Rhabdoviridae, they are known to infect plants and can be transmitted by arthropod vectors, during vegetative propagation, or by mechanical means. In 2010, an alfalfa (Medicago sativa) plant showing virus-like symptoms was collected from Stadl-Paura, Austria and sent to Julius Kühn Institute for analysis.Nucleorhabdoviruses possess bacilliform particles which contain a single-stranded negative-sense RNA genome. They replicate and mature in the nucleus of infected cells. Together with viruses of three other genera of the family Electron microscopy (EM) of leaf extracts from infected plants revealed the presence of rhabdovirus-like particles and was further used for ultrastructural analyses of infected plant tissue. Partially-purified preparations of rhabdovirus nucleocapsids were used for raising an antiserum. To determine the virus genome sequence, high throughput sequencing (HTS) was performed. RT-PCR primers were designed to confirm virus infection and to be used as a diagnostic tool.Nucleorhabdovirus (family Rhabdoviridae). Since the virus originated from an alfalfa plant in Austria, the name alfalfa-associated nucleorhabdovirus (AaNV) is proposed. Viroplasms (Vp) and budding virions were observed in the nuclei of infected cells by EM, thus confirming its taxonomic assignment based on sequence data.EM revealed bacilliform virions resembling those of plant-infecting rhabdoviruses. HTS of ribosomal RNA-depleted total RNA extracts revealed a consensus sequence consisting of 13,875 nucleotides (nt) and containing seven open reading frames (ORFs). Homology and phylogenetic analyses suggest that this virus isolate represents a new species of the genus In this study, we identified and characterised a new nucleorhabdovirus from alfalfa. It shared only 39.8% nucleotide sequence identity with its closest known relative, black currant-associated rhabdovirus 1. The virus contains an additional open reading frame (accessory gene) with unknown function, located between the matrix protein and the glycoprotein genes. Serological and molecular diagnostic assays were designed for future screening of field samples. Further studies are needed to identify other natural hosts and potential vectors.The online version of this article (10.1186/s12985-019-1147-3) contains supplementary material, which is available to authorized users. Medicago sativa L.), a member of the Fabaceae family, is used as perennial forage crop which is important as fodder for livestock, as green manure for soil fertility, and can be used as food and medicine for humans  based on the nucleotide alignment of the whole genomes of AaNV and selected members of different genera of the family Rhabdoviridae. AaNV indicated by a blue solid diamond shape. The names and the accession numbers of the viruses are as follow: Nucleorhabdovirus (green): alfalfa-associated nucleorhabdovirus , black currant-associated rhabdovirus 1 , datura yellow vein virus , eggplant mottled dwarf virus , maize fine streak virus , maize Iranian mosaic virus , maize mosaic virus , physostegia chlorotic mottle virus , potato yellow dwarf virus , rice yellow stunt virus , sonchus yellow net virus  and taro vein chlorosis virus . Cytorhabdovirus (red): alfalfa dwarf virus , barley yellow striate mosaic virus  and lettuce yellow mottle virus . Lyssavirus (black): rabies virus . Perhabdovirus (violet): eel virus European X . Figure S2. Comparisons between AaNV and selective members of the Nucleorhabdovirus genus. The consensus sequence of the intergenic conserved sequences (a), the 3′ and 5′ ends (b), and the genome organisation (c). The names and the accession numbers of the viruses can be found under Figure S1. Figure S3. Electron micrograph of the JKI-1607 reacting with AaNV ribonucleoprotein (RNP). a Enriched nucleocapsids after immunosorbent step; b Enriched nucleocapsids but not virions are covered (decorated) with antibodies (DOCX 1320 kb)


Tools to detect human norovirus infectivity have been lacking. Using human intestinal enteroid cultures inoculated with GII.Pe-GII.4 Sydney–infected fecal samples, we determined that a real-time reverse transcription PCR cycle threshold cutoff of 30 may indicate infectious norovirus. This finding could be used to help guide infection control. Human norovirus accounts for 18% of acute gastroenteritis cases worldwide  values of a widely used diagnostic rRT-PCR to represent high to very low norovirus levels (<20 passages in the presence of bile acid (glycochenodeoxycholic acid). We measured norovirus RNA levels in supernatant at 1, 24, and 72 h after inoculation by using rRT-PCR with a 10-fold serially diluted standard of in vitro–transcribed norovirus RNA. We considered a >10-fold increase in RNA level at 72 h after inoculation from baseline (1 h after inoculation) to indicate productive viral replication and to confirm the presence of infectious virus. We also subjected fecal filtrate dilutions to norovirus antigen detection by use of the Food and Drug Administration–cleared commercial RIDASCREEN Norovirus 3rd Generation EIA , according to the manufacturer’s instructions. We used the same amount of fecal filtrate for inoculation into HIE and EIA measurement and compared the analytical sensitivity of HIE and EIA. We examined the infectivity of human pandemic norovirus genogroup II genotype 4 (GII.Pe-GII.4 Sydney) strains at different inoculating levels by using the adult stem cell–derived HIE line J2 as described previously (10) to 45,793 (4.7 log10). Higher levels of replication were obtained from fecal samples from adults  were 27.7, 29.0, and 30.0 for each of the 3 strains. By using linear regression analysis on pooled data of the 3 strains, we estimated that a Ct cutoff of <30.1 in inoculating fecal filtrates would indicate the ability to generate productive norovirus GII.Pe-GII.4 Sydney replication   . t values >30 . Among the 1,579 (90.0%) genotyped samples, the proportion of GII.4 was 49.1%; other GII, 44.8%; GI, 5.2%; and co-infections with >1 norovirus capsid genotype, 0.9%. Analytical sensitivity of virus replication in HIEs for measuring moderate norovirus shedding was higher than that of EIA by being able to detect infectious virus in fecal filtrate dilutions with Ct values of 25–30  of 1,754 norovirus-positive fecal samples from patients admitted to the Prince of Wales Hospital, Sha Tin, Hong Kong, with acute gastroenteritis had Cof 25–30 .t<30 can robustly yield productive virus replication in HIE, suggesting the presence of infectious virus. This value concurs with findings of a study that proposed an optimal Ct cutoff of 31 when attributing a disease to norovirus by comparing between symptomatic and asymptomatic cases (t >30) may not be infectious.The limitations of highly sensitive molecular nucleic acid tests and the clinical value of proving virus infectivity were demonstrated in a recent study of Zika virus infection that found that the virus could be detected by culturing samples with high viral RNA levels only , a national norovirus surveillance network in the United States, the median Ct value among asymptomatic patients was 28  (,t >30 might still contain infectious virus and that low amounts of replicating norovirus would only be detected with further serial propagation of the virus. Third, norovirus replication varies between samples and virus genotypes in HIE culture (The use of a fixed Ct cutoff of 30 for a widely used clinical diagnostic rRT-PCR can indicate the presence of infectious GII.Pe-GII.4 Sydney norovirus in an HIE culture model. Patients shedding low levels of norovirus RNA may not be infectious, which should be considered both for estimation of attributable norovirus burden and for clinical management of viral gastroenteritis.In summary, we demonstrate that a C


To determine the costs to develop, roll out and maintain electronic immunisation registries (EIRs) and a related suite of data use interventions.The Better Immunisation Data (BID) Initiative conducted the activities from 2013 to 2018 in three regions in Tanzania and one province in Zambia. The Initiative’s financial records were used to account for the financial costs of designing and developing the EIRs, BID staff time, expenditures for rolling out the EIR systems and the related suite of interventions to health facilities, and recurrent costs. Total financial costs, cost per facility and cost per child were calculated in 2018 US$.Total expenditures were ~US$4.2 million in Tanzania and US$3.6 million in Zambia. System design and development costs accounted for ~33% and 26% of the expenditures in each country, respectively, while BID staff costs accounted for 39% and 52%, respectively. Average expenditures per health facility for rolling out the EIR system were between US$709 and US$1320 for the Tanzania regions and US$2591 for Zambia. The annualised average expenditure per child was estimated to be between US$3.30 and US$3.81 for the regions in Tanzania and US$8.46 in Zambia. Expenditures per child were higher in Zambia partly because of a much smaller birth cohort compared with Tanzania.Other countries may benefit from the investments made and lessons learnt in Tanzania and Zambia by leveraging these now existing EIR platforms and rollout strategies, and hence may be able to implement EIRs at lower costs than reported here. Immunisation programme in low/middle-income countries (LMICs) face challenges with data quality and use and so electronic immunisation registries (EIRs) combined with data use interventions may be a solution.Information on the costs of developing, deploying and rolling out the EIRs in LMICs is lacking.Evidence from Tanzania and Zambia show that the costs of developing, deploying