Smart Community Health: A Comprehensive Community Resource

Recommendation Platform

Mehdi Mekni

and David Haynes

Department of Computer Science & Information Technology, St. Cloud State University, St. Cloud, MN, U.S.A.

Institute for Health Informatics, University of Minnesota, Minneapolis, MN, U.S.A.

Keywords:

Social Determinants of Health, Informatics, Mobile Application Development, Software Engineering.

Abstract:

Health disparities and inequities are explained by the conditions of places where people live, learn, work and

play. In fact, the health of an individual is partially related to access and quality of health care and mainly

associated to his behaviours, socioeconomic conditions and other community related factors that are often

challenging to address by health care organizations. To meet the need for information about local social

services organizations and the ability to offer resource referrals, a number of platforms have been proposed

that provide electronic social resource directories and facilitate referrals to social service agencies. However,

these platforms show limitations with regards to their dependancy to health care organizations, application

portability, service availability, and user engaging interactions such as tracking, monitoring and notiﬁcation.

Moreover, existing social resource referral platforms suffer from a fragmentation of services and a discon-

nection between individuals in need and service providers. In this paper, we introduce Smart Community

Health (SCH), a novel independent platform that prioritizes connecting people in need with local community

resources. SCH is a full-service, end-to-end community service provider recommendation platform designed

to help address pressing social, environmental, and health needs within our communities. The platform is

composed of a mobile application for individuals looking for services and a web application dashboard for the

management of community service providers and health care organizations.

1 INTRODUCTION

The Social Determinants of Health (SDOH), deﬁned

as conditions of places where people live, learn, work

and play, are known to affect health. SDOH explain,

in part, why health disparities and health inequities

exist (McGowan et al., 2019). In fact, only 20 percent

of what inﬂuences the health of a group of patients

is related to access and quality of health care. The

other 80 percent—commonly known as the social de-

terminants of health—is found in patients’ behaviors,

socioeconomic conditions and other factors that are

often challenging to address in clinical visits (Smith

et al., 2019). For patients and families with complex

health issues (e.g., chronic disease, substance abuse,

mental health issues), effectively managing care is in-

creasingly complex (Koh et al., 2011).

Racial and ethnic minorities—populations who

are more likely to be poor, have lower educational lev-

els, or both—are fundamentally at greater risk of ill

health than their non-minority, non-poor, better edu-

cated peers (Smith et al., 2007). Multiple factors, both

within and outside the health care delivery system,

probably explain these disparities. Health care and so-

cial factors associated with such disparities relate di-

rectly to access to care, and access to care is important

because it is believed to lead to better health (Lurie

and Dubowitz, 2007). It is widely acknowledged that

addressing social risk factors is crucial when comes

the time to improve care quality and reduce costs, par-

ticularly for low-income patients.

The health care sector’s interest in addressing pa-

tients’ social and economic needs has grown dra-

matically over the past few years (Cartier et al.,

2019). For example, health care organizations are

interested in diminishing food insecurity to im-

prove outcomes for patients with diabetes and other

nutrition-related chronic diseases (Gundersen and Zil-

iak, 2015). Moreover, they are showing curiosity

in reducing housing insecurity and homelessness to

lower health care utilization among high-frequency

users of emergency health care services (Kushel et al.,

2006). In addition, they are engaging in improving

access to transportation as a way to reduce no-show

614

Mekni, M. and Haynes, D.

Smart Community Health: A Comprehensive Community Resource Recommendation Platform.

DOI: 10.5220/0009118306140624

In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 5: HEALTHINF, pages 614-624

ISBN: 978-989-758-398-8; ISSN: 2184-4305

rates and to improve specialty care access (Molfenter,

2013).

Health care organizations are also particularly in-

terested in referring their patients to local community-

based social service providers that can assist with

non-medical needs (Cartier et al., 2019).

For example, health care staff may want to refer

patients to food banks, beneﬁts enrolment programs,

emergency housing services, or multi-need social ser-

vice agencies, depending on the patients’ social risks.

