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Towards a Unified Blockchain-Based Dental Record Ecosystem for Disaster Victims Identification

S. AlQahtani1, S. AlSalamah2,3, A. Alimam2, A. AlAdullatif2, M. AlAmri2, M. AlThaqeb2, S. Alqahtani2,

and K. Aschheim4

1 College of Dentistry, King Saud University, Riyadh, Saudi Arabia 2 College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

3 Global Co-Creation Laboratory, MIT Institute for Medical Engineering and Science (IMES), Massachusetts Institute of Technology (MIT), Cambridge, MA, USA.

4 College of Dentistry, New York University, New York, New York, USA

Abstract – Mass Disasters are on the increase, leaving behind unidentified victims from around the globe, which makes victim identification challenging to Disaster Victim Identification (DVI) teams. Such identification is done by matching Ante-Mortem (AM) and Post-Mortem (PM) records of a primary identifier (DNA, Fingerprints and Teeth). Although all available identifiers should be utilized following INTERPOL standards, teeth are considered the most robust and could survive inhumation well. Nevertheless, inconsistent dental codes across countries, poor quality of AM dental records, and sometimes the absence of digital formats are major challenges hindering victims’ identification in a timely manner. Using qualitative and quantitative methods, this paper identifies the requirements for a universal dental data record and unification ecosystems, and proposes a system design model where inconsistent primary dental records can be automatically converted into a DVI INTERPOL standards and stored in a blockchain-based distributed ledger accessible for international DVI teams to help bring closure to victims’ families around the globe.

Keywords: Blockchain, Dental Record, Disaster Management, Victim Identification, Forensic Odontology.

1 Introduction A disaster is an unexpected event causing death or injury to many people [1]. Many types of events can lead to disasters, from simple ones like multiple motor vehicle road accidents, technical accidents (fires, explosions), terrorist attacks to the most severe like flooding tsunamis or wars. Tragically, disasters are very difficult to predict and, in most cases, cannot be prevented. The number of casualties involved in such disasters varies depending on a number of factors including disaster type or location. Such disasters leave behind a large number of unidentified victims from around the globe, whose identity is a fundamental basic human right as no one deserves to remain unidentified.

1.1 Disaster Management Managing any disaster starts with a Disaster Victim Identification (DVI) team. This team utilizes a formal method of identification [2]. The DVI team consists of: Forensic Pathologists, Anthropologists, Odontologists and the police. DNA, Fingerprints and Teeth, are the primary identifiers used by the DVI teams following INTERPOL standards. The identification is basically done by matching Ante-Mortem (AM) and Post-Mortem (PM) records. In the process of DVI, the set guidelines based on INTERPOL protocol and legal standards must be adhered to [3]. According to INTERPOL DVI, there are five phases to manage a disaster and identify the victims [4], the most important from a forensic point of view are: Mortuary phase: where Forensic Specialists examine all human remains to determine the cause of death and collect Post-Mortem (PM) information); the Ante-Mortem (AM) data collection phase: where the police collect all historic information to aid in the identification process (to be matched with the PM data), collection of AM data can be very lengthy, covering aspects like the missing person’s physical characteristics, such as build, hair and eye color, scars, tattoos, etc. also DNA from their home or family and most importantly: the full medical and dental records; and the Reconciliation phase: where PM and AM data are matched to make an identifications, which could take months to complete because of its complexity. These phases are illustrated in Figure 1.

Fig 1 Disaster Management and Victim Identification Phases

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ISBN: 1-60132-500-2, CSREA Press ©

1.1.1 DVI Using Forensic Odontology

Although fingerprint testing is considered highly reliable, it cannot be implemented all the time due to loss of the fingerprint because of fire, decomposition or the whole loss of the limbs. Similarly, DNA, although reliable, has its own limitations because the analysis is technique sensitive, prone to contamination, expensive and in cases of casualties from the same family or of adopted children, DNA is not helpful [5]. Information from teeth, also known as Dental data, is reliable, accurate and efficient as fingerprint and DNA testing techniques [5-7]. Moreover, teeth survive damage that may affect other body parts and dental characteristics have unique features that can be used for identification. Legal human identification by dental means is done by Forensic Odontologists, who are highly experienced, specially trained dentists.

