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Information and communication technology adoption for business benefits: A case analysis of an integrated paperless system
International Journal of Information Management 32 (2012) 196–202
Contents lists available at SciVerse ScienceDirect
International Journal of Information Management journal homepage: www.elsevier.com/locate/ijinfomgt
Case study
Information and communication technology adoption for business benefits: A case analysis of an integrated paperless system Mário Caldeira a,∗ , António Serrano b , Rui Quaresma b , Cristiane Pedron a , Mário Romão c a b c
ISEG – Technical University of Lisbon, Lisbon, Portugal Évora University, Portugal ISCTE, Portugal
a r t i c l e
i n f o
Article history: Available online 14 January 2012 Keywords: Health care information systems Benefits management Paperless systems
a b s t r a c t This case study analyses the benefits of implementing a paperless software solution (Alert® pfh–Alert Paperfree Hospital, developed by Alert Life Sciences Computing) in a Portuguese Hospital, the Espírito Santo Hospital, in the city of Évora. Alert® pfh is a complete hospital clinical information system with real time clinical information input. It was implemented in emergency medical services, inpatient and outpatient services, and operating room services. Data were collected between 2006 and 2011 prior to, during and after the system’s implementation. The case analysis demonstrates that paperless software systems have a significant potential when applied in healthcare organization services. Besides financial benefits, other important organizational features were identified, namely higher levels of patient and professional satisfaction; an increase in efficiency in hospital operations; improvement in the quality of information for management decision-making; and a reduction in medical errors. Lessons learned are noted and conclusions drawn for both theoretical and practical ICT benefits analysis. © 2011 Elsevier Ltd. All rights reserved.
1. Introduction Investments in information technology and communication systems (ICT) have been growing considerably. According to Gartner Group (2010), the investment ICT worldwide for 2010 is 3215.7 billion USD. However, the academic literature frequently claims that the level of success with adoption is far from satisfactory. A high percentage of ICT implementation projects fail significantly in at least one of the following issues: completion time; falling within the budget; or fulfilling all business requirements (Han & Huang, 2007; Pan, Hackney, & Shan, 2008). When organizations invest in ICT they expect to improve their efficiency and effectiveness, and to enable business benefits. A proper analysis of business benefits from such investments must go far beyond the financial perspective, especially in health care organizations, where this research was conducted. Nowadays, because ICT has an important role in healthcare, many hospitals and clinical organizations are deeply dependent on these systems for electronic health records, computer assisted triage, electronic prescription, computer provider order entry, or telemedicine (Wager, Lee, & Glaser, 2009).
∗ Corresponding author. Tel.: +351 966217788. E-mail addresses: [email protected] (M. Caldeira), [email protected] (A. Serrano), [email protected] (R. Quaresma), [email protected] (C. Pedron), [email protected] (M. Romão). 0268-4012/$ – see front matter © 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijinfomgt.2011.12.005
This case study analyses the business benefits of implementing a paperless software solution (Alert® pfh) between 2007 and 2011 in the Espírito Santo Hospital in the city of Évora, in the south of Portugal. Alert® pfh is an integrated software system that was developed by Alert Life Sciences Computing, a Portuguese software house whose turnover was 47 million euros in 2010. This software house is dedicated to developing and maintaining health care information systems. The Espírito Santo Hospital in Évora serves a population of around 174,000 inhabitants. In 2008 the hospital had 350 beds. It held 158,000 outpatient appointments in 2008, 175,000 in 2009, and 200,000 in 2010. In 2010, it also had 77,000 emergency episodes, 8921 surgeries and 1.8 million clinical analysis and therapy acts. The hospital implemented Alert® pfh which system helped to manage all the clinical areas of the hospital: outpatients, emergency episodes, inpatients, and operations room. The clinical system is also integrated with an Enterprise Resource Planning system of the hospital, which is implemented using Microsoft Navision and is used to manage administrative processes and some other clinical software like PACS (Picture Archiving and Communication Systems). Alert® pfh also provides a data warehouse that allows analysis of the healthcare services provided to each patient, a process performance analysis and a cost analysis. Implementing ICT in organizations often results in significant situations of resistance to change and Hospitals are complex organizations, with many stakeholders. On the other hand, these systems are not merely technological artifacts, they include an
M. Caldeira et al. / International Journal of Information Management 32 (2012) 196–202
Identify and structure benefits
Potential for further benefits
Review and evaluate results
Plan benefits realization
Execute benefits plan
Fig. 1. The benefits management process. (source: Ward & Daniel, 2006).
organizational and political dimension because they alter the work routines and established power relations and interests within the organization. A system such as Alert® pfh is obviously no exception. Assessing the business benefits should not be a one-off task carried out in an initial phase of the implementation. Assessing the benefits is an on-going process because some benefits may not be immediate and will only appear at a later stage when the system has been fully integrated into the running of the organization by all of its users. 2. Case study approach
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completed. Quantifiable benefits provide sufficient evidence of how much improvement should result from the implementation of the new system. In financial benefits, a financial value can be calculated. The benefits realization plan consists of a set of changes that are essential for attainment of the benefits. It includes the time when benefits should be attained and the resources needed to implement benefits management. It is important that project management should also be accomplished by change management in order to achieve organizational benefits. This is in fact what happened in the case of Alert® pfh in the Hospital. The management plan must include the most appropriate measures and mechanisms to control benefits realization. Monitoring progress against the activities and deliverables of the business benefits plan is important. Benefits do not occur on the first day the new system starts operating; some benefits require time before they are attained. Since it is difficult to predict all the benefits of a system in advance, further benefits may be identified during its implementation. A Benefits Dependence Network is an important tool that links information technology investment objectives and the required benefits to business changes (i.e. the ways necessary to deliver those benefits) and the information technology capabilities that enable those changes. 2.2. Data collection Data were collected between 2006 and 2011, covering periods before, during and after the implementation of Alert® pfh. The following techniques for data collection were used: • • • •
Semi-structured interviews; Real-time quantitative data in the emergency services; Participant observation; and Document analysis.
