Pre PRINT Version – Communications of the AIS
Institutionalizing Information Systems for Universal
Health Coverage in Primary Health Care and the Need
for New Forms of Institutional Work
Department of Informatics
University of Oslo
Department of Informatics
University of Oslo
Department of Informatics
University of Oslo
Today, many countries around the world focus on ensuring that all people can access health services of sufficient quality
without experiencing financial hardship (i.e., universal health coverage). To measure progress towards this goal,
countries need to build robust health information systems. Because countries need to root universal health coverage in
primary health care, they also needs to sensitively anchor health information systems that support universal health
coverage in existing routine health information systems. However, doing so involves significant challenges, which we
study via empirically analyzing an Indian state's effort to implement a universal health coverage health information
system in primary care. Using a theoretical lens informed by institutional theory, we seek to answer the question: “What
type of change do institutions need to undergo to use the new technologies and associated work processes that
universal health coverage entails?”. We identify the contradictions that emerge when new systems clash with existing
ones, and we discuss what implications such contradictions have in terms of system design, work processes, and
institutions. We contribute to the literature by explaining inherent complexities in universal health coverage health
information system design and implementation and providing system design guidelines.
Keywords: Universal Health Coverage, Health Information Systems, Primary Health Care, Institutional Work.
[Department statements, if appropriate, will be added by the editors. Teaching cases and panel reports will have a
statement, which is also added by the editors.]
[Note: this page has no footnotes.]
This manuscript underwent editorial review. It was received 06/26/2017 and was with the authors for 8 months for 5 revisions. The
Associate Editor chose to remain anonymous.
1 Institutionalizing UHC Health Information Systems within Primary
According to the World Health Organization (n.d.):
Universal health coverage (UHC) means that all people and communities can use the promotive,
preventive, curative, rehabilitative and palliative health services they need, of sufficient quality to
be effective, while also ensuring that the use of these services does not expose the user to
This definition entails three related objectives: equity, sufficient quality of service, and protection against
financial hardship. Achieving universal health coverage (UHC) represents an urgent global priority, and low-
and middle-income countries need to engage in measuring progress towards achieving it. Further, as Chan
(2007, p. 5), notes: data forms a key ingredient in measuring this progress:
Without these fundamental health data, we are working in the dark. We may also be shooting in
the dark. Without these data, we have no reliable way of knowing whether interventions are
working, and whether development aid is producing the desired health outcomes.
In the Global Health 2035 report, the Lancet Commission on Investing in Health put forth an ambitious
investment framework for transforming global health through UHC, which included building pathways to
provide access to services and financially protecting the poor. While various reports have documented
sound technical advice about achieving these goals, such as about designing health service packages and
financing systems (Bump et al., 2016), guidance on designing and implementing supporting health
information systems (HIS) has arguably attracted less focus.
The Institute for Health Metrics and Evaluation has published a composite indicator-based model to
measure progress towards the United Nation’s Sustainable Development Goals (SDG) and since turned its
attention to measure UHC progress (Maurice, 2016). Boerma, Eozenou, Evans, Kieny, and Wagstaff (2014,
p. 2) describe the UHC measurement challenge as follows:
The UHC monitoring framework focuses on simultaneous monitoring of coverage of population
with essential health services and with financial protection against catastrophic out-of-pocket
health payments, stratified by wealth quintile, place of residence and sex.
Today, few countries have a UHC monitoring framework, and data for measurement typically comes from
infrequent household and facility surveys that use standardized questions or rely on potentially unsound
estimates (Boerma, Victoria, & Abouzahr, 2018). The lack of data severely hinders financial measurement.
Thus, countries need to invest in strengthening routine facility HIS and regular health examination surveys,
which they can achieve only by institutionalizing UHC-HIS in primary healthcare, which, in turn, requires a
larger architectural, operational, and institutional integration. As Stigler, Macinko, Pettigrew, Kumar, and
van Weel (2016, p. 1811) argue, primary healthcare forms a necessary foundation for UHC:
Health systems development requires more than financing and human resource considerations.
Although essential, these components must be integrated into an overall framework for organizing
and delivering care…. Primary health care provides such a framework…. [It builds the backbone
of an effective health care system.
However, one cannot easily materialize the above design since UHC involve new and different work
practices compared to traditional primary healthcare with significant implications on the HIS. Sahay,
Sundararaman, and Mukherjee (2014) elaborate on these differences in noting that UHC needs:
1) An expanded basket of services (including non-communicable diseases (NCDs)), not just
primarily maternal and child health as with traditional HIS.
3) To ensure continuity of care, whereas traditional HIS provided care more incidentally and
4) To monitor the cost of care.
5) To allocate resources based on facility needs, not on uniform allocation models.
Such changes will entail collecting other types of information from different sources as the service coverage
expands. As such, [what/who?] will need to organize the way they manage information directly to support
continuous and episodic care and to reshape the demand-driven way they provide service to a planning-
In this paper, we focus on understanding how countries can ensure that these new practices take root in
the health system. We believe that we need to understand change as more than a reconfiguration of work
practices that one can achieve via installing new systems and training staff. On the contrary, we argue that
this entails more profound institutional changes and that, in making such changes, one needs to ask whether
the required supporting institutional structures for a UHC-HIS exist. For example, the HIS in the primary
healthcare settings in most low- and middle-income countries has historically relied on aggregated data
(e.g., on counts of “number of children born last month”). Technologies designed to enable upward reporting
rather than local action support these reporting needs. In contrast, UHC requires data about patients and
their individual encounters with the health system (e.g., date, time, and place they attend hospital). This
requires a radically different HIS that new institutions and technology support. For example, a new technical
solution could use biometrics to enable personal identification, which requires supporting institutions such
as personal and unique identification numbers and data-protection regulations. Based on this, we
investigate the following research question (RQ):
RQ: What type of change do institutions need to undergo to use the new technologies and
associated work processes that universal health coverage entails?
This paper proceeds as follows: in Section 2, we elaborate on our theoretical perspective that we use to
address this question. In Section 3, we present our research approach and, in Section 4, the empirical study.
The study describes an Indian state’s effort to implement a UHC-HIS in the primary healthcare sector, and
we analyze the challenges of this undertaking as indicating institutional tensions. Based on the analysis, in
Section 5, we suggest strategies for systems design and implementation that help [who] successfully
instutionalize a UHC-HIS in the primary healthcare sector.
