**2.1 Participants and measures**

The participants are all new admissions, aged 65 years and older, to LTCHs in the Canadian province of Ontario during the financial year April 1st 2010 to March 31st 2011. They include 20,414 residents from 631 LTCHs. The distribution of men to women is 33.6% to 66.4%. The mean age of men is 83.03 years with a standard deviation of 7.37 years. The mean age of women is 85.29 years with a standard deviation of 7.19 years.

The main assessment tool used here is the RAI 2.0, which, to the authors' knowledge, (1) is used in more countries, (2) has a more thorough psychometric evaluation, and (3) is more comprehensive than any other geriatric assessment tool. The RAI 2.0 requires trained heath care professionals to score quantifiable assessment items relevant to medical diagnoses, levels of functioning, behavioral and emotional problems, forms of treatment, etc. The information is from medical records, clinical observations, and communication with residents, their family members and the facility's staff members. As already indicated, the RAI also contains objective scales that are evaluated against 'gold standard' measures from the relevant literature. The measures in the present analyses are the CHESS and items on antipsychotic, analgesic, antidepressant, anxiolytic and hypnotic medication use. The latter items record the number of days of usage during the week preceding an assessment. We report here on three usage categories: no use, PRN (i.e., intermittent) use, and daily use.

The RAI 2.0 also provides information on the mortality of residents in a LTCH. Other databases linked to the RAI 2.0 are the Discharge Abstract Database (DAD) and the National Ambulatory Care Reporting System (NACRS). The DAD reports mortality data for hospital discharges and the NACRS reports mortality in settings for emergency and ambulatory care. Consequently, our data encompasses mortality throughout the health care system. We are grateful to the Canadian Institute for Health Information (CIHI) for the provision of the data with encrypted personal and facility level identifiers.

Residents receive RAI 2.0 assessments upon admission and thereafter at quarterly intervals. The maximal follow-up period in the present study is 1-year. We report here on data from the final assessment, with mortality indexed by its absence or presence during 90 days following that assessment (i.e., a period that precedes the scheduled date of any subsequent assessment).

#### **2.2 Statistical analyses**

The statistical analyses relate to three issues. The first concerns the types of concurrent combination of usage frequencies between antipsychotics with other psychotropics. These analyses begin graphic and tabular statistics that relate to concurrent relationships between frequencies antipsychotic usage with frequencies for other types of psychotropic usage. Then follows findings from *Statistical Package for the Social Sciences* (SPSS Version 25) GLMM multinomial analysis of frequencies of antipsychotic usage (i.e., the target variable) against corresponding frequencies for each other psychotropic (i.e., the fixed effect variables). The random variable for this and every subsequent GLMM analysis are LTCHs.

The second issue concerns mortality within 90 days of the final assessment. The primary analysis is a GLMM interval censored survival model (i.e., a binomial distribution with a complementary log–log link). The CHESS (i.e., centered on its grand mean) and concurrent combinations of frequencies for antipsychotic and other psychotropic usage comprise the fixed effects. Then follows GLMM interval censored survival models that attempt to clarify implications of the preceding by analyzing

**191**

**Figure 2.**

*for antipsychotic medication.*

antidepressants.

*Effects of Antipsychotic Medication on Mortality in Long-Term Care Home Residents*

summative categories that respectively relate to antipsychotic use and other psychotropic use. Next, we analyze models that examine combinations of antipsychotics with each type of psychotropic. The purpose is to ascertain the types of antipsychotic that may ameliorate of exacerbate risk of mortality at different levels of usage. All the latter

The final issue concerns the effects on mortality of changes in health condition and prescribing practices from the penultimate to final assessment. This GLMM analysis examines whether changes in the CHESS and PRN prescriptions have independent implications for survival. In contrast, an alternative hypothesis suggests that changes in PRN prescription are a consequence of changes in health condition,

The following graph and table illustrate relationships between frequencies of usage for antipsychotic medication with corresponding usage of all other psychotropic medications. **Figure 2** shows 95% confidence intervals for the totality of any other psychotropic use against no use, PRN, and daily use for antipsychotic medication. The mean use of other psychotropic medication is significantly lower with no use of antipsychotic medication than for PRN and daily use, as evidenced by non-overlapping confidence intervals. **Table 2** shows percentages of residents with a given frequency of antipsychotic medication combined with the use of 1, 2, 3 or 4 other psychotropic medications. The statistical mode (i.e., the most frequent value) within columns of this table indicates that residents without antipsychotics most frequently receive one other psychotropic, whereas those with PRN and daily

antipsychotic use most frequently use two other psychotropic medications.

The following figures illustrate frequencies of use of specific psychotropics that accompany no, PRN or daily use of antipsychotics. **Figure 3** shows findings associated with antidepressant medication. The findings indicate that approximately 60% of residents with daily antipsychotics and just over 40% of those with no antipsychotics receive antidepressants on a daily basis. Of those residents with PRN use of antipsychotics, the majority show either PRN (18%) or daily (35%) use of

*95% confidence intervals for summative Co-medication frequencies for other psychotropics against frequencies* 

*DOI: http://dx.doi.org/10.5772/intechopen.95388*

*2.2.1 Analyses of psychotropic combinations*

models include the CHESS as a measure of mortality risk.

with the former having with no direct implications for survival.

#### *Effects of Antipsychotic Medication on Mortality in Long-Term Care Home Residents DOI: http://dx.doi.org/10.5772/intechopen.95388*

summative categories that respectively relate to antipsychotic use and other psychotropic use. Next, we analyze models that examine combinations of antipsychotics with each type of psychotropic. The purpose is to ascertain the types of antipsychotic that may ameliorate of exacerbate risk of mortality at different levels of usage. All the latter models include the CHESS as a measure of mortality risk.

The final issue concerns the effects on mortality of changes in health condition and prescribing practices from the penultimate to final assessment. This GLMM analysis examines whether changes in the CHESS and PRN prescriptions have independent implications for survival. In contrast, an alternative hypothesis suggests that changes in PRN prescription are a consequence of changes in health condition, with the former having with no direct implications for survival.

#### *2.2.1 Analyses of psychotropic combinations*

*Suggestions for Addressing Clinical and Non-Clinical Issues in Palliative Care*

The participants are all new admissions, aged 65 years and older, to LTCHs in the Canadian province of Ontario during the financial year April 1st 2010 to March 31st 2011. They include 20,414 residents from 631 LTCHs. The distribution of men to women is 33.6% to 66.4%. The mean age of men is 83.03 years with a standard deviation of 7.37 years. The mean age of women is 85.29 years with a standard

The main assessment tool used here is the RAI 2.0, which, to the authors' knowledge, (1) is used in more countries, (2) has a more thorough psychometric evaluation, and (3) is more comprehensive than any other geriatric assessment tool. The RAI 2.0 requires trained heath care professionals to score quantifiable assessment items relevant to medical diagnoses, levels of functioning, behavioral and emotional problems, forms of treatment, etc. The information is from medical records, clinical observations, and communication with residents, their family members and the facility's staff members. As already indicated, the RAI also contains objective scales that are evaluated against 'gold standard' measures from the relevant literature. The measures in the present analyses are the CHESS and items on antipsychotic, analgesic, antidepressant, anxiolytic and hypnotic medication use. The latter items record the number of days of usage during the week preceding an assessment. We report here on three usage categories: no use, PRN (i.e., inter-

