abstract
This topic reviews current research directions in healthcare mobility and assesses its impact on the provision of remote intensive care unit (ICU) clinical management. Intensive care units boast a range of state of the art medical monitoring devices to monitor a patient’s physiological parameters. They also have devices such as ventilators to offer mechanical life support. Computing and IT support within ICUs has focused on monitoring the patients and delivering corresponding alarms to care providers. However many intensive care unit admissions are via intra and inter health care facility transfer, requiring receiving care providers to have access to patient information prior to the patient’s arrival. This indicates that opportunities exist for mobile gadgets, such as personal digital assistants (PDAs) to substantially increase the efficiency and effectiveness of processes surrounding healthcare in the ICUs. The challenge is to transcend the use of these mobile devices beyond the current usage for personal information management and static medical applications; also to overcome the challenges of screen size and memory limitations. Finally, the deployment of mobile-enabled solutions within the healthcare domain is hindered by privacy, cost and security considerations and a lack of standards. These are some of the significant topics discussed in this topic.
INTRODUCTION
Intensive care units (ICUs) worldwide offer support for patients in need of critical care. The research, development, and adoption of new information technologies (ITs) and information systems (ISs) within ICUs, and particularly neonatal intensive care units (NICUs) to support patient and care provider mobility, is currently lagging behind other industries and other areas of healthcare (McGregor, Heath, & Wei, 2005a; McGregor, Kneale, & Tracy, 2005b; Wu, Wang, & Lin, 2005). In order to understand and improve upon this lag, we need to understand the current healthcare scenario within the context of intensive care.
To start with, mobile clinical management solutions within the context of intensive care units need to consider not only the mobility of the patient, but equally importantly, the mobility of the care provider. When an incident requiring critical care occurs, patients may already be located in the care provider’s ICU. However, the patient may also be located elsewhere in the care provider’s hospital, in another hospital, in their home, or in another location outside the hospital of the care provider. Patients may also be in transit between any of these locations via an ambulance, helicopter, or inter-hospital transport.
Care providers can be understood in this topic as any physician, clinician, or nursing specialist responsible for some aspect of the clinical management of the ICU patient. In daily routines, physicians, clinicians, nurses, and other staff of the hospital have to be reached and updated of new incidents and information while they are commuting in their work environments (Kaf-eza, Chiu, Cheung, & Kafeza, 2004). However, similar to the patients, care providers may also be located within the ICU, their office, elsewhere within their hospital, in their home, or in another location outside their hospital (e.g., attending an off-site meeting or conference).
Ammenwerth, Buchauer, Bludau, and Haux (2000) report that one of the major clinical management issues that mobile technologies can help with within the hospital is communication and reachability of care providers. This clinical management issue has the additional challenge of determining to whom the message should be sent (Kafeza et al., 2004). Both of these issues are particularly relevant within the ICU setting.
When critical care clinical management is required, the sooner the patient/care provider(s) information exchange can commence, the faster the clinical management can commence. In the case where the patient and care provider(s) are not located together within the ICU, critical care can still commence, provided there is adequate clinical management support to facilitate clinical decision making and execution.
Mobile healthcare systems (MHSs) have been defined by Wu et al. (2005) as the use of IS/IT to exchange healthcare information and services via mobile devices anytime and anywhere, providing patients and care providers with easy access to resources whether stationary or moving.
Recent research directions for computing and IT support within ICUs has focused on the delivery of alarms/alerts to care providers (Catley & Frize, 2003; Catley, Frize, Walker, & St. Germain, 2003; Shabot, LoBue, & Chen, 2000; Sukuvaara, Makivirta, Kari, & Koski, 1989; van der Kouwe & Burgess, 2003). However these approaches do not enable mobility in healthcare and neither do they exploit the substantial benefits possible by proper application of mobility. Furthermore, many intensive care unit admissions are via intra-and inter-healthcare facility transfer, requiring receiving care providers to have access to patient information, prior to the patient’s arrival and often while the care provider is also in transit. These are some interesting challenges in terms of communication and reachability of care providers.
