Using GETS for Medical Technology Management: A drill down case study

Using GETS for Medical Technology Management: A drill down case study A. C. B. Eboli 1, E. T. Silva 1, E. T. Costa 1,2, J. W. M. Bassani 1,2 1 Universidade Estadual de Campinas UNICAMP / Centro de Engenharia Biomédica CEB, Campinas, SP, Brasil 2 Universidade Estadual de Campinas / Departamento de Engenharia Biomédica Faculdade de Engenharia Elétrica e de Computação DEB/FEEC/UNICAMP, Campinas, SP, Brasil Abstract This paper presents the application of software for medical technology management in a particular case study. It is outlined the structure of the software and how it can provide proper information on a given technology (Intensive Care Unit Ventilators) and help the Clinical Engineering Team to detect problems and find solutions to minimize the downtime of such life support equipment. We present the analysis of the occurrence of maintenance calls of 125 ventilators with different ages (0-5, 5-10, 10-15, >15 years). We have found that, although expecting that older equipment should need more servicing, brand new ventilators presented an increasing number of calls even though when in the warranty period requiring manufacturers staff visiting and/or taking the equipment to their facilities in order to solve the problems. This have impacted on the execution time and overall CE staff performance that, with GETS data information in hand, was able to look for the best solution through negotiation with manufacturers technical staff. Although data presented is related to ventilators, it became clear that GETS is an unquestionable tool for proper technology management in Brazilian hospitals. It is expected that it be freely distributed for public hospitals and allow regulatory agencies and government organs to perform public policies based on real data coming from hospitals and clinical units. Keywords clinical engineering, health institutes, management of medical technology, web-based software. and standardization of nomenclature and of the function of equipment. But this is still not enough. It is necessary to know the state of the technology and establish an unbiased evaluation strategy. It is considered that the feedback obtained by health care professionals, manufacturers, or even outsourced maintenance teams (whose main objective is intended to earn profits) is not unbiased. So the best way to approach this problem is to obtain quantitative data on the behavior (e.g. performance) of the technology, without forgetting its complex interaction with users and maintenance staff and its constructive aspects [2]. The Biomedical Engineering Center (CEB) has extensive experience in managing the entire technology park of UNICAMP s Health Area. Based on this experience, and aiming at studying the best generic approach to the problem of managing the technology in use on Brazilian s HCC, it was developed a method for managing the technology park based on CE information, generated from the equipment acquisition process, its installation, preventive and corrective maintenance, up to its deactivation. In order to apply this method in the context of CE in our country, the project whose structure is shown in Fig. 1 relies on the construction of a National Laboratory for Management of Health Technology (LNGTS), which is being funded by the Brazilian Ministry of Health (MS) with investment of resources via FINEP. I. INTRODUCTION Clinical Engineering (CE) Teams in Brazil, although in continuous grow in recent years, is still insufficient to attend the number of Health Care Centers (HCC), and poorly organized in various regions of the country, partly due to the lack of proper tools and standardization to assist in managing the technology park [1]. The government, that finances the acquisition and distribution of many of the medical technologies to HCCs, tries to control their location and functionality, but faces enormous difficulties to get information about their operating conditions in HCCs. This has reflexes, making it difficult to define the amount of resources to invest in maintenance. Brazil and probably others countries, has not management control of the installed technology, since not even a good inventory in order to extract quantitative information is available in most hospitals [2]. To know what really exists is important and requires technical knowledge Fig. 1: Data Network of Clinical Engineering, illustrating the spread of GETS system in several Health Centers (HCC) and Clinical Engineering Centers (NEC) connected to the network controlled by the Information Center of Technology in Health (CITS). CAISM, HC and HEMO are university hospitals at UNICAMP. 1 1 All abbreviations in acronyms used in figures, tables and text were kept in Portuguese since it is the natural output of GETS.

