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The Configuration of an ALS Platform Case
Forty-First International Conference on Information Systems, India 2020 1
A Configuration Approach to Multi-Sided
Platforms in Healthcare: An ALS Platform Case
Completed Research Paper
Daniel
Fürstenau
1,2,3
1Copenhagen Business School
Department of Digitalization
Howitzvej 60, 2000 Frederiksberg
dfu.digi@cbs.dk
2Freie Universität Berlin
School of Business & Economics
Garystr. 21, 14195 Berlin
3Einstein Center Digital Future
Wilhelmstr. 67, 10117 Berlin
Carolin
Auschra
Freie Universität Berlin
School of Business & Economics
Garystr. 21, 14195 Berlin
carolin.auschra@fu-berlin.de
Stefan Klein
WWU Münster
Interorganisational Systems Group
Leonardo Campus 11, 48149 Münster
stefan.klein@wi.uni-muenster.de
Abstract
Amyotrophic Lateral Sclerosis (ALS) is a severe neurological disease; as a result, patient
care requires a complex network of specialists and equipment providers. Despite best in-
tentions, the organizational and regulatory structures in Germany have not been geared
towards efficient and effective coordination of care for patients and their caregivers. This
situation calls for innovation of care procurement and provision. APST is a multi-sided,
patient-centric platform, addressing the coordination of ALS care by combining case
management and platform-based service/equipment exchanges. Over time two feedback
cycles, quality of platform service and of care, as well as two research cycles, evidence-
based care and medical research, have been established and the platform has become an
infrastructure for ALS care, exemplifying social entrepreneurship for digital innovation
in patient care. We use an interorganizational configuration lens (Lyytinen and Dams-
gaard 2011) to reconstruct how the organizing logic shaped four components of APST
(case management, transaction, information, and research platform).
Keywords: Multi-sided platform, configuration analysis, ALS, care innovation,
interprofessional collaboration, social entrepreneurship
Introduction
In healthcare, digital multi-sided platforms (MSPs) promise to improve intersectoral and interprofessional
collaboration among diverse stakeholder groups, with an emphasis on active participation and engagement
from patients and patient communities (Irwin et al. 2014; Zenooz and Fox 2019). In general, MSPs are
defined as systems that create value by enabling direct – and as our analysis will show also indirect – inter-
actions between two (or more) otherwise distinct parties, such as suppliers and users (Hagiu and Wright
2015). By connecting these parties, they enable cross-side positive network effects, which describes a ten-
dency of mutual preconditioning and reinforcement of the different sides (Parker et al. 2016; Song et al.
2018). Depending on the founders’ mission, they can even qualify as social entrepreneurs (Saebi et al. 2019).
The Configuration of an ALS Platform Case
Forty-First International Conference on Information Systems, India 2020 2
The market is split between highly visible, profit-oriented examples (e.g., Apple Health) and a broader,
differentiated, and less visible group of specialized platforms (and platform initiatives). The latter of which
address an array of diseases, some rare and complex, such as amyotrophic lateral scleroris (ALS), which is
under discussion in the current paper. Procurement of care offerings is a complex administrative process
between patients, general practitioners (GPs), specialized doctors, care centers, hospitals, therapists, pro-
viders of assistive technology devices (ATD), pharmacies, and even insurance companies. Patients and their
immediate medical community are often overwhelmed by the complexity and fragmentation of the special-
ized care offerings, ATDs, and medicines, while simultaneously faced with their own quickly deteriorating
health condition (Bakker et al. 2015).
While some papers have applied a perspective on digital healthcare platforms from the viewpoint of MSPs
(Yaraghi et al. 2015; Otto and Jarke 2019), few have taken a multi-stakeholder, processual perspective on
platform design and management (e.g., Vassilakopoulou et al. 2017; Fürstenau et al. 2019). Given the se-
lective nature of the cases studied so far, we need more evidence to understand how MSPs in healthcare can
become sustainable and how the trade-offs and unintended consequences could be considered, in light of
the changing conditions in which these platforms operate. Furthermore, most contributions so far have
considered platforms based in the United States or the Scandinavian countries, which each have relatively
unique regulatory and social policy conditions. This leaves a void in our understanding of the dynamic con-
ditions and mechanisms of platform establishment in other settings, especially with regard to different na-
tional health systems.
The purpose of this paper is to shed light on a single case example of a specialized platform for ALS care
and to reconstruct the platform’s organizing logic and network structure in a nuanced and detailed man-
ner over time. This paper follows an abductive approach (cf. Alvesson and Kärreman 2007; Locke et al.
2008). We start with the puzzle of how an MSP could (1) improve the coordination and improvement of
ALS care and (2) be successfully established in the German healthcare market, to (3) eventually be devel-
oped into a research platform. Or conversely, how can the logic on a commercial MSP be transformed into
a social value creating platform for care and research. To this end, the paper reconstructs the design and
development of Ambulanzpartner.de (APST), a case and care management platform focused on ALS pa-
tients and representing an example of social entrepreneurship. In line with the recommendations for mul-
tidisciplinary ALS care teams (Nagasaka and Takiyama 2015) and guidelines for care (Mitchell 2000), APST
has developed a platform for case management or concerted care, linking patients and their helpers, med-
ical care providers (therapists, doctors, pharmacists, and care institutions), supply partners (medical supply
and equipment stores), and cost supporters (insurance companies). It thus operates as a multi-sided inte-
gration platform across multiple stakeholder groups. The platform is patient-centered and orchestrates
customized care, which integrates care providers and supply partners. It represents a hybrid care manage-
ment concept based on a combination of coordinated services with a digital management platform (Meyer
and Münch 2016).
We are reconstructing the contribution and innovation of the APST platform by applying a multi-stake-
holder, processual perspective. The case discussed is an illustration of how a digital health platform can
facilitate inter-professional coordination and cooperation across multiple providers. It also shows areas of
conflict and diverging perceptions on the platform’s value, which reinforces the need for a nuanced analysis
of the incentives and disincentives of various stakeholders to participate in a digital healthcare platform.
We also aim to reveal how this organizations’ visions, its cognitive models on how the platform contributes
value to its various communities, have emerged over time.
Conceptual Background
Multi-Sided Platforms
Multi-sided platforms get two or more stakeholder groups on board and enable interactions between them
(Hagiu and Wright 2015). The “theory” of MSPs is at the intersection of various discourses (Baldwin and
Woodward 2009; Gawer 2014), and within industry infrastructure (Gawer and Cusumano 2014), platform
ecosystems (Ceccagnoli et al. 2012; Parker et al. 2017), modes of networking (Raivio and Luukkainen 2011),
The Configuration of an ALS Platform Case
Forty-First International Conference on Information Systems, India 2020 3
cross-side network effects (Anderson et al. 2014; Rochet and Tirole 2003; Song et al. 2018), business mod-
eling (Muzellec et al. 2015), and (development) strategy (van Alstyne et al. 2016) alike. While most works
have addressed MSPs in the for-profit sector, an upcoming research stream also understands platforms as
a means to follow social missions (e.g., Logue and Grimes 2019) and to enact social entrepreneurship (Dacin
et al. 2010); a situation where “individuals and organizations use a business logic in a novel and entrepre-
neurial way to improve the situation of segments of the population that are … themselves not capable of
changing this situation” (Saebi et al. 2019, p. 70f.).
