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The impact of geographical location on trends in hospitalisation rates and outcomes for fall‐related injuries in older people

The impact of geographical location on trends in hospitalisation rates and outcomes for... mortality and morbidity, both globally Objective: This population-based study investigates the influence of geographical location on Fand in Australia. It is the 15th-highest hospital admissions, utilisation and outcomes for fall-related injury in older adults, adjusting specific cause of death of people aged over 70 for age, sex and comorbidities. worldwide, responsible for an estimated 1.41% of deaths in 2012, and the 9th-highest specific Methods: A linked dataset of all admissions of NSW residents aged 65 and older, hospitalised cause of Disability-Adjusted Life Years (DALYs) at least once for a fall-related injury between 2003 and 2012, was used to estimate rates of in this group. In Australia, there were 1,920 hospitalisations, total lengths-of-stay, 28-day readmissions, and 30-day mortalities. These were deaths directly due to falls in 2013, causing standardised for age, sex, comorbidity, and remoteness. 6,269 Years of Potential Life Lost (YLLs). Results: Compared to urban residents, rural residents were hospitalised less (p<0.0001) and Most falls are not fatal. In Australia, one hospitalisation rates increased at a lower rate (0.8% vs 2.6% per year) from 2003 to 2012. Rural in every 10 days spent in hospital by a residents had a shorter median total length of stay (5 vs 7 days, p<0.0001), a higher 28-day person aged 65 years and older is directly readmission rate (18.9% vs 17.0%, p<0.0001) and higher 30-day mortality (5.0% vs 4.9%, attributable to an injurious fall. There is also p=0.0046). evidence that the rate of fall-related injury Conclusions: Over the study period, rural residents of NSW had lower rates of fall-related hospitalisation continues to increase over injury hospitalisation and a lower annual increase in hospitalisation rates compared to urban time, with a 3.8% per year increase from 1998 residents. When hospitalised, rural residents had a shorter length-of-stay, but higher rates of to 2012 in New South Wales (NSW). readmission and mortality. These differences existed following standardisation. A number of factors influence the provision Implications: This study highlights the need for further research to characterise and explain of health care and the ability to provide this variability. equitable access to care, including Key words: geography, aged, accidental falls, data linkage, hospitalisation geographical location. Evidence to date highlights differences in health care access, urban centres in coastal regions, particularly injury hospitalisations of older people, and to utilisation and quality between rural and Sydney. Population density ranges from determine whether any observed differences urban populations. People in rural areas 6,7 more than 14,300 persons per km to fewer remain after adjustment for age, sex and the experience higher hospitalisation rates, 2,17 than 1/km placing considerable demands presence of comorbidities. higher rates of readmission, and higher rates 9,10 on the provision of accessible, equitable of mortality than residents in urban areas. health care services. The distribution is Other factors known to affect health use and Methods similar to the state populations of Victoria, outcomes include age, sex and any present 11-16 South Australia and Western Australia, and is comorbidities. Study population and data sources representative of Australia as a whole. The geography and population distribution The study population comprised 185,670 This population-based study investigated of Australia presents a particular challenge to NSW residents aged 65 years and older, with the influence of geographical location on the aspiration of health care parity. NSW has at least one admission to a public or private hospitalisation rates, utilisation (total length a population of more than 7.3 million people, hospital in NSW for an injury resulting of stay and 28-day readmission), and patient of whom 14.9% are aged 65 and older. from a fall between 1 January 2003 and 31 outcomes (30-day mortality) for fall-related Most of this population is concentrated in December 2012. 1. Falls and Injury Prevention Group, Neuroscience Research Australia, New South Wales 2. Prince of Wales Clinical School, UNSW Australia, New South Wales 3. Australian Institute of Health Innovation, Macquarie University, New South Wales Correspondence to: Professor Jacqueline Close, Falls and Injury Prevention Group, Neuroscience Research Australia, Barker Street, Randwick, NSW 2031; e-mail: j.close@neura.edu.au Submitted: August 2015; Revision requested: October 2015; Accepted: December 2015 The authors have stated they have no conflict of interest. Aust NZ J Public Health. 2016; 40:342-8; doi: 10.1111/1753-6405.12524 342 Australian and New Zealand Journal of Public Health 2016 vol . 40 no . 4 © 2016 Public Health Association of Australia Older People The impact of geographical location on trends for fall-related injuries Two data sources were linked for use in Regional Australia, Remote Australia and and included in the total LOS calculation. 6,10 this study: the NSW Admitted Patient Data Very Remote Australia). As of 2013, 93.5% Leave days were not included in the total. Collection (APDC) and the NSW Registry of of the state population live in urban areas, Admission and discharge on same day was Births, Deaths and Marriages (RBDM) mortality with an average density of 75.85 people/km . considered a one-day stay. A truncation was data. The APDC is a register of all ‘episodes of The other 6.5% live in rural areas, with 0.68 applied for total length of stay, at the level of 2,17 care’ from all public and private hospitals in people/km. In 2003, these proportions were three standard deviations above the mean, to NSW. An ‘episode of care’ ends upon a patient’s 92.7% and 7.3%, respectively, suggesting a net avoid extreme outliers due to data errors or 17 29 death, discharge, transfer or change in type of migration towards urban centres. unrepresentative care practices. As length care (from acute to subacute or rehabilitation). of stay is generally positively skewed with a Comorbidities were identified using the Thus, for a single injury event, a person may long tail, the data was log-transformed prior Charlson Comorbidity Index and assigned have multiple ‘episodes of care’ recorded. Data to analysis. A Wilcoxon-Mann-Whitney test to each individual, based on the presence in the APDC is coded using the International was used to compare distributions of total or absence of comorbidity recorded in any Statistical Classification of Diseases and Related length of stay of the two groups. A linear of the first 40 diagnosis fields using the Health Problems, Tenth Revision, Australian regression model was fitted to total length ICD-10 coding algorithm developed by Quan Modification (ICD-10-AM). The RBDM 24 of stay using a robust M-estimator, using age and Sundararajan. A one-year look-back contains records of all deaths of NSW residents, group, sex, all Charlson comorbidity groups period was used, consistent with Preen and certified by a coroner or medical practitioner. 25 and remoteness. The resultant regression Holman. Binary variables for each Charlson Date and fact of death were obtained from the coefficient for remoteness was reported. comorbidity group were used instead of the RBDM. aggregated weighted score, as these provide A subsequent hospital admission, for any better model fit. cause, beginning within 28 days of discharge Data linkage was defined as a ‘28-day readmission’. The Centre for Health Record Linkage (CHeReL) Data management and analysis Hospital stays ending with in-hospital death linked records from the APDC and RBDM. were excluded from readmission analysis. Data was analysed using SAS Enterprise Guide Choicemaker was used to probabilistically 27 Thirty-day mortality was defined as death 6.1. P values less than 0.05 were considered match identifying information (full name, from any cause within 30 days of admission statistically significant. date of birth, sex and address), followed from the index fall-related hospitalisation. Demographic characteristics were described, by a manual review of uncertain matches Relative risks were calculated for 28-day using chi-square tests to analyse differences when necessary. A unique person project readmission and 30-day mortality, adjusted in the two subsets. Comorbidities were number (PPN) for each individual identified for age group, sex, Charlson comorbidity grouped into three categories, based on in the linkage process was created, allowing groups and remoteness. Modified Poisson number of comorbidities present within one for accurate determination of admission and regression models