Introduction
The goal of pharmacovigilance
(PV) is to protect patients from unnecessary harm. When medicine is marketed,
the identification and monitoring of adverse events (AEs) and reactions is a
part of a post-marketing safety surveillance program as required by federal
regulations (Kothari, Shah,
& Patel, 2018; Tan et al., 2016).
Health regulatory agencies have regulations to ensure that drug products are
safe for human consumption. Companies that are licensed marketing authorization
holders are required by regulation to perform active drug safety surveillance
and monitor the safety profiles of the products during the entire marketing
lifecycle (Basile, Yahi,
& Tatonetti, 2019). Companies use safety databases and reporting
software to process and report AEs to health authorities around the world (Lewis
& McCullum, 2019). Companies can use innovative information technology
(IT) solutions based on artificial intelligence and robotics to detect,
process, and report AEs, thereby adopting automation (Beninger, 2018; Donzanti, 2018). Companies can adopt an automation-enabled digital PV path for drug
safety surveillance and redirect the savings from PV operations towards
investing in the actual PV tasks like benefit-risk assessments of products,
thereby making the products more efficacious and safer for human use.
Problem Statement
In 2020, the U.S. Food & Drug Administration (2021) received reports of 2.2
million adverse events (AEs), which was a 350 % increase since 2010, with an
associated increase in pharmaceutical companies' AE-related operational costs.
AEs are one of the top three
reasons for drug recalls and can cost pharmaceutical companies $900 million for
a recall (Hall, Stewart,
Chang, & Freeman, 2016). The general business problem is that PV
systems managers may experience high operational costs for AE detection and
reporting leading to poor financial performance. The specific business problem
is that some PV systems managers in the pharmaceutical industry lack the
strategies to implement innovative technology solutions to automate AE case
processing (Easwar, 2020).
Methods
The purpose of this
qualitative single case study was to explore the strategies that PV systems
managers in the pharmaceutical industry use to implement innovative technology
solutions to automate AE case processing (Easwar, 2020). Since not many company managers
have implemented innovative technology like artificial intelligence (AI) and
robotics-based solutions for PV (Beninger & Ibara, 2016), we have focused on a select group
of managers who have successfully used strategies to implement innovative
technology solutions to automate AEs case processing. Therefore, because of the
need to use qualitative data collection procedures like interviews and
documentation reviews, a qualitative method was more appropriate than
quantitative or mixed methods.
We used a purposive sampling technique to select four PV systems
managers working in a pharmaceutical company located in the Boston area of
Massachusetts, United States, who have used successful strategies to implement
innovative automation technology solutions for AEs case processing.
We collected data from semistructured interviews, conducted using an
interview protocol until data saturation was reached, and triangulated the data
with documents collected from the participants. We used the TTF model as the
conceptual framework to guide our research on identifying the strategies PV
systems managers use for automating PV case processing.
We used ATLAS.ti software to organize and analyze the data collected
from the interviews. We manually analyzed the documents collected from the
participants for document review. For initial analysis, we used word cloud for
a visual representation of word frequency to get the first look and summarize
the interview transcripts. The words were then mapped to the themes and
strategies that were identified during the detailed analysis.
Research Question
The primary research question for this study was: What strategies do PV
systems managers use to implement innovative technology solutions to automate
AEs case processing?
Results
Three themes with nine strategies emerged during data analysis. The
themes were (a) automation solution selection and implementation strategies,
(b) business operational model changes, and (c) communication and training
strategies. On initial analysis, the word cloud showed system, project, vendor,
automation, implementation, communication, change, issues, and users as the key
and most frequently used words by participants in the interviews as shown in
Figure 1.
Fig. 1: Word cloud
Word cloud showing the most frequently used words in the interview data. Created from ATLAS.ti.
The organization had contracted an external vendor to build a strategic
long-term partnership for their PV database, which was their foremost selection
and implementation strategy. On detailed analysis, three main themes and nine
key strategies emerged as shown in Table 1 below. The references coded refers
to the number of times the data references were coded to the strategies.
