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Use of telephone and SMS reminders to improve attendance at hospital appointments: a systematic review:

Use of telephone and SMS reminders to improve attendance at hospital appointments: a systematic... RESEARCH Systematic review ................................................................................................................................. Use of telephone and SMS reminders to improve attendance at hospital appointments: a systematic review Per E Hasvold and Richard Wootton Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway, Tromsø, Norway Summary Patients failing to attend hospital appointments contribute to inefficient use of resources. We conducted a systematic review of studies providing a reminder to patients by phone, short message service (SMS) or automated phone calls. A PubMed search was conducted to identify articles published after 1999, describing studies of non-attendance at hospital appointments. In addition, we searched the references in the included papers. In total, 29 studies were included in the review. Four had two intervention arms which were treated as independent studies, giving a total of 33 estimates. The papers were analysed by two observers independently. A study quality score was developed and used to weight the data. Weighted means of the absolute and the relative changes in non-attendance were calculated. All studies except one reported a benefit from sending reminders to patients prior to their appointment. The synthesis suggests that the weighted mean relative change in non-attendance was 34% of the baseline non-attendance rate. Automated reminders were less effective than manual phone calls (29% vs 39% of baseline value). There appeared to be no difference in non-attendance rate, whether the reminder was sent the day before the appointment or the week before. Cost and savings were not measured formally in any of the papers, but almost half of them included cost estimates. The average cost of using either SMS, automated phone calls or phone calls was E0.41 per reminder. Although formal evidence of cost-effectiveness is lacking, the implication of the review is that all hospitals should consider using automated reminders to reduce non-attendance at appointments. However, there is little information about the magnitude of Introduction ...................... ....................... ................. this effect and we are only aware of one previous review of the effect of reminders on non-attendance at hospital Non-attendance for appointments in health care results in appointments. This was a narrative review of telephone wasted resources and disturbs the planned work-schedules. and postal reminders, which concluded that reminders can Cancellations and rescheduling of appointments are usually improve attendance and reduce non-attendance dealt with administratively and vacant slots are often filled by qualitatively. We have therefore conducted a systematic other patients, which reduces the loss in overall efficiency for review. The research questions were: the health-care staff concerned. In hospitals, the problem of non-attendance can be met by a number of different (1) What is the best estimate of the effect of sending strategies, such as overbooking the appointment list or reminders on non-attendance rates? sending some kind of reminder in advance of the (2) Are there any differences in non-attendance when appointment. However, overbooking may not be considered using reminders sent manually (i.e. from phones an appropriate method in modern health-care delivery. On operated by a human) or automatically (i.e. by SMS the other hand, reminders directly to the patient from a text messages or by automated voice recordings)? hospital are generally acceptable. This can be viewed as a form (3) Does the time at which the reminder is sent influence of telemedicine, since it is an application of technology to the the effect on non-attendance rates? health-care process which involves distance. (4) What are the costs and benefits of using reminders? It seems reasonable to expect that sending reminders would decrease the no-show rate at hospital appointments. Methods ...................... ....................... ................. Accepted 1 August 2011 Correspondence: Per E Hasvold, Norwegian Centre for Integrated Care and Papers were selected following the PRISMA Telemedicine, University Hospital of North Norway, PO Box 6060, 9038 Tromsø, Norway (Fax: þ47 77 75 40 98; Email: [email protected]) methodology. A search of the PubMed database was Journal of Telemedicine and Telecare 2011; 17: 358 – 364 DOI: 10.1258/jtt.2011.110707 P E Hasvold and R Wootton Telephone and SMS reminders conducted on 21 February 2011 using the following This gave a possible score for study quality from zero to keywords: 14. Similar quality indicators have been used previously by 33,34 others. (telephone OR phone OR mobile OR cellphone) AND (outpatient OR out-patient) AND (attendance OR Effect size appointment OR reminder) Two effects were examined: the absolute and the relative change in DNA rate. The absolute change in the DNA rate Only papers published in 2000 or later, in English or any was calculated as the percentage of DNA in the control of the Scandinavian languages (Danish, Swedish or group minus the percentage of DNA in the intervention Norwegian) were included. In addition we examined the group. The relative change in the DNA rate was calculated reference lists of the papers selected for review. Duplicates by dividing the absolute change by the percentage of DNA were then eliminated. These were screened for relevance, i.e. in the control group. to confirm that they reported reminders using phones or SMS, leaving papers for full-text eligibility assessment. Papers were eliminated from the study if they provided Pooled estimate of effect size insufficient data about change in attendance or did not Weighted mean values were calculated using the quality describe reminders for a particular appointment, but scores as weights. general adherence to long-term programmes. Data extraction Data analysis In papers reporting the DNA rates only, we did not attempt All papers were analysed by both authors independently. to contact the authors for clarification or additional Any disagreements in interpretation were resolved by information about their data. We checked the numbers of consensus. Four of the selected papers described multi-arm patients involved and recalculated the rates to four studies in which reminders were sent both by phone and significant figures based on an integer number of by SMS, or by phone and by automated