Figure 1. Conceptual Configuration Framework for Digital Healthcare Platform Analysis
Configuration Analysis of Multi-Sided Platforms in Health Care
We have chosen, what we consider to be, the under-utilized configuration analysis (Lyytinen and Dams-
gaard 2011) as a theoretical lens and methodological approach to reconstruct the organizing logic and net-
work structure of a digital health platform in a detailed and nuanced manner. Configuration analysis is
The Configuration of an ALS Platform Case
Forty-First International Conference on Information Systems, India 2020 4
defined as a conceptual and methodological approach, which is simultaneously considering organizing logic
and (network) structure in economic units spanning more than a single organization. By organizing logic,
we refer to managerial rationales for designing and evolving specific platform arrangements in response to
environmental and strategic imperatives (cf. Yoo et al. 2010), including vision and functionality of the plat-
form. By network structure, we refer to the scope, volume, and intensity of relationships among stakeholder
groups, including revenue streams and modes of appropriation. Lyytinen and Damsgaard (2011) examined
patterns of adoption units, which are the participating organizations in inter-organizational information
systems (not just individual organizations), and thereby suggest a multi-perspectival analysis. While previ-
ous research has used configuration analysis primarily as a framework for static analyses, we are using this
form of analysis to illustrate the emergent and dynamic processual characteristics of MSPs; in other words,
the transition between different configurations over time. By configuration, we refer to the way in which
the different configuration elements, such as organizing vision, structure, and mode of interaction are in-
troduced and instantiated. Figure 1 depicts how we have adopted Lyytinen and Damsgaard’s conceptual-
ization for the analysis of MSPs in healthcare, specifically, of the evolution of configuration patterns.
Research Design
Case Context and Selection
We use the case of APST to illustrate how a digital health platform can contribute to patient care improve-
ments. APST was founded in 2011 as a spin-off from the Charité Universitätsmedizin in Berlin, a large uni-
versity hospital, aiming to coordinate and enhance treatment for ALS patients. ALS is a severe, relentlessly
progressive and eventually fatal neurodegenerative disease without a known cure. It is characterized by
progressive weakness of voluntary muscles of movement as well as those for swallowing, speech and respi-
ration (Soriani and Desnuelle 2017). Most patients pass away within 2-4 years after the onset of symptoms
due to respiratory failure. Only 5-10% of patients will go on to live for more than ten years (Seitzer et al.
2016). Given the dire prognosis and swift progression of the disease, patients and their community are often
overwhelmed by the challenges of organizing medical care and dedicated equipment. As one patient repre-
sentative and affected person (#10) himself described: “The further the disease progresses, the greater the
dependence on external help.” ALS care also faces profound coordination challenges (for a review, see Seit-
zer et al. 2016). Ideally, interdisciplinary teams, which include hospitals, primary health care provision and
patient and family associations, will help to deal with the disease and to provide comprehensive care, and,
if possible, also at the home of the patient. Various care models have emerged, with interprofessional teams
usually including nurses, physiotherapists, occupational therapists, neurologists, cardiologists, respiratory
medicine experts, psychologists, and social workers. “The key objectives of these teams are to optimize
medical care, facilitate communication between team members, and thus to improve the quality of care”
(Güell et al. 2013, p. 529; the care network is shown in Soriani and Desnuelle 2017, p. 289).
Data Collection and Analysis
Our emphasis will be to analyze how APST developed its organizing logic and network structure over time
towards contributing to the improvement of patient care. APST is unique (Yin 2018), there are currently no
comparable platforms for ALS care. To reconstruct the development of this platform in light of its distinc-
tive contingencies, we follow an in-depth, qualitative case study approach (Eisenhardt 1989; Yin 2018). The
single case study design is consistent with an abductive analysis and is a prerequisite for deep insights into
this revelatory case and to highlight crucial phases of its development. The analysis thus provides a refer-
ence point for other case studies and the basis for theoretical generalization (see also Eisenhardt 1989,
about the benefits of single case studies).
Data Collection: For the basis of an unbiased analysis, we used several data sources for triangulation
purposes (e.g. Lincoln and Guba 1985; Yin 2018) (see Table 1). First, we have collected primary interview
data from APST (n=8). Building on an informal talk with one founder in January 2019, the primary author
conducted two confirmatory formal interviews with the founders (first with one and a second with both
founders). Through the founders, other employees of the platform firm could be bought in, such as the care
research manager, allowing us further insights into the firm’s internal logic and processes. Further, we have
The Configuration of an ALS Platform Case
Forty-First International Conference on Information Systems, India 2020 5
attended an APST supplier workshop in November 2019 and interviewed suppliers to complement the plat-
form owners’ perspective (n=9). The full-day event also allowed us to administer a survey and to collect
structured responses from n=14 individuals. As a third perspective, we gathered formal interview data from
patient representatives. These organizations were contacted and interviewed in April 2020 (n=6). Since
one interview partner was not able to speak due to his illness, a written conversation was conducted in place
of an interview. These voices helped us to relate the platform and supplier responses to concrete patient
needs and challenges. All formal interviews were transcribed by student assistants while we took extensive
notes about the informal talks that took place in ad-hoc situations. Further secondary and archival docu-
ments were collected to supplement, complete, and expand the analysis. One author attended two presen-
tations given by APST and was able to receive the slides afterwards. APST also provided us further internal
documents (e.g., outlining its governance structure). Moreover, we collected the totality of news articles
and facebook posts (including uploaded videos) regarding APST, as well as academic articles on APST pub-
lished in general outlets and in media coverage since its foundation in 2011 up until April 2020.
#
Source,
role
and
description
Period
Quantity
A
-
Primary
interview
data
from
platform
owner
firm
(APST)
n
=8
1
Formal
confirmatory
interview
with
founders
(#1.1
-
1.2)
March
/
July
2019
2
2
Informal
talk
with
founders
(#2)
January
2019
1
3
Informal
talks
with
care
research
manager
(#3.1
-
3.2)
July
/
Sept.
2019
2
4 Informal talks with other employees at supplier workshop
(e.g., case management) (#4.1-4.3) November 2019 3
B
-
Primary
interview
and
observational
data
from
suppliers
n=
9
5
Informal
interviews
at
supplier
workshop
(#5.1,
…,
5.5)
November
2019
5
6 Formal interviews with suppliers (e.g., medical supply stores,
assistive device firms) (#6.1 … 6.4) April 2020 4
7 Attendance of / observation at supplier workshop (incl. field
notes, gathered materials) (#7) November 2019 Full 1-day work-
shop
8
Short
s
urvey
administered
at
supplier
workshop
(#8)
(potential overlaps with supplier interviews)
November
2019
14
valid
re-
sponses
C
-
Primary
interview
data
from
patient
representatives
n=6
9 Formal interviews with patient representatives (#9.1-9.5) April 2020 5
10
Written
conversation
with
patient
representative
(#10)
April
2020
1
D - Internal data from platform n=6
11
Internal
documents
by
APST
(e.g.,
internal
platform
govern-
ance concept (2018), general terms and conditions for suppli-
ers, patients, medical partners; presentation to students
(2019), neurology congress presentation (2019))
2018
–
2020
6
E
-
Secondary
and
archival
documents
220
sources
12 News articles 2012 – 2018 40
13
Facebook
posts
by
APST
2011
–
2020
163
14
Videos
uploaded
by
APST
2013
–
2014
5
15 Scientific publications on health services research of the plat-
form 2013 – 2018 7
16 Media coverage (e.g., Spiegel, Ärztezeitung) 2011 – 2015 5
Table 1. Data Sources
Data Analysis: We analyzed our data following an abductive approach (Alvesson and Kärreman 2007;
Locke et al. 2008), questioning theoretical ideas based on data, developing new inductive categories when
necessary, and constantly cycling back and forth between one and the other. After storing our data in a case
study database (Yin 2018) using the software MAXQDA, we conducted a qualitative content analysis (e.g.,
Mayring 2000; Schreier 2014) by systematically assigning “successive parts or the material to the categories
of a coding frame” (Schreier 2014, p. 170). We were thus able to reduce our data and to focus on selected
meanings related to our research objective. Coding started in a deductive manner. The framework of Lyyt-
inen and Damsgaard (2011) (see also Table 1) is the basis of our coding scheme. We thus started to code for
The Configuration of an ALS Platform Case
Forty-First International Conference on Information Systems, India 2020 6
(1) the organizing vision, (2) key functionalities, (3) structure, (4) modes of interaction, and (5) modes of
appropriation, which represent overarching configuration elements of APST at several points of time. We
operationalized each element by sub-categories. For instance, regarding modes of interaction, we coded as
a first sub-category for types of linkages (either brokered by the platform while acting as an intermediary
or facilitated by the platform as direct linkage by its participants). We described each linkage in detail by
naming the connected actors, therefore taking on a multi-stakeholder perspective. A second sub-category
to operationalize modes of interaction focuses on the type of interaction enabled by the platform (e.g., pur-
chasing of goods and services, collecting data for research, providing information for platform participants).
