Journal of Hospital Infection (1990) 15, 1-5

LEADING

Information,

ARTICLE

computers

and infection

control

Computerization was an early and obvious answer to the problem of data Within microbiology laboratories handling in pathology departments. computers are well established, (Williams et al., 1978; Blair & Brown, 1981) and are of value in the classification and identification of micro-organisms (Sneath, 1969), reporting and storing results (Andrews & Vickers, 1974; Goodwin, 1976; Goodwin & Smith, 1976; Ridgway et al., 1980) and in laboratory management (the provision of Kijrner statistics, work flow, duty rosters etc.) (Phillips, 1978). However, computers are now found in almost every area of hospital activity, gathering and generating data, and communication between them has become easier. The increasing power, compactness and availability of computing systems during the past twenty-five years has been accompanied by an increase in the generation of ‘information’ and a flourishing industry to manage it-‘Information Technology’. How are these systems and information being used in the management and prevention of infection in hospital and what advances may we expect? At the simplest level, within the microbiology laboratory, in the early assessment of possible outbreaks, infection control personnel now use computer-generated lists of organisms grouped by hospital area (ward, operating theatre etc.), consultant or service (Feldman & Ridgway, 1988). These lists of ‘alert’ organisms and clusters may be generated automatically each day and may be supplemented by ad hoc enquiries (Gaunt & Phillips, 1987), which usually require the creation of a specific program. Organisms and resistance patterns of interest vary in different parts of the hospital and with time; they can change frequently and at short notice, so the regular listing of ‘alert’ organisms must be readily reprogrammable by the infection-control team. Even in the absence of an outbreak with a single strain, an increase in the number of infections in a particular area may indicate falling standards of hygiene that need investigation. At present, such listings are used as the basis for a sortie by the infection-control team into the particular hospital area under suspicion, where further collection of epidemiological data is carried out by hand and stored on paper. Small hand-held computers may facilitate the gathering of data which are down-loaded to a larger computer for subsequent analysis. Improvements in portable (lap-top) computers may further simplify the process (Gaunt & Phillips, 1987). 0195-6701/90/010001+05

$03.00/O

0 1990 The Hospital

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Infection

Society

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Information,

computers

and infection

control

In the surveillance of nosocomial infection, interest has long been shown in the gathering of data on particular types of infection (more so in the United States than in the United Kingdom). The effort required on the part of the infection-control team is great in order to study even a single type of infection, not only because of the difficulty in collecting data on patients with infection, but also in determining the denominator figures in order to calculate infection rates. While the value of collecting much of these data has been called into question (Casewell, 1980), Cruse & Foord have shown that an important factor in reducing post-operative sepsis is the provision of surgeon-specific wound infection rates (Cruse & Foord, 1973; Cruse, 1977). However, the busy microbiologist in the UK, constrained by lack of resources, finds it difficult to record the rate of wound infection for all types of surgery. If the process were made easier and more accurate, perhaps enthusiasm for surveillance might be rekindled and its benefits analysed. Computer access to microbiological, patient and theatre information would provide one solution and take away the drudgery from the documentation. Computers are used in some hospitals for the generation of operating-theatre lists, and in the production of discharge letters, so information on both patient and treatment is already available for capture. Hospital staff will more readily co-operate in the collection of such information if it is made a by-product of routine patient care and if the staff derive some benefit from the process. Given accurate data input and careful programming, computer-generated infection rates will do much to obviate the errors that inevitably accompany manual reports and that can undermine the infection-control team’s credibility with surgical staff (Haley, 1986). Epidemiological studies need sound planning and execution and the computer can assist in the analysis (French, Cheng & Farrington, 1987). Complicated multivariate analysis of the risk factors for infections can be performed on desk-top personal computers with statistical program packages (Shapiro et al., 1984; Wenzel, 1986). Such analysis of the risk factors for acquisition of nosocomial infection will help to target more effectively infection-control measures, teaching, prevention, etc. At present, in our hospitals, increasingly sophisticated computing systems are found, microcomputers flourish and there is improved communication capability between individual computers. Together these changes have created an appetite for information and applications (Black, 1989). Now the White Paper (Working for Patients Cm 555) has added impetus in this direction by calling for an expansion of the Resource Management Initiative to increase knowledge of the costs of patient care. What could be achieved by better communication of information systems within the hospital in terms of infection control? Viewed in isolation, the reports from a microbiology laboratory are of limited value in assessing the prevalence and incidence of nosocomial infection. More useful information derives from the combination of microbiological data and other