and maintain EIRs cost <US$10 per child aged under 1 year of age, but these costs can be lower than US$5 per child in a country like Tanzania that has a large birth cohort.Hardware and deployment of the EIRs are the cost categories that account for a large share of these costs.These estimates can be used by stakeholders when planning and budgeting for similar interventions.Subsequent EIR development and deployment costs may be less than those reported in this study because of the ability of other LMICs to leverage these EIR systems that were developed for Tanzania and Zambia and also through leveraging learnings generated from these deployments.Health programmes, including immunisation programmes, in low/middle-income countries (LMICs) face challenges resulting from poor-quality data and poor use of existing data.In an attempt to tackle these challenges, including the lack of child-level immunisation records and poor quality data for decision-making and information management, the Better Immunisation Data (BID) InitiativeWhen BID’s work began, there was no existing EIR system that met the requirements of each country. Part of the initial strategy of BID was to support the development of two different systems to meet diverse country needs, thus reducing the likelihood of other countries needing to invest in new software development. It is challenging to develop one system that meets diverse country needs, and so BID developed two different systems in order to provide options for countries to choose from in order to have a system that best meets their needs and country context. Hence, Tanzania and Zambia each developed their own EIR: Open Immunize (OpenIZ) in Tanzania and Open Smart Registry Platform (OpenSRP) in Zambia. Both software platforms are open source and therefore have freely available source codes for other countries interested in using similar software. The source code for both platforms is in English, but the source code for OpenIZ is also available in Swahili. These respective EIRs were then rolled out by the initiative to three regions in Tanzania and one province in Zambia.Critical to implementing any new system is monitoring and understanding start-up and ongoing costs to ensure sustainability and scalability. For BID, this was especially important as no previous evidence existed on the costs of implementing EIRs in LMICs. Therefore, we integrated an evaluation of the total cost of ownershipBefore implementation of the EIRs, health workers in both countries were using paper-based immunisation registers, tools and reports. The EIRs were implemented and designed for health workers to electronically register and track children through their vaccine schedules and to automate reporting. At implementation start-up, tablets preloaded with EIR software and barcode/quick response code scanners were provided to health facilities as the core tools for interfacing with the EIR system.When a child first presents at a health facility, the child is registered into the EIR with a unique identification number. A label containing a barcode or quick response code with this number is then placed on the child’s health card. The child’s record can then be accessed at any facility the child visits. If the caregiver does not have the child’s health card at the next visit, staff can search the registry using the child’s name, caregiver’s name, village or unique identification number. The child record in the EIR includes the child’s demographic information such as their gender and date of birth and also vaccination information such as vaccination schedule and records including vaccines they have received in the past and those they are due for. In addition, information on the child weight, vitamin A receipt, nutrition and deworming status are included, as these services are provided together with immunisation services. Caregiver information such as their name, village and contact information are also included in the electronic record and can be used contacting the caregiver when the child is due for their next vaccination or following up if the child has missed an appointment. Both countries’ EIRs also contain simple reports that inform health workers when a child is due for the next vaccination and whether he or she has missed a scheduled appointment. The health worker can use this information to follow-up with caregivers. The EIRs also contain an inventory management component that can be used to show when a facility is running low on vaccine stock or supplies. The EIRs developed through the Initiative focused mainly on immunisation; however, given that other health services are provided at the same time as vaccinations, these data were also captured. The EIR systems are both web-based and tablet-based, in on and offline functions. The data in the EIR mirrors the monthly child health and immunisation reports the health workers completed. The systems used in both countries are interoperable with DHIS-2 in both countries, and the governments are in the process of adjusting policy to receive the reporting information into the DHIS-2 electronically. Additional details on the functionality of the EIRs are provided in previous publications.This study’s analysis focuses on the development and rollout costs of the BID Initiative: In 2014, work began in Tanzania on development of an EIR. This system was initially deployed in Arusha Region but was later shelved due to challenges that arose during deployment. A second EIR system was developed on the OpenIZ platform, which is the EIR included in this costing analysis and currently in use in Arusha, Tanga and Kilimanjaro regions . In Zambia, initial work on the EIR platform DHIS eTracker was never deployed. In 2016, a different partner developed an EIR system for Zambia on the OpenSRP platform. This is now in use in Southern Province and is applicable to other provinces in the country. Our study includes the costs for developing the initial EIRs which were later shelved; these ‘learning costs’ are included as the upper-bound estimates of the study.The Initiative intended to use data capture software to back enter vaccination records for children aged <9 months from the paper registers into the EIRs; otherwise, health workers would have to back enter the complete record of each child at the child’s first encounter with the new system. However, the data capture software did not work as expected, and there was no suitable alternative other than manually entering the records. This manual back entry was done by contracted staff in each country until the initial cohorts of children were registered in the EIRs.Deployment of the EIR was done through a series of on-the-job trainings for health workers. A tablet, charger and barcode/quick response code scanner were provided to each health facility, with a few facilities that served larger populations receiving two tablets and scanners. During the visits, health workers in the immunisation programme were introduced and trained on the EIR and related suite of interventions, which included targeted supportive supervision for facilities, peer support networks, data use guides and posters, and simplified and visualised reporting. This training was done in the context of the clinical care workflows and procedures and aimed to ensure that health workers were equipped to strengthen data collection, improve the quality of data available and increase the use of the data for decision-making.This analysis focuses on the financial expenditures incurred by the BID Initiative in Tanzania and Zambia for developing the EIRs, deploying them and the related suite of interventions and maintaining the systems. This analysis does not include economic costs. By focusing on the financial costs, we present actually monetary outlays incurred for developing and deploying the EIRs. Financial costs are most relevant for budgeting and planning and we present these to provide an accounting of the expenditures that were spent on developing, deploying and maintaining EIRs. The data were obtained from BID’s financial records and tracked over the period 2013–2018. We focused on BID’s financial costs hence the opportunity costs for government staff for time to participate in meetings, be involved in training (on the job or offsite) and use of existing government resources such as vehicles to attend the meetings were not captured. These costs would have been included if this analysis was focused on economic costs which take into account the opportunity costs of using existing resources. The financial expenditures for government staff that were accounted for in this analysis were those covered by BID, such as per diems for government staff to attend the meetings and fuel and transportation allowances when government vehicles were used. The analysis focuses on financial expenditure and so the full costs for system development and hardware procurement are included in the analysis. As a result, capital depreciation costs are not included as this would be double counting of costs. Any costs for system maintenance and upgrades that were incurred during the 5-year project period are also accounted for and included. The analysis also includes the costs that were borne in each country and excludes project costs for PATH staff based in the headquarters office or in-country that were related to administration and research. In Tanzania, some expenditures were not reported separately by region. These included costs for data hosting, internet, vehicle hire and printing. As a consequence, costs were allocated to each region based on the relative size of the EPI target population.We present the total expenditures for BID