with robust error variances year of hospitalisation. outcome rates. were used to calculate confidence intervals Trends in the number and rate of 30 for the adjusted relative risks. Identification of fall-related injury, hospitalisations over time were investigated Ethics approval for this study was obtained remoteness and patient comorbidities using a negative binomial regression on the from the NSW Population and Health Services annual count of admissions. Hospitalisation A fall-related injury hospitalisation was Research Ethics Committee (HREC/13/CIPHS/49). rates were calculated using the age-specific defined as such if the principal diagnosis for number of admissions and the population the initial episode of care of a hospitalisation of the corresponding age group of that Results was an injury (ICD-10-AM codes S00-T75 or year. These were directly standardised to T79) with an associated primary external Demographic characteristics the 2001 Australian Bureau of Statistics cause code of a fall (ICD-10-AM codes 28 There were 256,536 fall-related injury Standard Population. Trends in rates over W00-W19). The principal diagnosis was hospitalisations of people aged 65 and older time were investigated using a negative defined as the diagnosis primarily responsible during the 10-year study period. Of these, binomial regression on the standardised for the hospitalisation episode. 7.4% (n=18,862) of hospitalisations were rates. Hospitalisations were also indirectly The Australian Statistical Geographical of rural residents, with the majority (92.6%, standardised to the equivalent hospitalised Standard Remoteness Area (ASGS RA) is a n=237,674) of people resident in urban areas. population for 2012 to generate both age- five-category classification using defined More than two-thirds of all hospitalised standardised and age-, sex- and comorbidity- index scores of distance to service centres of individuals were female, from both urban standardised hospitalisation rate ratios various sizes (settlements with at least 1,000, and rural areas. There was a clear age-related between rural and urban residents. 5,000, 18,000, 48,000 and 250,000 residents, trend in number of hospitalisations, with Total length of stay was defined as the respectively). The score is initially calculated older age associated with a greater number number of days from date of admission in the on a one-kilometre grid, and then the mean of hospitalisations. Just under half (49.4%) the index ‘episode of care’ until final discharge value for each Census Collection District is hospitalised patients had no comorbidities, from hospital. Hospitalisations that consisted aggregated to form the Remoteness Areas. with a further 40.7% presenting with one of multiple contiguous episodes of care for an For ease of reporting and comparability, the or two comorbidities. Dementia (19.9%), injury event, where the discharge code was five categories were collapsed into two: urban congestive heart failure (10.2%), diabetes a transfer to another facility or a type change (from Major Cities of Australia and Inner complications (8.9%), pulmonary disease transfer, were considered as one hospital stay Regional Australia) and rural (from Outer (8.7%) and cerebrovascular disease (8.1%) 2016 vol . 40 no . 4 Australian and New Zealand Journal of Public Health 343 © 2016 Public Health Association of Australia Sukumar et al. Article were the most common comorbidities increased for rural residents by 2.1% per year for age, this difference was less pronounced. recorded. Compared to people living in urban (p=0.0002), which was significantly lower Standardising for age, sex, and comorbidity areas, a higher proportion of rural residents than the 5.8% per year increase for urban further reduced this disparity; however, hospitalised for a fall were male (p<0.0001), residents (p<0.0001). Rates of hip fracture significant differences remained from 2005 aged 65–74 years (p<0.0001), and with fewer hospitalisations were not significantly onwards. recorded comorbidities (p<0.0001). different between urban and rural residents. Rural HRRs for fall-related fractures were For both urban and rural residents, fractures Observed hospitalisation rate ratios (HRRs) consistently lower than urban, and this were the most common injury type, for all fall-related injury in rural residents remained true when standardising for age, comprising 59.8% and 53.9% of fall-related were consistently lower than those in urban sex, and comorbidity. Conversely, non- injury hospitalisations, respectively. However, areas (Table 2). However, when standardised fracture injury of rural residents HRRs were the proportion of rural residents hospitalised Table 1: Demographic characteristics of patients aged 65 years and older hospitalised for an injurious fall, by with a fracture was lower than urban remoteness, linked hospitalisation and mortality records NSW, 2003–2012. residents (p<0.0001). Hip fracture was the Characteristic Urban Rural Statistic most common fracture type, and injury to the head and neck the most common non- χ (df ), p value N % N % fracture injury (Table 1). Sex 63.60 (1), p<0.0001 Male 72,051 30.3 6,242 33.1 Hospitalisations Female 165,623 69.7 12,620 66.9 The number of fall-related injury Age group 415.57 (4), p<0.0001 hospitalisations increased by 5.6% per year (95%CI 5.2–5.9, p<0.0001) from 19,749 in 65–69 years 20,381 8.6 2,160 11.5 2003 to 32,006 in 2012. While the number 70–74 years 26,009 10.9 2,470 13.1 of hospitalisations increased for both urban 75–79 years 38,712 16.3 3,352 17.8 and rural residents, hospitalisations for rural 80–84 years 54,976 23.1 4,257 22.6 residents increased at a significantly lower 85+ years 97,596 41.1 6,623 35.1 rate than that of urban residents (4.1%; 95%CI Comorbidities 3.4–4.8, p<0.0001 and 5.7%; 95%CI 5.3–6.0, p<0.0001, respectively, per year). Dementia 48,234 20.3 3,057 16.21 182.48 (1), p<0.0001 Overall, the age-standardised statewide Congestive heart failure 24,275 10.2 1,930 10.2 0.01 (1), p = 0.9351 hospitalisation rate for fall-related injury Diabetes complications 21,500 9.1 1,396 7.4 58.17 (1), p<0.0001 increased from 2,209 per 100,000 population Pulmonary disease 20,353 8.6 1,880 10.0 43.50 (1), p<0.0001 in 2003 to 2,755 per 100,000 population in Cerebral vascular disease 19,379 8.2 1,347 7.1 24.11 (1), p<0.0001 2012, an increase of 2.5% per year (95%CI Number of comorbidities 150.10 (2), p<0.0001 2.0–2.9, p<0.0001). No significant trend 0 116,614 49.1 10,102 53.6 was identified for fractures, while non- 1-2 97,221 40.9 7,155 37.9 fracture injury increased through the study 3+ 23,839 10.0 1,605 8.5 period by 5.5% annually (95%CI 4.6–6.4%, Injury type p<0.0001), from 749 per 100,000 population Fractures 142,100 59.8 10,169 53.9 250.03 (1), p<0.0001 to 1,191 per 100,000 population. Hip fracture hospitalisation rates decreased by 1.3% per – head and neck 5,692 2.4 315 1.7 40.15 (1), p<0.0001 year (95%CI 0.4–2.2%, p=0.005) from 539 – arm 37,200 15.7 2,498 13.2 77.48 (1), p<0.0001 per 100,000 population to 496 per 100,000 – trunk 30,621 12.9 2,094 11.1 49.87 (1), p<0.0001 population. – hip 50,514 21.3 3,767 20.0 17.22 (1), p<0.0001 Age-standardised hospitalisation rates – leg 18,030 7.6 1,484 7.9 1.97 (1), p=0.1602 for all fall-related injury, fractures, non- – multiple/unspecified 43 0.0 11 0.1 13.44 (1), p=0.0002 fractures and hip fractures by remoteness Nonfracture injury 94,159 39.6 8,554 45.4 239.29 (1), p<0.0001 category are shown in Figure 1. Rates of all fall-related injury hospitalisations for rural – Traumatic brain injury 9,516 4.0 603 3.2 30.03 (1), p<0.0001 residents increased at a significantly lower b – head and neck 34,242 14.4 3,001 15.9 31.82 (1), p<0.0001 rate (0.8% per year) than those of the urban – arm 14,087 5.9 1,355 7.2 48.79 (1), p<0.0001 population (2.6% per year) over the study – trunk 12,207 5.1 1,286 6.8 99.21 (1), p<0.0001 period. Hospitalisation rates for fractures – leg 22,809 9.6 2,151 11.4 64.98 (1), p<0.0001 were consistently lower for rural residents. – multiple/unspecified r egions 1,298 0.6 158 0.8 26.32 (1), p<0.0001 No significant trend over time was identified for rural residents (p=0.5), in comparison Unspecified region and type 1,415 0.6 139 0.7 5.82 (1), p=0.0159 to an observed increase of 0.6% per year in Notes: a: Statistic calculated specifically for each injury subtype urban residents (p<0.04). Correspondingly, b: Excludes Traumatic Brain Injury (TBI) rates of non-fractures hospitalisations 344 Australian and New Zealand Journal of Public Health 2016 vol . 40 no . 4 © 2016 Public Health Association of Australia Older People The impact of geographical location on trends for fall-related injuries were readmitted within 28 days (Table 4). When adjusted for age group, sex, and comorbidities, rural residents were readmitted more than urban residents (ARR 1.12; 95%CI 1.08–1.16, p<0.0001). Comparable results were found for fracture, non-fracture injury, and hip fracture. 