International Journal for Quality in Health Care Advance Access originally published online on April 14, 2005
International Journal for Quality in Health Care 2005 17(4):363-367; doi:10.1093/intqhc/mzi041
International Journal for Quality in Health Care vol. 17 no. 4 © The Author 2005. Published by Oxford University Press on behalf of International Society for Quality in Health Care; all rights reserved
The DNA damage response and patient safety: engaging our molecular biology-oriented colleagues
Karin Pukk1 and
David C. Aron2
1 Medical Management Center, Karolinska Institute, Stockholm, Sweden, 2 Division of Clinical and Molecular Endocrinology, Case Western Reserve University School of Medicine, and 2VA HSR&D Center for Quality Improvement Research, Louis Stokes Cleveland, Department of Veterans Affairs Medical Center, Cleveland, Ohio, USA
The imperative to improve patient safety is clear. Biomedical scientists, who account for a large proportion of medical school faculty, and clinicians tend to speak different languages. Biological systems are remarkable for their high robustness, flexibility, and efficiency. Biomedical scientists possess a profound understanding of the complex mechanisms that govern organisms. Their insights may inform the design of safer health care systems. We propose a model to assist in bi-directional communication between these disciplines. We use the principles and mechanisms of the DNA damage response to describe the central concepts of safety science and discuss similarities and differences between the systems of DNA repair and organizational approaches to safety in health care. We suggest that such biomedical scientists can and should be engaged in the effort to bring education about patient safety management into the medical school curriculum and to make patient care safer.
Keywords: complexity, DNA repair, medical education, patient safety, systems thinking
Address reprint requests to David C. Aron, Education Office 14(W), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, 10701 East Blvd, Cleveland, OH 44106, USA. E-mail: david.aron{at}med.va.gov
Accepted for publication March 6, 2005.
Medical schools have responsibility for preparing every graduate to practice medicine in ways that ensure the safety of patients, but have fallen short [1,2]. A number of factors in medical education that allow for the graduation of students unable to practice safely or improve their care have previously been identified [3]. We suggest that another contributing factor is the difficulty of integrating basic science, the science of normal disease biology, and clinical medicine, the science and art of practice. This issue has underlain much of the effort in curricular reform over the past 100 years. In fact, it has been suggested that the gap between basic scientists and clinicians has increased over the past quarter century [4]. Among the reasons we have previously suggested is the organizational culture of academic medicine in which the ethos is the value of the discovery of new knowledge over all else and the relative merit of the ‘hard’ science of molecular biology as opposed to the ‘softer’ social sciences [3]. Moreover, basic scientists, who account for a large proportion of medical school full-time faculty, and clinicians tend to speak different languages or at least different dialects. The language of molecular biology, the lingua franca of academic medicine, has been very different from the language of patient safety and systems thinking, yet both talk about complex interdependent processes and activities in their work. The Rosetta stone, a tablet from the 2nd century BCE consists of three inscriptions that represent a single text. This parallel translation allowed the deciphering of Egyptian hieroglyphics. A Rosetta stone to translate between the languages of molecular biology and patient safety management could help faculty understand each other. Such communication could facilitate meaningful reform of the medical school curriculum to include patient safety management. In recent years there has been an increasing application of biological concepts to describe organizations as well as in system design [5–9]. We propose the outline of such a model to assist in bi-directional communication between these disciplines. We use the principles and mechanisms of the DNA damage response to describe the central concepts of safety science and discuss similarities and differences between the systems of DNA repair and organizational approaches to safety in health care.
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Can cells teach us about health care organizations?
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Parallels between organisms and organizations can be drawn from
complex systems theory [
5,
10]. Tables
1 and
2 illustrate some
of these parallels. A complex system is any system that involves
a number of elements, arranged in structure(s) that can exist
on many scales (Table
1). Such a system is characterized by
structures with interacting components, processes, and patterns
of behavior or outcomes [
11,
12]. The interactions of the system’s
components lead to an emergent phenomenon whereby the whole
is greater than the sum of its parts; biochemical reactions
are observed at the level of the cell whereas consciousness
appears at the level of the organism. Non-linear behavior is
also common; large interventions may have little effect while
small changes may have large effects. Although there may be
qualitative as well as quantitative differences as one moves
along the hierarchy, there are also some striking similarities.
