Navigation in the Electronic Health Record a Review of the Safety and Usability Literature

Abstruse

Purpose of the Study.

Evaluating driving safety of older adults is an important health topic, but primary care providers (PCP) confront multiple barriers in addressing this issue. The written report'south objectives were to develop an electronic health tape (EHR)-based Driving Clinical Back up Tool, train PCPs to perform driving assessments utilizing the tool, and systematize documentation of assessment and management of driving safety issues via the tool.

Design and Methods.

The intervention included development of an show-based Driving Clinical Support Tool within the EHR, followed by training of internal medicine providers in the tool'southward content and use. Pre- and postintervention provider surveys and chart review of driving-related patient visits were conducted. Surveys included self-report of preparedness and knowledge to evaluate at-risk older drivers and were analyzed using paired t-test. A chart review of driving-related office visits compared documentation pre- and postintervention including: completeness of appropriate focused history and exam, identification of deficits, patient education, and reporting to appropriate government when indicated.

Results.

Data from 86 providers were analyzed. Pre- and postintervention surveys showed significantly increased self-assessed preparedness (p < .001) and increased driving-related knowledge (p < .001). Postintervention charts showed improved documentation of right cognitive testing, more referrals/consults, increased patient education well-nigh customs resources, and appropriate regulatory reporting when deficits were identified.

Implications.

Focused training and an EHR-based clinical support tool improved provider self-reported preparedness and knowledge of how to evaluate at-risk older drivers. The tool improved documentation of driving-related issues and led to improved access to interdisciplinary care coordination.

Few older adults expect to end driving, although retirement from driving is the "norm"; on average men and women cease driving 6 and 10 years prior to death, respectively (Carr, Schwatzberg, Manning, & Sempek, 2010). This paradigm of driving until one dies originates from driving existence considered a correct; the social significance of driving as information technology relates to autonomy and independence; as well as the pragmatics of transportation (Stephens et al., 2005). Older drivers now drive afterward in life and they drive further than previous generations, representing a 27% increment in the number of drivers aged 65 from 1997 to 2011 (Centers for Affliction Control and Prevention [CDC], 2013; Carr et al., 2010; Insurance Establish for Highway Prophylactic [IIHS] and Highway Loss Data Plant [HLDI], 2014).

Although the incidence of fatal crashes is decreasing in this population and some older drivers practice self-limit their driving, historic period-related physiological changes can negatively impact driving ability and are contributing factors in crashes involving older drivers (CDC, 2013; Insurance Constitute for Highway Safety [IIHS] and Highway Loss Data Found [HLDI], 2014). Driving-related mortality is the leading cause of accident-related death in people anile 65–74 and 2nd only to falls for people 75 and older (Carr et al., 2010), underscoring the need for chief care providers (PCPs) to skillfully place at-risk drivers and promote good for you driving behaviors. Providers cite barriers to discussing driving bug with patients, including time constraints; the potential to negatively bear upon the relationship with patients; a lack of noesis virtually how to assess fitness to drive; and uncertainty nearly how to intervene if necessary (Adler and Rottunda, 2011; Betz et al., 2014; Carr et al., 2010; Jang et al., 2007; Miller and Morley, 1993).

Electronic health records (EHRs) are increasingly leveraged to support clinical practice by delivering tools within the EHR to support healthcare determination-making. This effort has been promoted nationally by the Establish of Medicine's [IOM] (2001) report, "Crossing the Quality Chasm: A New Wellness System for the 21st Century" (Englebardt & Nelson, 2002; Institute of Medicine's [IOM], 2001). No description of driving-related clinical support tools exists in the current literature. All the same, literature on EHR use generally supports topic-specific tool development; studies show summarized material to exist more than effective than mere admission to database searches (Hersh, Crabtree, Hickam, Sacherek, Rose, & Friedman, 2000; Hersh et al., 2002; McKibbon & Fridsma, 2006; Wallace, Bigelow, Xu, & Elstein, 2007; Westbrook, Coiera, & Gosling, 2005). Provider preference in the literature supports design that minimizes interruptions, is opened on-demand, and is easily attainable during patient encounters (Ash, Sittig, Campbell, Guappone, & Dykstra, 2007; Ash et al., 2012; Epstein, Tannery, Wessel, Yarger, LaDue, & Fiorillo, 2010; McKibbon & Fridsma, 2006; Wallace et al., 2007). Voluntary employ of tools prevents the unintended upshot of alert fatigue, which can lead to ignoring available resources (Ash et al., 2007).

