Change management

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Change management refers to a systematic approach to adapting to, controlling and effecting change within an organization. In the context of HIT system implementation, Change Management takes into account the engineering and physical process management aspects of installing the new system, as well as the “people” aspects of redesigning organizational and individual work-flow and workers' roles within the new system.

Importance

Changing clinical practice to adhere to evolving clinical guidelines, healthcare policy and quality improvement advances is essential to improving patient outcomes. Automated reminders, electronically prescribed medications, medication interaction alerts, and clinical decision support provide an opportunity to improve patient care utilizing technological advances.

Change management is not limited to technological interventions, however, but also accounts for technological interaction with clinicians. Thus, a complete approach to change management must include effective understanding of behavior change theory in order maximize change efficacy.2


Philosophy

Innovation diffusion described by Glanz et al. in 2008 describes the important features of how change is accomplished. It attests that the rate at which change spreads is based upon three principles: the attributes and perception of the innovation, the characteristics and behaviors of the adopters, and the context within which it is introduced.1

Rogers in 2003 described attributes of an innovation which lead to increased change to include relative advantage, compatibility, complexity, trial-ability, and observability. Relative advantage addresses the idea that the innovation improves the current situation. Compatibility encourages that change should remain consistent with previous experience and needs. Complexity describes the perceived difficulty with the application of the change is made. Trial-ability and observability describe the ability to try a change and the ability to observe others utilizing the change prior to its implementation respectively.

The adopters described by Rogers are separated into groups based upon the timing of their decision to accept change: innovators, early adopters, early majority, late majority, and laggards. It is noted that these adopters are placed under a bell curve with the early and late majority adopters falling within one standard deviation of the mean.

The context within which the innovation is introduced is also thought to substantially influence change. As a profession, medicine is filled with complex and nuanced decision making which is presented under time constraint and sometimes with limited background information. Change management strategies in healthcare must wisely reference this context in order to achieve successful implementation.4

Application to HIT

A recent meta-analysis publication by Keyworth, Armitage, and Tully (2018) analyzed studies in health information technology with three aims: identifying interventions which resulted in change, determining the theory behind such interventions by placing them within the classification of behavior change techniques and determining facilitators and challenges to implementation.

Of the studies assessed, the intervention which was most successful was based in the behavior change theory classified as “instruction on how to perform a behavior,” namely clinical decision support. Targeted behaviors within clinical decision support included adherence to clinical guidelines, evidence based medication management and utilization of screening tests, and increasing knowledge/confidence in decision making. This strategy was most effective for general practitioners and was more effective in the hospital than in the clinic environment.

Studies were assessed for common themes for successful and unsuccessful change. Facilitating themes and barriers were categorized in four areas: Role of the healthcare professional, design/content/technical issues, usability, and practice/workload issues.

The roll of the healthcare worker, consistent with the Glanz theory of innovation diffusion1, was very important in facilitating change. Individual characteristics of the physicians in the studies had a great impact on facilitating change. Those with positive attitudes toward uptake, endorsement from senior peers, and those with active engagement were the most successful interventions. Where interventions increased the physicians confidence in the decision being made, successful change was most prominent.

Technical issues, design and content dramatically impacted successful change. Technical aspects which were prominent in successful studies included preliminary pilot testing as well as links to external patient information resources and guidelines. Consistency and relevance of the external resources were important to building confidence in the suggested clinical decision support. Technical barriers to success included limited technology staff and resources, frequent software updates, and inconvenient physical location of computers.

Usability was another critical aspect of change management. Beneficial to change included ease of access to clinically relevant information, consideration of the clinical complexities, and facilitation of patient discussion and teaching. Ample time and support for learning the technology was important for successful change as well. As might be expected, poor interaction with user interface was a barrier to change.

Workload concerns and time constraints were also assessed in regard to successful change interventions. Users were more likely to adhere to the above goals when systems were integrated well within their established work flows and aligned with practice goals and organizational purpose. Improved communication between healthcare professionals also improved workload and thus adoption of systems. Where technology increased time spent or required additional staff for utilization, adoption and change were hindered.3

Conclusion

Change management within HIT systems reflects not only technological advancement but also the complex nature of behavioral intervention. Based on the above meta-analysis, four recommendations were made for successful change within health information systems:

  1. Interventions need to “make sense” to clinicians with a clear function which aligns with organizational and clinic goals.
  2. Interventions must be undertaken with support from key professionals.
  3. Interventions must integrate easily within an existing clinical workflow while taking into consideration the current clinical work load and the setting in which technology is utilized.
  4. Every HIT intervention needs to serve the basic purpose of improving the patient encounter.3

These characteristics clearly fall within the baseline theory of innovation diffusion and should be central to strategy and planning when instituting change within any healthcare institution.


References

  1. Glanz, K., Rimer, Barbara K, & Viswanath, K. (2008). Health behavior and health education : theory, research, and practice (4th ed.). Jossey-Bass.
  2. Joshi M, Ransom, Elizabeth R., Nash, David B., Ransom, Scott B. The Healthcare Quality Book : Vision, Strategy, and Tools. Third edition. Health Administration Press ; Association of University Programs in Health Administration (AUPHA); 2014.
  3. Keyworth, C, Hart, J, Armitage, C J, Tully, M P. What maximizes the effectiveness and implementation of technology-based interventions to support healthcare professional practice? A systematic literature review. BMC medical informatics and decision making. 2018;18(1):93-93. doi:10.1186/s12911-018-0661-3
  4. Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.


Submitted by Heather Gardner, MD