=Paper=
{{Paper
|id=Vol-1304/STIDS2014_T10
|storemode=property
|title=An Ontology for Medical Treatment Consent
|pdfUrl=https://ceur-ws.org/Vol-1304/STIDS2014_T10_YuEtAl.pdf
|volume=Vol-1304
|dblpUrl=https://dblp.org/rec/conf/stids/YuWC14
}}
==An Ontology for Medical Treatment Consent==
https://ceur-ws.org/Vol-1304/STIDS2014_T10_YuEtAl.pdf
An Ontology for Medical Treatment Consent
Bo Yu, Duminda Wijesekera and Paulo Costa
Department of Computer Science
George Mason University,
Fairfax VA, USA
{byu3, dwijesek, pcosta}@gmu.edu
Abstract— Active duty military personnel, their families and Part of the process of obtaining consent involves the caregiver
veterans seek medical services from the Military Health Service, providing a risk/benefit analysis and explaining alternative
which partners with private care, or the Veterans Administration, treatments in a way that the patient understands, and accurately
respectively. Indeed, medical services for active duty personnel, communicates the care provider’s understanding in an unbiased
who need medical services on deployment, is a readiness issue. way [3].
Laws that govern the practice of medicine, licensing to practice
medicine and the permission to treat a patient is based on local State law specifies acceptable explanation. Further, consent
laws (state level) that are specific to medical sub-specialties. That laws obligate the caregiver to attest that the patient and/or the
provides a daunting challenge to patients who move frequently, guardian have the capacity (including physical/mental capacity
such as active duty military and their families. As most medical and maturity) to provide consent. Over the years, federal, state,
providers are transforming their record keeping to Electronic and local governments and healthcare organizations have
Medical Record (EMR) system, it is desirable to obtain, verify and developed laws, regulations, and standards for obtaining and
act according to the legally enforced medical consent using EMRs. memorializing informed consent. However, consent laws and
We present an Ontology-based framework and a prototype regulations are complex and sometimes ambiguous, and
system that provide end-to-end services using an open source change often. Therefore EMR must take these changes as they
EMR system. Providing an electronically verifiable, but compliant are mandated. We postulate that having a consent service that
with locally mandated laws in one universal system can be
is aware of the semantics of informed medical consent can
beneficial to VA and other DoD EMR systems.
satisfy the evolving and diverse nature of mandated informed
Keywords—informed medical consent; medical consent law; treatment consents.
workflow management system; ontology As a substantiation of our postulate, we provide a semantic
web driven, medical workflow aware [4] control system to
I. INTRODUCTION obtain and enforce treatment consent. The medical personnel
that use our system do not see a difference between the
Failure to obtain informed consent is listed as a top ten
existing EMR system and our prototype. Some highlights of
reason for medical malpractice claims [1]. The improvement in
our system are: A refined Workflow-based EMRs that allow
flexibility, automation and enforcement for electronic patient
the medical staff to obtain consents dynamically--i.e., if
informed consent management are especially beneficial to
required by a procedure in a treatment workflow; and
patients who relocate, such as active duty military and their
evaluating these consents automatically as a care team goes
families. This mobility entails their medical treatment be
from one step to another in the treatment workflow [5].
subject to local regulations. Given that EMRs services can be
Furthermore, our combined workflow based consent
centralized, cloud based or being offered remotely, having a
management engine ensures that treatment workflow move
consent management system that can provide a diverse
forward only if consents have been granted (including break-
collection of consents for every treatment would benefit EMR
the-glass kind of emergency treatments). This enhancement
services generally, and especially the Military Health Service.
improves current practice of patient informed consent
Although some VA hospitals have implemented electronic
management.
consent process, iMedConsent [2], they do not provide
enforcement mechanism and is considered mostly educational Following this Introduction, Section 2 describes related
for the patients. The system we prototype can accommodate work; Section 3 explores ontology-based reasoning to derive
(i.e. obtain and enforce though out long chains of treatment the informed treatment consent; Section 4 shows architecture
processes), can be deployed from one location but cover of our consent-based workflow control in a Workflow-based
multiple regions (such as states, countries) and be helpful for EMR system; and finally, Section 5 contains concluding
the military, military dependants and as well as for other comments.
mobile populace.
