L Tanner1, Rpw Kenny1, M Still1, J Ling2, F Pearson3, K Thompson4, R Bhardwaj-Gosling1,2. 1. Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK. 2. Faculty of Health Sciences and Wellbeing, University of Sunderland, Sunderland, UK. 3. Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK Fiona.pearson2@newcastle.ac.uk. 4. Public Health England, London, UK.
This review summarises newly identified evidence, from January 1996 to December 2019, evaluating the NHS Health Check (NHS-HC) programme, building on an earlier rapid review published in 2017.The methods involved searches of published and grey literature sources, duplicate blinded screening, data extraction and quality appraisal and assessment of the quality of the overall body of evidence for each objective.Meta-analysis was not feasible due to the heterogeneous nature of the included studies.The results indicate that the NHS-HC programme increases the detection of individuals at risk of cardiovascular disease and that inequalities exist in NHS-HC attendance between population subgroups. Opportunistic invitations could increase uptake among these under-represented demographic groups.The overall body of evidence addressing the review objectives were ‘very low’ to ‘moderate’ quality therefore caution should be used when interpreting findings.
Introduction
The NHS Health Check (NHS-HC) programme is a cardiovascular disease (CVD) prevention programme introduced in 2009 aiming to assess all adults in England aged between 40 and 70 years old for CVD risk factors including obesity, physical inactivity, smoking and high alcohol consumption, high blood pressure and high cholesterol. Following assessment, using established tools, the level of individual risk is communicated to patients and evidence-based risk reduction interventions are implemented where appropriate.1 2An important aspect of the NHS-HC is the long-term goal of reducing inequalities in premature deaths from CVD, although the how was not explicitly stated.3 An observational study which used records from 9.5 million patients reported that NHS-HC attendees were more likely to be older and women, but were similar in terms of ethnicity and deprivation, compared with non-attendees.4 To address NHS-HC provider concerns5 regarding equity of access and to achieve the aim of reducing inequalities in premature CVD deaths, potential discrepancies in equity of access and outcomes must be identified and addressed.Cost-effectiveness of the NHS-HC has been a focal point for discussion. Original modelling estimated the programme could prevent 1600 heart attacks and strokes, at least 650 premature deaths and over 4000 new cases of diabetes each year, with an estimated cost per quality adjusted life year (QALY) of approximately £3000.6 Since then, it has been suggested that the programme is wasting large amounts of money (~£450 million).7 However, some evidence suggests the checks may be cost-effective, with small changes in body mass index (BMI) equating to a small but positive QALY gain of 0.05 per participant (cost-effectiveness ratio of £900/QALY).8 Additionally, such programmes could potentially be cost saving in the future if they correctly identify large numbers of people with CVD risk.9Given these challenges it is important to consistently update and review available evidence to assess the impact of NHS-HC and the extent to which it is meeting the goal of addressing health inequalities. Additionally, a review of the NHS-HC programme was announced in the government’s prevention green paper10 and this evidence review was undertaken with the intention of informing that review and potential changes to policy. We therefore aimed to update a previously completed rapid synthesis of published research evidence on the NHS-HC programme, which incorporates evidence from studies published up to 9 November 2016.1 The main findings of this earlier review included that NHS-HCs are associated with small increases in disease detection. Higher attendance (number of attendees as a function of those who are eligible) was found among older people, women, the most deprived populations (which may reflect targeting) and non-smokers. Take-up (number of attendees as a function of those who are invited) of an NHS-HC varied between population subgroups, with older persons, women in younger age groups, men in older age groups and people from the least deprived areas were more likely to attend. People did not take up the offer of an NHS-HC due to factors including lack of awareness of the service, competing priorities and difficulty with getting a general practitioner (GP) appointment. Of those who attended NHS-HC, satisfaction levels were high. Methods which could increase uptake are invitation modifications and text message invitations or reminders. Health professionals expressed concerns regarding inequalities in uptake of the programme and the clinical and cost-effectiveness of NHS-HC.The rapid review reported here aimed to update the aforementioned review, using the same objectives (as stated below).