2 A Theoretical Perspective to Understand Changing Institutions
We focus on understanding how new work practices will emerge and take root [where]. We chose an
institutional lens to better focus on the institutionalized and embedded practices at our case organization.
As a result, we obtain a frame to discuss whether one may need to dismantle or deinstitutionalize existing
institutions and how one could create (or re-institutionalize) new ones that could support the new practices
that UHC and UHC-HIS entail. Through an institutional analysis, we hope to uncover what it takes to
successfully implement UHC-HIS.
We build on existing research on the impact of information technology on institutions (Gawer & Phillips,
2013; Rajão & Hayes, 2009) and argue that we can attend to what users can do and what they actually do
with available technology to understand how information technology can contribute to dismantling
institutionalized practices. Information technology artefacts potentially afford or constrain different
possibilities of users’ actions, which depend on their goals (Majchrzak & Markus, 2013; Markus & Silver,
2008). In traditional HIS in the primary healthcare sector in low- and middle-income countries, the dominant
institutional norms concern data reporting from the local to the national levels and serve primarily
bureaucratic needs. These norms may conflict with the norms that the UHC-HIS inscribe and that need to
focus more on patients (not on bureaucracy) to improve their health and wellbeing. Such tensions between
the old and new norms can lead to different forms of user resistance (Currie, 2012) and, consequently, to
suboptimal data use. Understanding the possibilities of action that the UHC-HIS provides to its users can
help one to more insightfully analyze how the systems may contribute to deinstitutionalizing historically
embedded work and technical practices.
2.1 Institutions, Institutional Change, and the Role of Technology
Institutions involve assumptions, values, and norms that regulate human behavior (Berger & Luckmann,
1991), which influence how users implement and use information systems (Srivastava & Shainesh, 2015;
Srivastava, Teo, & Devaraj, 2016). [What] understands institutions has its foundations in conceptualizations
of human agency. North (1990, p. 97), for example, describes institutions as:
Humanly devised constraints that structure political, economic and social interaction. They consist
of both informal constraints (sanctions, taboos, customs, traditions, and codes of conduct) and
formal rules (constitutions, laws and property rights).
Jepperson’s (1991, pp. 143-145) describes institutions as the product (intentional or otherwise) of purposive
action, as “an organized, established procedure” that reflects a set of “standardized interaction sequences”.
Researchers have used this lens to develop institutional accounts to understand how existing institutions
influence work practices and vice versa and how these work practices affect whether or not [who/what]
uptakes information technologies or not (Orlikowski, 2000).
Creating new institutions necessarily involves replacing or breaking down existing ones, a process called
deinstitutionalization (Oliver, 1992). With a particular focus on cultural and political factors, Nicholson and
Sahay (2009) draw on this notion in a policy-based analysis in Costa Rica to analyze how introducing new
practices that contradict or cannot coexist with existing practices can help to deinstitutionalize those existing
practices and build the grounds to reinstitutionalize new ones. Accounts of deinstitutionalization have
typically not highlighted the key role that technology plays, something we emphasize in this paper. Different
users may see the same technology as providing them with varying possibilities of action, as shaping their
practices, and as influencing change in different ways. For example, community health workers may see an
organization’s introducing mobile phone work practices as allowing them to send their reports through SMS
and to give their work more visibility. (Mukherjee, 2017). In this way,.
Technology can impact institutionalization processes in other ways as well. The complexity and
interconnectedness of sector-wide health information infrastructure in itself generates a resistance to
change due to its pre-existing arrangements: “an installed base riddled with social (e.g., legal rights and
ownership) and technical (e.g., legacy systems and technical standards) interdependencies” (Sanner,
Manda, & Nielsen, 2014, p. 221). One can change existing institutions, social practices, and technology only
Various studies of HIS in low- and middle-income countries have adopted an institutional lens to highlight
the relation between HIS, users’ practices, and institutions and how may affect information use (Chilundo &
Aanestad, 2004; Kimaro & Sahay, 2007; Noir & Walsham, 2007). We build on this stream of work and further
contribute to it . This approach resembles the one that Braa, Hanseth, Heywood, Mohammed, and Shaw
(2007) followed in showing how a new “flexible standards” model could break down an existing institution
that involved reporting all locally collected data to the national government. Only a new flexible and user
friendly technology could enable this new institution: it allowed actors the freedom to include or exclude
different data elements for stakeholders at different levels. In this way,.
2.2 Strategies for Changing Institutions: Institutional Work
While much research has focused on studying how institutions influence practices, it has insufficiently
studied the reverse relation. Researchers have examined the role of actors and practices in affecting
institutional change either through focusing on the “institutional entrepreneur” (DiMaggio, 1988; Eisenstadt,
1980) or on deinstitutionalization process. Lawrence and Suddaby (2006) brought these various research
streams together with their notion of institutional work: the work that actors purposefully perform to create,
maintain, or disrupt institutions. This practice-oriented lens views institutional work as “intelligent, situated
institutional action” that actors who “may or may not achieve…[their] desired ends” and who “interact with
existing social and technological structures in unintended and unexpected ways” (p. #) perform. Lawrence
and Suddaby identify nine ways to build institutions: 1) advocacy (the mobilization of support), 2) defining
(create identity, rules, boundaries etc.), 3) vesting (allocation of property rights, confer rights), 4)
constructing identities, 5) changing normative associations (redefining the moral and cultural foundations
for practices), 6) constructing normative networks (inter-organizational sanctioning of practice), 7) mimicry
(leverage existing practices, rules, structures), 8) theorizing (naming new concepts and practices), and 9)
educating (providing skills and knowledge). Further, they identify six ways to maintain and reproduce
institutions: 1) enabling work (create rules that facilitate and support the institution), 2) policing (ensuring
compliance), 3) deterrence (establish barriers to change), 4) valorizing and demonizing (evaluations of
moral status), 5) mythologizing (emphasize normative underpinnings), and 6) embedding and routinizing
(inscribing into practices). Further still, they identify three ways to disrupt institutions: 1) disconnecting
sanctions and rewards (from certain practices, such as through legal changes), 2) disassociating moral
foundations (redefining appropriateness), and 3) undermining assumptions and beliefs. While the authors
do not claim to exhaustively list all possible types of institutional work, their framework shows that an actor
can perform many activities to create, maintain, or change institutions. In Table 1 below, we briefly
summarize these three different categories of institutional work.