phone calls to patients. We analysed the data on an ‘intention separate groups. In these cases we used data from both to treat’ basis. arms of the study as though they were independent We categorised the interventions as manual or studies. automated. Manual reminders were telephone calls made by The outcome variable of interest was the Did Not Attend members of staff. Automated calls were either computer (DNA) rate. When a paper reported that a reminder was sent driven voice messages or computer driven SMS text ‘within a week before the appointment’ the reminder time messages. was assumed to be 3.5 days. We categorised the ages of the patients as child (neonatal/ paediatric/adolescent) (0–17 years), adult (18–60 years) or geriatric (.60 years). In some cases the age of the patients Study quality was unclear and we assumed it to be adult. A compound quality indicator was created for weighting the results according to the following indices: Results (1) Study size (0 ¼ not stated; 1 ¼ 1–100; 2 ¼ 101–1000; ...................... ....................... ................. 3 ¼ 1001–10000; 4 ¼ .10000); (2) Duration of intervention (0 ¼ duration not stated; The search returned 321 records. The reference lists of 1 ¼ 1–3 months; 2 ¼ 4–12 months; 3 ¼ .12 months); relevant papers (see below) produced another 99 records. (3) Study design (0 ¼ not stated; 1 ¼ retrospective After duplicates were eliminated there were 269 records. controls; 2 ¼ before and after, or non-randomized These were screened for relevance and the screening control study; 3 ¼ RCT). Note that in a retrospective eliminated 232 papers, leaving 37 papers for full-text trial, the baseline may have been measured in the year eligibility assessment. Of these, eight papers were before the intervention, i.e. there would have been an eliminated from the study, which left 29 papers for full 3–31 interval before the intervention started. In a before and analysis, see Table 1. Figure 1 shows the PRISMA after study, the intervention starts immediately after flowchart of the selection process. the baseline has been measured; (4) Cost of intervention (0 ¼ not stated; 1 ¼ estimate of Analysis costs; 2 ¼ measurements of costs according to current guidelines for economic evaluation in health care ); The analysis below is based on data from 29 studies (5) Savings from intervention (0 ¼ not stated; 1 ¼ estimate reporting a total of 33 estimates. Eighteen of the of savings; 2 ¼ measurements of savings according to interventions were based on manual reminders (i.e. phone current guidelines ). calls made by health staff) and 15 were based on automated Journal of Telemedicine and Telecare Volume 17 Number 7 2011 359 P E Hasvold and R Wootton Telephone and SMS reminders Table 1 Papers selected for review Reminder type (manual or Study Baseline Intervention Study automatic) size Country Study design DNA % DNA% Adams, 2004 Manual 2823 Australia Telephone reminders for 3 months; retrospective comparison with 12.2 9.0 previous year Booth, 2004 Manual 100 UK Telephone reminders for 4 months; concurrent and matched 40.0 14.0 groups Bos, 2005 Manual Automatic 216 Netherlands Telephone and SMS reminders for 0.75 months; concurrent 6.5 M: 2.7 A: 2.0 groups Chen, 2008 Manual Automatic 1848 China Telephone and SMS reminders for 2 months; RCT 19.6 M: 11.7 A: 12.5 Corfield, 2008 Manual 1077 UK Telephone reminders for 2 months; retrospective control group 21.4 19.7 da Costa, 2010 Automatic 29014 Brazil SMS reminders for 11 months; concurrent, non-randomized 25.6 19.4 ( patients who accepted SMS were sorted into the intervention group) Dockery, 2001 Manual 162 UK Telephone reminders for 2 months; before and after study 29.5 17.9 Downer, 2005 Automatic 2864 Australia SMS reminders for 1 month; retrospective comparison with 23.4 14.2 previous month Downer, 2006 Automatic 45110 Australia SMS reminders for 3 months; retrospective comparison with 19.5 9.8 previous year Foley, 2009 Automatic 709 UK SMS reminders for 1 month; retrospective comparison with 23.9 10.4 previous year Geraghty, 2007 Automatic 8966 Ireland SMS reminders for 36 months; historical control group consisted of 33.6 22.0 patients not sent SMS in the intervention period Hardy, 2001 Manual 325 UK Telephone reminders; duration not stated; single centre, 7.3 1.4 prospective, non-randomized, controlled study Hashim, 2001 Manual 823 USA Telephone reminders for 1 month; RCT 25.6 19.8 Haynes, 2006 Manual 515 USA Telephone reminders for 7 months; non-randomized controlled 11.6 4.7 study Irigoyen, 2000 Manual 653 USA Telephone reminders for 5 months; non-randomized controlled 35.0 34.9 trial Koshy, 2008 Automatic 9959 UK SMS reminders for 6 months; non-randomized controlled trial 18.1 11.2 Kruse, 2009 Automatic 1027 Denmark SMS reminders for 1 month; prospective cohort study 10.0 5.9 Lee, 2003 Manual 161 Ireland Telephone reminders for 2 months; before and after study 23.3 5.7 Leong, 2006 Manual Automatic 993 Malaysia Telephone and SMS reminders for 7 months; RCT 51.9 M: 40.4 A: 41.0 MacDonald, 2000 Manual 719 New Zealand Telephone reminders for 36 months; non-randomized controlled 24.4 18.4 study Maxwell, 2001 Automatic 1370 USA SMS reminders for 2 months; RCT 40.0 36.9 McPhail 2010 Automatic 145 USA SMS reminders for 12 months; non-randomised controlled study? 72.5 20.4 Milne, 2006 Automatic 16400 UK SMS reminders for 2 months; retrospective study 15.4 12.0 Parikh, 2010 Manual Automatic 9835 USA Telephone and SMS reminders for 5 months; RCT 23.1 M: 13.6 A: 17.3 Perron, 2010 Manual 2123 Switzerland Telephone reminders for 3 months; RCT 11.4 7.8 Reti, 2003 Manual 74 New Zealand Telephone reminders for 3 months; RCT 27.0 8.1 Roberts, 2007 Manual 504 UK Telephone reminders for 10 months; RCT 20.9 13.8 Satiani, 2009 Automatic 8766 USA SMS reminders for 17 months; non-randomized controlled study 5.9 8.9 Sawyer, 2002 Manual 171 Australia Telephone reminders for 6 months; RCT 20.0 7.9 reminders (i.e. automated phone messages or SMS automated calls; this was true for both the absolute and messages). The study characteristics are summarised in the relative change in DNA rates, see Figure 5 and 6 Table 2. respectively. The median DNA rate reported at baseline (i.e. in the The mean estimates of effect size are summarised in control group) was 23%. All studies except one reported that Table 4. the intervention improved the DNA rate. The median DNA rate reported after the intervention was 13%, Costs and savings see Table 3. Nine of the 29 studies were randomised controlled trials. None of the papers included costs and savings data to the The median study quality score was seven, see Figure 2. standard of accepted guidelines