The health care sector have traditionally relied on in-

formal approaches such as hard-copy or electronic

lists of local or community service providers or the

experiential knowledge of social or community health

workers to determine where to refer patients for non-

medical needs. Community service providers’ listings

are rarely kept up-to-date and are not always available

organization-wide. Furthermore, ad hoc approaches

do not enable efﬁcient tracking of referral outcomes,

which is increasingly a need as health care organiza-

tions seek to systematically address patients’ social

risk factors and assess the impacts of these activities.

As health care organizations’ interest in addressing

patients’ social risks has grown however, many have

found these informal approaches insufﬁcient and in-

efﬁcient to effectively facilitate systematic social risk

referrals.

To meet the health care sector’s need for infor-

mation about local social services organizations and

the ability to make electronic referrals, a number

of new technology platforms that provide electronic

community resource directories and facilitate refer-

rals to social service agencies. However, these tech-

nology platforms show several critical limitations.

First, these platforms use web technology and do not

use the valuable advantages of mobile applications

(Han Rebekah Wong, 2012). These advantages in-

clude a better response time, a better service avail-

ability (off-line and on-line), a full exploitation of the

mobile device resources (i.e. camera and localization

services). Moreover, mobile applications enable push

notiﬁcations, instant updates and interactive engage-

ment to name a few. Second, these platforms rely on

key words or labels to search social service providers

directory ignoring two key factors: needs and loca-

tions. The social service referrals suggested by exist-

ing technology platforms suffer from a fragmentation

of services and a disconnect between individuals in

need and service providers. Finally, the coordination

between health care organizations or social services

agencies in one side and the patient in the other side

is systematically not supported in existing service re-

source referral platforms.

In this paper, we present Smart Community

Health (SCH), an end-to-end platform that exists out-

side the domain of any organization. SCH prioritizes

connecting people in need with local community re-

sources. Smart Community Health is a full-service,

end-to-end community service provider recommen-

dation platform designed to help address pressing so-

cial, environmental, and health needs within our com-

munities.

The paper is organized as follows. In Section 2,

we provide an overview of existing resource referral

systems. We highlight our motivations to use mo-

bile application technology and more precisely mo-

bile applications over web-based applications to em-

phasize the portability of our platform. We also of-

fer a comprehensive technical discussion of the intro-

duced existing resource referral systems from a soft-

ware functional and non-functional requirements per-

spective. Next, in Section 3, we detail the requirement

engineering, the software architecture along with an

overview of the two main components of our Smart

Community Health platform: the mobile application

and the web application dashboard. Finally, in Sec-

tion 4, we conclude this paper with a synthesis of the

main contributions and we share the key elements of

our future work.

2 RELATED WORK

In this section, we ﬁrst provide a short overview on

existing local resource referral platforms. Second, we

highlight our motivations behind choosing mobile ap-

plication development over web technology. Finally,

we provide a discussion that summarizes the main

ﬁndings and outline the key functionalities that are

needed in a comprehensive, independent, end-to-end

community resource recommendation platform.

2.1 Overview on Community Resource

Referral Systems

Nine platforms currently dominate the ﬁeld of com-

munity resource referral services; Aunt Bertha (Aunt,

2019), CharityTracker (Charity, 2019), CrossTx

(Cross, 2019), Healthify (Healthify, 2019), NowPow

(Now, 2019), One Degree (One Degree, 2019), Pieces

Iris (Pieces Iris, 2019), TAVConnect (TAVHealth)

(TAVHealth, 2019) and Unite Us (Unite Us, 2019).

Cartier et al. studied the existing resource referral

technology platforms and provided a comprehensive

guide for health care organizations (Cartier et al.,

2019). Authors in (Cartier et al., 2019) have iden-

tiﬁed four groups of such technology platforms; (1)

Smart Community Health: A Comprehensive Community Resource Recommendation Platform

615

Platforms designed for health care-centred social ser-

vice referrals; (2) Platforms designed for health care-

coordination; (3) Platforms designed for individual

social service referrals; and (4) Platforms designed

for health care professionals.

Healthify, NowPow, and Pieces Iris were devel-

oped speciﬁcally for health care sector users for

the purpose of fostering referrals to social services

organizations as part of efforts to improve health

by addressing patients’ social needs. As a result,

they have a strong focus on providing comprehen-

sive community-wide resource directories and refer-

ral management. CrossTx and TAVConnect were also

originally developed speciﬁcally for health care users

but with a greater focus on care coordination and less

on the resource directory, though TAV- Connect has

recently shifted its focus to become a tool primarily

for social service organizations.

