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Impacts of chronic disease prevention programs implemented by private health insurers: a systematic review

Abstract

Background

Chronic diseases contribute to a significant proportion (71%) of all deaths each year worldwide. Governments and other stakeholders worldwide have taken various actions to tackle the key risk factors contributing to the prevalence and impact of chronic diseases. Private health insurers (PHI) are one key stakeholders, particularly in Australian health system, and their engagement in chronic disease prevention is growing. Therefore, we investigated the impacts of chronic disease prevention interventions implemented by PHI both in Australia and internationally.

Method

We searched multiple databases (Business Source Complete, CINAHL, Global Health, Health Business Elite, Medline, PsycINFO, and Scopus) and grey literature for studies/reports published in English until September 2020 using search terms on the impacts of chronic disease prevention interventions delivered by PHIs. Two reviewers assessed the risk of bias using a quality assessment tool developed by Effective Public Healthcare Panacea Project. After data extraction, the literature was synthesised thematically based on the types of the interventions reported across studies. The study protocol was registered in PROSPERO, CRD42020145644.

Results

Of 7789 records, 29 studies were eligible for inclusion. There were predominantly four types of interventions implemented by PHIs: Financial incentives, health coaching, wellness programs, and group medical appointments. Outcome measures across studies were varied, making it challenging to compare the difference between the effectiveness of different intervention types. Most studies reported that the impacts of interventions, such as increase in healthy eating, physical activity, and lower hospital admissions, last for a shorter term if the length of the intervention is shorter.

Interpretation

Although it is challenging to conclude which intervention type was the most effective, it appeared that, regardless of the intervention types, PHI interventions of longer duration (at least 2 years) were more beneficial and outcomes were more sustained than those PHI interventions that lasted for a shorter period.

Funding

Primary source of funding was Geelong Medical and Hospital Benefits Association (GMHBA), an Australian private health insurer.

Peer Review reports

Introduction

Worldwide, 71 % (41 million) of all deaths each year are attributed to chronic diseases [1], with chronic diseases responsible for nine out of ten deaths in Australia [2]. Chronic or non-communicable diseases are illnesses that “tend to be of long duration and are the result of a combination of genetic, psychological, environmental and behavioural factors” [1]. Chronic diseases lead not only to deteriorating quality of life for individuals [3] but also cause an economic burden on individuals, health systems and wider society [4].

Governments and other stakeholders worldwide have taken a broad range of actions to tackle the key risk factors which contribute to the prevalence and impact of chronic diseases [5]. In Australia in 2011, it was estimated that 31% of the total burden of disease was potentially preventable through actions on 29 behavioural, metabolic, environmental and dietary risk factors [6]. Health insurers are one of the key stakeholders in health systems worldwide with the capacity to act on chronic disease prevention and management. While globally there are a number of different health insurance settings, such as private health insurance (PHI), employer-sponsored health plans, veteran’s affairs and public health insurance [7], our focus in this study is on the emerging role of private health insurers in chronic disease prevention [8].

Globally, prepaid private health spending, which included PHI, accounted for 17.4% of total health financing in 2014 [9]. This varied across countries. For example, PHI spending accounted for 6.6%, 7.1%, 38.3%, 44.2% of total health spending in New Zealand, UK, USA, South Africa respectively [9]. These differences reflect the fact that the scope, coverage and structure of PHI cover varies substantially between countries. Australia offers publicly funded universal health coverage for all citizens and permanent residents, through the national Medicare program and via the public health and hospital systems in each state and territory of the Federation. Yet PHIs play an important role in the Australian health system, accounting for some 9% of total health expenditure [10], especially in the funding of elective surgery and hospital care. However, in the Australian setting, PHI does not have full responsibility for the integrated care of insured members, most crucially because PHI is not permitted to fund primary health care and general practice [11]. Despite these constraints, interest in the role, incentives and ability of PHI to engage more closely in the prevention of chronic diseases is growing [12]. Action is growing not only in programs focused on primary and secondary prevention but also in self-management, which plays a crucial role in managing chronic diseases successfully to prevent further occurrence of symptoms or further complications [13]. Chronic disease management (CDM) activities focus on people with already-diagnosed chronic conditions. Despite legislation permitting PHI funds to pay benefits for CDM services having been in place for more than 10 years in Australia, insurers are still in an early stage of implementation and evaluation of CDM activities. During a qualitative study in 2019, PHI representatives reported identifying target groups; evaluating service outcomes; and collaborating with other healthcare providers as challenges to providing appropriate CDM programs [11]. Nonetheless, PHI’s role in chronic disease prevention and supporting people with chronic diseases to improve quality of life is emerging [11], through adopting chronic disease prevention interventions beyond the coverage of specific insurance products.

Previously there have been systematic reviews undertaken on financial incentives provided by both public and private health insurers for the prevention and management of overweight and obesity [7] and rapid or systematic reviews on chronic disease prevention interventions, but these were either focused on one kind of intervention or delivered by stakeholders other than PHI [14, 15]. Therefore, the aim of this paper is to systematically review to summarise the impacts of chronic disease prevention interventions implemented by PHI both in Australia and internationally, in order to provide lessons on how PHI might engage most effectively with primary, secondary and/or tertiary prevention of chronic diseases.