This quality improvement project aimed to: (1) develop a Driving Clinical Back up Tool in an EHR to assist PCPs in evaluating at-risk drivers based on a synthesis of current bear witness and resources; (two) railroad train PCPs to use the tool and its content; (3) via the training and utilize of the tool, increase provider knowledge and self-perceived preparedness to evaluate driving abilities in older adults and implement a plan of care; and (iv) improve provider documentation of driving evaluation assessment and management within the EHR.

Methods

Blueprint

This study was a brief intervention, a training, to enhance principal care internal medicine provider assessment, and direction of at-risk older drivers using an EHR tool designed to guide clinical intendance. Pre- and postintervention surveys evaluated change in provider knowledge and preparedness to appraise driving-related abilities in older adults and in developing appropriate plans for at risk older drivers. In addition, driving-focused role visit encounters were reviewed for compliance with expert driving cess practices before and subsequently the intervention.

Sample

Participants were recruited from an academic primary care practice that included 25 faculty providers and 100 medical residents. All providers were invited to participate; 98 (78%) attended the training and completed the survey. The report was canonical by the University Institutional Review Board and all included providers signed informed consent.

Process

EHR Driving Clinical Support Tool development

An EHR-based Driving Clinical Support Tool was developed to help PCPs evaluate at-run a risk drivers. Central to the EHR tool was the creation of a driving evaluation algorithm based on a literature review of bear witness-based do for evaluating at-risk drivers, besides as a visit annotation template focused on driving (come across Figures 1 and 2). Guidelines of the American Medical Association (AMA) and the American Academy of Neurology (AAN) informed the algorithm and note (Carr, Schwartzberg, Manning, & Sempek, 2010; Iverson, Gronseth, Reger, Classen, Dubinsky, & Rizzo, 2010). Prior research has shown that executive function and speed of processing are important predictors of driving abeyance that can sometimes be improved with training (Ackerman, Edwards, Ross, Ball, & Lunsman, 2008; Edwards, Delahunt, & Mahncke, 2009). The Trails B was recommended as part of the Driving Clinical Support Tool since it can quickly assess patient attention, psychomotor speed, and visual scanning in a busy principal care setting (Aksan, Anderson, Dawson, Uc, & Rizzo, 2015; Hetland, Carr, Wallendorf, & Barco, 2014; Iverson et al., 2010).

Effigy 1.

Algorithm of Evaluation and Management of At-Risk Drivers. The informational symbol serves every bit a hyperlink within the electronic wellness tape and can be linked to additional resources or forms for that particular topic.

Content for the tool evolved through an iterative process including a literature review; a review of local licensing laws and definitions; an outline of the provider procedure for referring to the Section of Motor Vehicles (DMV) for a driving evaluation or for mandatory reporting of patients with severe and uncontrollable impairments; easy access to the definition of 'severe and uncontrollable harm'; an overview of the associated fees for driving evaluation by the DMV or private driving rehabilitation, which is not typically covered by insurance; and possible outcomes for patients after being reported as an at-risk driver (license revocation, opportunity for testing, reinstatement of license). The tool also included a synthesis of local community resources available for vehicle modification, driver grooming, rehabilitation services, and culling transportation resources. Patient and family unit educational materials to be used at office visits were developed to summarize the findings of an at-take chances driving evaluation; offer an example of a family driving agreement; depict what information technology means to submit a mandatory referral; and provide a listing of the community resources described previously (rehabilitative evaluation, alternative transportation, mobility adaptation companies; see the Patient Instructions department of the Driving Social club Set equally shown in Figure 2). Considerations of usability and utility collection the blueprint of the overall tool. Content and finish-user experts reviewed the tool for accuracy, clarity, utility, and omissions. The development of a comprehensive compilation of driving-related provider and patient materials adapted for use in the EHR represented an interdisciplinary collaboration including PCPs, social service providers, and information technology specialists.

