Core Technologies

Implementation of an Evidence-Based Electronic Health Record (EHR) Downtime Readiness and Recovery Plan

Nurse using mobile nursing information system

Health care facilities have become gradually dependent on information technology to computerize almost all aspects of patient care. In the United States, as of 2015, electronic health record (EHR) systems had been installed in 96% of hospitals. Adoption of EHRs among non-federal acute care hospitals was nearly universal. Computers have become embedded in clinical workflow processes, and any disruptions to access the computer system were found to have severe consequences to hospital operations, finance, patient safety, providers, and especially the clinical staff. The need to implement an evidence-based downtime readiness and recovery plan was recognized early to ensure meaningful and enhanced management of computer systems and more importantly to guarantee safe patient care.

The site of this capstone project is Baylor St. Luke’s Medical Center (BSLMC), a teaching hospital licensed for 850 beds (629 operating beds) and a tertiary referral center serving both the greater Houston area and the global community. Guided by Roger’s Innovation Adoption Theory (2003), the project found that after implementation of an EHR downtime readiness and recovery tool kit (budge buddies, downtime algorithm and downtime kits), nurses were prepared for any EHR scheduled or unscheduled downtime. Staff nurses can correctly articulate EHR preparation, downtime and recovery and identify the process of responding to EHR downtime after using the badge buddies. The project was able to achieve the following goals: assess the readiness of staff nurses for any scheduled or unscheduled EHR downtime, design and implement evidence-based downtime readiness and a recovery plan toolkit, and compare the readiness of staff nurses for any scheduled or unscheduled EHR downtime before and after implementation of the evidence-based downtime readiness and recovery plan toolkit.

Problem Recognition

Health care facilities have become gradually dependent on information technology to computerize almost all aspects of patient care (Larsen, Haubitz, Wernz, & Ratwani, 2016). The Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 has led to amplified implementation and use of health information technologies (Sittig, Gonzalez, & Singh, 2014). The HITECH Act required that all healthcare facilities use a certified electronic health record (EHR) to achieve and receive incentive payments for meaningful use. In the United States, as of 2015, EHR systems had been installed in 96% of hospitals and adoption of EHRs among non-federal acute care hospitals is nearly universal (Henry, Pylypchuk, Searcy, & Patel, 2016).

The EHR is an integral component of many healthcare institutions. Several hospitals have implemented successful programs to promote the use of EHRs. As information management becomes progressively complex, the systems that computerize healthcare services likewise increase in difficulty and functionality. Computers become embedded in clinical workflow processes, and any disruptions to access the computer system have severe consequences to hospital operations, finance, patient safety, providers, and especially the clinical staff. EHR technology offers a blanket of protection during patient care; however, multiple reports of patient safety threats during EHR system downtime highlight the unintended consequences of integrating technology into health care delivery (Kashiwagi, et al., 2016). In a 2014 survey of U.S. health care organizations, 96% of the institutions reported at least one unplanned downtime in the last three years and 70% had at least one unplanned downtime lasting eight or more hours in the previous three years (Sittig, et al., 2014). Furthermore, the survey also revealed that three hospitals reported that one or more patients were injured as a consequence of either planned or unplanned downtime.

A study conducted by Chen, Wang, & Magrabi (2017) revealed four distinct causes of downtime in hospitals. Network issues were most common, accounting for 69-90% of downtime events and power outages that include power failures either from the supplier, human error or standby power failures. Software failures, partial or total loss of functionality of the EHR software during which end-users experience either the slow response of the system or inaccessibility are some of the typical reasons. System interface failure happens if the EHR has connections to a third-party system that has a direct or indirect impact on the EHR. A good example is the Laboratory Information System and Radiology Imaging System. If one of these systems fails to communicate with the primary EHR, this leads to delays in patient care because results are inaccessible. Computer viruses or a malicious software program that infect the computer system is one of the widely reported causes of computer downtime. Power failure, extreme weather conditions, incorrect computer configuration, wireless connectivity issues, old building infrastructure, and human failure are some of the causes that contribute to the increase in system downtime. Learning the origins of computer failures and knowing how to address and prevent them can be of vital importance for overall business continuity or the downtime and recovery plan of the institution. Furthermore, the financial effects of system downtime range from $7,000 to $17,000 per minute, based on the proceedings of the Sixth Annual Benchmark Study on Privacy and Security of Healthcare Data report (Ponemon Institute, 2016).