Methods

Search strategy

This systematic review is reported following Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA guidelines) [16], 2020 checklist (Additional File 1). We conducted a systematic literature search across seven online databases: Business Source Complete, CINAHL, Global Health, Health Business Elite, Medline, PsycINFO (APS PsycINFO), and Scopus. Additional relevant literature and grey literature (i.e. reports) were searched using Google, Google Advanced, and reference lists of the included articles. Search terms were developed around PHI and chronic disease prevention or health promotion programs (see Additional File 2).

Studies were included if they evaluated the impacts of chronic disease prevention interventions implemented by PHIs. Primary, secondary and tertiary prevention interventions are defined respectively as reducing the incidence of disease before onset; preventing diseases at very early stage from progressing; and managing the manifest disease and its complication to improve quality of life [17]. Studies on the impacts of chronic disease management programs by PHIs were also included if prevention strategies were incorporated. Studies published in English until September 2020 were included. The search was not limited to specified study designs or a population. Studies were excluded if they were on impacts of programs primarily not implemented by PHI; or programs implemented by government funded public health insurers; or programs implemented by workplaces/employers with no sponsorship from PHI; or chronic disease care/treatment programs with no prevention strategies involved; or studies about expanded private health insurance coverage for various health conditions; or value based insurance designs (i.e. programs that provide reduced prescription drug co-payment costs for targeted chronic diseases). Studies published in languages other than English, abstracts, conference papers, newspaper articles, and study protocols were excluded.

Study selection and data extraction

The selection of studies during the screening process was based on the above eligibility criteria. Two reviewers (SWAD and NH) first screened all the titles and abstracts independently using EndNote software. Selected papers were then divided equally between the two reviewers (SWAD & NH) for full-text screening and cross-checked. Any disagreement in either of these steps was discussed with one other author of this paper (MH) to reach a consensus. If full text articles were not found, they were retrieved by contacting Deakin University librarians via inter-library loan requests. Two reviewers (SWAD and NH) independently extracted the following data on an Excel table: country, program name, description of the program, health insurer, target population (community/members), study design, time period of the study, sample, any outcome measure and results. The literature was synthesized thematically; no meta-analysis or statistical analysis was conducted due to wide heterogeneity of the intervention types and outcome measures reported in this literature. As this review is exploratory in nature, we summarised any outcomes that have been used in this area and effect measures as reported in studies. Summary results of the studies are provided in tabular forms in the text and as additional files. Given the heterogeneity and observational nature of studies, we used the available evidence as possible and did not attempt to assess the reporting bias or certainty of outcomes.

Risk of bias and quality assessment

For assessing risk of bias of included studies, two reviewers conducted the quality assessment independently (SWAD and MR). The review team discussed and resolved any discrepancies in the overall quality rating. The quality of selected studies was checked using the quality assessment tool for quantitative studies developed by Effective Public Healthcare Panacea Project (EPHPP), Canada [18]. We considered a range of tools for the assessment of risk of bias, including CASP, NIH, and STROBE; EPHPP was chosen due to the variety of methods and the quantitative nature of the included studies. The tool includes six components to rate study quality as Strong, Moderate or Weak. Studies that were rated strong were considered to have a low risk of bias, while weak studies were considered as having a high risk of bias.

Results

Search results

A total of 29 studies were included in the final thematic synthesis (Fig. 1). Table 1 provides the characteristics of the included studies. The majority of the studies were from the USA (n = 16, 55%) followed by South Africa (n = 6, 21%). The other countries were Australia (n = 5) and Germany (n = 2). Four studies were randomised controlled trials (RCT), but the majority of the studies were cohort studies (n = 14, 48%). Other study designs were cross sectional (n = 6), case control (n = 2), mixed method (n = 1), a pre and post evaluation study (n = 1), and a systematic review (n = 1).

Fig. 1
figure1

Consort chart

Table 1 General Characteristics of the included studies

Twelve studies (41%) looked at the impacts of primary prevention measures delivered by PHI to reduce chronic diseases. Two studies evaluated the impacts of secondary prevention measures, and eleven studies were based on tertiary prevention measures. Three studies evaluated programs that incorporated mixed strategies of prevention levels such as both secondary and tertiary prevention (Table 2). The majority of the programs were for PHI members (n = 28, 93%) while the others were at community level. Table 2 provides the description of interventions evaluated in the studies.

Table 2 Description of chronic disease prevention programs

A summarised quality assessment of studies is presented in Additional File 3. The majority of studies (n = 24, 83%) were scored as having an overall weak quality in methodology according to the quality assessment tool for quantitative studies developed by EPHPP. Four studies were of moderate quality and only one study was rated as strong quality.

Impacts of PHI chronic disease prevention programs

This review identified four main categories of chronic disease prevention interventions being delivered by PHI. The selected studies were summarised based on these types: Financial incentives, health coaching, wellness programs, and group medical appointments. The outcomes and effect measures are varied across studies as summarised in this section (see Additional File 4).

