A Registration System in an Intensive Care Unit

  • Lis Dragsted
  • J. Qvist
  • F Janstrup
  • S H. Johansen
Conference paper
Part of the Lecture Notes in Medical Informatics book series (LNMED, volume 16)

Summary

A simple registration system is presented that gives information on long term and short term outcome from intensive therapy, on the activity level or life quality after discharge and an evaluation of the function of various organ systems. The system makes comparisons of outcome from therapy in different units possible. The system can be used in a continuous “production” control and can be of help in establishing criterias for selecting patient categories for treatment in the ICU.

During the last thirty years intensive therapy has been developed and intensive care units (ICU) are found in almost all hospitals with acute care.

Though many lives have been saved and the number of units have increased, the ICU’s have remained under almost constant scrutiny and criticism. There have been published several papers (1,2,3) concerning the outcome of intensive therapy, each using their own classification system to measure the success of treatment. It is necessary to compare the outcome for different patient categories treated in different ICU’s, this can only be done if all the units use the same registration system.

In the intensive care unit at Herlev Hospital we have in cooperation with the Danish Institute for Clinical Epidemiology developed a patient registration system that fulfils the needs we have for evaluation of the effects of intensive therapy. The system is designed for data processing and used with specific processing programmes presents the outcome in terms of mortality compared to the expected mortality of a normal population, besides the other informations we gain.

The informations gained are:
  1. A:

    Results of treatment

     
  2. B:

    “Prognostic indicators”

     
  3. C:

    Life quality

     
A: Results of treatment are presented as
  1. 1)

    Demographic data (age, sex, number, origin)

     
  2. 2)

    Disease categories

     
  3. 3)

    In-unit and in-hospital outcome

     
With these data we are able from one year to another to compare our patients according to the demographic data, disease categories and the short term outcome, that is in-unit and in-hospital mortality.
B: Prognostic indicators expressed by
  1. 1)

    The need for ventilatory assistance with a high inspiratory oxygen content.

     
  2. 2)

    Parenchymal involvement (kidney, lung, liver)

     
  3. 3)

    Immunocompetence (test for anergy)

     
The most common cause of death in the ICU is multiorgan failure and the early identification of symptoms showing involvement of different organ systems is very important. In the study on extracorporal membrane oxygenation (ECMO-study) (4) it was demonstrated that patients on ventilators demanding 50% or more oxygen during the first 24 hours had a significantly higher mortality than those patients who required a lower oxygen content. Fry et al (1980) (5) found a mortality of 41% in patients with uncomplicated acute respiratory failure, if it was accompanied by renal failure the mortality was 85%. If 4 or more organ systems failed the mortality was 100%. In our system we get an evaluation of the renal, the liver and the pulmonary function shortly after the patients admission. MacLean et al (1975) and Meakins et al (1979) (6,7) showed that skintesting for anergy was a reliable method to identify a group of patients in high risk of developing sepsis with a high mortality after elective surgery. Skintesting for anergy in the ICU during the first 24 hours after admission, reflects the patients immunocompetence (the host defense mechanism) and can be used in identification of high risk patients at an early stage of their disease.
C: Life quality expressed as
  1. 1)

    Patients activity level after discharge.

     
  2. 2)

    Mortality after discharge.

     
The short term outcome has our interest because it serves as a kind of immediate production control, but we are very interested in the patients activity after discharge from the hospital, because it is to us a better measure of success from intensive therapy. After discharge the patients at regular intervals receive a questionnaire concerning their activity level, if they are back in normal activity, in limited activity or still under care. We have found that one year after admission to the ICU 45% of the patients have died, 27% are back in normal activity, 24% in limited and the rest are still under care. These results are in accordance with those from other studies (8,9).

Through the National Register we get information concerning the mortality after discharge and the Danish Institute for Clinical Epidemiology can by special processing programmes calculate the expected mortality for a normal population of same age and sex distribution and thereby we get a comparison between our patients’ mortality and the expected mortality, the results are presented in graphic form. Likewise we can compare the long term outcome for patients with a specific diagnosis to a normal population and to the long term outcome for patients with the same diagnosis treated in another ICU.

All the informations we gain through our registration system can be used as
  1. A)

    a continuous production control on our therapy - and in combination with the search for reliable, early identified prognostic indicators.

     
  2. B)

    it contributes to the continued effort of establishing improved criterias for which patients should be selected for intensive therapy with all its ensuing consequences.

     

Keywords

Europe Avant 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Shoemaker WC, Chang P, Czer L et al. Cardiorespiratory monitoring in postoperative patients I. Prediction of outcome and severity of illness. Crit Care Med 1979; 7: 237.CrossRefGoogle Scholar
  2. 2.
    Cullen DJ, Ferrara LC, Gilbert J, Briggs BA, Walker PF. Indicators of intensive care in critically ill patients. Crit Care Med 1977; 5: 173.CrossRefGoogle Scholar
  3. 3.
    Cullen DJ, Civetta JM, Briggs BA, Ferrara LC. Therapeutic intervention scoring system: a mèthod for quantitative comparison of patient care. Crit Care Med 1974; 2: 57.CrossRefGoogle Scholar
  4. 4.
    Rie MA, Zapol WM, Stabile J, Pontoppidan H. High mortality of ventilatory assistance for 24 hours with FiO2 gt; 0.5. Am Rev Resp Dis 1976; 154.Google Scholar
  5. 5.
    Fry DE, Garrison N, Heitsch RC, Calhoun K, Polk HC. Determinants of death in patients with intraabdominal abcesses. Surgery 1980; 517.Google Scholar
  6. 6.
    Meakins JL, Christau NV, Shizgal HM, Maclean LD. Therapeutic Approaches to Anergy in Surgical patients. Ann Surg 1979; 286.Google Scholar
  7. 7.
    MacLean LD, Meakins JL, Taguchi K et al. Host resistance in sepsis and trauma. Ann Surg 1975; 182: 207.CrossRefGoogle Scholar
  8. 8.
    Cullen DJ, Ferrara LC, Briggs BA, Walker PF, Gilbert I. Survival, hospitalization charges and follow-up results in critically ill patients. N Eng J Med 1976; 294: 982.CrossRefGoogle Scholar
  9. 9.
    LeGall JR, Latournerie J, Plevin D, Trunet P, Candau P. Evaluation de l’etat de sante avant et apres hospitalisation en reanimation (1981). In: Medical Informatics Europe 81. Editors: F. Grémy, P. Degoulet, B. Barber and R. Salamon. Springer Verlag, Berlin-Heidelberg-New York 1981.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1982

Authors and Affiliations

  • Lis Dragsted
    • 1
    • 2
  • J. Qvist
    • 1
    • 2
  • F Janstrup
    • 1
    • 2
  • S H. Johansen
    • 1
    • 2
  1. 1.Department of AnesthesiaHerlev HospitalHerlevDenmark
  2. 2.Danish Institute for Clinical EpidemiologyCopenhagenDenmark

Personalised recommendations