Abstract
INTRODUCTION:
Financial support system available to geriatric populations affects their adherence level to the prescribed treatment leading to a rise in chronic disease burden.
OBJECTIVE:
The aim of this study was to ascertain the disease pattern, health expenditure, and adherence to the prescriptions among geriatric patients reporting to a hospital in North India.
METHODOLOGY:
This descriptive, cross-sectional study was conducted from July 2017 to June 2018. Patients who were 60 or above years in age, already diagnosed and were on treatment for more than 3 months were included in the study. A total of 310 patients were selected using convenient sampling method. Data were collected by a pretested and validated questionnaire.
RESULTS:
The mean age of the patients was 66.16 years ± 5.37 years (54.8% males). Monthly average family income was Rs. 15202.97 ± 1134.63. Overall, 25% of the treatment cost was met through various social schemes (52% = pension scheme, 32% of patients had no such schemes and only 2% through health insurance schemes). Rest was out-of-pocket expenditure. Common diseases were hypertension (60.64%), diabetes mellitus (35.8%), cancer (28.38%), and coronary artery disease (22.58%). More than half (52.9%) of the patients had two or more illnesses; about 35.8% of them were taking treatment for 1–5 years. Moderate adherence was observed among the majority of the patients. Statistically significant (P < 0.05) difference in treatment adherence to the prescriptions was observed.
CONCLUSION:
Geriatric patients had many chronic morbidities. They had high out-of-pocket expenditure and suboptimal financial support affecting their level of adherence to the prescriptions.
Keywords: Adherence, chronic morbidities, geriatric, out-of-pocket expenditure, social schemes
Introduction
In India, life expectancy at birth has recently gone up, and the population will be around 21% (301 million) by 2050. The elderly suffers from many chronic diseases such as diabetes, hypertension, coronary artery disease, musculoskeletal, psychiatric, and cancers. A high disease burden in the elderly puts immense pressure on limited health resources and services.[1,2,3] Long-term therapies and polypharmacy associated with multiple comorbidities lead to a higher risk of nonadherence to medications in elderly patients.[4,5] This results in frequent hospital and doctors’ visits, longer stays and higher readmission rates in hospitals, decreased treatment benefits for the patients and increased expenditure treatment.[6,7]
Two-thirds of the elderly live in rural India and half of these come from poor socioeconomic strata.[4] Three-fourth of the elderly are either fully or partially dependent on others. A significant number remains either uninsured or underinsured. This is more true for females.[2,4]
Need of the study
India is committed to Universal Health Coverage. However, the efforts are in their early stages only. Health insurance has only recently been given attention by the health-care administrators. Whatever financial support schemes are available geriatric patients are utilized suboptimally.
For having any worthwhile impact of the financial support system to be developed for geriatric patients, it is important to create a database on the research questions such as – (a) What is the disease pattern in geriatric patients; (b) What is their case load on hospitals, and (c) What is the existing health security schemes for them.
Against this background, this study was conducted with the objectives: (i) to ascertain the disease pattern among the geriatric patients visiting a tertiary care hospital of India, (ii) to evaluate the existing financial support system through any health security schemes for their treatment, and (iii) to determine the treatment adherence level in them.
Methodology
The descriptive, cross-sectional questionnaire-based study was conducted from July 2017 to June 2018. The study population included the patients who were 60 years or above in age, already diagnosed and were on treatment for more than 3 months (chronic conditions) before they were admitted in inpatient department (IPD) or had attended the outpatient department (OPD) of the study hospital. Only those patients who were willing to participate and met the inclusion criteria were recruited in the study. There was a total of 31 study areas selected using the lottery method. These were divided into 18 OPD and 13 IPD areas of different departments of the study hospital. Ten patients per study area were selected using the lottery method. One study area was visited per day to collect the data. Each area was visited three times but not on consecutive days. Sociodemographic details disease profile of the patients, number of illnesses, duration of treatment, and any other relevant information in respect of the ongoing treatment was also recorded on the proforma. Previous medical records available with the patients were seen to obtain relevant information pertaining to the case.
The level of adherence to the treatment was assessed using eight-item Morisky Medication Adherence Scale-8 (MMAS-8).[8] The total score on the MMAS-8 can range from 0 to 8. A total score of “0” reflects high adherence, a score of “1–2” reflects medium adherence, whereas a 14 score of “>2” reflected low adherence levels.
The sociodemographic data were analyzed using descriptive statistics, namely mean and standard deviation. Significance of the association between dependent and independent variables were evaluated using the Chi-square test. The SPSS version 22(IBM, Chicago, USA) and Epi-info version 7 were used for the analysis of data.
