Diffusion of robotic innovations in health care environments using the interactive evaluation...

241

Robotics in Health and Human Services

Diffusion of Robotic Innovations in Health Care Environments Using the Interactive Evaluation Methodology

Roger Edwards Adjunct Research Associate, Center for Human Service Robotics, Carnegie-Mellon University, Pittsburgh, PA 15213, U.S.A.

Numerous factors will determine the successful diffusion of robotic technologies into health and human service domains. This paper will present an overview of some of the issues that require consideration for the application of smart technologies to service roles. Adaptat ion of classical diffusion of innovation theory [23] in conjunction with recent innovative methodologies for advanced technology research, design, and development [10] provide the framework for discugsion of these issues.

Kwwords: Diffusion of innovation, Technology transfer, Com- mercialization, Prototype evaluation.

Roger Edwards is an Adjunct Re- search Associate in the Health and Human Services Robotics Laboratory (HHSRL) in the Robotics Institute at Carnegie Mellon University, Pitts- burgh, PA, USA. He has worked with robotics since 1982 and has recently become President of Intervention Technologies, Inc. which is a company that is transferring prototype robotics technology out of CMU and into the private sector for commercialization.

North-Holland Robotics and Autonomous Systems 5 (1989) 241 250

1. Introduction

The realization of health and human service robots will depend on financial and human resource commitment to the research and development of systems that can "function as smart, programmable tools, and that can sense, think, and act to benefit or enable humans" [8]. More productive utilization of these scarce research and development resources is the premise underlying the discussions in this paper.

The most thorough and most often cited framework in the general (social science and business) literature is the Diffusion of Innovation Model conceived and developed by Everett M. Rogers during the past twenty years [23]. The Model states (identifies) four basic elements of every innovation diffusion: 1. the innovation: its sources and characteristics

(relative advantage, compatibility, complexity, trialability, observability),

2. communication through channels, 3. innovation decisions occurring over time

through the following steps: knowledge, persuasion, decision, implementation, and confirmation,

4. in the context of a Social System [23]. The model further states that adopters of innovations can be categorized as: innovators, early adopters, early majority, late majority, and laggards. Consequences of innovation decisions can be direct/ indirect , intended/unintended, and desirable/undesirable. This Diffusion of Innovation Model has primarily been utilized to examine market read), products' diffusion.

0921-8830/89/$3.50 ~,~ 1989, Elsevier Science Publishers B.V. (North-Holland)

242 R. Edwards /Diffusion of Robotic Innovations in Health Care Environments

Yet, results from such an analysis can be useful in assessing the potential success of pre-production prototypes and product ideas. Improved methods for evaluating innovations during the design-diffusion lifecycle is one of the multiple objectives of the Interactive Evaluation methodology.

Engelhardt conceived and developed Interac- tive Evaluation: "Interactive Evaluation (I /E) is a process for delineating needs and assessing the feasibility of developing and disseminating prototype robotic systems. The Interactive process was conceived to facilitate the creation of systems that incorporate recent advances in robotic technology and artificial intelligence and to gather research information on human-machine integration [9]. Evaluative research conducted within this framework begins with need as the basic driving force for exploration of advanced technology and ideas. This dynamic, iterative, and interdisciplinary approach affords opportunities to consider how new technological tools can be utilized to identify and address unmet or undermet human needs [9].

Interactive Evaluation calls for three stages of prototype evaluation: (1) Feasibility, (2) Utility, (3) Potential Marketability. An interactive process of assessing both technical and clinical/ psychosocial factors simultaneously over several cycles or iterations of pre-production prototypes and product ideas is required during each stage of interactive evaluation. Application of the Diffu-

sion of Innovation theory during the Utility and Potential Marketability stages can yield valuable information necessary for the successful diffusion of an innovation. (See Exhibit 1.) This paper will apply the Diffusion of Innovation theory to the diffusion of robotic technology in health and human services applications. We hypothesize that considerations of the issues presented will lead to a more rapid development of appropriate robotic technology in this new market.

It is less costly to make design changes in the pre-production stages than after the product is already on the market. We utilize I / E methodology in order to determine the information needed to make design changes. By applying Diffusion of innovation theory, we can identify significant factors during the research and development phases that will determine the success of robotics technology in health and human services.

