Dictionary

The Dictionary provides concise definitions of health economics terms, arranged alphabetically for quick reference. Use it to understand unfamiliar terminology or confirm the meaning of a specific term.

37 terms matching Algorithm

A

Algorithm
A finite sequence of well-defined computational steps for solving a problem or performing a calculation.
Algorithm Development
The process of creating a structured, step-by-step clinical decision pathway guiding appropriate diagnosis or treatment for a specific condition.

B

Big O Notation
An asymptotic notation that expresses an upper bound on how an algorithm?s resource use grows as input size increases, disregarding constant factors and lower-order terms.
Binary Search
A search algorithm for sorted data that repeatedly compares the target with the middle item and eliminates the half in which the target cannot occur.

C

Clinical Algorithm
A structured, step-by-step clinical decision pathway outlining recommended diagnostic or treatment steps for a condition, increasingly built into decision support systems.
Computational Complexity
A measure of the computational resources required by an algorithm as the size of the input increases.
Convergence Assessment
An evaluation of whether an iterative algorithm, such as a Markov chain Monte Carlo simulation, has run enough iterations to produce stable results.

D

Data Structure
An organization of information designed to support efficient storage, access, modification, or processing by algorithms.
Decision Algorithm
A structured framework guiding how an assessment body should weigh and combine evidence and criteria to reach a final recommendation.
Diagnostic Analytics
The application of data analysis techniques to support diagnostic decision-making, from statistical risk prediction models to machine learning algorithms trained on clinical data.
Digital Safety
The degree to which a digital health technology avoids causing unintended harm, covering both clinical safety and data security or algorithmic bias.
Divide and Conquer
An algorithmic technique that divides a problem into smaller instances, solves those instances?often recursively?and combines their solutions.
Dynamic Programming
An algorithmic technique that solves a problem by combining solutions to overlapping subproblems and storing those solutions to avoid repeated computation.

G

Genetic Algorithm
An optimisation technique inspired by evolution that iteratively selects and combines the best candidate solutions across generations to improve results.
Gibbs Sampling
A Markov chain Monte Carlo algorithm generating samples from a complex joint distribution by iteratively sampling each variable from its conditional distribution.
Gradient Descent
An iterative optimisation algorithm adjusting parameters in the direction that most rapidly reduces an objective function until a minimum is reached.

H

Health Index
A single numerical summary of overall health status, derived by combining scores across multiple health dimensions using a specified scoring algorithm.

I

Indirect Elicitation
A health state valuation approach in which a descriptive questionnaire's responses are converted into a utility value using a pre-existing scoring algorithm.
Indirect Utility Assessment
The process of obtaining a health state utility value by applying a scoring algorithm from a prior valuation study to a respondent's questionnaire answers.
Interior-Point Method
An optimisation algorithm that approaches the optimum of a constrained problem by traversing the interior of the feasible region.

K

Kalman Filter
A recursive algorithm estimating a dynamic system's unknown state over time by combining noisy observations with a model of how the system evolves.

M

Mapping Algorithm
A statistical model predicting a health utility value from responses on a non-preference-based instrument, used when a preference-based measure was not collected.
Mapping Function
The specific statistical relationship, typically estimated through regression, used within a mapping algorithm to convert a health status score into a predicted utility value.
Markov Chain Monte CarloMCMC
A class of algorithms generating samples from a complex probability distribution by constructing a Markov chain that converges to that distribution.
Metropolis-Hastings
A Markov chain Monte Carlo algorithm generating samples by proposing candidate values and accepting or rejecting them by a rule ensuring convergence.

N

Nelder-Mead Method
A numerical optimisation algorithm searching for a function's minimum using a moving shape, called a simplex, without needing the function's derivative.

P

Pseudo-Random Number
A number generated by a deterministic algorithm that approximates the statistical properties of true randomness, used because genuine randomness is hard to compute.

R

Recursive Algorithm
An algorithm that solves a problem by invoking itself on one or more smaller or simpler instances until a base condition is reached.

S

Scoring Algorithm
The specific formula, derived from a population valuation study, used to convert health status questionnaire responses into a single utility value.
Sequential Monte Carlo
A class of algorithms, including particle filtering, estimating a sequence of unknown quantities over time by updating weighted samples as new data arrive.
SF-6DShort Form-6 Dimension
A preference-based utility measure derived from a subset of SF-36 or SF-12 items, combined using a scoring algorithm into a single utility index.
Simplex Method
An optimisation algorithm that solves linear programming problems by moving systematically between feasible solutions until the optimum is found.
Sorting Algorithm
An algorithm that arranges a collection of items into a predetermined order according to their keys or a comparison rule.
Space Complexity
A measure of how the memory requirements of an algorithm grow as the size of the input increases.

T

Time Complexity
A measure of how the execution time of an algorithm grows as the size of the input increases.
Treatment Algorithm
A structured, step-by-step clinical decision pathway outlining the recommended sequence of treatment decisions for a specific condition.

V

Value Set Development
The process of designing, conducting, and analysing a population valuation study to produce a scoring algorithm for a health status instrument.