2.1. Benefits management Benefits management is a process of organizing and managing ICT (Peppard, Ward, & Daniel, 2007; Ward & Daniel, 2006). Its objective is to ensure that the potential benefits arising from the use of information technology in organizations are actually attained. The benefits management process is structured in five fundamental phases, illustrated in Fig. 1: The phase of identifying and structuring business benefits is probably the most complex phase in the whole process, and it is a critical one. In this phase, all potential benefits should be identified, classified according to their nature, and located in the organizational processes. According to this approach, a benefit is an advantage on behalf of a particular stakeholder or group of stakeholders (Ward & Daniel, 2006). Hence, reducing costs or improving financial results can be perceived as a benefit, as well as increasing customers’ satisfaction or improving employees’ working conditions. Each benefit must have an “owner” within the organization, someone responsible for its achievement. It is also important to determine whether a benefit can be measured in order to prove that it has occurred. Benefits must be structured in order to understand the potential effect of information technology in the organizational processes and measures must be developed for most benefits. Benefits can be classified as observable, measurable, quantifiable, or financial. Observable benefits are benefits where, on the basis of experience, an expert or a specific group of people uses agreed criteria to decide to what extent the benefits have been realized. Measurable benefits are those that are currently being measured, or appropriate measures can be implemented, but it is not possible to estimate within a reasonable degree of rigor, the future improvement of organizational processes when the changes are
The use of several techniques for data collection is recommended in the literature on case study research (for example, Yin, 2002). Thirty-nine semi-structured interviews were conducted with members of the board of directors, doctors, nurses, IT staff, and IT consultants. The interviews provide for a detailed perspective of the clinical and administrative processes of the hospital and potential benefits. One of the difficulties in identifying the business benefits was that the hospital lacked enough data on clinical process performance. For example, there were inadequate data on the average duration times of clinical appointments, detailed costs of patient treatments, among others. To overcome this, several times were measured before the system was implemented, particularly in the Emergency Room (Table 1). Table 2 shows the data on clinical analysis and therapy acts in the Emergency Room. Table 3 displays some patients’ duration times measured in the Emergency Room sample. The times are classified according to the different phases in the emergency room from being admitted, triage, and being seen to by the doctor to being discharged. Table 4 shows a breakdown of the waiting times for patients for each of the diagnostic and therapy acts in Emergency Room. Participant observation was carried out on several visits to the hospital, in particular to the Emergency Room and the services that work closely with Emergency Room. It included studying how data are collected in Emergency Room. In addition, the diverse documents related to the process of implementing Alert® pfh software were analyzed. Analyses of the observation visits and the documentation on the software and its implementation led to the identification of additional potential benefits that the introduction of Alert® pfh software could bring about. The visits also
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Table 1 Descriptive characteristics of the Emergency Room sample. 08:00–16:00 Number of patients in the sample Female patients Male patients Patients classified as “yellow” (Manchester screening) Patients classified as “green” (Manchester screening) Orthopedics surgery patients Specialty surgery patients Medicine surgery patients Age of youngest patient Age of the oldest patient
16:00–24:00 104
48 56 63 41 26 25 53
113 46.2% 53.8% 60.6% 39.4% 25.0% 24.0% 51.0%
68 45 65 48 25 34 54
60.2% 39.8% 57.5% 42.5% 22.1% 30.1% 47.8%
15 97
15 95
Table 2 Clinical analysis and therapy acts in Emergency Services. 08:00–16:00 Number of patients in the sample Therapy treatment Analyses Imaging CT scan Ultrasound Therapy treatment – twice or more Analyses – twice or more Imaging – two or more CT scan – two or more Ultrasound – two or more
104 44 37 46 5 0 4 1 0 0 0
16:00–24:00 113 43 43 46 6 0 3 3 2 0 0
42.3% 35.6% 44.2% 4.8% 0.0% 3.8% 1.0% 0.0% 0.0% 0.0%
38.1% 38.1% 40.7% 5.3% 0.0% 2.7% 2.7% 1.8% 0.0% 0.0%
Table 3 Time spent by patients in Emergency Room in hours and minutes. 08:00–16:00 All Number of patients in the sample 104 From admittance to discharge Shortest time 20 min Longest time 10 h 17 min Average time 2 h 25 min From triage to discharge 13 min Shortest time Longest time 10 h 7 min Average time 2 h 22 min From consultation with doctor to discharge Shortest time 1 min 9 h 52 min Longest time 1 h 54 min Average time From admittance to triage 0 min Shortest time 17 min Longest time 3 min Average time From triage to consultation with doctor 4 min Shortest time 1 h 56 min Longest time 27 min Average time
16:00–24:00 Yellow
Green
All
Yellow
Green
113 27 min 10 h 17 min 2 h 47 min
20 min 7 h 46 min 1 h 51 min
17 min 16 h 15 min 2 h 37 min
18 min 16 h 15 min 2 h 58 min
17 min 13 h 39 min 2 h 8 min
20 min 10 h 7 min 2 h 43 min
13 min 7 h 42 min 1 h 48 min
11 min 16 h 10 min 2 h 32 min
11 min 16 h 10 min 2 h 52 min
13 min 13 h 36 min 2 h 4 min
1 min 9 h 52 min 2 h 12 min
1 min 7 h 7 min 1 h 27 min
1 min 15 h 55 min 1 h 58 min
1 min 15 h 55 min 2 h 21 min
1 min 13 h 23 min 1 h 26 min
0 min 17 min 4 min
0 min 11 min 3 min
0 min 15 min 5 min
0 min 15 min 5 min
0 min 11 min 4 min
8 min 1 h 56 min 31 min
4 min 59 min 21 min
5 min 2 h 59 min 34 min
5 min 2 h 44 min 31 min
7 min 2 h 59 min 38 min
furnished information that was essential for an understanding of how the Emergency Room works, and this consequently influenced the planning and organization of the process for collecting data. Coordinating and following through the data collection process contributed to reinforcing the expectations of the benefits to be gained by the introduction of Alert® pfh. Use of the system is both significant and wide ranging. In addition to the doctors and nurses, ancillary staff also use it in their daily tasks. For example if a patient needs to be transported from one hospital unit to another, touch screen computers in the corridors enable the staff to keep a register of the patient’s movements.
