Automatic generation of natural language nursing shift summaries in neonatal intensive care: BT-Nurse
نویسندگان
چکیده
INTRODUCTION Our objective was to determine whether and how a computer system could automatically generate helpful natural language nursing shift summaries solely from an electronic patient record system, in a neonatal intensive care unit (NICU). METHODS A system was developed which automatically generates partial NICU shift summaries (for the respiratory and cardiovascular systems), using data-to-text technology. It was evaluated for 2 months in the NICU at the Royal Infirmary of Edinburgh, under supervision. RESULTS In an on-ward evaluation, a substantial majority of the summaries was found by outgoing and incoming nurses to be understandable (90%), and a majority was found to be accurate (70%), and helpful (59%). The evaluation also served to identify some outstanding issues, especially with regard to extra content the nurses wanted to see in the computer-generated summaries. CONCLUSIONS It is technically possible automatically to generate limited natural language NICU shift summaries from an electronic patient record. However, it proved difficult to handle electronic data that was intended primarily for display to the medical staff, and considerable engineering effort would be required to create a deployable system from our proof-of-concept software.
منابع مشابه
BT-Nurse: computer generation of natural language shift summaries from complex heterogeneous medical data
The BT-Nurse system uses data-to-text technology to automatically generate a natural language nursing shift summary in a neonatal intensive care unit (NICU). The summary is solely based on data held in an electronic patient record system, no additional data-entry is required. BT-Nurse was tested for two months in the Royal Infirmary of Edinburgh NICU. Nurses were asked to rate the understandabi...
متن کاملAutomatic Generation of Textual Summaries from Neonatal Intensive Care Data
Effective presentation of data for decision support is a major issue when large volumes of data are generated as happens in the Intensive Care Unit (ICU). Although the most common approach is to present the data graphically, it has been shown that textual summarisation can lead to improved decision making. As part of the BabyTalk project, we present a prototype, called BT-45, which generates te...
متن کاملSummarising complex ICU data in natural language: demonstration of the BT-45 system.
As ICUs generate increasing amounts of information, writing medical reports involves complex time-consuming reasoning to build a coherent text which will be meaningful to those who will use it for decision making (e.g.: for nurse handover). Moreover, it has been shown that summarizing complex multi-channel physiological and discrete data in natural language (text) can lead to better decision-ma...
متن کاملEffect of Clustered Nursing Care on Sleep Behaviors of the Preterm Neonates Admitted to the Neonatal Intensive Care Unit
Background: Premature neonates admitted to the neonatal intensive care unit (NICU) undergo sleep disorder due to various manipulations. The present study aimed to investigate the effect of clustered nursing care on sleep behaviors in premature neonates admitted to NICUs. Methods: This clinical trial study was conducted on 60 neonates sel...
متن کاملThe Importance of Narrative and Other Lessons from an Evaluation of an NLG System that Summarises Clinical Data
The BABYTALK BT-45 system generates textual summaries of clinical data about babies in a neonatal intensive care unit. A recent taskbased evaluation of the system suggested that these summaries are useful, but not as effective as they could be. In this paper we present a qualitative analysis of problems that the evaluation highlighted in BT-45 texts. Many of these problems are due to the fact t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Artificial intelligence in medicine
دوره 56 3 شماره
صفحات -
تاریخ انتشار 2012