for economic evaluation in There was little evidence for publication bias based on a health care. An estimate of the cost of the intervention was funnel plot, see Figure 3. reported in 16 of the papers. Two of the estimates were not There was no obvious relation between effect size and the included in the present study as the cost estimates time at which the reminder was issued, see Figure 4 depended on circumstances or cost sharing models that (Spearman correlation 0.18). Three of the 29 studies stated were particular to the case. The cost estimates were that the reminder was sent within a week of the converted into Euros, using the exchange rate giving the appointment, which we assumed to be within 3.5 days for highest costs for the year the paper was published. The the purposes of analysis. The effect of reminders on DNA average estimated costs in these 14 studies was E 0.41 per rates was higher for manual reminder calls than for patient. The mean cost of phone reminders was E 0.90, 360 Journal of Telemedicine and Telecare Volume 17 Number 7 2011 P E Hasvold and R Wootton Telephone and SMS reminders Figure 1 The PRISMA flowchart for the paper selection process while the mean cost of SMS or automated phone call found no evidence that this was the case. Taking into reminders was E 0.14. The three highest reported costs were account the quality of the studies, the pooled estimates from phone reminders. show that manual reminders can achieve a reduction in the While savings were estimated in 10 papers, the DNA rate of 39% of the baseline value, while automated circumstances and cases could not be compared. reminders can achieve a reduction of 29% of the baseline value. It seems intuitive that reminders from a health-care professional would be more effective than those sent automatically by a computer. Our pooled estimate of effect size was based on a weighted Discussion ...................... ....................... ................. mean, using study quality as the weighting factor. We did not attempt a formal meta-analysis for several reasons. First, The present study concerns a systematic review of the use of only nine of the 29 studies were RCTs. Second, the studies telephone reminders (manual and automated) to improve were very heterogeneous. Finally, it was not possible to attendance at hospital appointments. All studies except one estimate the SE of the treatment effect from many of the found that sending reminders improved DNA rates. This published reports. Most of the papers reported the absolute suggests the possibility of publication bias, although we change in DNA. We used the relative change in DNA to Table 2 Study characteristics Lower Upper Median quartile quartile Study size 823 325 2864 Duration of intervention (months) 3 2 7 Reminder time (days before 2.75 1.00 3.13 appointment) Table 3 DNA rates reported in 29 studies (33 estimates), unweighted Lower Upper Median quartile quartile Baseline DNA rate (%) 23.1 15.4 27.0 Intervention DNA rate (%) 12.5 8.1 19.4 Absolute change in DNA rate (%) 7.0 4.2 11.5 Relative change (% of baseline value) 38.1 24.1 58.0 Figure 2 Study quality (median quality score ¼ 7) Journal of Telemedicine and Telecare Volume 17 Number 7 2011 361 P E Hasvold and R Wootton Telephone and SMS reminders Figure 5 Absolute change in DNA for manual and automated (SMS or Figure 3 Funnel plot of relative change in DNA rate (% of baseline automated phone call) reminders value) compensate for the different baseline DNA rates in the different settings of the studies. Although the quality of the economic data was weak, the apparent cost of sending reminders was much lower than the expected savings from avoided missed appointments. The time between the reminder and the appointment did not seem to have any strong effect on the DNA rate for any of the methods (see Figure 4). All studies involved reminders being sent out within a week, which appears to be an appropriate time ahead of an appointment to avoid people forgetting about it. An analysis of the relation between the age of the patients and the observed effect showed no difference between the age groups. Figure 6 Relative change in DNA (% of baseline) for manual and automated (SMS or automated phone call) reminders Limitations In the papers which studied two kinds of reminder studies since they were separate groups, when there might simultaneously, we treated the two arms as independent have been interdependencies. Our initial search was conducted using a single database and clearly if more databases had been used, more references might have been found. However a study by Bahaadinbeigy et al. suggests that more than 80% of telemedicine papers can be found by searching in Medline alone. We also conducted a search in the Psycinfo database, Table 4 Pooled estimates No of Weighted Unweighted estimates mean mean Manual reminders absolute change in DNA 18 8.3 8.9 rate (%) relative change in DNA rate 18 39.1 42.2 (% baseline) Automated reminders absolute change in DNA 15 8.9 9.7 rate (%) relative change in DNA rate 15 28.9 32.5 Figure 4 Effect size (relative change in DNA rate) and the time at which (% baseline) the reminder was issued 362 Journal of Telemedicine and Telecare Volume 17 Number 7 2011 P E Hasvold and R Wootton Telephone and SMS reminders 2 The PRISMA Statement. See http://prisma-statement.org/statement.htm using the same terms, but found no additional relevant (last checked 25 July 2011) studies. 3 Adams LA. Nonattendance at outpatient endoscopy. Endoscopy All studies except one showed a positive effect from using 2004;36:402–4 4 Booth PG, Bennett HE. Factors associated with attendance for first reminders. The exception was the study by Satiani et al. appointments at an alcohol clinic and the effects of telephone This study also differed from the others because the patients prompting. J Subst Use 2004;9:269–79 themselves chose in advance whether they wished to 5 Bos A, Hoogstraten J, Prahlandersen B. Failed appointments in an orthodontic clinic. Am J Orthod Dentofacial Orthop 2005;127:355–7 receive a reminder or not. This may have introduced a bias 6 Chen ZW, Fang LZ, Chen LY, Dai HL. Comparison of an SMS text in the intervention group. messaging and phone reminder to improve attendance at a health promotion center: a randomized controlled trial. J Zhejiang Univ Sci B 2008;9:34–38 7 Corfield L, Schizas A, Williams A, Noorani A. Non-attendance at the Further studies colorectal clinic: a prospective audit. Ann R Coll Surg Engl 2008;90:377–80 8 da Costa TM, Salomao PL, Martha AS, Pisa IT, Sigulem D. The impact of We recommend that rigorous health economics studies of short message service text messages sent