Bruce Reiner, MD

Whether we would like to admit it or not, medical imaging is slowly on its way to becoming a commodity, which has been defined by Wikipedia as "anything for which there is a demand, but which is supplied without qualitative differentiation across a given market." 

In the original, simplified sense, commodities are described as things of value (e.g., pork bellies, oil) that are produced in large quantities by multiple manufacturers, the products of which are considered equivalent. A critical factor in determining what is a commodity is the consumer's perception that the products or services being defined are of uniform quality. When the products and/or services provided by one company are perceived to be supplied equally well by other companies, then that product and/or service becomes undifferentiated and commoditization occurs. Cost becomes the principal factor in determining supplier selection.

Commoditization occurs as a goods or services market loses differentiation across its supply base, often by the diffusion of the intellectual capital necessary to acquire or produce it efficiently. Relevant examples in the current marketplace include generic pharmaceuticals and silicon chips, which at one time in their life cycles justified a premium price within the market but over time lost their differentiation and pricing power. Globalization, increased information exchange, and technological developments are rapidly accelerating the trend toward commoditization.

While many within the medical imaging community may not see the direct relevance of this trend, I believe that the commoditization of medical imaging, if left to its own devices, is inevitable. As medical imaging service providers strive to maximize operational efficiency through an assembly line approach and traditional geographic boundaries disintegrate, service deliverables come to be measured in quantitative terms. The qualitative differentiators that have been the historic main-stay and protective force against commoditization become lost.

Consumers of these services begin to view medical imaging service providers as interchangeable parts providing comparable service. As a result, the provider selection begins to focus more on price, eventually leading to "survival of the cheapest."





A number of traditional marketing strategies are used in an attempt to counteract commoditization, including branding, segmentation and customization, and bundling. The major medical imaging technology vendors, for example, have committed vast resources to creating the perception in the marketplace that their products are of superior quality (branding), can be customized to the specific needs of individual customers (segmentation and customization), and can be combined in tandem with other products/services to create an all-inclusive, comprehensive solution (bundling).

The end goal is to create the perception that the supplier has created added value for its customers, thereby differentiating the supplier from its competitors and providing justification for commanding a higher price.

While medical imaging product providers (vendors) have used these marketing strategies for years, few service providers have engaged in this practice. This reluctance may in part stem from the stigma associated with proactive medical advertisement, as well as the economic and geographic protection typically afforded to the medical imaging service community.

A traditional hospital-based radiology group is offered exclusivity for all medical imaging studies performed within the institution, thereby creating a monopoly on professional service delivery. At the same time, the analog radiology practice offers limited portability of medical imaging exams, which serves as a relative deterrent to seeking professional services outside of the host institution.

With the expansion of radiology practice outside of hospitals, the transition to digital imaging, and the expansion of teleradiology across geographic boundaries, however, many of these protective barriers have completely disintegrated. As a result, both technical and professional medical imaging service providers are faced with new challenges that threaten the commoditization of the industry.

The solution to this commoditization threat lies in the ability of the medical imaging community to shift the focus from quantitative to qualitative differentiation and to create a pro-active mechanism for objective data-driven analysis using quality-oriented metrics. These metrics need to be comprehensive in nature (bundling), address the individual priorities of different customer groups (segmentation and customization), and create an objective means of product/service differentiation (branding).





The table lists some of the different priorities of individual stakeholders and consumers of medical imaging services. While all of the priorities listed are of importance to the individual and collective stakeholders, the relative importance of these priorities may differ, depending upon each individual's perspective. The one denominator common to them all is diagnostic accuracy, which in the end is the principal determinant of clinical outcomes analysis, the proverbial holy grail of all medical providers. 

If product or service suppliers can demonstrate in objective and unequivocal terms that they can achieve improved clinical outcomes compared with their competitors, then price differential becomes moot and quality effectively eliminates all threats of commoditization.

