Measuring the Total Amount of Care Needed by Clinical Surgical Patients

Wednesday, July 13, 2011: 2:05 PM

Catharina J. Oostveen, RN, MSc
Department of surgery, Academic Medical Center Amsterdam, Amsterdam, Netherlands

Learning Objective 1: The learner will be able to gain insight in the complex theory of measuring surgical patients demand for care.

Learning Objective 2: The learner will be able to get insight in a model to predict medical and nursing care needed, based on readily available clinical data.

Purpose:

Development of an instrument based on readily available parameters to determine the total demand for medical and nursing care in surgical patients.

Hospitals provide care for patients with a variety of diseases, co-morbidities and complications.  The amount of care these different patients require is unclear. Given the recent developments such as aging, multimorbidity and stagnating growth of the population, it is important for caregivers and managers to identify the factors determining the (trends in the) demand and costs for care.

Methods:  

Six surgical wards in a Dutch university hospital participated during 7 weeks. Surgeons, nurses and paramedical personnel recorded the time spent on patient care 24/7 by means of PDAs. Possibly determining factors were based on a previous systematic literature review and an expert focus group: number of care pathways, surgical intervention, age, gender,  co-morbidities, complications, medication at admission, ASA-classification, body mass index, nutritional status, medical specialty, delirium, pressure ulcers, patient isolation, admission and discharge type, and mortality. Total amount of care needed by the patients was expressed as costs involved in medical and nursing time, surgical interventions and diagnostics. Linear regression analysis was applied to detect significant independent determinants.

 Results:

In total, 174 surgical patients were monitored. Median costs for care were €8455 per patient. Factors significantly influencing the amount of care needed were: Medication at admission, complications, co-morbidity, medical specialty, ASA-classification, as well as surgical interventions and length of stay.

Conclusion:

We were able to develop an instrument that predicts the total (costs of) care needed for surgical patients in a university hospital. The input for this instrument can be derived from readily available data in hospital databases. This instrument may help caregivers and managers to appreciate the amount of care needed on (surgical) wards and may be used to appreciate any trends in time.