Ethical clearance was taken from the Institute Ethics Committee, and written informed consent was taken from each participant.
Results
Demographic details of the patients are described in Table 1.
Table 1.
Demographic profile of the study population (n=310)
| Variables | n (%) |
|---|---|
| Patient care area | |
| IPD | 130 (41.9) |
| OPD | 180 (58.1) |
| Age group (years) | |
| 60-69 | 233 (75.2) |
| 70-79 | 69 (22.3) |
| ≥80 | 8 (2.6) |
| Gender | |
| Female | 140 (45.2) |
| Male | 170 (54.8) |
| Residence | |
| Rural | 161 (51.9) |
| Urban | 149 (48.1) |
| Marital status | |
| Married | 248 (80.0) |
| Widow | 41 (13.2) |
| Widower | 21 (6.8) |
| Unmarried | 0 (0) |
| Divorced | 0 (0) |
| Family type | |
| Joint | 244 (78.7) |
| Nuclear | 66 (21.3) |
| Educational status | |
| Illiterate group | 82 (26.5) |
| Secondary | 57 (18.4) |
| Graduates | 45 (14.5) |
| Postgraduation | 17 (5.5) |
| Occupational status | |
| Housewives | 119 (38.4) |
| Government employees | 81 (26.1) |
| Private jobs | 51 (16.5) |
| Farmers | 42 (13.5) |
| Driver | 1 (0.3) |
| Income status (monthly), INR | |
| 900-10,000 | 150 (48.4) |
| 10,001-20,000 | 72 (23.2) |
| 20,001-30,000 | 40 (13.4) |
| 30,001-4000 | 40 (13.4) |
| ≥40,000 | 5 (1.6) |
IPD=In patient department, OPD=Outpatient department
The total number of patients in the study population (n) was 310. Among these, 130 (41.9%) were from IPD and 180 (58.1%) were from OPD. The mean age of the patients was 66.16 years ± 5.37 years; 54.8% were males and 51.9% of patients belonged to rural areas. Most (80%) patients were married and 78.7% were from the joint families. Some (26.5%) of the patients were illiterate. Occupation-wise, one-fourth were government employees’ beneficiaries and 38.4% were homemakers.
Their mean monthly income was Rs. 15202.97 ± 1134.63 which included salaries, pensions, income of family members, and assistance from health schemes. Most (90%) of the patients were from the above poverty line category. Most (81.9%) of the patients gave no history of addiction (taking alcohol and smoking). Overall, 25% treatment cost was incurred by some social schemes. Rest was out-of-pocket expenditure [Figure 1].
Figure 1.
Mode of payment for treatment
In 68% of patients, treatment cost was covered by pension or other scheme; about 32% of patients were found uncovered by any social safety schemes [Figure 2].
Figure 2.
Type of health schemes availed by the patients
Majority (64%) of the patients spent Rs. 1000–1500/month on their treatment. Figure 3 shows the prevalence of chronic diseases reported by them, for example, hypertension (60.64%), diabetes mellitus (35.8%), cancer (28.38%), and coronary artery disease (22.58%). More than half (52.9%) of the patients had two illnesses and most (35.8) of them was taking treatment for 1 year–5 years [Figure 4]. Details of treatment adherence are described in Table 2. Majority of them (64%) often forgot to take the prescribed medicines; most (95.5%) did take their medicines yesterday; many (28%) found it difficult to stick to their treatment plan; and few (12.3%) stopped taking their medicines without telling their doctor because they felt worse.
Figure 3.
Disease patterns among geriatrics
Figure 4.
Chronicity of the diseases
Table 2.
Morisky 8-item treatment adherence questions
| Morisky questions | Yes | No |
|---|---|---|
| Forgot to take medicine | 198 (63.9) | 112 (36.1) |
| Missed medicines in past 2 weeks for reasons other than forgetting | 37 (11.9) | 273 (88.1) |
| Stopped taking their medicines without telling their doctor because they felt worse | 38 (12.3) | 272 (87.7) |
| Number of patients who forget to bring their medicines when they leave their home | 39 (12.6) | 271 (87.4) |
| Number of patients who took their medicines yesterday | 296 (95.5) | 14 (04.5) |
| Patients who stopped taking their medicines when they felt that their health is under control | 20 (6.5) | 290 (93.5) |
| Patients who found it difficult to stick to their treatment plan | 87 (28.1) | 223 (71.9) |
| Difficulty in remembering to take all medications | n (%) | |
| 0 (never/rarely) | 125 (40.3) | |
| 1 (once in a while) | 162 (52.3) | |
| 2 (sometimes) | 23 (7.4) | |
| 3 (usually) | 00 (0.0) | |
| 4 (all the time) | 0 (0.0) | |
| Total | 310 (100.0) | |
Better adherence (P=0.007***) to their medications was seen in patients from OPD (66.4%) as compared to 59.2% in IPD patients [Table 3]. There was a declining level of adherence to treatment with increasing age of the patients. Most of the patients showed medium level of adherence (44.2%). The maximum number of patients in the study (52.9%) population had two illnesses. With an increase in the number of comorbidities, the level of adherence to treatment significant decreased (P < 0.05). Significantly, lower adherence levels were observed when the duration of chronicity was higher (P = 0.00).