Figure ii. Driving order set and provide note template. The symbols *** trigger the provider to enter data. The phrases surrounded past brackets ({,}) are prompted lists (as shown) that the provider can select one or more than appropriate clinical options.

Provider Training

A 20-min training intervention was developed to train PCPs on the clinical evaluation of an at-risk driver and how to utilise the Driving Clinical Support Tool within the EHR during an office visit. Provider trainings occurred during regularly scheduled team meetings for each of the practice's five provider teams and via regularly scheduled ambulatory conferences for residents. A full of nine trainings (given past two study investigators) were completed with 20 faculty and 78 residents. A survey was done prior to and immediately following each educational session to measure provider knowledge and preparedness to evaluate older adults for safe driving.

Measures

Demographic data was obtained from the participants and included clinical team, part (kinesthesia or resident), and degree.

Provider Knowledge and Preparedness Survey

The Provider Knowledge and Preparedness Survey included an 11-item survey of 4 Likert scale and 7 multiple-choice questions adult specifically for this study (see Supplementary Appendix A for the survey). Questions assessed knowledge of important physical examination findings, state reporting requirements, medications that cause driving impairment, rehabilitation of driving-related deficits, and billing for the evaluation of driving-related deficits; clinical questions were taken from the AMA and the AAN driving-related guidelines (Carr et al, 2010; Iverson et al., 2010). 4 questions addressed cocky-perceived skill in the ability to assess driving condom; programme driving-related interventions; access driving resources; and appropriately report unsafe driving to licensing bodies (Likert Scale 1–five, with a higher score indicating greater self-perceived skill). Five conten experts, including a geriatrician, geriatric nurse practitioner, gerontologist-driving specialist, social worker, and nurse researcher reviewed the items for face validity.

Driving-Related Office Visits

Driving-related visits were evaluated based on documentation in the electronic health tape. Driving-related encounters were included for analysis if they were coded using the ICD-9 lawmaking v58.19 (driving condom issue) or the EHR Driving Clinical Back up Tool was utilized; the provider attended i of the driving training sessions and completed the surveys; patient was age 65 or older; and the patient was seen between January 2011 (27 months prior to the intervention) through June 2014 (15 months after the intervention).

Investigators reviewed eligible charts to evaluate adoption of the Driving Clinical Support Tool, including use of evidence-based assessments and adequate documentation of appropriate plans when indicated. Key components of the chart review are outlined in Tabular array 1 and include: driving evaluation and assessment (using best practice as outlined on the driving algorithm [see Figures one and ii]); capability of planning based on clinical findings (appropriate referrals, medication changes, instructions to stop driving if indicated); adherence to legal requirements (mandatory reporting for drivers with astringent and uncontrolled deficits); and bear witness of patient education, including use of appropriate community resource (Table 1).

Tabular array 1.

Summary of Key Chart Review Data

Driving evaluation elements	Preintervention (n = 12) Northward (%)	Postintervention (north = 18) North (%)
Evaluation and assessment
Driving dotphrase utilization (including notation template or patient education)	NA	10 (56)
Trails B examination utilization	2 (17)	half-dozen (33)
Driving-related patient education in afterward visit summary	ii (17)	15 (83)
Referrals
Referrals not made (but likely indicated)	4 (33)	2 (xi)
Mandatory referrals indicated	3 (25)	6 (33)
Mandatory referrals filed	0	6 (33)

Driving evaluation elements	Preintervention (due north = 12) N (%)	Postintervention (n = 18) N (%)
Evaluation and cess
Driving dotphrase utilization (including annotation template or patient didactics)	NA	10 (56)
Trails B test utilization	2 (17)	six (33)
Driving-related patient teaching in after visit summary	2 (17)	15 (83)
Referrals
Referrals not made (merely likely indicated)	4 (33)	2 (xi)
Mandatory referrals indicated	3 (25)	6 (33)
Mandatory referrals filed	0	6 (33)

Note: Mandatory referrals includes 2 DMV commuter evaluation referrals, the step prior to mandatory referral.

