Comparative Risk of Harm Associated with Zopiclone or Trazodone Use in Nursing Home Residents: a Retrospective Cohort Study in Alberta, Canada

Jennifer A. Watt, MD, PhD1,2,3,4, Susan E. Bronskill, PhD3,4, Meng Lin5, Erik Youngson, MMath5, Joanne Ho, MD, MSc6,7, Brenda Hemmelgarn, MD, PhD8, Sharon E. Straus, MD, MSc1,2,4, Andrea Gruneir, PhD9

1Knowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael’s Hospital-Unity Health Toronto, Toronto, ON
2Division of Geriatric Medicine, Department of Medicine, University of Toronto, Toronto, ON
3ICES, Toronto, ON
4Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON
5Data and Research Services, Alberta SPOR Support Unit and Provincial Research Data Services, Alberta Health Services, Edmonton, AB
6Division of Geriatric Medicine, Department of Medicine, McMaster University, Kitchener, ON
7Schlegel Research Institute for Aging, University of Waterloo, Waterloo, ON
8Faculty of Medicine and Dentistry, University of Alberta, WC Mackenzie Health Sciences Centre, Edmonton, AB
9Department of Family Medicine, University of Alberta, Edmonton, AB

DOI: https://doi.org/10.5770/cgj.26.575

ABSTRACT

Background

There is growing evidence of harm associated with trazodone and nonbenzodiazepine sedative hypnotics (e.g., zopiclone); however, their comparative risk of harm is unknown.

Methods

We conducted a retrospective cohort study with linked health administrative data, which enrolled older (≥66 years old) nursing home residents living in Alberta, Canada, between December 1, 2009, and December 31, 2018; the last follow-up date was June 30, 2019. We compared the rate of injurious falls and major osteoporotic fractures (primary outcome) and all-cause mortality (secondary outcome) within 180 days of first prescription of zopiclone or trazodone with cause-specific hazard models and inverse probability of treatment weights to control for confounding; primary analysis was intention-to-treat and secondary analysis was per-protocol (i.e., residents censored if dispensed the other exposure drug).

Results

Our cohort included 1,403 residents newly dispensed trazodone and 1,599 residents newly dispensed zopiclone. At cohort entry, the mean resident age was 85.7 (standard deviation [SD] 7.4), 61.6% were female, and 81.2% had dementia. New zopiclone use was associated with similar rates of injurious falls and major osteoporotic fractures (intention-to-treat-weighted hazard ratio 1.15, 95% confidence interval [CI] 0.90–1.48; per-protocol-weighted hazard ratio 0.85, 95% CI 0.60–1.21) and all-cause mortality (intention-to-treat-weighted hazard ratio 0.96, 95% CI 0.79–1.16; per-protocol-weighted hazard ratio 0.90, 95% CI 0.66–1.23) compared to trazodone.

Conclusions

Zopiclone was associated with a similar rate of injurious falls, major osteoporotic fractures, and all-cause mortality compared to trazodone—suggesting one medication should not be used in lieu of the other. Appropriate prescribing initiatives should also target zopiclone and trazodone.

Key words: adverse drug event, trazodone, zopiclone, cohort studies

INTRODUCTION

Older adults living in nursing homes commonly experience neuropsychiatric symptoms such as sleep disturbances and agitation.(1) Pharmacologic interventions such as antipsychotics, antidepressants, benzodiazepines, and nonbenzodiazepines sedative hypnotics (i.e., z-drugs) are prescribed to treat these symptoms.(2) The pooled prevalence of chemical (e.g., antipsychotics, benzodiazepines) and physical (e.g., mittens, lap belt) restraint use in a systematic review of nursing home prevalence estimates was 32% and 33%, respectively.(3) Efficacious alternatives to chemical and physical restraints include massage therapy, music therapy, and multidisciplinary care plans; however, health-care provider knowledge of these interventions and resource limitations are perceived as barriers to their implementation.(46)

