Perinatal data collection: current practice in the Australian nursing and midwifery healthcare context.
The continual implementation of new e-health technology into the scope of practice for all healthcare professionals is unrelenting. Such increases within nursing and midwifery are purported to improve the productivity of health services, increase efficiency, combat skill shortages and reduce costs (Eley et al. 2008b; Healy, Sharman & Lokuge 2006; Smedley 2005; Yu & Comensoli 2004). To date, the research in this area has been equivocal (Fawdry et al. 2011). Despite the ever-increasing growth in technological data entry, little is understood about what influences midwives when they enter data utilising e-health processes. Population datasets are collected worldwide to monitor outcomes in areas such as obstetrics, midwifery and neonatal care as well as provide information for research. Accurate statistical information assists in the effective planning of efficient healthcare services. Therefore, the importance of collecting such data cannot be underestimated. One such set of population data that is collected in the Australian context within obstetrics and midwifery, which contributes to areas such as funding, research, and education is perinatal data.
Developed countries have different methods for collecting perinatal data, but in essence use the data that have been gathered in the same way. In Australia, perinatal data collection is mandated nationally and contemporary practice now sees the majority of perinatal data entered via e-health technologies of various types as opposed to the use of the more traditional paper form. Within the State of Queensland specifically, the Queensland Health Perinatal Data Collection Unit (2009) reports that the move to an e-health platform for perinatal data collection has had a positive impact. The use of e-health practices is not consistent across all healthcare facilities, and the tyranny of distance inherent in the Australian healthcare landscape contributes to this diversity of practice. Currently in some areas, midwives are recording perinatal data by hand into a paper medical record as well as into an online perinatal data collection form or directly into a health information system (HIS). With such variations in practice, the accuracy of the perinatal data collection is questionable and the consequences of possible inaccurate information may have profound effects. The aim of this paper is to discuss current practice regarding the collection of perinatal data worldwide with particular attention to Queensland, Australia, and perinatal data collection via e-health platforms.
In their extensive review of the literature in relation to e-health, Pagliari et al. (2005) determined that the term first appeared in the literature in 2000 and then quickly became widely used. The World Health Organization (WHO) defined e-health as 'use of information and communication technologies (ICT) in health to, for example, treat patients, pursue research, educate students, track diseases and monitor public health' (World Health Organization 2011: 1). Harrison and Lee (2006: 284) argued that e-health 'broadly refers to any electronic exchange of health related data collected or analysed through an electronic connectivity for improving efficiency and effectiveness of healthcare delivery. Therefore it is often used to describe virtually everything related to computers and medicine'. For the purposes of this paper, e-health is defined as any electronic exchange of data used in the delivery of healthcare.
Using e-health in nursing and midwifery practice
The success of e-health technology in healthcare depends on how well it is adopted by nurses (Lang 2006). Despite the increased use of technology within practice, confidence and competence of e-health technology use by nurses is seen to vary in relation to age, computer use at home, education and training (Chan, Brew & De Lusignan 2004; Lang 2006; Campbell & McDowell 2011; Dillon et al. 2003, Darbyshire 2004). Dillon (2003) surveyed nurses in Kentucky (USA) regarding their confidence, attitude and computer skills and how these related to their ability to use an information system prior to the installation of a dedicated HIS. This author found that nursing education as well as home and previous computer use predicted self-efficacy or confidence of system use. Dillon, Blankenship and Crews (2005) identified that improvement to nurses' computer confidence takes time and is something to which healthcare organisations should commit. Other research conducted in the USA determined that overall, online nursing documentation improves the data quality and end user satisfaction (Langowski 2005). Satisfaction though, regarding the use of online data collection tools, is dichotomous. Indeed Langowski (2005) argued that some nurses may view the changes that e-health brings as both exciting and challenging, compared to others who find these changes anxiety provoking. Kaya (2010) in Turkey, found nurses exemplified a positive attitude to computers, but significant differences were identified for age of the nurse, education, prior computer experience and duration of computer use. In the United Kingdom (UK), Chan, Brew and De Lusignan (2004) surveyed a small group of community nurses, finding that nurses over 50 years of age were lacking in confidence and used computers less than younger staff even though they had received more training. They reported that only 53% of district nurses self-identified as confident in using computerised medical records. Brumini et al. (2005) concluded from their study that computer education and experience are the key contributing factors in the development of positive nurse attitudes towards computers.
