Implementation of a clinical information system in nurse-managed care.

The Penn Nursing Network Information System Project is a collaborative effort of practitioners, academic researchers, and a health-care software developer. The Penn Nursing Network, a group of nurse-managed practices owned and operated by the University of Pennsylvania School of Nursing, has taken a leadership role in the project. PNN is developing an information system specific to the needs of nurse-managed care and creating a data warehouse for nursing centres in the Philadelphia region. Important components of this project include the identification of key data elements to represent the problems treated, interventions performed, and outcomes sensitive to the nursing care provided. The Omaha System provided a useful framework for capturing the necessary data elements. However, additional data were needed. In addition, attention was paid to the development of a software program that would complement the workflow of the practitioner while capturing data efficiently. The main goal of the project is development of a longitudinal database reflective of clinical practice, to be used for both research and evaluation.

The concept of integration: a foundation for evaluating outcomes of nursing care.

Changes in the health care environment, an aging population, and an increase in chronic health conditions require consideration of the adequacy of concepts available for demonstrating the effectiveness of nursing care. One concept that has potential utility for nursing in this regard is the concept of integration. Analysis of the concept of integration was conducted to alleviate existing ambiguity and to explore ways in which this concept has been employed in diverse disciplines. The concept of integration is characterized primarily as a process of combination: two or more elements are merged with sufficient interaction so that unity of the newly formed entity is achieved. The attributes of the concept of integration, therefore, include process, combination, interaction, and unity. The concept of integration is useful in evaluation of reconciliation of past and present identities and altered role relationships within the environment.

Testing the Uniform Needs Assessment Instrument for hospital discharge planning with older adults.

The Uniform Needs Assessment Instrument (UNAI) was developed to systematically assess the continuing care needs of high-risk older adults in response to the 1986 Omnibus Budget Reconciliation Act. Based on previous studies, a revised UNAI was tested with 103 hospitalized older adults, comparing usual discharge planning with the UNAI. High interrater reliability was obtained. The UNAI had high (> or = 85%) sensitivity and specificity when comparing needs identification on the UNAI with subjects' reported needs at 10 to 14 days after discharge. Overall, the UNAI was more effective (sensitive and specific).

Evaluating physical functional outcomes: one category of the NOC system.

All professional health care disciplines are now being held accountable to demonstrate the outcomes they produce. It is imperative that nurses demonstrate the difference they make in patient care to justify the cost of professional nursing. Standardized language is needed to aggregate data and report information on nursing interventions and associated outcomes. The Nursing Outcomes Classification (NOC) system is the first comprehensive classification of nursing-sensitive patient outcomes. In this review, the development of this classification system with specific results related to physical functional status and implications of NOC for nursing practice are discussed.

Optimization of decision support tool using medication regimens to assess rehospitalization risks.

BACKGROUND: Unnecessary hospital readmissions are costly for the U.S. health care system. An automated algorithm was developed to target this problem and proven to predict elderly patients at greater risk of rehospitalization based on their medication regimens. OBJECTIVE: Improve the algorithm for predicting elderly patients' risks for readmission by optimizing the sensitivity of its medication criteria. METHODS: Outcome and Assessment Information Set (OASIS) and medication data were reused from a study that defined and tested an algorithm for assessing rehospitalization risks of 911 patients from 15 Medicare-certified home health care agencies. Odds Ratio analyses, literature reviews and clinical judgments were used to adjust the scoring of patients' High Risk Medication Regimens (HRMRs). Receiver Operating Characteristic (ROC) analysis evaluated whether these adjustments improved the predictive strength of the algorithm's components. RESULTS: HRMR scores are composed of polypharmacy (number of drugs), potentially inappropriate medications (PIM) (drugs risky to the elderly), and Medication Regimen Complexity Index (MRCI) (complex dose forms, dose frequency, instructions or administration). Strongest ROC results for the HRMR components were Areas Under the Curve (AUC) of .68 for polypharmacy when excluding supplements; and .60 for PIM and .69 for MRCI using the original HRMR criteria. The "cut point" identifying MRCI scores as indicative of medication-related readmission risk was increased from 20 to 33. CONCLUSION: The automated algorithm can predict elderly patients at risk of hospital readmissions and its underlying criteria is improved by a modification to its polypharmacy definition and MRCI cut point.

Exploring the value of clinical data standards to predict hospitalization of home care patients.