Objectives
Our aim was to update an earlier rapid review1 and summarise newly identified evidence addressing the following research objectives:Who is and who is not having an NHS-HC?What are the factors that increase take-up among the population and subgroups?Why do people not take up an offer of an NHS-HC?How is primary care managing people identified as being at risk of CVD or with abnormal risk factor results?What are patients’ experiences of having an NHS-HC?What is the effect of the NHS-HC on disease detection, changing behaviours, referrals to local risk management services, reductions in individual risk factor prevalence, reducing CVD risk and on statin and antihypertensive prescribing?
Methods
A rapid review update reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A checklist of PRISMA items is presented in the online supplemental file S1.11
Patient and public involvement
No patients involved.
Literature searches
The following databases were searched, from January 1996 to November 2016 in the earlier review1 and from January 2016 to December 2019 for this update: MEDLINE, PubMed, Embase, Health Management Information Consortium (HMIC), Cumulative Index of Nursing and Allied Health Literature (CINAHL), Global Health, PsycINFO, the Cochrane Library, NHS Evidence, Google Scholar, Google, ClinicalTrials.gov and the ISRCTN registry, Web of Science, Science Citation Index and OpenGrey. Hand searching of key article reference lists was also completed. The search strategy is available in the online supplemental file S2.
Study selection
Studies from the earlier review1 were included in the review update. The studies from updated searches were split into batches and each record was independently reviewed by two authors (either RPWK and LT or LT and FP) based on title, abstract and full text using prespecified inclusion and exclusion criteria (available in the online supplemental file S3) to identify those eligible for inclusion in the update. Conflicts were resolved through discussion, with adjudication by a third reviewer (either FP or RB-G depending on who had not previously reviewed the record) where necessary.
Data extraction
A random sample of 10% of the data extraction completed in the original review1 was checked by LT and found to be consistent with information reported in the primary studies. Data from newly identified studies were extracted onto prespecified, piloted, data proformas. Data from each quantitative study was extracted by a single reviewer (either RPWK or LT). Extracted data were then checked for accuracy by a different reviewer (either RPWK or LT). Any conflicts were resolved through discussion or via adjudication by a third reviewer (FP) when necessary. Pertinent qualitative data including direct participant quotes, researcher interpretations and concepts were extracted in duplicate (by MS and FP) with discrepancies discussed and resolved. Data were coded against the themes previously identified.1 Emergent themes not previously identified were discussed and coded (by MS and FP). Duplicate extraction was completed for each qualitative paper by two reviewers from differing standpoints so as not to subconsciously affect the data being extracted and synthesised.
Quality appraisal
The quality of newly identified studies was assessed by a single reviewer then verified by a second. Any discrepancies were resolved through discussion and, where required, adjudicated by a third reviewer. Qualitative studies were assessed by MS or FP using The Critical Appraisal Skills Programme (CASP) checklist for qualitative research.12 Quantitative studies were assessed by RPWK or LT using a tool that was developed using CASP tools12 and implemented by the previous review authors1 to accommodate the range of study designs included.
Data synthesis
Synthesis of new quantitative and qualitative data were completed as an extension to that undertaken in the original review. Numerical data were combined using a structured, narrative synthesis. Meta-analysis was not methodologically appropriate due to high heterogeneity and a low number of high-quality studies reporting on each objective in a consistent manner. For the qualitative data, a three-stage thematic synthesis approach13 was planned in which newly identified studies could add to and potentially revise the original findings. This approach involves ‘line-by-line’ coding of the findings according to the content and meaning; developing ‘descriptive themes’ by grouping codes according to similarities and differences; generating ‘analytical themes’ based on the reviewer’s interpretation of the data in relation to the research question.13
Assessment of the certainty of the evidence
Grading of Recommendations Assessment, Development and Evaluations (GRADE),14 GRADE-Confidence in the Evidence from Reviews of Qualitative Research (GRADE-CERQual)15 and a method for assessing certainty of evidence in mixed methods reviews16 were used to assess the certainty and confidence in quantitative, qualitative and mixed methods evidence, respectively, contributing to each objective and subobjective as appropriate.