The RAI 2.0 also provides information on the mortality of residents in a LTCH. Other databases linked to the RAI 2.0 are the Discharge Abstract Database (DAD) and the National Ambulatory Care Reporting System (NACRS). The DAD reports mortality data for hospital discharges and the NACRS reports mortality in settings for emergency and ambulatory care. Consequently, our data encompasses mortality throughout the health care system. We are grateful to the Canadian Institute for Health Information (CIHI) for the provision of the data with encrypted personal

Residents receive RAI 2.0 assessments upon admission and thereafter at quarterly intervals. The maximal follow-up period in the present study is 1-year. We report here on data from the final assessment, with mortality indexed by its absence or presence during 90 days following that assessment (i.e., a period that

The statistical analyses relate to three issues. The first concerns the types of concurrent combination of usage frequencies between antipsychotics with other psychotropics. These analyses begin graphic and tabular statistics that relate to concurrent relationships between frequencies antipsychotic usage with frequencies for other types of psychotropic usage. Then follows findings from *Statistical Package for the Social Sciences* (SPSS Version 25) GLMM multinomial analysis of frequencies of antipsychotic usage (i.e., the target variable) against corresponding frequencies for each other psychotropic (i.e., the fixed effect variables). The random variable

The second issue concerns mortality within 90 days of the final assessment. The

primary analysis is a GLMM interval censored survival model (i.e., a binomial distribution with a complementary log–log link). The CHESS (i.e., centered on its grand mean) and concurrent combinations of frequencies for antipsychotic and other psychotropic usage comprise the fixed effects. Then follows GLMM interval censored survival models that attempt to clarify implications of the preceding by analyzing

precedes the scheduled date of any subsequent assessment).

for this and every subsequent GLMM analysis are LTCHs.

**2.1 Participants and measures**

deviation of 7.19 years.

mittent) use, and daily use.

and facility level identifiers.

**2.2 Statistical analyses**

**190**

The following graph and table illustrate relationships between frequencies of usage for antipsychotic medication with corresponding usage of all other psychotropic medications. **Figure 2** shows 95% confidence intervals for the totality of any other psychotropic use against no use, PRN, and daily use for antipsychotic medication. The mean use of other psychotropic medication is significantly lower with no use of antipsychotic medication than for PRN and daily use, as evidenced by non-overlapping confidence intervals. **Table 2** shows percentages of residents with a given frequency of antipsychotic medication combined with the use of 1, 2, 3 or 4 other psychotropic medications. The statistical mode (i.e., the most frequent value) within columns of this table indicates that residents without antipsychotics most frequently receive one other psychotropic, whereas those with PRN and daily antipsychotic use most frequently use two other psychotropic medications.

The following figures illustrate frequencies of use of specific psychotropics that accompany no, PRN or daily use of antipsychotics. **Figure 3** shows findings associated with antidepressant medication. The findings indicate that approximately 60% of residents with daily antipsychotics and just over 40% of those with no antipsychotics receive antidepressants on a daily basis. Of those residents with PRN use of antipsychotics, the majority show either PRN (18%) or daily (35%) use of antidepressants.

#### **Figure 2.**

*95% confidence intervals for summative Co-medication frequencies for other psychotropics against frequencies for antipsychotic medication.*


**Table 2.**

*Percentage of residents with No, PRN or daily use of antipsychotics 1, 2, 3 or 4 other psychotropics.*

**Figure 3.**

*Percentage antidepressant frequency against antipsychotic frequency.*

**193**

**Figure 6.**

*Effects of Antipsychotic Medication on Mortality in Long-Term Care Home Residents*

Levels of analgesic medication are uniformly high. **Figure 4** shows PRN or daily use among approximately 65–70% of residents regardless of frequency of usage of antipsychotic medication. Consistent with finding for antidepressants and anxiolytics (see below), the highest PRN use of analgesics corresponds with PRN use

**Figure 5** indicates a low overall use of anxiolytic medication. The levels of daily use are approximately 7–10% regardless of frequency of use for antipsychotics. However, among residents with PRN use of antipsychotics, PRN use of anxiolytics is approximately 14%, which is considerably higher than daily use for this subgroup

**Figure 6** shows hypnotic use to be lower than for any of other psychotropic (i.e., approximately 6.3% of residents). The highest PRN use of hypnotics occurs

*DOI: http://dx.doi.org/10.5772/intechopen.95388*

of residents.

**Figure 5.**

antipsychotic medication (approximately, 22%).

*Percentage Anaxiolytic frequency against antipsychotic frequency.*

*Percentage hypnotic frequency against antipsychotic frequency.*

**Figure 4.** *Percentage analgesic frequency against antipsychotic frequency.*

*Effects of Antipsychotic Medication on Mortality in Long-Term Care Home Residents DOI: http://dx.doi.org/10.5772/intechopen.95388*

Levels of analgesic medication are uniformly high. **Figure 4** shows PRN or daily use among approximately 65–70% of residents regardless of frequency of usage of antipsychotic medication. Consistent with finding for antidepressants and anxiolytics (see below), the highest PRN use of analgesics corresponds with PRN use antipsychotic medication (approximately, 22%).

**Figure 5** indicates a low overall use of anxiolytic medication. The levels of daily use are approximately 7–10% regardless of frequency of use for antipsychotics. However, among residents with PRN use of antipsychotics, PRN use of anxiolytics is approximately 14%, which is considerably higher than daily use for this subgroup of residents.

**Figure 6** shows hypnotic use to be lower than for any of other psychotropic (i.e., approximately 6.3% of residents). The highest PRN use of hypnotics occurs

**Figure 5.** *Percentage Anaxiolytic frequency against antipsychotic frequency.*

**Figure 6.** *Percentage hypnotic frequency against antipsychotic frequency.*

*Suggestions for Addressing Clinical and Non-Clinical Issues in Palliative Care*

**Number of other of psychotropics Percentage of residents**

*Percentage of residents with No, PRN or daily use of antipsychotics 1, 2, 3 or 4 other psychotropics.*

 18.6% 13.6% 13.2% 41.4% 35.6% 36.6% 31.8% 38.6% 38.9% 7.7% 11.2% 10.4% 0.5% 1.0% 1.0%

**Antipsychotic use None PRN Daily**

**192**

**Figure 4.**

**Figure 3.**

**Table 2.**

*Percentage antidepressant frequency against antipsychotic frequency.*

*Percentage analgesic frequency against antipsychotic frequency.*


#### **Table 3.**

*Fixed effects coefficients and odds ratios for prediction of antipsychotic frequency by frequencies of all other antipsychotic categories.*

in combination with PRN use of antipsychotics. Daily use of hypnotics has approximately similar levels among residents with no of daily use of antipsychotic medication.