2. Elements of Diffusion: (I) The Innovation

2.1. Relative Advantage

According to Rogers, the first characteristic of the innovation that will impact its subsequent adoption is the innovation's relative advantage over existing methods of performing the task/service. Cost will clearly be a major consideration in the

Research and Development Activities to produce an innovation

I 1 I

Number

or / S-shaped Percentage / diffusion curve

of

, I ( ' " ~ , , , , I , , , ,, ,

Time ~ '~'~ J Time

Exhibit 1.

R. Edwards / Diffusion of Robotic Innovations in Health Care Environments 243

decision to employ robots in health and human service roles as it has been in industrial settings. Demonstrating the potential cost savings of robots, however, is not as straightforward since the output of "care" is more difficult to define and measure than the output of industrial machinery. Initially, the robot will be an additional input along with the other individuals and technology which provide "care". Then, by changing the mix of these inputs (with the robotic assistant included), we can begin to measure the total savings of "care" delivered with the robot and a different mix of health care professionals, family, and technology. In some 'robotic' innovations, there will not be technology existing to meet the need so that relative advantage is derived from the unique technological answer to previously unsolvable problems (e.g. wandering technologies or voice output re- minding technologies).

A more difficult relative advantage to demonstrate will be those tasks that the robotic assistant might actually perform BETTER than existing delivery methods do. Through increased reliability, prompt response, increased patient control, increased job satisfaction or safety for health care staff (because odious, tedious tasks are done by the robotic assistant), there may be the potential for increased quality of care in certain situations. Applications research will also need to describe environments in which improvement in care is likely to occur.

2.1.1. Relative Advantage." The Individual Relative advantage will be an important factor

in the adoption of a robotic system. As is the case with most innovative products, cost will be critical in determining the relative advantage of the technology. Many individuals, both able-bodied and disabled alike, will be able to afford to purchase a robotic aid outright. In considering the potential market for these devices, it is important to note that the 55 65 age group has the highest personal disposable income. However, for many disabled individuals, there are also Third Party Payers: that is, private insurance companies as well as state and local governments (for instance, Medicare and Medicaid). These third party payers contrib- ute a large portion of the funds for health care benefits to disabled individuals. These agencies only reimburse services or products that are defined as medically necessary as defined by physi-

cians. Reimbursement approval, and consequent placement on an approved list, is dependent on this medical necessity. In designing robots for dissemination to individuals, it will be important that the robot can be classified as prescription worthy durable medical equipment (DME) and be pre- scribed by a physician for an infirm patient; in this way, it may be approved for reimbursement by an authorized third party payer.

Cost can also be reduced if a general purpose device is applicable rather than an 'individual specific' device. This is because economies of scale in manufacturing are more easily generated with general purpose devices. Volume sales to able- bodied users may help lower cost. Cost advantage and medical necessity will be required for robots to be utilized in this particular market.

2.1.2. Relative Advantage: The Institution Cost Effectiveness is especially crucial on the

Institutional level because of the high degree of accountability for major resource expenditures in health care institutions. A diagnostic or surgical related robot will require strong physician and administrative support before a hospital will in- stall it. If the robotic system is costly, it might be categorized under Certificate of Need (CON) regulations which require hospitals to file an application with the state in order to make a large capital expenditure. (Some states still have $50,000 expenditures requiring state approval.)

The user can more easily determine the relative advantage of a device if it replaces an existing device, than if it represents a completely new class of assistive devices. This may present special challenges to robot designers and manufactures, because the concept of a robotic aid is new. It also offers new challenges to market researchers who must develop methodologies for assessing robotic need. In this new market niche, developers will have to identify the areas of need and then create and integrate the technology to fill those demands [81.

2.2. Compatibility

A second characteristic of the innovation that will affect its adoption is its compatibility with existing environments, other people who interact with the patient, and other devices already in use. The compatibility of factors such as noise, smell,

244 R. Edwards / Diffusion of Robotic Innovations in Health Care Environments

appearance, agility, grace, and sterility will affect acceptance of a robot assistant into human service environments. If it will be designed for sterile environments, like operating rooms, it will need some of the same considerations mandated by 'clean rooms' in industrial settings. Aesthetics will play an increasingly important role in systems that must move into established settings such as hospitals or homes.

One example cited by Engelhardt [8] is the compatibility of nursing home hallways and door- ways with wheeled vehicles. Beds, gueneys, wheelchairs, therapeutic and diagnostic equipment, and meal carts have few (if any) barriers to movement in health care settings. Robots on wheels will have the same environmental compatibility.