In addition to deductive coding and as part of our abductive approach, new inductive codes emerged during
data analysis. For instance, different roles of the platform representing its key functions that were not fore-
seen by Lyytinen and Damsgaard became visible (e.g. offering offline-trainings for platform participants
like medical professionals but also patients and their care givers). Our coding was therefore both concept-
and data-driven. In a following step of data analysis, we linked our codes to four phases of platform devel-
opment, representing different configurations. With the help of this axial coding structure (Strauss and
Corbin 1990), we are able to reconstruct the dynamic configurations of APST. The first and second authors
each coded data (with around one fifth being coded by both authors to achieve a common coding approach),
and all authors held regular discussion meetings on emergent findings. During each step of data analysis
we compared coding and upcoming interpretations, such as the platforms two modes of operation as a
multi-sided platform and a research infrastructure. By following this approach of data analysis, we are able
to reconstruct the platform’s configuration and development.
Configuration Analysis
Our configuration analysis of APST follows the conceptual model’s logic as proposed in Figure 1.
Organizing Vision
Both founders work as professors for neurology at Charité and are confronted with deficiencies of ALS care
in their daily work. They launched APST with a vision consisting of two guiding principles: The first princi-
ple is in using the economic mechanisms of a digital multi-sided platform to improve the coordination
efficiency and quality of care, especially in more complex cases. As one patient representative in-
terviewee (#9.1) noted in regards to the importance of fast and efficient treatment: “the patients and those
affected simply need to be treated as soon as possible.” Use of the platform for patients, their relatives and
doctors is free. Within interviews, the founders constantly mention the platform’s benefit for patients in-
stead of potential financial revenues created by the platform.
APST is empowering patients by providing more information, transparency, and informed choices to them.
The same representative (#9.1) indicated, as a result of APST and similar platforms, “that those affected
have more insight into their care.” Another patient representative remarked (#9.3), the aim is that “patients
are independently informed, they are informed promptly, they are informed about all ongoing studies and
treatment options, they are informed about medicines.” This helps patients to retain control over their data
creating health care and medication files, with strict data security and data access policies consciously im-
plemented. This assessment was also shared by a patient representative (#9.1) who said: "The main chal-
lenge is of course data protection.” Likewise, the founders claim (Meyer et al. 2013, p. 166): “Through APST
… the patient can take a direct influence on their own care. The involvement of the patient in the decision-
making and treatment process … corresponds to socio-medical and social progress, which focuses on the
co-determination and self-determination of the patient.”
APST is improving care for ALS patients, i.e. creating an information platform (repository of care files etc.),
which yields coordination efficiencies and provides the basis for feedback between the platform’s stake-
holders. As one patient representative (#9.1) insisted: “That's what we want, patient care … that we get a
little more involved and that we get a little more together. And just get more information to help and support
those affected.” The patient community and platform-based-data provide unique opportunities for ALS re-
search. For instance, one supplier (#7) envisioned that “biofeedback” represents one such unique oppor-
tunity for research-based insights.
The Configuration of an ALS Platform Case
Forty-First International Conference on Information Systems, India 2020 7
The second guiding principle is to use APST as a research platform or infrastructure for multiple func-
tions in research, including epidemiological public health research (e.g. register studies, “real world evi-
dence”), medical trials, and contract research (Meyer et al. 2018, Meyer et al. 2019, Meyer et al. 2020). In
essence, the platform combines two modes of operation: a multi-sided platform for ALS care management
and a research infrastructure for secondary use of patient data, care research and medical studies.
In contrast to the majority of platforms, the ‘hidden engines’ of growth and profit for the platform providers,
we qualify the vision of APST to be an example of social entrepreneurship (Saebi et al. 2019), which is to
prioritize patient care and wellbeing over profit. While revenue generation is a necessary constraint and
condition for sustainability for APST, it is not a goal in itself. Improving care for complex neurological dis-
eases and doing care research are likely not being considered as fields for swift scaling.
Primary Model - Multi-Sided Platform for ALS Care Management
Figure 2 illustrates main products and services coordinated via the platform (i.e., ATDs, therapeutics, med-
icines, and care opportunities) as well as the main stakeholder groups towards who these products and
services are targeted.
Figure 2. APST’s Multi-Sided Platform Model (adapted from Meyer and Münch 2016, p. 34)
Moreover, the platform has become a significant data repository - each patient’s electronic health record
and additional medical and technical information required for the procurement and provision of ATD are
documented on the APST platform. Digitized administrative information (prescriptions refills, etc.) is used
in their procurement processes. Patients are consistently polled by the platform in order to provide feed-
back and to assess the services and product quality.
Secondary Model – Research Infrastructure for Secondary Use of Patient Data and Medical Studies
One of the overall aims of the platform is evidence-based improvements of the quality of provision of care
and ATDs to ALS patients. Based on the data collected on the platform and access to a unique patient com-
munity, the platform is used as a research infrastructure for (1) health services research and (2) ALS and
neurology-related medical and pharmaceutical research. Patient information, transaction data and system-
atically structured patient feedback regarding the quality of services and equipment have been combined
to study the overall quality of care provision (e.g., a comparative study of the provision of ATD across four
ALS centers, which showed that only 64% of indicated ATDs reached the patients) (Funke et al. 2015, p.
1010). Given that APST supports about 50% of the German ALS population, there is rich data on a repre-
sentative sample, which can be used for multiple studies - amongst others for a registry study, analyzing
results in the patient population. The two founders of APST state: “Data generated in the context of care
management is used for a systematic analysis of care on the basis of informed patient consent. This results
in a ‘double effect’: The digitization of care data on the APST Internet portal serves directly to coordinate
care and at the same time provide research into care through the evaluation of ‘routine’ data (real world
The Configuration of an ALS Platform Case
Forty-First International Conference on Information Systems, India 2020 8
evidence)” (Meyer and Münch 2016, p. 35). Access to APST’s patient population provides a unique oppor-
tunity for ALS research. The prediction of the progression of ALS based on voice data, medication trials or
experimental research on assistive technologies being at the forefront.
Key Functionality
The two models support four functional areas: Case management aims at matching individual patient’s
needs involving medical, therapeutic and pharmaceutical care providers as well as providers of ATD. To
support case management and to be able to scale it, APST functions as a transaction platform for effi-
cient procurement of care services and equipment, i.e. process facilitation and automation. Consequently,
the traditional process (patient – doctor – insurance – care or equipment provider) is transformed and
APST has been established as an intermediary between patients (or prescribing medical doctors) and ser-
vice suppliers.
Figure 3. Workflow for ATD Provisioning (a
dapted
from Meyer and Münch 2016, p. 36)
Figure 3 depicts the workflow supporting the platform for the provisioning of ATDs, such as wheelchairs,
walkers, and toilet seat raisers. APST coordinates the entire workflow, considering the kind of wheelchair
needed, the supplier who could deliver the product fastest, and whether the wheelchair is suitable to the
patient’s specific situation, as well as supporting the prescription until cost estimations for the health in-
surance. This process did not yet function completely smoothly, and some suppliers have complained about
(a) a lack of automation and interfaces, (b) support of the platform in the insurance approval processes, as
well as (c) support in case of rejected approvals, which occur frequently. One supplier (#6.3) raised the
concern that “double entries are negative, we lack csv import/export interfaces to connect APST with our
own warehouse management system.” Another supplier (#7) wished for more options, “to contact patients
directly in the system in case of contradictions.” One care partner (#6.4) pointed out economic and ethical
dilemmas that fall together in cases where care is not delivered fast enough, saying “It is unfortunate if a
patient passes away before the reimbursement is approved, because the service cannot then be billed.”
As part of process facilitation and coordination across care providers, APST functions as an information
and communication platform. It hosts extensive documentation for case management, as evidenced
by the data structure of the platform, which includes: Medical partners (doctors, pharmacists, caregivers
etc.), picture galleries (e.g. with a profile picture of the patient, optional), diagnoses and guiding symptoms,
as well as a document center with the upload and download functionality of supply-relevant documents
(therapy report, test report, doctor's letter, etc.), an overview of existing aids (type, product name, area of
application, etc.), provision of aids (status of the regulation, payment and delivery), overview of the reme-
dies (physiotherapy, speech therapy, occupational therapy, specific subdivision into measures catalog, pre-
scription quantity, frequency recommendations, etc.), provision of remedies (status of the prescription),
medication plan with overview of all current and completed medications, overview of all nursing services
(care location, nursing care, type of care, etc.), evaluations of treatments, products and medicines by the
patient based on questionnaires, grading and comments (APST - Versorgungsnetzwerk n.d., p. 6).
Based on the patient community and the extensive data collection, APST functions as a research plat-
form, first and foremost, to identify evidence-based improvements for the care of ALS patients and there-
within engender ambidextrous learning dynamics, i.e. transaction-based identification of improvements
and community-based feedback for care providers. Such a platform also provides opportunities for medical
The Configuration of an ALS Platform Case
Forty-First International Conference on Information Systems, India 2020 9
research (medication trials etc.) and contract research, e.g. for pharmaceutical companies or equipment
manufacturers.
On a 5-point Likert scale with 5 as the highest value, suppliers (n=14) rated the case management and
transaction platform for ATD transactions as 3.69, (patient-related) information and communication
platform as 3.71, and in the context of the research platform’s service improvement as 2.85, with contract
research possibilities as 2.71. This shows that while the case management and transaction platform build
the core of the platform, advanced functions around the research platform are still under development.
Structure
The key stakeholders of the APST platform – except for the research partners – are depicted in Figure 2.
The structure of the relationships follows these main functions of the platform:
Information, communication and coordination
Care provision including ATD (assistive technology devices)
Payments (transaction fees, payments for research contracts).
The platform facilitates exchanges between its various stakeholders in a hub-spoke model, which em-
phasizes direct exchanges between the different “customer” segments of the platform. This is in line with
the definition of an MSP, as well as with coordination and exchanges within the respective segments, most
notably in interprofessional care coordination among the care providers. In turn, how orders were distrib-
uted among suppliers remained somewhat “elusive” to them. As one supplier (#6.4) noted: “We are not the
only provider, which means there are other providers who are all part of the APST network. And it is not
necessarily obvious by which criteria sometimes one or the other is selected.” It was also apparent that some
of the suppliers were in a strong competitive relationship, which in some cases made overall coordination
more difficult. As one voice acknowledged (#7), “processes run sideways or in parallel”, which shows that
transactional support for suppliers could still be improved further.
The platform is governed by its owners, the platform providers, who have a dual roles as entrepreneurs
and ALS medical specialists and researchers. This is highly beneficial in terms of professional medical
knowledge, but problematic in terms of the strict separation between the responsibilities of medical doctors
on the one side and providers of medicine or ATD on the other side. At the supplier conference (#7), the
founders noted that this conflict is often mitigated because money is passed on to ALS ambulances and thus
supports ALS research, and that the platform plans to collect even more data in the future to conduct its
own health care research, which will benefit patients. APST can be described as a provider-driven compe-
tence network, in contrast to strictly (patient) community-driven, or vendor-driven approaches.
The revenue model is based on the following pillars: (1) research grants, (2) transaction fees of care and
ATD providers on the platform and (3) contract research. Moreover, in line with many MSPs, one segment
- the patients - is subsidized, which drove membership growth on all sides. The founders note that,
“APST is financed via a multi-sided platform model ... For the medical partners (patients, rela-
tives, doctors), the services and the Internet portal are provided free of charge. The service archi-
tecture and technology platform are financed from licenses of the supply partners (aid and remedy
providers, pharmacies and other licensees)… The willingness of the supply partners to pay results
from efficiency advantages of their own service provision, an increase in quality and improved
resource management” (Meyer und Münch 2016, p. 38)
This ties back to the patients who are offered the service of the platform without charges, thus contributing
to facilitating positive cross-sided network externalities.
Mode of Interaction
To reiterate, the interaction structure between patients, the platform, care providers and research partners
is divided in line with the two models of the platform. A) facilitated, which provides direct links between
platform segments, while the other links are b) brokered and thus intermediated by the platform. The
The Configuration of an ALS Platform Case
Forty-First International Conference on Information Systems, India 2020 10
primary types of platform-based exchanges include that of: information, (sensor, log) data, communication
and coordination, transactions (service provision, ATDs, prescriptions, etc.), and payments.
The platform combines interpersonal, trust-based relationships between patients and care coordinators via
information-based, automated exchanges with the business partners.
Mode of Appropriation
APST improves the provision of patient care in four distinct ways: first, through individual case-manage-
ment, i.e. the platform links individual patients with a network of care providers. The “individual coordina-
tion of the care package“ (Merl and Stöger 2014, p. 112) is supported through the process structures of the
platform. Thus, it reduces coordination efforts (costs) and accelerates the set-up of a care network, so that
distribution of crucial data can be securely shared via the platform. Second, the patient-feedback functions
as peer review for other patients. Further, customer feedback to the care providers increases transparency
regarding perceived service and equipment quality. For example, the patients can rate the platform, sup-
pliers, assistive technologies, and their medicine. It is thus meant to yield a learning process and increase
quality of provided care and ATDs. As one founder suggested, “We want to make the processes for ALS
patients still better, also through new assistance technologies”. Third, the monitoring and documentation
of ALS care management across a large sample of patients with aggregated feedback to the care service
providers contributes to evidence-based insights into ALS care and metrics for the furthest reaching impact
of the platform. Finally, the platform reduces data collection costs for ALS research based on a large patient
sample (e.g., register study).
The platform has successfully scaled and yields positive cross-sided, and – with respect to the patient com-
munity - same sided network externalities, which the Dynamic Analysis section will show in more detail.
The facilitation of quality improvements, as well as learning and research opportunities, have become a key
driver for the platform development, as the implemented rating system demonstrates.
Summary
In essence, the APST configuration (Table 2) combines an MSP (hub-spoke), with two types of sub-net-
works, (a.) the care network (Primary Model) and (b.) the research network (Secondary Model) together
with three stakeholder groups (or market sides): the patient community, the care provider community, and
the medical research community.
Dynamic Analysis
Scaling the Platform. The APST platform started in 2011 with 200 registered users consisting of almost
exclusively ALS patients treated at the Charité – Universitätsmedizin Berlin (Charité – University Hospi-
tal). Within a period of eight years, the user base exceeded 8,000 patients (50% suffer from ALS, the other
users come from different complex neurological diseases such as stroke, multiple sclerosis, Parkinson's dis-
ease or muscle diseases) and amounts to approximately 50% of the ALS patient population in Germany1.