**195**

*Effects of Antipsychotic Medication on Mortality in Long-Term Care Home Residents*

Inferences from the preceding graphs and table include the following. First, residents with PRN or daily use of antipsychotics have higher concurrent use of other psychotropic medications than those without antipsychotic use. **Table 2** shows that over 80% of residents without antipsychotic use receive at least one other psychotropic. The psychotropics that appear most frequently in these combinations are antidepressants and analgesics, which have the highest overall frequency of usage. Second, PRN use of antipsychotics combines with the highest PRN in each other psychotropic category. This finding suggests a clustering of PRN prescribing that

The final analysis this section is a GLMM multinomial analysis. This analysis includes LTCHs as a random variable and fixed effect predictors that evaluate the independent contributions by other psychotropics to frequencies of antipsychotic use. The target and predictor variables are on nominal scales of no use, PRN use and

The findings in **Table 3** include the regression coefficients, standard errors, levels of statistical significance and 95% confidence intervals. **Table 3** also includes derivative exponential coefficient for readers that prefer odds ratios over regression coefficients. Positive or negative regression coefficients respectively indicate mean values above or below those associated with the reference category, with odds ratios greater or less than unity having comparable meaning. The overall findings for the model include significant random effects of LTCHs at *p* < .001. Findings for the

Daily antidepressants, daily anxiolytics and PRN anxiolytics are all positive predictors of daily antipsychotic use (all *p* < .001). Daily analgesics and PRN analgesics are negative predictors (both *p* < .001). These findings suggest that psychotropics purportedly relevant to mood improvement and anxiety reduction are likely to accompany daily antipsychotic use, whereas medications purportedly relevant to pain relief are less likely to occur in combination with daily antipsychotic

PRN use of antidepressants (*p* < .001), anxiolytics (*p* < .001), analgesics (*p* < .001) and hypnotics (*p* < .001) are positive predictors of PRN use of antipsychotics. There are no significant relationships between daily use of other psychotropics and PRN use of antipsychotics. These findings indicate a clustering of PRN

Mortality during the 1-year follow-up period of data collection is 18.1% overall.

The mortality rates for men and women are 21.1% and 16.3% respectively. The distribution of mortality across assessments indicates that 45% of residents died within 90 days of the admission assessment, with a decreasing proportion of deaths

The primary interval censored survival analysis shows a significant random effect for LTCHs *p* < .001. Because the same level of significance is present in all subsequent GLMM analyses, we need not report them henceforth. **Table 4** shows findings for the fixed effects. Unsurprisingly, the positive coefficient for the CHESS indicates higher mortality for residents at greater risk of mortality. The reference category for combinations of medications is the daily use of both antipsychotics and other psychotropics, which numerically is associated with the lowest level of mortality. This combination has significantly lower mortality (*p* < .005 or beyond) than any other combination except for those that combine no antipsychotics with daily psychotropics and PRN use of antipsychotics with daily psychotropics.

daily use, respectively, with the former designated as reference category.

*DOI: http://dx.doi.org/10.5772/intechopen.95388*

encompasses all types of psychotropic medication.

fixed effect terms are as follows.

medication.

prescribing.

*2.2.2 Survival analyses*

at each subsequent assessment.

#### *Effects of Antipsychotic Medication on Mortality in Long-Term Care Home Residents DOI: http://dx.doi.org/10.5772/intechopen.95388*

Inferences from the preceding graphs and table include the following. First, residents with PRN or daily use of antipsychotics have higher concurrent use of other psychotropic medications than those without antipsychotic use. **Table 2** shows that over 80% of residents without antipsychotic use receive at least one other psychotropic. The psychotropics that appear most frequently in these combinations are antidepressants and analgesics, which have the highest overall frequency of usage. Second, PRN use of antipsychotics combines with the highest PRN in each other psychotropic category. This finding suggests a clustering of PRN prescribing that encompasses all types of psychotropic medication.

The final analysis this section is a GLMM multinomial analysis. This analysis includes LTCHs as a random variable and fixed effect predictors that evaluate the independent contributions by other psychotropics to frequencies of antipsychotic use. The target and predictor variables are on nominal scales of no use, PRN use and daily use, respectively, with the former designated as reference category.

The findings in **Table 3** include the regression coefficients, standard errors, levels of statistical significance and 95% confidence intervals. **Table 3** also includes derivative exponential coefficient for readers that prefer odds ratios over regression coefficients. Positive or negative regression coefficients respectively indicate mean values above or below those associated with the reference category, with odds ratios greater or less than unity having comparable meaning. The overall findings for the model include significant random effects of LTCHs at *p* < .001. Findings for the fixed effect terms are as follows.

Daily antidepressants, daily anxiolytics and PRN anxiolytics are all positive predictors of daily antipsychotic use (all *p* < .001). Daily analgesics and PRN analgesics are negative predictors (both *p* < .001). These findings suggest that psychotropics purportedly relevant to mood improvement and anxiety reduction are likely to accompany daily antipsychotic use, whereas medications purportedly relevant to pain relief are less likely to occur in combination with daily antipsychotic medication.

PRN use of antidepressants (*p* < .001), anxiolytics (*p* < .001), analgesics (*p* < .001) and hypnotics (*p* < .001) are positive predictors of PRN use of antipsychotics. There are no significant relationships between daily use of other psychotropics and PRN use of antipsychotics. These findings indicate a clustering of PRN prescribing.

#### *2.2.2 Survival analyses*

*Suggestions for Addressing Clinical and Non-Clinical Issues in Palliative Care*

**Model term Coefficient Std.** 

Antidepress. Daily

Antidepress. PRN

Antidepress. None

Anxiolytic Daily

Anxiolytic None

Antidepress. Daily

Antidepress. PRN

Antidepress. None

Anxiolytic Daily

Anxiolytic None

**error**

Analgesic Daily −.134 .0347 .000 −.201 −.066 .875 Analgesic PRN −.384 .0701 .000 −.521 −.246 .681 Analgesic None 0 . . . . 1.00

Anxiolytic PRN .561 .0863 .000 .392 .730 1.753

Hypnotic Daily −.033 .0694 .634 −.169 .103 .967 Hypnotic PRN −.302 .2145 .160 −.722 .119 .740 Hypnotic None 0 . . . . 1.00

Analgesic Daily −.120 .1398 .389 −.394 .154 .887 Analgesic PRN .703 .1777 .000 .355 1.052 2.020 Analgesic None 0 . . . . 1.00

Anxiolytic PRN 1.399 .1907 .000 1.025 1.773 4.050

Hypnotic Daily −.392 .3289 .234 −1.036 .253 .676 Hypnotic PRN .986 .3710 .008 .259 1.713 2.680 Hypnotic None 0 . . . . 1.00

PRN Intercept −4.151 .1246 .000 −4.395 −3.907 .016

Daily Intercept −1.119 .0372 .000 −1.192 −1.046 .327

**Sig. 95% confidence interval**

.682 .0329 .000 .617 .746 1.977

−.242 .1705 .155 −.576 .092 .785

0 . . . . 1.00

.207 .0484 .000 .112 .302 1.230

0 . . . . 1.00

.054 .1330 .683 −.206 .315 1.056

2.378 .1898 .000 2.006 2.750 10.788

0 . . . . 1.00

−.312 .2373 .188 −.777 .153 .732

0 . . . . 1.00

**Lower Upper**

**Exponential coefficient**

**Antipsych. frequency**

in combination with PRN use of antipsychotics. Daily use of hypnotics has

approximately similar levels among residents with no of daily use of antipsychotic

*Fixed effects coefficients and odds ratios for prediction of antipsychotic frequency by frequencies of all other* 

**194**

medication.