Another example of the importance of compatibility is laboratory robots which must be compatible with other electronic and mechanical equipment in the laboratory in order to perform sample preparation tasks. Success has already been achieved by selecting equipment that is compatible or redesigning it and marketing a "solution package" to the consumer.

As mentioned above, robots may 'come in many flavors' and have diverse characteristics. They could range from the efficient, 'machine-like' devices such as those used in present chemical laboratory applications to more anthropomorphic robots that demonstrate "robotal i ty" [9] - that is, characteristics such as voice, appearance, and movement which give the device 'personality'. Robots that demonstrate robotality might be more compatible in human care settings for children.

2.3. Complexity

A third characteristic of the innovation that will affect its diffusion is its complexity. A user's familiarity with a system's control interface can facilitate its adoption. Most people use buttons and dials to operate televisions, ovens, and tele- phones. A robot that is operated with buttons or dials would be easier (less complex) for average users to learn to control. These interfaces may not always be acessible to some of the most needy users. For instance, if the robot is operated with a mouthstick (a common control interface for high injury level quadriplegics), it might be more readily adopted if the potential user understands mouthstick control techniques. The same could be

true of voice control of robotic aids as a human interface. Training procedures that allow easy access will reduce complexity. Research of com- mand and control variables related to voice activa- tion of mobile robotic systems is underway in the Center for Human Service Robotics [10].

Complexity is particularly relevant when it comes to the time and effort required to learn the use of a new innovation. A user is more likely to devote more energy to learning a more complex device if (s)he expects the benefits to be high.

Applications research can provide demonstra- tions (evidence) of non-technical persons' ability to use robotic technology when instructions, man- uals, and interfaces are designed and written with the knowledge and experience of the end-user in mind. The interface should be configured to place maximum control and ease of usability with the people operating the system. Training procedures that allow easy access to the system can help reduce complexity and potential rejection of the innovation.

2.4. Trialability

A fourth characteristic of the innovation that influences its adoption is its trialability. If potential users have access to testing the system before purchase, then they can better determine its possi- ble usefulness to them. Pre-testing o f new applications by targeted user groups can help facilitate diffusion. Our work with users has generated over fifty applications areas [6]. At GE a "Rent-a- Robot" program created a mechanism for placing robots in plants on a try-out basis which resulted in an acceleration of identified applications throughout the company [7]. Zymark is presently testing out a potential client's application in their own laboratories in order to prove its guarantee of 999/1000 accurate repetitions [17].

2.5. Observability

A fifth characteristic of the innovation that impacts on its adoption is observability. If the robot is stylish and aesthetically pleasing to its owner, then it might be a status symbol such as a new car might be.

If a potential user's introduc!ion to a new product is positive (i,e. observed in a positive framework), then (s)he is more likely t o later adopt the

R. Edwards / Diffusion of Robotic Innovations in ttealth Care Em, ironrnents 245

product. James Baker of GE provides an example: Up to this point our experience with the interaction between our hourly employees and robots has been reasonably successful. I've recently read a report that attributes the enthusiastic acceptance of robots l~v the Japanese workforce to management stress of the positive effects of robots, such as new opportunities for higher level employment and the creation of new industries. We've followed that approach at GE and I believe it is right. We've taken great pains to get them and their representatives on board earl)," in our planning to introduce the devices into our plants [7].

3. Elements of Diffusion; (2) Communication through Channels

A channel is the means by which a product (message) gets from a source to a receiver [23].

We presently have a communication gap between health and human service professionals and robot manufacturers. That information exchange gap can be addressed with two types of communication channels: mass media and interpersonal. Communication channels are particularly important during the first stages in the innovation adoption process.

3.1. Mass Media Channels

The mass media plays a pivotal role in determining public attitudes toward robots. Mass Media channels: (1) reach a large audience rapidly, (2) create knowledge and spread information, and (3) lead to changes in weakly held attitudes [23]. There is little doubt among people in the industry that "R2D2 and C3PO" the friendly androids of the Star Wars trilogy have up to a point helped to provide a more open and responsive environment to market robots in. In the long run, however, there is little doubt that the Star Wars imagery will be good for the industry. As one source points out, the teenage audience that forms the greatest box office support for films like Star Wars will be the ones in a position to purchase home robotic technology when it comes into existence in a few decades [1].