Both DNA replication and health care delivery can be thought
of as complex systems. Similarly the DNA damage sensing and
repair system and the system for ensuring patient safety can
be thought of as complex systems. They all have structures and
processes to manage variability in order to ensure proper functioning
and outcomes, although adverse outcomes may certainly occur
(Table
2). This variability may be in input or output. Each
has features to identify and reduce the variability in the input,
features enabling the system to be resilient against residual
variability, and finally, features enabling the system to learn
from variability of the output. All of these actions must occur
in the setting of considerable distraction or ‘noise’
[
13].
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Noise
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Genomic integrity must be maintained to ensure an organism’s
(and species’) healthy survival. Genetic changes and the
consequent synthesis of abnormal proteins or altered expression
of normal proteins may cause cancer, premature aging, and inheritable
disease. Maintaining this integrity must be done in the face
of considerable external mutagenic load (e.g. environmental
hazards—chemicals and UV and ionizing radiation). In addition,
noise (stochastic fluctuation) is inherent in biochemical reactions
[
14,
15]. More than 100 DNA lesions occur in each mammalian cell
daily from spontaneous decay and replication errors. To meet
this challenge successfully, a series of enzymic repair systems
has evolved that sense the presence of DNA damage and transmit
the signal to downstream effectors to either repair DNA damage
or prevent the DNA damage from causing harm. It is a highly
reliable system—risky, but safe and effective and its
crucial importance is reflected in its early appearance in evolutionary
development and conservation over time [
16]. Stochastic fluctuation
is inherent in organizations and they, like cells, are under
constant threat from errors [
17]. The frequency of errors is
high. Many occur related to people, the technologies used, and
the organization itself (e.g. policies and structure), but most
often, errors occur as a result of the interactions among people,
technology, and the organization [
17,
18]. In the case of an
intensive care unit (ICU) this noise can be figurative (e.g.
variability in the workload, use of complicated error-prone
devices, and information overload) or literal (auditory alarms
on ICU equipment) [
19]. Yet, although not as robust as the so-called
high reliability industries/organizations (commercial and military
aviation and nuclear power) [
20], health care organizations
are robust in that they can manage and cure a variety of diseases
despite the exposure to constant intrinsic and extrinsic noise.
In one sense, both DNA replication and health care are fragile,
i.e. very risky: a single mutation may be lethal and a single
serious medical error can be lethal. Like the DNA damage response,
patient safety is not so much a priority, but rather a precondition.
How the highly reliable DNA damage response system manages the
risk—deals with the variability in inputs, organizes the
defenses, and learns from the outputs offers lessons for health
care.
|
Variability in input
|
|---|
There are many different types (>100) of DNA damage including
base damage and deletions, strand breakage, protein–DNA
cross-links, and DNA–DNA cross-links (variability in input).
There is also base mismatch that occurs during the normal replication
process. Current models for DNA damage recognition include multiple
types of sensors that detect characteristics specific to damaged
DNA. Similarly, there are repair pathways for different types
of damage. The DNA repair system is resilient/robust. Not only
are the enzymes in the pathways inducible, they are redundant.
The network of interacting repair systems and backup enzymes
ensures that more than one repair system can correct the same
defect [
21]. The network structures, modular architectures,
and layers of feedback regulation confer a higher degree of
robustness [
22–
25].