1.1.2 Indian Ocean Tsunami, 2004

The effects of the 2004 South East Asia tsunami in countries around the Indian Ocean resulted in more than 300,000 people being deceased or missing [8]. One of the most affected was Thailand, which, coupled with limited resources to tackle mass mortality, had many foreign tourists. The sheer magnitude of the disaster, combined with the number of multinational casualties, produced an unparalleled effort from DVI teams from over 30 separate countries [8]. Forensic Odontologists from 21 countries dedicated their dentists to the DVI process: Australia, Austria, Belgium, Canada, Denmark, France, Finland, Germany, Greenland, Iceland, Italy, Japan, Netherlands, New Zealand, Norway, Singapore, South Korea, Switzerland, Sweden, UK, and the USA. The DVI teams had to join efforts and work collectively for several reasons: the overwhelming number of victims, the indistinguishable features of the bodies (due to decomposition) [9], and the lack of AM dental records for Thai victims as most dental records in Thailand were paper-based and lost during the tsunami, which led to the low number of identifications of Thai victims. Only 2.0% Thais were identified (18.1% of missing Thais had dental records and only 0.8% had dental radiographs), compared with 76.4% identified Europeans and 76.5% of North Americans who had 94.4% and 88.2% of dental records and 75.5% and 76.5% of dental X-rays, respectively [8]. The identification process of western tourists was faster than the Thai victims mainly due to the availability of good quality dental records. The challenge, however, was to acquire the dental records from the countries of origin. Another challenge was related to the dental procedure codes, which were very complicated because they were in a different code formats, so the DVI teams had to decipher them then manually translate them into INTERPOL standard codes, which lead to delays in the process of identification.

1.1.3 Information Challenges for Disaster Management

Ultimately, in the management of a disaster, large amounts of heterogeneous data are required to be created, collected and integrated [10]. Therefore, a successful implementation of DVI process is highly dependent on giving the right person access to the right resources at the right time to make the most accurate identification. When the available AM records are not available in the digital format, Forensic Odontologists have to manually enter AM dental information into a missing persons’ database after obtaining access to such records in order to conduct the matching process with the PM records collected [11]. The AM dental data includes all available material (dental records, X-rays, CT scans, dental models, full face photographs and casts [12]), respecting the rights of the patient to medical confidentiality. The content of the original dental data have to be carefully read, analyzed and transcribed into INTERPOL forms. In case of any doubts, the Forensic Odontologist in the AM DVI team should contact the patients’ dentists to discuss the issue and clarifies it [13].

Consequently, this highlights three fundamental information challenges in disaster management. Firstly, the absence of good quality AM data, which prevents matching missing victims with gathered PM data. Secondly, the quantity and quality of AM dental data are variable across the world, which presents a number of key issues. If dental charts, teeth present, and treatments done, were not recorded accurately, matching them with PM data would be impossible [8]. Also, many less developed countries do not have stringent legislation on keeping dental records [14], which could be due to the lack of infrastructure, resources required for record keeping, or data privacy and information security restriction. Finally, each country has its own dental procedure codes and dental record forms and formats [15]. This necessitates the manual translation to convert the AM data into a consistent standard code to match them with PM data that are recorded in the standardized format.

This paper aims to shed light on key challenges hindering DVI process, identify requirements for universal dental data record and unification ecosystems, and propose a design model that would meet all information challenges to assist international DVI teams.