Financial incentives

Nine studies were based on the impacts of financial incentives and focused on primary prevention [19,20,21,22,23,24,25,26,27]. Six studies evaluated Vitality program (Healthy Food program) by Discovery Health, which is one of the largest PHI (or “medical aid”) funds in South Africa. Table 2 provides a description of the program. Eight of the studies were high risk of bias [19,20,21,22,23,24, 26, 27], and one was moderate risk of bias [25]. According to Sturm et al., 10% and 25% discounts on healthy food choices led to an increase in healthy/total food ratio of 6% and 9.3% as well as in fruit and vegetables/total food ratio by 5.7% and 8.5% respectively. A decrease in the ratio of less desirable/total food expenditure by 5.6% and 7.2% respectively [23]. A repeated survey of 350,000 participants and nonparticipants of HealthyFood program, which was part of Vitality, found out that subsidies on healthier foods significantly increased the purchase and consumption of promoted products [20]. Their study showed that discounts were associated with statistically significant positive changes in self-reported dietary behaviours compared to no discounts (p < 0.0001). Larger discounts were always associated with a larger effect compared to smaller discounts. Daily fruits and vegetable consumption increased by 40% and 60% for 10% and 25% discounts respectively. People (who receive 10% or 25% rebate) were twice and three times more likely to have three or more servings of wholegrain foods on a daily basis than no rebate. Similarly, people were 25% (10% discount) and 65% (25% discount) less likely to have foods high in sugar, as well as 40% (10% discount) and 75% (25% discount) less likely to have foods high in salt [20].

A longitudinal study on the incentivised Vitality program found a significant reduction in the prevalence of physical inactivity from 76 to 68% over a 5-year period, which is a risk factor for chronic diseases. Increased physical activity was associated with reduced probability of hospital admissions due to chronic diseases [21]. Members who were highly active within the first 3 years had less hospital admissions in year 4 to 5 (20.7%) compared to inactive members (22.2%). Gym use increased from 27 to 33.1% over the 5-year period and for each two extra gym visits per week the likelihood of a hospital admission was reduced by 13% (OR = .87; 95% CI 0.801, 0.949) [21]. Participants who were in the high active Vitality group (greater than 48 gym visits per year) had 35% less cancer and mental illness admissions than members in other groups. Admissions associated with endocrine, nutritional, metabolic disorders, kidney and urinary tract disorders were 20% lower compared with members in other activity groups. Admission rates were also 7.4% lower for cardiovascular disease, 13.2% lower for cancers [22].Another incentive based 4-month physical activity program, the ACHIEVE study, recruited inactive individuals aged 40–65 years via GMHBA in Australia and found that there were large increases in leisure time physical activity by 212.1 mins/week in men from 106.7 ± 135.1 to 318.8 ± 263.6 (p-value < 0.001) and 281.6 mins/week in women from 81.4 ± 105.3 to 363.0 ± 486.7 (p-value < 0.001); transport related physical activity by 139.6 mins/week in men from 73.4 ± 85.8 to 213.0 ± 223.3 (p-value < 0.001) and 207.1 mins/week in women from 81.2 ± 94.9 to 288.3 ± 371.4 (p-value < 0.001). Sitting time reduced by 3.1 h/day for both genders from 8.6 ± 2.6 to 5.5 ± 1.9 for men (p-value < 0.001) and from 8.4 ± 2.4 to 5.3 ± 2.1 for women (p-value < 0.001). There were also reductions in BMI by 1.3 kg/m2 (p-value < 0.001) and systolic blood pressure by 5.1 mmHg [25].

Regarding the long term effects of incentives, after a weight loss and lifestyle modification program within three Australian insurance companies, participants of the program reported non-cash (i.e. incentive with a monetary value but not cash) (85.2%) and cash (77%) incentives would be a motivation, but 40.5% reported deposit contracts (i.e. making a monetary deposit which is refunded if weight loss is maintained) would motivate maintaining weight loss [27]. 93.9% of respondents supported the idea of a maintenance program following the weight loss program. More than half of respondents were positive about providing financial incentives 3 to 6 months after the program. The majority (85.2%) thought non-financial incentives would motivate maintaining weight loss [27].

Health coaching

Nine studies looked at the impacts of health coaching delivered by PHI [13, 28,29,30,31,32,33,34,35]. Eight studies were high risk of bias [13, 28,29,30,31,32, 34, 35], and one was moderate risk of bias [33]. In a health coaching program delivered by Kaiser Permanente, members who attended two or more sessions reported improvements compared to prior session they attended, such as having more healthy eating (68% vs. 54%, p = 0.04), increased physical activity (71% vs. 45%, p = < 0.001), improved health (79% vs. 61%, p = 0.005), improved quality of life (83% vs. 61%, p < 0.001), and reduced risk of diseases (73% vs. 51%, P = 0.10) [28]. Similarly, Lawson et al. found that telephonic health coaching significantly improved stress levels, healthy eating, exercise levels, physical and emotional health by 11.9%, 12.8%, 20.9%, 11.6% and 15.4% respectively [30]. General health status and quality of life was improved in all participants.

A randomised control study in a US Health Management Organisation (HMO) found that well-integrated mental health clinicians offering Medical Crisis Counselling (MCC) straight after a distressing diagnosis, (e.g., cancer or heart attack) found significant reductions in stress, anxiety and depression, increased patient satisfaction and increased perceived social support. Over the 6 months of the study, no increases in overall medical costs were found but some decreased mental health utilization and costs were noted with MCC use. Favourable patient outcomes were seen regardless of the number of MCC sessions and therefore the cost-efficiency of the MCC approach was described by the authors as “impressive” [29].

