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Design, Implementation and Evaluation of an Architecture based on the CDA R2

Document Repository to Provide Support to the Contingency Plan

Fernando Campos a,c

, Daniel Luna a , Dean F. Sittig

b , Fernán González Bernaldo de Quirós

a Health Information Department, Hospital Italiano de Buenos Aires, Argentina

b School of Biomedical Informatics, University of Texas Health Sciences Center at Houston, Houston, TX, USA

c HL7 Argentina

Abstract

The pervasive use of electronic records in healthcare

increases the dependency on technology due to the lack of

physical backup for the records. Downtime in the Electronic

Health Record system is unavoidable, due to software,

infrastructure and power failures as well as natural disasters,

so there is a need to develop a contingency plan ensuring

patient care continuity and minimizing risks for health care

delivery. To mitigate these risks, two applications were

developed allowing healthcare delivery providers to retrieve

clinical information using the Clinical Document Architecture

Release 2 (CDA R2) document repository as the information

source. In this paper we describe the strategy, implementation

and results; and provide an evaluation of effectiveness.

Keywords:

Electronic Health Record; CDA repository; Contingency plan.

Introduction

There is an increasing use of electronic health record,

specifically the replacement of paper-based health record with

Electronic Health Records (EHR) [1]. Therefore, every

healthcare delivery process relies on information systems to

ensure patient care. This brings up the threat of a lack of

information for decision making in case of system downtime.

One of the biggest risks in this scenario is inaccessibility of

information needed to administer medication [2, 3].

Unexpected information technology (IT) downtime occurs

more and more often with widespread adoption of electronic

systems in healthcare [4]. Although the reliability of

computing hardware has improved significantly, the

complexity of software has escalated, especially in healthcare

[4]. Risk identification and risk assessments are essential steps

for developing preventive measures. Equally important is

institutionalization of contingency plans as our data show that

not all failures of health IT can be predicted and thus

effectively prevented [5].

Most institutions had only partially implemented

comprehensive contingency plans to maintain safe and

effective healthcare during unexpected EHR downtimes [6].

Preparing for these unexpected downtimes should be a part of

every EHR-enabled healthcare organization’s overall patient

safety strategy.

As most experts state, an effective contingency plan should

address the causes and consequences of EHR unavailability,

triggering processes and preparations that can minimize the

frequency and impact of such events, ensuring continuity of

care [7-9].

The objective of this paper is to describe the design,

implementation, and evaluation of the IT component of a

contingency plan that uses the Clinical Document Architecture

(CDA) Release 2 (R2) document repository to support

continuity of care during system downtime.

Methods

Settings

The Hospital Italiano of Buenos Aires (HIBA) is a nonprofit

academic medical center founded in 1853. HIBA has a

network of two hospitals with 750 beds (250 for intensive

care), 800 home care patients under care, 25 outpatient care

centers, and 41 operating rooms. There are more than 2,800

physicians, an equal number of medical team members and

1,900 administrative and support staff. During 2013-2014

there were 45,000 admissions, 3 million outpatient visits and

45,000 surgeries (half of them ambulatory).

In 1998 HIBA began the gradual implementation of a

Healthcare Information System (HIS) developed in-house,

from data capture to analysis. It includes a web based,

modular, problem-oriented and patient-centered EHR. This

EHR is known as Italica and allows inpatient, outpatient,

home care, and emergency care records. Italica also allows

users to order ancillary tests, prescribe medications and view

results including imaging through an integrated picture

archiving and communications system (PACS).

The EHR has a relational database record and also a CDA R2

document-based repository, which is digitally signed by

professionals participating in healthcare delivery. This

repository is used to interoperate with payers and other EHRs,

and to make information portable for patients or other external

healthcare providers. The system architecture for sharing

medical information is based on HL7 CDA and a

repository/registry XDS (Cross Enterprise Document Sharing)

model defined by IHE (Integrating the Healthcare Enterprise).

The document repository currently contains 36.4 million

CDAs [10].