as appointment reminders to the costs and savings of reminders should be carried out, patients’ cell phones at outpatient clinics in Sao Paulo, Brazil. Int J Med preferably in the form of randomized controlled trials. Inform 2010;79:65–70 9 Dockery F, Rajkumar C, Chapman C, Bulpitt C, Nicholl C. The effect of Without such studies, it is not possible to know with reminder calls in reducing non-attendance rates at care of the elderly certainty whether automated reminders such as SMS text clinics. Postgrad Med J 2001;77:37–39 messages are better than human-generated telephone calls 10 Downer SR, Meara JG, da Costa AC. Use of SMS text messaging to improve outpatient attendance. MJA 2005;183:366–8 (which are more expensive, but produce bigger 11 Downer SR, Meara JG, da Costa AC, Sethuraman K. SMS test messaging improvements in DNA rates). Future research should also be improves outpatient attendance. Aust Health Rev 2006;30:389–96 carried out to investigate the benefits of sending multiple 12 Foley J, O’Neill M. Use of mobile telephone Short Message Service (SMS) as a reminder: the effect on patient attendance. Eur Arch Paediatr Dent reminders, and whether that leads to ‘reminder fatigue’ in 2009;10:15–18 the recipients. Some of the papers in the present review 13 Geraghty M, Glynn F, Amin M, Kinsella J . Patient mobile telephone ‘text’ reported that the patients were not necessarily happy about reminder: a novel way to reduce non-attendance at the ENT out-patient clinic. J Laryngol Otol 2008;122:296–8 the reminder they had received, despite stating that they 14 Hardy KJ, O’Brian SV, Furlong NJ. Information given to patients before would still like to be reminded about any future appointments and its effect on non-attendance rate. BMJ appointments. 2001;323:1298–300 15 Hashim MJ, Franks P, Fiscella K. Effectiveness of telephone reminders Most papers only provided numbers for attendance or in improving rate of appointments kept at an outpatient clinic: non-attendance. Cancellations and rescheduling were not a randomized controlled trial. J Am Board Fam Pract 2001;14:193–6 reported in enough papers to be considered in the analysis, 16 Haynes JM, Sweeney EL. The effect of telephone appointment-reminder calls on outpatient absenteeism in a pulmonary function laboratory. but this is an important aspect of how reminders may Respir Care 2006;51:36–39 contribute to a better and more efficient use of the resources 17 Irigoyen MM, Findley S, Earle B, Stambaugh K, Vaugha R. Impact of and it is possible that the time of the reminder may have a appointment reminders on vaccination coverage at an urban clinic. Pediatrics 2000;106:919–23 more interesting effect on cancellations than on 18 Koshy E, Car J, Majeed A. Effectiveness of mobile-phone short message non-attendance. service (SMS) reminders for ophthalmology outpatient appointments: observational study. BMC Ophthalmol 2008;8:9 19 Kruse LV, Hansen LG, Olesen C. Udeblivelse fra aftale i børneambulatoriet. Ugeskr Laeger 2009;171:1372–5 Conclusions 20 Lee CS, McCormick PA. Telephone reminders to reduce non-attendance rate for endoscopy. J R Soc Med 2003;96:547–8 Sending appointment reminders from hospitals to patients 21 Leong KC, Chen WS, Leong KW, et al. The use of text messaging to can be seen as a form of telemedicine since it involves improve attendance in primary care: a randomized controlled trial. Fam distance and is an application of technology which Pract 2006;23:699–705 22 MacDonald J, Brown N, Ellis P. Using telephone promts to improve initial contributes to the health-care process. The evidence is attendance at a community mental health center. Psychiatr Serv overwhelming that reminders have a positive effect on 2000;51:812–4 non-attendance rates. Our study shows that a 39% 23 Maxwell S, Maljanian R, Horowitz S, Pianka MA. Effectiveness of reminder systems on appointment adherence rates. J Health Care Poor improvement in the baseline DNA rate can be expected Underserved 2001;12:504–14 when manual reminders are employed, and a 29% 24 McPhail GL, Ednick MD, Fenchel MC, et al. Improving follow-up in improvement when automated reminders are used. While hospitalised children. Qual Saf Health Care 2010;19:1–4 25 Milne RG, Horne M, Torsney B. SMS reminders in the UK National Health the costs were only estimated, the studies reviewed suggest Service: an evaluation of its impact on “no-shows” at hospital out-patient that reminders cost less than E 0.50 per patient for SMS or clinics. Health Care Manage Rev 2006;31:130–6 automated reminders. This seems likely to be much less 26 Parikh A, Gupta K, Wilson AC, Fields K, Cosgrove NM, Kostis JB. The effectiveness of outpatient appointment reminder systems in reducing than the cost of missed appointments and we therefore no-show rates. Am J Med 2010;123:542–8 recommend that reminders are used routinely for all 27 Perron NJ, Dao MD, Kossovsky MP, et al. Reduction of missed hospital appointments. appointments at an urban primary care clinic: a randomised controlled study. BMC Fam Pract 2010;11:79 28 Reti S. Improving outpatient department efficiency: a randomized controlled trial comparing hospital and general-practice telephone reminders. N Z Med J 2003;116:U458 References 29 Roberts N, Meade K, Partridge M. The effect of telephone reminders on 1 Henderson R. Encouraging attendance at outpatient appointments: can attendance in respiratory outpatient clinics. J Health Serv Res Policy we do more? Scott Med J 2008;53:9–12 2007;12:69–72 Journal of Telemedicine and Telecare Volume 17 Number 7 2011 363 P E Hasvold and R Wootton Telephone and SMS reminders 30 Satiani B, Miller S, Patel D. No-show rates in the vascular laboratory: 33 Hailey D, Ohinmaa A, Roine R. Study quality and evidence of benefit in analysis and possible solutions. J Vasc Interv Radiol 2009;20:87–91 recent assessments of telemedicine. J Telemed Telecare 2004;10:318–24 31 Sawyer SM, Zalan A, Bond LM. Telephone reminders improve adolescent 34 Bensink M, Hailey D, Wootton R. A systematic review of success and clinic attendance: a randomized controlled trial . J Paediatr Child Health failures in home telehealth. Part 2: final quality rating results. J Telemed 2002;38:79–83 Telecare 2007;13 (Suppl. 3):10–14 32 Drummond MF, Jefferson TO. Guidelines for authors and peer reviewers 35 Bahaadinbeigy K, Yogesan K, Wootton R. MEDLINE versus EMBASE of economic submissions to the BMJ. BMJ 1996;313:275–83 and CINAHL for telemedicine searches. Telemed J E Health 2010;16:916–9 364 Journal of Telemedicine and Telecare Volume 17 Number 7 2011 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Telemedicine and Telecare SAGE