Recent surveys show that between 25-35% of physicians, as distinct from care providers in general, use personal digital assistants (PDAs) (Carroll & Christakis, 2004; Fontelo, Kim, & Locatis, 2003). However, Carroll et al. (2003) further note that these PDAs are mainly for personal information management and static medical applications. Opportunities exist for PDAs and similar handheld devices to enhance and effectively deliver services within the ICU clinical management sector. However, PDA screen size and memory are seen as crucial factors in the development of PDA applications. In addition, deployment of mobile-enabled solutions within the healthcare domain is impacted by privacy, confidentiality, cost, and security considerations in addition to a current lack of standards.
This topic reviews current research directions in healthcare mobility and assesses its impact on the provision of remote intensive care unit clinical management. A background to intensive care unit clinical management is first introduced. Recent computing and IT-related research to support ICUs is then presented. Hardware and associated research to support ICU clinical management mobility is then described. A comparison of recent ICU research within the context of its ability to support mobility is presented. Issues impacting the implementation of mobile ICU clinical management solutions are then detailed. Finally, the conclusion and future directions are presented.
BACKGROUND TO ICU CLINICAL MANAGEMENT
Clinical management systems are designed to assist care providers in diagnosis and treatment using existing, already established methods of diagnosis and accepted treatments (Gross-Portney & Watkins, 2000). Hence, mobility in clinical management must support mobility in relation to diagnosis and treatment. Tasks such as medication monitoring, emergency hospitalization of patients, laboratory examination results, ordering and shipment of drugs, and exchange of information relating the patient clinical management occur frequently (Kafeza et al., 2004). Within the ICU context, clinical management systems must respond actively and very timely to the patient’s needs, which can be life critical.
One of the most prominent objectives within the modern hospital is the need for accurate, safe, and continuous communications among departments and highly specialized medical staff. In addition, the need for flexible communications to enable communication with other hospitals is also dominant. As a result there has been a great demand among the care providers for a mobile alert management system that is robust, efficient, cost effective, simple, and user friendly (Kafeza et al., 2004).
Intensive care units (ICUs) worldwide offer support for patients in need of critical care. They boast a range of state-of-the-art medical monitoring devices to monitor a patient’s physiological parameters such as blood oxygen, blood pressure, and heart rate. Other devices such as ventilators offer mechanical life support.
Broadly, there are three types of intensive care, namely, adult, pediatric, and neonatal. While the age of the patient is the differentiator between adult and pediatric ICUs, the clinical management differs greatly from these ICUs to the neonatal ICUs (NICUs)—where gestational age greatly impacts clinical management.
Approximately 18% of babies born in New South Wales (NSW), Australia, require special care or neonatal intensive care admission (NSW Health Department, 1994). Premature babies can be up to 17 weeks early and may only weigh 450 grams; they can spend three or four months in intensive care and have dozens of specific diseases before discharge. In addition, 15% of neonatal intensive care admissions are transferred after delivery from smaller remote hospitals without intensive care facilities. Similar conditions apply elsewhere within Australia and internationally, where small remote hospitals are spread throughout a given country supported by centrally located referral hospitals with NICUs.
Remote hospitals have equipment to provide limited NICU support within ‘special care nurseries’; but without the ability for a neonatologist to receive information from this equipment, the baby must be moved to a referral hospital with neonatologist support. Given the critical requirement to maintain a consistent environment, moving a baby at this time can be life threatening. Critically ill, term and pre-term babies that have to be transferred have higher mortality rates and much higher rates of long-term disability than similar babies born in hospitals with intensive care facilities (McGregor, Bryan, Curry, & Tracy, 2002). A major limitation is that the attending care provider at the remote hospital must contact a neonatal specialist (neonatologist) via telephone, or in some instances the provider—who may or may not be located at the NICU at that time—must describe via e-mail (Deodhar, 2002) the baby’s symptoms and, where possible, relay any physiological information verbally, or narratively in the context of an e-mail. The consulting neonatologist must then make decisions based on this verbal or textual exchange.
It is very common for critically ill babies to have significantly abnormal variation in the measured parameters minute by minute, and not all these variations are made available to the consulting neonatologist. Frequent transient falls in blood pressure and blood oxygen content, often with swings into the high range, may be of critical importance in survival and quality of survival, free of significant disability (Lister, Bryan, & Tracy, 2000).
