A Preliminary Study Of Telemedicine For Patients With .

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Journal of Inherited Metabolic Disease (2018) 7-2GLYCOGEN STORAGE DISEASEA preliminary study of telemedicine for patients with hepatic glycogenstorage disease and their healthcare providers: from bedsideto home site monitoringIrene J. Hoogeveen 1 & Fabian Peeks 1 & Foekje de Boer 1 & Charlotte M. A. Lubout 1 & Tom J. de Koning 1 &Sebastiaan te Boekhorst 2 & Robert-Jan Zandvoort 3 & Rob Burghard 4 & Francjan J. van Spronsen 1 & Terry G. J. Derks 1Received: 21 December 2017 / Revised: 22 February 2018 / Accepted: 1 March 2018 / Published online: 29 March 2018# The Author(s) 2018AbstractBackground The purpose of this project was to develop a telemedicine platform that supports home site monitoring andintegrates biochemical, physiological, and dietary parameters for individual patients with hepatic glycogen storage disease(GSD).Methods and results The GSD communication platform (GCP) was designed with input from software developers, GSDpatients, researchers, and healthcare providers. In phase 1, prototyping and software design of the GCP has occurred. TheGCP was composed of a GSD App for patients and a GSD clinical dashboard for healthcare providers. In phase 2, the GCPwas tested by retrospective patient data entry. The following software functionalities were included (a) dietary registration andprescription module, (b) emergency protocol module, and (c) data import functions for continuous glucose monitor devices andactivity wearables. In phase 3, the GSD App was implemented in a pilot study of eight patients with GSD Ia (n 3), GSD IIIa(n 1), and GSD IX (n 4). Usability was measured by the system usability scale (SUS). The mean SUS score was 64/100[range: 38–93].Conclusions This report describes the design, development, and validation process of a telemedicine platform for patients withhepatic GSD. The GCP can facilitate home site monitoring and data exchange between patients with hepatic GSD and healthcareproviders under varying circumstances. In the future, the GCP may support cross-border healthcare, second opinion processesand clinical trials, and could possibly also be adapted for other diseases for which a medical diet is the cornerstone.Keywords Hepatic glycogen storage diseases . Telemedicine . Monitoring . Mobile application . Dietary management . RarediseasesAbbreviationsAPIApplication programming interfaceCEConformité EuropéenneCGMContinuous glucose monitoringGCPGSDDMIoTMetabERNResponsible Editor: Daniela KarallSUSTM* Terry G. J. Derkst.g.j.derks@umcg.nl1Section of Metabolic Diseases, Beatrix Children’s HospitalUniversity Medical Center Groningen, University of Groningen, POBox 30 001, 9700 RB Groningen, The Netherlands2Patient Connect B.V., Bilthoven, The Netherlands3Pi IQ, Groningen, the Netherlands4enerGQcare B.V., Groningen, The NetherlandsGSD communication platformGlycogen storage diseaseDiabetes mellitusInternet of thingsEuropean Reference Network for RareHereditary Metabolic DisordersSystem usability scaleTelemedicineIntroductionHepatic glycogen storage diseases (GSDs) are a group of inborn errors of carbohydrate metabolism, for which a strict dietis the cornerstone of management. Patients with hepatic GSDdisplay perturbed glucose homeostasis due to a deficiency of a

