Adults were eligible for inclusion in the study if they were aged over 60, lived at home or in a care home in one of four primary care trust areas (population 639

789) in Nottinghamshire, United Kingdom, and had contacted the East Midlands Ambulance Service through the emergency telephone system because of a fall but had not been taken to hospital. The four primary care trusts were Nottingham City, Rushcliffe, Broxtowe and Hucknall, and Gedling, which cover city, suburban, and rural addresses. We identified potential participants from ambulance service records and invited them by post to take part in the study. A researcher (PAL) visited respondents at home to explain the study, obtain written informed consent, and collect baseline data. People were excluded if they were unable to give consent, were deemed too ill to participate (for example, terminally ill), or already in a falls prevention rehabilitation programme.
Intervention
The intervention was provided by four community fall teams, which included occupational therapists, physiotherapists, and nurses. An individualised multifactorial intervention programme was undertaken. This followed the UK clinical fall guidelines
10 in which participants and therapists set treatment goals. Intervention was primarily delivered in the participants’ homes, but the participants were also offered group sessions in community centres.
The interventions at home included training in strength and balance for at least six sessions led by the physiotherapist; an assessment of hazards in the home and modifications to the environment, including provision of equipment such as chair raisers, minor adaptations such as grab handles, and advice, such as removal of items from the floor and improved lighting; and practice in getting up from the floor (provided by the occupational therapists). The nurse completed a review of drugs and blood pressure readings. As required, the participants were referred to other agencies such as the family doctor for a medical review, or social care for help at home. The same fall prevention team also provided an established rolling programme of 12 group sessions on fall prevention, twice weekly over six weeks, in local community centres. Each session lasted two hours, including one hour of muscle strengthening and balance training led by a physiotherapist and one hour of education and functional activities led by an occupational therapist. Sessions also covered advice on nutrition, pacing, strategies for coping with activities of daily living, hazards in the home, equipment, footwear, and how to get up from the floor.
Participants received as many sessions in their own homes as deemed clinically necessary and attended as many group sessions in the rolling programme as they wished, up to a maximum of 12. The number of techniques used, their duration, and type was recorded for both the home and the group sessions. Participants allocated to the control group had no further study intervention after recruitment and were advised by letter to use existing social and medical services as usual.
Objectives and outcomes
We hypothesised that rehabilitation for falls prevention would reduce the rate of falls over 12 months compared with usual practice.
Data collected at baseline by questionnaire administered by a researcher in the participants’ homes included sex; date of birth; number of falls in the three months before recruitment; the Barthel activities of daily living index,
11 to measure personal ability with activities of daily living; the Nottingham extended activities of daily living scale,
12 to measure ability with instrumental activities of daily living; and the falls efficacy scale,
13 to measure fear of falling.
The primary outcome measure was the rate of falls over 12 months, calculated using the number of falls reported by each participant as the numerator and their follow-up time as the denominator. Data on falls were recorded monthly using a diary.
14 Participants were sent a diary by post each month with a stamped addressed envelope to return the completed previous month’s diary. If diaries were not returned researchers masked to group allocation used telephone prompts. The researcher showed participants at the time of recruitment how to complete the diaries and discussed the Prevention of Falls Network Europe
15 definition of a fall “an unexpected event in which the participant comes to rest on the ground, floor, or lower level.” The participants were reminded to include every time that they had a slip or trip in which they lost their balance and landed on the floor, ground, or lower level.
Secondary outcome measures were the time to a first fall within 12 months and whether the participant had or had not fallen at least once during the 12 months of follow-up. In addition to the monthly diaries, participants were sent a questionnaire by post at 12 months to obtain information on other secondary outcome measures: the Barthel activities of daily living index,
11 the Nottingham extended activities of daily living scale,
12 and the falls efficacy scale.
13 A trained assessor who was independent of the community fall team and masked to group allocation contacted by telephone or visited those participants who did not return their diaries or questionnaires. To examine the potential for assessor bias, we asked assessors to indicate if they were aware of the group to which the participant had been allocated. Two researchers checked and double entered the data on to a database. A third researcher checked all the diary data.
Additional secondary outcome measures were the number of hospital admissions, the number of days in hospital, and any fall related fracture over 12 months. To determine these outcomes a researcher blind to allocation checked the Nottingham University Hospital computer system. The East Midlands Ambulance Service computer system was also checked to determine the number of emergency ambulance calls received for falls over 12 months and the number of such participants taken to an accident and emergency department or left at home.
Sample size
We determined that to detect a 35% reduction in the rate of falls from an expected rate of 2.0 falls per year to 1.3 falls per year with 80% power and 5% significance (two sided), and assuming an overdispersion of 1.5, we needed a sample size of 160 participants (80 in each arm). Allowing for 20% dropout, we set a recruitment target of 200 people (100 in each arm).
Randomisation
Before the study started, the Nottingham Clinical Trials Unit produced a computer generated randomisation scheme with stratification by primary care trust. The allocation sequence was concealed until allocation. After written consent had been obtained, PAL accessed the randomisation sequence through the internet and assigned the participants to their group. Participants had an equal chance of being assigned to the intervention group (referral to the falls prevention rehabilitation service) or the control group (standard care). On the day of randomisation PAL made a referral to the falls rehabilitation team by telephone who then dealt with the referral in their normal manner. Participants in the intervention group were informed by letter that they would be approached by their local falls prevention team.
Blinding
It was not possible to blind the participants and treating therapists to allocation group as they would be aware of receiving or giving falls rehabilitation. The assessors who contacted the participants to collect missing data on outcome measures and the research staff who input data were blinded to allocation group.
Statistical analysis
We carried out the analyses according to a prespecified statistical analysis plan. Participants were analysed on an intention to treat basis—that is, according to their allocated group, irrespective of intervention received.
We used descriptive statistics to compare baseline data. The incidence rate ratio of falls comparing the rate of falls between the two groups was estimated using negative binomial regression models. These models analysed the total number of falls reported by each participant allowing for variable lengths of follow-up up to a maximum of 12 months. Patients were included assuming that each completed falls diary covered 30 days or until they died, withdrew from the study, or reached the end of the 12 month follow-up. The primary analyses only included adjustment for primary care trust. Additional models adjusted for sex, age (61-74, ≥75), drug use (taking more than four drugs at baseline: yes or no), falls in previous three months at baseline (only the index fall, ≥2), and residential status (living at home alone, living at home with others, living in a care home or hospital). We checked residuals and influential points. Tests for interaction were also carried out between the intervention group and age (61-74, ≥75) and number of falls in the previous three months (only the index fall, ≥2).
We used a Cox proportional hazards model to analyse time to first fall and a log-minus-log plot to check the assumption of proportional hazards. The proportions with at least one fall during follow-up were compared using a log-binomial regression model to estimate a risk ratio. We compared the Barthel index, the Nottingham extended activities of daily living, and falls efficacy scale using linear regression or logistic regression, splitting the outcome at the median if the assumptions of linear regression were not valid, and adjusting for primary care trust and baseline values of each respective variable. Using negative binomial regression, adjusting for primary care trust and accounting for length of follow-up, we analysed the number of hospital admissions, the number of days in hospital, and the number of emergency ambulance calls received for falls over 12 months. We analysed falls related fractures over 12 months using Cox proportional hazards model based on time to first fall related fracture resulting in hospital admission during follow-up.