Workforce survey of Australian graduate health information managers: Employability,employment,and knowledge and skills used in the workplace

Abstract

Background:

Employability, employment destinations and utilisation of knowledge–skill domains of new graduate health information managers (HIMs) have not been explored.

Objectives:

To capture the timing from course completion to employment and employment locations of a 5-year cohort of health information management graduates of La Trobe University, Australia, in 2017–2018; identify professional knowledge and skills used by the graduates in executing their roles; and map these to four domains of the health information management curriculum.

Method:

A mixed-methods descriptive study utilising a survey investigated early career pathways of new graduates of health information management courses from 2012 to 2016. Demographic data included age, year of graduation, lead time from course completion to employment, position title, number of positions held post-graduation and knowledge–skills used in the workplace.

Results:

Eighty percent (n = 167) of graduates working in Australia with known contact details responded to the survey. Of these, 96.4% (n = 161) worked in at least one “health information management-related” position since graduation. Forty-five percent (n = 72) of graduates obtained a position before course completion, and over 94% (n = 150) were employed in the profession within 6 months of completion. Sixty percent (n = 97) of graduates had worked in two or more positions from 2012 to 2016. The large majority of new graduate HIMs (82.4%) were employed in the public healthcare sector in “health information management” (44%), or “health classification” (28.1%) roles. Most graduates (61%) had utilised at least three or four domains of professional knowledge–skills in the workplace. Whereas 16% (n = 26) of graduates used, solely, their health classification knowledge–skill set, almost 74% (n = 117) undertook some health classification-related activities. Only 16% (n = 26) of graduates were over 40 years of age, and there were no statistically significant differences between Bachelor and Master (Combined Degree Programs) graduates and Graduate-entry Master degree graduates in terms of lead time to employment, number of positions held, type of employing agency and professional knowledge–skills utilised in the workplace.

Conclusion:

Graduate HIMs have very high employability, demonstrate job mobility consistent with the national trends, are largely represented in the public sector but have presence throughout the healthcare system and utilise most or all of the specialised domains of professional knowledge and skills studied at university.

Keywords

health information manager health information management health workforce health information management workforce health information management profession health informatics education professional health education professional competence workplace health manpower

Introduction

The Health Information Management Association of Australia (HIMAA) (2015) defined a health information manager (HIM) as a university-trained health professional who “plans, develops, implements and manages health information services, such as patient information systems, and clinical and administrative data, to meet the medical, legal, ethical and administrative requirements of health care delivery, or who teaches or does research in these areas.” The professional knowledge and skills of qualified HIMs are critical to the delivery of high-quality healthcare, particularly in relation to the advancement of digital health initiatives, including electronic health records, health funding, patient safety and quality of care, classification and analytics that underpin state and national epidemiological and population health data, and the enabling and governance of the health information landscape within the Australian healthcare system.

There are long-standing and very significant workforce shortages of HIMs (Australian Institute of Health and Welfare [AIHW], 2010; Health Workforce Australia [HWA], 2013). Therefore, it is important to identify the extent of this health information management workforce supply problem and to establish what knowledge and skills these professionals require in their work. In its investigation into Australia’s health information workforce, HWA (2013: 5) determined that HIMs constituted the first of five key professions that form the level 1 “Specialist health information workforce.” Other Australian studies have explored the characteristics and supply issues associated with the health information management and/or clinical coding workforce, the “clinical coding” component being partly comprised of HIMs (AIHW, 2010; Victorian Government, Department of Health, 2008). HWA advocated for improved data to enable workforce delineation and planning. In the spirit of addressing this need, academics from La Trobe University (LTU) undertook a study in 2017–2018 of the early employment profiles of a segment of the health information workforce, specifically a 5-year cohort of new graduate HIMs.