Results
The PRISMA flow diagram of included and excluded studies is shown in figure 1.
Figure 1
Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow chart depicting the flow of included and excluded studies.
Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow chart depicting the flow of included and excluded studies.Twenty-nine newly identified studies were eligible for inclusion. The numbers of newly identified studies mapping to each research objective are as follows: objective 1 (n=6), objective 2 (n=9), objective 3 (n=0), objective 4 (n=4), objective 5 (n=2) and objective 6 (n=13). Quality appraisal scores for each study are shown in online supplemental file S4. GRADE assessments are shown in online supplemental file S5. The overall certainty of evidence ranged from ‘very low’ to ‘moderate’. Results are also synthesised below in relation to each objective and subobjective.
Objective 1: differences in demographics of those attending and not attending an NHS-HC
NHS digital and Public Health England (PHE) published attendance data from 2012 to 2018.17 The national average attendance was 44.2%, with variation across regions (range=41.3%–49.2%). The variation was greater at a local authority level where 2017–2018 attendance varied from 19.5% to 75.8%. The original review identified 24 studies for this objective. This update identified six new studies.Generally, more older adults (eg, >60 years old) attended than younger adults.18–20 Evidence suggested men are less likely to attend than women,17–19 21 22 as statistically evidenced in21 (adjusted OR (AOR): 0.75, 95% CI: 0.67 to 0.84) and19 (AOR: 0.73, 95% CI: 0.67 to 0.8). Another study20 however, provide some evidence that men may be more likely to attend than women when the NHS-HCs were conducted opportunistically, where health checks are offered to patients during face-to-face medical consultations for other reasons.Attendance data regarding ethnic groups is inconclusive. The NHS Digital data17 shows that over the time period of 2012–2018, those of an Asian or black background had greater numbers of attendance than not attendance. While those of a white British background had a greater number of non-attendees compared with attendees. However, this varied greatly by year with no single ethnic group consistently attending more often than not attending.17 18 The authors of one study,18 however, claim that white British had greater attendance at a national level but given that white British make up most of the eligible population this finding could be misleading. Attendance by ethnicity probably varies depending on location. For example, community data from Leicester showed that people from black and minority ethnic groups were more likely to attend than white people.20 In terms of socioeconomic status, there is some evidence those from a higher level of deprivation (identified by Index of Multiple Deprivation (IMD)) are less likely to attend an NHS-HC.19 20 However, opportunistic NHS-HCs show an increase in attendance from those of a higher deprivation level.22There is evidence to suggest lower levels of NHS-HC attendance among smokers.20 21 One study20 also reported the effect of religion on attendance, suggesting higher attendance of non-Christians than Christians. Those with no religious background were less likely to attend overall. This finding was from a single small community-based study and it is, therefore, difficult to make any inferences about the wider population.The GRADE certainty in evidence rating for Objective 1 was ‘low’ due to the observational nature of study designs that contributed evidence.
Objective 2: what factors increase take-up among population and subgroups?
Uptake has maintained a range of 45%–50%, with recent national data from PHE reporting an uptake of 45.9% for 2018/2019.23 There are, however, variations by region and constituency. For example, in the North East uptake varied between 25% and 61%.
