A prospective study of symptoms, function, and medication use during acute illness in nursing home residents: design, rationale and cohort description
© Hung et al; licensee BioMed Central Ltd. 2010
Received: 20 October 2009
Accepted: 14 July 2010
Published: 14 July 2010
Nursing home residents are at high risk for developing acute illnesses. Compared with community dwelling adults, nursing home residents are often more frail, prone to multiple medical problems and symptoms, and are at higher risk for adverse outcomes from acute illnesses. In addition, because of polypharmacy and the high burden of chronic disease, nursing home residents are particularly vulnerable to disruptions in transitions of care such as medication interruptions in the setting of acute illness. In order to better estimate the effect of acute illness on nursing home residents, we have initiated a prospective cohort which will allow us to observe patterns of acute illnesses and the consequence of acute illnesses, including symptoms and function, among nursing home residents. We also aim to examine the patterns of medication interruption, and identify patient, provider and environmental factors that influence continuity of medication prescribing at different points of care transition.
This is a prospective cohort of nursing home residents residing in two nursing homes in a metropolitan area. Baseline characteristics including age, gender, race, and comorbid conditions are recorded. Participants are followed longitudinally for a planned period of 3 years. We record acute illness incidence and characteristics, and measure symptoms including depression, pain, withdrawal symptoms, and function using standardized scales.
76 nursing home residents have been followed for a median of 666 days to date. At baseline, mean age of residents was 74.4 (± 11.9); 32% were female; 59% were white. The most common chronic conditions were dementia (41%), depression (38%), congestive heart failure (25%) and chronic obstructive lung disease (27%). Mean pain score was 4.7 (± 3.6) on a scale of 0 to 10; Geriatric Depression Scale (GDS-15) score was 5.2 (± 4.4). During follow up, 138 acute illness episodes were identified, for an incidence of 1.5 (SD 2.0) episodes per resident per year; 74% were managed in the nursing home and 26% managed in the acute care setting.
In this report, we describe the conceptual model and methods of designing a longitudinal cohort to measure acute illness patterns and symptoms among nursing home residents, and describe the characteristics of our cohort at baseline. In our planned analysis, we will further estimate the effect of the use and interruption of medications on withdrawal and relapse symptoms and illness outcomes.
Nursing home residents are at high risk for developing acute illnesses [1, 2]. Acute illnesses in older adults often are associated with complications, such as functional decline and death [3–5]. Although the consequences of acute illnesses and hospitalizations among community dwelling older adults are well described [3–5], less is known about the consequences of acute illnesses among nursing home residents. Compared with community dwelling adults, nursing home residents are often more frail, prone to multiple medical problems and symptoms, and are at higher risk for adverse outcomes from acute illnesses [1, 2].
In the setting of acute illness, because of frailty and high burden of chronic disease, nursing home residents are particularly vulnerable to disruptions in transitions of care such as medication interruptions due to inadequate reconciliation [6–8]. In addition, interruption of medications which act on the central nervous system (CNS), including opioid analgesics, antidepressants and antipsychotic medications, confer a risk of adverse withdrawal events [9–13]. These medications are commonly used to manage pain, depression, psychosis and other symptoms among nursing home residents [9–13]. Interruptions of these medications, which act on the central nervous system, can lead to withdrawal syndromes, which often include distressing symptoms such as nausea, vomiting, anxiety, agitation, tremor and restlessness [14–16].
In order to better estimate the effect of acute illness on nursing home residents, we have initiated a study which will allow us to observe patterns of acute illnesses and the consequence of acute illnesses, including symptoms and function, among nursing home residents. We also aim to examine the patterns of CNS medication interruption, and identify patient, provider and environmental factors that influence continuity of medication prescribing at different points of care transition.
The study is a prospective observational study of nursing home residents in 2 nursing homes in metropolitan New York--Jewish Home Lifecare (JHL), New York, NY and the James J. Peters VA (JJP VA) Community Living Center (CLC) in Bronx, NY. These nursing homes were chosen because during acute illness episodes, residents needing hospital care are referred predominantly to the Mount Sinai Hospital for JHL residents, and to the James J Peters VA Medical Center for JJP VA CLC residents; thus we are able to follow residents at these hospitals, if necessary, during their acute illnesses to monitor withdrawal of CNS medications and to measure outcomes.