Data from the HIMAA’s (2017a) triennial surveys of its members’ industry positions were limited to the proportion of the HIM population who held membership. Therefore, informed in part by HIMAA’s definition, our research drew upon other authorities including Hersh’s (2006) recognition of HIMs internationally as a core component of the health information technology workforce, Cooper’s (2009: 39) description of the expanding “breadth, depth and scope” of Australian HIMs, Robinson’s (2017) study of Australian HIMs’ work, and Danish studies of the work of medical secretaries (similar in some respects to the work of HIMs) (Bertelsen and Nøhr, 2005; Bossen et al., 2014). Our study also acknowledged Dimick’s (2012) and the American Health Information Management Association’s (2017) projections of HIM role changes in the United States, and the Canadian Health Information Management Association’s reporting of past and predicted workforce shortages in Canada, and its identification of the need for a refocusing of the Canadian HIMs’ professional knowledge and skills (Gibson et al., 2015). The international literature on graduates’ roles in the broader field has tended to focus on medical and health informaticians, for instance in Germany (Knaup et al., 2003; Leven et al., 2004), Austria (Ammenwerth and Hackl, 2015), Brazil (Macedo et al., 2016) and the United States (AMIA, 2017).

Aims and objectives

This research is part of a larger study exploring employment and mobility of health information management graduates and the applicability of their university education to their work, which aims to fill a gap in existing health information management workforce research. The current study focused specifically on the employability of new graduate HIMs, their early workforce mobility and workplace utilisation of professional knowledge and skills learned at university. The objectives of the component reported in this article were:

To identify industry roles in which the 2012–2016 cohort of LTU’s health information management graduates have successfully gained employment in Australia, and

To identify the primary knowledge and skill sets utilised by new graduate HIMs in the performance of their professional roles.

Method

Sample

Australia’s LTU and, previously, Lincoln Institute of Health Sciences have produced health information management graduates continuously for four and a half decades (Watson, 2013). The LTU curriculum comprises four domains of specialist professional knowledge and skills within digital health: health information science and management (including professional practice), health information and communication technologies (health ICT) and informatics, clinical knowledge and health classification, and health data analytics. These domains have been identified elsewhere (Robinson, 2017) as constituting and representing, in practice, the HIMs’ specialist professional work throughout the healthcare system. The LTU courses hold current accreditation from HIMAA, for which purpose relevant components of the curriculum are mapped to the Association’s health information management graduate-entry competency standards (HIMAA, 2017b).

The study’s purposive sample comprised LTU graduates of the Bachelor–Master Combined Degree Programs (CDP)¹ and the Graduate-entry² Master (GEM) degree in health information management, who graduated within the 5-year period, 2012–2016. Graduates who could not be located or who did not respond to the researchers’ communication, and those employed offshore, were excluded from the sample as the focus of the research was career outcomes in Australia.

Data collection

Lists of all graduates who qualified within the study time frame were obtained from the University’s Alumni Association Office and University Client Services. The process for contacting graduates involved the following steps:

First contact was attempted through email maintained by the Alumni Association: to the graduate’s email address where available or, failing this, via email obtained through the research team’s personal sources and informal networks.

Two follow-up emails were attempted if the graduate did not respond within a 2-week time frame.

Where there was no response after three email attempts, the graduate was excluded from the study.

Eligible graduates were given a link to an electronic survey instrument created and distributed via SurveyMonkey.

Survey instrument

The draft survey instrument drew upon broad question categories contained in Ammenwerth and Hackl’s (2015) survey of biomedical informatics graduates but was otherwise purposely designed. The survey instrument was piloted on 15 earlier graduates and amended, based on the feedback. A mixed-methods approach was used to obtain information on graduate outcomes and knowledge and skills utilised in the workplace. The survey instrument incorporated a forced response format to obtain the following items: current age; qualification(s) awarded and the year; previous qualification(s); additional postgraduate education; time elapsed between completion of the course (i.e. final examinations) and employment in the graduate’s first HIM position; titles of up to three HIM positions held post-graduation; major duties performed in each role categorised under the four streams in the curriculum and details of non-HIM-related employment, post-graduation. Information was also collected in open-ended format, specifically the respondents’ comments on their career pathways and use of the knowledge–skills learned on the job or at university. Full details of the study were given in the approach email, and consent was obtained from participants through their agreement to access and complete the online survey. Feedback from this question will inform future discussions around curriculum design and is outside the scope of this article.

Categorisation of position titles

The position titles identified by the respondents were categorised (and validated by agreement between the researchers) into five broad areas, shown in Box 1. These categories are not independent and some positions may fit equally well into two or more categories (e.g. the financial analyses relate partly to health classification and partly to health data analytics). In such cases, a hierarchy was used and the position was categorised into the most common group. Inclusion of the “Other” category was necessary because of a paucity of information provided by respondents in some roles.