Time trend analyses conducted before the COVID-19 pandemic in Canada, the United States, and the United Kingdom suggested that antipsychotic and benzodiazepine use was stabilizing or decreasing, but use of alternative psychotropic medications such as antidepressants and anticonvulsants was increasing.(79) For example, 21.3% of older adults living in nursing homes in Ontario, Canada, were dispensed trazodone in 2013, compared to only 7.7% in 2002, which may have been in response to a growing body of literature describing harms associated with antipsychotic and benzodiazepine use, and initiatives targeting their appropriate prescribing.(10) From 2011 to 2014, 39.8% of older adults living in nursing homes in Oslo municipality, Norway, were prescribed nonbenzodiazepine sedative hypnotics (i.e., zopiclone or zolpidem); other studies have shown that nonbenzodiazepine sedative hypnotic use in people with dementia varies considerably by country.(2,11,12) Unlike benzodiazepines and antipsychotics, quality improvement work aimed at reducing potentially inappropriate prescribing of these alternative psychotropic medications has been limited.(1315) This is important because there is growing evidence describing the risk of falls and fractures in older adults dispensed trazodone and nonbenzodiazepine sedative hypnotics (e.g., zopiclone).(1618) Further, trazodone is associated with a similar risk of harm from injurious falls or fractures as benzodiazepines and atypical antipsychotics.(16,17)

Despite how commonly trazodone and zopiclone are prescribed in nursing homes, their comparative risk of harm in nursing home residents is unknown.(2,10) Our objective was to describe the risk of harm from injurious falls, fractures, and death associated with new use of zopiclone compared to new use of trazodone among older adults living in nursing homes in Alberta, Canada.

METHODS

This manuscript is reported in accordance with the STROBE (strengthening the reporting of observational studies in epidemiology) and RECORD-PE (reporting of studies conducted using observational routinely collected health data—pharmacoepidemiology) statements.(19, 20)

Setting and Data Sources

We created our cohort using linked health administrative databases in Alberta, Canada. Alberta has a largely publicly funded health-care system, in which individuals aged 65 years or older can access publicly funded nursing homes, when necessary, and receive universal coverage for physician services and most prescription medications. Between April 1, 2016, and March 31, 2017, there were 20,073 residents living in nursing homes in Alberta, and each resident received 10 different medications in the seven days before their Resident Assessment Instrument—Minimum Data Set, version 2.0 (RAI-MDS 2.0) assessment.(21) We linked patient-level data from these databases using each patient’s health insurance program number: National Ambulatory Care Reporting System, Provincial Registry, Discharge Abstract Database, Practitioner Claims Database, Pharmacy Information Network, and the Alberta Continuing Care Information System (see Appendix A for database details). These databases are accurate and reliable.(2224)

Study Design

In this retrospective cohort study, the date of a new prescription for oral trazodone or zopiclone between December 1, 2009, and December 31, 2018, was our index date. We included nursing home residents, aged 66 years or older, who received a full RAI-MDS 2.0 assessment within 45 days before our index date. The RAI-MDS 2.0 is a validated assessment tool that records information about residents’ health status (e.g., independence in activities of daily living and cognitive impairment severity).(25) Choosing assessments within 45 days of the index date ensured a close temporal association between drug exposure and residents’ current health status. Our observation window was 180 days, which balanced the time required for event accrual against a need to minimize residual confounding over time. The maximum follow-up date was June 30, 2019. We excluded residents from our cohort if they: 1) did not have a complete Resident Assessment Instrument—Minimum Data Set, version 2.0 assessment within 45 days prior to cohort entry; 2) had an invalid identifying number or died on or before the index date; 3) had no drug claims in the year prior to cohort entry; 4) were dispensed trazodone or zopiclone in the 180 days prior to cohort entry; 5) were newly dispensed both trazodone and zopiclone on the index date; 6) received palliative care services in the 180 days prior to cohort entry; or 7) were dispensed trazodone at a dose greater than 300 mg/day or zopiclone at a dose greater than 15 mg/day (see Figure 1).

We defined our primary outcome as a composite of fall-related emergency department visit (i.e., injurious fall) or major osteoporotic fracture, defined as a hip, pelvis, humerus, or forearm fracture (see Appendix B).(26) These outcomes are identified with a high positive predictive value in administrative databases and high level of agreement during medical chart re-abstraction.(22,26,27) Our secondary outcome was all-cause mortality. Where numbers permitted, we planned to report primary outcome components (i.e., fall, hip fracture, major osteoporotic fracture) as secondary outcomes. See Appendix A for all International Classification of Diseases, Tenth Revision (ICD-10) codes used to define residents’ baseline characteristics and study outcomes.(22,23,26)

Statistical Analysis

We summarized categorical baseline characteristics as frequencies (and percentages) and compared across exposure groups with chi-square tests. We summarized continuous baseline characteristics as means (and SDs) and compared across exposure groups with independent t-tests. We reported the proportion of residents missing data for individual baseline characteristics.