2 Related Work

There are less than a handful number of solutions today that can assist DVI teams in AM dental data management for victim identification, which mostly have been discarded. A dental solution, named WinID, was designed to assist Forensic Odontologists’ human identification [16]. WinID makes use of dental and anthropometric characteristics to rank possible matches. It does not require authorization, and thus anyone can use it. WinID was never updated and is not being used by DVI teams [17]. Another system is UDIM: a Unified Dental identification Module. It is dental forensics computer software

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that comes in numerous versions, from a standalone program (UDIM-SA), to an integrated module in a disaster management software system (UDIM-UVIS), which is an Internet-enabled database system developed for the Office of Chief Medical Examiner of the City of New York (OCME) in the aftermath of the September 11 attacks on New York City and the crash of American Airlines Flight 587. It is intended to handle critical fatality management functions made necessary by a major disaster [18]. All versions of UDIM have been built in security for levels of user rights and have SQL-based security system. UDIM utilizes propriety reconciliation algorithms and has an easy to use interface to assist in the data entry and reconciliation processes. Although UVIS and UVIS-CMS can integrate with some external enterprise level health care reporting systems the dental modules requires manual entry of dental data. Finally, INTERPOL developed a system called PlassData, which is the only one being used by DVI teams today [19]. AM Data of missing persons and PM data of unidentified victims are entered manually or imported into the system. PlassData requires a password to ensure authorization to only the privileged. The recording is based on INTERPOL DVI Forms, since the DVI only deal with the INTERPOL format, therefore the dental codes are converted manually, in order to import the dental record and conduct the matching process, which is a limitation [19]. Also it is very expensive that only few countries afford using it. Another prototype system, called DEnTAS (Dental Encoding Translator), was created by the National Institute of Science and Technology (NIST) in 2016 as a proof of concept. However it was never developed into a commercial product.

All of the solutions above are extremely limited and fall short of meeting DVI information challenges. This is due to the fact that the majority mainly focus on the matching process between AM and PM records. Therefore, they are neither designed for AM data recording and collection, nor the unification of dental data inconsistencies. Therefore, they all require a manual entry of dental procedure codes in a standardized code format before the matching process. Another limitation is the lack of access to missing persons’ AM records, which is currently a difficult process.

3 Methodology

Using a pragmatic approach, this project implements a mixture of quantitative and qualitative methods. First, semi-structured interviews were conducted for primary data collection needed to identify DVI information challenges, and requirements to meet them holistically. The project’s scope is limited to dental procedure codes from Saudi Arabia and the USA at this stage for the proof of concept, and scalability will be considered for future work. Two interviews were conducted with Dr. Kenneth Aschheim [20] Assistant Chief Forensic Odontologist; Adjunct Associate Professor at New York University College of Dentistry; and Associate Professor, Mount Sinai School of Medicine, USA. The second interview

was conducted with Dr. Sakher AlQahtani, Assistant Professor, College of Dentistry and Head of the Forensic Odontology Unit, King Saud University; Member of the DVI Forensic Odontology sub-working group, INTERPOL; and Consultant Pediatric Dentist [21].

Second, a seven-question questionnaire was designed to gather additional primary information regarding the proposed solution. The questionnaire targeted specifically Forensic Odontologists who are members of international DVI teams. Therefore, the sample included members from one of the largest international communities of DVI Forensic Odontologists: The International Group of Forensic Odontologists (formally known as Dentify.Me [22]) that has 125 members representing 48 countries. Qualitative results from the interviews were synthesized and quantitative results from the questionnaires were analyzed and presented in the next section. Finally, Hard Systems Methodology in problem solving was chosen over a Soft System Methodology to solve such a well-defined problem. Therefore, Software Engineering Methods were applied to help define a specific set of requirements. A Waterfall Software Development Life Cycle Model was followed for the proposed blockchain-based solution design, which was illustrated using Unified Modeling Language (UML) modeling tools. Blockchain is a technology that stores data in one place and was considered the best data structure option for the distributed ledger design in this paper (details explained in finer detail in Subsection 5.2).

