Preliminary Evaluation of a Guideline Classification System

In a previous paper, we presented a proposed expansion of the National Guideline Clearing-house (NGC) classification1. We performed a preliminary evaluation of the classification based on 100 guidelines randomly selected from the NGC collection. We found that 89 of the 100 guidelines could be assigned to a single guideline category. To test inter-observer agreement, twenty guidelines were also categorized by a second investigator. Agreement was found to be 40-90% depending on the axis, which compares favorably with agreement among MeSH indexers (30-60%)2. We conclude that categorization is feasible. Further research is needed to clarify axes with poor inter-observer agreement.

Patient classification system: An integrated method for measuring nursing intensity and optimizing resource allocation

A patient classification system was developed integrating a patient acuity instrument with a computerized nursing distribution method based on a linear programming model. The system was designed for real-time measurement of patient acuity (workload) and allocation of nursing personnel to optimize the utilization of resources.^ The acuity instrument was a prototype tool with eight categories of patients defined by patient severity and nursing intensity parameters. From this tool, the demand for nursing care was defined in patient points with one point equal to one hour of RN time. Validity and reliability of the instrument was determined as follows: (1) Content validity by a panel of expert nurses; (2) predictive validity through a paired t-test analysis of preshift and postshift categorization of patients; (3) initial reliability by a one month pilot of the instrument in a practice setting; and (4) interrater reliability by the Kappa statistic.^ The nursing distribution system was a linear programming model using a branch and bound technique for obtaining integer solutions. The objective function was to minimize the total number of nursing personnel used by optimally assigning the staff to meet the acuity needs of the units. A penalty weight was used as a coefficient of the objective function variables to define priorities for allocation of staff.^ The demand constraints were requirements to meet the total acuity points needed for each unit and to have a minimum number of RNs on each unit. Supply constraints were: (1) total availability of each type of staff and the value of that staff member (value was determined relative to that type of staff's ability to perform the job function of an RN (i.e., value for eight hours RN = 8 points, LVN = 6 points); (2) number of personnel available for floating between units.^ The capability of the model to assign staff quantitatively and qualitatively equal to the manual method was established by a thirty day comparison. Sensitivity testing demonstrated appropriate adjustment of the optimal solution to changes in penalty coefficients in the objective function and to acuity totals in the demand constraints.^ Further investigation of the model documented: correct adjustment of assignments in response to staff value changes; and cost minimization by an addition of a dollar coefficient to the objective function. ^

Classification of support staff in a consortium medical library: a case study.

A representative committee of Houston Academy of Medicine-Texas Medical Center Library staff and faculty, under the direction of the library administration, successfully redesigned a job classification system for the library's nonprofessional staff. In the new system all nonprofessionals are assigned to one of five grade levels, each with a corresponding salary range. To determine its appropriate grade level each job is analyzed and assigned a numerical value using a point system based on a set of five factors, each of which is assigned a relative number of points. The factors used to measure jobs are: education and experience, complexity of work, administrative accountability, manual skill, and contact with users. Each factor is described according to degrees, so that a job can be given partial credit for a factor. An advisory staff classification committee now participates in the ongoing administration of the classification system.