Informed patient consent – either express or derived -- II. RELATED WORKS
expresses the patient’s wishes, and consists of an agreement
between the care providers and patient, including choice A. Informed Consent in Current EMRs
between potential treatment regimes or terminating treatment. The American Medical Association considers the term
72
informed consent, first used by a California appeals court in representation of the biomedical domain, founded upon Basic
1957 [6], “an ethical obligation of the practice of medicine and Formal Ontology [28]; NCBO Bioportal, biological and
a legal requirement per statute and case law in all 50 States” [7] biomedical ontologies and associated tools to search, browse
y. Medical informed consent falls mainly into two categories: and visualize [29]; NIFSTD Ontologies from the Neuroscience
consent for medical information disclosure; and consent for Information Framework: a modular set of ontologies for the
medical treatments. Herein we mainly address the latter, with a neuroscience domain [30]; SNOMED
focus on informed consent for procedure-oriented treatment CT (Systematized Nomenclature of Medicine --
regimes. Clinical Terms) [31]; OBO Foundry, a suite of interoperable
reference ontologies in biology and biomedicine [32]; OBO-
In the past decade, consent management has received Edit, an ontology browser for most of the Open Biological and
considerable attention from researchers and healthcare Biomedical Ontologies [33]; PRO, the Protein Ontology of the
organizations who proposed different ways to improve Protein Information Resource from Georgetown University
electronic consent management system. For example, “e- [34], and so on. Yet, no works have efficiently leveraged a
Consent: The Design and Implementation of Consumer technique for informed treatment consent in EMRs. In this
Consent Mechanisms in an Electronic Environment” [8] paper, we provide a methodology to address this gap.
provided guidelines on how to design an e-consent system.
Another relevant work is by Ruan C. & Yeo S.S. [9], who used
the UML Model to design an e-consent system. They first III. USING ONTOLOGY-BASED REASONING TO DERIEVE
identify various parts necessary to specify the e-Consent rules INFORMED TREATMENT CONSENTS
about patient record protection, and then used UML to model
the properties required by an e-consent system and to make the A. Entities of Medical Treatment Consent Ontology
associated patient record protection rules explicit and verifiable. To create our ontology for medical treatment consents, we
However, that work was theoretical; they neither designed nor studied several medical treatments in actual medical facilities,
implemented a system that works with EMR systems. obtained their consent forms and studied state law governing
medical consents. We combined information obtained from
Rusello G. et al. proposed creating consent-based
interviews with the various paper-based documents used to
workflows for healthcare management [10] where patients can
record events and data that are associated with the workflows.
control disclosure of their medical data for inter-institutional
We found there are common entities used in the informed
consults. This work does not address workflows for procedure-
treatment consents, such as patients (may or may not be an
oriented treatment regimes, treating consent contents as black
Informed consent giver), treatments (usually, consisting of
boxes. Others have proposed e-consent management to be
several treatment procedures – so called tasks in the treatment
integrated with EMR or EHR systems [11-14]. Win et al. in
workflow specifications), treatment performance locations
their paper “Implementing patients consent in electronic health
(some treatments may be not be permitted in some states) and
record systems” [15] expressed patient consent using an
informed consents (where some procedures within a treatment
interface-based approach. However, those e-consent
regime may not require consent). Based on our observations,
approaches focus mainly on sharing medical data, privacy, and
we created the following classes, attributes and rules on the
security aspects [16-18], but not the complicated nature of
ontologies.
treatments.
Many healthcare organizations attempted to have electronic B. Classes, Propertities Created in Ontology
consent management in their EMRs. Veterans Administration ¾ Classes
Medical Centers use iMedConsent™ [2] that supports
electronic access, completion, signing, and storage of informed 1. Patient: (one requiring medical assistance) with
consent forms and advance directives. iMedConsent has two attributes such as age, name and active status used to evaluate
parts: software application and clinical content library. It maturity.
generates consents on each procedure without workflows. 2. Treatment: Methods used to manage
Nonetheless, the system neither dynamically gains informed ameliorate, or prevent a disease, disorder, or injury. Each
consents at the point of providing treatments nor enforces
Treatment has a name (such as eye surgery, dialysis etc.).
consents on medical procedures.
3. Procedures: generally, every treatment consisted of a
B. Ontologies in the Healthcare Domain set of predefined procedures. Each procedure has a procedure’s
name.
Ontologies have been used to represent actionable
4. Consent: legal documents expressing the willingness
knowledge in biomedicine [19–23], decision support [24],
information integration, etc. Some examples are: BioPAX, an for the patient to be subjected to treatments and encompassing
ontology for the exchange and interoperability of biological procedures (referred to as TreatmentConsent) or providing the
pathway (cellular processes) data [25]; CCO and GexKB, authority share medical information (SharingConsent).
