Ann Schoofs Hundt

SEIPS 2.0: A human factors framework for studying and improving the work of healthcare professionals and patients

Healthcare practitioners, patient safety leaders, educators and researchers increasingly recognise the value of human factors/ergonomics and make use of the disciplines person-centred models of sociotechnical systems. This paper first reviews one of the most widely used healthcare human factors systems models, the Systems Engineering Initiative for Patient Safety (SEIPS) model, and then introduces an extended model, ‘SEIPS 2.0’. SEIPS 2.0 incorporates three novel concepts into the original model: configuration, engagement and adaptation. The concept of configuration highlights the dynamic, hierarchical and interactive properties of sociotechnical systems, making it possible to depict how health-related performance is shaped at ‘a moment in time’. Engagement conveys that various individuals and teams can perform health-related activities separately and collaboratively. Engaged individuals often include patients, family caregivers and other non-professionals. Adaptation is introduced as a feedback mechanism that explains how dynamic systems evolve in planned and unplanned ways. Key implications and future directions for human factors research in healthcare are discussed. Practitioner Summary: SEIPS 2.0 is a new human factors/ergonomics framework for studying and improving health and healthcare. It describes how sociotechnical systems shape health-related work done by professionals and non-professionals, independently and collaboratively. Work processes, in turn, shape patient, professional and organisational outcomes. Work systems and processes undergo planned and unplanned adaptations.

Human factors systems approach to healthcare quality and patient safety

Human factors systems approaches are critical for improving healthcare quality and patient safety. The SEIPS (Systems Engineering Initiative for Patient Safety) model of work system and patient safety is a human factors systems approach that has been successfully applied in healthcare research and practice. Several research and practical applications of the SEIPS model are described. Important implications of the SEIPS model for healthcare system and process redesign are highlighted. Principles for redesigning healthcare systems using the SEIPS model are described. Balancing the work system and encouraging the active and adaptive role of workers are key principles for improving healthcare quality and patient safety.

Implementation of an electronic health records system in a small clinic: the viewpoint of clinic staff

In this study, we examined the implementation of an electronic health records (EHR) system in a small family practice clinic. We used three data collection instruments to evaluate user experience, work pattern changes, and organisational changes related to the implementation and use of the EHR system: (1) an EHR user survey, (2) interviews with key personnel involved in the EHR implementation project, and (3) a work analysis of clinic staff. A longitudinal design with two data-collection rounds was employed: data were collected prior to EHR implementation and after EHR implementation. Both quantitative and qualitative data were collected and analysed. Employees of the small clinic perceived few changes in their work after the implementation of the EHR system, except for increased dependency on computers and a small increase in perceived workload. The work analysis showed a dramatic increase in the amount of time spent on computers by the various job categories. The EHR implementation did not change the amount of time spent by physicians with patients. On the other hand, the work of clinical and office staff changed significantly, and included decreases in time spent distributing charts, transcription and other clerical tasks. The interviews provided important contextual information regarding EHR implementation, and showed some positive elements (e.g., planning of training), but also some negative elements (e.g., unclear structure of the project) that would have deserved additional attention.

Righting wrong site surgery.

BACKGROUND As defined by the Joint Commission on Accreditation of Healthcare Organizations (JCAHO), wrong site surgery includes wrong side or siteof the body, wrong procedure, and wrong-patient surgeries. Although many health care organizations are implementing guidelines and procedures to decrease the occurrence of wrong site surgery, numerous barriers to their effectiveness have been identified. HUMAN FACTORS ENGINEERING (HFE) ANALYSIS A human factors system analysis can be used to better understand how elements of a work system combine andinteract to contribute to breakdowns in the system. A case study of wrong site surgery in an outpatient setting illustrates how the different work systtem elements can contribute to the occurrence of a wrong site surgery. In analyzing the care process, it is particularly important to identify the transitions of care, which can be sources of patient safety problems when deficits in communication and information transfer occur (for example, miscommunication, information not transmitted on time, wrong information transmitted, misunderstanding of the information transmitted). RECOMMENDATIONS After a wrong site surgery, conduct a root cause analysis that uses the work system model and includes a surgery care process analysis similar to the one described in the case study; collaborate with human factors engineers to learn how to apply the work system model; apply the work system model to process analysis; and optimize work systems.

Macroergonomics in Health Care Quality and Patient Safety

The US Institute of Medicine and healthcare experts have called for new approaches to manage healthcare quality problems. In this chapter, we focus on macroergonomics, a branch of human factors and ergonomics that is based on the systems approach and considers the organizational and sociotechnical context of work activities and processes. Selected macroergonomic approaches to healthcare quality and patient safety are described such as the SEIPS model of work system and patient safety and the model of healthcare professional performance. Focused reviews on job stress and burnout, workload, interruptions, patient-centered care, health IT and medical devices, violations, and care coordination provide examples of macroergonomics contributions to healthcare quality and patient safety. Healthcare systems and processes clearly need to be systematically redesigned; examples of macroergonomic approaches, principles and methods for healthcare system redesign are described. Further research linking macroergonomics and care processes/patient outcomes is needed. Other needs for macroergonomics research are highlighted, including understanding the link between worker outcomes (e.g., safety and well-being) and patient outcomes (e.g., patient safety), and macroergonomics of patient-centered care and care coordination.