30-day mortality The 30-day mortality rate for all fall-related injury over the study period was 4.9% (Table 5). Overall, there was no difference in 30-day mortality rates between fall-related fracture and non-fracture injuries (4.9% vs 5.0%, respectively); however, 30-day mortality for hip fracture was significantly higher (8.3%). After adjustment for age, sex and Figure 1: Fall-related injury, fracture, non-fracture and hip fracture hospitalisations of individuals aged 65 years comorbidity, rural residents were 15% more and older, age-standardised, by remoteness, NSW, 2003–2012. likely (ARR 1.15; 95%CI 1.08–1.23, p<0.0001) to die within 30 days of hospitalisation higher than the urban HRRs from 2003 to was seven days (Table 3). Rural residents for a fall-related injury than their urban 2005, with an overall observed reduction had a shorter median length of stay than counterparts. This pattern varied by injury over the 10 years. This result remained after urban residents (5 vs 7 days, p<0.0001). type, with rural residents experiencing age, sex, and comorbidity standardisation. When adjusted for age group, sex and higher 30-day mortality rates for all fractures Although the observed HRR for hip fractures comorbidities, remoteness remained a (ARR 1.28; 95%CI 1.18–1.40, p<0.0001) was consistently lower for rural residents, significant factor (p <0.0001). This pattern was and hip fractures (ARR 1.19; 95%CI 1.07– standardisation reduced this difference over consistent for fractures, non-fracture injuries, 1.32, p<0.0001), but no difference for non- the 10 years of the study. and hip fractures. fracture injuries (p=0.3631). Total length of stay 28-day readmission Discussion Median length of stay for all fall-related Overall, 17.1% of patients discharged This study has demonstrated that rural injury hospitalisations over the study period following a fall-related injury hospitalisation residents had lower rates of fall-related Table 2: Observed and standardised hospitalisation rate ratios for rural residents, compared to urban residents, aged 65 and older admitted for a fall-related injury, by remoteness, NSW, 2003–2012. 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 All Injury Hospitalisation Rate Ratio Observed 0.94* 0.92** 0.86*** 0.88*** 0.84*** 0.90*** 0.82*** 0.85*** 0.77*** 0.83*** Age-Standardised 0.99 0.98 0.92** 0.94* 0.89*** 0.96* 0.88*** 0.90*** 0.82*** 0.89*** Age-, Sex-, Comorbidity-Standardised 1.00 0.99 0.93* 0.95* 0.90*** 0.97 0.89*** 0.91*** 0.83*** 0.90*** Fracture Hospitalisation Rate Ratio Observed 0.84*** 0.79*** 0.73*** 0.78*** 0.76*** 0.78*** 0.74*** 0.77*** 0.75*** 0.78*** Age-Standardised 0.88*** 0.84*** 0.77*** 0.82*** 0.81*** 0.83*** 0.78*** 0.83*** 0.80*** 0.83*** Age-, Sex-, Comorbidity-Standardised 0.90** 0.85*** 0.79*** 0.84*** 0.82*** 0.84*** 0.80*** 0.84*** 0.81*** 0.84*** Non-Fracture Injury Hospitalisation Rate Ratio Observed 1.12* 1.19*** 1.10* 1.04 0.95 1.07* 0.95 0.94* 0.80*** 0.90** Age-Standardised 1.18** 1.26*** 1.17*** 1.12* 1.02 1.15*** 1.01 1.01 0.86*** 0.97 Age-, Sex-, Comorbidity-Standardised 1.19*** 1.27*** 1.17*** 1.12* 1.02 1.15*** 1.02 1.01 0.86*** 0.97 Hip Fracture Hospitalisation Rate Ratio Observed 0.88* 0.87* 0.69*** 0.87* 0.74*** 0.75*** 0.73*** 0.85** 0.81*** 0.84*** Age-Standardised 0.96 0.94 0.75*** 0.95 0.80*** 0.81*** 0.79*** 0.92 0.88* 0.92 Age-, Sex-, Comorbidity-Standardised 0.97 0.96 0.76*** 0.96 0.81*** 0.83*** 0.80*** 0.93 0.89* 0.93 Notes: * p<0.05,** p<0.001,*** p<0.0001 a: Indirectly standardised to the corresponding internal 2012 population 2016 vol . 40 no . 4 Australian and New Zealand Journal of Public Health 345 © 2016 Public Health Association of Australia Sukumar et al. Article injury hospitalisation, and that these Table 3: Median length of stay (days) of individuals aged 65 years and older hospitalised for a fall-related injury, by hospitalisations were shorter, with higher remoteness, NSW, 2003–2012. rates of 28-day readmission and 30-day Observed median total length Wilcoxon–Mann–Whitney Robust regression mortality. of stay (days) test for total length of stay coefficient for remoteness Overall Urban Rural Trends in hospitalisations All fall-related injury 7 7 5 Z = 24.7894 p<0.0001 β=0.2220 p<0.0001 Both the observed number and the age- Fall-related fractures 13 13 10 Z = 16.5710 p<0.0001 β=0.1660 p<0.0001 standardised rate of fall-related injury Fall-related non-fracture injury 3 3 2 Z = 8.5309 p<0.0001 β=0.1113 p<0.0001 hospitalisations increased over the study Fall-related hip fractures 23 24 18 Z = 14.0391 p<0.0001 β=0.2171 p<0.0001 Note: period, which is consistent with results from a: Adjusted for age, sex, and comorbidity other countries, including the Netherlands and the US. This increase may reflect the Table 4: 28-day readmission rates, and relative risk of rural residents, of individuals aged 65 years and older change in population demographics in hospitalised for a fall-related injury, by remoteness, NSW, 2003–2012. many high income countries, with more Overall readmission Urban readmission Rural readmission Relative risk Relative risk people now living longer and a greater (observed) (observed) (observed) (observed) (adjusted) proportion of older people living beyond 1.12 (1.08–1.15) 1.12 (1.08–1.16) All fall-related 17.1% 17.0% 18.9% 85 years. Life expectancy in NSW over the injury (17.0%–17.3%) (16.8%–17.1%) (18.4%–19.5%) p<0.0001 p<0.0001 study period increased from 80.8 years in 1.14 (1.09–1.19) 1.14 (1.09–1.19) Fall-related 16.8% 16.7% 19.0% 2003 to 82.3 in 2011. New treatments and fractures (16.7%–17.0%) (16.5%–16.9%) (18.2%–19.8%) p<0.0001 p<0.0001 better management of common debilitating 1.08 (1.03–1.13) 1.09 (1.04–1.15) Fall-related non- 17.5% 17.4% 18.8% diseases are contributing to longevity, with fracture injury (17.3%–17.8%) (17.2%–17.7%) (17.9%–19.6%) p=0.0018 p=0.0002 more people living longer, including those 1.26 (1.17–1.35) 1.24 (1.16–1.33) Fall-related hip 16.6% 16.3% 20.5% with previously life-shortening chronic fractures (16.2%–16.9%) (16.0%–16.6%) (19.1%–21.8%) p<0.0001 p<0.0001 diseases. Equally, there is a societal Note: trend to promote functional mobility and a: Adjusted for age, sex, and comorbidity independence in the older population. It is possible that the resulting increased exposure injury over the past 12 months compared to Non-fracture injury hospitalisations are to risk may have contributed to the increasing respondents resident in urban areas. Trends increasing at a faster rate than fracture- rate of fall-related injury hospitalisation of increasing incidence rates internationally related hospitalisation, particularly in urban 31,32 observed in this and previous studies. would suggest that the difference in NSW is residents. This finding is similar to that of There is evidence to suggest increased largely due to unexpectedly lower rates of Watson and Mitchell, who also used NSW exposure to risk is resulting in increased injury hospitalisation due to fall-related injury in hospitalisation data – albeit unlinked – rates among older people across a range of rural settings, rather than a disproportionately from 1998–99 to 2008–09. Again, this may mechanisms such as motor vehicle crashes, high rate of fall-related injury hospitalisations reflect a frailer population, where a fall may 35-37 pedal cycle injuries and scalds. in NSW urban residents. This difference is not precipitate a significant functional decline This study found that hospitalisation explained by the differences in age, sex or and reduced capacity to remain at home rates for fall-related injury were lower for comorbidity status between rural and urban even in the absence of a fracture. Hip fracture rural residents, and that this difference populations, as evidenced by the consistently hospitalisation rates consistently decreased increased over time. This finding is not lower hospitalisation rate ratios following across the study period, matching recent data consistent with previous studies from adjustment for these factors. Given the from other countries, which also indicate a 6-8 other jurisdictions, which have reported geographical challenges in accessing hospital ‘reversal’ of the long-term upwards tendency increased hospitalisation rates for rural 41,42 care in rural NSW, where a hospital can be of hip fractures. Further research is residents for all causes, all injury and fall- hundreds of kilometres away, it is possible required to further explore the differences related injury. However, the current findings that people elect not to go to hospital in trends by injury type between rural and are consistent with results from a population- following a fall or that emergency services urban residents and to ascertain the relative based survey of NSW residents aged over and general practitioners provide care closer contributions of personal sociodemographic 65 years, which found a lower proportion of to or within the home environment. and health characteristics, service specific rural respondents reported a fall resulting in Table 5: 30-day mortality rates, and relative risk of rural residents, of individuals aged 65 years and older hospitalised for a fall-related injury, by remoteness, NSW, 2003–2012. Overall mortality Urban mortality Rural mortality Relative risk Relative risk (observed) (observed) (observed) (observed) (adjusted) All fall-related injury 4.9% (4.9%–5.0%) 4.9% (4.8%–5.0%) 5.0% (4.7%–5.4%) 1.02 (0.96–1.09) p=0.4971 1.15 (1.08–1.23) p<0.0001 Fall-related fractures 4.9% (4.8%–5.0%) 4.8% (4.7%–5.0%) 5.6% (5.1%–6.0%) 1.15 (1.06–1.25) p=0.0013 1.28 (1.18–1.40) p<0.0001 Fall-related non-fracture injury 5.0% (4.8%–5.1%) 5.0% (4.9%–5.2%) 4.3% (3.9%–4.7%) 0.86 (0.77–0.95) p=0.0048 0.95 (0.86–1.06) p=0.3631 Fall-related hip fractures 8.3% (8.1%–8.6%) 8.3% (8.0%–8.5%) 9.2% (8.2%–10.1%) 1.11 (0.99–1.23) p=0.0619 1.19 (1.07–1.32) p=0.0011 Notes: a: Adjusted for age, sex, and comorbidity 346 Australian and New Zealand Journal of Public Health 2016 vol . 