This repository allows the organization to operate without

need for paper records, because information exchange

between actors or systems is facilitated by these documents.

For instance, for ancillary systems like imaging or laboratory,

order is no longer paper-based but a digitally signed CDA R2.

Likewise, result reports are not printed, but reviewed directly

in the EHR through a CDA R2 sent by the ancillary service.

Since 2012, and based on this implementation, all procedures

and communications for healthcare continuity while systems

recover from a meaningful interruption have been redesigned,

mainly for the inpatient setting. Two levels of contingency

were identified:

MEDINFO 2015: eHealth-enabled Health I.N. Sarkar et al. (Eds.) © 2015 IMIA and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License. doi:10.3233/978-1-61499-564-7-173

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F. Campos et al. / Design, Implementation and Evaluation of an Architecture Based on the CDA R2 Document Repository174

Using the CDA repository, only 1 query is needed, involving a

snapshot of the current active inpatients or emergency care

episodes, and the query to the document repository for the

URL for the patient’s last prescription CDA. Rendering the

information only requires transformation of the XML using an

XSLT stylesheet.

The downtime record between March 2012 and June 2014 is

presented in Table 2. This table shows dates and times when

the EHR was not available, and for how long. The column

‘Type’ indicates if the lack of EHR was programmed or not,

and then the cause. The column “Level” indicates the severity

level assigned to the cause and for each event, the quantity of

pages printed.

Table 2 – Downtime Record and Pages Printed

Date

Begin Time

Duration

(Hrs.)

Type

Motive Level Pages

08/03/12 09:15 05:55 U EHR bug 1 365

05/04/12 23:10 02:00 U DB issue 2 301

07/04/12 20:00 02:00 P DB mainte- nance

2 10

27/04/12 09:50 06:15 U EHR bug 1 303

12/05/12 22:40 07:50 P Upgrade DB

2 1254

09/06/12 22:00 07:00 P Upgrade Server memory

2 867

29/12/12 05:30 04:30 U EHR bug 1 425

23/04/13 05:30 25:01 U Shut- down power

2 1450

26/04/13 12:30 01:00 U Router down.

2 23

27/04/13 18:00 03:00 P Server mainte- nance

2 150

25/05/13 16:00 05:05 P Server mainte- nance

2 1050

15/06/13 17:00 07:38 P Server mainte- nance

2 1080

26/07/13 20:00 13:30 P New DB cluster

2 1250

14/09/13 18:00 02:00 P Update switches firmware

2 306

11/01/14 02:00 04:30 P Update switches firmware

2 309

24/06/14 12:10 01:10 U DB issue 2 124

*Type: U: Unplanned - P: Planned

As an example, a change of servers’ operating system

produced downtime of 13:30 hours. In this contingency, all

prescriptions were printed, and 1,250 sheets of paper were

used to print 759 prescriptions in 1 hour 15 minutes.

In the contingency Level 1 case, even though the CDA

browser was used, the critical care units and emergency care

areas preferred to print out the prescriptions in order to be able

to make written notes of instructions and any other changes.

Details of each test simulation are presented in Table 3,

including the time elapsed since last generation (mins), the

number of inpatients at that moment, records that matched at

the simulated downtime and the differences found.

Table 3 - Evaluation Cases

Case # Minutes

elapsed

since last

generation

Inpatients

at down-

time

Matches Diffe-

rences

1 2 654 650 4

2 10 695 667 34

3 18 712 668 44

4 25 730 666 64

5 5 759 723 36

6 12 759 707 52

7 26 762 686 76

8 5 771 759 12

9 5 721 697 24

10 15 678 630 48

11 14 699 643 56

12 10 712 680 32

13 17 734 686 48

14 5 723 707 16

15 15 745 709 36

16 13 711 671 40

17 22 733 657 76

18 5 732 712 20

19 1 722 722 0

20 25 745 673 72

14,497 13,713 784

The differences were evaluated in each case: how many were

caused by a patient being admitted or discharged, how many

were caused by a change in medications. Medications for

newly admitted patients and missing updates were deemed

errors. New inpatients with no medications and discharged

patients still in the contingency system were not deemed

errors.

