A Cross-sectional Study of the Length of Stay of Persons with Mental Illnesses and Revenue to a Government Tertiary Neuropsychiatric Hospital Under Ayushman Bharat

Abstract

Background:

Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (AB-PMJAY) is a health insurance scheme launched by the Government of India (GOI) in 2018 to cover the in-patient (IP) treatment expenditures, including mental illness treatment expenditures, for 500 million Indians. AB-PMJAY pays 100% of treatment expenditures for persons below the poverty line (BPL) and 30% for people above the poverty line (APL). Ayushman Bharat Arogya Karnataka (ABAK) trust implements this scheme in Karnataka, a southern Indian state.

Methods:

Data of persons with mental illness (PMI) admitted under AB-PMJAY at a tertiary care neuropsychiatric hospital between 2018 and 2021 was analyzed to understand the socio-demographic and clinical variables, the average length of stay (LOS), and the amount claimed by the hospital.

Results:

Median LOS for PMI with any clinical diagnoses was 18 days (range 2–145),14 for those with substance use or mood disorders, and 24 days for those with schizophrenia and other psychotic disorders. The hospital claimed an amount of Indian Rupees (INR) 15,291,349 for treating 868 PMI under AB-PMJAY.

Conclusions:

The minimum and maximum LOS varied 70-fold, and there was a significant difference between different PMIs based on their clinical diagnosis. ABAK paid ₹3,488–12,750 per PMI for their treatment. Further research is needed to determine the variables influencing the LOS and the cost to the implementing agency.

Keywords

Ayushman Bharat-Pradhan Mantri Jan Arogya Yojana (AB-PMJAY)Ayushman Bharat mental illness length of stay in-patient treatment claim health insurance

Key Messages:

AB-PMJAY is a health insurance scheme that covers in-patient treatment expenditures, including mental illness treatment.

The study analyzed data from persons with mental illness (PMI) admitted under AB-PMJAY.

The Hospital claimed ₹15,291,349 for treating PMI under AB-PMJAY.

Further research is needed to determine variables influencing the length of stay and the cost to the implementing agency.

By 2014, about 80% of the Indian population was not covered by any health insurance scheme, two-thirds approached private hospitals for treatment and spent about Indian rupees (INR) 21,736, equal to United States America (USA) dollars ($) 265 for their in-patient (IP) treatment as an out-of-pocket expenditure (OOPE).¹ Persons with mental illnesses (PMI) report “Catastrophic expenditures (more than 10% of their total household spending)” for their IP treatment at private healthcare facilities.² Persons with severe mental illness in southern India spend about ₹15,074/- per year for availing treatment as an OOPE.³ Persons with health insurance coverage are more likely to utilize IP treatment services compared to the uninsured.⁴ Health insurance coverage is likely to reduce OOPE and mortality rates.⁵ However, this may not always be the case. Having health insurance coverage alone may not lead to increased mental healthcare service utilization by PMI.⁶ Increased utilization of mental health services requires proactive interventions from healthcare providers.⁷

In the year 2018, the Government of India (GOI) launched the Ayushman Bharat Pradhan Mantri Jan Aarogya Yojana (AB-PMJAY), estimated to cover 500 million vulnerable persons under the Indian National Health Policy 2017.⁸ AB-PMJAY is a family floater plan where beneficiaries can avail of free and cashless treatment at the empaneled hospitals.⁹ AB-PMJAY offers up to ₹500,000/ per below-poverty line (BPL) family per year and up to ₹1,50,000/- per above-poverty line (APL) family per year for the IP treatment of any of the 1393 listed health conditions categorized under 24 medical specialities with very few exclusions.^10-12 AB-PMJAY covers 100% of expenses of persons from the BPL category with a cap of ₹500,000 per year, compared to 30% of expenses incurred by persons from the APL category who have a cap of ₹150,000 per year. Treatment expenses to the empaneled hospitals are paid as a fixed package for a specified intervention to an illness or as a fixed amount per day multiplied by the number of days in the hospital. For example, AB-PMJAY pays ₹118,100 to the hospital for a Coronary Artery Bypass Graft (CABG) procedure at a fixed price. However, in contrast, ₹1500 per day in the general ward and ₹2500 per day in the high-dependency unit are paid to the hospital providing treatment for PMI covered under health insurance (Table 1).¹³ All mental illnesses categorized under the. International Classification of Diseases (ICD) 10th edition, including substance use-related disorders, are eligible for cashless treatment under the impaneled hospitals. No other health insurance policy or scheme explicitly covers the treatment of mental illness associated with substance use disorders.¹⁴