related to the EIRs and associated interventions. We also present the average costs per health facility for rolling out the EIR systems which were calculated by dividing the total regional/provincial costs for rolling out the EIR by the number of health facilities in each region/province. In addition, we calculated the cost per child in the EPI target population. To do this, we annualised the costs in each of the categories included in Financial expenditure for the EIR systems and related suite of interventions per child = + + + + + + / region or province EPI target population.All costs are presented in 2018 US$.Ethics clearance was not required for this study because the data for the analysis were obtained from project financial records.This research was done without patient or public involvement. It was not appropriate or possible to involve patients or the public in the design, or conduct, or reporting, or dissemination of our research as the study focused on analysis of expenditure data.When looking at the region-/province-level expenditures for rollout, we observed that expenditures for hardware and for deploying the interventions to health facilities and districts was the largest share of the expenditure. Total expenditures for hardware ranged from about US$93 000 to US$187 000 per region in Tanzania  and abouRecurrent costs accounted for 2.6% of the initiative’s total expenditures in Tanzania and 0.7% in Zambia . Of thesWhen looking at the expenses per health facility (including hardware to district offices) for Tanzania, these expenditures averaged US$299 to US$657, while for Zambia the average expenditure was US$865 . The aveOur evaluation shows that the total costs for developing, rolling out and maintaining the BID interventions were US$4.2 million and US$3.5 million in Tanzania and Zambia, respectively, over the 5-year period. We estimated an annualised cost per child ranging from US$3.30 to US$3.81 in the three regions in Tanzania and US$8.46 in the one province in Zambia. Our literature search did not find any previous studies that had evaluated costs of EIRs in LMICs; limited evidence on the costs of EIRs is from high-income countries and thus hardly comparable to settings in sub-Saharan Africa. For example, a study conducted in Massachusetts, USA, in 2002 found that the cost per child for an immunisation registry was US$8.46 per child under 23 years of age and US$15.51 per child when including only children under 8 years of age (adjusted to 2018 US$).Our study found that hardware and deployment costs were the two largest expenditures associated with rolling out the interventions to the health facilities. This is not unexpected given the equipment that has to be procured for each health facility and also the per diem, lodging and transport expenditures to travel to each health facility to train the healthcare workers on using the new system.We found that the rollout costs for Arusha region were higher than for the other two regions in Tanzania because some facility visits in Arusha region had to be repeated after the EIR system was redesigned in order to train health workers on the new EIR system. However, each subsequent rollout in Tanzania had lower costs because implementing the learnings gained from previous rollouts reduced the costs of conducting the deployment of the interventions in each subsequent region.While we present the data for Tanzania and Zambia together, the aim of this evaluation was not to compare results between the two countries due to significant differences in country context. For example, EIR development costs in Tanzania were higher in Tanzania than in Zambia because Tanzania was the first country to engage in the software development activities and more activities were conducted in Tanzania than in Zambia. Some of these include the landscaping analysis done during the design phase work to ensure interoperability with existing systems. The learnings from the initial Tanzania experience informed the Zambia development process, where the team identified challenges earlier and more swiftly to inform the change to a second software at an earlier stage. In Zambia, the intervention rollout costs were higher due to delays in system development which required the team to adopt relatively more expensive strategies to complete the rollout within the initiative’s funding time frame. In addition, the strategies used to roll out the interventions differed in the two countries, with Tanzania able to use more government staff time for implementation in the Tanga and Kilimanjaro regions compared with Zambia, where the government could provide only limited implementation support in Southern Province. Hardware costs were also higher in Zambia because the per unit costs for tablets was higher in Zambia than in Tanzania. Some of these differences reflect differences in local procurement costs for electronics. Our results also show that the cost per child in Zambia was much higher than in Tanzania despite similar total financial expenditures. One reason is that Zambia had a much smaller national birth cohort than Tanzania (about a third of the size), hence, the costs in Tanzania were spread over a larger group of beneficiaries. In general, because of economies of scale, the cost per child would be lower in larger countries because these costs are spread over a larger EPI population. Furthermore, the Zambia rollout did not benefit from expanding to other provinces and capitalising on the lessons learnt in Southern Province, which would presumably reduce the average cost of rolling out the interventions as it did in Tanzania. It will be important for the programme to continue to share the costs of deployment to additional regions or provinces and facilities to enable comparison with the costs we present here and also to inform decision-making and budgeting. Tanzania has continued to rollout the EIR to additional regions after the BID initiative ended. The government of Tanzania is now scaling the EIR nationally with their Gavi Health System Strengthening funds, and to date (October 2019) the EIR is currently in nine regions with plans to scale the rest of the country in 2020. The government of Zambia is also using their Gavi funding to continue work in Southern Province and has provisional approval on funding to expand to Western Province.The following considerations should be kept in mind when using these findings as a benchmark. First, the expenditures we report included the actual software development costs in each country, which is a significant expense that other countries may not have to incur, as they can build from these EIR systems that are available now. Second, learning costs associated with the EIRs that were shelved increased system development and rollout costs for Tanzania and Zambia; again, other countries need not go through these same learning processes as the intent is that they can build off of the either of the software systems developed for Tanzania or Zambia. Third, BID staff labour costs were a significant share of the expenditures; costs may be lower if government staff conduct some of the activities undertaken by BID. For these reasons, the costs we report here may be the upper-bound costs for EIR system development and rollout in LMICs. It should also be noted that recurrent costs may shift as governments take over the running of EIR systems, depending on how they choose to host the data, how they conduct the maintenance and management of the system and what level of ongoing training and support they choose to provide to users. Additionally, as governments scale up EIRs to other regions, financial expenditures may change as they use existing resources or choose different strategies to implement and deploy interventions. Although we found that recurrent costs were a small share of the expenditures, governments may (or may not) be able to negotiate reduced rates for costs such as internet connectivity and data hosting. Nevertheless, our study can be used to estimate future expenditures for EIR development and deployment in LMICs. Finally, the expenditures presented here may seem a relatively large share of the country’s immunisation spending. Tanzania’s total expenditure for the routine immunisation programme was ~US$73 million in 2017 while for Zambia it was US$38 million.This analysis had several limitations. First, we included the financial expenditures only of the BID initiative; because this analysis focuses on financial rather than economic costs we did not quantify the opportunity costs for government employees’ time spent in trainings or the economic costs of using existing government resources for deploying the interventions. Second, in this study, we only present expenditures and not the benefits of the EIRs; however, these benefits were evaluated and will be disseminated through other publications by the BID initiative research team. Last, electronic registries are an important source of more reliable denominator data, yet we present our cost-per-child estimates using EPI target population data. To the extent that the EPI target populations are underestimated, we have overestimated the cost per child and vice versa.Our study may be the first to provide the total costs of ownership for EIR development and rollout at scale in a province or region in Africa. Stakeholders can use this evidence to benchmark expenditures for future investments. We anticipate that other countries will benefit from the investments made and lessons learnt in Tanzania and Zambia by leveraging these now existing EIR platforms and rollout strategies, and hence may be able to implement EIRs at lower costs than reported here.


