设计有效的电子健康记录的参与工具

by Subrata Acharya, PhD, and Niya Werts, MS EHS, MIS, PhD

抽象的

As healthcare systems continue to expand their use of electronic health records (EHRs), barriers to robust and successful engagement with such systems by stakeholders remain tenacious. To this effect, this research presents the results of a survey tool utilizing both original and modified constructs from the Consolidated Framework for Implementation Research to assess key points of engagement barriers and potential points of intervention for stakeholders of EHRs in a large-scale healthcare organization (500-bed level II regional trauma center). Based on the extensive assessment, the paper presents recommendations for the utility of engagement process modeling and discusses how intervention opportunities can be used to mitigate engagement barriers.

Keywords: electronic health records; consolidated framework for implementation; intervention; adoption

Background and Introduction

The integration of technology into healthcare systems presents a complex narrative. While technology use in healthcare settings (clinical and nonclinical) has been touted as an asset for healthcare providers, healthcare consumers, and other relevant business stakeholders,1–3对技术实施的抵抗力和随后的健康信息系统失败已得到充分记录。4, 5A more realistic perspective on the implementation of technology would be one that views implementation as an iterative process that must continually take into account the variability of complexity6和医疗保健环境中的背景。但是,将基于技术的系统实施到医疗保健环境(财务,人类,时间和风险管理)中所涉及的大量资源需要所有利益相关者的早期实施成功和充分参与,以最大程度地利用该系统的好处。电子健康记录(EHRS)的使用是一个说明性的案例,因为使用的好处可能在很大程度上取决于患者,医疗保健提供者和其他医疗保健系统专业人员的参与互动。7–9术语engagementmay be most often used to reflect interest in and access to a technology. However, for purposes of this study, the term is applied to a broader context encompassing the range of practices and processes of stakeholders from adoption to integration of EHRs.

As part of a continuation of work on leveraging the cloud for EHR access,10研究人员开发了一个过程modeling. A key component of this modeling approach was the construction of a survey tool based on constructs of the Consolidated Framework for Implementation Research (CFIR) to investigate barriers to full engagement of the technologies involved in EHR access and implementation. The CFIR is one of several emergent models from the field of implementation science.11–13尽管有心理测量挑战,但14the CFIR has shown great promise as a highly adaptable model for investigating the implementation of technology in healthcare settings.15–18CFIR介绍了一组整体且定义明确的实施构建类别类别,其主要部分来自其父理论,罗杰的创新理论的扩散,19以及随后由Damshroeder等人进行的工作。20and others.21In summary, the CFIR explores how characteristics of the intervention, the inner and outer settings of where an intervention will be deployed, the characteristics of the individuals who will interact with the intervention, and the functional processes involved with implementing the intervention are all key assessment domains.22, 23Information gleaned from the variables within each of the main construct categories24可以利用所有stakeh受益olders and potentially minimize barriers to successful EHR engagement.

工具设计和方法论

在临床环境中实施医疗保健技术的障碍包括从与人类相关的因素(例如医疗保健提供者的抵抗)到技术因素(例如,系统设计失败)的广泛和多样化的连续体。25–27而这样的外部政策Meaningful Use program can spur adoption and initial implementation, long-term implementation requires committed engagement by all relevant stakeholders (healthcare providers, information technology [IT] staff, and, to some extent, patient end users). Developing a stakeholder engagement model process may be advantageous for organizations to maintain successful implementation by highlighting priority areas where stakeholders have either concordance or discordance on barriers and benefits of the technology.

This research identifies the CFIR as a beneficial framework for engagement modeling because of the comprehensive and holistic nature of the constructs, as detailed inTable 1. These constructs allow for domain flexibility and a thorough investigation of perceptions of benefits and barriers. Although the CFR includes numerous constructs, it includes only five primary areas to investigate. The categories are defined here in context of the current research.

