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<article xmlns:xlink="http://www.w3.org/1999/xlink">
  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Using the DTW method for estimation of deviation of care processes from a care plan</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>© Alexey Molodchenkov</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Proceedings of the XVIII International Conference «Data Analytics and Management in Data Intensive Domains» (DAMDID/RCDL'2016)</institution>
          ,
          <addr-line>Ershovo</addr-line>
          ,
          <country country="RU">Russia</country>
        </aff>
      </contrib-group>
      <fpage>242</fpage>
      <lpage>246</lpage>
      <abstract>
        <p>Hospitals increasingly use process models for structuring their care processes. Activities performed to patients are logged to a database or a log. These data can be used for managing and improving the efficiency of care processes and quality of care. In this article, we propose the method for estimation of deviation of care processes from a care plan. Care plan defines the steps of a patient treatment for a certain disease in a specific hospital. Care plan is built on the base of care process model. A care process model is built on the base of exemplars of care processes, stored in a database or a log. The Dynamic Time Warping (DTW) algorithm was used for estimation of deviation. The DTW algorithm measures a distance-like quantity between two given traces containing information about execution or not execution of actions defined by care plan.</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>1 Introduction</title>
      <p>Explore of methods for management of care process
(CP) as a flow of therapeutic and diagnostic activities
allows us to analyze situations with patients and
recommend to decision-makers (DM) appropriate action
for the treatment of patients. In this connection, occurs
increased interest in an automation of hospitals units
(accounting, reception, offices, warehouse and so on)
and an analysis and a formal representation of care
processes in order to support doctors work.</p>
      <p>The first area is deep enough elaborated - powerful
medical information systems for supporting of
therapeutic and diagnostic processes are developed.
Flows of patients can be optimized by simulation in order
to identify bottlenecks.</p>
      <p>
        The second area requires additional researches to
estimate stages of a care process and to develop
recommendations for decision-makers. Currently tools
for analysis and medical diagnostics, using different
classifiers with high accuracy and precision are
developed [
        <xref ref-type="bibr" rid="ref11 ref17 ref18 ref24 ref3 ref4 ref8">3, 4, 8, 11, 17, 18, 24</xref>
        ]. This area has a number
of features and is of great interest for us. A care process,
despite the standards, always has an individual
(personalized) character. There may be various deviation
from the selected care plan, depending on the changing
care conditions, concomitant deceases, etc. Therefore,
there are not only problems replying of a care process,
and operational management of a care process in terms
of possible deviations. Management is a particular
sequence of treatment actions (operations), which is
based on states of a patient, a prescribed care plan and
medical databases, i.e., precedents.
      </p>
      <p>The aim of our research is to develop algorithms and
tools that assist to a doctor by making proposals
(recommendations) on the organization of care process
in accordance with an actual patient’s state and care plan.
One of the objectives is to assess the quality of the
rendered medical services by comparing a patient’s care
process and care plan. The care plan defines the actions
of the doctor and is based on the care process model,
discovered from precedents.</p>
      <p>The multi-dimensional distance based on Dynamic
Time Warping (DTW) algorithm is used to differences
between care process and care plan. Experiments show
that DTW algorithm is effective to compare sequences of
actions in relation to care processes. We consider the use
of DTW algorithm to detect deviations between real care
process of a patient and care plan.
2 Formalization and optimization of care
processes</p>
      <p>
        Some methods for formalization and application of
care processes are described in [
        <xref ref-type="bibr" rid="ref1 ref12 ref17">1, 12, 17</xref>
        ]. Methods and
algorithms for discovery of models of care processes on
the base of event logs and precedents are described in [
        <xref ref-type="bibr" rid="ref12 ref13 ref14 ref15 ref16 ref19 ref3 ref6">3,
6, 12-16, 19</xref>
        ]. The model includes all traces from event
logs and precedents. Fig. 1 illustrates the Petri net
workflow process definition for handling a medical
complaint. In this figure we can identify the following
routing constructs: transitions “Identification” and
“Cardiologist” are AND-splits, “I diagnosis OK”, “I
diagnosis NOK” and “decide surgery” are AND-joins,
c4, c5, c8 and c10 are OR-splits and c6, c9 and c11 are
OR-joins.