Hence the neonatologists located at referral hospitals require the ability to obtain information from the monitors attached to babies. Similarly, a neonatologist need not be located at a PC within the hospital to view patient data, but should be free to view this information through any device offering a secure Internet/intranet connection. These scenarios open up opportunities for application of mobility in ICU management, as discussed in this topic.
RECENT COMPUTING AND IT RESEARCH TO SUPPORT ICU CLINICAL MANAGEMENT
Much of the recent computing and IT related research to support intensive care units (ICUs) has focused on clinical alerts (Catley & Frize, 2003; Catley et al., 2003; Shabot et al., 2000; Su-kuvaara et al., 1989; van der Kouwe & Burgess, 2003). The information made available to these systems is limited to a small set of physiological data and/or clinical data from patients located within their ICUs. In addition, care provider access to these systems is limited to the receipt of alerts, with minimal content via e-mail and in some cases pagers.
An integrated XML-based healthcare framework for NICU clinical alerts is described by Catley and Frize (2003) and Catley et al. (2003). The alerting is based on the individual device alarms, and predicts mortality and ventilation requirement probability and estimated length of stay. In the implementation as presented, only e-mail alerts and Java GUI alerts are generated. They indicate that future directions for this research are a WML-based alert using Java Servlet technology running on a Web server connected to a WAP Gateway. The WAP Gateway would transmit alerts via WML to mobile devices.
Shabot et al. (2000) describe a software system which extracts clinical information from clinical information systems on a continuous basis and sends it through event detection algorithms. Alerts for detected events are forwarded through a commercial paging system to designated care providers and pharmacists.
InCare was a rule-based alarming system prototype to support clinical management within ICUs (Sukuvaara et al., 1989) that detected four important patient pathological conditions, which develop gradually during postoperative recovery of cardiac patients, namely: (1) hyperdynamic state, (2) hypoventilation, (3) hypovolemia and left ventricular failure. User interface to the alarms was via a PC.
Van der Kouwe and Burgess (2003) present an architecture for continuous electrophysiological monitoring within a neurointensive care unit. While this information is available in real time through Web-based interface, access is limited to PCs via the hospital’s secure intranet.
Shin, Huh, Lee, and Kim (2003) have developed Web-based real time for checking temperature and humidity within infant incubators in NICUs. However the access to this information was limited to the NICU central monitoring station PC, with the information delivered via the hospital intranet.
The Bush Babies Broadband research project (McGregor, Kneale, & Tracy, 2005b), supported by the Telstra Broadband Fund, aims to significantly improve the quality of treatment for babies born in regional and remote areas by providing the first on-demand virtual neonatal intensive care unit architecture in Australia. The Bush Babies architecture is shown in Figure 1. Real-time data collected from medical monitors and ventilators attached to the baby, audiovisual streams, and static physiological data such as x-ray images are transmitted from the data collection unit (DCU) to the consulting neonatologist to gain a better picture of the patient’s condition than is currently available. The Bush Babies Remote Station enables the remote care provider to initiate a bush babies session. The BRS uses a centralised Bush Babies Control Centre database to select a neonatologist from a NICU where space for the baby would be available if transport was required. A limitation of that research is that the only consulting physician station (CPS) device that neonatologists can use to view this patient condition information is via the screen of a PC or laptop. Given that consulting neonatologists are not always located in their offices within their NICU when there services are required, alternate and more portable technologies to deliver the information need to be investigated.
In association with the Bush Babies project, McGregor et al. (2005a) and McGregor, Purdy, and Kneale (2005c) propose a Web service-based framework for the transmission of XML-encoded physiological data output by medical monitoring and life support devices. That research, together with the previously mentioned Bush Babies, are portions of the “e-Baby” research collaboration (McGregor et al., 2002, 2005a, 2005b, 2005c) that is researching new approaches to the application of computing and information technology to support mobility in healthcare through local and remote neonatal intensive care. The high level e-Baby architecture is shown in Figure 2.