Application Ontologies (APO) that integrate diverse types of 5. TreatmentConsent: A subclass of Consent, modeling
knowledge with the Cell Cycle Ontology (CCO) and the Gene the agreement to receive treatment. Its nature is determined by
Expression Knowledge Base (GexKB) [26]; Disease Ontology, state law, federal law or medical sub-discipline. Thus, the
designed to facilitate the mapping of diseases and associated attributes are the state, treatment name, treatment type. An
conditions to particular medical codes [27]; Linkbase, a formal example, anesthesiaConsent
Identify applicable sponsor/s here. If no sponsors, delete this text box
(sponsors).
73
1) MandatoryConsent: a sub-class of TreatmentConsent Fig. 1. Entities of treatment consent ontology
with attributes active (or passive). An example is
anesthesiaConsent for Suegery.
2) OptionalConsent: is a sub-class of TreatmentConsent,
but its omission does not affect performing the procedures. An
example is anesthesia consent for giving birth. Most states do
not mandate this consent.
6. AdultPatient: is the patient’s maturity status.
Competent adult patients may give their own treatment
consents.
7. MinorPatient: is a patient’s maturity status. Without
exception, such as during an emergency, minor patients cannot
provide treatment consent.
8. PerformInState: is a State in which the treatment is to
be performed. They associate with Treatment.
¾ Properties (express the relationship of two classes) in Rule (1) Information Disclosure Standard: Obligates the
Ontology care provider to disclose and discuss information relevant to
the proposed treatment, their risks and benefits and the
TABLE 1 PROPERTIES TABLE available alternatives with their risks and benefits [36]. These
come in two main standards: The normal person’s standard and
Property Name Domain Range
the professional standard. 25 states mandate the use of the
asksMandatoryConsentByPatient Patient class MandatoryConsent patient standard, while 23 have mandated the professional
OptionalConsent standard. The laws in the remaining two states, Colorado and
asksOptionalConsentByPatient Patient class
class
Georgia, are not easily classifiable as one or the other [37].
has Treatment class Procedures class
Nonetheless, the scope of required information to be disclosed
AdultPatient
class or
is still being debated. Two states, Minnesota and New Mexico,
isPatient Patient class require the care provider to explain using both these standards.
MinorPatient
class Rule (2) Decisional Capability: Evaluation of patient’s
PerformInState competence to understand the information and providing
isState State class
class
MandatoryConsent rational and voluntary decisions about the healthcare
needsMandatoryConsent Procedures class treatment. In [38], authors described four psycho-legal
class
needsOptionalConsent Procedures class
OptionalConsent standards, communicating a choice, factual understanding,
class
appreciation of the situation, and rational manipulation of
performedIn Treatment class State class
information, all used to evaluate a patient’s competence in
requiresMandatoryConsent Procedures class Consent class giving consent. However, to date this lacks a widely accepted
requiresOptionalConsent Procedures class Consent class standard. Hence, we do not codify this aspect.
Rule (3) Competency: Validation of patient’s maturity to
Table 1 shown relationship between two classes. grant informed consent. For the informed treatment consents,
Properties may have a domain and a range specified. For an essential component of the conception of autonomy is
example, row1 in above table indicates: allowing competent adult persons and emancipated children to
asksMandatoryConsentByPatient: it links individuals make their own health care decisions. Our examinations have
belonging to the class Patient to individuals belonging to led to categorizing the consents as follows:
the class MandatoryConsent. 1. Informed consent giver (governed by Rule (3) -
competence): the person with the legal right to make
A view of the entities of treatment consent ontology
health care decisions, such as parents or legal
developed in Protégé 4.3. shown in Fig.1.
guardians of minors, healthcare proxies, healthcare
providers or third parties.
C. Rules for Enforcing Informed Treatment Consent
We now show how to use the ontological syntax and create 2. Treatment information (governed by Rule (1) -
rules that specify treatment consent. As stated, these rules information or disclosure): at a minimum, includes
formalize contents taken from the many natural language treatment name, procedures for this treatment,
documents consisting of state laws and sub-disciplines treatment preformed location.
regulations that govern specific institutional practices [35]. 3. Patient’s decision of the treatment (governed by Rule
These rules specify in the consent components: (2) - decisional capability): includes the decision
74
(deny or accept) by providing all required conditions married minor may consent for medical, dental, or psychiatric
such as patient’s and other attributes such as care, without parental consent, knowledge, or liability.
signatures, date, etc. We create patient maturity evaluation rules for each state
Consequently, formalization of informed consent should based on its consent laws. Table 2 shows a part of the summary
base its consents on all the above-mentioned attributes. of 50 states’ patient maturity evaluation rules.