Clinicians have long bemoaned the inconsistency and ambiguity within traditional radiology reporting and communication, which have changed little in form and content over the past century despite dramatic technological advances. The opportunity for radiologists to add value in the eyes of their clinical colleagues largely resides in the radiology report. In order to create objective and reproducible quality-oriented metrics tied to the radiology report, a number of prerequisites must first take place to facilitate large-scale radiology report data min-ing. These include the creation of structured input data (using a standardized lexicon such as RadLex), the ability to pool multiple nonproprietary database repositories (i.e., meta-analysis), and the capability to objectively analyze these data relative to reference peer groups.

The data analyzed could include any number of report elements perceived to be of importance to the referring clinician group, including timeliness and consistency of critical results communication and reporting of diagnostic confidence, follow-up recommendations, and clinical significance tied to individual pathologic findings. These measures would not only provide an objective means of assessing radiologist report performance but can also be used by service providers (radiologists) to en-hance educational and training efforts, along with new technology development by product providers (vendors).

The primary focus of radiology and hospital administrators is often predicated on operational efficiency measures such as report turnaround time, scheduling backlog, retake rates, and image quality. Many of these time-stamped measures can be directly derived from data residing in existing information system technologies (HIS, RIS, PACS) and modalities.

While assessment of image quality is currently done in a somewhat idiosyncratic and subjective fashion, efforts are under way to develop soft-ware integrated into the modality, RIS, and PACS that would automate and objectify the quality assurance process. This would create an objective and reproducible means to track retake rates and image quality, while providing valuable feedback to both service and product providers. This would, in effect, become an iterative process, in which the quality-oriented data would provide objective feed-back and be used to continuously drive both operational efficiency and image quality, along with the supporting technologies.

While multiple quality indicators are of high importance to the patient population, perhaps the most important priority is safety. Within the delivery of medical imaging services, safety measures would consist of individual and collective radiation dose monitoring, utilization review, and adverse outcomes (e.g., contrast reaction) monitoring.

Radiation dose optimization is a particularly high priority within certain patient populations (e.g., pediatric, oncology) that is taking on greater importance as more patients access the Internet for medical information and become aware of radiation as a carcinogen.

The ability to prospectively record, track, and analyze individual and collective radiation dose exposures currently exists, but these steps are not routinely being performed. This creates an excellent opportunity for both imaging service providers and imaging product manufacturers to capitalize on the gap by creating an important value-added service. At the same time, service providers have the capability of proactively reducing radiation dose exposure through optimization of the acquisition parameters and utilization of state-of-the-art technology (hardware and software).

By prospectively tracking and analyzing these radiation dose data, service providers could improve patient safety and be differentiated based on objective radiation dose measures.



Third-party payers make up perhaps the single group that benefits from the commoditization of medical imaging services, which can drive the selection of service based on cost alone. The sad reality is that the providers who prosper in an environment of commoditization are those who maintain profitability though austere cost-cutting and consolidation, often at the expense of quality.

The best way to counteract this phenomenon is to create objective quality measures that are directly available to the payers: utilization review, exam appropriateness, length of stay (hospital), and time to initiate clinical management.

At the same time, the response of these third-party payers to these quality-data metrics can be shared with their own consumers (patients), so as to maintain the focus of attention on quality indicators and service selection based on performance. These objective metrics, in effect, create a reliable check and balance to ensure that service providers are maintaining or exceeding community-wide quality thresholds and that consumers of these services (payers) are using these services in accordance with the same quality standards.

Another important outcome of this quality-centric data analysis is the potential to reestablish radiologists as the de facto experts and deliverers of medical imaging services. As more and more nonradiologists provide medical imaging services, often through self-referral, effective checks commoditization-globalization, increased information exchange, and technological developments-also offer a solution to prevent it. The ability to create, store, analyze and cross-reference objective quality-oriented data metrics is the most effective means we have to ensure that qualitative differentiation is maintained within the delivery of medical imaging services.