40 no . 4 © 2016 Public Health Association of Australia Older People The impact of geographical location on trends for fall-related injuries characteristics such as supply of general the limited specialised orthogeriatric services analysis (i.e. urban and rural) and this may practitioners and geographical location on in rural settings. Recent research identified have masked some subtle differences in these disparate trends. that 30-day mortality following a hip fracture categories. The APDC contains the ASGS RA was significantly lower in hospitals with an categorisation of place of residence, rather Hospital utilisation orthogeriatric service in NSW. In contrast, than place of injury. While many injuries do non-fracture injury mortality was consistently happen at home, this precludes inferences A significant difference in length of stay was lower in rural residents. The reason for being made on the aetiology of rural–urban observed between urban and rural residents this trend is unknown, but may relate to disparities. following a fall-related injury hospitalisation. differences in the nature and severity of Median length of stay was shorter for rural non-fracture injury between rural and urban residents, and this was consistent across all Conclusion residents, and requires further investigation. injury types. This was an unexpected finding and is contrary to other studies that suggest This is the first long-term, large-size study Limitations rural residents stay longer in hospital because to use linked hospitalisation data in the of limited availability of transport or services While the large sample size, long time examination of geographical differences in to support them in the community. In frame, and use of linked hospitalisation fall-related injury care in older individuals. contrast, the 28-day readmission rate was and mortality data are strengths of the Over the study period, rural residents of higher for rural residents across all injury study, a number of limitations should be NSW had a lower rate of fall-related injury types and remained so after adjusting for age, acknowledged. hospitalisation and a lower annual increase sex and comorbidity. Brameld and Holman in hospitalisation rates, when compared to Presentations to the Emergency Department reported similar findings from Western urban residents. When hospitalised for a without hospital admission were not Australia and suggested it may be due to fall-related injury, rural residents had a shorter considered, so this study may under-represent difficulty in accessing ambulatory care for length of stay, but higher rates of 28-day the full impact of fall-related injury on health rural residents. This may equally apply to readmission. Thirty-day mortality was higher service utilisation. Further, common to all the NSW context, as a lower proportion of for rural residents for most injury types, with population studies using administrative older NSW residents in rural areas report the exception of non-fracture injury, where data, accurate coding is critical to the validity accessing a general practitioner and a higher mortality rates were the same. These patterns of the data extracted. A previous study in proportion report having difficulty accessing remained consistent when differences in the New Zealand found that 89.8% of injury health care when needing it compared to age, sex and comorbidity status between diagnosis codes were correctly coded to their urban counterparts. 45 urban and rural populations were taken into three characters, and an Australian study consideration. Further research is required to found that 93.8% of fall-related external cause characterise and explain this variability. Patient outcomes codes were correctly categorised to the falls ‘block’ classification. Both these studies were Mortality within 30 days was higher for undertaken in the context of the introduction rural residents for all fall-related injury Acknowledgements of what was then a relatively new ICD10AM hospitalisations. Unexpected deterioration This research was funded by the Dementia coding, a system that has now been standard following return to their more isolated place Research Collaborative Centres – Assessment for over 15 years. Data linkage was undertaken of residence has been suggested as a possible and Better Care. The authors thank the NSW using probabilistic methods, hence there is reason for the observed difference. This is Ministry of Health for providing access to the likely to be some degree of linkage errors. contrary to findings by Mitchell and Chong, APDC, the NSW Registry of Births, Deaths and However, a technical assessment conducted who report a standardised mortality ratio Marriages for providing access to mortality by the CHeReL estimates the false positive rate of 0.80 for rural fall-related injury mortality. data, and the Centre for Health Data Linkage (incorrect links) to be 3/1000, and the false Mitchell and Chong calculated this based (CHeReL) for conducting the record linkage. negative rate (missed links) to be 0.6/1000. on unlinked mortality data, and so this Socioeconomic status was not considered figure is in fact the overall rate of death in this study and may be a potential source directly attributable to falls, not only those References of bias, although there is evidence from within 30 days of hospitalisation for a fall. 1. World Health Organization. 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Sydney (AUST): CHeReL; 36. Sanford T, McCulloch CE, Callcut RA, Carroll PR, Breyer an under-recognised public-health problem. Lancet. 2012 [cited 2014 Sep 3]. Available from: http://www. BN. Bicycle trauma injuries and hospital admissions in 2008;372(9651):1765-73. cherel.org.au/quality-assurance the United States, 1998-2013. JAMA. 2015;314(9):947-9. 10. Mitchell RJ, Chong S. Comparison of injury-related 23. Australian Bureau of Statistics. 1270.0.55.005 - 37. Duke J, Wood F, Semmens J, Edgar DW, Spilsbury K, hospitalised morbidity and mortality in urban and rural Australian Statistical Geography Standard (ASGS): Willis A, et al. Rates of hospitalisations and mortality areas in Australia. Rural Remote Health. 2010;10(1):1326. Volume 5 - Remoteness Structure, July 2011 [Internet]. of older adults admitted with burn injuries in Western 11. Peel NM, Kassulke DJ, McClure RJ. Population based Canberra (AUST): ABS; 2013 [cited 2014 Sep 3]. Australian from 1983 to 2008. Australas J Ageing. study of hospitalised fall related injuries in older people. Available from: http://www.abs.gov.au/AUSSTATS/ 2012;31(2):83-9. Inj Prev. 2002;8(4):280-3. abs@.nsf/ D etailsP age/1270.0.55.005July%20 38. NSW Department of Health. New South Wales Falls 12. Anderson C, Dolansky M, Damato EG, Jones KR. 2011?OpenDocument Prevention Baseline Survey: 2009 Report. Sydney (AUST ): Predictors of serious fall injury in hospitalized patients. 24. Quan H, Sundararajan V, Halfon P, Fong A, Burnand State Government of New South Wales; 2010. Clin Nurs Res. 2015;24(3):269-83. B, Luthi JC, et al. Coding algorithms for defining 39. Chan L, Hart LG, Goodman DC. Geographic access to 13. Rochon PA, Katz JN, Morrow LA, McGlinchey-Berroth comorbidities in ICD-9-CM and ICD-10 administrative health care for rural medicare beneficiaries. J Rural R, Ahlquist MM, Sarkarati M, et al. Comorbid illness data. Med Care. 2005;43(11):1130-9. Health. 2006;22(2):140-6. is associated with survival and length of hospital 25. Preen DB, Holman CDJ, Spilsbury K, Semmens 40. Watson WL, Mitchell RJ. Coni fl cting trends in fall-related stay in patients with chronic disability: A prospective JB, Brameld KJ. Length of comorbidity lookback injury hospitalisations among older people: variations comparison of three comorbidity indices. Med Care. period affected regression model performance by injury type. Osteoporos Int. 2011;22(10):2623-31. 