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KANT BerliN

HealtH

The reporT

TABLE OF CONTENTS

1. IntroductionHow to read this report

2. TrendsKey developments

Software and mobile applications.Hardware and self tracking gadgets.Data sharingTelemedicineAugmentation

3. The changing environment of health careTracking Personal DataSelf-managing your illnessManaging medical service providers

4. The Patient ExperienceChanging behavior through motivationDealing with sensitive data

5. SoftwareApps

FitnessTracking & The Quantified SelfHealth managementSymptom analysis & background information

Big Data changes how medical software worksSoftware for medical service providersElectronic Health RecordsOpen-source Electronic Health RecordsPatient-controlled EHR'sDeveloping software in a regulated environment

6. HardwarePersonal TrackingShaping OutcomesEasing the Burden

7. Key Challenges and BenefitsChallenges

Privacy and ConfidentialitySecurity

BenefitsA more complete pictureEfficiency & autonomyBetter Research Data

8. Outlook / What to expect9. KANT

10. About the AuthorsAlper CugunChris EidhofMartin SpindlerMatt PattersonPeter Bihr

INTRODUCTION

This report aims to cover (primarily technology-related) macro trends in thelarger health space. As "health" is a vast space or industry, our mental model –and the terminology we used – when approaching the field is this:

Health: The traditional health industry as dominated by insurance andgovernment-based health system; the heavily regulated end of the spectrum.

Fitness/lifestyle/sports: The largely unregulated, more consumer-driven part ofthe industry that includes a wide range from the dietary to the brand-related(Nike+, etc.) to personal analytics and the Quantified Self. This is the much morevague and permeable area, and we approached it as such.

The health market is huge. In Germany alone, the health industry spending(including health, prevention and treatment) contributes close to 300 billionEuros to the German GDP. This does not include the fitness & lifestyle markets.

What we see is that the lines between health and fitness/lifestyle markets areincreasingly blurred. This is particularly true where technology empowersindividuals by giving them access to information about themselves – their bodyand behavioral data – and the tools to analyze that data. This is information thatused to belong firmly in the hands of healthcare professionals.

The umbrella terms Quantified Self and personal analytics, driven by increasinglycheap and ubiquitous sensors, are just one set of examples of where individualstake more responsibility and get more active in their health management. Thisgoes from tracking heart rates and the speed of a run all the way to personalgenome analysis. When these well-informed, active users seek out a doctor, theyexpect that encounter to be on eye-level. As patients, their expectations of theirdoctors differ wildly from former generations.

The relationship between patient, medical professionals and the healthcaresystem is changing dramatically. This means doctors needs to reassess theirpositions and find ways of incorporating empowered patients into the treatmentprocess. It also means that new business models emerge and are evaluated in amarketplace of ideas. New key players entering this market range from sportsbrands (Nike+) to technology startups (FitBit, Withings) to small teams ofsoftware developers who produce smartphone or mobile apps (Massive Health,etc.). And even established vendors of medical equipment are re-evaluating theirstrategies.

The landscape is changing. With this report, we attempt to provide a map tonavigate this rapidly changing space.

HOW TO READ THIS REPORTThis report is the result of a so-called topic sprint, based vaguely on the booksprint methodology: Five authors writing for one full day in a highly collaborativefashion.

We wrote it as an introduction and overview into the macrotrends shaping thehealth and fitness (as well as related) industries. If you work in these industries –be it on the insurance side, at a technology company, at a publisher within thesector or at a brand in the field – this is for you.

We aimed at giving you an easy-to-read, quick introduction to what we seehappening in the space from our specific perspectives. To learn more aboutthese perspectives, see the author profiles at the end of this book or our websiteKANTBerlin.com.

TRENDS

Two of the macro trends we see driving these developments are:

(1) Data - the massive amount of data available through ubiquitous sensors (insmartphones or dedicated devices) and other connected devices (Internet ofThings), made actionable by apps and web services

and

(2) Empowered users (rather than the more passive notion of “patients”) that arein a position to actively manage their health based on better informationavailable from external sources (professional and academic research, experts,peers) as well as through tracking their own vital signs and behavior.

These drivers both influenced and are influenced by more granular trends andinfluences on a technological level (both through advances in research andthrough adaption of emerging technologies), as well as through a changing self-perception of users and healthcare professionals.

KEY DEVELOPMENTSLet’s highlight some of these trends and implementations.

SOFTWARE AND MOBILE APPLICATIONS.

According to a Gartner study from August 2013, global sales for smart phonesexceeded sales of feature phones for the first time ever. This makes thesmartphones of today the predominant computing platforms and we can expectthat vendors for medical software will adapt to this trend. We also see a growinginterest in web-based consumer-focussed health platforms and fully expect thistrend to continue. (See the Software chapter for more detail.)

HARDWARE AND SELF TRACKING GADGETS.

Smartphones serve as personal computing hubs that connect sensors andfitness devices with users, each other, and the internet. The smartphone hasbecome the backbone of the Quantified Self. (With their array of built-in sensors,smartphones also are one of the primary tools of capturing data.) It is likely thatwe will see the role of the smartphone increase from the fitness & lifestyle areainto a tool that helps manage the patient-doctor relationship as well. On theother hand, there is a growing array of dedicated health devices, many of themconnected (via smartphone or directly to the internet). (See the Hardwarechapter for more detail.)

DATA SHARING

Among users of data-intensive services awareness is growing that ownership ofdata is an issue worth paying attention to. Who can access data, who can shareit, with whom and under which circumstances? Can the service provider shareuser data with third parties for commercial and marketing purposes? Can usersdownload their data in useful formats? Are services built with data exchange andcompatibility with other services in mind and offer an API?

TELEMEDICINE

Remote, tech-supported diagnostics ranging from “remote visits to the doctor” tosending vital signs data to the clinic for analysis. A prominent and promisingexample is Molly, an experimental avatar-based research project by the SanMateo Medical Center that aims to replace visits to the physical therapist forpatients living remotely or unable to visit the doctor. Molly is able to watchpatients’ movements through Kinect, a 3D-capable movement sensor originallydeveloped for a game console.

AUGMENTATION

Augmentation of physical capabilities is certainly the yet least developed area,but also one with tremendous potential. With massive developments in thedexterity of artificial limbs and the fidelity of cochlear implant hearing aids tomore subtle augmentations like insulin sensors embedded in the body, we canexpect a big wave of innovation here.

THE CHANGING ENVIRONMENT OFHEALTH CARE

The relationship between the health care provider and the patient is changing.Patients are taking matters into their own hands, and are better informed thanever before. They track personal data, have access to the vast resources on theinternet, and self-manage their illnesses. While dealing with empowered patientsmight take some getting used to for traditional medical professionals, there aregood reasons for doctors to embrace their users’ favorite health apps.

TRACKING PERSONAL DATAWith the advances in technology, personal data tracking is nearing ubiquity.Many individuals already track heart rate, sleep patterns, blood pressure, foodintake and many more variables. They know how their bodies react to changes,and have this data ready before going to a health care professional.

SELF-MANAGING YOUR ILLNESSWith the vast information available online, many patients already started to takematters into their own hands. People with chronic illnesses use their owntracking devices to manage their illnesses. With smartphones, there's an app fortracking almost any variable, and patients use that to gain insight into theircondition. For example, diabetes patients track their food intake and correlatethat with their blood sugar levels to find out what causes spikes.

MANAGING MEDICAL SERVICE PROVIDERSWhen individuals become chronically ill, it is also common that they managetheir own team of service providers, such as doctors, insurance companies andother advisors. In case of serious illness, it is also common that the family getsinvolved in managing the teams. Individuals and their families use the internetto search for possible treatments and other healthcare professionals.

THE PATIENT EXPERIENCE

The patient experience is a key part of the health ecosystem, and experiencesfrom the traditional field of user experience are increasingly being translatedinto the health space. When designing services in this area, it is essential todesign towards concrete goals and behaviors to sustainably influence behaviorin positive ways.

CHANGING BEHAVIOR THROUGHMOTIVATIONChanging behaviour is often desired either by a person themselves or thirdparties. In both cases it is rather hard to achieve due to all manner ofpsychological factors. Self-Determination The ory (SDT) is a psychologicalframework which puts the needs and desires of the user at its cen tre and pro -vides a good frame work to ask the right questions to have a chance of creatingbehaviour change.

The basic needs for intrin sic moti va tion accord ing to SDT are:Auton omy, allow ing peo ple to con trol their own directionsCom pe tence, help ing peo ple become bet ter in things and giv ing them feed -back on itRelat ed ness, sit u at ing people’s actions in a social context

Autonomy is essential because people will tend to resist doing anything basedpurely on external pressure. Being able to choose goals to work towards createsthe necessary intrinsic motivation that is required to create behaviour change.