Whether as the result of defective acquisition technology, noncertified technologists, or physicians untrained in radiation safety; many of these practitioners engage in the delivery of sub-optimal service. A data-driven quality analysis provides the means to shed light on all service providers and create a reliable mechanism to raise quality standards while rewarding those practitioners with the highest performance measures.

One may find it somewhat ironic that the same forces bringing about commoditization-globalization, increased information exchange, and technological developments-also offer a solution to prevent it. The ability to create, store, analyze and cross-reference objective quality-oriented data metrics is the most effective means we have to ensure that qualitative differentiation is maintained within the delivery of medical imaging services.

The various consumers of these services can objectively determine which service providers are best suited to address their own individual priorities and select service in kind. Those service providers who can objectively demonstrate improved quality measures relative to their competitors will be able to command a premium, in the form of higher reimbursement and/or market share.

In the end, Darwinian natural selection is at work: The highest quality providers survive and flourish. Instead of survival of the cheapest, we will have survival of the fittest. That's the way it should be to best serve the interests of patients.

Articles

Whether we would like to admit it or not, medical imaging is slowly on its way to becoming a commodity, which has been defined by Wikipedia as "anything for which there is a demand, but which is supplied without qualitative differentiation across a given market."

Strategies can limit imaging fungibility

Genes doom driven radiologist's daughter to life of impatience and the trouble it brings 

We should take care not to make the intellect our god; it has, of course, powerful muscles, but no personality." -Albert Einstein

"Personality is the entire mental organization of a human being at any stage of his development. It embraces every phase of human character: intellect, temperament, skill, morality, and every attitude that has been built up in the course of one's life." -Warren HC, Carmichael L. Elements of human psychology. Rev. ed. Boston: Houghton Mifflin, 1930:333

It all started when my 13-year-old daughter had another meltdown.

"It's all your fault, Dad," she screamed.

My response was what any good-natured, beaten-down father would say.

"I got into trouble today because of my impatience, and I got it from you."

As I pondered this, I began to think about the power of genetics and self-determination, and what defines the essence of our very being.

The next day at work, as I was garbaging through an endless stack of portable chest radiographs, my mind returned to my daughter's words. Maybe it was my fault after all. My daughter had indeed inherited my deficient genes (my wife says she did the best she could with what little she had to work with) and had been schooled in the fast-paced habits of my sprinting tendencies. Why expect her not to be impatient?

But is impatience necessarily a character flaw? It is the fuel that drives me through another busy, stressed-out, and technically challenging day. My impatient, extreme goal-oriented behavior could be the most important attribute to explain my work-related productivity. If only I could figure out how to turn it on and off at appropriate times, I would be the master of my own personality.

I began to think about the relationship between personality and work performance. Was I an outlier among my radiology colleagues, or was my personality emblematic of an ever-changing, technology-driven field that has dramatically transformed itself in the past decade? Perhaps the only real way to answer this question was to survey the radiology community and scientifically analyze what common personality traits appear and what features make some radiologists better adapted than others.

With the help of Diagnostic Imaging, we placed a survey online and sought out volunteers within the readership to share their experiences as they relate to population demographics, work experience, personality, and perceived stress. To date, we have received 270 completed surveys, and the results are fascinating. We look forward to expanding the data collection and sharing our collective knowledge with the community, in the hopes of better understanding the interaction of personality, stress, technology, and work experience.

One of the most widely accepted theories of personality is the "Big Five" taxonomy developed by Goldberg.1,2 This describes five basic dimensions, or factors, that define personality:

- agreeableness (compatibility with others);

- conscientiousness (consideration for others); and

- openness (adjustability to new ideas and experiences).

Neuroticism (N) is the most pervasive domain of personality and assesses both emotional stability and susceptibility to psychological distress. Because disruptive emotions interfere with adaptation, high N individuals are prone to higher degrees of irrationality, stress, and poor impulse control. This has profound significance for the current practice environment, in which radiologists must deal with rising workload, increasingly large and complex data sets, and ever-changing technologies.