Professional robotics associations such as Na- tional Service Robotics Association, and Robotics International can serve as information conduits to

the general public, to health care professionals, and to robot enthusiasts. They can help promote positive uses of robotic Itechnology and reduce societal hesitancy toward dissemination of these important innovations. R botics International of Society of Manufacturing lEngineers and Carnegie Mellon University sponsored the first invitational roundtable, entitled: "Strategic Planning for Robotics in Health and Human Services." This meeting, chaired by K.G. Engelhardt, brought to- gether expert representatives from medicine, robotics, nursing, academic, manufacturing industries, health care delivery administration, food service industries, and robot ic /v i s ion /compute r manufacturers to discuss the potential for robotics in health and human service domains. Issues that were considered included: safety, product development, product liability, marketing, responsible implementation, priority setting, and technology transfer [9].

3.2. Interpersonal Channels:

(1) provide a two-way exchange of infi)rmation. One individual can secure clarification of additional information about innovation from another individual. This characteristic' of interpersonal networks sometimes allows them to overcome the social-psy- chological barriers of selective exposure, perception and retention. (2) Persuade an indiL, idual to form or to change a strongly held attitude. This role of interpersonal channels is especially important in persuading an individual to adopt an innovation [23].

The strength of the professional interpersonal channels is an example which exists in the medical industry. The whole concept of a profession is based on maintaining professional norms which are reinforced through the interpersonal channels within a facility and at medical conferences. The success of robotic physician assistants may depend on their successful introduction at professional medical conferences. Continuing education courses as well as medical school training will be important avenues for informing physicians abodt the potential of robots; and at the same time, provide robot developers opportunity to gain in- sight on physician needs and attitudes toward robotic technology. This will apply to other medically related professional and allied health fields. For example, nursing and social work each have their own professional organizations and educa-


tional milieu into which robots will need to be introduced.

4. Elements of Diffusion: (3) Innovation Decisions Occur Over Time

channels are very important to the innovation decision in a different way. Mass media channels are relatively more important at the knowledge stage and interpersonal channels are relatively more important at the persuasion stage in the innovation-decision process [23].

4.1. Knowledge 4.2. Persuasion

Exhibit 2 displays the innovation decision process over time. Initially, Knowledge about innovations is gained primarily from other users, from media coverage of prototype research and development, from periodicals directed toward health care professionals, therapists, physicians, and from suppliers' catalogues.

Medical equipment distribution channels, as well as advertisements in medically related mag- azines and journals are mechanisms for informing health care professionals about robotic innovations.

Negative advertising can often be offset by positive interpersonal influences. Interpersonal

Persuasion is a challenging task to robot designers, developers, and suppliers. The classic diffusion study of gammanym a new antibiotic drug - illustrates the importance of interpersonal channels in persuading a health care professional to adopt an innovation. Information that a new drug existed couM be crech'bly communicated by commercial sources or channels, but doctors relied on the experiences of their peers, conveyed via interpersonal network~ for evaluative information. Adopters of other types of innovation haoe been found simi- larly to depend on near-peers rather than commercial or other change agents at the persuasion and decision stages of the innooation-decision process...

PRIOR CONDITIONS

1. Previous practice 2. Felt needs/problems 3, Irtnovxtivcrtess 4. Norms of the

social systems.

COMMUNICATION CHANNELS

Characteristics of the Decision-Making Unit

1. Socio.¢,,conornic characteristics

2. peno, udity variables

3. Communication behavior

Perceived Clua'actea'istics of the lrmovation

1. Relative advantage 2. Comtmlibility 3. Complexity 4. Trialability 5. Obr.ervabtltty

1. Adoption ~ ~ Continued Adoption

2. Rejection "f ~ ~ R e j e c t i o t a

E x h i b i t 2.

R. Edwards / Diffusion of Robotic Innovations in Health Care Environments 247

individuals depend on near-peers for innovation- evaluation information, which decreases their uncer- tainty about the innovation's expected consequences [23].

If physicians and allied health professionals understand that their peers helped design a health care robotic aid, they are also more likely to readily accept robotic technology in their work- space. This is another premise for utilizing I / E during the design, development, and evaluation of a robotic acid.

Robot marketers must also convince the many gatekeepers who exist within the health care industry as to the merits of robotic aids. These gatekeepers can be any of a wide spectrum of health professionals, depending on the situation. A physician acts as a gatekeeper for rehabilitative robotic aids because a prescription is likely to be required for the robotic aid if third parties, such as Medicare, Medicaid, and private insurance companies, are going to pay for the device. The discharge planner at a hospital may serve as a gatekeeper for home health services by recom- mending a home health agency to the patient.

