Rural-urban differences in use of health services before and after dementia diagnosis: a retrospective cohort study

BACKGROUND

Rural-urban differences in health service use among persons with prevalent dementia are known. However, the extent of geographic differences in health service use over a long observation period, and prior to diagnosis, have not been sufficiently examined. The purpose of this study was to examine yearly rural-urban differences in the proportion of patients using health services, and the mean number of services, in the 5-year period before and 5-year period after a first diagnosis of dementia.

METHODS

This population-based retrospective cohort study used linked administrative health data from the Canadian province of Saskatchewan to investigate the use of five health services [family physician (FP), specialist physician, hospital admission, all-type prescription drug dispensations, and short-term institutional care admission] each year from April 2008 to March 2019. Persons with dementia included 2,024 adults aged 65 years and older diagnosed from 1 April 2013 to 31 March 2014 (617 rural; 1,407 urban). Matching was performed 1:1 to persons without dementia on age group, sex, rural versus urban residence, geographic region, and comorbidity. Differences between rural and urban persons within the dementia and control cohorts were separately identified using the Z-score test for proportions (p < 0.05) and independent samples t-test for means (p < 0.05).

RESULTS

Rural compared to urban persons with dementia had a lower average number of FP visits during 1-year and 2-year preindex and between 2-year and 4-year postindex (p < 0.05), a lower likelihood of at least one specialist visit and a lower average number of specialist visits during each year (p < 0.05), and a lower average number of all-type prescription drug dispensations for most of the 10-year study period (p < 0.05). Rural-urban differences were not observed in admission to hospital or short-term institutional care (p > 0.05 each year).

CONCLUSIONS

This study identified important geographic differences in physician services and all-type prescription drugs before and after dementia diagnosis. Health system planners and educators must determine how to use existing resources and technological advances to support care for rural persons living with dementia.

Utilization of Health Services Before and After Diagnosis in a Specialist Rural and Remote Memory Clinic

Background

Limited research exists on the use of specific health services over an extended time among rural persons with dementia. The study objective was to examine health service use over a 10-year period, five years before until five years after diagnosis in the specialist Rural and Remote Memory Clinic (RRMC).

Methods

Clinical and administrative health data of RRMC patients were linked. Annual health service utilization of the cohort (N = 436) was analyzed for 416 patients pre-index (57.5% female, mean age 71.2 years) and 419 post-index (56.3% female, mean age 70.8 years). Approximately 40% of memory clinic diagnoses were Alzheimer's disease (AD), 20% non-AD dementia, and 40% mild or subjective cognitive impairment or other condition. Post-index, 188 patients (44.9%) moved to permanent long-term care and were retained in the sample; 121 patients died (28.9%) and were removed yearly.

Results

Over the ten-year study period, a significant increase occurred in the average number of FP visits, all-type drug prescriptions, and dementia-specific drug prescriptions (all p <.001). The highest proportion of patients hospitalized was observed one year pre-index, the highest average number of specialist visits was observed one year post-index, and both demonstrated a significant decreasing trend in the five-year post-index period (p = .037).

Conclusions

A pattern of increasing FP visits and drug prescriptions over an extended period before and after diagnosis in a specialist rural and remote memory clinic highlights a need to support FPs in post-diagnostic management. Further research of longitudinal patterns in health service utilization is merited.

The impact of alternate level of care on access block and operational strategies to reduce emergency wait times: a multi-center simulation study

OBJECTIVES

Lengthy emergency department (ED) wait times caused by hospital access block is a growing concern for the Canadian health care system. Our objective was to quantify the impact of alternate-level-of-care on hospital access block and evaluate the likely effects of multiple interventions on ED wait times.

METHODS

Discrete-event simulation models were developed to simulate patient flows in EDs and acute care of six Canadian hospitals. The model was populated with administrative data from multiple sources (April 2017-March 2018). We simulated and assessed six different intervention scenarios' impact on three outcome measures: (1) time waiting for physician initial assessment, (2) time waiting for inpatient bed, and (3) patients who leave without being seen. We compared each scenario's outcome measures to the baseline scenario for each ED.

RESULTS

Eliminating 30% of medical inpatients' alternate-level-of-care days reduced the mean time waiting for inpatient bed by 0.25 to 4.22 h. Increasing ED physician coverage reduced the mean time waiting for physician initial assessment (∆ 0.16-0.46 h). High-quality care transitions targeting medical patients lowered the mean time waiting for inpatient bed for all EDs (∆ 0.34-6.85 h). Reducing ED visits for family practice sensitive conditions or improving continuity of care resulted in clinically negligible reductions in wait times and patients who leave without being seen rates.

CONCLUSIONS

A moderate reduction in alternate-level-of-care hospital days for medical patients could alleviate access block and reduce ED wait times, although the magnitude of reduction varies by site. Increasing ED physician staffing and aligning physician capacity with inflow demand could also decrease wait time. Operational strategies for reducing ED wait times should prioritize resolving output and throughput factors rather than input factors.

The effect of body weight on employment among Canadian women: evidence from Canadian data

OBJECTIVES

This paper examines the impact of obesity on labour market participation among Canadian women by using various Canadian population health surveys.