We derived inverse probability of treatment weights from an estimated propensity score, which we derived by regressing exposure status on baseline covariates (see Appendix B for covariates), including medications dispensed in the year before cohort entry. In our study, the propensity score was the probability that a resident would be dispensed trazodone or zopiclone, conditional on their baseline characteristics.(28) We included missing values for categorical variables as an additional category. There were no missing values for continuous variables. We modeled the average treatment effect because we could foresee any cohort member potentially receiving either exposure drug and we wished to understand the average effect of treatment in the entire cohort.(29) Treatment weights were inspected for outlying values (greater than 50).(30) Crude (i.e., unweighted) and weighted cause-specific hazard ratios comparing outcome rates associated with zopiclone or trazodone use were derived from cause-specific hazards models, because we wanted to understand the association between our exposure and outcome rate in residents who had not yet had an outcome and were, therefore, at risk of having an outcome.(31) Weighted cause-specific hazards models were adjusted for all baseline characteristics for which there were statistically significant differences (i.e., p<.05) between exposure groups. We verified that hazard ratios did not vary over time, and we used robust standard errors to account for within-subject homogeneity in outcomes induced by weighting.(32)

Our primary analyses were based on an intention-to-treat principle (i.e., residents who were newly dispensed either exposure drug remained in the cohort even if they were dispensed the other exposure drug during the follow-up period); residents were followed until the first of the outcome of interest, death, or 180 days after index date. In secondary analyses, we censored residents who were dispensed the other exposure drug during the 180-day follow-up period (i.e., per protocol). We reported weighted incidence rates as the number of events per 100 person-years. Where numbers permitted, we planned to conduct subgroup analyses based on residents’ age, sex, dementia severity, and concurrent antipsychotic prescription. Analyses were conducted with SAS (version 9.4; Cary, NC) and STATA SE (version 13.0; StataCorp LP, College Station, TX).

Ethics Approval

We obtained ethics approval for this study from the University of Alberta Research Ethics Board (Pro00091328).

RESULTS

We included 3,002 residents in our study cohort: 1,403 residents were newly dispensed trazodone, and 1,599 residents were newly dispensed zopiclone (Figure 1). The median total daily dose of zopiclone was 7.5 mg (interquartile range 3.75 mg to 7.5 mg) and trazodone was 25 mg (interquartile range 25 mg to 50 mg). There were no outlying inverse probability of treatment weights. After applying inverse probability of treatment weights, exposure groups were similar at baseline (Table 1 and Table B1 in Appendix B). The mean age of residents on the date of cohort entry was 85.7 (SD 7.4), 61.6% were female, and 81.2% had a diagnosis of dementia.

 


 

FIGURE 1 Flow diagram of cohort creation
N = number; RAI-MDS 2.0 = Resident Assessment Instrument – Minimum Data Set, version 2.0.

TABLE 1 Baseline characteristics of a cohort of older adults dispensed trazodone or zopiclone (number [n] =3,002)


 

In both intention-to-treat and per-protocol analyses, residents newly dispensed zopiclone experienced a similar rate of falls and major osteoporotic fractures compared to residents newly dispensed trazodone (crude hazard ratio 0.89, 0.70 to 1.13; intention-to-treat-weighted hazard ratio 1.15, 95% CI 0.90 to 1.48; per-protocol-weighted hazard ratio 0.85, 95% CI 0.60 to 1.21) (Table 2). Similarly, residents newly dispensed zopiclone experienced a similar rate of all-cause mortality compared to residents newly dispensed trazodone (crude hazard ratio 0.96, 95% CI 0.82 to 1.13; intention-to-treat-weighted hazard ratio 0.96, 95% CI 0.79 to 1.16; per-protocol-weighted hazard ratio 0.90, 95% CI 0.66 to 1.23) (Table 2). We did not conduct subgroup analyses because there were too few outcomes in exposure groups.