Residents are eligible to be enrolled in the study if they are receiving opioids, antidepressants, or antipsychotics on a routine basis for a duration of time considered to be a minimal therapeutic trial or in which tolerance develops. Because of the differences in pharmacokinetics and biologic effects among the 3 drug classes, a minimal therapeutic trial of 14, 30 and 7 days was selected for opioids, antidepressants, and antipsychotics respectively. We are including residents taking more than one medication in a class, or more than one class of medication if there are no known interactions between the medications. We are excluding residents receiving antidepressants who score fewer than 21 points on the Mini-Mental Status Examination  because the assessment of symptoms of depression, which is a main outcome, among those with more severe degrees of dementia, is less reliable. We are excluding residents who have an acute medical illness (defined below) at the time of screening and rescreening them for enrollment after it has resolved. Informed consent is obtained from residents or proxies. The study was approved by the Institutional Review Board at JHL and JJP VA Medical Center.
Acute Illness Surveillance and Points of Care Transition
Acute illness surveillance is performed twice weekly at the nursing home through communication with nursing home nursing staff and medical providers using established clinical criteria  for incipient cases. The clinical criteria for acute illness are meant to be sensitive for all acute medical problems experienced by nursing home residents and include clinical symptoms such as chest pain, dyspnea, diarrhea, acute change in mental status; clinical signs such as persistent increase or decrease in blood pressure, fever or hypothermia; and abnormalities in laboratory values such as a drop in hematocrit > 5 points with signs of acute bleeding. We follow patients for 14 days after illness onset, and if applicable, an additional 14 days each after hospital admission and hospital discharge. During each follow-up interval we assess the following signs and symptoms by patient and staff interview in the nursing home or in the hospital: pain, delirium, and withdrawal symptoms including gastrointestinal and cardiopulmonary signs and symptoms three times weekly, and mood and behavior once weekly, using validated instruments adapted for this population described below.
Baseline demographic information including age, gender, and race of each participant is collected. In addition, at baseline we collect information on chronic medical conditions and medication use through medical record abstraction, and on physical and cognitive function by interviews with patients, or proxies, and nursing home staff. Functional status is measured using items from the Minimum Data Set Activities of Daily Living Scale (MDS-ADL) adapted for interview with nursing home staff . The MDS-ADL scale ranges from 0 to 6 with higher scores indicating poorer functional status. Cognitive function is measured using items from the Minimum Data Set Cognitive performance scale (MDS-CPS)  adapted for interview with nursing home staff and from the Mini Mental Status Examination (MMSE) . Illness severity is measured using a physiologic measure, the Inpatient Physiologic Failure Score (IPFS) , which is adapted and validated for use in the elderly population. In the setting of acute illness, participants are assessed for delirium using the Confusion Assessment Method (CAM) .
Withdrawal symptoms from opiate withdrawal are measured using the Clinical Opiate Withdrawal Scale (COWS) , which contains measurements of several common signs and symptoms of withdrawal including tachycardia, sweating, restlessness, tremor, yawning, anxiety or irritability, gastrointestinal upset, pupil dilation, gooseflesh skin, running nose or tearing, and bone or joint aches. Scores on this scale vary from 0 to 48 with higher scores indicating more severe withdrawal. Withdrawal symptoms from antidepressants are measured using the Discontinuation Emergent Signs and Symptoms (DESS) scale . We modified the scale to include only items within the proposed diagnostic criteria for Serotonin Reuptake Inhibitor syndrome , which includes the following symptoms--headache, insomnia, irritability, anxiety, fatigue, paresthesias, tremors, visual changes, dizziness, nausea, diarrhea, stomach cramps, chills, flushing and gait instability. We classify delirium as a separate complication from withdrawal, although we consider it consistent with withdrawal.