3. Data analysis and discussion A total of 54 benefits were identified as resulting from the investment in the Alert® system. Some of the benefits noted in an early stage were later disregarded either because there was evidence lacking or the directors of the Hospital considered them to have had little impact. Neither the sources of nor the stakeholders associated with each benefit are given in order to maintain their anonymity. The benefits were grouped into “macro-benefits”, or rather first level benefits (MB1–MB7). These macro-benefits will later be featured in the
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Table 4 Waiting times for diagnostic or therapy acts for patients in Emergency Room in hours and minutes. 08:00–16:00 Number of patients in the sample Therapy Shortest time between request and use Longest time between request and use Average time between request and use Analyses Shortest time between request and nurse accompanying patient Longest time between request and nurse accompanying patient Average time between request and nurse accompanying patient Shortest time between sample taken and results Longest time between sample taken and results Average time between sample taken and results Imaging Shortest time between request and nurse accompanying patient Longest time between request and nurse accompanying patient Average time between request and nurse accompanying patient Shortest time between nurse accompanying patient and returning Longest time between nurse accompanying patient and returning Average time between nurse accompanying patient and returning
benefit dependence network. The benefits and macro-benefits (MB) identified as follows: MB1 – greater precision in diagnosis and clinical prescription: • Reduction in time and processing costs for Manchester Triage; • Reduction in number of patients who are reclassified by Manchester Triage system; • Reduction in radiation levels received by patient; • Faster and better justified clinical decision making; • Easier patient identification; • Integration and availability of patient’s clinical information. MB2 – reduction in costs for tests and clinical analyses: • Reduction in the costs for analyses ordered; • Reduction in the number of X-rays ordered; • Reduction in the number of CT scans ordered: • Reduction in the number of ultrasounds ordered. MB3 – greater systematicity in information for management purposes: • Computation of the real cost per patient treated; • Real time processing and emission of invoices in Emergency Room. MB4 – reduction in personnel costs: • Reduction of costs for medical assistants; • Reduction of personnel costs in Clinical Records Service; • Reduction of costs related to studies on the Emergency Room functioning; • Reduction in costs for administrative personnel in laboratories; • Reduction in costs for administrative personnel in Imaging; • Reduction in costs for overtime in Emergency Room (doctors); • Reduction in personnel costs for the Printing Service. MB5 – reduction in costs for facilities, equipment and material supplies: • Reduction in administrative costs for data collection; • Reduction in paper consumption; • Reduction in costs for office supplies; • Reduction in costs associated with printing imaging exams; • Reduction in use of identification tags; • Reduction in costs linked to printing identification tags; • Elimination of the use of printed/photocopied forms; • Increase in service fees collected on patient discharge; • Reduction in space needed to store clinical records; • Reduction in space needed to store office stationery; • Elimination of the need to transfer clinical records between Emergency Room and the Clinical Records Service and vice versa. MB6 – improved patient service:
16:00–24:00
104
113
0 57 6
0 min 2 h 32 min 15 min
1 2 h 18 min 21 min 37 min 3 h 14 min 1 h 15 min
0 min 33 min 8 min 18 min 2 h 50 min 1 h 15 min
0 min 2 h 11 min 12 min 3 min 2 h 47 min 55 min
0 min 51 min 8 min 9 min 1 h 42 min 34 min
• • • • • • • • • • • •
Reduction in patient waiting time for triage; Reduction in patient waiting time for their first call; Reduction in patient waiting time for therapy treatment; Reduction in patient waiting time for analyses; Reduction in patient waiting time for X-rays; Reduction in patient waiting time for CT scans; Reduction in patient waiting time for ultrasounds; Reduction in patient waiting time for results of analyses; Reduction in patient waiting time for X-ray results; Reduction in patient waiting time for CT scan results; Reduction in patient waiting time for ultrasound results; Reduction in patient waiting time while patient’s clinical records are brought from Clinical Records Service; • Reduction in patient’s time spent at the hospital; • Increase in confidentiality and security of personal data and health data in clinical files; • Improvement in service for patient’s family; MB7 – improved working conditions for professional health workers: • Elimination of difficulties in reading prescriptions for medicine/therapy; • Elimination of difficulties in reading orders for analyses; • Elimination of difficulties in reading orders for X-rays; • Elimination of difficulties in reading orders for CT scans; • Elimination of difficulties in reading orders for ultrasounds; • Reduction in environmental impact from X-rays; • Improved working conditions; • Improvement in quality of doctors’ files/consultation with doctor; • Reduction in administrative work carried out by Imaging technicians; MB8 – increase in activity–outpatient appointments: • Coping with the rise in outpatient appointments.
Table 5 shows how the business benefits were structured. The macro-benefits were included in the Benefit Dependency Network, presented in Fig. 2. Implementing the Alert® pfh system in the Hospital brought considerable benefits. Some of these benefits are immediately apparent from a financial perspective. Other benefits do not show a clear financial value, and have been classed as measurable, quantifiable or observable in accordance with the methodology adopted. There are still others that are potentially financial, but it is not yet possible to identify or estimate their monetary value accurately. Nonetheless, the benefits deriving from implementing
200
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Table 5 Structure of business benefits enacted. ID
Benefit
Macrobenefit type
Measure
Current value
Expected value
Benefit typea
Impact
B1
Reduction in processing time and costs for Manchester Triage System Reduction in costs for analyses ordered
Bm1
Average time and cost to process a case
6 min 24 s (D 2/case)
3 min 12 s (D 1/case)
F
D 1800/year
Bm2
Number of analyses ordered and the respective value (sample: 6 days) Number of X-rays ordered (sample: 6 days)
42 analyses (8:00–16:00) 47 analyses (16:00–00:00) 52 X-rays (8:00–16:00) 49 X-rays (16:00–24:00) 5 CT scans (8:00–16:00) CT scans (16:00–00:00) 5 ultrasounds (8:00–16:00) 1 ultrasounds (16:00–00:00) D 30,000/year
Reduction 10%
F
D 300,000/year
Reduction 5%
Q
No significant financial gain
Reduction 5%
F
D 150,000/year
Reduction 5%
F
D 50,000/year
D 20,000/year
F
D 10,000/year
...
...
...
B2
B3
Reduction in number of X-rays ordered
Bm2
B4
Reduction in number of CT scans ordered
Bm2
Number of CT scans ordered and value (sample: 6 days)
B5
Reduction in number of ultrasounds ordered
Bm2
Number of ultrasounds ordered (sample: 6 days)
B6
Reduction in administrative costs for data collection ...
Bm5
Administrative costs for data collection (paper, etc.)
...
...
... a
...
Benefit type: F, financial; Q, quantifiable; M, measurable; O, observable.
Information Technology
T1. Software Alert.pfh
Change factors
F1. Prepare change management for adoption of T1
Organizational
change
M1. New identification rules and control for those involved in processes
Benefíits (main)
T3. Network infrastructure
T4. PCs, printers & barcode readers.
T5. Parameters: Backoffice, MyAlert . T6. Interfaces with Sonho, Apolo, PACS,.
F5. Technical training for incorporating Alert system
F2. Training for users of the Alert system
M3. Implementation of information security procedures
M2. Alteration of administrative and clinical files
Reduction in costs for clinical tests and analyses (MB2) Greater systematicity in information for management purposes (MB3) Reduction in personnel costs (MB4)
F3.Redesign organizational processes
F4.Define motivation mechanisms for users
M4. Improvement of functional content
M5. Need for more data collection
Reduction in costs for facilities, equipment and material supplies (MB5)
Improved working conditions (MB7)
Increase in activity (MB8)
Fig. 2. The Benefits Dependency Network.