Table 1. Different Categories of Institutional Work (Lawrence & Suddaby, 2006)
Work that focuses on creating new
Forms of institutional work:
advocacy, defining, vesting,
constructing identities, changing
normative associations, constructing
normative networks, mimicry,
theorizing, and educating.
Supporting, repairing, or recreating
the social mechanisms that ensure
actors comply with institutions.
Forms of institutional work:
enabling work, policing, deterring,
valorizing and demonizing,
mythologizing, and embedding and
Attacking or undermining the
mechanisms that lead members to
comply with institutions.
Forms of institutional work:
Disassociating moral foundations, and
undermining assumptions and beliefs.
Researchers have used this framework to unpack how the design of HIS relates to underlying changes in
healthcare models (Thorseng & Grisot, 2017; Vikkelsø, 2010). In the context of UHC, we ned to ask which
institutions actors need to maintain, disrupt, or create and how (through which strategy) they can do so. At
the same time, we critically discuss the role of contradictions that emerge from different and potentially
conflicting institutional arrangements (new and old) and the transformational power that lies in them (Seo &
Creed, 2002). In summary, we focus on:
1) Understanding the institutional nature of the existing and new practices around the UHC-HIS,
the institutional work, and the ensuing contradictions and tensions the new practices entail when
they clash with the traditionally existing practices and systems.
2) Analyzing these institutional contradictions as opportunities for change and deriving insights on
how actors can effectively leverage this potential on the ground.
3) Deriving insights on the necessary technological material features (design guidelines) that
support the institutional work that actors need to undertake to redesign institutions to create an
3 The Empirical Approach
3.1 Case Study Context
3.1.1 Background on Research Project
We conducted a case study in a state in North India. While UHC represents a national priority in India,
different states have shown unequal progress in pursuing the UHC reform agenda, which includes
revamping their HIS (Patel et al., 2015; Devadasan, Ghosh, Nandraj, & Sundararaman, 2014). However,
the state we examined had initiated at least two alternative models (including the one we report on) for
implementing UHC-HIS. We began our case study by focusing on understanding the experience that health
facilities across various districts in the state had with the pilot UHC-HIS implementation, which had ran for
about nine months and had delivered less than expected results. Specifically, we focused on incorporating
the lessons from the first unsuccessful pilot (reported here) into a new attempt to design and anchor a UHC-
HIS in this setting. This new project, which adopted a UHC framework, focused on designing, developing,
and implementing a patient-centric information system for the healthcare facilities, testing its effectiveness,
and allowing the state to evaluate and scale it up if it found the system useful.
The case study forms part of a larger project (called “Building patient-centric systems for primary healthcare
in resource-constrained setting) that we—two researchers from a university in Norway and one researcher
from a public health university in Norway—undertook with various other stakeholders from 2016 to 2018.
This project focused on. The other stakeholders included two informatics students (one at each university
in Norway and India) who pursued master’s theses on topics relevant to the project (one studied the
evolution of requirements for such a patient-centric system, and the other studied the role of standards and
how to align system design with national-level standards on nomenclature and formats) and a medical
doctor in India who studied the effectiveness of patient-based systems more generally in India and how the
new system impacted patients’ health. In addition to the two research institutions, a third entity, an Indian
NGO, helped to develop the technical systems. The first author of this paper has worked in the public HIS
context in India since 2000 and, more specifically, in the state we examined since 2008. Thus, he has come
to deeply understand the research context, , the state under study, and HIS problems in India more
generally, such as its deeply embedded existing institutional norms and assumptions.
3.1.2 Existing Structures, Systems and Work Practices in the Research Setting
The pilot site (i.e., the state) comprised one rural and one semi-urban distinct. In our project, we focused on
one primary healthcare facility in each district and the five or six outreach centers (called subcenters) that
fell under the primary healthcare facility’s jurisdiction. Each subcenter had one or two field nurses (called
auxiliary nurse midwifes (ANMs)) that provided outreach and clinic-based care (primarily related to maternal
and child health) to three to five villages. A primary healthcare facility, which a medical doctor who provides
outpatient services and limited support staff (e.g., a lab technician) operate, represented the first call for
patients to receive medical care.
The healthcare facilities had preexisting HIS in place that staff members used to, for example, report to
national-level organizations and track pregnant mothers and children for immunization (we counted nine
such reporting systems). The ANMs had the responsibility to provide the data for these HIS. Typically, they
recorded data in their field diaries at the point of care and then transferred it to their primary registers
(typically, each subcenter had about 20 registers that related to antenatal care, immunization, TB, Malaria,
and others) where they entered each patient’s name and the date and details of the service encounter. The
ANMs typically entered information about individuals in multiple registers and also multiple times in the same
On a monthly basis, [who] extracted the required data from the respective registers and transferred it to
various reporting forms that [who] sent to the primary healthcare facility. In the facility, staff members entered
the data into a computer. As such, the new system for our project had to engage with (and hopefully replace)
the cumbersome preexisting systems that featured significant redundancy and involved significant manual
processing (in the registers) but also introduce new informational requirements associated with UHC-HIS
(such as population coverage, non-communicable diseases, referral linkages, etc.).
3.2 Data Collection
. While we draw on the data from both projects to inform our analysis, the case we present primarily draws
from the first one.
3.2.1 Third Party Vendor’s UHC-HIS Project
We began collecting data for this project with a state-level review meeting that the state principal secretary
of health convened in April, 2016. At the meeting, the vendor demonstrated the system under development
and discussed the issues it faced in the presence of various state and district level staff. In this meeting, in
addition to seeing the demonstration, [who] held discussions with the principal secretary, the state project
coordinator, and the vendor. Not satisfied with the project’s progress, the secretary requested the first author
(who had worked in the state for many years) to visit the empirical site to assess the issues and give her a
report. Subsequently, the first author first visited the primary healthcare clinic and then two subcenters under
it over two days. At the primary care clinic, the author conducted three interviews: two with the medical
officers and one with the pharmacist who maintained the computer system. Additionally, the author sat in
the doctor’s cabin and observed his interactions with patients and how he used the pilot UHC-HIS to record
the transaction details. Following the visit, we wrote an assessment report and presented it to the principal
3.2.2 Our Own Projects
As we mention above, we began a research project with two universities and various stakeholders in 2016.