Further, the number of suppliers on the platform grew consistently as can be demonstrated, that in 2017,
1,273 suppliers took part in the APST network, up from 1,061 suppliers in 2015. Similarly, the number of
medical partners has increased; Initially the ALS center at the Charité had focused coordinating ATD supply
(67% or 941 ATDs between June 2011 and October 2014; Funke et al. 2015). While APST started with 4 ALS
centers, today it includes 15 ALS centers throughout Germany. 155 medical doctors took part in patient care
through APST in 2014 and their number has increased since then. These scaling dynamics suggest a super-
linear growth of patients enrolled in the platform, which represents a critical patient sample for real-world
research and evidence (i.e. that of use beyond the platform). Our data on suppliers and medical partners
does not show a specific trend; yet, data indicates that growth is also increasing. The revenue model has
also developed significantly over time: (1) the platform was initially funded by a research grant, (2) this
funding was complemented and increasingly substituted by transaction fees of care and ATD providers on
1 While up-to-date data on prevalence of ALS is lacking (Longinetti and Fang 2019), it has been reported that ~8,000
patients in Germany suffer from ALS (ALS-hilfe.org 2020), of which more than 4,000 are using APST
The Configuration of an ALS Platform Case
Forty-First International Conference on Information Systems, India 2020 11
the platform and gradually (3) funding based on contract research has been solicited. The transaction rev-
enue has benefited from the increasing number of patients as well as care providers.
Extending the Scope of the Platform. The scope of the platform was (gradually) extended to other
complex neurological diseases, such as stroke, multiple sclerosis, Parkinson's disease and muscle diseases
(Meyer and Münch 2016). The prerequisite was an extendable portal structure and service architecture.
According to the founders, “The extension to other indication areas is technologically possible and scalable,
as the Internet portal has already been financed and confirmed with a revenue model.” (Meyer and Münch
2016). Neurological diseases commonly cause high organizational expenses in the coordination of patient
care, require a high level of specialization to ensure care quality, and impose a high need for coordination
between different medical partners and providers. Specific neurological diseases differ in their severity,
chronic versus non-chronic, and may be rare diseases (such as ALS). Therefore, the platform indicated at
the supplier workshop (#5) that it hoped to scale its model to those indications within the next years.
Configuration
elements
APST Characteristics
Organizing
vision Two guiding principles: social entrepreneurship (including improving ALS care and empowering
patients) and platform as a research infrastructure; manifested in two interdependent models:
(1) A multi-sided transaction platform for ALS care management,
(2)
t
he
platform
as
a
research
infrastructure.
Key
functionality (1) Case management: Facilitating matching of individual patient and ATD, care providers.
Care management: Platform-based coordination (process facilitation and automation).
(2) Transaction platform: Efficient procurement of care services and equipment and coordi-
nation of care providers. Traditional process is transformed: APST as new intermediary.
(3) Information and communication platform: Extensive documentation of and for case
management: Patient health, care, and medication record. Consolidated patient feedback,
which functions as peer review or other patients and customer feedback to the care providers.
(4) Research platform: Research is based on
a. monitoring of transactions evidence-based care research,
b. patient feedback and participation in surveys,
c. patient sensor data,
d.
patient
participation
in
(medication)
trials.
Structure
S
takeholders:
patients,
service
suppliers,
medical
doctors,
relatives/community,
research
partners
(1) Direct and indirect exchanges among the platform segments.
(2) Platform provider-based governance poses regulatory challenges.
(3) ‘Shared value’ model: healthcare providers pay transaction fees, the service is free for the
patients
.
Research
funds
and
contract
research
as
additional
funding
sources.
Mode
of
interaction Interaction structure between patients, the platform, care providers and research, differentiated
by the basic models. Types of exchanges:
Information,
(sensor, log) data,
communication and coordination,
transactions (service provision, ATDs, prescriptions etc.),
payments.
Mode
of
appropriation Four main contributions and areas of impact:
(1) Reduced coordination cost and increase allocation efficiency (matching)
(2) Increased transparency and learning based on patient feedback
(3) Large scale evidence-based insights about ALS care
(4)
Reduced
data
collection
costs
for
research
Table 2. Summary Configuration of the APST Platform
The functionality of the platform has gradually been extended as well. The portal started in its first version
with a focus on ATD and therapeutic product management, emphasizing the platform’s main focus as a case
The Configuration of an ALS Platform Case
Forty-First International Conference on Information Systems, India 2020 12
management and transaction platform. In 2012, the care management module went live. It accounted for a
high degree of complexity in nursing care, since dynamic forms of care are implemented in the spectrum of
outpatient, day-care or inpatient care during the progression of ALS disease (Meyer et al. 2013). In 2013, a
module to coordinate medications across care sectors was launched. As the founder noted within the sup-
plier workshop (#7), “in the field of pharmaco-therapy, prescriptions are already put online as PDF files at
APST at the time of application and before assessment by the health insurance.” This also strengthened the
platform’s core as a care management and transaction platform. In 2014, a survey module was integrated
into the platform. This allowed one to rate ATP, therapeutic products, medicines, delivered care, as well as
providers, medical partners, and the platform itself. It enabled constant feedback and learning and pre-
sented an important step in the direction of an information platform. Suppliers (n=14) indicated on a 5-
point scale, at 2.86 that feedback from the platform had already helped them to improve their services,
showing further room for improvement. It also laid the foundation for the research platform, which became
one of the APSTs’ main focuses today. In 2018, a new therapeutic product module went live.
Configuration Dynamics: Primary Model as a Multi-Sided Platform for ALS Care
Our data illustrates two main development stages of the platform’s logic, which often affected several as-
pects of the platform’s configuration. These stages were not as clear-cut as they are presented here, but
represent different nuances in the platform’s main emphasis.
From a manually to digitally-mediated platform (2011 – 2013): A first shift taking place early in
the platform’s development was from manual to digital support of care management. Manual processes of
care management supported by telephone and personal contact have been replaced by digitally-mediated
transactions. This became possible by the provision of new functionality on the platform, in particular the
‘ATD’ and ‘Therapeutic Product Management’ module, supporting the case management and transaction
platform. At the end of this phase in 2013, key functionality of the platform was in place. The logic of this
phase is characterized by a professionalization of the processes for all stakeholders and thus affecting the
configuration: The organizing vision of a multi-sided platform was enacted and APST began to emerge as
a new intermediary, coordinating and matching between patients, medical partners, and providers. The key
functionality of case management and the transaction platform was prominent in this phase. In terms of
structure, the platform began to coordinate between the different stakeholder groups. In this phase APST
was still mainly financed through research projects, but its “shared value” model began to emerge (as de-
scribed in the Structure section). Its governance began to become more separated from research institu-
tions, as the newer organizational form (limited liability company) established. Modes of interaction fol-
lowed the primary model, including case management and care coordination, as well as digitally-mediated
payments. The mode of appropriation followed the patient-centric model, while other aspects such as net-
work effects, feedback, and learning came to the fore later on.
Beyond transactions - information and documentation platform (2013 – 2015): A second
shift took place when new mechanisms for patient feedback and document exchanges were established. The
platform aimed to connect different stakeholders (providers, patients, and medical partners) in order to
create an individualized “personal private network” for patients’ needs. To achieve this, the possibility for
data exchange between parties involved had to be created. This included the storage and exchange of doc-
uments via the platform within secure and private data spaces. As an example, the reimbursement process
for a wheelchair can be complex and requires extensive information exchange, which is benefitted by access
to past order history. In addition, a survey module was established to provide feedback from the patient,
thus gearing to close the loop between transaction and demand. This phase ended around 2015 when all
areas of the platform were open to assessment: ATD, therapeutics, care products, providers, medical part-
ners, as well as the platform itself, participated.
