Non communicable disease multimorbidity and associated health care utilization and expenditures in India: cross-sectional study

Improvements in living conditions, changing lifestyles and progress in healthcare effectiveness have led to an increase in the prevalence of non-communicable diseases (NCDs) globally [1, 2]. Much attention has been focused on the increasing burden of single or selected NCD groupings, especially diabetes and cardiovascular diseases [3]. Yet recent epidemiological studies suggest that the prevalence of NCD multimorbidity is high and increasingly the norm for patients in high income settings [4]. For example, a general practice database study conducted in Scotland found that over half of the patients (54.9%) with at least one NCD had multimorbidity [5].

International bodies and individual health systems are increasingly recognizing the importance of NCDs [6, 7]. However, most policy responses to date emphasize improving the identification and management of individual diseases [8, 9]. For example, a series of national service frameworks introduced in the UK’s National Health Service since 2000 are focused on single conditions, such as coronary heart disease. Other quality improvement strategies, including clinical guidelines and pay for performance programs, are similarly focused in single disease areas [10]. These approaches are increasingly at odds with growing information that patients with multimorbidity have higher health service utilization, health care expenditure and poorer health outcomes [11]. For example, a study of US Medicare population found that the risk of an avoidable inpatient admission and per capita medical expenditures increase dramatically with the number of chronic conditions [12‐14]. The situation is not different in low and middle income countries (LMICs). In India, most of the current health programs have singular disease specific vertical approach [15, 16]. There is little information about the epidemiology of NCD multimorbidity and associated impacts on citizens and health systems in LMICs. This is an important knowledge gap given the growing burden of NCDs, the limited capacity of health systems to manage this burden and the low levels of financial protection in LMICs, resulting in a high level of out-of-pocket expenditures. Our study assessed the prevalence and predictors of NCD multimorbidity and associated impacts on health care utilization and out-of-pocket expenditure (OOPE) in India.

We analyzed data from 10,973 respondents. Table 1 presents respondents’ socioeconomic and demographic characteristics of the respondents. The median age of the respondents was 40 years (IQR = 30-49). There were about equivalent proportion of female and male respondent, 82.1% were married, 61.5% of the respondents have educational attainment of primary school completed or less, and 25.7% were residing in urban area.

NCD multimorbidity is increasingly common globally with growing implications for the management of individual patients, assessment of disease burden in populations and health system efficiency and effectiveness [5, 19]. However, very little research has been undertaken in LMICs, where 80% of the burden of NCDs falls [20]. Our study reveals that more than one in four adults in India has at least one NCD, with 8.9% having two or more NCDs. We found no significant difference in the prevalence of multimorbidity across gender or educational attainment. Multimorbidity appears to be more common in affluent households and there is a dramatic rise in prevalence with age, increasing from 1.3% in the youngest group (18–29 years) to 30.6% in the oldest (≥70 years).

The prevalence of multimorbidity in our study appears to be lower than that reported in high income countries. A study conducted in Spain in 2007 has shown that 42% of the registered population aged 14 years and above had at least one chronic condition, with almost one quarter having multimorbidity [21]. Another study undertaken in a family practice settings in Canada has reported nine out of ten patients to have more than one chronic condition [22]. It should be noted that most of these studies have been conducted in primary care practice populations, using clinical and administrative databases [22‐25]. The prevalence of multimorbidity when estimated in general population surveys has been found to be lower than when examined using clinical databases [26], partly due to the more limited numbers of conditions (only eight diseases in our study) included in these analyses. Thus, estimation studies preferably in primary care settings using broad nosological spectrum of chronic conditions would be insightful.

Our study confirms previous findings from high income countries that multimorbidity increases with age [21‐23]. Available data has not demonstrated consistent associations between gender and multimorbidity, with some studies indicating a higher prevalence in women while others found similar results in men [24, 27, 28]. Recent studies emphasize the importance of examining multimorbidity across life course and not just the elderly population [29]. However NCD prevalence estimates in women should be interpreted cautiously in South Asian context, where they may have lower health care seeking behavior [30]. The possible interplay of multimorbidity with social and economic deprivation has already been identified. Studies conducted in high income countries have generally found that persons with low socio-economic status (SES) are more likely to have multimorbidity when compared to their affluent counterparts [31]. However, we did not find similar evidence in our study. A study from Bangladesh has also reported the prevalence to be more in high income group [32]. This might be due to higher health literacy levels and more frequent utilization of health care facilities in higher income groups [33].

