| Autor: |
A, Freytag, G, Schiffhorst, R, Thoma, K, Strick, C, Gries, A, Becker, R-D, Treede, G, Müller-Schwefe, H-R, Casser, C, Luley, A, Höer, M, Ujeyl, H, Gothe, J, Kugler, G, Glaeske, B, Häussler |
| Jazyk: |
němčina |
| Rok vydání: |
2010 |
| Předmět: |
|
| Zdroj: |
Schmerz (Berlin, Germany). 24(1) |
| ISSN: |
1432-2129 |
| Popis: |
The ICD classification does not provide the opportunity to adequately identify pain patients. Therefore we developed an alternative method for the identification and classification of pain patients which is based on prescription and diagnoses data from the year 2006 of one nationwide sickness fund (DAK) and which is led by two main assumptions: 1. Beneficiaries without prescription of an analgetic drug but with a diagnosis pattern that is characteristic of patients who are treated with opioids are also likely to be pain patients. 2. Each combination of diagnosis groups can be traced back to one primary diagnosis out of a diagnosis group according to the patient classification system CCS (Clinical Classifications Software). The selection of this diagnosis group (CCS) allows for the allocation of the beneficiary to only one pain type. As a result we identified 65 combinations of CCS diagnosis groups--aggregated to nine "CCS pain types"--to which 77.1% of all patients with at least two opioid prescriptions can be allocated: 26.3% to pain due to arthrosis, 18.0% to pain due to intervertebral disc illnesses, 13.1% to other specific back pain, 6.7% to neuropathic pain, 4.5% to unspecific back pain, 4.2% to headache, 2.4% to pain after traumatic fractures, 1.3% to pain of multimorbid, high-maintenance patients, and 0.6% to cancer pain. Based on our method beneficiaries who have a high probability of suffering from moderate to strong pain can be identified and included in further claims data analyses of health care delivery and utilization pattern of pain-related disorders in Germany. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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Full text from SpringerLink