Hospital managers

A hospital is unique because the organisation consists of different types of professionals and technologies, dealing with both internal and external customers, and provides a wide range of services (clinical and non-clinical). Hospital employees (e.g., clinicians, administrators, managers) deal with different types of problems, which may increase the level of task complexity associated with their roles. Goodhue and Thompson (1995) propose that information systems have a positive impact on performance only when there is correspondence between their functionality and the task requirements of information system users.

Hospital managers need reliable information to solve problems within their organisation. As a result, their organisation provides information systems to help them collect, process, produce and deliver data needed. Hospital managers need to have a particular skill set to obtain information and use it to make informed decisions to deal with problems. However, not all managers have sufficient capability to retrieve data stored in information systems nor for extracting the information they need. Our literature study findings suggest that digital literacy (i.e., computer skills, informational skills, and media skills) is essential for a manager to help maximise organisational performance and attain an organisation’s goals.

Why do we need to do this study?

First, the number of digital literacy studies involving hospital managers as participants is limited. Kuek and Hakkennes (2020) highlight the need to conduct more digital literacy studies involving hospital leaders to learn how they use information systems and use the data retrieved to obtain information. Second, healthcare is becoming increasingly complex. Reese et al. (2018) recognise that modern health workforces need the ability to cope with complex work environments.

Research aim

This research aims to analyse the relationships between digital literacy level, task complexity level, and information system use. To achieve this aim, we will collect data from hospital staff in management roles via an online survey. We will employ a statistical modelling tool and procedures to analyse data collected.

Inclusion Criteria

People are invited to participate in our research if they are

  1. An active employee that works as a hospital staff in New Zealand
  2. Working in a managerial role and/or leadership role at any management level in a hospital in New Zealand, including but not limited to the following job title: hospital directors, hospital CEOs, operations managers, nurse leads, head of emergency department, and other similar roles.
  3. On leave, e.g., maternal leave, sabbatical, annual leave
  4. Able to understand the participant information given
  5. Willing and able to provide half an hour of their time to complete the survey
  6. Working in any hospital type (public or private, general, or specialised).

Data collection

This survey is done online, anonymously, and may take up to 30 minutes to complete. Participants can access the survey link using a preferred digital device (e.g. desktop PC, laptop, mobile phone), a good Internet connection, and a reliable web browser (e.g., Google Chrome, Mozilla Firefox, or Safari).

We will do the following approaches in recruiting the participants:

  1. We have contacted hospital research offices to introduce the research project and have completed the forms for locality approval.
  2. Once a hospital has approved our application, a contact person in the hospital will help us distribute the invitation to those in management roles to participate in our research.

Participants’ rights

This survey is voluntary. If a person starts the survey and wants to withdraw, they can do so without saying why. However, if a person has already submitted their survey responses, they cannot withdraw their data because we won’t be able to find it (their responses were anonymous).

We do not ask for identifiable information such as names, addresses, email addresses, phone numbers, NHI number, photos, hospital name or other information that can be used to compile an identity. We do ask for participants’ role title and job description, which could allow us to identify individuals – we will mask identities in how we report on the data, e.g., by clustering roles.

The aggregated datasets will be stored electronically in a password-protected encrypted database in a University of Auckland computer system backed up by a server for six years and then deleted.

Survey data analysis 

We will employ structural equational modelling tools and procedures to analyse the survey data (Beran and Violato, 2010; Westland, 2015). A descriptive-analytical procedure will be employed to analyse respondents’ demographic profiles (e.g. gender, age, educational level, and ethnicity), organisation profiles (e.g. hospital region, type, and bed size), role characteristics (e.g. job title, years of experience, key duties/responsibilities, and span of control) and hospital information systems software use. A regression analytical procedure will be employed to analyse the composite scores of digital literacy (i.e. computer skills, online information search, information content evaluation, information processing, information compilation and application) levels, task complexity levels (i.e. to perform hospital manager role and to perform informational role), information quality levels and perceived hospital information systems quality and use.

Results dissemination

The student researcher will use the study results to write a PhD thesis and scientific publications (e.g. journals, posters, presentations). A summary report of the research results will be sent to each hospital research centre that has approved our research ethics application, and participants can request the report at the end of the survey.   

Links to the survey and more information

Click here to read the Information Sheet

Click here to go to the survey or use this QR code

The research team

Principal Investigator/Main Supervisor (PI): Dr Karen Day

Co-supervisor: Prof David Sundaram

Advisors: Dr Peter Carswell, Dr Linda Haultain

Student Researcher: Tito Yustiawan (PhD Student)

References

Beran, T.N. and Violato, C. (2010). ‘Structural equation modelling in medical research: a primer’, BMC Res Notes, 3 (267), pp:-, DOI: https://doi.org/10.1186/1756-0500-3-267.

Goodhue, D. L. and Thompson, R. L. (1995). ‘Task-technology fit and individual performance’. MIS Quarterly, 19(2), pp. 213–236. DOI: https://doi.org/10.2307/249689.

Kuek, A. and Hakkennes, S. (2020) ‘Healthcare staff digital literacy levels and their attitudes towards information systems’, Health Informatics Journal, 26 (1), pp. 592–612. DOI: https://doi.org./10.1177/1460458219839613. 

Rees, GH., Crampton, P., Gauld, R., MacDonell, S. (2018). ‘New Zealand s health workforce planning should embrace complexity and uncertainty’. New Zealand Medical Journal. 131(1477), pp. 109-115.

Westland, J.C. (2015). Structural Equation Models: From Paths to Networks, 1st Ed. Springer Cham, DOI: https://doi.org/10.1007/978-3-319-16507-3.

Approved by the University of Auckland Human Participants Ethics Committee on 02/12/2022 for three years. Reference Number UAHPEC25154

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