Health care has high variability of input: the patient case mix, the nature and number of diseases as well as variation between different patients with regard to clinical manifestations and time of presentation. There is variability in the training and experience of health care staff, the effects of drugs, the design and function of technology, and in the way health care processes are organized. The complexity of health care also means that there are many different types of error. For example, a medication error could occur at any one of four stages: ordering, transcribing, preparation, or administration. Each of these stages is prone to different types of error. For example, an ordering error could relate to wrong choice of drug or wrong dose. As in the case of DNA damage response, there are repair pathways for different types of damage. There are multiple means for sensing damage. For example, decision support built into computerized physician order entry systems can identify drug incompatibilities, drug–drug interactions, anomalous dosing, or contraindications such as known allergy or decreased renal function [26]. One of the factors that account for the major reduction in deaths due to anesthetic administration was the development of pulse oximetry. This method permitted the detection of hypoxemia before it was manifest in either the patient turning blue or in the development of cardiac arrhythmia. A number of monitoring methods may be brought into play during anesthetic administration. These may include continuous electrocardiography, intermittent or continuous monitoring of blood pressure, and a variety of others. There is a network of interacting systems that includes the anesthesiologist himself or herself, providing a degree of redundancy. The specificity of replication enzymes has its parallel in the forcing function that makes it impossible to attach the nitrogen tank to the oxygen intake valve on an anesthesia machine. Reduction in input variability may be a driver in the development of specialized facilities that deal with relatively few conditions. This also allows for more focus on the processes involved.
|
Variability in processes/system
|
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There are mechanisms to prevent the development of variability
in the first place—defect prevention. There are systems
that defend the organism against oxidative damage to DNA including
the enzymic removal of reactive oxygen species, enzymic nucleotide
pool sanitation (i.e. removal of damaged nucleotides to prevent
them from being incorporated into DNA) as well as DNA repair.
DNA polymerase is of high accuracy [
27,
28]. Moreover, as the
DNA gets replicated and DNA polymerase adds new nucleotides
to the growing DNA strand, it reduces the number of errors by
removing incorrectly incorporated nucleotides with a proofreading
function (inspection and quality assurance) [
29]. DNA repair
is closely integrated into cell cycle regulation, transcription,
and replication through a system of checkpoint proteins [
30].
When DNA damage cannot be repaired, the cell may respond by
inducing transient cell cycle arrest or by inhibiting replication,
transcription, and chromosome segregation causing cell death
(apoptosis). This ensures that the damage will not be propagated
further. At the same time, there are mechanisms to ensure that
too much unnecessary apoptosis does not take place [
20].
In health care there is variability in processes of care and in our attempts to diagnose and treat patients. Failure to follow protocol because of stress, lack of communication, or distractions are all examples of sharp-end errors that put the patients at risk of injury. Further on there is understaffing, lack of routines regarding hand-offs, and outdated policies that become visible in frontline patient care but are caused by latent errors that come from the organizational or blunt end of the system [18,31]. The system of defenses in depth within the cell has its parallel in organizations. Organizations can cope with the risk of adverse events by creating layers of defense to prevent errors from propagating in the system and causing harm. These layers may be individual, team, institutional, or technical in nature. These layers may involve variability detection and feedback mechanisms, protective barriers that prevent errors from causing injuries, or any of a number of mechanisms. Because the layers of defense are multiple, multiple contributors (holes in the defenses) are required for any adverse event to occur.However, in contrast to the DNA repair system, most of the recovery actions in health care are dependent upon the people in the organizations who through heedfulness and quick adaptation to new situations play an important role in creating organizational resilience [20].
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Variability in output and learning from that variability
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Despite a highly evolved system for DNA repair, not all DNA
damage is prevented or repaired. There are features that enable
the organism to be resilient against this residual variability.
Not all modification of DNA leads to mutation; not all base
substitutions result in a change in the amino acid encoded by
the RNA. Balancing the features of the system that ensure genomic
integrity, e.g. the integration of the DNA damage response into
cell cycle regulation, the system also ‘learns’
from its mistakes, i.e. learns from variability of the output.
This accounts, in part, for the evolution of species better
adapted to their environments. In a sense, this is a system
that allows a certain amount of experimentation.
