Strategies can limit imaging fungibility

November 1, 2008

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."

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."

CREATING THE SOLUTION

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).

DIFFERENT PRIORITIES

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.

QUALITY METRICS

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.