title: [Implementation of a patient data management system. Effects on intensive care documentation].
abstract: BACKGROUND
  Patient data management systems (PDMS) enable digital documentation on intensive care units (ICU). A commercial PDMS was implemented in a 25-bed ICU replacing paper-based patient charting. The ICU electronic patient record is completely managed inside the PDMS. It compiles data from vital signs monitors, ventilators and further medical devices and facilitates some drug dose and fluid balance calculations as well as data reuse for administrative purposes. Ventilation time and patient severity scoring as well as coding of diagnoses and procedures is supported. Billing data transferred via interface to the central billing system of the hospital. Such benefits should show in measurable parameters, such as documented ventilator time, number of coded diagnoses and procedures and others. These parameters influence reimbursement in the German DRG system. Therefore, measurable changes in cost and reimbursement data of the ICU were expected.
  
  
  METHODS
  A retrospective analysis of documentation quality parameters, cost data and mortality rate of a 25-bed surgical ICU within a German university hospital 3 years before (2004-2006) and 5 years after (2007-2011) PDMS implementation. Selected parameters were documented electronically, consistently and reproducibly for the complete time span of 8 years including those years where no electronic patient recording was available. The following parameters were included: number of cleared DRG, cleared ventilator time, case mix (CM), case mix index (CMI), length of stay, number of coded diagnoses and procedures, detailed overview of a specific procedure code based on daily Apache II and TISS Core 10 scores, mortality, total ICU costs and revenues and partial profits for specific ICU procedures, such as renal replacement therapy and blood products.
  
  
  RESULTS
  Systematic shifts were detected over the study period, such as increasing case numbers and decreasing length of stay as well as annual fluctuations in severity of disease seen in the CM and CMI. After PDMS introduction, the total number of coded diagnoses increased but the proportion of DRG relevant diagnoses dropped significantly. The number of procedures increased (not significantly) and the number of procedures per case did not rise significantly. The procedure 8-980 showed a significant increase after PDMS introduction whereas the DRG-relevant proportion of those procedures dropped insignificantly. The number of ventilator-associated DRG cases as well as the total ventilator time increased but not significantly. Costs and revenues increased slightly but profit varied considerably from year to year in the 5 years after system implementation. A small increase was observed per case, per nursing day and per case mix point. Additional revenues for specific ICU procedures increased in the years before and dropped after PDMS implementation. There was an insignificant increase in ICU mortality rate from 7.4 % in the year 2006 (before) to 8.5 % in 2007 (after PDMS implementation). In the following years mortality dropped below the base level.
  
  
  CONCLUSIONS
  The implementation of the PDMS showed only small effects on documentation of reimbursement-relevant parameters which were too small to set off against the total investment. The method itself, a long-term follow-up of different parameters proved successful and can be adapted by other organizations. The quality of results depends on the availability of long-term parameters in good quality. No significant influence of PDMS on mortality was found.
authors.affiliation: Anästhesiologische Klinik, Universitätsklinikum Erlangen, Krankenhausstr. 12, 91054, Erlangen, Deutschland, ixchel.castellanos@kfa.imed.uni-erlangen.de.
authors.forename: I
authors.initials: I
authors.lastname: Castellanos
authors.forename: T
authors.initials: T
authors.lastname: Ganslandt
authors.forename: H U
authors.initials: HU
authors.lastname: Prokosch
authors.forename: J
authors.initials: J
authors.lastname: Schüttler
authors.forename: T
authors.initials: T
authors.lastname: Bürkle
mesh_terms: D003365:Costs and Cost Analysis; D003422:Critical Care / Q000191:economics / Q000458:organization & administration*; D003628:Database Management Systems / Q000191:economics / Q000458:organization & administration*; D003953:Diagnosis-Related Groups; D004282:Documentation; D057286:Electronic Health Records; D005858:Germany; D017052:Hospital Mortality; D006785:Hospitals, University; D006801:Humans; D007349:Insurance, Health, Reimbursement; D007362:Intensive Care Units / Q000191:economics / Q000458:organization & administration*; D012121:Respiration, Artificial / Q000706:statistics & numerical data; D012189:Retrospective Studies