For example, for the second case, 34 differences were found,

22 of them due to patients admitted during the 10 minutes

from the listing generation but with no prescription, 6 patients

with their prescriptions updated, 13 patients discharged and 3

patients had new prescriptions. The evaluation result is

presented in Table 4.

Table 4 – Evaluation Results for Contingency Listing

Case

Diff.:

New

Admissi

(1) Diff.

Medicat

ion

Change

Diff.:

Dischar

ged

patient

(2) New

patient

with

prescripti

ons

Errors

(1) + (2)

1 1 1 2 0 1

2 12 10 6 6 16

3 22 6 13 3 9

4 34 10 17 3 13

5 18 3 15 0 3

6 26 4 20 2 6

7 8 10 55 3 13

F. Campos et al. / Design, Implementation and Evaluation of an Architecture Based on the CDA R2 Document Repository 175

8 6 3 3 0 3

9 12 3 9 0 3

10 22 2 20 4 6

11 29 6 19 2 8

12 16 5 11 0 5

13 23 10 6 9 19

14 8 2 6 0 2

15 17 5 12 2 7

16 20 7 13 0 7

17 39 17 16 4 21

18 10 3 7 0 3

19 0 0 0 0 0

20 36 9 23 4 13

359 116 273 42 158

The results show that printed prescriptions concur in 98.91%

(14,339/14,497) of those registered in the EHR.

The relationship between the time elapsed since the last

generation and the differences found after downtime are

presented in Figure 3.

Figure 3 – Differences (Time)

Discussion

This architecture allows information to be available from all

delivery care locations, and allows every actor requiring the

information to access it.

The printing process has a predefined sequence for the various

locations, prioritizing critical care units, emergency care,

pediatric care, and then other services.

The more time elapses between the generation of the latest list

and the EHR unavailability, the greater the difference in the

prescription record. Although the medical staffs understand

that any changes made in less than 30 minutes could be re-

prescribed, they are aware that the nurse work based on the

lists received and these should be corrected manually after the

EHR disruption.

In the real scenario, other times should be evaluated because

doctors do not make decisions on every patient immediately

after the system goes down. Other changes could have been

made during the downtime and will not be represented in the

print version (prescriptions, bed changes, etc.). So we have

two mechanisms that generate gaps between the information

documented and the reality: gaps between the last local

backup and the down time and gaps between the down time

and the moment at which the caregiver uses the print version.

This study evaluated the differences between Point 1 and

Point 2. The effectiveness of this architecture at Point 3 is

pending evaluation and will be the subject of a future study.

The alternating folder strategy was required because in one of

the tests if network connectivity or power was interrupted just

when the folder was being generated, its structure could be

corrupted. If this happens, the other folder can be accessed.

Prescription printed forms are used mainly by the nurses to

ensure care continuity for patients. They continue recording

their actions there in order to update the EHR when the system

comes back, or scanned as part of the care record.

One limitation, as shown by the evaluation of the results, is

that not all the information is available because there can be

changes between the executions of the refresh process: patient

transfers, new prescriptions, admissions or discharges.

No other experience in creating this kind of repository was

found in the literature, either as a redundant repository or for

use on a contingency basis.

Conclusion

Downtime in information systems, both planned and

unplanned, is inevitable, even in the healthcare environment,

where systems need to be available 24-7-365. Implementing

tools such as the one presented in this paper provides

contingency plan support and helps mitigate many risks that

threaten information availability at the point of care.

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Address for correspondence

MSc. Fernando Campos Chief of Software Engineering Health Informatics Department Hospital Italiano de Buenos Aires HL7 Argentina Chairman [email protected]

F. Campos et al. / Design, Implementation and Evaluation of an Architecture Based on the CDA R2 Document Repository 177

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