Schwartz et al. also looked at cost impact of Blues on Call program with telephone outreach to members with chronic disease started by Blue Cross Blue Shield in Pennsylvania. An economic evaluation found the health care costs per person per year were $757 less than predicted for participants undertaking ‘Blues on Call’ compared with matched non-participants. This equated to a return on investment of $9.89 for every dollar spent on the program [35]. The intervention group had significantly lower same-day admission costs and fewer same-day admissions per 1000 person-years. The health coached group also had significantly fewer hospital admissions for patients with COPD and fewer same-day admissions for patients with diabetes. The Blues on Call program also had significant differences in service utilisation for total number of services, professional services, and pharmacy services (p < .05). Patients had fewer total inpatient days and shorter length of stay per person per year and showed a declining trend from 2005 to 2007 [35]. However, Bupa Australia reviewed their health coaching program and found the total cost 1 year post-randomisation of health coaching compared to standard care was not significantly different [34]. Harmar et al. reported on a chronic disease program which incorporated telephonic outreach by nurses to members regarding self-care measures and educating on health-related behaviours and adherence to care by a German PHI [32]. After one-year of the intervention, the hospital admission rate decreased by 6.2% for the intervention group compared to the control group with a 14.9% increase (p < 0.001). The admission rate was recorded to be lower with but the number of telephone calls higher (p = 0.004) [32]. Nonetheless, another evaluation of the telephonic complex care program over 6 months in the Australian context (no name given for the PHI) found there was no significant difference in the number of hospital admissions or total hospital days between both participants and non-participants in the 12 months after the intervention [33].

Moreover, a study on health coaching by German PHI, KKH-Allianz, found that 78% of members were satisfied with coaching and 82% would recommend it to others [13]. More than half the participants discovered new options, via health coaching, to influence their health condition [13].

Wellness programs

There were nine studies on wellness programs delivered by PHIs [36,37,38,39,40,41,42,43,44].Eight studies are high risk of bias [36, 37, 39,40,41,42,43,44], and one study is moderate risk of bias [38]. One US study examined the impacts of the Blue Shield California’s Internet based Wellness program (Healthy Lifestyle Rewards) and participants in wellness programs exercised more frequently, consistently ate more fruits and vegetables, and reported lower stress levels. They revealed that it was associated with statistically significant declines in all measures of outpatient utilization (including non-hospital physician and non-physician visits, and physician visits) in the following year. There were no significant effects on claims spending for cholesterol and depression medications, or in utilization in the categories of emergency department visits, and inpatient admissions [37].

Schwartz and colleagues evaluated a 4 year wellness and disease prevention program called ‘HealthPass’ and estimated a net savings of $374, $34, $132, and $124 per year per participant yielding an estimated return on investment of $2.83, $1.16, $1.56, and $1.58 for every dollar invested for the years of 2002–2005, respectively [44]. Similar to the health care expenditures, non-participants made more claims for inpatient and pharmacy services (p < 0.0001 for all years) compared to participants, who made more claims for medical services (p < 0.0001 for all years). The outpatient claims were not significantly different between the two groups (p > 0.10 for all years). HealthPass participants consistently had fewer inpatient days per year and shorter average length of stay per admission compared to non-participants. Another study on ‘MyHealth Rewards’, an employee health-plan driven health and wellness program in the USA, showed that on average program participants experienced heart problems later than non-participants did (p < 0.01). This corresponded with a 10 to 13% cost reduction during the 2nd and 3rd year of the program [40]. Similarly, a systematic review on health-plan sponsored fitness centres showed a significant healthcare cost saving after a 2 years through reduced hospital admissions ($500; 95% CI $892 to 106, P=0.01) compared to a 1 year which had no difference between participants and non-participants of the program [39].

Another wellness intervention by PHIs was screening programs. Oxford Health Plan initiated a nutrition screening program to screen at-risk members and offer interventions related to nutrition such as visits from a dietitian and follow-ups. This program was able to reduce the nutrition risk and led to reduction in the number of insurance claims and emergency department visits, resulting in a 538% return on the investment [41].

Coombs et al. indicated that at a cost of only 21 cents per member per month for malnutrition screening, they found reduced insurance claims, reduced claim dollars, and reduced ED visits after implementation of nutrition screening [41]. Another approach to wellness was the Kaiser Permanente Online Personal Action Plan (oPAP), using the member web portal to better enable members to access information about prevention, health promotion, and care gaps. Users of oPAP were more likely than non-registered members to close healthcare gaps, especially cancer screening tests [38].

As a community initiative, Kaiser Permanente updated community playgrounds and found that children engaging in moderate to vigorous physical activity during recess increased by 23.3% (p < 0.01), and the percentage engaged in vigorous physical activity increased by 26.2% [36]. These increases were sustained at 1 year from baseline. Cheadle et al’s study on a community level ‘Healthy Eating Active Living Zones’ initiative also indicated that positive changes in diet and physical activity within population can be seen when the intervention is delivered to a larger number of people for a longer duration.

