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Background: Population-based estimates of HIV prevalence, rates of new HIV diagnoses, and mortality rates among persons with HIV who have entered care are needed to optimize health service delivery and to improve the health outcomes of these individuals. However, these data have been lacking for Ontario.

Methods: Using a validated case-finding algorithm and linked administrative health care databases, we conducted a population-based study to determine the prevalence of HIV and rates of new HIV diagnoses among adults aged 18 years or older in Ontario between fiscal year 1996/1997 and fiscal year 2009/2010, as well as all-cause mortality rates among persons with HIV over the same period.

Results: Between 1996/1997 and 2009/2010, the number of adults living with HIV increased by 98.6% (from 7608 to 15,107), and the age- and sex-standardized prevalence of HIV increased by 52.8% (from 92.8 to 141.8 per 100,000 population; p < 0.001). Women and individuals 50 years of age or older accounted for increasing proportions of persons with HIV, rising from 12.8% to 19.7% (p < 0.001) and from 10.4% to 29.9% (p < 0.001), respectively, over the study period. During the study period, age- and sex-standardized rates of new HIV diagnoses decreased by 32.5% (from 12.3 to 8.3 per 100,000 population; p < 0.001) and mortality rates among adults with HIV decreased by 71.9% (from 5.7 to 1.6 per 100 adults with HIV; p < 0.001).

Interpretation: The prevalence of HIV infection in Ontario increased considerably between 1996/1997 and 2009/2010, with a greater relative burden falling on women and individuals aged 50 years of age or older. These trends may be due to the decreased rate of new diagnoses among younger men. All-cause mortality rates declined among persons with HIV who entered care.

Background: The Permanent Resident Database of Citizenship and Immigration Canada (CIC) contains sociodemographic information on immigrants but lacks ethnic group classifications. To enhance its usability for ethnicityrelated research, we categorized immigrants in the CIC database into one of Canada's official visible minority groups or a white category using their country of birth and mother tongue.

Methods: Using public data sources, we classified each of 267 country names and 245 mother tongues in the CIC data into 1 of 10 visible minority groups (South Asian, Chinese, black, Latin American, Filipino, West Asian, Arab, Southeast Asian, Korean, and Japanese) or a white group. We then used country of birth alone (method A) or country of birth plus mother tongue (method B) to classify 2.5 million people in the CIC database who immigrated to Ontario between 1985 and 2010 and who had a valid encrypted health card number. We validated the ethnic categorizations using linked selfreported ethnicity data for 6499 people who responded to the Canadian Community Health Survey (CCHS).

Results: Among immigrants listed in the CIC database, the 4 most frequent visible minority groups as classified by method B were South Asian (n = 582 812), Chinese (n = 400 771), black (n = 254 189), and Latin American (n = 179 118). Methods A and B agreed in 94% of the categorizations (kappa coefficient 0.94, 95% confidence interval [CI] 0.93-0.94). Both methods A and B agreed with self-reported CCHS ethnicity in 86% of all categorizations (for both comparisons, kappa coefficient 0.83, 95% CI 0.82-0.84). Both methods A and B had high sensitivity and specificity for most visible minority groups when validated using self-reported ethnicity from the CCHS (e.g., with method B, sensitivity and specificity were, respectively, 0.85 and 0.97 for South Asians, 0.93 and 0.99 for Chinese, and 0.90 and 0.97 for blacks).

Interpretation: The use of country of birth and mother tongue is a validated and practical method for classifying immigrants to Canada into ethnic categories.

Background: Hospitalists have become dominant providers of inpatient care in many North American hospitals. Despite the global growth of hospital medicine, no objective method has been proposed for defining the hospitalist discipline and delineating among inpatient practices on the basis of physicians' clinical volumes. We propose a functional method of identifying hospital-based physicians using aggregated measures of inpatient volume and apply this method to a retrospective, population-based cohort to describe the growth of the hospitalist movement, as well as the prevalence and practice characteristics of hospital-based generalists in one Canadian province.

Methods: We used human resource databases and financial insurance claims to identify all active fee-for-service physicians working in Ontario, Canada, between fiscal year 1996/1997 and fiscal year 2010/2011. We constructed 3 measures of inpatient volume from the insurance claims to reflect the time that physicians spent delivering inpatient care in each fiscal year. We then examined how inpatient volumes have changed for Ontario physicians over time and described the prevalence of full-time and part-time hospital-based generalists working in acute care hospitals in fiscal year 2010/2011.

Results: Our analyses showed a significant increase since fiscal year 2000/2001 in the number of high-volume hospital-based family physicians practising in Ontario (p < 0.001) and associated decreases in the numbers of high-volume internists and specialists (p = 0.03), where high volume was defined as ≥ 2000 inpatient services/ year. We estimated that 620 full-time and 520 part-time hospital-based physicians were working in Ontario hospitals in 2010/2011, accounting for 4.5% of the active physician workforce (n = 25 434). Hospital-based generalists, consisting of 207 family physicians and 130 general internists, were prevalent in all geographic regions and hospital types and collectively delivered 10% of all inpatient evaluation and care coordination for Ontario residents who had been admitted to hospital.