Hurricanes and other extreme weather disturbances can cause widespread damage to hospitals that can result in loss of network connectivity, power outages, and structural damage. The year 2017 is considered one of the top seven most active years for hurricanes and storms (Erdman, 2017). The devastation of Hurricanes Harvey, Irma and Maria was unprecedented for the community, hospitals and infrastructure. In August 2005, Hurricane Katrina shocked New Orleans and left 11 hospitals without power, severed communications, and caused a failure to provide hospitals with essential supplies (Hebert & Gray, 2007). Houston is 40 miles from the Gulf Coast, making the city especially susceptible to storms and hurricane.

Computer system inaccessibility, regardless of primary cause, can create chaos for clinical users and organizations. Information can be lost or compromised and clinical staff must return to manual documentation processes. Healthcare computer system downtime poses a threat to patient safety and patient care continuity. Any disruption of clinical workflow and care delivery can lead to patient harm (Chen, et al., 2017). Nurses and other clinical staff are some of the primary users and beneficiaries of EHRs. Nursing is typically the first group of clinicians to report if the computer system is inaccessible. The clinical staff’s dependence on the system is tied to their day-to-day workflow; performing patient assessments, measuring vital signs, intake and output, acknowledging and completing orders, ordering supplies, reviewing patient information and consults, to name a few. A study conducted by Wang and colleagues (2016) at a 350-bed metropolitan teaching hospital in Australia demonstrated the feasibility of using consistently collected EHR data to measure the effects of downtime on delays and errors in clinical processes. Clinician follow-up of test results was considerably delayed by downtime. The study established that the effect of downtime on clinician follow-up differs according to the type of IT problem (Wang et al., 2016). The transformation from paper records to electronic documents, by definition, involved numerous changes in the documentation process for clinical staff and an added burden due to variations of workflow. Furthermore, downtime planning activities are de-prioritized or deferred during EHR implementation as the focus is on the operations and ensuring a running system for the clinical staff (Shepard, 2017).

Downtime can be attributed to planned system maintenance and upgrades, or to the unexpected loss of connection or power failure. Understanding the cause of computer failures may be the first step. Understanding the implications of downtime to nurses and clinicians can make way for dialogue and learning. Implementing evidence-based downtime readiness and recovery planning can lead to meaningful and enhanced management of computer systems and safe patient care. Nursing and other clinical staff will greatly benefit from a clinically focused evidence-based downtime toolkit for use during system failure. Understanding computer downtime impacts on nurses, providers and other clinical users of EHRs can lead to a robust step-by-step downtime and recovery plan.

Setting

The site of this capstone project was Baylor St. Luke’s Medical Center (BSLMC), an acute tertiary care nonprofit teaching hospital which opened in 1954 in the Texas Medical Center and is one of 17 hospitals under Catholic Health Initiatives (CHI) Texas Division with a combined service area of 22,724 square miles. BSLMC is a teaching hospital licensed for 850 beds (629 operating beds) and a tertiary referral center, serving both the greater Houston area and the global community. BSLMC’s primary focus is to provide quality, patient-focused care. Physicians in 23 clinical services covering more than 40 specialties are supported by the most advanced technologies available. An EHR was first installed in the institution in 2001 and transitioned to a more robust EHR in 2012.