BACKGROUND: There is a critical need to reduce hospitalizations for Medicare patients and electronic health record (EHR) home care data provide new opportunities to evaluate risk of hospitalization for patients. OBJECTIVES: The objectives of this study were to 1) develop a measure to predict risk of hospitalization among home care patients, the Hospitalization Risk Score (HRS), and 2) compare it with an existing severity of illness measure, the Charlson Index of Comorbidity (CIC). METHODS: A convenience sample of clinical data from 14 home care agencies' EHRs, representing 1,643 home care patient episodes was used for the study. The development of the HRS was based on review of the literature, and expert panel evaluation to construct the HRS. Descriptive statistics and generalized linear models were used for comparative analysis; areas under curve (AUC) values were compared for receiver operating curves (ROC), and cut points predicting hospitalization were evaluated. RESULTS: The HRS for this sample ranged from 0 to 5.6, with a median of 1.25. The CIC for this sample ranged from 0 to 9 and with a median of 0. Nearly three fourths of the sample was hospitalized at an HRS of 2, and a CIC of 1. AUC values for ROC were 0.63 for HRS and 0.59 for the CIC. The ROC curves were significantly different (t = -7.59, p <0.003). CONCLUSIONS: This preliminary study demonstrates the potential value of the HRS using Omaha System EHR data. There was a statistically significant difference for predicting hospitalization of home care patients with the HRS versus the CIC; however the AUC values for both were low. Continued research is needed to further refine the HRS, determine whether it is more sensitive for particular subgroups of patients, and combine it with additional risk factors in understanding rehospitalization.

Analysis of free text with omaha system targets in community-based care to inform practice and terminology development.

The Omaha system is one of the most widely used interface terminologies for documentation of community-based care. It is influential in disseminating evidence-based practice and generating data for health care quality research. Thus, it is imperative to ensure that the Omaha system reflects current health care knowledge and practice. The purpose of this study was to evaluate free text associated with Omaha system terms to inform issues with electronic health record system use and future Omaha system standard development. Two years of client records from two diverse sites (a skilled homecare, hospice, and palliative care program and a maternal child health home visiting program) were analyzed for the use of free text as a component of the intervention when structured targets for interventions were not identified. Intervention text entries very commonly contained duplicate "carry forward entries", multiple concepts, mismatched problem focus, or failure to identify an existing appropriate target. Our findings support the need to better address education gaps for clinicians. We identified additional suggested targets for Omaha system problems, and propose new targets for consideration in future Omaha system revisions.

Evidence-based Standardized Care Plans for Use Internationally to Improve Home Care Practice and Population Health.

OBJECTIVES: To develop evidence-based standardized care plans (EB-SCP) for use internationally to improve home care practice and population health. METHODS: A clinical-expert and scholarly method consisting of clinical experts recruitment, identification of health concerns, literature reviews, development of EB-SCPs using the Omaha System, a public comment period, revisions and consensus. RESULTS: Clinical experts from Canada, the Netherlands, New Zealand, and the United States participated in the project, together with University of Minnesota School of Nursing graduate students and faculty researchers. Twelve Omaha System problems were selected by the participating agencies as a basic home care assessment that should be used for all elderly and disabled patients. Interventions based on the literature and clinical expertise were compiled into EB-SCPs, and reviewed by the group. The EB-SCPs were revised and posted on-line for public comment; revised again, then approved in a public meeting by the participants. The EB-SCPs are posted on-line for international dissemination. CONCLUSIONS: Home care EB-SCPs were successfully developed and published on-line. They provide a shared standard for use in practice and future home care research. This process is an exemplar for development of evidence-based practice standards to be used for assessment and documentation to support global population health and research.

The Nursing Minimum Data Set: abstraction tool for standardized, comparable, essential data.

The Nursing Minimum Data Set (NMDS) represents the first attempt to standardize the collection of essential nursing data. These minimum core data, used on a regular basis by the majority of nurses in the delivery of care across settings, can provide an accurate description of nursing diagnoses, nursing care, and nursing resources used. Collected on an ongoing basis, a standardized nursing data base will enable nurses to compare data across populations, settings, geographic areas, and time. Public health nurses will be able to evaluate and compare services. The purpose of this article is to discuss briefly the following aspects of the NMDS: background including definition, purposes, and elements; availability and reliability of the data; benefits; implications of the NMDS with emphasis on nursing research; and health policy decision making.

Development of the home care client satisfaction instrument.

Client (patient) satisfaction has been studied extensively in the health care sector, yet those receiving home health care services have been the focus of few studies. The purpose of this study was to test the reliability and validity of the Home Care Client Satisfaction Instrument (HCCSI). A total of 400 clients, randomly selected from 20 randomly chosen home care agencies in one state, completed the HCCSI and demographic form. Most respondents were older adults with multiple health problems and their families or informal support systems. Since data were skewed, item analysis was used. The revised instrument (HCCSI-R) is unidimensional and includes 12 items rated on a 5-point Likert scale measuring specific aspects of care. In addition, there are three global measures of satisfaction rated on a 10-point scale. All items except one had significant item-total correlations greater than .59. The total score correlates with likeliness to recommend the agency to others (.37, p = .0001), showing some evidence for criterion-related validity.