Assuming that consent rules and patient information is
available in an EMR, we show how to generate the consent
TABLE 2 PATIENT MATURITY EVALUATION RULES (50 STATES)
decisions. Auto-generation of the appropriate forms to be
signed by the consent giver will be described elsewhere. State
State
Abbreviation
General -‐Medical
-‐ Treatment Pregnancy
19 years of age or older (Ala. Code § 26 1 1)
The following example shows the complicated nature of
1. Minor age equal or greater than 18, less than 19, and minor has an emancipation order
(Ala. Code §§ 26-13-1 and 26-13-5);
2. Minor age 14 or old, has graduated from high school (Ala. Code § 22-8-4);
decisions made by our consent service. Most states set the age ALABAMA AL
3. Minor is married (Ala. Code § 22-8-4; Ala. Code § 22-8-5);
4. Minor having been married and divorced (Ala. Code § 22-8-4; Ala. Code § 22-8-5);
1. Any minor (Ala. Code §
22-8-6);
at 18 years, but Alabama allows health care consent to be made 5. Minor is pregnant (Ala. Code § 22-8-4);
6. Minor has child(ren) (Ala. Code § 22-8-5);
by minors 19 years of age and older [39]. So, can an 18 year- ● ● ● ● ● ●
18 years of age or older (Cal. Fam. Code § 6500)
old resident of Virginia requiring dialysis treatment during a 1. Minor is an emancipation minor (Cal. Fam. Code § 7050);
visit to Alabama give consent for the treatment? Answering CALIFORNIA CA
2. Minor is 15 years of age or older, who is living separate and apart from the minor's
parents or guardian and managing the minor's own financial affairs (Cal. Fam. Code §
1. An unemancipated minor
6922);
this question will determine the adult status of the VA resident, 3. Married Minor is an emancipation minor (Cal. Fam. Code § 7002);
4. Minor is 16 years of age or older, who serves in the armed forces of the United States or
(Cal. Fam. Code § 6925);
but that too depends on the treatment sought as described has court order is an emanicpated minor (CAL. FAM. CODE § 6950 (2012));
-‐ -‐
● ● ● ● ● ●
below. 18 years of age or older (Wyo. Stat. Ann. § 14 1 101(a))
1. Minor is or was legally married – minor is married, widow (Wyo. Stat. Ann. § 14-1-
101(b));
2. Minor is or was legally married – minor is divorced (Wyo. Stat. Ann. § 14-1-101(b));;
Depending on the treatment type, the age of the minors WYOMING WY 3. Minor who is in active military service of the United States may consent for healthcare
treatment (Wyo. Stat. Ann. § 14-1-101(b)); 1. No explicit law
who may consent may differ. 4. Minor who is living apart from his parents or guardian and managing his/her own affairs
may consent for healthcare treatment(Wyo. Stat. Ann. § 14-1-101(b));
5. Minor is an emancipated minor (Wyo. Stat. Ann. § 14-1-101(b));
Example: In CA, for General Medical Treatments, Cal. Fam.
Code § 6500, states a minor 18 years of age or older may D. Deriving Informed Treatment Consents
give his/her own treatment consent. However, for We use the patient maturity rules of California (CA) as an
Pregnancy (not include sterilization and abortion), CAL. example to explain Semantic Web Rule Language (SWRL)
FAM. CODE § 6925 (2012) states that a minor may rules:
consent to medical care related to the prevention or
treatment of pregnancy, but this law does not authorize a x For General Treatment (we consider eye surgery belongs
to general treatment)
minor: (1) To be sterilized without the consent of the
minor’s parent or guardian. (2) To receive an abortion 1. Minor is an emancipation minor may consent for
without the consent of a parent or guardian other than as medical, dental, or psychiatric care, without parental
provided in Section 123450 of the Health and Safety Code. consent, knowledge, or liability. (Cal. Fam. Code §
7050);
Even if the patients are minors, for certain treatment with
2. Minor is 15 years of age or older, who is living
some minor active status such minors are allowed to give
separate and apart from the minor's parents or
their own treatment consent.
guardian and managing the minor's own financial
Example: (1) Cal. Fam. Code § 7050 provides that an affairs (Cal. Fam. Code § 6922)is an emancipation
emancipated minor may consent for medical, dental, or minor;
psychiatric care, without parental consent, knowledge, or 3. Married Minor is an emancipation minor (Cal. Fam.