1996;34(11):1093-101. of administrative health data. J Clin Epidemiol. 41. Chevalley T, Guilley E, Herrmann FR, Hoffmeyer P , Rapin 14. Hindmarsh DM, Loh M, Finch CF, Hayen A, Close JCT. 2006;59(9):940-6. CH, Rizzoli R. Incidence of hip fracture over a 10-year Ee ff ct of comorbidity on relative survival following 26. Toson B, Harvey LA, Close JCT. The ICD-10 Charlson period (1991–2000): Reversal of a secular trend. 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Aust of comorbidities and postoperative complications (AUST): ABS; 2013 [cited 2014 Jul 17]. Available Health Rev. 2000;23(2):47-61. on mortality after hip fracture in elderly people: from: h ttp://w w w.abs.gov.au/aussta ts/ abs@.nsf/ 44. Zeltzer J, Mitchell RJ, Toson B, Harris IA, Ahmad L, Close Prospective Observational Cohort Study. Br Med J. Lookup/3101.0Feature+Article1Mar%202013 JCT. Orthogeriatric services associated with lower 30- 2005;331(7529):1374. 29. Australian Health Performance Authority. Hospital day mortality for older patients who undergo surgery 17. Australian Bureau of Statistics. 3218.0 - Regional Performance: Length of Stay in Public Hospitals in 2011– for hip fracture. Med J Aust. 2014;201(7):409-11. Population Growth, Australia, 2012-13 [Internet]. 12, Technical Supplement. Sydney (AUST): National 45. Davie G, Langley J, Samaranayaka A, Wetherspoon Canberra (AUST): ABS; 2013 [cited 2014 Sep 17]. Health Performance Authority; 2013. ME. Accuracy of injury coding under ICD-10-AM for Available from: http://www.abs.gov.au/AUSSTATS/ 30. Zou G. A Modified poisson regression approach to New Zealand public hospital discharges. Injury Prev. abs@.nsf/DetailsPage/3218.02012-13?OpenDocument prospective studies with binary data. Am J Epidemiol. 2008;14(5):319-23. 18. Australian Bureau of Statistics. 1301.0 - Year 2004;159(7):702-6. 46. Mackenzie K, Enraght-Mooney E, Waller G, Walker Book Australia, 2012 [Internet]. Canberra (AUST): 31. Hartholt KA, van der Velde N, Looman CN, van Lieshout S, Harrison J, McClure R. Causes of injuries resulting ABS; 2012 [cited 2014 Sep 18]. Available from: EMM, Panneman MJM, van Beeck EF, et al. Trends in in hospitalisations in Australia: Assessing coder h ttp://w w w.abs .go v.au/aussta ts/abs@.nsf/ fall-related hospital admissions in older persons in the agreement on external causes. Injury Prev. 2009;15:188- Lookup/by%20Subject/1301.0~2012~Main%20 Netherlands. Arch Intern Med. 2010;170(10):905-11. 96. Features~Geographic%20distribution%20of%20 the%20population~49 348 Australian and New Zealand Journal of Public Health 2016 vol . 40 no . 4 © 2016 Public Health Association of Australia http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Australian and New Zealand Journal of Public Health Wiley

The impact of geographical location on trends in hospitalisation rates and outcomes for fall‐related injuries in older people

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Wiley
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© 2016 Public Health Association of Australia
ISSN
1326-0200
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1753-6405
DOI
10.1111/1753-6405.12524
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27197714
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Abstract

mortality and morbidity, both globally Objective: This population-based study investigates the influence of geographical location on Fand in Australia. It is the 15th-highest hospital admissions, utilisation and outcomes for fall-related injury in older adults, adjusting specific cause of death of people aged over 70 for age, sex and comorbidities. worldwide, responsible for an estimated 1.41% of deaths in 2012, and the 9th-highest specific Methods: A linked dataset of all admissions of NSW residents aged 65 and older, hospitalised cause of Disability-Adjusted Life Years (DALYs) at least once for a fall-related injury between 2003 and 2012, was used to estimate rates of in this group. In Australia, there were 1,920 hospitalisations, total lengths-of-stay, 28-day readmissions, and 30-day mortalities. These were deaths directly due to falls in 2013, causing standardised for age, sex, comorbidity, and remoteness. 6,269 Years of Potential Life Lost (YLLs). Results: Compared to urban residents, rural residents were hospitalised less (p<0.0001) and Most falls are not fatal. In Australia, one hospitalisation rates increased at a lower rate (0.8% vs 2.6% per year) from 2003 to 2012. Rural in every 10 days spent in hospital by a residents had a shorter median total length of stay (5 vs 7 days, p<0.0001), a higher 28-day person aged 65 years and older is directly readmission rate (18.9% vs 17.0%, p<0.0001) and higher 30-day mortality (5.0% vs 4.9%, attributable to an injurious fall. There is also p=0.0046). evidence that the rate of fall-related injury Conclusions: Over the study period, rural residents of NSW had lower rates of fall-related hospitalisation continues to increase over injury hospitalisation and a lower annual increase in hospitalisation rates compared to urban time, with a 3.8% per year increase from 1998 residents. When hospitalised, rural residents had a shorter length-of-stay, but higher rates of to 2012 in New South Wales (NSW). readmission and mortality. These differences existed following standardisation. A number of factors influence the provision Implications: This study highlights the need for further research to characterise and explain of health care and the ability to provide this variability. equitable access to care, including Key words: geography, aged, accidental falls, data linkage, hospitalisation geographical location. Evidence to date highlights differences in health care access, urban centres in coastal regions, particularly injury hospitalisations of older people, and to utilisation and quality between rural and Sydney. Population density ranges from determine whether any observed differences urban populations. People in rural areas 6,7 more than 14,300 persons per km to fewer remain after adjustment for age, sex and the experience higher hospitalisation rates, 2,17 than 1/km placing considerable demands presence of comorbidities. higher rates of readmission, and higher rates 9,10 on the provision of accessible, equitable of mortality than residents in urban areas. health care services. The distribution is Other factors known to affect health use and Methods similar to the state populations of Victoria, outcomes include age, sex and any present 11-16 South Australia and Western Australia, and is comorbidities. Study population and data sources representative of Australia as a whole. The geography and population distribution The study population comprised 185,670 This population-based study investigated of Australia presents a particular challenge to NSW residents aged 65 years and older, with the influence of geographical location on the aspiration of health care parity. NSW has at least one admission to a public or private hospitalisation rates, utilisation (total length a population of more than 7.3 million people, hospital in NSW for an injury resulting of stay and 28-day readmission), and patient of whom 14.9% are aged 65 and older. from a fall between 1 January 2003 and 31 outcomes (30-day mortality) for fall-related Most of this population is concentrated in December 2012. 1. Falls and Injury Prevention Group, Neuroscience Research Australia, New South Wales 2. Prince of Wales Clinical School, UNSW Australia, New South Wales 3. Australian Institute of Health Innovation, Macquarie University, New South Wales Correspondence to: Professor Jacqueline Close, Falls and Injury Prevention Group, Neuroscience Research Australia, Barker Street, Randwick, NSW 2031; e-mail: j.close@neura.edu.au Submitted: August 2015; Revision requested: October 2015; Accepted: December 2015 The authors have stated they have no conflict of interest. Aust NZ J Public Health. 2016; 40:342-8; doi: 10.1111/1753-6405.12524 342 Australian and New Zealand Journal of Public Health 2016 vol . 40 no . 4 © 2016 Public Health Association of Australia Older People The impact of geographical location on trends for fall-related injuries Two data sources were linked for use in Regional Australia, Remote Australia and and included in the total LOS calculation. 