      </p>
      <p>
        Automatic discovery of care process model is
difficult and actual problem. Some methods and
algorithms to solve this problem are described in articles
[
        <xref ref-type="bibr" rid="ref12 ref13 ref14 ref15 ref16 ref19 ref3 ref6">3, 6, 12-16, 19</xref>
        ]. Every trace in event logs and in a care
process model are characterized, in general, the timing
associated with the time of applying operations by
physician, and is characterized by quality indicators
(signs), defining the current state of the patient. In real
life we have deviations of real care processes from care
plans built on the base of care process model. These
deviations can be associated with a change in the
patient's state, lack or replacement of some drugs or other
medical devices, influence of other disease or other
causes.
      </p>
      <p>Identification
Radiologist
3 Identification of possible deviations of a
care process from the care plan</p>
      <p>
        Qualitatively expert assessment of a trace as a way on
the graph with temporary marks will allow to reveal and
estimate various deviations from the course of medical
and diagnostic process due to both objective and
subjective reasons and to eliminate them in the
subsequent realizations of care process.
Nonperformance of action which has to be surely executed in
care process, non-compliance of actions sequence,
performance of actions not provided by care process, etc.
[
        <xref ref-type="bibr" rid="ref2 ref9">2, 9</xref>
        ] are considered to be deviations. In care process it
is necessary to emphasize the deviations associated with
time limits imposed on actions. For example, some
actions have to be performed on the first day of the
patient arrival. The situation when the action has been
performed after the specified time interval is the
deviation in this case.
      </p>
      <p>
        The method for detection and visualization of the
deviations associated with performance of actions not
included in the model of care process and
nonperformance of actions that need to be executed is
described in the article [
        <xref ref-type="bibr" rid="ref10">10</xref>
        ]. In articles [
        <xref ref-type="bibr" rid="ref1 ref14 ref21 ref23">1, 14, 21, 23</xref>
        ] the
fitness function is used to check conformance of a care
process model and processes in event log. Petri nets are
used as formal representation of the care process model.
Let k is the number of different traces from the
aggregated log. For each log trace i, (1 ≤ i ≤ k), ni is the
number of process instances combined into the current
trace, mi the number of missing tokens, ri the number of
remaining tokens, ci the number of consumed tokens, and
pi the number of produced tokens during log replay of the
current trace. The token-based fitness metric F is defined
as follows [
        <xref ref-type="bibr" rid="ref1 ref21 ref23">1, 21, 23</xref>
        ]:
      </p>
      <p>
1 
F  1 
2 

ik1 n i mi  1 
ik1 n i ci   2 1 </p>
      <p>k
i1 n i ri 
ik1 n i pi </p>
      <p>In case of deviation detection in the course of
treatment of a specific patient, n and k are equal to 1 since
there is one trace and one instance. Function f will be as
follows:</p>
      <p>1 
f  1 
2 
m </p>
      <p> 
c 
1 
1 

2 
r 


p </p>
      <p>
        If f is equal to 1, then the trace is completely
consistent with the care process model. Otherwise, there
are deviations. In [
        <xref ref-type="bibr" rid="ref23">23</xref>
        ] it is shown that deviations from
the care plan lead to increased cost of treatment. In [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ]
the method that could check for deviations of care
process of a patient from a plan and locate specific points
of these deviations is described.