Table 1.

Summary of Central Chart Review Data

Driving evaluation elements	Preintervention (due north = 12) N (%)	Postintervention (due north = 18) N (%)
Evaluation and assessment
Driving dotphrase utilization (including annotation template or patient education)	NA	10 (56)
Trails B test utilization	2 (17)	six (33)
Driving-related patient instruction in after visit summary	2 (17)	15 (83)
Referrals
Referrals not fabricated (only probable indicated)	iv (33)	2 (11)
Mandatory referrals indicated	3 (25)	6 (33)
Mandatory referrals filed	0	6 (33)

Driving evaluation elements	Preintervention (n = 12) N (%)	Postintervention (n = 18) N (%)
Evaluation and cess
Driving dotphrase utilization (including note template or patient teaching)	NA	10 (56)
Trails B examination utilization	2 (17)	six (33)
Driving-related patient educational activity in later visit summary	2 (17)	fifteen (83)
Referrals
Referrals not fabricated (but likely indicated)	four (33)	2 (eleven)
Mandatory referrals indicated	3 (25)	6 (33)
Mandatory referrals filed	0	6 (33)

Note: Mandatory referrals includes 2 DMV driver evaluation referrals, the step prior to mandatory referral.

Data Analysis

Analysis of the development of the EHR Driving Clinical Support Tool (research question #1) occurred iteratively through content skilful review and refinement as described above. Analysis of the PCP training on the utilize of the Driving Clinical Support Tool (research question #2) was descriptive in terms of training attendance and attendee demographics. For research question #iii, pre- and postsurvey data were matched using a unique identifier allowing for paired comparison. Survey data were entered into Excel, using EZAnalyze software for analysis later on v% of data were verified and determined to exist authentic. Survey items using a Likert calibration were analyzed individually and as a composite score using paired t-tests. Multiple-selection questions were analyzed individually using Chi-squared tests and as a blended score using a paired t-test.

For inquiry questions #4, clinical data from driving-related role visits were analyzed using quantitative descriptive techniques to code whether the Driving Clinical Support Tool could assistance ameliorate the documentation of the evidence-based components of the evaluation and plan for an at-risk older driver. Tandem review of charts by ii investigators occurred for fifty% of the office visit encounters.

Results

A total of 98 internal medicine faculty and resident providers attended a training session during monthly clinical team meetings or a resident teaching seminar, respectively, over a menses of 6 weeks. In addition to physicians, the sample included 2 nurse practitioners and i md assistant.

Provider Knowledge and Preparedness Survey

Information from 86 providers were included in the final analysis, including xiv faculty and 72 residents. Information from 12 providers were excluded either because both pre- and postsurveys were non completed or pre- and postsurveys could not be correctly linked using a unique identifier. Posttest cocky-perceived preparedness scores were significantly higher (xiv.9) than pretest scores (10.9), both at the item and composite level (p < .001) (See Figure three). Composite noesis scores improved significantly after the intervention (mean score 5.3 vs. 3.5, p < .001). When analyzed individually, Chi-squared tests showed no statistically significant difference at the item level of the knowledge questions (See Effigy 4). The post-test included a request for comments, which universally indicated PCPs anticipated using the tool in practice.

Effigy 3.

Mean score (1–5, v is best) and total score (out of 20) of provider self-cess of preparedness and cognition related to caring for at-risk older drivers (p < .001).

Figure 4.

Knowledge related to caring for at-risk older drivers. Percent of right provider responses to knowledge questions (p > .05). Hateful total score (not graphically depicted) for preintervention knowledge was three.4 versus postintervention v.iii (p < .001).

Chart Review of Driving-Related Visits

30 office visits (12 pre- and 18 postintervention), involving 26 patients, met the criteria for chart review analysis (Table 1). Considering these driving-focused visits occurred equally role of routine care, not all providers who participated in the trainings saw patients needing a driving evaluation. Iii patients had multiple office visits that addressed driving (2–iv office visits per patient). 1 faculty used the tool but did not attend the grooming intervention and another faculty used the tool on a patient < 65 years onetime; these function visits were not included in the analysis.