liability; (2) Cal. Fam. Code § 6922 provides that a minor, 15 Code § 7002);
years of age or older, is living separate and apart from the 4. Minor is 16 years of age or older, who serve in the
minor's parents or guardian, whether with or without the armed forces of the United States or has court
consent of a parent or guardian and regardless of the duration order(Cal. Fam. Code § 6950);
of the separate residence; and the minor is managing the
minor's own financial affairs, regardless of the source of the x For Pregnancy Treatment (exclude to be Sterilization and
minor's income can give consent for medical treatments. to receive Abortion)
Some consent rules are not found in specific provision 1. An un-emancipated minor may consent for medical
explicitly, but can be retrieved from combining laws. care related to the prevention or treatment of
pregnancy (Cal. Fam. Code § 6925);
Example: Cal. Fam. Code § 7002 provides a minor who has Let S be a SWRL knowledge base, where {t, p, s} is a set
married is emancipated; according to another rule (Cal. Fam. of OWL class names. In here, {t, p, s} refers to {Treatment,
Code § 7050 provides that an emancipated minor may consent Patient, and State} coordinately. performedIn is an OWL
for medical, dental, or psychiatric care, without parental property name to show the relationship between Treatment and
consent, knowledge, or liability). The combination implies a State, and {“eyesurgery”, “CA”, age, fi, ls, m, iem, iaf, hco,
tpi} is a set of OWL constants and SWRL variables. In here,
75
age refers to patient’s age;; fi refers to patient’s financial status;; Part (4) provided constrains. Part (5) implied the consequent
ls refers to patient’s resident status;; m refers to patient’s marital ((5)) from the antecedent ((1) ~ (4)).
status; iem refers to patient maturity level; iaf refers to patient’s
career status; hco refers to a legal issue related to patient, tpi Table 3 shows the part of summary of the syntax of
refers to patient seeking treatment which is an attribute of consent laws of patient’s maturity in 50 states.
Patient. Some SWRL rules have the form:
TABLE 3 THE SYNTAX OF CONSENT RULES OF PATIENT
Example 1: (CA consent Laws for General Medical Treatment: MATURITY IN 50 STATES
rule2 shown in Table 2) State SWRL rule
State
Abbreviation Ge ne ral M e dic al Tre at m e nt P re gnanc y
patientRequiresTreatment(?p, "eyesurgery"), hasT reatmentName(?t, "eyesurgery"), patientRequiresT reatment(?p, "eyesurgery"),
hasAge(?p, ?age), patientT reatmentPerformedIn(?p, ?tpi), hasStateName(?s, ?tpi),
hasAge(?p, ?age), performedIn(?t, ?s), containsIgnoreCase("AL", ?tpi), greaterT hanOrEqual(?age, 19) ->
(1) AdultPatient(?p) hasT reatmentName(?t,
patientFinancialIndependent(?p, ?fi), hasT reatmentName(?t, "eyesurgery"), patientRequiresT reatment(?p, "eyesurgery"),
"pregnancy"),
patientRequiresT reatment(?p
patientLivesSeparately(?p, ?ls), ALABAMA AL
hasAge(?p, ?age), patientDivorced(?p, ?d), patientIsPregnant(?p, ?ip), patientMarried(?p,
?m), patientHasChild(?p, ?hc), stringConcat(?v, ?m, ?d, ?ip, ?hc), containsIgnoreCase(?v,
, "pregnancy"),
patientT reatmentPerformedI
"T "), patientT reatmentPerformedIn(?p, ?tpi), hasStateName(?s, ?tpi), performedIn(?t, n(?p, ?tpi), hasStateName(?s,
hasTreatmentName(?t, "eyesurgery"), ?s), containsIgnoreCase("AL", ?tpi), lessT han(?age, 19) -> AdultPatient(?p) ?tpi), performedIn(?t, ?s),
containsIgnoreCase("AL",
patientTreatmentPerformedIn(?p, ?tpi), ●
●
?tpi) -> AdultPatient(?p)
(2) hasStateName(?s, ?tpi), performedIn(?t, ?s), ●
containsIgnoreCase("AL || AK || CA || MA", ● ● ● ● ● ●