Competence shows people how far they are into creating the change they want.Because change is hard to achieve people will have to start with small steps toreach the goal. Feedback on the progress towards the ultimate goal helps breakdown the task into manageable steps.

Relatedness finally is a way to help people relate their actions to others and tofigure out how they are doing individually or as a group. Social software inparticular has a lot to add to this part of SDT. Surfacing their own and their peergroups activity and performance can work wonders. Social pressure andcompetition are powerful motivators.

DEALING WITH SENSITIVE DATADigital healthcare means the collection of large amounts of data. Data yieldsgreat benefits but it also carries with it a lot of issues that commissioning partieswould rather ignore. The idea of having a turn-key solutions that work withouthesitation is too seductive.

Some issues to consider when dealing with collection and management of data:

Data applications in their current state often do not yield any more insight thanwe already have. Many applications of data yield patterns that we already knew.This is caused by a limitation in the explanatory power of data applications.Often data is processed and presented in the wrong way to be able to drawnovel conclusions from it. New presentations or visualisations of data arecreated in a supervised fashion and the creator applies their interpretation toreach a certain goal. This interpretation guides the data collection andpresentation towards a known entity and is the reason why we often get thingswe already knew. Data needs to be interpreted and translated into actionableoptions.

Even though it may appear that adding more knowledge and modeling to thedata processing will give us better results this is not necessarily true. Addingmore factors to a model improves the results only to a certain point. After thispoint added information actually reduces the explanatory power because ofover-modeling. Throwing more data after something therefore is not a solutionto all the problems. The key is to find the right balance between quantity andquality.

Reliability and incentives: Anytime the data or the results from the data areoutput to people who have a certain interest in the outcome or who are thesubject to a power relation, they might have an incentive to massage the data insuch a way that it will provide them with an advantageous outcome. This is aphenomenon that is known as ‘juking the stats’ and it has destroyed many well-intentioned projects from bearing fruit. To prevent this, service designers shouldbe very careful – if not outright reluctant – to automate consequences from datainference and to use data in way that support power relations. Again, balancingincentives and data capturing/analysis is essential.

Data often flows through complex, winding systems, in and out of institutionsbased on organically grown processes translated from a paper-based into thedigital world. In many cases, any one institution does not have an in-depthunderstanding of the extent or scope of the whole system. (They might counttheir blessings if the system just works.) Sometimes parts of the system evenchange in ways that aren’t necessarily transparent to some other parties – mostoften the patients – who might not have consented. There are plenty scenariosin which a patient’s data could be used in ways that were previously unexpectedor even undesirable for a patient.

As it is nigh impossible to fully understand these systems, all the related termsof services involved and the potential implications of how their data might beused in the future, trust is essential. Trust between patient and medicalinstitutions as well as private service providers needs to be earned and fostered.Patients should never be forced to adopt a defensive stance.

The most promising way to create a favorable outcome is to legally guaranteebasic rights. The data should be ultimately owned by the person it’s about. Theconsensus between patient and health provider should be for patients to allowuse of their data in exchange for being able to take the data out and to otherservices whenever they choose to, in standardized formats.

SOFTWARE

The software field in health is extremely varied. At one end we have the personalfitness and healthcare apps for the home and for personal devices: softwareapps with a hardware component like the Withings connected scale and even WiiFit and software-only apps like Massive Health’s Eatery. At the other end are thepatient record management systems used by primary care providers like familydoctors, the similar but vastly different in scale systems used by healthinsurance companies, like Kaiser Permanente HealthConnect, or the NHS in theUK, and clinical software for providing information to assist diagnosis or drugprescription.

To try and make sense of this, we’ll cover the two ends of the spectrumdifferently. At the personal end we'll talk about the specifics of developing appsfor personal fitness and health at the non-clinical end of the spectrum: the kindsof apps that are not subject to regulatory approval or constraint, which is to saythe kind of apps that you can use but your doctor can't. At the large-scale clinicalend we'll talk about the general challenges and look at some of the successesand failures in that space.

In the in-between space, developers build software for use in applications likeclinical research trials, and primary care doctors buy in software for their ownpractices. We'll look at what it means to develop software under a complexregulatory framework, and what some of the particular needs of those users are.