Box 1

Foci and broad categories of position titles of health information managers

Health information management focus (HIM): This category groups positions that have health information management as the role descriptor. It includes responsibilities such as the management of staff, records and forms, Freedom of Information and patient/client access to information, patient admissions, and other administrative components of patient flow.

Health classification, including financial focus (HC): In this category of HIM work, the positions identify health classification, colloquially termed “clinical coding,” as the major role. This also includes health insurance industry–based work involving health classification.

Data management and analytics focus: This is a category whose major activities are related to the management, interpretation, analysis and reporting of health data.

Health information systems focus (health ICT): This category groups those positions where the role’s primary focus is the information systems that manage the health information, for example, systems administrator, implementation manager.

Other foci: This category represents roles that do not fit into the above categories or incorporate several categories equally, for example, academic, project officer (non-ICT), policy officer.

Data analysis

Responses to the closed questions were analysed using SPSS version 24. Descriptive statistics were utilised to analyse and present the quantitative data. When respondents reported having had more than one position, these data were analysed by position rather than by respondent; therefore, the number of positions exceeds the number of graduate-respondents. Items with missing responses were excluded from the current analysis. The qualitative data will be reported in a separate paper.

The χ ² and p values (α = 0.05) were used to determine if there were any statistically significant differences between graduates of the CDP and GEM programs in selected areas. All data were de-identified to ensure that no individual respondent could be identified.

Ethics approval

Approval to undertake the study was obtained from the LTU Human Research Ethics Committee.

Results

Demographics

From 2012 to 2016, inclusive, there were 230 graduates from the three health information management courses offered by LTU (see Table 1). This cohort comprised 121 (52.6%) qualified CDP graduates and 109 (47.4%) qualified GEM graduates.

Table 1.

Health information manager qualifications awarded to graduates, 2012–2016.

	Year completed
	2012		2013		2014		2015		2016
Qualification	No.	%	No.	%	No.	%	No.	%	No.	%	Total
Combined Degree Program (CDP) graduates^a	22	57.9	16	50.0	32	54.2	31	54.4	20	45.5	121
Graduate-entry Master (GEM) graduates^b	16	42.1	16	50.0	27	45.8	26	45.6	24	54.5	109
Total	38	100.0	32	100.0	59	100.0	57	100.0	44	100.0	230

^aBachelor of Health Sciences and Master of Health Information Management, and Bachelor of Information Systems and Master of Health Information Management.

^bMaster of Health Information Management.

Of the 230 graduates, 22 (9.6%) were confirmed to be working offshore and were excluded from the study as the primary focus of the research was career pathways in Australia. This left a target population of 208 graduates. Figure 1 outlines the survey response pathway.

Figure 1.

Response pathway to the La Trobe University Health Information Management Graduate Careers Survey, 2012–2016.

Detailed information on graduate careers and position-based knowledge–skills was available for 167/190 (87.9%) graduates for whom a contact address was available and who completed the survey. Three graduates declined to participate and 20 graduates did not respond to the survey; of these 23 non-respondents, 19 were in the CDP program category and 4 were GEM graduates.³ The reasons for non-response were unknown.

The following results are based upon the answers of the 167 respondents, which represents a response rate of 80%. Denominators between figures and tables vary because items with missing responses were excluded from the analysis. Eighty-nine (53.3%) of the survey respondents (n = 167) completed the CDP and 78 (46.7%) respondents completed the GEM program. Over 80% of CDP graduates were aged between 20 and 29 years when they completed the survey, whereas just under 70% of GEM graduates were over 30 years of age. Only 7% (n = 6) of the CDP graduates were over the age of 40 years, compared to 28% (n = 22) of the GEM graduates (results not tabulated).

Employment

Of the 167 respondents, 161 (96.4%) had worked in at least one “health information management-related” position (typically considered to be a hospital health information service position) since graduation. Two of the six respondents who had not worked in a health information management-related position had proceeded directly to further study. One hundred sixty respondents provided information on when they obtained their first health information management-related position. Forty-five percent of these had secured a position before completing the course and almost 94% (n = 150/160) had done so within 6 months of the final examinations (see Table 2). There was no significant difference between the proportions of CDP graduates and GEM graduates who obtained a position before course completion (χ ² = 1.02, p = 0.31).

Table 2.

