Designing Colorectal Cancer Screening Decision Support: A Cognitive Engineering Enterprise

Decision-centered design of a clinical decision support system for acute management of pediatric congenital heart disease

Background and Objectives

Children with congenital heart disease (CHD), have fragile hemodynamics and can deteriorate due to common childhood illnesses and the natural progression of their disease. During these acute periods of deterioration, these children often present to their local emergency departments (ED) where expertise in CHD is limited, and appropriate intervention is crucial to their survival. Previous studies identified that determining the appropriate intervention for CHD patients can be difficult for ED physicians, particularly since key components of effective decision making are not being met. Although key components of effective decision making for ED physicians have been identified, they have yet to be transformed into actionable guidance. We used decision centered design (DCD) to translate key components of decision making into decision requirements and associated design concepts, that we subsequently incorporated into a prototype clinical decision support system (CDSS).

Methods

Using framework analysis, transcripts from Critical Decision Method interviews of CHD experts and ED physicians were inductively coded to identify key decision requirements for ED physicians that are currently not well supported, and their associated design concepts. A design workshop was held to refine the identified key decision requirements and design concepts as well as to sketch information that would satisfy the identified requirements. These were iteratively incorporated into a prototype CDSS.

Results

Three decision requirements: (1) distinguish the patient's unique physiology based on their unique cardiac anatomy, (2) explicitly consider CHD specific differential diagnoses to allow a more structured reflection of diagnosis, and (3) select CHD appropriate interventions for each patient, were identified. These requirements along with design concepts and information needs identified through the design workshop were incorporated into the CDSS prototype.

Conclusion

We identified key decision requirements and associated design concepts, that informed the design of a CDSS to provide actionable guidance for ED physicians when managing CHD patients. Meeting ED physicians' decision components with a CDSS requires the translation of their key decision requirements in its design. If not, we risk creating designs that interfere with clinician performance.

Human-centered design of team health IT for pediatric trauma care transitions

BACKGROUND

As problems of acceptance, usability and workflow integration continue to emerge with health information technologies (IT), it is critical to incorporate human factors and ergonomics (HFE) methods and design principles. Human-centered design (HCD) provides an approach to integrate HFE and produce usable technologies. However, HCD has been rarely used for designing team health IT, even though team-based care is expanding.

OBJECTIVE

To describe the HCD process used to develop a usable team health IT (T3 or Teamwork Transition Technology) that provides cognitive support to pediatric trauma care teams during transitions from the emergency department to the operating room and the pediatric intensive care unit.

METHODS

The HCD process included seven steps in three phases of analysis, design activities and feedback.

RESULTS

The HCD process involved multiple perspectives and clinical roles that were engaged in inter-related activities, leading to design requirements, i.e., goals for the technology, a set of 47 information elements, and a list of HFE design principles applied to T3. Results of the evaluation showed a high usability score for T3.

CONCLUSIONS

HFE can be integrated in the HCD process through a range of methods and design principles. That design process can produce a usable technology that provides cognitive support to a large diverse team involved in pediatric trauma care transitions. Future research should continue to focus on HFE-based design of team health IT.

Patient Adherence to Therapy After Myocardial Infarction: A Scoping Review

BACKGROUND

Patients with myocardial infarction have low adherence to secondary prevention. Patients with acute coronary syndromes usually decide not to take cardiac drugs for 7 days after discharge for various reasons and adherence rates are usually very low. The aim of this scoping review was to identify factors influencing treatment adherence after myocardial infarction and the role of interventions to improve treatment adherence.

METHODS

Two electronic databases (PubMed and Web of Science) were systematically searched for relevant published reviews of interventions for adherence after myocardial infarction. Inclusion criteria were study design: randomized control trial, systematic reviews; published in English; sample age ≥18 years. The methodological framework proposed by Arksey & O'Malley was used to guide the review process of the study.

RESULTS

Thirteen articles met the inclusion/exclusion criteria. Four of the thirteen studies assessed factors influencing patient adherence to therapy after myocardial infarction, the remaining studies examined various interventions increasing adherence to treatment after myocardial infarction.

CONCLUSION

There is a need to improve adherence of patients to treatment after myocardial infarction. Studies show that the use of modern technologies and communication with the patients by phone improve adherence to treatment.

Elderly Medication Adherence Intervention Using the My Interventional Drug-Eluting Stent Educational App: Multisite Randomized Feasibility Trial

BACKGROUND

A lifesaving treatment for myocardial infarction is the placement of a stent in a closed or obstructed coronary artery. The largest modifiable risk factor after receiving a stent is medication adherence to Dual AntiPlatelet Therapy, a combination of P2Y12 inhibitors and aspirin.