6,10 this study: the NSW Admitted Patient Data Very Remote Australia). As of 2013, 93.5% Leave days were not included in the total. Collection (APDC) and the NSW Registry of of the state population live in urban areas, Admission and discharge on same day was Births, Deaths and Marriages (RBDM) mortality with an average density of 75.85 people/km . considered a one-day stay. A truncation was data. The APDC is a register of all ‘episodes of The other 6.5% live in rural areas, with 0.68 applied for total length of stay, at the level of 2,17 care’ from all public and private hospitals in people/km. In 2003, these proportions were three standard deviations above the mean, to NSW. An ‘episode of care’ ends upon a patient’s 92.7% and 7.3%, respectively, suggesting a net avoid extreme outliers due to data errors or 17 29 death, discharge, transfer or change in type of migration towards urban centres. unrepresentative care practices. As length care (from acute to subacute or rehabilitation). of stay is generally positively skewed with a Comorbidities were identified using the Thus, for a single injury event, a person may long tail, the data was log-transformed prior Charlson Comorbidity Index and assigned have multiple ‘episodes of care’ recorded. Data to analysis. A Wilcoxon-Mann-Whitney test to each individual, based on the presence in the APDC is coded using the International was used to compare distributions of total or absence of comorbidity recorded in any Statistical Classification of Diseases and Related length of stay of the two groups. A linear of the first 40 diagnosis fields using the Health Problems, Tenth Revision, Australian regression model was fitted to total length ICD-10 coding algorithm developed by Quan Modification (ICD-10-AM). The RBDM 24 of stay using a robust M-estimator, using age and Sundararajan. A one-year look-back contains records of all deaths of NSW residents, group, sex, all Charlson comorbidity groups period was used, consistent with Preen and certified by a coroner or medical practitioner. 25 and remoteness. The resultant regression Holman. Binary variables for each Charlson Date and fact of death were obtained from the coefficient for remoteness was reported. comorbidity group were used instead of the RBDM. aggregated weighted score, as these provide A subsequent hospital admission, for any better model fit. cause, beginning within 28 days of discharge Data linkage was defined as a ‘28-day readmission’. The Centre for Health Record Linkage (CHeReL) Data management and analysis Hospital stays ending with in-hospital death linked records from the APDC and RBDM. were excluded from readmission analysis. Data was analysed using SAS Enterprise Guide Choicemaker was used to probabilistically 27 Thirty-day mortality was defined as death 6.1. P values less than 0.05 were considered match identifying information (full name, from any cause within 30 days of admission statistically significant. date of birth, sex and address), followed from the index fall-related hospitalisation. Demographic characteristics were described, by a manual review of uncertain matches Relative risks were calculated for 28-day using chi-square tests to analyse differences when necessary. A unique person project readmission and 30-day mortality, adjusted in the two subsets. Comorbidities were number (PPN) for each individual identified for age group, sex, Charlson comorbidity grouped into three categories, based on in the linkage process was created, allowing groups and remoteness. Modified Poisson number of comorbidities present within one for accurate determination of admission and regression models with robust error variances year of hospitalisation. outcome rates. were used to calculate confidence intervals Trends in the number and rate of 30 for the adjusted relative risks. Identification of fall-related injury, hospitalisations over time were investigated Ethics approval for this study was obtained remoteness and patient comorbidities using a negative binomial regression on the from the NSW Population and Health Services annual count of admissions. Hospitalisation A fall-related injury hospitalisation was Research Ethics Committee (HREC/13/CIPHS/49). rates were calculated using the age-specific defined as such if the principal diagnosis for number of admissions and the population the initial episode of care of a hospitalisation of the corresponding age group of that Results was an injury (ICD-10-AM codes S00-T75 or year. These were directly standardised to T79) with an associated primary external Demographic characteristics the 2001 Australian Bureau of Statistics cause code of a fall (ICD-10-AM codes 28 There were 256,536 fall-related injury Standard Population. Trends in rates over W00-W19). The principal diagnosis was hospitalisations of people aged 65 and older time were investigated using a negative defined as the diagnosis primarily responsible during the 10-year study period. Of these, binomial regression on the standardised for the hospitalisation episode. 7.4% (n=18,862) of hospitalisations were rates. Hospitalisations were also indirectly The Australian Statistical Geographical of rural residents, with the majority (92.6%, standardised to the equivalent hospitalised Standard Remoteness Area (ASGS RA) is a n=237,674) of people resident in urban areas. population for 2012 to generate both age- five-category classification using defined More than two-thirds of all hospitalised standardised and age-, sex- and comorbidity- index scores of distance to service centres of individuals were female, from both urban standardised hospitalisation rate ratios various sizes (settlements with at least 1,000, and rural areas. There was a clear age-related between rural and urban residents. 5,000, 18,000, 48,000 and 250,000 residents, trend in number of hospitalisations, with Total length of stay was defined as the respectively). The score is initially calculated older age associated with a greater number number of days from date of admission in the on a one-kilometre grid, and then the mean of hospitalisations. Just under half (49.4%) the index ‘episode of care’ until final discharge value for each Census Collection District is hospitalised patients had no comorbidities, from hospital. Hospitalisations that consisted aggregated to form the Remoteness Areas. with a further 40.7% presenting with one of multiple contiguous episodes of care for an For ease of reporting and comparability, the or two comorbidities. Dementia (19.9%), injury event, where the discharge code was five categories were collapsed into two: urban congestive heart failure (10.2%), diabetes a transfer to another facility or a type change (from Major Cities of Australia and Inner complications (8.9%), pulmonary disease transfer, were considered as one hospital stay Regional Australia) and rural (from Outer (8.7%) and cerebrovascular disease (8.1%) 2016 vol . 40 no . 4 Australian and New Zealand Journal of Public Health 343 © 2016 Public Health Association of Australia Sukumar et al. Article were the most common comorbidities increased for rural residents by 2.1% per year for age, this difference was less pronounced. recorded. Compared to people living in urban (p=0.0002), which was significantly lower Standardising for age, sex, and comorbidity areas, a higher proportion of rural residents than the 5.8% per year increase for urban further reduced this disparity; however, hospitalised for a fall were male (p<0.0001), residents (p<0.0001). Rates of hip fracture significant differences remained from 2005 aged 65–74 years (p<0.0001), and with fewer hospitalisations were not significantly onwards. recorded comorbidities (p<0.0001). different between urban and rural residents. Rural HRRs for fall-related fractures were For both urban and rural residents, fractures Observed hospitalisation rate ratios (HRRs) consistently lower than urban, and this were the most common injury type, for all fall-related injury in rural residents remained true when standardising for age, comprising 59.8% and 53.9% of fall-related were consistently lower than those in urban sex, and comorbidity. Conversely, non- injury hospitalisations, respectively. However, areas (Table 2). However, when standardised fracture injury of rural residents HRRs were the proportion of rural residents hospitalised Table 1: Demographic characteristics of patients aged 65 years and older hospitalised for an injurious fall, by with a fracture was lower than urban remoteness, linked hospitalisation and mortality records NSW, 2003–2012. residents (p<0.0001). Hip fracture was the Characteristic Urban Rural Statistic most common fracture type, and injury to the head and neck the most common non- χ (df ), p value N % N % fracture injury (Table 1). Sex 63.60 (1), p<0.0001 Male 72,051 30.3 6,242 33.1 Hospitalisations Female 165,623 69.7 12,620 66.9 The number of fall-related injury Age group 415.57 (4), p<0.0001 hospitalisations increased by 5.6% per year (95%CI 5.2–5.9, p<0.0001) from 19,749 in 65–69 years 20,381 8.6 2,160 11.5 2003 to 32,006 in 2012. While the number 70–74 years 26,009 10.9 2,470 13.1 of hospitalisations increased for both urban 75–79 years 38,712 16.3 3,352 17.8 and rural residents, hospitalisations for rural 80–84 years 54,976 23.1 4,257 22.6 residents increased at a significantly lower 85+ years 97,596 41.1 6,623 35.1 rate than that of urban residents (4.1%; 95%CI Comorbidities 3.4–4.8, p<0.0001 and 5.7%; 95%CI 5.3–6.0, p<0.0001, respectively, per year). Dementia 48,234 