hasT reatmentName(?t, "eyesurgery"), patientRequiresT reatment(?p, "eyesurgery"),
?tpi), hasAge(?p, ?age), patientT reatmentPerformedIn(?p, ?tpi), hasStateName(?s, ?tpi),
performedIn(?t, ?s), containsIgnoreCase("CA", ?tpi), greaterT hanOrEqual(?age, 18) ->
AdultPatient(?p)
containsIgnoreCase("T", ?fi), hasT reatmentName(?t, "eyesurgery"), patientRequiresT reatment(?p, "eyesurgery"), hasT reatmentName(?t,
(3) hasAge(?p, ?age), patientFinancialIndependent(?p, ?fi), patientLivesSeparately(?p, ?ls), "pregnancy"),
containsIgnoreCase("T", ?ls), patientMarried(?p, ?m), patientIsEmancipatedMinor(?p, ?iem), patientIsArmedForce(?p,
?iaf), patientHasCourtOrder(?p, ?hco), containsIgnoreCase("F", ?hco),
patientRequiresT reatment(?p
, "pregnancy"),
CALIFORNIA CA patientIsEmancipatedMinor(?p, ?iem), stringConcat(?u, ?fi, ?ls), containsIgnoreCase("FF- patientT reatmentPerformedI
lessThan(?age, 16), FT -T F", ?u), stringConcat(?v, ?iaf, ?hco), containsIgnoreCase("FF-FT -T F-T T ", ?v), n(?p, ?tpi), hasStateName(?s,
(4) containsIgnoreCase(?iem, "F"), containsIgnoreCase(?m, "F"), ?tpi), performedIn(?t, ?s),
greaterThanOrEqual(?age, 15) patientT reatmentPerformedIn(?p, ?tpi), hasStateName(?s, ?tpi), performedIn(?t, ?s),
containsIgnoreCase("CA", ?tpi), lessT han(?age, 16), greaterT hanOrEqual(?age, 15) ->
containsIgnoreCase("CA",
?tpi) -> AdultPatient(?p)
MinorPatient(?p)
(5) -> AdultPatient(?p) ●
●
●
Example 2: (CA consent Laws for General Medical Treatment: ● ● ● ● ● ●
rule1 ~ rule4 shown in Table1)
hasT reatmentName(?t, "eyesurgery"), patientRequiresT reatment(?p, "eyesurgery"),
hasAge(?p, ?age), patientMarried(?p, ?m), patientDivorced(?p, ?d),
patientIsArmedForce(?p, ?iaf), patientIsEmancipatedMinor(?p, ?iem), stringConcat(?v,
?m, ?d, ?iaf, ?iem), containsIgnoreCase(?v,"T "), patientT reatmentPerformedIn(?p, ?tpi),
patientRequiresTreatment(?p, "eyesurgery"), WYOMING WY hasStateName(?s, ?tpi), performedIn(?t, ?s), containsIgnoreCase("WY", ?tpi),
lessT han(?age, 18) -> AdultPatient(?p)
1. No explicit law
hasAge(?p, ?age), ●
patientFinancialIndependent(?p, ?fi),
●
●
patientLivesSeparately(?p, ?ls),
(1) patientMarried(?p, ?m), E. Evaluation
patientIsEmancipatedMinor(?p, ?iem),
Here, we show consequences of our rule base that comply
patientIsArmedForce(?p, ?iaf),
with state consent laws and sub-disciplines regulations. The
patientHasCourtOrder(?p, ?hco),
scenario of a use case is a 15 year-old patient named Kate
patientIsEmancipatedMinor(?p, ?iem),
seeking eye surgery in California. She is not married nor has
hasTreatmentName(?t, "eyesurgery"), she done an emancipated minor evaluation. She also does not
patientTreatmentPerformedIn(?p, ?tpi), have a court order of giving medical consent nor is serving in
(2) hasStateName(?s, ?tpi), performedIn(?t, ?s), the U.S. Armed Forces. However, she does not live with her
containsIgnoreCase("AL || AK || CA || MA", parents and manages her own financial affairs. In this situation,
?tpi), what kind of informed consents should be obtained by her care
providers? May she provide these consents herself? We derive
stringConcat(?v, ?fi, ?ls), that Kate is an adult patient according to CA consent laws of
containsIgnoreCase("FF-FT-TF", ?v), patient’s maturity. Therefore, she is able to consent by herself,
containsIgnoreCase(?iem, "F"), even if her age is under CA’s required maturity age.
(3)
containsIgnoreCase("F", ?m),
containsIgnoreCase("T-F", ?iaf), We now show how Pellet generates data properties of an
containsIgnoreCase("T-F", ?hco), individual of class Patient, here Kate, and object properties of
this individual, reasoned with rules to infer the head of rule
lessThan(?age, 16), (see example 1).
