Repetita Iuvant: Exploring and Supporting Redundancy in Hospital Practices

Workarounds in the Shadow System: An Ethnographic Study of Requirements for Documentation and Cooperation in a Clinical Advisory Center

OBJECTIVE

Hospital information systems (HIS) are meant to manage complex work processes across healthcare organizations. We describe limitations of HIS to address local information requirements and how they are circumvented at different organizational levels. Results can be used to better support collaboration in socio-technical systems.

BACKGROUND

Workarounds describe a mismatch between a technology's purpose and its actual use, whereas shadow systems are unofficial IT systems circumventing limitations of official systems to support workflows. Boundary infrastructures are conceptualized as the entirety of all (in)formal digital and analog systems connecting different communities of practice in a socio-technical system.

METHODS

An ethnographic study with observations and semi-structured interviews was conducted and analyzed through categorization and iterative coding.

RESULTS

Several digital-analog workarounds are employed for documentation and a shared server functions as a shadow system to support workflows in ways the HIS cannot. For collaborative documentation, all (official and informal) information sources were used simultaneously as part of an interconnected boundary infrastructure.

CONCLUSION

Formal and informal IT systems are interconnected across different organizational levels and provide insights into unmet information requirements, effective and problematic work practices, and how to address them to improve system functioning. An integrated perspective on boundary infrastructures, workarounds, and shadow systems may advance system analysis, providing a more comprehensive picture of IT requirements than any concept alone.

APPLICATION

Workarounds and shadow systems highlight that HIS should support systemic and local needs. Customized interfaces in HIS to support search, access, and exchange of relevant data might help to mitigate current shortcomings.

Qualitative and quantitative approach to assess of the potential for automating administrative tasks in general practice

OBJECTIVE

To identify the extent to which administrative tasks carried out by primary care staff in general practice could be automated.

DESIGN

A mixed-method design including ethnographic case studies, focus groups, interviews and an online survey of automation experts.

SETTING

Three urban and three rural general practice health centres in England selected for differences in list size and organisational characteristics.

PARTICIPANTS

Observation and interviews with 65 primary care staff in the following job roles: administrator, manager, general practitioner, healthcare assistant, nurse practitioner, pharmacy technician, phlebotomist, practice nurse, pharmacist, prescription clerk, receptionist, scanning clerk, secretary and medical summariser; together with a survey of 156 experts in automation technologies.

METHODS

330 hours of ethnographic observation and documentation of administrative tasks carried out by staff in each of the above job roles, followed by coding and classification; semistructured interviews with 10 general practitioners and 6 staff focus groups. The online survey of machine learning, artificial intelligence and robotics experts was analysed using an ordinal Gaussian process prediction model to estimate the automatability of the observed tasks.

RESULTS

The model predicted that roughly 44% of administrative tasks carried out by staff in general practice are 'mostly' or 'completely' automatable using currently available technology. Discussions with practice staff underlined the need for a cautious approach to implementation.

CONCLUSIONS

There is considerable potential to extend the use of automation in primary care, but this will require careful implementation and ongoing evaluation.