Marcelline R. Harris

The Stability and Workload Index for Transfer score predicts unplanned intensive care unit patient readmission: initial development and validation.

Objective:Unplanned readmission of hospitalized patients to an intensive care unit (ICU) is associated with a worse outcome, but our ability to identify who is likely to deteriorate after ICU dismissal is limited. The objective of this study is to develop and validate a numerical index, named the Stability and Workload Index for Transfer, to predict ICU readmission. Design:In this prospective cohort study, risk factors for ICU readmission were identified from a broad range of patients’ admission and discharge characteristics, specific ICU interventions, and in-patient workload measurements. The prediction score was validated in two independent ICUs. Setting:One medical and one mixed medical-surgical ICU in two tertiary centers. Patients:Consecutive patients requiring >24 hrs of ICU care. Interventions:None. Measurements:Unplanned ICU readmission or unexpected death following ICU dismissal. Results:In a derivation cohort of 1,131 medical ICU patients, 100 patients had unplanned readmissions, and five died unexpectedly in the hospital following ICU discharge. Predictors of readmission/unexpected death identified in a logistic regression analysis were ICU admission source, ICU length of stay, and day of discharge neurologic (Glasgow Coma Scale) and respiratory (hypoxemia, hypercapnia, or nursing requirements for complex respiratory care) impairment. The Stability and Workload Index for Transfer score predicted readmission more precisely (area under the curve [AUC], 0.75; 95% confidence interval [CI], 0.70–0.80) than the day of discharge Acute Physiology and Chronic Health Evaluation III score (AUC, 0.62; 95% CI, 0.56–0.68). In the two validation cohorts, the Stability and Workload Index for Transfer score predicted readmission similarly in a North American medical ICU (AUC, 0.74; 95% CI, 0.67–0.80) and a European medical-surgical ICU (AUC, 0.70; 95% CI, 0.64–0.76), but was less well calibrated in the medical-surgical ICU. Conclusion:The Stability and Workload Index for Transfer score is derived from information readily available at the time of ICU dismissal and acceptably predicts ICU readmission. It is not known if discharge decisions based on this prediction score will decrease the number of ICU readmissions and/or improve outcome.

Discharge Planning, Transitional Care, Coordination of Care, and Continuity of Care: Clarifying Concepts and Terms from the Hospital Perspective

SUMMARY Hospital discharge planning is a key element of continuity of care for persons leaving the hospital. Yet many important questions regarding processes and effects of discharge planning have not been addressed, in part because the multiple terms associated with discharge planning have not been consistently defined or used. Failure to clearly name, define, and consistently use terms creates a barrier that inhibits scientific progress and best practice. This article reviews the use of terms and definitions and compares concepts associated with hospital discharge planning across key documents frequently referenced by hospitals. A conceptual model is proposed to facilitate consistent use of these concepts.

FIM score, FIM efficiency, and discharge disposition following inpatient stroke rehabilitation

&NA; The Functional Independence Measure™ (FIM) is a widely accepted scale used to measure the functional abilities of patients undergoing rehabilitation. Scores at the extremes of this scale correlate with discharge disposition, while mid‐range scores are less well understood. This study evaluated the rate of FIM change with time (“efficiency”), admission and discharge FIM scores, and discharge disposition of 748 patients who underwent stroke inpatient rehabilitation. Patients with low scores at admission or discharge were likely to be discharged to a facility (63% and 78%, respectively), and those with high scores at admission or discharge almost always returned home (88% and 81%, respectively). Those with midrange scores at admission were more likely to return home (62%) than those with similar scores at discharge (33%). Greater FIM efficiency scores were associated with home discharge. Findings provide insight into discharge planning for stroke patients and indicate the need for more detailed evaluation of the midrange group.

Development and validation of a screen for specialized discharge planning services.

Background: There is no rigorously developed and empirically validated screening tool to identify, early in the hospital stay, those adults who will use specialized hospital discharge planning services. Objectives: To develop and validate a screen using hospital admission clinical data that discriminates between adults who use and do not use specialized discharge planning services. Methods: Subjects consisted of prospectively sampled adult patients admitted to two hospitals located in a Midwestern United States city in 1998 (tool development sample, n = 991) and 2002 (validation sample, n = 303). Variables suggestive of being predictive of use of specialized hospital discharge planning services were identified from the literature and were obtained from direct participant interviews, record review, and administrative databases. The outcome was a documented referral for involvement of specialized discharge planning personnel with the patients plan of care and was identified from review of hospital records. Results: Of 24 variables examined, only age, disability, living alone, and self-rated walking limitation were jointly predictive of use of specialized discharge planning services in the development sample. Standardized coefficients from the joint model were used to estimate a screening score. A cut-point was derived and had a sensitivity of 75% and specificity of 78% in the development sample. The screen performed equally well in the validation sample and the development sample. Conclusion: A screening tool consisting of a limited number of characteristics readily available early in the hospital stay that were shown to be highly predictive of the use of specialized discharge planning services was developed. The application of such a tool will hopefully assist providers to deploy services appropriately and in a timely fashion.