  • Intervention characteristics: the attributes and qualities of the intervention (in this case the EHR system)
  • Outer setting: the external forces shaping adoption and implementation of the EHR system
  • Inner setting: the internal organizational forces shaping adoption and implementation of the EHR system
  • 个人特征:EHR系统的利益相关者和最终用户的属性
  • Process mandates: the contextual specificities of the implementation process of the EHR

使用这五个类别,可以对利益相关者参与的“为什么或为什么不”的“为什么或为什么不这样做,并可以深入研究并专注于每个类别下的特定结构。

Maximizing the opportunity for successful implementation requires identifying and recommending pivotal attributes to improve engagement outcomes for any given healthcare organization. The current research leverages the CFIR to this effect. The proposed research identified three primary groups of participants for the study: the medical/healthcare staff of a large sized federally recognized healthcare organization, the IT staff at the healthcare organization, and the core in-hospital patients at the organization. The key to a successful healthcare engagement is the focused and directed participation of the stakeholders of the healthcare technology. The three phases, as discussed below, identify the operational process used to design an effective engagement tool across the stakeholder groups.

The first phase of the study (construct identification) included a set of targeted interview sessions conducted to gather qualitative data about the most relevant CFIR constructs for the evaluation study. The interviews were conducted anonymously with the key stakeholders of the healthcare intervention and implementation process. Note that a new iteration of the construct identification process can be conducted if the application domain and/or the patient service environments are modified. Furthermore, our study indicates and recommends that to ensure effective adoption and implementation, the organization should conduct periodic assessments of the construct identification to provide a seamless integration of the developing technology landscape.28Figure 1details the overall interaction diagram, which leverages the CFIR framework for the design of the proposed EHR engagement model.

The construct identification phase lays out the qualitative interviewing process and aids in the instrumentation of the tool to help guide the choice of the constructs. The steps followed in this phase include stakeholder vetting and unique stakeholder identification (this process is done in an anonymous fashion, preserving only the type/experience level of the stakeholder); stakeholder engagement process establishment and verification; and, finally, the controlled study of the process with the target group/community.

After the targeted interview sessions, the researchers used a concept mapping approach (proprietary tool) to identify the CFIR variables29(i.e., variables under each of the main construct categories previously identified) that are most relevant to the pilot healthcare organization. These variables were then integrated with the authors’ previous work on EHRs to augment (add to or modify) the construct categories to yield an integrated construct domain tailored to the specific healthcare IT environment.

工具设计过程的下一阶段是data collection and analysis phase. This phase is important to review the appropriate feedback on the identified constructs and assimilate stakeholder input to provide accurate metrics and priorities for the appropriate interventions. The steps followed in this phase include data collection, priority selection, and data analysis (via interview sessions to determine metrics for tool development). The constructs are iteratively modified on the basis of stakeholder feedback to ensure that they are mapped to the appropriate implementation domain.

The next phase of this process is the tool implementation phase, which is based on the feedback from the previous phases. The implementation phase included a targeted functional review of the tool and an iterative evaluation and analysis prior to dissemination. The tool was designed and implemented with a modified set of CFIR constructs identified for the domain-specific study. It also included an augmentation of additional constructs necessary for the specific domain of assessment, such as accountability, interoperability, and organizational compliance. The detailed definitions and mapping of the constructs for the engagement modeling are stated in表格1。

The final phase is the dissemination of the designed tool over the three vital stakeholder domains, namely medical staff, IT staff, and patients. The survey was disseminated over a 500-bed Level II certified regional trauma center at stage 6 of the HIMSS Analytics Electronic Medical Record Adoption Model, managing more than 500,000 patient admissions per year. The healthcare organization houses a large data center that caters to three medium-scale auxiliary hospitals and 20 participating specialized clinical practice centers. The tool included an intuitive tiered numerical mapping for the survey. The participants were advised by the tool to identify, with a score of 0 (no relevance), 1 (positive relevance), or −1 (negative relevance), each construct’s influence on EHR healthcare technology adoption and their role’s mandate to achieve the goal. The data collection was conducted over six months through an online secure anonymous survey tool, with only limited role identification required from the participants.

