Howard S. Gordon

Patient Participation in Medical Consultations: Why Some Patients are More Involved Than Others

Background:Patients vary in their willingness and ability to actively participate in medical consultations. Because more active patient participation contributes to improved health outcomes and quality of care, it is important to understand factors affecting the way patients communicate with healthcare providers. Objectives:The objectives of this study were to examine the extent to which patient participation in medical interactions is influenced by 1) the patients personal characteristics (age, gender, education, ethnicity); 2) the physicians communication style (eg, use of partnership-building and supportive talk); and 3) the clinical setting (eg, the health condition, medical specialty). Research Design and Subjects:The authors conducted a post hoc cross-sectional analysis of 279 physician–patient interactions from 3 clinical sites: 1) primary care patients in Sacramento, California, 2) patients with systemic lupus erythematosus (SLE) from the San Francisco Bay area, and 3) patients with lung cancer from a VA hospital in Texas. Main Outcome Measures:The outcome measures included the degree to which patients asked questions, were assertive, and expressed concerns and the degree to which physicians used partnership-building and supportive talk (praise, reassurance, empathy) in their consultations. Results:The majority of active participation behaviors were patient-initiated (84%) rather than prompted by physician partnership-building or supportive talk. Patients who were more active participants received more facilitative communication from physicians, were more educated, and were more likely to be white than of another ethnicity. Women more willingly expressed negative feelings and concerns. There was considerable variability in patient participation across the 3 clinical settings. Female physicians were more likely to use supportive talk than males, and physicians generally used less supportive talk with nonwhite compared with white patients. Conclusions:Patient participation in medical encounters depends on a complex interplay of personal, physician, and contextual factors. Although more educated and white patients tended to be more active participants than their counterparts, the strongest predictors of patient participation were situation-specific, namely the clinical setting and the physicians communicative style. Physicians could more effectively facilitate patient involvement by more frequently using partnership-building and supportive communication. Future research should investigate how the nuances of individual clinical settings (eg, the health condition, time allotted for the visit) impose constraints or opportunities for more effective patient involvement in care.

Racial and ethnic disparities in the use of health services: Bias, preferences, or poor communication?

African Americans and Latinos use services that require a doctor’s order at lower rates than do whites. Racial bias and patient preferences contribute to disparities, but their effects appear small. Communication during the medical interaction plays a central role in decision making about subsequent interventions and health behaviors. Research has shown that doctors have poorer communication with minority patients than with others, but problems in doctor-patient communication have received little attention as a potential cause, a remediable one, of health disparities. We evaluate the evidence that poor communication is a cause of disparities and propose some remedies drawn from the communication sciences.

Racial differences in doctors' information‐giving and patients' participation

Whether doctor‐patient communication differs by race was investigated in patients with pulmonary nodules or lung cancer.

Racial Variation in the Use of Do-Not-Resuscitate Orders

OBJECTIVE: To compare the use of do-not-resuscitate (DNR) orders in African-American and white patients using a large, multisite, community-based sample.MEASUREMENTS: Our sample included 90,821 consecutive admissions to 30 hospitals in a large metropolitan region with six nonsurgical conditions from 1993 through 1995. Demographic and clinical data were abstracted from medical records. Admission severity of illness was measured using multivariate risk-adjustment models with excellent discrimination (receiver-operating characteristic curve areas, 0.82–0.88). Multiple logistic regression analysis was used to determine the independent association between race and use of DNR orders, adjusting for age, admission severity, and other covariates.MAIN RESULTS: In all patients, the rate of DNR orders was lower in African Americans than whites (9% vs 18%; p<.001). Rates of orders were also lower (p<.001) among African Americans in analyses stratified by age, gender, diagnosis, severity of illness, and in-hospital death. After adjusting for severity and other important covariates, the odds of a DNR order remained lower (p<.001) for African-Americans relative to whites for all diagnoses, ranging from 0.38 for obstructive airway disease to 0.71 for gastrointestinal hemorrhage. Results were similar in analyses limited to orders written by the first, second, or seventh hospital day. Finally, among patients with DNR orders, African Americans were less likely to have orders written on the first hospital day and more likely to have orders written on subsequent days.CONCLUSIONS: The use of DNR orders was substantially lower in African Americans than in whites, even after adjusting for severity of illness and other covariates. Identification of factors underlying such differences will improve our understanding of the degree to which expectations for care differ in African American and white patients.