Theme 1: Selection and Implementation Strategies
Automation solution selection and implementation strategies were some of
the key themes that emerged from the interview data. Initial analysis of the
word cloud created by ATLAS.ti included vendor, system, project, time,
implementation, automation, and communication as the keywords. The word cloud
reflected the strategies identified in the analysis of data. The leaders of the
PV organization decided to strategically engage with an external vendor to
supply the automation solution and implement the same. This organization
adopted the leader strategy for automation. The following five key strategies
emerged for selection and implementation strategies from the interview data:
Internal drivers like vision, objectives, timelines, cost, and
compliance. All participants identified internal drivers as one of the
important strategies to guide the selection and implementation of automation
solutions for AEs case processing. The participants identified multiple
internal drivers or factors like organization vision and objectives for
automation, tight timelines, cost, and competing priorities while ensuring
regulatory compliance. The PV organization created a long-term vision to
leverage automation as much as possible to build efficiencies within PV
business operations.
Ensure the solution is fit for purpose. All participants unanimously
identified the fit of the automation solution to effectively perform as
expected and match the tasks and constraints as a key strategy. Certain tasks
which were performed manually were now replaced by a tactical automated
solution. Therefore, the solution must be a fit for the tasks that needed to be
performed, only more efficiently.
Strong project management with a defined plan, dedicated resources, and
stakeholders. The project team consisted of internal employees and external
vendor team members. To successfully execute the project, a strong project
management function was led by an internal temporarily contracted project
manager to track the project and manage stakeholder engagement. To ensure the
milestones and deliverables were met as defined in the project plan, a
structured project plan was built, and dedicated resources and stakeholders
were identified. All participants indicated strong project management and
leadership as a key strategy.
Strategic partnership with an external vendor. Since the automation
solution was sourced and implemented by an external vendor, the PV systems
managers decided to strike a strategic partnership with the vendor selected
after a rigorous vetting process. Participants shared the realization that
being a small pharmaceutical company, they did not have the relevant expertise
in-house. Therefore, PV management decided to build a strategic partnership
with an external vendor who can source the automation solution and implement
it. In addition, the participants stressed partnering with a vendor with a
vision, who was invested in the technology and the solution for the long term.
Participants summarized that a good partnership ensured the vendor was engaged
and acted on any issue escalations.
Defined metrics to measure the effectiveness of the solution and the
project. The PV leaders built multiple metrics to measure the effectiveness of
both the automation solution and the execution of the project. To ensure the
solution was fit for purpose, before and after metrics measuring the time and
resources were built. All participants indicated that the metrics measured the
amount of time taken to create and process AEs before and after the automation
solution was implemented. To ensure the project matched the internal drivers,
the project was closely monitored to ensure all the milestones were achieved.
Documents provided by the participants showed automation, business
process improvements, elimination of nonvalue-added activities, and metrics
were the key internal strategies of focus. The documents also indicated strong
leadership, open communication, and collaboration as key strategies for
successfully implementing automation solutions for AEs case processing.
Technical limitations like multi-tenant cloud implementation and adopting ISP
configuration were included as internal drivers. The document review revealed
the timeline as an internal driver, as mentioned by all the participants in
their interviews.
The findings matched the academic literature review. PV managers must create a vision and project new technology as a product
designed to create, attract, and satisfy demand (Gherasim, 2011). Padgett, Gossett, Mayer, Chien,
and Turner (2017) found that as an organization developed a culture of safety,
the staff gained skills required to handle dynamic patient conditions within
the facility, reducing their preventable medical errors and dependence on
external healthcare and emergency medical services. Though many companies
automate many steps in the PV process, plenty of opportunities exist to make PV
agile and efficient (Ghosh et al., 2020). Organization
leaders have realized that proactive external collaboration is beneficial for
the creation of new products and solutions (Di Fiore et al.,
2017). Therefore, the PV leadership decided to partner with an external
vendor.