Evaluation

The survey instrument was successful in retrieving more than 60 responses from the participants. Participation was mainly targeted toward the medical staff who provide clinical services, to assess their views on the factors necessary for effective EHR adoption.

Table 2根据每个构造的响应详细介绍每个构造的汇总分数。例如,对于“复杂性”的构造,35名医务人员参与者中有20个回答说,该构建体是解决和改善有效采用的相关因素。同样,对于构造“参与”,15名患者参与者都没有回答该结构与他们执行和/或促进采用的作用无关。对于IT员工职位的参与者,诸如“适应性”,“可尝试性”,“复杂性”,“客户需求/需求”和“监管政策和激励措施”之类的构造具有最高的意义,可有效实施技术干预措施。

Note that the negative relevance identified by some participants in a given group has the potential to reduce the summative rank and score of the construct for that particular category. The survey tool enabled the researchers to analyze the data collected and identify interventions for each stakeholder group.Table 3details the engagement barriers with priority rankings for each such group. The priority levels designed for each group are proportional to the participation ratio.

The survey tool and the analyzed results enabled the development of the five-step engagement process identified inFigure 2. Each step identifies the barriers to engagement and prompts output to design the appropriate engagement implementation. An iterative feedback loop is integrated to ensure periodic assessment of the outcomes and provide feedback for use in the tool design and analysis phase. The proposed engagement process is portable and can be applied in both inpatient and outpatient healthcare settings.

Discussion and Recommendations

On the basis of the areas identified as the highest priorities, the researchers developed the EHR engagement barrier model (seeFigure 1). The model stratifies participant groups, highlights the areas of highest priority to support robust engagement with the EHR system, and notes preliminary recommendations to begin the process of addressing the barriers within the organization. While all the identified barriers hold importance, the focus on the shared highest-priority areas may yield the most benefit in time- and resource-limited environments; therefore, the researchers chose to leverage those specific constructs for the model.

Recommendations for Shared Engagement Barriers across All Stakeholder Groups (Adaptability, Complexity, and Barriers and Needs)

Perceptions of adaptability, complexity, and barriers and needs were noted as significant engagement barriers across stakeholder groups. Both adaptability and complexity correspond to the “intervention characteristic” domain of the CFIR. In this context, the intervention would be the EHR technology innovation purchased and/or built and utilized. Possible interventions include ensuring that all stakeholders have early input on vendor-based or in-house EHR projects via demos prior to adoption. End users (patients and medical staff) sometimes are not included in these decisions until later stages, if at all. Perceptions of complexity can be mitigated via training opportunities, particularly peer-to-peer trainings. The modified “barriers and needs” construct aligns with the CFIR “outer setting” domain. The outer setting domain frames the importance of external variables in the implementation of new processes and products. While barriers and needs may be considered end-user issues, the survey results highlight how important these issues are perceived to be from the perspective of the IT staff as well. In effort to better understand and communicate the landscape of barriers and needs, an iterative rather than a static process of needs assessment and usability testing may be a preferred approach. Additionally, greater understanding of the technology products that end users interact with regularly outside of the organization may give IT staff valuable information regarding barriers, preferred interfaces, and features to support fuller engagement.