Information,

computers

and infection

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computerized patient data, e.g. pharmacy, radiology, admissions, operating theatre, etc. The more detailed and accurate these other sources are, the more sophisticated will be the infection report. Furthermore, the process should continue in the background, the laboratory computer automatically scanning microbiological and epidemiological data and able to detect, for example, clusters of infection that at present go unnoticed. If these interconnections seem far from reality they are not. An example of such a computing system is in use in the LDS Hospital in Salt Lake City, Utah. The HELP (Health Evaluation by Logical Processing) system receives input from clinical areas such as cardiology, physiotherapy, pharmacy, medical records, clinical laboratories, nursing, surgery and intensive-care monitoring devices (Pryor et al., 1983). As only one of numerous tasks, the HELP system reviews all patients’ microbiology results, as well as information on the long-term patient file (to detect previous admissions), surgery (date and type), radiology (chest X-ray results), nursing (isolation information), physiotherapy (purulence of respiratory secretions) and pharmacy (antibiotic use). The system can detect ‘nosocomial infection’ as determined by preset criteria such as positive culture result in a catheter specimen of urine which follows a previously clear sample. The computer logic has also been developed to identify those patients not receiving antibiotics to which the patient’s isolates are susceptible, those for whom a cheaper suitable antibiotic is available and those patients receiving ‘prophylactic’ antibiotics more than 48 h after surgery, in the absence of evidence of infection (Evans et al., 1986). By comparing the patient’s pharmacy record with the planned time for surgery, reminders are !generated should the surgeon have failed to prescribe appropriate antibiotic prophylaxis. The Quality Assurance Department also uses information from the HELP system, to monitor wound infection rates for clean surgery, by ward and surgical service and they will soon retrieve surgeon specific rates which may influence the decision to reappoint a surgeon (such sensitive data are kept in a restricted local network rather than in the larger system). In the United States, accreditation of hospitals requires continued monitoring of hospital-acquired infection rates and antibiotic use. The extension of the Resource Management Initiative in this country and the moves towards more detailed clinical audit call for greater knowledge of these and other aspects of patient care. In Britain’s first steps towards interest is now being shown in potential ‘clinical ‘quality assurance’, outcome indicators’ in assessing the quality of care patients receive in hospital (Shaw, 1989). Included in such indicators may be the incidence of adverse events such as surgical wound infection after clean or clean/contaminated surgery, the initiation of antibiotic administration 24 h or more after a full-term vaginal delivery in hospital, pneumonia in patients in special-care units and infections related to intravenous access devices (Shaw, 1989). In more general terms there may be moves towards the

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Information,

computers

and infection

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routine investigation and recording of ‘critical events’ as a means of monitoring quality of health care; included among such events are nosocomial infections. The microbiology computer has still more to offer in the management of infection. The provision of current background-sensitivity data permit a more rational prediction of empirical therapy in the management of infection, both inside and outside the hospital (Phillips, 1978). Analysis of the sensitivity patterns of isolates from different anatomical sites and geographical sites in the hospital have shown remarkable variations. Sensitivity patterns change over time, not only over years but also in the short term as may occur in an epidemic involving a resistant organism. It is possible to refine and improve the choice of initial empirical therapy in the management of infection (Manncke & Heizmann, 1988). Perhaps we can look forward to improved analysis of patterns of infecting organisms and their sensitivities in particular groups of patients, which in conjunction with some refinement from human experts may produce readily accessible suggestions for the empirical and indeed definitive treatment of infection (Gransden, 1988). The advantages and costs of the use of computers in infection control remain to be established (Wenzel & Streed, 1989). However, it seems likely that we may anticipate within the health service further expansion in the quality of information held on computers about many aspects of patients and the care they receive. Such information will be put to differing uses with a large degree of overlap: in the management of scarce resources, in the production of performance indicators, and in the measurement of the quality of patient care. Microbiologists and others interested in the control of infection should be aware of the enormous potential of such systems and must be ready to add their requirements to the specification for new systems, if they are to make any use of the information that could be available. This paper is based, in part, on experience at the LDS possible by the Hospital Infection Society Travelling

Hospital, Salt Lake City, Scholarship.