TABLE 2 Intention-to-treat and per-protocol analyses of the comparative risk of (i) fall or major osteoporotic fracture and (ii) all-cause mortality for new users of zopiclone vs. trazodone within 180 days

 

DISCUSSION

In our cohort of older nursing home residents, we found a similar rate of injurious falls, major osteoporotic fractures, and death in residents newly dispensed trazodone or zopiclone. Our findings are important because trazodone is associated with a similar risk of injurious falls and fractures compared to benzodiazepines and atypical antipsychotics, and these outcomes are common and important to residents and the health-care system: the mean incidence of falls in nursing homes is 1.5 falls per bed per year and 4% of falls result in a fracture.(16,17,33) Further, our findings provide direct estimates of the comparative risk of harm associated with trazodone or zopiclone use, which will inform quality improvement initiatives and highlight potential dangers associated with medication substitution as clinicians are discouraged from administering certain medications without having access to feasible and evidence-based alternatives.

There is mounting evidence of harm associated with trazodone and zopiclone use in older adults.(1618) Trazodone is associated with a similar risk of harm from injurious falls or fractures as benzodiazepines or atypical antipsychotics.(16,17) Similarly, a systematic review and meta-analysis describing harms associated with nonbenzodiazepine sedative hypnotic use in older adults identified an increased risk of fractures and injuries, but it did not identify an increased risk of falls associated with their use.(18) However, a subsequent cohort study by Westerlind and colleagues identified an increased risk of falls associated with zopiclone or zolpidem use.(34) Our findings bridge the gap between these bodies of literature to show that trazodone and zopiclone are associated with a similar risk of harm in nursing home residents. Further, our findings, combined with the work of others, demonstrate that trazodone, zopiclone, atypical antipsychotics, and benzodiazepines are all associated with a similar risk of harm from injurious falls and fractures in this patient population.(16,17)

Unlike benzodiazepines and antipsychotics, there has been less research directed at reducing the potentially inappropriate prescribing of alternative psychotropic medications, such as trazodone and nonbenzodiazepines sedative hypnotics (i.e., z-drugs), despite growing evidence of harm associated these alternative psychotropic medications.(1315,35) A multi-hospital study demonstrated that a sedative-hypnotic reduction quality improvement bundle, which consisted of order set changes, audit feedback, pharmacist-enabled medication reviews, sleep hygiene, daily sleep huddles, and education, decreased benzodiazepine and nonbenzodiazepine sedative hypnotic use.(35) Other potentially efficacious interventions that could be implemented instead of psychotropic medications include multidisciplinary care, massage and touch therapy, outdoor activities, and cognitive stimulation. However institution- and individual-level barriers, including perceived lack of effectiveness, lack of knowledge of the dangers associated with psychotropic medication use, inadequate staffing, and clinician attitudes towards neuropsychiatric symptom management, prevent their widespread use.(6,3640) Institution-level (e.g., hospitals, non-profit organizations, nursing homes) policies that 1) establish an interprofessional team responsible for psychotropic medication stewardship; 2) agree on psychotropic medication appropriateness criteria, educate care staff; 3) inform and involve family and friend carers; 4) establish a regular medication review process; 5) discontinue potentially inappropriate medications; and 6) implement nonpharmacologic interventions are needed to ensure that inappropriate administration of psychotropic medications is minimized, and feasible nonpharmacologic alternative interventions are available.(41)

Our study has limitations. The nonrandomized study design means there are potential residual confounders that could influence our results; however, we 1) used comprehensive RAI-MDS 2.0 data containing information about resident health status, including functional and cognitive impairment; 2) restricted our cohort to a population of older nursing home residents (in Alberta, Canada, where residents are supported in completing basic and instrumental activities of daily living, which ensures they receive medications); and 3) utilized a propensity score to balance between-group differences. We also limited our definition of falls to those requiring transfer to hospital (i.e., injurious falls), which means our reported estimate of falls or major osteoporotic fractures per 100 person-years is likely an underestimate of true incidence.