Group medical appointments

There were two studies that incorporated group medical appointments with prevention strategies, such as education and improving self-care measures [45, 46]. One study was high risk of bias [46] while the other one was low risk of bias [45]. Beck et al. evaluated the impact of PHI initiated group medical visits (which included health education, socialisation opportunities, mutual support, and prevention measures) on hospital utilisation and costs for chronically ill older members compared with standard care [45]. They found that after 1 year members in the intervention arm had less emergency department visits (p = 0.009), less specialist visits (p = −.028) and less hospital admissions (p = 0.051), instead they made more nurse calls (p = 0.038) and fewer physician calls (p = 0.019) than the control group. Average cost saving per participant of the intervention was $14.79. Moreover, after a year, a greater percentage of intervention participants received vaccinations for influenza and pneumonia and had a greater satisfaction with care compared to the control group (81% vs. 64%) [45]. Another program that utilised group medical appointment and education was Operation Zero (O.Z.) in paediatric obesity [46]. At 8 weeks after program completion compared with baseline, there were significant reductions in the percentage of body fat and waist size for those who attended 6 or more sessions. The program showed effectiveness after 6 months for weight maintenance, but not after 1 year. After 1 year, the mean change in weight and BMI in the O.Z. group was not statistically different compared to the control group [46].

Discussion

In recent years, there has been a growing interest in prevention of chronic diseases within the PHI setting. Many chronic disease prevention interventions have been delivered by PHIs in many countries. However, to the best of our knowledge, a systematic review has not yet been conducted on the impact of these interventions, and this is the first systematic review that explored the impact of variety of chronic disease prevention interventions implemented by PHIs. Twenty-nine studies were included in our final thematic synthesis.

Our results confirmed earlier systematic reviews on chronic disease prevention programs in different settings [15], highlighting that these interventions are generally effective in reducing risk factors of chronic diseases. The studies in our review had evaluated interventions for various outcome measures. While some studies measured healthy behaviour or weight loss as outcomes, other studies measured healthcare utilization or a mix of both. This review showed that the most studies were about health coaching, wellness programs and incentives, which could indicate that these intervention types were the most commonly used by PHIs.

Studies on health coaching found them to be effective in improving healthy eating, physical activity, quality of life, and reducing hospital utilisation [28]. However, the duration of effects was different for each intervention. Incentive programs were shown to increase healthy food consumption, and to achieve a statistically significant difference in self-reported dietary behaviours. However, An et al. concluded that there was no evidence to support the association between Vitality incentive programs for healthy food and reducing BMI or preventing obesity, despite self-reported reductions on BMI [20]. This shows the need for evaluating such programs by using measured BMI as an outcome measure in future studies. Vitality program interventions that were based on activities around fitness, screening and health assessment, education and healthy choices showed evidence of increased use of gym and physical activities. However, more than two-thirds of members still failed to use their gym benefits in a meaningful way for health improvement, suggesting that the incentives and subsidy are not sufficient to overcome behavioural inertia in a majority of members.

Regardless of the intervention types, it appeared that PHI interventions that of longer duration (more than 2 years) were more beneficial and outcomes were more sustainable than those PHI interventions that lasted for a shorter period. For example, incentive programs showed higher achievements in the short term: the 4-month incentive program by GMHBA indicated a statistically significant difference in increase of leisure time physical activities, transport related physical activities, reduced sitting time and BMI at the end of 4 months. However, once incentives ceased, these impacts also reduced or were lost in the long run. This pattern was visible for both health coaching and wellness programs. King et al. also mentioned that a significant healthcare cost reduction due to reduced hospital admission was visible by the end of a 2 year fitness program, but the participation rates were starting to decline in the program’s second year, with only 61% of participants continuing to participate [39].

Group medical appointments also indicated the same pattern of short-term improvements which were harder to sustain. While group medical appointments for weight loss management were shown to be effective after a year in reducing hospital utilisation and costs, and the changes were statistically significant, they were not effective for weight loss management after a year. For example, the O.Z. program was effective after 6 months, but after a year the mean change in weight and BMI of O.Z. participants were no longer statistically different to those of the control group. These results indicate that PHI group medical appointment programs can produce positive outcomes in the shorter term, but do not usually offer sustainable, long-term benefits once the intervention ceases.

The strengths of this systematic review are: the search of both academic and grey literature; and that the search was not limited to one geographical area or population. The limitations include: diversity of the interventions, methodology, and outcome measures of studies made comparability across interventions and outcomes challenging. Studies comparing different intervention types were not found, and the outcomes presented across the studies were varied and not sufficiently comparable to allow any decision on which intervention is the most effective. Many of the included studies were likely to have a high risk of bias, and therefore there is a need for future research to evaluate chronic disease prevention interventions by PHIs to establish their effectiveness and cost effectiveness in real practice settings.