Operational Downtime Incident Management (ODIM), the CHI Texas division downtime governance, was formed in July 2017 due to communication challenges between IT and hospital operations during critical downtime incidents and increasing number of downtime events experienced by the organization from 2016 to 2018. The group consists of the project proponent and interdisciplinary leaders from nursing, laboratory, radiology, pharmacy, clinics, IT and revenue cycle from all CHI Texas facilities. The group’s task is to come up with the best communication structure to deploy during critical downtime incidents. A clinical system downtime audit was conducted at BSLMC during August 2017 and recommendations for improvement of downtime management were presented to the clinical informatics director to establish specific action plans.

Stakeholders for this project are nurses, clinical staff, IT, the clinical informatics (CI) department, and hospital leadership, as they are main players during any downtime event. Nurses and clinical staff are the first group of hospital staff that identifies and reports if the EHR is not working. They need information and resources to continue delivery of care during EHR outages.  IT, CI and hospital leadership approve, develop and manage the effective and efficient implementation of downtime readiness and recovery. Capstone project sponsors were the current division Vice President of nursing practice, education and research; the Division Director for clinical informatics; and the BSLMC Senior Vice President and Chief Nursing Officer. A detailed presentation of BSLMC strengths, weaknesses, opportunities and threats (SWOT) analysis for the Information Technology Downtime Process is presented in Table 1.

Table 1. SWOT Analysis of the BSLMC Information Technology Downtime Process

Evidence-Based Initiative

Research on healthcare EHR downtime is in its early stages, especially in a clinical or hospital setting (Larsen, et al., 2016). There is no active monitoring of the occurrence and scope of downtime currently experienced by hospitals in the United States or other institutions in the world. In a recorded downtime event in a 350-bed hospital in Australia, researchers found that the average downtime disruption in care delivery was 49 hours per year with 51% of total downtime between 9 a.m. and 5 p.m. (Chen, et al., 2017), normally the busiest time for hospital personnel in terms of need to access the system. As the global utilization of EHRs continues to grow, the need for further studies to measure the effects of downtime on patient care and patient outcomes is more acute.

Preparation

Downtime preparedness is essential to ensure patient safety and continuity of care when clinical systems are impaired or completely unavailable (Kashiwagi, et al., 2016). Downtimes are unavoidable and prolonged ones can be catastrophic, so it is essential to have policies, processes, and procedures in place, both for the information technology staff to recover from the downtime and for the clinical staff to continue to provide safe care during these times (Coffey, Postal, Houston, & McKeeby, 2016). A study conducted by Oral, Cullen, Diaz, Hod, & Kratz (2015)  suggested that clinicians need to collaborate, review systems capabilities, and design innovative ways to optimize patient care during downtimes. The downtime protocol was developed based on the work of an interprofessional collaborative team from intensive care unit (ICU), emergency department (ED), inpatient units, procedural areas, laboratory information system (LIS) and hospital leadership. Armour (2015) mentioned that the business continuity profession has been following a methodology that has barely evolved since its inception and proposed a new approach to the discipline and new tactics in preparation for computer outages.

Recovery

To effectively deliver care to patients, providers must have a contingency plan in place to handle EHR downtimes (Larsen, et al., 2016). In the United States and in other countries this has become a legal mandate. The primary contingency plan requires the use of back-up manual versions of the electronic forms. The problem is that clinical staff have become so accustomed to solely documenting in the EHR that many of them are not even aware that paper versions exist, nor are they familiar with the manual forms designed to be used in a downtime situation (Coffey, et al., 2016).
Typically, and currently, in a downtime situation, a downtime cart is made available for the staff to use. The cart consist of a plastic storage bin with downtime paper forms that are grouped by category (e.g., downtime checklist, physician orders, progress notes, patient care flowsheet, medication administration record, admission, transfer and discharge, and other patient care forms). The downtime cart provides all necessary paper forms that should be used during downtime to continue documentation of safe patient care. Cook (2015) provided a six-step process for successful business continuity and disaster recovery planning that included a governance structure or executive commitments, identification of staff responsible for the plan, business impact analysis, designing the plan, testing and training, and maintenance. Cook further stated that proper planning would allow continuity and recovery regardless of the cause of system failure. What matters is a team that understands and knows what to do. EHR downtime algorithms provide a clear pathway of recognizing downtime, communication and recovery processes. The algorithm delineates appropriate staff action for each downtime step.

