Impact of An Emergency Response System on Anxiety and Health-Care Use

2014-08-27 03:44:26 | BioPortfolio


What to do after an elderly patient falls but is not seriously injured can be a very challenging decisions for the patient and the Emergency Physician. Unfortunately, homecare support is often unavailable for weeks. The patient and physician must then choose between discharge home without support, or hospitalization. An emergency response service (ERS) allows the patient to summon assistance from anywhere in their home, and may provide another option.

Objectives: To see how an ERS affects patients’ anxiety, fear of falling, and use of the health-care system after discharge. We will study patients over 70 years of age who have fallen but do not need to be hospitalized. Our belief is that the ERS will improve patient anxiety, and may prevent return visits to the Emergency or episodes of prolonged immobilization after a fall.

Methods: Patients agreeing to participate in the study will be assigned by chance to receive either current standard discharge care, or standard care plus the use of the emergency response system. Patients will be interviewed one month after discharge to compare the impact of the ERS. This study is a first step in deciding whether the ERS is a useful new technology.


Research Design & Methods:

3.1. Study Design & Setting: A prospective, assessment blinded, randomized study design will be used. Patients randomized to the intervention group will be given an ERS communicator for a period of 30 days following their visit to the ED. Patients in the conventional care group will receive standard advice upon discharge. (See Control Group, below). Sunnybrook and Women’s College Health Sciences Center is a tertiary, university-affiliated teaching hospital with an annual Emergency Department census of 40,000 patients. An audit of patients presenting to our Emergency Department for the month of December 2000 identified 87 patients over 70 years attending after a fall or fall-related injury who were discharged.

3.2. Study Population: The study will include elderly patients who present to the Emergency Department of our institution with a complaint of a fall, and who are being discharged home by the treating physician.

The proposed trial is designed to guide practical choices rather than merely to acquire scientific information. In the terms of Schwartz and Lellouch, it is ‘pragmatic’ rather than ‘explanatory’. Patients who do not comply with their allocated treatment will be analyzed according to the “intention–to-treat” principle .

3.2.1. Inclusion Criteria:

1. Age Greater than or equal to 70 years.

2. Primary complaint of a fall and discharged home directly from the Emergency Department.

3.2.2. Exclusion Criteria: Definition and Rationale: Exclusion Criteria: Definition /Rationale

1. Admitted to hospital Will not benefit from intervention

2. Not independently living Not living in own domicile, or Seniors residence if subject responsible for own activities of daily life /Dependant individuals not likely to benefit from intervention

3. No Phone Line Required to install ERS Line

4. Unable to give informed consent Communication barrier, dementia (MMS < 23)

5. Living outside catchment area Postal code of Residence/Follow-up impractical

3.3. Patient recruitment: All eligible patients presenting during study hours (08.00h-22.00h, 7 days a week) will be introduced to the study by a Research Nurse. Patients expressing an interest in study participation will be asked to provide formal written consent and will be randomized to either control or intervention groups (see “Intervention”, below) prior to discharge from the Emergency Department. To maximize follow-up, contact information will be verified prior to discharge, including information on next of kin and family physician.

3.4. Control Group Current standard care of the elderly who have fallen at our institution involves referral to an Emergency Geriatric Nurse Clinician, who is available between 9 and 5, seven days a week. Patients referred after hours currently receive a telephone follow-up the next day. Based on the face-to face or telephone interview, the Geriatric Nurse Clinician arranges follow-up with the Regional Geriatric Assessment program, suggests gait-aids such as a cane or walker, or may recommend a change in the client’s living arrangement.

3.5. Intervention Patients randomized to the intervention group will receive standard care as outlined above. In addition, they will be given an emergency response system (ERS) for a trial period of 30 days following their visit to the ED. The ERS consists of a battery operated personal alarm system, kept within reach of the patient at all times. The ERS is monitored 24 hours per day by a response team, with access to an updated summary of the medical history and social circumstances of the client. Patients are instructed to activate the ERS for falls or other events requiring assistance. Once the system is activated, an automated log of the event is generated. The response team can communicate with the individual via a 2-way speaker, and determine what resources are required (e.g. dispatching an ambulance, mobilization of home care, private health care, or family support). The proposed benefits of this system are to provide timely access to assistance by a team with specific knowledge of the patient for clients with restricted mobility, impaired visual or auditory acuity, or cognitive impairments that might interfere with their ability to access or choose an appropriate level of response from the health care system using existing methods such as 911 or Telehealth.

3.6. Length of Follow-up All patients will be contacted by telephone after one week to arrange a follow-up home visit interview between 30-37 days after discharge from the ED. Previous studies have shown that the highest return rates occur during the first month of discharge, , and that visits during this first month are more likely to be for the same problem than latter visits 31.