20.3 3,057 16.21 182.48 (1), p<0.0001 Overall, the age-standardised statewide Congestive heart failure 24,275 10.2 1,930 10.2 0.01 (1), p = 0.9351 hospitalisation rate for fall-related injury Diabetes complications 21,500 9.1 1,396 7.4 58.17 (1), p<0.0001 increased from 2,209 per 100,000 population Pulmonary disease 20,353 8.6 1,880 10.0 43.50 (1), p<0.0001 in 2003 to 2,755 per 100,000 population in Cerebral vascular disease 19,379 8.2 1,347 7.1 24.11 (1), p<0.0001 2012, an increase of 2.5% per year (95%CI Number of comorbidities 150.10 (2), p<0.0001 2.0–2.9, p<0.0001). No significant trend 0 116,614 49.1 10,102 53.6 was identified for fractures, while non- 1-2 97,221 40.9 7,155 37.9 fracture injury increased through the study 3+ 23,839 10.0 1,605 8.5 period by 5.5% annually (95%CI 4.6–6.4%, Injury type p<0.0001), from 749 per 100,000 population Fractures 142,100 59.8 10,169 53.9 250.03 (1), p<0.0001 to 1,191 per 100,000 population. Hip fracture hospitalisation rates decreased by 1.3% per – head and neck 5,692 2.4 315 1.7 40.15 (1), p<0.0001 year (95%CI 0.4–2.2%, p=0.005) from 539 – arm 37,200 15.7 2,498 13.2 77.48 (1), p<0.0001 per 100,000 population to 496 per 100,000 – trunk 30,621 12.9 2,094 11.1 49.87 (1), p<0.0001 population. – hip 50,514 21.3 3,767 20.0 17.22 (1), p<0.0001 Age-standardised hospitalisation rates – leg 18,030 7.6 1,484 7.9 1.97 (1), p=0.1602 for all fall-related injury, fractures, non- – multiple/unspecified 43 0.0 11 0.1 13.44 (1), p=0.0002 fractures and hip fractures by remoteness Nonfracture injury 94,159 39.6 8,554 45.4 239.29 (1), p<0.0001 category are shown in Figure 1. Rates of all fall-related injury hospitalisations for rural – Traumatic brain injury 9,516 4.0 603 3.2 30.03 (1), p<0.0001 residents increased at a significantly lower b – head and neck 34,242 14.4 3,001 15.9 31.82 (1), p<0.0001 rate (0.8% per year) than those of the urban – arm 14,087 5.9 1,355 7.2 48.79 (1), p<0.0001 population (2.6% per year) over the study – trunk 12,207 5.1 1,286 6.8 99.21 (1), p<0.0001 period. Hospitalisation rates for fractures – leg 22,809 9.6 2,151 11.4 64.98 (1), p<0.0001 were consistently lower for rural residents. – multiple/unspecified r egions 1,298 0.6 158 0.8 26.32 (1), p<0.0001 No significant trend over time was identified for rural residents (p=0.5), in comparison Unspecified region and type 1,415 0.6 139 0.7 5.82 (1), p=0.0159 to an observed increase of 0.6% per year in Notes: a: Statistic calculated specifically for each injury subtype urban residents (p<0.04). Correspondingly, b: Excludes Traumatic Brain Injury (TBI) rates of non-fractures hospitalisations 344 Australian and New Zealand Journal of Public Health 2016 vol . 40 no . 4 © 2016 Public Health Association of Australia Older People The impact of geographical location on trends for fall-related injuries were readmitted within 28 days (Table 4). When adjusted for age group, sex, and comorbidities, rural residents were readmitted more than urban residents (ARR 1.12; 95%CI 1.08–1.16, p<0.0001). Comparable results were found for fracture, non-fracture injury, and hip fracture. 30-day mortality The 30-day mortality rate for all fall-related injury over the study period was 4.9% (Table 5). Overall, there was no difference in 30-day mortality rates between fall-related fracture and non-fracture injuries (4.9% vs 5.0%, respectively); however, 30-day mortality for hip fracture was significantly higher (8.3%). After adjustment for age, sex and Figure 1: Fall-related injury, fracture, non-fracture and hip fracture hospitalisations of individuals aged 65 years comorbidity, rural residents were 15% more and older, age-standardised, by remoteness, NSW, 2003–2012. likely (ARR 1.15; 95%CI 1.08–1.23, p<0.0001) to die within 30 days of hospitalisation higher than the urban HRRs from 2003 to was seven days (Table 3). Rural residents for a fall-related injury than their urban 2005, with an overall observed reduction had a shorter median length of stay than counterparts. This pattern varied by injury over the 10 years. This result remained after urban residents (5 vs 7 days, p<0.0001). type, with rural residents experiencing age, sex, and comorbidity standardisation. When adjusted for age group, sex and higher 30-day mortality rates for all fractures Although the observed HRR for hip fractures comorbidities, remoteness remained a (ARR 1.28; 95%CI 1.18–1.40, p<0.0001) was consistently lower for rural residents, significant factor (p <0.0001). This pattern was and hip fractures (ARR 1.19; 95%CI 1.07– standardisation reduced this difference over consistent for fractures, non-fracture injuries, 1.32, p<0.0001), but no difference for non- the 10 years of the study. and hip fractures. fracture injuries (p=0.3631). Total length of stay 28-day readmission Discussion Median length of stay for all fall-related Overall, 17.1% of patients discharged This study has demonstrated that rural injury hospitalisations over the study period following a fall-related injury hospitalisation residents had lower rates of fall-related Table 2: Observed and standardised hospitalisation rate ratios for rural residents, compared to urban residents, aged 65 and older admitted for a fall-related injury, by remoteness, NSW, 2003–2012. 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 All Injury Hospitalisation Rate Ratio Observed 0.94* 0.92** 0.86*** 0.88*** 0.84*** 0.90*** 0.82*** 0.85*** 0.77*** 0.83*** Age-Standardised 0.99 0.98 0.92** 0.94* 0.89*** 0.96* 0.88*** 0.90*** 0.82*** 0.89*** Age-, Sex-, Comorbidity-Standardised 1.00 0.99 0.93* 0.95* 0.90*** 0.97 0.89*** 0.91*** 0.83*** 0.90*** Fracture Hospitalisation Rate Ratio Observed 0.84*** 0.79*** 0.73*** 0.78*** 0.76*** 0.78*** 0.74*** 0.77*** 0.75*** 0.78*** Age-Standardised 0.88*** 0.84*** 0.77*** 0.82*** 0.81*** 0.83*** 0.78*** 0.83*** 0.80*** 0.83*** Age-, Sex-, Comorbidity-Standardised 0.90** 0.85*** 0.79*** 0.84*** 0.82*** 0.84*** 0.80*** 0.84*** 0.81*** 0.84*** Non-Fracture Injury Hospitalisation Rate Ratio Observed 1.12* 1.19*** 1.10* 1.04 0.95 1.07* 0.95 0.94* 0.80*** 0.90** Age-Standardised 1.18** 1.26*** 1.17*** 1.12* 1.02 1.15*** 1.01 1.01 0.86*** 0.97 Age-, Sex-, Comorbidity-Standardised 1.19*** 1.27*** 1.17*** 1.12* 1.02 1.15*** 1.02 1.01 0.86*** 0.97 Hip Fracture Hospitalisation Rate Ratio Observed 0.88* 0.87* 0.69*** 0.87* 0.74*** 0.75*** 0.73*** 0.85** 0.81*** 0.84*** Age-Standardised 0.96 0.94 0.75*** 0.95 0.80*** 0.81*** 0.79*** 0.92 0.88* 0.92 Age-, Sex-, Comorbidity-Standardised 0.97 0.96 0.76*** 0.96 0.81*** 0.83*** 0.80*** 0.93 0.89* 0.93 Notes: * p<0.05,** p<0.001,*** p<0.0001 a: Indirectly standardised to the corresponding internal 2012 population 2016 vol . 40 no . 4 Australian and New Zealand Journal of Public Health 345 © 2016 Public Health Association of Australia Sukumar et al. Article injury hospitalisation, and that these Table 3: Median length of stay (days) of individuals aged 65 years and older hospitalised for a fall-related injury, by hospitalisations were shorter, with higher remoteness, NSW, 2003–2012. rates of 28-day readmission and 30-day Observed median total length Wilcoxon–Mann–Whitney Robust regression mortality. of stay (days) test for total length of stay coefficient for remoteness Overall Urban Rural Trends in hospitalisations All fall-related injury 7 7 5 Z = 24.7894 p<0.0001 β=0.2220 p<0.0001 Both the observed number and the age- Fall-related fractures 13 13 10 Z = 16.5710 p<0.0001 β=0.1660 p<0.0001 standardised rate of fall-related injury Fall-related non-fracture injury 3 3 2 Z = 8.5309 p<0.0001 β=0.1113 p<0.0001 hospitalisations increased over the study Fall-related hip fractures 23 24 18 Z = 14.0391 p<0.0001 β=0.2171 p<0.0001 Note: period, which is consistent with results from a: Adjusted for age, sex, and comorbidity other countries, including the Netherlands and the US. This increase may reflect the Table 4: 28-day readmission rates, and relative risk of rural residents, of individuals aged 65 years and older change in population demographics in hospitalised for a fall-related injury, by remoteness, NSW, 2003–2012. many high income countries, with more Overall readmission Urban readmission Rural readmission Relative risk Relative risk people now living longer and a greater (observed) (observed) (observed) (observed) (adjusted) proportion of older people living beyond 1.12 (1.08–1.15) 1.12 (1.08–1.16) All fall-related 17.1% 17.0% 18.9% 85 years. Life expectancy in NSW over the injury (17.0%–17.3%) (16.8%–17.1%) (18.4%–19.5%) p<0.0001 p<0.0001 study period increased from 80.8 years in 1.14 (1.09–1.19) 1.14 (1.09–1.19) Fall-related 16.8% 16.7% 19.0% 2003 to 82.3 in 2011. New treatments and fractures (16.7%–17.0%) (16.5%–16.9%) (18.2%–19.8%) p<0.0001 p<0.0001 better management of common debilitating 1.08 (1.03–1.13) 1.09 (1.04–1.15) Fall-related non- 17.5% 17.4% 18.8% diseases are contributing to longevity, with fracture injury (17.3%–17.8%) (17.2%–17.7%) (17.9%–19.6%) p=0.0018 