Page 1 of 6 Clinically quantifiable benefits of biomedical device integration (BMDI)? Historically, benefits of connected medical devices within the healthcare enterprise have been measured in terms of time-in-motion studies and workflow relating to time saving associated with accomplish a specific task or end goal 1. These are valid measures. Yet, the question remains as to whether there is something more tangible clinically that can be used as a measure of effectiveness related to interoperability. There are numerous examples almost as many as there are clinical guidelines, which are many thousands of ways to exemplify the benefits of biomedical device integration. Yet, it is important to distinguish that in this sense the term integration does not solely apply to medical devices: it reflects the totality of communication and interfacing of information in a manner that is truly understandable by the systems and end users consuming that information, in a way that is clinically useable by the end user. Where medical device integration is a necessary adjunct for interoperable data communication generally becomes most apparent in areas where data from medical devices are necessary for the status and management of patients in large measure. Within the hospital, these are typically: Emergency Department Surgery Cardiac-Catheterization Labs Intensive Care Medical/Surgical Units Radiology While the outpatient ambulatory spaces also require access to and monitoring of data from biomedical devices (e.g.: glucometers, spirometers, blood pressure cuffs, etc.), I will leave the extra-hospital environment until later as this is a specialized application of medical devices and the consumption of medical device data for patient care is primarily focused on chronic disease management. Within the in-patient environments listed above, medical device data on patients are used for assessing status of patients primarily cardiovascular and pulmonary / respiratory state: the bodily functions most associated with 1 M. Kelly, K. Schernekau, (UAB Health System) BMDI: Increasing Patient Safety while Improving Clinician Workflow. HIMSS 2009. McCormick Center, Chicago, IL.
Page 2 of 6 maintaining existence. Specific examples of measurements taken in these environments include: Pulse; ECG; O2 saturation; Temperature; Respirations, Tidal Volume; End-tidal CO2; Drug administration; and, Blood volume & blood flow. The automatically-collected medical device data requirements of clinical end users (e.g.: physician, nurse, respiratory therapist, etc.) are based on their needs for treating and guiding the care of the patient through the standard practice of medicine. Like subjective observations, these medical device measurements communicate how the various patient systems are responding to treatment, sedation, or both. Therefore, in terms of clinical decision-making, both of these environments usually involve the integration of multi-source information to assist in communicating and projecting how the patient state is evolving over time. Furthermore, in terms of length of stay, there are very few environments nowadays in which a patient spends multiple days. Both cost reduction initiatives and treatment plans tend to drive moving the patient to discharge as quickly as possible. If patients require extended care in sub-acute settings they are normally moved to facilities outside of the hospital. Normal inpatient stays not of the acute variety are not typically longer than 30 days. Beyond that, ambulatory facilities are typically used. However, intensive care settings can be different. It is not unusual for critically ill patients to spend many weeks to months in these units. Because of the acuity and the duration, much of the focus in hospital settings is devoted to caring for the most ill of patients. Patients in intensive care are either admitted in association with a post-surgical event or directly through an ailment already diagnosed. For instance, coronary bypass surgery is a major feeder for intensive care units, as well as head trauma, cancer, or ailments acquired at home that requires treatment in the acute setting. Patients in intensive care often require pulmonary assistance in the form of mechanical ventilation. This not only increases the complications and cost of their treatment, it exposes them to the likelihood of infection. Because the patients in this environment tend to be elderly having several co-morbidities, these
Page 3 of 6 patients are also prone to ailments that can exacerbate their reasons for being in the unit as well as their decline over time. Hospital acquired infections (HAI) as well as the more specific ventilator associated pneumonia (VAP) are killers and become real threats the longer the stay in intensive care and the longer the duration on mechanical ventilation. One study 2 on the duration and costs of patients in intensive care related to mechanical ventilation made the follow finding: Days of intensive care and mechanical ventilation were identified using billing data, and daily costs were calculated as the sum of daily charges multiplied by hospital-specific costto-charge ratios Approximately 36% of identified patients were mechanically ventilated at some point during their intensive care unit stay. Mechanically ventilated patients were older (63.5 yrs vs. 61.7 yrs, p <.0001) and more likely to be male (56.1% vs. 51.8%, p < 0.0001), compared with patients who were not mechanically ventilated, and required mechanical ventilation for a mean duration of 5.6 days... Mean intensive care unit cost and length of stay were $31,574 14.4 days for patients requiring mechanical ventilation and $12,931 8.5 days for those not