PV managers must ensure the technology
solutions are aligned with the business needs and led by business operations (Mishra et al., 2019). Managers must improve employeesÕ job
satisfaction and solution adoption by implementing IT solutions that fit the
tasks and employeesÕ long-term professional needs (Wang et al.,
2020). Internal drivers of a company, specifically, organizational
culture and environmental issues must be considered to leverage the advantages
of data analytics (Hawley,
2016). Automation can support the human workforce in managing the
increasing AE volume, complexity, reporting timelines, and increasing
efficiency, consistency, and compliance (Routray et al., 2020).
Companies typically measure the benefits of automation in terms of quality,
compliance, and efficiency (Ghosh
et al., 2020).
The TTF model links the task requirements, individual abilities, and the
functionality of technology (Goodhue
& Thompson, 1995). TTF theory focuses
on the application and the general reliance on technologies and does not
recommend any task or technology pairings that could produce a strong effect (Howard & Rose, 2019). The participants explained that the manual redundant tasks were
identified first and then the automation solution that matched the tasks and
the constraints were selected to ensure that the automation initiative was a
success. Therefore, the TTF conceptual framework provided the correct lens for
exploring strategies used by the PV systems managers to successfully automate
AEs case processing.
Theme 2: Business Operational Model Changes
The second key theme that emerged from the data was business operational
model changes and referred to the outcome of implementing the automation
solution. Initial analysis of the word cloud created by ATLAS.ti included AEs
also called cases, system, automation, change, implementation, and
automatically as the keywords. Business
operational model changes theme included the following two strategies:
Simplified, standardized, and efficient business processes by
supplementing and reducing the operational workforce. All participants stated
that the introduction of the automation solution simplified and standardized
the business processes and assisted in building efficiencies, as intended.
Although reduction of the workforce was not the primary intention, the managers
were able to successfully supplement the manual, redundant tasks like double
data entry to free up and repurpose the workforce to focus on more value-added
tasks. The PV operations team could reduce the number of full-time employees.
Changes to organizational structure and job profiles. The introduction
of automation solutions led to changes in the way the AEs case processing
employees performed their jobs. Participants indicated that the AE case
processor now only has to read the data on the screen as opposed to having to
type or enter it manually. The mailbox that had to be monitored for new AEs
need not be monitored because the AEs were automatically created in the
database and the task was eliminated.
A review of the documents provided by the participants showed process
improvements and elimination of nonvalue-added activities as key objectives for
automation. One of the challenges that the PV organization targeted to resolve
was manual, time-consuming, and inefficient processes. Ever-increasing AE case
volume, derivative operational cost, and resources were the other key
challenges that the PV leadership decided to mitigate.
The findings for business operational model changes matched previous
studies in this regard. Stergiopoulos et
al. (2019) noted that all PV leaders believed implementing AI-based
solutions will decrease costs for PV operations including simplifying AE
detection and processing. Mishra et al. (2019) summarized that business
process simplification, standardization, and re-engineering are the critical
factors for a successful automation strategy. Routray et al. (2020) confirmed that human intervention and review of AE
seriousness will be required and that automation can augment human review by
increasing efficiencies and consistency, thereby enabling reporting compliance.
Beninger (2018) emphasized the new skillsets, which will define the roles of
the next generation of professionals who perform PV activities. Tomita (2019)
added that organizations must expect to supplement the human workforce with
expert systems.
The TTF model matches the tasks as the events occur with the ability of
a technology to address these events. TTF focuses on the application of
technology (Howard
& Rose, 2019). The results of this study
were in line with those of Wang et al.
(2020) and indicated that the automation technology implementation resulted in
business process re-engineering. The results also indicated that if the
automation solution fits the business processes to complete the tasks and
enables employees' fulfillment, then the managers can expect enhanced adoption
of the technologies from the employees and a favorable attitude towards their
jobs.
