Creating Collaborative Innovation Networks(COINs) to Reduce Infant Mortality
Peter A. Gloor1, Francesca Grippa2
1
MIT Sloan Center for Collective Intelligence, 245 First Street, Cambridge, MA 02142.
pgloor@mit.edu
2

Northeastern University, 360 Huntington Ave-101 Belvidere Street, Boston, MA, 02115.
f.grippa@northeastern.edu

Abstract This case study illustrates the growth process of a collaborative
innovation network in healthcare. It tracks e-mail communication of COIN
members through a method we call “virtual mirroring”, and measures the online
perception of the topics of the COIN by coolhunting on social media such as
Twitter and blogs. It also describes how the COIN members through“coolfarming” self-organize and identify new sub-topics for their work. In
particular, the paper describes the growth process of the US Department of Healthand Human Services Infant Mortality CoIIN (Collaborative Improvement andInnovation Network), applying both improvement and innovation concepts to
reducing infant mortality among disadvantaged families in the US.

1 Introduction
Collaborative Innovation Networks (COINs) are self-organizing groups of
intrinsically motivated people who get together to create something radically new(Gloor 2006). While they occasionally meet face-to-face, they mostly collaborate
over the Internet to innovate and change the world. In this case study we illustrate
the COIN creation and growth process by studying the communication among
COIN team members inside the organization through e-mail, and outside theorganization by examining social media. In particular, we demonstrate the use of
e-mail based social network analysis and virtual mirroring to measure and support
the growth of the IM-CoIIN project of the Maternal and Child Health Bureau(MCHB) of the US Health Resource Administration (HRSA). “IM-CoIIN” stands
for “Infant Mortality reduction Collaborative Improvement and Innovation
Network”. It is defined as “a multiyear national movement engaging federal, stateand local leaders, public and private agencies, professionals, and communities to
employ quality improvement, innovation and collaborative learning to reduce
infant mortality and improve birth outcomes”. The project was started in 2012,2

and will be completed in 2017 and is active in all states of the US. The CoIIN as
envisioned by the MCHB Associate Administrator combines both improvement
and innovation concepts. For the improvement part IM-CoIIN applies the IHI
breakthrough model (IHI2003), which brings together healthcare practitioners to
one to two day learning sessions, where they share their experiences to learn fromeach other and improve their own healthcare processes. For innovation, IM-CoIIN
is based on the COIN concept, trying to nurture breakthrough innovation incollaborative innovation networks.
As part of the IM-CoIIN, six sub-CoIINs were created: the first CoIIN has beenworking on improving safe sleep practices for babies. The second CoIIN is trying
to get smoking mothers to stop or at least reduce smoking before, during and after
pregnancy. The third CoIIN focuses on improving women’s health before, afterand in between pregnancies. The fourth CoIIN works to improve social
determinants of health (SDOH) and equity in birth outcomes. The fifth CoIIN istrying to prevent births before 39 weeks. The sixth CoIIN works to increase thedelivery of higher risk infants and mothers at appropriate level facilities.
In the remainder of this paper, we will first describe the e-mail based virtual
mirroring process of the entire IM-CoIIN, then we will describe how we didcoolhunting for SDOH related topics on online social media to get the innovation
aspect of this sub-CoIIN started, and finally describe how we brought together
small groups of innovators to coolfarming workshops to create new COINs around
SDOH.

2. E-Mail Based Virtual Mirroring
Our first step was to apply the virtual mirroring process which promotes selfreflection and ultimately impacts organizational performance (Gloor et al. 2017b;
Gloor et al 2010). Virtual mirroring involves measuring communication patterns
and mirroring the resulting social network variables back to the individual. In thisstudy we conducted virtual mirroring sessions of 7 key members of the SDOH
community based on their e-mail archives from November 2014 to March 2016.
Similarly to feedback or learning sessions, which are commonly used in industrial
and social psychology studies (Ramos 2007), our virtual mirroring process is a
way to promote organizational awareness and change. In a recent study, Gesell etal. (2013) presented social network analysis results to organizational leaders to
support change management programs. The healthcare sector is also becoming
increasingly interested in measuring information flows and team dynamics among
physicians, nurses and other healthcare professionals. Grippa and colleagues(2012) involved three interdisciplinary care delivery teams in similar monthly
learning sessions focused on social network-based results, which resulted in an
increased awareness that informed decision making. Very recently, Gloor andcolleagues (2017) involved leaders of 26 large accounts in monthly virtual

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mirroring sessions, where the communication characteristics of the teams working
with clients were shared and discussed in plenary and individual sessions. In theirstudy they measured the structure of the communication network, looking at who
is interacting with whom, the average complexity of the vocabulary used, as wellas the responsiveness of employees to customers’ e-mails.
Another recent study (Gloor et al 2017b) found that customer satisfaction
increases after employees are involved in learning sessions to reflect on their own
communication behaviors. In their study, Gloor, Colladon, Giacomelli, Saran andGrippa (2017) correlated employees’ communication patterns with customer
satisfaction and found that responsiveness, low oscillation of betweenness
centrality, and complexity of communication are good predictors of customer
satisfaction.