APPSApps, short for applications, is a catch-all phrase software running on mobiledevices. All leading mobile vendors allow for third-party applications to beinstalled on their platforms. Most current mobile phones are equipped with avast array of sensors, for tracking location, motion, voice and cameras on thefront and the back, and these sensors are available to software developers.

Currently, there are about 25,000 apps on the Apple App Store in the category"Health & Fitness". Most of these apps are targeted at prevention and stayinghealthy, by tracking certain of the users' variables. A quick glance at the top listsshow that the apps can be divided into the following categories:

FITNESS

There’s a multitude of apps that aim to assist in fitness programs, either bycapturing data during the workout and analyzing it afterwards, or by givinginstructions during training sessions. Differences also exist in how workouts aretracked, that is, whether the user is supposed to enter training sessionsmanually, or whether the smartphone app will monitor activity in thebackground, as it is usual in most bike or running apps.

One recent development is apps that track what users do on a permanent basis.

A prime example of these apps is Moves, which analyzes the type of movement(biking, running, walking, or other forms of transportation) and gives their usersfeedback about their day and shows the extent of their baseline activity.

The other big theme in fitness-related apps are instructional apps that show howto perform specific workouts. The advantage of having these instructions in anapp (compared to traditional forms such as DVDs or books) is the accessibility ofthe instructions.

TRACKING & THE QUANTIFIED SELF

Also referred to as personal analytics, Quantified Self or tracking are termsdescribed to capture the increasing ability to track body and behavioral data(pulse, heart pressure, steps taken, food intake, etc.) through sensors embeddedin smart phones or dedicated devices (Jawbone Up, FitBit, etc.) or throughmanual data entry (for nutrition tracking apps like The Eatery). By tracking dataover time, individuals get insight into their personal history with minimal effort.To learn more about the Quantified Self, we recommend the sitequantifiedself.com

One app that helps people track their food intake is Foodzy with which peoplecan easily keep a food journal on their phones while other efforts have focusedon people taking pictures of their meals for either others to validate or for thesystem to determine automatically based on image processing and statisticalinference.

There are tools and websites to track more or less anything imaginable, frommood and exercises to stool and sex – there is hardly a bodily function that isnot subject to digital tracking.

HEALTH MANAGEMENT

For diabetics, tracking their body functions is nothing new, but getting automaticmeasurements of their insulin levels sent to their phone or even automaticinjections can make their lives a little bit easier. For individuals that use regularmedication, apps and devices like the GlowCap help users manage their taking ofmedicine by setting up reminders and alarms. Women can track their periods viaapps and connected thermometers and can use that software in helping themdetermine their fertility.

SYMPTOM ANALYSIS & BACKGROUND INFORMATION

Apps can also enable patients to self-diagnose, or to support them in theirevaluation of potential health issues as well as to better inform themselves.Ranging from apps helping with diagnosing sources of pain or identifying skindiseases all the way to guiding young parents-to-be through all stages of

pregnancy, there exists a plethora of applications on any particular health issue.

The methods used are manifold. Some require the user to answer questions,others automate the process further by, for instance, analyzing photos of theskin to determine chances of skin cancer or other less critical diseases.

BIG DATA CHANGES HOW MEDICALSOFTWARE WORKSFor finding trends on a larger scale, social networks and big data analysis allowfor unprecedented prediction of trends. This includes analyzing flu outbreaksbased on twitter data or Google searches, or analyzing drugs experiences basedon crawling websites. Cloud services like Amazon Web Services make it possibleto rent a lot of computing power for any desired amount of time, thus allowinganalysis of large datasets without having to build and maintain expensivehardware infrastructure. Startups like 23andme offer genome sequencing toindividuals and thereby increase the analytic base for genetic research and thusmake it much easier to identify potentially harmful variations in the humangenome.

SOFTWARE FOR MEDICAL SERVICEPROVIDERSThe legal, regulatory, and structural differences between different countries,even within the EU, mean that there are a lot of smaller, local providers ofElectronic Health Records (EHR) and similar software for primary care providerslike family doctors, and even small hospital groups. There are too many playersto cover here, but for more information you may well find that local news mediawhich cover healthcare will have a decent overview, for example The Guardian'sUK healthcare coverage.