Since our research project began, we collected data through two primary modes. First, the first author made
five trips to the research site to attend workshops and have discussions with health staff at the clinics. During
this process, he conducted at least six interviews with the staff of the clinics and many rounds of formal and
informal meetings with other researchers from the Indian health university. Second, we established a
research team at the project site that included a medical doctor, a data-entry operator, and some support
staff. This team.
Importantly, we set up and used a living lab in the clinic site to collect data and enable system design in
context. This lab enabled the research team, in collaboration with the clinical health staff, to jointly discuss
current systems, work practices, information needs and gaps, and other issues to appropriately design the
new UHC-HIS. The research team could also study the registers in use, seek clarifications on why staff
collected certain data, and observe everyday interactions between patients and doctors.
To date, [who] has hosted at least four workshops to discuss larger research issues and to review project
progress. In the first workshop, we invited various national- and state-level stakeholders who presented
varying experiences of similar patient-centric systems in the country. By sharing these experiences, they
helped [who] understand the strengths and weaknesses of existing systems and provided design inputs for
the system we had begun to develop. In the second workshop, we directly interacted with health staff to
understand design considerations. We studied the different registers and input and output formats, and the
health staff described the kind of changes and improvements they wanted in the new system. In the third
workshop in Oslo, four researchers from India in addition to the Norwegian team and other stakeholders
such as the directorate of e-health shed light on how Norway implemented patient-centric systems, which
helped the research team to identify areas of learning, such as the key role that regulation plays in protecting
patients’ privacy. In the fourth workshop held in India in 2018, we presented the systems we had developed
to date and solicited feedback from various participants for further improvements.
As we state above, two Norwegian master’s students in informatics also worked on this project. The first
student diligently recorded the evolution of requirements that resulted from emerging discussions we had
with health staff and the NGO responsible for building the system. Sometimes, particular design choices did
not work, and, through discussions, we identified new requirements, which led to changes in the master
requirements document. The other student, who worked on standards (especially about nomenclature and
formats), produced a wealth of data for his thesis work that became a common shared data resource for
analysis. Further, one PhD student from the Indian side worked on the project and studied the impacts of
the ICT intervention.
In addition to these direct data-collection activities, the research project also included designing, developing,
and implementing the UHC-HIS and training healthcare staff. In the process of building different versions of
the system prototypes and training, we received much feedback that became important sources of data for
the project. These different activities helped generate insights into the institutional challenges of reforming
the old HIS and introducing a new UHC-HIS.
All stakeholders documented the data in the form of interview notes, minutes for meetings, project review
reports, and PowerPoint presentations. Additionally, we compiled informal messages over phone and email
where relevant and often shared and discussed them through face-to-face meetings. We made this data
available to the research team using Google drive, which became the data repository for the project. Table
2 summarizes the different data we collected.
Table 2. Summary of Data Sources
Means of data collection
At project site of third party vendor
At research project site
Five interviews: two with medical officers
and three with field nurses. All conducted
in respective clinics.
Six formal interviews including two with
medical officers and four with field nurses
and clinic staff.
One at the office of state principal
Multiple meetings with research team
during the course of the workshops held.
Four workshops: three in India and one in
Developed assessment report.
Two master’s students and one PhD
One at principal secretary health office and
one at primary health care clinic.
At least three formal system demos
Carried out in the primary healthcare clinic
and subcenter of work practices and how
[who] used registers and reports.
We extensively observed HIS-related
activities and interactions between health
staff and patients.
3.3 Data Analysis
To analyze the overall case, we draw on the learning and insights we developed as we designed and
developed the UHC-HIS as we conducted the research project. As a first-level analysis, we compiled data
into various progress reports at different stages of the project and shared it with others. For example, in the
third workshop in Norway, participants intensively discussed a report compiled on the “landscape of patient-
centric systems in India” based on data we collected during the first workshop in India. We prepared and
discussed a preparation based on this report along with other presentations from the Norwegian
participants. We made all various policy documents (such as privacy regulations) available in the common
As a second-level analysis, based on studying different documents and reports, we identified and discussed
themes to help link the themes to the theoretical concepts that we drew primarily from institutional theory.
We contextualized these identified themes and concepts in the broader historical understanding of the state
health system, which led to our developing the case study description.
The research themes identified through the conceptual analysis focused on the challenges that the different
healthcare staff we interacted with reported. We grouped these challenges into five categories: 1) increased
work burden for health staff, 2) the new UHC-HIS added little value, 3) an increase in UHC-HIS complexity
due to the need to both combine individual and aggregate data, 4) extreme technical and institutional
contradictions between the old and the new systems, and 5) severe capacity and resource constraints in
effectively working with the new systems. We then used these themes as focal points to develop an
institutional-inspired analysis to identify the contradictions that UHC-HIS encounter. In Table 3, we provide
some examples that show we inductively identified the themes.
Table 3. Inductive Identification of Themes
Sample evidence to generate this theme
Increased work burden for the health
Health staff said that, with the new system, they now needed to spend
nearly 60 percent of their work time on data-management activities—much
more than before.
The new UHC-HIS added little value.
We saw that the system did not strengthen their local care practices, such
as being able to electronically synchronize data from their tablets to the
primary healthcare facility system to build the referral system.
Extreme technical and institutional
contradictions between the old and the
Technical contradiction: in the clinic, we saw a nurse trying to log in
unsuccessfully into the internet. The system we designed relied 100 percent
on the Internet.
Institutional contradiction: the ANMs now had to screen all people over 35
years for conditions of hypertension, diabetes, oral cancer, and others,
which represented new tasks as compared to her earlier focus on
reproductive and child healthcare.
An increase in UHC-HIS complexity
due to the need to combine individual
and aggregate data.
We saw that [who] needed to collect a lot of new information from diverse
sources, which heightened the complexity of the HIS.
Severe capacity and resource
The same ANM who was already overburdened with work now had a
significant amount of additional work through the UHC without more
resources to help.
