Computer clinical decision support that automates personalized clinical care: a challenging but needed healthcare delivery strategy.

How to deliver best care in various clinical settings remains a vexing problem. All pertinent healthcare-related questions have not, cannot, and will not be addressable with costly time- and resource-consuming controlled clinical trials. At present, evidence-based guidelines can address only a small fraction of the types of care that clinicians deliver. Furthermore, underserved areas rarely can access state-of-the-art evidence-based guidelines in real-time, and often lack the wherewithal to implement advanced guidelines. Care providers in such settings frequently do not have sufficient training to undertake advanced guideline implementation. Nevertheless, in advanced modern healthcare delivery environments, use of eActions (validated clinical decision support systems) could help overcome the cognitive limitations of overburdened clinicians. Widespread use of eActions will require surmounting current healthcare technical and cultural barriers and installing clinical evidence/data curation systems. The authors expect that increased numbers of evidence-based guidelines will result from future comparative effectiveness clinical research carried out during routine healthcare delivery within learning healthcare systems.

Evaluation in Life Cycle of Information Technology (ELICIT) framework: Supporting the innovation life cycle from business case assessment to summative evaluation.

OBJECTIVE: Our objective was to develop an evaluation framework for electronic health record (EHR)-integrated innovations to support evaluation activities at each of four information technology (IT) life cycle phases: planning, development, implementation, and operation. METHODS: The evaluation framework was developed based on a review of existing evaluation frameworks from health informatics and other domains (human factors engineering, software engineering, and social sciences); expert consensus; and real-world testing in multiple EHR-integrated innovation studies. RESULTS: The resulting Evaluation in Life Cycle of IT (ELICIT) framework covers four IT life cycle phases and three measure levels (society, user, and IT). The ELICIT framework recommends 12 evaluation steps: (1) business case assessment; (2) stakeholder requirements gathering; (3) technical requirements gathering; (4) technical acceptability assessment; (5) user acceptability assessment; (6) social acceptability assessment; (7) social implementation assessment; (8) initial user satisfaction assessment; (9) technical implementation assessment; (10) technical portability assessment; (11) long-term user satisfaction assessment; and (12) social outcomes assessment. DISCUSSION: Effective evaluation requires a shared understanding and collaboration across disciplines throughout the entire IT life cycle. In contrast with previous evaluation frameworks, the ELICIT framework focuses on all phases of the IT life cycle across the society, user, and IT levels. Institutions seeking to establish evaluation programs for EHR-integrated innovations could use our framework to create such shared understanding and justify the need to invest in evaluation. CONCLUSION: As health care undergoes a digital transformation, it will be critical for EHR-integrated innovations to be systematically evaluated. The ELICIT framework can facilitate these evaluations.

Implementing lung cancer screening in primary care: needs assessment and implementation strategy design.

Lung cancer screening with low-dose computed tomography (CT) could help avert thousands of deaths each year. Since the implementation of screening is complex and underspecified, there is a need for systematic and theory-based strategies. Explore the implementation of lung cancer screening in primary care, in the context of integrating a decision aid into the electronic health record. Design implementation strategies that target hypothesized mechanisms of change and context-specific barriers. The study had two phases. The Qualitative Analysis phase included semi-structured interviews with primary care physicians to elicit key task behaviors (e.g., ordering a low-dose CT) and understand the underlying behavioral determinants (e.g., social influence). The Implementation Strategy Design phase consisted of defining implementation strategies and hypothesizing causal pathways to improve screening with a decision aid. Three key task behaviors and four behavioral determinants emerged from 14 interviews. Implementation strategies were designed to target multiple levels of influence. Strategies included increasing provider self-efficacy toward performing shared decision making and using the decision aid, improving provider performance expectancy toward ordering a low-dose CT, increasing social influence toward performing shared decision making and using the decision aid, and addressing key facilitators to using the decision aid. This study contributes knowledge about theoretical determinants of key task behaviors associated with lung cancer screening. We designed implementation strategies according to causal pathways that can be replicated and tested at other institutions. Future research is needed to evaluate the effectiveness of these strategies and to determine the contexts in which they can be effectively applied.

Patient-Generated Health Data in Pediatric Asthma: Exploratory Study of Providers' Information Needs.