Extraversion (E) is a measure of sociability. High E scores are typically seen in cheerful people who enjoy personal interaction, large groups, and stimulating activity. Low E scorers (i.e., introverts) tend to be more reserved and independent and to work alone. It is historically interesting to relate extraversion to the design and layout of radiology departments. In a film-based department, technologist work spaces and radiologist reading rooms were traditionally wide open areas that accommodated social interaction, consultation, and continuous dialogue. With the transition to filmless operation, technologists and radiologists tend to work more in isolation, partly in response to productivity and workflow optimization demands. Studies have shown that physician consultations dramatically decrease with the advent of PACS, due to the ability of referring clinicians to access images and reports without traveling to the imaging department.3 Technology development and innovation may have lessened the impact of high E scores on the current generation of practicing radiologists.

Agreeableness (A) is a dimension of interpersonal tendencies, with high A scores associated with altruism, sympathy, and cooperation. Low A score individuals tend to be antagonistic in nature, skeptical of others' intentions, and competitive rather than cooperative. It is important to realize that agreeableness is not always a virtue, and readiness to fight or defend one's own interests can be advantageous. In today's practice environment, radiologists are faced with heightened malpractice risk, decreasing reimbursements, and turf battles with their clinical colleagues. At the same time, skeptical and critical thinking contributes to accurate analysis, which is crucial in scientific research and decision-making. Individuals with low A scores may be best suited to address these challenges, thereby serving an important role.

Conscientiousness (C) is often associated with academic and occupational achievement. High C individuals are purposeful, strong-willed, and determined, and they are described as possessing the will to succeed. Unfortunately, these same people can also demonstrate fastidiousness, compulsive behavior, and workaholic tendencies. This illustrates the dichotomy of personality factor scores, in that both positive and negative attributes can be observed, often in specific contexts. In the medical field, goal-oriented behavior is commonly viewed in a positive light, for it drives the individual to overcome the stresses and challenges of medical school, residency, and professional life.

Openness (O) is especially relevant to the ever-changing world in which we live and work. High O score individuals tend to be curious about both inner and outer worlds, and their lives are experientially richer than their low O score counterparts. High O scorers tend to entertain novel ideas and unconventional values, experiencing both positive and negative emotions to a greater degree than closed individuals. Adaptability to change and innovation has become a necessary prerequisite for the modern-day radiologist. In the last decade alone, new imaging and information technologies have transformed the way imaging data are acquired, archived, displayed, interpreted, and reported. If new and emerging technologies are to be successfully developed and implemented, this process will require the collective openness of the radiology community.

These Big Five personality factors have been shown to be universal in nature,4 stable throughout adult life,5 and the result of a strong genetic predisposition.6 Using this knowledge and scientific foundation, we selected the NEO Personality Inventory,7,8 which was developed to operationalize this model of personality. The survey data reported were the composite result of 270 online responses from radiologists (which does to some extent skew the respondent population by excluding non-Internet users). A few highlights of the data reflect job satisfaction, technology, and stress:

- Job satisfaction. With all the heightened economic, medicolegal, and professional challenges radiologists face, it is no surprise that many are frustrated and dissatisfied with their jobs. While this sentiment is undoubtedly multifactorial, one surprising observation is the direct correlation observed among survey respondents between personality and job satisfaction. Of the Big Five personality factors, three were shown to have statistically significant correlation with reported job satisfaction: neuroticism, extraversion, and agreeableness. Extraversion and agreeableness demonstrated a positive correlation with job satisfaction, while neuroticism had a negative one. These data do not imply that all high N score radiologists are dissatisfied with their jobs, but they do give scientific credence to the well-known fact that emotional stability and job satisfaction often go hand in hand.

- Technology. This is the proverbial double-edged sword of the radiology community. On one hand, it is our lifeline, while on the other, it can be the bane of our existence. Radiology is the only medical specialty that is 100% technology-dependent. Preliminary analysis of survey results suggests that personality and technology are related, and, not surprisingly, the most important personality factor defining this relationship is openness. Additional investigation of this fascinating subject will specifically seek to identify how technology can become more adaptive to different personality types.