Implications and conclusion

Chronic disease prevention interventions by PHI, such as the Vitality program, health coaching, wellness programs, financial incentives and group medical appointments, have been shown to generate measurable health benefits for participants. Discovery Health and its Vitality program stand out as having made a particularly innovative contribution both in the design and the evaluation of interventions in this field. The results of this review show that all these approaches to chronic disease prevention by PHIs have been shown to be effective in the short term, but their impacts did not last in the long run once the intervention was ceased. It therefore seems likely that PHI prevention programs must themselves be sustained for long periods if their beneficial outcomes are also to be sustained. Future research should therefore focus on how best to design and deliver programs and interventions to achieve sustained behaviour change over long periods. This research shows that PHI insurers do have the potential to play a significant and beneficial role in improving the health of their members and the wider community, but only if they can take a longer-term perspective and act as “patient investors” in health and well-being.

Other information

The study protocol was registered in PROSPERO (CRD42020145644) [47] and can be accessed via https://www.crd.york.ac.uk/PROSPERO/. The protocol was amended to include a researcher who contributed to the study and to update the completion date.

Availability of data and materials

All data generated or analysed during this study are included in this article and its additional files.

References

  1. 1.

    World Health Organization. Noncommunicable diseases. 2018. https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases. Accessed 25 Feb 2021.

    Google Scholar 

  2. 2.

    Moodie AR, Tolhurst P, Martin JE. Australia’s health: being accountable for prevention. Med J Aust. 2016;204(6):223–5. https://doi.org/10.5694/mja15.00968.

    Article  PubMed  Google Scholar 

  3. 3.

    Preto O, Amaral O, Duarte J, Chaves C, Coutinho E, Nelas P. Quality of life and chronic disease in patients receiving primary health care. 2nd International Conference on Health and Health Psychology; 2019.

    Google Scholar 

  4. 4.

    Bloom DE, Chen S, Kuhn M, McGovern ME, Oxley L, Prettner K. The economic burden of chronic diseases: estimates and projections for China, Japan, and South Korea. J Econ Ageing. 2020;17:100163.

  5. 5.

    Beaglehole R, Bonita R, Horton R, Adams C, Alleyne G, Asaria P, et al. Priority actions for the non-communicable disease crisis. Lancet. 2011;377(9775):1438–47. https://doi.org/10.1016/S0140-6736(11)60393-0.

    Article  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Barnes T. Australian burden of disease study: impact and causes of illness and death in Aboriginal and Torres Strait islander peoples, 2011; 2016.

    Google Scholar 

  7. 7.

    Ananthapavan J, Peeterson A, Sacks G. Paying people to lose weight: the effectiveness of financial incentives provided by health insurers for the prevention and management of overweight and obesity - a systematic review: Wiley; 2018.

    Book  Google Scholar 

  8. 8.

    Mattke S, Mengistu T, Klautzer L, Sloss EM, Brook RH. Improving Care for Chronic Conditions: current practices and future trends in health plan programs. Rand Health Q. 2015;5(2):3.

    PubMed  PubMed Central  Google Scholar 

  9. 9.

    Dieleman J, Campbell M, Chapin A, Eldrenkamp E, Fan VY, Haakenstad A, et al. Evolution and patterns of global health financing 1995–2014: development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries. Lancet. 2017;389(10083):1981–2004. https://doi.org/10.1016/S0140-6736(17)30874-7.

    Article  Google Scholar 

  10. 10.

    Australian Institute of Health Welfare. Health expenditure. Canberra: AIHW; 2020. https://www.aihw.gov.au/reports/australias-health/health-expenditure. Accessed 20 Feb 2021

    Google Scholar 

  11. 11.

    Khoo J, Hasan H, Eagar K. Emerging role of the Australian private health insurance sector in providing chronic disease management programs: current activities, challenges and constraints. Aust Health Rev. 2019;43(5):572–7. https://doi.org/10.1071/AH18164.

    Article  PubMed  Google Scholar 

  12. 12.

    Biggs A. Chronic disease management: the role of private health insurance. Research paper (Parliamentary Library) ISSN 1834–9854; 2013.

    Google Scholar 

  13. 13.

    Härter M, Dwinger S, Seebauer L, Simon D, Herbarth L, Siegmund-Schultze E, et al. Evaluation of telephone health coaching of German health insurants with chronic conditions. Health Educ J. 2013;72(5):622–34. https://doi.org/10.1177/0017896912453990.

    Article  Google Scholar 

  14. 14.

    Bellew B. Primary prevention of chronic disease in Australia through interventions in the workplace setting: a rapid review. Sax Institute for the Chronic Disease Prevention Unit, Victorian Government Department of Human Services; 2008.

    Google Scholar 

  15. 15.

    Reynolds R, Dennis S, Hasan I, Slewa J, Chen W, Tian D, et al. A systematic review of chronic disease management interventions in primary care. BMC Family Practice. 2018;19(1):1–13. https://doi.org/10.1186/s12875-017-0692-3.

  16. 16.

    Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. https://doi.org/10.1136/bmj.n71.

    Article  PubMed  PubMed Central  Google Scholar 

  17. 17.

    Solomon A, Mangialasche F, Richard E, Andrieu S, Bennett DA, Breteler M, et al. Advances in the prevention of Alzheimer's disease and dementia. J Intern Med. 2014;275(3):229–50. https://doi.org/10.1111/joim.12178.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  18. 18.

    Effective Public Health Practice Project. Quality Assessment Tool for Quantitative Studies. 2009. http://www.ephpp.ca/tools.html. Accessed 02 Nov 2020.