BACKGROUND: Adolescents are using mobile health apps as a form of self-management to collect data on symptoms, medication adherence, and activity. Adding functionality to an electronic health record (EHR) to accommodate disease-specific patient-generated health data (PGHD) may support clinical care. However, little is known on how to incorporate PGHD in a way that informs care for patients. Pediatric asthma, a prevalent health issue in the United States with 6 million children diagnosed, serves as an exemplar condition to examine information needs related to PGHD. OBJECTIVE: In this study we aimed to identify and prioritize asthma care tasks and decisions based on pediatric asthma guidelines and identify types of PGHD that might support the activities associated with the decisions. The purpose of this work is to provide guidance to mobile health app developers and EHR integration. METHODS: We searched the literature for exemplar asthma mobile apps and examined the types of PGHD collected. We identified the information needs associated with each decision in accordance with consensus-based guidelines, assessed the suitability of PGHD to meet those needs, and validated our findings with expert asthma providers. RESULTS: We mapped guideline-derived information needs to potential PGHD types and found PGHD that may be useful in meeting information needs. Information needs included types of symptoms, symptom triggers, medication adherence, and inhaler technique. Examples of suitable types of PGHD were Asthma Control Test calculations, exposures, and inhaler use. Providers suggested uncontrolled asthma as a place to focus PGHD efforts, indicating that they preferred to review PGHD at the time of the visit. CONCLUSIONS: We identified a manageable list of information requirements derived from clinical guidelines that can be used to guide the design and integration of PGHD into EHRs to support pediatric asthma management and advance mobile health app development. Mobile health app developers should examine PGHD information needs to inform EHR integration efforts.

Analysis of the cognitive demands of electronic health record use.

The goal of this study was to elicit the cognitive demands facing clinicians when using an electronic health record (EHR) system and learn the cues and strategies expert clinicians rely on to manage those demands. This study differs from prior research by applying a joint cognitive systems perspective to examining the cognitive aspects of clinical work. We used a cognitive task analysis (CTA) method specifically tailored to elicit the cognitive demands of an EHR system from expert clinicians from different sites in a variety of inpatient and outpatient roles. The analysis of the interviews revealed 145 unique cognitive demands of using an EHR, which were organized into 22 distinct themes across seven broad categories. In addition to confirming previously published themes of cognitive demands, the main emergent themes of this study are: 1) The EHR does not help clinicians develop and maintain awareness of the big picture; 2) The EHR does not support clinicians' need to reason about patients' current and future states, including effects of potential treatments; and 3) The EHR limits agency of clinicians to work individually and collaboratively. Implications for theory and EHR design and evaluation are discussed.

QuitSMART Utah: an implementation study protocol for a cluster-randomized, multi-level Sequential Multiple Assignment Randomized Trial to increase Reach and Impact of tobacco cessation treatment in Community Health Centers.

BACKGROUND: Tobacco use remains the leading cause of death and disability in the USA and is disproportionately concentrated among low socioeconomic status (SES) populations. Community Health Centers (CHCs) are a key venue for reaching low SES populations with evidence-based tobacco cessation treatment such as Quitlines. Electronic health record (EHR)-based interventions at the point-of-care, text messaging (TM), and phone counseling have the potential to increase Quitline reach and are feasible to implement within CHCs. However, there is a lack of data to inform how, when, and in what combination these strategies should be implemented. The aims of this cluster-randomized trial are to evaluate multi-level implementation strategies to increase the Reach (i.e., proportion of tobacco-using patients who enroll in the Quitline) and Impact (i.e., Reach × Efficacy [efficacy is defined as the proportion of tobacco-using patients who enroll in Quitline treatment that successfully quit]) and to evaluate characteristics of healthcare system, providers, and patients that may influence tobacco-use outcomes. METHODS: This study is a multilevel, three-phase, Sequential Multiple Assignment Randomized Trial (SMART), conducted in CHCs (N = 33 clinics; N = 6000 patients). In the first phase, clinics will be randomized to two different EHR conditions. The second and third phases are patient-level randomizations based on prior treatment response. Patients who enroll in the Quitline receive no further interventions. In phase two, patients who are non-responders (i.e., patients who do not enroll in Quitline) will be randomized to receive either TM or continued-EHR. In phase three, patients in the TM condition who are non-responders will be randomized to receive either continued-TM or TM + phone coaching. DISCUSSION: This project will evaluate scalable, multi-level interventions to directly address strategic national priorities for reducing tobacco use and related disparities by increasing the Reach and Impact of evidence-based tobacco cessation interventions in low SES populations. TRIAL REGISTRATION: This trial was registered at ClinicalTrials.gov (NCT03900767) on April 4th, 2019.

