M. Grabert, R.W. Holl, P. Merkle, J. Högel, F. Schweiggert, W. Gaus, E. Heinze

Matthias Grabert, P. Merkle and F. Schweiggert
University of Ulm
Department of Applied Information Processing (SAI)
Helmholtzstr. 18
D-89069 Ulm
Tel.: +49 731 502 3575
Fax: +49 731 502 3579

R.W. Holl and E. Heinze
University of Ulm
Department of Pediatrics I
Prittwitzstr. 45
D-89070 Ulm

J. Högel and W. Gaus
University of Ulm
Department of Statistic and Documentation
D-89070 Ulm

Keywords: Diabetes, Chronic Disease, Information System, Quality Control

The necessity of using electronic databases in the treatment of chronic diseases is evident and has been demanded for diabetes mellitus since 1989 [1]. Three major goals can be reached with the help of such information systems: monitoring the quality of care, support for daily routine work and scientific investigations. A diabetes information system has been developed during the last five years. Using the system, summaries of patient data for the physician as well as patient reports after an outpatient or inpatient visit can be generated. Patient data are displayed in tabular and graphical form. To monitor the quality of care, statistics of several quality indicators concerning diabetes can be generated on a keystroke serving for internal or external quality control as well as quality circles. The program is currently used in about 35 German, Austrian and Swiss diabetes centers. Due to the open architecture of the information system, new tables and masks can be added to the program at each center. This supports individual investigations as well as joint studies among several diabetes centers.


Regarding the current discussion about medicine in Germany, it is conspicious, that beside the demand for better economic efficiency of the public health system, the discussion is focussed on quality assurance. Since 1988, measures for external and internal quality control have been anchored in the German Social Statute Book [2]. This is mostly implemented through the use of indicators, tracers and their interpretation and comparison in quality circles. For efficiency reasons, the data collected should be processed by computer programs. Especially during the course of treatment of chronic diseases like insulin-dependant diabetes mellitus (IDDM), very much patient data is accumulated over the years. To manage this vast amount of data and to obtain information about the outcome of care - and to improve it - , the use of information technology in diabetology was demanded in the declaration of St.Vincente in the year 1989 [1]. Thus the necessity of information systems in diabetes care is evident.

Background and goals

The diabetes information system DPV has been developed at the University of Ulm in a team of statisticians, physicians and information scientists during the years of 1989 until 1995 [3][9]. The first step was made with a self constructed database on a UNIX system, written in C. But this program was a dead-end street. Only the data could be saved from this effort. Now we are using a Xbase-application on an IBM PC. The program was originally designed to support the outpatient and inpatient treatment of pediatric patients with IDDM and was later adapted for adults. A primary goal was to reduce the time for routine work, as writing patient reports and data summaries about one patient. Many general practitioners are never informed about the visits of their patient at a diabetes center due to the lack of time for writing patient reports at the center. Secondly we wanted a flexible but all-in-one database for the many research projects performed at the diabetes center of an university hospital. And, last but not least, we wanted to improve and to assess the quality of care for diabetes patients. These three goals implemented in one currently usable program, seem to be unique in Germany today. Some centers have implemented solutions for writing patient reports (e.g. [4]). The approach at DIABCARE is pursuing external quality control, implementing the plans of St.Vincente [5]. And the MEDWIS project, which will include a documentation and decision system among other things, will not be finished before the late nineteen-nineties [6].