Figure 1. Bush Babies architecture
The Web service-based framework for the transmission of XML-encoded physiological data forms part of the solution manager service (SMS). The SMS is situated in the referral hospital NICU and receives and stores data collected by the data collection units via the physiological log Web service for near-real-time analysis and trend detection. The consulting physician station is used by the neonatologists to access the physiological data located in SMS via a set of analyse Web services or via a direct link to the data as it is streamed through the physiological log Web service. That research enables patient and care provider mobility, as a result of the Web service-based data transmission. However, the prototype as presented only tests transmission of data from patients located either within the NICUs or remote hospital and care providers located within the hospital with the NICU. In addition, care provider access is only available through the PC-based CPS, though future research indicates the forwarding of data to consulting physician PDAs.
Figure 2. e-Baby architecture
HARDWARE TO SUPPORT ICU CLINICAL MANAGEMENT MOBILITY
The variety of mobile devices available for use to support clinical management within ICUs include: PDAs, laptops, notebooks, GPSs, and smart-phones. Recent surveys show that approximately 25% or more of physicians use PDAs, although mainly for personal information management and static medical applications. A PDA provides many advantages. It starts quickly at the push of a button. It is convenient to carry around, fitting easily into a shirt pocket or handbag. Some devices can function for weeks of regular use after a quick battery recharge. However, PDA screen size and memory are seen as crucial factors in the development of PDA applications (Fontelo et al., 2003).
Carroll and Christakis (2004) recently surveyed pediatricians in relation to their use of PDAs and found that 35% currently use PDAs at work; the most common uses were for drug reference (80%), personal scheduling (67%), and medical calculations (61%).
A plethora of software packages are available for PDAs to support clinical management in the broad areas of medical handheld software collections, university medical handheld resources, document readers, access to medical literature, pharmacopoeias, specialty specific, and patient tracking. Patient tracker (www. handheldmed.com) gives the user the option to enter patient records, including demographics, laboratory results, medication,/allergy lists, test results, and radiology reports. Wardwatch (www. torlesse.com) was designed to aid medical staff in ward rounds. Medical Pocket Chart (www. gemedicalsystems.com) is an electronic medical record keeper (Fischer, Mehta, Wax, & Lapinsky, 2003).
Providing care providers with the ability to perform research at the bedside via PDA access to PubMed and clinical trial Internet sites was described by Fontelo et al. (2003).
Carroll (2001, 2002) and Carroll, Tarczy-Hor-noch, O’Reilly, and Christakis (2004) describe the implementation of a PDA-based patient record and charting system for an NICU; however, the charting component relies on the care providers completing patient flowsheets manually into the PDA, rather then having the physiological data streaming to the PDA.
A PDA-based approach for managing patient data is defined by Lapinsky et al. (2001). Patient data was entered into the Memopad using a customized template. This data was transferred between care providers using the PDAs’ infrared ability. Daily paper notes were generated via infrared link to a HP LaserJet printer, as the hospital policy required paper records.
NICU Notes (Schulman, 2003) enables care providers to collect data at the point of care and utilizes synchronization to move the patient data from the PDA via an ODBC DSN to a secure Microsoft Access application.
A critical PDA issue as defined by Carroll (2002) is the asynchronous nature of hot syncing. Information on the PC and PDA only match immediately after hot syncing. The sheer volume of data being passed during the hot sync process caused the hot sync process to fail intermittently, resulting in incomplete or duplicated information.
COMPARISON OF RECENT RESEARCH
Having discussed the routine usage of mobility in healthcare thus far, we now focus our attention on comparing the previously presented computing and IT research to support ICU clinical manage-ment—with an aim to assess the ability of that research to support mobility.
The comparison is broadly categorized into the areas of broad functionality, patient and care provider mobility, and finally architecture mobility. Within the context of broad functionality, three areas were considered: the clinical management function(s) that was (were) being supported, the time sensitivity of the decision, and the decision quality sensitivity. Time sensitivity was considered important, as Panniers (1999) has stated that only low and medium urgency decisions are suitable for computerization into a decision support system to support clinical management. The comparison based on broad functionality is presented in Table 1.