930J Inherit Metab Dis (2018) 41:929–936functional enzyme or transporter in glycogen synthesis, glycogenolysis, and/or gluconeogenesis. This generally leads tofasting intolerance, failure to thrive and hepatomegaly, and isbiochemically associated with (non)ketotic hypoglycemia,(fasting or postprandial) hyperlactacidemia, increased liverenzymes and hyperlipidemia (Walter et al 2016). The aim ofdietary management is to maintain euglycemia, to suppresssecondary metabolic derangements and to prevent long-termcomplications. The natural histories of several subtypes ofhepatic GSD were reported by international cohort studies(Rake et al 2002a; Sentner et al 2016), review articles (Baliet al 2006; Dagli & Weinstein 2009; Goldstein et al 2011;Dagli et al, 2010; Magoulas & El-Hattab 2013), and guidelines (Rake et al 2002b; Visser et al 2002; Kishnani et al 2010;Kishnani et al 2014).In line with the observations that strict diabetes management prevents long-term complications, observational cohortstudies of GSD I patients have emphasized the importance ofgood metabolic control for the prevention of liver adenomas(Wang et al 2011), nephropathy (Wolfsdorf et al 1997;Martens et al 2009; Melis et al 2015; Okechuku et al 2017)and bone disease (Minarich et al 2012; Melis et al 2014). ForGSD IIIa patients, an association between overtreatment withcarbohydrates and hypertrophic cardiomyopathy was suggested by several case-reports (Dagli et al 2009;Valayannopoulos et al 2011; Sentner et al 2012). In addition,a case report on two patients with GSD IXa presented improvement in liver cirrhosis on ultrasound after improvingmetabolic control (Tsilianidis et al 2013).Continuous glucose monitoring (CGM) systems have beendeveloped to facilitate glucose monitoring. Originally, CGMsystems were developed for patients with diabetes mellitus(DM) (Juvenile Diabetes Research Foundation ContinuousGlucose Monitoring Study Group 2008), but the applicationof CGM in GSD patients has also been reported by severalgroups (Hershkovitz et al 2001; Maran et al 2004; White &Jones 2011; Kasapkara et al 2014). The introduction of CGMsystems has increased opportunities for home site monitoring.Nevertheless, day-to-day healthcare for the GSD patients isstill challenging of which suboptimal metabolic control is onlyone of many reasons (as summarized in Table 1).Telemedicine (TM) has emerged rapidly as a novel tool todeliver healthcare tailored to the individual patient’s needs(Moore 1999; Steinhubl et al 2015; Heintzman 2016).Besides this, TM seems promising to provide cross-borderhealthcare for patients with rare diseases (Saliba et al 2012).Surprisingly, to date, there is only one publication on a mobileapplication for dietary management of patients with inbornerrors of metabolism (Ho et al 2016).To support home site monitoring and to integratebiochemical, physiological, and dietary parameters, wehave designed, validated, and implemented a TM platform for patients with hepatic GSD. This TM platform,now further referred to as GSD communication platform(GCP), consists of the GSD application (GSD App) forpatients and their caregivers and the GSD clinical dashboard for healthcare providers.MethodsThe GCP was intended to support rather than replace currenthealthcare as provided by our center of expertise for hepaticGSD and recommendations were only generated after approval by a healthcare provider. The usability pilot study has beencarried out in accordance with ethical and legal guidelines ofthe University Medical Center Groningen (Medical EthicalCommittee, 2016/466) and The Code of Ethics of the WorldMedical Association (Declaration of Helsinki). Technicaldocumentation and user manuals of the GCP were prepared for the validation of the GCP as a class I medicaldevice, as described in the Medical Device Directive 93/42/EEC. The creation of the technical documentationwas supported by DRS consultancy (http://drs.nu/enUS/) and subsequently reviewed by the qualityconsultant medical devices of the University MedicalCenter Groningen, in preparation of notifying the GCPto the national Inspectorate of Health for a ConformitéEuropéenne (CE) mark.For the software development and validation process of theGCP, three phases were constructed.Table 1Challenges in current healthcare for individual patients with hepatic GSD1.Suboptimal metabolic control (due to under- or overtreatment with carbohydrates) still occurs, associated with co-morbidity and long-termcomplications.There is a gap of knowledge between clinical guidelines and management in daily practice.There is large heterogeneity between individual patients with identical GSD subtypes and genotypesThere is a discrepancy between prescribed diets and actual used diets.Clinical parameters are mostly measured in the hospital on relatively random moments.Traditional biomarkers are suboptimal and biochemically distant from the primary metabolic block.Patients with rare diseases usually do not live close to so-called centers of expertise, which challenges ‘shared care models’.2.3.4.5.6.7.