This shift affected the platform configuration: It laid the foundation for an expanded organizing vision,
which the research platform modelled for secondary use of patient data and medical studies. Key function-
alities enabling this shift were the survey module as well as data and information spaces, bringing together
providers, medical partners, and patients. Regarding the structure, the shift contributed to the empower-
ment of patients by providing options for feedback and assessment. It also laid the foundation for new
stakeholder networks to emerge. Especially during the secondary use of the platform and interactions with
The Configuration of an ALS Platform Case
Forty-First International Conference on Information Systems, India 2020 13
research partners, which only became possible in this phase. This also created the base for new revenue
models, which were not however the focus at that point. Community-based assessment and learning was
one important mode of interaction emerging in this phase, as was structured and consolidated quality as-
sessment. In terms of modes of appropriation, this shift brought about increased transparency for providers
and patients regarding perceived service and equipment quality based on patient feedback.
Configuration Dynamics: Secondary Model as a Research Infrastructure
From transaction and information toward a research platform (2015 – 2017): The platform
succeeded to build a large sample of ALS patients. While transaction model had been designed to benefit
from electronic patient and transaction records, the operation of the platform generated and accumulated
an increasing amount of data, which became a treasure trove for evidenced based-research on ALS. The
platform facilitates a portfolio of research projects and initiatives.
This shift affected the platform profoundly. The organizing vision for the secondary model now began to
materialize. More studies were conducted. Implications tended to be richer since the enrolled sample grew.
The key functionality was not affected as much during this phase. Earlier functionality such as the survey
module were drawn upon. Structurally, the networks of the platform extended considerably, as the scaling
dynamics indicated. New networks emerged with new research partners from academia and industry.
Modes of interaction became more data-based, using transaction data for research purposes as well as scru-
pulously collected data from patients. Finally, regarding appropriation modes, a growing number of pa-
tients and care providers linked to the platform yielded positive cross-side externalities in this phase. Re-
search foci allowed insights and learning for public healthcare research and thus contributed – directly or
indirectly – to improve the quality of care.
From B2B to P2B2B platform (2018 – today): A last shift in the platform configuration has just
begun to emerge as we collected the data. Initially, the patient received help through the platform mainly
due to his medical condition (coordinated through his/her care coordinator). This last phase indicated a
change towards a more active involvement of the patient on the platform. Instruments for this purpose are
surveys and assessment procedures to assess the quality of life of patients as well as extend feedback and
assessment mechanisms. The vision is an even more individualized matching between patients and medical
providers and ATD/therapeutic providers. As one supplier (#7) envisioned to, “start the care process before
the patient identifies his or her needs.” For this purpose, sensor and movement data of the patient are also
increasingly included. Using increasingly available sensor and tracking data to match between patients and
medical providers becomes a focus of attention. One of the founders (#2) noted that, today, APST functions
mostly as a business-to-business-platform between specialized physicians and providers. What is still prob-
lematic is to integrate patients in the first place and to match them to specialized physicians. To fill this gap,
he mimicked the principles of the “internet of things.”
Summary. The shift from a purely transactional (primary model) to research model (secondary model) is
affected the configuration in several ways. The organizing vision regarding the primary model becomes
more detailed and fine-grained. New secondary uses emerge. This results in an improved integration be-
tween primary and secondary uses of the platform, with an emphasized on the research component. New
research functionalities include patient sensor data and more detailed tracking. This enables more individ-
ualized diagnoses based on a large sample, from which the individual potentially benefits. Structure-wise,
the shift enables new networks including monetizing data and conducting research as a contract research
organization. It also strengthens the existing partnerships as partners receive more individualized feedback.
In terms of modes of interaction, algorithmic analyses of patient data come to the fore. Research-wise,
survey data become more individualized and offer real-time higher prognostic values. Finally, in terms of
modes of appropriation, algorithmic assessments of the patient need via monitoring and tracking contrib-
ute to an evidence-based discourse about healthcare quality and outcomes.
Discussion
We have analyzed a specialized health platform, which reflects the contingencies of ALS care in Germany.
The analysis has reconstructed the platform’s organizing logic and network structure in a detailed manner.
The Configuration of an ALS Platform Case
Forty-First International Conference on Information Systems, India 2020 14
For this purpose, we have adapted and extended a configuration analysis as proposed by Lyytinen and
Damsgaard (2011), which had been developed to study interorganizational information system adoption.
Our analysis has revealed a pattern of (1) starting with individualized case management to address imme-
diate patient needs, and supporting it through a digital multi-sided platform. This is to mobilize economies
of scale and improve transaction efficiencies. As the platform grew, network effects and allocation efficien-
cies in a small and highly specialized segment of healthcare became visible. (2) Professionalizing the ex-
changes through building an information platform to document information about the platform partici-
pants (from care records to technical specifications of ATDs). (3) Initiating several feedback loops for learn-
ing across multiple stakeholders and research goals, in order to increase the quality of care services and the
value of the platform for its participants. These insights contribute to care research for the benefit of the
patients, the care providers and for public health. (4) Extension of the platform towards a patient-to-busi-
ness-to-business (P2B2B) model, using sensor and tracking data for more individualized matching of pa-
tients and (medical) research partners.
Next to linking patients, medical professionals, and relatives with service suppliers (cf. Figure 2), APST also
connects these groups to research partners, as well as facilitating inter-professional coordination and col-
laboration among specialized suppliers. The design and development of the platform are encouraging ex-
amples of social entrepreneurship through their focus on the improvement of patient care. This applies
especially to a country like Germany, where the digitalization of health care is still in need of crucial im-
provements (e.g., no nationwide digital health infrastructure, few regional health information exchanges),
and where intersectoral care and integrated health systems are not the norm. The platform has improved
the workflows around patients, which was initially insufficient for the needs of ALS patients, while inter-
mittently recognizing and protecting the patients’ interests.
By taking a multiple stakeholder perspective, the platform design and development shows not only how an
incentive compatible configuration can be achieved, but also how the dynamic of ongoing learning and im-
provement can be facilitated across and between different stakeholders, in order to improve patient care
through coordination and research. APST puts substantial effort into protecting patients’ rights, interests
and independence. Voluntary and structured feedback provided valuable information for care providers
and other patients. Platform transactions provided unique insights in care research. The patient community
constitutes a unique sample for ALS-related research. APST’s respect for the patients, and the quality of
this health platform’s service to their patient-users, is a strong motivator for those users to volunteer as
participants in research initiatives and projects, and donate their data for research purposes (APST 2020).
The use and impact of technology has moved from minimal support during the initial phase of case man-
agement, with the support from state-of-the-art process and documentation (information platform), to-
wards cutting edge development of algorithmic analysis of sensor-based patient data for diagnosis, forecast,
and therapeutic recommendations. Data collection, analysis, research and monetization are key drivers for
the development of the platform. However, the founders took great care that the patients would be the
sovereign net beneficiaries rather than the pawns of surveillance and exploitation (Zuboff 2019).
While APST is a single case study, we clearly see the merits of an in depth, dynamic, multi-stakeholder,
configuration analysis (cf. also Flyvbjerg 2006; Eisenhardt 1989). The research design affords to under-
stand the contingencies of ALS as an extreme case for care, which puts even the most highly functional
healthcare system to its limits in terms of complexity and time constraint; Providing the appropriate care
in a timely manner for patients with a quickly deteriorating condition, who need a highly diverse spectrum
of care and assistance, is a daunting challenge. As configuration analysis is geared towards identifying com-
plex pattern of actor constellations, future research should extend its’ use to further cases in order to iden-
tify, contrast and compare further patterns and dynamics.