*antipsychotic categories.*

**Table 3.**

Mortality during the 1-year follow-up period of data collection is 18.1% overall. The mortality rates for men and women are 21.1% and 16.3% respectively. The distribution of mortality across assessments indicates that 45% of residents died within 90 days of the admission assessment, with a decreasing proportion of deaths at each subsequent assessment.

The primary interval censored survival analysis shows a significant random effect for LTCHs *p* < .001. Because the same level of significance is present in all subsequent GLMM analyses, we need not report them henceforth. **Table 4** shows findings for the fixed effects. Unsurprisingly, the positive coefficient for the CHESS indicates higher mortality for residents at greater risk of mortality. The reference category for combinations of medications is the daily use of both antipsychotics and other psychotropics, which numerically is associated with the lowest level of mortality. This combination has significantly lower mortality (*p* < .005 or beyond) than any other combination except for those that combine no antipsychotics with daily psychotropics and PRN use of antipsychotics with daily psychotropics.

#### *Suggestions for Addressing Clinical and Non-Clinical Issues in Palliative Care*


#### **Table 4.**

*Fixed effect coefficients for the CHESS and combinations of antipsychotic (AP) and other psychotropic (PT) frequencies in prediction of mortality.*


#### **Table 5.**

*Fixed effect coefficients for combined categories of antipsychotic frequencies with other psychotropic medications.*

An implication is that daily use of psychotropics ameliorates mortality associated with antipsychotics to levels below that associated with no use of the latter.

A Bonferroni multiple comparison with the combination that includes neither antipsychotic nor any other psychotropic provides further support for this inference. The only other combination with significantly lower mortality than zero use of any psychotropic is that of no antipsychotics but daily use of other psychotropics (*p* < .001). Consequently, the latter ameliorates mortality below the level associated with zero psychotropic medications.

The next two analyses condense the preceding array of combinations into those associated with antipsychotic use (i.e., none, PRN and daily) and other psychotropic use, respectively (i.e., none, mixed, PRN and daily). Both analyses include the CHESS, with daily use as the reference category for the combinational variable.

**197**

**Table 7.**

*in prediction of mortality.*

*Effects of Antipsychotic Medication on Mortality in Long-Term Care Home Residents*

**error**

Intercept −1.879 .0262 .000 −1.930 −1.827 .15 CHESS .572 .0135 .000 .546 .598 1.77 No Psychotropics .294 .0455 .000 .205 .383 1.34 Mixed Psychotropics .457 .0578 .000 .344 .570 1.58 PRN Psychotropics .589 .0626 .000 .466 .712 1.80 Daily Psychotropics 0 . . . . 1.00

**Sig. 95% Confidence** 

**interval**

**Lower Upper**

**Exponential coefficient**

The findings in **Table 5** show the findings from the analysis of psychotropic use. In addition to significance for the CHESS, daily use of antipsychotics is associated with significantly lower mortality than no use or PRN use (*p* < .005 or beyond). Moreover, a Bonferroni multiple comparison shows that no use has a significantly lower level of mortality than PRN use. These findings replicate the trends for

**error**

Intercept −1.984 .0464 .000 −2.075 −1.893 .14 CHESS .575 .0135 .000 .549 .601 1.78 AP, None: AD, None .370 .0510 .000 .270 .470 1.45 AP, None: AD, PRN .718 .1374 .000 .448 .987 2.05 AP, None, AD, Daily .069 .0547 .207 −.038 .176 1.07 AP, PRN: AD, None .819 .1541 .000 .517 1.121 2.27 AP, PRN: AD, PRN 1.040 .2203 .000 .608 1.472 2.83 AP, PRN, AD, Daily .301 .2127 .157 −.116 .718 1.35 AP, Daily: AD, None .320 .0647 .000 .193 .447 1.38 AP, Daily: AD, PRN .625 .2955 .034 .046 1.204 1.87 AP, Daily, AD, Daily 0 . . . . 1.00

*Fixed effect coefficients for the CHESS and combinations of antipsychotic (AP) and antidepressant (AD) use* 

**Sig. 95% Confidence** 

**interval**

**Lower Upper**

**Exponential coefficient**

*Fixed effect coefficients for combined categories of other psychotropic medication use with antipsychotic use.*

**Table 6** shows findings from the analysis of the use of other psychotropics. With daily use as the reference category, no use, mixed use and PRN use are associated with higher levels of mortality (*p* < .005 or beyond). Sequential Bonferroni multiple comparisons of no, mixed and PRN use reveal higher mortality for PRN than no use (*p* < .001), with no comparison that involves mixed use significant at *p* < .01 level. These findings suggest that daily use of other psychotropics has ameliorative effects on mortality. **Figure 7** provides a graphic portrayal of the combined finding from last two analyses, indicating inverted-V or inverted-U structures corresponding to frequencies of no, mixed, PRN and daily use, with lowest frequencies associated

antipsychotic use reported in our earlier publication [1].

with daily use of other psychotropics.

**Fixed effects Coefficient Std.** 

*DOI: http://dx.doi.org/10.5772/intechopen.95388*

**Table 6.**

**Fixed effects Coefficient Std.** 

*Effects of Antipsychotic Medication on Mortality in Long-Term Care Home Residents DOI: http://dx.doi.org/10.5772/intechopen.95388*


**Table 6.**

*Suggestions for Addressing Clinical and Non-Clinical Issues in Palliative Care*

**error**

Intercept −1.938 .0412 .000 −2.019 −1.858 .14 CHESS .569 .0136 .000 .543 .596 1.77 AP, None: PT, None .366 .0600 .000 .248 .483 1.44 AP, None: PT, Mixed .552 .0776 .000 .400 .704 1.74 AP, None: PT, PRN .643 .0782 .000 .490 .797 1.90 AP, None: PT, Daily .084 .0459 .066 −.005 .174 1.09 AP, PRN: PT, None .999 .2851 .000 .441 1.558 2.72 AP, PRN: PT, Mixed .818 .2480 .001 .332 1.304 2.27 AP, PRN: PT, PRN .910 .1978 .000 .522 1.298 2.48 AP, PRN: PT, Daily .346 .1739 .047 .005 .687 1.41 AP, Daily: PT, None .273 .0944 .004 .088 .458 1.31 AP, Daily: PT, Mixed .421 .1036 .000 .218 .624 1.52 AP, Daily: PT, PRN .549 .1537 .000 .248 .850 1.73 AP, Daily: PT, Daily 0 . . . . 1.00

**Sig. 95% Confidence** 

**Sig. 95% Confidence** 

**interval**

**Lower Upper**

**interval**

**Lower Upper**

**Exponential coefficient**

**Exponential coefficient**

**Fixed effects Coefficient Std.** 

An implication is that daily use of psychotropics ameliorates mortality associated with antipsychotics to levels below that associated with no use of the latter.