4 The Case: Indian State's Effort to Implement UHC-HIS
From initially reading the relevant literature on UHC and having discussions with researchers and the state’s
administration, we realized that the requirements of the UHC-HIS fundamentally differ from existing HIS for
the primary healthcare sector. Changing from a HIS to UHC-HIS involves a radical shift from an aggregate
routine reporting system to what resembles a community-based, electronic medical record that focuses on
individuals and tracking them continuously over the care cycle. While the traditional system focused on
routinely reporting aggregate maternal and child health data, under UHC, ANMs also had to screen the
entire population in their catchment area for eight additional conditions (diabetes, hypertension, anaemia,
oral cancer, etc.) and maintain and share this information electronically. In the UHC-HIS pilot, ANMs
received a tablet to register this information in and synchronize with the facility’s database, which stored the
information. With this tablet, the ANMs also had to electronically refer cases to the primary healthcare
doctor’s system, which further linked with the district hospital. Both hospitals and primary healthcare facilities
also had to electronically back-refer patients after a consultation to ANMs for follow-up home-based care.
To actually comprehensively screen an entire population necessarily took time, and, in the meanwhile, one
could only cover a certain number of people. As such, it would take time to register all potential patients in
the new system, which would result in the need to maintain a dual set of work processes in the clinic. In a
visit to one of the primary healthcare facilities, we found the staff there had created two categories of
patients: “UHC group” and “non-UHC group”. The former included those patients that the ANMs had already
screened and the rest that the ANMs had not. Only 10 percent of the daily outpatients (of total 60) were in
the “UHC group”. In terms of the information flow, we saw that a patient who visited the primary healthcare
facility would first go to the pharmacist who maintained the computer system and showed their health card,
which included an identification number. A UHC-HIS assumes that the primary healthcare facility computer
has a patient’s record prior to the patient’s visit based on the rationale that, after screening all patients in an
area, the ANMs electronically register the information in a tablet that constantly synchronizes with the
primary healthcare system. However, we found that this information did not exist in all cases, and, as a
result, the pharmacist had to enter the registration details.
Further, the infrastructural constraints that challenged the UHC-HIS’s usability in practice impeded the way
it should have worked. Once the pharmacist registered a patient’s case record, it appeared on the doctor’s
screen for an outpatient consultation. But, due to the poor Internet, the doctor required many minutes to log
on to the system. Filling the case record in the system while examining the patient could take about 10
minutes, which led a frustrated patient to say: “Doctor, why don’t you do your personal work on the computer
later and first deal with me?”. In the case of electricity failures, the doctor would note case details on paper;
however, due to long power outages and the continuous stream of patients, they seldom had time to enter
these details into the system afterwards. Over time, this practice contributed to a growing number of
unrecorded cases. After A consultation, the doctor could not take a printout due to a lack of printing paper
and so noted everything on paper, gave it to the patient, and also entered the same details in a local register.
Additionally, the patient showed the slip to the pharmacist who maintained a similar register of outpatient
cases for statistical reporting. When asked if work had become simpler, the doctor replied: “No, it has
become a torture”. Further, in the case that the primary healthcare system did have information about a
patient, the system could not automatically synchronize data with the ANMs’ tablets. As such, only the
particular doctor could access the record via that doctor’s desktop computer. To take this data to the tablet,
the patient needed to show the outpatient slip to the ANMs, but patients rarely did so, which contributed to
a rising number of incomplete and unsynchronized records and undermined continuity of care (i.e.,
undermined the ANMs’ ability to follow up on patients that needed it).
While UHC focuses on strengthening continuity of care, we found that the doctor did not use the UHC-HIS
to view patients’ history. As for why, the doctor reported that [he/she] found the search function cumbersome
since it required [him/her] to search record rather than allowing [him/her] to view aggregated patient profiles.
Further, patients’ records did not normally contain historical data related to drugs because primary
healthcare facility doctor had the mandate to prescribe only certain medicines from an approved medicine
list. If unavailable or if the doctor wanted to prescribe something not on this list, they would write it on a slip,
and not in the computer, to escape possible reprimand for not following the norms. As a result, the doctor
had a skewed perception about the system’s utility in terms of continuity of care.
The system did also not stimulate or support an intended shift to a population-oriented and preventive-
planning practice. For example, the doctor could not see summarized outputs (by graphs and charts) that
showed, for example, the total number of hypertensive cases by village. Similarly, the system could not
generate referral linkages, so the district hospital would start a new record for every new patient even though
they may come through the primary healthcare that already had a record for the patient’s medical history.
We found that the doctor did not use the readily available functionality in the UHC-HIS to schedule follow-
up visits since the doctor believed it was the patients’ responsibility to come and not theirs to follow up.
In one subcenter, we met the two ANMs responsible for the UHC-HIS who regarded themselves as
competent in using tablets. One ANM’s tablet had not functioned for many months and had not been fixed
despite her multiple requests. As a result, she made entries on paper to later enter into the tablet when
fixed. Both ANMs struggled with bad network connections, and, in the two hours that we observed them,
could not log in despite multiple attempts. They also reported that they found it difficult to use the tablet
outdoors due to sun glare. As a result, they did their outdoor work on paper and later when indoors they
entered the data into the tablet, which duplicated their work. After initially screening the patients on eight
UHC conditions, the ANMs did not update their base records until a later time due to their high workload.
As a result, the records often became outdated.
ANMs reported a significant increase in their workload with the advent of the UHC-HIS, which required them
to spend about 60 percent of their time on data-related activities. They entered data in multiple places such
as primary registers, the health management information system for aggregate reporting, and the mother
and child tracking system for tracking pregnant mothers and children by name, which another system (called
RCH +) had recently replaced and included about 100 extra entries. The UHC-HIS was the latest addition
to their workload, and they still had to continue to use the earlier systems. They first noted most work on
paper and then entered it into the tablet. Overall, doctors and ANMs expressed frustration because they
obtain extra value but rather additional work from the UHC-HIS.
The case study illustrates both challenges that [who] typically face when working with institutions and
information infrastructures in a primary healthcare context in a low- and middle-income country. These
generic challenges include multiple overlapping systems and practices that contribute to double reporting
and fragmentation both technically and institutionally. Specific challenges relate to technical infrastructure
(e.g., Internet, electricity, technical support) that constrain system use and data-sharing across unevenly
and poorly resourced contexts. In this section, we analyze these challenges using the three categories of
institutional work (i.e., creating, maintaining, and disrupting) that Lawrence and Suddaby (2006) suggest.
Further, we discuss the institutional contradictions that the new requirements of a UHC-HIS cause and how
[who] can positively leverage them for change.