Understanding Primary Care Providers' Information Gathering Strategies in the Care of Children and Youth with Special Health Care Needs.

Background: Effective care coordination of children and youth with special health care needs (CYSHCN) is critical but challenging. Objective: To investigate clinicians' information-gathering strategies while preparing for visits with CYSHCN. Methods: Critical incident interviews with primary care physicians and care coordinators. Results: Six themes emerged indicating 1) substantial reliance on the electronic health record; 2) a central role of the problem list in organizing and summarizing information; 3) Medical Home's central role in organizing clinical documentation; 4) universal need to integrate information from external records; 5) lack of well-organized and labeled encounter documentation; and 6) lack of tools reconcile medication lists. Conclusion: Our findings have important implications to the design of informatics tools to support information-gathering in the care of CYSHCN.

Information needs of physicians, care coordinators, and families to support care coordination of children and youth with special health care needs (CYSHCN).

OBJECTIVES: Identify and describe information needs and associated goals of physicians, care coordinators, and families related to coordinating care for medically complex children and youth with special health care needs (CYSHCN). MATERIALS AND METHODS: We conducted 19 in-depth interviews with physicians, care coordinators, and parents of CYSHCN following the Critical Decision Method technique. We analyzed the interviews for information needs posed as questions using a systematic content analysis approach and categorized the questions into information need goal types and subtypes. RESULTS: The Critical Decision Method interviews resulted in an average of 80 information needs per interview. We categorized them into 6 information need goal types: (1) situation understanding, (2) care networking, (3) planning, (4) tracking/monitoring, (5) navigating the health care system, and (6) learning, and 32 subtypes. DISCUSSION AND CONCLUSION: Caring for CYSHCN generates a large amount of information needs that require significant effort from physicians, care coordinators, parents, and various other individuals. CYSHCN are often chronically ill and face developmental challenges that translate into intense demands on time, effort, and resources. Care coordination for CYCHSN involves multiple information systems, specialized resources, and complex decision-making. Solutions currently offered by health information technology fall short in providing support to meet the information needs to perform the complex care coordination tasks. Our findings present significant opportunities to improve coordination of care through multifaceted and fully integrated informatics solutions.

Evaluation of the effect of information integration in displays for ICU nurses on situation awareness and task completion time: A prospective randomized controlled study.

OBJECTIVE: The study measured whether nurses' situation awareness would increase and task completion time decrease when they used an integrated information display compared to traditional displays for medication management, patient awareness and team communication. SETTING: The Burn Trauma Intensive Care Unit (BTICU) at the University Hospital, University of Utah Health Science Center, Salt Lake City, Utah, USA. PARTICIPANTS: 12 experienced BTICU nurses. MEASURES: Situation awareness (accuracy of the participants' answer) and task completion time (response time from seeing the question to submitting the answer) were measured using paper prototypes of both displays. STUDY DESIGN: Counter-balanced (on display order), repeated-measures design. MAIN RESULTS: Nurses had a higher situation awareness when using the integrated display, with an overall accuracy of 85.3% compared to 61.8% with the traditional displays (odds ratio 3.61, P<.001, 95% CI=2.34…5.57). Task completion times were nearly half with integrated displays compared to traditional displays (median 26.0 and 42.1s, hazard ratio 2.31, P<.001, CI=1.83…2.93). CONCLUSIONS: An integrated ICU information display increased nurses' situation awareness and decreased task completion time. Information integration has the potential to decrease errors, increase nurses' productivity and may allow nurses to react faster to a patient's clinical needs. Bidirectional device communication is needed for these displays to achieve full potential in improving patient safety.

Efficacy of a computerized simulation in promoting walking in individuals with diabetes.