OBJECTIVE

This study aimed to determine the acceptability of a protocol and an intervention using the My Interventional Drug-Eluting Stent Educational App (MyIDEA) and to evaluate medication adherence using the proportion of days covered (PDC) and platelet activation tests in a multisite randomized controlled trial.

METHODS

Potential participants who received a post percutaneous coronary intervention (PCI) procedure with a drug-eluting stent were approached. All patients older than 50 years and who spoke English were recruited. Participants were recruited, baseline demographics were collected, and the Hospital Anxiety and Depression Scale (HADS), Rapid Estimate of Adult Literacy in Medicine-Short Form, Burden-Benefit questionnaire, 36-Item Short Form Health Survey, and PCI knowledge questionnaire were administered. Block randomization was used to randomize participants to either usual care or MyIDEA supplementation. MyIDEA is a personalized educational intervention based on the Kolb experiential learning theory using patient narratives for education. During the visits, participants' blood was collected to measure platelet suppression from medication. During the second and third encounters, the Morisky medication adherence score and cardiology outcomes were measured. The study was conducted at the University of Illinois Hospital and John H Stroger Jr Cook County Hospital with appropriate ethical approvals. Platelet suppression was measured through aspirin reactive units and P2Y12 reactive units. Medication adherence was measured using the PDC. The analysis team was blinded to the participants' group membership. The primary outcome was a feasibility analysis of recruitment and retention.

RESULTS

The mean age of participants was 60.4 years (SD 7.1); the majority of patients were black and non-Hispanic. The majority of patients' reading levels were seventh grade or above, and they were not very familiar with other electronic devices for information and communication. The number of control subjects was 21, and the number of participants in the interventional arm was 24. The interventional group was able to use MyIDEA in both the hospital and outpatient setting. However, there was no significant difference in platelet suppression or medication adherence between groups. There were also differences between the groups in terms of depression and anxiety, initially, as measured by HADS. No documented adverse event associated with the intervention was found.

CONCLUSIONS

Elderly patients are willing to use tablet devices to be educated about health conditions. Additional studies are required to measure the effectiveness and determine the most suitable timing and location for patient education.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04439864; https://clinicaltrials.gov/ct2/show/NCT04439864.

Development and evaluation of an electronic hospital referral system: a human factors approach

Coordinating care across hospitals has been identified as a patient safety risk as referrals are often paper-based and poorly documented. Electronic referral systems have the potential to improve the situation but can fail to gain uptake. We applied a human factors/ergonomics (HFE) approach to place analysis of local workflow and user engagement central to the development of a new regional electronic referral system. The intervention was evaluated with a before-and-after study. Referral quality improved, referrals containing sufficient clinical information for continuation of care increased from 36.9% to 83.5% and completeness of referral information significantly improved. There was a 35.7% reduction in the number of calls to the on-call specialist, and the mean period between admission and surgery for expedited transfers was reduced. Applying HFE informed design with use-based evidence; the system maintains sustained uptake three years after implementation. Reliable recording of information translates to better patient safety during inter-hospital transitions. Practitioners summary: This study developed, implemented and evaluated a clinical referral system using a human factors approach. Process analysis and usability studies were used to inform the application requirements and design. Region-wide implementation in hospitals resulted in the improved quality and completeness of clinical referral information and efficiencies in the referral process.

Mapping the territory of renal care: a formative analysis of the cognitive work involved in managing acute kidney injury

The design and evaluation of healthcare work systems requires an understanding of the cognitive work involved in healthcare tasks. Previous studies suggest that a formative approach would be particularly useful to examine healthcare activities for this purpose. In the present study, methods from cognitive work analysis and cognitive task analysis are combined in a formative examination of managing acute kidney injury, an activity that occurs across primary and secondary healthcare settings. The analyses are informed by interviews with healthcare practitioners and a review of practice guidelines. The findings highlight ways in which the task setting influenced practitioners' activity, and ways in which practitioners approached the activity (for example, how they used data to make decisions). The approach taken provided a rich understanding of the cognitive work involved, as well as generating suggestions for the design of work systems to support the clinical task. Practitioner summary: Healthcare tasks often require decision-making in complex and dynamic circumstances, potentially involving collaboration across different practitioner roles and locations. We demonstrate the use of a formative analysis to understand the cognitive work in managing a clinical syndrome across primary and secondary care settings, and consider the implications for work design.

