The Use of Information Systems for Clinical Decision Support by Primary Health Care Practices in a Medium Sized PHO

• Abstract
• Introduction
• Methods
• Methodology
• Fieldwork
• Ethical approval and Identification of target practices
• Survey techniques
• Questionnaire design
• Results
• Discussion
• Conclusions
• Acknowledgements
• References
• Footnotes

Abstract
The aim of this research is to elucidate how health professionals in Primary Health Organisation (PHO) practices, are using computer-based information systems to help support clinical decision making (CDM). Knowledge about the usage of systems by these practices could contribute to the planning of efficient information acquisition and sharing within the organisation, resulting in benefits for the PHO members and their patients.

This paper presents the findings derived from responses to a postal questionnaire sent to the general practitioner (GP) practices within a medium-sized PHO. The results illustrate that there are wide differences in the use of information systems (IS) for the support of CDM by the responding practices, and indicate that a proportion of practices could benefit from incorporating some additional use of IS into their routines. Practices perceive a number of barriers to the improved use of their existing systems that support CDM, with the most highly ranked barriers relating to non-technical issues.

Introduction
The New Zealand primary health care sector has undergone restructuring in recent years and has moved to population-based care structured around not-for-profit Primary Health Organisations (PHOs). PHOs are composed of health care professionals, including general practitioners (GPs), nurses, pharmacists, Maori and Pacific Island health care providers, and community representatives.^[1] There are currently 81 PHOs which, together with their District Health Boards and local communities, are responsible for the care of their patient populations. These PHOs vary greatly in size from those with enrolled populations of just over 3000, to those responsible for over 300,000.^[1,2] Under the new organisational structure, a team-based, multi-disciplinary approach is taken to the provision of services and new ways of collaborating are being developed.^[1]

Against this background, there is an increasing crisis “at the coal-face”, with a high proportion of GPs leaving or retiring from the profession and replacements often being difficult to find.^[3,4] For some time it has been recognised that GPs face problems in managing the vast amount of information they need to process,^[5,6,7] and researchers have reported that doctors need to be able to find answers to their queries rapidly or questions can remain unanswered.^[8,9] Further, a recent report has suggested that increased paperwork associated with PHO requirements has contributed to the burden experienced by GPs.^[4] The use of information systems (IS) is widely seen as a way of addressing some of these problems and reducing the burdens faced by health professionals in their every-day work, eg, by providing access to timely and accurate information.^[6,9,10,11] This paper focuses on the use of IS in the support of clinical decision making (CDM). A report prepared for Australia’s health sector^[12] defined clinical decision support (CDS) as “Access to knowledge stored electronically to aid patients, carers, and service providers in making decisions on health care”, and it is this broad definition which is adopted in this research.

The research this paper reports on forms part of a project studying the use of computerised support for CDM in the PHO environment. It reports on findings from part of a pilot case study which was conducted with a New Zealand PHO in the last quarter of 2005. The paper aims to elucidate how health professionals in PHO primary health care practices are using computer-based systems to help support CDM in the care of their patients. Information on the use of IS by these practices could contribute to planning for efficient information acquisition and sharing within the organisation, resulting in benefits for the PHO members and their patients. By reporting on current usage of these systems in PHO primary health care practices it is intended that strategies for the improved use of existing and/or implementation of improved systems and support will be developed.

Methods
Methodology
Because the research involved a study of the use of IS in the support of CDM in the primary health care sector, and because of the newness of the study environment, a case study research strategy was selected. A multiple case study design was chosen including a pilot study. A review of the literature contributed to the identification of IS useful in CDS, including broadly based systems, tools and support features, and barriers to the use of CDS systems.^[13-18]An iterative process was used to develop a questionnaire during the pilot case study, using this information, which provided the results reported on in this paper.

Fieldwork
Ethical approval and Identification of target practices
Before fieldwork was undertaken, full ethical approval was received from both the Massey University Human Ethics Committee and the Central Regional Health and Disability Ethics Committee. PHOs in the Lower North Island were approached by letter and invited to discuss further their possible involvement with the project. The pilot case study PHO was chosen because of its geographical accessibility and existing research connections, including ongoing consultation with the local Iwi Council of Elders.^[a] The PHO suggested practices it would be appropriate to contact and which would provide a range of practice sizes and information technology (IT) usage, to reflect the spectrum of practice types in the organisation. These were then approached either by letter or email and invited to take part in the research.
 