These 26 patients were evaluated past 9 of the 86 providers trained to use the Driving Clinical Support Tool, including 4 kinesthesia and 5 residents. All four of the kinesthesia who attended the training intervention and used the Driving Clinical Support Tool subsequently the training had also evaluated at-hazard older drivers prior to the availability of the tool. A single resident evaluated at-risk older drivers before and later on the intervention; three residents used the tool after the grooming. Residents who used the driving EHR tool were precepted by 3 kinesthesia who had attended the training intervention, just did non independently use the EHR Driving Clinical Support Tool. Therefore, a full of eight kinesthesia of the fourteen who were trained on the tool either used information technology themselves or facilitated resident use of the tool. The average historic period of patients evaluated for driving across both pre- and postintervention period was 82.

The pre- and postintervention charts were like in the history and exam documented, although the preferred test of executive function (Trails B) was used more frequently posintervention. Assessments consistently documented cognitive issues equally a trigger for the driving evaluation. Notable differences existed in the completeness of documentation of a plan to address deficits, patient education, and country-mandated reporting; all improved after the intervention. Prior to the intervention, providers identified severe and uncontrolled deficits that met criteria for mandatory reporting to the Section of Motor Vehicle (DMV) but did not document filing a written report. Postintervention, providers accordingly referred 4 mandatory reports to the DMV and submitted paperwork for 2 additional DMV evaluations, the stride before mandatory revocation. Postintervention, providers more consistently made and documented referrals for advisable follow upwards services and resources. Referrals or consults included ophthalmology, neurology, neuropsychiatry, geriatrics, concrete therapy, occupational therapy, cognitive therapy, social piece of work, and driving rehabilitation specialists.

Chart review showed that providers utilized the EHR tool to admission educational resources to provide patients with driving-related data at the office visit; utilize of the provider note template was not every bit uniformly adopted. Just a unmarried role visit postintervention included all components of the full provider note template and patient educational materials. Almost oftentimes, providers used portions of the notation template (history or exam) to guide their evaluation.

Discussion

This written report tested a newly developed evidence-based EHR Driving Clinical Support Tool to increase PCP skill to treat at-risk older drivers. The written report demonstrated that the incorporation of a topic-specific geriatric clinical tool into the EHR is feasible every bit an approach to deliver geriatric bear witness-based practice to generalist providers. Dissemination and training on the tool successfully occurred by using existing venues for faculty and resident education. The study's aims related to improving provider knowledge and documentation of evaluation at-chance drivers were modestly achieved. PCP knowledge and self-perceived power to care for at-chance older drivers both increased.

A higher proportion of faculty providers (57%) than residents (v%) used the Driving Clinical Back up Tool after the preparation intervention. While non an explicit aim of the study, driving-related role visits increased after the grooming intervention; 12 driving-related office visits occurred over the 27 months prior to the intervention, while 18 occurred in the 15 months post-obit the intervention. The low adoption charge per unit by providers, particularly residents, after the intervention, might point to the demand for continued educational exposure on a periodic footing, the testimony by early adopters speaking to the utility of the tool, or a systematic approach to identify at-adventure drivers.

The Driving Clinical Support Tool did not include a tiered-algorithm for screening patients for driving risk in which widespread screening is followed past in-depth evaluation for those patients who screen positive (Betz et al., 2014). A systematic screening approach might atomic number 82 to a higher rate of identified at-risk drivers, with greater uptake of the Driving Clinical Back up Tool. The evolution of an EHR-based Driving Clinical Back up Tool is timely and consistent with current efforts underway by the AMA, the American Elderliness Society, and the National Highway Traffic Prophylactic Administration to increase standing medical education of providers on how to assess and counsel older drivers (Hansen, 2014).