As a fundamental part of LNGTS, a web-based software called GETS was developed, which is responsible for gathering information from the several agents that act in the system in an orderly way. This software is based on previously defined concepts and standardization [4] allowing CE to grow in the HCCs in a coordinated way and with appropriate tools. In this paper we present GETS system application to the study of ventilators maintenance profile in a case study at our institution health care area. LNGTS and GETS II. METHODOLOGY The organizational structure of LNGTS with GETS allows the interaction of the Information Center of Technology in Health (CITS) with Clinical Engineering Centers (NECs) and with institutions of strategic importance such as regulatory agencies (e.g. ANVISA), Ministry of Health (MS) and the Brazilian Public Health System (SUS), besides the possible interaction with Institutions involved in Research and Development (P&D) and with the business sector. In order to form this large data network and the CITS operate in a robust way, it is part of the project some standardization [4] such as: equipment nomenclature, maintenance flows, information on actions taken, and others which are critical to maintain the database updated over the years. Any standardization performed assumes that the system needs to be replicable, robust and usable via web to conquer the scope desired and the resulting social impact. The system shall be distributed freely to public HCCs, providing conditions to support its implementation and for continuous education of technical staff in order to disseminate common procedures in health technology management. Each NEC must contain a minimum structure which includes a home team to monitor all processes involving the equipment life cycle. CITS, based at CEB/UNICAMP, that is a Center with extensive experience in CE, will supply registering information about the technology and secure that the standardizations is maintained and updated all over the years to the NECs in addition to gradually provide training courses to teach people from institutions or companies interested in create a NEC, thus enlarging the CE horizons in the country. A NEC can also operate in standalone mode. The set of information about cost, failure, age, time and repair profile, generated in a non-bureaucratic form, based on multiple feedbacks from actual CE data (specification, purchase, installation, maintenance, decommissioning) allows the evaluation of the applied technology in an uniform, robust and practical way. Agencies and organs such as MS and ANVISA can act more effectively on the control of the technology, with proper information on its standard local use and overall performance. In practical terms, LNGTS will allow to evaluate, for example, if a given equipment with unsatisfactory performance in a specific NEC maintains the same profile in others NECs, and similarly the technical assistance and the CE as a whole. In addition to standardizations, the other important point of GETS is that each intervention in a given equipment (throughout its life cycle) is recorded in the system as a trajectory (also standardized), composed by micro-processes involved in the Service Orders (OS) flow (Fig. 2) [5]. In the trajectory highlighted in the figure, the OS is open (SOS), referred to a maintenance group (AE), then assigned to the technician (EE), who executes and ends the OS (OSP) and later the OS is closed after the user accepts the repaired equipment (CO). Each transition composing the trajectory implies that the person responsible for a particular action changes and is obliged to feed GETS database with all OS information. More details are shown in [5]. The analysis of trajectories allows seeing the behavior of the technology, maintenance service profile, cost and time spent on interventions [4] [5]. The transitions analysis allows the estimation of cost and time delay of each micro-process since it is possible to assign a standard operating cost to the micro-processes [5]. T1: SOS-AE-EE-OSP-CO T2: SOS-AE-EE-AE-OSP- CO T3:...AV... T4:...AM...... Time SOS-AE EE-OSP-CO Transition Activity Cost Technical and administrative Information Fig. 2: Diagram of transitions generated from GETS, illustrating that when micro-processes are activated (using a screen with input and output data), they form transitions that construct the OS trajectories, according to the pathway of each intervention (acquisition, installation, corrective maintenance, preventive, etc.) The highlighted states and transitions form the simplest trajectory. [5]

GETS is operational in CEB/UNICAMP since March 2010, making it possible to monitor the work developed by the CEB s CE for UNICAMP Health Area. Two aspects are identified quite clearly with GETS: first the evaluation of teams production and performance in meeting the demands of HCCs, that allows identify the volumes, delays, and services profiles; and secondly the monitoring and evaluation of technologies used, and their behavior. The first set of indicators obtained from GETS refers to the amount of OS s request, executed, pendent, analyzed by any of the available filters or a set of them, such as period, maintenance group, OS class, HCC, department, equipment type, etc. The second set of indicators refers to the OS s execution time (ET). ET assessment may be by trajectory (from OS request to its closing), or by transition (time of each individual micro-process). It is always interesting to calculate the average or median of these filtered values for the NEC as a whole, and then compare them with the overall values. Regular tests will help to create a profile of expected behavior in each case, and when an indicator come out of expected range one should investigate the reasons for that (a drill down study). The procedure for finding information from GETS does not consider irrelevant the views of the teams involved. In fact, the warnings offered by the system, from the initial search and drill-downs, are key points in the search for answers to possible problems and help the CE team to interact with health administrators and clinical staff as well as with the business sector. III. RESULTS In making the analysis of data at the end of 2010, one of several indicators assessed was the rating of the equipment that demanded more service calls (MC), external service from manufacturers or their representative (SE) and total costs with respect to the maintenance costs done by CEB CE team. From this set, a class of equipment was highlighted by being present in the top five of all those lists: the intensive care ventilators, called here UTI ventilators. Although these devices represent only 1.1% of the nearly 12,000 equipments served by CEB, they represented in the period analyzed the 5 th type of equipment with higher call for MC, the 2 nd greatest demand and cost for SE, the 4 th in cost for parts and pieces and the 2 nd largest volume of technical hours worked. Ventilator is a life-support equipment and its maintenance must always be safe and fast, and due to the fact that there are virtually no spare of such equipment in the hospital, we decided to use GETS database on ventilators as a case study. From this initial observation, we attempted to trace the age profile of these devices: as the ventilator gets older there is evidence of significant increase in the number of maintenance calls [6]. The results on age have shown an unexpected behavior (Fig. 3). The UTI ventilators are distributed almost evenly in the age groups 0-5 years, 5-10, 10-15, >15 years (29%, 23%, 21% e 27%), and also the MC OS s demand was almost similarly distributed by age group (26%, 27%, 20%, 27%). There is evidence that the equipments considered new have also shown a high number of failures. Fig. 3: Analysis of the distribution of UTI ventilators by age group, with the quantity of equipment, amount of corrective maintenance OS s (MC) and the quantity of equipment without corrective maintenance (without MC) in the period studied. (# quantity of) Based on this information, seeking more precise answers to the profile of these equipments, it was necessary to survey other indicators available on GETS in order to understand why such a profile was so different from the expected. It was observed that 30.4% of the equipment showed no failure during the period studied, whereas 69.6% that present MC had execution time (ET) of six days 2, with an average of two OS s per device (and there was also a case with up to 5 OS s for the same equipment). Table I summarizes some of the indicators found with GETS relative to ventilators. TABLE I PROFILE OF UTI VENTILATORS EXTRACTED FROM GETS INDICATORS. Indicator 2 All times are calculated by the median, in days. Occurrence % ET* (median in days) Attendance and repair in HCC 45.8 % 5 Attendance and repair in NEC 54.2 % 7 OS s with simplest trajectory (SOS-AE-EE- OSP-CO) 32.4 % 2 OS s with transport of equipment (AV) 28.3 % 11 OS s with changing of execution group (AE-AE) 14.5 % OS s dependent of user liberate equipment (ADE) 2.9 % 71 OS s with acquisition of spare parts (AM) 9.8 % 31 OS s with external servicing (SE) 17.3 % 38 SE with equipment in warranty 56.7 % 23 SE with call of manufacturer s technical staff (VT) 50 % 17 SE with equipment sent to manufacturer site for repair (CE) 50 % 52 * ET is the execution time.

For CEB CE team, it is expected that more than half of the OS s follow the simplest trajectory (SOS-AE-EE-OSP- CO), which indicates a profile of fast servicing and low cost (no need for additional material or SE). However this was not observed in the indicators of the UTI ventilators (Table I): only about a third followed this trajectory and with twice the expected time (2 days). Almost a third of the OSs have used transport of equipment between HCC and NEC (identified by micro-process AV), which involved more time and operational cost. In the OSs with slower trajectories, 2.9% of them depended on the users to allow access to the equipment for servicing (this means that, possibly, the equipment was used in procedures that did not need immediate intervention of our technicians or could wait until a solution for a specific problem arises without compromising its use in patients). The availability of the equipment took 71 days (median), which shifts the time negatively, showing the scarcity of equipment in the HCC. Another important information of the slower trajectories is that 9.8% of them have shown the need for materials acquisition (AM), taking up to 31 days for this task. External Service occurred in 17.3% of the trajectories with a median time of 38 days (time only for SE, not including the whole OS time), and 56.7% of these were executed while the equipment was in warranty (median of 23 days for complete attendance), and the other 43.3% not in warranty at a