Table 1.

List of Mental Illnesses Covered Under ABAK and the Specified Rates for Treatment.

Sl No	Name of the Conditions (Insurance Code)	Payment per Day Offered for In-patient Care in the Routine Ward in INR	Payment per Day Offered for In-patient Care in High Dependency Ward in INR	Required Investigations/Documents for Approval
1	Mood disorders, psychotic disorders, substance use-related disorders, and organic mental illness (2A.M8.00001–00004)	750	1250–1875	Clinical notes, including CT * Brain
2	Neurotic stress-related disorders, behavioral syndromes with physiological disturbances, mental retardation (2B M8 00005–00007)	1125	1250–1875	Clinical notes, bedside rounds notes, lab investigations
4	Pre-electroconvulsive therapy and pre-transcranial magnetic stimulation workup, including appropriate investigations (2B M8 00015)	7500		Blood investigations, brain imaging, electrocardiography, electroencephalogram
5	Electro convulsive therapy per session (2B M8 00016)	2250		Clinical notes, bedside notes, lab investigations
6	Transcranial electromagnetic stimulation	750		Clinical notes, bedside notes, lab investigations

*CT= Computed Tomography; 2B M8 00001–00016 Alphanumeric coding for treatments under health insurance; INR = Indian Rupees.

State governments that are adapting the AB-PMJAY can implement it in two ways: creating a special trust for monitoring the implementation or forming an association with an approved insurance agency to run the scheme. The Department of Health and Family Welfare (DHFW) in Karnataka, a southern Indian state with a population of about 61 million (5% of the Indian population) as per the 2011 census,^15,16 has adopted the trust mode to implement AB-PMJAY. DHFW of Karnataka launched the Ayushman Bharat - Arogya Karnataka (ABAK) on October 30, 2018.

The ABAK Trust, using a provision that allows it to modify the coverage rates, reduced the per day cost of treatment from ₹1500 to 750 per day in the general ward and from ₹2250/- per day to 1250 in the high dependency ward (HDU) in contrast to the rates as decided by AB-PMJAY. HDUs are units with more staff per patient ratio for those requiring a higher degree of support for their behavioral control. They are meant for PMI and require closer monitoring. A total of 16 broad mental illness treatments are described in a list updated in 2020 by the AB-PMJAY in Karnataka state. Following is the list of conditions and treatment rates prescribed by the ABAK.¹¹

Examining the utilization data of AB-PMJAY by eligible PMI will offer insights into the utilization pattern of this innovative health insurance scheme and information like the length of stay (LOS) of those admitted under this scheme.

Objectives

This research was carried out to study the proportion of PMI utilizing AB-PMJAY in an empaneled tertiary care psychiatric hospital, their socio-demographic variables, the average LOS for their treatment, any significant difference in the LOS between groups of PMI with different clinical diagnoses, and the claims made by the hospital for the treatment offered.