      </p>
      <p>
        Let’s consider a method for detection of the
deviations associated with the performance of actions not
provided by the care plan and non-performance of
actions provided by care process. The DTW method was
applied calculate the deviation or distance. The method
allows to find closeness between two measurement
sequences for a certain period of time. Generally, the
length of sequences can be different, and measurements
can be made with different rates [
        <xref ref-type="bibr" rid="ref7">7</xref>
        ]. DTW method
became widely spread in medicine. A theory of modified
DTW algorithms and its applications are presented in
[
        <xref ref-type="bibr" rid="ref22">22</xref>
        ]. In particular, recognition of human activity is
considered by comparison of the gestures presented in
the form of two-dimensional time series. Recognition of
such activity of the patients can be very useful in modern
healthcare for monitoring of patients condition and
automatic reporting creation for health workers. The
results of experiments confirmed the sufficient accuracy
of one modification.
      </p>
      <p>
        DTW algorithm calculates the optimal sequence of
transformation (deformation) between two time series [
        <xref ref-type="bibr" rid="ref20 ref7">7,
20</xref>
        ]. Let two numerical sequences (a1, a2, …, an), (b1,
b2, …, bm) are given. We obtain deviations matrix D,
where dij = |ai - bj|, i = 1,..,n, j = 1,..,m. At the second step
we build deformations matrix. Each element rij is defined
by means of dynamic programming algorithm and local
optimization criteria: rij = dij + min(ri-1, j-1, ri-1, j, ri, j-1).
The path in the deformation matrix defining a deviation
begins in its left upper corner and ends in the right lower.
The value R of deformation is defined by the sum of the
minimum local deviations of each path element. R is
divided by the number of path elements and is considered
as distance estimation between sequences.
      </p>
      <p>We consider the example of DTW algorithm
application for comparison of processes of bronchial
asthma treatment that is presented in Table 1 (data are
provided by the Medical center of the Central bank of the
Russian Federation). Table contains care plan that
includes operations mandatory to perform and reports of
real care processes of three patients.</p>
      <p>To formalize care process reporting we will define
the following variables: «executed» → α = 1, «not
executed» → β = -1, «not required» → σ = 0.The distance
between «executed» and «not executed» operations we
will define as |α - β| = 2, and the distance between
«executed» («not executed») and «not required»,
respectively |α - σ| = |β - σ| = 1.</p>
      <p>Obtained care process parameters are included in
Table 2 in the form of sequences</p>
      <p>The sequences can now be compared. We will apply
the DTW method to calculate care process deviations of
care processes from the care plan. In Fig. 2 the process
of comparison of the Patient 3 (P3) course of treatment
with the plan (P) is presented as comparison of two
sequences by the DTW method using the dynamic
programming scheme. In the table the way determining
the minimum value of deviation R is highlighted in color.
In this case R =2.257.</p>
      <p>We will apply the DTW method to calculate
deviations of Patients 1 and 3 (respectively P1 and P3)
care processes. All necessary data for comparison of
processes are shown in Fig. 3.</p>
      <p>Table 3 demonstrates possibility of distances
calculation between precedents. The more the distance,
the more precedents are differed from each other. The
table shows that Precedent 1 (care trace of the Patient 1)
is close to the plan.</p>
      <p>Transfer from the
reception area to
the ward with
beds /ICU through
2 hours or less
External
respiration
function or Peak
expiratory flow
rate
Pulse oximetry</p>
      <sec id="sec-1-1">
        <title>Chest radiography</title>
      </sec>
      <sec id="sec-1-2">
        <title>Pulse oximetry</title>
      </sec>
      <sec id="sec-1-3">
        <title>Peak Flow Meter</title>
      </sec>
      <sec id="sec-1-4">
        <title>Peak Flow Meter External respiration function</title>
        <p>Inhaled
glucocorticosteroi
ds
Inhaled
ß2agonists</p>
      </sec>
      <sec id="sec-1-5">
