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Navigating NHS Administrative
Data
David A. Ellis
Missed Appointments
• Proxy for low engagement
• As a health harming behaviour
• Proxy for poor health and social vulnerability
Results
Results
Step Back
Process
code appointments
attended = 830,039
DNA = 56,441
appointments.csv
N=892,216
patients.csv
N=73,012
clinical.csv
N=704,828
remove non-appointments
based on time rules
compute number of
appointments attended/missed
for each patient
appointmenthistory dataframe
patient ID
DNA
attended
total
percentage missed
annual DNA rate
Categorise each patient. zero,
low medium, high
appointment History merged with
Patients file
(using patient ID as link)
patientappointments dataset
(N=70,165)
ID
sex
age
distance
Rur8
PracticeRur8
SIMD
PracticeSIMD
Ethnic
attended
DNA
total
percentage missed
category
annual rate (attended)
Ready for analysis and visualization
(N=67,705)
reclassify based on
codes of interest
N=825,784 remaining after (7.4%)
removed
Zero N = 44,685 (63.7%)
Low N = 19,281(27.5%)
Medium N = 5,097 (7.3%)
High N = 1,102 (1.6%)
N = 491 patients (<1%) with no
appointment data removed
remove patients with missing
data
N=2,460
(3.5%)
patients classified as frequent/non
frequent attenders
(10th centile (annual attendance
rate>=8.66))
Yes = 7,283
No = 62,882
subset to remove
remove ethnicity data
add age categories
remove administrative/
secretary appointments
N=891,921 remaining after (<.01%)
removed
remove duplicate
patients
N=2,356
Replication/Transparency?
Key References
Ellis, D. A., McQueenie, R., McConnachie, A., Wilson, P and Williamson, A. E.
(2018). Non-attending patients in general practice. The Lancet Public Health,
3(3), e113
Smits, F. T. and ter Riet, G. (2017). Non-attending patients in general
practice. The Lancet Public Health, 2(12), e538.
Ellis, D. A., McQueenie, R., McConnachie, A., Wilson, P and Williamson, A. E.
(2017). Demographic and practice factors predicting repeated non-
attendance in primary care: A national retrospective cohort analysis. The
Lancet Public Health. 2(12), e551-e559
Williamson, A., Ellis, D. A., Wilson, P., McQueenie, R. and McConnachie, A.
(2017). Understanding repeated non-attendance in health services - pilot
analysis of administrative data and full study protocol. BMJ Open, 7(2),
e01412

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Navigating NHS Administrative Data

  • 2. Missed Appointments • Proxy for low engagement • As a health harming behaviour • Proxy for poor health and social vulnerability
  • 6. Process code appointments attended = 830,039 DNA = 56,441 appointments.csv N=892,216 patients.csv N=73,012 clinical.csv N=704,828 remove non-appointments based on time rules compute number of appointments attended/missed for each patient appointmenthistory dataframe patient ID DNA attended total percentage missed annual DNA rate Categorise each patient. zero, low medium, high appointment History merged with Patients file (using patient ID as link) patientappointments dataset (N=70,165) ID sex age distance Rur8 PracticeRur8 SIMD PracticeSIMD Ethnic attended DNA total percentage missed category annual rate (attended) Ready for analysis and visualization (N=67,705) reclassify based on codes of interest N=825,784 remaining after (7.4%) removed Zero N = 44,685 (63.7%) Low N = 19,281(27.5%) Medium N = 5,097 (7.3%) High N = 1,102 (1.6%) N = 491 patients (<1%) with no appointment data removed remove patients with missing data N=2,460 (3.5%) patients classified as frequent/non frequent attenders (10th centile (annual attendance rate>=8.66)) Yes = 7,283 No = 62,882 subset to remove remove ethnicity data add age categories remove administrative/ secretary appointments N=891,921 remaining after (<.01%) removed remove duplicate patients N=2,356
  • 8. Key References Ellis, D. A., McQueenie, R., McConnachie, A., Wilson, P and Williamson, A. E. (2018). Non-attending patients in general practice. The Lancet Public Health, 3(3), e113 Smits, F. T. and ter Riet, G. (2017). Non-attending patients in general practice. The Lancet Public Health, 2(12), e538. Ellis, D. A., McQueenie, R., McConnachie, A., Wilson, P and Williamson, A. E. (2017). Demographic and practice factors predicting repeated non- attendance in primary care: A national retrospective cohort analysis. The Lancet Public Health. 2(12), e551-e559 Williamson, A., Ellis, D. A., Wilson, P., McQueenie, R. and McConnachie, A. (2017). Understanding repeated non-attendance in health services - pilot analysis of administrative data and full study protocol. BMJ Open, 7(2), e01412