median cost of R$1,507.07. A half of SE occurred with visit from manufacturer s technical staff (VT) and it has taken 17 days for that external service to be complete. The other half of SE occurred with external repairs with transporting of the equipment to the technical assistance of the manufacturer, in 52 days. Comparing these values with the median of whole CEB trajectories which is 7.53% with SE, the ventilators OS s showed a profile composed of very large execution times with many delays and external services. Observing that a substantial part of them was corrective maintenance on warranty and technical visit from manufacturer staff, it was expected a shorter time to solve the problems but it was not the actual situation. In addition to the indicators in Table I, the ventilators OSs have used 7.13% of the general budget for CEB maintenance by CE staff, being 11.53% of the spending on SE and 4.71% of the spending in AM. Considering that the warranty repairs should not have costs, this profile of high costs attributed to new equipments is another indicator also considered alarming. This profile obtained from numbers and indicators can also be seen in the graphical analysis of the trajectories, shown in Fig. 4. It is expected that a group of equipment presents a few set of trajectories as an accepted behavioral profile, concentrating the majority of the OSs (80-90%) in this narrow set of trajectories (paths 5-10). Unfortunately, this is not observed in Fig. 4 for UTI ventilators, where the high dispersion in the profile indicates the complexity of the OSs attendance directly affecting the overall performance. Fig. 4 shows that for the ventilators, five trajectories represent little more than 60% of the total OSs, but if we add five other trajectories we still do not reach 70% of the OSs (we expect 80-90% as seen before). So, as already seen with Table I data, the graphical analysis suggests a complex service, without a standard, slow and expensive to this category of equipment. Fig. 4: Analysis of UTI ventilators trajectories: five distinct trajectories concentrate only 61.4% of OSs, and if we add another five possible trajectories we still do not reach 70% of OSs. This shows a very complex behavior, negatively affecting overall performance of service. Therefore, it is noteworthy that some important indicators were higher than expected, as the amount of OSs with SE, the high rate of warranty repairs and the high number of calls for maintenance of new equipment (0-5 years) that, according to [6], should present less calls for maintenance. These results led us to individualize the study by ventilators manufacturer and to study the kind of defects found in the equipments. Just over 82% of the equipment are concentrated in five major manufacturers, representing nearly 95% of the OSs, distributed as shown on Table II. Maker TABLE II INFORMATION OF UTI VENTILADORES SEPARETED BY MANUFACTURER Amount of equipm ents Median age (years) % of all equipm ents Amount of MC % of MC #OS/ #EQ A 13 13.4 10.4% 24 13.9% 24/12 B 18 2.0 14.4% 41 23.7% 41/17 C 23 9.5 18.4% 20 11.6% 21/10 D 24 15.5 19.2% 42 24.3% 42/21 E 25 5.0 20.0% 37 21.4% 37/18 125 9.8 82.4% 172 94.8% 172/125 Another highlight was the high execution time when there was the need for external servicing, even in cases of visits of manufacturers technical staff and when the equipments were in warranty, as shown in Table III. For each of the makers studied were extracted the information of the defect found in their equipments. The main results were: maker A 46% of defects on the command keyboard; maker B 44% of defects were on the

inner valves; maker C 35% of defects in the batteries; makers D and E number of occurrence were not concentrated on the same defects with slight concentration on structural parts of casters and arms. TABLE III ANALYSIS OF INDICATORS OF SERVICES IN UTI VENTILATORS Makers Simple pathway Time* OS without SE Time* # SE As explained, GETS system provides indicators for many analysis at various levels, and can be detailed up to a certain limit and, if necessary, discussion by the technical staff involved in the equipment maintenance to find ways for identifying particular problems and define the final solution. With the information obtained from GETS system, it was necessary to question the technical staff of CEB CE team servicing these equipments, especially those of manufacturer B, to understand the reasons for such a prestigious maker in the market have equipments presenting bad performance for the clinical staff, contradicting the expectations. Apparently, the problem was very fragile input valve regulation which would easily be damaged under typical gas pipeline pressure oscillations common in most Brazilian hospitals. IV. DISCUSSION SE Time* SE Times min/max A 8.3% 6 14 / 4 2 CE 81 65 / 97 14 VT 11 0 / 51 B 31.7% 2 12 / 3 1 CE 157 157 C 35.0% 1 17 / 6 3 CE 52 5 / 56 D 45.2% 3 8 / 4 4 CE 41 29 / 62 E 32.4% 1 15 / 4 4 CE 48 5 / 55 General 32.4% 2 CEB * Times were calculated by the median of each OS s time, expressed in days. # quantity of SE GETS system allows the realization of several studies on the HCCs installed medical technology, from monitoring of team performance, the HCC s, the HCC s sectors, the types of equipment, and even makers and models of equipment. In the case presented here, UTI ventilators, the data pointed to indicators out of the expected range on stopping