Business Drivers External:
Greater precision in diagnoses and clinical prescriptions (MB1)
Better patient service (MB6) T2. Data center
Objectives
Improve patient service (O1)
Current economic recession implies budget restrictions (D2) HESE transfer to EPE (D1)
Provide efficient health care (O3)
Improve financial results (O4)
Availability on the market of sophisticated IS/IT for hospital support (D3) Population’s growing expectations for quality of health care services (D4) --Internal: Need for HESE to improve performance (D6) Administrative Council open to IS/IT. (D5)
Increase professional satisfaction (O2)
M. Caldeira et al. / International Journal of Information Management 32 (2012) 196–202
ALERT makes it possible to estimate an annual reduction in costs or gains achieved of 3,869,896 euros. In the interviews, the directors noted that the most relevant benefit brought about by Alert® pfh was the fact that the system – electronic health records – made it possible for doctors in the Emergency Room to access a patient’ clinical history, something that they were unable to do previously. The fact that doctors could do this decreased committing mistakes in a diagnosis. Other relevant non-financial benefits included the following benefits: • Reduction in the number of X-rays and radiation levels received by patients (5%); • Length of the triage process (from 6.5 min before the system to 1.96 min using the system); • Reduction in time from the triage to first observation (from 33 min before the system to 27 min after the system); • Reduction in the time from prescription to medical administration (from 11 min before the system to 1.68 min after the system); • Reduction in waiting time for X rays results (44.5 min before the system to 23.5 min after the system); • Reduction in waiting time for CT-scan results (1 h and 16 min before the system to 31 min after the system); • Increased confidentiality and protection of clinical data; • Better service for patient and family members; • More precise information for management decision-making. In order that the above-mentioned benefits might be attained, appropriate and effective management of the process of organizational change to a digital system is essential. During the process both the system supplier and the Hospital directors were clearly concerned about this aspect, so it is expected that the organizational changeover will not constitute an obstacle to realizing the afore-mentioned benefits in the medium/long term. Increasing the protection and confidentiality of patient clinical data is an important benefit. Electronic health records constitute a significant technological advance in the way medical information is stored, transmitted, and processed by the multiple parties involved in health care delivery. However, in spite of the anticipated value potential of this technology, there is widespread concern that privacy issues may impede its diffusion (Angst & Agarwal, 2009). According to Portuguese law, the personal and health data that are collected in hospitals and are essential for the patient’s treatment entail both rights and responsibilities for the patient, the professional who collects the data, and the Administrative Council of the hospital. While the patient has a right to privacy with regard to his/her information, the responsibility to guarantee such privacy lies with the health professional who collects the data. The introduction of Alert® pfh helps to ensure greater protection of a patient’s personal data and health records because access to electronic data can easier be restricted to authorized people only. This restricted access applies to both personal data and health records, including information registered in Alert® pfh on prior occasions. Before the use of Alert it was possible to find personal clinical data, relatively unprotected, in many places within the hospital, including corridors. Since the system registers in the data warehouse costs and times of organizational processes, it contributes to improve decisionmaking. For example, when a doctor calls a patient in an outpatient appointment, times are systematically registered, which makes it possible to analyze the duration of each outpatient appointment or clinical act, improving resource allocation and effectiveness of clinical processes. 4. Case analysis – lessons learned Despite the importance of significant financial savings, support for an increase in outpatient appointments constitutes an
201
important gain for a hospital, which provides a public service. The Alert® pfh system was instrumental in enabling a significant increase in the number of outpatient appointments. Prior to implementation of the system, the number of outpatient appointments was 125,000/year. In 2009 the hospital had 150,000 outpatients and, in 2010, this number increased to 200,000. It should be noted that this increase in the number of outpatients was due not only to the ALERT system, but also to other factors, which include a regional reorganization of the health services. Nonetheless, the system played an important role. According to the Administrative Council, it would not be possible to increase the number of outpatient appointments with the same resources but without Alert® pfh. Analysis of the organizational processes suggests that about one third of the increase in outpatient appointments are due to the use of Alert® pfh. Given that there is an expected increase of 75,000 outpatient appointments in 2010 and that each appointment earns 120 euros, this represents an estimated gain of 3,000,000 euros/year. The benefit is indirect. The system provides more precise clinical information and better information management which enable more effective measures to reduce costs and negotiate contracts. Interestingly, although the time required for a first consultation did not decline because of the need to enter data into the system, significant gains in time for second and third consultations were achieved because the essential information is already available in the system. The reduction in the number of analyses stems from the following. In cases where a patient has recently been seen by another doctor, in the emergency room, on consultation of the patient’s clinical record, the doctor may decide not to order a specific clinical analysis because the patient had done one recently, and no different results from those on file would be expected. The reduction in personnel in the Clinical Records Service arises from the fact that the clinical records and other documents related to them can be held in digital format, which means that fewer staff are needed to look after patients’ records. The task of the Records personnel is to collate and organize patients’ clinical records, file them, retrieve them, and send them to the relevant service upon request. Currently 25 people are employed in the Records Service. It is predicted that by implementing Alert® pfh the number of personnel can be reduced to 15. Given that the annual cost of a Records employee is approximately 21,000 euros, reducing the staff by 10 employees entails an estimated saving of around 210,000 euros per year. In addition to the financial gains obtained directly by a reduction in costs or growth in income, the Alert® pfh system contributes considerably to improvements in the quality of service provided to patients, and it has a positive impact on the work of the health professionals. Improved quality of service is reflected in shorter patient waiting times and greater confidentiality and structuration of medical information. The system also enables streamlining the tasks of the health workers, improving their working conditions, and making additional relevant information available to aid administrative and clinical management of the hospital. Nevertheless, although there is evidence for these gains, and although they are important, it is not easy to quantify them from a financial perspective. For example, it is not possible to place a financial value on the fact that using the system could contribute to saving a person’s life despite the undisputable relevance of the fact.
5. Conclusion The benefit management approach applied to investment in systems and technology proved useful to study the case of the implementation of Alert® pfh software in the Espírito Santo
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Hospital. Since a large number of business benefits were identified, it was necessary to classify the benefits into two levels and include only macro-benefits in the Benefit Dependence Network. As far as results are concerned, implementation of the system brought several significant organization benefits to the hospital. The macro-benefits include greater precision in diagnoses and clinical prescriptions; reduction in costs for tests and clinical analyses; greater systematicity in information for management purposes; reduced personnel costs; reductions in costs for facilities, equipment and material supplies; improved service for patients; improved working conditions for health workers; and the capacity to increase the volume of activity, especially in outpatient appointments, with no extra expenditure. The contribution of Alert® pfh to case processing at the hospital in conjunction with the Government’s restructuration of the health services is apparent in the significant increase in volume of outpatient appointments. The hospital was able to cope with a rise in outpatient appointments from 125,000 in 2006 before the system implementation, to 200,000 in 2010, incurring no additional costs. The impact of the system from
a purely financial perspective has been valued at around 3.8 million euros from 2010 onwards. References Angst, C., & Agarwal, R. (2009). Adoption of electronic health records in the presence of privacy concerns: The elaboration likelihood model and individual persuasion. MIS Quarterly, 33(2), 339–370. Gartner Group. (2010). Press release of 21st January, 2010. Han, W., & Huang, S. (2007). An empirical analysis of risk components and performance on software projects. The Journal of Systems and Software, 80, 42–50. Pan, G., Hackney, R., & Shan, P. (2008). Information Systems implementation failure: Insights from prism. International Journal of Information Management, 28, 259–269. Peppard, J., Ward, J., & Daniel, E. (2007). Managing the realization of business benefits from IT investments. MIS Quarterly Executive, 6(1), 1–11. Wager, K., Lee, F., & Glaser, J. (2009). Health care information systems—A practical approach for health care management (2nd ed.). San Francisco: John Wiley & Sons/Jossey-Bass. Ward, J., & Daniel, E. (2006). Benefits management: Delivering value from IS & IT investments. Chichester: Wiley. Yin, R. (2002). Case study research: Design and methods (3rd ed.). Thousand Oaks: Sage.