- Stress. This was assessed in the survey in two separate ways. Survey respondents were first asked to subjectively rate their degree of perceived occupational stress. Second, the survey included the 14-item Perceived Stress Scale (PSS),9 a Likert-type rating scale that was developed to quantify the psychological construct of perceived stress.

In both instances, respondents overwhelmingly reported a strong positive correlation between neuroticism and stress and a strong negative correlation between agreeableness and stress. Extraversion was also shown to have a negative correlation with stress, but to a far lesser degree than neuroticism. The data raise as many questions as they answer, and additional research is required to better delineate the complex relationship between personality and stress. For the practicing radiologist, several important and timely questions arise:

- Can personality be modified to reduce stress?

- What role can technology play in reducing stress (e.g., affective computing)?

- How can the physical environment be modified according to specific personality profiles to reduce stress?

- What cumulative role does personality play in predicting job burnout?

- What role does personality play in overall job performance?

While additional work is planned to investigate these complex relationships, the data already suggest potential long-term ramifications. If personality does indeed play an important role in predicting job satisfaction, stress, and technology avidity, should pre-employment and preresidency personality profiling be performed on a regular basis? In the current business climate, this is being done on a regular basis, with approximately 30% of employers using some version of personality testing in hiring.10 Eighty-nine of the Fortune 100 companies report using the Myers-Briggs personality test in hiring and promoting. The whole science of personality profiling creates both an interesting opportunity and a dilemma for the radiology community as it strives to address increasing levels of stress. As for me and my high N score, my life would have in all likelihood dramatically changed if personality profiling had been a commonplace event in my earlier years. I would not have been accepted into a radiology residency and would not have been deemed an acceptable spouse by my loving wife. While the acorn may not fall far from the tree, I haven't yet decided if that is a good or bad thing.

All interested radiologists are encouraged to go to the site http://www.zoomerang.com/survey.zgi?p=WEB225C5CHHWWN and participate in the survey.

Dr. Reiner is director of radiology research at the VA Maryland Health Care System in Baltimore. Dr. Eliot Siegel contributed substantially to this article and is vice chair of diagnostic radiology at the University of Maryland School of Medicine and chief of radiology and nuclear medicine at the VA Maryland Health Care System.

1. Goldberg LR. Standard markers of the Big Five factor structure. Unpublished report. Oregon Research Institute, 1990.

2. Saucier G, Goldberg LR. What is beyond the Big Five? J Pers 1998;66:495-524.

3. Reiner B, Siegel E, Protopapas Z, et al. Impact of filmless radiology on the frequency of clinician consultations with radiologists. AJR 1999;173:1169-1172.

4. McCrae RR, Costa PT Jr. Personality trait structure as a human universal. Am Psychol 1997;52:509-516.

5. Soldz S, Vaillant GE. The Big Five personality traits and the life course: A 45-year longitudinal study. J Res Pers 1999;33:208-232.

6. Jang KL, McCrae RR, Angleitner A, et al. Heritability of facet-level traits in a cross-cultural twin sample: Support for a hierarchical model of personality. J Pers Soc Psychol 1998;74:1556-1565.

7. Costa PT Jr, McCrae RR. Normal personality assessment in clinical practice: The NEO Personality Inventory. Psychol Assess 1992;4:5-13.

9. Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24:385-396.

10. Cullen LT. Sats for jobs. Time April 2, 2006:89.

Genes doom driven radiologist's daughter to life of impatience and the trouble it brings

Acorn doesn't fall too far from the tree

If a man does not keep pace with his companions, perhaps it is because he hears a different drummer.

Let him step to the music which he hears, however measured or far away.