4 Results 4.1 Qualitative Results

The interviews identified the pressing challenges DVI teams face when identifying multi-national victims in a mass disaster. Although single dental billing codes are used in the USA, incompatibilities in dental software output require manual recode to forensically useful codes [20]. In addition, USA DVI teams deal with non-US victims for multi-national incidents further complicating the process. In Saudi Arabia [21], the process is time consuming, not only to find the original source date and understand the codes, but to also convert them for forensic use. Inconsistencies between international code formats as well as human error during the conversion process can further complicate the identification process. Finally, when multiple individuals need to handle patient identifiable information, there is always the risk of breaches in victim’s privacy.

4.2 Quantitative Results

According to the questionnaires, 81.1% of the respondents had to deal with different dental code formats and 83% agreed that a software that automatically and electronically converts a dental chart into the INTERPOL format is helpful (Figure 2A). Different dental code formats are an issue to 73.6% (Figure 2B). Furthermore, 94.2% agreed that the process of manually converting one dental



code format to the standard code is time consuming (Figure 2C). In addition, 66% agreed that during the identification process, it is an issue having to deal with different dental code formats (Figure 2D). Finally, 66% agreed that having a global blockchain to store patient's dental records, will reduce the identification process time (Figure 2E).

With no doubt, both qualitative and quantitative results show that the proposed solution is of high importance and that it would help DVI team identify multi-national victims in mass disasters better than traditional methods.

5 System Design Overview 5.1 System Requirements

The results above identify the fundamental system design requirements for building universal dental record and

unification solutions in compliance with INTERPOL standards for international DVI teams. Such requirements should, first, record and automatically convert inconsistent primary dental data into the DVI INTERPOL AM standard dental codes. Second, create a neutral AM dental data record for unified records, and store it in a distributed database. Finally, share the unified record equally among international DVI teams on disaster basis and grant them access to related victims’ AM dental data on a need-to-know basis.

5.2 Blockchain-Based Distributed Dental Record

Blockchain is a distributed ledger technology that can store and track transactional records efficiently by supporting key features [23]. First, it ensures data transaction authenticity and integrity using information security mechanisms including private and public key digital signatures [23]. Second, blockchain provides equal access rights to each and every authorized DVI team member to access victim records. Third, it can be applied in decentralized environments, which enables DVI teams to access victim records from anywhere at any time. Fourth, one of the key features of blockchain technology is the fact that the ledger is immutable, where data cannot be modified [23]. Finally, it tracks transactional data in chronological order using immutable timestamp. Furthermore, there are different types of blockchain platforms depending on the accessibility and visibility. A blockchain is built based on the permission to read the information tracked in each blockchain unit; this limits the parties who can transact on the blockchain and permits who can serve the network by writing new block units into the blockchain [24]. Using UML, in the next subsection, a design that meets the above requirements while utilizes blockchain technology is presented.

5.3 UML Diagrams

The proposed solution is illustrated using a mixture of UML tools. Initially, a system Use Case Diagram (illustrated in Figure 3) paints the full picture presenting the system users and all use cases. The system has three actors: Dental Practitioner and DVI Specialist, who both inherent from the User actor. Each User (whether a dentist or DVI specialist) is able to Login and Logout. While the Dental Practitioner actor is able to import their primary dental record in XML format in the Import Primary Dental Record use case, which the system automatically converts into the standard code then stores it in a unified distributed ledger using an <<include>> dependency. This is illustrated in the Convert Primary Dental Record and Store Converted Dental Record use cases, respectively, which are illustrated using a use case diagram in Figures 4 and 5.

The DVI Specialist actor is able to view all converted dental records completed by the system in chronological order in the View Converted Dental Record use case, which is further explained in the use case diagram (Figure 6), and export a reported missing person’s AM dental record in the Export Converted Dental Record use case explained in finer detail in a use case diagram (Figure 7). A role-based access

Figure 2: Survey results. 53 respondents. A; Is a software that automatically convert any code into INTERPOL standard code helpful? B: Does the existence of different Dental code an issue? C: Is manual conversion of Dental code time consuming? D: Is dealing with different Dental code in the identification process an issue? E: Will a global Block-chain reduce the identification process time.



control model is selected to achieve information security for this system design. This access control model complies with national and international data protection laws and regulation for healthcare information systems based on a “Need-to-Know” information security principle [25].

