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Sunday, November 1, 2009
Learning Objective 1: identify hospitalized patient factors that predict referral to nurse case management services.
Learning Objective 2: discuss how automated clinical decision support systems could assist referral to nurse case management and potentially impact on quality of care.
Background: Evidence supports the importance of early discharge planning, beginning shortly after hospital admission, as the most effective way to address the patient needs during shortened hospital stays and to provide for continued services should patient needs persist into the post-discharge environment. Hospital systems have addressed this deficiency through the availability of a specialized practitioner, the nurse case manager (NCM). Referral to the NCM, if early in the hospital care of complex patients, could potentially improve outcomes, such as reduced length of stay, reduced cost of care, and reduced hospital readmission. Purpose: The electronic health record (EHR) has potential to support nurses' clinical decision-making, including assistance in calculating risk for readmission and identifying patients who could benefit from a referral to nurse case management. A recent change in the EHR is the inclusion of an automatic NCM referral based on literature supported patient factors. This retrospective, cohort study will investigate, in a pre- and post- decision-support EHR environment, patient factors present in the nursing admission history of hospitalized medical and surgical patients on predicting referral to NCM services. Sample and Methods: A sample of 175 patients in each the pre- and post-decision support period will be retrospectively reviewed via the EHR for patient factors (IV) and type of referral (DV). Outcome varibles of cost, length of stay and readmission will be investigated. Data Analysis: Logistic regression, ANOVA and Chi square analysis will be used to determine which factors predict referral for NCM. Findings: The study findings will be reported in descriptive and frequencies for the samples and odds ratios with the corresponding confidence intervals will be reported.