Objective 2.1: socio-demographic determinants of uptake
There were 11 quantitative studies included in the original review. We identify one new quantitative study conducted in two London boroughs (18 GP practices) reporting socio-demographic differences in uptake.24 A randomised control trial (RCT) assessing uptake via standard invitation letter or a question behaviour effect (QBE) questionnaire (with/without financial incentive) followed by the invitation letter. Uptake across the three trial arms was 15.3%. This is significantly lower than previously reported (27% in25; 34.1% in26 and 44.8% in27). One study24 also found men and younger people less likely to attend an NHS-HC. Those with a non-white ethnic background were more likely to attend, however, this study area includes a large proportion of individuals from a non-white ethnic background and results may not be reflective of the wider population. Contradictory to Objective 1 findings, those from the second least deprived quintile were more likely to attend than those from the most deprived.
Objective 2.2: invitation methods
Six new studies, adding to seven previously identified, assess the effects of different invitation methods, compared with the standard invitation letter, on uptake.24 28–32 Use of the QBE questionnaire alone or with a financial incentive (£5) did increase uptake when it was returned. There were, however, no statistically significant changes in risk difference between the two invitation types (1.52%, 95% CI: −0.03% to 3.07%, p=0.054). This is lower than previous research estimating a 3%–4% change.33 One study compared the use of modified letters and telephone invitations.30 While a different study compared a letter with yes/no SMS (short messaging service) pre and post invitation.32 Another study implemented new shorter leaflet styles (two vs four pages) but there were no statistically meaningful changes in uptake.31 Use of SMS reminders and time limited letters did, increase uptake31; confirming the positive results previously reported in a similar study.34 Telephone invitations also improved uptake compared with the standard letter invitation and a personalised CVD risk.30 A cost analysis suggests that for every 1000 patients invited by telephone (compared with standard letters) an additional 180 NHS-HCs could be expected, with an extra cost of £0.24/patient. Telephone invitations are also strongly preferred by primary care and outreach workers.35 Finally, the use of opportunistic invitations compared with the standard invitation letter improved uptake of those identified at greater CVD risk (ie, risk score 10%).29 Using opportunistic invitations also lead to an increase in younger patients attending.22
Objective 2.3: setting
This update identified two quantitative studies which assessed the impact of setting on uptake rates; none were identified in the earlier review. These studies compared a GP setting to an outreach service36 or community pharmacy.37 One of the studies targeted hard-to-reach groups using opportunistic methods. While GP attendance was three times more than the outreach services, people of a South Asian ethnicity and higher IMD were more likely to attend the outreach services.36 Men, however, were more likely to attend a GP than an outreach or community pharmacy service.36 37 The other study found minimal differences in uptake of NHS-HCs after invitation by letter.37 Opportunistic methods may provide greater uptake in some harder-to-reach patients.The GRADE certainty in evidence ratings for Objectives 2.1–3 ranged from ‘low’ due to the observational nature of study designs to ‘very low’ due to high risk of bias ratings.
Objective 3: why do people not take up an offer of an NHS-HC?
No new studies identified addressed this objective.
Objective 4: how primary care is managing people identified as being at risk of CVD or with abnormal risk factor results
The only study across both reviews to focus on risk management was.38 They assessed CVD risk factors in England over a 6-year follow-up period. An interrupted time series analysis revealed mean BMI following a health check was 0.3 kg/m2 (95% CI: 2 to 0.39 kg/m2) lower, while control patients’ (no health check) BMI increased (0.08 kg/m2, 95% CI: 0.07 to 0.09 kg/m2 per year).38 Additionally, after the 6-year period, patients who had a health check were less likely to be smokers (AOR: 0.9, 95% CI: 0.87 to 0.94). NHS-HC attendees also had lower systolic and diastolic blood pressure, and lower total cholesterol.38 High density lipoprotein was, however, slightly higher after 6 years (0.01, 95% CI: 0.002 to 0.02). This single large study provides evidence that NHS-HCs can increase provision of risk management advice and interventions.Fifteen qualitative studies were identified by the previous review, a further three are presented here. Three qualitative studies35 39 40 investigated the views of those responsible for delivery of NHS-HCs. Healthcare professionals interviewed by39 suggested that an NHS-HC was unlikely to be successful because people already knew the positive health behaviours they needed to engage with, but chose to ignore public health messaging. In a later study40 it was found that GPs seemed more negative towards delivery of NHS-HCs than other staff. NHS-HCs were seen as time consuming or unclear in terms of outcome. Several GPs felt that it would be more efficient if healthcare assistants (HCAs) conducted the NHS-HC as the HCAs role is more focused on health promotion activities so they are more likely to have the opportunity and skills to elicit more personal information from patients. In contrast, HCAs were unsure if they had the right skills to undertake NHS-HCs, and indeed, whether this should be part of their role. One study found health professionals thought it was beneficial to have someone from a similar ethnic background invite a patient for an NHS-HC, as they understood how certain elements of the NHS-HC would relate to specific communities.35 They also identified that employing outreach workers freed up GP and practice staff time to focus on other tasks. However, as outreach staff worked across multiple practices in the district, some practice managers were negative about the system as it meant they did not operationally manage them.The certainty in evidence rating for Objective 4 was ‘moderate’. Lack of objectivity was the main area of concern across studies addressing this objective.