    Google Scholar 

  19. 19.

    Hubbert K, Bussey B, Allison D, Beasley T, Henson C, Heimburger D. Effects of outcome-driven insurance reimbursement on short-term weight control. Int J Obes Relat Metab Disord. 2003;27(11):1423–9. https://doi.org/10.1038/sj.ijo.0802403.

    CAS  Article  PubMed  Google Scholar 

  20. 20.

    An R, Patel D, Segal D, Sturm R. Eating better for less: a National Discount Program for healthy food purchases in South Africa. Am J Health Behav. 2013;37(1):56–61. https://doi.org/10.5993/AJHB.37.1.6.

    Article  PubMed  PubMed Central  Google Scholar 

  21. 21.

    Patel D, Lambert EV, Da Silva R, Greyling M, Kolbe-Alexander T, Noach A, et al. Participation in fitness-related activities of an incentive-based health promotion program and hospital costs: a retrospective longitudinal study. Am J Health Promot. 2011;25(5):341–8. https://doi.org/10.4278/ajhp.100603-QUAN-172.

    Article  PubMed  Google Scholar 

  22. 22.

    Patel DN, Lambert EV, Da Silva R, Greyling M, Nossel C, Noach A, et al. The association between medical costs and participation in the vitality health promotion program among 948,974 members of a south African health insurance company. Am J Health Promot. 2010;24(3):199–204. https://doi.org/10.4278/090217-QUAN-68R2.1.

    Article  PubMed  Google Scholar 

  23. 23.

    Sturm R, An R, Segal D, Patel D. A cash-Back rebate program for healthy food purchases in South Africa: results from scanner data. Am J Prev Med. 2013;44(6):567–72. https://doi.org/10.1016/j.amepre.2013.02.011.

    Article  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Schwartz J, Mochon D, Wyper L, Maroba J, Patel D, Ariely D. Healthier by Precommitment. Psychol Sci. 2014;25(2):538–46. https://doi.org/10.1177/0956797613510950.

    Article  PubMed  Google Scholar 

  25. 25.

    Ball K, Hunter RF, Maple J-L, Moodie M, Salmon J, Ong K-L, et al. Can an incentive-based intervention increase physical activity and reduce sitting among adults? The ACHIEVE (active choices IncEntiVE) feasibility study; 2017.

    Book  Google Scholar 

  26. 26.

    Lambert EV, da Silva R, Fatti L, Patel D, Kolbe-Alexander T, Derman W, et al. Fitness-related activities and medical claims related to hospital admissions - South Africa, 2006. Prev Chronic Dis. 2009;6(4):A120.

    PubMed  PubMed Central  Google Scholar 

  27. 27.

    McGill B, O'Hara BJ, Grunseit AC, Bauman A, Osborne D, Lawler L, et al. Acceptability of financial incentives for maintenance of weight loss in mid-older adults: a mixed methods study. BMC Public Health. 2018;18:244.

    Article  Google Scholar 

  28. 28.

    Adams SR, Goler NC, Sanna RS, Boccio M, Bellamy DJ, Brown SD, et al. Patient satisfaction and perceived success with a telephonic health coaching program: the natural experiments for translation in diabetes (NEXT-D) study, northern California, 2011; 2013.

    Google Scholar 

  29. 29.

    Koocher GP, Curtiss EK. Medical crisis counseling in a health maintenance organization: preventive intervention. Prof Psychol Res Pr. 2001;32(1):52–8. https://doi.org/10.1037/0735-7028.32.1.52.

    Article  Google Scholar 

  30. 30.

    Lawson KL, Jonk Y, O'Connor H, Riise KS, Eisenberg DM, Kreitzer MJ. The impact of telephonic health coaching on health outcomes in a high-risk population. Glob Adv Health Med. 2013;2(3):40–7. https://doi.org/10.7453/gahmj.2013.039.

    Article  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Schmittdiel JA, Brown SD, Neugebauer R, Adams SR, Adams AS, Wiley D, et al. Health-plan and employer-based wellness programs to reduce diabetes risk: The kaiser permanente northern california next-d study. Prev Chronic Dis. 2013;10(1):E15.

    PubMed  PubMed Central  Google Scholar 

  32. 32.

    Hamar B, Wells A, Gandy W, Haaf A, Coberley C, Pope JE, et al. The impact of a proactive chronic care management program on hospital admission rates in a German health insurance society. Popul Heath Manage. 2010;13(6):339–45. https://doi.org/10.1089/pop.2010.0032.

    Article  Google Scholar 

  33. 33.

    Morello RT, Barker AL, Watts JJ, Bohensky MA, Forbes AB, Stoelwinder J. A telephone support program to reduce costs and hospital admissions for patients at risk of readmissions: lessons from an evaluation of a complex health intervention; 2016.

    Google Scholar 

  34. 34.

    Scuffham PA, Byrnes JM, Pollicino C, Cross D, Goldstein S, Ng S-K. The impact of population-based disease management services on health care utilisation and costs: results of the CAPICHe trial. J Gen Intern Med. 2019;34(1):41–8. https://doi.org/10.1007/s11606-018-4682-5.

    Article  PubMed  Google Scholar 

  35. 35.

    Schwartz SM, Day B, Wildenhaus K, Silberman A, Wang C, Silberman J. The impact of an online disease management program on medical costs among health plan members. Am J Health Promot. 2010;25(2):126–33. https://doi.org/10.4278/ajhp.091201-QUAL-377.

    Article  PubMed  Google Scholar 

  36. 36.

    Frost MC, Kuo ES, Harner LT, Landau KR, Baldassar K. Increase in Physical Activity Sustained 1 Year After Playground Intervention. Am J Prev Med. 2018;54(5, Supplement 2):S124–9.

    Article  Google Scholar 

  37. 37.

    Harris ZK. Private health insurance sponsored wellness programs: examining participation in the healthy lifestyle rewards financial incentives program on health care costs, utilization, and risk behaviors: ProQuest Information & Learning; 2011.

    Google Scholar 

  38. 38.

    Henry SL, Shen E, Ahuja A, Gould MK, Kanter MH. The online personal action plan: a tool to transform patient-enabled preventive and chronic care. Am J Prev Med. 2016;51(1):71–7. https://doi.org/10.1016/j.amepre.2015.11.014.

    Article  PubMed  Google Scholar 

  39. 39.

    King HA, Gierisch JM, Williams JW Jr, Maciejewski ML. Effects of health plan-sponsored fitness center benefits on physical activity, health outcomes, and health care costs and utilization: a systematic review; 2012.

    Google Scholar 

  40. 40.

    Maeng D, Pitcavage J, Tomcavage J, Steinhubl S. Can health insurance improve employee health outcome and reduce cost? An evaluation of Geisinger's employee health and wellness program. J Occup Environ Med. 2013;55(11):1271–5. https://doi.org/10.1097/JOM.0000000000000009.

    Article  PubMed  Google Scholar 

  41. 41.

    Coombs J. The role of nutrition screening and intervention programs in managed care. Manag Care Q. 1998;6(2):43–50.

    CAS  PubMed  Google Scholar 

  42. 42.

    Cheadle A, Atiedu A, Rauzon S, Schwartz PM, Keene L, Davoudi M, et al. A community-level initiative to prevent obesity: results from Kaiser Permanente's healthy eating active living zones initiative in California. Am J Prev Med. 2018;54(5 Suppl 2):S150–s159. https://doi.org/10.1016/j.amepre.2018.01.024.

    Article  PubMed  Google Scholar 

  43. 43.

    McGill B, Bauman A, Phongsavan P, Grunseit AC, Lees D, Shepherd L, et al. Beyond weight loss: impact of a weight management programme for mid-older Australians in private health insurance. Clin Obes. 2020;10(3):e12359. https://doi.org/10.1111/cob.12359.

    Article  PubMed  Google Scholar 

  44. 44.

    Schwartz SM, Ireland C, Strecher V, Nakao D, Wang C, Juarez D. The economic value of a wellness and disease prevention program. Popul Heath Manage. 2010;13(6):309–17. https://doi.org/10.1089/pop.2009.0070.

    Article  Google Scholar 

  45. 45.

    Beck A, Scott J, Williams P, Robertson B, Jackson D, Gade G, et al. A randomized trial of group outpatient visits for chronically ill older HMO members: the cooperative health care clinic. J Am Geriatr Soc. 1997;45(5):543–9. https://doi.org/10.1111/j.1532-5415.1997.tb03085.x.

    CAS  Article  PubMed  Google Scholar 

  46. 46.

    Hinchman J, Beno L, Mims A. Kaiser Permanente Georgia's experience with operation zero: a group medical appointment to address pediatric overweight. Perm J. 2006;10(3):66–71. https://doi.org/10.7812/tpp/05-126.

    Article  PubMed  PubMed Central  Google Scholar 

  47. 47.

    National Institute for Health Research. Impacts of chronic disease prevention programs implemented by private health insurers: a systematic review. PROSPERO 2020 CRD42020145644. UK: National Institute for Health Research; 2020. https://www.crd.york.ac.uk/prospero/display_record.php? ID=CRD42020145644. Accessed 25 Feb 2021

    Google Scholar 

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Acknowledgements

We would like to Thank our Deakin University librarians for their support in the development of search strategies and in finding full text articles.

Funding

We gratefully acknowledge funding received from Geelong Medical and Hospital Benefits Association (GMHBA), an Australian private health insurer, for undertaking this review of the evidence related to chronic disease prevention interventions implemented by private health insurers in Australia and worldwide.

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SWAD and NH initiated the conceptualization of the study design and led the systematic review. SWAD and NH conducted the title and abstract review, full text review, data extraction under the guidance of MH. SWAD and MRA conducted the quality assessment under guidance of MH. SWAD, NH, MRA and MH did manuscript writing and preparation. All senior reviewers (JJW, AP and MH) reviewed all the drafts. All authors have read and approved the final manuscript.

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Correspondence to Martin Hensher.

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Wanni Arachchige Dona, S., Angeles, M.R., Hall, N. et al. Impacts of chronic disease prevention programs implemented by private health insurers: a systematic review. BMC Health Serv Res 21, 1222 (2021). https://doi.org/10.1186/s12913-021-07212-7

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Keywords

  • Chronic diseases
  • Private health insurers
  • Prevention