Relapse symptoms such as depression, psychosis and pain are measured using standardized instruments. Depression is measured using the Geriatric Depression Scale (GDS) , a 15-point scale for measuring depression in the elderly; a score of 5 or above indicates a positive screen for depression. Psychosis and disturbed behavior are measured using the Cohen Mansfield Agitation Inventory (CMAI) . This scale contains 29 behaviors including verbal and physical behaviors, examples of which are repetitiveness, screaming, verbal aggression, and wandering. On the scale, these behaviors are measured on how frequently they are observed. Scores range from 29 to 103, with higher scores indicating more agitation. We used this scale as a measurement of the effect of antipsychotic cessation, because antipsychotic withdrawal has been associated with relapse symptoms , which can be reliably measured using this scale.
Pain is measured using a variety of measures based on whether the participant can reliably indicate their pain and severity. For participants who can indicate their pain, a modified Brief Pain Inventory (BPI)  is used, which measures the location and the severity of pain experienced currently and also in the past 24 hours. Participants are also asked to indicate how much their pain has interfered with their mood, sleep, walking ability and other activities. If the participant is unable to complete the BPI, a McGill Present Pain Intensity Scale  from 0 to 5 is attempted, and if unable to complete this, the participant is asked if they have pain currently (yes/no). If the participant is unable to provide answers regarding their pain, the checklist of nonverbal pain indicators (CNPI)  is used. Nursing staff are asked if they have observed any vocal complaints including verbal complaints and non-verbal sounds such as moans or groans, facial grimaces, restlessness, bracing, and rubbing during activity or rest.
Baseline demographic characteristics and symptoms measured on scales described above are summarized using descriptive statistics. Characteristics of acute illness including illness type and severity, are described. Planned analyses include estimation of the effect of acute illness on functional decline by comparing magnitude of functional change during periods with acute illness with periods without acute illness. Additional analyses include a description of the pattern of interruption of CNS medications during the acute illness and, to examine predictors of CNS medication interruption, estimation of a multivariable logistic regression model using occurrence of interruption in CNS medication as dependent variable, and patient, illness, and provider characteristics as independent variables. We will select independent variables to include in the model based on whether a factor is associated with the outcome in univariate analysis.
To examine the impact of CNS medication interruption on patient outcomes, we plan to estimate multivariable logistic regression models with pain, depression and disturbed behavior at the moderate or severe level as dependent variables and interruption in CNS medications as independent variable. Covariates will include patient and illness characteristics outlined in Figure 1. Furthermore, we plan to describe the effect of the interruption of CNS medications on hospital use, illness duration and functional outcomes, using similar multivariable regression models.
We also plan to compare proportions of patients who developed withdrawal symptoms who had medication interruption to those who did not have medication interruption. For the sample size of 200 AI episodes, we estimated that 20% of them would have an interruption of CNS medications. Assuming that the proportion who would have withdrawal symptoms without interruption of CNS medications (due to other causes such as the acute illness itself) to be 15%, this will provide 83% power (with an alpha of 0.05) to detect an absolute difference of 25% in the proportion with interruption of CNS medications who develops withdrawal symptoms (with a proportion of 40%). To estimate the effect of acute illness on function, we collected functional status data at the time of enrollment, subsequently at 3 month intervals, and at the time of illness onset and 14 days after illness. We plan to use a linear mixed model to account for such repeated measurements.