Interpretation: These analyses confirmed a substantial increase in the prevalence of general hospitalists in Ontario from 1996 to 2011. Systems-level analyses of clinical practice data represent a practical and valid method for defining and identifying hospital-based physicians.

Background: Both herpes zoster and malignancy are associated with immunosuppression. However, the association between herpes zoster and the subsequent diagnosis of malignancy is unclear. We undertook this study to assess whether a diagnosis of herpes zoster is a risk factor for subsequent malignancy.

Methods: For this matched retrospective cohort study, a physician billing database was used to identify individuals 18 years of age or older with a diagnosis of herpes zoster and no prior diagnosis of cancer or HIV infection. Individuals with a herpes zoster diagnosis were matched one-to-one to individuals without a herpes zoster diagnosis, and both groups were examined for up to 5 years for diagnosis of cancer.

Results: A total of 542,575 individuals with a diagnosis of herpes zoster were identified. Compared with matched controls, these patients were more likely (p < 0.001) to have a history of myocardial infarction, asthma, congestive heart failure, chronic obstructive pulmonary disease, diabetes mellitus, and hypertension. The incidence of cancer was significantly greater among individuals with herpes zoster than among those without herpes zoster, for both men and women and across all time intervals studied (up to 5 years). The greatest adjusted hazard ratio was seen 180 days after a herpes zoster diagnosis (1.19, 95% confidence interval 1.12-1.25); the hazard ratio decreased as the time from herpes zoster diagnosis increased. Lymphoma was the type of cancer with the greatest relative increase in incidence following diagnosis of herpes zoster.

Interpretation: There is a risk of malignancy following an episode of herpes zoster in both men and women and in all age groups 18 years and over. The risk is greatest during the first 180 days following the diagnosis of herpes zoster.

Background: Antibiotic-associated diarrhea (AAD) and Clostridium difficile infection (CDI) are associated with high morbidity, mortality, and health care costs. Probiotics may mitigate the existing disease burden. We performed a systematic review and meta-analysis to evaluate the efficacy of co-administration of probiotics with antibiotics in preventing these adverse outcomes in adult inpatients.

Methods: Systematic searches of MEDLINE (1946 to May 2012), Embase (1980 to May 2012), and the Cochrane Central Register of Controlled Trials were undertaken on May 31, 2012, to identify relevant publications. We searched for randomized controlled trials, published in English, of adult inpatients who were receiving antibiotics and who were randomly assigned to co-administration of probiotics or usual care, with or without the use of placebo. Studies were included if they reported on AAD or CDI (or both) as outcomes. Data for predetermined criteria evaluating study characteristics, methods, and risk of bias were extracted. Trials were given a global rating of good, fair, or poor by at least 2 reviewers. Meta-analyses were performed using a random-effects model, and pooled relative risks (RRs) and 95% confidence intervals (CIs) were calculated.

Results: Sixteen trials met the criteria for inclusion in this review. Four studies were of good quality, 5 were of fair quality, and 7 were of poor quality. Pooled analyses revealed significant reductions in the risks of AAD (RR 0.61, 95% CI 0.47 to 0.79) and CDI (RR 0.37, 95% CI 0.22 to 0.61) among patients randomly assigned to co-administration of probiotics. The number needed to treat for benefit was 11 (95% CI 8 to 20) for AAD and 14 (95% CI 9 to 50) for CDI. With subgroup analysis, significant reductions in rates of both AAD and CDI were retained in the subgroups of good-quality trials, the trials assessing a primarily Lactobacillus-based probiotic formulation, and the trials for which the follow-up period was less than 4 weeks.

Interpretation: Probiotics used concurrently with antibiotics reduce the risk of AAD and CDI.

Background: Large multispecialty physician group practices, with a central role for primary care practitioners, have been shown to achieve high-quality, low-cost care for patients with chronic disease. We assessed the extent to which informal multispecialty physician networks in Ontario could be identified by using health administrative data to exploit natural linkages among patients, physicians, and hospitals based on existing patient flow.

Methods: We linked each Ontario resident to his or her usual provider of primary care over the period from fiscal year 2008/2009 to fiscal year 2010/2011. We linked each specialist to the hospital where he or she performed the most inpatient services. We linked each primary care physician to the hospital where most of his or her ambulatory patients were admitted for non-maternal medical care. Each resident was then linked to the same hospital as his or her usual provider of primary care. We computed "loyalty" as the proportion of care to network residents provided by physicians and hospitals within their network. Smaller clusters were aggregated to create networks based on a minimum population size, distance, and loyalty. Networks were not constrained geographically.

Results: We identified 78 multispecialty physician networks, comprising 12,410 primary care physicians, 14,687 specialists, and 175 acute care hospitals serving a total of 12,917,178 people. Median network size was 134,723 residents, 125 primary care physicians, and 143 specialists. Virtually all eligible residents were linked to a usual provider of primary care and to a network. Most specialists (93.5%) and primary care physicians (98.2%) were linked to a hospital. Median network physician loyalty was 68.4% for all physician visits and 81.1% for primary care visits. Median non-maternal admission loyalty was 67.4%. Urban networks had lower loyalties and were less self-contained but had more health care resources.