If you were to ask any veteran radiologist what the best and worst parts of his or her radiology practice are today, you might get the same answer to both questions: technology. While technology is what attracts many medical students to the field in the first place, it is also one of the primary variables increasing stress in the radiology workplace. For better or worse (and till death do us part), radiologists and technology go hand in hand. It is therefore not surprising that technology brings out both the best and the worst in its practitioners.

The relationship between technology and stress likely accelerated around 1936, when Hans Selye first described the general adaptation syndrome, otherwise known as stress. Within the next few years, several important technological inventions specifically related to the computer occurred, including the development of digital electronics by Claude Shannon in 1937, the Atanasoff-Berry computer in 1938, and the ENIAC in 1943. From that point on, technology and stress became inextricably intertwined.

A number of factors contribute to increasing levels of stress in the radiology workplace today; many are directly job related, and others are unique to the individual. Job-related stressors include the imbalance of supply and demand for both radiologists and technologists, the increasing size and complexity of imaging data sets, ever-changing imaging and information technologies, decreasing reimbursements, and heightened medicolegal risk. Internal stressors unique to each individual involve genetics, lifestyle, and personality. Examples of type A personalities abound throughout medicine, as the profession often self-selects for highly motivated, driven, and goal-oriented individuals who place tremendous internal stress on themselves in their pursuit of excellence.

The convergence of these increasing stressors, both external and internal, and rapidly evolving technology has created an atmosphere ripe for job burnout, which represents a combined physical, mental, and emotional response to repetitive levels of intense stress within the workplace. The stress itself represents a temporary state of mind that typically dissipates over time, while burnout represents a state of emotional fatigue that is long lasting. The end result is job-related exhaustion, cynicism, and ineffectiveness. In the end, many radiologists and technologists elect to drop out.

Surprisingly, little scientific study has been done within the radiology community regarding the relationship of stress and technology. While technology has been championed as the catalyst for productivity gains and advanced clinical care, little is really known about its impact on cumulative stress. At the same time, questions remain unanswered concerning how specific factors such as personality affect perceived stress levels from one individual to another and how we can use this knowledge to customize technology to simultaneously enhance job performance and minimize stress.

In an attempt to facilitate this understanding, we have designed a survey that investigates the relationship of personality, perceived stress, technology, and practice environment. The survey is available in both print and electronic versions and can be completed in 12 to 15 minutes. All responses will remain anonymous and confidential, and summary data will be made available to all participants.

Here is how we see technology evolving in the near future.

Radiologist R enters the sound-proof high-tech reading suite after being recognized by the retinal scanner. Before the environmental factors are adjusted to his individual preferences, an "affective scan" evaluates his facial expression, heart rate, body temperature, and galvanic skin response. Based on a combination of affective and personality data, the computer recognizes our radiologist as unusually anxious this morning (due to the combination of an argument over his daughter's new tattoo, the ticket he received on his way to work, and his favorite football team's loss in the playoffs). The ubiquitous computing network adjusts the environmental factors accordingly by dimming the lights, setting the air conditioning to 68 degrees and high ventilation, playing Pachelbel's Canon in D Major, and displaying the amber external light that suggests that a visitor enters at his or her own risk. The network directs the computerized ergonomic chair to the incline position, presents a cup of ginseng tea (no coffee today!), and pulls up the CNN Financial Web Page (knowing Dr. R's stock portfolio was up 2.1% yesterday). As Dr. R begins to relax (as detected by the affective computing sensors), the computer asks if he is ready to begin work.

Radiologist R puts on his computerized headset and issues the verbal command, "Open unread CT work list." Based on Dr. R's personality and technology profiles, affective data inputs, and recent workflow data, the computer selects the optimum hanging protocol and navigation formats, user interface, and decision support tools. As the unread CT work list is opened, Dr. R realizes that his supposed close friend and colleague Dr. S left 20 cases on the queue from the prior day, including a postoperative neck. As soon as this information is registered, the computer senses his heightened anxiety and responds in kind by adjusting the navigational device (foot pedal instead of mouse), selecting the "simplified" UI, and 1:1 display format. The reading queue is rearranged to display the noncontrast trauma head CT first, allowing Dr. R to regain his composure. Before beginning, Dr. R directs the PACS to send the unread postoperative neck CT case to Dr. S's reading queue with an attached audio file that would not pass the scrutiny of this journal's censors.