5.1 Creating Institutions
Lawrence and Suddaby (2006) categorize institutional work involved in creating institutions into three
subsets: 1) advocacy, defining, and vesting represents overt political work where actors define access to
material resources based on rules, property rights, and boundaries (e.g., how interest organizations lobby
for resources or new legislations); 2) constructing identities, changing normative associations, and
constructing normative networks represents work towards reconfiguring belief systems (e.g., developing
new professions and creating private-sector approaches in interventions in the public sector); and 3)
mimicry, theorizing, and educating represent alterations of abstract categorizations (e.g., associating new
practices with existing practices and establishing common concepts).
The UHC model that the state implemented implied that ANM and doctors had to change their work
practices. For ANMs, they needed to acquire new forms of knowledge (e.g., screening for diabetes and oral
cancer) when previously they had primarily dealt only with pregnancies and immunizations. Further, they
had to refer at-risk patients to the primary healthcare facility doctor for consultation. The nurses typically did
not have to refer such patients previously since the patients themselves initiated the referrals. The ANMs
also had to receive “back-referrals” (follow up with patients after consultation from the primary healthcare
facility at home). The UHC model also placed new expectations on doctors related to continuity of care. The
model assumed that the doctor would establish a longitudinal relationship with the patient in a way that
involved using both the functionality for reviewing patients’ history data and for scheduling future
appointments with them. These work tasks represent novel institutions since the doctors were not used to
referring to written history or to scheduling patient visits.
UHC requires ANM and doctors to perform institutional work to reorient their identity related to continuity of
care. They needed to learn to see themselves as having the responsibility to follow up with patients over
time through reviewing history, scheduling future appointments, and handling referrals. [Who?] also needs
to perform institutional work to help ANM in providing an expanded basket of services in terms of identity
and to educate them so they can establish the new practices.
5.2 Maintaining Institutions
Lawrence and Suddaby (2006) argue that few institutions have the strength to operate without maintenance,
and, to ensure social compliance, [who] must support, repair, and recreate [what?]. They categorize
institutional work involved in maintaining institutions into two subsets: 1) enabling work, policing, and
deterring focus on ensuring adherence to rule systems (e.g., using sanctions and incentives to ensure
compliance) and 2) valorizing and demonizing, mythologizing, and embedding and routinizing focus on
reproducing existing norms and belief systems (e.g., public displays of normative foundations and
embedded routines and practices).
While the UHC model introduced new ways to work, many of the existing work practices prevailed. Due to
sun glare and the tablets’ limited connectivity, ANMs added the new UHC-related information-gathering
activities to the already institutionalized paper-based practices. For some of the primary healthcare doctors,
they had used computers to enter details of patient encounters in real time for the first time. However,
because severe limitations in power supply and Internet connectivity made doing so difficult, the doctors
reverted back to a known institutionalized practice: maintaining local, paper-based documentation. Also,
other institutional conditions such as the limitations of the approved drug list and absence of printing paper
meant that they often did not use the system and, when they did, also entered the details on paper. As a
result, their workload significant increased; instead of a paperless system, the reverse occurred: doctors
generated more paper, such as through the local register they had to maintain to record out-patient
In reverting back to their paper-based practices, the ANMs and the doctors reproduced and extended them
and, thus, compensated for the weak infrastructure.
5.3 Disrupting Institutions
Lawrence and Suddaby (2006) also describe activities. They describe this work as disconnecting sanctions,
disassociating moral foundations, and undermining existing assumptions and beliefs (e.g., non-state actors’
Introducing UHC requires disruptive work related to the institutionalized practices that the ANM and doctors
followed and to the way in which patients understand their responsibility for own health and care. First, the
ANMs largely catered to the population who came to them either in their facility or during their field visits.
However, UHC meant they had to screen the entire population in their homes, which took time and required
travel support and ubiquitous access to infrastructure. Second, and in addition to the shift to a population-
oriented practice, preventive planning and continuity of care form UHC’s core, which differs from episodic
care where patients themselves have a responsibility to go see healthcare practitioners. In our case, doctors
refused to specify repeated visits through the system because they believed that the responsibility to return
lied with the patients. Third, the existing and deeply rooted reporting regime enabled upward reporting rather
than reporting between care givers to enable local action.
To change the institutionalized practices that we describe, [who?] could focus on undermining the existing
assumptions and beliefs of demand-driven and episodic care, which includes enhancing patients’ role in
taking care of their own health. [Who?] could also change the deep-rooted upward-reporting regime by
changing existing incentives and sanctions related to reporting and information use.
5.4 Institutional Contradictions
In the analysis above, we focus on how introducing the UHC model led to different kinds of institutional work
and how it would require further institutional work to. Motivated by the extreme challenges that different
healthcare staff we interacted with experienced in dealing with the new and old systems, we now elaborate
on and analyze these challenges as contradictions emerging from different and potentially conflicting
institutional arrangements. In Section 6, we return to these contradictions and discuss how one can use
them as opportunities for institutional work and change. First, the technological infrastructure did not support
the new responsibilities that the ANMs and doctors had to contend with. For example, the tablet that ANMs
had to use promised mobility but various practical challenges (e.g., charging, sun glare, and the demand
for an online connection) undermined its use in practice. Similarly, the absence of printing paper and limited
electricity and connectivity undermined doctors’ work. Second, and as a consequence of the infrastructure
challenges, the new system became just another system that often overlapped with and duplicated data
that already existed on paper. As a result, the ANMs’ workload significantly increased without appropriately
adding value in terms of supporting their everyday work with more granular information on people, diseases,
and costs over time. Because the UHC system became just yet another reporting system and did not
adequately consider the linkages between systems, significant contradictions arose between the expected
and provided value for its different users. Third, and again related to the infrastructure, since it ignored actual
conditions in the design phase, the system (e.g., the ANMs’ tablets and the medical records the primary
healthcare doctors used) did not become the expected tools. While the UHC system focused on providing
connectivity between the ANMs’ tablets and the primary healthcare doctors’ computers, in practice, the
design, infrastructure conditions, and work practices made the different units act in a standalone manner.
Fourth, and again related to the inadequacies of the technical system, the ANMs did not meet their new
responsibility to follow up on back-referred patients. The institutionalization of these new practices could not
happen without concurrent support from the technology, which required two-way information
synchronization about patients’ trajectory. Fifth, while the UHC-HIS had a readily available functionality to
schedule follow-up visits, doctors did not use it since they believed the patients themselves had the
responsibility to come. Patients themselves also lacked any expectation that doctors would follow up with
As the case study and its analysis reveal, the new UHC-HIS suffered many difficulties and contradictions.