BACKGROUND: Regular walking is a recommended but underused self-management strategy for individuals with type 2 diabetes mellitus (T2DM). OBJECTIVE: To test the impact of a simulation-based intervention on the beliefs, intentions, knowledge, and walking behavior of individuals with T2DM. We compared two versions of a brief narrated simulation. The experimental manipulation included two components: the presentation of the expected effect of walking on the glucose curve; and the completion of an action plan for walking over the next week. Primary hypotheses were (1) intervention participants' walking (minutes/week) would increase more than control participants' walking, and (2) change in outcome expectancies (beliefs) would be a function of the discrepancy between prior beliefs and those presented in the simulation. Secondary hypotheses were that, overall, behavioral intentions to walk in the coming week and diabetes-related knowledge would increase in both groups. METHODS: Individuals were randomly assigned to condition. Preintervention measures included self-reported physical activity (International Physical Activity Questionnaire [IPAQ] 7-day), theory of planned behavior-related beliefs, and knowledge (Diabetes Knowledge Test). During the narrated simulation we measured individuals' outcome expectancies regarding the effect of exercise on glucose with a novel drawing task. Postsimulation measures included theory of planned behavior beliefs, knowledge, and qualitative impressions of the narrated simulation. The IPAQ 7-day was readministered by phone 1 week later. We used a linear model that accounted for baseline walking to test the main hypothesis regarding walking. Discrepancy scores were calculated between the presented outcome and individuals' prior expectations (measured by the drawing task). A linear model with an interaction between intervention status and the discrepancy score was used to test the hypothesis regarding change in outcome expectancy. Pre-post changes in intention and knowledge were tested using paired t tests. RESULTS: Of 65 participants, 33 were in the intervention group and 32 in the control group. We excluded 2 participants from analysis due to being extreme outliers in baseline walking. After adjustment for baseline difference in age and intentions between groups, intervention participants increased walking by 61.0 minutes/week (SE 30.5, t(58 = 1.9, )P = .05) more than controls. The proposed interaction between the presented outcome and the individual's prior beliefs was supported: after adjustment for baseline differences in age and intentions between groups, the coefficient for the interaction was -.25, (SE 0.07, t(57 = -3.2, )P < .01). On average participants in both groups improved significantly from baseline in intentions (mean difference 0.66, t(62 = 4.5, )P < .001) and knowledge (mean difference 0.38, t(62 = 2.4, )P = .02). CONCLUSIONS: This study suggests that a brief, Internet-ready, simulation-based intervention can improve knowledge, beliefs, intentions, and short-term behavior in individuals with T2DM.

Nurse's role in tracking adverse drug events: the impact of provider order entry.

Adverse drug events (ADE), or injuries caused by drug therapy, are a frequent and serious problem in hospitalized patients. Monitoring, preventing, and treating ADEs is an important patient safety function. Nurses play a significant role in this function, because their data is a unique and important indicator of ADEs and because they are the final point of medication administration. New provider order entry systems with electronic medical records have been viewed as an effective innovation and solution to high rates of ADEs. These systems increase legibility of drug orders, provide decision support, and increase access to the medical record. However, they may not interface with nursing processes effectively. This study reports the experience of a team conducting an ADE surveillance study in a Veterans Health Administration setting where extensive computerized innovations are in place. Lessons learned regarding the integration of nursing work processes with the computerized setting are described. Three areas of concern are highlighted: decreased access to nursing narratives, lack of decision support for medication administration, and failure to code nursing data. Each of these is discussed in terms of relevance to patient safety and the design of information systems.

Critical gaps in the world's largest electronic medical record: Ad Hoc nursing narratives and invisible adverse drug events.

The Veterans Health Administration (VHA), of the U.S. Department of Veteran Affairs, operates one of the largest healthcare networks in the world. Its electronic medical record (EMR) is fully integrated into clinical practice, having evolved over several decades of design, testing, trial, and error. It is unarguably the world's largest EMR, and as such it makes an important case study for a host of timely informatics issues. The VHA consistently has been at the vanguard of patient safety, especially in its provider-oriented EMR. We describe here a study of a large set of adverse drug events (ADEs) that eluded a rigorous ADE survey based on prospective EMR chart review. These numerous ADEs were undetected (and hence invisible) in the EMR, missed by an otherwise sophisticated ADE detection scheme. We speculate how these invisible nursing ADE narratives persist and what they portend for safety re-engineering.