Routine work

The database contains all important parameters of a patient concerning his diabetes:
anthropometric data (weight and length), treatment modalities (e.g. number of injections and quantity of insulin), acute and chronic complications (e.g. hypoglycemic episodes, retinopathy, neuropathy and microalbuminuria) level of metabolic control (e.g. blood glucose, fructosamine and HbA1c) as well as risk parameters (e.g. blood pressure and cholesterol). Furthermore, data of diabetes education and examinations of relatives are collected in the database. In total, the database consists of 16 tables of patient data and 21 tables of system control data (including hardware settings, measuring units, normal values of healthy persons, ICD/9 code, types of insulin, classification of eye examination etc.).
Data is not information. They have to be structured, summarized and displayed in relation to healthy persons, if necessary.
We are generating patient summaries and graphical printouts prior to every outpatient visit. The parameters for the printouts can be configured freely from a predefined list.
The graphical printouts display length, weight, body-mass-index, HbA1c-level and insulin units per kilogram. Length, weight and body-mass-index are shown on the background of the 3rd, 50th and 97th percentile of healthy children. Standard values can be chosen from different control studies, as for example the Zurich Longitudinal Growth Study [7].
HbA1c-levels are adjusted for different laboratory methods, which are changing from time to time. We are using a transformation based on mean and standard deviation of HbA1c, taken from 100 non-diabetic persons at the laboratory.
After the outpatient or inpatient visit we are automatically generating patient reports and treatment plans. One or two weeks after their visit, patients are directly informed in a letter about their degree of metabolic control.
The last two points play an important part in the communication with general pratitioners and patients.
Furthermore, it is possible to write serial letters to invite groups of patients for diabetes education or research projects. Patients can be selected by name, address, age, sex, diabetes duration and so on.
As a result of the DCCT study it is known, that patients with poor metabolic control have a very high risk for late complications as e.g. blindness and amputation [10].
Therefore patients with risk factors, dependant on e.g. levels of metabolic control, blood pressure, body-mass-index, microalbuminuria or cholesterol can be identified by the program, in order to target special treatment plans to this high risk groups.
All letters printed by the system have the original letter-head of the hospital on it, which is reproduced with the help of a scanner.

Quality monitoring

The fear to give away data for external quality control, is wide spread. On the other hand it is hardly feasible to compare raw data of treatment outcome among several hospitals, without detailed knowledge about interferring variables (e.g. different patient population, different laboratory methods).
We decided to integrate quarterly statistical evaluations into our program, stratifying for chronological age and duration of diabetes.
The following statistics are generated:

      overview on       percentage of patients with
-     risk factors      body-mass-index > 90th percentile
                        length < 10th percentile
                        blood pressure >90th percentile
                        HbA1c > 5 standard deviations of the mean
-     acute complicationshypoglycemic episodes, admission for ketoacidosis
-     chronic           retinopathy
      complications     neuropathy
-     completeness of   control of blood pressure and eye examination 
      examinations      HbA1c, cholesterol, urinary albumine, length and weight
-     therapy           educated in diabetes
                        number of insulin injections / day
                        number of blood glucose level determinations / day

Furthermore, overviews on cost factors as e.g. total number of treated patients, average duration of inpatient care are given.
The computation of all these printouts takes on a 80486/66 MHz computer about three hours for about 11.000 datasets from 500 patients.
After this time the hospital has a complete summary of the patient data. In addition, it is possible to join external epidemiologic and quality studies:
a program routine can export all data into the DIABCARE dataformat. Each hospital decides whether to give away data or to interprete it internally.


The goal is to support retrospective as well as prospective investigations in the context of diabetes. Therefore the parameters of the datasets are documented in the manual. The wide-spread dBASE dataformat is used, which allows data processing by many other commercial software systems marketed for use on PCs. For prospective investigations it is often necessary to add new parameters to the database. There are two features to satisfy this demand: several fields of the main dataset can be customized by the user, and it is possible to add new tables to the database at each center.
For this job a dBASE IV or dBASE V system for DOS is required. The masks and tables must be created within the dBASE system, copied into the program directory and added to the program system table. After this procedure they can be processed identical to the other predefined tables: adding, editing and deleting datasets is possible.
These features support also data collection in prospective multi-center studies. A pilot example was presented at the German Diabetes Congress in 1994 [8].