The presence of multimorbidity was associated with substantially higher levels of health care utilization, in both outpatient and hospital settings, and markedly with higher levels of OOPE in our study. These findings are consistent with those from previous studies conducted in high income settings which have identified a positive correlation between multimorbidity with health care utilization and cost [14, 34, 35]. For example, a recent Scottish study found that persons with multimorbidity were six times more likely to have an unplanned hospital admission [11]. Our study builds on previous research in India which has documented the impoverishing impact of health care costs among persons with NCDs, wherein nearly half of OOPE was incurred in the purchase of medicine, diagnostic investigations and medical appliances [36]. We too observed that more than 50% of total expenditure is spent towards getting medicines. However, out of pocket expenditure was not specific for NCDs, and might have included treatment for conditions not related to NCDs The impact of multimorbidity alone on catastrophic and impoverishing household health care spending in LMICs merits further investigation [37]. It would be interesting first to investigate, what proportion of the identified demand of chronic healthcare is being currently delivered in primary care practice and the consequential impact on OOPE if there is transfer of healthcare services from specialist setting to primary care settings.

The key strength of this study is the use of a nationally representative sample; which permits robust cross-sectional level estimates of key variables. We identify certain limitations in our study. SAGE is a cross sectional survey which limit the causal inference between multimorbidity and health care utilization and expenditure. Identification of NCDs was based on self report of a doctor diagnosis which may be biased due to a potential under or over reporting and/or poor quality diagnosis. This may result in greater under-reporting of NCDs in persons from lower socio-economic status in particular [38, 39]. However, the amount of error may not have been substantial since studies have documented that self reported prevalence produce estimates near to true prevalence and simple disease counts may have equal predictive value of morbidity burden when compared with other, more complex measurement approaches to multimorbidity [40, 41]. With the available data, it was not possible to measure the severity of the disease or its health impacts on survey participants. Utilization and OOPE data were based on self-report, and therefore subject to recall bias, and only relate to the most recent episode of care. SAGE did not include detailed questions about the presence of communicable disease and although, reasons for health care utilization were solicited from respondents, responses were generally non-specific and incomplete. Given this, we chose to include all outpatient visits or hospital admissions in these outcome measures which could have included some health care utilization that is unrelated to NCDs.

The high prevalence of NCD multimorbidity identified here underlines the importance of current efforts to strengthen health systems in many LMICs, including India. It is essential that these efforts focus on strengthening primary care, given its key role in providing continuous, well coordinated and comprehensive care to patients with complex health needs including those with multiple NCDs. This requires a shift away from current approaches, which frequently emphasize vertical, disease specific programs with primary care having a more limited role around the management of acute illness. A collaborative, patient-centerd approach accommodating multiple care processes in primary care is required. Developing clinical practice guidelines on managing multimorbidity for primary care practitioners is an important component of this new approach. Current proposals to achieve universal health coverage (UHC) in India highlight the importance of primary care strengthening but need to be cognizant of the rising burden of multimorbidity and work to strengthen health system and individual practitioner responsiveness to this challenge. The financial burden of having multiple NCDs highlights the importance of strengthening financial protection as part of universal coverage proposals. Efforts to reduce the cost of medications, which are the major source of OOPE, are already underway in India [42].

Further research is required to better understand the epidemiology of multimorbidity and associated impacts on health care utilization and costs in India and other LMIC settings. Primary care records-based prevalence studies may provide more definite estimates of the true extent of the problem. It has been hypothesized that clustering of diseases in multimorbidity could be underpinned with common etiology and thus looking at commonly occurring patterns through cluster analysis could further elucidate the dynamics of co-morbidities [43]. As cross sectional studies only reflect the diseases present at the time of data collection, and their impact on other domains is specific to this time, it would be more useful to undertake longitudinal studies to understand the progression and impact of multimorbidity over time. Furthermore, the consequences of multimorbidity on health related quality of life, poly-pharmacy, therapeutic decision making and care preferences of patients need to be investigated. The knowledge gained from such research could help in aligning current strategies along with prioritization of health services to prepare for the challenge of multimorbidity. A stronger primary care to deal with multimorbidity in a cost effective way poses a challenging task ahead for the health systems in India.

Our study provides evidence on the emerging burden of NCD multimorbidity in the Indian context, highlighting the need for better recognition by physicians, health planners and policy makers. Specifically our findings indicate a need for the growing burden of multimorbidity to be considered within the context of health system planning, encompassing workforce training and quality improvement strategies, including the development of clinical guidelines and quality indicators. Our findings reinforce the importance of strengthening primary care systems in LMICs, which is the most appropriate setting for these patients to be managed, and emphasize the need to improve financial protection in these settings. Further research is required to better understand the epidemiology of multimorbidity and associated impacts on health care utilization and costs in India and other LMIC settings.