Patients classification System

tools for
Cost management

tools for
Quality management

tools for
HOSPITAL PLANNING

4  Why to choose US

4  implementation

4  ANECDOTE

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

Classifying patients is not simple, because patients often have a unique complexion of diagnoses sometimes with procedures. The SQLape® classification returns this diversity, allowing multiple groups of diagnoses or procedures to describe a specific patient.

The SQLape® grouper include 207 diagnostic categories and 185 procedure categories. Each category is defined by inclusion and exclusion criteria. The inclusion criteria are specified with internationally used codes: ICD-10 for diagnoses and ICD-9-CM for procedures (2014 updates).

To avoid coding biases, the classification apply reduction rules to retain only relevant information to adjust for case mix:

1.      A procedure excludes the diagnoses related to the same organ.

2.      The most invasive procedure category excludes those related to the same organ.

3.      Predominant diagnoses (obstetrical conditions) and procedures (transplants) exclude all other categories.

4.      Major diagnoses and procedures categories - justifying a hospitalization - exclude other categories.

5.      Some categories are not retained if more severe conditions occurred. For instance, renal failure is not retained with a cardiac shock or a muscular procedure will be excluded if a shoulder operation is performed.

At the end of the classifying process, the majority of patients only have a unique SQLape® group. A special focus has been applied the robustness of the assigned groups with respect to coding practice: results are independent of the main diagnosis choice, chemo- and radiotherapy can be coded through procedure or diagnostic codes, etc.

The SQLape® classifier allocates a principal category to each stay (designed by the letter p in the group output), in the following order: predominant operations, predominant affections, major operations, major affections, minor affections, minor operations. Furthermore, the most vital systems takes precedence (prematurity, respiratory, nervous, cardiac, hepatic, digestive, urinary, musculoskeletal, etc.). Thus, a primary category is attributed independently of the order in which health problems are coded in medical records.

To reduce statistical confidence intervals, only the most relevant categories are used to compute expected values. For instance, length of stay and cost prediction are mainly based on acute medical conditions, readmissions prediction depend more on chronic and recurrent illnesses. Thus, specific prediction models are built for each cost and quality management indicator.

Contrarily to other groupers - like DRGs - complications and other conditions presumably not present at patient’s admission are not taken into account. Procedures depending more on medical practice than health status (respiratory assistance, length of stay, etc.) are also ignored when computing expected values.

© Yves Eggli, 2014. Last update: 28.02.2016