On the health care institutional level, a whole spectrum of decision-makers may need to be convinced, to varying degrees, of the potential benefits of robotic technology. Examples include: physicians, nurses, therapists, laboratory techni- cians, housekeeping and maintenance staff, food service staff, hospital administration, hospital board, patients, patients' family and friends, discharge planners, third parties such as Medicare officials, Medicaid officials, private insurance companies, and group insurance (employer coali- tions), state and local government officials, oc- cupational safety inspectors, university officials, religious officials, community organization offi- cers, unions, and professional associations.

Most major resource expenditure decisions in health care institutions are made by collective bod- ies. The decision to implement a robotic innovation in a health care environment generally does not simply depend on convincing administration and employees. The innovation adoption decision to adopt an innovation can take several forms: optional, collectiue, authority, and contingent. Not only does a whole range of individuals need to be convinced (a collective decision), but many hospitals are now part of proprietary and non-

profit chains which utilize the economies of group purchasing. The VA is an example of a collective, authority innovation adoption decision-maker. Decisions are often made on a system wide level as to what technologies are utilized in its facilities [15]. This collective decision can be very beneficial to the manufacturer whose product is on the approval list. As mentioned earlier, the VA also decides collectively which aids it will approve for its beneficiaries. The individual patient may not have the option to acquire a robotic aid because (s)he cannot afford it and the VA has not approved it.

Selection pools of available products can also be limited by collective a n d / o r authoriO, decisions. Supply purchasers for multihospital chains, and federal agencies, such as the Veterans Administra- tion, choose which devices will be made available to their respective clients. Third Party payers also determine the pool of available products in decid- ing what they will reimburse. Physicians, the gatekeepers with prescriptive authority for third party reimbursement, help determine what will be reimbursed. Allied health professionals, who are often responsible for much of the rehabilitation technology information that becomes part of the prescription, are also gatekeepers who make decisions regarding available technologies.

Another type of collect ive/authori ty decision maker is the FDA. The exact role of FDA regulations, with regard to robotic technologies, is largely unknown. There are few, if any, regulations aimed specifically at robots or robotic aids. Assistive devices are generally covered under the 1976 Medical Device Amendments to the Food, Drug, and Cosmetic Act. A 1982 Harris poll of medical device manufacturers concluded that: A young, vigorous, and successful medical device industry (exists') whose growth and expansion seem to be largely unaffected by the introduction of the Medical Deuice Amendments. of 1976. It further stated, however, that most manufacturers (64%) believe that the burden of FDA regulations has fallen unequally on the small manufacturers [16].

An innovation adoption decision may be a contingent one. In some cases, acquisition of a robotic system might be contingent on prior ownership of other equipment. In other cases, the robotic system will come with any needed periph- eral equipment. In this case adoption may be


contingent on available floor space and power sources.

5. Elements of Diffusion: (4) In the Context of a Social System

4.3. Implementation

Implementation of an innovation decision is sometimes dependent on appropriate training in the use of the device. This is especially true with sophisticated innovative systems such as robotics. Training of potential users is a crucial factor in user acceptance and acquisition of any technology.

A key element in encouraging health care professionals to utilize and accept a robotic system will be demonstration of job augmentation with robotization rather than job replacement.

Aesthetics and the robot fit into the health care environment will also be important to successful implementation. Functional capability will not be the only requirement for a successful robot fit (robots must fit into their area of needs application in more than mere functional capability). As we bring these systems into closer proximity with humans, their appearance will become increasingly important in achieving acceptability... "Robotality" might be used to evoke the concept of a robot's personality. The human user's own unique characteristics will in- fluence the "alities" (s)he may choose for h is /her robot tasks... Perhaps professionals or patients in a sterile hospital setting (such as an operating room) will want their aid to have minimal robotality [8].

4.4. Confirmation

Confirmation of the innovation decision is at- tained as the device proves reliable over time. Dependability is more critical with regard to robot assistive devices in health services because these devices may be essential to daily existence. Robot systems may require autonomous or auxiliary power systems that are on other life-saving medical equipment. Maintenance and ease of service will be major factors in the continued use or disuse of robotic assistants. New technology establishes precedent. Since the interpersonal, professional ties are so strong in health care, early entrants into this market need to be sensitive to the reliability issue in order to ensure that false hopes and unnecessary skepticism are not created.