2.1 Virtual Mirroring: Dimensions and Metrics
The process of virtual mirroring relies on e-mail based social network analysis.
We provided feedback to the IM-CoIIN community presenting them with results
based on three dimensions: degree of connectivity, content sharing and degree ofinteractivity (Gloor 2006, p. 175). Connectivity refers to how well connectedindividuals are within their social network using indicators such as betweenness
centrality and degree centrality (Everett & Borgatti, 2005; Wasserman & Faust,
1994). The second dimension, degree of sharing, describes the complexity of thelanguage used based on the average difficulty of the words in each e-mail.
Complexity is calculated as the likelihood distribution of words within an e-mailtext, i.e. the probability of each word of a dictionary to appear in the text
(Brönnimann 2014). The algorithm used to calculate complexity measures how
common a word is in an individual message compared to the word’s occurrence inthe overall text collection; the more relatively rare words a message uses, thehigher is the message’s complexity. Beside complexity, we also extracted asentiment indicator based on a multi-lingual classifier that uses a machine learning
method trained on large datasets from Twitter (Brönnimann, 2014). Finally, we
included emotionality which is measured as standard deviation of sentiment: themore fluctuations in positivity and negativity an e-mail has, the more emotional itis.
The third dimension of our virtual mirroring model, interactivity, includes
metrics such as contribution index and average response time (ART) of an actor to
respond to a message. Contribution index is calculated as the frequency of sending
and receiving messages: it is +1 if somebody only sends messages and does notreceive any; it is –1 if somebody only receives messages; it is 0, if somebody
sends and receives the same number of messages. The average response time(ART) indicates how fast an individual or a group responds to e-mails, offeringsome insights into the degree of “respect” and “passion” within the community.

4

We also distinguished between “alter ART” and “ego ART”. These metrics arepart of the six honest signals of collaboration described in (Gloor 2017).
In other studies, we have been able to demonstrate that the faster other people
respond to a person, the more they respect this person. For example, in a recent
study on managerial turnover and online communication behavior (Gloor et al2017a), turnover is associated to e-mail responsiveness, mainly in terms of nudges
shared with colleagues: the more frequently managers interact with others, themore central they and the more nudges they send and receive, the less likely they
are to quit. This could be possibly explained with an increase in respect andpolitical power that managers have acquired over time. In the same study, Gloor etal (2017a) found that language complexity was a good predictor of managerial
turnover: managers who stay in their job tend to express themselves in a lessemotional way, switching to a more emotional content over time as they approach
the time they quit. These results are aligned with Pennebaker’s research (2001 and2011) indicating that life-changing events influence the use of both positive andnegative emotion words.
To measure collaboration among the IM-CoIIN members, we collected all IMCoIIN related e-mails of seven key participants of the IM-CoIIN from September
2014 to March 2016 using the software tool Condor (Gloor 2017). We had shownin earlier work that having 14% to 18% of the mailboxes of a community wasadequate to capture 90% of their e-mail traffic, thanks to community members
cc’ing each other (Zilli et al. 2006). Through this virtual mirror of seven key
members of the community based on their e-mail archives we were able to give
feedback to the entire community and come up with recommendations for
improved collaboration.

2.2 Virtual Mirroring Applied to the DSOH community
Figure 1 illustrates the overall e-mail activity of the community over the entire
time period from September 2014 to March 2016. The community sent up to 3000
messages on the most active days, with an average of 500 messages per day, theweekends are clearly visible with much less traffic. The periods of intense
communication and high activity are recognizable by slopes in the evolution ofgroup betweenness centrality and high-density structure of the community. The
spikes indicate the time right before a learning session, when the organization
running the community (NICHQ, a Boston-based non-profit) reached out to healthofficials and administrators in the 52 US States inviting them to the learning
sessions.

