Patients classification System

tools for
Cost management

tools for
Quality management

tools for

4  Why to choose US

4  implementation


4  contact

4  Logic

4  diagnoses

4  procedures

4  inpatients

4  outpatients

4  insurance

4  readmissions

4  reoperations

4  complications

4  deaths

4  length of stay

4  day surgery

4  unjustified stays


Why to choose us ?

1)        to have a simple and intelligible patients classification system

2)        To rigorously compute health indicators

3)        To adjust for case mix with highly predictive expected values, but without perverse incentives

You are interested to control health expenditure, to monitor the quality of health care, and to plan the use of hospital resources…

You believe that patients’ classification systems should reflect the diversity of patients with a limited number of categories (about 200 diagnoses and procedures groups) that are medically intelligible … (clinical homogeneity, explicit co-morbidities, etc.)

You think that issues cannot be solved only by managers or by health care providers, but only with a constructive interdisciplinary effort based on commonly accepted indicators…

You are aware of the importance to have sensitive, specific and rigorously defined health indicators…

You need highly predictive models, specifically developed for each indicator and scientifically validated…

You want to reduce the risk of manipulation of the indicators (reliability against coding practice)…

Last but not least, you advocate an ethical management, lowering as much as possible such perverse incentives…

… then the SQLape® tools are here to help you !

“Most current financing models reward hospitals having more complications or inappropriate admissions. A lot of case mix adjustment models include complications to predict unexpected events. Insurance risk adjustments are rarely based on benchmarked references, potentially leading to disputable financial effects. Patients’ classification systems and indicators are not neutral, they often reflect preferences and political priorities. But if they are rigorously defined and designed, their potentially harmful effect would be reduced.” [Y. Eggli, 2002]

© SQLape s.à.r.l. 2014. Last update: 20.05.2014