Adoption challenges of iNICU in first 3 NICUs

by | Dec 22, 2017 | Articles | 0 comments

In the progressively digitizing world, India is not far left behind considering the country has got significant potential for digital growth because of its current technology penetration, advancing economy, growing population and accelerating healthcare industry.[1] Healthcare industry seems an appropriate target for digitization as the industry generates large amounts of data which is mostly stored in hardcopy form.[2] In this context, India appears to offer an ideal atmosphere to implement a novel innovation called integrated neonatal intensive care unit (iNICU), a technology with the ability to digitize the working of NICUs. iNICU, with the aim of automatizing the workflow of NICU, addresses the challenges of capturing entries with minimal probabilities of error and multi-dimensional clinical electronic patient records from lab, devices and other third party systems. It comes with the capability of integrating manifolds of data from biomedical devices, clinical documents, laboratory reports, pharmacy reports and diagnosis codes, in turn helping in establishing early prognosis, prevention, and diagnosis of preterm babies.[3]

In order to realise the complete potential of the system, we implemented iNICU in 3 NICUs of the country: one in a rural facility, one at an evolving site in urban region and at an established site in urban region.

In the rural facility, the workforce did not seem IT savvy considering most of the staff was inhabitant of rural area. So, getting a “not-so-techno-familiar” staff to adapt to a tablet for almost every routine work was a challenge. In the initial phases, they were unwilling to make entries in tablets and preferred files. To address this, we provided them with an alternative option of making entries in a laptop. They still had to be persuaded by senior resident doctors again and again to make entries in laptop as well. Another significant challenge that we faced initially was simple human tendency of forgetfulness towards something they are not habitual to. The nurses used to forget to make digital entries and if remembered, they used to forget the functioning of the system when they attempted to enter. They needed frequent guidance before being capable of making entries independently. Since, all the devices in NICU of the rural facility were of diverse brands (depending upon the availability of the machine in that particular area) and were not upgraded according to the latest trends, integration was a major challenge for us.

Fortunately, the problems encountered in the urban facilities were not the same; but they could not be overlooked. The evolving site of urban region came with a separate set of hiccups initially. Since it was two-year-old facility, the number of neonates assigned to each nurse seemed high and the doctors were occupied for most of the time. The hierarchy of staff was not well-defined, so the doctor and nurses had their hands full with the responsibilities of managing OPD in addition to NICU commitments. Therefore, asking them to replicate the paper entries in tablet did not seem a feasible idea. Additionally, training was required whenever the duties of consultants were rotated.

On the other hand, the established site in urban region had a well-defined hierarchy of staff. Although, this seemed an absolute advantage in comparison to the evolving site, this was not the case. We had to follow complete flow of the hierarchy in implementation of iNICU since nobody had the discretion to take independent decisions. After being through with the process of implementation that took approximately 2-3 months, the duty of the personnel who was in charge of the complete process was rotated. Despite all this, the nurses of the facility were very receptive; nevertheless, they were reluctant to follow both paper and digital process. They had a well-established paper system since years. So, they expected an absolutely perfect digital system to which they can immediately switch from working on files without going through the paper plus tablet phase.

After closely monitoring the working of iNICU in these 3 NICUs, we came up with strategies to overcome these roadblocks in the path of easy adoption of iNICU. We built well-defined training collaterals in association with domain specialists where the NICU staff would be trained professionally regarding the system via presentation and hands-on session. After a 3-4 days professional training session, one of the trainer would be extending the stay to teach the NICU staff on how to capture the data in a real-time scenario. In order to augment the adoption, the trainer will himself/herself record vitals initially and demonstrate the ease with which the system works. For further support we will be providing with tutorials (self-explanatory videos) which can be accessed on our website. To provide 24*7 off-site support and assistance, we establish WhatsApp groups involving entire staff of the respective NICUs.

Additionally, to analyse the current status of adoption, the system itself contains an adoption screen for nurses and doctors to view the status of adoption in a single click. For the ease of understanding, we developed two types of scores: data adoption score and data quality score. The former acknowledges that at least minimal entries are being made by the staff during stay of the patient while the latter is for the later stages of implementation where the HOD can assess if entries are being made on a regular basis; at least 1 entry per day of patient stay.
To further acknowledge and counter the footfalls that may be encountered in the adoption process, we are keeping ourselves updated by regularly participating in neonatology conferences.

1. Indian healthcare on the cusp of a digital transformation. Available at: Accessed on: 12-12-2017.

2. Raghupathi W, Raghupathi V. Big data analytics in healthcare: promise and potential. Health Information Science and Systems. 2014;2:3.

3. Singh H, Yadav G, Mallaiah R, et al. iNICU – Integrated Neonatal Care Unit: Capturing Neonatal Journey in an Intelligent Data Way. Journal of Medical Systems. 2017;41(8):132.

Credits: Dr Yashika Dr Suneyna Ms Ravneet


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