Donor funding for HIV/AIDS services is declining in Cambodia, and domestic resources need to be mobilized to sustain and expand these services. However, the cost of delivering HIV/AIDS services is not well studied in Cambodia. This study aims to assess the costs of delivering HIV/AIDS services, identify the major components of costs, and sources of funding.Four of the six highest HIV burden provinces were selected at random for this study. Within each province, four health centers and two hospitals were selected for detailed data collection. A mix of top-down and bottom-up methods were used to assess the costs for HIV testing and antiretroviral therapy (ART) from the provider perspective. We assessed the differences in the quantity and prices of inputs between health facilities of the same type to identify cost-drivers.The average cost per visit for HIV testing was $8.92 at health centers and $14.03 at referral hospitals. Differences in the number of visits per staff were the primary determinant of differences in the cost per visit. First-line ART costed about $250 per patient per year, and the number of patients per staff was an important cost driver. Second-line ART costed from $500 to $716 per patient per year, on average, across the types of facilities, with the quantity and mix of second-line antiretroviral drugs being an important cost driver. Inpatient care at referral and provincial hospitals in total represented less than 2 percent of costs of outpatient ART.Costs are similar to neighboring countries, but over 50% of the costs of ART are financed by donors. Cambodia now is scaling up social health insurance coverage; the data from this study could serve as one input when setting reimbursement rates for HIV/AIDS services to help ensure that providers are adequately reimbursed for their services. One of the targets of Sustainable Development Goal 3 is to end the acquired immune deficiency syndrome (AIDS) epidemic by 2030. The number of people receiving antiretroviral therapy (ART) has risen to 17 million people from 15 million people in 2015, a target set by the United Nation General Assembly in 2011[Despite these achievements, huge challenges remain to end AIDS by 2030. There were around 2.1 million new infections worldwide in 2015, which increased the total number of PLHIV to about 36.7 million people. The Fast-Track approach to ending AIDS by 2030 is estimated to require about US$ 26.2 billion in 2020 . The gloCambodia, a country that has been internationally praised for its successes in combating the HIV epidemic , has, liHIV/AIDS programs in Cambodia have historically been financed by donors, the Ministry of Health (MoH), and out-of-pocket spending. However, in recent years Health Equity Funds (HEFs), a social insurance scheme for the poor, have begun to provide financing for some HIV/AIDS services that are not funded by the National Center for HIV/AIDS, Dermatology and Sexually Transmitted Diseases (NCHADS) , 9. ThisA key factor driving provider incentives is whether, for each patient treated, the revenue brought in from various sources such as government, health insurance schemes, donors, and direct patient payments is less than, equal to, or greater than the cost of delivering those services. Revenue is largely known, but costs are not. As HEFs and perhaps NSSF take on a greater share of HIV/AIDS financing in future, cost data from health facilities can be used to shape the payment mechanisms used to purchase services and inform the rates at which HIV/AIDS services are reimbursed.This study aims to understand the unit costs of delivering HIV/AIDS services, identify the major components of costs, and the sources of funding. The results can be used to inform HEFs or NSSF payment rates, contribute to resource estimation models, and help identify current sources of financing for HIV facility-based services.The study population consisted of all the health facilities  offering HIV/AIDS services in the six provinces in Cambodia with the highest burden of HIV: Bantey Meanchey, Battambang, Kampong Cham, Phnom Penh, Siem Reap and Tbong Khum. Four of these six provinces were selected using simple random selection to be included in the study sample: Battambang, Kampong Cham, Phnom Penh, and Siem Reap. Within each province, we selected four health centers and two hospitals, including provincial and referral hospitals, using simple random sampling. In Cambodia, health centers serve as the point of primary care, typically offering general outpatient services with two or three specialized clinics  and 11 or fewer total staff . ReferraCosts for services, to the extent possible, were inclusive of all the inputs used to deliver services at the health facility level. The services accounted for in the costing include:HIV counseling and testing: Including the costs of voluntary and confidential counseling and testing (VCCT), testing and counseling of pregnant women, and provider initiated testing and counseling (PICT).Antiretroviral treatment (ART): The provision of antiretroviral therapy, including first line antiretroviral drugs (ARVs), second-line ARVs, pediatric ARVs, laboratory monitoring, and outpatient treatment of opportunistic infections(OIs). Costs were calculated for ART overall, and then broken down into costs for patients on first-line, second-line, and pediatric ART. Pediatric ART costs included the costs of early infant diagnosis of HIV. These costs did not include the costs of community-based activities.Prevention of mother-to-child transmission of HIV (PMTCT): Due to difficulty in allocating costs, only costs for visits and treatment of infants exposed to HIV were included while testing of pregnant women was included in VCCT. As HIV-positive pregnant women were all enrolled in ART, costs for these services were included in ART.Inpatient care for the treatment of OIs (where applicable); costs for inpatient care are not included in costs for outpatient ART and are presented separately.The direct costs associated with the services at the health facility level were included in the cost analyses. These include:ARVs and other drugs (primarily drugs used for OI prophylaxis or treatment) that could directly be tracked at the clinic offering HIV services within the health facility. Costs for drugs represent the amount dispensed from the health facility to ART patients, inclusive of any wastage, for outpatient care.Medical supplies were included as direct costs if records of medical supply consumption were available at the relevant clinic, or staff could estimate medical supply usage. If these costs could not be obtained at the clinic level, medical supplies costs obtained at the facility level were included as an indirect cost.Human resources costs for staff working directly in the clinic providing the service. These costs were based on interviews with staff estimating the amount of time they spent working in different clinics within the health facility.Laboratory consumables associated with HIV/AIDS services. This included reagent and annual equivalent machine costs based on the number of tests performed for ART or VCCT patients, inclusive of CD4, viral load, alanine aminotransferase / aspartate aminotransferase, hemoglobin, creatinine, hepatitis B surface antigen, hepatitis C, and DNA polymerase chain reaction (for early infant diagnosis) tests. Note that other laboratory costs such as human resources and other overhead cost  are included in laboratory costs. These costs included the cost associated with the transport of laboratory samples to another facility, when applicable. Reagents and consumables associated with laboratory tests done off-site were included in these analyses based on estimated reagent usage per test. However, we could not include the human resources and other costs associated with conducting laboratory tests off-site due to lack of data from the referral laboratories unless the referral laboratory was located at a site included in our sample. To avoid double counting of costs, we did not include the costs of laboratory tests done off-site if the testing was referred to a type of facility that was included in the sample.Ancillary services directly related to HIV/AIDS services, including partner notification, loss-to-follow-up tracking, contact tracing done by health facilities’ staff, etc.HIV/AIDS-specific training, mentoring, and supervision.Annual equivalent costs for equipment and furniture costs for items in the clinic where HIV/AIDS services were offered. As with human resources, in cases where HIV/AIDS services were provided in clinics with multiple functions, equipment and furniture costs were allocated to HIV/AIDS services based on the number of visits.Costs for pharmaceutical products and laboratory investigations for inpatient care: In