The social system in U.S. health care delivery is complex and in transition. Increasing costs are forcing new restrictions on professional medical authority, new payment structures, and renewed interest in alternative health care strategies. The rising population of older citzens and our success with life-saving technologies (thereby creating more disabled individuals of all ages) have generated new demands for health care, especially longterm care. Ethical considerations also must be examined [18].

Hospitals are being forced by government payers and volume purchasers such as employers to reduce their own costs. The labor component of community hospital expenditures accounted for 54% ($75.8 billion) of overall expenses. Expendi- tures for employee benefits alone account for $11.2 billion, 15.8% of total labor costs, and 8.4% of total community hospital expenditures [2]. Cost- effective robots which might save labor costs and improve quality of care are likely to succeed in the current health care climate provided health care personnel accept robotic technology. Further- more, robotic technology that can increase job satisfaction for nurses by decreasing the odious. demeaning, tedious aspects of their jobs could help retain good nursing staff. This factor is especially important in light of the current and pro- jected nursing shortages.

An overall strategy would be to develop widespread awareness of benefits among the opinion leaders in this social system. Opinion leaders are usually the persons who deternune the adoption of new technologies. Prominent members of the various professional organizations are most likely to have the strongest and largest interpersonal networks and be the opinmn leaders. Solicit- ing their cooperation in the development and evaluation of potential health and human service robots will facilitate eventual adoption of those robots.

Government is clearly an opinion leader in health care. If government (such as state governments, Medicare, or the Veterans Administration) approves a service robotic assistant, others will follow. This leadership is based on the recognition that the government has the evaluative resources for assessing new technologies, such as a robotic

R. Edwards / Diffusion o/Robotic Innovations in Health Care Environments 249

aid, and private insurance generally does not. The latter, therefore, rely on government decisions as guidelines for their own lists of approved devices.

5.1. Adopters Categories

Adopters of innovations can be divided up into categories: innovators, early adopters, early majority, late majority, and laggards. The first 2.5% who adopt an innovation are known as Innovators. They have the resources and the motivation to be first. Outstanding research institutions often seek to be innovators in order to maintain their vanguard status. The founding of the Center for Human Service Robotics, by one of the leading international academic research institutions identified it as an innovator because it had recognized robots in service domains as the next frontier for this hybrid class of advanced technologies.

Early Adopters are respectable and often the opinion leaders. They comprise the next 13.5% of innovation adopters. Acceptance of the innovation by this group will lead to continued innovation adoption. Well-endowed, non-profit, private health care organizations (such as university or religious affiliated institutions) are likely to be early adopters of robotic systems. They are likely to contain the leaders of the medical professional associations and have the resources to purchase and approve an innovation.

The Early Majority adopters are deliberate and will probably not adopt a robotic system until cost effectiveness and quality of care indications are evident. On the individual patient level, third party reimbursement approval would be required for diffusion to this next 34% of adopters.

The Late Majority adopters (next 34%) are skeptical. They are often uninformed and more isolated from the mainstream. Rural individuals are likely to be late majority adopters as are small, rural health care organizations. They might adopt robotic systems only after cost-benefit has been proven and safety well established during a long history of use.

The Laggards are traditional and may never adopt an innovation, such as a robot, unless it is absolutely vital to their survival. Thety comprise the last 16% of the potential adopters.

5.2. Consequences of Innovation Adoption

Consideration of consequences of an innovation adoption must occur during the design, development, and evaluation of an innovative product idea, prototype, and product. Consequences of adoption of an innovative robotic aid may be direct, desirable, and intended. Examples include cost efficiency, increased user independence and control and greater job satisfaction through relief from odious or tedious tasks. Examples of indirect consequences include improved self-esteem of professionals and patients using the robotic aid. An example of an unintended consequence might be the acquisition of new skills through use of a robotic aid. New vocational opportunities may become available as a result of the increased independence and new skills. Undesirable consequences might include non-compliance, physical hazards/ injury, false confidence/hope, and additional staff to maintain the robots, yielding no net cost savings or improved care. Decreased physical requirements of nursing staff (such as lifting) is an intended, direct consequence from utilizing a transfer robot. An indirect consequence is that this transfer robot might allow older nurses to remain on the job longer.