Objective 5: patient views on NHS-HCs
One study found patients felt a sense of obligation to attend and be ‘a willing patient’, but family history affected how likely they were to make a change.41 Some pointed to longevity in their family as a reason to avoid changing their health behaviours, others felt that as family members had high risk of CVD disease, it was inevitable they too would experience high risk, regardless of any behaviour change. In two studies by the same author39 40 patients could not recall a specific risk score but did remember discussions around their current state of health. People felt more able to make changes when their family and friends supported and facilitated them to do so. Individuals valued being able to use their results from their NHS-HC to converse with their support networks identifying and introducing changes to their behaviours. While one patient found the form filling and nature of the questioning to be off-putting,41 the majority felt the experience of having a health check was positive.The certainty in evidence rating for Objectives 5 was ‘low’ due to the subjective nature of participant data, to ‘moderate’.
Objective 6: effects of the NHS-HC programme on health outcomes
Studies mapped to Objective 6 assessed the effects of the NHS-HC on one of the following predefined health outcomes: disease detection, changing behaviours, referrals to local risk management services, reductions in individual risk factor prevalence, reducing CVD risk and statin and antihypertensive prescribing.
Objective 6.1: disease detection
Seventeen studies reported data on disease detection, five of these were newly identified. One of the newly identified studies used data from 455 GP practices across England.42 Incidence rates of detected non-diabetic hyperglycaemia and type 2 diabetes were significantly higher among individuals registered at GP surgeries with high NHS-HC coverage, compared with low coverage surgeries. Rates of non-diabetic hyperglycaemia were reported to be 19% higher in the high coverage compared with the low coverage group (HR 1.19, 95% CI: 1.01 to 1.41) and rates of type 2 diabetes were 10% higher (HR 1.11, 95% CI: 1.03 to 1.19).42Four studies used samples from smaller areas of England. One of the studies reported that individuals who received opportunistic NHS-HCs offered during patient encounters for other reasons, were significantly more likely to have a higher 10-year risk of CVD (CVD risk score ≥10%, assessed using the Joint British Societies’ ‘JBS3’ risk calculator) compared with individuals who chose to attend following an invitation.29 Two studies reported that NHS-HC attendance compared with non-attendance was associated with significant increase in detection or diagnosis of the following conditions: CVD risk >10%43; diabetes and hypertension,43 44 total cholesterol43 and chronic kidney disease (CKD).44 A different study compared disease detection rates between NHS-HC attendees from different socioeconomic groups and reported a significant increase in the detection of CVD risk >20% among individuals from the most deprived IMD decile.21
Objective 6.2: health-related behaviours
Five studies (one newly identified) reported data on health-related behaviours. The newly identified study used national (England) data from the Clinical Practice Research Datalink data set. NHS-HC participants were less likely to be smokers compared with a control group after 6 years’ follow-up (health check 17% vs controls 25%; OR 0.90, 95% CI: 0.87 to 0.94, p<0.001) however, a greater reduction in smoking prevalence was reported for the control group.38
Objective 6.3: risk management referrals
Ten studies (four newly identified) reported data quantifying the proportion of NHS-HC attendees who were referred to lifestyle services. Two of the new studies used data from across England,40 45 one study involved a sample of 151 general practices in Hampshire43 and the other from 38 GP practices in Bristol.19The proportions of NHS-HC attendees who were offered risk management advice or referrals varied between studies and in relation to the risk factor addressed, from 1.8% to 90% for smoking cessation interventions, <1%–73% for weight management interventions among patients with a BMI of ≥30 and between 0.01%, and 33.9% for interventions to reduce alcohol consumption among patients who consumed ≥14 units per week. This is likely reflective of geographical variations in referrals between areas.
