The in the area Billing contained features and tools enable an accurate cost allocation & control and also provide meaningful statistics & reports.
certified & tested
XR is one of the Federation of Austrian Social Security Institutions tested & certified software package and provides the Austria-wide cost allocation with all health insurance companies.
Also the financial reporting via internet/ELDA or sending bills by MedicalNet or DaMe is supported.
A big advantage is the name health insurance companies independent investigationlabel because an easy and comfortable operation is possible. The names of the investigations are optional. At the input you can use freely chosen abbreviations, standardized examination catalogs or codes, a descriptive text helps additionally.
This eliminates the learning of the settlement specifics and the vocational adjustment for new employees is much easier. When even the billing, the collected information will be processed in accordance with the requirements of the contractor, implemented on the nomenclature of the respective health insurance and create appropriate records. These are checked for plausibility, and so its possible for you to mend possible mistakes in advance.
XR RIS manage is the best assistance in the preparation and monitoring of the health insurance bills.
The billing data can be generated directly from the application and creates an overview of the expected revenues. In addition XR RIS manage offers the opportunity to create corresponding control lists or individual performance records for the respective health insurance. So an efficient control and a good differentiation between expected and actual revenues is given.
accounting & dunning
In XR RIS manage, all current health insurance rates are included and easily updatable.
If special rates are used, for example, special hospital rates or different private tariffs, so this can be easily configured at any time. The rates are directly considered in the statistics. In addition, there is a feature that is designed to quickly give a private patient information about what is going to cost his investigation. By assessing the status of an assignment (note missing - missing approval - billed - paid for) it is possible to create reminders or dunning letters.
The statistics of XR RIS manage will help you to assess the capacity of your institution or ordination, to identify the structure of your assignments and obtain an overview of revenue and its distribution to referring physicians, insurance carriers, etc.
In principle it is possible to evaluate all data collected in XR RIS manage. You have the ability to break down your data to patients, referring doctors or insurance or to evaluate visits, investigations, services, time or money. In addition to the quantitative analysis it is also possible with XR RIS manage to collect qualitative information. XR RIS manage offers the opportunity to create statistics based on diagnosis, eg: "How is the cancer incidence at over 40-year-old patients?".
simple & complex
The statistics accomplish on one side the basic concerns of an statistical analysis to give you a quick overview. Such simple evaluations are intended to answer questions like "What have doctors assigned in the last few months at most?" or "How many mammograms have been made in the last quarter?".
On the other hand, with XR RIS manage, more complex questions can be answered. Questions like: "How many patients were founded of what doctors in the last month?", "What was the room utilization or equipment usage in the last year?".
For dictations, a separate statistic is available, which can calculate for example the fee for locum doctors or internal settlement keys. Investigations can be multiplied with a factor of effort to map the diagnosis accomplishments realistically.
With XR RIS manage, you can generate statistics over a time course and compare your figures with a past period at an hourly, daily, weekly, monthly, quarterly or yearly basis.
Thus, questions like "Do I have more or less assignments than in the same quarter a year ago?" are easy to answer. Thus it is also possible to create statistics on the average waiting time.
The statistic calculates the average waiting time for your patients, in a detail view you can exactly view the respective status changes.
This analysis was created specifically to assist you in optimizing your workflow. Thus, it´s e.g. easily to identify the times at which the waiting times increase sharply in order to take this into account in service planning.
Another feature is the user-definable statistic. Here you can select patients from your data base and choose from free formulated criterias to answer further questions that would not be answerable with the prefabricated statistics.
dose measurement & statistics
In conjunction with XR RIS procedure, dose statistics can also be created. Based on over time collected measured values, you can calculate averages and compare them with reference values. Also room amounts & analyses based on examination types are supported.
These reports contain all the values that are necessary for an examination by the authorities for radiation protection. This will bring you to your documentation requirements, and the manual record is lapsed.
data mining extension
XR RIS cube is an extension of a so-called statistical data mining function. The product defines several cubes (data cubes) that can be evaluated in all dimensions. The analysis of data cubes is the most flexible and meaningful form of statistics.
Questions can be answered with XR RIS cube are, for example, "How distributes the arrival time of my patients over the day and varies it during the week" or "How long on average, a diagnosis is written and how long takes a speech recognition correction?" or "How long patients are waiting for their investigation depending on the daytime? ".
graphic processing & data export
A graphical representation of data in the form of pie charts & bar diagram is offered in addition. The statistics of XR RIS manage supports data export to eg Microsoft Excel (TM) to process further the collected data.