*Fixed effect coefficients for combined categories of antipsychotic frequencies with other psychotropic* 

*Fixed effect coefficients for the CHESS and combinations of antipsychotic (AP) and other psychotropic (PT)* 

**error**

Intercept −1.846 .0355 .000 −1.915 −1.776 .16 CHESS .577 .0134 .000 .550 .603 1.78 No Antipsychotics .113 .0380 .003 .039 .188 1.12 PRN Antipsychotics .566 .1095 .000 .352 .781 1.76 Daily Antipsychotics 0 . . . . 1.00

A Bonferroni multiple comparison with the combination that includes neither antipsychotic nor any other psychotropic provides further support for this inference. The only other combination with significantly lower mortality than zero use of any psychotropic is that of no antipsychotics but daily use of other psychotropics (*p* < .001). Consequently, the latter ameliorates mortality below the level associated

The next two analyses condense the preceding array of combinations into those associated with antipsychotic use (i.e., none, PRN and daily) and other psychotropic use, respectively (i.e., none, mixed, PRN and daily). Both analyses include the CHESS, with daily use as the reference category for the combinational variable.

**196**

**Table 4.**

**Table 5.**

*medications.*

*frequencies in prediction of mortality.*

**Fixed effects Coefficient Std.** 

with zero psychotropic medications.

*Fixed effect coefficients for combined categories of other psychotropic medication use with antipsychotic use.*

The findings in **Table 5** show the findings from the analysis of psychotropic use. In addition to significance for the CHESS, daily use of antipsychotics is associated with significantly lower mortality than no use or PRN use (*p* < .005 or beyond). Moreover, a Bonferroni multiple comparison shows that no use has a significantly lower level of mortality than PRN use. These findings replicate the trends for antipsychotic use reported in our earlier publication [1].

**Table 6** shows findings from the analysis of the use of other psychotropics. With daily use as the reference category, no use, mixed use and PRN use are associated with higher levels of mortality (*p* < .005 or beyond). Sequential Bonferroni multiple comparisons of no, mixed and PRN use reveal higher mortality for PRN than no use (*p* < .001), with no comparison that involves mixed use significant at *p* < .01 level. These findings suggest that daily use of other psychotropics has ameliorative effects on mortality. **Figure 7** provides a graphic portrayal of the combined finding from last two analyses, indicating inverted-V or inverted-U structures corresponding to frequencies of no, mixed, PRN and daily use, with lowest frequencies associated with daily use of other psychotropics.


#### **Table 7.**

*Fixed effect coefficients for the CHESS and combinations of antipsychotic (AP) and antidepressant (AD) use in prediction of mortality.*

#### *Suggestions for Addressing Clinical and Non-Clinical Issues in Palliative Care*


#### **Table 8.**

*Fixed effect coefficients for the CHESS and combinations of antipsychotic (AP) and analgesic (AN) use in prediction of mortality.*


#### **Table 9.**

*Fixed effect coefficients for the CHESS and combinations of antipsychotic (AP) and anxiolytic (AX) use in prediction of mortality.*

The following GLMM interval censored survival analyses examine combinations of antipsychotic with separate types of other psychotropic. These combinations correspond to frequencies of usage outlined in last four columns of **Table 1**. All these analyses include the CHESS among the fixed effects, with daily usage of both

**199**

combinations.

*prediction of mortality.*

**Table 10.**

than the reference category.

antipsychotic or another psychotropic (*p* < .001).

*Effects of Antipsychotic Medication on Mortality in Long-Term Care Home Residents*

**error**

Intercept −1.707 .1230 .000 −1.948 −1.466 .18 CHESS .576 .0134 .000 .550 .602 1.78 AP, None: HY, None −.027 .1237 .828 −.269 .216 .97 AP, None: HY, PRN .657 .2081 .002 .249 1.065 1.93 AP, None, HY, Daily −.123 .1495 .411 −.416 .170 .88 AP, PRN: HY, None .450 .1633 .006 .130 .770 1.57 AP, PRN: HY, PRN .001 .5223 .999 −1.023 1.025 1.00 AP, PRN, HY, Daily .350 .5583 .531 −.744 1.444 1.42 AP, Daily: HY, None −.149 .1264 .239 −.397 .099 .86 AP, Daily: HY, PRN −.009 .4182 .982 −.829 .810 .99 AP, Daily, HY, Daily 0 . . . . 1.00

**Sig. 95% Confidence** 

**interval**

**Lower Upper**

**Exponential coefficient**

an antipsychotic and the other specified psychotropic as the reference category for

*Fixed effect coefficients for the CHESS and combinations of antipsychotic (AP) and hypnotic (HY) use in* 

**Tables 9** and **10** show findings for combinations of antipsychotic use with anxiolytic and hypnotic use, respectively. Neither psychotropic has a high prevalence of usage in LTCHs. The findings mainly indicate non-significant differences in mortality against the reference category. The significant differences include higher mortality than for the reference category for combinations that include PRN use of

A final analysis in this section relates mortality to the duration of residence in a LTCH. Because previous reviews indicate higher mortality during the beginning phase of antipsychotic use, we would be remiss not to examine such effects [10, 11]. We report at the beginning of this section that nearly half the deaths occurred within 90 days of the admission assessment. Consequently, the following GLMM multinomial analysis uses as the target variable categories of (1) death after the admission assessment, (2) death after subsequent assessments, with (3) absence of mortality as the reference category. Findings in **Table 11** for death after the initial assessment indicate significantly lower mortality for the daily antipsychotic with other psychotropic use combination than for any other combination (*p* < .005 and beyond). Bonferroni multiple comparison also shows that the no antipsychotic but other daily psychotropic use combination has lower mortality than the combination with neither antipsychotic nor other

**Tables 7**–**10** show fixed effect findings for combinations that include antidepressants, analgesics, anxiolytics and hypnotics respectively. **Tables 7** and **8** show coefficients for the combinations that include the most frequently used psychotropics. **Table 7** shows significantly lower mortality for a combination of daily antipsychotic with antidepressant use than for two of three combinations without antipsychotics (*p* < .001); the exception being a combination of no antipsychotics with daily antidepressants. **Table 8** shows comparable findings for the combination of daily antipsychotics with analgesic use. Also, every combination that includes PRN use of an antipsychotic and/or another psychotropic has significantly higher mortality

*DOI: http://dx.doi.org/10.5772/intechopen.95388*

**Fixed effects Coefficient Std.** 


*Effects of Antipsychotic Medication on Mortality in Long-Term Care Home Residents DOI: http://dx.doi.org/10.5772/intechopen.95388*

#### **Table 10.**

*Suggestions for Addressing Clinical and Non-Clinical Issues in Palliative Care*

**Error**

Intercept −1.891 .0450 .000 −1.979 −1.803 .15 CHESS .573 .0136 .000 .546 .599 1.77

AP, None: AN, PRN .566 .0714 .000 .426 .706 1.76

AP, PRN: AN, None .701 .2015 .001 .306 1.096 2.02 AP, PRN: AN, PRN .721 .2139 .001 .302 1.140 2.06 AP, PRN, AN, Daily .510 .1579 .001 .200 .819 1.67

AP, Daily: AN, PRN .546 .1117 .000 .327 .764 1.73

*Fixed effect coefficients for the CHESS and combinations of antipsychotic (AP) and analgesic (AN) use in* 