Objective 6.4: CVD risk
Five studies (one newly identified) assessed the change in CVD risk factor values following the NHS-HC. The newly identified study used national data from across England. Adjusted mean differences in 10-year CVD risk scores between intervention recipients and non-recipients at 6 years post-NHS-HC, were as follows: BMI (Kg/m2) −0.30 (95% CI: −0.39 to −0.20, p<0.001); systolic blood pressure (mean, mm Hg) −1.43 (95% CI: −1.70 to –1.16, p<0.001); diastolic blood pressure (mean, mm Hg) −0.93 (95% CI: −1.11 to −0.75, p<0.001) total cholesterol (mean, mmol/L) –0.05 (95% CI: −0.07 to –0.03, p<0.001), high density lipoprotein cholesterol (mean, mmol/L) 0.01 (95% CI: 0.002 to 0.02, p>0.05).38
Objective 6.5: prescribing of statins and antihypertensives
Sixteen studies (four newly identified) reported data on prescribing after the implementation of NHS-HC. One of the newly identified studies which used national data from across England reported that NHS-HC participants were more likely to receive statins (HR 1.24, 95% CI: 1.21 to 1.27, p<0.001) and were less likely to receive antihypertensive drugs (HR 0.86, 95% CI: 0.85 to 0.88, p<0.001) compared with non-attendees.38 One study found that new statin prescriptions were higher for NHS-HC attendees compared with non-attendees.44 The proportions of new statin prescriptions administered to NHS-HC attendees versus non-attendees were 11.5% and 8.2%, respectively. These data were from 143 general practices in three clinical commissioning groups in east London (England, UK). A different study also reported that NHS-HCs led to increased use of statins (OR 1.54, 95% CI: 1.39 to 1.71) in addition to antihypertensives (OR 1.15, 95% CI: 1.06 to 1.24) using data from 151 GP practices in Hampshire.43 Another study compared prescribing rates between population subgroups (men/women and age group) among NHS-HC attendees using data from GP practices in Bristol.19 The results indicated that women were more likely than men to be prescribed a cardiovascular drug, (OR 1.18, 95% CI: 1.03 to 1.35) as were patients aged ≥70 years compared with aged ≤70 years (OR 1.64, 95% CI: 1.14 to 2.35). In the same study, individuals classified as being at high risk of CVD were most likely to be prescribed CVD medication (OR 6.16, 95% CI: 4.51 to 8.40). There was no evidence of any association between the prescribing of CVD medication and socioeconomic status or ethnicity.
Objective 6.6: economic modelling studies
Six studies (three newly identified) assessed the cost-effectiveness of the NHS-HC programme based on different implementation approaches. Two of the new studies, which are related, assessed implementation and redesign scenarios using demographic data from Liverpool’s population, exposure to risk factors and CVD epidemiology to assess health benefits, equity and cost-effectiveness.46 47 The third study assessed whether the impact of the checks on BMI was sufficient to justify its costs.48 The two related studies reported that the equitability and cost-effectiveness of the NHS-HC programme would be increased through the addition of policies targeting dietary consumption and through combining current provision with targeting of the intervention in deprived areas.46 47 The third study reported that even modest changes in BMI from the NHS-HC programme are associated with significant cost-saving benefits making the programme cost-effective.48The GRADE certainty in evidence ratings for Objectives 6.1–5 ranged from ‘very low’ due to risk of bias, indirectness, imprecision and inconsistency, to ‘moderate’.
