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      Using Automated Health Plan Data to Assess Infection Risk from Coronary Artery Bypass Surgery

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          Abstract

          We determined if infection indicators were sufficiently consistent across health plans to allow comparison of hospitals’ risks of infection after coronary artery bypass surgery. Three managed care organizations accounted for 90% of managed care in eastern Massachusetts, from October 1996 through March 1999. We searched automated inpatient and outpatient claims and outpatient pharmacy dispensing files for indicator codes suggestive of postoperative surgical site infection. We reviewed full text medical records of patients with indicator codes to confirm infection status. We compared the hospital-specific proportions of cases with an indicator code, adjusting for health plan, age, sex, and chronic disease score. A total of 536 (27%) of 1,953 patients had infection indicators. Infection was confirmed in 79 (53%) of 149 reviewed records with adequate documentation. The proportion of patients with an indicator of infection varied significantly (p<0.001) between hospitals (19% to 36%) and health plans (22% to 33%). The difference between hospitals persisted after adjustment for health plan and patients’ age and sex. Similar relationships were observed when postoperative antibiotic information was ignored. Automated claims and pharmacy data from different health plans can be used together to allow inexpensive, routine monitoring of indicators of postoperative infection, with the goal of identifying institutions that can be further evaluated to determine if risks for infection can be reduced.

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          Most cited references19

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          Guideline for prevention of surgical site infection, 1999. Hospital Infection Control Practices Advisory Committee.

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            The efficacy of infection surveillance and control programs in preventing nosocomial infections in US hospitals.

            In a representative sample of US general hospitals, the authors found that the establishment of intensive infection surveillance and control programs was strongly associated with reductions in rates of nosocomial urinary tract infection, surgical wound infection, pneumonia, and bacteremia between 1970 and 1975-1976, after controlling for other characteristics of the hospitals and their patients. Essential components of effective programs included conducting organized surveillance and control activities and having a trained, effectual infection control physician, an infection control nurse per 250 beds, and a system for reporting infection rates to practicing surgeons. Programs with these components reduced their hospitals' infection rates by 32%. Since relatively few hospitals had very effective programs, however, only 6% of the nation's approximately 2 million nosocomial infections were being prevented in the mid-1970s, leaving another 26% to be prevented by universal adoption of these programs. Among hospitals without effective programs, the overall infection rate increased by 18% from 1970 to 1976.
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              A chronic disease score from automated pharmacy data.

              Using population-based automated pharmacy data, patterns of use of selected prescription medications during a 1 year time period identified by a consensus judgement process were used to construct a measure of chronic disease status (Chronic Disease Score). This score was evaluated in terms of its stability over time and its association with other health status measures. In a pilot test sample of high utilizers of ambulatory health care well known to their physicians (n = 219), Chronic Disease Score (CDS) was correlated with physician ratings of physical disease severity (r = 0.57). In a second random sample of patients (n = 722), its correlation with physician-rated disease severity was 0.46. In a total population analysis (n = 122,911), it was found to predict hospitalization and mortality in the following year after controlling for age, gender and health care visits. In a population sample (n = 790), CDS showed high year to year stability (r = 0.74). Based on health survey data, CDS showed a moderate association with self rated health status and self reported disability. Unlike self-rated health status and health care utilization, CDS was not associated with depression or anxiety. We conclude that scoring automated pharmacy data can provide a stable measure of chronic disease status that, after controlling for health care utilization, is associated with physician-rated disease severity, patient-rated health status, and predicts subsequent mortality and hospitalization rates. Specific methods of scoring automated pharmacy data to measure global chronic disease status may require adaptation to local prescribing practices. Scoring might be improved by empirical estimation of weighting factors to optimize prediction of mortality and other health status measures.
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                Author and article information

                Journal
                Emerg Infect Dis
                Emerging Infect. Dis
                EID
                Emerging Infectious Diseases
                Centers for Disease Control and Prevention
                1080-6040
                1080-6059
                December 2002
                : 8
                : 12
                : 1433-1441
                Affiliations
                [* ]Centers for Disease Control and Prevention Eastern Massachusetts Prevention Epicenter, Boston, Massachusetts, USA
                []Harvard Medical School and Harvard Pilgrim Health Care, Boston, Massachusetts, USA
                []Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
                [§ ]Tufts Health Plan, Boston, Massachusetts, USA
                [# ]Blue Cross Blue Shield of Massachusetts, Boston, Massachusetts, USA
                [** ]Centers for Disease Control and Prevention, Atlanta, Georgia, USA
                [†† ]Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
                Author notes
                Address for correspondence: R. Platt, 133 Brookline Ave, 6th floor, Boston, MA 02215, USA; fax: 617-859-8112; e-mail: richard.platt@ 123456channing.harvard.edu
                Article
                02-0039
                10.3201/eid0812.020039
                2737830
                12498660
                5eb52e7c-a4a8-4115-9b98-f17d37660ec5
                History
                Categories
                Research

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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