Aggregate information life cycle of the organization
A logical question that might arise after the discussion of information system life cycles is whether the organization as a whole has a life cycle of its own. In other words, can a composite picture of an organization-wide information system life cycle be visualized if all information system life cycles are aggregated into a whole? This is an appropriate question because an organization’s level of experience and sophistication with IT has an impact on how it manages the technology. For example, an organization that is just starting to automate its information functions would have a different emphasis in management of its technology than an organization in which most of the information functions were already automated.
Nolan4 first described the concept of organizations that have information system life cycles. The view postulated by Nolan is that an organization at any given point in time is at a certain maturity or level of sophistication in deployment of IT. Nolan postulated the following stages in his organization-wide information system process:
At each of these stages, the organization usually takes a different approach to management of IT. For example, in the early stages of initiation and expansion, the organization is likely to assume a laissez-faire attitude, allowing expansion of the technology with little or no organization-wide control. For example, a clinician in a particular clinic may develop a small system that works well within that clinic. In the meantime, the organization is looking for an electronic record system that will meet the needs of its ambulatory services. After the organization makes a decision to move forward with an organizational approach, the clinic with its own system will be expected to participate in the organization-wide system. Resources will be redirected to the organizational system.
As the growth of technology expands, the organization becomes most concerned with budget, allocation of funds for technology expansion, and centralizing resources. In other words, the organization tries to gain control over the resources. As time goes on, the organization becomes more sophisticated in its management of the technology. The organization grows to realize the need for integration of technology and information management. In the stages of integration and data administration, the organization treats information and its associated technologies and management as critical to the survival of the organization. The main focus in these stages is to distribute functions but also to centralize standards for both technology and information management. In the final stage, maturity, the organization views information as a strategic resource and emphasizes development of applications that further the strategic advantage of the enterprise. At this point in development, the organization’s IT planning will align with the business strategic plans. If the strategic plan includes a major new purchase, resources may or may not be allocated to continue support for the older IT system. The new technology and its advocates are competing with maintenance needs of the older system and its advocates.
Although it is important to understand that individual information systems have their own life cycles, it is equally important to recognize that an enterprise will also be at a certain stage of IT management maturity. Being able to identify an enterprise’s point in its life cycle helps explain why certain policies exist or why specific strategies are deployed. For instance, if a health information manager works in an organization that is in the integration stage of the life cycle, he or she would likely have been part of developing centralized standards. This might be in areas related to the type of communication protocols, electronic signature tools, template management, or documentation amendment approaches that are allowed. On the other hand, if the health information manager is employed in an organization in which technology is newly implemented, there may be few policies and procedures that help to direct information growth. Understanding at which stage of maturity an organization is in the information life cycle helps the health information manager play a more effective role in the organization’s information system process. The ability of the health information manager to identify, analyze, organize, and write and revise the necessary overarching policies as a system is deployed is a critical skill. Frequently, these policies are influenced by laws, regulations, and standards as well as the specific needs of the organization.
Information systems become obsolete for several reasons. A system may be obsolete because it uses older technology that cannot meet current information-processing demands. The use of older technology in itself does not necessarily mean that the information system is obsolete. Rather, it is whether technology meets required needs that determines obsolescence. Systems can also become obsolete because they cannot handle an increase in the volume of data or cannot handle more sophisticated data management tasks. Systems frequently become obsolete because they do not support the strategic objectives of the organization. The release of information tracking system described in the first part of this chapter is a good example. The strategic objective of the organization in that example was to provide a broader range of services at multiple, diverse sites. Because of the change in strategic objectives to include multiple distributed sites and the changes in the laws, the release of information tracking system could not meet the needs of the organization. Common examples of systems that quickly become obsolete are those in the area of administrative decision support. Decision support systems provide a variety of tools that help management in making decisions about semistructured and unstructured problems. Because the health care environment marketplace is changing at such a rapid pace, there is a need for accurate, reliable, and user-friendly decision support systems. Many decision support systems and their associated tools are not flexible enough to meet current demands for information access and analysis and quickly become outdated. As International Classification of Diseases, Tenth Revision (ICD-10) is implemented in the United States, the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) coding systems will be completely redesigned. Clinical decision support systems are also used to help make decisions about patient care. Some of these systems provide basic alerts, whereas others are very sophisticated. Again these systems require tending and rely on quality data. This is a growing area of health information systems, and today’s expectations of EHR systems include the integration of real-time EHRs and clinical decision support tools. For example, as medications are ordered the clinical decision support tools can cross-check interactions with other medications already prescribed for a patient, check patient allergies, and flag potential orders for review. These decision support systems need to be updated regularly on the basis of determinations of quality-of-care profiles.
Sometimes information systems become obsolete because of a change in user expectations. For example, a hospital-wide information system may provide the necessary functionality for nursing care, but users expect the functionality to be enhanced in some way. The users might expect to be able to take their computer device with them, perhaps in their pocket rather than having to enter data at a central nursing station/terminal. An EHR systems may not take advantage of all the interactive capabilities possible after the record is a database instead of narrative forms. Perhaps follow-up and patient reminders were not built into the system or the system does not have a smart feature that notes that for patients of a given age or sex, certain exams are due.
As organizations work to advance health information exchange, new requirements for wide-area networks require a technology infrastructure that allows access from multiple external locations. Even a single user wants to be able to work from home or use wireless technology to check on information. Many organizations have multiple work sites, and even if this is not the case, health care providers are distributed. Care providers may be visiting a patient at home or simply working from an off-site location. All of this capability must be provided within the bounds of confidentiality and security of protected health information.
At the level of the user interface, another system improvement might elect to use color on the display screen to alert clinical providers to out-of-range laboratory values rather than using asterisks to mark such values. Or because clinicians who copy and paste within an EHR’s electronic progress notes do not always provide appropriate attribution to the original author, automatically adding color to copied text is a way to alert the reader that the original text can be found elsewhere in this patient’s record. Or because certain information may be pulled forward into a note by design, the information added to this visit or progress notes is highlighted in a different color. As users become more sophisticated about how information systems can help them perform their daily tasks more optimally and experience new ways to view data on workstations or on their handheld devices, they are likely to expect system enhancements.
In addition to changes in technology, operational functions, strategic objectives, and user expectations, information systems may become obsolete because they simply wear out—in other words, break down. Mechanical failures with storage devices, input devices, output devices, or processing components are more likely to occur as the system grows older.