Development and validation of algorithms to identify acute diverticulitis.

PURPOSE: The objectives of this study were to develop and validate algorithms to accurately identify patients with diverticulitis using electronic medical records (EMRs). METHODS: Using Kaiser Permanente Southern California's EMRs of adults (≥18 years) with International Classification of Diseases, Clinical Modifications, Ninth Revision diagnosis codes of diverticulitis (562.11, 562.13) between 1 January 2008 and 31 August 2009, we generated random samples for pilot (N = 692) and validation (N = 1502) respectively. Both samples were stratified by inpatient (IP), emergency department (ED), and outpatient (OP) care settings. We developed and validated several algorithms using EMR data on diverticulitis diagnosis code, antibiotics, computed tomography, diverticulosis history, pain medication and/or pain diagnosis, and excluding patients with infections and/or conditions that could mimic diverticulitis. Evidence of diverticulitis was confirmed through manual chart review. Agreement between EMR algorithm and manual chart confirmation was evaluated using sensitivity and positive predictive value (PPV). RESULTS: Both samples were similar in socio-demographics and clinical symptoms. An algorithm based on diverticulitis diagnosis code with antibiotic prescription dispensed within 7 days of diagnosis date, performed well overall. In the validation sample, sensitivity and PPV were (84.6, 98.2%), (95.8, 98.1%), and (91.8, 82.6%) for OP, ED, and IP, respectively. CONCLUSION: Using antibiotic prescriptions to supplement diagnostic codes improved the accuracy of case identification for diverticulitis, but results varied by care setting.

Acute colonic diverticulitis: diagnostic evidence, demographic and clinical features in three practice settings.

BACKGROUND AND AIMS: Diverticulitis is often diagnosed in outpatients, yet little evidence exists on diagnostic evidence and demographic/clinical features in various practice settings. We assessed variation in clinical characteristics and diagnostic evidence in inpatients, outpatients, and emergency department cases and effects of demographic and clinical variables on presentation features. METHODS: In a retrospective cohort study of 1749 patients in an integrated health care system, we compared presenting features and computed tomography findings by practice setting and assessed independent effects of demographic and clinical factors on presenting features. RESULTS: Inpatients were older and more often underweight/normal weight and lacked a diverticulitis past history and had more comorbidities than other patients. Outpatients were most often Hispanic/Latino. The classical triad (abdominal pain, fever, leukocytosis) occurred in 78 (38.6%) inpatients, 29 (5.2%) outpatients and 34 (10.7%) emergency department cases. Computed tomography was performed on 196 (94.4%) inpatients, 110 (9.2%) outpatients and 296 (87.6%) emergency department cases and was diagnostic in 153 (78.6%) inpatients, 62 (56.4%) outpatients and 243 (82.1%) emergency department cases. Multiple variables affected presenting features. Notably, female sex had lower odds for the presence of the triad features (odds ratio [95% CI], 0.65 [0.45-0.94], P<0.05) and increased odds of vomiting (1.78 [1.26-2.53], P<0.01). Patients in age group 56 to 65 and 66 or older had decreased odds of fever (0.67 [0.46-0.98], P<0.05) and 0.46 [0.26-0.81], P<0.01), respectively, while > / =1 co-morbidity increased the odds of observing the triad (1.88 [1.26-2.81], P<0.01). CONCLUSION: There was little objective evidence for physician-diagnosed diverticulitis in most outpatients. Demographic and clinical characteristics vary among settings and independently affect presenting features.

Sociodemographic characteristics of members of a large, integrated health care system: comparison with US Census Bureau data.

BACKGROUND: Data from the memberships of large, integrated health care systems can be valuable for clinical, epidemiologic, and health services research, but a potential selection bias may threaten the inference to the population of interest. METHODS: We reviewed administrative records of members of Kaiser Permanente Southern California (KPSC) in 2000 and 2010, and we compared their sociodemographic characteristics with those of the underlying population in the coverage area on the basis of US Census Bureau data. RESULTS: We identified 3,328,579 KPSC members in 2000 and 3,357,959 KPSC members in 2010, representing approximately 16% of the population in the coverage area. The distribution of sex and age of KPSC members appeared to be similar to the census reference population in 2000 and 2010 except with a slightly higher proportion of 40 to 64 year olds. The proportion of Hispanics/Latinos was comparable between KPSC and the census reference population (37.5% vs 38.2%, respectively, in 2000 and 45.2% vs 43.3% in 2010). However, KPSC members included more blacks (14.9% vs 7.0% in 2000 and 10.8% vs 6.5% in 2010). Neighborhood educational levels and neighborhood household incomes were generally similar between KPSC members and the census reference population, but with a marginal underrepresentation of individuals with extremely low income and high education. CONCLUSIONS: The membership of KPSC reflects the socioeconomic diversity of the Southern California census population, suggesting that findings from this setting may provide valid inference for clinical, epidemiologic, and health services research.

Health plan administrative records versus birth certificate records: quality of race and ethnicity information in children.

BACKGROUND: To understand racial and ethnic disparities in health care utilization and their potential underlying causes, valid information on race and ethnicity is necessary. However, the validity of pediatric race and ethnicity information in administrative records from large integrated health care systems using electronic medical records is largely unknown. METHODS: Information on race and ethnicity of 325,810 children born between 1998-2008 was extracted from health plan administrative records and compared to birth certificate records. Positive predictive values (PPV) were calculated for correct classification of race and ethnicity in administrative records compared to birth certificate records. RESULTS: Misclassification of ethnicity and race in administrative records occurred in 23.1% and 33.6% children, respectively; the majority due to missing ethnicity (48.3%) and race (40.9%) information. Misclassification was most common in children of minority groups. PPV for White, Black, Asian/Pacific Islander, American Indian/Alaskan Native, multiple and other was 89.3%, 86.6%, 73.8%, 18.2%, 51.8% and 1.2%, respectively. PPV for Hispanic ethnicity was 95.6%. Racial and ethnic information improved with increasing number of medical visits. Subgroup analyses comparing racial classification between non-Hispanics and Hispanics showed White, Black and Asian race was more accurate among non-Hispanics than Hispanics. CONCLUSIONS: In children, race and ethnicity information from administrative records has significant limitations in accurately identifying small minority groups. These results suggest that the quality of racial information obtained from administrative records may benefit from additional supplementation by birth certificate data.