J Inherit Metab Dis (2018) 41:929–936931Phase I — Prototyping and software design:The GCP was designed during monthly meetings withinput from software developers, (parents of) GSD patients, researchers, and healthcare providers fromJune 2014 till present. The GCP was composed of twoweb applications; the GSD App for patients and theircaregivers and the GSD clinical dashboard for healthcareproviders. The GSD App was developed in Dutch, thenative language for most of our patients, whereas theGSD clinical dashboard was developed in English.Figure 1 presents the detailed architecture of the GCP.Intended uses — The intended use of the GSD App is toallow individuals with hepatic GSD to support their dietary management provided by healthcare providers, under normal circumstances and intercurrent illness, bymonitoring and sharing home site collected data withhealthcare providers. The intended use of the GSD clinical dashboard is to integrate data collected by hepaticGSD patients, either at home or during a hospital admission, and to provide subsequent GSD dietary management advice for normal circumstances, intercurrent illness, and those situations where the emergency protocolis applicable.Data security and management — For both applications,the Hypertext Transfer Protocol Secure (HTTPS) and theOpen Web Application Security Project Top Ten awareness document (https://www.owasp.org/) was adopted tosecure integrity and privacy of online communicationwithin the GCP. Access to the applications required ausername and password. Passwords were stored with asalted and one-way encryption method to protect fromFig. 1 Architecture of the GSDcommunication platform.Legend: 1, no API was availablefor the CGM data, these data weremanually imported to the GSDclinical dashboard by thehealthcare provider. API,application programminginterface; CGM, continuousglucose monitoring; GSD,glycogen storage diseaseaccidental or unlawful loss. Software test plans and complaints management procedures were set up for postmarket evaluation. The GCP was hosted on MicrosoftAzure (refer to Azure subscription agreement: bscriptionagreement/). For the GSD App development, the opensource frameworks AngularJS, JavaScript jQuery, andBootstrap were chosen. A non-commercial license fromHighcharts (https://www.highcharts.com) was used todisplay the graphs in the GSD clinical dashboard.Phase II — Software development and retrospective clinical data entry:Features and functionality were reviewed and issues onusability were managed, processed, and documented withthe use of a Jira issue tracker from Atlassian by softwaredevelopers, researchers, and healthcare providers.The following software functionalities were included:Dietary registration and prescription module — TheDutch Food Composition Table (NEVO table) (NationalInstitute for Public Health and the Environment 2012)was used for the development of the dietary registrationmodule in the GSD App and the prescription module fordieticians in the GSD clinical dashboard, respectively. The NEVO table contains information on macroand micronutrients content and total kilocalories ofall food items frequently eaten by the Dutch population. The NEVO table also includes data on themedical formulas, dietary supplements, maltodextrinproducts, and uncooked cornstarch, such asGlycosade .Cloud-based platformNEVOFoodTableFitbitAPIInternetUser environmentActivitywearableGSD AppGSD Clinical DashboardCGM export file1PATIENT USERHEALTHCARE PROVIDER

932J Inherit Metab Dis (2018) 41:929–936Emergency protocol module — The local hospital emergency protocol guideline was used as a template for theemergency protocol module in the GSD clinical dashboard. The emergency protocol module was designed insuch a way that it could automatically generate an emergency letter with the use of the patient’s GSD type andactual body weight. After generation, the emergency letter was shared with the corresponding patient in the GSDApp.Data import functions — In the GSD clinical dashboard,an import function for CGM data (Dexcom G4/G5 CGMsystem, Dexcom Inc., San Diego, CA) was created. AnApplication Programming Interface (API) was acquiredby Fitbit, Inc. to import data from the activity wearable inthe GSD App.Retrospective data entry — Data from written food andclinical measurement diaries were retrospectively collected in the GCP by the researchers to test the usability andcorrectness of the GCP functionalities. These data werefrom patients who visited the University Medical CenterGroningen GSD center of expertise between March andOctober 2016 and who gave written informed consent forthe use of their data collected during their visit.Phase III — Implementation and pilot study prospectiveclinical data entry:Subjects and pilot study design — Between March andJuly 2017, data were prospectively collected in the GCPby selected GSD patients visiting our center. Patientswere introduced to the GSD App by the treating physician (TGJD) and researcher (IJH). All subjects receivedan up-to-date manual for the use of the GSD App. Dataexchange was requested by the healthcare provider toallow individual data integration in the GCP and criticalfollow-up after dietary changes. Subjects were asked touse the GSD App for home site monitoring before, during, and/or after a clinic visit, according to the purpose oftheir visit. Furthermore, subjects could temporarily use anactivity wearable with a heart rate function (Fitbit ChargeHR ). A CGM system by Dexcom was used only whenneeded for regular care. Data from the CGM were retrospectively imported in the GSD clinical dashboard by thehealthcare providers. Results of data integration in theGSD clinical dashboard (i.e., updated dietary plans andemergency protocols) were discussed with the subjects/patients and their parents during the outpatient clinic visitand/or via a telephone or videoconference consultationfollowing the (outpatient) clinic visit.Survey methods — User feedback was documented in astructured logbook and usability issues from differentusers (patients, caregivers, and healthcare providers) wereuploaded in the Jira issue tracker for further softwareimprovements. Subjects and/or caregivers were asked togive feedback on the GSD App via an open feedbackform on paper or electronically via a SurveyMonkeyquestionnaire and to fill in the system usability scale(SUS) (Brooke 1996). An adjective scale was used forthe interpretation of individual SUS scores (Bangor et al2009).ResultsPhase I: prototyping and software designFigure 2 displays screenshots of the GSD App and the GSDclinical dashboard. The GSD App can be accessed by going tohttps://app.gsdapp.nl in the internet browser on a mobilephone. The GSD clinical dashboard can be accessed via adesktop browser: https://clinicaldashboard.gsdapp.nl.Phase II: software development and retrospectiveclinical data entryAccess to individual patient registered data in the GSD Appwas restricted to the patient user and their caretakers. Datashare requests by healthcare providers via the GSD clinicaldashboard (for instance, for the preparation of an outpatientclinic visit) were only answered by and with the permission of(the caretakers of) the patient.Data import and visualization The combo graph in the GSDclinical dashboard displayed combined data of the patientfrom the requested period in one interactive graph (see Fig.2c). The GSD clinical dashboard also displayed a histogramand a pie chart to provide more insight into the differences inmacronutrient distributions and total calorie intake betweenprescribed and registered diets.Dietary prescription module The implementation of theNEVO table supported dietary registration, prescription, andmacronutrient calculations. An extra function was added forthe entry of drip-feeding to simplify the determination of therate of drip-feeding in milliliters per hour and the macronutrient intake.Retrospective data entry Table 2 summarizes retrospectivedata on dietary management and CGM profiles from five patients with GSD Ia (n 3), GSD IIIa (n 1), and GSD IX (n 1). Improvements for dietary registration in the GSD App anddata visuals in the GSD clinical dashboard were implemented.Eventually, retrospective data entry led to the development ofthe GSD App and GSD clinical dashboard versions for theusability pilot study in phase III.

