Impact 2013: HCLS capabilities create client confusion, but perception promises progress
Akshata Pai 270005SCF5 email@example.com | | Tags:  systems real-time patient hospitals aim expert care mobilefirst integrated providers capabilities healthcare
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Contributed by Pete Melrose, WW WebSphere Industry Marketing Manager, Healthcare and Life Sciences
IBM Healthcare and Life Sciences (HCLS) clients attending Impact 2013, and also others on recent sales calls, appear confused by WebSphere Application and Integration Middleware (AIM) and the capabilities enabled by this much-needed but poorly understood category of information technology (IT).
Healthcare providers such as hospitals and physicians view IT as a collection of hardware and software components to be bought and/or built into application-specific solutions. HCLS organizations have to understand that these systems of record are in principal industry-specific databases and are valuable, easier-to-use access methods. However, their potential is not fully tapped until they are incorporated using Systems of Interaction in true systems of engagement. So, why is this understanding a priority?
The focus for HCLS organizations is to maximize the economy, efficiency and effectiveness of health management, medical practice and healthcare delivery. Every HCLS organization must become an expert engaged enterprise (E3), the critical characteristics of which are:
These six characteristics of an E3 can be cost-effectively realized with IBM AIM as IBM is the only IT vendor to provide:
Therefore, the HCLS client confusion at Impact 2013 and elsewhere can be mitigated by thinking in terms of augmenting legacy capabilities with features and functions obtained from the use of AIM in a Service Oriented Architecture (SOA) ‘wrap and reuse’ style that implements these features:
Consider the following contrasting examples of a hospital in-patient admission process:
Typical hospital environment, including legacy HIS and ancillary/departmental systems
A patient presents for admission to hospital, the history and physical examination ‘workup’ is performed, the patient is admitted with a ‘provisional/admission diagnosis’ on the basis of the diagnostic laboratory tests. The HIS admission/discharge/transfer module (A/D/T) and the ancillary/departmental order entry/ results reporting (OE/RR) system (provided by an ISV other than that providing the HIS), are updated via the data interface engine system (DIE) (provided by a third ISV), to reflect the staff actions and system transactions that have occurred. At some later time, test results are received and fail to confirm the provisional/admission diagnosis, necessitating a re-examination of the patient and perhaps a specialist consultation to revise diagnosis, followed by determination of an appropriate treatment protocol and care plan; and perhaps a repetition of these activities if the care and treatment prove ineffective. The time delay stemming from the erroneous provisional diagnosis and repeat of patient work-up and perhaps repetition of entire process based on revised diagnosis, forces extra days in hospital, which adds costs. More significantly, this repetition and consequent delay could lead to significantly greater patient morbidity or even death, depending on the progression rate of the presenting pathology.
E3 hospital environment, including legacy HIS and ancillary/departmental systems supplemented by IBM AIM with analytics
A patient presents for admission to hospital, the history and physical examination ‘workup’ is performed, the patient is admitted with a ‘provisional/admission diagnosis’ on the basis of diagnostic tests. The HIS admission/discharge/transfer module (A/D/T) and the ancillary/departmental order entry/ results reporting (OE/RR) system (provided by an ISV other than that providing the HIS) both are updated via the data interface engine system (provided by a third ISV) to reflect the staff actions and system transactions that have occurred. However, the entire admission process is automated and monitored by a BPM process, instantiated by an operational decision management activity for admission event detection and a business rules activity interoperable with SPSS analytics to automate the provisional diagnosis activity. Therefore, work-up history and physical data are utilized automatically in real-time immediately upon conclusion of the admission activity to search the hospital’s patient database for similar patient records and analysis of variables using previously specified rules and conditions recorded by hospital subject-matter experts to generate the differential diagnosis. Also, another operational decision management activity determines the appropriateness of the tests ordered for each of the differential diagnosis alternatives and informs the admitting physician via stationary or mobile form factors of their (in)appropriateness with recommendations for (re)ordering. This way, the best/correct diagnosis is made and confirmed on the same day or even hour of the admission, confirming the appropriateness of clinical decisions already made; or, as often is the case, correcting decisions and actions in real-time. This way, the hospital incorporates its systems of record with systems of interaction to create systems of engagement while minimizing IT total cost of ownership (TCO) and maximizing return on investment (ROI).