The study population consisted of all women who had a vaginal delivery or cesarean section at Brigham and Women's Hospital from January 1, 1993, to June 30, 1995, and who received postpartum care at Harvard Pilgrim Health Care (HPHC)/Harvard Vanguard Medical Associates (HVMA) centers with automated full-text ambulatory medical records. HPHC is a multimodel health maintenance organization that included a staff model division (now a multispecialty group practice, HVMA) with approximately 300,000 members in the greater Boston area at the time of the study. Brigham and Women's Hospital is the most active obstetrical facility for these members.

HMO data included three sources: an extensively automated ambulatory record, pharmacy dispensing data, and administrative claims for hospital, emergency room, and other care delivered outside the health center. The automated ambulatory medical record system (4) uses standardized forms that are completed for every patient encounter at HPHC/HVMA centers, including telephone calls, office visits (scheduled or unscheduled), urgent care visits, and hospitalizations. Information is recorded on forms that are customized for the type of encounter. The provider either writes in or selects from a list of all coded diagnoses, tests, procedures, and prescriptions relevant to that encounter and enters additional comments as free text. All information, including free text, is entered into an automated medical encounter record. The results of diagnostic tests are entered directly into the automated record linked to the patient encounter during which they were ordered. Information about hospitalizations and emergency room visits appears in both encounter records and separate administrative records. HPHC/HVMA pharmacies are also computerized and linked to the automated medical record. Ninety percent of HPHC members have prepaid coverage for pharmaceuticals and so are likely to use HPHC/HVMA pharmacies.

The study population consisted of 2,746 HPHC/HVMA members who underwent 2,301 vaginal deliveries and 525 cesarean sections. Ninety-five confirmed infections were identified among the random sample of 100 women who had at least one screening code and whose ambulatory medical records were reviewed, plus the additional 210 women identified by patient questionnaire results or inpatient surveillance. Extrapolation of the reviewed sample to the entire source population predicted a total of 169 infections, for an overall infection rate of 6.0% (95% confidence interval [CI] 5.1%, 6.9%). The extrapolated postpartum infection rates were 7.4% after cesarean section (95% CI 5.3%, 10.0%) and 5.5% (95% CI 4.6%, 6.5%) after vaginal delivery.

Figure 1

Figure 1. . Extrapolated site-specific infection rates following vaginal and cesarean delivery.

Among women undergoing cesarean section, the site-specific infection rates (number of infections/100 deliveries) were mastitis 1.7% (0.8%, 3.2%), urinary tract infection 1.1% (0.4%, 2.5%), surgical site infection (excluding endometritis) 3.4% (2.0%, 5.4%), and endometritis 0.8% (0.2%, 1.9%). Following vaginal delivery, the infection rates were mastitis 3.0% (2.4%, 3.8%), urinary tract infection 2.0% (1.4%, 2.6%), episiotomy site infection 0.3% (0.2%, 1.9%), and endometritis 0.2% (0.1%, 0.5%) (Figure 1).

Approximately 94% of these infections were detected after hospital discharge. For these post-discharge infections, 74% of patients did not return to the hospital where they delivered for evaluation or treatment.

Predictors of Infection

Figure 2

Figure 2. . Sensitivities and predictive value positives of differing cutoff probabilities of infection based on 1,000 bootstrap samples. A cutoff probability of infection of >0.20 yielded a sensitivity of 87% and a...

Important predictors of postpartum infection included rehospitalization within 30 days of delivery; cesarean versus vaginal delivery; dispensing of antistaphylococcal antibiotics (cephalexin, dicloxacillin, or both); diagnosis codes for mastitis, endometritis, and wound infection; and test codes for blood and wound microbiology cultures (Table 2). Cesarean section, although not statistically significant in this model, is included because it is a significant predictor of surgical site infection and endometritis. A cutoff probability of infection of >0.20 yielded an expected sensitivity of 87% (95% CI 72%, 94%), specificity of 97% (95% CI 96%, 98%), and predictive value positive of 55% (95% CI 41%, 68%). A cutoff probability of infection of 0.40 yielded an expected sensitivity of 73% (95% CI 59%, 84%), specificity of 98% (95% CI 98%, 99%), and predictive value positive of 64% (95% CI 52%, 77%) (Figure 2).