Baseline characteristics of nursing home residents in the cohort
(n = 76)
(n = 46)
(N = 30)
Age (mean (SD))
Comorbid Conditions (%)
Medications (total no. ± SD)
7.6 ± 3.2
8.0 ± 3.6
6.8 ± 2.6
CNS Medications (%)
Any combination of 2 or more
Duration of NH residence
(Median, Inter Quartile Range)
Number of hospitalization in the year prior to enrollment ± SD
1.2 ± 1.1
1.5 ± 1.2
0.7 ± 0.5
Number of acute illness episodes (per resident per year)
1.5 ± 2.0
1.7 ± 2.2
1.0 ± 1.3
2.3 ± 2.1
2.2 ± 2.3
2.4 ± 2.0
Cognitive function (MDS-CPS)
1.1 ± 1.6
1.0 ± 1.8
1.3 ± 1.5
5.2 ± 4.4
5.5 ± 4.4
4.8 ± 4.5
Pain (0-10 scale)
4.7 ± 3.6
5.5 ± 3.3
3.4 ± 3.7
Psychosis and disturbed behavior (CMAI)
35.8 ± 8.1
35.9 ± 7.9
35.7 ± 8.6
Characteristics of Acute Illness Episodes
Managed at NH
Managed in Hospital
Number of Acute Illness Episodes
IPFS score (SD), Illness Severity
Urinary tract infection
List of research questions potentially addressed in this cohort study
A. Health services and quality of care
1. Among nursing home residents, what is the impact of acute illness, managed at the nursing home or in the hospital, on patient outcomes including function and mortality?
2. What is the impact of acute illness on symptoms such as pain, depression, agitation?
3. What is the effect of acute illness on functional status, which is a publicly-reported measure of nursing home quality?
4. How often are CNS medications interrupted during care transition periods and what are the factors affecting the pattern of medication interruption?
B. Clinical decision
1. What is the balance of benefit and risk of holding opiates and other CNS medications during acute illness episodes?
1. What is the longitudinal symptom burden, including pain, depression, agitation and others, among nursing home residents?
Our study also highlights some methodological features which may be utilized by other investigators designing similar studies in this population. In order to determine the impact of acute illness, the research team actively surveys for the occurrence of acute illness. Previous studies relying on medical records or referrals from providers are likely to miss acute illnesses which are less severe or are treated in the nursing home setting. Because reliable reports of symptoms such as pain, delirium, and withdrawal symptoms require real-time ascertainment, the active surveillance by the research team is essential to capture acute illnesses and symptoms prospectively. In addition, because transitions of care across multiple settings occur in nursing home residents experiencing acute illnesses, it is essential for the research team to conduct symptom monitoring in these different settings. Symptoms are assessed frequently in this study because symptoms of withdrawal can occur acutely and resolve in a short period of time.
Furthermore, the choice of the two nursing homes in our study also allows us to examine the effect of an integrated medical system with electronic medical record sharing on medication interruption and continuity of care. Medication and treatment information is readily available across nursing home and hospital settings through an electronic medical record system in the VA-based nursing home. On the other hand, JHL does not have an integrated electronic system. Therefore, providers rely on traditional methods of communication using transition documents or telephone communication.
A limitation of our study is that our examination of different levels of factors affecting medication interruption is limited by the proportion of AI with medication interruption. The analysis of the effects of multiple factors may require a larger sample size. However, we will likely be able to observe clinically important effects that are of larger magnitude. In addition, considering the two cohorts included in the sample, there were significant differences in the characteristics of the VA cohort compared with the JHL cohort. The VA cohort was younger, more likely to be male, black and less likely to have dementia. The different characteristics of the VA cohort may limit generalizability to community nursing homes, but the inclusion of the VA cohort also help complement the gender and racial makeup of the study sample.
In this paper, we described the methods of our study in detail and our cohort characteristics. The aim of our study is to inform nursing home physicians the effect of acute illness on symptoms, function change and medication use in nursing home residents. Considering that nursing home residents are likely to have high symptom burden, and to be vulnerable to acute illness and to disruptions in care across care settings, the study has the potential to improve the care of nursing home residents across care settings.
The authors thank Jennifer Kwak, Julia Siegel and Jessica Singleton for data collection, and Daniel Signor for database management support.