After successfully completing the first five cases, Dr. R begins to settle in and relax. As he does, the computer senses his more relaxed state and makes "on the fly" adjustments accordingly. As he opens up a chest CT angiography exam, the computer notifies him that another user is reviewing the same study. Dr. R decides to consult electronically with Dr. P, the pulmonologist, as she simultaneously reviews the same exam in the mobile ICU. Dr. R instant messages Dr. Q to notify him that he is reviewing the same case. After a few kind words are exchanged (using the pleasantries template), Dr. R directs the computer to use Dr. Q's default settings for the consultation. One might not even realize they were reviewing the same exam or using the same PACS, given the vast differences in the presentation state, reconstruction algorithms, workstation tools, and user interface. In the old one-size fits-all days, every user was forced to use standardized software that allowed for a bare minimum of customized features.

The first generations of PACS trained the users rather than the other way around. Now, with user-specific personality and technology profiles embedded into the sign-on and adjustments made based on real-time affective data inputs, workflow is consistently optimized to each end user's preferences and abilities. One single CT data set can be processed, displayed, navigated, interpreted, and reported using completely different schemas, which to the untrained eye appear completely different from one another.

As Dr. R continues his work, the computer continuously updates its user-specific database, based on numerous variables (including the modality, exam size and complexity, clinical indication, affective state, time of day, work list size, and recorded abnormalities). These data are, in turn, processed to automatically provide future workflow recommendations and contrast with other users with similar personality and technology profiles. This step has served to provide valuableshort-cuts, in a continuous attempt to optimize each user's productivity, in accordance with his or her unique skill set, personality, and technical aptitude.

While this scenario may seem futuristic and far-fetched, it is actually not out of the realm of near-term reality. Recent affective neuroscience and psychology studies have reported that human affect and emotional experience play a significant, useful role in learning and decision making. Affective-based personality assessments can be a valuable resource in optimizing job selection and performance. These findings validate our experiential knowledge that tells us some people are better suited for some professions.

Many of us have experienced the notion that internists think and behave differently from surgeons, who in turn are different from radiologists. But in the end, we must ask ourselves where the similarities and differences among the radiologist community begin and end. How can we use this knowledge to make better informed decisions regarding subspecialty training, job selection, and practice planning? As radiologists everywhere experience increasing levels of job-related stress, what impact does this have on overall work performance, and what can be done to alleviate these stressors? Does technology serve as an enabler or impediment to stress, and which types of technology are best suited to which types of personality?

While technology continues to evolve at a breakneck pace, the engineering that goes into these technical advances is typically conducted in a vacuum. To a large extent, engineering is designed by technologically savvy nonclinicians who do not always appreciate the diversity of the end-user population. The one-size fits-all approach does not take into account considerable differences in personality and affect, education and training, technical skills, and susceptibility to stress. An adaptive approach to technology development is necessary, but before that can be done, it is essential that we better understand similarities and differences in personality and stress.

We encourage all of our readers and colleagues to play an active role in this endeavor and take a few minutes out of your stressful schedules. In addition to letting off a little steam, responding to our survey should be fun, informative, and maybe a little therapeutic. We thank you in advance for your participation and look forward to using this information to serve the betterment of the community. You can complete the survey at 

Dr. Reiner is director of radiology research at the VA Maryland Health Care System, and Dr. Siegel is vice chair of diagnostic radiology at the University of Maryland School of Medicine and chief of radiology and nuclear medicine at the VA Maryland Health Care System.

Bruce Reiner, MD

Articles

Strategies can limit imaging fungibility

Acorn doesn't fall too far from the tree

Stress reflects dichotomy in march of progress