Contents lists available at SciVerse ScienceDirect
International Journal of Information Management journal homepage: www.elsevier.com/locate/ijinfomgt
Case study
Information and communication technology adoption for business benefits: A case analysis of an integrated paperless system Mário Caldeira a,∗ , António Serrano b , Rui Quaresma b , Cristiane Pedron a , Mário Romão c a b c
ISEG – Technical University of Lisbon, Lisbon, Portugal Évora University, Portugal ISCTE, Portugal
a r t i c l e
i n f o
Article history: Available online 14 January 2012 Keywords: Health care information systems Benefits management Paperless systems
a b s t r a c t This case study analyses the benefits of implementing a paperless software solution (Alert® pfh–Alert Paperfree Hospital, developed by Alert Life Sciences Computing) in a Portuguese Hospital, the Espírito Santo Hospital, in the city of Évora. Alert® pfh is a complete hospital clinical information system with real time clinical information input. It was implemented in emergency medical services, inpatient and outpatient services, and operating room services. Data were collected between 2006 and 2011 prior to, during and after the system’s implementation. The case analysis demonstrates that paperless software systems have a significant potential when applied in healthcare organization services. Besides financial benefits, other important organizational features were identified, namely higher levels of patient and professional satisfaction; an increase in efficiency in hospital operations; improvement in the quality of information for management decision-making; and a reduction in medical errors. Lessons learned are noted and conclusions drawn for both theoretical and practical ICT benefits analysis. © 2011 Elsevier Ltd. All rights reserved.
1. Introduction Investments in information technology and communication systems (ICT) have been growing considerably. According to Gartner Group (2010), the investment ICT worldwide for 2010 is 3215.7 billion USD. However, the academic literature frequently claims that the level of success with adoption is far from satisfactory. A high percentage of ICT implementation projects fail significantly in at least one of the following issues: completion time; falling within the budget; or fulfilling all business requirements (Han & Huang, 2007; Pan, Hackney, & Shan, 2008). When organizations invest in ICT they expect to improve their efficiency and effectiveness, and to enable business benefits. A proper analysis of business benefits from such investments must go far beyond the financial perspective, especially in health care organizations, where this research was conducted. Nowadays, because ICT has an important role in healthcare, many hospitals and clinical organizations are deeply dependent on these systems for electronic health records, computer assisted triage, electronic prescription, computer provider order entry, or telemedicine (Wager, Lee, & Glaser, 2009).
∗ Corresponding author. Tel.: +351 966217788. E-mail addresses: [email protected] (M. Caldeira), [email protected] (A. Serrano), [email protected] (R. Quaresma), [email protected] (C. Pedron), [email protected] (M. Romão). 0268-4012/$ – see front matter © 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijinfomgt.2011.12.005
This case study analyses the business benefits of implementing a paperless software solution (Alert® pfh) between 2007 and 2011 in the Espírito Santo Hospital in the city of Évora, in the south of Portugal. Alert® pfh is an integrated software system that was developed by Alert Life Sciences Computing, a Portuguese software house whose turnover was 47 million euros in 2010. This software house is dedicated to developing and maintaining health care information systems. The Espírito Santo Hospital in Évora serves a population of around 174,000 inhabitants. In 2008 the hospital had 350 beds. It held 158,000 outpatient appointments in 2008, 175,000 in 2009, and 200,000 in 2010. In 2010, it also had 77,000 emergency episodes, 8921 surgeries and 1.8 million clinical analysis and therapy acts. The hospital implemented Alert® pfh which system helped to manage all the clinical areas of the hospital: outpatients, emergency episodes, inpatients, and operations room. The clinical system is also integrated with an Enterprise Resource Planning system of the hospital, which is implemented using Microsoft Navision and is used to manage administrative processes and some other clinical software like PACS (Picture Archiving and Communication Systems). Alert® pfh also provides a data warehouse that allows analysis of the healthcare services provided to each patient, a process performance analysis and a cost analysis. Implementing ICT in organizations often results in significant situations of resistance to change and Hospitals are complex organizations, with many stakeholders. On the other hand, these systems are not merely technological artifacts, they include an
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Identify and structure benefits
Potential for further benefits
Review and evaluate results
Plan benefits realization
Execute benefits plan
Fig. 1. The benefits management process. (source: Ward & Daniel, 2006).
organizational and political dimension because they alter the work routines and established power relations and interests within the organization. A system such as Alert® pfh is obviously no exception. Assessing the business benefits should not be a one-off task carried out in an initial phase of the implementation. Assessing the benefits is an on-going process because some benefits may not be immediate and will only appear at a later stage when the system has been fully integrated into the running of the organization by all of its users. 2. Case study approach
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completed. Quantifiable benefits provide sufficient evidence of how much improvement should result from the implementation of the new system. In financial benefits, a financial value can be calculated. The benefits realization plan consists of a set of changes that are essential for attainment of the benefits. It includes the time when benefits should be attained and the resources needed to implement benefits management. It is important that project management should also be accomplished by change management in order to achieve organizational benefits. This is in fact what happened in the case of Alert® pfh in the Hospital. The management plan must include the most appropriate measures and mechanisms to control benefits realization. Monitoring progress against the activities and deliverables of the business benefits plan is important. Benefits do not occur on the first day the new system starts operating; some benefits require time before they are attained. Since it is difficult to predict all the benefits of a system in advance, further benefits may be identified during its implementation. A Benefits Dependence Network is an important tool that links information technology investment objectives and the required benefits to business changes (i.e. the ways necessary to deliver those benefits) and the information technology capabilities that enable those changes. 2.2. Data collection Data were collected between 2006 and 2011, covering periods before, during and after the implementation of Alert® pfh. The following techniques for data collection were used: • • • •
Semi-structured interviews; Real-time quantitative data in the emergency services; Participant observation; and Document analysis.