What's important to note is that many of these companies share similar origins:spun off from software built in-house by healthcare professionals for a specificpractice. They also seem, as a general rule, to be modelled after traditionalenterprise-y software: powerful, but complex and hard to understand and use.

ELECTRONIC HEALTH RECORDSThe core part of these systems are concerned with capturing, storing, andpresenting patient data. The aggregated data for a patient is generally called anElectronic Health Record (EHR). EHR’s consist of everything from notes taken bydoctors, data logged by heart rate monitors, to X-Ray images.

Many governments are aggressively lobbying for the adoption of EHRs. The USgovernment has offered incentives to early adopters working for Medicare, butwill penalise providers after 2015 if they are not using EHR's.

The UK's NHS tried to implement a central, national, EHR system which failed

after several years at a cost of £12bn. One of the key reasons as stated by theUK Department of Health: “... we need to move on from a top down approachand instead provide information systems driven by local decision-making.”

We see a trend for open-source systems to be adopted by large organisations orgovernments: The US Veterans Health Administration system, VistA_EHR, isopen-source, and has been adopted by the Jordanian government. Parts of theUK's NHS are now considering adopting it, after the failure of the nationalsystem.

OPEN-SOURCE ELECTRONIC HEALTHRECORDSWe see are a lot of standards around EHR at ISO (ISO 18308 and many otherstandards under ISO/TC 215), CEN (EN 13606), and ANSI (many HL7 relatedstandards). Some are concerned with how to capture and store data, some withwhat to capture, and others with how to transmit that data betweenorganisations.

There are, unsurprisingly, many interoperability problems: While many standardsspecify data formats and structures, the way different systems use thoseformats can vary widely and often mean that two systems which use the sameformat to store or exchange records can't meaningfully do it. One organisation'srecords are gibberish to another's systems.

Open-source initiatives like the openEHR Foundation are attempting to solvethese problems by providing specifications and implementations, intended toprovide the building blocks of distributed and interoperable systems.

This is still an organisation-centric view of the data though: Healthcare providershold patient records for their own use. Patients themselves may well be unableto access most, or any, of the data held about them.

PATIENT-CONTROLLED EHR'SThe Australian government recently launched a system called The PersonallyControlled eHealth Record System, a centrally-provided system that allowspatients who opt-in to the system to control who can access, or even knowabout, their personal data.

Currently it's only summary data, and full records are held by individualinstitutions still, but it's indicative of what we think the future will hold:

Encryption used to secure personal data and to manage access to itCryptographic signing used to ensure that people's data hasn't beentampered with, either by themselves, by institutions or by third partiesGovernments providing cloud-like storage and APIs for these records

The UK's NHS central IT provisioning department N3 already provides an NHS-specific cloud compute platform, ideally placing them to offer a central API-oriented service.

Personally-controlled EHR's which allowed for patients to input data too opensthe door to formalising and integration many of the Quantified Self practiceswe're seeing emerging elsewhere, as well as offering the possibility of better caredelivered in part through better data: both richer and more frequently sampled.

DEVELOPING SOFTWARE IN A REGULATEDENVIRONMENTThere are several distinct areas of regulation that might affect software, and ofcourse these will vary by jurisdiction. In the US, for example, software forkeeping records related to clinical research trials of new drugs are subject to theFDA's Title 21 CFR Part 11, while software to run on a 'Medical device' must meetIEC 62304. EHR systems must comply with a host of standards under Title 45 CFRPart 170.

These standards typically mandate that their various criteria must bedemonstrably met. This usually means that you have to be able to documentwhat you say the code will do and trace through from that to the relevant part ofthe code, along with proof that it does do what you say.

While the standards don't generally explicitly mandate a particular way ofworking, most were written while traditional 'Waterfall' style softwaredevelopment methodologies were the norm, and often appear to endorse that.However, the basic requirements of feature, or point of compliance, tied to thecode and proof of its function can also be thought of as akin to the 'outside-in'approach of Behaviour Driven Development, combined with a rigorous approachto documentation. One of this report's authors consulted on a project anddeveloped documentation using this approach, and the initial results were verypromising.

Given the documentation and QA burden traditionally associated with regulatorycompliance, an approach based on generating compliance documentation as aby-product of product design and development, rather than with a post-hocscramble, has the potential to yield significant competitive advantage.