(4)
greaterThanOrEqual(?age, 15)
Using Pellet, the informed treatment consents retrieved
(5) -> MinorPatient(?p) easily and appropriately. The outcome of the proof of patient
In Part (1) we defined a set of OWL constants and SWRL maturity and explanation is shown in Fig. 2. In this
variables of a specific patient; and the information we can illustration, the left red box exposed that the outcome matches
retrieve from EMRs. Part (2) checked whether the treatment our presuming result. For more details of how Pellet reasons,
that patients seek may be performed in the state where patient see the following explanation provided by Protégé.
does the treatment; and which treatment can be performed in
which states is known information. Part (3) established rules.
76
Explanation for: The existing EMRs lack a mechanism for dynamically
Kate Type AdultPatient
obtaining appropriate informed treatment consents and lack a
1. Kate has Age “15”^^ int standard way for specifying, updating and checking
compliance with governmental consent laws and sub-
2. Kate patientRequiresTreatment “eyesurgery”^^string
discipline regulations. Our goal here is to build a novel EMRs
3. Kate patientTreatmentPerformedIn “CA”^^string by adopting a variety of technologies to address this gap.
4. Kate patientFinancialIndependent “T”^^string We developed a prototype consent management system on
5. Kate patientLivesSeparately “T”^^ string a Workflow-based EMR system. In our system, consents are
issued electronically using the EMR interface and enforced
6. eyesurgery hasTreatmentName “eyesurgery”^^string using the workflow runtime. Furthermore, those consents can
7. CALIFORNIA hasStateName “CA”^^ string be used to control corresponding medical procedures
dynamically. In addition, we use ontology-based knowledge
8. eyesurger performedIn CALIFORNIA representation and reasoning mechanisms to obtain required
9. performedIn(?t, ?s), hasAge(?p, ?age), informed consents based on each patient’s situation and ensure
hasStateName(?s, ?tpi), hasTreatmentName(?t, compliance with governmental consent laws and sub-
"eyesurgery"), patientFinancialIndependent(?p, ?fi), disciplines regulations.
patientLivesSeparately(?p, ?ls), Our consent enforcement system, shown in Fig. 1 consists
patientRequiresTreatment(?p, "eyesurgery"), of (1) User Interface (UI) for EMR Operations;; (2) EMR’s
patientTreatmentPerformedIn(?p, ?tpi), Runtime System; (3) Workflow Management System -- a
containsIgnoreCase(?fi, "T"), runtime system that enforces medical treatment workflow and
containsIgnoreCase(?ls, "T"), checks for consents before enabling a workflow; (4) A
containsIgnoreCase("CA", ?tpi), Consent Management System that ascertains which consents,
greaterThanOrEqual(?age, 15), lessThan(?age, 18) if any, are missing and must be issued; (5) A Consent Rule
Fig. 2. Outcome of the proof of patient maturity using Pellet reasoner Management System – a system connects to an ontology
application and the Consent Service to obtain the appropriate
informed consent automatically; and (6) Related Databases.
See, the high-level architecture shown in Fig. 3.
Our implementation uses an open source EMR system,
OpenMRS [40], and a workflow system YAWL [41]. In our
implementation, the EMR user community interacts with the
EMR using the well-designed OpenMRS user interfaces. All
patient data is stored in OpenMRS’ databases. Whenever a
treatment procedure (a task to the WfMS) requires a patient’s
informed consent to move to the next stage, WfMS will call the
consent service to retrieve or obtain related consents as a
prerequisite to proceeding with the treatment. Patient consents
are stored in the OpenMRS’ databases as part of their medical
records. Consent Management Service is plugged in YAWL as
In sub-section D above, we reviewed these rules, see
a custom service.
Example 1. The input facts of individual patient, Kate, are
shown in line 1 ~ line 6 from Kate’s data prosperities;; line 9 is As stated, we enforce medical workflows upon the
the rule that used by Pellet to infer the new fact, in other OpenMRS EMRs by using the YAWL workflow management
words Kate belongs to adult patient base on her active status system. We did so because, first, YAWL workflow system has
based on this particular rule. been used to implement many workflows in industry and
academia [42]. Second, YAWL uses a domain independent
Our goals are proposing a novel approach, named
syntax to specify workflows, and provides an editor and a
Workflow-based EMRs with a consent management
runtime engine that can enforce workflows specified in YAWL
component to allow gaining informed treatment consents
syntax for any applications. Therefore, our models can be
required by a procedure in a treatment workflow dynamically,
audited and verified by third-parties for workflow accuracy.