**error**

Intercept −1.925 .0886 .000 −2.099 −1.751 .15 CHESS .574 .0134 .000 .548 .601 1.78 AP, None: AX, None .199 .0898 .027 .023 .375 1.22 AP, None: AX, PRN .537 .1322 .000 .278 .797 1.71

AP, PRN: AX, None .546 .1503 .000 .251 .840 1.73 AP, PRN: AX, PRN 1.143 .2503 .000 .652 1.633 3.14 AP, PRN, AX, Daily .649 .4058 .110 −.146 1.444 1.91 AP, Daily: AX, None .081 .0941 .390 −.104 .265 1.08 AP, Daily: AX, PRN .302 .1580 .056 −.007 .612 1.35 AP, Daily, AX, Daily 0 . . . . 1.00

**Sig. 95% Confidence** 

.225 .0551 .000 .117 .333 1.25

.055 .0501 .276 −.044 .153 1.06

.012 .0705 .860 −.126 .151 1.01

0 . . . . 1.00

**Sig. 95% Confidence** 

.042 .1078 .695 −.169 .254 1.04

**interval**

**Lower Upper**

**Interval**

**Lower Upper**

**Exponential Coefficient**

**Exponential coefficient**

**Fixed Effects Coefficient Std.** 

AP, None: AN, None

AP, None, AN, Daily

AP, Daily: AN, None

AP, Daily, AN, Daily

*prediction of mortality.*

AP, None, AX, Daily

**Fixed effects Coefficient Std.** 

**Table 8.**

The following GLMM interval censored survival analyses examine combinations

of antipsychotic with separate types of other psychotropic. These combinations correspond to frequencies of usage outlined in last four columns of **Table 1**. All these analyses include the CHESS among the fixed effects, with daily usage of both

*Fixed effect coefficients for the CHESS and combinations of antipsychotic (AP) and anxiolytic (AX) use in* 

**198**

**Table 9.**

*prediction of mortality.*

*Fixed effect coefficients for the CHESS and combinations of antipsychotic (AP) and hypnotic (HY) use in prediction of mortality.*

an antipsychotic and the other specified psychotropic as the reference category for combinations.

**Tables 7**–**10** show fixed effect findings for combinations that include antidepressants, analgesics, anxiolytics and hypnotics respectively. **Tables 7** and **8** show coefficients for the combinations that include the most frequently used psychotropics. **Table 7** shows significantly lower mortality for a combination of daily antipsychotic with antidepressant use than for two of three combinations without antipsychotics (*p* < .001); the exception being a combination of no antipsychotics with daily antidepressants. **Table 8** shows comparable findings for the combination of daily antipsychotics with analgesic use. Also, every combination that includes PRN use of an antipsychotic and/or another psychotropic has significantly higher mortality than the reference category.

**Tables 9** and **10** show findings for combinations of antipsychotic use with anxiolytic and hypnotic use, respectively. Neither psychotropic has a high prevalence of usage in LTCHs. The findings mainly indicate non-significant differences in mortality against the reference category. The significant differences include higher mortality than for the reference category for combinations that include PRN use of antipsychotic or another psychotropic (*p* < .001).

A final analysis in this section relates mortality to the duration of residence in a LTCH. Because previous reviews indicate higher mortality during the beginning phase of antipsychotic use, we would be remiss not to examine such effects [10, 11]. We report at the beginning of this section that nearly half the deaths occurred within 90 days of the admission assessment. Consequently, the following GLMM multinomial analysis uses as the target variable categories of (1) death after the admission assessment, (2) death after subsequent assessments, with (3) absence of mortality as the reference category. Findings in **Table 11** for death after the initial assessment indicate significantly lower mortality for the daily antipsychotic with other psychotropic use combination than for any other combination (*p* < .005 and beyond). Bonferroni multiple comparison also shows that the no antipsychotic but other daily psychotropic use combination has lower mortality than the combination with neither antipsychotic nor other


#### **Table 11.**

*Fixed effect coefficients for the CHESS and combinations of antipsychotic (AP) and other psychotropic (PT) frequencies in the prediction of mortality after the first and later assessments.*

psychotropic use (*p* < .001). These findings are comparable to those reported for mortality over the full range of assessments. However, the findings for mortality after the admission assessment show no significant effects. We conclude, therefore, that effects associated with the medicinal combinations are stronger for mortality that occurs shortly after the admission assessment.

#### *2.2.3 Survival analysis against measures of change*

The preceding analyses relate mortality to CHESS scores and prescription profiles on the final assessment. Questions raised in our preceding chapter concern issues about causality with respect to relationships between health and medicinal

**201**

higher levels of mortality.

*Effects of Antipsychotic Medication on Mortality in Long-Term Care Home Residents*

**error**

Intercept −2.249 .0308 .000 −2.309 −2.188 .053

CHESS Change, None 0 . . . . 1.522

PRN Change, None 0 . . . . 1.00

*Fixed effect coefficients for the CHESS and PRN levels on penultimate assessment and their changes from the* 

**Sig 95% Confidence** 

1.958 .2346 .000 1.499 2.418 1.745

0 . . . . 2.474

2.015 .0756 .000 1.867 2.163 3.356

−1.052 .2904 .000 −1.621 −.482 4.148

.349 .1005 .001 .152 .545 7.995

0 . . . . 4.977

.648 .0731 .000 .505 .791 5.549

−.123 .1247 .325 −.367 .122 2.268

**interval**

**Lower Upper**

**Exponential coefficient**

prescriptions, with potential implications for subsequent mortality [1]. One hypothesis is that changes toward higher PRN prescribing explains both worsening

*penultimate to final assessments in the prediction of mortality after the final assessment.*

prescribing and subsequent mortality, such that any relationship between PRN and mortality is artifactual rather than actual. A third hypothesis is that changes toward higher PRN prescribing and changes in health conditions make independent

A second hypothesis is that worsening of health condition results in higher PRN

The following GLMM analysis tests these hypotheses with the data necessarily restricted to the penultimate and final assessments among residents with two or more assessments. With mortality as the target variable, the fixed effects include binary scores of (1) high-risk scores *versus* low risk on the CHESS (i.e., high risk scores are 4 or 5 on a 5-point scale) (2) the presence or absence of any PRN prescription on the penultimate assessment; and (3) changes in the CHESS index and (4) the PRN index from the penultimate to final assessment. **Table 12** shows the findings. Levels of mortality are significantly higher for high risk scores on the CHESS and the presence of PRN prescription. Changes on the CHESS toward worsening health are associated with significantly higher mortality, whereas changes toward lower risk scores are associated with significantly lower mortality, when compared an absence of change on the CHESS index. Compared to no change on the PRN index, an increased frequency of PRN prescription is associated with significantly increased mortality. Consequently, the findings indicate that detrimental levels and detrimental changes on the CHESS and PRN indexes contribute independently to

in health condition and subsequent mortality.

contributes to levels of mortality.

