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

ABSTRACT:

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.

SUBMITTER: Willis M 

PROVIDER: S-EPMC7282326 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature