DÄ internationalArchive39/2019Increasing Influenza Vaccination Rates in People With Chronic Illness

Original article

Increasing Influenza Vaccination Rates in People With Chronic Illness

A systematic review of measures in primary care

Dtsch Arztebl Int 2019; 116: 645-52. DOI: 10.3238/arztebl.2019.0645

Sanftenberg, L; Brombacher, F; Schelling, J; Klug, S J; Gensichen, J

Background: The safety and efficacy of influenza vaccination for the chronically ill are clearly supported by the evidence, yet vaccination rates in this vulnerable population remain low. This leads to many avoidable hospitalizations and deaths in Germany every year. The goal of this systematic review is to identify measures in primary care medicine that can be used to increase influenza vaccination rates among the chronically ill.

Methods: This review was carried out as recommended in the PRISMA statement. A systematic literature search was performed. Only randomized, controlled trials were included in the analysis. Details can be found in the study protocol (PROSPERO, CRD42018114163).

Results: 15 trials were included in the analysis. Training sessions for medical practice teams focusing on a particular disease raised the vaccination rates by as much as 22%. A financial incentive had the greatest effect (relative risk [RR]: 2.79; 95% confidence interval: [1.18; 6.62]). Reminders via text message yielded a maximum 3.8% absolute increase in vaccination rates. Complex interventions were not found to be of any greater benefit than simple ones.

Conclusion: A variety of approaches can be effective. Focusing training sessions for medical practice teams on certain diseases may be of greater benefit than vaccination-centered training sessions. Reminder systems for doctors should be more reliably implemented. Simple strategies are perhaps the most suitable ones in the heterogeneous population of chronically ill persons. The limitations of this systematic review include the heterogeneity of the studies that we examined and the small number of studies in each category.

LNSLNS

In the 2017/2018 influenza season, around 45 000 patients were admitted to hospital for treatment of seasonal influenza in Germany alone; 1674 deaths due to this disease were reported to the Robert Koch Institute (e1). The course of the illness and the risk of hospitalization or death vary depending on the general health status of the individual patient. The young, the elderly, and the chronically ill are especially vulnerable (1, e1). For instance, a study published in 2017 showed that 86% of patients admitted to the hospital with an “influenza-like illness” (ILI) had at least one chronic (≥ 65 years) medical condition. The prognosis was poor despite adequate treatment: more than 30% of the patients needed intensive care, and 14.8% of them died in the hospital (1). Besides the individual consequences, the additional consultations and hospitalizations caused by seasonal influenza represent a heavy burden on the entire healthcare system. Chronically ill patients have frequent contacts with their primary care physicians (e2), who therefore carry a large share of the extra load (2).

The treatment of influenza is primarily symptomatic; in the early stage, the population at risk should also be given antiviral drugs (3). The most effective way of combating the virus is prophylactic vaccination, shown in many studies to be efficacious and safe, particularly with reference to the chronically ill (4, e3e6).

A vaccination rate of 90% among the chronically ill is necessary to attain herd immunity (5). However, this quota is rarely achieved. Depending on country, population, and age group, rates of between 9% and 70% have been observed (68). In Germany, the vaccination rate in chronically ill patients below 60 years of age was 24.1% in the season 2012/2013 and 22.6% in 2013/2014 (9). Among those over 60, the rate was 43.6% in 2010/2011, but only 34.8% in 2016/2017 (e7). Consequently, it is essential to improve vaccination rates, especially in high-risk populations. Given their coordinating role in the healthcare system and their professional focus, primary care physicians would appear especially well suited to implement these interventions.

The aim of our study was to evaluate measures taken to increase the rates of vaccination against seasonal influenza among people with chronic illness in the primary care setting.

Methods

This systematic review was conducted in accordance with the PRISMA Statement for systematic reviews (e8). A detailed description of the methods can be found in the study protocol (PROSPERO CRD42018114163) and in the eMethods (10). We included randomized controlled trials that had been carried out by or were focused on primary care physicians and which examined strategies to increase the rate of vaccination against influenza in the chronically ill. The systematic literature survey (eBox) was performed in October 2018.