We found that zopiclone use was associated with a similar rate of injurious falls, major osteoporotic fractures, and all-cause mortality compared to trazodone in older nursing home residents. Our findings suggest that quality improvement initiatives should target trazodone and nonbenzodiazepine sedative hypnotic use in older adults, in addition to benzodiazepine and antipsychotic use; trazodone and zopiclone, despite their potential for harm, are not currently targeted by many of these initiatives.(2,10,14,35,42) Our findings, combined with earlier research, suggest that 1) trazodone, zopiclone, benzodiazepines, and atypical antipsychotics are all similarly harmful in older adults with respect to a risk of falling or sustaining a fracture; 2) trazodone and zopiclone should also be targeted by quality improvement initiatives to decrease their inappropriate use; 3) further comparative safety research is needed on other psychotropic medications to inform decision-making for patients and caregivers that will help them understand the risks and benefits of choosing pharmacologic or nonpharmacologic interventions for reducing neuropsychiatric symptoms; and, 4) greater resources should be dedicated to implementing feasible nonpharmacologic interventions to antipsychotics and benzodiazepines in nursing homes so we can avoid inappropriate substitution of potentially harmful alternative medications.(1618,34)

ACKNOWLEDGEMENTS

Not applicable.

CONFLICT OF INTEREST DISCLOSURES

We have read and understood the Canadian Geriatrics Journal’s policy on conflicts of interest disclosure and declare there are no conflicts of interest.

FUNDING

This research did not receive any funding from agencies in the public, commercial, or not-for-profit sectors. In-kind support was provided by the Alberta SPOR Support Unit Data and Research Services team.

REFERENCES

1 Webster L, Costafreda Gonzalez S, Stringer A, Lineham A, Budgett J, Kyle S, et al. Measuring the prevalence of sleep disturbances in people with dementia living in care homes: a systematic review and meta-analysis. Sleep. 2020;43(4):zsz251.
cross-ref  

2 Fog AF, Straand J, Engedal K, Blix HS. Drug use differs by care level. A cross-sectional comparison between older people living at home or in a nursing home in Oslo, Norway. BMC Geriatr. 2019;19(1):49.
cross-ref  pubmed  

3 Lee DA, Robins LM, Bell JS, Srikanth V, Mohler R, Hill KD, et al. Prevalence and variability in use of physical and chemical restraints in residential aged care facilities: A systematic review and meta-analysis. Int J Nurs Stud. 2021;117:103856.
cross-ref  pubmed  

4 Sivertsen B, Omvik S, Pallesen S, Bjorvatn B, Havik OE, Kvale G, et al. Cognitive behavioral therapy vs zopiclone for treatment of chronic primary insomnia in older adults. JAMA 2006;295(24):2851–58.
cross-ref  pubmed  

5 Brown CA, Wielandt P, Wilson D, Jones A, Crick K. Healthcare providers’ knowledge of disordered sleep, sleep assessment tools, and nonpharmacological sleep interventions for persons living with dementia: a national survey. Sleep Disord. 2014;2014:286274.
cross-ref  

6 Watt JA, Goodarzi Z, Veroniki AA, Nincic V, Khan PA, Ghassemi M, et al. Comparative efficacy of interventions for aggressive and agitated behaviors in dementia: a systematic review and network meta-analysis. Ann Intern Med. 2019;171(9):633–42.
cross-ref  pubmed  

7 Vasudev A, Shariff SZ, Liu K, Burhan AM, Herrmann N, Leonard S, et al. Trends in Psychotropic Dispensing Among Older Adults with Dementia Living in Long-Term Care Facilities: 2004–213. Am J Geriatr Psychiatry. 2015;23(12):1259–69.
cross-ref  pubmed  

8 Gerlach LB, Kales HC, Kim HM, Bynum JPW, Chiang C, Strominger J, et al. Trends in antipsychotic and mood stabilizer prescribing in long-term care in the US: 2011–2014. J Am Med Dir Assoc. 2020;21(11):1629–35.
cross-ref  pubmed  

9 Donegan K, Black N, Livingston G, Banerjee S, Burns A. Trends in diagnosis and treatment for people with dementia in the UK from 2005 to 2015: a longitudinal retrospective cohort study. Lancet Public Health. 2017;2(3):e149–56.
cross-ref  pubmed  

10 Iaboni A, Bronskill SE, Reynolds KB, Wang X, Rochon PA, Herrmann N, et al. Changing pattern of sedative use in older adults: a population-based cohort study. Drugs Aging. 2016;33(7):523–33.
cross-ref  pubmed  

11 Richardson K, Savva GM, Boyd PJ, Aldus C, Maidment I, Pakpahan E, et al. Non-benzodiazepine hypnotic use for sleep disturbance in people aged over 55 years living with dementia: a series of cohort studies. Health Technol Assess. 2021;25(1):1–202.
cross-ref  