Survey techniques
Face-to-face, semi-structured interviews were carried out with a total of 15 volunteers: eight staff members of a PHO management organisation and seven staff members drawn from three PHO member GP practices. The interviews were analysed, and information gained contributed to the preparation of a questionnaire, which was pre-tested and submitted for approval by the Central Regional Ethics Committee. Having gained approval, it was then sent to 23 GP practices in the PHO, excluding only those practices which had contributed already to the study in the interview phase. After the initial mail-out and subsequent return of completed questionnaires, a follow-up letter and second copy of the questionnaire were sent to non-respondents. This elicited further responses. The results of part of the postal questionnaire are discussed in this paper.
 

Questionnaire design
The questionnaire consisted of two parts. This paper presents the findings from the responses to four questions from the second part, which dealt with inter-related aspects of CDS. Computer systems can provide a variety of support for CDM.^[13] For example, broadly based IS such as the Internet and email can be utilised to access health information and networks and provide communication channels, and practice management systems (PMS) are often hybrid systems which combine management capabilities with more specifically focused decision support tools. CDS tools are more specific in their functions and include many different decision support systems (DSS) and diagnostic tools,^[14] which can be integrated with other systems or provide stand alone support. A number of features/functions provided by clinical systems and tools support particular purposes.^[15,16]

Question 1 was based on a study of the IS support for CDM during the consultation process in two New Zealand primary care practices^[13] which found that the Internet, email and PMS were used in varying ways to support CDM during the GP–patient consultation process. The extent of their use in the PHO practices was explored with this question.

Question 2 addressed the extent to which respondents are using different electronic CDS tools. Currently available clinical tools include:

• Alerts and reminders, both for efficient time-management and also for recalls of patients for various procedures such as immunisations, etc. Alerts for prescribing are available aimed at reducing the risk of the patient being prescribed incompatible medications.
• Diagnostic tools to assist the clinician at the point of care both in developing an appropriate differential diagnosis, also in refining the answer by recommending differentiating tests.
• Evidence-based health information in focused form that is readily available to the clinician at the point of patient contact.
• “Expert” opinions are available especially involving the transmission of data from organ imaging scanning technologies.^[14]

Question 3 explored the extent to which features of current tools were utilised in, or provided by, the respondents’ practice systems. It drew on the results of a systematic review carried out on studies of the ability of CDS systems to improve clinical practice.^[15] The review included 70 randomised control trials and concluded that the four most important features for predicting the ability of a decision support system to improve patient care were:

. . . automatic provision of decision support as part of clinician workflow. . ., provision of actionable recommendations rather than just assessments. . ., provision of decision support at the time and location of decision making. . ., and computer based decision support.^[15]

The authors of the review suggested that these features should therefore be present when possible in CDS systems.^[15] Additionally, the question incorporated information from a report on the use of current electronic decision support tools in small independent practices in the US. The US report presents features of tools which can benefit physicians by:

• Bringing accessible information and knowledge to the point of clinical decision-making.
• Bringing knowledge relevant to the particular clinical situation (for example, the specific patient, the specific issue, or the specific medication) to the physician when needed.
• Combining clinical knowledge with patient information to help the physician stay abreast of the patients health status (for example, identifying preventative interventions that are due or issues requiring follow-up).
• Identifying patients lost to follow-up or overdue for recommended interventions.
• Alerting the physician to contraindications or potential problems by checking planned actions against other patient information and generally accepted clinical knowledge.^[16]

Lastly, question 4 sought to determine the importance of barriers faced by practitioners in their use of computers for the support of CDM. Barriers to the implementation of CDS in primary care practices were identified from the literature. They included issues with time, cost, hardware, software, system speed, on-going systems support, credibility, skills in using CDS programmes, programme flexibility and ease of adjustment, and the format, functionality, and order of content.^[17,18] Further barriers such as knowledge of appropriate systems/tools, training, security and privacy, were identified during discussion with colleagues, and from pilot case study interviews. This information was combined to provide the items considered in question 4.  

Results
Ten completed questionnaires were returned in the postal survey, giving a response rate of 43.5 percent of practices surveyed. Of these, 60 percent had been completed by clinicians and 40 percent by practice administrators. The total number of staff employed at each of the practices varied between 3 and 21, with GP full time equivalents of between 1 and 5. All responding practices used computer systems and one of two types of practice management system (PMS), with 80 percent using the currently predominant system in New Zealand GP practices. The responses to questions 1–4, focusing on the use of IS in the support of CDM, were analysed and the results are presented below. The questions were designed using a linear numeric scale of 1–7 where 1 equals “Not at all” and 7 equals “Very much”. Respondents were asked to rate their response on the scale and were also given a “Not applicable” (0=N/A) choice. Blank and N/A responses are treated as missing data. For ease of description, ratings have sometimes been combined to group the responses into categories of “low” (2 and 3), “moderate” (4 and 5), or “high” ratings (6 and 7). Tables have been sorted using a combination of the “moderate” and “high” category values to rank their lists in descending order of importance.