Within Australia, nurses have been found to lack knowledge, confidence and readiness for e-health technology in their workplace (Edirippulige et al. 2006). Other authors, Eley et al. (2008a) and Smedley (2005), have reported that nurses' confidence in using ICT in their practice generally, as well as their overall acceptance of ICT in the workplace, is low. A strategy to address this low confidence and general acceptance may be education and training. The importance of professional development in health informatics, ICT and e-health at an undergraduate level and as part of continuing education is widely discussed, supported and recommended in the literature (Barnard, Nash & O'Brien 2010; Booth 2006; Edirippulige et al. 2008; Eley et al. 2008b; Garde, Harrison & Hovenga 2005; Ward et al. 2008). In what is often described as an already full curriculum (Hinton 2004), increasing content related to ICT within undergraduate nursing programs will prove challenging. However, the use of ICT as a competence is embedded within the Australian Nursing and Midwifery Council competency standards (Australian Nursing & Midwifery Council 2006).
The consequences of little or no professional development and lack of proper preparation, training and motivation could mean that nursing and midwifery as professions within Australia may miss the opportunity to be closely involved in e-health innovation. It may also mean that nurses and midwives may not be as sufficiently skilled and confident in utilising e-health technology as is increasingly required, particularly as it becomes more and more integrated within their daily practice. This notion is not new and is becoming increasingly important as healthcare moves further into the twenty first century. Contemporary practice requires efficient and appropriate use of ICT (Chan, Brew & De Lusignan 2004; Gerrish et al. 2006; Lupi-6ez-Villanueva et al. 2011)
Reported aims and investment in, as well as utilisation of, e-health technologies are reported as cost saving, improving efficiency of healthcare delivery and better management of growing skill shortages (Eley et al. 2008b; Healy, Sharman & Lokuge 2006; Smedley 2005; Yu & Comensoli 2004). Despite there being a growing body of literature making such assertions, to date most e-health technology has not clearly demonstrated these benefits. Black et al (2011) strongly suggest that further research in the area of e-health technologies will provide knowledge to support the ongoing and increasing spending in e-health. These authors identify a large gap between the stated and demonstrated benefits of e-health technologies. With an e-health explosion currently occurring and very likely to continue this message should not fall on deaf ears. Filling gaps in the knowledge within this space is not only important but is necessary in order to justify the vast amounts of resources and money that now go into e-health.
ICT is increasingly being integrated into healthcare practice worldwide (Ward et al. 2008). Within Australia, midwives working in urban, regional and rural areas are exposed to ICT, thus overcoming huge distances. This is important in a vast continent spanning 7,617,930 square kilometers, one that is almost as large as the US, about 50% greater than Europe and 32 times greater than the UK. The use of ICT in midwifery includes online professional education packages, email, patient records management, pathology results retrieval and digital imaging to name a few (Eley et al. 2008a). Within obstetric practice, the majority of maternity centres in Queensland collect perinatal data using e-health technology. Adding to this, a growing number of hospitals Australia-wide are using or introducing HIS utilising electronic medical records (Smedley 2005). The Australian Nurses Federation, the national union for nurses, midwives, assistants in nursing and nursing students, envisages that nurses and midwives will be the largest users of e-health, including the personally-controlled electronic health record (PCEHR), nationally released in July 2012. This proliferation in the use of e-health technology in healthcare within Australia requires a paralleled move by midwives to embrace ICT and engage in professional development in e-health technology for its successful integration into practice.