and reasoning these consents automatically by using
Third, YAWL is open source software. Last, many research
ontologies to ensure those consents comply with consent laws
projects have recently used YAWL as a workflow-modeling
and regulations.
tool. Our medical workflow system is implemented as a
loadable module in OpenMRS and incorporates the knowledge
IV. WORKFLOW-BASED EMRS WITH CONSENT MANAGEMENT of the treatment processes as a YAWL specification. The
To achieve our goals, we proposed a prototype, shown in YAWL workflow engine uses these specifications to provide
Fig. 1. We develop a consent management component the caregivers the ability to step through the tasks. In addition,
incepted Workflow-based EMRs which refers back to our the workflow engine logs every incident into a database
previous works. creating the audit-able record of the work process provided by
77
Fig. 3. High level view of workflow based EMRs with consent management existing only required CMS. Asking what kind of
consents should be issued.
Consent Rule OWL
Management API
8. OpenMRS -> CMS (Step 8): Same as the previous
System step, this is additional step existing only required
Ontology of Consent
Rules
CMS. CMS return the answers to OpenMRS. The
WfMS decides whether the treatment should continue
Consents
Management or be aborted based on the treatment specification
System and on the patient’s treatment decision.
constraints on the
careflow X = f(x1,x2,…,xn) Fig. 4. Interactions between the system components
1. Request to YAWL YAWL
OpenMRS Management
6. Result to OpenMRS System
Workflow-based EMRs
2. Request to CMS
5. Result to YAWL
YAWL
Editor YWAL WfMS
Modeling Medical
Workflows
7. Request to
OpenMRS – CMS
Consent 3. Request to OS Ontology
YAWL Interface Gate
Management
OWL
way API Service (OS)
Service (CMS) 4. Result to CMS
8. Result to
OpenMRS
User ─ EMRs
Interface
OpenMRS
Finally, we pay attention to the privacy and security issues,
which are important considerations for any EMRs.
the medical organizations. In another hand, the Consent Access Control: The medical team as a whole provides
Management System acts as a customized workflow service in the required services to a patient who visits the medical center,
YAWL. from acceptance of a patient to the end of the treatment at the
1. OpenMRS -> YAWL: (Step 1) - When a caregiver facility. Each team member plays a designated role in
starts a medical treatment procedure in OpenMRS, a providing care with a set of assigned duties that are
“launch case” event request with workflow choreographed with each other, forming workflows. The team
specification id or name is sent to YAWL engine; together provides the care planned for the patient. We used a
YAWL engine enables some work item(s); If the role-based access control model to provide confidentiality.
enabled work item(s) does not request Consent Furthermore, enforced informed consent is an access control
Service, Then (Step 6) - OpenMRS checks out the with more complex rules.
enabled work item(s) and executes them. Accountability: To monitor quality of care and consistent
2. YAWL enables other appropriate work items based on with continuous improvement, an EMR system must have
control flow defined in the workflow specification, auditing capabilities. In our workflow-enforced EMR system
sends notification to OpenMRS. Then the with consent management, the quality care team can review
interactions between YAWL and OpenMRS are both procedures and outcomes from workflow logs and
repeated. Otherwise, consent logs, which provide an audit trail that satisfies
accountability requirements.
3. YAWL -> Consent Management Service (CMS):
(Step2) – If a task needs to check patient’s informed
consent, the consent management service is triggered. V. CONCLUSIONS
Enforcing diverse consent laws in an EMR system is useful
4. CMS -> Ontology Service (OS) (Step 3): CMS uses
for any and all EMR systems, but especially for EMR systems
OWL API to connect to the OS with patient’s
that treat mobile populations, such as military personnel and
information and other required consent information.
dependents. We have described an architecture and a prototype
An individual has be created and can be used Pellet
system that is based on an open source EMR system, a generic
to reason appropriate outcomes.
workflow engine and an Ontological rule system. Our system
5. OS -> CMS (Step 4): OS retunes the results reasoned enforces consents for medical treatments, which when
based on the SWRL rules to CMS. deployed will reduce medical malpractice, potential medical
treatment errors caused by missing informed consents, and
6. CMS -> YAWL (Step 5): CMS passed results to improve the patient-caregiver relationship. The processes of
YAWL, if valid consents have been hold, obtaining obtaining the consent and including exception processes are
consent from patients medical recodes; otherwise, also be recorded in the workflow management system, thus
asks OpenMRS (Step 6) retrieve appropriate consent becoming available for quality of care audits and reviews.
forms based on specific treatment task requirements.
7. OpenMRS -> CMS (Step 7): This is additional step
78
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