2.1. Benefits management Benefits management is a process of organizing and managing ICT (Peppard, Ward, & Daniel, 2007; Ward & Daniel, 2006). Its objective is to ensure that the potential benefits arising from the use of information technology in organizations are actually attained. The benefits management process is structured in five fundamental phases, illustrated in Fig. 1: The phase of identifying and structuring business benefits is probably the most complex phase in the whole process, and it is a critical one. In this phase, all potential benefits should be identified, classified according to their nature, and located in the organizational processes. According to this approach, a benefit is an advantage on behalf of a particular stakeholder or group of stakeholders (Ward & Daniel, 2006). Hence, reducing costs or improving financial results can be perceived as a benefit, as well as increasing customers’ satisfaction or improving employees’ working conditions. Each benefit must have an “owner” within the organization, someone responsible for its achievement. It is also important to determine whether a benefit can be measured in order to prove that it has occurred. Benefits must be structured in order to understand the potential effect of information technology in the organizational processes and measures must be developed for most benefits. Benefits can be classified as observable, measurable, quantifiable, or financial. Observable benefits are benefits where, on the basis of experience, an expert or a specific group of people uses agreed criteria to decide to what extent the benefits have been realized. Measurable benefits are those that are currently being measured, or appropriate measures can be implemented, but it is not possible to estimate within a reasonable degree of rigor, the future improvement of organizational processes when the changes are
The use of several techniques for data collection is recommended in the literature on case study research (for example, Yin, 2002). Thirty-nine semi-structured interviews were conducted with members of the board of directors, doctors, nurses, IT staff, and IT consultants. The interviews provide for a detailed perspective of the clinical and administrative processes of the hospital and potential benefits. One of the difficulties in identifying the business benefits was that the hospital lacked enough data on clinical process performance. For example, there were inadequate data on the average duration times of clinical appointments, detailed costs of patient treatments, among others. To overcome this, several times were measured before the system was implemented, particularly in the Emergency Room (Table 1). Table 2 shows the data on clinical analysis and therapy acts in the Emergency Room. Table 3 displays some patients’ duration times measured in the Emergency Room sample. The times are classified according to the different phases in the emergency room from being admitted, triage, and being seen to by the doctor to being discharged. Table 4 shows a breakdown of the waiting times for patients for each of the diagnostic and therapy acts in Emergency Room. Participant observation was carried out on several visits to the hospital, in particular to the Emergency Room and the services that work closely with Emergency Room. It included studying how data are collected in Emergency Room. In addition, the diverse documents related to the process of implementing Alert® pfh software were analyzed. Analyses of the observation visits and the documentation on the software and its implementation led to the identification of additional potential benefits that the introduction of Alert® pfh software could bring about. The visits also
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Table 1 Descriptive characteristics of the Emergency Room sample. 08:00–16:00 Number of patients in the sample Female patients Male patients Patients classified as “yellow” (Manchester screening) Patients classified as “green” (Manchester screening) Orthopedics surgery patients Specialty surgery patients Medicine surgery patients Age of youngest patient Age of the oldest patient
16:00–24:00 104
48 56 63 41 26 25 53
113 46.2% 53.8% 60.6% 39.4% 25.0% 24.0% 51.0%
68 45 65 48 25 34 54
60.2% 39.8% 57.5% 42.5% 22.1% 30.1% 47.8%
15 97
15 95
Table 2 Clinical analysis and therapy acts in Emergency Services. 08:00–16:00 Number of patients in the sample Therapy treatment Analyses Imaging CT scan Ultrasound Therapy treatment – twice or more Analyses – twice or more Imaging – two or more CT scan – two or more Ultrasound – two or more
104 44 37 46 5 0 4 1 0 0 0
16:00–24:00 113 43 43 46 6 0 3 3 2 0 0
42.3% 35.6% 44.2% 4.8% 0.0% 3.8% 1.0% 0.0% 0.0% 0.0%
38.1% 38.1% 40.7% 5.3% 0.0% 2.7% 2.7% 1.8% 0.0% 0.0%
Table 3 Time spent by patients in Emergency Room in hours and minutes. 08:00–16:00 All Number of patients in the sample 104 From admittance to discharge Shortest time 20 min Longest time 10 h 17 min Average time 2 h 25 min From triage to discharge 13 min Shortest time Longest time 10 h 7 min Average time 2 h 22 min From consultation with doctor to discharge Shortest time 1 min 9 h 52 min Longest time 1 h 54 min Average time From admittance to triage 0 min Shortest time 17 min Longest time 3 min Average time From triage to consultation with doctor 4 min Shortest time 1 h 56 min Longest time 27 min Average time
16:00–24:00 Yellow
Green
All
Yellow
Green
113 27 min 10 h 17 min 2 h 47 min
20 min 7 h 46 min 1 h 51 min
17 min 16 h 15 min 2 h 37 min
18 min 16 h 15 min 2 h 58 min
17 min 13 h 39 min 2 h 8 min
20 min 10 h 7 min 2 h 43 min
13 min 7 h 42 min 1 h 48 min
11 min 16 h 10 min 2 h 32 min
11 min 16 h 10 min 2 h 52 min
13 min 13 h 36 min 2 h 4 min
1 min 9 h 52 min 2 h 12 min
1 min 7 h 7 min 1 h 27 min
1 min 15 h 55 min 1 h 58 min
1 min 15 h 55 min 2 h 21 min
1 min 13 h 23 min 1 h 26 min
0 min 17 min 4 min
0 min 11 min 3 min
0 min 15 min 5 min
0 min 15 min 5 min
0 min 11 min 4 min
8 min 1 h 56 min 31 min
4 min 59 min 21 min
5 min 2 h 59 min 34 min
5 min 2 h 44 min 31 min
7 min 2 h 59 min 38 min
furnished information that was essential for an understanding of how the Emergency Room works, and this consequently influenced the planning and organization of the process for collecting data. Coordinating and following through the data collection process contributed to reinforcing the expectations of the benefits to be gained by the introduction of Alert® pfh. Use of the system is both significant and wide ranging. In addition to the doctors and nurses, ancillary staff also use it in their daily tasks. For example if a patient needs to be transported from one hospital unit to another, touch screen computers in the corridors enable the staff to keep a register of the patient’s movements.