Question 1
This question asked the survey practices to rate how much, if at all, their PMS, the Internet and email are used in the support of CDM when caring for their patients. One-third of practice respondents reported that they used their PMS “Very much” (7) whilst another third said they did not use it at all (1). Reported use of the Internet also varied and was reported to be used “Very much” (7) by only 20 percent of subjects, with a further 30 percent reporting no use of it at all (1). However, email results were somewhat more uniform with 62.5 percent reporting that it was not used at all (1) for CDM support. See Figure 1.

Figure 2 shows that the use of email to support CDM tended to be reported only by larger practices, whilst a lack of use of any or all three systems was more common in the smaller practices. Eighty percent of practices reported some use of one or more of the systems for CDS with 30 percent using email, 60 percent using PMSs and 70 percent using the Internet.

Figure 1: Percentage of practices using popular IS for CDS

Figure 2: Usage of popular IS for CDS by practices

Question 2
The second question asked practice respondents how much, if at all, existing software tools were used to support CDM when caring for their patients, and the results are illustrated in Figure 3. Alerts and reminders (eg, for allergies or drug interactions) scored highly (6 and 7) with two-thirds of respondents, with all respondents reporting some use of them. Expert opinions (eg, MIMS) were also rated highly (6 and 7) by 50 percent of respondents, with a further 25 percent giving them a moderate score (5). The use of diagnostic tools (eg, algorithms), varied from 16.7 percent using them “Very much” (7) to 50 percent of practices not using them at all (1), whilst focused evidence-based information (eg, Medline, Cochrane) was rated highly (7) by only 14.3 percent, and also had a high negative response with 42.9 percent reporting usage as “Not at all” (1).

Figure 3: Percentage of practices using popular CDS tools

Question 3
Table 1 presents the results from the third question, which asked respondents to what extent their computer systems provide certain types of support for CDM, with the list ranked according to their combined “moderate” and “high” scores. Seven CDS features are listed in the first column of the table. The feature “Identify patients lost to follow up or overdue for recommended interventions” stood out as the most used, with 77.8 percent of practices reporting moderate to high usage. All other features were rated as low or not used at all by at least 50 percent of practices. Four of the features were reportedly provided to some extent by practice systems at all responding practices, whereas three features (marked with asterisks^[b]) were not provided at all in a small percentage of practices, and were ranked at the lower end of the list.

Question 4
The last question probed the importance of barriers to the improved use of computer systems for the support of CDM by GPs. The percentage distribution of practices’ responses to Question 4 are presented in Table 2. The barriers are ranked according to their combined “moderate” and “high” scores. The majority of respondents (88.9 percent) reported “Time” and “Cost” as the most important barriers. “Training” followed at 77.7 percent, with “Credibility” and “Skills in using clinical decision support programmes”, being rated similarly by 75 percent of respondents. 44.4 percent of practices responded that “On-going system support”, “Software”, and “Functionality” were not barriers at all, and “Format” rated similarly with 55.6 percent of respondents. “Hardware”, “Content” and “System speed” were also represented in the lower rankings.

Discussion
In terms of the use of broadly based IS to support CDM by primary care general practices, the results were well distributed across the spectrum of usage for two applications studied, those being PMS and the Internet. The use of email in the support of CDM was not as strong, with a high percentage of practices reporting they did not use it at all for that purpose. Results indicated that the use of email in CDS was more prevalent in larger practices, and an absence of use of the applications was more likely to be found amongst the smaller practices. This reflects findings from the US which show that practice size can influence the adoption of IT in health care, and that single practitioner and small practices are less likely to use new technologies and are likely to have a slower adoption rate than larger practices..^[19,20]The results indicate a wide difference in the use of these technologies by the practices studied and indicate that non-users might benefit from incorporating some additional use of broadly based IS into their routines, to support CDM.

With regard to CDS tools, alerts and reminders were very popular and were often used by most practices. Expert opinions were moderately to highly used by half the practices with a small percentage claiming no use of them at all. The differences reported in practice use of diagnostic tools was striking – they were not used at all by half the practices, but were used moderately to highly by the other half, and the use of focused evidence-based information varied across the usage continuum with over 40 percent of practices not using it at all. These results again illustrate that while some practices find certain decision support tools useful, other practices may not be taking advantage of them at all. As these tools can be provided by PMS, through the Internet or as stand-alone systems, the potential exists for increased utilisation of available systems to ease the GP’s CDM and administrative burdens.