Search strategy for MEDLINE and Embase via Ovid
Search strategy for MEDLINE and Embase via Ovid
eBox
Search strategy for MEDLINE and Embase via Ovid

The Cochrane risk-of-bias tool was used to assess the risk of bias in the studies included for analysis (e9). After assigning the individual criteria 0 points for high, 1 point for unclear, and 3 points for low risk of bias, we summed the risk scores to form a quality factor (QF; modified according to [11]), which served to enhance comparability. On the basis of this factor the quality of each trial was rated as low (0–10 points), moderate (11–14 points), or high (at least 15 points).

We preferentially extracted adequately corrected results (e10) from cluster-randomized studies. Whenever possible, intention-to-treat analyses were carried out. Owing to the high methodological, clinical, and statistical heterogeneity of the trials, meta-analysis with calculation of a pooled effect estimator was not a suitable means of synthesizing our data.

Results

Fifteen trials were included for analysis (Figure 1) (1226). The populations studied varied widely. At least 77% of the patients included were below 65 years of age. Eleven of the trials had investigated patients with cardiovascular disease, while the remaining four focused on chronic obstructive pulmonary disease (COPD) or asthma. There were no studies on patients with mental illness. The categorization of the trials is shown in Table 1, their characteristics in Table 2 and the eTable. Besides their methodological and clinical heterogeneity, the trials exhibited marked statistical heterogeneity: assessed according to Higgins and Thompson (e11), the heterogeneity of the studies was I2 = 87 % for those focusing on training of office teams, I2 = 85% for those on enhancing the competence of medical professionals, and I2 = 94% for those on sending text-message reminders.

Flow chart for selection of studies
Flow chart for selection of studies
Figure 1
Flow chart for selection of studies
Categorization of the interventions
Categorization of the interventions
Table 1
Categorization of the interventions
Characteristics of the studies included for analysis
Characteristics of the studies included for analysis
Table 2
Characteristics of the studies included for analysis
Detailed characteristics of the studies included for analysis
Detailed characteristics of the studies included for analysis
eTable
Detailed characteristics of the studies included for analysis

The quality of the trials included for analysis also varied widely (for details see the eFigure). Blinding of outcome assessment was mostly assessed as bearing a low risk of bias, because many authors used objective recording methods. Assessment of the risk of incomplete outcome data or selective outcome reporting was often not possible because study protocols were not available.

Assessment of the risk of bias
Assessment of the risk of bias
eFigure
Assessment of the risk of bias

Effectiveness of interventions

Patient-centered studies tended to have larger samples. Overall, studies focused on medical personnel were of higher quality (Figure 2).

Forest plot: effect of interventions
Forest plot: effect of interventions
Figure 2
Forest plot: effect of interventions

Interventions focussed on medical personnel

Training for office teams was examined in three trials. COPD care packages, investigated by Markun et al. (18) and Zwar et al. (26), demonstrated significant positive effects (relative risk [RR] 1.35, 95% confidence interval [1.14; 1.59] and RR 1.29 [1.03; 1.62], respectively), with control group vaccination rates of 61.6% and 49.1%. Siriwardena et al. (23) achieved improvement of the vaccination rate by 22% in patients post splenectomy by means of a vaccination-centered workshop, but the sample was very small (n = 169 patients), so the effect size was not significant (RR 1.08 [0.90; 1.25]). Only slight, non-significant improvements were achieved in patients with coronary heart disease or diabetes mellitus (RR 1.02 [1.00; 1.04]); however, very high proportions of patients were vaccinated even without intervention (72.5 % and 70.2 %, respectively). Studies in this category were of moderate to high quality (QF 12 to 18).

Automatic reminder systems for physicians with printed vaccination recommendations on documentation forms proved effective in the trial by Chambers et al. (15) (RR 1.86; p = 0.001). The vaccination rate was lower among participants whose physicians received reminders for only half of their patients. For unknown reasons, digital reminders were also generated for only half of the patients included in the trial by Tierney et al. (25), leading to a vaccination rate 2.2% lower than in the control group (RR 0.95; [0.67; 1.35]). In both cases, the control group vaccination rate was around 20%. Studies in this category were of moderate to high quality (QF 14 to 15).

Programs to enhance the competence of medical professionals were generally complex interventions of low to moderate quality (QF 9 to 12). Beck at al. (14) achieved a significantly positive result by treating patients in the framework of structured group visits under the supervision of medical professionals (RR 1.27 [1.11; 1.46]). In contrast, a study by Hermiz et al. (16) showed that home visits by a community nurse in contact with the responsible primary care physician resulted in a vaccination rate 7.4% lower than in the control group (RR 0.89 [0.70; 1.12]); there were problems with the quality of implementation and the communication between nurse and physician. In both cases, the control group vaccination rate was around 65%.

Altogether, simple interventions achieved greater effects and were more likely to produce significant results than complex interventions.

Interventions focussed on patients

The effect of sending text-message reminders to patients was investigated in two high-quality studies (QF 17 to 18) by Herrett et al. (17) and Regan et al. (22). The former had a vaccination rate of 50% in the control group and were able to achieve an absolute increase of only 1.7% (RR 1.05 [1.00; 1.11]), while the latter attained a significant absolute increase of 3.8% over the rate of 9.1% in the control group (RR 1.41 [1.22; 1.63]).

Personalized postcard reminders were used by Spaulding et al. (24) in a high-quality study (QF 16) and by Baker et al. (13) in a low-quality study (QF 10). Compared with the 9% figure in the control group, Spaulding et al.’s personalized postcard raised the vaccination rate by 16.1% (RR 2.77 [2.05; 3.75]). Baker et. al. found that only a personalized postcard achieved a significant result in both subgroups, with generally greater effect sizes (RR 1.09 and 1.11; p <0.05) than for a non-personalized postcard (RR 1.05 and 1.07; p >0.05). The control group vaccination rate was 35.8 for patients under 65 and 50.7% for those over 65.

Studies in which the patients received reminder letters were of low quality (QF 7 to 10). The letters were personalized and featured an educational element. Only in their younger subpopulation did Baker et al. (13) achieve a significant effect (RR 1.09; p <0.05). In the study by Moran et al. (19), a single reminder letter reduced the vaccination rate by 0.5% in comparison with the control group (RR 0.99 [0.60; 1.63]). Mullooly et al. (21) found a significant increase of 8.8% in the vaccination rate compared with 30.1% in the control group (RR 1.29 [1.15; 1.45]).

Moran et al. (20) investigated the effectiveness of sending an educational brochure and providing a financial incentive, alone and in combination, in a study of moderate quality (QF 13). All three interventions achieved statistically significant improvements over the vaccination rate of 9.4% in the control group. The combination of brochure and financial incentive (RR 2.78 [1.13; 6.87]) was superior to the brochure alone (RR 2.53 [1.04; 6.15]), but not to the financial incentive alone (RR 2.79 [1.18; 6.62]).

Ahmed et al. (12) and Moran et al. (19) compared sending two reminders to each patient with sending only one reminder. In the former study, the vaccination rate fell by 5.8% in 18- to 49-year-olds and rose by 4.6% in 50- to 64-year-olds (RR 0.94 [0.84; 1.05] and RR 1.08 [1.00; 1.15], respectively). In the latter, the rate went down by 6.1% (RR 0.80 [0.46; 1.38]).

Discussion

The identified interventions designed to increase the vaccination rates for seasonal influenza among people with chronic illness in the primary care setting are heterogeneous. We found that both interventions focused on patients and interventions focussed on medical personnel have been implemented successfully.

Interventions focussed on medical personnel

Both Kovacs et al. (11) and Forsetlund et al. (27) conjectured that training programs alone can exert only limited influence on complex behavior patterns. Among the studies we analyzed, training courses for office teams that were oriented on the management of a particular disease (18, 26) achieved better results than a vaccination-centered approach (23). Consequently, training programs with an obvious bearing on routine practice may be effective; however, the effect should not be overestimated.

Reminder systems for physicians were effective only when the messages were generated for all eligible patients (15, 25). Therefore, any such system needs to be highly reliable. A related approach involves standardized checklists: these are intended to help assess the indication for vaccination and were found by Mendu et al. (28) and Merkel et al. (29) to have a positive effect on vaccination rates.

Group visits to enhance the competence of medical professionals showed positive effects (14), whereas cooperation between community nurses and primary care physicians may be difficult (16). A related approach is the blanket delegation of vaccination—indications and implementation—by physicians to their office nurses (30). Overall, there is broad evidence for the efficacy of extending the competence of medical professionals (31); indeed, this is now common practice in countries such as the UK and the USA (32).

Interventions focussed on patients

Text-message reminders to remind patients about vaccination, investigated in two recent high-quality studies (17, 22), showed no advantage over letters or postcards. Both studies found that such reminders achieved only slight increases in vaccination rates. The great strength of this type of intervention is its wide scope; the two studies analyzed here had extremely large sample sizes (102 257 and 6245 patients respectively). Consequently, there is sufficient evidence for the positive effect of text-message reminders in increasing chronically ill patients’ adherence to their physicians’ recommendations (e12).

Overall, the implementation of patient reminder systems in Germany seems inadequate (33); universal coverage would be desirable. Written reminders addressed directly to patients can also be effective in Germany, as shown by Schulte et al. (34) in a sample of patients with chronic kidney disease.

A number of publications described the use of financial incentives as an element of influenza vaccination campaigns (e13). Like other researchers before us (20), we found that this type of intervention had the greatest effect.

A personal recommendation by the patient’s own doctor has been described as a powerful predictor of subsequent vaccination (e14, e15). The credibility of the source is also a major factor in the assessment of the indications for vaccination and the associated risks following an educational program (e16). Personalized invitations to attend for screening colonoscopy showed a positive effect in Germany (35, 36). Our findings do not permit any clear conclusions with regard to the respective effects of personalized and non-personalized invitations, but overall one can by all means assume a benefit of personalization.

Educational interventions have previously been described as an appropriate way of filling gaps in knowledge (e17) and improving vaccination rates (e18). Addition of an educational element to patient reminders yielded indifferent results in our study, however, leading to neither an increase nor a decrease in vaccination rates.

Complexity of interventions

In the studies we investigated, simple interventions displayed higher quality and wider-reaching effects than complex interventions. A second reminder had no additional effect, and the inclusion of an educational element did not necessarily improve the end result. The combination of an educational brochure and a material incentive was not significantly superior to either measure alone. All this supports the previous observation that complex interventions do not automatically generate greater effects (11, 31, e19). Simple approaches may therefore prove eminently suitable means of improving the vaccination rate in large populations with heterogeneous attitudes and requirements.

Perspective

Authors have described promising interventions to increase the vaccination rates of at-risk populations in settings other than primary care and outpatient clinics. One suitable environment may be the emergency room, where the proportion of patients at risk is much higher than in the total population (37). Rimple et al. (38) increased the influenza vaccination rate of high-risk patients in a surgical emergency department from 16% to 83% by screening all patients for indications. Screening before certain operations or in the presence of particular clinical constellations in the inpatient setting, as reported by Gurfinkel et al. (39), also led to higher vaccination rates. As outlined by Schulte et al. (34), vaccination programs in Germany could in future be implemented largely by health insurance funds or federal institutions.