Badge Buddy

A Badge Buddy is a double-sided, badge-sized reference card or cheat sheet that can help clinical staff to find available resources and actions to take during EHR downtime (Figure 1). The cards attach to a badge holder for speedy access, bringing key EHR downtime information in an easy-to-remember acronym. The widespread use of cheat sheets both in education and the medical arena is evident in various studies. A study by de Raadt (2012) revealed that students who create and use cheat-sheets performed better, on average, in an introductory programming examination. Certain features of cheat sheets were found to be related to superior performance, which may relate to student understanding. Mascioli, Laskowski-Jones, Urban, & Moran (2009) did a study on handoff that revealed that accessibility of the tools is crucial to project success. The team developed pocket cards with abbreviated handoff information that guided the staff during handoff. Krombach, Edwards, Marks, & Radke (2015) did a study that embraced the concept of checklists and other cognitive aids. This was true for all providers for checklists for procedural time outs, anesthesia crisis situations, and those that addressed routine procedures that providers rarely perform.

Furthermore, Bulson, Van Dyke, & Skibinski (2017) suggested a strong collaboration between information systems and emergency preparedness departments was key to the success and the ongoing improvement of the downtime response model. By redesigning the incident management process, response outcomes and end-user experiences increased from 57% to 86% over the past three years.

Figure 1. The Badge Buddy is designed using laminated paper that works with existing institution ID badges.

Project Plan

Purpose of the Project with Objectives

The following are the purpose and objectives of this project:

  1. To assess the readiness of staff nurses for any scheduled or unscheduled EHR downtime.
  2. To design an evidence-based EHR downtime readiness and recovery plan toolkit.
  3. To implement the use of the evidence-based EHR downtime readiness and recovery plan toolkit.
  4. To compare the readiness of staff nurses for any scheduled or unscheduled EHR downtime, before and after implementation of the evidence-based EHR downtime readiness and recovery plan toolkit.

Type of Project and Theory to Guide Implementation

This is a quality improvement project. Roger’s (2003) Innovation Adoption Theory was used to guide the implementation of this evidence-based project. Diffusion of innovation theory purports that users’ motivation in using technology is based on the usage benefit, work value, ease of use, trial and error, and visible outcome of use. The diffusion of innovation theory established by Rogers (2003) explained how individuals and communities respond to new ideas, practices or objects. Diffusion of innovation is the manner in which an innovation is transferred through certain channels, over time, among members of a social system. Innovations may be either accepted or rejected. Rogers explained that even when a new idea has positive advantages, it can be challenging for an individual or organization to adopt the idea. It is up to each individual clinical user to accept or reject the new idea.

Implementation of a new evidence-based downtime toolkit is considered a new idea and will create a new clinical practice, and a new set of guidelines will be introduced. Hospital leaders need to establish metrics to achieve the desired goal and find champions to accelerate the adoption of a new EHR downtime toolkit. Clinicians and organizations as a whole vary in how they respond to innovations. The perceived attributes of the project innovation through a selection of super users or project champions, organizational education, training of end-users, organizational communication, and ongoing evaluation can influence the quick adoption and the change diffusion of the project.  Figure 2 presents a graphical presentation of Diffusion of Innovation Theory.

Figure 2. Diffusion of Innovation Theory

Setting and Needed Resources

The site of this capstone project was Baylor St. Luke’s Medical Center (BSLMC), a teaching hospital licensed for 850 beds (629 operating beds) and a tertiary referral center, serving both the greater Houston area and the global community. Collaboration with the Informatics Council at BSLMC was essential for the success of this project. The Informatics Council is one of the staff nurse councils of the shared governance structure of BSLMC. It is composed of staff nurse representatives from various nursing units that meet monthly to discuss issues with electronic applications used at the hospital. The council verbally agreed to support this capstone project. The division Vice President for nursing practice, education and research is a committee member of this project.