Use of telephone and SMS reminders to improve attendance at hospital appointments: a systematic review:

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10.1258/jtt.2011.110707
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Abstract

RESEARCH Systematic review ................................................................................................................................. Use of telephone and SMS reminders to improve attendance at hospital appointments: a systematic review Per E Hasvold and Richard Wootton Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway, Tromsø, Norway Summary Patients failing to attend hospital appointments contribute to inefficient use of resources. We conducted a systematic review of studies providing a reminder to patients by phone, short message service (SMS) or automated phone calls. A PubMed search was conducted to identify articles published after 1999, describing studies of non-attendance at hospital appointments. In addition, we searched the references in the included papers. In total, 29 studies were included in the review. Four had two intervention arms which were treated as independent studies, giving a total of 33 estimates. The papers were analysed by two observers independently. A study quality score was developed and used to weight the data. Weighted means of the absolute and the relative changes in non-attendance were calculated. All studies except one reported a benefit from sending reminders to patients prior to their appointment. The synthesis suggests that the weighted mean relative change in non-attendance was 34% of the baseline non-attendance rate. Automated reminders were less effective than manual phone calls (29% vs 39% of baseline value). There appeared to be no difference in non-attendance rate, whether the reminder was sent the day before the appointment or the week before. Cost and savings were not measured formally in any of the papers, but almost half of them included cost estimates. The average cost of using either SMS, automated phone calls or phone calls was E0.41 per reminder. Although formal evidence of cost-effectiveness is lacking, the implication of the review is that all hospitals should consider using automated reminders to reduce non-attendance at appointments. However, there is little information about the magnitude of Introduction ...................... ....................... ................. this effect and we are only aware of one previous review of the effect of reminders on non-attendance at hospital Non-attendance for appointments in health care results in appointments. This was a narrative review of telephone wasted resources and disturbs the planned work-schedules. and postal reminders, which concluded that reminders can Cancellations and rescheduling of appointments are usually improve attendance and reduce non-attendance dealt with administratively and vacant slots are often filled by qualitatively. We have therefore conducted a systematic other patients, which reduces the loss in overall efficiency for review. The research questions were: the health-care staff concerned. In hospitals, the problem of non-attendance can be met by a number of different (1) What is the best estimate of the effect of sending strategies, such as overbooking the appointment list or reminders on non-attendance rates? sending some kind of reminder in advance of the (2) Are there any differences in non-attendance when appointment. However, overbooking may not be considered using reminders sent manually (i.e. from phones an appropriate method in modern health-care delivery. On operated by a human) or automatically (i.e. by SMS the other hand, reminders directly to the patient from a text messages or by automated voice recordings)? hospital are generally acceptable. This can be viewed as a form (3) Does the time at which the reminder is sent influence of telemedicine, since it is an application of technology to the the effect on non-attendance rates? health-care process which involves distance. (4) What are the costs and benefits of using reminders? It seems reasonable to expect that sending reminders would decrease the no-show rate at hospital appointments. Methods ...................... ....................... ................. Accepted 1 August 2011 Correspondence: Per E Hasvold, Norwegian Centre for Integrated Care and Papers were selected following the PRISMA Telemedicine, University Hospital of North Norway, PO Box 6060, 9038 Tromsø, Norway (Fax: þ47 77 75 40 98; Email: [email protected]) methodology. A search of the PubMed database was Journal of Telemedicine and Telecare 2011; 17: 358 – 364 DOI: 10.1258/jtt.2011.110707 P E Hasvold and R Wootton Telephone and SMS reminders conducted on 21 February 2011 using the following This gave a possible score for study quality from zero to keywords: 14. Similar quality indicators have been used previously by 33,34 others. (telephone OR phone OR mobile OR cellphone) AND (outpatient OR out-patient) AND (attendance OR Effect size appointment OR reminder) Two effects were examined: the absolute and the relative change in DNA rate. The absolute change in the DNA rate Only papers published in 2000 or later, in English or any was calculated as the percentage of DNA in the control of the Scandinavian languages (Danish, Swedish or group minus the percentage of DNA in the intervention Norwegian) were included. In addition we examined the group. The relative change in the DNA rate was calculated reference lists of the papers selected for review. Duplicates by dividing the absolute change by the percentage of DNA were then eliminated. These were screened for relevance, i.e. in the control group. to confirm that they reported reminders using phones or SMS, leaving papers for full-text eligibility assessment. Papers were eliminated from the study if they provided Pooled estimate of effect size insufficient data about change in attendance or did not Weighted mean values were calculated using the quality describe reminders for a particular appointment, but scores as weights. general adherence to long-term programmes. Data extraction Data analysis In papers reporting the DNA rates only, we did not attempt All papers were analysed by both authors independently. to contact the authors for clarification or additional Any disagreements in interpretation were resolved by information about their data. We checked the numbers of consensus. Four of the selected papers described multi-arm patients involved and recalculated the rates to four studies in which reminders were sent both by phone and significant figures based on an integer number of by SMS, or by phone and by automated phone calls to patients. We analysed the data