J Inherit Metab Dis (2018) 41:929–936933Fig. 2 Screenshots from theGSD App and the GSD clinicaldashboard: a) the home screen,b) the logbook, c) evaluationdisplay in the GSD clinicaldashboard. Legend: a) thecutlery button presents theprescribed diets; the share buttondisplays the users and the shareddata periods. The emergencyprotocol and personal emergencyphone numbers are accessible viathe information button. b) thelogbook gives a clear overview ofall registered meals over the dayin a chronological manner.Macronutrient totals can bedisplayed per food item, per meal,and/or per day. Besides dietaryregistration, the GSD App allowspatients to enter their bloodglucose/ketones measurements,physical activities, andsymptoms. c) the combo graph inthe GSD clinical dashboardpresents all individual data in oneinteractive graph. Data sets can beadded or deleted from the graphPhase III: implementation and pilot study prospectiveclinical entryHR ) to monitor heart rate and activity as an extra physiological marker for the assessment of his sport regimen.Subjects The GSD App was prospectively used by eight patients with GSD type Ia (n 3), IIIa (n 1), and IX (n 4).Table 2 presents an overview of the patients’ characteristics.Three patients participated in both the retrospective clinicaldata entry and the pilot study. The GSD App was used by bothGSD patients (n 3) and caregivers (n 5). Patient #P01 usedthe GSD App together with her parents as a first step towardautonomy.Feedback from users Feedback on the GSD App could becollected for 7/8 GSD App users (see Table 2), unfortunately#P02 has not returned written feedback, despite reminders.The mean SUS score was 64/100 [range: 38–93]. Two subjects scored the GSD App usability with ‘excellent’ on theadjective scale for interpretation of individual SUS scores.The mean SUS was higher among parents with younger children (n 3, mean SUS 83) compared to adult patients or parents with older children ( 12 years of age) (n 4, mean SUS50). Patients reported in the open feedback form that it waseasy to have their dietary prescription at hand and that theGSD App worked more efficiently compared to the paperfood diaries. Points for improvements were the search strategyfor the right food items and the feedback from healthcareproviders on registered data.Pilot study outcome Table 2 displays the different purposesfor which the GSD App was used. In phase III (P02, P04P08), data were collected in the GSD App outside the hospitalenvironment. The distance to our hospital ranged between 158and 397 km, emphasizing the potential in home site monitoring. Only one patient used the activity wearable (Fitbit Charge

934Table 2J Inherit Metab Dis (2018) 41:929–936Patient characteristics for phase II and III data collection in the GCPPt vityimportcDietaryadvicePhase II: retrospective clinical data entryR0112IaFNocturnal Glycosade versus CNGDF R02R033136IaIIIaMFRegular outpatient clinic visit for metabolic monitoringMonitoring introduction of MCT R040IXMMetabolic monitoring during breastfeeding on demand– –– – R0519IaMMetabolic monitoringPhase III: pilot study prospective clinical d

Sebastiaan te Boekhorst2 & Robert-Jan Zandvoort3 & Rob Burghard4 & Francjan J. van Spronsen1 & Terry G. J. Derks1 Received: 21 December 2017/Revised: 22 February 2018 /Accepted: 1 March 2018/Published online: 29 March 2018 # The Author(s) 2018 Abstract Background The purpose of this project was to develop a telemedicine platform that supports home site monitoring and integrates biochemical .

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