Time from course completion to securing employment, by qualification, 2012–2016.^a

	CDP^a		GEM^b		Total
Time of employment	No.	%	No.	%	No.	%
Prior to completion of the course	37	44.0	35	46.1	72	45.0
Within 2 months of course completion	26	31.0	21	27.6	47	29.4
Within 4 months of course completion	8	9.5	10	13.2	18	11.3
Within 6 months of course completion	8	9.5	5	6.6	13	8.1
More than 6 months after course completion	5	5.6	5	6.6	10	6.3
Total^c	84	100	76	100	160	100

CDP: Combined Degree Programs; GEM: Graduate-entry Master.

^aBachelor of Health Sciences and Master of Health Information Management, and Bachelor of Information Systems and Master of Health Information Management.

^bMaster of Health Information Management.

^cExcludes six graduates who had not worked in a health information management-related position, and one with a missing response.

There was no difference in the relative proportion of graduates in each age group who obtained a position prior to completing the course. While the number of graduates in each age group significantly decreased from the highest number in the 20–29 years age group (n = 94/160) to the lowest number in the 40+ years age group (n = 28/160), approximately 42–47% in each age group obtained a position before graduating.

The only item in the survey that related to the employing agency concerned its public or private status. More graduates were employed in their first position in a public sector agency (82.4%) than in the private sector (17.6%). There was no significant difference between CDP and GEM graduates in the type of agency of employment for a first position (χ ² = 2.27, p = 0.13).

Approximately 55% (n = 88/161) of the graduates who had worked in health information management-related positions between 2012 and 2016 held one position only, 29.4% (n = 47) had worked in two positions and 15.6% (n = 25) had worked in three or more positions. One graduate did not indicate how many positions she/he had held. Those who had held three or more positions were more likely to have graduated earlier than those who had held only one position as a HIM. Of the 25 respondents who had held three or more positions, 44% (n = 11) graduated in 2012, 12% (n = 3) in 2013, 28% (n = 7) in 2014 and 16% (n = 4) in 2015–2016, combined. Overall, 20.5% (n = 17) of CDP graduates held three or more positions between the years 2012 and 2016 compared to 10.5% (n = 8) of the GEM graduates (Figure 2). There was no statistically significant difference between CDP graduates or GEM graduates in holding three or more positions post-graduation (χ ² = 2.9, p = 0.09).

Figure 2.

Number of health information management-related positions held since graduation, by qualification and year of graduation.

Respondents identified the position titles for up to three HIM positions held since graduation. From 2012 to 2016, 256 position titles were identified by the respondents who had worked in at least one health information management-related position. All position titles were assigned to one of five categories (see Table 3), the most prevalent being health information management (44%) followed by health classification (28.1%), data management and analytics (10.2%), health ICT (6.3%) and, finally, “other” (11.7%). Appendix A shows the detailed list of position titles by category.

Table 3.

Categorisation of position titles for graduate health information managers.

	First position		Second position		Third position
	No.	%	No.	%	No.	%
Health information management	71	44.7	32	44.4	10	40.0
Health classification	49	30.8	17	23.6	6	24.0
Data management and analysis	16	10.1	8	11.1	2	8.0
Health information systems focus	10	6.3	2	2.8	4	16.0
Other	13	8.2	13	18.1	3	12.0
Total^a	159	100.0^b	72	100.0	25	100.0

^aExcludes graduates whose response was missing for position title.

^bVariation due to rounding.

Knowledge and skills used by health information management graduates in their work

An analysis of the major categories of duties undertaken in each position, and mapped against the four knowledge–skills domains taught in our courses, demonstrated that most graduates were undertaking roles that required them to utilise three (35.2%) or four (26.4%) of the knowledge–skills domains taught at university. Twenty-two percent of respondents (n = 35) reported that they focused on only one domain of knowledge–skills in their position(s) (see Figure 3), leaving the remaining 78% of graduates who reported using between two and four domains of knowledge–skills in their workplace.

Figure 3.

Breadth of knowledge and skills applied in the health information workplace.