Methods

This cross-sectional research was conducted at a state-funded tertiary care neuropsychiatric hospital empaneled under ABAK for treating PMI under AB-PMJAY. Hospital data concerning the insurance claim submission with ABAK was examined for the IPs admitted under the psychiatry department between January 1, 2019 and December 31, 2021, after obtaining an Institute ethical committee-wide letter numbered (Blinded). All the PMI aged above 18 years, admitted under the department of psychiatry using the AB-PMJAY scheme during the above-mentioned study period, were included for analysis without any exclusion. The treating psychiatrist made all the clinical diagnoses as per the International Classification of Diseases (ICD) for the diagnosis of mental disorders10th Edition (ICD 10). Data was analyzed to study the socio-demographic variables of all those who were admitted under AB-PMJAY during the research period, diagnosis made by their treating psychiatrist at the time of their discharge, duration of hospitalization, insurance claim for the amount made by the hospital with ABAK trust following the discharge. For convenience and comparison, data on PMI is arranged under six broad groups based on their clinical diagnosis, that is, F 0–9, F10–19, F20–29, F30–39, F40–69, and F 70–79. Due to the smaller number of PMI admitted under F40–49, F50–59, and F60–69 diagnosis categories in contrast to other diagnostic groups, they were clubbed as a single F40–69 category. The hospital database of PMI admitted under AB-PMJAY was analyzed using a Microsoft Excel spreadsheet for frequency distribution, and appropriate statistical tests were used to determine the normality of data and significance between the LOS using a web-based and freely accessible statistics calculator, Statistics Kingdom.¹⁷ DP carried out the data collection and analysis in an Excel sheet. HA cross-checked the data to minimize errors before frequency distribution analysis. All the PMI, 878 persons admitted during the study period were analyzed. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines were used for this research.¹⁸

Results

The proportion of PMI who availed AB-PMJAY annually increased from 1.4% in 2019 to 26.9% by 2021, as summarized in Tables 2 and 3. The mean age of this population was 37.6 years. Three-fourths were males. Approximately 90% either had a diagnosis of substance use-related disorder, a mood disorder, or a schizophrenia-related disorder.

Table 2.

Proportion and Economic Status of PMI Admitted Under AB-PMJAY.

	Year	Total Number of PMI Under AB-PMJAY (BPL+ APL)	Total Admissions for In-patient Care in the Hospital, Including Those Without AB-PMJAY	% of Total Admissions Made Under AB-PMJAY
1	2019	47 (47+0)	3421	1.4%
2	2020	152 (149+3)	1635	9.2%
3	2021	679 (620+59)	2527	26.9%
4	Total	878 (816+62)	7783	11.3%

PMI: Person with a mental illness; BPL: Below the poverty line; APL: Above the poverty line; AB-PMJAY: Ayushman Bharat-Pradhan Mantri Jan Arogya Yojana.

Table 3.

Socio-demographic Details and the LOS of PMI Admitted Under AB-PMJAY.

S.No	Variable	Numbers (n = 878)
1	Gender	Male: 642 (73%) Female: 236 (27%)
2	Age in years:	Median = 36 (Range 18–82) Mean = 37.61 (Std. Dev: 12.96)
3	Economic status: BPL APL	816 (93%) 62 (7%)
4	Domicile State to which the person belongs to	Karnataka 859 (97.8%) Tamilnadu 15 (1.7%) Others 3 (0.3%)
5	Categorization of persons with mental illness based on the length of stay at the hospital for in-patient care	Up to 10 days: 177 (20%) 11–20 days: 358 (41%) 21–30 days: 181 (21%) 31–40 days: 69 (7%) 41–50 days: 52 (6%) Above 51 days: 43 (5%)
6	LOS in days for PMI admitted under BPL (n = 816)	Median 18 (range 2–145) Q1, Q3, IQR: 12,26,14 Mean 22 (SD:16)
7	LOS in days for PMI admitted under APL (n = 62)	Median 17 (range 4–65) Q1, Q3, IQR: 11,27,16 Mean: 21 (SD: 14)
8	Average LOS for all PMI	Median 18 (range 2–145) Q1, Q3, IQR: 12,26,14 Mean: 21.46 (SD 15.4)
9	Claimed amount in INR for persons belonging to the BPL category	Total: 14,959,925 Median: 12750; range 2250–109500 Q1, Q3, IQR: 9000, 24000, 15000 Mean: 18333; S.D:14,166
10	Claimed amount in INR for persons belonging to the APL category (30% of the total treatment expenditure)	Total: 331,424 Median: 3488; range 1125–19575 Q1, Q3, IQR: 2700, 6638, 3938 Mean: 5345; SD: 4,102
	The total claim amount for the treatment of 868 PMI (BPL + APL) by the hospital is INR	15,291,349