The project was implemented in two nursing units at BSLMC. A rounding tool was used to assess the readiness of staff nurses for any scheduled and unscheduled downtime (Tables 2 and 3). The rounding tool was presented to the Informatics Council and feedback was used to optimize the tool. The initial project assessment was conducted on two nursing units at BSLMC during the months of January and February 2019. An electronic survey was developed using the questions on the rounding tool and was used on two identified nursing units before and after the implementation of an evidence-based EHR downtime readiness and recovery toolkit. The tool was used to assess readiness of the BSLMC nursing staff during scheduled or unscheduled EHR downtime. The electronic survey was tested by the members of Informatics Council prior to use for validity.

Table 2. Rounding Tool used to assess nurse readiness for downtimes: Preparation

Table 3. Rounding Tool used to assess nurse readiness for downtimes: Downtime & Recovery

Design for the Evidence-based Initiative

This quality improvement project focused on the implementation of an evidence-based downtime readiness and recovery toolkit. The project intervention was the creation and distribution of Badge Buddies to all inpatient nurses; the Badge Buddies defined two essential components of the existing EHR downtime algorithm called PREP and CLEAR (Table 4).

Table 4. Electronic Health Record (EHR) Downtime Protocol

Badge Buddies are laminated cheat-sheets that hang from existing institution ID badges (Figure 1). An electronic learning module was designed to explain the details of PREP and CLEAR, and one on one in-service was provided to all inpatient nurses on the two nursing units at BSLMC. The EHR downtime toolkit was composed of the Badge Buddy, downtime algorithm, clinical downtime checklist, carts, and downtime paper forms. Only the clinical downtime checklist, carts and downtime paper forms were available pre-intervention on the nursing units.

The project design was composed of four phases: initial assessment, project implementation, assessment and results reporting. Several steps were followed to achieve objectives for each phase (Figure 3). The survey questionnaire was created based on components of the downtime checklist and toolkit.

Figure 3. Project Design Phases and Steps

The survey was tested for content validation and readability by the Informatics Council members and validated by the BSLMC Nursing Research Department. Automated Readability Index posted an overall score of 59, demonstrating that the content was readable for a college student (Figure 4). A simple T-test of equal and unequal variance was used to test the success of the project implementation by comparing the survey results before and after project implementation.

Figure 4. Automated Readability Index (ARI)

Retrieved from: http://www.readabilityformulas.com/free-readability-formula-tests.php

Participants, Sampling and Recruitment Strategies

Taking the project survey were 68 staff nurses (35 during the pre-assessment and 33 post-implementation) working as full-time or part-time employees in two inpatient nursing units of BSLMC for the implementation of the project during the months of January to May of 2019. The selection of the two nursing units was based on the recommendation of the SVP & CNO of BSLMC and division Vice President of nursing practice, education and research. Staff nurses were asked to complete the following during the project:

  1. Rounding tool/survey, before and after project implementation, to assess readiness during scheduled and unscheduled downtime.
  2. One-on-one training that included the components of evidence-based EHR downtime readiness toolkit.
  3. Badge Buddy access that detailed the steps for PREP and CLEAR and the downtime algorithm and instructions for its use.

Measurement: Sources of Data and Tools

A rounding tool/survey was created to assess staff readiness during scheduled and unscheduled downtime. The rounding tool/survey was tested initially with the members of the Informatics Council to ensure content readability before distribution to nursing staff of the selected nursing units before and after project implementation. Comparison of the rounding tool/survey results before and after project implementation was used to assess the project’s success. (Tables 2 and 3)

Outcomes indicators were as follows:

  1. 85% of the staff will be able to correctly articulate EHR preparation, downtime and recovery process after using the Badge Buddies.
  2. 85% of the staff will be able to correctly identify the process of responding to EHR downtime using the Badge Buddies.
  3. 75% of the staff will be able to participate successfully in one downtime drill.