HARDWARE

With the onset of cheaper microprocessors and increasingly pervasiveconnectivity, the health environment is seeing massive changes in terms of thecapabilities of medical equipment. Following the trend line of consumer devicesand utilizing advances in mobile computing and information display and capture,healthcare has so far only seen the tip of the iceberg when it comes totechnological adoption. There are, however, promising steps to bring labour-intensive tasks in medical care up to date and adopt more automation.

A lot of data can already be captured passively by connected devices, andincreasingly, that data is relevant for the well-being of individuals, be it inpreventative care or under clinical conditions. More data, captured passively, canalso mean a better understanding for a patients baseline data and well-being, aswell as freeing up capacities that would otherwise be devoted to manuallycapturing vital signs from patients.

PERSONAL TRACKINGWhen talking about connected devices in the healthcare environment, the samedistinctions as touched upon earlier apply: there are big differences in speed ofexecution and exploration of potentially interesting avenues depending onwhether companies or vendors target individual users in the unregulated fitnessmarket, or whether they target medical professionals which operate underconditions of regulation, peer-review and cost-pressures by the health system.Participants in this segment of the market is much less likely to lend themselvesto experimentation. Any company trying to enter this market needs to make aconscious decision as to which part of this spectrum which does not have aclearly defined boundary they want to fall on.

Recent years have seen an onslaught of personal fitness devices which havedeveloped to measure far more than just fitness performance. What started, inthe consumer market, with specialised products for runners, such as the PolarHeartbeat monitor or the Nike+iPod has matured into an industry that farextends sports, but still notionally focuses on fitness and the well-being ofindividuals. Companies likes Withings have started manufacturing a whole rangeof devices that ease the consistent collection of vital signs, be it with their debutproduct, the Withings Smart Scale, which makes it easier to track thedevelopment of an individual’s weight, or more recently with a connected BloodPressure monitor, that automatically uploads its measurements and makes itthus possible to easily have longitudinal data on a crucial health indicator.

In conjunction with the rise of the “Quantified Self Movement”, a lot of pervasiveactivity trackers have come to market as well. What started with the FitBit as ameans to regularly remind info workers to take breaks and exercise, and tomake data about their actual exercise available to them, has blossomed into avaried product range, that capture all kinds of vital signs, with the mostcomprehensive probably being the Basis watch which sports sensors for heartrate, skin temperature, perspiration and a 3-axis accelerometer and thus claimsto give insight into general activity, stress levels and quality of sleep.

SHAPING OUTCOMESConnected devices aren’t necessarily restricted to measuring and collecting data,however, but can drive behaviour by the actions that get triggered by them, andthus change outcomes. One of the best illustrations in this regard is the VitalityGlowCap – basically a connected cap for pill bottles and a companion basestation. The GlowCap monitors whether medication is taken in adherence withthe schedule, and will start to blink and make sounds if the patient has forgottento take their medication. If, after two hours, the patient still hasn’t taken theirpills, it will start a social feedback mechanism of first having a call made to theindividual by Vitality’s service center and then alerting previously specifiedrelatives. It also gives healthcare professionals much better insight into thecompliance of their patients.

The GlowCap is a good example which sits right at the intersection of privatelymanaged, unregulated “gadgets” and regulated “medical equipment”.

In the regulated health care industry, similar approaches will be fruitful.Automatically having a pulse or blood pressure reading committed to a patient’smedical history file without human intervention would free up time with medicalstaff and reduce the chance of mistakes in transcribing the measurements. In ascenario of hospitalized patients, this could go even so far as the patient, bymeans of a Bluetooth Low Energy-equipped bracelet, identifying himself to themeasurement device and thus reducing the probability of mistakes even further.

EASING THE BURDENMaking the life of diabetes patients easier and safer is another avenue which isbeing explored. The AgaMatrix Glucose Meter, for instance, is an iPhoneperipheral with a companion app. The measurement of your blood glucoselevels works just as usual with this device. It’s ability to utilize the capabilities ofits host mobile computing platform, however, allows it to combine themeasurement with all kinds of other data, and automatically log it for you. It’snot especially hard to imagine an insulin injection kit which automatically adjuststhe dose to be administered on the last reading and the historical trendlines. Itcould also be possible to use additional information, such as workout data, orlogged meals consumed. A more granular, and more accurate, view intolongitudinal blood glucose data would also allow healthcare professionals tomake much better determinations about the current status and future prognosisof an individual patient.