12 Lukacisinova A, Fialova D, Peel NM, Hubbard RE, Brkic J, Onder G, et al. The prevalence and prescribing patterns of benzodiazepines and Z-drugs in older nursing home residents in different European countries and Israel: retrospective results from the EU SHELTER study. BMC Geriatr. 2021;21(1):277.
cross-ref  pubmed  

13 AMDA. Ten things clinicians and patients should question. Columbia, MD: AMDA Choosing Wisely; 2015.

14 Caswell L, Hoosen I, Vassilas CA, Haque S. Reducing hypnotic use on two older adult functional wards: an effective audit? Psychiatr Bull. 2006;30(3):95–97.
cross-ref  

15 Joglekar NN, Patel Y, Keller MS. Evaluation of clinical decision support to reduce sedative-hypnotic prescribing in older adults. Appl Clin Inform. 2021;12(3):436–44.
cross-ref  pubmed  

16 Bronskill SE, Campitelli MA, Iaboni A, Herrmann N, Guan J, Maclagan LC, et al. Low-dose trazodone, benzodiazepines, and fall-related injuries in nursing homes: a matched-cohort study. J Am Geriatr Soc. 2018;66(10):1963–71.
cross-ref  pubmed  

17 Watt JA, Gomes T, Bronskill SE, Huang A, Austin PC, Ho JM, et al. Comparative risk of harm associated with trazodone or atypical antipsychotic use in older adults with dementia: a retrospective cohort study. CMAJ. 2018;190(47):E1376–83.
cross-ref  pubmed  

18 Treves N, Perlman A, Kolenberg Geron L, Asaly A, Matok I. Z-drugs and risk for falls and fractures in older adults-a systematic review and meta-analysis. Age Ageing. 2018;47(2):201–08.
cross-ref  

19 Vandenbroucke JP, von Elm E, Altman DG, Gotzsche PC, Mulrow CD, Pocock SJ, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. Int J Surg. 2014;12(12):1500–24.
cross-ref  pubmed  

20 Langan SM, Schmidt SA, Wing K, Ehrenstein V, Nicholls SG, Filion KB, et al. The reporting of studies conducted using observational routinely collected health data statement for pharmacoepidemiology (RECORD-PE). BMJ. 2018;363:k3532.
cross-ref  pubmed  

21 Government of Alberta. Alberta Health Continuing Care. Alberta long-term care resident profile 2016/2017. 2018. Available from: https://open.alberta.ca/dataset/90c128a6-3a8e-4c6e-8591-58e88fe6b6f9/resource/894a3a9c-8999-4487-b7e5-2850b3bb1a2e/download/cc-ltc-resident-profile-2017.pdf

22 Juurlink D, Preyra C, Croxford R, Chong A, Austin P, Tu J, et al. Canadian Institute for Health Information Discharge Abstract Database: a validation study. Toronto: Institute for Clinical Evaluative Sciences; 2006.

23 Wodchis WP, Naglie G, Teare GF. Validating diagnostic information on the minimum data set in ontario hospital-based long-term care. Med Care. 2008;46(8):882–87.
cross-ref  pubmed  

24 Gibson D, Richards H, Chapman A. The national ambulatory care reporting system: factors that affect the quality of its emergency data. Int J Inform Qual. 2008;2(2):97–114.
cross-ref  

25 Hirdes JP, Ljunggren G, Morris JN, Frijters DH, Finne Soveri H, Gray L, et al. Reliability of the interRAI suite of assessment instruments: a 12-country study of an integrated health information system. BMC Health Serv Res. 2008;8(1):277.
cross-ref  

26 Welk B, McArthur E, Fraser LA, Hayward J, Dixon S, Hwang YJ, et al. The risk of fall and fracture with the initiation of a prostate-selective alpha antagonist: a population based cohort study. BMJ. 2015;351:h5398.
cross-ref  

27 Tamblyn R, Reid T, Mayo N, McLeod P, Churchill-Smith M. Using medical services claims to assess injuries in the elderly: sensitivity of diagnostic and procedure codes for injury ascertainment. J Clin Epidemiol. 2000;53(2):183–94.
cross-ref  pubmed  