Assessing Suicide Ideation:Comparing Self-Report Versus Clinician Report

BACKGROUND: The accurate identification of suicidal individuals is an important but complex process. Common approaches to suicide assessment include self-report tools and clinician interview. PURPOSE: The purpose of this study was to examine and compare two assessment methods for determining suicidal ideation of patients admitted for treatment of a mood or anxiety disorder. DESIGN: A secondary analysis of an existing dataset was conducted. Sixty-eight inpatients treated for mood or anxiety disorders completed the Beck Depression Inventory (BDI) and were assessed by a clinician using an investigator-developed interview schedule. One item from BDI and one question from the interview schedule were used to compare two methods for assessing suicidal ideation. RESULTS: In 80% of cases, responses were in agreement between the two assessment methods. However, disagreement between assessment methods was found for 13 (19.4%) cases. The rate of disagreement was beyond chance (p = .00). CONCLUSION: The findings support inclusion of both a self-report method and a face-to-face interview to assess suicide ideations. Further research is warranted to examine if both methods for assessing suicide ideations are indicated during the first 24 hours after admission to an inpatient unit. J Am Psychiatr Nurses Assoc, 2004; 10(1), 9-15.

A term extraction tool for expanding content in the domain of functioning, disability, and health: proof of concept

Among the challenges in developing terminology systems is providing complete content coverage of specialized subject fields. This paper reports on a term extraction tool designed for the development and expansion of terminology systems concerned with functioning, disability, and health. Content relevant to this domain is the emphasis of the foci and targets of many nursing terminologies. We extend previously published term extraction algorithms by applying two filters. The first filter is based on the raw frequency of the content words in the lexical string under consideration. The second filter applies the notion of a complete syntactic node to discover relevant noun or verb phrases. While we report on a limited corpus (30,607 words comprising 4103 terms from 60 dismissal note summaries), the recall, precision, and F-measures we observed are encouraging and suggest continued development and testing of the tool is merited.

The first step toward data reuse: disambiguating concept representation of the locally developed ICU nursing flowsheets.

Although an unambiguous and consistent representation is the foundation of data reuse, a locally developed documentation system such as nursing flowsheets often fails to meet the requirement. This article presents the domain modeling process of the ICU nursing flowsheet to clarify the meaning that its contents represent and the lessons learned during the activity. This study has been done as a first step toward reusing the data documented in a computerized nursing flowsheet for an algorithmic decision making. Following the ontology development processes proposed by other researchers, a conceptual model was developed using Protégé. Then, the existing information model was refined by fully specifying the embedded information structures and by establishing linkages to the conceptual model at the finest-grained concept level. Domain knowledge that the experienced nurses provided was critical to correctly interpret the meaning of the flowsheet contents as well as to verify the newly developed models. This study reassured the importance of the roles of a nurse informaticist to develop a computerized nursing documentation system that accurately represents the information needs in nursing practice.

Modeling nursing interventions in the act class of HL7 RIM Version 3

The proposed Health Level 7 Reference Information Model (HL7 RIM) Version 3 is the foundation for expressing data to be communicated across health care information systems. The general objective of this analysis was to examine whether the RIM supports the expression of nursing interventions, considering both terminological and structural perspectives. The Nursing Terminology Summit Interventions Group focused on patient education about breast cancer, an intervention that differs sufficiently from other medical processes already considered by HL7 and represents issues surrounding both definition and execution of nursing process. Relevant actors, actions, and action relationships were culled from use cases and modeled into the proposed RIM structure and attributes by using modified instance diagrams. This method was effective and reproducible, and the RIM proved to be an adequate model for supporting breast cancer education. Additional interventions must be studied to fully assess the adequacy of the model to support all aspects of nursing process and terminology.

Prospective evaluation of a screen for complex discharge planning in hospitalized adults

OBJECTIVES: To test the predictive ability of the Probability of Repeated Admission (PRA) screen for nonroutine discharge planning (requiring new referrals for formal services).

Using present-on-admission coding to improve exclusion rules for quality metrics: The case of failure-to-rescue

Background:The Agency for Healthcare Research and Quality (AHRQ) patient safety indicator “death among surgical inpatients with serious treatable complications” (failure-to-rescue) uses rules to exclude complications presumed to be present-on-admission (POA). Like other administrative data-based quality measures, exclusion rules were developed with limited information on whether complications were POA. We examine whether the accuracy of failure-to-rescue exclusion rules can be improved with data with good POA indicators. Methods:POA-coded data from 243,825 discharges from a large academic medical center were used to develop 3 failure-to-rescue exclusion rules. Data from 82,871 discharges from California hospitals screened for good POA coding practices was used as a validation sample. The AHRQ failure-to-rescue measure and 3 new measures based on alternative exclusion rules were compared on sensitivity, specificity, and C-statistics for prediction of POA status. Using data from the AHRQ HCUP National Inpatient Sample, the alternative specifications were tested for sensitivity to nurse staffing. Results:The AHRQ exclusion rules had sensitivity of 18.5%, specificity 92.1%, and a C-statistic of 0.553. All POA-informed specifications of exclusion rules improved the C-statistic of the failure-to-rescue measure and its sensitivity, with modest losses of specificity. For all tested specifications, higher licensed hours and proportions of registered nurse were statistically significant and associated with lower risk of death. Conclusions:Failure-to-rescue is a robust quality measure, sensitive to nursing across alternative exclusion rule specifications. Despite expanded POA coding, exclusion-based rules are needed to analyze datasets not coded for POA, legacy datasets, and datasets with poor POA coding. POA-informed construction of exclusions significantly improves rules identifying POA complications.