each facility where inpatient care was offered to HIV positive patients, up to 20 patient medical records for HIV were randomly sampled. In facilities with fewer than 20 admissions for a particular condition, all applicable medical records were taken. Data on the type and quantity of drugs and lab tests received were extracted from the patient medical records to estimate the costs for these categories of items. Thus, unlike for outpatient care, the costs of pharmaceutical products for inpatient care reflect the costs of prescriptions, rather than actual usage.Cost was done from the provider perspective. Patient payments, including out-of-pocket payments at point-of-service, costs for accessing services such as payments for transportation and food expenditure were not included.Indirect costs included: vehicle costs, medical gases, oxygen, medical supplies, patient food, staff food, estimated cost of rent for the building, electricity, fuel and oil, cooking gas, water and water disposal, building and general maintenance, vehicle maintenance, repair and licensing, cleaning supplies and expenses, bed and linen supplies, telecommunications, office supplies and printing, insurance, meeting and visitor reception costs, uniforms, treasury tax, festival/ceremony expenses, and other indirect costs .We include costs of offices, services, and ancillary units that provide services to HIV clinics , within a health facility.Six data collectors and one data collection supervisor received five days of training on the data collection tools and process starting 22 June 2017. Two data collection teams, consisting of two data collectors and one team leader, visited each facility and undertook structured data extraction. Data collection ended on 21 August 2017. The two teams each visited the same provinces at the same time, and were accompanied by a data collection supervisor who reviewed data collected each day. They interviewed staff, reviewed personnel and clinic/ward registered, reviewed drug stack cards, observed physical infrastructure, and reviewed financial records . Data were recorded on paper data collection forms. The paper-based data was double entered into prepared templates in Microsoft Excel, and differences between the two data entry forms were reconciled based on the paper-based data collection form. Entered data were further reviewed and corrected by research staff.http://dx.doi.org/10.17504/protocols.io.2eggbbw.The Abt Associates Institutional Review Board approved this study on 12 May 2017, and the National Ethics Committee for Health Research (Cambodia) on 07 June 2017. The National Center for HIV/AIDS, Dermatology and STD (NCHADS) endorsed the study on 16 May 2017. Interviews of health facility staff were done only in their official capacity. The information collected from the health facilities comprised routinely collected data on utilization, supply usage, and financial records. Names, sex, age, and other direct or indirect identifying data on patients were not recorded as part of the data collection , nor were patients interviewed or contacted as part of this research. Summary of the research protocol for this study in English can be accessed at Data were first analyzed for each facility separately. For each facility, a Microsoft Excel workbook was set up based on the Management Accounting Systems for Hospitals template for costing health facilities . The appCosts are reported on average for each type of facility included in the sample, with costs for the NGO clinic reported separately from other types of facilities. Total costs are also broken down by source of financing. Unit costs reflect the total cost divided by the number of services provided. Due to the small sample sizes, ranges in total and unit costs are reported rather than with standard errors.We assessed the differences in the quantity of inputs and the prices of inputs between health facilities of the same type . In order to do this, we replaced the individual input (quantity or price) of each health facility with the average amount/price of the input for that type of facility. We then recalculated the unit costs of services, and assessed the change in the average unit cost of the service. We identified all input quantities or prices that changed the average unit costs by more than 2 percent from the observed average unit costs. The items that changed the average unit costs by more than 2 percent are considered to be ‘cost drivers’–that is, inputs that potentially could be leveraged to increase the efficiency of service delivery . ResultsOne hospital sampled for inclusion declined to participate in the study; a replacement hospital was selected from the same province. Further, the provincial hospital in Battambang is a very large hospital, and data collection at this facility took longer than anticipated. In order to maintain data collection within the available budget, data were not collected from health centers in Battambang. Thus, the final sample included 21 health facilities: 2 provincial hospitals, 6 referral hospitals, 12 health centers, and 1 non-governmental (NGO) clinic . None ofResults for each of the service categories  are presented below. Each of these sections discusses the total cost, on average, for the provision of services at different types of health facilities, summarizes the components of the total costs, assesses the sources of financing for the total costs, presents total utilization numbers on average for the provision of services at different types of health facilities, the results for the unit costs of delivering the service, and finishes with a discussion of the variance analysis.On average across the sample, the total cost of VCCT at health centers was about $4,800, ranging from $760 to $13,600 . At refeAt government-owned facilities , costs for staff were the largest category of costs, comprising over a third of costs at all levels. At the NGO clinic, ‘other direct activities’ comprised the second largest cost category at 20 percent of costs (after intermediate services step-down costs); most of these were costs incurred for a risk tracking pilot. These costs likely will change in the future as the risk tracking program matures. Costs for the rapid tests were under 20 percent of the costs, on average, across facility types.The Royal Government of Cambodia (RGC) financed the majority of costs at government owned facilities, while the US Government funded the majority of costs at the NGO clinic . ExternaHealth centers and referral hospitals averaged about 1,000 visits for VCCT. However, at health centers, 81 percent of visits for VCCT were from pregnant women, while less than 10 percent of visits for VCCT at referral hospitals were from pregnant women . PICT coThe cost per VCCT visit costed, on average, $8.92 (range: $2.10 to $18.34) at health centers, $13.09 at the NGO clinic, $14.03 (range: $5.75 to $29.05) at referral hospitals, and $8.79 (range: $5.89 to $11.69) at provincial hospitals. Cost per initial test was similar to the cost per visit because most visits included a test.The variance analysis showed the same two inputs were cost drivers at health centers, referral hospitals, and provincial hospitals. When the number of full time equivalent (FTE) staff per visit was changed to the average across health centers and unit costs recalculated using this average, the cost per VCCT visit changed by 19 percent (a change of $1.68 from the baseline average of $8.92), and at referral hospitals the cost per VCCT visit changed by 30 percent (a change of $4.21 from the baseline average of $14.03). At provincial hospitals, the change was 6 percent (a change of $0.49 from the baseline average of $8.79). The second cost driver was the average salary of staff, which changed unit costs by 5 percent, 2 percent, and 5 percent at health centers, referral hospitals, and provincial hospitals, respectively.On average across the sample, the cost of ART at referral hospitals was about $104,000  in total . The twoCost for first-line ARVs was the largest category of costs across the facility types, ranging from 34 percent to 42 percent of total costs. At provincial hospitals, second-line ARVs were the second largest cost category , while at the NGO clinic and referral hospitals, staff salaries and remuneration were the second largest cost category . All ARVs comprised 44 percent, 46 percent, and 49 percent of costs at the NGO clinic, referral hospitals, and provincial hospitals, respectively.The Global Fund, which finances the majority of costs for CD4 and Viral Load laboratory tests and about 90 percent of the costs for ARVs and some of the drugs for treating OIs, accounted for the majority of costs across the three facility types, on average . The US At the start of the year, provincial hospitals