3.7. Primary Outcome: Hospital Anxiety Scale The primary goal of the current pilot study will be to determine the impact of the ERS on patient quality of life after discharge from the Emergency Department, as measured by the Hospital Anxiety Scale 1. The HAD-A scale has been used widely in the assessment of anxiety for many different patient groups, including the elderly 21, , both as a screening tool and as an outcome measure, and has been shown to have satisfactory levels of psychometric validity 42. The scale consists of seven Likert scales, scored between 0 and 3, for a theoretical range of 0 to 21.

3.7.1. Secondary Outcomes: Fear of Falling Efficacy Scale: The falls efficacy scale is previously validated scale designed to measure elders self-confidence in their ability to avoid falling in daily living activities 2,28. Elders rate their confidence to avoid a fall a 0 to 10 scale during ten activities (see Appendix A.). In addition, we will measure patients’ confidence that, were they to fall, they would be able to get up on their own.

3.7.2. Health Care Utilization: Health care utilization will be measured by patient reports of utilization of the following health care resources in the month following presentation: to the ED

1. Total return visits to an emergency department;

2. Total family physician visits;

3. Total contacts with Tele-health;

4. Total admissions to hospital and length of stay; 3.7.3. Patient and caregiver perceptions of the ERS It is important to document the behavioural and social processes attendant upon the introduction of any new technology, or any innovative application of an existing technology. In this instance we shall, through a short series of semi-structured questions, ask patients who are in receipt of Lifeline to reflect on their day to day experiences in relation to the possession and use of the equipment, during the month following their visit to the emergency department, and the perceived impacts of the scheme on family and friends. This component of the study derives from a phenomenological paradigm , and will specifically adopt an ethnographic methodology in order elicit patient-centered accounts of the technology 3.7.4. Patient Morbidity

We will compare the following measures of patient morbidity:

1. Self-reported falls

2. Self-reported injuries

3. Length of immobilization or “Down time”. The ERS has the potential to reduce patient morbidity by preventing the terrifying experience of prolonged periods of immobility or incapacitation after falling. In the literature, “downtime” has generally been estimated by patient self-report . When the patient is unable to estimate, the last witnessed time that the patient was ambulatory or in contact with another individual will be used as a proxy.

3.8. Data Collection Demographic variables (age, gender, home circumstance, mini mental status, and social support) will be recorded from the patient’s ED chart relating to the presenting event. A questionnaire (see Appendix A) will be administered during face-to-face interviews with patients in both the treatment and the conventional care groups. Baseline interviews will be conducted prior to randomization to ensure blinding. The questionnaire includes both the HAD-A scale and the Fear-Efficacy scale 2. In addition to these core items, people in the intervention group will be asked to describe their experiences and views of the ERS. Their responses will be recorded verbatim.

3.9. Data Analysis Plan Numerical data will be entered directly into a SAS (v10) database for statistical analysis, following the general principles of Pocock in relation to a simple one-way trial, and will be by ‘intention to treat’. The narrative (or “qualitative”) data will be analyzed using the framework method .

3.10. The sample size calculation was based on the ability to detect a difference in anxiety, our primary outcome, measured by the HADS-A. There is no definition in the literature for the minimal clinically important difference (MCID) for the HADS-A. Two previous large studies of community dwelling elders found that a 3 point change in HADS-A represented two-standard deviations from their baseline assessment.33 Using 3 points as the MCID yielded a sample size requirement of only 11 subjects per group. Such a small sample size would not permit analysis of secondary endpoints, and might be judged to lack face validity. Thus, a more conservative definition of the MCID for HADS-A of 1.5 points was chosen. Because of uncertainty regarding the distribution of HADS-A scores in our target population, we used the Wilcoxon rank sum test to estimate the required sample size. Given a standard deviation of 3.4, and an alpha of 0.05, with 40 subjects per group, the study would have over 95% power to detect a between-group reduction of 1.5 points from 6.0 to 4.5 in the mean HADS-A score.

3.10.1. Recruitment rate A pilot study at our institution demonstrated that during a one month period, 87 patients over 70 years of age were discharged from the emergency department. Assuming that 45% of attendees were recruited, we estimate that approximately 39 people per month will be available for recruitment. Assuming a further 10% loss to follow-up, we estimate that a five-month period will be required to recruit 160 subjects.

3.11. Ethical Considerations Ethical approval is being sought from our institutional research ethics board of SWCHSC. The Research Nurse will obtain full written informed consent.

Patient confidentiality will be strictly maintained. Data will be made anonymous before analysis, and results will be published such that it is impossible to identify any participant. Documents with patient identification will be kept in a, separate, locking filing cabinets. The data will be archived for five years following completion of the study, and then destroyed.

Study Design

Allocation: Randomized, Control: Active Control, Endpoint Classification: Efficacy Study, Intervention Model: Single Group Assignment, Masking: Single Blind, Primary Purpose: Treatment




Emergency Response System (Device)


Sunnybrook Health Sciences Center
M4S 3M5




Sunnybrook Health Sciences Centre

Results (where available)

View Results


Published on BioPortfolio: 2014-08-27T03:44:26-0400

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