Care transitions in the outpatient surgery preoperative process: facilitators and obstacles to information flow and their consequences

Patient care transitions have been shown to be critical points at which failure as well as recovery from potential failure may occur. The purpose of this research was to identify transitions in patient care and the flow of associated information at different steps in the outpatient surgery preoperative care process and, in turn, attempt to identify breakdowns in the information flow process and their ramifications. A study of one organization’s preoperative process for outpatient surgery was conducted, employing four means of data collection to gather information on preoperative work processes: employee shadowing, patient shadowing, clinic observation, and dictated feedback. Various facilitators and obstacles in information flow were found to be present in the preoperative care process. Obstacles often resulted in negative consequences for healthcare providers and patients. Helping care providers understand how their actions affect the various elements of the preoperative process, through improved awareness, may be one way to improve information flow problems within the outpatient surgery process.

Macroergonomic factors in the patient work system: examining the context of patients with chronic illness

Abstract Human factors/ergonomics recognises work as embedded in and shaped by levels of social, physical and organisational context. This study investigates the contextual or macroergonomic factors present in the health-related work performed by patients. We performed a secondary content analysis of findings from three studies of the work of chronically ill patients and their informal caregivers. Our resulting consolidated macroergonomic patient work system model identified 17 factors across physical, social and organisational domains and household and community levels. These factors are illustrated with examples from the three studies and discussed as having positive, negative or varying effects on health and health behaviour. We present three brief case studies to illustrate how macroergonomic factors combine across domains and levels to shape performance in expected and unexpected ways. Findings demonstrate not only the importance of context for patients’ health-related activities but also specific factors to consider in future research, design and policy efforts. Practitioner Summary: Health-related activities of patients are embedded in and shaped by levels of social, physical and organisational context. This paper combined findings from three studies to specify 17 contextual or macroergonomic factors in home- and community-based work systems of chronically ill patients. These factors have research, design and policy implications.

Data collection challenges in community settings: insights from two field studies of patients with chronic disease

AbstractPurposeCollecting information about health and disease directly from patients can be fruitfully accomplished using contextual approaches, ones that combine more and less structured methods in home and community settings. This paper’s purpose was to describe and illustrate a framework of the challenges of contextual data collection. MethodsA framework is presented based on prior work in community-based participatory research and organizational science, comprised of ten types of challenges across four broader categories. Illustrations of challenges and suggestions for addressing them are drawn from two mixed method, contextual studies of patients with chronic disease in two regions of the USA.ResultsThe first major category of challenges was concerned with the researcher–participant partnership, for example, the initial lack of mutual trust and understanding between researchers, patients, and family members. The second category concerned patient characteristics such as cognitive limitations and a busy personal schedule that created barriers to successful data collection. The third concerned research logistics and procedures such as recruitment, travel distances, and compensation. The fourth concerned scientific quality and interpretation, including issues of validity, reliability, and combining data from multiple sources. The two illustrative studies faced both common and diverse research challenges and used many different strategies to address them.ConclusionCollecting less structured data from patients and others in the community is potentially very productive but requires the anticipation, avoidance, or negotiation of various challenges. Future work is necessary to better understand these challenges across different methods and settings, as well as to test and identify strategies to address them.

Challenges to care coordination posed by the use of multiple health IT applications

Coordinating care for hospitalized patients requires the use of multiple sources of information. Using a macroergonomic framework (i.e. the work system model), we conducted interviews and observations of care managers involved in care coordination across transitions of care. When information is distributed across multiple health IT applications, care managers experience a range of challenges, including organizational barriers, technology design problems, skills and knowledge issues, and task performance demands (i.e. issues related to individual information processing and management and sharing of information). These challenges can be used as a checklist to evaluate the proposed IT infrastructure that will allow the integration of multiple health IT applications and, therefore, support coordination across transitions of care.

Using Human Factors and Systems Engineering to Evaluate Readmission after Complex Surgery.

BACKGROUND Our objective was to use a human factors and systems engineering approach to understand contributors to surgical readmissions from a patient and provider perspective. Previous studies on readmission have neglected the patient perspective. To address this gap and to better inform intervention design, we evaluated how transitions of care relate to and influence readmission from the patient and clinician perspective using the Systems Engineering Initiative for Patient Safety (SEIPS) model. STUDY DESIGN Patients readmitted within 30 days of discharge after complex abdominal surgery were interviewed. A focus group of inpatient clinician providers was conducted. Questions were guided by the SEIPS framework and content was analyzed. Data were collected concurrently from the medical record for a mixed-methods approach. RESULTS Readmission occurred a median of 8 days (range 1 to 25 days) after discharge. All patients had follow-up scheduled with their surgeon, but readmission occurred before this in 72% of patients. Primary readmission diagnoses included infection, gastrointestinal complications, and dehydration. Patients (n = 18) and clinician providers (n = 6) identified a number of factors during the transition of care that may have contributed to readmission, including poor patient and caregiver understanding; inadequate discharge preparation for home care; insufficient educational process and materials, negatively affected by electronic health record design; and inadequate care team communication. CONCLUSIONS This is the first study to use a human factors and systems engineering approach to evaluate the impact of the quality of the transition of care and its influence on readmission from the patient and clinician perspective. Important targets for future interventions include enhancing the discharge process, improving education materials, and increasing care team coordination, with the overarching theme that improved patient and caregiver understanding and engagement are essential to decrease readmission and postdischarge health care use.