In contrast, Aunt Bertha, CharityTracker, One De-

gree, and Unite Us were not originally developed for

health care users. Therefore, they tend to emphasize

a community collaboration or patient-focused model

of platform implementation rather than a health-care

centric approach. Aunt Bertha and One Degree are

the only platforms developed to be used by individ-

uals seeking help for themselves; they are the only

two that offer a free public-facing online community

resource directory that is accessible without logging

in. CharityTracker and Unite Us were both originally

developed for use by social service organizations and

approach referral management more from a commu-

nity perspective than from a health-care organization

perspective. For instance, CharityTracker is the only

platform that provides the ability to have unstructured

back and forth conversations with a number of orga-

nizations through its bulletin board feature. Unite Us

stresses in its pitch to users that it approaches imple-

mentation from a community wide perspective, rather

than only from a health care organization perspective.

2.2 Mobile Application Development

Most of the existing community resource referral sys-

tems we introduced in sub-section 2.1 use web tech-

nology (desktop or mobile websites) to enable user

interactions. However, we believe that web technol-

ogy is not enough to power user engagement or to

optimize users’ interaction with community resource

referral platforms. In 2018, 51% of the time spent on-

line in the US is on mobile devices. Moreover, 90%

of the time people spend on mobile devices is spent

in apps (BroadBandSearch, 2018). Mobile apps have

higher engagement rates than mobile-optimized web-

sites or desktop web viewing.

Existing community resource referral will soon

need to consider mobile app development to meet

users’ needs and expectations. The key question here

is; why should community resource referral platforms

be built as mobile apps? And what are the key ben-

eﬁts of mobile applications over mobile websites? In

the following, we present the key advantages mobile

apps have over web technology (desktop or mobile

websites) that motivated the software architecture of

our Smart Community Health platform.

Response Time. Mobile applications are usually

1.5 times faster than mobile websites and they per-

form actions much faster too. Mobile applications

store data locally on the mobile device. In web tech-

nology, data needs to be fetched from web servers

which can can be a time consuming task depending

upon the network speed and data size (Baby, 2019).

Personalized Content. With respect to the user ’s

interest, location, preferences, mobile apps make it

easy to personalize content and enable a user-centred

experiences (Pinpin et al., 2019).

Instant Online & Ofﬂine Access. All mobile apps

offer instant access by a tap. They allow users to con-

sume their content quickly offering seamless experi-

ence via storing vital data that can be accessed of-

ﬂine too. Web technology rely on pre-deﬁned URLs

that need to be typed in a web browser (Cupala et al.,

2019).

Leveraging Mobile Devices’ Capabilities. Mobile

apps have a unique advantage where access and uti-

lize features from the mobile device such as camera,

NFC, GPS, ﬁngerprint scanner for authentication and

other apps such as calendar, payment, or QR reader,

etc (Sen et al., 2019).

Push Notiﬁcations. Push notiﬁcations are received

on mobile devices regardless a user opens an app or

not. Notiﬁcations are valuable to maintain an open

reliable communication channels with users. These

notiﬁcations could express updates, reminders, warn-

ings, etc (Pang and Teh, 2019).

Usability. Unlike web technology that relies on web

browsers to support functions, mobile applications

support a wide range of functions enabling various in-

teractions and swipe gestures like a drag, pinch, hold,

tap, double tap and more, each performing a certain

action that increases user friendliness (Kaya et al.,

2019).

HEALTHINF 2020 - 13th International Conference on Health Informatics

616

Figure 1: An overview of basic, desired and advanced functionalities of a community resource referral system. Smart Com-

munity Health outperforms the traditional platforms and offers advanced innovative features including push notiﬁcation,

interactive user engagement and scheduling functionalities.

2.3 Synthesis

In most existing platforms, users can either browse

for services or search based on keywords, usually

based on a program, organization, service, need, or

geographic area. Another limitation that character-

ize most of existing platforms is preventing users to

search for multiple needs simultaneously. All plat-

forms, except CrossTx, offer the possibility to initi-

ate a community resource referral. This referral is

either directly to the community service provider or

through the individual. With CrossTx, users cannot

provide referrals to the individual, instead all referrals

are made directly to the community service provider.

