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Web Resources for Nosokinetics
 ICD-10 search
Relevant Clinical Literature
Pubmed on Nosokinetics
RCT with Nosokinetics
Systematic reviews of Nosokinetics
Nosokinetics in N Eng J Med, Lancet, JAMA, BMJ
Nosokinetics in Cochrane Collaboration
TRIP Database on Nosokinetics
Google Scholar on Nosokinetics
Bandolier on Nosokinetics
UK Guidance
NHS Evidence on Nosokinetics
Nice Guidance on Nosokinetics
Centre for Reviews and Dissemination databases -DARE & NHS EED (evaluates reliability of research)
SNOMED search
NICE Clinical Knowledge Summaries on Nosokinetics
Other Wikis
Wikipedia on Nosokinetics (Less technical, ? quality control)

Nosokinetics (Service care delivering modelling) is a term used to describe the science/subject of measuring and modelling the process of care in health and social care systems.


Greek: nosos: disease and kinetikos: to move



Why model

  • Prediction
  • Objectivity to decisions
  • Consequences of decisions
  • Identifying what is important
  • Performance & monitoring measures
  • Explaining what went wrong

Modelling limitations

  • Measurable parameters must exist
  • Assumptions
    • Usually include political and social stability
  • Chaos limitations
    • War, earthquake or that unexpected epidemic

Modelling strengths

  • Can often use data that is routinely collected
  • Assumption examination can allow what if scenario planning
  • Can allow for regular or repeating in time events such as seasonal influenza, effect of weekends and public holidays
  • Can allow for demography changes

Model types

  • Stochastic
    • Assume you do not know precisely what will happen in advance, but past experience and reasonable population size allow assumption of randomness that underlies many real-world phenomena
    • Allows a range of estimates
    • More useful when you want a background level of guaranteed service
    • More complicated so less likely to appeal to decision makers
  • Deterministic
    • Returns a most likely estimate
    • Is easier to grasp but is far more likely to lead to chaos if used in prediction
      • Health and social care decisions based on deterministic modelling have created major system crises in most such systems
        • Examples include:
          • Creating assessment panels or other rationing (queuing) steps such as waiting lists for inpatient investigations in patients who are already inpatients.
          • Decreasing social service funding while increasing health funding leading to game playing by the underfunded service

Stocastic models

  • Will tend to have to use phase-type (PH) distributions such as length of stay in an institution
    • State transitions need the mathematical concept of the (finite-state) continuous-time Markov chain (CTMC) which is rendered vis vector arithmetic.
    • Coxian distributions, a subtype of phase-type distributions are useful in healthcare modelling
      • Care home residents classically have a two state coxian distribution to their length of stay, because a subgroup rapidly die (or move on to more dependent institutional care) as they have a subacute unstable medical condition while the other subgroup have a chronic and only slowly progressive condition.
    • General phase-type (PH) distributions would be better for modelling patient flow around a hospital since the processes in the emergency department, theatres and wards are so different with the potential for readmissions and indeed use of complex numbers to =best fit the observed distrution of length of stay.

External links

  • Nosokinetics Group web site
  • NHS institute modelling and simulation tools

This article is a work in progress. Please feel free to contribute to it.