Newsgroups: bit.listserv.ethics-l
Date:         Wed, 29 Jul 1992 12:24:00 EDT
From:         SchwartzM@DOCKMASTER.NCSC.MIL
Subject:      Re: Medical Applications Of Computers
Comments: To: ethics-l@UGA.CC.UGA.EDU

Subject: In response to ethics-l question on use of computers in
         medicine

Date:    July 29, 1992
From:    Marc Schwartz  (schwartzm at dockmaster.ncsc.mil)


A message was posted to ethics-l regarding the use of computers in medicine
with respect to prediction systems used for intervention/therapy decision
making and with respect to primary diagnostic use.

In the first case, I can comment based on personal experience.  As Director
of Clinical Services for Summit Medical Systems, I am directly involved in
the development of predictive algorithms for use in assisting physicians
and health care providers in making interventional determintations.  We
(my company) are involved in the design, implementation and management of
several national and international databases for cardiac surgery and
cardiology.  We have access to large quantities of data, as well as
recognized experts in each field for the purpose of design and on-going
statistical analysis of the programs.

At the present time we are developing a predictive algorithm, based on
Bayes Theorem, that will in fact be used for two purposes.  We are also
reviewing the use of neural networks for the same application.  The first is
to give the surgeon the ability to review his or her practice experience
to allow for comparison with "national" standards of care.  This will
report a comparison between the actual observed "operative mortality" in
cardiac surgery for patients undergoing coronary bypass procedures with
what has been predicted by the implemented algorithm.  Thus, the surgeon
can compare their practice experience against this defacto standard derived
from a national database that contains the experience of a large portion
of the practicing cardiac surgeons in the U.S.

This can be used to identify practices that have an outcome that may be
either better than, the same as, or worse than predicted based upon the
algorithm.  This is in fact already in place in New York State, where it
is used as part of the credentialing process.  The so-called risk
adjusted mortality rates have already been posted by hospital and
physician in the general media.  The main problem has been to develop an
appropriate algorithm that takes into account the fact that a surgeon
that operates on "older and sicker" patients, should expect to see a
higher mortality rate than one who sees mainly younger, more elective
types of patients.  Thus a surgeon in Miami, where the mean patient age
is somewhere near 70, should expect to have a higher mortality than a
surgeon here in Minneapolis, where the mean age is about 62.  Increasing
age is a significant risk factor in cardiac surgery.  It can be used as
one tool in the effort to implement some form of quality assurance so
that surgeons that are not performing up to some specified standard can
review their practice, alter the types of patients they operate on or
in extreme cases, as has happened in New York, their license to practice
is revoked or suspended pending review by the state agencies involved.
To paraphrase a recent report on Prime Time Live, the ABC network news
magazine, "We spend more time trying to decide on which car we want to
buy, than we do learning about the surgeon that is going to split our chest
open."  These predictive algorithms used in a retrospective fashion are the
first step to a "Consumers' Reports" for cardiac surgery.  In fact, the
state of Pennsylvania is involved in exactly trying to do that this year.
They have already published a draft of "A Consumer's Guide to Choosing a
Surgeon and Hospital for Cardiac Surgery."

The second application of the predictve models is to attempt to apply them
in a prospective fashion to allow for a more informed judgement on the
part of the medical providers in determining the appropriate intervention
for an individual patient.  This can be done for either short term or long
term outcome.  We are working on two models at this point, one for short
term operative mortality (30 day), the other for long term (15 year) outcome
predictions.  This gives the doctors and patient the ability to consider
options for treatment in a more objective fashion and can become part of
the "informed consent" process.

The danger here is that one option that is already being considered is the
use of this type of system for cost containment reasons.  For example, if
the predicted risk of mortality is over some threshold level, the insurance
payors may not cover the procedure. Therefore, one now has a risk based
mechanism for determining payment and therefore access to some medical
procedures.  While I do not want to get into a political discussion here,
one has to consider that another option being reviewed, such as in the
state of Oregon, is to simply put together a "value list" of procedures
that some panel decides they will pay for and others that they will not as
part of a health care rationing system.  Is this better to deny totally
a procedure that may be beneficial to some, and grant procedures to a group
that may not have a positive outcome.  For example, should we allow a 95
year old, already in the intensive care unit of a hospital to undergo open
heart surgery (which happens by the way), considering they have a short
life expectancy as is, and deny an infant some new procedure that can
offer a high probability of long term survival simply based on a global
rationing system that says we will pay for adult cardiac surgical
procedures, but not for "high tech" congenital surgery.  Should we not
base this decision on the probability of positive outcome?  A rhetorical
question to ponder.  A question society will need to answer as part of
current efforts to control escalating health care costs while trying
to maintain quality at the same time.

A personal comment:  Some may want to say to me that if it was my mother
in that hospital ICU, I would demand that the surgeons "do everything"
they can to help her.  I am not insensitive to the issues.  I spent 5 years
working as a cardiac surgical assistant before joining my present employer
6 years ago.  I participated in some of those discussions with family
members of patients.  Two and a half years ago my wife's mother died at
age 51 (yes 51) from recurrence of pancreatic cancer.  We went through many
of those same heart wrenching decisions.

In terms of computer based diagnostic systems, the second part of the
posting, there are many such systems in use at the present time.  The key
with all of these systems, is to have an appropriate knowledge base to
work from, whether that is composed of recognized experts in the field or
existing empiric databases of actual clinical experience.  The other
important factor is to develop a set of standards for data reporting and
interpretation to remove the subjective bias likely to occur in any such
system.  These standards must include the definition of the data dictionary
(the actual data being tracked) and the criteria for defining the data
that is entered so that all reporting sites are defining a heart attack or
other clincal presenting symptoms in the same way.  This is mandatory if
one is going to be able to develop a system that can be extensible to
the general medical community.  Too often, a clinical trial or study can
be used for the institutions that participated in the trial, but cannot be
made general enough to be used by the broad provider population.  A study
or system based at a large academic hospital may not be appropriate for
a small community hospital due to patient referral differences or differing
availability of certain diagnostic technologies such as CAT scans or MRI
procedures.

There are implications in terms of FDA scrutiny with these systems as well.
The FDA has a very significant role in the regulation of computer systems
used in the patient care setting.  To oversimplify, the level of scrutiny
depends upon the threat to the patient of system failure and the ability
to intervene by the medical personnel involved in the patient's care.  There
is no scrutiny for medical texts, for example, where physician judgement
must be used to interpret the application of that knowledge to a patient.
However, the regulation is tight for a cardiac valve prosthesis where
failure can result in instant death.  I would speculate that such scrutiny
for "medical expert" systems, will likley increase over time as they become
more prevalent in the patient care setting and medical professionals utilize
these systems more and more in their provision of care to the patient.

I would be open to further discussion of the issues if it is deemed
important enough by the readers.

Marc Schwartz
Director, Clinical Services
Summit Medical Systems
Minneapolis, Minnesota
e-mail: SchwartzM at dockmaster.ncsc.mil
voice:  612-473-3250

Note: The opinions expressed above are my own and do not imply support
      by my employer.
Comments: Gated by NETNEWS@AUVM.AMERICAN.EDU