on an ‘intention separate groups. In these cases we used data from both to treat’ basis. arms of the study as though they were independent We categorised the interventions as manual or studies. automated. Manual reminders were telephone calls made by The outcome variable of interest was the Did Not Attend members of staff. Automated calls were either computer (DNA) rate. When a paper reported that a reminder was sent driven voice messages or computer driven SMS text ‘within a week before the appointment’ the reminder time messages. was assumed to be 3.5 days. We categorised the ages of the patients as child (neonatal/ paediatric/adolescent) (0–17 years), adult (18–60 years) or geriatric (.60 years). In some cases the age of the patients Study quality was unclear and we assumed it to be adult. A compound quality indicator was created for weighting the results according to the following indices: Results (1) Study size (0 ¼ not stated; 1 ¼ 1–100; 2 ¼ 101–1000; ...................... ....................... ................. 3 ¼ 1001–10000; 4 ¼ .10000); (2) Duration of intervention (0 ¼ duration not stated; The search returned 321 records. The reference lists of 1 ¼ 1–3 months; 2 ¼ 4–12 months; 3 ¼ .12 months); relevant papers (see below) produced another 99 records. (3) Study design (0 ¼ not stated; 1 ¼ retrospective After duplicates were eliminated there were 269 records. controls; 2 ¼ before and after, or non-randomized These were screened for relevance and the screening control study; 3 ¼ RCT). Note that in a retrospective eliminated 232 papers, leaving 37 papers for full-text trial, the baseline may have been measured in the year eligibility assessment. Of these, eight papers were before the intervention, i.e. there would have been an eliminated from the study, which left 29 papers for full 3–31 interval before the intervention started. In a before and analysis, see Table 1. Figure 1 shows the PRISMA after study, the intervention starts immediately after flowchart of the selection process. the baseline has been measured; (4) Cost of intervention (0 ¼ not stated; 1 ¼ estimate of Analysis costs; 2 ¼ measurements of costs according to current guidelines for economic evaluation in health care ); The analysis below is based on data from 29 studies (5) Savings from intervention (0 ¼ not stated; 1 ¼ estimate reporting a total of 33 estimates. Eighteen of the of savings; 2 ¼ measurements of savings according to interventions were based on manual reminders (i.e. phone current guidelines ). calls made by health staff) and 15 were based on automated Journal of Telemedicine and Telecare Volume 17 Number 7 2011 359 P E Hasvold and R Wootton Telephone and SMS reminders Table 1 Papers selected for review Reminder type (manual or Study Baseline Intervention Study automatic) size Country Study design DNA % DNA% Adams, 2004 Manual 2823 Australia Telephone reminders for 3 months; retrospective comparison with 12.2 9.0 previous year Booth, 2004 Manual 100 UK Telephone reminders for 4 months; concurrent and matched 40.0 14.0 groups Bos, 2005 Manual Automatic 216 Netherlands Telephone and SMS reminders for 0.75 months; concurrent 6.5 M: 2.7 A: 2.0 groups Chen, 2008 Manual Automatic 1848 China Telephone and SMS reminders for 2 months; RCT 19.6 M: 11.7 A: 12.5 Corfield, 2008 Manual 1077 UK Telephone reminders for 2 months; retrospective control group 21.4 19.7 da Costa, 2010 Automatic 29014 Brazil SMS reminders for 11 months; concurrent, non-randomized 25.6 19.4 ( patients who accepted SMS were sorted into the intervention group) Dockery, 2001 Manual 162 UK Telephone reminders for 2 months; before and after study 29.5 17.9 Downer, 2005 Automatic 2864 Australia SMS reminders for 1 month; retrospective comparison with 23.4 14.2 previous month Downer, 2006 Automatic 45110 Australia SMS reminders for 3 months; retrospective comparison with 19.5 9.8 previous year Foley, 2009 Automatic 709 UK SMS reminders for 1 month; retrospective comparison with 23.9 10.4 previous year Geraghty, 2007 Automatic 8966 Ireland SMS reminders for 36 months; historical control group consisted of 33.6 22.0 patients not sent SMS in the intervention period Hardy, 2001 Manual 325 UK Telephone reminders; duration not stated; single centre, 7.3 1.4 prospective, non-randomized, controlled study Hashim, 2001 Manual 823 USA Telephone reminders for 1 month; RCT 25.6 19.8 Haynes, 2006 Manual 515 USA Telephone reminders for 7 months; non-randomized controlled 11.6 4.7 study Irigoyen, 2000 Manual 653 USA Telephone reminders for 5 months; non-randomized controlled 35.0 34.9 trial Koshy, 2008 Automatic 9959 UK SMS reminders for 6 months; non-randomized controlled trial 18.1 11.2 Kruse, 2009 Automatic 1027 Denmark SMS reminders for 1 month; prospective cohort study 10.0 5.9 Lee, 2003 Manual 161 Ireland Telephone reminders for 2 months; before and after study 23.3 5.7 Leong, 2006 Manual Automatic 993 Malaysia Telephone and SMS reminders for 7 months; RCT 51.9 M: 40.4 A: 41.0 MacDonald, 2000 Manual 719 New Zealand Telephone reminders for 36 months; non-randomized controlled 24.4 18.4 study Maxwell, 2001 Automatic 1370 USA SMS reminders for 2 months; RCT 40.0 36.9 McPhail 2010 Automatic 145 USA SMS reminders for 12 months; non-randomised controlled study? 72.5 20.4 Milne, 2006 Automatic 16400 UK SMS reminders for 2 months; retrospective study 15.4 12.0 Parikh, 2010 Manual Automatic 9835 USA Telephone and SMS reminders for 5 months; RCT 23.1 M: 13.6 A: 17.3 Perron, 2010 Manual 2123 Switzerland Telephone reminders for 3 months; RCT 11.4 7.8 Reti, 2003 Manual 74 New Zealand Telephone reminders for 3 months; RCT 27.0 8.1 Roberts, 2007 Manual 504 UK Telephone reminders for 10 months; RCT 20.9 13.8 Satiani, 2009 Automatic 8766 USA SMS reminders for 17 months; non-randomized controlled study 5.9 8.9 Sawyer, 2002 Manual 171 Australia Telephone reminders for 6 months; RCT 20.0 7.9 reminders (i.e. automated phone messages or SMS automated calls; this was true for both the absolute and messages). The study characteristics are summarised in the relative change in DNA rates, see Figure 5 and 6 Table 2. respectively. The median DNA rate reported at baseline (i.e. in the The mean estimates of effect size are summarised in control group) was 23%. All studies except one reported that Table 4. the intervention improved the DNA rate. The median DNA rate reported after the intervention was 13%, Costs and savings see Table 3. Nine of the 29 studies were randomised controlled trials. None of the papers included costs and savings data to the The median study quality score was seven, see Figure 2. standard of accepted guidelines for economic evaluation in There was little evidence