LOS: Length of Stay; PMI: Person with a mental illness; BPL: Below poverty line; APL: Above the poverty line; INR: Indian Rupees; SD: Standard Deviation; INR: Indian Rupees; Q1, Q3, IQR: Quartile 1, Quartile 3, Inter Quartile Range.

As depicted in the figure, there was a significant variation in the range of LOS for PMI admitted across diagnostic groups. The Shapiro-Wilk test (α = 0.05) check indicates that the data spread for each group was skewed. Therefore, the Kruskal Wallis H test was used to understand the statistical difference between the median LOS of different groups, followed by the post-hoc Dunn’s test.

The Kruskal-Wallis H test indicated that there was a significant difference in the median LOS between the different groups, χ²(5) = 104.25, p < .001, with a mean rank score of 399.77 for F0–9, 330.57 for F10–19, 554.31 for F20–29, 459.49 for F30–39, 463.4 for F40–69, 364.14 for F 70–79. The Post-Hoc Dunn’s test using a Bonferroni corrected alpha of 0.0033 indicated that the mean ranks of the following pairs are significantly different: F0–9 & F20–29 (p < .001), F10–19 & F20–29 (p < .001), F10–19 & F30–39 (p < .001), F10–19 & F40–69 (p = .001), F2–39 & F40–69 (p < .001), F20–39 & F40–69 (p = .030), F 20–29 & F70–79 (p = .006). There was no significant difference between the LOS and other group comparisons. The table with details pertaining to the Kruskal-Wallis H test for differences between different groups has been provided in the supplementary material.

Discussion

There was a steady increase in AB PMAJY beneficiaries over three years, possibly due to increased awareness. LOS in ten PMIs, irrespective of their diagnosis, was just two to three days. In our experience, such a short LOS could be mostly related to PMI requesting an early discharge for a range of reasons. The LOS in 185 (21%) PMI was less than ten days. Only 18% required admission for more than 30 days, irrespective of their diagnoses, suggesting that 82% of PMI require less than four weeks in IP care.

As summarized in Table 2, the median LOS of PMI admitted was 18 days for any diagnosis, ranging from 14 to 24 days across diagnostic categories. The median LOS for those admitted with schizophrenia and related psychotic disorders was 24 days, about two times the Median LOS (14 days) of those admitted due to mood disorders or substance use-related disorders. The range of LOS in PMI belonging to the BPL group was 2–145 days compared to 4–64 days in the APL group. As depicted in Figure 1, there were only three who were treated as IPs for more than 90 days. All of them either had a diagnosis of F20–29 or F30–39. Non-response to drugs in the first few weeks, followed by electro-convulsive therapy or clozapine drug trial, might have contributed to prolonged hospitalization. However, as medical records were not reviewed, we cannot comment on the reasons for the variance in the LOS.

Figure 1.

Length of Stay of PMI Admitted Under ABAK Based on Diagnosis.

