In all, we can identify four main forms of HCIS failure:
• The total failure of a system never implemented or in which a new system is implemented but immediately abandoned. A much-reported example is that of the London Ambulance Service’s new computerised dispatching system. This suffered a catastrophic failure within hours of implementation, leaving paramedics unable to attend health care emergency victims in a timely manner (Health Committee, 1995).
• The partial failure of an initiative in which major goals are unattained or in which there are significant undesirable outcomes. Anderson (1997:87), for instance, cites the case of “An information system installed at the University of Virginia Medical Center [which] was implemented three years behind schedule at a cost that was three times the original estimate.”
• The sustainability failure of an initiative that succeeds initially but then fails after a year or so. Some of the case mix systems installed under the UK National Health Service’s Resource Management Initiative fall into this category. They were made fully operational and achieved some partial use but with limited enthusiasm from staff for using them. Ultimately, they were just switched off (HSMU, 1996).
• The replication failure of an initiative that succeeds in its pilot location but cannot be repeated elsewhere. Although presenters may not realize it at the time, every health informatics conference is jam-packed with replication failures about to happen; The with wonderful innovations that are tested once and then disappear without trace. As an audience, we hear all about the pilot, but we tend not to hear about the replication failure.
Source: Why Health Care Information Systems Succeed or Fail
Central to e-health success and failure is the amount of change between 'where we are now' and 'where the e-health project wants to get us'.
'Where we are now' means the current realities of the situation. 'Where the e-health project wants to get us' means the model or conceptions and assumptions built into the project's design. eHealth success and failure therefore depends on the size of gap that exists between 'current realities' and 'design of the e-health project'.
The larger this design-reality gap, the greater the risk of e-health failure. Equally, the smaller the gap, the greater the chance of success.
Analysis of e-health projects indicates that seven dimensions - summarized by the ITPOSMO acronym - are necessary and sufficient to provide an understanding of design-reality gaps:
- I nformation
- T echnology
- P rocesses
- O bjectives and values
- S taffing and skills
- M anagement systems and structures
- O ther resources: time and money
Putting these dimensions together with the notion of gaps produces the model for understanding success and failure of e-health that is shown below.