Discussion
The goal of the NHS-HC programme is to identify and reduce CVD risk in those aged between 40 and 74 years. This rapid review aimed to update existing evidence on a previously completed review.1
Principal findings
The proportion of published studies has increased by 43% since the earlier review.1 However, the majority of the key findings from the original review remain unchanged in this review update. The overall results from the earlier review and the review update are summarised as follows for each objective along with the findings from a body of relevant evidence identified prior to the publication of this review:
Objective 1: who is and who is not having an NHS-HC?
There is higher NHS-HC attendance among women and people aged 60 years and over. The association between female gender and NHS-HC attendance was confirmed by a newly identified study.49 The evidence synthesised in this review indicated that smokers and those from high levels of deprivation are least likely to take up an invitation to attend an NHS-HC, although a more recent study on over 9.5 million people reported no significant evidence of inequity of attendance by deprivation level.4 There is mixed evidence regarding the association between ethnicity and NHS-HC attendance. Newly located studies report higher attendance among South Asian ethnic groups49 and people with serious mental illnesses.50
Objective 2: what are the factors that increase take-up among the population and subgroups?
Opportunistic invitations, telephone invitations and text message reminders increased uptake compared with the standard invitation letters. Additionally, delivery setting influenced uptake in population subgroups, with people of a South Asian ethnicity and higher IMD more likely to attend the outreach services.35 An RCT published in 2021 found that automated prompts to clinical staff to invite patients to NHS-HCs, delivered via computer systems in general practice, improved uptake, especially for men and younger patients.51
Objective 3: why do people not take up an offer of an NHS-HC?
The earlier review1 reported that lack of awareness or knowledge, competing priorities, misunderstanding the purpose, an aversion to preventive medicine, difficulty getting an appointment with a GP and concerns about privacy and confidentiality reduced NHS-HC attendance among the general population. A newly identified study, published in 2020, identified barriers to NHS-HC uptake among prisoners, which included poor accessibility to the healthcare department, stigma of visiting healthcare and fear surrounding the NHS-HC.52
Objective 4: how is primary care managing people identified as being at risk of CVD or with abnormal risk factor results?
We found variations in risk management referrals across the reviewed studies, possibly reflecting geographical variations. A newly retrieved study reported that overall fidelity of delivery of NHS-HCs in general practice was high, however, important elements of the NHS-HC, including assessments in relation to ethnicity and family history of disease, in addition to the Alcohol Use Disorders Identification Test and dementia risk management, were being regularly omitted.53 Another new study found that practitioners often demonstrated limited understanding and confidence in explaining the 10-year risk score to patients, whereas confidence in the JBS3 lifetime CVD risk calculator, with its visual information summaries, was higher.54
Objective 5: patient views on the NHS-HC programme
Overall patient satisfaction levels with the programme were high, however the risk score was less helpful to patients than discussion about their health with the clinician during the NHS-HC. Although more recent research suggests that visual representations of CVD risk were more easily understood than a percentage risk score.55 Behaviour change may be influenced by perceived risk based on family history and social support. A newly identified study reported that participants did not like the form-filling aspect of the NHS-HC.56
Objective 6: what is the effect of the NHS-HC on disease detection…?