Table 4 outlines the number of graduates who utilised each specific knowledge–skills domain in their position, stratified by qualification. The most common domain for graduates who used only one domain of knowledge–skills in their position was health classification (all graduates combined, 16.4%). There were significantly more GEM graduates who used only their health classification skills in their employment compared to CDP graduates (χ ² = 3.85, p < 0.05). Twenty-six percent of graduates utilised all four domains of knowledge–skills in their work, with equal distribution between CDP graduates and GEM graduates. Thirty-five percent of graduates utilised three domains of knowledge–skills in their work, the most common combination being “health classification, analytics and health information management” (18.2%) followed closely by “health ICT, analytics and health information management” (14.5%). There was no statistically significant difference between the number of CDP graduates and GEM graduates who used only one domain of knowledge–skills in their positions (χ ² = 1.17, p = 0.28), or who used four domains of knowledge–skills (χ ² = 0.11, p = 0.74).

Table 4.

Number and type of knowledge–skills competency domains utilised in graduates’ position(s), stratified by qualification.

No. of domains	Domain combinations	CDP (n = 83)^a	GEM (n = 76)
1	Health Classification	9	17
	Health ICT	1	2
	Analytics	0	2
	Health Information Management	3	1
	Total	13	22
2	Health Classification, Health ICT	0	1
	Health ICT, Analytics	0	3
	Health Classification, Analytics	6	3
	Analytics, Health Information Management	2	1
	Health ICT, Health Information Management	2	2
	Health Classification, Health Information Management	4	2
	Total	14	12
3	Health Classification, Health ICT, Analytics	1	0
	Health ICT, Analytics, Health Information Management	13	10
	Health Classification, Analytics, Health Information Management	19	10
	Health Classification, Health ICT, Health Information Management	2	1
	Total	35	21
4	Health Classification, Health ICT, Analytics, Health Information Management	21	21

CDP: Combined Degree Programs; GEM: Graduate-entry Master; Health ICT: health information and communication technologies.

^aExcludes one response which did not identify the tasks used in the position.

Discussion

New graduate HIMs’ employability, employment destinations and utilisation of knowledge–skill domains have not previously been explored. By surveying an entire 5-year graduate cohort, our research has provided a comprehensive picture of the career destinations of LTU’s health information management graduates. The high response rate has led us to conclude that the responses received were representative of the cohort. Our finding that new graduates were employed very quickly post graduation – and some even pre-graduation – supports the findings of other studies, that there is a severe shortage of HIMs across Australia (AIHW, 2010; HWA, 2013). Our findings have also indicated that graduate HIMs have very high employability, demonstrate job mobility consistent with the national trends, are largely represented in the public sector but have presence throughout the healthcare system and utilise most or all of the specialised domains of professional knowledge and skills studied at university. HWA reported on “workers who self-identify with the health information workforce and who work full-time with health information systems” (2013: 14). This broad categorisation has made the HWA’s findings difficult to compare to those of our research, owing to differences in focus and scope between the two studies.

Health information management workforce

Lead time from course completion to employment

Over the 5-year period captured by this study, the cohort of 230 health information management graduates from LTU approximates to 45 graduates per annum; this supports previous reports of a workforce shortage of HIMs (and clinical coders) (AIHW, 2010; HWA, 2013; Shepheard, 2010; Victorian Government, Department of Health, 2008). Arguably, this shortage has continued to contribute to the very favourable employment statistics for the graduates from our study, 45% of whom had secured a health information management-related position before completing their course, and 94% of whom had obtained a professional position within 6 months of completion. Our results show that in relation to the time taken to secure a job, there is little difference between graduates who complete a CDP and those who complete a GEM course to qualify as a professional HIM.

Age

The AIHW (2010: 38) highlighted the age of the estimated national health information management and clinical coding workforce: 51.8% of that survey’s self-selected respondents were aged 45 years or older, whereas only 35.7% in Victoria were in that age group. This is consistent with the Victorian Department of Health’s (2008) earlier statistic (i.e. only 36.6% of that state’s health information management and clinical coding workforce was aged 45 years or over). These data present a partial picture as both the AIHW and Victorian Department of Health studies focused on the clinical coding component of the health information workforce and included non-HIM clinical coders, and the AIHW study excluded the presumably large number of HIMs engaged in non-clinical coding roles. This may have artificially inflated the overall age of the workforce reported in that study because younger graduates may gravitate towards the non-traditional (non-clinical coding) health information management roles. The trend of younger graduates in Victoria is seen in our 2012–2016 cohort, with only 16.8% of graduates being over 40 years of age.