W. R. Gransden

Utah,

made

Department of Microbiology U.M.D.S. St. Thomas’ Campus London SE1 7EH References

Andrews, H. J. & Vickers, M. (1974). microbiology reporting at Charing 185-191. Black, N. (1989). Information please-and Blair, J. N. & Brown, P. P. (1981). An description of its development and Pathology 34, 1132-1137.

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quick. British Medical Journal 298, 586-587. on-line computer system for hospital bacteriology: comments after five years’ use. Journal of Clinical

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Casewell, M. W. (1980). Surveillance of infection in hospitals. Journal of Hospital Infection 1, 293-297. Cruse, P. J. E. (1977). Infection surveillance: Identifying the problems in the high-risk patient. Southern MedicalJournal 70 (Suppl. l), 4-8. Cruse, P. J. E. & Foord, R. A. (1973). A five-year prospective study of 23,649 surgical wounds. Archives of Surgery 107, 206-210. Evans, R. S., Larsen, R. A., Burke, J. P., Gardner, R. M., Meier, F. A., Jacobson, J. A., Conti, M. T., Jacobson, J. T. & Hulse, R. T. (1986). Computer surveillance of hospital-acquired infections and antibiotic use. Journal of the American Medical Association 256, 1007-l 011. Feldman, R. G. & Ridgway. G. L. (1988). Database handling for infection control and 11 (Suppl. A), 3742. hospital epidemiology. journal of‘Hospita1 Infection French. G. L.. Cheng. A. & Farrineton. M. (1987). Prevalence survey of infection in a Hong Kong hospital u~ng a standayd protocol and microcomputer data analysis. Journal of Hospital Infection 9, 132-142. Gaunt. P. N. & Phillips, I. (1987). Computers and hospital infection. journal of_ Hospital _ Infection 9, 106-lb91 1 ’ Goodwin. C. S. (1976). Comouter minting and filing of microbioloev reoorts. 2 Evaluation and comparison with a manual-system: and comparison of two manual systems. Journal of Clinical Pathology 29, 553-560. Goodwin, C. S. & Smith, C. B. (1976). Computer printing and filing of microbiology reports. 1 Description of the system. Journal of Clinical Pathology 29, 543-552. Gransden, W. R. (1988). The St Thomas’ bacteraemia database, Medical Microcomputer Workshop [Abstract S), Middlesborough. A strategy for Haley, R. W. (1986). Managing hospital infection control for cost-effectiveness: reducing infectious complications. American Hospital Publishing, Inc. and advantage to clinicians of a Manncke, K. & Heizmann, W. (1988). B enefit computer-assisted diagnosis and database system. Infection 16, 75-80. Phillips, I. (1978). The computer in a microbiology department. In Computing in Clinical Laboratories (Siemaszko, F., Ed.), pp. 265-268. London: Pitman Medical. Pryor, T. A., Gardner R. M., Clayton, P. D. & Warner, H. R. (1983). The HELP system. Journal of Medical Systems 7, 87-102. Ridgway, G. L., Batchelor, J., Luton, A. & Barnicoat, M. (1980). Data processing in microbiology: an integrated, simplified system. Journal of Clinical Pathology 33, 744-749. Shaw, C. D. (1989). Clinical outcome indicators. Health Trends 21, 37-39. Shapiro, M., Simchen, E., Israeli, S. & Sacks, T. G. (1984). A multivarate analysis of risk factors for acquiring bacteriuria in patients with indwelling urinary catheters for longer than 24 hours. Infection Control 5, 525-532. Sneath, P. H. A. (1969). Computers in bacteriology. Journal of Clinical Pathology 22 (Suppl. Coil. Path. 3), 87-92. Wenzel, R. P. (1986). The evolving art of hospital epidemiology. Journal of Infectious Diseases 153, 462470. Wenzel, R. P. & Streed, S. A. (1989). Surveillance and use of computers in hospital infection control. Journal of Hospital Infection 13, 217-229. Williams, K. N., Davidson, J. M. F., Lynn, R., Rice, E. & Phillips, I. (1978). A computer system for clinical microbiology. Journal of Clinical Pathology 31, 1193-l 201.

Information, computers and infection control.

Journal of Hospital Infection (1990) 15, 1-5 LEADING Information, ARTICLE computers and infection control Computerization was an early and obvi...
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