Conclusion
Our study makes three main new contributions. Our first contribution is to apply configuration analysis to
an MSP. We have adapted and transferred Lyytinen and Damsgaard’s (2011) configuration analysis ap-
proach for the reconstruction and analysis of an emerging healthcare platform. Using an example from
coordinating complex care processes with respect to neurological patients, we demonstrate the productivity
The Configuration of an ALS Platform Case
Forty-First International Conference on Information Systems, India 2020 15
of the theoretical approach for our empirical research, extending previous accounts of MSPs in healthcare
(Yaraghi et al. 2015; Fürstenau et al. 2019; Otto and Jarke 2019) and extending IOS research to the field of
MSP (Robey et al. 2008). The dynamic configuration analysis provides insights into a rich case of individ-
ualized patient-centric coordination of care (transaction platform). It is the beginning of creating a digital
information platform to facilitate inter-professional cooperation in the provision of care, and a research
platform for evidenced-based research on the provision of ALS care, ALS medicine and ATD, as well as
algorithmic analysis of ALS patient data to improve diagnosis, prediction and care. Changes in the plat-
form’s configuration were the result of the close linkage between patient care and research, which was there
from the very beginning. At the same time, this close dovetailing creates the basis for further development
steps in the direction of higher patient value.
Our second contribution is in social entrepreneurship. We show how a platform uses economic mechanisms
to achieve social benefits (Saebi et al. 2019). In stark contrast to “platform capitalism” (Srnicek 2016), APST
is an example of social entrepreneurship, using technology and economic principles to improve the quality
of patient care. APST is initiated by two motivated founders combining public health and economic value
creation with the help of a digital platform to enable a two-sided value model (as proposed by Saebi et al.
2019). A strict data policy ensures that the patient data generated and collected on the platform are not
used nor monetized without the patients’ consent. Instead, patients are invited to donate their data or vol-
untarily participate in studies, aimed at improving medication and ATD. The case also sheds light on one
trajectory of a social entrepreneur’s business model development that could be helpful for future platform
founders: APST started with research grants, later income shifted towards transaction fees from providers
(multi-sided model), while finally today it combines research grants, transaction fees, and contract research
incomes in order to create social value. This approach, as it turns out, enabled the growth and scalability of
the APST platform within the confines of individualized care-complex neurological diseases.
From a practical perspective, highlighting the example of APST, we show how and under which conditions
platform innovation in health care delivery is possible. The platform-based case management focusses on
the optimal, customized care for individual patients. It aims at empowering the patients by providing in-
formation and creating transparency about care options. Moreover, it aims to facilitate feedback on the
quality of care, medication and equipment, in order to improve matching, inform learning and innovation
of the care providers and thereby increase benefits to the patient community. This case is a prime example
of how a multi-sided platform model can be used to achieve and coordinate care in a better way. It also
demonstrates the power of research platforms as an additional organizing vision for health care platforms.
In its configuration, it exemplifies a European model of patient-centric health care platforms. While APST
mitigates some of the shortcomings of the current ALS care system in Germany, it also sets an example of
how care could be organized within the organizational and regulatory structures of public health care. The
paper thus contributes at least one answer to the question of how inter-organizational configurations can
contribute to patient-centric innovation in healthcare management.
Conflict of interest: All authors declare that they have no conflict of interest.
References
ALS-Hilfe.org. 2020. “Fragen und Antworten: Informationen zur ALS,“ http://www.als-hilfe.org/fra-
gen_und_antworten.html (accessed 2020-04-29)
APST – Versorgungsnetzwerk. n.d. “Information für Medizinische Partner,” https://www.Ambulanzpart-
ner.de/teilnehmen/informationen-zur-teilnahme-fur-medizinische-partner/ (accessed 2019-05-01).
APST. 2020. “ALS App for People with ALS: Now Available for Smartphones and Tablets,”
https://www.ambulanzpartner.de/als-app-for-people-with-als-now-available-for-smartphones-and-
tablets/?lang=en (accessed 2020-05-02)
Alvesson, M., and Kärreman, D. 2007. “Constructing Mystery: Empirical Matters in Theory Develop-
ment,” Academy of Management Review (32:4), pp. 1265–1281.
Anderson, E. G. J., Parker, G. G., and Tan, B. 2014. “Platform Performance Investment in the Presence of
Network Externalities,” Information Systems Research (25:1), pp. 152–172.
The Configuration of an ALS Platform Case
Forty-First International Conference on Information Systems, India 2020 16
Bakker, M., Creemers, H., Schipper, K., Beelen, A., Grupstra, H., Nollet, F., and Abma, T. 2015. “Need and
Value of Case Management in Multidisciplinary ALS Care: A Qualitative Study on the Perspectives of
Patients, Spousal Caregivers and professionals,” Amyotrophic Lateral Sclerosis and Frontotemporal
Degeneration (16:3-4), pp. 180-186.
Baldwin, C. Y., and Woodward, C. J. 2009. “The Architecture of Platforms: A Unified View,” in Platforms,
Markets and Innovation, A. Gawer (ed.), Cheltenham, UK: Edward Elgar, pp. 19–39.
Ceccagnoli, M., Forman, C., Huang, P., and Wu, D. J. 2012. “Cocreation of Value in a Platform Ecosystem:
The Case of Enterprise Software,” MIS Quarterly (36:1), pp. 263–290.
Dacin, P.A., Dacin, M.T., and Matear, M. 2010. “Social Entrepreneurship: Why We Don’t Need a New
Theory and How We Move Forward from Here,” Academy of Management Perspectives (24:3), pp. 36-56.
Eisenhardt, K. M. 1989. “Building Theories from Case Study Research,” Academy of Management Review
(14:4), pp. 532–550.
Flyvbjerg, B. 2006. “Five Misunderstandings about Case-Study Research,” Qualitative Research Methods (12:2), 219–245.
Funke, A., Grehl, T., Großkreutz, J., Münch, C., Walter, B., Kettemann, D., Karnapp, C., Gajewski, N.,
Meyer, R., Maier, A., Gruhn, K.M., Prell, T., Kollewe, K., Abdulla, S. Kobeleva, X., Körner, S., Petri, S.,
and Meyer, T. 2015. “ Hilfsmittelversorgung bei der amyotrophen Lateralsklerose: Analyse aus 3 Jah-
ren Fallmanagement in einem internetunterstützten Versorgungsnetzwerk,“ Nervenarzt (86), pp. 1007-1017.
Funke A., Spittel S., Grehl, T., Grosskreutz, J., Kettemann, D., Petri, S., Weyen, U., Weydt, P., Dorst, J.,
Ludolph, A., Baum, P., Oberstadt, M., Jordan, B., Hermann, A., Wolf, J., Boentert, M., Walter, B.,
Gajewski, N., Maier, A., Münch, C., Meyer T. 2018. “Provision of Assistive Technology Devices among
People with ALS in Germany: A Platform-Case Management Approach, Amyotrophic Lateral Sclerosis
and Frontotemporal Degeneration (19:5-6), pp. 342-350.
Fürstenau, D., Auschra, C., Klein, S., and Gersch, M. 2019. “A Process Perspective on Platform Design and
Management: Evidence from a Digital Platform in Health Care,” Electronic Markets (29:4), pp. 581–596.
Gawer, A. 2014. “Bridging Differing Perspectives on Technological Platforms: Toward an Integrative
Framework,” Research Policy (43:7), pp. 1239–1249.
Gawer, A., and Cusumano, M. A. 2014. “Industry Platforms and Ecosystem Innovation,” Journal of Product
Innovation Management (31:3), pp. 417–433.
Güell, M. R., Antón, A., Rojas-García, R., Puy, C., and Pradas, J. 2013. “Comprehensive Care of Amyo-
trophic Lateral Sclerosis Patients: A Care Model,” Archivos de Bronconeumologia (49:12), pp. 529–533.
Hagiu, A., and Wright, J. 2015. “Multi-Sided Platforms” International Journal of Industrial Organization
(43:11), pp. 162-174.
Irwin, G., Topdjian, J., and Kaura, A. 2014. “Putting an I in Healthcare,” Strategy+Business (71), pp. 1–8.