times, external services calls, costs, and recurrence of defects. As the indicators are analyzed, GETS allows individualization of numbers until it reaches the particular set of data that are leading the indicators out of the expected range. So, together with information of maintenance technical team, it is possible to identify the reasons and act looking for the solution of the problem. Sometimes the solution is not straightforward, and could indicate training needs, equipment manufacturing defects, recurrent operational errors, etc. However, in this particular case study, a very interesting conclusion was obtained: new and sophisticated equipments, although having great precision and more capabilities than older ones, may present an increase in the rate of failure, in demand for outsourcing services and in costs. That is because several of these devices are designed and manufactured based on the reality of hospitals of countries rather different than that of Brazilian HCCs. They possibly have extreme sensitivity to fluctuations in pipelines common in our day-to-day, and greater dependency on specific manufacturer tools, including software, reducing the capacity of the home team for repairs due to the lack of technology domain and spare parts, directly affecting the service performance. The reality of most of Brazilians HCCs is that the gases network is not stabilized, especially in older HCCs and those that have undergone several reconstructions over the years. Additionally, it is common the use of the equipment with virtually no downtime due to the non-existence of backup units, and therefore with few preventive interventions, and high turnover of equipment between units of the hospital, with frequent connections and disconnections at different points of the network. V. CONCLUSION We have presented a case study using GETS, a webbased tool for analysis and management of medical technology installed in the several units of the university health care area. Although with only 10 months of actual use by the Clinical Engineering Team based on the Biomedical Engineering Center, it was possible to show the high flexibility and complexity of the system, applied to a very important life supporting equipment used mainly in intensive care units (UTI Ventilators). GETS data analyses with flow graphs and tables have shown specific problems with very new equipments and allowed the CE team to pinpoint the problem that apparently was not with the equipment itself but how it interacts with hospital environment. In general, it was possible to show that strategic decisions may be taken based on the database stored in a standardized way by GETS, allowing hospital administrators, clinical professionals and the clinical engineering staff to better manage the medical technology installed in their facilities. We understand that as our database grows with data coming from several hospital units as well as from other hospitals in the country linked to GETS via LNGTS, more robust shall be the system. We think that it will be easier to detect errors in the design of a given equipment, for instance, because transcending a unique HCC frontier we shall have more reliable data (not based on a single and possibly vicious way of dealing with a particular technology). GETS will also facilitate the staff dealing with specification of technology for proper and best acquisitions. In our case study, it became clear that it is necessary to adequate the gases network of the particular

ventilator type (manufacturer B) to adequately operate under harsher environment. ACKNOWLEDGMENT The authors acknowledge the support of CEB Clinical Engineering team for their criticisms and suggestions. Financial Support MS / FNS (nº 4368/2005), FINEP (nº 357-08 e nº 01-08-0637-00). REFERENCES [1] L. F. M. Brito, Clinical Engineering in Brazil, in Clinical Engineering Handbook, J.F. Dyro, Ed. New York, NY: Academic Press, 2004, cap. 20, pp 69-72 (Series in Biomedical Engineering). [2] S. J. Calil, and M. S. Teixeira, "Gerenciamento de Manutenção em Equipamentos Hospitalares," in Equipamentos Médicohospitalares e o Gerenciamento da Manutenção: Capacitação a Distância, BRASIL. Secretaria de Gestão de Investimentos em Saúde. Projeto REFORSUS. Brasília, DF: Ministério da Saúde, cap. 1, pp. 11-132. (in Português) [3] A. F. Souza, Indicadores de desempenho In Gestão de Manutenção em Serviços de Saúde, A. F. Souza, C. H. T. Heringer, J. Santos Jr., and J. R. Moll. São Paulo, SP: Blucher, 2010, cap. 4, pp. 71-82. (in Portuguese) [4] A. C. B. Eboli, Padronização de Informação para um Sistema de Gerenciamento de Equipamentos Médico-Hospitalares, Dissertação de Mestrado em Engenharia Elétrica, Faculdade de Engenharia Elétrica e de Computação, Universidade Estadual de Campinas, Campinas, Brasil, 2005. (in Portuguese) [5] J. W. M. Bassani, L. S. Rocha, M. L. Lüders, W. J. Bizinotto, Micro-process based management of medical equipment maintenance, in Annual International Conference of the Engineering in Medicine and Biology Society and Annual Fall Meeting of the Biomedical Engineering Society EMBS/BMES, 24, Houston, USA, 2002, pp. 1942-1943. [6] N. F. Oshiyama, A. C. Silveira, J. W. M. Bassani Health technology management: medical equipment classification, in IFMBE Proc. vol. 22, European Conference of the International Federation for Medical and Biological Engineering, 4, part 11, Antwerp, Belgium, 2008, pp. 1581-1584