Theme 3: Communication and Training Strategies
The third key theme that emerged from the data was communication and
training strategies also included change management-related strategies. Initial
analysis of the word cloud created by ATLAS.ti included communication, vendor,
training, project, team, and management as the keywords. Effective communication and training
strategies played a key role in successful change management and adoption of
the innovative technology solution within the PV organization. Communication
and training strategies theme included the following two strategies:
Open communication, collaboration, and engagement
with stakeholders including end-users and the vendor. Considering the high
priority and ranking of the AE management automation project, the project team
maintained open communication and collaboration channels to ensure all the
relevant stakeholders stayed engaged throughout the implementation. All
participants indicated that communication was key and that introducing
automation was viewed as a welcome change for the AE processing operational
activities. The end-users were made an integral part of the project, which made
change management effortless. Managing the vendor using open communication and
collaboration was critical. Multiple touchpoints like steering committee and
core team meetings were built to ensure the information is flowing through the
organization and timely escalation and resolution of issues. Collaborating
externally with other companies to explore the opportunities for automation,
which can be practically implemented.
Training. Since the introduction of automation changed the way certain
business processes were managed, training was a critical aspect. The
participants noted that multiple cycles of training were provided to the
end-users and the impacted third-party call center vendor. The end-users were
engaged in the implementation project and were trained multiple times.
A review of the documents shared by the
participants revealed that open communication and collaboration were key to
setting up an optimum governance structure during implementation. Lack of
efficient collaboration tools was a key challenge in the initial stages of the
project. Considering varied stakeholders, both internal and external, and the
vendor implementation team located remotely added to the communication
challenges. The team used online collaboration tools like Google and Smart
Sheets to help track tasks and keep the teams aligned.
Findings regarding communication and training strategies matched
previous studies. Training and re-learning initiatives assist in preparing and
guiding the in-house staff for digital transformation (Mishra et al.,
2019). The human and technology relationship should also include user
training, interaction, and collaboration sub-goals to be effective (Oyekan et al., 2017). PV systems managers realized the importance
of communication and collaboration early during the implementation project and
ensured adequate measures were included to create open communication channels
assisting in timely escalations and change management. (Ghosh et
al. 2020) also recommended collaboration across the pharmaceutical
industry between regulators and companies to build a generic process flow to
fuel third-party innovations.
In the TTF model, (Goodhue
and Thompson, 1995) linked the technology solution with individual
performance. (Wang et al., 2020) used the user task
technology fit model to summarize that the technology solutions alter business
processes and existing work patterns leading to re-training and re-learning,
which could increase employeesÕ work-related stress. The study results showed that engaging the users early during the
technology implementation led to easier change management and enhanced adoption
of the solution and possibly job satisfaction since the solution was fit for
purpose.
Significance of the
Study
Applications to
Professional Practice
Processing of an AE is an expensive
resource-intensive process, which includes a high risk of errors and
operational inefficiencies (Ghosh et al.,
2020). A detailed review of the literature concluded
that innovative technology such as data mining, machine
learning, AI, and robotics could result in new operating models for PV (Beninger & Ibara, 2016; Lai,
2017), improve efficiencies and reduce PV operations costs (Karimi et al., 2015; Lu, 2009;
Schmider et al., 2018), better allocation of resources, and improve
patient outcomes (Lewis
& McCallum, 2019). In this doctoral study, we explored the
strategies that PV systems managers in the pharmaceutical industry use to
implement innovative technology solutions to automate AEs case processing (see
SystemÕs model in Fig 2)
The single case that we selected to study was the implementation of an
innovative technology solution to automate AE processing. The organization had
a larger vision to automate PV business operations and this project was a part
of that vision. Leaders and managers in the PV function decided to partner with
a vendor to source and implement the solution, having realized that the
organization lacked the necessary expertise on the technology. Multiple
internal drivers such as objectives, timelines, cost, and compliance shaped the
strategies the PV systems managers used to execute the project. Considering
this being their first automation solution, the team ensured that the solution
is fit for purpose, both task (functionality) and technology (architecture) perspectives.