had, on average, 2,569 patients on first line ART and 170 patients on second line ART, while referral hospitals had 350 patients on first line ART and 12 patients on second line ART. Referral hospitals had just less than 2,000 visits per year, on average, serving about 380 patients per year . The NGOThe cost per patient per year for first-line ART was $323, $263, and $214 on average for the NGO clinic, referral hospitals, and provincial hospitals, respectively . At indiWhen replacing individual facility input values with the average values for provincial hospitals, none of the inputs changed the cost per person per year for first-line ARV patients by 2 percent or more. At referral hospitals, changing the number of non-CD4 and non-viral load (VL) laboratory tests changed the average cost per patient per year for first-line ARV patients by 9 percent (by $23.29 compared to a baseline average of $263.18). One referral hospital reported a high number of non-CD4 and non-VL laboratory tests compared to other facilities in the sample. Replacing the facility-specific number of patient-years per FTE with the average changed the cost for first-line ARV patients by 7 percent (by $19.18 compared to a baseline average of $263.18).Facilities showed that patients on second-line ARVs predominantly were on an Atazanavir + Ritonavir or a Lopinavir + Ritonavir based regimen. Provincial hospitals had a higher cost per patient per year ($772) than referral hospitals ($618) for second-line ART predominantly because of different ARV mix (which accounted for 81% of the higher unit cost), with greater use of laboratory tests also contributing (accounting for 18% of the higher unit cost). At referral hospitals, the number of non-CD4 and non-VL laboratory tests is again found to be a cost-driver, again due to one facility with a high number of these types of laboratory tests. The number patients per staff, similar to patients on first-line ARVs, is also found to be a cost driver at referral hospitals, and replacing the facility-specific number of patient-years per FTE with the average changed the cost for first-line ARV patients by 5 percent.Variation in unit costs for VCCT, first line ART, and second line ART by type of health facility and service is shown in The average total cost of inpatient care for OIs was about $1,650 at referral hospitals and $12,300 at provincial hospitals . In bothReferral hospitals and provincial hospitals had a similar admission rate of about 40 admissions per 1,000 ART patient-years (the NGO clinic reported that they did not refer any ART patients for inpatient care) . ReferraThis study summarizes the cost of providing HIV/AIDS services at health facilities in Cambodia. It presents a detailed and comprehensive approach to assessing the costs of these services, including facility step-down costs and indirect costs. As such, it can serve as the basis for future resource need assessments and other financial projections assessing the costs of these services in the future. It could also be used to track how and why unit costs change over time.The results of this study showed that the number of visits per year for VCCT was about 1,000 at health centers and referral hospitals, and the cost per visit for VCCT averaged $8.92 at health centers, and up to $14.03 at referral hospitals. The costs of providing VCCT vary from country to country, but our results suggest that costs for VCCT in Cambodia are roughly in-line with or possibly less than other countries. The costs of VCCT per client in Tanzania and Kenya were $29 and $27 in 2000, respectively . The cosFor VCCT, number of staff per visit and staff salaries were the two main cost drivers. These cost drivers reflect staff salaries and benefits as being the largest cost component of VCCT at government health facilities, and suggest that standardizing the level of effort per visit is a potential mean of increasing the efficiency of services. However, the level of effort of staff was not precisely measured in this study. At health centers especially, VCCT was delivered in other clinics  and thus variation in FTE per visit also reflects overall usage of the clinic where VCCT is delivered. While standardizing facility overhead and indirect costs does not affect the unit cost of services by more than 2 percent, it does reduce the variance in the cost per VCCT visit by over 50 percent across the three types of health facilities, again suggesting that overall facility utilization (or efficiency) is an important source of variation in the unit costs for VCCT.The provision of first-line ART costed around $250 per patient per year, and the number of patients per staff was an important cost driver. The result is reasonably similar to the studies from Vietnam ranging from $272  to $325 The results suggest that HIV/AIDS services in Cambodia are dependent on donor funding. ART is the most donor dependent, with upwards of two-thirds of all costs financed by the US Government or The Global Fund. The bulk of this  is for procurement of ARVs, and procurement for disease specific HIV drugs is largely financed by donors. Procurement of HIV commodities has been a challenge in other settings during financial transitions, and securing not just the financing, but ensuring that logistic and administrative capacity is in place may also need to be addressed in Cambodia. There is a substantial amount  of investment from the US Government in terms of staff salaries and support for ART activities. Further, all referral and provincial hospitals reported that NGO staff worked to provide ART services. Thus, securing the staff necessary to deliver ART services at hospitals will be an important issue to address when financing of ART is transitioned from external to domestic financing. For VCCT, 20 percent to 35 percent of costs are paid by donors (excluding the NGO clinic with is largely dependent on donor funding for its operation). Because VCCT is overall less expensive than ART, these funds may be easier to replace with domestic resources, but still include staff salaries . Many ancillary support activities that are required to successfully deliver services, such as training, supervision, laboratory sample transport, loss to follow-up tracking, etc., are largely supported by donors. While not a substantial proportion of the total costs of delivering services , ensuring their continuity during transition remains important.There was a substantial range in the unit cost of providing services across facility types and among individual facilities. For example, the cost per patient-year for first-line ART at some referral hospitals is less than two-thirds the average cost at all referral hospitals, while at other referral hospitals it is more than 1.5 times greater than the average. Some variability in the unit costs of providing services is to be expected, given that different facilities will have different service volumes, staffing levels, etc. However, large ranges in unit costs may indicate inefficiencies in the delivery of services. Large ranges also make decisions about, for example, establishing reimbursement rates harder to accurately assess. Further work to understand the reasons for the wide ranges in unit costs and working to limit the variability in costs can help ensure that HIV/AIDS services are sustainable and help enable planning for financing of the services.In many cases, the level of effort of staff per patient served is an important determinant of the differences in costs. Staff salaries and benefits accounted for about one quarter to nearly one half of VCCT services. At health centers, HIV services typically  are delivered in a clinic that is not specifically for HIV . In these cases, deriving efficiencies from staff effort may be difficult. However, at referral and provincial hospitals, some efficiency may be gained by rationalizing staff load (while ensuring that enough staff with the necessary skills to deliver services remain).ARVs constitute nearly half of the costs of first-line ART, and well over half of the costs of second-line ART. As Cambodia moves to the ‘test and treat’ model of ART and more patients enroll on ART, the financing of ARVs must be accounted for. While patients on second-line ART constituted 5.8 percent of all ART patients, they represented 14.5 percent of ART costs, and second-line drugs can be up to 12 percent of the costs of delivering ART at some types of facilities. This analysis found use of second line ARVs was widely variable, on a per patient basis, across sites. Part of this variation found in this study may the result of poor record keeping, with pharmacy stock cards potentially being incomplete or inaccurate at some sites,  but likely some reduction in wastage of second-line antiretroviral drugs may be