requiring mechanical ventilation Adjusting for patient and hospital characteristics, the mean incremental cost of mechanical ventilation in intensive care unit patients was $1,522 dollars per day (p <.001) As stated earlier, as patients remain in intensive care for longer durations they become targets for HAIs, and particularly VAPs 3 : Ventilator-associated pneumonia (VAP) is common in the intensive care unit (ICU), affecting 8 to 20% of ICU patients and up to 27% of mechanically ventilated patients... Several risk factors have been reported to be associated with VAP, including the duration of mechanical ventilation, and the presence of chronic pulmonary disease, sepsis, acute 2 Dasta JF, McLaughlin TP, Mody SH, Piech CT. Daily cost of an intensive care unit day: the contribution of mechanical ventilation. Crit Care Med. 2005 Jun; 33(6):1266-71 3 Rea-Neto, A. et al. Diagnosis of ventilator-associated pneumonia: a systematic review of the literature. Critical Care 2008, 12:R56
Page 4 of 6 respiratory distress syndrome (ARDS), neurological disease, trauma, prior use of antibiotics, and red cell transfusions [2]. Mortality rates in patients with VAP range from 20 to 50% and may reach more than 70% when the infection is caused by multi-resistant and invasive pathogens. Yet, in terms of HAIs in general, the lethality of, the effect of HAIs cannot be understated, both from the patient s quality of life and from the cost per stay 4 : An analysis of a U.S. hospital database found that in-hospital mortality is four times higher in patients with a hospitalacquired infection (HAI) than in those without Moreover, the length of stay in the ICU doubled for infected patients, up from a mean of 8.1 days to 15.8 days. In particular, hospitalacquired pneumonia was associated with 16.9 percent of ICU stays, bloodstream infection with 14.5 percent, ventilatoracquired pneumonia with 3.7 percent and surgical-site infection with 1.5 percent, according to the study infections add an extra $16,000 to each ICU stay. In fact, an infected patient costs $37,500 per ICU stay, compared to $21,500 for a patient without infected patients stayed in the hospital three times longer than patients without, were far more likely to be readmitted with 30 days and were more than five times likely to die than patients without infections So, the care and treatment of the acutely ill patient is at the heart of improving medical practice in the hospital environment. For these reasons a considerable effort has been undertaken to apply various means, from compliance with clinical guidelines and basic lists 5 to algorithms that can take information from multiple sources and process them to herald the onset of HAIs. These algorithms guidelines usually fall under the category of clinical informatics applications. Clinical informatics algorithms and methods encompass the entirety of those health information technology functions that include physician order entry 4 Ibid 5 See Peter Pronovost. http://en.wikipedia.org/wiki/peter_pronovost. Accessed 4/27/2015.
Page 5 of 6 systems, electronic medical records with laboratory and radiology data, and computerized clinical decision support systems (CDSSs). 6 Studies have shown that CDSSs in ICU can improve outcomes in the mechanically ventilated patient. 7 What has become clear over time is the need for semantically integrated information at the point of care is key to the management of critically ill patients. Furthermore, the notion of Interventional Informatics has been on the rise using informatics algorithms and monitoring to provide intervention in the ICU and elsewhere to head off adverse events before they can happen. In one study of a 5 hospital, 8 facility, 787 bed institution in Northeastern Indiana, Interventional Informatics has been ascribed to a significant cost saving. 8 This study estimated the cost benefit per episode of saving in terms of a projected annualized cost benefit based upon cost avoidance per month: Benefit: ((X * 0.047) * $6536) * 12 X represents projected number of interventions/month. In this model, the Interventional Informatics model would involve generation of an alert remote from the patient care area where triage, investigation and intervention are coordinated by a clinically-trained informaticist. The time gap between collecting data, performing analytics and directly improving care and safety. To achieve such savings, it is necessary to integrate information from multiple sources within the environment. The cost saving above is based upon providing data from all points within the environment vital signs, laboratory, orders, infusions, observations and synchronizing them to provide an overall picture for the physician. Summary At the heart of clinical decision support are data. Data are the source of the engine and the means by which clinical value are derived. The clinical value 6 Adhikari, N, Sibbald, W. The large cost of critical care: realities and challenged. Anesthesia & Analgesia. February 2003 Vol. 96 no. 2 311-314 7 Ibid. 8 Pierce, M. Implementing An Interventional Informatics Program. https://www.researchgate.net/publication/242604985_implementing_an_interventional_info rmatics_program Accessed 4/27/2015.
Page 6 of 6 is measured in terms of treating patients and in reducing the likelihood of adverse events. By analogy, as described at the outset of this white paper, just as reduction in workflow steps implies reduced cost, reduction in the likelihood of adverse events does the same. As the calculation of clinical benefit implies, the benefit to the physician is in reducing the chance that the patient will acquire infections or will otherwise deteriorate within the environment.