In addition, all the existing platforms enable refer-

ral information to be sent directly to a social service

organization. These platforms do not offer commu-

nity service providers to securely access a dedicate

platform in order to view and act on referrals, to com-

municate with the individual, and potentially the abil-

ity to accept or decline a referral.

Moreover, a critical functionality that is missing

in most of existing platforms is closed-loop referral

tracking. The goal of closed-loop referral tracking is

to ﬁnd out what happened after a referral is made.

Notiﬁcations about services are an important part of

a community resource referral system. For exam-

ple, when information about a service is entered by

a community service provider, it should ideally trig-

ger a notiﬁcation to individuals who are expressing

needs that match that service. Similarly, a notiﬁ-

cation would ideally be sent to the community ser-

vice provider is an individual is seeking help with a

certain need. Other useful features to facilitate re-

ferrals included appointment scheduling and built-in

web forms that enable patients to apply for speciﬁc

services at the time of the referral.

Finally, most of existing platforms do not match

the assessment results with community service

providers. In fact, assessment results should automat-

ically trigger platform actions, for example, recom-

mendation of a list of service providers that address

identiﬁed needs ﬁltered with respect to criteria such as

distance, business hours, service quality rating, sup-

ported languages and ethnicities.

3 SMART COMMUNITY HEALTH

The main purpose of the Smart Community Health

is to provide an end-to-end platform that exists out-

side the domain of any organization that prioritizes

connecting people in need with community resources

in their area. Smart Community Health (SCH) is a

full-service, end-to-end community service provider

recommendation platform designed to help address

pressing social, environmental, and health needs

within our communities. The platform is composed of

a mobile application for individuals looking for ser-

vices and a web application for service providers to

tion about their respective organizations.

In the following section, we detail the fol-

lowed steps to support the Software Development

Life-Cycle (SDLC). (Mahalakshmi and Sundararajan,

2013). First, we present the requirement engineering

Smart Community Health: A Comprehensive Community Resource Recommendation Platform

617

process and highlight the key system requirements.

Next, we provide an overview on the system design

and architecture.

3.1 System Requirements Engineering

Smart Community Health has been designed to meet

speciﬁc requirements that aim to to help address

pressing social, environmental, and health needs

within our communities. Therefore, three key actors

have been identiﬁed; (1) Community Service Provider

User, (2) Individual User and (3) Health Care Pro-

fessional User. Moreover, with respect to the size

and scale of community service organizations, sev-

eral units or entities of such an organization need to

independently and autonomously set up and control

their instance of the community dashboard by manag-

ing its users and associated credentials and resources.

Hence a third actor has been added ton the list; (3)

Community Service Provider Administrator. Figure 2

presents the use case diagram of the Smart Commu-

nity Health platform.

Figure 2: Use Case Diagram of the Smart Community

Health platform.

Requirements describe the characteristics that a

system must have to meet the needs of the stakehold-

ers. These requirements are typically divided into

functional and non-functional requirements. Func-

tional Requirements [FR] describe how a software

must behave and what are its features and functions

(Shah and Rogers, 1988). Non-Functional Require-

ments [NFR] describe the general characteristics of a

system (Glinz, 2007) They are also known as software

quality attributes (Kim and Kim, 2019).

The following is a selection of functional require-

ments:

• [FR1] The system shall allow Community Service

Provider User, Community Service Provider Ad-

ministrator and Health Care Professional User to

create (register), view and edit accounts to be al-

lowed secure access to the platform;

• [FR2] The system shall allow to Health Care Pro-

fessional User to list and coordinate health care

services;

• [FR3] The system shall allow users to support

multiple languages (Internationalization);

• [FR4] The system shall allow Health Care Pro-

fessional User to safely share Health care infor-

mation;

• [FR4] The system shall allow Individual User to

take a smart assessment;

• [FR5] The system shall provide Individual

User with recommended and appropriate service

providers with respect to multiple criteria (i.e. lo-

cation, review, health network, etc.);

• [FR6] The system shall allow actors to inter-

act through reliable and synchronous communica-

tion channels such as instant messaging, internal

emails, routing services, appointment scheduling,

and review of services;