possible.Facility administration, logistics, ancillary services and indirect costs represent a substantial proportion of the overall costs for VCCT  and ART . The current financing of these costs has not been fully explored–it is likely a mix of government spending through budgetary process and block grants as well as user fee revenue. As financing of HIV/AIDS shifts, assessment of whether new payment mechanisms need to (and do) account for these costs may be necessary.The results of this analysis in general, and for sources of financing in particular, may not be applicable to parts of Cambodia not included in this analysis. Donor support is variable by province and region, and more detailed understanding of what activities are done and what activities use donor support in other parts of Cambodia may be necessary. Many regions not included in this analysis have fewer persons enrolled in ART care and otherwise may experience different volumes of service, which potentially indicates that they will have different cost structures that the facilities included in this analysis. Further, data available in the registers at some sites were of questionable quality; the results of this study should be seen as indicative of the costs of services rather than a precise estimate. This study did not include costs incurred by patients to access care or the costs of NGOs operating community-based programs, and thus do not provide a holistic picture of the costs of HIV/AIDS services in Cambodia. Further work is needed to assess these aspects of costs. Further work is also needed to track how costs of HIV/AIDS health services change over time, especially as treatment protocols change and as changing sources of finance influence health service providers’ behavior. Finally, assessing in more depth how to minimize variation in costs to make financing of HIV/AIDS services more predictable would also be warranted. With the limited sample size in this study, we have not attempted to assess the potential associations between scale, maturity, geography, etc. and costs but further work in this area is warranted.The results of this study give preliminary evidence on cost of providing HIV/AIDS services at public health facilities and one NGO facility in Cambodia. Out-of-pocket payments, most notably for accessing services, and community-based costs were not included. Cambodia now is scaling up its social health insurance coverage; thus, the data from this study could be used as one input to consider when setting reimbursement rates for HIV/AIDS services assessed by insurers to help ensure that providers are adequately reimbursed for their services. Similarly, these data could serve as a basis for negotiations to contract HIV/AIDS services to private providers. In addition, these data can be used as a starting point for tracking and monitoring the cost of delivering HIV/AIDS services over time as input prices change or as efforts to improve the efficiency of service delivery are made; this is especially important because since the completion of the data collection for this study PEPFAR and Global Fund financing of HIV services has become more limited. The sample frame did not include low burden of disease provinces, and was limited in the number and type of facilities that were visited; thus, interpreting or using the data presented in this study should be done cautiously.S1 FigFunders include Centers for Disease Control (CDC), Non-Governmental Organizations (NGOs), the President’s Emergency Plan for AIDS Relief (PEPFAR), and the Royal Government of Cambodia (RGC).(DOCX)Click here for additional data file.S2 FigFunders include Centers for Disease Control (CDC), Non-Governmental Organizations (NGOs), the President’s Emergency Plan for AIDS Relief (PEPFAR), and the Royal Government of Cambodia (RGC).(DOCX)Click here for additional data file.S3 Fig(DOCX)Click here for additional data file.


The purpose of this project was to develop a telemedicine platform that supports home site monitoring and integrates biochemical, physiological, and dietary parameters for individual patients with hepatic glycogen storage disease (GSD).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].The GSD communication platform (GCP) was designed with input from software developers, GSD patients, researchers, and healthcare providers. In phase 1, prototyping and software design of the GCP has occurred. The GCP was composed of a GSD App for patients and a GSD clinical dashboard for healthcare providers. In phase 2, the GCP was tested by retrospective patient data entry. The following software functionalities were included (a) dietary registration and prescription module, (b) emergency protocol module, and (c) data import functions for continuous glucose monitor devices and activity wearables. In phase 3, the GSD App was implemented in a pilot study of eight patients with GSD Ia (This report describes the design, development, and validation process of a telemedicine platform for patients with hepatic GSD. The GCP can facilitate home site monitoring and data exchange between patients with hepatic GSD and healthcare providers under varying circumstances. In the future, the GCP may support cross-border healthcare, second opinion processes and clinical trials, and could possibly also be adapted for other diseases for which a medical diet is the cornerstone. Hepatic glycogen storage diseases (GSDs) are a group of inborn errors of carbohydrate metabolism, for which a strict diet is the cornerstone of management. Patients with hepatic GSD display perturbed glucose homeostasis due to a deficiency of a functional enzyme or transporter in glycogen synthesis, glycogenolysis, and/or gluconeogenesis. This generally leads to fasting intolerance, failure to thrive and hepatomegaly, and is biochemically associated with (non)ketotic hypoglycemia,  hyperlactacidemia, increased liver enzymes and hyperlipidemia  systems have been developed to facilitate glucose monitoring. Originally, CGM systems were developed for patients with diabetes mellitus (DM) (Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group Telemedicine (TM) has emerged rapidly as a novel tool to deliver healthcare tailored to the individual patient’s needs Moore . BesidesTo support home site monitoring and to integrate biochemical, physiological, and dietary parameters, we have 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) for patients and their caregivers and the GSD clinical dashboard for healthcare providers.support rather than replace current healthcare as provided by our center of expertise for hepatic GSD and recommendations were only generated after approval by a healthcare provider. The usability pilot study has been carried out in accordance with ethical and legal guidelines of the University Medical Center Groningen  and The Code of Ethics of the World Medical Association (Declaration of Helsinki). Technical documentation and user manuals of the GCP were prepared for the validation of the GCP as a class I medical device, as described in the Medical Device Directive 93/42/EEC. The creation of the technical documentation was supported by DRS consultancy (http://drs.nu/en_US/) and subsequently reviewed by the quality consultant medical devices of the University Medical Center Groningen, in preparation of notifying the GCP to the national Inspectorate of Health for a Conformité Européenne (CE) mark.The GCP was intended to Phase I — Prototyping and software design:Intended uses — The intended use of the GSD App is to allow individuals with hepatic GSD to support their dietary management provided by healthcare providers, under normal circumstances and intercurrent illness, by monitoring and sharing home site collected data with healthcare providers. The intended use of the GSD clinical dashboard is to integrate data collected by hepatic GSD 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 protocol is applicable.https://www.owasp.org/) was adopted to secure integrity and privacy of online communication within the GCP. Access to the applications required a username and password. Passwords were stored with a salted and one-way encryption method to protect from accidental or unlawful loss. Software test plans and complaints management procedures were set up for post-market evaluation. The GCP was hosted on Microsoft Azure . For the GSD App development, the open source frameworks AngularJS, JavaScript jQuery, and Bootstrap were chosen. A non-commercial license from Highcharts (https://www.highcharts.com) was used to display the graphs in the GSD clinical dashboard.Data security and management — For both applications, the Hypertext Transfer Protocol Secure (HTTPS) and the Open Web Application Security Project Top Ten awareness document  GSD patients, researchers, and