Extending the use of clinical audit data: a resource planning model.

OBJECTIVE To create a means by which we can examine and understand the interrelations among the fundamental elements of hospital inpatient care (patients, beds, theatre time, and staff). DESIGN Predictive study of resource utilisation based on a computerised clinical information system of five years' audit data from a surgical management system. SETTING One surgical firm (of one consultant, one registrar, and one preregistration houseman) in a district general hospital. PATIENTS 5267 Patients whose admission records were part of the five years' audit of surgical management. MAIN OUTCOME MEASURES Mean length of stay; number of occupied beds; turnover interval; throughput (patients/bed); percentage elective theatre occupancy; waiting time for elective admissions; and theatre, hotel, and total costs. RESULTS Predicted outcome was analysed in the model, taking the actual outcomes in 1988-9 as baseline values, for four clinical scenarios: an increase in accident and emergency admissions, a reduction in beds, a reduced length of stay, and creation of a new firm. Baseline values showed a mean stay of just over five days in 15 beds and with a theatre occupancy of 94%; the total cost was 812,000 pounds (hotel costs 597,000 pounds). Increasing the accident and emergency admissions to 460/year (19%), based on projected trends from 1984 to 1988, resulted in increased hotel costs (55,000 pounds) and reducing bed numbers (by halving admissions) in decreased use of theatres to 71%, decreased throughput, and increased waiting time, from 20 to 92 weeks, at a saving of 99,000 pounds (12%). Reducing stay marginally reduced bed occupancy (8%) and hotel costs (14%), and creating a new surgical team considerably reduced bed occupancy (14%) and waiting time for elective operations (by 20%). The minimum number of beds for referrals, accident and emergency admissions, and planned admissions was 9.0; that for urgent elective admissions was 3.3 and for non-urgent admissions was 2.4. CONCLUSION A well designed clinical information system with the routine collection of data can provide the necessary output data to enable resource modelling. IMPLICATION Use of such a model will allow clinicians to participate in resource planning on the basis of what is actually happening within the hospital.