• [FR7] The system shall allow Individual User

to subscribe for a notiﬁcation service matching

needs of interest;

• [FR8] The system shall allow to track and evalu-

ate provided services;

• [FR9] The system shall allow to provide Commu-

nity Service Provider User, Community Service

Provider Administrator and Health Care Profes-

sional users with reporting and analytics;

The above listed functional requirements have

been analyzed and validated with stakeholders and the

following set of quality attributes (non-functional re-

quirement) has been derived:

• [NFR1] Availability: the system shall be available

24/7/365;

• [NFR2] Scalability: the system shall be capable

to scale in order to address large number of users

connecting and interacting with the platform.

HEALTHINF 2020 - 13th International Conference on Health Informatics

618

Figure 3: The Smart Community Health architecture.

• [NFR3] Portability: the system shall support

common iOS and Android-based mobile devices.

• [NFR4] Security: user access and access control

as well as data management and sharing must sup-

port security best practices and techniques and

comply with standard protocols;

3.2 System Architecture

The Smart Community Health platform architecture

is a the cloud-based architecture detailed in Figure 3.

The architecture uses the well-established infrastruc-

ture offered by Amazon Web Services (AWS) (Ko-

valcik and Altman, 2019). The main motivation be-

hind the use of AWS is the non-functional require-

ments validated with our stakeholders with regards to

availability (NFR1), scalability (NFR2) and security

(NFR4).

The Smart Community Health platform architec-

ture is composed of three layers; the mobile appli-

cation, the web application and the back-end cloud-

based modules hosted by AWS. The use of mobile

and web applications aims to address the portability

quality attribute supported by the non-functional re-

quirement NFR3.

The platform also heavily rely on Application Pro-

gram Interface (API). In fact, traditional web applica-

tion design, centred on client server architecture and

scripting languages to ensure dynamic rendering, has

delivered signiﬁcant improvements in web develop-

ment. But when facing the advanced characteristics of

interactive content with multiple channels such as the

Smart Community Health platform, the client-server

request-driven model alone hits its limits. Applica-

tions become harder to scale and the web application

harder to manage, leading to ever-more tightly cou-

pled systems. To move beyond the client server archi-

tecture, and to enable more scalable, contextual and

responsive systems, we integrated and implemented a

fully event-driven architecture (EDA) within the core

of our SCH platform and design capabilities.

3.3 SCH Mobile Application

The SCH mobile application supports the common

iOs and Android mobile operating systems. It aims to

target a large panel of mobile devices and hence reach

out to a large community of potential users (see Fig-

ure 4a). The SCH mobile application allows users to

securely register or simply to use the mobile applica-

tion without registration (see Figure 4b). Obviously,

registered users have access to personalized account-

based services such as scheduling, instant messag-

ing and internal mailing (see Figure 4c). In addition,

registered users have the possibility to share individ-

ual contact information cards with community service

providers. Sharing contact information allow individ-

uals and community service providers to engage in a

secure and interactive collaboration to initiate, exe-

cute, track and follow up on services. The SCH mo-

bile app allows for individual interaction tracking and

monitoring.

The main goal of the SCH mobile application

is to match individual needs to available services

Smart Community Health: A Comprehensive Community Resource Recommendation Platform

619

(a) SCH Home Page (b) SCH Welcome Page (c) Demographics

Figure 4: Examples of the Smart Community Health mobile application graphic user interfaces.

listed by community service providers. This mo-

bile application uses a smart assessment tool that

allows to self-identify health strengths, challenges

and needs. This SCH mobile application integrate

MyStrengths MyHealth

(MSMH), a whole-person

strengths-based consumer-facing tool designed for in-

dividuals, families, and communities to self-identify

strengths, challenges, and needs. This SCH mobile

application leverages the rigour of the Omaha System

(Martin and Scheet, 1992), a multi-disciplinary stan-

dardized health terminology and valid, reliable instru-

ment that addresses all of health across four domains

with 42 discrete concepts.

Surveys for each of the 42 concepts are embed-

ded using expert- and community-validated plain lan-

guage terms. In this SCH mobile application, the

Omaha System domains, Environmental, Psychoso-

cial, Physiological, and Health-related behaviors, are

called My Living, My Mind, Network, My Body, and

My Self-care (see Figures 5a). In the SCH mobile ap-

plication, signs/symptoms associated with the 42 con-

cepts were renamed Challenges (see Figure 5b), and

interventions are called Needs (see Figure 5c).