Table 1. Broad functionality
Research Identifier |
Clinical Management Function(s) Supported |
Decision Time |
Decision Quality |
(Catley & Frize, 2003; Catley et al., 2003) “ |
Clinical alerts predicting mortality, ventilation requirements, and length of stay |
Non-critical |
Not available |
(Shabot et al., 2000) |
Clinical event detection, laboratory results, and medication alerts |
Non-critical and life threatening |
High |
(Sukuvaara et al., 1989) |
Alarms relating to postoperative recovery of cardiac patients |
Life threatening |
High |
(van der Kouwe & Burgess, 2003) |
Samples electro physiological data |
Life threatening |
High |
(Shin et al., 2003) |
Infant humidicrib temperature and humidity monitoring |
Life threatening |
High |
(McGregor et al., 2005b) |
Video, image, and physiological data stream monitoring |
Life threatening |
High |
(McGregor et al., 2005a, 2005c) |
Physiological data stream monitoring |
Life threatening |
High |
(Carroll, 2002; Carroll et al., 2004) |
Patient record charting system |
Non-critical |
Medium |
(Lapinsky et al., 2001) |
Managing patient data |
Non-critical |
Medium |
(Schulman, 2003) |
Managing patient data |
Non-critical |
Medium |
Secondly, the degree of patient and care provider mobility was assessed, together with the extent of information that was available to the care provider and is summarized in Table 2.
Finally, the extent to which the proposed architectures incorporate mobility is summarized in Table 3.
Contrary to Panniers’ (1999) time sensitivity observations, the research indicates that clinical management systems are being developed to support life-threatening conditions by alerting care providers quickly of the development of the situation.
When data is being forwarded directly in a time series stream from medical devices, data quality is high. However, when PDAs are used to collect data from care providers, errors still occur.
Table 2. Degree of patient and care provider mobility
Research Identifier |
Extent of Patient Mobility |
Extent of Care Provider Mobility |
Extent of Information Available to (from) Care Provider |
(Catley & Frize, 2003; Catley et al., 2003) |
Located within NICU |
Accessing PC within hospital (wireless access proposed for future research) |
Text-based notification that physiological data values have exceeded threshold |
(Shabot et al., 2000) |
Located within ICU |
Alerts sent to pager |
Limited text-based alerts, based on type of alert |
(Sukuvaara et al., 1989) |
Located within ICU |
Accessing PC within ICU |
Physiological data streams |
(van der Kouwe & Burgess, 2003) |
Located within ICU |
Accessing PC within hospital |
Physiological data streams |
(Shin et al., 2003) : |
L ocated within NICU |
PC located at NICU control station |
Data stream |
(McGregor et al., 2005b) |
Located within local NICU or remote hospital |
Accessing PC within hospital |
Video, image, and physiological data stream |
(McGregor et al., 2005a, 2005c) |
Located within local NICU or remote hospital |
Accessing PC within hospital |
Physiological data stream |
(Carroll, 2002; Carroll et al., 2004) |
Located within NICU |
Located within NICU |
(Clinical charts updated by care provider) |
(Lapinsky et al., 2001) |
Located within ICU |
Located within ICU |
(Clinical charts updated by care provider) |
(Schulman, 2003) |
Located within NICU |
Located within NICU |
(Clinical charts updated by care provider) |
Table 3. Extent to which architectures incorporate mobility
Research Identifier |
User Interface Device(s) |
Networks |
Software/Middleware |
(Catley & Frize, 2003; Catley et al., 2003) |
Web-based |
Wired hospital intranet |
XML-based messaging |
(Shabot et al., 2000) |
Pager |
PageNet network |
Pager messaging |
(Sukuvaara et al., 1989) |
PC GUI |
W ired hospital intranet |
Not available |
(van der Kouwe & Burgess, 2003) |
Web-based |
Wired hospital secure intranet |
Not available |
(Shin et al., 2003) |
Web-based |
Wired hospital secure intranet |
HTML document |
(McGregor et al., 2005b) |
Web based |
Wired hospital secure intranet |
Simple Medical Data Protocol (SMDP) document |
(McGregor et al., 2005a, 2005c) |
Web-based |
Wired hospital secure intranet |
XML document |
(Carroll, 2002; Carroll et al., 2004) |
(PDA |
Hotsync to PC |
PDA HotSync |
(Lapinsky et al., 2001) |
PDA |
Between PDAs and printer via infrared |
PDA infrared |
(Schulman, 2003) |
PDA |
Hotsync |
PDA Hotsync |
None of the research reviewed catered to patients located elsewhere within the care provider’s hospital, and the only out- of-hospital location that was supported was another special care nursery within McGregor et al.’s (2005b) research.