Steps for Implementation of Project, including Timeline

The project commenced after the determination of non-human subject research from the IRB of CHI and Loyola University Chicago in December 2018 and January 2019 respectively. The project was presented to key hospital leadership to seek authorization and support. The BSLMC Informatics Council and unit educators’ project kick-off meeting was scheduled for the first week of November to provide clarity and shared understanding of the project design and timeline. The Informatics Council, unit nurse leaders and unit educators are considered the early adopters of any new hospital application or process to propel this project to full adoption.
Two other meetings were conducted to discuss pre-implementation and post-implementation results with unit nursing leaders, educators and members of the council. Steps of project implementation and timeline are presented in detail in Figure 5. Projected implementation during the month of March were delayed for four weeks because of regulatory survey conducted at BSLMC by the Centers for Medicare & Medicaid Services (CMS). The initial approved online education was also changed to one-on-one instructions with the project leader, unit educator and informatics resource nurse of the unit to decrease online-module burnout of the nurses during the two months preparation for the CMS visit.

Figure 5. Project Implementation Steps and Timeline

Project Evaluation Plan

Project evaluation was based on the following approaches: pre-implementation rounding tool/survey results were compared to post-implementation rounding tool/survey results to evaluate staff knowledge and understanding of EHR preparation, downtime and recovery process. The downtime rounding tool was used to provide a quick assessment of staff readiness for a scheduled or unscheduled EHR downtime event. A successful downtime drill was based on the overall score of two nursing units; a score of 85% completion/performance was the goal.

Ethics and Human Subjects Protection

No personal data were collected during the electronic survey; only demographic and unit-specific information, such as years of service as an RN and at BSLMC, were collected. The questions in the electronic survey were geared toward the assessment of the staff’s readiness during scheduled and unscheduled EHR downtime.

Sample and Setting

An average of 88.1% of the respondents was female, and 11.9% were male (Table 5).

Table 5. Respondents Demographics: Gender

The average age of 20-30 years was 38.4%, 31-40 years was 23.5%, followed by 41-50 years, with 27.9% of the respondents (Figure 6).

Figure 6. Respondents Demographics: Age

Respondents represented in the project who had been a nurse for only 0-5 years was 41.4%, 6-10 years was 11.7%, 11-15 years 16.3% (Figure 7).

Figure 7. Respondents Demographics: Nursing experience

The percentage of respondents who worked at BSLMC for 0-5 years was 47.2% (Figure 8). Worth noting in this project is that most of the nurses at BSLMC with an average age of 20-30 and working at BSLMC as an RN for 0-5 years were not exposed to the use of paper documentation. The EHR was only fully implemented at BSLMC in June 2012.

Figure 8. Respondents Demographics: Nursing experience at BSLMC

The project was highly recommended by BSLMC nursing leadership and the Informatics Council. Using early adopters such as the unit nursing leaders, educators and informatics resource nurses helped in the quick adoption of the evidence-based project. The early adopters helped in the preparation, education and assessment of the readiness of staff nurses during the EHR downtime readiness and recovery project. Different strategies to improve EHR downtime readiness and recovery were undertaken after the pre-assessment result was discussed with the unit leaders. Several outdated downtime forms that were found still existing in the unit downtime carts/kits were disposed of appropriately. Proper labeling and arrangement of the downtime forms, downtime PC and kits were undertaken before post-implementation assessment.

The unexpected CMS visit during the early month of March 2019 halted the implementation of the project. Online learning was changed to one-on-one training with the project leader with the help of the unit educator and informatics resource nurse to capture some staff nurses during nights and weekends. Several CMS educational modules were already assigned to all nursing staff from February to March, and adding an online module was judged to increase the chances of burnout and divert the staff education out of CMS preparation. Project implementation was completed in April 2019 after the completion of the CMS visit, followed by a post-implementation survey in May 2019.  