Worldwide perinatal data collection
In the US, perinatal data are collected via the birth certificate filled out soon after birth by a selection of hospital staff (Northam & Knapp 2006). These authors reviewed the literature assessing reliability and validity of birth certificate variables identifying birth certificates as being invalid sources of information on prenatal care, maternal risk, pregnancy complication, labour and delivery. A later study by Diers (2007) found that most of the data entered for birth registration was done by administrative clerks rather than the midwives who were the clinical professionals involved in the care.
In the four countries making up the UK, perinatal data are collected independently by country and not governed by one statutory minimum data set (Royal College of Obstetricians and Gynaecologists 2011). In England, perinatal data are currently collated and monitored by the Perinatal Institute. This institution, established in 2000, replaced the former perinatal audit unit in order to combat the high rates of perinatal mortality and morbidity in the region (Perinatal Institute NHS 2011). Johnson (1997) suggests that in this region there is also no real agreement on the data that should be collected or standard definitions of data items. Kenney and McFarlane (1999: 1) confirmed this by stating: 'It is widely acknowledged that national maternity data for England are incomplete and that some are inaccurate or unavailable and that they need to be improved'. Follow-up research linking population datasets in England and Wales found this situation has continued with at least one item such as birth-weight, gestational age, birth status, sex or date of birth missing (Dattani, Datta-Nemdharry & MacFarlane 2011).
Scandinavian countries have a long history of government mandated perinatal data collection. In Finland, the Medical Birth Register was established in 1987. It contains data on all mothers who have given birth in Finland and on all newborn infants up to the age of seven days. Gissler and Shelley (2002) reported a 98.5% correlation between birth history data recorded originally and at a subsequent birth within the Medical Birth Register.
Outside these western countries, perinatal data collection in developing countries remains poor, with the WHO reporting that the current data available remain incomplete and are therefore less reliable in demonstrating mortality and morbidity (Ahman & Zupan 2007). Worldwide, there is a high degree of variability in the nature and quality of perinatal data that are gathered and this inconsistency occurs in even the most developed of countries. This situation should be causing alarm bells to ring. Not only is the literature pointing to inaccuracies in data collection but it is also alludes to an absence of necessary information. This is not acceptable especially if healthcare systems are expected to cope with an ever-increasing birth rate.
In Australia, collection of perinatal data is mandated at a Federal Government level and it is reported that the collection has enormous power and is the envy of other developed countries (Diers 2007). These data are publicly available and have been mined to support changes in policy for midwife led care as well as to provide evidence of the increasing costs of intervention in childbirth. Mandatory data collection items for each state and territory are updated annually to reflect the Perinatal National Minimum Data Set regulated in Australia's capital, Canberra by the Australian Institute of Health and Welfare National Data Statistics Unit (AIHW National Perinatal Statistics Unit 2011). A minimum dataset is a list of data elements of uniform definition containing the least number of data items required to fulfill a particular job (Conrick et al. 2006).
Looking at Queensland specifically, perinatal data collection commenced in November 1986, via the Perinatal Data Collection form. This was completed by midwives on a carbon paper form. This systematised approach was due to an amendment to the Health Act 1937 to include perinatal data collection 'to provide a basic source of information for research into obstetric and neonatal care and to assist with the planning of Queensland's health services' (Queensland Health 2010: 8). The relevant component from this Act was replaced by the Public Health Act of 2005 that includes a requirement that perinatal data be provided to the Chief Executive of Queensland Health, Queensland's publicly run health organisation, for every baby born in Queensland. Data collected via this perinatal data form monitor patterns of obstetric and neonatal practice, analyses obstetric and perinatal outcomes such as mortality rate and congenital abnormalities, assist in the planning of Queensland Health services through provision of statistical information, provide a course of information for research into obstetrics and neonatal care in Queensland and are used in the education of midwifery and medical students (Queensland Health Perinatal Data Collection Unit 2010). Such uses demonstrate the significance of accurate perinatal data collection. Further to this is the important role that perinatal data collection has in funding health delivery in Queensland. Existence of the perinatal data form in the medical record, in part informs clinical coders to assist in allocating diagnostic related groups and casemix codes for a hospital admission, which are then used to determine funding for healthcare institutions (Healy, Sharman & Lokuge 2006). Healthcare funding requirements are generally contentious and involve large amounts of revenue. Recently, the Queensland Government budgeted $9.9billion for healthcare for the 2010/2011 period (Queensland Government 2010). Inaccurate or incomplete perinatal data entered for collection, which are then used as a determinate of service delivery needs, have the potential to lead to inadequate or misrepresented funding dissemination to healthcare facilities.