Interpretation: We demonstrated the feasibility of identifying informal multispecialty physician networks in Ontario on the basis of patterns of health care-seeking behaviour. Networks were reasonably self-contained, in that individual residents received most of their care from providers within their respective networks. Formal constitution of networks could foster accountability for efficient, integrated care through care management tools and quality improvement, the ideas behind "accountable care organizations."

In the speakers' bureau system, physicians are recruited and trained by pharmaceutical, biotechnology, and medical device companies to deliver information about products to other physicians, in exchange for a fee. Using publicly available disclosures, we assessed the thesis that speakers' bureau involvement is not a feature of academic medicine in Canada, by estimating the prevalence of participation in speakers' bureaus among Canadian faculty in one medical specialty, cardiology. We analyzed the relevant features of an actual contract made public by the physician addressee and applied the Canadian Medical Association (CMA) guidelines on physician-industry relations to participation in a speakers' bureau. We argue that speakers' bureau participation constitutes a form of peer selling that should be understood to contravene the prohibition on product endorsement in the CMA Code of Ethics. Academic medical institutions, in conjunction with regulatory colleges, should continue and strengthen their policies to address participation in speakers' bureaus.

Background: Adults with chronic medical conditions are more likely to report unmet health care needs. Whether unmet health care needs are associated with an increased risk of adverse health outcomes is unclear.

Methods: Adults with at least one self-reported chronic condition (arthritis, chronic obstructive pulmonary disease, diabetes mellitus, heart disease, hypertension, mood disorder, stroke) from the 2001 and 2003 cycles of the Canadian Community Health Survey were linked to national hospitalization data. Participants were followed from the date of their survey until March 31, 2005, for the primary outcomes of all-cause and cause-specific admission to hospital. Secondary outcomes included length of stay, 30-day and 1-year all-cause readmission to hospital, and in-hospital death. Negative binomial regression models were used to estimate the association between unmet health care needs, admission to hospital, and length of stay, with adjustment for socio-demographic variables, health behaviours, and health status. Logistic regression was used to estimate the association between unmet needs, readmission, and in-hospital death. Further analyses were conducted by type of unmet need.

Results: Of the 51 932 adults with self-reported chronic disease, 15.5% reported an unmet health care need. Participants with unmet health care needs had a risk of all-cause admission to hospital similar to that of patients with no unmet needs (adjusted rate ratio [RR] 1.04, 95% confidence interval [CI] 0.94-1.15). When stratified by type of need, participants who reported issues of limited resource availability had a slightly higher risk of hospital admission (RR 1.18, 95% CI 1.09-1.28). There was no association between unmet needs and length of stay, readmission, or in-hospital death.

Interpretation: Overall, unmet health care needs were not associated with an increased risk of admission to hospital among those with chronic conditions. However, certain types of unmet needs may be associated with higher or lower risk. Whether unmet needs are associated with other measures of resource use remains to be determined.

Background: In Ontario, Canada, the patient-centred medical home is a model of primary care delivery that includes 3 model types of interest for this study: enhanced fee-for-service, blended capitation, and team-based blended capitation. All 3 models involve rostering of patients and have similar practice requirements but differ in method of physician reimbursement, with the blended capitation models incorporating adjustments for age and sex, but not case mix, of rostered patients. We evaluated the extent to which persons with mental illness were included in physicians' total practices (as rostered and non-rostered patients) and were included on physicians' rosters across types of medical homes in Ontario.

Methods: Using population-based administrative data, we considered 3 groups of patients: those with psychotic or bipolar diagnoses, those with other mental health diagnoses, and those with no mental health diagnoses. We modelled the prevalence of mental health diagnoses and the proportion of patients with such diagnoses who were rostered across the 3 medical home model types, controlling for demographic characteristics and case mix.

Results: Compared with enhanced fee-for-service practices, and relative to patients without mental illness, the proportions of patients with psychosis or bipolar disorders were not different in blended capitation and team-based blended capitation practices (rate ratio [RR] 0.91, 95% confidence interval [CI] 0.82-1.01; RR 1.06, 95% CI 0.96-1.17, respectively). However, there were fewer patients with other mental illnesses (RR 0.94, 95% CI 0.90-0.99; RR 0.89, 95% CI 0.85-0.94, respectively). Compared with expected proportions, practices based on both capitation models were significantly less likely than enhanced fee-for-service practices to roster patients with psychosis or bipolar disorders (for blended capitation, RR 0.92, 95% CI 0.90-0.93; for team-based capitation, RR 0.92, 95% CI 0.88-0.93) and also patients with other mental illnesses (for blended capitation, RR 0.94, 95% CI 0.92-0.95; for team-based capitation, RR 0.93, 95% CI 0.92-0.94).

Interpretation: Persons with mental illness were under-represented in the rosters of Ontario's capitation-based medical homes. These findings suggest a need to direct attention to the incentive structure for including patients with mental illness.