- Alessi CA, Harker JO: A prospective study of acute illness in the nursing home. Aging (Milano). 1998, 10: 479-89.Google Scholar
- Barker WH, Zimmer JG, Hall WJ, Ruff BC, Freundlich CB, Eggert GM: Rates, patterns, causes, and costs of hospitalization of nursing home residents: a population-based study. Am J Public Health. 1994, 84: 1615-20. 10.2105/AJPH.84.10.1615.View ArticlePubMedPubMed CentralGoogle Scholar
- Sager MA, Franke T, Inouye SK, Landefeld CS, Morgan TM, Rudberg MA, Sebens H, Winograd CH: Functional outcomes of acute medical illness and hospitalization in older persons. Arch Intern Med. 1996, 156: 645-52. 10.1001/archinte.156.6.645.View ArticlePubMedGoogle Scholar
- Gill TM, Williams CS, Tinetti ME: The combined effects of baseline vulnerability and acute hospital events on the development of functional dependence among community-living older persons. J Gerontol A Biol Sci Med Sci. 1999, 54: M377-83.View ArticlePubMedGoogle Scholar
- Covinsky KE, Justice AC, Rosenthal GE, Palmer RM, Landefeld CS: Measuring prognosis and case mix in hospitalized elders. The importance of functional status. J Gen Intern Med. 1997, 12: 203-8.PubMedPubMed CentralGoogle Scholar
- Boockvar K, Fishman E, Kyriacou CK, Monias A, Gavi S, Cortes T: Adverse events due to discontinuations in drug use and dose changes in patients transferred between acute and long-term care facilities. Arch Intern Med. 2004, 164: 545-50. 10.1001/archinte.164.5.545.View ArticlePubMedGoogle Scholar
- Coleman EA, Smoth JD, Raha D, Min SJ: Posthospital medication discrepancies: prevalence and contributing factors. Arch Intern Med. 2005, 165: 1842-7. 10.1001/archinte.165.16.1842.View ArticlePubMedGoogle Scholar
- Boockvar KS, Liu S, Goldstein N, Nebeker J, Siu A, Fried T: Prescribing discrepancies likely to cause adverse drug events after patient transfer. Qual Saf Health Care. 2009, 18: 32-36. 10.1136/qshc.2007.025957.View ArticlePubMedPubMed CentralGoogle Scholar
- Won AB, Lapane KL, Vallow S, Schein J, Morris JN, Lipsitz LA: Persistent nonmalignant pain and analgesic prescribing patterns in elderly nursing home residents. J Am Geriatr Soc. 2004, 52: 867-874. 10.1111/j.1532-5415.2004.52251.x.View ArticlePubMedGoogle Scholar
- Teno JM, Weitzen S, Wetle T, Mor V: Persistent pain in nursing home residents. JAMA. 2001, 285: 2081-10.1001/jama.285.16.2081-a.View ArticlePubMedGoogle Scholar
- Liperoti R, Mor V, Lapane KL, Pedone C, Gambassi G, Bernabei R: The use of atypical antipsychotics in nursing homes. J Clin Psychiatry. 2003, 64: 1106-1112. 10.4088/JCP.v64n0918.View ArticlePubMedGoogle Scholar
- Brown MN, Lapane KL, Luisi AF: The management of depression in older nursing home residents. J Am Geriatr Soc. 2002, 50: 69-76. 10.1046/j.1532-5415.2002.50010.x.View ArticlePubMedGoogle Scholar
- Webber AP, Martin JL, Harker JO, Josephson KR, Rubenstein LZ, Alessi CA: Depression in older patients admitted for postacute nursing home rehabilitation. J Am Geriatr Soc. 2005, 53: 1017-1022. 10.1111/j.1532-5415.2005.53322.x.View ArticlePubMedGoogle Scholar
- Dilsaver SC: Withdrawal phenomena associated with antidepressant and antipsychotic agents. Drug Saf. 1994, 10: 103-114. 10.2165/00002018-199410020-00002.View ArticlePubMedGoogle Scholar
- Kosten TR, O'Connor PG: Management of drug and alcohol withdrawal. N Engl J Med. 2003, 348: 1786-1795. 10.1056/NEJMra020617.View ArticlePubMedGoogle Scholar