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5

Fig. 1. Activity of e-mail from Sept 2014 to March 2016
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Figure 2 illustrates the average speed with which everybody within thecommunity answers to e-mails sent by the seven owners of the mailboxes wecollected. In this analysis, we found that alter ART started at an alreadyrespectable 25 hours, and has been decreasing to a quite fast 17 hours on average
until an e-mail was answered. This means that mutual respect in this community
has been going up clearly over the observation period of 18 months, a very
positive sign of organizational health.

Fig. 2. Average response time of others to the mailbox owners (Alter ART)

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Figure 3 illustrates the change of ego ART, which is defined as the speed withwhich the owner of a mailbox answers to everybody else (Gloor 2017). The speedwith which somebody answers to everybody else’s e-mails is a proxy for thepassion of the person. In this community, ego ART starts at below 20 hours on
average, and stays like that for the entire observation period. While we would
have wished for an even stronger decrease in egoART, what we can say is that
passion is high to start with, and stays like that over the 18 months observation
period.
Fig. 3 Average response time of mailbox owners to all others (Ego ART)

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Figure 4 illustrates the number of new contacts per person per month. A newcontact is only counted if it has at least one e-mail exchange, this means that if
person A sends an e-mail to person B, B needs to respond to it. This exchange isincluded, if person B appears for the first time in the analysis of the particularmonth. The number of new e-mail contacts is a good proxy for the growth
dynamics of a community. Figure 4 tells us that growth per month more thandoubled from on average 250 new community members to on average over 600
new community members per month at the end of the observation period. It
illustrates the healthy growth of IM-CoIIN, which is confirmed in the real world,
where participation in the learning sessions has been steadily going up.

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Fig. 4. Number of new e-mail contacts per month

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Figure 5 shows the temporal social surface, which is a visual way to explore thecreative capabilities of a community. The x-axis of figure 5 shows all actors
involved, the y-axis shows time, from September 2014 at top left, to March 2016,at the bottom center. The z-axis shows betweenness centrality (Wassermann &Faust 1994) of each actor. The spikes at the rear of figure 5 display that a few
people are always more central than the rest, exhibiting strong leadership. The
growth pattern of figure 4 is again confirmed, in that the plateau, which shows thesomewhat active participants, is growing over time. But we also see that thecreativity of the entire community is relatively low, as the entire impression of
figure 5 is one of a “calm sea”, and not one of a “stormy ocean”, which would
indicate a lot of rotating leadership, which is a strong predictor of a creative
community. The impression arising from this analysis is one of steady
improvement, and not of radical innovation.

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Fig. 5. Temporal Social Surface of combined mailboxes, a visualization of team creativity

Figure 6 illustrates the social network structure of the entire e-mail network.
Each dot is a person, each connecting line means that two people have at leastexchanged one e-mail. The coloring by organization shows that the largest groupof participants, not surprisingly, is from the US government from HRSA, followedby members of the non-profit organizations “March of Dimes” and NICHQ. The
most central people measured by betweenness centrality in Figure 6 are the project
coordinator from HRSA, as well as the project director from NICHQ.

9Fig. 6. E-Mail social network of entire community (top 4000 users by communication frequency
shown)

Figure 7 shows the sentiment and activity over the observation period. We findthat the sentiment is strongly positive, from 0.6 to 0.73. Sentiment of 0.5 isdefined as neutral. This tells the observer that IM-CoIIN participants are very niceto each other, use positive language and give a lot of praise to each other. At thesame time, the oscillation in sentiment also indicates that occasionally they are not
shy of speaking out if something is not going as it should, which is a sign of anopen and honest communication.

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Fig. 7. Sentiment and Activity of e-mail from Sept 2014 to March 2016

Figure 8 shows the word usage over time of the most frequently used words inthe e-mails over the 18-month observation period. “Call” is the most popular
word, used with increasing frequency over time, which tells us that setting up calls
among participants is the most important activity of the IM-CoIIN. Somewhat
surprising, the use of the word “infant” is going down over time. “Learning” ispeaking beginning of 2015, when a face-to-face learning session was organized.
The term “SDOH” (social determinants of health) is becoming somewhat more
popular, as a COIN around this concept is developing. Overall, it emerges apicture of a community focused mostly on execution, indicated through usage ofthe term “call”, surfaces, with a smaller focus on innovation, indicated through theterm “SDOH”.