A separate model was constructed to predict surgical site infections among women who delivered by cesarean section. This model included as important predictors of surgical site infection ambulatory medical record test codes for blood and wound culture and diagnosis codes for endometritis and wound infection (Table 2). A cutoff probability of infection of >0.25 yielded an expected sensitivity of 78% (95% CI 60%, 100%), specificity of 88% (95% CI 0%, 97%), and predictive value positive of 75% (95% CI 23%, 92%). The stability of this model in the simulation analysis was limited by the small number of surgical site infections (22) among women who had full-text ambulatory record review and who delivered by cesarean section.

Accurate assessment of the epidemiology of postpartum infections has been hampered by the limitations of surveillance systems for identifying these infections, particularly infections detected after hospital discharge. In our study population, use of inpatient and ambulatory surveillance methods revealed that postpartum infections requiring medical attention were common following both vaginal delivery (5.5%) and cesarean section (7.4%). Mastitis and urinary tract infections accounted for >80% of these infections. The proportion of these infections directly attributable to health-care practices cannot be determined from the information available. Our study also does not address whether these infections were associated with modifiable (and therefore potentntially avoidable) risk factors, for example, suboptimal administration of perioperative prophylaxis during cesarean section or bladder catheterization.

Nearly all postpartum infections became manifest after hospital discharge (94%). Furthermore, most (74%) of these postdischarge infections were diagnosed and treated entirely in the ambulatory setting without the patients' returning to the hospital where they delivered for evaluation or treatment, emphasizing the need for postdischarge surveillance methods that are not dependent on hospital-based data.

Automated screening of ambulatory records was a sensitive method for identifying postpartum infections. Inpatient surveillance missed most infections that were diagnosed and treated in the ambulatory setting. Patient self-reported questionnaire results had limited sensitivity for detecting infections, explained in part by the large number of nonresponders. The questionnaire method was also more resource-intensive than automated ambulatory code screening. It is unclear whether questionnaire responders were representative of the entire postpartum patient population.

Although surveillance based on automated screening of ambulatory records depends on availability of ambulatory diagnoses, tests, and pharmacy information, an increasing number of patients receive their health care through managed care organizations that routinely collect this information for administrative purposes. The specific diagnosis and test screening codes used for this study were based on a coding system unique to this HMO; however, similar information could be obtained by using an ICD-9-based outpatient claims database (International Classification of Diseases, 9th revision, clinical modification, 3rd edition). In principle, this method or a modification of it should be applicable for most of the U.S. population who have health insurance that includes pharmacy benefits. An additional limitation of this study is that the accuracy of the extrapolated infection rates depends upon the assumption that very few infections occur among postpartum women with none of the screening codes. This assumption is supported, however, by the finding that even among women identified as potentially infected through patient questionnaire results and inpatient surveillance, very few infections were confirmed through medical record review without at least one screening code.

In conclusion, our results indicate that postpartum infections requiring medical attention are common and that most postpartum infections occur after hospital discharge, so that use of routine inpatient surveillance methods alone will lead to underestimation of postpartum infection rates. Use of automated information routinely collected by HMOs and insurers allows efficient identification of women who are very likely to have postpartum infections that are not detected by conventional surveillance. Information resulting from more complete surveillance could be used to identify settings with unusually high or low infection rates to identify practices associated with lower infection rates. This information could then be used to focus, motivate, and assess the effectiveness of practice changes aimed at improving infection rates in all settings. Additional research is needed to evaluate the generalizability of this surveillance methodology to other health-care provider and insurer systems and to assess resource utilization associated with these infections.