Literature DB >> 914529

Consultation frequencies in general practice.

S J Kilpatrick.   

Abstract

Some models of the process by which individuals seek medical care suggest the negative binomial as the underlying distribution of the frequencies of consultations in a given practice. Data from the 1970-71 National Morbidity Survey of General Practice are used to test these competing models. It is shown that the negative binomial distribution successfully fits consultation frequencies in aggregate and in subdivisions according to age, sex, and duration of registration. In this article is is assumed that the consultation process has two components: the patient's decision to visit his doctor for a new illness and the follow-up visits that results from this new problem. Supplementing previous evidence that the distribution of episodes of new illnesses follows a negative binomial distribution, this article shows that consultation frequencies among individuals presenting with one new illness also follow a negative binomial distribution. A unifying model is required to synthesize these findings.

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Year:  1977        PMID: 914529      PMCID: PMC1071997     

Source DB:  PubMed          Journal:  Health Serv Res        ISSN: 0017-9124            Impact factor:   3.402


  4 in total

1.  Frequent attendance in a family practice.

Authors:  M J Courtenay; M P Curwen; D Dawe; J Robinson; M J Stern
Journal:  J R Coll Gen Pract       Date:  1975-04

2.  The distribution of episodes of illness--a research tool in general practice?

Authors:  S J Kilpatrick
Journal:  J R Coll Gen Pract       Date:  1975-09

3.  Illness in general practice.

Authors:  J HORDER; E HORDER
Journal:  Practitioner       Date:  1954-08

4.  Factors affecting work load in general practice. II.

Authors:  G N Marsh; R A McNay
Journal:  Br Med J       Date:  1974-02-23
  4 in total
  2 in total

1.  The complementarity and substitution between unconventional and mainstream medicine among racial and ethnic groups in the United States.

Authors:  K Tom Xu; Tommie W Farrell
Journal:  Health Serv Res       Date:  2007-04       Impact factor: 3.402

2.  Modeling denominator populations for mental health care.

Authors:  L Kessler
Journal:  Health Serv Res       Date:  1983       Impact factor: 3.402

  2 in total

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