KEY CHALLENGES AND BENEFITS

CHALLENGESMore integrated systems of data capture and storage require differentapproaches to data management, disclosure and security. It is not sufficientanymore to just assume security as it could be in times of locked-away paperrecords. Platforms that actuate on specific parameters, like pacemakers orinsulin pumps, need to be sufficiently secure as to avoid security exploits thatcould cause bodily harm.

PRIVACY AND CONFIDENTIALITY

One of the main concerns regarding Electronic Health Records is who getsaccess to these records. After all, information about a person’s health conditiontends to be one of the most private and guarded sets of information, oftenprotected by special patient-doctor privilege which prohibits medicalpractitioners to disclose even the faintest bits of information about the status ofparticular patients without court warrants.

However, there are multiple third parties which have vested interests in gettingaccess to data about patients, be that on individuals or in anonymizedaggregates. Special care needs to be given to latitudinal data that tries tocombine a breadth of data across large parts of the populace to look intopotential early warning signs for the onset of specific diseases to not accidentallyde-anonymize and make individuals identifiable. (As studies have shown,relatively few data points can be sufficient to identify individuals.)

These considerations need to be accounted for even when developingapplications that fall not strictly within the realm of regulated health care. Asresponsibilities and management of healthcare fall more and more inside thepurview of individuals, the concerns that traditionally only applied to medicalprofessionals do, too.

SECURITY

As with any technological development that relies on computerized equipment,safety and security concerns need to be taken serious. Even more so as a lot ofmedical equipment has the capability to cause actual bodily harm or death ifmalfunctioning or compromised. Examples exist of poorly secured pacemakersor insulin pumps that were almost trivial to exploit. Luckily, those exploits havenot been visible in the wild. However, the question of security is one of the mostsalient in the discussion around a changing healthcare environment. It isimportant to note that the security of any particular technical device does notrely on the security features of that device alone. Accuracy of data must be

assured, if that data is relevant to the operation of a device, and it might benecessary to establish data provenance.

Security is also important in terms of measuring devices. Professionals need tobe able to rely on data collected by devices, and thus these devices themselvesneed to be secure and tamper-proof. The same is true for data transmission andstorage.

BENEFITS

A MORE COMPLETE PICTURE

As we gather more data, a more complete picture of our health emerges. Thisgoes both for the individual and the societal level: Aggregate, longitudinal datapaints a much clearer picture of the state of our health over time. This kind ofdata is priceless for research.

To enable individuals to make most of this data, app developers and serviceproviders need to make sure they capture, analyze and present the data back tothe user in actionable form. In other words, it needs to be clear at any time notjust what the data means – which story it tells – but also what the options foraction are on the individual level. Intelligently designed feedback loops areessential.

At the same time, ongoing data analysis might lead us to discover potentialhealth problems before a routine check-up would have surfaced them. As such,health data gains additional importance in the context of prevention.

EFFICIENCY & AUTONOMY

Technologically enhanced prevention, treatment and rehabilitation can – byempowering patients and doctors alike – increase efficiency and lower costs oftreatment. It can save further costs by enabling patients to take care ofthemselves better, or by supporting their families to care for them. The GlowCapis a powerful example of a relatively simple device – an internet-connected bottlepill – that increases compliance, thus increasing chances of successfultreatments.

As patients take more responsibility of their own health before, during and aftertreatment, costs are saved for the health system while at the same time allowingpatients to lead a more independent life for longer.

At the same time, automation of repeat tasks should lead to cost-saving acrossthe whole sector, and enable a more purposeful despatch of medical staff.Electronic Health Records should, when rolled out properly, enable much quickerdiagnosis on the basis of available medical history of a patient. Availability ofdata gathered from personal health tracking would enable practitioners access

to more data about the patient and thus make diagnosis even speedier andmore accurate.

BETTER RESEARCH DATA

The breadth of data becoming available spells a boon for medical research, as itdrastically increases the scope of what can be researched. The first effects of thiscan be seen in Genome analytics, but the whole field of medical research isbound to be changed by big data analytics.

OUTLOOK / WHAT TO EXPECT

The trends we outlined in this report are clearly set to continue onward.

More devices will reach the market that will track ever more of an ever largernumber of people. The devices highlighted above are in many cases initial proofof concept versions that reach only very limited numbers of people but as thistechnology matures and the market becomes more accustomed to this type oftechnology it is due to reach higher and higher levels of market penetration aswell as product maturity.