This community-friendly, consumer-facing instru-

ment generates data for community service providers,

health care organizations, education, and research.

Once an individual completes the assessment, the

SCH mobile application provide a selection of rec-

ommended community service providers that match

the expressed needs (see Figure 6).

3.4 SCH Community Dashboard

The SCH Community Dashboard is a web applica-

tion platform that serves community partners includ-

ing community service providers and health care or-

ganizations. It allows organizations to create an ac-

count and securely access and manage their proﬁle

(see Figure 7a and 7b). Once logged in, an organiza-

tion representative can deﬁne a geospatial service area

where this organization offer services (see Figure 8a).

Each deﬁned geospatial service area is characterized

with a set of services and ethnicities targeted by these

services (See Figures 8b and 9a ).

The SCH Community Dashboard has been de-

signed to address the needs from small, medium and

large scale organizations. Large scale organization

can hence deﬁne multiple branches, each servicing a

speciﬁc geospatial area and helping a set of commu-

nities or ethnicities. For example, an organization like

the Y (YMCA: Young Men’s Christian Association),

a worldwide organisation that aims to put communi-

ties into practice by developing a healthy ”body, mind,

and spirit”. Such a large organization counts 120 na-

tional associations worldwide and 2,700 separate lo-

cal YMCA entities in the USA only. The capability

of the SCH Community Dashboard to allow multiple

entities management and yet a centralized control tp

main entities make it a unique platform.

Using the SCH Community Dashboard, organi-

zations can reach out to individuals who experience

HEALTHINF 2020 - 13th International Conference on Health Informatics

620

(a) List of Domains (b) List of Challenges for My Living (c) List of Needs for Cleaning

Figure 5: The Smart Community Health mobile application component. Sub-Figures 5a, 5b, 5c describe the smart assessment

process. The illustrated challenges in Sub-Figure 5b are associated with the domain ”My Living”. The proposed screening

questions in Sub-Figure 5c are associated to the challenge ”Cleaning”.

Figure 6: The recommended community service providers

grouped by service category for the ”Cleaning” need. Note

the user engagement interactive anchors to useful services

including phone call, web browsing, routing and instant

messaging.

needs that can be addressed by their services. Organi-

zations utilize the internal messaging, email and cal-

endar services and beneﬁt from the notiﬁcation man-

aging services for a closed-loop tracking of referrals.

Finally, the SCH Community Dashboard provide or-

ganizations with a real-time analytics dashboard en-

abling full control, management and monitoring of

provided services and serviced communities (see Fig-

ure 9b).

4 CONCLUSION

In this paper, we presented Smart Community Health,

a full-service, end-to-end community service provider

recommendation platform designed to help address

pressing social, environmental, and health needs

within our communities. The platform is composed

of a mobile application for individuals looking for ser-

vices and the Community Dashboard platform for ser-

vice providers.

The mobile application integrates a health assess-

ment tool that builds on top of an existing validated

screening tool, My Strengths My Health. It gener-

ates international disease classiﬁcation (ICD) codes

that can be stored within all healthcare systems. Plac-

ing the assessment in the mobile app reduces the bar-

rier to accessing services, because the app is freely

available to anyone regardless of healthcare status or

the organization they belong to. When participants

Smart Community Health: A Comprehensive Community Resource Recommendation Platform

621

(a) Hme page (b) Service provider proﬁle page

Figure 7: The Smart Community Health web app Community Dashboard component. Community service providers securely

(a) Speciﬁcation of the geospatial service area. (b) Speciﬁcation of the offered services.

Figure 8: The Smart Community Health web app Community Dashboard component. Community Dashboard offers an

interactive map allowing for polygon drawing.

(a) Speciﬁcation of served ethnicities. (b) Available real-time analytics.

Figure 9: The Smart Community Health web app Community Dashboard component. Community service providers use this

platform as a dashboard to track, control and manage their listed services.

use the assessment and indicate they have a need they

are immediately presented with information connect-

ing them to organizations that provide those services.

