Hello, I'm Marc Beller and I'm here to talk

to you about information systems used in health care.

as you might expect, there are

many informations used, information systems used in

health care and there are many data produced by the use of these systems.

These data can be rich for use in research.

I chose to categorize the information systems in this fashion.

We have information systems that are used

for general administration, for research administration, clinical

operations, clinical care, there are ancillary clinical

systems, departmental systems, and data aggregation systems.

This drawing is intended to depict many of the information systems

that are commonly used in health care organized by the category.

You'll notice that one of the systems, the

electronic health records system, actually appears in both categories

because this system is used for direct clinical care

as well as it is considered an aggregation system.

Some of the general administration systems you

might encounter are the financial systems like

the general ledger which is responsible for

accounting functions such as budget, expenses, financial reporting.

Also, there is the procurement and disbursement system

used to track accounts payable, accounts receivable with vendors.

The human resources system is responsible for knowing

who the people are in the organization and payroll, very important, and the time

and attendance system is used to track

just that, time and attendance for hourly staff.

Contract systems are used to manage

legal agreements, such as expirations, and reminders.

And then incident management systems are used by help desks to record customer

inquiries and technical issues.

In research we have many administrative systems.

A clinical trials management system may be used for tracking the research

studies, the protocols, the study contacts and the study participants.

The institutional review board or IRB system is used for tracking research

studies, protocols, consent forms. Grant management

is used to spo, to track study sponsor information.

And data management systems are used to

collect information and for use in reporting.

You also might have a bio-specimen management system where

tissue samples can be used stored and tracked for research.

So a question, where would data be obtained to asses help desk call volume?

And the answer, would be, in our

incident management system, if your organization employs one.

Clinical operation systems at a, at their core include,

perhaps, a hospital admitting and registration and billing system where

we track patient stays, insurance billing, what we refer

to sometimes as technical charges, and room and bed charges.

The physician scheduling and billing system

tracks patients clinic visits, and also does

billing for physician type of services, which we refer to as professional.

There also may be a, a separate or integrated

bed management system, which tracks patients location within the facility.

Additional clinical operation systems includes staff

scheduling, which is used often by nursing.

A patient transport and housekeeping services systems, which track

tasks that are dispatched and then tracked to completion.

A nutrition management system where we

track patient meals and their distribution.

And a risk management system for

self reporting of incidents and tracking resolution.

So, another question, where would we obtain data to assess hospital admissions?

And the answer would be in our

core hospital admitting registration and billing system.

Clinical care systems, at their heart, would include a medical record or

an electronic health record, this is also referred to as a patient's chart.

This information would include allergies, immunizations,

diagnosis, medications, vital sights, procedures, lab

test results, interpretive reports, care plans

and many other pieces of information.

In addition to an electronic health record,

you might have a prescription writer which is

used to write prescriptions for patients to

take home and fill at their local pharmacy.

In addition, you might have in patient and outpatient order entry systems, which

allows providers to order procedures, lab tests or medications for their patients.

There are

documentation systems, some used by nursing, some used by physicians.

And there are biomedical systems, which include devices that are connected to

the patient and produce data output, which is, which can then be used.

Ancillary clinical systems include pharmacy,

laboratory, radiology and several others.

These systems tend to track orders and filling

of those orders for medications or diagnostic testing.

And the radiology systems typically include a procedure

tracking module as well as an imaging module.

Now I should point out that the imaging module may

be generalized for use across radiology and other services like cardiology

or they may be dedicated for individual applications.

In addition, you might have a materials management system,

which would track inventory, consumption and replenishment of those items.

And we have departmental systems, which

would include things like an emergency department

system for tracking patients and documentation.

operative services systems, which would be used in the OR

for scheduling procedures and tracking those procedures and documenting them.

And there might be a medical transport system used for air and ground transport

of patients to the facility or between

facilities, these sometimes also include a documentation component.

So, some more questions.

Where would we obtain data to assess inpatient medication dispensing?

The keyword there is dispensing.

We would obtain that from the pharmacy system where we

track the medication orders and the inventory as well as dispensing.

Where would we obtain data to assess ER wait times?

That would be in our Emergency Department patient

tracking system, which typically has a waiting room and

then the time between waiting and patient being

put in a particular room in the Emergency Department.

In addition, and finally, we have data aggregation systems.

These are systems that collect data from other source systems,

such as, as I previously mentioned, the electronic health record,

a personal health record, which is typically a patient-facing view

this could also be re, referred to as a patient portal.

There are enterprise data warehouses that aggregate data from a variety

of systems. And then there are research oriented, what

I would call data warehouses or data marts, such as patient

identifiable data sources as well as de-identified data sources.

Now there are some challenges to think about, specifically with data

aggregation systems, there's magic that happens in between the source systems and

the aggregation systems.

One of the potential issues is that not

all of the data is integrated from a particular

system or the, not all of the data sources

are pro, are provided in the enterprise data warehouse.

In, in addition you have to consider the

pros and cons of each each potential solution.

So for

example, obtaining data from the source systems, this data are not integrated with

other data and that integration would have to be performed on your own.

In addition, there could be some production

impact in obtaining data from the source

system such as response time based on

system resources when you're running such a query.

The alternative, ob, obtaining data from the aggregation

systems, the content may or may not be complete, again

as I mentioned, not all systems and not all the data.

There also can be time delays in getting the

data from the source systems to the aggregation systems which

may or may not be an issue for your

purposes but nightly updates are very typical in this environment.

Other potential challenges would include

duplicate patient medical record numbers where

a patient, the same patient has multiple medical

records and could be there for counted multiple times.

this is a common problem in health care that is consistently being addressed

and hopefully the small volume of this

occurrence would be negligible in your research.

In addition free text data is often available in the

medical record, but it's difficult to query because it's not discreet

data and therefore, there's some techniques like natural

language processing, which can be used to remedy that.

In addition, there can be different nomenclature

used across systems that could make things challenging.

Billing diagnosis codes, they can be used to rule

out a diagnosis and therefore, can not necessarily be used

to confirm a patient's diagnosis. Prescriptions,

they are written but they may or may not get filled by the patient and even if they

do get filled by the patient, we def, definitely don't know whether or not they

have taken them. And patient location information can be

incomplete or inaccurate. there are real-time location systems using

RFID or other technology that are improving on our ability to

be able to know where a patient was in our facility.

And, finally there can be duplicate systems used by different departments.

For example the adult versus pediatric areas of a hospital

may have different systems to track cardiology procedures

and, and imaging and that sort of thing.

So, there might be some challenges there in

obtaining a set of data from multiple systems

that should be the same but would potentially

be different based on different vendors being used.

with imaging data, imaging files can be quite large in size

and that takes a while to transfer, and the meta data are

usually available in the envelope that the imaging files are contained, but

this can be limited and may or may not meet your needs.

And, finally and importantly, de-identification

of image data can be difficult

because often there can be patient

identifiable information within the image itself.

So, in closing there are many information systems used to support health care.

The data produced by these systems is rich for research and knowing where

to find data to answer research questions will help you on your way.

Thank you.

Common Information Systems Used in Health Care

Data Management for Clinical Research

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