3. Data analysis and discussion A total of 54 benefits were identified as resulting from the investment in the Alert® system. Some of the benefits noted in an early stage were later disregarded either because there was evidence lacking or the directors of the Hospital considered them to have had little impact. Neither the sources of nor the stakeholders associated with each benefit are given in order to maintain their anonymity. The benefits were grouped into “macro-benefits”, or rather first level benefits (MB1–MB7). These macro-benefits will later be featured in the
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Table 4 Waiting times for diagnostic or therapy acts for patients in Emergency Room in hours and minutes. 08:00–16:00 Number of patients in the sample Therapy Shortest time between request and use Longest time between request and use Average time between request and use Analyses Shortest time between request and nurse accompanying patient Longest time between request and nurse accompanying patient Average time between request and nurse accompanying patient Shortest time between sample taken and results Longest time between sample taken and results Average time between sample taken and results Imaging Shortest time between request and nurse accompanying patient Longest time between request and nurse accompanying patient Average time between request and nurse accompanying patient Shortest time between nurse accompanying patient and returning Longest time between nurse accompanying patient and returning Average time between nurse accompanying patient and returning
benefit dependence network. The benefits and macro-benefits (MB) identified as follows: MB1 – greater precision in diagnosis and clinical prescription: • Reduction in time and processing costs for Manchester Triage; • Reduction in number of patients who are reclassified by Manchester Triage system; • Reduction in radiation levels received by patient; • Faster and better justified clinical decision making; • Easier patient identification; • Integration and availability of patient’s clinical information. MB2 – reduction in costs for tests and clinical analyses: • Reduction in the costs for analyses ordered; • Reduction in the number of X-rays ordered; • Reduction in the number of CT scans ordered: • Reduction in the number of ultrasounds ordered. MB3 – greater systematicity in information for management purposes: • Computation of the real cost per patient treated; • Real time processing and emission of invoices in Emergency Room. MB4 – reduction in personnel costs: • Reduction of costs for medical assistants; • Reduction of personnel costs in Clinical Records Service; • Reduction of costs related to studies on the Emergency Room functioning; • Reduction in costs for administrative personnel in laboratories; • Reduction in costs for administrative personnel in Imaging; • Reduction in costs for overtime in Emergency Room (doctors); • Reduction in personnel costs for the Printing Service. MB5 – reduction in costs for facilities, equipment and material supplies: • Reduction in administrative costs for data collection; • Reduction in paper consumption; • Reduction in costs for office supplies; • Reduction in costs associated with printing imaging exams; • Reduction in use of identification tags; • Reduction in costs linked to printing identification tags; • Elimination of the use of printed/photocopied forms; • Increase in service fees collected on patient discharge; • Reduction in space needed to store clinical records; • Reduction in space needed to store office stationery; • Elimination of the need to transfer clinical records between Emergency Room and the Clinical Records Service and vice versa. MB6 – improved patient service:
16:00–24:00
104
113
0 57 6
0 min 2 h 32 min 15 min
1 2 h 18 min 21 min 37 min 3 h 14 min 1 h 15 min
0 min 33 min 8 min 18 min 2 h 50 min 1 h 15 min
0 min 2 h 11 min 12 min 3 min 2 h 47 min 55 min
0 min 51 min 8 min 9 min 1 h 42 min 34 min
• • • • • • • • • • • •
Reduction in patient waiting time for triage; Reduction in patient waiting time for their first call; Reduction in patient waiting time for therapy treatment; Reduction in patient waiting time for analyses; Reduction in patient waiting time for X-rays; Reduction in patient waiting time for CT scans; Reduction in patient waiting time for ultrasounds; Reduction in patient waiting time for results of analyses; Reduction in patient waiting time for X-ray results; Reduction in patient waiting time for CT scan results; Reduction in patient waiting time for ultrasound results; Reduction in patient waiting time while patient’s clinical records are brought from Clinical Records Service; • Reduction in patient’s time spent at the hospital; • Increase in confidentiality and security of personal data and health data in clinical files; • Improvement in service for patient’s family; MB7 – improved working conditions for professional health workers: • Elimination of difficulties in reading prescriptions for medicine/therapy; • Elimination of difficulties in reading orders for analyses; • Elimination of difficulties in reading orders for X-rays; • Elimination of difficulties in reading orders for CT scans; • Elimination of difficulties in reading orders for ultrasounds; • Reduction in environmental impact from X-rays; • Improved working conditions; • Improvement in quality of doctors’ files/consultation with doctor; • Reduction in administrative work carried out by Imaging technicians; MB8 – increase in activity–outpatient appointments: • Coping with the rise in outpatient appointments.
Table 5 shows how the business benefits were structured. The macro-benefits were included in the Benefit Dependency Network, presented in Fig. 2. Implementing the Alert® pfh system in the Hospital brought considerable benefits. Some of these benefits are immediately apparent from a financial perspective. Other benefits do not show a clear financial value, and have been classed as measurable, quantifiable or observable in accordance with the methodology adopted. There are still others that are potentially financial, but it is not yet possible to identify or estimate their monetary value accurately. Nonetheless, the benefits deriving from implementing
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Table 5 Structure of business benefits enacted. ID
Benefit
Macrobenefit type
Measure
Current value
Expected value
Benefit typea
Impact
B1
Reduction in processing time and costs for Manchester Triage System Reduction in costs for analyses ordered
Bm1
Average time and cost to process a case
6 min 24 s (D 2/case)
3 min 12 s (D 1/case)
F
D 1800/year
Bm2
Number of analyses ordered and the respective value (sample: 6 days) Number of X-rays ordered (sample: 6 days)
42 analyses (8:00–16:00) 47 analyses (16:00–00:00) 52 X-rays (8:00–16:00) 49 X-rays (16:00–24:00) 5 CT scans (8:00–16:00) CT scans (16:00–00:00) 5 ultrasounds (8:00–16:00) 1 ultrasounds (16:00–00:00) D 30,000/year
Reduction 10%
F
D 300,000/year
Reduction 5%
Q
No significant financial gain
Reduction 5%
F
D 150,000/year
Reduction 5%
F
D 50,000/year
D 20,000/year
F
D 10,000/year
...
...
...
B2
B3
Reduction in number of X-rays ordered
Bm2
B4
Reduction in number of CT scans ordered
Bm2
Number of CT scans ordered and value (sample: 6 days)
B5
Reduction in number of ultrasounds ordered
Bm2
Number of ultrasounds ordered (sample: 6 days)
B6
Reduction in administrative costs for data collection ...
Bm5
Administrative costs for data collection (paper, etc.)
...
...
... a
...
Benefit type: F, financial; Q, quantifiable; M, measurable; O, observable.
Information Technology
T1. Software Alert.pfh
Change factors
F1. Prepare change management for adoption of T1
Organizational
change
M1. New identification rules and control for those involved in processes
Benefíits (main)
T3. Network infrastructure
T4. PCs, printers & barcode readers.
T5. Parameters: Backoffice, MyAlert . T6. Interfaces with Sonho, Apolo, PACS,.
F5. Technical training for incorporating Alert system
F2. Training for users of the Alert system
M3. Implementation of information security procedures
M2. Alteration of administrative and clinical files
Reduction in costs for clinical tests and analyses (MB2) Greater systematicity in information for management purposes (MB3) Reduction in personnel costs (MB4)
F3.Redesign organizational processes
F4.Define motivation mechanisms for users
M4. Improvement of functional content
M5. Need for more data collection
Reduction in costs for facilities, equipment and material supplies (MB5)
Improved working conditions (MB7)
Increase in activity (MB8)
Fig. 2. The Benefits Dependency Network.