Recommendations for Other High-Priority Engagement Barriers

其他订婚障碍可能是三个利益相关者群体中至少两个提到的障碍。当前研究中指出的其他高优先级障碍是互操作性(患者和医务人员),干预源(医务人员和IT人员),可审判性(医务人员和IT人员),客户需求(医疗人员和IT人员),资源可用性(医务人员和IT人员)和位置(患者和IT人员)。干预源和可试性结构对应于CFIR的“干预特征”领域,并且也适用上述建议以解决干预特征的建议。资源可用性适用于CFIR的“内部设置”域。内部设置域涵盖了影响创新实施的内部组织特征。值得注意的是,CFIR强调了财政之外的资源。为了增强EHR参与度,可能值得澄清利益相关者最重要的资源类别。互操作性,客户需求和位置分别与过程和外部设置域最紧密地保持一致。尽管当前研究的重点是相当大的郊区医院系统,但当医院与农村和遥远的护理伙伴互动时,资源挑战仍然是一个问题。 A lack of interoperability of EHR systems further exacerbates perceptions of the location barrier. Ensuring that health technology systems in place meet federal and regional recommendations for interoperability would mitigate this barrier. Meeting these guidelines may require federally based support resources (financial and training).

结论

The researchers formulated a multistakeholder EHR engagement process model by identifying and mapping the CFIR and modifying the relevant constructs for the domain of healthcare technology. The goal was to illustrate an effective process and engagement modeling tool that could be used to quantify EHR engagement barriers. The survey results identified the focus of each participant group and informed the appropriate stakeholders of the need to provide resources to address the high-frequency constructs. The results also aided in the data-driven process of requesting external (federal and/or state) support and funding opportunities, which are needed to provide a sustainable and construct-driven iterative intervention action plan for the healthcare system. The proposed process and tool can be seamlessly replicated in any healthcare organization.

Subrata Acharya博士,副教授the Department of Computer and Information Sciences at Towson University in Towson, MD.

Niya Werts, MS EHS, MIS, PhD, is an associate professor in the Department of Health Sciences at Towson University in Towson, MD.

Notes

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  4. Ibid.
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  6. Ibid.
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  9. McGinn, C. A., S. Grenier, J. Duplantie, N. Shaw, C. Sicotte, L. Mathieu, and M. P. Gagnon. “Comparison of User Groups’ Perspectives of Barriers and Facilitators to Implementing Electronic Health Records: A Systematic Review.”BMC Medicine9, no. 1 (2011): 46.
  10. Coats B., Acharya S., “Leveraging the Cloud for Electronic Health Record Access,”Perspectives in Health Information Management, January 2014,//www.baptist-tbc.com/leveraging-the-cloud-for-electronic-health-record-access/#.UyZIGoW2_QM.
  11. Ross, J., F. Stevenson, R. Lau, and E. Murray. “Factors That Influence the Implementation of E-health: A Systematic Review of Systematic Reviews (an Update).”Implementation Science11,不。1 (2016): 146.
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  13. “ CFIR指南。”CFIR Research Team, Center for Clinical Management Research,https://cfirguide.org/(accessed May 30, 2018).
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  15. Ross, J., F. Stevenson, R. Lau, and E. Murray. “Factors That Influence the Implementation of E-health: A Systematic Review of Systematic Reviews (an Update).”
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  18. Richardson,J。E.“桥接信息学和实施科学:评估一个评估社区环境中电子健康记录实施的框架。”AMIA Annual Symposium Proceedings(2012):770。
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  21. “ CFIR指南。”
  22. Ross, J., F. Stevenson, R. Lau, and E. Murray. “Factors That Influence the Implementation of E-health: A Systematic Review of Systematic Reviews (an Update).”
  23. “ CFIR指南。”
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  25. Kaplan, B., and K. D. Harris-Salamone. “Health IT Success and Failure: Recommendations from Literature and an AMIA Workshop.”
  26. Irizarry, T., A. D. Dabbs, and C. R. Curran. “Patient Portals and Patient Engagement: A State of the Science Review.”
  27. McGinn, C. A., S. Grenier, J. Duplantie, N. Shaw, C. Sicotte, L. Mathieu, and M. P. Gagnon. “Comparison of User Groups’ Perspectives of Barriers and Facilitators to Implementing Electronic Health Records: A Systematic Review.”
  28. Acharya S., Werts N., “Guiding Healthcare Adoption Implementation via the Consolidated Framework Approach,”22ndColloquium for Information Systems Security Education, June, 2018.
  29. “ CFIR指南。”

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