الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
A Neonatal Network is a collaboration involving more than one clinical site where a common protocol is used for randomized trials, observational studies and Quality improvement projects. These Networks are committed to improve the quality and efficiency of neonatal intensive care. The main interest of Neonatal Network includes discovery of scientific information and dissemination of evidence for effective interventions as well as evaluating the quality of care which involves comparison among different NICUs. Good decisions require good information, derived from raw facts known as data. Data can be managed most efficiently when they are stored in a Database which can be defined as, a collection of records or information which are stored in a computer in a systematic way. The idea behind hospital information systems is to make all of patient‘s medical reports, lab results, and images electronically available to clinicians, instantaneously, wherever they are. Data regarding neonatal patients are available from a variety of sources. Primary patient-level databases for neonatal patients can be developed locally, acquired commercially, or obtained as part of a multihospital neonatal network. Secondary data sources that are frequently used are the birth certificate, the hospital discharge abstract, and hospital billing data. It is important to define exactly whom do we care for, in order to plan for and justify resource allocation and to make meaningful comparisons between other institutions and our own over time. The data needed for these comparisons must include factors that reflect complexity and influence both morbidity and mortality. Because birth weight and gestational age are the most important determinants of both the level of intervention required and the outcome, they are crucial items in any neonatal database. Evaluating the quality of care involves comparison among NICUs, therefore, the documented outcomes of an individual NICU must be considered in the context of the severity and complexity of that NICU‘s case mix, using an appropriate analytic approach to measure and adjust for differences in risk. Risk adjustment requires accurate scores. Although it may be possible to derive a risk adjustment score in a particular study, investigators will often require a ready made score which has the advantage that it is more likely to be accepted by others. Usually, scores are created in one of two ways, medical or statistical. For the score to be clinically useful, the predicted and observed event rates should closely match. SNAP & CRIB are widely used scores for risk adjustment. DRG systems are classification schemes that use data that are routinely available in hospital discharge abstracts to group patients into relatively homogeneous categories. There are a number of DRG classification systems that have evolved over the past 2 decades. Because of the widespread use of DRGs, it is important for neonatologists to be familiar with these systems. The public release of comparative performance data and the use of such data for contracting and performance-based reimbursement will become increasingly common over the next few years. Neonatal intensive care is among the most expensive types of hospital care and it has come under increasing supervision by both public and private insurers seeking to reduce health care costs. We have to understand that we will be under increasing pressure to justify and reduce the costs of neonatal care. Insurers seek to compare treatment costs across institutions to determine whether costs at a given institution are excessively high. Meaningful comparisons of neonatal intensive care treatment costs across institutions are difficult to make. Although neonatologists should not be expected to become experts in databases and evaluation methods, they do need to develop a basic understanding that will allow them to work effectively with other professionals in the changing health care environment. We must all develop the knowledge and skills necessary to assume leadership roles in collaborative quality improvement within our institutions. Conclusion and Recommendation Improving the quality and efficiency of neonatal care may be impossible without reliable database. We have proposed a database that may be used in our unit within one year. This database has set quality control and system management protocols. Next, we hope to export this database to other units across our region and put a base for construction of a National Egyptian Neonatal Network. One of our important considerations is to create the option for exporting core data electronically to an international neonatal network. Only then, we can translate the potential benefits of modern databases and information systems into better medical care for newborn infants and their families in our country