On-line journal of nursing informatics最新文献

Childhood obesity and the resulting co-morbid conditions have become a massive burden for primary caregivers in West Virginia and across the United States. Building culturally sensitive clinical interventions to meet population health needs presents a multi-factorial challenge. Historically it has been is difficult to accurately assess the demographic characteristics of clinic populations. Fortunately, the use of electronic health records (EHR) has created a major shift in clinical documentation and ability to routinely collect essential demographic and clinical data. While data for Meaningful Use under the Centers for Medicare and Medicaid Services is increasingly used to evaluate clinical care and outcomes, use of EHR data outside of the Meaningful Use umbrella has not received sufficient attention. This study explores use of EHR data beyond Meaningful Use to obtain demographic characteristics of an obese and overweight pediatric population in a rural primary care center for the purpose of informing appropriate, locally relevant intervention strategies. We find that the breadth and depth of information recorded on each patient can collectively provide valuable information to describe and evaluate the clinic population, identify priority areas to address, and measure change over time. Application of EHR data to understand the demographic characteristics of this particular patient population highlights the ability to identify target patient populations, uncover critical patient-level and population-level outcomes, inform intervention development and implementation, and add value to efforts in quality improvement systems transformation. Use of EHR data outside of the Meaningful Use umbrella needs increased attention in primary care.

Objective: To examine the relationships among Electronic Health Record (EHR) adoption and adverse outcomes and satisfaction in hospitalized patients.

Materials and methods: This secondary analysis of cross sectional data was compiled from four sources: (1) State Inpatient Database from the Healthcare Cost Utilization Project; (2) Healthcare Information and Management Systems Society (HIMSS) Dorenfest Institute; (3) Hospital Consumer Assessment of Healthcare Providers and Systems Survey (HCAHPS) and (4) New Jersey nurse survey data. The final analytic sample consisted of data on 854,258 adult patients discharged from 70 New Jersey hospitals in 2006 and 7,679 nurses working in those same hospitals. The analytic approach used ordinary least squares and multiple regression models to estimate the effects of EHR adoption stage on the delivery of nursing care and patient outcomes, controlling for characteristics of patients, nurses, and hospitals.

Results: Advanced EHR adoption was independently associated with fewer patients with prolonged length of stay and seven-day readmissions. Advanced EHR adoption was not associated with patient satisfaction even when controlling for the strong relationships between better nursing practice environments, particularly staffing and resource adequacy, and missed nursing care and more patients reporting "Top-Box," satisfaction ratings.

Conclusions: This innovative study demonstrated that advanced stages of EHR adoption show some promise in improving important patient outcomes of prolonged length of stay and hospital readmissions. Strongly evident by the relationships among better nursing work environments, better quality nursing care, and patient satisfaction is the importance of supporting the fundamentals of quality nursing care as technology is integrated into practice.