Hardware and Software

Our major aim was to keep hardware requirements as low as possible. Many small hospitals can't afford to buy expansive computer equipment for a new program. We decided to use the IBM-compatible personal computer as the platform for the program.
The whole system is written in dBASE V for DOS, with one exception: the routine for the graphical printouts are using a C-program. The operating system is DOS rather than Windows, in order to keep the RAM requirements minimal. However, a Windows-version will be developed in 1995.
The current hardware requirements are: IBM-PC 80486/25 SX (better: 80486/33 DX because of the integrated co-processor), 4 MB of RAM (8 MB are certainly better), 20 MB space on the harddisk (for about 11.000 datasets) and a HP-compatible laserprinter.
DOS 3.31 (or higher) or OS/2 as operating system. A local area network like Novell- Netware is supported by the program. Finally dBASE IV 1.5 or higher is needed to define additional masks and tables.

Future plans

To use the benefits of existing hospital information systems, we are planning to integrate an interface for data exchange using the HL7 or the DICOM standard protocol.
As mentioned above, we will move from DOS to a graphical user environment like Microsoft Windows, to keep the time of getting used to the program as minimal as possible.
Last but not least we want to publish an English program version. This work will be started in spring 1995.
We thank the German Ministry of Health for financial support.


M. Krans, M. Porta, H. Keen: Diabetes care and research in Europe:
The Saint Vincent declaration action program. Implementation document.
Giornale Italiano di Diabetologia (1992)
Sozialgesetzbuch V (SGB V), Paragraphs 115a, 135 - 137, 1993
R.W. Holl, M. Grabert, F. Schweiggert, E. Heinze: Ein Computerprogramm zur
prospektiven Datenerfassung bei jugendlichen Patienten mit Typ-I-Diabetes
mellitus. Diabetes und Stoffwechsel 2:232-238 (1993)
B. Mertes, T. Seifert, U.A. Müller, K. Höffken: The Establishment of a
Scientific Database and the Generation of Doctor's Letters
Proceedings of Symposium: Computers in Diabetes, Düsseldorf, Germany, 1994
K. Piwernetz, P. Home, M. Massi Benedetti, A. Bruckmeier, K. S. Johanssen,
M. Krans: DIABCARE Quality Network in Europe: Quality Development in
Diabetes Care Utilizing Telecommunication and Bulletin Board Systems.
Proceedings of Symposium: Computers in Diabetes, Düsseldorf, Germany, 1994
W. Moser, K. Böhmer, G. Entenmann, K. Kirchner, W. Rathmann, T. Koschinsky
R. Engelbrecht, F.A. Gries: Integration Of Decision Support Into The
Computer-Based Patient Record: From Problems to Knowledge Bases
Proceedings of Symposium: Computers in Diabetes, Düsseldorf, Germany, 1994
A. Prader, L.H. Largo, L. Molinari, C. Issler: Physical Growth of Swiss
Children from birth to 20 years of age.
Helv. Paediatr. Acta 43 (1989) 1-128
R.W. Holl, M. Grabert, C. Brack, W. Hecker, M. Holder, A. Klinghammer, W.
Teller, E. Heinze: EDV-Dokumentation des Typ-I-Diabetes bei Kindern und
Jugendlichen: Die gemeinsame Datenauswertung in 4 Zentren zeigt
Beziehungen zwischen Manifestation und HLA-Typ.
Oral presentation on the German Diabetes Congress 1994
M. Grabert, R.W. Holl, F. Schweiggert, E. Heinze: A Computer Program For
Pediatric Patients with Type I Diabetes: Prospective Documentation,
Support For Patient Care And Quality Control.
Poster for the 33rd Annual Meeting of the European Society for Pediatric
Endocrinology, Maastricht, 1994
Diabetes Control and Complication Trial Research Group: The effect of
intensive treatment of diabetes on the development and progression of
longterm complications in insulin-dependant diabetes mellitus.
New England Journal of Medicine 329:977-986 (1993)