- Michelson D, Fava M, Amsterdam J, Apter J, Londborg P, Tamura R, Tepner RG: Interruption of selective serotonin reuptake inhibitor treatment. Double-blind, placebo-controlled trial. Br J Psychiatry. 2000, 176: 363-368. 10.1192/bjp.176.4.363.View ArticlePubMedGoogle Scholar
- Tamayo-Sarver JH, Dawson NV, Cyndulka RK, Wigton RS, Baker DW: Variability in emergency physician decision making about prescribing opioid analgesics. Ann Emerg Med. 2004, 43: 483-93. 10.1016/j.annemergmed.2003.10.043.View ArticlePubMedGoogle Scholar
- Folstein MF, Folstein SE, Mchugh PR: Mini-mental state. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research. 1975, 12: 189-198. 10.1016/0022-3956(75)90026-6.View ArticlePubMedGoogle Scholar
- Levenson S: Medical direction in long-term care: A guidebook for the future. 1993, Durham, NC: Carolina Academic Press, 2Google Scholar
- Morris JN, Fris BE, Morris SA: Scaling ADLs within the MDS. J Gerontol A Biol Sci Med Sci. 1999, 54: M546-553.View ArticlePubMedGoogle Scholar
- Morris JN, Fries BE, Mehr DR, Hawes C, Phillips C, Mor V, Lipsitz LA: MDS cognitive Performance Scale. J Gerontol. 1994, 49: M174-182.View ArticlePubMedGoogle Scholar
- Gray LK, Smyth KA, Palmer RM, Zhu X, Callahan JM: Heterogeneity in older people: examining physiologic failure, age and comorbidity. J Am Geriatr Soc. 2002, 50: 1955-61. 10.1046/j.1532-5415.2002.50606.x.View ArticlePubMedGoogle Scholar
- Inouye SK, van Dyck CH, Alessi CA, Balkin S, Siegal AP, Horwitz RI: Clarifying confusion: the confusion assessment method. A new method for detection of delirium. Annals of Internal Medicine. 1990, 113: 941-948.View ArticlePubMedGoogle Scholar
- Wesson DR, Ling W: The Clinical Opiate Withdrawal Scale (COWS). J Psychoactive Drugs. 2003, 35: 253-259.View ArticlePubMedGoogle Scholar
- Schatzberg A: Antidepressant Discontinuation Syndrome: Consensus Panel Recommendations for Clinical Management and Additional Research. J Clin Psychiatry. 2006, 67 (S4): 27-30.PubMedGoogle Scholar
- Black K, Shea C, Dursun S, Kutcher S: Selective serotonin reuptake inhibitor discontinuation syndrome: proposed diagnostic criteria. J Psychiatry Neurosci. 2000, 25: 255-61.PubMedPubMed CentralGoogle Scholar
- Yesavage JA: Geriatric Depression Scale. Psychopharmacol Bull. 1988, 24: 709-711.PubMedGoogle Scholar
- Cohen-Mansfield J, Marx MS, Rosenthal AS: A description of agitation in a nursing home. J Gerontol. 1989, 44: M77-84.View ArticlePubMedGoogle Scholar
- Margolese H, Chouinard G, Beauclair L, Bellanger MC: Therapeutic tolerance and rebound psychosis during quetiapine maintenance monotherapy in patients. J Clin Psychopharmacol. 2002, 20: 489-90.Google Scholar
- Mendoza T, Mayne T, Rublee D, Cleeland C: Reliability and validity of a modified Brief Pain Inventory short form in patients with osteoarthritis. Eur J Pain. 2005, 10: 353-61. 10.1016/j.ejpain.2005.06.002.View ArticlePubMedGoogle Scholar
- Pautex S, Michon A, Guedira M, Emond H, Le Lous P, Samaras D, Michel JP, Herrmann F, Giannakopoulos P, Gold G: Pain in severe dementia: self-assessment or observational scales?. J Am Geriatr Soc. 2006, 54: 1040-5. 10.1111/j.1532-5415.2006.00766.x.View ArticlePubMedGoogle Scholar
- Feldt KS: The checklist of nonverbal pain indicators (CNPI). Pain Manag Nurs. 2000, 1: 13-21. 10.1053/jpmn.2000.5831.View ArticlePubMedGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2318/10/47/prepub
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