Decision-centred design in healthcare: The process of identifying a decision support tool for airway management

Current decision support interventions for airway management in anaesthesia lack the application of Human Factors Engineering; leading to interventions that can be disruptive, inefficient and error-inducing. This study followed a decision-centred design process to identify decision support that can assist anaesthesia teams with challenging airway management situations. Field observations, Critical Decision Method interviews and focus groups were conducted to identify the most difficult decisions and their requirements. Data triangulation narrowed the focus to key decisions related to preparation and planning, and the transitioning between airway techniques during difficulties. Five decision-support interventions were identified and positively rated by anaesthesia team members in relation to their perceived effectiveness. An organized airway equipment trolley was chosen as the most beneficial decision support intervention. This study reiterated the key importance of both Human Factors Engineering and data triangulation when designing for healthcare.

Healthcare information systems: the cognitive challenge

BACKGROUND

Healthcare work is, to a considerable extent, cognitive. Subsequently, the analysis and the design of supporting technology must be sensitive to the cognitive and adaptive demands of the work and to the cognitive strategies employed by healthcare practitioners. Despite the vital role that cognition plays in healthcare work, current technocentric design approaches for healthcare technology do not account for it, failing to observe it during analysis and failing to develop support for it during design.

MAIN BODY

By review and analysis of case studies, we show that healthcare systems developed without input from cognitive analysis and cognitive design fail to take account of important healthcare work processes and workflows. In contrast, systems developed with a cognitively-focused design strategy demonstrate how it is possible to introduce technology that supports and enhances the work strategies of those engaged in patient care.

CONCLUSION

Significant problems emerge when technological support systems are developed without any serious and comprehensive attempt to understand the cognitive capabilities and skills deployed by those involved in patient care. In contrast, significant benefits accrue from taking full account of those cognitive capabilities and skills. Subsequently, the design and development of supporting technology must be sensitive to the cognitive demands of the work and the cognitive strategies employed by healthcare practitioners.

Evaluating a Modular Decision Support Application For Colorectal Cancer Screening

BACKGROUND

There is a need for health information technology evaluation that goes beyond randomized controlled trials to include consideration of usability, cognition, feedback from representative users, and impact on efficiency, data quality, and clinical workflow. This article presents an evaluation illustrating one approach to this need using the Decision-Centered Design framework.

OBJECTIVE

To evaluate, through a Decision-Centered Design framework, the ability of the Screening and Surveillance App to support primary care clinicians in tracking and managing colorectal cancer testing.

METHODS

We leveraged two evaluation formats, online and in-person, to obtain feedback from a range primary care clinicians and obtain comparative data. Both the online and in-person evaluations used mock patient data to simulate challenging patient scenarios. Primary care clinicians responded to a series of colorectal cancer-related questions about each patient and made recommendations for screening. We collected data on performance, perceived workload, and usability. Key elements of Decision-Centered Design include evaluation in the context of realistic, challenging scenarios and measures designed to explore impact on cognitive performance.

RESULTS

Comparison of means revealed increases in accuracy, efficiency, and usability and decreases in perceived mental effort and workload when using the Screening and Surveillance App.

CONCLUSION

The results speak to the benefits of using the Decision-Centered Design approach in the analysis, design, and evaluation of Health Information Technology. Furthermore, the Screening and Surveillance App shows promise for filling decision support gaps in current electronic health records.

Cognitive engineering and health informatics: Applications and intersections

Cognitive engineering is an applied field with roots in both cognitive science and engineering that has been used to support design of information displays, decision support, human-automation interaction, and training in numerous high risk domains ranging from nuclear power plant control to transportation and defense systems. Cognitive engineering provides a set of structured, analytic methods for data collection and analysis that intersect with and complement methods of Cognitive Informatics. These methods support discovery of aspects of the work that make performance challenging, as well as the knowledge, skills, and strategies that experts use to meet those challenges. Importantly, cognitive engineering methods provide novel representations that highlight the inherent complexities of the work domain and traceable links between the results of cognitive analyses and actionable design requirements. This article provides an overview of relevant cognitive engineering methods, and illustrates how they have been applied to the design of health information technology (HIT) systems. Additionally, although cognitive engineering methods have been applied in the design of user-centered informatics systems, methods drawn from informatics are not typically incorporated into a cognitive engineering analysis. This article presents a discussion regarding ways in which data-rich methods can inform cognitive engineering.