Studies published in many countries have shown that medical errors are common and that the consequences for patients and the health care system in general are enormous [1,32]. Cultural and legal barriers notwithstanding, there are many opportunities to learn from errors as well as near misses. High reliability organizations have been most successful in developing strategies for organizational learning from variability, e.g. having a good reporting culture (features that promote incident reporting, and feedback to the reporting community). When reported, lessons can be drawn and along with advances in science can serve as a starting point for continuous improvement both in the form of formalized organizational change and as more informal adaptation through change in work routines, in short, evolution.
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Conclusions
|
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We need to train physicians such that they are competent in
a variety of areas such as diagnosis, treatment, and safety
in order to provide excellent patient care. This will require
not only the involvement of scientists of different, but equally
legitimate disciplines, but also their active collaboration.
Fortunately, these groups have more in common than might be
readily apparent and each can learn from the other. Clearly,
there are many major differences between cells and health care
organizations. Types of behavior such as conscious action and
learning occur in the latter, but not the former. Because the
cells exist, we know that they can ‘afford’ the
levels of redundancy in the DNA damage response that they possess.
How much redundancy health care organizations can afford is
an open question. However, cells and health care organizations
share a variety of common features as well as problems they
must manage. As in the preservation of genomic integrity, safety
in organizations could be described as a dynamic non-event [
20]
where multiple safety strategies work together to create a dynamic
equilibrium where the effects of errors are coped with constantly.
These strategies must manage different sources of variability
in the input, processes, and output of patient care. In contrast
to the DNA damage response in which there is no conscious operator
who is aware of the status of the system’s defenses, i.e.
self-adaptation is an integral part of the system, high reliability
organizations seek to interpose such a knowledgeable agent.
Biological systems are remarkable for their high robustness,
flexibility, and efficiency. We think that demonstrating the
parallels between the DNA damage response and patient safety
is one way to engage our molecular biology colleagues to facilitate
getting patient safety management into the curriculum. Putting
their teaching of molecular biology in a conceptual framework
that allows for analogies to patient safety (and many other
things) allows for reinforcement of principles at multiple levels
of the curriculum. Although we do not expect molecular biologists
to teach patient safety management, biomedical scientists possess
a profound understanding of the complex mechanisms that govern
organisms. Their insights may inform the design of safer health
care systems. We suggest that such biomedical scientists can
and should be engaged in the effort to bring education about
patient safety management into the medical school curriculum
and to make patient care safer.
|
References
|
|---|
- Kohn LT, Corrigan JM, Donaldson, MS, eds. To Err Is Human: Building a Safer Health System. Washington, DC: National Academies Press, 2000.
- The Commonwealth Fund Task Force on Academic Health Centers. Training Tomorrow’s Doctors: The Medical Education Mission of Academic Health Centers. Commonwealth Fund Publication 156, 2002: http://www.cmwf.org/programs/taskforc/ahc_training-doctors_516.pdf=ref> Accessed 17 June 2004.
- Aron DC, Headrick LA. Educating physicians ready to improve care and safety is no accident: it requires a systematic approach. Qual Saf Health care 2002; 11: 168–173.[Abstract/Free Full Text]
- Rees J. Complex disease and the new clinical sciences. Science 2002; 296: 698–701.[Abstract/Free Full Text]
- Vancouver JB. Living systems theory as a paradigm for organizational behavior: understanding humans, organizations, and social processes. Behav Sci 1996; 41: 165–204.[Web of Science][Medline]
- Benyus JM. Biomimicry: Innovation Inspired by Nature. New York: Harper Collins, 1997.
- Ahari P. A living systems approach to product design and development. Trita-dissertation 3654; Trita-MMK. Stockholm: KTH Royal Institute of Technology, 2003: 41.
- Cowan FS, Allen JK, Mistree F. Exploring perspectives with living systems theory in the design of complex engineering systems. Paper No. 20138. In Allen JK and WilbyJ, eds. Proceedings of the 44th Annual Conference of the International Society for the Systems Sciences, ISSS, July 16–22, Toronto, Canada, 2000: http://www.srl.gatech.edu/~scottc/PDFs/fsc.isss.20138.pdf Accessed 24 June 2004.