IMPACT OF INTERHOSPITAL TRANSFERS ON OUTCOMES IN AN ACADEMIC MEDICAL CENTER : IMPLICATIONS FOR PROFILING HOSPITAL QUALITY

The purpose of this article is to determine whether a widely implement ed method of severity adjustment underestimated the risk of death and other outcomes among interhospital transfers (ie, patients transferred from other acute care hospitals) and to examine the impact of this potential bias on hospital outcomes profiles. The retrospective cohort study was conducted at a midwestern academic medical center with 40,820 adult medical and surgical patients from 1988 to 1991, of whom 38,946 were direct admissions and 1,874 were interhospital transfers. Hospital mortality, length of stay, and total charges in interhospital transfers and direct admissions were compared using multivariable regression methods that adjusted for admission severity of illness and other potential covariates (age, type of health insurance, diagnosis, emergent admission). Severity of illness was measured using the Medis-Groups methodology. Admission severity of illness was directly related (P<0.001) to rates of in-hospital death, length of stay, and charges, and was higher among interhospital transfers; 49% of transfers had moderate to high severity, compared with 35% of direct admissions (P<0.001) However, in a logistic regression model adjusting for severity and other covariates, the risk of in-hospital death was nearly two times (multivariable odds ratio, 1.99; 95% confidence interval [CI], 1.64-2.42) higher in transfers than in direct admissions. In linear regression models, length of stay and charges were 1.47 (95% CI, 1.42-1.53) and 1.40 (95% CI, 1.35-1.44) times higher, respectively, in transfers. Results were consistent in medical and surgical admissions, when examined separately, and among individual diagnostic categories. Based on their findings, the authors estimate that, independent of quality of care, severity adjusted mortality and length of stay would appear 17% and 8% higher, respectively, for hospitals in which 20% of patients were interhospital transfers than for hospitals in which 2% of patients were transfers. In an academic medical center, interhospital transfers had poorer severity adjusted outcomes than patients admitted directly. Failure to account for transfer status may produce biased performance profiles and, therefore, may create disincentives for hospitals to accept transfers from other acute care facilities.

Mortality after cardiac bypass surgery: prediction from administrative versus clinical data.

Background:Risk-adjusted outcome rates frequently are used to make inferences about hospital quality of care. We calculated risk-adjusted mortality rates in veterans undergoing isolated coronary artery bypass surgery (CABS) from administrative data and from chart-based clinical data and compared the assessment of hospital high and low outlier status for mortality that results from these 2 data sources. Study Population:We studied veterans who underwent CABS in 43 VA hospitals between October 1, 1993, and March 30, 1996 (n = 15,288). Methods:To evaluate administrative data, we entered 6 groups of International Classification of Diseases (ICD)-9-CM codes for comorbid diagnoses from the VA Patient Treatment File (PTF) into a logistic regression model predicting postoperative mortality. We also evaluated counts of comorbid ICD-9-CM codes within each group, along with 3 common principal diagnoses, weekend admission or surgery, major procedures associated with CABS, and demographic variables. Data from the VA Continuous Improvement in Cardiac Surgery Program (CICSP) were used to create a separate clinical model predicting postoperative mortality. For each hospital, an observed-to-expected (O/E) ratio of mortality was calculated from (1) the PTF model and (2) the CICSP model. We defined outlier status as an O/E ratio outside of 1.0 (based on the hospitals 90% confidence interval). To improve the statistical and predictive power of the PTF model, selected clinical variables from CICSP were added to it and outlier status reassessed. Results:Significant predictors of postoperative mortality in the PTF model included 1 group of comorbid ICD-9-CM codes, intraortic balloon pump insertion before CABS, angioplasty on the day of or before CABS, weekend surgery, and a principal diagnosis of other forms of ischemic heart disease. The models c-index was 0.698. As expected, the CICSP models predictive power was significantly greater than that of the administrative model (c = 0.761). The addition of just 2 CICSP variables to the PTF model improved its predictive power (c = 0.741). This model identified 5 of 6 high mortality outliers identified by the CICSP model. Additional CICSP variables were statistically significant predictors but did not improve the assessment of high outlier status. Conclusions:Models using administrative data to predict postoperative mortality can be improved with the addition of a very small number of clinical variables. Limited clinical improvements of administrative data may make it suitable for use in quality improvement efforts.

Mortality after noncardiac surgery: Prediction from administrative versus clinical data

Background:Hospital profiles are increasingly constructed using risk-adjusted clinical data abstracted from patient records. Objective:We sought to compare hospital profiles based on risk adjusted death within 30 days of surgery from administrative versus clinical data in a national cohort of surgical patients. Design:This was a cohort study that included 78,546 major noncardiac operations performed between October 1, 1991 and December 31, 1993 in 44 Veterans Affairs hospitals. Administrative data were used to develop and validate multivariable logistic regression models of 30-day postoperative death for all surgery and 4 surgical specialties (general, orthopedic, thoracic, and vascular). Previously developed and validated clinical models were obtained and reproduced for matching operations using data from the VA National Surgical Quality Improvement Program. Observed-to-expected 30-day mortality ratios for administrative and clinical data were calculated and compared for each hospital. Results:In multivariable logistic regression models using administrative data, characteristics such as patient age, race, marital status, admission from a nursing home, interhospital transfer, admission on the weekend, weekend surgery, and risk strata consisting of groups of principal and comorbidity diagnoses were predictive of postoperative mortality (P < 0.05). Correlations of the clinical and administrative observed-to-expected ratios were 0.75, 0.83, 0.64, 0.78, and 0.86 for all surgery, general, orthopedic, thoracic, and vascular surgery, respectively. When compared with clinical models, administrative models identified outlier hospitals with sensitivity of 73%, specificity of 89%, positive predictive value of 51%, and negative predictive value of 96%. Conclusions:Our data suggest that risk adjustment of mortality using administrative data may be useful for screening hospitals for potential quality problems.