Only Shabot et al. (2000) enabled care provider communication from outside the hospital, and this was via a pager. Hence, information available to care providers outside the hospital was limited.
While most user interfaces for the delivery of information were Web enabled, the task of delivery to devices other than PCs and notebooks has not been adequately addressed.
Standards for user interfaces and communications have not been developed as part of these research efforts, nor does the research contain references to other standards efforts. This indicates that such standards do not exist within the context of ICU clinical management.
ISSUES IMPACTING IMPLEMENTATION
In addition to considering PDA usage, there are several factors that to date are still issues impacting successful research, development, and implementation of mobile clinical management solutions within the ICU setting. These factors are indeed common to all clinical management solutions and include wireless network interference in ICUs, security, privacy, confidentiality, cost, and a lack of communications standards.
While the adoption of 802.11b wireless networks is increasing, Fontelo et al. (2003) state that security issues may preclude current deployment of wireless devices for medical data access and utilize infrared access stations within their research. This link was restricted to a 15-degree arc on each side of the centre and a maximum distance of 8 feet. They also found that a transient, rapid disruption of the infrared (IR) beam, such as a person walking between the IR point and the PDA, did not disconnect an established link. In addition, the use of devices via wireless networks within ICUs currently interferes with many of the devices used within ICUs for critical care.
Fischer et al. (2003) state that patient confidentiality and costs are the main implementation issues for handheld systems used within clinical management and that consumer interest may be the limiting factor to successful implementation. In addition, the lack of standards and limited bandwidth for data transfer may also impact increased implementation.
However, they conclude that a growing body of literature supports the use ofhandheld devices in a variety of medical settings and with the rapid advances in this technology, the mobile computer may well become an essential medical tool.
While the deployment of mobile clinical management solutions within ICUs offers the potential of improved patient care and service quality and increasing care efficiency, most applications within the broad healthcare context have failed or not been implemented as predicted, with 30% of failures attributed to non-technical factors (Wu et al., 2005).
For mobile IS/IT solutions to significantly impact ICU clinical management and result in a paradigm shift in the approaches to healthcare within this context, several standards need to be developed to support the ICU clinical management functions. These functions include the exchange of information relating to the patient clinical management, medication monitoring, ordering and shipment of drugs, and the examination of laboratory results.
While all monitoring and life support devices used within ICUs to supply physiological data have the ability to output the device readings usually via a serial port, the data formats vary greatly from device to device. As such, efforts to make device data from devices attached to local or remote patients accessible for mobile viewing are hampered by the myriad of formats required for transmission. McGregor et al. (2005a, 2005c) propose a Web service-based framework for the transmission of physiological data output by such devices, proposing an XML format for such data transmission; however, it has not to date resulted in mainstream standards adoption for the transmission of physiological data.
To enable ICU clinical management mobility, standards for physiological data transmission, medication monitoring, laboratory examination results, and the ordering and shipment of drugs are still required.
conclusion and future direction
While the paradigm shift to mobile clinical management for ICUs offers the potential to significantly improve the speed, efficiency, and effectiveness of critical care within ICUs, there are currently several factors impacting its mainstream adoption.
This topic has presented a review of current healthcare mobility within the context of ICU clinical management. A comparison of recent ICU computing and IT-related research indicates that the issue of both patient and care provider mobility has not been considered a priority within these research efforts.
Several issues continue to impact successful implementation of mobile clinical management solutions for ICUs; these include issues relating to the use of wireless networks, in addition to security, privacy, cost, and a lack of communications for data exchange and user interface standards.
Current computing and IT-related research to design and develop the next-generation IT/IS solutions for ICUs is not adequately incorporating the issue of mobility of patient and care provider.
Traditionally, clinical research is used as the catalyst for providing evidenced-based recommendations for change to clinical management practices. To gain care provider acceptance, changes to clinical management practices proposed through the introduction of computing and IT approaches should consider traditional clinical research approaches to validate findings and gain support and acceptance.