ABSTRACT
OBJECTIVE: To provide a report on year 1 results of a national study investigating nursing home information technology (IT) adoption, called IT sophistication. METHODS: A reliable and valid survey was used to measure IT sophistication. The target goal was 10% from each state in the United States, 1570 nursing homes. A random sample of homes from each state was recruited from Nursing Home Compare. RESULTS: The team reached 2627 nursing home administrators, among whom 1799 administrators agreed to participate and were sent a survey. A total of 815 surveys were completed (45.3% response rate), which was below the goal. Facilities in the participating sample have similar demographic characteristics (ownership, total population in a location, and bed size) to the remaining homes not participating. There are greater IT capabilities in resident care and administrative activities, less in clinical support. The extent of use of these capabilities appears to be highest in administrative activities and lowest in clinical support. IT in resident care appears to be the most integrated with internal and external stakeholders. IT capabilities appear to be greater than IT extent of use in all health domains, with the greatest difference in resident care. DISCUSSION: National evaluations of nursing home IT are rare. Measuring trends in IT adoption in a nationally representative sample provides meaningful analytics that could be more useful for policy makers and nursing home leaders in the future. CONCLUSION: Discovering national baseline assessments is a first step toward recognizing nursing home trends in IT adoption.
Subject(s)
Information Technology/statistics & numerical data , Nursing Homes/statistics & numerical data , Health Care Surveys , Information Systems/statistics & numerical data , United StatesABSTRACT
PURPOSE: Diagnostic delay in distinguishing psychogenic nonepileptic seizures (PNES) from epileptic seizures may result in unnecessary therapeutic interventions and higher health care costs. Previous studies demonstrated that video-recorded eye closure is associated with PNES. The present study prospectively assessed whether observer or self-report of eye closure could predict PNES, prior to video-EEG monitoring. METHODS: Adults referred to an epilepsy monitoring unit (EMU) were prospectively enrolled into the study. At baseline, self-report of eye closure was assessed by questionnaire, and observer report was obtained by interview. Physicians viewed video clips independent of EEG tracings and determined the duration of eye closure during PNES and epileptic seizures. We evaluated whether video-recorded eye closure identified an episode as PNES using random effects models that accounted for episode clustering by subject. The utility of observer and self-report of eye closure in predicting a diagnosis of PNES was tested using logistic regression. RESULTS: Of 132 enrolled subjects, 112 met study criteria during EMU stay for either PNES (n = 43, 38.4%) or epilepsy (n = 84, 75.0%). Fifteen of the 43 PNES subjects (34.9%) had coexisting epilepsy. Self and observer reports of eye closure were neither sensitive nor specific for the diagnosis of PNES. Self-report of eye closure more accurately predicted actual video-recorded eye closure than observer report. Video-recorded eye closure was 92% specific, but only 64% sensitive for PNES identification. DISCUSSION: Neither observer nor self-report of eye closure, prior to VEEG monitoring, predicts PNES. Video-recorded eye closure may not be as sensitive an indicator of PNES as previously reported.