TY - JOUR
KW - Adult
KW - Confidence Intervals
KW - Descriptive Statistics
KW - Female
KW - Funding Source
KW - Health Care Costs
KW - Health Resource Utilization
KW - Health Services -- Economics
KW - Human
KW - Male
KW - Middle Age
KW - Multiple Logistic Regression
KW - Odds Ratio
KW - P-Value
KW - Patient Health Questionnaire (PHQ)
KW - Questionnaires
KW - Research Instruments
KW - Resource Databases
KW - ROC Curve
KW - Self Report
KW - Sensitivity and Specificity
KW - Socioeconomic Factors
KW - Somatoform Disorders -- Diagnosis
KW - Somatoform Disorders -- Economics
KW - Somatoform Disorders -- Therapy
AU - A. J. Barsky
AU - E. J. Orav
AU - D. W. Bates
A1 - 
AB - BACKGROUND: Somatizing patients have maladaptive and increased rates of medical care utilization. If there were a way of routinely identifying such patients, one that did not require intensive, case-by-case review, they could be targeted for specific interventions to improve their use of medical care. OBJECTIVE: We sought to identify patterns of medical care utilization that would distinguish somatizing and nonsomatizing medical outpatients with acceptable sensitivity and specificity. DESIGN: Subjects completed questionnaires assessing somatization and sociodemographic characteristics. Their medical care utilization was obtained for the 12 months preceding the index visit. We then used multivariable logistic regression and recursive partitioning to identify patients with a provisional diagnosis of somatoform disorder. These exploratory models used various patterns of medical care utilization and sociodemographic characteristics as the independent variables. SUBJECTS: We studied consecutive adults attending 2 primary care practices on randomly chosen days. MEASURES: The provisional diagnosis of a somatoform disorder was assessed with a 15-item self-report questionnaire. The number of primary care visits, specialty visits, mental health visits, emergency visits, and inpatient and outpatient costs were obtained for the 12 months preceding the index visit from our hospital's automated medical records, which also provided a rating of aggregate medical morbidity. Self-reported utilization outside our hospital system was obtained from a subsample of patients. RESULTS: Complete data were obtained on 1440 patients. Somatizing patients had more specialty care than primary care visits, higher outpatient than inpatient costs, and more emergency visits than nonsomatizing patients. A regression model containing 7 measures of utilization and 4 sociodemographic characteristics distinguished somatizing and nonsomatizing patients with a c-statistic = 0.73. Recursive partitioning identified 10 terminal nodes with a very high specificity (99%) but a very low sensitivity (15%). CONCLUSIONS: We identified 7 discrete patterns of medical care utilization that distinguished somatizing and nonsomatizing patients. However, they did so with only modest specificity and sensitivity. This algorithm might be used effectively as the first step in a 2-step screening procedure whose second step would entail more intensive screening or individual, case-by-case review to identify somatizing patients in primary care practice.
BT - Medical care
C5 - Financing & Sustainability; Medically Unexplained Symptoms
CP - 9
CY - URL
IS - 9
JF - Medical care
N2 - BACKGROUND: Somatizing patients have maladaptive and increased rates of medical care utilization. If there were a way of routinely identifying such patients, one that did not require intensive, case-by-case review, they could be targeted for specific interventions to improve their use of medical care. OBJECTIVE: We sought to identify patterns of medical care utilization that would distinguish somatizing and nonsomatizing medical outpatients with acceptable sensitivity and specificity. DESIGN: Subjects completed questionnaires assessing somatization and sociodemographic characteristics. Their medical care utilization was obtained for the 12 months preceding the index visit. We then used multivariable logistic regression and recursive partitioning to identify patients with a provisional diagnosis of somatoform disorder. These exploratory models used various patterns of medical care utilization and sociodemographic characteristics as the independent variables. SUBJECTS: We studied consecutive adults attending 2 primary care practices on randomly chosen days. MEASURES: The provisional diagnosis of a somatoform disorder was assessed with a 15-item self-report questionnaire. The number of primary care visits, specialty visits, mental health visits, emergency visits, and inpatient and outpatient costs were obtained for the 12 months preceding the index visit from our hospital's automated medical records, which also provided a rating of aggregate medical morbidity. Self-reported utilization outside our hospital system was obtained from a subsample of patients. RESULTS: Complete data were obtained on 1440 patients. Somatizing patients had more specialty care than primary care visits, higher outpatient than inpatient costs, and more emergency visits than nonsomatizing patients. A regression model containing 7 measures of utilization and 4 sociodemographic characteristics distinguished somatizing and nonsomatizing patients with a c-statistic = 0.73. Recursive partitioning identified 10 terminal nodes with a very high specificity (99%) but a very low sensitivity (15%). CONCLUSIONS: We identified 7 discrete patterns of medical care utilization that distinguished somatizing and nonsomatizing patients. However, they did so with only modest specificity and sensitivity. This algorithm might be used effectively as the first step in a 2-step screening procedure whose second step would entail more intensive screening or individual, case-by-case review to identify somatizing patients in primary care practice.
PP - URL
PY - 2006
SN - 0025-7079
EP - 11
EP - 803+
T1 - Distinctive patterns of medical care utilization in patients who somatize
T2 - Medical care
TI - Distinctive patterns of medical care utilization in patients who somatize
U1 - Financing & Sustainability; Medically Unexplained Symptoms
U2 - 16932131
VL - 44
VO - 0025-7079
Y1 - 2006
ER -