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Query: UMLS:C0018681 (headache)
 56,091 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

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.
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PMID:[Identification and grouping of pain patients according to claims data]. 2002 Mar 9

The identification of beneficiaries with persistent, recurrent or chronic pain in claims data by means of individual diagnoses or analgesic prescription is not sufficient and reliable. By using CLASSIFICATION AND REGRESSION TREES (CART) it was possible to identify specific diagnosis patterns for patients suffering from pain. Diagnosis patterns are considered as specific if they occur more frequently among beneficiaries with at least two opioid prescriptions within one year compared with beneficiaries who did not receive any analgesic therapy. Diagnosis and prescription data of 2006 were provided by the German sickness fund DAK. As a result, 65 diagnosis patterns occurred more frequently among beneficiaries treated with opioids than among the control group. These 65 patterns can be classified as follows: cancer-related pain (4), specific back pain/osteoporosis (8), spine-related pain (6), arthritis-related pain/rheumatoid arthritis (22), pain after traumatic fractures (5), pain in multimorbid, dependent patients (3), neuropathic pain (7), headache (5), non-specific back pain (5). The derived diagnosis patterns showed high predictive values (sensitivity: 78%, specificity: 66%) and are suitable for the identification of beneficiaries suffering from pain - the first step towards health services research in pain-based on claims data.
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PMID:[Pain-specific diagnosis patterns in claims data - Identification by means of classification and regression trees (CART)]. 2048 Apr 61