Overall, the NHS-HC programme is associated with increased detection of CVD risk factors and diagnoses, increased prescribing of cardiovascular medications and with a general reduction in CVD risk factors. The results from two newly identified studies confirmed these findings.49 57 The economic evidence indicated that the cost-effectiveness of the NHS-HC programme varies; population-wide interventions were more cost-effective than individual level interventions and interventions targeted at deprived areas were more cost-effective compared with non-targeted interventions. A study published in 2020 found that people with serious mental illnesses were more likely to: attend an NHS-HC; have higher rates of CKD and type 2 diabetes; and have received treatment with statins and antihypertensive medication, compared with people without these conditions.50
Strengths and weaknesses of the study
The methods used to review the evidence available on the NHS-HC programme involved searches of published and grey literature sources, duplicate blinded screening, data extraction and quality appraisal and assessment of the quality of the overall body of evidence for each objective. Methods used to synthesise the new data with the existing body of evidence were appropriate given the quantity and types of new studies identified. Review limitations included that it was not possible to perform meta-analysis due to the heterogeneous nature of the included studies. The use of ‘vote counting’ methods potentially compromises the precision of the results.58 Also, the searches undertaken for this review update were completed in December 2019, 2 years prior to publication of this manuscript. The evidence presented therefore, does not include more recent publications.
Strengths and weaknesses of the available evidence
General consistency of findings across studies in relation to each review objective supports causal inferences regarding the direction of effect of the NHS-HC programme on the health-related outcomes assessed. The overall quality of evidence varied between objectives and ranged from ‘very low’ to ‘moderate’, reflecting issues including that most studies were observational with confounding and poor internal validity (assessed using risk of bias). Furthermore, inconsistent data collection and reporting across many of the studies reduces precision of estimated effect of the NHS-HC programme on health-related outcomes.
Implications for policy and practice
The results from this review could inform changes to the methods used to invite eligible individuals to attend an NHS-HC, for example, by modifying the invitation method (eg, telephone invitations and sending text message reminders). Opportunistic recruitment could be used to selectively target specific groups who are at greater risk, as well as those who are less likely to engage with the NHS-HC programme.
Unanswered questions and future research
There is a need to understand more fully the effect of the programme on lifestyle behaviours including further research to explore the impact of attending an NHS-HC on physical activity, diet and alcohol consumption. The identified barriers to the uptake of an NHS-HC need to be explored in more depth as they could inform improvement of recruitment to the programme. In particular, future research should examine the potential of NHS-HC to widen inequalities given the demographics of participants identified in our review. A review of interventions for CVD (eg, physical activity or diet change), outside of the NHS-HC programme could help inform further development of the programme.
Conclusions
The NHS-HC programme increases the detection of individuals at risk of CVD. The overall body of evidence addressing the review objectives were ‘very low’ to ‘moderate’ quality therefore caution should be used when interpreting findings, which appear to show that inequalities exist in NHS-HC attendance between population subgroups. There are also geographical variations rates of referral to lifestyle services following NHS-HC. Targeting NHS-HC towards high-risk communities (eg, deprived communities) may increase the cost-effectiveness of the programme. Uptake may be increased through opportunistic invitations in addition to addressing misconceptions regarding the purpose, importance and confidential nature of the programme. Discussion between NHS-HC attendees regarding their health and their GP may be more helpful than receiving a risk score, which may not be understood or remembered by the patient. Family history of disease and social support could determine the impact of the intervention on behaviour change.
Authors: Chris Kypridemos; Brendan Collins; Philip McHale; Helen Bromley; Paula Parvulescu; Simon Capewell; Martin O'Flaherty Journal: PLoS Med Date: 2018-05-29 Impact factor: 11.069
Authors: Victoria R Cornelius; Lisa McDermott; Alice S Forster; Mark Ashworth; Alison J Wright; Martin C Gulliford Journal: Trials Date: 2018-06-27 Impact factor: 2.279
Authors: Martin C Gulliford; Bernadette Khoshaba; Lisa McDermott; Victoria Cornelius; Mark Ashworth; Frances Fuller; Jane Miller; Hiten Dodhia; Alison J Wright Journal: J Public Health (Oxf) Date: 2018-06-01 Impact factor: 2.341