whenhealthcare systems are coming under increasingstrain. The International Data Corporation hasestimated that healthcare data volumes are likely toexpand from 153 exabytes (1 exabyte = 1 billiongigabytes) in 2013 to 2,314 exabytes in 2020.1 Thedevelopment of IoT and wearable technologies,digitisation of the electronic health record (EHR) aswell as the electronic medical record (EMR),together with generic healthcare data generated bypatients will profoundly change the primacy of self-reported data. Clinical data alone, will no longeract as the sole determinant of how digital servicesare shaped in the future.

Hitachi’s Smart Digital Diabetes Preventionleverages data-driven insights, dynamicintelligence and data capabilities to reimaginehow diabetes prevention services are personalised,enhanced and optimised in the future.

The Anatomy of DataCohort DataThe first, and perhaps most important, buildingblock of a credible data model provides adetailed profile of patients being referred todigital services. This provides information on keypatient demographics, such as age, gender,ethnic association and broad geographic andsocio-economic groupings. A detailed digitalprofile of the patient also provides a detailedpicture of patients’ presenting clinical needs atthe point of referral.

Hitachi’s Smart Digital Diabetes Preventionsolution captures cohort data, building-up adetailed picture of patient needs, including clinical(weight, bloods, waist circumference, BMI) anddemographic data (age, gender, geographicallocation, ethnic group etc). Cohort data can be

see our website

03

Hitachi’s Smart Digital Diabetes Preventionsolution helps to builds up a detailed picture ofpatient engagement throughout their time withthe digital service. A detailed profile of patientengagement at a population- or cohort-level helpsto develop a picture of engagement trends acrossthe pathway, highlighting focus areas for the HeathAdvisor dialogue with the patient as well asopportunities for future service improvement.

Hitachi’s Smart Digital Diabetes Preventionsolution leverages cohort, progress andengagement analytics to help surface actionableinsights at population, cohort and patient-specificlevels in order to personalise, enhance andoptimise the digital service.

Co-Creation of Data-Driven Insights Building Working Trends Through Correlation Analysis Hitachi’s extensive experience in analytics, datascience, user-centric design and digital engineeringhas enabled it to construct a rich data model wherediverse data sets are combined and analysedthrough various means to surface actionable datainsights. Hitachi’s multidisciplinary team combinequalitative and quantitative analysis to evaluateinsights and identify potential opportunities forimprovement; correlational analysis is leveraged todevelop ‘working trends’ that can then be takenforward into service design workshops. Some of the‘working trends’ surfaced through Hitachi’s SmartDigital Diabetes Prevention solution are:

• Positive correlation between age, presentingBMI and weight-loss probability.

• Positive correlation between log-on frequency,proxy engagement and lifestyle goalachievement rate.

• Positive correlation between presenting BMI,log-on frequency in first eight weeks followingacceptance into service and weight-lossprobability.

Co-Creation ‘Working trends’ are subsequently ratifiedthrough service design workshops, whichleverage co-creation with commissioners, digitalteams and front-line Health Advisors. Theseworkshops draw upon a wide array of clinical,operational and user-led multi-disciplinarycapabilities to explore the ‘working trends’,scrutinise findings and verify opportunities. Theemergent improvement strategies represent aconsensus of opinion across those participating inthe workshops and provide the basis for serviceand solution improvement initiatives. Applyinguser-centric design methods and leveraging thepower of co-creation as part of Hitachi’s SmartDigital Diabetes Prevention offering, haveproduced some of the following insights:

• Patients with a BMI over 38 generally requiremore intensive support during the first 3months of their lifestyle change pathway.

• Patients showing low engagement with thedigital service in the first 2-4 weeks of serviceare often less likely to meet their lifestyle goals.

• Patients in the 60+ age cohort may requiremore support to engage with digital tools in thefirst 2-4 weeks of service but generally tend toengage positively where this support isprovided.

Bringing Together Insights to Build Dynamic Intelligence Data insights surfaced from a critical mass ofcredible data, provide the basis for delivering‘dynamic intelligence’ to commissioners (whethernational, regional or local), providers (whetherclinical or digital) and researchers. Access to areliable source of real-time insights can empowerstakeholders to take appropriate and timelyactions which help them improve delivery againsttheir respective goals. Similarly, front line staff canleverage intelligence in real-time as they deliverthe service to their patients, personalising theexperience to presenting needs, cohortcharacteristics and stated preferences.

04

Future of Data-Driven Insights & Dynamic IntelligenceApplication of Data-Driven Insights & DynamicIntelligenceHitachi’s Smart Digital Diabetes Preventionsolution is geared to help support futurecommissioning decision-making at bothpopulation and cohort-level. Actionable data-insights surfaced through dynamic intelligencecan help enable commissioners to:

• Determine the scope of support to beprovided, considering factors such as pathwayduration, frequency of active engagement andtypes of lifestyle support required to addressparticular cohort needs.

• Commission services which support bothdominant and minority cohort groups, such asgroups with particular accessibility needs(audio-visual needs), low levels or digitalmaturity or specific cultural / ethnic needs.

• Consider flexible pathways where the level ofsupport offered to patients can be personalisedand flexed dynamically during the pathway.

Hitachi’s Smart Digital Diabetes Preventionsolution is also designed to help:

• Personalise services to the presenting needsand preferences of the patients and enableHealth Advisors to respond to identified patientneeds during of the pathway.

• Further develop capabilities to support specificcohorts, whether demographic, clinical orotherwise.

• Leverage insights to help drive continuousimprovement and respond to the changingpatient needs over time.

Data Privacy & Machine Learning Generating working trends through correlationanalysis, data-driven insights through co-creation

workshops and dynamic intelligence throughcontinuous multi-disciplinary/cross-organisationalengagement is predicated on patients consentingto their data being processed for the purpose offuture service improvement and provision ofpersonalised services. Patients who decide not toconsent to this use of their data, or who withdrawtheir consent, would not be included in the above analysis.

Hitachi’s experience and knowledge in dataanalytics, data science, user-led design and digitalsolution design make it ideally placed to work withpartners and clients to leverage technologicaldevelopments in the nascent machine learning(ML) space. This will allow Hitachi’s Smart DigitalDiabetes Prevention to further benefit from futuredevelopments in ML to identify and propagateviable correlation analysis and so as to informfuture insights on patient needs, allowing for moreeffective care to be delivered at the right time,through the most appropriate channels.

Hitachi’s Smart Digital Diabetes Preventionmakes use of cutting-edge technologies and data capabilities to leverage multi-dimensionaldata to inform data-driven trends and dynamicintelligence needed to personalise, enhance andoptimise diabetes prevention services of thefuture within the context of Hitachi’s vision of‘Prevention 3.0.’

1 “The Digital Universe of Opportunities: Rich Data and the Increasing

Value of the Internet of Things,” EMC Digital Universe with Research

and Analysis by IDC, April 2014. Cited in in https://med.stanford.edu/

content/dam/sm/sm-news/documents/StanfordMedicineHealthTrends

WhitePaper2017.pdf

Innovating Healthcare, Embracing the Future

see our website

05

InnovatingHealthcare

Embracingthe Future

Hitachi ConsultingTel: +44 (0) 20 7842 7800Email: healthcare@hitachiconsulting.com Website: http://bit.ly/HSDDP Twitter account: @HIT_Consulting

see our website