Effect of definition of mortality on Hospital profiles

Background: Hospitals are ranked based on risk-adjusted measures of postoperative mortality, but definitions differ about which deaths following surgery should be included. Objective: To determine whether varying the case definition of deaths following surgery that are included in coronary artery bypass surgery quality assessment affects the identification of outlier hospitals. Research Design: The study used a prospective cohort design. Subjects: A total of 15,288 patients undergoing coronary artery bypass surgery without other cardiac procedures from October 1993 to March 1996 at all (N = 43) Veterans Affairs hospitals that conduct cardiac surgery. Measures: The first measure included any death occurring within 30 days after surgery, regardless of cause, in or out of the hospital (30-day mortality). The second measure included 30-day mortality plus any death occurring 30 days to 6 months after surgery that was judged to be a direct result of a perioperative complication of the surgery (all procedure-related mortality). Results: Hospital performance as assessed by the two different definitions of death varied substantially. The rankings of hospitals differed for 86% (37/43) of hospitals. Twenty-one percent (9/43) changed their quartile of rank, and five hospitals changed their outlier status. The correlation of observed-to-expected ratios was high (r = 0.96), but there was disagreement of outlier status (&kgr; = 0.71). Conclusions: Judgments regarding the quality of a hospital’s performance of coronary artery bypass surgery vary depending on the definition of postoperative mortality that is used. Further research is needed to assess what definition is most appropriate to identify quality of care problems.

Race and patient refusal of invasive cardiac procedures.

AbstractOBJECTIVE: To determine whether patients’ decisions are an important determinant of nonuse of invasive cardiac procedures and whether decisions vary by race. DESIGN: Observational prospective cohort. PARTICIPANTS: Patients (N=681) enrolled at the exercise treadmill or the cardiac catheterization laboratories at a large Veterans Affairs hospital. MEASURES: Doctors’ recommendations and patients’ decisions were determined by both direct observation of doctor and patient verbal behavior and by review of medical charts. Performance of coronary angiography, angioplasty, and bypass surgery were determined by chart review for a minimum of 3 months follow-up. RESULTS: Coronary angiography was recommended after treadmill testing for 83 of 375 patients and 72 patients underwent angiography. Among 306 patients undergoing angiography, recommendations for coronary angioplasty or bypass surgery were given to 113 and 45 patients and were completed for 98 and 33 patients, respectively. Recommendations were not significantly different by race. However, 4 of 83 (4.8%) patients declined or did not return for recommended angiograms and this was somewhat more likely among black and Hispanic patients, compared with white patients (13% and 33% vs 2%; P=.05). No patients declined angioplasty and 2 of 45 (4.4%) patients declined or did not return for recommended bypass surgery. Other recommended procedures were not completed after further medical evaluation (n=32). There was no difference (P>.05) by race/ethnicity in doctor-level reasons for nonreceipt of recommended invasive cardiac procedures. CONCLUSIONS: Patient decisions to decline recommended invasive cardiac procedures were infrequent and may explain only a small fraction of racial disparities in the use of invasive cardiac procedures.

Process of care in hispanic, black, and white VA beneficiaries

Objective. To examine whether process of hospital care differs among Hispanic, black, and white VA beneficiaries. Subjects. Two thousand eight-hundred fifty-two Hispanic, black, and white male VA beneficiaries from a case-control study discharged alive from one of twelve southern veterans hospitals with one of three diagnoses, diabetes mellitus (DM), congestive heart failure (CHF), or chronic obstructive pulmonary disease (COPD). Methods. We applied diagnosis-specific explicit criteria for the process of hospital care to each patient’s hospital record and computed the adherence score; the percentage of applicable criteria performed during the hospital stay. We compared mean scores in Hispanic, black, and white patients and then compared adjusted scores using multiple linear regression. Main Outcome Measure. Process of inpatient care (adherence score) in Hispanic, black, and white patients at admission, treatment, and discharge. Results. Mean admission adherence scores differed (P = 0.003) among Hispanic patients, black patients, and white patients for CHF and COPD, but not DM. Mean treatment and discharge scores were not different among Hispanic patients, black patients, and white patients. In bivariate comparisons, mean admission scores were higher in black patients compared with white patients for CHF (P = 0.003) and COPD (P = 0.01). In stratified analyses, admission and treatment scores were higher (P = 0.0001) in patients admitted to teaching compared with nonteaching hospitals. Process of inpatient care did not differ among Hispanic, black, and white patients after adjusting for admission to a teaching hospital and other covariates. Conclusion. In contrast to findings in other studies, process of inpatient care was generally similar in Hispanic patients, black patients, and white patients. Our findings may reflect several characteristics of veterans’ hospitals that may lead to care that is more equitable.