Number of positions

Sixty percent of our health information management graduate cohort had worked in two or more positions since graduating. Statistics from the Melbourne Institute and Department of Social Services’ longitudinal survey (2017) showed the average length of time spent in any one job in Australia as 3 years and 4 months, across all age groups. Among workers aged under 25 years, the national average job tenure is 1 year and 8 months, a statistic that has not changed significantly since 1975. The health information management graduates reflected this pattern, with a higher proportion of CDP graduates than GEM graduates having occupied two or more positions. This also reflects the national figures on average job tenure, by age. Therefore, recent health information management graduates moved positions, but not more frequently than did other Australian workers.

Position titles, duties and domains

Almost three-quarters (72.1%) of the position titles held by the graduates related to the more traditional roles of “health information management” and “health classification” or a combination of both. This statistic is arguably reflective of the durability of the health information management qualification, the embeddedness of the profession within the wider health workforce and employers’ continuing need for qualified HIMs’ specialised knowledge and skills.

Skills and knowledge taught in health information management programs and applied to work

In its 2008 survey of the health information management and clinical coding workforce in the state of Victoria, that state’s Department of Health identified that 61% of this workforce spent some time in clinical coding (Victorian Government, Department of Health, 2008: 38). Our research has found that 73.6% of recent graduates reported their role as including some aspect of health classification. This included clinical coding for activity-based/casemix funding, coding for non-casemix purposes (e.g. research, or disease registry), coding auditing, coder education, development or revision of the classification or clinical terminologies, or other classification-related activities. Interestingly, this emphasis differs from predictions of American HIMs’ reduced “coding” (classification) in an increasingly technological environment, reported in the literature from that country (AHIMA, 2017; Sandefer et al., 2015). We note that, in contrast, our study examined the status quo and was not predictive. Our survey responses demonstrated that three-quarters of recent health information management graduates were involved in health classification–based activity of some type and that knowledge of and practice skills in the International Classification of Diseases constituted a critical area of professional preparedness for the health information management graduate. However, our results also demonstrated that 16.4% of recent graduates were using only this domain in their work, thus highlighting the necessity for HIMs to have a broad base of knowledge and skills across the other domains.

The number of GEM graduates who identified as using only health classification knowledge–skills in their roles was almost double that of CDP graduates (17 and 9, respectively). While these numbers are small, the data show that GEM graduates were more likely than CDP graduates to begin with a health classification-only (clinical coding) role. This is perhaps unsurprising as many GEMs come to the health information management profession from clinical backgrounds to pursue a career change to specialist health classification.

Limitations

While we are confident, with our high (80%) response rate, that our sample is representative of new graduate HIMs, our results must be considered in light of some limitations. For instance, the healthcare orientation of each graduate’s employing agency was collected but further details of the organisation were omitted, and no definition of each knowledge and skill-based activity was provided for participants (their descriptions of their work were coded by the researchers). The statistics related to graduates who identified their employment as “health information management-related”; no definition was provided to participants of what constituted a “health information management-related” position other than some examples (e.g. research, registry, database manager, health insurance, classification development, ICT development or implementation). As with the HWA (2013) report, in the absence of an agreed definition of the health information workforce, the participants self-identified.

Conclusions

These findings inform our understandings of new graduate HIMs’ early career profiles including their employability, mobility and workplace applications of professional knowledge and skills learnt at university. Significantly, the majority of the graduates utilised all or three-quarters of the knowledge and skills domains taught in the courses, indicating relevance of their content and foci. Furthermore, the domain of health classification remains very important, as evidenced by almost 74% of the graduates having drawn upon this in their first 5 years of professional employment. Our finding that the majority of the graduates were initially employed in the public sector is perhaps reflective of both the size of that sector and the long-standing importance of HIMs’ presence and work in it.

Finally, and importantly, Australia’s graduate HIMs are very highly employable with almost half securing a professional HIM position prior to completing the course. Their employability is affected neither by age nor course level (CDP or GEM), and their mobility within 5 years of graduation is consistent with the national job retention statistics. This key finding of high employability reflects the dire shortage of qualified HIMs in the Australian health workforce. It has particular significance in the context of Australia’s progression to electronic health records and, especially, the Australian Government’s digital health agenda (ADHA, 2018) and points to the need for increased support for university HIM programs and, especially, for increased incentives (such as advocacy for the profession and its opportunities, and scholarships) for students to enrol in these programs in order to meet the demonstrated workplace demand for these critically important health professionals.