Strong project leadership and steering committee were established for robust
governance and monitoring.
The managers established an open communication, collaboration, and
training model to engage with the relevant stakeholders across multiple functions
within the organization and the vendor. Measures were established to capture
metrics in terms of volume, time, and quality of the business AE processing
tasks before and after automation. Regular project governance and monitoring
measures ensured the automation solution was implemented on time. The metrics
defined the successful outcome of this implementation.
The results showed that implementing the automation solution resulted in
favorable changes to the PV business operational model. Business processes are
now more simplified, standardized, and efficient. The metrics revealed major
savings in terms of time and effort, which led to a reduction in the
operational workforce and better allocation of resources. The organization has
started reallocating the savings from manual labor towards more value-added
tasks. By successfully implementing the automation solution, the PV
organization managers have started defining a sustainable model for PV business
operations. Other pharmaceutical companies can use the strategies identified in
this study to realize the benefits of implementing innovative automation
technology solutions to build a resilient and sustainable PV business
operations organization. The themes
and strategies and internal processes are described in the following model as
an outcome of this study.
Implications for Social Change
The successful strategies identified in this study can be used by
organizations to adopt a digitized PV future. The study findings show a
positive outcome and realization of savings from PV business operations because
of strategically implementing and embedding automation. PV leaders can redirect
the savings from PV operations towards investing in the actual PV tasks like
benefit-risk assessments of products, thereby improving patient outcomes and
making the products more efficacious and safer for human use.
The challenges from the pharmaceutical industry's perspective include
the management of the high volume of AEs, globally diverse and changing
regulations, complex and evolving systems, and sparse PV expertise and talent (Price, 2018). Automation
technologies can detect, database, and report AEs quicker, and manage the high
volume of AEs, which can help in protecting patients from unnecessary harm. The
implications for positive social change include the identification of
strategies to assist in making pharmaceutical medicines safer for human
consumption. The savings from PV operations could also be used to help or
assist with community projects that could bring about social change. Companies
can also use the savings to offer scholarships to students pursuing courses and
majoring in PV, thereby contributing to increasing PV expertise and talent.
Processing of an AE is an expensive
resource-intensive process, which includes a high risk of errors and
operational inefficiencies (Ghosh et al.,
2020). As deducted in multiple previous research,
technology can accelerate efficiencies and can be used to identify and process
AEs faster and contribute to a reduction of costs (Beninger, 2018; Donzanti, 2018; Karimi et al., 2015; Kusch et al., 2020; Lewis & McCullum,
2019; Schmider et al., 2018; Stergiopoulos et al., 2019). Organizations must internalize digitalization
and incorporate it in the operations methodology and structure to select the
most suitable technological solutions and reap the maximum benefits (Buyukozkan & Gocer, 2018).
Many pharmaceutical organizations are experimenting, and some are implementing
automation technology solutions for AEs case processing.
Conclusions
This study focused on one such company whose PV organization managers
have implemented an automation solution for AEs case processing. The results of
the study are in line with previous research. By prudently executing automation
solution selection and implementation strategies and establishing communication
and training strategies, the organization is now benefitting from simplified
and efficient AEs case processing business operations. Multiple factors such as
internal drivers like cost and timelines, the functionality of the automation
solution, strong project leadership, stakeholder partnerships, and engagement,
including the size of the organization play an important role in shaping the
outcome of the digitalization initiative. With careful planning and execution,
intelligent AEs case processing automation initiatives can be a success and be
sustained over the long term.
Acknowledgment
We want to acknowledge the contribution that Dr. M. S. Hammoud (Walden
University) made in the development of the model for this study.
Conflict of Interest
No conflict of interest.
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Mythily Easwar a, *, Kenneth Gossett b,
Manish Shashi c