        <title>Peak Flow Meter External respiration function</title>
        <p>Systemic
glucocorticosteroi
ds
Inhaled
glucocorticosteroi
ds
Inhaled
ß2agonists</p>
      </sec>
      <sec id="sec-1-6">
        <title>Execute Not</title>
        <p>d required
Execute Execute
d d
1 day in ICU / ward with beds
Not Not
required required
Iaoncrhtfiaonlrgemdßo2sth-eaorgortol-nists Exedcute
2-7 days in ward with beds
edCxooecnrtsocuirsletatthioenraopfyan Exedcute
Consultation of a
physiotherapist</p>
      </sec>
      <sec id="sec-1-7">
        <title>Execute d</title>
      </sec>
      <sec id="sec-1-8">
        <title>Execute d Execute d</title>
      </sec>
      <sec id="sec-1-9">
        <title>Execute d</title>
      </sec>
      <sec id="sec-1-10">
        <title>Execute d Not required</title>
      </sec>
      <sec id="sec-1-11">
        <title>Execute d</title>
      </sec>
      <sec id="sec-1-12">
        <title>Execute d</title>
      </sec>
      <sec id="sec-1-13">
        <title>Execute d Execute d</title>
      </sec>
      <sec id="sec-1-14">
        <title>Execute d</title>
      </sec>
      <sec id="sec-1-15">
        <title>Execute d</title>
      </sec>
      <sec id="sec-1-16">
        <title>Execute Execute d d</title>
        <p>8-21 days in ward with beds
Execute Not</p>
        <p>d required</p>
      </sec>
      <sec id="sec-1-17">
        <title>Execute d Not required</title>
      </sec>
      <sec id="sec-1-18">
        <title>Execute d</title>
      </sec>
      <sec id="sec-1-19">
        <title>Execute d Not required</title>
        <p>Not
required</p>
        <p>Not
required</p>
        <p>Not
required
Not
execute
d</p>
      </sec>
      <sec id="sec-1-20">
        <title>Execute d Execute d</title>
      </sec>
      <sec id="sec-1-21">
        <title>Execute</title>
        <p>d</p>
        <p>Not
execute
d</p>
      </sec>
      <sec id="sec-1-22">
        <title>Execute d</title>
      </sec>
      <sec id="sec-1-23">
        <title>Execute d</title>
      </sec>
      <sec id="sec-1-24">
        <title>Execute d Execute d</title>
        <p>Not
execute
d</p>
      </sec>
      <sec id="sec-1-25">
        <title>Execute d</title>
      </sec>
      <sec id="sec-1-26">
        <title>Execute d</title>
      </sec>
      <sec id="sec-1-27">
        <title>Execute d</title>
      </sec>
      <sec id="sec-1-28">
        <title>Execute d Not required</title>
      </sec>
      <sec id="sec-1-29">
        <title>Execute d</title>
      </sec>
      <sec id="sec-1-30">
        <title>Execute d</title>
        <p>The distance according to the established scheme is
R = 1.935. Results of pair comparison of all patients care
processes are given in Table 3.</p>
      </sec>
    </sec>
    <sec id="sec-2">
      <title>3 Conclusion</title>
      <p>Medical processes describing care of patients are
useful in daily work of physicians, especially in difficult
situations. Certain step towards the creation of tools to
support physician’s work in the course of care process is
taken in the article. At the current stage of research,
methods for the analysis and evaluation of deviations
associated with performance and non-performance of
actions for elementary care processes are chosen and
studied. The problem is solved on the existing
generalized care process model and reduced to
evaluation of deviations of care precedent from available
traces. The proposed method allows verifying
compliance of treatment with the care plan and
procedures established by care standard. In addition it
helps the decision-maker with the choice of a rational
way of the treatment carried out with the use of strategies
and rules. In reality, to make a choice of a rational way
of treatment it is necessary to sort and estimate rather
large number of admissible trajectories taking into
account strict binding of operations at the time-point that
certainly complicates process of comparison and
determination of distances. Authors intend further to
research similar processes.</p>
      <p>The reported study was funded by RFBR according
to the re-search project No 16-37-00034 «Research and
development of methods for analysis of deviations of
executed medical processes from their model»</p>
    </sec>
  </body>
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