Results/Outcomes

Out of the 33 staff nurses from the two nursing units at BSLMC, 92.8% - 99.3% were able to correctly articulate EHR preparation, downtime, and recovery process using the Badge Buddies.  Out of the 33 staff nurses from the two nursing units at BSLMC, 92.8% - 99.3% were able to correctly identify the process of responding to EHR downtime using the Badge Buddies. Out of the 33 staff nurses from the two nursing units at BSLMC, 84.8% participated successfully in a downtime drill after the project completion. See Figures 9 and 10 for details of the graphical presentation of project outcomes on pre-assessment and post-implementation assessment. Out of the 17 questions of the downtime rounding tool, all 16 items posted a marked improvement based on the pre- and post-assessment survey, except for the question on downtime recovery of staff knowing how to call IT support or 58000. 

The eight questions pertaining to downtime readiness on preparation were statistically significant with a p-value of 0.00 with a 95% confidence interval using t-tests of equal and unequal variance. T-tests was used to determine if there is a significant difference between the means of the pre-assessment and post-implementation rounding tool. An average of n=31 or 93% of staff demonstrated a marked improvement in downtime preparation on locating downtime policy, downtime PC and checklist, evaluation, and validation of the downtime forms comparing pre-assessment and post-assessment data. A marked improvement was also evident on the number of staff who were able to participate in downtime drills, from n= 0 to n=28 after post-assessment (Figure 6).

Figure 9. Preparation - EHR Downtime Readiness

The five questions pertaining to downtime readiness on CLEAR were statistically significant with a p-value of 0.00 with 95% confidence interval using t-tests of equal and unequal variance, with the exception of staff knowing how to call 5800 with a p-value of 0.08. Improvement of an average n=15 to n=33 or from 43.5% to 99.3% of the staff were able to correctly identify the process of downtime recovery from verifying EHR status; locating the downtime plans, kits, and BCA PC; and disposing of manual forms after documentation in the EHR. BSLMC staff had been previously trained to call 58000 for any IT-related concerns, including EHR downtime, which is the main reason why there is only a slight improvement from pre-assessment and post-assessment.

Figure 10. CLEAR – EHR Downtime Readiness

Regarding questions on staff knowing the procedure for verifying EHR status, staff know how to report EHR downtime and notify the manager. Although statistically significant with p-value of 0.04, 0.01 and 0.01 respectively, the result signifies that BSLMC staff have reached a level of maturity of knowing when the EHR is not accessible and can articulate how and who to report for downtime (see Table 6 for details of significance testing). These findings can be attributed to staff exposure on the number of downtimes BSLMC had experienced for the past five years before the project implementation.

Table 6. Project Significance Testing Results

Conclusion

The implementation of an EHR downtime readiness and recovery tool kit, Badge Buddies, downtime algorithm, and downtime kits prepare nurses for any EHR scheduled or unscheduled downtime. Staff nurses can correctly articulate EHR preparation, downtime and recovery and identify the process of responding to EHR downtime after using the Badge Buddies. The use of EHR Badge Buddies made information for downtime preparation and recovery easily accessible to staff nurses and was considered a useful tool. The EHR downtime algorithm also provided a clear pathway for staff action during downtime. The rounding tool was able to assess staff readiness on EHR downtime preparation and recovery processes. Collaboration with unit nursing leaders, educators and informatics nurses helped in the early adoption of the evidence-based EHR downtime readiness and recovery tool in the two nursing units.

Limitations

The project was limited to only two nursing units in a single hospital institution. The project was limited in only assessing the readiness of the staff nurses during EHR scheduled or unscheduled downtime. EHR downtime checklist and forms were not reviewed during the project because this would have extended the project timeline. Staff was only trained with the contents of the Badge Buddies, algorithm and downtime kits. Paper documentation using the EHR downtime forms was not included in the education plan.

