Touchscreen task efficiency and learnability in an electronic medical record at the point-of-care.

The objective of this study was to determine the relative efficiency of novices compared to a prediction of skilled use when performing tasks using the touchscreen interface of an EMR developed in Malawi. We observed novice users performing touchscreen tasks and recorded timestamp data from their performances. Using a predictive human performance modeling tool, the authors predicted the skilled task performance time for each task. Efficiency and rates of error were evaluated with respect to user interface design. Nineteen participants performed 31 EMR tasks seven times for a total of 4,123 observed performances. We analyzed twelve representative tasks leaving 1,596 performances featuring six user interface designs. Mean novice performance time was significantly slower than mean predicted skilled performance time (p<0.001). However, novices performed faster than the predicted skilled level in 208 (13%) of successful task performances. These findings suggest the user interface design supports a primary design goal of the EMR--to allow novice users to perform tasks efficiently and effectively

Understanding determinants of acute stroke thrombolysis using the tailored implementation for chronic diseases framework: a qualitative study

Abstract Background The Tailored Implementation in Chronic Disease (TICD) framework is a comprehensive framework describing the determinants of implementation success that has been used extensively in primary care settings. We explored the utility of the TICD to identify determinants of practice in an acute setting, namely guideline concordant acute stroke thrombolysis in a low-resourced, predominately minority serving, large, Emergency Department (ED). Methods Through workshops and expert review, we developed an interview guide informed by the TICD framework. We then conducted semi-structured interviews with data collected through written transcripts, audio transcripts or interviewer notes based on participant availability. Three independent coders then performed a content analysis using template analysis, but open to new determinants that arose from the data, into the TICD framework. Results We performed a total of 15 semi-structured interviews with ED acute stroke providers including medical technicians, nurses, and physicians. We found that guideline factors, individual health professional factors, and patient factors domains were barriers to guideline concordant acute stroke thrombolysis. The domain professional interactions was a facilitator to treatment. We identified three determinants, healthcare professional burnout, health care professional turnover and surrogate decision making, that are not part of the TICD framework. Conclusions Most determinants of acute stroke thrombolysis are included within the TICD framework. Inclusion of healthcare professional burnout, healthcare professional turnover and surrogate decision making may assist in expanding the TICD to time-sensitive ED conditions. Further work is needed to confirm this finding and to establish whether the TICD is applicable for use in non-time sensitive ED conditions. Interventions that address guideline, individual health professional and patient factors may improve guideline concordant acute stroke thrombolysis.https://deepblue.lib.umich.edu/bitstream/2027.42/148315/1/12913_2019_Article_4012.pd

Comparing a mobile decision support system versus the use of printed materials for the implementation of an evidence-based recommendation : protocol for a qualitative evaluation

1-9Background: The distribution of printed materials is the most frequently used strategy to disseminate and implement clinical practice guidelines, although several studies have shown that the effectiveness of this approach is modest at best. Nevertheless, there is insufficient evidence to support the use of other strategies. Recent research has shown that the use of computerized decision support presents a promising approach to address some aspects of this problem. Objective: The aim of this study is to provide qualitative evidence on the potential effect of mobile decision support systems to facilitate the implementation of evidence-based recommendations included in clinical practice guidelines. Methods: We will conduct a qualitative study with two arms to compare the experience of primary care physicians while they try to implement an evidence-based recommendation in their clinical practice. In the first arm, we will provide participants with a printout of the guideline article containing the recommendation, while in the second arm, we will provide participants with a mobile app developed after formalizing the recommendation text into a clinical algorithm. Data will be collected using semistructured and open interviews to explore aspects of behavioral change and technology acceptance involved in the implementation process. The analysis will be comprised of two phases. During the first phase, we will conduct a template analysis to identify barriers and facilitators in each scenario. Then, during the second phase, we will contrast the findings from each arm to propose hypotheses about the potential impact of the system. Results: We have formalized the narrative in the recommendation into a clinical algorithm and have developed a mobile app. Data collection is expected to occur during 2018, with the first phase of analysis running in parallel. The second phase is scheduled to conclude in July 2019. Conclusions: Our study will further the understanding of the role of mobile decision support systems in the implementation of clinical practice guidelines. Furthermore, we will provide qualitative evidence to aid decisions made by low- and middle-income countries’ ministries of health about investments in these technologies

Complexities, variations, and errors of numbering within clinical notes: the potential impact on information extraction and cohort-identification

Abstract Background Numbers and numerical concepts appear frequently in free text clinical notes from electronic health records. Knowledge of the frequent lexical variations of these numerical concepts, and their accurate identification, is important for many information extraction tasks. This paper describes an analysis of the variation in how numbers and numerical concepts are represented in clinical notes. Methods We used an inverted index of approximately 100 million notes to obtain the frequency of various permutations of numbers and numerical concepts, including the use of Roman numerals, numbers spelled as English words, and invalid dates, among others. Overall, twelve types of lexical variants were analyzed. Results We found substantial variation in how these concepts were represented in the notes, including multiple data quality issues. We also demonstrate that not considering these variations could have substantial real-world implications for cohort identification tasks, with one case missing > 80% of potential patients. Conclusions Numbering within clinical notes can be variable, and not taking these variations into account could result in missing or inaccurate information for natural language processing and information retrieval tasks.https://deepblue.lib.umich.edu/bitstream/2027.42/148519/1/12911_2019_Article_784.pd