At first sight, we could conclude that these contradictions contributed to the system’s overall failure.
However, institutional theory notes that these contradictions need not always be negative because they may
carry in them the potential for change. In this section, we discuss possible approaches to leverage their
potential through “judicious design”.
6.1 Design Guidelines based on Institutional Contradictions and Emerging
One can develop design guidelines or principles to transform descriptive case studies into a more normative
design theory (Walls, Widmeyer, & El Sawy, 1992; Markus, Majchrzak, & Gasser, 2002). (e.g., Miller,
Cafazzo, & Seto, 2014; Sultan, Kuluski, McIsaac, Cafazzo, & Seto, 2018) and IS research in particular (e.g.,
Aanestad & Jensen, 2011; Nguyen, Nielsen, & Braa, 2016) has used it. In this paper, we do not develop a
complete design theory for UHC-HIS. Our design guidelines are socio-technical and not limited to describing
user requirements and system features or to giving guidance in system-development processes. Rather,
they give broad guidance on where [who] needs to focus [whose?] design efforts to support system
designers but also other actors involved in the institutional work needed to establish a well-functioning UHC-
When the existing and new institutions meet, contradictions will inherently arise. First, while UHC requires
health workers to put more time into care, it also enhances their data-related work. Second, the work (care
and data related) demand a working infrastructure that may not yet exist adequately in practice. And third,
UHC puts new and demanding responsibilities on both doctors and patients that historically did not exist.
However, these contradictions also create opportunities for change. First, [who] has an opportunity to revise
and rationalize what data gets collected and for whom. Second, [who] has the opportunity to better accept
the integrating systems due to the increasing burden of data-related work. Third, doctors and patients have
an opportunity to build awareness about their responsibilities. Fourth, [who] has an opportunity to recognize
the acute need for a more appropriate infrastructure that can assist healthcare workers in their work.
Implementing UHC-HIS entails new forms of institutional work. This work should necessarily seek to
maintain and add value to established work practices and support new ones. One cannot implement UHC-
HIS in a void, and one should design it to leverage what already exists in the primary healthcare system
(e.g., institutionalized practices for collecting data). We observed that the institutionalized data-collection
practices salvaged the care the ANMs and doctors provided from a complete breakdown in the face of an
insufficient system. However, [who] needs to disrupt and challenge these institutions in that they allow data
collection for only upward reporting. In deliberately redesigning institutions, one needs to address the
rationale and emphasize the value of information to strengthen care rather than control and to design
systems that enable work and support more efficient care practices.
We argue that effectively introducing a UHC-HIS requires four new forms of institutional work that also
leverage the potential of the contradictions that arise when existing and new institutions meet. First, the
UHC-HIS needs to strengthen ANMs’ care practices, such as through training in new knowledge domains
(e.g., dealing with non-communicable diseases). Second, it requires work practices and supporting
infrastructure that connect patients and information (e.g., referrals between outreach and primary healthcare
facilities). Third, to expand ANMs’ capacity to reach out to the entire population, they need more travel
support and better infrastructure, such as Internet coverage. Fourth,(see also Table 4 below).
UHC requires the delegitimization of some current institutions and the creation of new and redefined ones.
For example, it requires aggregate systems for upward reporting and new information for patient-based
care. In terms of Oliver’s (1992) different organizational responses to institutional change, . When primary
healthcare and UHC-HIS come together, inconsistencies between institutional expectations and internal
objectives related to efficiency or autonomy emerge, which require organizations to find compromises in
building new and redefining existing institutions. The different stakeholders involved (e.g., health ministry,
ministry for civil registration and vital statistics, donors, and software developers) need to come together to
discuss the various contradiction and opportunities that arise and identify the optimal compromised
approach to meet needs of both the primary healthcare and UHC-HIS.
6.2 6.2 Judicious Design of HIS
The term judicious design (Mukherjee, Aanestad, & Sahay, 2012) reflects an approach that does not seek
to obliterate the past to create something new but to cultivate what exists, the installed base, to achieve the
new in an incremental manner. This design approach reflects the principle of “airplanes don’t fly, airlines
do”, which emphasizes the interconnected nature of the technical and social domains and the need to build
them as heterogeneous networks (Hanseth & Lyytinen, 2010). We find. Further, a judicious design
acknowledges that one cannot design and implement all functionality in one go but that one has to build it
through small-scale and incremental steps. Therefore, UHC-HIS requires an open architecture to allow
system development and use to evolve in a way that can easily support future changes.
Traditional HIS inherently conflict with UHC-HIS because the former does not support localized care.
Further, one should not design UHC-HIS based on sharing data with other existing (and future) systems
technically and across institutional borders. At its core, the system must allow health workers to deliver
essential care and also help to reduce the burden they experience in recording, tracking, and reporting data
(e.g., digitized primary registers could reduce data redundancies). At core, UHC-HIS requires a population
database, to support clinical care, and enable health workers to generate all required reports. This approach
will support the “build once, use multiple times” design principle. Beyond supporting local work, UHC-HIS
should also support information sharing across organizational boundaries (e.g., to enable interoperability
and data sharing with other systems such as hospital systems and births and deaths registration). Such
systems must further allow health workers to generate required referral linkages across levels to strengthen
continuity of care services. Building interlinkages with systems requires one to understand integration on a
case-by-case approach and to materialize that integration in an incremental manner. Both semantic (i.e.,
business logic and nomenclature) and syntactic (i.e., technical protocols to exchange data across systems)
[what] require defined standards based on multi-level and multi-sector coordination and governance across
institutions. However, a lack of regulation related to freely flowing information between institutions and
authority levels presents a key challenge in developing such standards. Finally, the UHC-HIS must cater for
the challenging work context that ANM and doctors experience (e.g., fluctuating Internet connections and
an unreliable electricity supply). These uneven and often technology-sparse contexts need hybrid solutions
that combine information technology and paper, online digital solutions that also offer offline support,
uninterruptible power supply solutions, and affordable and functional mobile units (phones and tablets). We
summarize these contradictions, opportunities, and design guidelines in Table 4.