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Fig. 8. Key concepts over time

To resume this analysis, through analyzing the e-mail communication of the IMCoIIN community, we have been able to gain deep insights into the innerworkings and knowledge flow of the community. We find that the community is
showing healthy growth, and community members are treating each other with
passion and respect. However, we also find that the community is focusing mostly
on improvement, with the innovation component of the CoIIN somewhat lagging
behind.

3 SDOH Coolhunting
To address the innovation aspect in IM-CoIIN, project leadership decided to set
up an innovation COIN (with one “I”) focused on social determinants of health(SDOH). As part of helping to get the SDOH COIN started, we conducted a
coolhunting on Twitter and on the Web to identify the key terms around social
determinants of health, and to collect innovative new ideas. Coolhunting is basedon a degree-of-separation search that allows to quickly find the most influential
nodes in a relevant subset of the Web. Combining multiple datasets, eachcontaining the degree of-separation Web sites collected through querying a searchengine for the name of one search term (SDOH in our case), allowed us to find themost central node in a group of stars (Gloor 2006).
For the coolhunting, we collected key words from SDOH experts who are partof the IM-CoIIN. Topics they identified were to “reduce poverty”, increase the“graduation rate” among disadvantaged teenagers, increase the “minimum wage”,
and increase general “happiness”. Figure 9 shows the results of our coolhunting
using Condor for these search terms on Twitter (Gloor, 2017). The Twitter12

network picture in Condor measures the importance of search terms through theirbetweenness centrality in the bipartite graph. Each node except the search term isa Twitter user, each connecting line means that the user is tweeting about the term,or is mentioned in a tweet by another user, or is retweeting somebody else’s tweet.
The main conclusion in figure 9 is that “minimum wage” is the most importantterm, while SDOH is rarely tweeted about, as shown in the pink little cluster at thevery right of the picture, and the low betweenness centrality in the comparative
bar chart.

Fig. 9. Twitter Coolhunting Results for SDOH

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13

Figure 10 shows the word cloud illustrating the key attributes of the four main
search terms. The green color of words indicates that they are used in positive
context, the red words are using in negative context. Health and happiness are themost important, and most positive words in our Twitter search, minimum wage
and poverty the most important negative words.
Fig. 10. Coolhunting Results for all SDOH related terms on Twitter

Figure 11 shows the occurrence of the search terms on the World map.
Minimum wage is a big topic in both North America and in Europe, however
graduation is not an issue in Europe, where education is basically free. The Irish
union SIPTU comes up in Europe, as it is talking about a raise in minimum wagein Ireland considered insufficient by SIPTU. In Asia the “harvesting happiness”
talk radio show of host Lisa Cypers Kamen is mentioned.

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Fig. 11. Global distribution of Coolhunting Results for SDOH on Twitter

Figure 12 illustrates an identical search done on the Web for the same searchterms. Minimum wage is again the biggest topic, but social determinants of healthare more popular on the Web than they are on Twitter. This is most likely because
SDOH is a relatively complex topic, which is better explained in blog posts thanin the 140 characters of Twitter. We can also identify the most important
newsfeeds about these topics, such as PBS and NPR, and the Robert WoodJohnson Foundation.

15
Fig. 12. Key search terms and Web sites about SDOH on the Web         




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!Figure 13 shows the most important attributes related to the search terms. The
context seems more positive, as more words are in green. The words are also morefactual and less emotional, such as “education”, “news”, “resources”, and“information”. What stands out is the “state of Texas”.

16
Fig. 13. Coolhunting results for all SDOH related terms on the Web

Based on the insights from this coolhunting, it was decided to invite a small
group of IM-CoIIN members passionate about SDOH to coolfarming workshops,
to meet for half a day before a learning session and brainstorm innovative ideas tocreate new COINs.

4 Creating New COINs
We conducted two half-day workshops with the goal to create new COINs to
reduce infant mortality, tackling social determinants of health as a new initiative.
The goal was to reach out to innovative people with far out ideas, who wereinterested in developing them further and recruit a team to work with turning theirideas into a first prototype. Figure 14 describes the full COIN creation process(Gloor 2017b). At the beginning a small group of enthusiasts gets together for an
initial brainstorming workshop, where the topics of the COIN are defined. Such an
initial design workshop to create a new COIN follows a six-step process. In thefirst step workshop participants are familiarized with key COIN concepts such as
rotating leadership and balanced contribution. In the second step, inspirational
leaders - who have solved similar problems in other areas - are invited to present
their approach and get the creative thinking of participants going. During step
three of the COIN creation process, participants list and select the topics theywould like to turn into products of COINs. Step four consists of the creation ofsmall groups around each topic for a COIN, working on developing a vision for
their COIN. Once they have defined the vision, step five requires participants to
map out an action plan. In the final, sixth step COIN members do a “waggle
dance”, developing a marketing plan to recruit additional outside COIN members.