5.4 Putting It All Together in the Blockchain

With this solution, the process of DVI should be more efficient and done in a less time-consuming manner. It allows dental practitioners to import their patient’s dental data records and convert the input to a standard INTERPOL dental procedure code, which should solve the inconsistency of coding. The universal record is then stored into a global immutable blockchain-based ledger that is shared among DVI teams assigned for a specific disaster for effective, accurate and speedy access to international victims’ AM dental records.

A permissioned private blockchain type is needed based on the problem; permission needs to be given to the privileged person, which is the dentist, to import their patient’s dental records. The process is private because only the DVI teams can access the blockchain. Ultimately, this systems solution is concerned with providing the DVI team with the right information at the right time; to do the correct identification, transform inconsistent dental data codes into an immutable blockchain-based ledger of AM dental data in compliance with DVI INTERPOL standards automatically, and distribute it among international DVI teams to grant them access to victims’ AM dental data anywhere in a timely manner.

A permissioned private blockchain type is needed based on victims’ AM dental data anywhere in a timely manner. Although it is designed as a stand-alone solution without an integration with other solutions, it still can be integrated with both or either dentist software, and DVI software. Regardless, the primary feature is to automate the conversion of the dental codes of any AM dental data into the INTERPOL standard format, which the DVI team works with. By that, eliminating the need of a DVI member to manually convert the local coded dental data into the INTERPOL standard format to be entered in the matching software. This solution can be integrated with any dental software from the dentist’s side, in order to store the living patients’ AM records from all around the world. Furthermore, it can be easily integrated with any DVI matching software and the DVI teams will have access to the victim’s AM records from a blockchain to enable them to conduct the matching process efficiently. Finally, this solution should equip DVI Forensic Odontologists with the right ecosystem to shift current manual dental data unification workflow to the digital world for a more efficient, secure, convenient, and trustworthy workflow.

Figure 4: Covert Primary Dental Record use case activity diagram.

Figure 3: System Use Case Diagram



6 Conclusion

Mass disasters result in large numbers of unidentified victims. Human identification is done by matching AM with PM record of a victim’s primary identifiers. Although DNA, Fingerprints and Teeth are the primary identifiers used by DVI teams following INTERPOL standards, teeth are considered the most robust and could survive inhumation well

However, inconsistencies in international dental codes, poor quality of AM dental records, and sometimes the absence of digital formats are the three major obstacles faced by DVI teams hindering victims’ identification in a timely manner. In this paper, a universal dental data translation ecosystem design was proposed to solve this global problem. This is by, first, automatically converting primary dental records into a DVI INTERPOL standard codes. Second, store this unified record in an immutable blockchain-based ledger, and finally, distribute it among international DVI teams bring justice to today’s global victims. This proposed system design should have a great impact on disaster management locally and globally. This is because it, first, facilitates record keeping of the living, which helps protect the most basic rights of a person (protecting their identity). Second, it also complies with INTERPOL protocol for standards, which strengthens its adoption in the field of DVI. Finally, it saves unified dental data records to an immutable global blockchain-based record, which accelerates the transfer of this request to the DVI specialists, and most importantly, saves much needed time and effort.

Figure 5: Store Converted Dental Record use case activity diagram.

Figure 6: Import Primary Dental Record use case activity diagram.

Figure 7: View Converted Dental Record use case activity diagram.



Despite the huge global impact of this solution, it has some limitations. Initially, people who have never been to the dentist or have an alias, won’t have any dental records under their name and therefore cannot benefit from this solution. Also victims from developing countries that do not keep dental records due to resources or infrastructure limitations. Furthermore, for the prototype design, two incompatible dental data codes for Saudi Arabia and USA were considered, but in the future, scalability is considered to eventually include all international codes. Finally, this system design should equip international DVI teams with the right tools to identify today’s global victims to bring them justice and give their families closure.

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