ArticleSchmerz (Berlin, Germany)2010
[Identification and grouping of pain patients according to claims data].
Article in Schmerz (Berlin, Germany), 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 24 citations in OpenAlex.
- Feasibility and long-term efficacy of a proactive health program in the treatment of chronic back pain: a randomized controlled trial.BMC health services research · 2019Trial
- Exploring heterogeneity in coxarthrosis medication use patterns before total hip replacement: a State Sequence Analysis.BMJ open · 2024Article
- Pain And The Use Of Gabapentinoids In German Nursing Home Residents - Results From An Analysis Based On Statutory Health Insurance Data.Journal of pain research · 2019Article
- Article
- Diagnoses indicating pain and analgesic drug prescription in patients with dementia: a comparison to age- and sex-matched controls.BMC geriatrics · 2014Article
- [Opioid therapy in patients with back pain. Claims data analysis for patient group characterization, influence on opioid therapy and work disability].Schmerz (Berlin, Germany) · 2011Article
- [The new code F45.41].Schmerz (Berlin, Germany) · 2010Article
- [Coming to light. The problem of identification and grouping of pain patients].Schmerz (Berlin, Germany) · 2010Article
- Article
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Authors and funding
16 authors at 8 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.