The Community Dashboard powers the mobile

app assessment, by allowing community organiza-

tions to register services they provide into our appli-

cation. It start by providing a suite of curated ser-

vices from our partnered organizations, then it allows

the community to add their “pop-up services”. It also

provides community service providers with analytics

for informed and meaningful actions. The Dashboard

platform provides full-service analytics for organiza-

HEALTHINF 2020 - 13th International Conference on Health Informatics

622

tions, allowing them to understand what is happen-

ing in their community. In particular, it focuses on

providing a common framework that allows health

providers and city planners to understand the spatial

and temporal relationships between social determi-

nants of health and health outcomes.

To conclude, the main contribution of Smart

Community Health is it community focused design,

its community curation, its community engaged ap-

proach and its advanced analytics that allow for a

greater understanding of community needs.

5 FUTURE WORK

The development of the Smart Community Health

platform has not ﬁnish yet. Several features and func-

tionalities in the product backlog are still waiting for

grooming to be addressed by the coming sprints. The

coming steps will include a live pilot with a real com-

munity service provider and a representative focus

group of actual users.

One of the areas we are interested in investi-

gating is the assessment component. Although the

SmartCommunity Health platform integrates a well-

established health assessment tool that builds on top

of an existing validated screening tool, My Strengths

My Health. We believe emerging Artiﬁcial Intelli-

gence technologies and more particularly conversa-

tional agents could beneﬁt our platform. The term

‘Conversation Agent’ has come to mean a wide vari-

ety of systems with varying capabilities and purposes,

with the underlying assumption that the agent partic-

ipates in a human-machine dialog. Licklider’s ‘Man-

machine symbiosis’ (Licklider, 1960) was one of the

earliest discourses from a Human Computer Interac-

tion (HCI) perspective that visualized humans inter-

acting with machines in a natural manner. Research

in conversation agents started with messaging-based

chatbots, whose purpose was to maintain a conversa-

tion with a human user.

In the last decade, conversational agents started

focusing more on utility, with the goal of accom-

plishing speciﬁc tasks. Nowadays, conversational

agents range across several modalities, including

speech (such as Siri, Alexa, Cortana), text-messaging

(such as Domino’s, CNN, Pandorabots, Burberry, etc.

found on Messenger, Slack, and/or Skype platform),

and as multimodal embodied agents. Table 1 provides

a summary of most popular text-messaging based

CAs, called chatbots.

Using chatbots to engage individuals in a natu-

ral language based conversation will move our Smart

Community Health platform from static assessments

Table 1: Timeline of Chatbot (Bieliauskas and Schreiber,

2017).

Year Timeline of Chatbots

1950 Chatbots Revolution Concept of truly in-

telligent Machine

1966 Eliza – MIT – Simulate Human Conversa-

tion

1972 Parry- Added Conversational Strategy

1988 JABBERWACKEY- Simulate natural hu-

man Chat with Entertaining and Humorous

Manner

1992 Dr. SBAITSO- Speech Synthesis Program

1995 Alice- Artiﬁcial Linguistic Internet Com-

puter Entity – Heuristic Patten

2001 SMARTERCHILD- Fun Personalized net-

work; Precursor to Apple’s SIRI

2006 IBM’s WATSON- Natural Language Pro-

cessing; Machine Language

2010 SIRI- Apple’s IOS, Natural Language UI

2012 Google Now- uses natural language for

google search on mobile

2015 Alexa- Amazon Echo Device; using lan-

guage processing Algorithms

2015 CORTANA- Bing Search; Natural Voice;

Different Language

2016 Facebook user bots

2016 TAY- Microsoft to mimic the speech and

habit of teenage girl

towards more dynamic evolutive and learning assess-

ment approach.

REFERENCES

Baby, K. T. (2019). Generating internal motivation through

mobile application technology. In Metacognition in

Learning. IntechOpen.

Bieliauskas, S. and Schreiber, A. (2017). A conversational

user interface for software visualization. In 2017 IEEE

Working Conference on Software Visualization (VIS-

SOFT), pages 139–143. IEEE.

BroadBandSearch (2018). Mobile Vs. Desktop Usage.

Cartier, Y., Fichtenberg, C., and Gottlieb, L. (2019). Com-

munity resource referral platforms: A guide for health

care organizations. Technical report, Social Interven-

tions Research & Evaluation Network (SIREN).