Footnotes

Authors’ note

All authors had full access to the data in the study.

Author contributions

MR and NP designed the study; KR revised the study; MR, NP and BG prepared the survey; DW set up the survey and helped with survey workflow; MR provided statistical advice; NP and EB piloted the survey; MR, NP and EB contacted participants; MR, KR, NP, BG, EB and JP analysed and interpreted data; MR, KR and BG prepared the manuscript.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Notes

Appendix A. Position title for first,second and third positions,as described by graduates.

Health Information Managers

Area Health Information Manager – Mental Health and Community

Deputy Chief Health Information Manager

E-forms Manager and VEMD Data Manager

Freedom of Information Officer

Health Information Manager/Manager of Typing Service

Health Information Management Advisor

Health Information Management Tutor

Health Information Manager

Health Information Manager – FOI Manager/Clinical Coder

Health Information Manager – Statutory Reporting

Health Information Manager (Forms Management and EMR Implementation)

Health Information Manager (Paper Forms and Data Management)

Health Information Manager (VINAH Data Manager)

Health Information Manager/FOI Officer/Data Manager

Health Information Manager/Operations and Clerical Team Manager

Health Information Service Officer

Health Information Service Team Leader

Health Records Clerk

HIM – Forms Coordinator/E-forms

HIM Lead EMR

Manager, Health Information Services

Manager of Admissions, Registrations, Switchboard and Transport

Operations Manager, HIS

Senior Health Information Manager

Site Manager – Health Information Services

Health Classification and/or Financial Focus

Clinical Coder

Coding and Casemix Manager

Coding Auditor

Health Fund Contract Manager

Hospital and Medical Claims Auditor

Medical Coder

Clinical Documentation Consultant

Clinical Coder/Administration Supervisor

Health Information Manager/Clinical Coder

Health Information Manager – Coding Auditor and Educator

Data Management and Analysis Focus

Business Analyst, Clinical Applications

Clinical Analyst

Clinical Costing Officer

Data Analyst or Assistant Data Analyst

Data and Administration Officer

Data and Quality Manager/Assistant

Data Manager

Data Processing Officer

Follow-up Manager for VCCR and SACSR (Cervical Cancer Registries)

Health Data Reports Officer/Dataset Officer

HIM Data Integrity, Analysis and Reporting

Team Lead, Quality and Audit, Clinical Records

VAED Data Manager, PROV Record Keeping Standards Project Manager

VAED Officer

Health Information Systems Focus (Health ICT)

Application Support – Clinical Applications

Delivery Consultant/Manager

DHR/Scanning Operations Manager

Digital Health Officer

EMR Analyst

EMR Project Officer

Implementation and Training Assistant

Implementation Manager – Enhancements

Informatics Project Officer

Scanning Operations Manager

Systems Administrator and Quality Assistant

Other

Associate Lecturer

Information Advisor

Information Management Consultant

Operational Coordinator Referral Management

Policy Officer

Programs and Services Advisor

Project Co-ordinator/Manager

Project HIM Resource

Project Officer – Multi-site Ethics

Project Officer/Resolutions Support Officer – Mental Health Complaints Commissioner

Project Officer/Senior Project Officer

Quality Coordinator

Quality Improvement Project Officer

Registry Coordinator

Research Assistant

Specialist Consulting Coordinator

DHR: Digital Health Record(s); EMR: Electronic Medical Record; FOI: Freedom of Information (legislation); HIM: Health Information Manager; HIS: Health Information Service; ICT: Information and Communication Technologies; PROV: Public Record Office Victoria; SACSR: South Australian Cervix Screening Program; VAED: Victorian Admitted Episode Dataset; VCCR: Victorian Cervical Cytology Register; VEMD: Victorian Emergency Minimum Dataset; VINAH: Victorian Integrated Non-Admitted Health Dataset.

References

American Health Information Management Association (AHIMA) (2017) HIM Reimagined: Transformation Starts With You. Chicago: AHIMA.

American Medical Informatics Association (AMIA) (2017) AMIA Informatics Workforce Survey. Bethesda: AMIA. Available at: https://www.amia.org/search/node/workforce%20survey (accessed 3 April 2018).

Ammenwerth

Hackl

(2015) Job profiles of biomedical informatics graduates. Results of a graduate survey. Methods of Information in Medicine 54(4): 372–375.