healthcare providers from June 2014 till present. The GCP was composed of two web applications; the GSD App for patients and their caregivers and the GSD clinical dashboard for healthcare providers. The GSD App was developed in Dutch, the native language for most of our patients, whereas the GSD clinical dashboard was developed in English. Figure Phase II — Software development and retrospective clinical data entry:Features and functionality were reviewed and issues on usability were managed, processed, and documented with the use of a Jira issue tracker from Atlassian® by software developers, researchers, and healthcare providers.Dietary registration and prescription module — The Dutch Food Composition Table (NEVO table)  was created. An Application Programming Interface (API) was acquired by Fitbit, Inc. to import data from the activity wearable in the GSD App.Retrospective data entry — Data from written food and clinical measurement diaries were retrospectively collected in the GCP by the researchers to test the usability and correctness of the GCP functionalities. These data were from patients who visited the University Medical Center Groningen GSD center of expertise between March and October 2016 and who gave written informed consent for the use of their data collected during their visit.The following software functionalities were included:Subjects and pilot study design — Between March and July 2017, data were prospectively collected in the GCP by selected GSD patients visiting our center. Patients were introduced to the GSD App by the treating physician (TGJD) and researcher (IJH). All subjects received an up-to-date manual for the use of the GSD App. Data exchange was requested by the healthcare provider to allow individual data integration in the GCP and critical follow-up after dietary changes. Subjects were asked to use the GSD App for home site monitoring before, during, and/or after a clinic visit, according to the purpose of their visit. Furthermore, subjects could temporarily use an activity wearable with a heart rate function (Fitbit Charge HR™). A CGM system by Dexcom was used only when needed for regular care. Data from the CGM were retrospectively imported in the GSD clinical dashboard by the healthcare providers. Results of data integration in the GSD clinical dashboard  were discussed with the subjects/patients and their parents during the outpatient clinic visit and/or via a telephone or videoconference consultation following the (outpatient) clinic visit.Survey methods — User feedback was documented in a structured logbook and usability issues from different users  were uploaded in the Jira issue tracker for further software improvements. Subjects and/or caregivers were asked to give feedback on the GSD App via an open feedback form on paper or electronically via a SurveyMonkey questionnaire and to fill in the system usability scale (SUS) Brooke . An adjePhase III — Implementation and pilot study prospective clinical data entry:For the software development and validation process of the GCP, three phases were constructed.https://app.gsdapp.nl in the internet browser on a mobile phone. The GSD clinical dashboard can be accessed via a desktop browser: https://clinicaldashboard.gsdapp.nl.Figure Access to individual patient registered data in the GSD App was restricted to the patient user and their caretakers. Data share requests by healthcare providers via the GSD clinical dashboard  were only answered by and with the permission of (the caretakers of) the patient.The combo graph in the GSD clinical dashboard displayed combined data of the patient from the requested period in one interactive graph see Fig. c. The GSThe implementation of the NEVO table supported dietary registration, prescription, and macronutrient calculations. An extra function was added for the entry of drip-feeding to simplify the determination of the rate of drip-feeding in milliliters per hour and the macronutrient intake.n = 3), GSD IIIa (n = 1), and GSD IX (n = 1). Improvements for dietary registration in the GSD App and data visuals in the GSD clinical dashboard were implemented. Eventually, retrospective data entry led to the development of the GSD App and GSD clinical dashboard versions for the usability pilot study in phase III.Table n = 3), IIIa (n = 1), and IX (n = 4). Table n = 3) and caregivers (n = 5). Patient #P01 used the GSD App together with her parents as a first step toward autonomy.The GSD App was prospectively used by eight patients with GSD type Ia  compared to adult patients or parents with older children (≥12 years of age) . Patients reported in the open feedback form that it was easy to have their dietary prescription at hand and that the GSD App worked more efficiently compared to the paper food diaries. Points for improvements were the search strategy for the right food items and the feedback from healthcare providers on registered data.Feedback on the GSD App could be collected for 7/8 GSD App users  legislation, as discussed below.This report describes the design, development, and validation process of a TM platform for patients with hepatic GSD. The GCP can facilitate home site monitoring and data exchange between patients with hepatic GSD and healthcare providers under varying circumstances. Rather than a The GCP has been developed as a supportive tool for GSD patients and healthcare providers in our center of expertise. The GSD App allows patients to easily collect data at home as a preparation for an outpatient clinic visit, for the monitoring of in-hospital dietary interventions, and for the evaluation of metabolic control at home and during physical activity. In addition, the GSD App gives patients access to their individual dietary management plan and emergency letter. Based on the collected SUS scores in the pilot study, it can be suggested that parents of GSD patients are in more need of a home site monitoring tool like the GSD App to manage everyday care for their child. The GSD clinical dashboard for healthcare providers facilitates diet prescription and emergency letter generation. Furthermore, the GSD clinical dashboard offers healthcare providers the possibility to analyze home site collected data from the individual patient. For several hepatic GSD subtypes there are international guidelines  in healthcare Dimitrov . IoT allThe revolution of the internet has generated increasing interest for home site or remote monitoring in healthcare that can overcome many of the issues listed in Table Some limitations need to be addressed. First, we performed a pilot study with a small number of patients only focusing on the usability and functionalities of the GSD App. Future research must focus on the effect of the GCP intervention on metabolic control, quality of life, and cost-effectiveness. Usability of the GSD clinical dashboard for healthcare providers should also be studied. Second, new versions of the GSD App have been released in between the collection of SUS scores. Continuous improvement of the GSD App based on patient’s feedback was possible due to close collaboration with the patient population and software developers, but therefore SUS score interpretation should be done with caution. Third, for the development of the GCP, the team collaborated especially with parents of GSD patients, hence the needs of (young) patients may have been underestimated.Currently, the European Medical Device Directive 93/42/EEG is still the legal fundament guiding CE mark procedures of medical software, whereas ISO 14155:2011 addresses the good clinical practice of clinical investigations with humans to assess the safety and performance of medical devices. Since the start of our project, however, in our rapidly changing technological society, new European legislation has been approved regarding medical devices  and data privacy . Hence, technical, societal, medical, and legal developments are continuously influencing the process, demonstrating the complex dependency of different stakeholders to support healthcare for our patients and their caregivers.Future perspectives and applications of the GCP are numerous. The platform could facilitate cross-border healthcare, support second opinion processes, and provide support during clinical trials. In theory, the GCP could be adapted for patients with congenital hyperinsulinism and ketogenic diets  and inherited metabolic diseases for which a medical diet is the cornerstone. For these purposes, multiple translations and integration of the GCP with national food databases and electronic patient file systems will be crucial. The — in 2016 formally recognized — European Reference Network for Rare Hereditary Metabolic Disorders (MetabERN) could support the generation and  maintenance of such TM projects Raposo , or alte