Dataset Information

Characterizing the demographics of chronic pain patients in the state of Maine using the Maine all payer claims database.

ABSTRACT:

Background

Chronic pain is currently a significant health problem in the United States. A comprehensive strategy is needed to increase prevention of chronic pain and to improve care for chronic pain patients. However, development of a successful strategy relies, in part, on a better understanding of the demographics and socioeconomics of patients living with chronic pain conditions. The current study was designed to understand the burden of chronic pain in the state of Maine by identifying the prevalence of chronic pain and its relationship with selected demographic and socioeconomic factors in Maine.

Methods

The Maine All Payer Claims Database (MEAPCD) (2006-2011) was used in the secondary data analysis to assess the demographic characteristics (such as age, sex, insurance type, and county of residence) of chronic pain patients in Maine. Chronic pain patients were identified based on the presence of pre-identified chronic pain-associated ICD-9 code(s) and opioid prescription information. Potential associations between the prevalence of chronic pain and a number of socioeconomic factors were determined by comparisons to Maine Census data.

Results

More women in the state were identified as having chronic pain across all counties and all age groups (>?10 years old). Surprisingly, the majority of chronic pain patients were identified based on the diagnostic code criteria and not the opioid prescription criteria. A greater utilization of public health insurance was seen within the chronic pain patients. At the county level, although neither education level nor income were associated with the prevalence of chronic pain, these factors significantly correlated with the usage of public health insurance.

Conclusions

Further detailed characterization of the chronic pain patient population in the state of Maine, using multiple data sources, can help design population-targeted strategies to prevent and manage chronic pain.

SUBMITTER: Malon J

PROVIDER: S-EPMC6022454 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Characterizing the demographics of chronic pain patients in the state of Maine using the Maine all payer claims database.

Malon Jennifer J Shah Parth P Koh Woon Yuen WY Cattabriga Gary G Li Edward E Cao Ling L

BMC public health 20180628 1

<h4>Background</h4>Chronic pain is currently a significant health problem in the United States. A comprehensive strategy is needed to increase prevention of chronic pain and to improve care for chronic pain patients. However, development of a successful strategy relies, in part, on a better understanding of the demographics and socioeconomics of patients living with chronic pain conditions. The current study was designed to understand the burden of chronic pain in the state of Maine by identifyi ...[more]

PMID: 29954350

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Project description:Techniques of data mining and machine learning were applied to a large database of medical and facility claims from commercially insured patients to determine the prevalence, gender demographics, and costs for individuals with provider-assigned diagnosis codes for myalgic encephalomyelitis (ME) or chronic fatigue syndrome (CFS). The frequency of diagnosis was 519-1,038/100,000 with the relative risk of females being diagnosed with ME or CFS compared to males 1.238 and 1.178, respectively. While the percentage of women diagnosed with ME/CFS is higher than the percentage of men, ME/CFS is not a "women's disease." Thirty-five to forty percent of diagnosed patients are men. Extrapolating from this frequency of diagnosis and based on the estimated 2017 population of the United States, a rough estimate for the number of patients who may be diagnosed with ME or CFS in the U.S. is 1.7 million to 3.38 million. Patients diagnosed with CFS appear to represent a more heterogeneous group than those diagnosed with ME. A machine learning model based on characteristics of individuals diagnosed with ME was developed and applied, resulting in a predicted prevalence of 857/100,000 (p > 0.01), or roughly 2.8 million in the U.S. Average annual costs for individuals with a diagnosis of ME or CFS were compared with those for lupus (all categories) and multiple sclerosis (MS), and found to be 50% higher for ME and CFS than for lupus or MS, and three to four times higher than for the general insured population. A separate aspect of the study attempted to determine if a diagnosis of ME or CFS could be predicted based on symptom codes in the insurance claims records. Due to the absence of specific codes for some core symptoms, we were unable to validate that the information in insurance claims records is sufficient to identify diagnosed patients or suggest that a diagnosis of ME or CFS should be considered based solely on looking for presence of those symptoms. These results show that a prevalence rate of 857/100,000 for ME/CFS is not unreasonable; therefore, it is not a rare disease, but in fact a relatively common one.

Dataset Information

Characterizing the demographics of chronic pain patients in the state of Maine using the Maine all payer claims database.

Background

Methods

Results

Conclusions

Publications

Characterizing the demographics of chronic pain patients in the state of Maine using the Maine all payer claims database.

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