Australian Digital Health Agency (ADHA) (2018) Safe, Seamless and Secure: Evolving Health and Care to Meet the Needs of Modern Australia. Australia’s National Digital Health Strategy. Canberra, Australian Capital Territory: ADHA.

Australian Institute of Health and Welfare (AIHW) (2010) The Coder Workforce Shortfall. Canberra: Australian Capital Territory: AIHW.

Bertelsen

Nøhr

(2005) The work practice of medical secretaries and the implementation of electronic health records in Denmark. Health Information Management Journal 34(4): 103–111.

Bossen

Jensen

Udsen

(2014) Boundary-object trimming: on the invisibility of medical secretaries’ care of records in healthcare infrastructures. Computer-Supported Cooperative Work 23(1): 75–110.

Cooper

(2009) Changing roles of health information managers: an education perspective. Health Information Management Journal 38(3): 38–42.

Dimick

(2012) Health information management 2025. Journal of the American Health Information Management Association 83(8): 24–31.

10.

Gibson

Abrams

Crook

(2015) Health information management workforce transformation: new roles, new skills and experiences in Canada. Perspectives in Health Information Management (International issue, May). Available at: http://library.ahima.org/doc?oid=301180#.XA8yj2gzbt0 (accessed 1 March 2019).

11.

Health Information Management Association of Australia (HIMAA) (2015) Health Information Management Professional – Definition, Version 2. North Ryde: HIMAA. Available at: http://himaa2.org.au/index.php?q=node/2438 (accessed 1 March 2019).

12.

Health Information Management Association of Australia (HIMAA) (2017a) Health Information Manager (HIM) Entry-level Competency Standards, Version 3.0. North Ryde: HIMAA.

13.

Health Information Management Association of Australia (HIMAA) (2017b) Submission on the Australian Digital Health Agency (ADHA) National Digital Health Strategy Development. North Ryde: HIMAA.

14.

Health Workforce Australia (HWA) (2013) Health Information Workforce Report. Adelaide: Health Workforce Australia.

15.

Hersh

(2006) Who are the informaticians? What we know and should know. Journal of the American Medical Informatics Association 13(2): 166–170.

16.

Knaup

Frey

Haux

, et al. (2003) Medical informatics specialists: what are their job profiles? Results of a study on the first 1024 medical informatics graduates of the Universities of Heidelberg and Heilbronn. Methods of Information in Medicine 42(5): 578–587.

17.

Leven

Knaup

Schmidt

, et al. (2004) Medical informatics at Heidelberg/Heilbronn: status-evaluation-new challenges in a specialised curriculum for medical informatics after thirty years of evolution. International Journal of Medical Informatics 73(2): 117–125.

18.

Macedo

Ruiz

EES

Baranauskas

(2016) A survey of the job profiles of biomedical informatics graduates. Methods of Information in Medicine 55(5): 473–477.

19.

Melbourne Institute: Applied Economic and Social Research (2017) Household, Income and Labour Dynamics in Australia (HILDA) Survey. Selected Findings From Waves 1-15. Melbourne: Melbourne Institute: Applied Economic and Social Research, University of Melbourne, and Canberra, Australian Capital Territory: Australian Government Department of Social Services, National Centre for Longitudinal Data. Available at: https://melbourneinstitute.unimelb.edu.au/__data/assets/pdf_file/0010/2437426/HILDA-SR-med-res.pdf (accessed 1 March 2019).

20.

Robinson

(2017) The dynamics of health information management in Australia: the emergence and shaping of a profession. PhD Thesis, University of Tasmania, Hobart.

21.

Sandefer

Marc

Mancilla

, et al. (2015) Survey predicts future HIM workforce shifts: HIM industry estimates to job roles, skills needed in the near future. Journal of the American Health Information Management Association 86(7): 32–35.

22.

Shepheard

(2010) Health information management and clinical coding workforce issues. Health Information Management Journal 39(3): 37–41.

23.

Victorian Government, Department of Health (2008) Health Information Management/Clinical Coder Workforce. Melbourne: Department of Health.

24.

Watson

(2013) The First Fifty Years 1949-1999: Medical Record Librarian to Health Information Manager. A History of the Medical Record/Health Information Management Profession in Australia. North Ryde: Health Information Management.