METHODS

We estimate the impact of obesity on labour market participation using probit and bivariate probit regression models. To correct for a potential endogenous relationship between obesity and labour market participation, we also use instrumental variables in the bivariate probit regression context.

RESULTS

The results suggest that the probability of employment has negative association with the body weight of women. This effect is statistically significant and has substantial impact on employment. The results show that obesity decreases employment probability by about 25 percentage points for women.

CONCLUSION

In addition to well-known negative health consequences, obesity also has additional negative effect on employment. This negative impact on employment is comparable to the impacts of mental health or illicit drug use on employment. Public health policies aimed at reducing obesity would generate additional benefits to society. Our results also provide additional evidence for lawmakers to amend the labour laws in Canada in order to acknowledge and prohibit hiring practices that discriminate against individuals with high body weight.

Osteoporosis-related fracture case definitions for population-based administrative data

Background

Population-based administrative data have been used to study osteoporosis-related fracture risk factors and outcomes, but there has been limited research about the validity of these data for ascertaining fracture cases. The objectives of this study were to: (a) compare fracture incidence estimates from administrative data with estimates from population-based clinically-validated data, and (b) test for differences in incidence estimates from multiple administrative data case definitions.

Methods

Thirty-five case definitions for incident fractures of the hip, wrist, humerus, and clinical vertebrae were constructed using diagnosis codes in hospital data and diagnosis and service codes in physician billing data from Manitoba, Canada. Clinically-validated fractures were identified from the Canadian Multicentre Osteoporosis Study (CaMos). Generalized linear models were used to test for differences in incidence estimates.

Results

For hip fracture, sex-specific differences were observed in the magnitude of under- and over-ascertainment of administrative data case definitions when compared with CaMos data. The length of the fracture-free period to ascertain incident cases had a variable effect on over-ascertainment across fracture sites, as did the use of imaging, fixation, or repair service codes. Case definitions based on hospital data resulted in under-ascertainment of incident clinical vertebral fractures. There were no significant differences in trend estimates for wrist, humerus, and clinical vertebral case definitions.

Conclusions

The validity of administrative data for estimating fracture incidence depends on the site and features of the case definition.

Measurement equivalence of the SF-36 in the Canadian Multicentre Osteoporosis Study

BACKGROUND

Studies that compare health-related quality of life (HRQOL) and other patient-reported outcomes in different populations rest on the assumption that the measure has equivalent psychometric properties across groups. This study examined the measurement equivalence (ME) of the 36-item Medical Outcomes Study Short Form Survey (SF-36), a widely-used measure of HRQOL, by sex and race in a population-based Canadian sample.

FINDINGS

SF-36 data were from the Canadian Multicentre Osteoporosis Study, a prospective cohort study that randomly sampled adult men and women from nine sites across Canada. Confirmatory factor analysis (CFA) techniques were used to test hypotheses about four forms of ME, which are based on equality of the factor loadings, variances, covariances, and intercepts. Analyses were conducted for Caucasian and non-Caucasian females (n = 6,539) and males (n = 2,884). CFA results revealed that a measurement model with physical and mental health factors provided a good fit to the data. All forms of ME were satisfied for the study groups.

CONCLUSIONS

The results suggest that sex and race do not influence the conceptualization of a general measure of HRQOL in the Canadian population.

Comparing comorbidity measures for predicting mortality and hospitalization in three population-based cohorts

Background

Multiple comorbidity measures have been developed for risk-adjustment in studies using administrative data, but it is unclear which measure is optimal for specific outcomes and if the measures are equally valid in different populations. This research examined the predictive performance of five comorbidity measures in three population-based cohorts.

Methods

Administrative data from the province of Saskatchewan, Canada, were used to create the cohorts. The general population cohort included all Saskatchewan residents 20+ years, the diabetes cohort included individuals 20+ years with a diabetes diagnosis in hospital and/or physician data, and the osteoporosis cohort included individuals 50+ years with diagnosed or treated osteoporosis. Five comorbidity measures based on health services utilization, number of different diagnoses, and prescription drugs over one year were defined. Predictive performance was assessed for death and hospitalization outcomes using measures of discrimination (c-statistic) and calibration (Brier score) for multiple logistic regression models.

Results

The comorbidity measures with optimal performance were the same in the general population (n = 662,423), diabetes (n = 41,925), and osteoporosis (n = 28,068) cohorts. For mortality, the Elixhauser index resulted in the highest c-statistic and lowest Brier score, followed by the Charlson index. For hospitalization, the number of diagnoses had the best predictive performance. Consistent results were obtained when we restricted attention to the population 65+ years in each cohort.

Conclusions

The optimal comorbidity measure depends on the health outcome and not on the disease characteristics of the study population.

The effect of cassava leave intake on thyroid hormone and urinary iodine

The effect of consuming large amounts of cassava leaves on thyroid function and urinary iodine was studied. Twenty volunteers were given 200 gm of boiled cassava leaves twice a day for 12 consecutive days. Thyroid hormones triiodothyronine and thyroxine were significantly lower by 9 days. Urinary iodine excretion was also significantly decreased. Cassava leaves, consumed in large amounts by aborigines, probably caused goitres by decreasing iodine absorption.