- Demeester L, Eichler K, Loch H. Organic production systems: what the biological cell can teach us about manufacturing. Manufacturing Service Operations Management 2004; 6: 115–132.
- Miller JG. Living Systems. New York: McGraw-Hill, 1978.
- Capra F. The Web of Life: A New Understanding of Living Systems. New York: Random House, Inc., 1996
- Plsek P. Redesigning health care with insights from the science of complex adaptive systems. In Institute of Medicine, ed. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: National Academies Press, 2000: 309–317.
- Gauthereau V. Toward a System for Managing Organisational Factors of Safety under Operation: Insights from the Quality Movement, in Quality and Human Systems Engineering. Linköpings: Linköping Universitet, 2001.
- Rao CV, Wolf DM, Arkin AP. Control, expoloitation and tolerance of intracellular noise. Nature 2002; 420: 231–237.[CrossRef][Medline]
- Tao Y. Intrinsic and external noise in an auto-regulatory genetic network. J Theor Biol 2004; 229: 147–156.[CrossRef][Web of Science][Medline]
- Slupphaug G, Kavli B, Krokan HE. The interacting pathways for prevention and repair of oxidative DNA damage. Mutat Res 2003; 531: 231–251.[Web of Science][Medline]
- Perrow C. Normal Accidents: Living with High Risk Technologies. New York: Basic Books, 1984.
- Reason J. Managing the Risks of Organizational Accidents. Aldershot, UK: Ashgate Publishing Ltd, 1997.
- Donchin Y, Seagull FJ. The hostile environment of the intensive care unit. Curr Opin Crit Care 2002; 8: 316–320.[CrossRef][Medline]
- Weick KE, Suthcliffe KM. Managing the Unexpected: Assuring High Performance in an Age of Complexity. San Francisco: Jossey-Bass, 2001.
- Yarosh DB. Why is DNA damage signaling so complicated? Chaos and molecular signaling. Environ Mol Mutagen 2001; 38: 132–134.[CrossRef][Web of Science][Medline]
- Ravasz E, Somera AL, Mongru DA, Oltvai ZN, Barabasi AL. Hierarchical organization of modularity in metabolic networks. Science 2002; 297: 1551–1555.[Abstract/Free Full Text]
- Alon U. Biological networks: the tinkerer as an engineer. Science 2003; 301: 1866–1867.[Abstract/Free Full Text]
- Dipple KM, Phelan JK, McCabe ERB. Consequences of complexity within biological networks: Robustness and health, or vulnerability and disease. Mol Genet Metab 2001; 74: 45–50.[CrossRef][Web of Science][Medline]
- Csete ME, Doyle JC. Reverse engineering of biological complexity. Science 2002; 295: 1664–1669.[Abstract/Free Full Text]
- Bates DW, Gawande AA. Improving safety with information technology. N Engl J Med 2003; 348: 2526–2534.[Free Full Text]
- Friedberg EC, Wagner R, Radman M. Specialized DNA polymerases, cellular survival and the genesis of mutations. Science 2002; 296: 1627–1630.[Abstract/Free Full Text]
- Goodman MF. Error-prone repair DNA polymerases in prokaryotes and eukaryotes. Annu Rev Biochem 2002; 71: 17–50.[CrossRef][Web of Science][Medline]
- Lindahl T, Wood RD. Quality control by DNA repair. Science 1999; 286: 1897–1905.[Abstract/Free Full Text]
- Carr AM. DNA structure dependent checkpoints as regulators of DNA repair. DNA Repair 2002; 1: 983–994.[CrossRef][Medline]
- Cook RI, Render M, Woods DD. Gaps in the continuity of care and progress on patient safety. Br Med J 2000; 320: 791–4.[Free Full Text]
- Baker, GR, Norton PG, Flintoft V et al. The Canadian Adverse Events Study: the incidence of adverse events among hospital patients in Canada. CMAJ 2004; 170: 1678–1686.[Abstract/Free Full Text]
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