Complexities, variations, and errors of numbering within clinical notes: the potential impact on information extraction and cohort-identification

Background Numbers and numerical concepts appear frequently in free text clinical notes from electronic health records. Knowledge of the frequent lexical variations of these numerical concepts, and their accurate identification, is important for many information extraction tasks. This paper describes an analysis of the variation in how numbers and numerical concepts are represented in clinical notes. Methods We used an inverted index of approximately 100 million notes to obtain the frequency of various permutations of numbers and numerical concepts, including the use of Roman numerals, numbers spelled as English words, and invalid dates, among others. Overall, twelve types of lexical variants were analyzed. Results We found substantial variation in how these concepts were represented in the notes, including multiple data quality issues. We also demonstrate that not considering these variations could have substantial real-world implications for cohort identification tasks, with one case missing > 80% of potential patients. Conclusions Numbering within clinical notes can be variable, and not taking these variations into account could result in missing or inaccurate information for natural language processing and information retrieval tasks

Implementing goals of care conversations with veterans in VA long-term care setting: a mixed methods protocol

Abstract Background The program “Implementing Goals of Care Conversations with Veterans in VA LTC Settings” is proposed in partnership with the US Veterans Health Administration (VA) National Center for Ethics in Health Care and the Geriatrics and Extended Care Program Offices, together with the VA Office of Nursing Services. The three projects in this program are designed to support a new system-wide mandate requiring providers to conduct and systematically record conversations with veterans about their preferences for care, particularly life-sustaining treatments. These treatments include cardiac resuscitation, mechanical ventilation, and other forms of life support. However, veteran preferences for care go beyond whether or not they receive life-sustaining treatments to include issues such as whether or not they want to be hospitalized if they are acutely ill, and what kinds of comfort care they would like to receive. Methods Three projects, all focused on improving the provision of veteran-centered care, are proposed. The projects will be conducted in Community Living Centers (VA-owned nursing homes) and VA Home-Based Primary Care programs in five regional networks in the Veterans Health Administration. In all the projects, we will use data from context and barrier and facilitator assessments to design feedback reports for staff to help them understand how well they are meeting the requirement to have conversations with veterans about their preferences and to document them appropriately. We will also use learning collaboratives—meetings in which staff teams come together and problem-solve issues they encounter in how to get veterans’ preferences expressed and documented, and acted on—to support action planning to improve performance. Discussion We will use data over time to track implementation success, measured as the proportions of veterans in Community Living Centers (CLCs) and Home-Based Primary Care (HBPC) who have a documented goals of care conversation soon after admission. We will work with our operational partners to spread approaches that work throughout the Veterans Health Administration.http://deepblue.lib.umich.edu/bitstream/2027.42/134645/1/13012_2016_Article_497.pd

Stroke Ready: a multi-level program that combines implementation science and community-based participatory research approaches to increase acute stroke treatment: protocol for a stepped wedge trial

Abstract Background Post-stroke disability is common, costly, and projected to increase. Acute stroke treatments can substantially reduce post-stroke disability, but few patients take advantage of these cost-effective treatments. Practical, cost-efficient, and sustainable interventions to address underutilized acute stroke treatments are currently lacking. In this context, we present the Stroke Ready project, a stepped wedge design, multi-level intervention that combines implementation science and community-based participatory research approaches to increase acute stroke treatments in the predominately African American community of Flint, Michigan, USA. Methods Guided by the Tailored Implementation of Chronic Disease (TICD) framework, we begin with optimization of acute stroke care in emergency departments, with particular attention given to our safety-net hospital partners. Then, we move to a community-wide, multi-faceted, stroke preparedness intervention, with workshops led by peer educators, over 2 years. Measures of engagement of the safety-net hospital and the feasibility and sustainability of the implementation strategy as well as community intervention reach, dose delivered, and satisfaction will be collected. The primary outcome is acute stroke treatment rates, which includes both intravenous tissue plasminogen activator, and endovascular treatment. The co-secondary outcomes are intravenous tissue plasminogen activator treatment rates and the proportion of stroke patients who arrive by ambulance. Discussion If successful, Stroke Ready will increase acute stroke treatment rates through emergency department and community level interventions. The stepped wedge design and process evaluation will provide insight into how Stroke Ready works and where it might work best. By exploring the relative effectiveness of the emergency department optimization and the community intervention, we will inform hospitals and communities as they determine how best to use their resources to optimize acute stroke care. Trial registration ClinicalTrials.gov Trial Identifier NCT03645590 .https://deepblue.lib.umich.edu/bitstream/2027.42/148211/1/13012_2019_Article_869.pd

Correction to: Implementing goals of care conversations with veterans in VA long-term care setting: a mixed methods protocol

Correction The authors would like to correct errors in the original article [1] that may have lead readers to misinterpret the scope, evidence base and target population of VHA Handbook 1004.03 “Life-Sustaining Treatment (LST) Decisions: Eliciting, Documenting, and Honoring Patients’ Values, Goals, and Preferences”.https://deepblue.lib.umich.edu/bitstream/2027.42/142349/1/13012_2018_Article_724.pd

Using Touchscreen Electronic Medical Record Systems to Support and Monitor National Scale-Up of Antiretroviral Therapy in Malawi

Gerry Douglas and colleagues describe the rationale and their experience with scaling up electronic health records in six antiretroviral treatment sites in Malawi