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Fig. 14. Coolfarming and COIN Creation Process

Not all topics at the workshop will become successful COINs. COINs with
passionate leaders will recruit more members for their COIN, and do an in-depth
coolhunting to learn what’s already out there and available. They will set up
regular meetings, do more coolhunting, set up a Website, advertise their COIN,
and grow the community. As the community grows, other communities getcreated as a product of the COINs members’ “waggle dance”. Gloor (2006) foundthat through the application of social analysis, it is possible to recognize two typesof these networks: Collaborative Interest Network (CIN) and Collaborative
Learning Networks (CLN). Members of a CLN share a common interest,
knowledge and a practice, being motivated to join the network by a desire to learn
from each other. Members of CIN have similar interests, without necessarily
working together. Both CLN and CIN tend to be characterized by specific network
properties, such as lower density and high group centrality, since external
members are mainly connected to core members, but not among themselves.
Collaborative Interest Networks and Collaborative Learning Networks are
created through the same waggle dance and spreading of “attraction pheromones”
that is at the basis of the creation of COINs. To continue with the metaphor,“Coolhunter bees mark the location of the new hive by spraying it with attraction
pheromone, such that the flying swarm of bees will find their goal irresistible assoon as they get close. At the same time, the coolhunting bees will direct theflying swarm by rapidly flying back and forth in the midst of the flying cloud ofbees” (Gloor, Margolis and Dellal, 2012, p.12).

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5 Discussion and Conclusion
In this paper we have illustrated the use of virtual mirroring, coolhunting, andcoolfarming to create COINs. While our case study focused on the HRSA IMCoIIN to reduce infant mortality in the US, this process is widely applicable. It has
been applied in other healthcare environments, for instance for patients of chronic
diseases as described in (Gloor 2017b), but it has much wider applicability.
COINs offer huge potential for any organization not afraid of creating anenvironment supportive of disruptive innovation.
The two workshops conducted at IM-CoIIN learning sessions led to thecreation of a vibrant COIN on the impact of early childhood trauma inspired by
the ACES (Adverse Childhood Experiences) study. Three more COINs, on
Babybox for safe sleep (giving poor mothers a cushioned cardboard box as a babybed), doulas (women trained to assist mothers at childbirth), and “Care Bundles”(groups of services provided to mothers on welfare) are in the process of being
formed.
Through the application of a virtual mirroring process, we offered community
members the opportunity to reflect on their communication styles. A longitudinal
analysis of the e-mail communication patterns of the community “Social
Determinants of Health” indicated an exponential growth in only a few months(150% more members). Over 16 months, there was an increase in both the degreeof respect (reduced average response time) and passion (average response time of
20 hours). By measuring sentiment, emotionality and complexity of the content
exchanged via e-mail, we noticed that the community exchanged a creative,
emotional, though positive response.
The application of the virtual mirroring to the SDOH community is based on
extensive previous studies demonstrating how promoting self-awareness ofpeople’s communication style has the potential to induce behavior change andincrease organizational effectiveness. This is aligned with the results of several
studies on the effect of feedback sessions on individual, team and organizational
performance (Kluger and DeNisi 1996; Barr and Conlon 1994; Ivancevich andMcMahon 1982), which indicated that providing employees with the opportunity
to reflect on their performance could enable positive behavioral change. Virtual
mirroring sessions take this approach to a deeper level, by providing monthly
description of individuals’ communication patterns. This continuous mirroringprocess lets individuals receive timely and practical information about theircommunication patterns that can be used to improve their individual andcommunity performance.
Besides reflecting on their own online communication, participants were
offered the opportunity to visualize topics that were attracting the interest of theswarm. Through the Coolhunting process, community leaders were able torecognize the importance of themes that impacted infant mortality, such as
reducing poverty, increasing the graduation rate among teenagers, increasing theminimum wage, and promoting general happiness. The process helped community

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leaders to identify important terms used by online users in various parts of theworld, such as minimum wage and poverty. Creating new COINs and coolhunting
for trends on the Web represent important methods to help design quality
improvement initiatives. Similarly, virtual mirroring gave participants the ability
to recognize the impact of their communication behavior, and to observe how theirconnections grew across and beyond the community boundaries.

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