6. Conclusion

In the Center for Human Service Robotics Laboratory, we are designing and conducting baseline research on the best mechanisms for in- troducing robotic technology in the service sector in order to better understand how interactive Evaluation principles and Diffusion of Innovation considerations might impact on the commercial success of service robotic systems. Community partners for each project enable us to utilize spe- cialized health care professional expertise while, at the same time, educating these professionals regarding the potential for new caregiving tools.

Interactive Evaluation is based on the premise that end-users understand their needs best. This concept will hold true for robotic applications in health and human services. Users and application- specific professionals in these fields, as well as service robot developers, will often be the best sources for identifying innovative robotic applications. Robotics engineers alone may not ade-


quately understand the needs; however, in partnership with prospective end-users, appropriate innovations can result. Most industrial robot manufacturers are not aware of how existing robotic principles can be applied in health and human service settings. They will need to work with health care staff and other end-users who understand the needs first hand.

References

[1] D. Abrahamson, Robots: overcoming fear first, Market- ing Communications (October 1983) 36-38.

[2] American Hospital Association, Hospital Statistics, 1987 edition (American Hospital Association, Chicago, IL, 1984).

[3] American Machinist, On the road to CIM, American Machinist (January 1984) 91-98.

[4] I. Asimov, I Robot (Doubleday Inc., Garden City, NY, 1950).

[5] R.E. Awad, Rehabilitation technology and innovation: a case study of MediCal reimbursement procedures and their impact on diffusion, Masters thesis, Stanford Uni- versity School of Medicine (1983).

[6] R.U. Ayres and S.M. Miller, Robotis Applications and Social Implications (Cambridge, MA, Ballinger Publishing Co., 1983).

[7] J.A. Baker, Robots: A GE perspective, Marketing Com- munications (October 1983) p. 37.

[8] K.G. Engelhardt, Statement before the House Select Com- mittee on Aging, U.S. Congress, Washington D.C. (May 22, 1984).

[9] K.G. Engelhardt, Robotic concepts and applications in health and human services, Proceedings oflnterrobot, Long Beach, CA (October 1984).

[10] K.G. Engelhardt et al., Interaction evaluation of voice control for a robotic aid: implications for training and applications, Proceedings of the American Voice Input / Output Society, Arlington, VA (September 1984).

[11] K.G. Engelhardt et al., Evaluation of a robotic aid: from theory to application using an interactive model, Proceed- ings of the 6th Annual Conference on Rehabilitation En- gineering, San Diego, CA (June 1983).

[12] K.G. Engelhardt and R.E. Awad, Evaluating and disseminating robotic aids for human uses, Proceedings of the West Coast Computer Faire, San Francisco. CA (March 1984).

[13] K.G. Engelhardt and L.J. Leifer, The VA RR&D Center: where computers and robots serve elders, Generations, 8 (4) San Francisco, CA (Summer 1984) 38--9.

[14] P. Haber, The role of technology in the longterm care for the aged, Medical Instrumentation, 16 (1) (Feb. 1982).

[15] P. Haber, Statement before Senate Committee for Veterans Affairs, U.S. Congress, Washington D.C., (Sept. 30, 1977) 673.

[16] Harris Poll, The Medical Device Industry (Harris, 1982). [17] In Vivo, Helping Hands 1 (5) 14-21. [18] R. Keating, Zymar Corporation, Walnut Creek, CA, per-

sonal communication (July 1984). [19] G. Lesnoff-Caravaglia, Technology an d aging, Technology

and Aging Conference, University of Massachusetts Medi- cal Center, Worcester, MA (1986).

[20] America's robotic rising, Management Today (February 1983) 54-58.

[21] Office Technology Assessment, Technology and Handi- capped People (U.S.G.P.O., May 1982).

[22] C. Ris, Electronic age brings new aids for the disabled, but economics put them out of reach of many, Wall Street Journal (August 26, 1982) 52.

[23] E.M. Rogers, Diffusion of Innovations, Third Edition (New York, NY, The Free Press, 1983).

[24] Machines that think, U.S. News & World Report ( ~ m - ber 5, 1983) 59-61.

[25] E.A. Von Hippel, Users as innovators, Innovation/ Technology Review (1980).

[26] C.R. Waters, There's a robot in your future, INC. (June 1982) 64-74.

[27] J.S. Williams, The relationship between the diffusion of medical technology and the organization and economics of health care delivery, Medical Technology, NCHSR, DHEW (September 1979).

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