Business Drivers External:
Greater precision in diagnoses and clinical prescriptions (MB1)
Better patient service (MB6) T2. Data center
Objectives
Improve patient service (O1)
Current economic recession implies budget restrictions (D2) HESE transfer to EPE (D1)
Provide efficient health care (O3)
Improve financial results (O4)
Availability on the market of sophisticated IS/IT for hospital support (D3) Population’s growing expectations for quality of health care services (D4) --Internal: Need for HESE to improve performance (D6) Administrative Council open to IS/IT. (D5)
Increase professional satisfaction (O2)
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ALERT makes it possible to estimate an annual reduction in costs or gains achieved of 3,869,896 euros. In the interviews, the directors noted that the most relevant benefit brought about by Alert® pfh was the fact that the system – electronic health records – made it possible for doctors in the Emergency Room to access a patient’ clinical history, something that they were unable to do previously. The fact that doctors could do this decreased committing mistakes in a diagnosis. Other relevant non-financial benefits included the following benefits: • Reduction in the number of X-rays and radiation levels received by patients (5%); • Length of the triage process (from 6.5 min before the system to 1.96 min using the system); • Reduction in time from the triage to first observation (from 33 min before the system to 27 min after the system); • Reduction in the time from prescription to medical administration (from 11 min before the system to 1.68 min after the system); • Reduction in waiting time for X rays results (44.5 min before the system to 23.5 min after the system); • Reduction in waiting time for CT-scan results (1 h and 16 min before the system to 31 min after the system); • Increased confidentiality and protection of clinical data; • Better service for patient and family members; • More precise information for management decision-making. In order that the above-mentioned benefits might be attained, appropriate and effective management of the process of organizational change to a digital system is essential. During the process both the system supplier and the Hospital directors were clearly concerned about this aspect, so it is expected that the organizational changeover will not constitute an obstacle to realizing the afore-mentioned benefits in the medium/long term. Increasing the protection and confidentiality of patient clinical data is an important benefit. Electronic health records constitute a significant technological advance in the way medical information is stored, transmitted, and processed by the multiple parties involved in health care delivery. However, in spite of the anticipated value potential of this technology, there is widespread concern that privacy issues may impede its diffusion (Angst & Agarwal, 2009). According to Portuguese law, the personal and health data that are collected in hospitals and are essential for the patient’s treatment entail both rights and responsibilities for the patient, the professional who collects the data, and the Administrative Council of the hospital. While the patient has a right to privacy with regard to his/her information, the responsibility to guarantee such privacy lies with the health professional who collects the data. The introduction of Alert® pfh helps to ensure greater protection of a patient’s personal data and health records because access to electronic data can easier be restricted to authorized people only. This restricted access applies to both personal data and health records, including information registered in Alert® pfh on prior occasions. Before the use of Alert it was possible to find personal clinical data, relatively unprotected, in many places within the hospital, including corridors. Since the system registers in the data warehouse costs and times of organizational processes, it contributes to improve decisionmaking. For example, when a doctor calls a patient in an outpatient appointment, times are systematically registered, which makes it possible to analyze the duration of each outpatient appointment or clinical act, improving resource allocation and effectiveness of clinical processes. 4. Case analysis – lessons learned Despite the importance of significant financial savings, support for an increase in outpatient appointments constitutes an
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important gain for a hospital, which provides a public service. The Alert® pfh system was instrumental in enabling a significant increase in the number of outpatient appointments. Prior to implementation of the system, the number of outpatient appointments was 125,000/year. In 2009 the hospital had 150,000 outpatients and, in 2010, this number increased to 200,000. It should be noted that this increase in the number of outpatients was due not only to the ALERT system, but also to other factors, which include a regional reorganization of the health services. Nonetheless, the system played an important role. According to the Administrative Council, it would not be possible to increase the number of outpatient appointments with the same resources but without Alert® pfh. Analysis of the organizational processes suggests that about one third of the increase in outpatient appointments are due to the use of Alert® pfh. Given that there is an expected increase of 75,000 outpatient appointments in 2010 and that each appointment earns 120 euros, this represents an estimated gain of 3,000,000 euros/year. The benefit is indirect. The system provides more precise clinical information and better information management which enable more effective measures to reduce costs and negotiate contracts. Interestingly, although the time required for a first consultation did not decline because of the need to enter data into the system, significant gains in time for second and third consultations were achieved because the essential information is already available in the system. The reduction in the number of analyses stems from the following. In cases where a patient has recently been seen by another doctor, in the emergency room, on consultation of the patient’s clinical record, the doctor may decide not to order a specific clinical analysis because the patient had done one recently, and no different results from those on file would be expected. The reduction in personnel in the Clinical Records Service arises from the fact that the clinical records and other documents related to them can be held in digital format, which means that fewer staff are needed to look after patients’ records. The task of the Records personnel is to collate and organize patients’ clinical records, file them, retrieve them, and send them to the relevant service upon request. Currently 25 people are employed in the Records Service. It is predicted that by implementing Alert® pfh the number of personnel can be reduced to 15. Given that the annual cost of a Records employee is approximately 21,000 euros, reducing the staff by 10 employees entails an estimated saving of around 210,000 euros per year. In addition to the financial gains obtained directly by a reduction in costs or growth in income, the Alert® pfh system contributes considerably to improvements in the quality of service provided to patients, and it has a positive impact on the work of the health professionals. Improved quality of service is reflected in shorter patient waiting times and greater confidentiality and structuration of medical information. The system also enables streamlining the tasks of the health workers, improving their working conditions, and making additional relevant information available to aid administrative and clinical management of the hospital. Nevertheless, although there is evidence for these gains, and although they are important, it is not easy to quantify them from a financial perspective. For example, it is not possible to place a financial value on the fact that using the system could contribute to saving a person’s life despite the undisputable relevance of the fact.
5. Conclusion The benefit management approach applied to investment in systems and technology proved useful to study the case of the implementation of Alert® pfh software in the Espírito Santo
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Hospital. Since a large number of business benefits were identified, it was necessary to classify the benefits into two levels and include only macro-benefits in the Benefit Dependence Network. As far as results are concerned, implementation of the system brought several significant organization benefits to the hospital. The macro-benefits include greater precision in diagnoses and clinical prescriptions; reduction in costs for tests and clinical analyses; greater systematicity in information for management purposes; reduced personnel costs; reductions in costs for facilities, equipment and material supplies; improved service for patients; improved working conditions for health workers; and the capacity to increase the volume of activity, especially in outpatient appointments, with no extra expenditure. The contribution of Alert® pfh to case processing at the hospital in conjunction with the Government’s restructuration of the health services is apparent in the significant increase in volume of outpatient appointments. The hospital was able to cope with a rise in outpatient appointments from 125,000 in 2006 before the system implementation, to 200,000 in 2010, incurring no additional costs. The impact of the system from
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