When asked to rate to what extent their systems provided each of seven CDS features, most practices reported some provision of each of the features listed. However, the provision of all features except one were rated as “low” by a high proportion of practices, with the exception of “Identify patients lost to follow up or overdue for recommended interventions”, which was moderately to highly rated by more than 75 percent of practices.

It is notable that a small proportion of practice respondents did not think their systems provided three features at all, those being (1) “Bring information to the point of clinical decision making”, (2) “Provide decision support automatically as part of the workflow” and (3) “Provide actionable recommendations”, and that these features were ranked within the four last places on the list. These features have been described as being three of the four most important indicators of the ability of CDS systems to improve clinical practice,^[15] and this result indicates that efforts should be directed at encouraging the use of these features.

In general, the results were well dispersed showing a range of opinions. Although the provision of these features by practice systems varies in the opinion of the respondents, it is possible that some systems can provide the features but they are not being utilised fully. Systems might not be set up to advantage, staff could be unaware of some aspects of their system’s capabilities, or useful modules or extensions to the software may not have been included at installation.

The last question sought to identify and evaluate the importance of barriers to the use of computer systems for CDM support in primary health care practice. Resource and clinical issues such as “Time”, “Cost”, “Training”, “Credibility”, and “Skills in using CDS programmes” were considered to be moderate/important barriers, each with more than 75 percent of respondents. Technical and systems considerations appear to be secondary barriers, being represented in the lower half of the rankings. These results highlight areas upon which the management of service organisations could focus attention. This finding agrees with other research which has found that time, costs, lack of technical support and the need for large initial capital investments were important barriers to clinical computerisation.^[17] A number of barriers were reported as not being at all important by some practices, whilst other practices held the opposite view, showing that opinions are varied. However, many practices do agree that there are a considerable number of barriers to the improved use of computer systems for the support of GPs’ CDM. The variety of experience within the GP practices of one PHO could potentially be utilised, by passing on the knowledge gained by early adopters of CDS technologies to others, although this variety may also indicate that a “one size fits all” policy in support or barrier removal might not be appropriate, and the very individual nature of member practices needs to be taken into account when designing technology initiatives.

A recent report on health information technology adoption in the US,^[19] suggests that IS adoption could be encouraged by incentives at the corporation rather than provider level. It is feasible that the relatively new PHOs could provide the environment which would encourage further IS adoption by member practices. This could also be facilitated at the practice level by an increased knowledge of the possibilities of IS usage and by taking steps to alleviate barriers experienced within their practices.

Analysis of the questionnaire results was limited due to the small number of respondents. In addition, potential differences in response patterns between doctors and administrators should be considered in further research. The researchers’ ability to generalise from the results is, therefore, restricted to GP practices which are part of a medium sized PHO, and as the case study was carried out in an organisation which was relatively newly formed, findings of a similar study conducted in a more established organisation, or the same one at a later date, could show differences due to the rapidly changing environment of PHOs.

Conclusions
This research illustrates that there are wide differences in the use of existing information technologies to support CDM by the GP practices studied, with some practices finding certain systems and CDS tools useful, while other practices appear not be taking advantage of available IS support at all. The results indicate that a proportion of practices could benefit from incorporating some additional use of broadly based IS and CDS tools into their routines. Whilst in the opinion of the respondents the provision of certain decision support features by their systems varies, it is possible that in some cases systems are not being utilised fully and could already have the potential to provide more features if set up differently or extended.

Three of the most important features indicating the ability of CDS systems to improve clinical practice^[15] are not provided at all in some practices and were generally ranked low in the study. Results indicate that practices could benefit from the improved use of existing or new computer systems. However, practices perceive a number of barriers to the improved use of their systems in the support of CDM, with the most highly rated barriers being non-technical in nature. These findings could be of use to PHO management service organisations in the planning of future CDS initiatives.

Acknowledgements
With thanks to the staff of the pilot case study PHO management organisation and health care practices, for their generosity in sharing their knowledge and time, the local Iwi Council of Elders Te Mauri O Rangitaane O Manawatu for their support and advice, and to the Tertiary Education Commission for the support provided by a Tertiary Education Commission Top Achiever Doctoral Scholarship.

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Footnotes

(a). An Iwi is a Maori (indigenous people of New Zealand) tribe, the largest social group within Maoridom. Iwi were divided into hapu (sub-tribe), which in turn are made up of whanau (households).

(b). See discussion.