Knowledge Share Systems in the Healthcare Industry, Research Paper Example

Healthcare Management Information Systems (HMIS) offer integrated systems platforms and applications to the entire range of chain operations management activities within and between institutions that provide patient care. Consistent with the emergent interests in organizational knowledge sharing networks, healthcare institutions are looking to IT solutions for a number of reasons, and especially the growing impetus toward: 1) healthcare provider connectivity; 2) increased focus in tracking and management of chronic diseases; 3) heightened patient expectations regarding personal input in care process; 4) market pressures driving hospital-physician alignment; and 5) advances in the technological facilitation of systems operability in this area (Tan and Payton, 2010).

Design of systems architecture from institution to institution still varies, as data management and interconnectivity may be distinct and also subject to existing ‘legacy systems’ issues that might be incorporated in the new HMIS model. The core competency of HMIS is the more ephemeral side of systems planning which is the knowledge sharing path – where data and information become meaningful. The other key components to consideration of HMIS integration include: 1) the basic hardware, software and network schema; 2) process, task and system(s); 3) integration and inoperability aspects; and 4) user, administration and/or management inputs and oversight.

Increased spending and strategic planning toward realization of new HMIS operations is ultimately an acknowledgement that healthcare institutions are inevitably Healthcare Information Technology (HIT) organizations and that Health Informatics (HI) are the foundation to professional practice settings. The classification of HI within HIT is predominantly dictated by existing operations channels, and by the range of record and reporting functions within the clinical care environment. From a technological perspective HI classification presents a natural taxonomy from which to archive data. Relatively standardized taxonomies of codified data are generated through database repositories such as: Customer Relations Management (CRM); Electronic Health Records (EHR); Enterprise Resource Planning (ERP); Personal Health Records (PHR); and Supply Chain Management (SCM) dedicated to total operations management control, patient referral and professional knowledge sharing (Tan and Payton, 2010).

This is not to say that ‘total’ HMIS systems models do not have their opponents. Some argue that integration of database information from patient-centric and insurance applications such as CRM with supply chain management of supply logistics, for example, does not make sense. However, proponents of the total systems approach involved in finance and operations units within those institutions argue otherwise, as executive direction looks toward better integration of budgetary allocations and accountability.  One of the biggest challenges to monitoring and regulating HMIS infrastructure is the persistence of ‘legacy systems’ or older propriety architectures that are non-standard to standardized command syntax. Service nomenclature should be standardized effectively with enterprise-wide or ‘universal’ use by the various access levels in mind. Older systems may also contain counter-intuitive logics beyond data codification, that were implemented into unique secured networks that have proved to be risky at time of emergency, rather than merely discretionary in moments of urgent response.  Open source software optimizes programming competency and ensures apt protective measures with specification in control systems architecture type, with platforms that might be shored up with sufficient firewalls, intrusion detection, and encryption.

In a recent, 2010 RAND Corporation study on fiscal waste reductions by healthcare institutions, the think tank found that American health organizations have the potential to save up to $3.6 trillion with cost saving initiatives that all could be tackled effectively with HMIS systems integration (Pizzi, 2010). Addressing five (5) key factors impacting the finance of healthcare organizations, recommendation was toward the this end: 1) fiscal risk reductions to patients through better information;  2) records sharing optimization toward reduction in the duplication of tests and inappropriate treatments estimated to cost up to $50 billion annually; 3) managed care and wellness education for disease prevention, early detection and care of chronic diseases; 4) quality assurance toward risk mitigation of preventable medical errors which currently account for $50 billion to $100 billion in annual healthcare spending; and 5) reduction of fraud which constitutes 5-10% of the roughly $2.3 trillion in government spending on healthcare in the U.S. (Pizzi, 2010). Ultimately, innovation in HMIS will do much for American healthcare, linking healthcare institutions to a new level of market competitiveness with the highest caliber intelligence available to physician and specialists seeking new paths to the oversight of patient care.

References

Blue Shield of California extends contract for MedeAnalytics’ claims transparency solution (2010). Healthcare Finance News, February 12, 2010. Retrieved from: http://www.healthcarefinancenews.com

Tan, J. and Payton, F.C. (2010). Adaptive Health Management Information Systems: Concepts, Cases, & Practical Applications, Third Edition. Sudbury, MA: Jones & Bartlett Learning.

The imperative to be customer-centric IT leaders (2010). CIO.com. Retrieved from: www.cio.com

Pizzi, R. (2010). Actuarial survey says transparency would reduce healthcare costs. Healthcare Finance News, 29 July 2010. Retrieved from: http://www.healthcarefinancenews.com

(2010). Study outlines $3.6T in potential healthcare waste reductions. Healthcare Finance News, 14 June 2010. Retrieved from: http://www.healthcarefinancenews.com