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. 2019 Jan 11;17(1):2.
doi: 10.1186/s12916-018-1234-0.

Morbidity, mortality and missed appointments in healthcare: a national retrospective data linkage study

Ross McQueenie  1 , David A Ellis  2 , Alex McConnachie  3 , Philip Wilson  4 , Andrea E Williamson  5
Affiliations

Morbidity, mortality and missed appointments in healthcare: a national retrospective data linkage study

Ross McQueenie et al. BMC Med. .

Abstract

Background: Recently, studies have examined the underlying patient and practice factors for missed appointments, but less is known about the impact on patient health. People with one or more long-term conditions who fail to attend appointments may be at risk of premature death. This is the first study to examine the effect of missed primary healthcare appointments on all-cause mortality in those with long-term mental and physical health conditions.

Methods: We used a large, nationwide retrospective cohort (n = 824,374) extracted from routinely collected general practice data across Scotland over a 3-year period from September 2013 until September 2016. This data encompasses appointment history for approximately 15% of the Scottish population, and was linked to Scottish deaths records for patients who had died within a 16-month follow-up period. We generated appointment attendance history, number of long-term conditions and prescriptions data for patients. These factors were used in negative binomial and Cox's proportional hazards modelling to examine the risk of missing appointments and all-cause mortality.

Results: Patients with a greater number of long-term conditions had an increased risk of missing general practice appointments despite controlling for number of appointments made, particularly among patients with mental health conditions. These patients were at significantly greater risk of all-cause mortality, and showed a dose-based response with increasing number of missed appointments. Patients with long-term mental health conditions who missed more than two appointments per year had a greater than 8-fold increase in risk of all-cause mortality compared with those who missed no appointments. These patients died prematurely, commonly from non-natural external factors such as suicide.

Conclusions: Missed appointments represent a significant risk marker for all-cause mortality, particularly in patients with mental health conditions. For these patients, existing primary healthcare appointment systems are ineffective. Future interventions should be developed with a particular focus on increasing attendance by these patients.

Keywords: Missed appointments; administrative data; health inequalities; health promotion; health utilisation; long-term conditions; morbidity; mortality; primary care; social vulnerability.

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Conflict of interest statement

Ethical approval

Letters of comfort were issued by the West of Scotland NHS Ethics Committee and the University of Glasgow College of Medical, Veterinary & Life Sciences Ethics Committee confirming that the full study did not need NHS ethics permission. Public Benefit and Privacy Panel approval was granted by NHS Information Services Scotland in December 2016. Data were aggregated where necessary to ensure individual patient privacy.

Consent for publication

No personal information was given so consent to publish was not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
a Fully adjusted negative binomial modelling of risk of missing appointments for no, one to two, and four plus long-term conditions. Model controlled for age, sex, socioeconomic status (SIMD), distance between home and the practice, appointment delay, mean appointment time per patient, number of appointments per patient, rurality index, and mean practice socioeconomic status. The model is also offset for the number of appointments made. Circles represent relative risk ratios (RRRs) with 95% confidence intervals. b Fully adjusted negative binomial modelling of risk of missing appointment for physical health-related long-term conditions. Model controlled for age, sex, socioeconomic status, distance between home and the practice, appointment delay, mean appointment time per patient, number of appointments per patient, rurality index, mean practice socioeconomic status, and number of mental health-related long-term conditions. c Fully adjusted negative binomial modelling of risk of missing appointment for mental health-related long-term conditions. Model controlled for age, sex, socioeconomic status, distance between home and the practice, appointment delay, mean appointment time per patient, number of appointments per patient, rurality index, mean practice socioeconomic status and number of physical long-term conditions. All models are also offset for the number of appointments made. Circles represent RRRs with 95% confidence intervals
Fig. 2
Fig. 2
Cumulative incidence Kaplan–Meier plot showing proportions of deaths (all-cause mortality) over the follow-up period of 480 days. Graph shows zero, low, medium and high number of missed appointment groupings. Missed appointment categories were defined as the average annual number of missed appointments over a 3-year period, as follows: zero, 0; low, < 1; medium, 1–2; or high, > 2
Fig. 3
Fig. 3
Fully adjusted Cox’s proportional hazards showing risk of all-cause mortality for zero, low, medium and high number of missed appointment groupings. Model controlled for age, sex, socioeconomic status (SIMD), distance between home and the practice, appointment delay, mean appointment time per patient, number of appointments per patient, rurality index, mean practice socioeconomic status and number of long-term conditions. Missed appointment categories were defined as the average annual number of missed appointments over a 3-year period, as follows: zero, 0; low, < 1; medium, 1–2; or high, > 2. Graph shows hazard ratios (HRs) with 95% confidence intervals
Fig. 4
Fig. 4
Fully adjusted Cox’s proportional hazards showing risk of all-cause mortality for zero, low, medium and high missed appointments groupings in (a) patients with any physical or mental health long-term conditions, (b) patients with any physical conditions only, (c) patients with mental health conditions only, and (d) patients with both physical and mental health conditions. Model controlled for age, sex, socioeconomic status (SIMD), distance between home and the practice, appointment delay, mean appointment time per patient, number of appointments per patient, rurality index, mean practice socioeconomic status, and number of long-term conditions. Missed appointment categories were defined as the average annual number of missed appointments over a 3-year period, as follows: zero, 0; low, < 1; medium, 1–2; or high, > 2. Graph shows hazard ratios (HRs) with 95% confidence intervals
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