28 Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res. 2011;46(3):399–424.
cross-ref  pubmed  

29 Austin PC, Stuart EA. The performance of inverse probability of treatment weighting and full matching on the propensity score in the presence of model misspecification when estimating the effect of treatment on survival outcomes. Stat Methods Med Res. 2017;26(4):1654–70.
cross-ref  

30 Lee BK, Lessler J, Stuart EA. Weight trimming and propensity score weighting. PLoS One. 2011;6(3):e18174.
cross-ref  pubmed  

31 Austin PC, Lee DS, Fine JP. Introduction to the analysis of survival data in the presence of competing risks. Circulation. 2016;133(6):601–09.
cross-ref  pubmed  

32 Austin PC. Variance estimation when using inverse probability of treatment weighting (IPTW) with survival analysis. Stat Med. 2016;35(30):5642–55.
cross-ref  pubmed  

33 Rubenstein LZ, Josephson KR, Robbins AS. Falls in the nursing home. Ann Intern Med. 1994;121(6):442–51.
cross-ref  pubmed  

34 Westerlind B, Ostgren CJ, Molstad S, Midlov P, Hagg S. Use of non-benzodiazepine hypnotics is associated with falls in nursing home residents: a longitudinal cohort study. Aging Clin Exp Res. 2019;31(8):1078–95.
cross-ref  

35 Soong C, Ethier C, Lee Y, Othman D, Burry L, Wu PE, et al. Reducing sedative-hypnotics among hospitalized patients: a multi-centered study. J Gen Intern Med. 2022;37:2345–50.
cross-ref  pubmed  

36 Simmons SF, Bonnett KR, Hollingsworth E, Kim J, Powers J, Habermann R, et al. Reducing antipsychotic medication use in nursing homes: a qualitative study of nursing staff perceptions. Gerontologist. 2018;58(4):e239–e50.
cross-ref  

37 Walsh KA, Sinnott C, Fleming A, Mc Sharry J, Byrne S, Browne J, et al. Exploring antipsychotic prescribing behaviors for nursing home residents with dementia: a qualitative study. J Am Med Dir Assoc. 2018;19(11):948–58.
cross-ref  pubmed  

38 Kuntz J, Kouch L, Christian D, Peterson PL, Gruss I. Barriers and facilitators to the deprescribing of nonbenzodiazepine sedative medications among older adults. Perm J. 2018;22:17–157.
cross-ref  pubmed  

39 Watt JA, Goodarzi Z, Veroniki AA, Nincic V, Khan PA, Ghassemi M, et al. Comparative efficacy of interventions for reducing symptoms of depression in people with dementia: systematic review and network meta-analysis. BMJ. 2021; 372:n532.
cross-ref  pubmed  

40 Halek M, Reuther S, Muller-Widmer R, Trutschel D, Holle D. Dealing with the behaviour of residents with dementia that challenges: a stepped-wedge cluster randomized trial of two types of dementia-specific case conferences in nursing homes (FallDem). Int J Nurs Stud. 2020;104:103435.
cross-ref  pubmed  

41 BC Patient Safety & Quality Council. When psychosis isn’t the diagnosis: a toolkit for reducing inappropriate use of antipsychotics in long term care. 2019. Available from: https://bcpsqc.ca/resource/when-psychosis-isnt-the-diagnosis-a-toolkit-for-reducing-inappropriate-use-of-antipsychotics-in-long-term-care/

42 Farrell B, Tsang C, Raman-Wilms L, Irving H, Conklin J, Pottie K. What are priorities for deprescribing for elderly patients? Capturing the voice of practitioners: a modified delphi process. PLoS One. 2015;10(4):e0122246.
cross-ref  pubmed  


Correspondence to: Dr. Jennifer A. Watt, MD, PhD, Li Ka Shing Knowledge Institute, St. Michael’s Hospital-Unity Health Toronto, 209 Victoria Street, East Building, Room 723, Toronto, ON, Canada, M5B 1W8, Email:jennifer.watt@utoronto.ca

(Return to Top)


APPENDIX A. Variable definitions used for cohort creation






 

APPENDIX B.

TABLE B1 Complete baseline characteristics of a cohort of older adults dispensed trazodone or zopiclone (number [n] =3,002)


 


Canadian Geriatrics Journal, Vol. 26, No. 1, March 2023