*DOI: http://dx.doi.org/10.5772/intechopen.95388*

CHESS Preceding,

CHESS Preceding,

CHESS Change, Worse

CHESS Change, Better

PRN Preceding, Present

PRN Preceding, Absent

PRN Change, Increase

PRN Change, Decrease

**Table 12.**

High

Low

**Model term Coefficient Std.** 


*Effects of Antipsychotic Medication on Mortality in Long-Term Care Home Residents DOI: http://dx.doi.org/10.5772/intechopen.95388*

#### **Table 12.**

*Suggestions for Addressing Clinical and Non-Clinical Issues in Palliative Care*

**error**

CHESS .557 .0230 .000 .512 .602 1.745 AP, None: PT, None .906 .0961 .000 .717 1.094 2.474 AP, None: PT, Mixed 1.211 .1223 .000 .971 1.450 3.356 AP, None: PT, PRN 1.423 .1187 .000 1.190 1.655 4.148 AP, None: PT, Daily .420 .0802 .000 .263 .577 1.522 AP, PRN: PT, None 2.079 .3858 .000 1.323 2.835 7.995 AP, PRN: PT, Mixed 1.605 .4089 .000 .803 2.406 4.977 AP, PRN: PT, PRN 1.714 .3130 .000 1.100 2.327 5.549 AP, PRN: PT, Daily .819 .2808 .004 .268 1.369 2.268 AP, Daily: PT, None .688 .1474 .000 .399 .977 1.991 AP, Daily: PT, Mixed .839 .1701 .000 .506 1.172 2.314 AP, Daily: PT, PRN .768 .2735 .005 .232 1.304 2.156 AP, Daily: PT, Daily 0 . . . . 1.00

Initial Intercept −2.932 .0717 .000 −3.072 −2.791 .053

Subsequent Intercept −2.315 .0558 .000 −2.424 −2.206 .099

CHESS .773 .0214 .000 .731 .815 2.166 AP, None: PT, None .006 .0908 .949 −.172 .184 1.006 AP, None: PT, Mixed .152 .1253 .225 −.094 .397 1.164 AP, None: PT, PRN .015 .1361 .912 −.252 .282 1.015 AP, None: PT, Daily −.140 .0636 .028 −.265 −.015 .869 AP, PRN: PT, None .206 .5757 .720 −.922 1.334 1.229 AP, PRN: PT, Mixed .626 .4299 .145 −.216 1.469 1.871 AP, PRN: PT, PRN .882 .3216 .006 .252 1.513 2.416 AP, PRN: PT, Daily .058 .2753 .834 −.482 .597 1.059 AP, Daily: PT, None .075 .1397 .589 −.198 .349 1.078 AP, Daily: PT, Mixed .331 .1522 .030 .033 .629 1.392 AP, Daily: PT, PRN .483 .2271 .033 .038 .928 1.621 AP, Daily: PT, Daily 0 . . . . 1.00

**Sig 95% Confidence interval**

**Lower Upper**

**Exponential coefficient**

**Assessment Model term Coefficient Std.** 

psychotropic use (*p* < .001). These findings are comparable to those reported for mortality over the full range of assessments. However, the findings for mortality after the admission assessment show no significant effects. We conclude, therefore, that effects associated with the medicinal combinations are stronger for

*Fixed effect coefficients for the CHESS and combinations of antipsychotic (AP) and other psychotropic (PT)* 

The preceding analyses relate mortality to CHESS scores and prescription profiles on the final assessment. Questions raised in our preceding chapter concern issues about causality with respect to relationships between health and medicinal

mortality that occurs shortly after the admission assessment.

*frequencies in the prediction of mortality after the first and later assessments.*

*2.2.3 Survival analysis against measures of change*

**200**

**Table 11.**

*Fixed effect coefficients for the CHESS and PRN levels on penultimate assessment and their changes from the penultimate to final assessments in the prediction of mortality after the final assessment.*

prescriptions, with potential implications for subsequent mortality [1]. One hypothesis is that changes toward higher PRN prescribing explains both worsening in health condition and subsequent mortality.

A second hypothesis is that worsening of health condition results in higher PRN prescribing and subsequent mortality, such that any relationship between PRN and mortality is artifactual rather than actual. A third hypothesis is that changes toward higher PRN prescribing and changes in health conditions make independent contributes to levels of mortality.

The following GLMM analysis tests these hypotheses with the data necessarily restricted to the penultimate and final assessments among residents with two or more assessments. With mortality as the target variable, the fixed effects include binary scores of (1) high-risk scores *versus* low risk on the CHESS (i.e., high risk scores are 4 or 5 on a 5-point scale) (2) the presence or absence of any PRN prescription on the penultimate assessment; and (3) changes in the CHESS index and (4) the PRN index from the penultimate to final assessment. **Table 12** shows the findings.

Levels of mortality are significantly higher for high risk scores on the CHESS and the presence of PRN prescription. Changes on the CHESS toward worsening health are associated with significantly higher mortality, whereas changes toward lower risk scores are associated with significantly lower mortality, when compared an absence of change on the CHESS index. Compared to no change on the PRN index, an increased frequency of PRN prescription is associated with significantly increased mortality. Consequently, the findings indicate that detrimental levels and detrimental changes on the CHESS and PRN indexes contribute independently to higher levels of mortality.

## **2.3 Discussion**

Our previous research with this database [1] includes a number of resident-level and facility-level control variables from the RAI 2.0. The analyses reported here simplify the presentation of results by inclusion of only the CHESS as a control variable. The justification is that unreported analyses, which included a wider range of fixed effect predictors of mortality, did not substantially alter the present findings. We should also mention findings from unreported analyses with Cox regression, which is a common form of survival analysis that takes no account for correlated error in SPSS 25. Despite this limitation, the findings with Cox regression are otherwise comparable to those reported here.

The present findings indicate that approximately 30% of residents are in receipt of antipsychotic medication, with more than 99% of those residents in receipt of at least one other psychotropic medication. The most frequently used among the latter are antidepressants and analgesics. The GLMM analysis in **Table 3** indicates that psychotropics with positive effects on mood and anxiety are frequently combined with daily use of antipsychotics, whereas analgesics are more frequent in residents without antipsychotic usage. PRN use of other types of psychotropic significantly predicts PRN use of antipsychotics, which indicates that residents typically receive PRN prescription for multiple types of psychotropic medication.

To our knowledge, the study presented here is the first to examine how concurrent prescriptions of other psychotropics can affect elevated mortality among the elderly, which is attributed in many previous studies to the use of antipsychotics. Although limitations in present data includes absence of information on the types and dosages of psychotropics, a limitation common to previous studies is an absence of information on the frequencies of usage. Although prior evidence indicates the good overall quality of RAI 2.0 data [2], a limitation for present purposes is an absence of information about medicinal use prior to admission. A consequence is uncertainty about whether high mortality shortly after admission reflects effects associated with short-term antipsychotic use, relocation to a LTCH, or other unknown effects. However, the findings reported in **Table 12** on residents with at least two RAI 2.0 assessments indicate that changes in prescribing practices do have effects on mortality beyond those associated with changes in high risk health conditions measured by the CHESS. Consequently, we conclude that the relationship between PRN usage and mortality is one of primary determination, rather than secondary to the relationship between declining health and mortality.