for publication bias based on a health care. An estimate of the cost of the intervention was funnel plot, see Figure 3. reported in 16 of the papers. Two of the estimates were not There was no obvious relation between effect size and the included in the present study as the cost estimates time at which the reminder was issued, see Figure 4 depended on circumstances or cost sharing models that (Spearman correlation 0.18). Three of the 29 studies stated were particular to the case. The cost estimates were that the reminder was sent within a week of the converted into Euros, using the exchange rate giving the appointment, which we assumed to be within 3.5 days for highest costs for the year the paper was published. The the purposes of analysis. The effect of reminders on DNA average estimated costs in these 14 studies was E 0.41 per rates was higher for manual reminder calls than for patient. The mean cost of phone reminders was E 0.90, 360 Journal of Telemedicine and Telecare Volume 17 Number 7 2011 P E Hasvold and R Wootton Telephone and SMS reminders Figure 1 The PRISMA flowchart for the paper selection process while the mean cost of SMS or automated phone call found no evidence that this was the case. Taking into reminders was E 0.14. The three highest reported costs were account the quality of the studies, the pooled estimates from phone reminders. show that manual reminders can achieve a reduction in the While savings were estimated in 10 papers, the DNA rate of 39% of the baseline value, while automated circumstances and cases could not be compared. reminders can achieve a reduction of 29% of the baseline value. It seems intuitive that reminders from a health-care professional would be more effective than those sent automatically by a computer. Our pooled estimate of effect size was based on a weighted Discussion ...................... ....................... ................. mean, using study quality as the weighting factor. We did not attempt a formal meta-analysis for several reasons. First, The present study concerns a systematic review of the use of only nine of the 29 studies were RCTs. Second, the studies telephone reminders (manual and automated) to improve were very heterogeneous. Finally, it was not possible to attendance at hospital appointments. All studies except one estimate the SE of the treatment effect from many of the found that sending reminders improved DNA rates. This published reports. Most of the papers reported the absolute suggests the possibility of publication bias, although we change in DNA. We used the relative change in DNA to Table 2 Study characteristics Lower Upper Median quartile quartile Study size 823 325 2864 Duration of intervention (months) 3 2 7 Reminder time (days before 2.75 1.00 3.13 appointment) Table 3 DNA rates reported in 29 studies (33 estimates), unweighted Lower Upper Median quartile quartile Baseline DNA rate (%) 23.1 15.4 27.0 Intervention DNA rate (%) 12.5 8.1 19.4 Absolute change in DNA rate (%) 7.0 4.2 11.5 Relative change (% of baseline value) 38.1 24.1 58.0 Figure 2 Study quality (median quality score ¼ 7) Journal of Telemedicine and Telecare Volume 17 Number 7 2011 361 P E Hasvold and R Wootton Telephone and SMS reminders Figure 5 Absolute change in DNA for manual and automated (SMS or Figure 3 Funnel plot of relative change in DNA rate (% of baseline automated phone call) reminders value) compensate for the different baseline DNA rates in the different settings of the studies. Although the quality of the economic data was weak, the apparent cost of sending reminders was much lower than the expected savings from avoided missed appointments. The time between the reminder and the appointment did not seem to have any strong effect on the DNA rate for any of the methods (see Figure 4). All studies involved reminders being sent out within a week, which appears to be an appropriate time ahead of an appointment to avoid people forgetting about it. An analysis of the relation between the age of the patients and the observed effect showed no difference between the age groups. Figure 6 Relative change in DNA (% of baseline) for manual and automated (SMS or automated phone call) reminders Limitations In the papers which studied two kinds of reminder studies since they were separate groups, when there might simultaneously, we treated the two arms as independent have been interdependencies. Our initial search was conducted using a single database and clearly if more databases had been used, more references might have been found. However a study by Bahaadinbeigy et al. suggests that more than 80% of telemedicine papers can be found by searching in Medline alone. We also conducted a search in the Psycinfo database, Table 4 Pooled estimates No of Weighted Unweighted estimates mean mean Manual reminders absolute change in DNA 18 8.3 8.9 rate (%) relative change in DNA rate 18 39.1 42.2 (% baseline) Automated reminders absolute change in DNA 15 8.9 9.7 rate (%) relative change in DNA rate 15 28.9 32.5 Figure 4 Effect size (relative change in DNA rate) and the time at which (% baseline) the reminder was issued 362 Journal of Telemedicine and Telecare Volume 17 Number 7 2011 P E Hasvold and R Wootton Telephone and SMS reminders 2 The PRISMA Statement. See http://prisma-statement.org/statement.htm using the same terms, but found no additional relevant (last checked 25 July 2011) studies. 3 Adams LA. Nonattendance at outpatient endoscopy. Endoscopy All studies except one showed a positive effect from using 2004;36:402–4 4 Booth PG, Bennett HE. Factors associated with attendance for first reminders. The exception was the study by Satiani et al. appointments at an alcohol clinic and the effects of telephone This study also differed from the others because the patients prompting. J Subst Use 2004;9:269–79 themselves chose in advance whether they wished to 5 Bos A, Hoogstraten J, Prahlandersen B. Failed appointments in an orthodontic clinic. Am J Orthod Dentofacial Orthop 2005;127:355–7 receive a reminder or not. This may have introduced a bias 6 Chen ZW, Fang LZ, Chen LY, Dai HL. Comparison of an SMS text in the intervention group. messaging and phone reminder to improve attendance at a health promotion center: a randomized controlled trial. J Zhejiang Univ Sci B 2008;9:34–38 7 Corfield L, Schizas A, Williams A, Noorani A. Non-attendance at the Further studies colorectal clinic: a prospective audit. Ann R Coll Surg Engl 2008;90:377–80 8 da Costa TM, Salomao PL, Martha AS, Pisa IT, Sigulem D. The impact of We recommend that rigorous health economics studies of short message service text messages sent as appointment reminders to the costs and savings