Lincoln, Y. S., and Guba, E. G. 1985. Naturalistic Inquiry, Beverly Hills: Sage.
Locke, K., Golden-Biddle, K., and Feldman, M. S. 2008. “Perspective—Making Doubt Generative: Re-
thinking the Role of Doubt in the Research Process,” Organization Science (19:6), pp. 907–918.
Logue, D.; and Grimes, M. (2019): “Platforms for the People: Enabling Civic Crowdfunding through the
Cultivation of Institutional Infrastructure,” Strategic Management Journal (in press).
Longinetti, E., and Fang, F. 2019. “Epidemiology of Amyotrophic Lateral Sclerosis: An Update of Recent
Literature,” Current Opinion Neurology (32:5), pp. 771-776.
Lyytinen, K., and Damsgaard, J. 2011. “Inter-Organizational Information Systems Adoption – A Configu-
ration Analysis Approach,” European Journal of Information Systems (20:5), pp. 496–509.
Mayring, P. 2000. “Qualitative Content Analysis,” Forum: Qualitative Social Research, 1(2), Art. 20.
http://www.qualitative-research.net/index.php/fqs/article/download/1089/2384 (accessed 2019-05-01).
Merl, T., Stöger, U. 2014. “Kooperative Dienstleistungssysteme erfordern Interaktionsarbeit,“ In Bieber, D.,
Geiger, M. (eds.). Personenbezogene Dienstleistungen im Kontext komplexer Wertschöpfung. Springer VS: Berlin.
Meyer, T., and Münch, C. 2016. “‘APST‚ – digital unterstütztes Versorgungsmanagement,” NeuroTransmit-
ter (27:Sonderheft 1), pp. 33–38.
Meyer, T., Grosskreutz, J., Münch, C., Maier, A., Meyer, R., d. Kettemann, and Grehl, T. 2013. “APST –
multiprofessionelles und internet-unterstütztes Versorgungsmanagement bei der ALS,” Klinische Neu-
rophysiologie (44:2), pp. 159–166.
Meyer, T., Kettemann, D., … , and Spittel, S. 2020. “Symptomatic Pharmacotherapy in ALS: Data Analysis
from a Platform-Based Medication Management Programme,” Journal of Neurology, Neurosurgery,
and Psychiatry (91:7), pp. 783–785.
The Configuration of an ALS Platform Case
Forty-First International Conference on Information Systems, India 2020 17
Meyer, T., Funke, A., Münch, C., Kettemann, D., Maier, A., Walter, B., Thomas, A., and Spittel, S. 2019.
“Real World Experience of Patients with Amyotrophic Lateral Sclerosis (ALS) in the Treatment of
Spasticity Using Tetrahydrocannabinol:cannabidiol (THC:CBD),” BMC Neurology (19:1), pp. 1-13.
Meyer, R., Spittel, S., Steinfurth, L., Funke, A., Kettemann, D., Münch, C., Meyer, T., and Maier, A. 2018.
“Patient-Reported Outcome of Physical Therapy in Amyotrophic Lateral Sclerosis: Observational
Online Study,” JMIR Rehabilitation and Assististive Technologies (5:2), pp. e10099.
Mitchell, J. D. 2000. “Guidelines in Motor Neurone Disease (MND)/Amyotrophic Lateral Sclerosis (ALS)
- From Diagnosis to Patient Care,” Journal of Neurology (247 Suppl 6), VI/7-12.
Muzellec, L., Ronteau, S., and Lambkin, M. 2015. “Two-Sided Internet Platforms: A Business Model
Lifecycle Perspective,” Industrial Marketing Management (45:1), pp. 139–150.
Nagasaka, T., and Takiyama, Y. 2015. “Home- and Community-based Medical Care for Neurodegenerative
diseases: ALS as an illustration,” in Neurodegenerative Disorders as Systemic Diseases, K. Wada
(ed.), Tokyo: Springer, pp. 237–275.
Otto, B., and Jarke, M. 2019. “Designing a Multi-Sided Data Platform: Findings from the International
Data Spaces Case,” Electronic Markets (29:4), pp. 561–580.
Parker, G., van Alstyne, M., and Choudary, S. P. 2016. Platform Revolution: How Networked Markets Are
Transforming the Economy and How to Make Them Work for You, New York, NY: W.W. Norton and Company.
Parker, G., Van Alstyne, M., and Jiang, X. 2017. “Platform Ecosystems: How Developers Invert the Firm,”
MIS Quarterly (41:1), pp. 255–266.
Raivio, Y., and Luukkainen, S. 2011. “Mobile Networks as a Two-Sided Platform - Case Open Telco,” Jour-
nal of Theoretical and Applied Electronic Commerce Research (6:2), pp. 77–89.
Robey, D., Im, G., & Wareham, J. D. (2008). ”Theoretical Foundations of Empirical Research on Interor-
ganizational Systems: Assessing Past Contributions and Guiding Future Directions,” Journal of the
Association for Information Systems (9:9), pp. 497–518.
Rochet, J.-C., and Tirole, J. 2003. “Platform Competition in Two-Sided Markets,” Journal of the Euro-
pean Economic Association (1:4), pp. 990–1029.
Saebi, T., Foss, N. J., and Linder, S. 2019. “Social Entrepreneurship Research: Past Achievements and Fu-
ture Promises,” Journal of Management (45:1), pp. 70–95.
Schreier, M. 2014. Qualitative Content Analysis. In U. Flick (Ed.), The SAGE Handbook of Qualitative
Data Analysis (pp. 170–183). London: Sage.
Seitzer, F., Kahrass, H., Neitzke, G., and Strech, D. 2016. “The Full Spectrum of Ethical Issues in the Care
of Patients with ALS: A Systematic Qualitative Review,” Journal of Neurology (263:2), pp. 201–209.
Song, P., Xue, L., Rai, A., and Zhang, C. 2018. “The Ecosystem of Software Platform: A Study of Asymmetric
Cross-Side Network Effects and Platform Governance,” MIS Quarterly (42:1), pp. 121-142.
Soriani, M.-H., and Desnuelle, C. 2017. “Care Management in Amyotrophic Lateral Sclerosis,” Revue Neu-
rologique (173:5), pp. 288–299.
Srnicek, N. 2016. Platform Capitalism, Cambridge: Polity.
Strauss, A. L., and Corbin, J. M. 1990. Basics of Qualitative Research: Grounded Theory Procedures and
Techniques, Newbury Park, CA.: SAGE Publications.
Vassilakopoulou, P., Grisot, M., Jensen, T.B., Sellberg, N., Eltes, J., Thorseng, A.A., Aanestad, M. 2017.
Building National eHealth Platforms: the Challenge of Inclusiveness. ICIS 2017 Proceedings.
van Alstyne, M. W., Parker, G. G., and Choudary, S. P. 2016. “Pipelines, Platforms, and the New Rules of
Strategy,” Harvard Business Review (94:4), pp. 54–62.
Yaraghi, N., Du, A. Y., Sharman, R., Gopal, R. D., and Ramesh, R. 2015. “Health Information Exchange as
a Multisided Platform: Adoption, Usage, and Practice Involvement in Service Co-Production,” Infor-
mation Systems Research (26:1), pp. 1–18.
Yoo, Y., Henfridsson, O., Lyytinen, K. 2010. “The New Organizing Logic of Digital Innovation: An Agenda
for Information Systems Research,” Information Systems Research (21:4), pp. 724-735.
Yin, R. K. 2018. Case Study Research: Design and Methods, Los Angeles: Sage.
Zenooz, A.M., Fox, J. (2019) How New Health Care Platforms Will Improve Patient Care. Harvard Busi-
ness Review (10:1), pp. 1-8.
Zuboff, S. (2019). The Age of Surveillance Capitalism: The Fight for a Human Future at the New Fron-
tier of Power (First edition). New York: PublicAffair.