Table 3.
Association with adherence with other variables
| Variables | Adherence to medication, n (%) | P<0.05 | |||
|---|---|---|---|---|---|
| Low | Medium | High | Total | ||
| Patient care area | 0.007** | ||||
| IPD | 53 (40.8) | 63 (48.5) | 14 (10.8) | 130 (100) | |
| OPD | 61 (33.9) | 74 (41.4) | 45 (25) | 180 (100) | |
| Total | 114 (36.8) | 137 (44.2) | 59 (19) | 310 (100) | |
| Age group | |||||
| 60-69 | 81 (34.8) | 103 (44.2) | 49 (21.0) | 233 (100.0) | 0.523 |
| 70-79 | 29 (42.0) | 31 (44.9) | 9 (13.0) | 69 (100) | |
| ≥80 | 4 (50.0) | 3 (37.5) | 1 (12.5) | 8 (100) | |
| Total | 114 (36.8) | 137 (44.2) | 59 (19.0) | 310 (100) | |
| Educational status | |||||
| Illiterate | 36 | 32 | 14 | 82 | 0.194 |
| Primary | 18 | 21 | 7 | 46 | |
| Middle | 18 | 14 | 8 | 40 | |
| Secondary | 22 | 23 | 12 | 57 | |
| Higher secondary | 3 | 17 | 3 | 23 | |
| Graduates | 11 | 23 | 11 | 45 | |
| Postgraduates | 6 | 7 | 4 | 17 | |
| Total | 114 | 137 | 59 | 310 | |
| Area of residence | |||||
| Rural | 62 (38.5) | 62 (38.5) | 37 (23.0) | 161 (100.0) | 0.065** |
| Urban | 52 (34.9) | 75 (50.3) | 22 (14.8) | 149 (100.0) | |
| Total | 114 (36.8) | 137 (44.2) | 59 (19.0) | 310 (100.0) | |
| Gender | |||||
| Female | 49 (35.0) | 67 (47.9) | 24 (17.1) | 140 (100) | 0.479 |
| Male | 65 (38.2) | 70 (41.2) | 35 (20.6) | 170 (100) | |
| Total | 114 (36.8) | 137 (44.2) | 59 (19.0) | 310 (100) | |
| Income/month (Rs) | |||||
| 900-10,000 | 59 | 66 | 25 | 150 | 0.766 |
| 10,001-20,000 | 23 | 36 | 13 | 72 | |
| 20,001-30,000 | 20 | 24 | 14 | 58 | |
| 30,001-40,000 | 11 | 8 | 6 | 25 | |
| ≥40,000 | 1 | 3 | 1 | 5 | |
| Total | 114 | 137 | 59 | 310 | |
| Knowledge of health schemes | |||||
| No | 52 | 57 | 27 | 136 | 0.774 |
| Yes | 62 | 80 | 32 | 174 | |
| Total | 114 | 137 | 59 | 310 | |
| Number of co-morbidities | |||||
| 1 | 16 | 18 | 24 | 58 | 0.00** |
| 2 | 66 | 72 | 26 | 164 | |
| 3 | 31 | 39 | 7 | 77 | |
| 4 | 1 | 8 | 2 | 11 | |
| Total | 114 | 137 | 59 | 310 | |
| Duration of chronicity | |||||
| 3 months-1 year | 18 | 14 | 45 | 77 | 0.00** |
| 1-5 years | 43 | 58 | 10 | 111 | |
| 5-10 years | 35 | 41 | 3 | 79 | |
| ≥10 years | 18 | 24 | 1 | 43 | |
| Total | 114 | 137 | 59 | 310 | |
***Statistically significant. IPD=In patient department, OPD=Outpatient department
Overall, 56% of the patients knew about health or any social security schemes, but no significant association was observed between knowledge and adherence level [Table 4].
Table 4.