Discussion / Summary

EHR downtime preparation and recovery is a complex process, and implementation of an evidence-based tool kit to make the process simple and easy for staff to understand and perform will tremendously improve and prevent the negative impact of EHR downtime to clinical processes and patient outcomes. Readiness, preparation and knowing where the resources are during EHR downtime can be the first step, but further research is warranted on the EHR downtime itself. Training staff on how to use downtime forms, monthly EHR downtime audits, drills, and creating instructions on how to use the paper downtime forms must be included in future EHR downtime projects. As well, hospital facilities need to identify and designate an appropriate time frame to start the EHR downtime process. Delays in starting the EHR downtime process also delays patient care and downtime recovery.

Stakeholder Support/Sustainability

Approval from BSLMC leadership was secured after the presentation of the project schedule in November 2018. Leadership support was anticipated and subsequently obtained for the overall project, as well as for the distribution to all concerned nursing staff of the EHR downtime toolkit that included the Badge Buddies, downtime algorithm and complete downtime carts/kit. After a one-time downtime drill, a monthly or quarterly downtime drill is also recommended to sustain the purpose and objectives of the project. Moreover, it is recommended that all newly hired and current staff be given access to the Badge Buddy and toolkit after this project. Creation of the learning management system module targeted at learning downtime standards of procedure should be in place for newly hired and current staff and should be repeated on an annual basis. The project can be implemented hospital-wide and possibly division-wide.

Implications for Practice

Downtime preparedness is essential to ensure patient safety and continuity of care when electronic health records are completely inaccessible. The EHR downtime toolkit can serve as a quick guide and tool for the clinician to navigate available resources during the period of outages to continue patient care and documentation. The project can be easily replicated and adopted by other departments and institutions to supplement their EHR downtime plans. This project will serve as a springboard to increase facility and staff engagement during EHR outages. The project can also be part of the growing EHR downtime nursing science. As the utilization of EHRs is growing around the world, further studies are essential to measure the effects of downtime on patient care and patient outcomes.

The views and opinions expressed in this blog or by commenters are those of the author and do not necessarily reflect the official policy or position of HIMSS or its affiliates.

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Bulson, J., Van Dyke, M., & Skibinski, N. (2017). Rebooting healthcare information technology downtime management.Journal of Business Continuity & Emergency Planning, 11(1), 63-72.

Chen, J., Wang, Y., & Magrabi, F. (2017). Downtime in digital hospitals: An analysis of patterns and causes over 33 months. Studies in Health Technology and Informatics, 239, 14-20. doi:10.3233/978-1-61499-783-2-14

Coffey, P. S., Postal, S., Houston, S. M., & McKeeby, J. W. (2016). Lessons learned from an electronic health record downtime. Perspectives in Health Information Management, (Summer). Retrieved from https://perspectives.ahima.org/lessons-learned-from-an-electronic-healt…

Cook, J. (2015). A six-stage business continuity and disaster recovery planning cycle. SAM Advanced Management Journal, 80(3), 23-68.

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Author Bios:

Jonathan G. Gecomo, DNP, RN

John is a Lead Clinical Informaticist and Manager, Patient Care Informatics at Baylor St. Luke’s Medical Center. He earned a DNP – Informatics from Loyola University Chicago in2019; a
MSN from Loyola University New Orleans in 2012; and a BSN from the University of the City of Manila in1992.

Audrey Klopp, PhD, RN, NHA

Audrey is an Assistant Professor at Loyola University Chicago and is the Director of the DNP and Adult Health/Gero Clinical Nurse Specialist Programs at  Loyola University Chicago. She earned a PhD from University of Illinois at Chicago in 1988, a MS from Rush University in 1978, and a BSN from the University of Illinois at Chicago in 1974.

Melissa Rouse, PhD, APRN, CNS-BC, NEA-BC
Melissa is the Division Vice President of Nursing Practice, Education and Research at St. Luke’s Health in Houston, Texas.