Cupala, S. J., Ye, L., and Garg, N. (2019). Selective update

of core mobile device user interface through applica-

tion marketplace. US Patent App. 10/235,155.

Glinz, M. (2007). On non-functional requirements. In 15th

IEEE International Requirements Engineering Con-

ference (RE 2007), pages 21–26. IEEE.

Gundersen, C. and Ziliak, J. P. (2015). Food insecurity and

health outcomes. Health affairs, 34(11):1830–1839.

Smart Community Health: A Comprehensive Community Resource Recommendation Platform

623

Han Rebekah Wong, S. (2012). Which platform do our

users prefer: website or mobile app? Reference Ser-

vices Review, 40(1):103–115.

Kaya, A., Ozturk, R., and Gumussoy, C. A. (2019). Usabil-

ity measurement of mobile applications with system

usability scale (sus). In Industrial Engineering in the

Big Data Era, pages 389–400. Springer.

Kim, S.-H. and Kim, W.-J. (2019). Evaluation of soft-

ware quality-in-use attributes based on analysis net-

work process. Cluster Computing, 22(1):2101–2114.

Koh, H. K., Piotrowski, J. J., Kumanyika, S., and Field-

ing, J. E. (2011). Healthy people: a 2020 vision for

the social determinants approach. Health Education

& Behavior, 38(6 suppl):551–557.

Kovalcik, J. and Altman, E. (2019). Amazon web services

(aws) & digital initiatives.

Kushel, M. B., Gupta, R., Gee, L., and Haas, J. S. (2006).

Housing instability and food insecurity as barriers to

health care among low-income americans. Journal of

general internal medicine, 21(1):71–77.

Licklider, J. C. (1960). Ire transactions on human factors

in electronics. online]. URL https://goo. gl/vndAUs

(2017-11-13).

Lurie, N. and Dubowitz, T. (2007). Health Disparities and

Access to Health. JAMA, 297(10):1118–1121.

Mahalakshmi, M. and Sundararajan, M. (2013). Traditional

sdlc vs scrum methodology–a comparative study. In-

ternational Journal of Emerging Technology and Ad-

vanced Engineering, 3(6):192–196.

Martin, K. S. and Scheet, N. (1992). The omaha system. Ap-

plications for Community health nursing, page 1992.

McGowan, A. K., Kramer, K., and Teitelbaum, J. B. (2019).

Healthy people: The role of law and policy in the

nation’s public health agenda. The Journal of Law,

Medicine & Ethics, 47(2 suppl):63–67.

Molfenter, T. (2013). Reducing appointment no-shows: go-

ing from theory to practice. Substance use & misuse,

48(9):743–749.

One Degree (2019). One Degree.

Pang, K. L. and Teh, H. S. (2019). Mobile-based access

control system. US Patent App. 16/059,537.

Pieces Iris (2019). Pieces Iris.

Pinpin, M. B. G., Greathouse, W. E., Wall, J. J., Kendall,

K. L., and Li, D. (2019). User personalization of third-

party webpage images. US Patent App. 10/248,812.

Sen, S., Spatscheck, O., Huang, J., Mao, Z. M., and Qian,

F. (2019). Facilitation of mobile device resource opti-

mization. US Patent App. 10/172,041.

Shah, J. J. and Rogers, M. T. (1988). Functional re-

quirements and conceptual design of the feature-

based modelling system. Computer-Aided Engineer-

ing Journal, 5(1):9–15.

Smith, T., Mattingly, T. J., and Slabaugh, L. (2019). Im-

proving health determinants outside of the clinic does

not mean outside of clinical science. In Healthcare.

Elsevier.

Smith, W. R., Betancourt, J. R., Wynia, M. K., Bussey-

Jones, J., Stone, V. E., Phillips, C. O., Fernandez,

A., Jacobs, E., and Bowles, J. (2007). Recommen-

dations for teaching about racial and ethnic disparities

in health and health care. Annals of Internal Medicine,

147(9):654–665.

TAVHealth (2019). TAVHealth/TAVConnect.

Unite Us (2019). Unite Us.

HEALTHINF 2020 - 13th International Conference on Health Informatics

624