Treatment adherence and health schemes
| Adherence level | Knowledge of the patients about health schemes Mode of payment for treatment expenses | |||||
|---|---|---|---|---|---|---|
| Yes | Total | No | Total | |||
| Out-of-pocket | Health schemes | Out-of-pocket | Health schemes | |||
| Low | 40 | 22 | 62 | 46 | 6 | 52 |
| Medium | 48 | 32 | 80 | 54 | 3 | 57 |
| High | 18 | 14 | 32 | 26 | 1 | 27 |
| Total | 106 | 68 | 174 | 126 | 10 | 136 |
| P | 0.720 | 0.328 | ||||
Discussion
In old age, chronic diseases burden increases due to senescence. Similar trend was observed in this study on geriatric patients based in a tertiary care facility of India where the most common presenting illnesses were hypertension, diabetes mellitus, cancer, coronary artery disease followed by others involving many systems of the body. Similar disease pattern was seen in a study on geriatric patients conducted by Sarode et al.[9]
Quality of life in geriatric patients is immensely affected by the level of adherence to the prescribed treatment, which is affected by multiple factors. In our study, high adherence to medication was observed only in 19% of patients. Overall, it was deficient, i.e., medium in 44.2% and low levels in 36.8% of patients. A study by Shruthi et al. conducted on 251 geriatric participants in OPD with chronic illnesses showed that 45.41% had good, 35.45% moderate, and 19.12% had poor adherence levels.[10]
A similar study conducted by Lee et al. showed 65.1% of patients had good adherence to treatment (high and moderate), whereas 32.6% were of poor adherence to treatment.[11] A study by Korb-Savoldelli et al. showed that of 199 patients included in the study, the adherence level was high 43.7%, 37.7% medium, and 17.6% low.[12] A study conducted by Waari et al. showed the adherence levels to be low for 28.3%, medium for 26.2%, and high for 45.5% of the patients.[13] Another study conducted by Holt et al. showed that 51.7% of the patients had high adherence levels, 34.2% had medium, and 14.1% of patients had low adherence levels to medication.[14] Therefore, our study reflected much lower treatment adherence levels among the geriatric patients compared to other studies.
In our study with the increase in the number of illnesses, the adherence levels significantly decreased. This may be due to patients with multiple illnesses require more number of drugs than those with single illness with complex dosing regimen and increased medication costs. Furthermore, patients with single illness are likely to be more adherent to treatment because of the simpler dosing regimen.
A study conducted by Shruthi et al. also showed that the patients with multiple illnesses with longer duration of treatment receiving multiple medication showed lower levels of adherence. Forgetfulness was the most common cause for missing the medications apart from other causes such as polypharmacy, the complexity of regime, lack of time, side effects, and others.[10] In our study also, most of the patients had answered to question no. 1 of MMAS-8 with “yes” response (63.9%) showing a high degree of forgetfulness.
In a study conducted by Balkrishnan, revealed that no association was observed between the number of illnesses and the level of drug adherence.[15]
Although better (25%) adherence level was observed in OPD patients in comparison to IPD (10.8%) patients in our study. This may be because the indoor patients might have been less adherent to the treatment they were taking earlier which led to the admission (P < 0.05).
It was significant to note that in the majority (68%) the patients, treatment cost was covered by pension or other health schemes. Despite that, the patients had to make out-of-pocket expenditure. This hints at inadequacy of the existing schemes.
Only one-third (32%) of the patients were uncovered by any schemes. However, this data may not be exclusively representative of the general population.
Conclusion
Majority (81%) of our patients had moderate/poor treatment adherence
The most common morbidity was hypertension, followed by diabetes mellitus, cancer, coronary artery disease, and others
One-third (32%) of our patients had no financial assistance for their treatment. Existing schemes were inadequate to prevent out-of-pocket expenditure
Significant difference was observed between the level of adherence and the patient care areas, number of morbidities, and duration of treatment.
Recommendations
Further study is required to know the problem of poor adherence and lack of financial assistance among the geriatric patients despite the existing social safety schemes for the poor
Geriatric patients and their family members should be counseled about the importance of health promotion activities, disease prevention strategies, and treatment adherence for healthy aging.
Strengths
This study assessed on the same platform, the three interlinked health problems of the elderly, i.e., disease pattern, their adherence level to prescribed medications and the financial support system available for the treatment
This study highlights the determinants of nonadherence of treatment among geriatric patients.
Weakness
This is a facility-based study and community-level data would have added to the quality of the study
We did convenient sampling method with a small sample size, it will be better if we did it by simple random sampling with a larger sample size
Checking adherence with Morsiky 8-item tool has inherent limitations, as it is very subjective. It would have been better if we checked their adherence by “pill count” method
In this study we did only cost analysis; full economic evaluation would have given us a better insight of and health-care expenditure among the geriatrics, including out of pocket and catastrophic expenditure.