p=0.0002 more people living longer, including those 1.26 (1.17–1.35) 1.24 (1.16–1.33) Fall-related hip 16.6% 16.3% 20.5% with previously life-shortening chronic fractures (16.2%–16.9%) (16.0%–16.6%) (19.1%–21.8%) p<0.0001 p<0.0001 diseases. Equally, there is a societal Note: trend to promote functional mobility and a: Adjusted for age, sex, and comorbidity independence in the older population. It is possible that the resulting increased exposure injury over the past 12 months compared to Non-fracture injury hospitalisations are to risk may have contributed to the increasing respondents resident in urban areas. Trends increasing at a faster rate than fracture- rate of fall-related injury hospitalisation of increasing incidence rates internationally related hospitalisation, particularly in urban 31,32 observed in this and previous studies. would suggest that the difference in NSW is residents. This finding is similar to that of There is evidence to suggest increased largely due to unexpectedly lower rates of Watson and Mitchell, who also used NSW exposure to risk is resulting in increased injury hospitalisation due to fall-related injury in hospitalisation data – albeit unlinked – rates among older people across a range of rural settings, rather than a disproportionately from 1998–99 to 2008–09. Again, this may mechanisms such as motor vehicle crashes, high rate of fall-related injury hospitalisations reflect a frailer population, where a fall may 35-37 pedal cycle injuries and scalds. in NSW urban residents. This difference is not precipitate a significant functional decline This study found that hospitalisation explained by the differences in age, sex or and reduced capacity to remain at home rates for fall-related injury were lower for comorbidity status between rural and urban even in the absence of a fracture. Hip fracture rural residents, and that this difference populations, as evidenced by the consistently hospitalisation rates consistently decreased increased over time. This finding is not lower hospitalisation rate ratios following across the study period, matching recent data consistent with previous studies from adjustment for these factors. Given the from other countries, which also indicate a 6-8 other jurisdictions, which have reported geographical challenges in accessing hospital ‘reversal’ of the long-term upwards tendency increased hospitalisation rates for rural 41,42 care in rural NSW, where a hospital can be of hip fractures. Further research is residents for all causes, all injury and fall- hundreds of kilometres away, it is possible required to further explore the differences related injury. However, the current findings that people elect not to go to hospital in trends by injury type between rural and are consistent with results from a population- following a fall or that emergency services urban residents and to ascertain the relative based survey of NSW residents aged over and general practitioners provide care closer contributions of personal sociodemographic 65 years, which found a lower proportion of to or within the home environment. and health characteristics, service specific rural respondents reported a fall resulting in Table 5: 30-day mortality rates, and relative risk of rural residents, of individuals aged 65 years and older hospitalised for a fall-related injury, by remoteness, NSW, 2003–2012. Overall mortality Urban mortality Rural mortality Relative risk Relative risk (observed) (observed) (observed) (observed) (adjusted) All fall-related injury 4.9% (4.9%–5.0%) 4.9% (4.8%–5.0%) 5.0% (4.7%–5.4%) 1.02 (0.96–1.09) p=0.4971 1.15 (1.08–1.23) p<0.0001 Fall-related fractures 4.9% (4.8%–5.0%) 4.8% (4.7%–5.0%) 5.6% (5.1%–6.0%) 1.15 (1.06–1.25) p=0.0013 1.28 (1.18–1.40) p<0.0001 Fall-related non-fracture injury 5.0% (4.8%–5.1%) 5.0% (4.9%–5.2%) 4.3% (3.9%–4.7%) 0.86 (0.77–0.95) p=0.0048 0.95 (0.86–1.06) p=0.3631 Fall-related hip fractures 8.3% (8.1%–8.6%) 8.3% (8.0%–8.5%) 9.2% (8.2%–10.1%) 1.11 (0.99–1.23) p=0.0619 1.19 (1.07–1.32) p=0.0011 Notes: a: Adjusted for age, sex, and comorbidity 346 Australian and New Zealand Journal of Public Health 2016 vol . 40 no . 4 © 2016 Public Health Association of Australia Older People The impact of geographical location on trends for fall-related injuries characteristics such as supply of general the limited specialised orthogeriatric services analysis (i.e. urban and rural) and this may practitioners and geographical location on in rural settings. Recent research identified have masked some subtle differences in these disparate trends. that 30-day mortality following a hip fracture categories. The APDC contains the ASGS RA was significantly lower in hospitals with an categorisation of place of residence, rather Hospital utilisation orthogeriatric service in NSW. In contrast, than place of injury. While many injuries do non-fracture injury mortality was consistently happen at home, this precludes inferences A significant difference in length of stay was lower in rural residents. The reason for being made on the aetiology of rural–urban observed between urban and rural residents this trend is unknown, but may relate to disparities. following a fall-related injury hospitalisation. differences in the nature and severity of Median length of stay was shorter for rural non-fracture injury between rural and urban residents, and this was consistent across all Conclusion residents, and requires further investigation. injury types. This was an unexpected finding and is contrary to other studies that suggest This is the first long-term, large-size study Limitations rural residents stay longer in hospital because to use linked hospitalisation data in the of limited availability of transport or services While the large sample size, long time examination of geographical differences in to support them in the community. In frame, and use of linked hospitalisation fall-related injury care in older individuals. contrast, the 28-day readmission rate was and mortality data are strengths of the Over the study period, rural residents of higher for rural residents across all injury study, a number of limitations should be NSW had a lower rate of fall-related injury types and remained so after adjusting for age, acknowledged. hospitalisation and a lower annual increase sex and comorbidity. Brameld and Holman in hospitalisation rates, when compared to Presentations to the Emergency Department reported similar findings from Western urban residents. When hospitalised for a without hospital admission were not Australia and suggested it may be due to fall-related injury, rural residents had a shorter considered, so this study may under-represent difficulty in accessing ambulatory care for length of stay, but higher rates of 28-day the full impact of fall-related injury on health rural residents. This may equally apply to readmission. Thirty-day mortality was higher service utilisation. Further, common to all the NSW context, as a lower proportion of for rural residents for most injury types, with population studies using administrative older NSW residents in rural areas report the exception of non-fracture injury, where data, accurate coding is critical to the validity accessing a general practitioner and a higher mortality rates were the same. These patterns of the data extracted. A previous study in proportion report having difficulty accessing remained consistent when differences in the New Zealand found that 89.8% of injury health care when needing it compared to age, sex and comorbidity status between diagnosis codes were correctly coded to their urban counterparts. 45 urban and rural populations were taken into three characters, and an Australian study consideration. Further research is required to found that 93.8% of fall-related external cause characterise and explain this variability. Patient outcomes codes were correctly categorised to the falls ‘block’ classification. Both these studies were Mortality within 30 days was higher for undertaken in the context of the introduction rural residents for all fall-related injury Acknowledgements of what was then a relatively new ICD10AM hospitalisations. Unexpected deterioration This research was funded by the Dementia coding, a system that has now been standard following return to their more isolated place Research Collaborative Centres – Assessment for over 15 years. Data linkage was undertaken of residence has been suggested as a possible and Better Care. The authors thank the NSW using probabilistic methods, hence there is reason for the observed difference. 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Arch Intern Med. 2010;170(10):905-11. 96. Features~Geographic%20distribution%20of%20 the%20population~49 348 Australian and New Zealand Journal of Public Health 2016 vol . 40 no . 4 © 2016 Public Health Association of Australia

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