of reminders should be carried out, patients’ cell phones at outpatient clinics in Sao Paulo, Brazil. Int J Med preferably in the form of randomized controlled trials. Inform 2010;79:65–70 9 Dockery F, Rajkumar C, Chapman C, Bulpitt C, Nicholl C. The effect of Without such studies, it is not possible to know with reminder calls in reducing non-attendance rates at care of the elderly certainty whether automated reminders such as SMS text clinics. Postgrad Med J 2001;77:37–39 messages are better than human-generated telephone calls 10 Downer SR, Meara JG, da Costa AC. Use of SMS text messaging to improve outpatient attendance. MJA 2005;183:366–8 (which are more expensive, but produce bigger 11 Downer SR, Meara JG, da Costa AC, Sethuraman K. SMS test messaging improvements in DNA rates). Future research should also be improves outpatient attendance. Aust Health Rev 2006;30:389–96 carried out to investigate the benefits of sending multiple 12 Foley J, O’Neill M. Use of mobile telephone Short Message Service (SMS) as a reminder: the effect on patient attendance. Eur Arch Paediatr Dent reminders, and whether that leads to ‘reminder fatigue’ in 2009;10:15–18 the recipients. Some of the papers in the present review 13 Geraghty M, Glynn F, Amin M, Kinsella J . Patient mobile telephone ‘text’ reported that the patients were not necessarily happy about reminder: a novel way to reduce non-attendance at the ENT out-patient clinic. J Laryngol Otol 2008;122:296–8 the reminder they had received, despite stating that they 14 Hardy KJ, O’Brian SV, Furlong NJ. Information given to patients before would still like to be reminded about any future appointments and its effect on non-attendance rate. BMJ appointments. 2001;323:1298–300 15 Hashim MJ, Franks P, Fiscella K. Effectiveness of telephone reminders Most papers only provided numbers for attendance or in improving rate of appointments kept at an outpatient clinic: non-attendance. Cancellations and rescheduling were not a randomized controlled trial. J Am Board Fam Pract 2001;14:193–6 reported in enough papers to be considered in the analysis, 16 Haynes JM, Sweeney EL. The effect of telephone appointment-reminder calls on outpatient absenteeism in a pulmonary function laboratory. but this is an important aspect of how reminders may Respir Care 2006;51:36–39 contribute to a better and more efficient use of the resources 17 Irigoyen MM, Findley S, Earle B, Stambaugh K, Vaugha R. Impact of and it is possible that the time of the reminder may have a appointment reminders on vaccination coverage at an urban clinic. Pediatrics 2000;106:919–23 more interesting effect on cancellations than on 18 Koshy E, Car J, Majeed A. Effectiveness of mobile-phone short message non-attendance. service (SMS) reminders for ophthalmology outpatient appointments: observational study. BMC Ophthalmol 2008;8:9 19 Kruse LV, Hansen LG, Olesen C. Udeblivelse fra aftale i børneambulatoriet. Ugeskr Laeger 2009;171:1372–5 Conclusions 20 Lee CS, McCormick PA. Telephone reminders to reduce non-attendance rate for endoscopy. J R Soc Med 2003;96:547–8 Sending appointment reminders from hospitals to patients 21 Leong KC, Chen WS, Leong KW, et al. The use of text messaging to can be seen as a form of telemedicine since it involves improve attendance in primary care: a randomized controlled trial. Fam distance and is an application of technology which Pract 2006;23:699–705 22 MacDonald J, Brown N, Ellis P. Using telephone promts to improve initial contributes to the health-care process. The evidence is attendance at a community mental health center. Psychiatr Serv overwhelming that reminders have a positive effect on 2000;51:812–4 non-attendance rates. Our study shows that a 39% 23 Maxwell S, Maljanian R, Horowitz S, Pianka MA. Effectiveness of reminder systems on appointment adherence rates. J Health Care Poor improvement in the baseline DNA rate can be expected Underserved 2001;12:504–14 when manual reminders are employed, and a 29% 24 McPhail GL, Ednick MD, Fenchel MC, et al. Improving follow-up in improvement when automated reminders are used. While hospitalised children. Qual Saf Health Care 2010;19:1–4 25 Milne RG, Horne M, Torsney B. SMS reminders in the UK National Health the costs were only estimated, the studies reviewed suggest Service: an evaluation of its impact on “no-shows” at hospital out-patient that reminders cost less than E 0.50 per patient for SMS or clinics. Health Care Manage Rev 2006;31:130–6 automated reminders. This seems likely to be much less 26 Parikh A, Gupta K, Wilson AC, Fields K, Cosgrove NM, Kostis JB. The effectiveness of outpatient appointment reminder systems in reducing than the cost of missed appointments and we therefore no-show rates. Am J Med 2010;123:542–8 recommend that reminders are used routinely for all 27 Perron NJ, Dao MD, Kossovsky MP, et al. Reduction of missed hospital appointments. appointments at an urban primary care clinic: a randomised controlled study. BMC Fam Pract 2010;11:79 28 Reti S. Improving outpatient department efficiency: a randomized controlled trial comparing hospital and general-practice telephone reminders. N Z Med J 2003;116:U458 References 29 Roberts N, Meade K, Partridge M. The effect of telephone reminders on 1 Henderson R. Encouraging attendance at outpatient appointments: can attendance in respiratory outpatient clinics. J Health Serv Res Policy we do more? Scott Med J 2008;53:9–12 2007;12:69–72 Journal of Telemedicine and Telecare Volume 17 Number 7 2011 363 P E Hasvold and R Wootton Telephone and SMS reminders 30 Satiani B, Miller S, Patel D. No-show rates in the vascular laboratory: 33 Hailey D, Ohinmaa A, Roine R. Study quality and evidence of benefit in analysis and possible solutions. J Vasc Interv Radiol 2009;20:87–91 recent assessments of telemedicine. J Telemed Telecare 2004;10:318–24 31 Sawyer SM, Zalan A, Bond LM. Telephone reminders improve adolescent 34 Bensink M, Hailey D, Wootton R. A systematic review of success and clinic attendance: a randomized controlled trial . J Paediatr Child Health failures in home telehealth. Part 2: final quality rating results. J Telemed 2002;38:79–83 Telecare 2007;13 (Suppl. 3):10–14 32 Drummond MF, Jefferson TO. Guidelines for authors and peer reviewers 35 Bahaadinbeigy K, Yogesan K, Wootton R. MEDLINE versus EMBASE of economic submissions to the BMJ. BMJ 1996;313:275–83 and CINAHL for telemedicine searches. Telemed J E Health 2010;16:916–9 364 Journal of Telemedicine and Telecare Volume 17 Number 7 2011

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Journal of Telemedicine and TelecareSAGE

Published: Sep 20, 2011

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