These devices will also increase the data shadow that everybody casts with eachdevice recording and transmitting data. All of this data will need to be storedsomewhere and processed. The storage solutions that are currently mostpopular will probably be considered too insecure and too limited. At the pointwhere just about everything is recorded, the architectures will need to change.

These large volumes of data will yield better insights but will also prove to beimmensely difficult to grasp as a whole. Combining disparate data streams in away that does not lose the goodwill of the users is going to be the tightrope actthat players in this industry will need to walk. Breaking down the data intofeedback loops that present the users with concrete options for action is key.

Overall spending on healthcare is rising. At the same time, it is highly doubtfulwhether these new technologies will be equally beneficial for all people:Financial aspects are just one dividing line that separates from those benefittingfrom those that don’t; Different speeds of adoption for new technologies (the so-called Digital Divide) is another.

On the one hand automation and technology hold the promise to be able to domore for more people at lower cost. On the other hand technology increases thescope of what is possible so that its full application will probably be prohibitivelyexpensive for all but a small elite. While we can expect improvements inproduction and development to increasingly become more accessible bothwithin the richer industrialised states and and the global South, we do notcurrently see a rising tide insofar as it does not lift all ships equally quickly.Overcoming this barrier to entry and making emerging technologies count for awider part of society will be a key challenge for the coming years.

In the meantime, we will need to work towards positive change in both policiesand cultural acceptance of data-intensive health applications to fully realize thepotential of technology in the health space.

KANT

KANT, the Kreuzberg Academy for Nerdery and Tinkering, is a Berlin based hubof creative technologists. KANT’s skill base covers everything in the fields ofemerging technology and user centered design and members of KANT do workin all stages from conception to design and implementation and also in the fieldsof analysis, review and commentary. This report is a product of our analysisbranch.

Want us to take a crack at some of the challenges you are working on?

Reach us at:Web: kantberlin.comEmail: info@kantberlin.comTwitter: @kantberlin

ABOUT THE AUTHORS

KANT consists of five collaborators:

ALPER CUGUNAlper Çuğun M.Sc. is a designer, developer and publicistactive on the focal point of technology, design andsociety. After graduating from Delft University ofTechnology, he has been active in the Amsterdam startupscene. Having built up an extensive network there, hemoved to Berlin. Alper currently is partner at Hubbub,one of Europe’s leading studios for the design of gamesand playful systems. Hubbub helps organizations withunderstanding and inventing new games and playfulsystems, primarily in the space of social issues, creativityand collaboration. Alper is also on the board of the Open

State Foundation, where he oversees the creation of open data and opengovernment policy for the Netherlands and the rest of Europe.

CHRIS EIDHOFChris Eidhof is a software developer and entrepreneuroriginally from The Netherlands. He currently focuses onbuilding iPhone and iPad products, from strategy downto implementation. Together with Peter and Matt, heorganizes UIKonf. He is one of the founders of objc.io, ahigh-profile magazine about Objective-C.

MARTIN SPINDLERMartin Spindler is interested in how digital technologiesfeed back into the world — how the bits start to shapethe atoms. As such, he works as a strategy consultant,speaker and writer focussing on the Internet of Thingsand Smart Energy. Martin is Co-Founder of Internet ofPeople, an international consultancy network centred onthe Internet of Things, and the Cognitive CitiesConference, which looks into how the pulse of citieschanges once they get equipped with “smarts.” Martinstudied Political Sciences, Economics and Islamic Studiesat the University of Heidelberg.

MATT PATTERSONMatt has been building for the web for over 10 years,doing everything from web design and front-enddevelopment all the way through to back-enddevelopment. He was one of the founding developers ofthe UK’s Government Digital Service, has worked oncritically-acclaimed video games, is involved with the RailsGirls movement, coaching aspiring developers, and hasbeen doing a lot of work with data and visualisation.

PETER BIHRPeter explores emerging technologies, their implications,and the people driving them. This translates into anumber of things: digital strategies, a great network ofcollaborators, curation services of sorts, and theoccasional product or prototype. He is an independentdigital strategist and consultant, serves as ProgramDirector for the conference NEXT Berlin, and co-foundedMakers Make. He also co-organizes events like UIKonf,Cognitive Cities Conference, TEDxKreuzberg and IgniteBerlin