Judith Chamberlin

Predictors of patient satisfaction

Correlates of patient satisfaction at varying points in time were assessed using a survey with 2-week and 3-month follow-up in a general medicine walk-in clinic, in USA. Five hundred adults presenting with a physical symptom, seen by one of 38 participating clinicians were surveyed and the following measurements were taken into account: patient symptom characteristics, symptom-related expectations, functional status (Medical Outcomes Study Short-Form Health Survey [SF-6]), mental disorders (PRIME-MD), symptom resolution, unmet expectations, satisfaction (RAND 9-item survey), visit costs and health utilization. Physician perception of difficulty (Difficult Doctor Patient Relationship Questionnaire), and Physician Belief Scale. Immediately after the visit, 260 (52%) patients were fully satisfied with their care, increasing to 59% at 2 weeks and 63% by 3 months. Patients older than 65 and those with better functional status were more likely to be satisfied. At all time points, the presence of unmet expectations markedly decreased satisfaction: immediately post-visit (OR: 0.14, 95% CI: 0.07-0.30), 2-week (OR: 0.07, 95% CI: 0.04-0.13) and 3-month (OR: 0.05, 95% CI: 0.03-0.09). Other independent variables predicting immediate after visit satisfaction included receiving an explanation of the likely cause as well as expected duration of the presenting symptom. At 2 weeks and 3 months, experiencing symptomatic improvement increased satisfaction while additional visits (actual or anticipated) for the same symptom decreased satisfaction. A lack of unmet expectations was a powerful predictor of satisfaction at all time-points. Immediately post-visit, other predictors of satisfaction reflected aspects of patient doctor communication (receiving an explanation of the symptom cause, likely duration, lack of unmet expectations), while 2-week and 3-month satisfaction reflected aspects of symptom outcome (symptom resolution, need for repeat visits, functional status). Patient satisfaction surveys need to carefully consider the sampling time frame as well as adjust for pertinent patient characteristics.

Depressive and Anxiety Disorders in Patients Presenting With Physical Complaints: Clinical Predictors and Outcome

PURPOSE To identify the predictors of depressive and anxiety disorders in general medical patients presenting with physical complaints and to determine the effect of these mental disorders on patient outcome. PATIENTS AND METHODS In this cohort study, 500 adults presenting to a general medicine clinic with a chief complaint of a physical symptom were interviewed with PRIME-MD to diagnose DSM-IV depressive and anxiety disorders. Clinical predictors were identified by logistic regression analysis. Outcomes were assessed immediately postvisit and at 2 weeks and 3 months. These included symptomatic improvement, functional status, unmet expectations, satisfaction with care, clinician-perceived patient difficulty, and health care utilization and costs. RESULTS A depressive or anxiety disorder was present in 146 (29%) of the patients. Independent predictors of a mental disorder included recent stress, multiple physical symptoms (ie, 6 or more), higher patient ratings of symptom severity, lower patient ratings of their overall health, physician perception of the encounter as difficult, and patient age less than 50. Patients with depressive or anxiety disorders were more likely to have unmet expectations postvisit (20% versus 8%, P < 0.001), be considered difficult (26% versus 11%, P < 0.0001), and report persistent psychiatric symptoms and ongoing stress even 3 months following the initial visit. Psychiatric status was not associated with symptomatic improvement, health care utilization, or costs. CONCLUSION Simple clinical clues in patients with physical complaints identify a subgroup who may warrant further evaluation for a depressive or anxiety disorder. Such disorders are associated with unmet patient expectations and increased provider frustration.

Epidemiology of Endemic Bartonella bacilliformis: A Prospective Cohort Study in a Peruvian Mountain Valley Community

Bartonella bacilliformis has caused debilitating illness since pre-Incan times, but relatively little is known about its epidemiology. A population-based, prospective cohort investigation was conducted in a Peruvian community with endemic bartonellosis. By use of house-to-house and hospital surveillance methods, cohort participants were monitored for evidence of bartonellosis. Of 690 participants, 0.5% had asymptomatic bacteremia at study initiation. After 2 years of follow-up, the incidence of infection was 12.7/100 person-years. The highest rates were in children <5 years old, and there was a linear decrease in incidence with increasing age. Seventy percent of cases were clustered in 18% of households. Age and bartonellosis in a family member were the best predictors of B. bacilliformis infection. There were multiple clinical presentations and significant subclinical infection. A cost-effective control strategy should include vector control and surveillance efforts focused on children and clusters of households with highest endemicity.

Population Genetic Analysis of Bartonella bacilliformis Isolates from Areas of Peru Where Carrion's Disease Is Endemic and Epidemic

ABSTRACT Carrions disease is caused by infection with the α-proteobacterium Bartonella bacilliformis. Distribution of the disease is considered coincident with the distribution of its known vector, the sand fly Lutzomyia verrucarum. Recent epidemics of B. bacilliformis infections associated with atypical symptomatology in nonendemic regions have raised questions regarding the historic and present distribution of this bacterium and the scope of disease that infection causes. Phylogenetic relationships and genomic diversity of 18 B. bacilliformis isolates (10 isolates from a region where Carrions disease is epidemic, Cuzco, Peru, and 8 isolates from a region where Carrions disease is endemic, Caraz, Peru) were assessed using genomic data generated by infrequent restriction site PCR and gene sequence analysis of the flagellin gltA and ialB genes. A population genetic analysis of the genomic diversity suggests that what was once considered an epidemic region of Peru did not result from the recent introduction of B. bacilliformis.

El Niño Helps Spread Bartonellosis Epidemics in Peru

The consequences of climate variability on human health, especially for poor and medically underserved populations, have received much attention in recent years. Some of the most severe health hazards induced by climate variability are epidemics of vector-borne infectious diseases. Entomologic studies have shown that insect vectors that transmit diseases, such as malaria, yellow fever, dengue, etc., are sensitive to temperature, humidity wind, and rainfall patterns, and therefore, their abundance is potentially influenced by climate variability. Because of its geographical location, the climate of tropical South America is strongly influenced by El Nino. The episodic outbreaks of various diseases in this region have been linked to the El Nino cycles. Yet, according to a report of the World Health Organization [1999], early results from South American epidemiological studies, which were based on the aggregated national disease data irrespective of the regional meteorological impacts, found no consistent correlation between the El Nino effect with the epidemics of malaria and yellow fever.