Table 4. Institutional Contradictions, Emerging Opportunities, and Design Guidelines
-Establish the required travel support
Establish the required Internet
Care and data work assumes non-
Develop the supporting infrastructure
necessary for information and
paitnets to flow between outreach
and primary healthcare centers.
Differing views on whether the
responsibility of care lies with the
doctor or the patient.
To build awareness about doctors’
and patients’ responsibilities.
Develop public awareness about
individuals’ responsibilities for their
own health and care.
Table 4. Institutional Contradictions, Emerging Opportunities, and Design Guidelines
System design must simultaneously
support new and existing evolving
systems and work practices.
Combine information technology and
paper, support information sharing
across organizational boundaries,
and reduce the work burden of
Develop systems with an open
architecture, with the ability to share
data across institutional borders,
using hybrid solutions that combine
information technology and paper,
and using online solutions that also
offer offline support.
7 Conclusions and Contributions
Where previous research on information infrastructures primarily has focused on the challenges of achieving
integration processes based on top-down approaches, we focus on practice-based approaches and on how.
This approach to achieving UHC also differs from global initiatives such as the Health Data Collaborative
and the Open Health Information Exchange
, whose integration strategies begin at the top and not at the
community level even though healthcare organizations at the community level need strengthened care
practices. Where [what/who?] discusses integration as a technical issue, we also focus on the challenge of
integrating new and old work practices (since one can never start on a clean slate) and the institutional work
that supports such integration. In this process of standardizing work practices in uneven and often
technology-sparse contexts, we show that the unique and new UHC phenomenon will remain tangled with
the past. Institutional work in this setting involves bridging the new and old and releasing the potential of
new practices in rationalizing the old.
In this paper, we specifically address the research question: “What type of change do institutions need to
undergo to use the new technologies and associated work processes that universal health coverage
entails?”. We identify and discuss central contradictions and three key challenges that arise with UHC:
increased work burden for health workers, a lack of working infrastructure, and uncertainties regarding the
responsibility of the patients’ wellbeing. Leveraging these contradictions, we further identify four new forms
of work to establish the required institutions to support new UHC-HIS-related technologies and practices:
training ANMs in diverse and new domains, developing the supporting infrastructure necessary to support
the flow of patients between outreach and primary healthcare centers, establishing travel support and
Internet infrastructure for ANM, developing public awareness about patients’ responsibilities for their own
health and care, developing systems with open architecture, using hybrid solutions including technology
and paper, and providing online and offline support. The contradictions we analyze in this paper help to
explain the inherent complexities in UHC-HIS design and implementation, and the design principles should
offer guidance to actors involved in developing and implementing UHC-HIS in a similar context. We also
contribute to existing work on institutional theory by using the concept of institutional work to discuss how
the material properties of technology can influence how actors adopt new institutions at the expense of
existing ones (e.g., a UHC-HIS that features an open architecture can enable interoperability and data
sharing among systems). As institutional work, this has the potential to change existing reporting practices
and reduce data redundancy across systems. Further, research on the creation of new institutions has
focused on the role of actors in establishing institutions and primarily on institutional entrepreneurs and
under which conditions entrepreneurship thrives (Lawrence & Suddaby, 2006). In this paper, we extend
such research by providing detailed accounts of the work that actors do when they create, maintain, and
Our analysis suggests that one needs to anchor UHC-HIS in the routine facility HIS that exists in the primary
healthcare sector to prevent it from becoming “yet another reporting system”. If one can do so, the UHC-
HIS can also provide an opportunity for change by helping to rationalize existing facility HIS and revitalizing
it with the new focus that UHC provides. Such a unified system can arguably meet both the demands for
routine facility and new UHC reporting. We can see an example in which a country effectively integrated
UHC into its primary healthcare sector in Thailand. Based on expanding the existing primary health care,
the country incrementally built its HIS on its existing platforms (e.g., the well-working civil-registration and
vital statistics systems) to ensure the HIS covered and provided services to all citizens
(Tangcharoensathien, Limwattananon, Patcharanarumol, & Thammatacharee, 2016). The community
forms the backbone of a UHC (Schneider & Lehmann, 2016), and a UHC-HIS needs a design that focuses
on community-based electronic medical records, which fundamentally differs from a typical electronic
medical record (which one typically sees in large private hospitals). This difference arises because UHC
encounters do not take place in a hospital but in a geographically spread community. The community
electronic medical record needs to capture individual-based data on services needed and received
associated costs incurred while simultaneously generating population profiles of health service coverage
and financial protection, the two vital pillars of UHC, with the necessary stratifications..
HIS that appropriately and relevantly integrate the old with the new can support health workers’ practices
and reduce their burden in terms of the time they spend on entering and reporting data and add value to
their ability to take local action. Strong and flexible linkages between the UHC-HIS and other systems can
enable a more comprehensive UHC. Further, different functions will provide value to different actors (e.g.,
ANMs, medical doctors, pharmacists and administrators).
Achieving UHC and measuring its progress represent global priorities. Currently, measurement models
typically rely on survey data and not on UHC monitoring frameworks. While UHC must build on existing
primary healthcare, [who?] inadequately discusses its implications for UHC-HIS.. UHC-HIS must feature a
strong architectural framework to support these evolving informational needs. With its implications on health
workers’ workload,. At the core of this, the UHC-HIS must support work practices at different levels and link
to other relevant systems on a case-by-case basis, such as for civil registration and vital statistics and
hospital systems. In this paper, we discuss how this alignment work inherently relates to existing socio-
technical structures and requires institutional work that contributes to changing existing norms and practices
even as it introduces new ones.
This research has several limitations. First, it builds on empirical insights from a project that designed and
implemented a UHC-HIS pilot in India. While one can likely find the challenges and contradictions that we
discuss here across the healthcare system in India, other contexts may differ. Scaling the system to the
state level would likely introduce further contradictions and require new kinds of institutional work. To release
the full potential UHC-HIS, one must implement it at the state or national level, and further research should
follow such initiatives. Second, . While we do not develop a complete design theory for UHC-HIS, empirical
research needs to examine how health workers and organizations use the design principles in the same or
other contexts to validate them. Future research could also develop a proper information systems design
theory for UHC-HIS that pertains to the different contexts in India, to developing countries, and to developed
countries. Doing so would require more research to underpin each principle with theory and to develop them
further to offer more specific guidance to practitioners (Walls et al., 1992).
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