The overall findings on mortality support our hypotheses that daily use of other psychotropics may ameliorate mortality levels associated with antipsychotic use, whereas PRN use of other psychotropics augments that mortality. **Figure 7** provides a cogent illustration of the supportive findings. The specific psychotropics that support amelioration with daily use are antidepressants and analgesics, whereas concurrent PRN use of analgesics, anxiolytics and hypnotics are associated with augmented mortality. However, despite the high percentage of death among LTCH residents with PRN prescriptions on the final assessment, it must be remembered that only 12.9% are in receipt of such prescription.

Implications of the findings are that retrospective studies may incorrectly estimate the mortality associated with antipsychotic prescriptions by failure to take account of the deleterious effects of PRN usage and the beneficial effects of daily usage of other psychotropics. We reasoned in our previous chapter that the clinical rationale for psychotropic prescription is to renormalize disturbances to a resident's equilibrium (e.g., aggression, depression, pain, anxiety, insomnia), with

**203**

*Effects of Antipsychotic Medication on Mortality in Long-Term Care Home Residents*

such disequilibrium considered a risk to wellbeing and mortality [1]. Successful treatment is associated with regained equilibrium after adaptation to regular prescription of the requisite medication. However, intermittent medication usage is antagonistic to adaptation, may exacerbate disequilibrium, with an elevation of mortality risk. Consequently, implications for caregiving of residents with BPSD may include daily antipsychotic and other daily psychotropic usage if non-pharmaceutical intervention fails to bring relief, but should avoid PRN usage of any form of

*Percentage mortality for frequency combinations of antipsychotic with other psychotropic medication.*

Behavioral disturbance is common among residents with dementia in LTCH. Such disturbance is associated with poor quality of life, caregiver burden and adverse health care outcomes. Although non-pharmacological procedures are recommended as the first line of treatment [15], the usual treatment in LTCHs includes the use of antipsychotics despite limited evidence for effectiveness and health outcomes reported to include elevated mortality. The research described here suggests that daily use of antipsychotics with daily use of other psychotropics (particularly antidepressants and analgesics) attenuate mortality whereas concurrent combinations that include PRN usage exacerbate mortality. The implications for caregiving

All the authors contributed to the research and manuscript preparation, and verified their authorship of this chapter. The authors wish to thank the editors, Robert Reynolds and Steven Day, for very helpful comments on an earlier draft.

include avoidance of PRN prescriptions of psychotropic medications.

*DOI: http://dx.doi.org/10.5772/intechopen.95388*

psychotropic medication.

**Acknowledgements**

**Conflict of interest**

No author has any conflict of interest.

**3. Conclusions**

**Figure 7.**

*Effects of Antipsychotic Medication on Mortality in Long-Term Care Home Residents DOI: http://dx.doi.org/10.5772/intechopen.95388*

#### **Figure 7.**

*Suggestions for Addressing Clinical and Non-Clinical Issues in Palliative Care*

are otherwise comparable to those reported here.

between declining health and mortality.

that only 12.9% are in receipt of such prescription.

Our previous research with this database [1] includes a number of resident-level and facility-level control variables from the RAI 2.0. The analyses reported here simplify the presentation of results by inclusion of only the CHESS as a control variable. The justification is that unreported analyses, which included a wider range of fixed effect predictors of mortality, did not substantially alter the present findings. We should also mention findings from unreported analyses with Cox regression, which is a common form of survival analysis that takes no account for correlated error in SPSS 25. Despite this limitation, the findings with Cox regression

The present findings indicate that approximately 30% of residents are in receipt of antipsychotic medication, with more than 99% of those residents in receipt of at least one other psychotropic medication. The most frequently used among the latter are antidepressants and analgesics. The GLMM analysis in **Table 3** indicates that psychotropics with positive effects on mood and anxiety are frequently combined with daily use of antipsychotics, whereas analgesics are more frequent in residents without antipsychotic usage. PRN use of other types of psychotropic significantly predicts PRN use of antipsychotics, which indicates that residents typically receive PRN prescription for multiple types of psychotro-

To our knowledge, the study presented here is the first to examine how concurrent prescriptions of other psychotropics can affect elevated mortality among the elderly, which is attributed in many previous studies to the use of antipsychotics. Although limitations in present data includes absence of information on the types and dosages of psychotropics, a limitation common to previous studies is an absence of information on the frequencies of usage. Although prior evidence indicates the good overall quality of RAI 2.0 data [2], a limitation for present purposes is an absence of information about medicinal use prior to admission. A consequence is uncertainty about whether high mortality shortly after admission reflects effects associated with short-term antipsychotic use, relocation to a LTCH, or other unknown effects. However, the findings reported in **Table 12** on residents with at least two RAI 2.0 assessments indicate that changes in prescribing practices do have effects on mortality beyond those associated with changes in high risk health conditions measured by the CHESS. Consequently, we conclude that the relationship between PRN usage and mortality is one of primary determination, rather than secondary to the relationship

The overall findings on mortality support our hypotheses that daily use of other psychotropics may ameliorate mortality levels associated with antipsychotic use, whereas PRN use of other psychotropics augments that mortality. **Figure 7** provides a cogent illustration of the supportive findings. The specific psychotropics that support amelioration with daily use are antidepressants and analgesics, whereas concurrent PRN use of analgesics, anxiolytics and hypnotics are associated with augmented mortality. However, despite the high percentage of death among LTCH residents with PRN prescriptions on the final assessment, it must be remembered

Implications of the findings are that retrospective studies may incorrectly estimate the mortality associated with antipsychotic prescriptions by failure to take account of the deleterious effects of PRN usage and the beneficial effects of daily usage of other psychotropics. We reasoned in our previous chapter that the clinical rationale for psychotropic prescription is to renormalize disturbances to a resident's equilibrium (e.g., aggression, depression, pain, anxiety, insomnia), with

**2.3 Discussion**

pic medication.

**202**

*Percentage mortality for frequency combinations of antipsychotic with other psychotropic medication.*

such disequilibrium considered a risk to wellbeing and mortality [1]. Successful treatment is associated with regained equilibrium after adaptation to regular prescription of the requisite medication. However, intermittent medication usage is antagonistic to adaptation, may exacerbate disequilibrium, with an elevation of mortality risk. Consequently, implications for caregiving of residents with BPSD may include daily antipsychotic and other daily psychotropic usage if non-pharmaceutical intervention fails to bring relief, but should avoid PRN usage of any form of psychotropic medication.

#### **3. Conclusions**

Behavioral disturbance is common among residents with dementia in LTCH. Such disturbance is associated with poor quality of life, caregiver burden and adverse health care outcomes. Although non-pharmacological procedures are recommended as the first line of treatment [15], the usual treatment in LTCHs includes the use of antipsychotics despite limited evidence for effectiveness and health outcomes reported to include elevated mortality. The research described here suggests that daily use of antipsychotics with daily use of other psychotropics (particularly antidepressants and analgesics) attenuate mortality whereas concurrent combinations that include PRN usage exacerbate mortality. The implications for caregiving include avoidance of PRN prescriptions of psychotropic medications.

#### **Acknowledgements**

All the authors contributed to the research and manuscript preparation, and verified their authorship of this chapter. The authors wish to thank the editors, Robert Reynolds and Steven Day, for very helpful comments on an earlier draft.

## **Conflict of interest**

No author has any conflict of interest.