Funding allocation on the basis of population data primarily requires information to be accurate if effective fiscal allocations are to be made. Nicholson and Penny (2004) asserted that decision-making is directly influenced by the quality of data and that a healthcare provider's future is linked to each professional's performance in relation to this. Such is the importance of accuracy, this proposition is reinforced by the Queensland Health, Perinatal Data Collection Unit (2010: 201) who state, 'the quality of information produced from the perinatal data collection depends on the accurate, consistent and timely completion of the forms'. Inadequate outcome reporting as related to poor data collection could also have negative implications for health service users.
Perinatal data collection via e-health platforms
In September 2009, after a short trial in a small number of healthcare facilities across Queensland, an online perinatal data form was introduced to selected maternity and neonatal units to replace the paper perinatal data form (Queensland Health Perinatal Data Collection Unit 2009). The online version contains field validations that control data entered into certain fields in an effort to reduce the number of errors and omissions historically submitted via paper forms. Field validations set parameters that define numerical or alphabetical field data requirements, date ranges, and prevent forms being submitted electronically when data are absent from mandatory fields. Although this online form has reduced the number of errors and omissions as determined by the validations used by the perinatal data unit (Queensland Health Perinatal Data Collection Unit 2011), these program validations cannot control the correctness of the data entered; that is the data integrity. Other hospitals in the private sector entering data into a HIS may submit data via an extract. Issues for this method of collection of perinatal data occur in relation to field definitions here as often the HIS definition does not exactly match the perinatal data requirements. When data entered into any online system do not match the data sources in the medical record, the many and varied services that the perinatal data collection provides information for, as well as funding, are placed at risk. This duplication of data is costly for service providers as well as time consuming for midwives within their already busy workload.
Midwifery, as a specialist practice, has historically been an interruption driven environment in which the workflow of midwives is dynamically changing (Cooper, Viller & Burmeister 2004). Efficient and accurate data entry into paper and e-health records may be influenced by environmental factors such as workload, access to computers, and ICT literacy of staff. As a result of the perceived problems in perinatal data collection, research that examines the quality and integrity of data collected has been conducted. As early as 1975, authors examined the accuracy of data that were being collected on mother and babies worldwide. In the US, David (1980) reported on quality and reliability of birth data collected and written on birth certificates and then sent on to be entered onto magnetic disk. This information was de-identified and made available to researchers. Completeness of data on birth weight ranged from 81.7% to almost 100% complete. Hangsleben and Schamber (1985) reported on the development of a paper form to collect midwifery data items, later entered into a computer for analysis. They identified data inaccuracy as a problem and cited methods to improve it, such as designating one person as responsible for checking as well as verifying the data at input. This approach was said to increase data accuracy but simultaneously largely increased costs. Within a tight fiscal environment, anything that increases costs is not likely to be adopted. In a comparison of case notes to a maternity database in the UK, Maresh, Dawson and Beard (1986) found a rate of 95% accuracy in midwife-entered data on 160 data items. Also in the UK, Cleary et al. (1994) found data matched at between 77% and 100% accuracy and reported this as supportive of using their data collection method as a model for other healthcare agencies. Lain et al. (2011) recently published a systematic review of data quality in perinatal population health databases worldwide, which reviewed 43 studies particularly looking at accuracy and completeness in relation to validation. They found birth data to be less accurate on a range of items than data from hospital discharge databases. Other research supports this contention, such as that by Devlin, Desai and Walaszek (2009) who demonstrated that hospital discharge data was generally more accurate than birth data. It should be noted that these studies are quantitative in nature and focus on validation of data rather than underlying factors that influence why this may be so.