Limitations

Although our search covered the four major relevant databases and the gray literature, pertinent publications may have been overlooked. The quality of the studies we evaluated was variable, and some had very small samples. Since we found no significantly negative results, publication bias cannot be ruled out. The Pearson correlation coefficient was significantly negative for the control group vaccination rate and the RR per study (r = −0:650; p = 0.01); consequently, our results could also suffer from ceiling effects (40). In some cases we had to use the results of cluster-randomized studies without sufficient correction, thus impairing quality and power. The studies were highly heterogeneous in terms of patients, country, healthcare system, and interventions, which particularly limits the external validity of our findings.

Funding

The project was not supported by external funding.

Conflict of interest statement
Prof. Schelling has received consultancy fees from Pfizer, MSD, GlaxoSmithKline, and Sanofi; lecture fees from Pfizer, MSD, and GlaxoSmithKline; and third-party funding for a project of his own initiation from Pfizer.

Dr. Sanftenberg has received payment for an expert opinion from the Society for Promotion of Vaccination Medicine (Gesellschaft zur Förderung der Impfmedizin).

The remaining authors declare that no conflict of interest exists.

Manuscript received on 2 April 2019, revised version accepted on
28 June 2019

Translated from the original German by David Roseveare

Corresponding author
Dr. rer. nat. Linda Sanftenberg
Institut für Allgemeinmedizin
Klinikum der Ludwig-Maximilians-Universität München
Campus Innenstadt

Pettenkoferstr. 10

80336 München, Germany
Linda.sanftenberg@med.uni-muenchen.de

Cite this as
Sanftenberg L, Brombacher F, Schelling J, Klug SJ, Gensichen J: Increasing influenza vaccination rates in people with chronic illness—a systematic review of measures in primary care. Dtsch Arztebl Int 2019; 116: 645–52.
DOI: 10.3238/arztebl.2019.0645

Supplementary material

For eReferences please refer to:
www.aerzteblatt-international.de/ref3919

eMethods, eBox, eTable, eFigure:
www.aerzteblatt-international.de/19m0645

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e24.
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e25.
Divine GW, Brown JT, Frazier LM: The unit of analysis error in studies about physicians’ patient care behavior. J Gen Intern Med 1992; 7: 623–9 CrossRef MEDLINE
e26.
Cochrane Effective Practice and Organisation of Care Review Group (EPOC): Data collection checklist. Institute of Population Health, University of Ottawa, 2002. https://methods.cochrane.org/sites/methods.cochrane.org.bias/files/public/uploads/EPOC%20Data%20Collection%20Checklist.pdf (last accessed on 1 August 2019)
Institute of General Practice and Family Medicine, University Hospital, LMU Munich, Munich: Dr. rer. nat. Linda Sanftenberg, cand. med. Felix Brombacher, Prof. Dr. med. habil. Jörg Schelling, Prof. Dr. med. Dipl. päd. Jochen Gensichen, MPH
Chair of Epidemiology, Faculty for Sport and Health Sciences, Technical University of Munich, Munich: Prof. Dr. rer. nat. et med. habil. Stefanie J. Klug, MPH
Flow chart for selection of studies
Flow chart for selection of studies
Figure 1
Flow chart for selection of studies
Forest plot: effect of interventions
Forest plot: effect of interventions
Figure 2
Forest plot: effect of interventions
Key messages
Categorization of the interventions
Categorization of the interventions
Table 1
Categorization of the interventions
Characteristics of the studies included for analysis
Characteristics of the studies included for analysis
Table 2
Characteristics of the studies included for analysis
Search strategy for MEDLINE and Embase via Ovid
Search strategy for MEDLINE and Embase via Ovid
eBox
Search strategy for MEDLINE and Embase via Ovid
Assessment of the risk of bias
Assessment of the risk of bias
eFigure
Assessment of the risk of bias
Detailed characteristics of the studies included for analysis
Detailed characteristics of the studies included for analysis
eTable
Detailed characteristics of the studies included for analysis
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