Chart review confirmed that regulatory referrals and referral to specialists and community resources, and documentation of these referrals, increased afterward the preparation and gyre out of the EHR Driving Clinical Back up Tool. Postintervention, changes in patient evaluation were minimal except for the more widespread adoption of the Trails B examination; but PCP'due south documented increased use of service integration, state reporting, and sharing of community resources with patients. Providers documented more than robust plans to address driving deficits, including an emphasis on interdisciplinary referrals and increased patient pedagogy about bachelor resource. These referrals are important to help identify deficits conducive to rehabilitation (Edwards et al., 2009; Edwards, Bart, O'Connor, & Cissell, 2010). For case, social work was used to address the touch on identity and autonomy, and occupational and cognitive therapies to independently evaluate driving abilities, including executive office. Taken together, providers addressing driving risk demonstrated improved competency as coordinators of a complex safety issue by using the EHR tool. These findings underscore the interprofessional nature of complex geriatric intendance that could exist facilitated by clinical tools designed to help integrate care (Reuben et al., 2013).

The driving discussion with patients often occurred over several part visits, even if not all of these visits used the driving safety evaluation codes. Multiple office visits included providers referencing prior conversations with a patient virtually driving or providers introducing the idea of a driving evaluation but deferring the total evaluation to a time to come visit. Providers clearly documented difficulty with the topic and the decision to report someone; and documented awareness of the social, emotional, and logistical implications of the loss of driving privileges.

This work adds to extant literature showing the potential role of EHR clinical tools to promote show-based care, especially given national efforts to promote adoption and utilise of EHRs (Adler-Milstein et al., 2014; Englebardt & Nelson, 2002; Wallace et al., 2007). Interprofessional geriatric team care often requires the coordination of multiple disciplines, such as social work and rehabilitation services, in improver to customs and governmental agencies outside of the healthcare system, to provide the most constructive intendance for older adults, many with multiple comorbidities (Reuben et al., 2013). In this intervention, access to referrals and to knowledge of community resource was systematized and produced the greatest change in knowledge and practice. A clinical support tool built into the EHR can help synthesize large amounts of data from multiple sources and integrate interdisciplinary content, both of which are hallmarks of optimal geriatric intendance (McKibbon & Fridsma, 2006).

Limitations

The generalizability and strength of this study are limited by its small sample size and descriptive design. The apply of a single grouping pre/posttest design increased the number of participants, but did not afford an unbiased control grouping. The algorithm and training did not include a systematic approach to screening at-adventure older drivers (Betz et al., 2014); use of the Driving Clinical Support Tools was triggered at the provider's discretion. Furthermore, if providers documented driving evaluations but did not utilize the created tools nor associated ICD-9 lawmaking, these encounters were not captured in the chart review analyses.

Limitations to the written report likewise included bug in coordinating training and information collection for decorated providers. The 88% response rate is primarily explained by PCPs arriving late or leaving early from trainings. Elapsing of training was too express, typical of a decorated clinical do environment. A qualitative evaluation of providers' perceptions of usability and utility of the clinical tool could besides have informed the project.

Conclusion

This quality improvement project demonstrated successful development of an EHR-based clinical support tool to help PCPs evaluate and manage at-chance older drivers using evidence-based standards of care. After training, documentation of at-risk older drivers improved; intendance plans demonstrated evidence-based interdisciplinary plans of care; and mandatory reporting occurred when indicated. This format for broadcasting of clinical information to back up PCPs caring for older adults, including those trained in elderliness and those without formal geriatric training, shows promise, and supports further EHR-based tool evolution to enhance PCP adoption of optimal bear witness-based geriatric practices.

Supplementary Material

Supplementary material tin be constitute at: http://gerontologist.oxfordjournals.org.

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Writer notes

Decision Editor: Barbara Resnick, PhD, CRNP, FAAN, FAANP

Published by Oxford University Press on behalf of the Gerontological Guild of America 2015.

andrewslachatiet.blogspot.com

Source: https://academic.oup.com/gerontologist/article/55/Suppl_1/S128/561808

Navigation in the Electronic Health Record a Review of the Safety and Usability Literature

Abstruse

Methods

Blueprint

Sample

Process

EHR Driving Clinical Support Tool development

Provider Training

Measures

Provider Knowledge and Preparedness Survey

Driving-Related Office Visits

Data Analysis

Results

Provider Knowledge and Preparedness Survey

Chart Review of Driving-Related Visits

Discussion

Limitations

Conclusion

Supplementary Material

References

Writer notes

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