In Australia, validation studies on perinatal data records have been published (Taylor et al. 2000; Riley & Griffin 1997; Riley & Halliday 1998; Riley, Phyland & Halliday 2004; Roberts et al. 2009; Robertson 1996). However, none of these relate specifically to online perinatal data entry or the processes that surround it. The underlying theme throughout these studies assessing quality of perinatal data is that high quality data are variable and researchers need to be more aware of the quality of data they are using. In contrast, Robertson's study (1996) validated the use of paper perinatal data forms in Victoria (Australia) quantitatively, but went on to examine the causal factors to inform a training program implemented for staff in an attempt to address matters of accuracy. Through qualitative investigation, the study identified issues with data entry such as confusion over perinatal definitions, underreporting relating to perceived sensitiveness of information and transcription errors (Robertson 1996). However, no follow-up research into these issues for midwives appears in the literature.
The literature reveals a diverse range of research in relation to nurses, midwives and information technology with foci around HIS implementation and the electronic health record. Areas researched included barriers to implementation of information technology and the harnessing of motivating factors of staff, to successfully integrate new systems, education and training needs, attitudes, beliefs and confidence to name a few. Although this research offers views into midwives use of information technology and e-health, none specifically addresses the needs of midwives entering perinatal data. There is clearly a gap in the literature that needs to be filled.
Implications for practice
As asserted, the importance of accurate and timely data cannot be underestimated. Midwives are using e-health technology at an ever-increasing rate without many of the perceived improvements to practice and from a position in which they lack confidence to do so. Worldwide collection of perinatal data is varied in quality with Australia's mandated system, in place for almost 30 years, which Diers (2007) argues is the envy of developed nations. With the majority of Australian maternity units now using e-health technologies, some of which result in perinatal data collection, the impact on practice needs investigation to ascertain the data integrity and issues for midwives. The anticipated benefit of improved quality, timeliness of submission and therefore improved service delivery is a matter for critical examination. The data that are collected impact on practice from funding, workloads through to ward or unit evaluations. However, the extent to which computerised perinatal data collection enables midwives to accurately record data remains unknown. This is due in part to the lack of information on how midwives interact with such systems. Future research should investigate the perceptions of midwives who collect and enter perinatal data to explain the phenomenon from the bedside to computer from their point of view. The need for accurate data is unquestionable.
This paper has identified the global inconsistencies with health-related data collection but has simultaneously highlighted how such data in varying states of completeness and accuracy are used to resource health services. The discussion has focused on perinatal data collection, which, in Australia, is most often done by midwives. Many factors contribute to inaccurate or incomplete data entry and given the significance of the gathered information, it is imperative that research is undertaken to understand what influences midwives when collecting and entering perinatal data. This is particularly significant in Queensland now that the process of entering these data has moved to an online format. The Australian perinatal data collection operates within a mandated systematised approach countrywide. Such an approach is used to monitor outcomes and therefore improve perinatal mortality and morbidity by the provision of resources directly where they are needed. The effective care of mothers and babies is something for which the community at large will not tolerate a second-best approach. By accurate data collection and understanding what influences this data collection, care will only ever be first class.
This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
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Alison Craswell RN, BN, GradDipMid, BA (InfMgmnt)
Faculty of Sciences, Medicine and Health
University of Wollongong
Wollongong NSW 2500
Lorna Moxham RN, MHN, PhD, MEd, BHSc, DASNsg, GradDip(OH&S), CertQulMngt, FACMHN, FCON
Professor of Mental Health Nursing
Faculty of Sciences, Medicine and Health
University of Wollongong
Wollongong NSW 2500
Marc Broadbent RN, MEd, PhD
Institute of Health and Social Science Research
PO Box 1128
Noosaville BC 4566
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|Author:||Craswell, Alison; Moxham, Lorna; Broadbent, Marc|
|Publication:||Health Information Management Journal|
|Date:||Feb 1, 2013|
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