Financial support and sponsorship
Nil.
Conflicts for interest
There are no conflicts for interest.
Acknowledgments
We acknowledge all researchers and authors who had contributed to preparing our manuscript directly and indirectly. We also acknowledge all the patients and health workers who cooperated us during this study.
References
- 1.Mathur N. Assessment of functional capacity in patients attending geriatrics outpatient department at civil hospital, Ahmedabad. CHRISMED J Health Res. 2016;3:28. [Google Scholar]
- 2.Geriatric morbidity pattern and depression in relation to family support in aged population of Kashmir valley. [Last accessed on 2019 May 30];Internet J Geriatr Gerontol. 2008 4:34–36. Available from: http://www.ispub.com/doi/10.5580/1ed1 . [Google Scholar]
- 3.Jamkhandi DM, Bhattacharji S. Profile of elderly attending a general practice clinic in a poor urban area: A cross-sectional study from South India. J Family Med Prim Care. 2016;5:792–7. doi: 10.4103/2249-4863.201172. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Lena A, Ashok K, Padma M, Kamath V, Kamath A. Health and social problems of the elderly: A cross-sectional study in Udupi taluk, Karnataka. Indian J Community Med. 2009;34:131–4. doi: 10.4103/0970-0218.51236. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Chiang-Hanisko L, Tan JY, Chiang LC. Polypharmacy issues in older adults. Hu Li Za Zhi. 2014;61:97–104. doi: 10.6224/JN.61.3.97. [DOI] [PubMed] [Google Scholar]
- 6.Toh MR, Teo V, Kwan YH, Raaj S, Tan SY, Tan JZ. Association between number of doses per day, number of medications and patient's non-compliance, and frequency of readmissions in a multi-ethnic Asian population. Prev Med Rep. 2014;1:43–7. doi: 10.1016/j.pmedr.2014.10.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Chisholm-Burns MA, Spivey CA, Hagemann T, Josephson MA. Women in leadership and the bewildering glass ceiling. Am J Health Syst Pharm. 2017;74:312–24. doi: 10.2146/ajhp160930. [DOI] [PubMed] [Google Scholar]
- 8.Morisky DE, Ang A, Krousel-Wood M, Ward HJ. Predictive validity of a medication adherence measure in an outpatient setting. J Clin Hypertens (Greenwich) 2008;10:348–54. doi: 10.1111/j.1751-7176.2008.07572.x. [DOI] [PMC free article] [PubMed] [Google Scholar] [Retracted]
- 9.Sarode GS, Sarode SC, Patil S. Under reporting of cancer data in India? J Contemp Dent Pract. 2017;18:81–2. doi: 10.5005/jp-journals-10024-1995. [DOI] [PubMed] [Google Scholar]
- 10.Shruthi R, Jyothi R, Pundarikaksha HP, Nagesh GN, Tushar TJ. A study of medication compliance in geriatric patients with chronic illnesses at a tertiary care hospital. J Clin Diagn Res. 2016;10:FC40–3. doi: 10.7860/JCDR/2016/21908.9088. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Lee GK, Wang HH, Liu KQ, Cheung Y, Morisky DE, Wong MC. Determinants of medication adherence to antihypertensive medications among a Chinese population using Morisky medication adherence scale. PLoS One. 2013;8:e62775. doi: 10.1371/journal.pone.0062775. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Korb-Savoldelli V, Gillaizeau F, Pouchot J, Lenain E, Postel-Vinay N, Plouin PF, et al. Validation of a french version of the 8-item morisky medication adherence scale in hypertensive adults. J Clin Hypertens (Greenwich) 2012;14:429–34. doi: 10.1111/j.1751-7176.2012.00634.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Waari G, Mutai J, Gikunju J. Medication adherence and factors associated with poor adherence among type 2 diabetes mellitus patients on follow-up at Kenyatta national hospital, Kenya. Pan Afr Med J. 2018;29:82. doi: 10.11604/pamj.2018.29.82.12639. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Holt EW, Muntner P, Joyce CJ, Webber L, Krousel-Wood MA. Health-related quality of life and antihypertensive medication adherence among older adults. Age Ageing. 2010;39:481–7. doi: 10.1093/ageing/afq040. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Balkrishnan R. Predictors of medication adherence in the elderly. Clin Ther. 1998;20:764–71. doi: 10.1016/s0149-2918(98)80139-2. [DOI] [PubMed] [Google Scholar]