Journal_1_2014_final_WEB

Scientific Communication
Inclusion and exclusion criteria
Inclusion
Patients >18 yrs-old suffering from at
least one of three chronic diseases:
COPD, diabetes, or CHF
Patients having cognitive limitations
took part with help from relatives
Exclusion
Non-English-speaking patients
Patients without telephone access
Comorbidity was not an exclusion criteria
Inclusion
Patients willing to take part in supplemental
questionnaires in addition to the above
criteria [8]
Exclusion
As above [8]
Inclusion
Patients willing to take part in supplemental
questionnaires in addition to the above
criteria [8]
Exclusion
Patients with cognitive limitations;
otherwise, as above criteria [8]
Patient characteristics
at study start
Telemedicine
n=1,625
Average age=70.9 yrs
Control group
n=1,605
Average age=69.7 yrs
Patients with COPD=48%
Patients with diabetes=24%
Patients with CHF=28%
Telemedicine
n=845
Average age=70.1 yrs
Control group
n=728
Average age=70.6 yrs
Telemedicine
n=534
Average age=70.0 yrs
Control group
n=431
Average age=70.1 yrs
– –
Inclusion
Patients who did not want to partake [8]
Average age=71 yrs
Randomization
The WSD was designed as a cluster-randomized study.
Every general practice (N=238) in three UK regions were
requested to take part and 179 of these (75.2%) accepted.
Randomization of the general practices was performed
centrally using an algorithm that ensured an equal distribution
according to practice size, geographic area, deprivation
index, proportion of non-white patients, and
prevalence of the major chronic diseases (i.e., chronic lung
disease, chronic heart disease, and diabetes).
Intervention
Patients in the control group were offered usual treatment,
while patients in the intervention group were additionally
offered telehealth. Telehealth includes a broad class of
technologies, but all patients had a base unit and tools to
measure weight (heart failure), pulse oximetry (COPD),
and blood glucose (diabetes). The patients performed
measurements up to 5 days per week. Questions regarding
symptoms and information concerning patient education
were forwarded to all participating individuals. Data from
these measurements were sent to monitoring centres and
handled by specially educated nurses. Each region was
supplied with different technologies and service models 9 .
Risk of bias
In existent papers on clinical and economic consequences
of telemedicine 9-11 , the randomization sequence is
described, data completeness is detailed, and results descriptions
are based on the protocol. However, patient
allocation is not hidden to investigators and statisticians,
and the patients are not blinded to their treatment group.
Clinical effects
In the study addressing use of secondary care and mortality,
the primary endpoint was the number of patients
admitted to hospital during a 12-month period 9 . Sample
size was calculated from an expected admission reduction
of 17.5%, and the study was based on registry data.
Between May 2008 and December 2009 a total of 3,230
individuals were recruited. No statistically significant differences
among patients in these two groups were found
at baseline.
The use of hospital services was generally lower in intervention
group versus control group patients (Table 2). The
number of admitted patients accordingly was found to be
Table 2. Hospital use and mortality after 12 months a
Control group
(n=1,584)
Intervention
group
(n=1,570)
Percentage
difference
(95% CI)
Admission proportion 48.2% 42.9% -10.8 (-18.0-3.7)
Mortality 8.3% 4.6% -44.5 (-65.3-23.8)
Emergency admissions/person 0.68 0.54 -20.6 (-33.8-7.4)
Elective admissions/person 0.49 0.42 -14.3 (-30.6-2.0)
Outpatient attendances/person 4.68 4.76 +1.7 (-8.3-11.8)
Emergency department visits/person 0.75 0.64 -14.7 (-28.0-1.3)
Bed days/person 5.68 4.87 -14.3 (-32.4-3.9)
DRG Tariff costs/person 2448b 2260 DKK -7.7 (-19.4-4.0)
CI=Confidence interval. a Based on [9, Table 3]. bPrice level 2009: 1 GBP=8.232 DKK.
EWMA Journal 2014 vol 14 no 1 45