How can postoperative delirium be predicted in advance? A secondary analysis comparing three methods of early assessment in elderly patients.

BACKGROUND: Postoperative impairment of the cerebral function can appear immediately after general anesthesia and may be predictive for a postoperative delirium. We compared three tools assessing patients on recovery room admission in order to detect early signs of postoperative brain dysfunction: the Postanesthetic Recovery Score (PARS), the Richmond Agitation-Sedation Scale (RASS) and the Nursing Delirium Screening Scale (Nu-DESC). METHODS: Inclusion criteria of this secondary analysis of the randomized SuDoCo trial were: age ≥60 years, schedule for elective non-cardiac surgery with an anticipated duration of ≥60 minutes, general anesthesia, ability to communicate in German language. A total of 996 patients were analyzed. Investigated scores were assessed 10 minutes after recovery room admission and analyzed in terms of association with postoperative delirium, mortality and length of stay in the recovery room. Multivariate analysis: linear or logistic regression. RESULTS: Abnormal scores in patients: RASS (values ≤-2 and ≥1) 36.8%, Nu-DESC (≥2 points) 54.2%, PARS (≤7 points) 20.3%. Abnormal RASS values were associated with postoperative delirium (RASS values ≥1: odds ratio (OR) 3.1, 95% CI: 1.7-5.6, P<0.001; RASS values ≤-2: OR=2.1, 95% CI: 1.3-3.3, P=0.001). Abnormal Nu-DESC values were also associated with postoperative delirium (OR=2.4, 95% CI: 1.5-3.9, P<0.001). Abnormal PARS values were associated with a longer recovery room stay (in minutes, OR=16.6, 95% CI: 1.7-31.4, P=0.029). CONCLUSIONS: The RASS and Nu-DESC were independent predictors for a delirium within seven postoperative days. Very early assessment of the cerebral function may help to advance detection, prevention and treatment of postoperative delirium in elderly patients.

An analysis of a case manager-driven emergent dialysis program.

PURPOSE OF THE STUDY: With the undocumented immigrant population in the United States on the rise, an increase in the number of patients with end-stage renal disease without access to a regular dialysis chair continues. This leaves hospital systems with the difficult decision of how best to care for this population. We sought to evaluate the feasibility, effectiveness, and costs of a case manager-driven emergent dialysis program. We hypothesized that this program would be feasible and would result in similar costs as the previous regularly scheduled dialysis program in place at our institution. PRIMARY PRACTICE SETTING: The study was conducted at Wishard Memorial Hospital, which is an urban public hospital in Indianapolis, IN. METHODOLOGY AND SAMPLE: We performed a before (March 11, 2010, to June 11, 2010) and after (June 14, 2010, to September 14, 2010) study to compare the treatment of a 6-patient cohort of dialysis patients without a "dialysis home" before and after the case manager-driven emergent dialysis program, using secondary data. RESULTS: The case manager-driven emergent dialysis process was feasible and led to a total expense of $101,802 as compared with a total cost of $122,890 when providing regular dialysis to this subset of patients. There were no differences in intensive care unit days, length of stay, and complications between the 2 groups in the short study period. IMPLICATIONS FOR CASE MANAGEMENT PRACTICE: The dialysis population without a "dialysis home" is a high-risk population in need of intensive medical care but the approach to these patients continues to be debated. Although this study does not prove or necessarily support a dialysis on "emergent" basis approach over chronic, scheduled dialysis, the study does demonstrate that case management can play a significant role in the care of these patients. Case management oversight and management of our patient population resulted in costs equal to, or better than, those who received chronic dialysis care without a difference in complications over a 6-month study period.

Preparing for an aging population and improving chronic disease management.

New models of health care delivery are inevitable. There is likely to be increasing emphasis on patient self-monitoring, health care delivery at patient homes, interdisciplinary treatment plans, a greater percentage of medical care delivered by non-physician health professionals, targeted health educational materials, and greater involvement and training of informal caregivers. The Information Technologies (IT) infrastructure of health systems will need to adapt. We have begun sorting out the implications of this future within a County public hospital system: defining the desirable features, relevant technologies, necessary modifications to the network, and additional data elements to be captured. We seek to build an infrastructure that will support new patient-focused technologies designed to more efficiently and effectively support older individuals. We hypothesize utility to further exploring the impact that new health care delivery models will have on health systems' IT infrastructures.