As summarized in Table 3, claim data analysis suggested that the hospital submitted claims for a median amount of ₹3488 for each APL PMI with a range of 1125–19,575. This is lower than the claim for each BPL PMI, that is, ₹12750, with a range of 2250–109,500. This difference can be explained by the observed variance in median LOS between BPL and APL groups, and ABAK pays only 30% of the hospital bill for APL PMI compared to 100% for BPL PMI. The APL PMI paid the remaining amount of the hospital bill out of their pocket. The hospital submitted an insurance claim of ₹15,291,349 for offering IP treatment of 868 PMI. There was a 48-fold variation between the minimum ₹2250 and the maximum 109500 claims submitted by the hospital. This can be explained by a similar variation in the LOS of PMI admitted.

The study examined only one state-funded hospital data and, therefore, cannot be generalized to other hospitals. The non-inclusion of medical record analysis in this study design was a limitation, as the variance in the LOS and cost claimed by the hospital for IP care could not be explained. Analysis of the average LOS under AB-PMJAY for PMI can help private health insurance companies that cite the lack of data on the LOS of PMI in the Indian context to finalize the underwriting terms.¹⁹ This preliminary data has provided scope for conceptualizing more focused research questions on the implementation, effectiveness, and penetration of AB-PMJAY for PMI.

Conclusion

The median LOS of 868 PMI admitted at a tertiary care center was 18 days (range is 2–145) and significantly varied across diagnostic categories. The median LOS of PMI due to SUD and mood disorders was lesser than those with schizophrenia and related psychotic disorders. The median LOS of APL PMI was less than BPL PMI. Empaneled hospitals can claim an amount of ₹3488–12,750 per eligible PMI offered treatment under AB-PMJAY as an IP (Table 4).

Table 4.

Categorization Based on Broad Clinical Diagnoses Group and Length of Stay (LOS).

	Broad Diagnostic Category as per ICD 10	Number of PMI (%)	Median LOS (Range) Q1, Q3, IQR	Mean LOS of PMI (Standard Deviation)
1	Organic, including symptomatic mental disorders (F0–F9)	43 (4.9)	14 (3–60) 11,27,16	19 (13)
2	Substance use-related disorders (F10–F19)	280 (31.9)	14 (2–64) 10,19,9	15 (9)
3	Schizophrenia and related psychotic disorder (F20–F29)	235 (26.7)	24 (2–129) 16,37,21	28 (18)
4	Mood disorders (F30–F39)	263 (29.9)	18 (2–145) 13,26,13	22(16)
5	Mental Retardation (F70–F79) was renamed as intellectual disability in ICD 11 edition	14 (1.5)	14 (5–70) 11,19,8	20 (19)
6	Others (F40–F69)	43 (4.8)	19 (3–77) 12,29,17	23(15)
7	Any clinical diagnosis (F0–F79)	878 (100)	18 (2–145) 12,16,14	21 (15)

F0–79 - Alphanumerical codes for mental illness under ICD 10; Q1, Q3, IQR: 1^st quarter, 3^rd quarter and Inter quartile range; PMI: Person with a mental illness.

Supplemental Material

Supplemental material for this article available online.

Supplemental Material

Supplemental material for this article available online.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Declaration Regarding the use of Generative AI

Only the institutional subscription version of Grammarly software WAS used to correct grammar and punctuation errors. We assume full responsibility for the entire content of the manuscript, including the parts generated by the AI tool.

Ethical Approval

The institute’s ethics committee approved the proposal for the present study (NIMH/Psy/DESC Meeting-10/RP/DPS/2022/21 Date: 28.06.2022).

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

References

Ministry of Statistics and Programme Implementation. National Sample Survey Office-Ministry of Statistics and Programme, Implementation (MOSPI), Government of India (GOI) [Internet]. 2023 sept 15; Available from: http://icssrdataservice.in/datarepository/index.php

Mathias

, Jacob

and Shukla

We sold the buffalo to pay for a brain scan–a qualitative study of rural experiences with private mental healthcare providers in Uttar Pradesh, India. Indian J Med Ethics, 2019; 4: 282–287.

Sivakumar

, James

, Basavarajappa

, . Impact of community-based rehabilitation for mental illness on ‘out of pocket’ expenditure in rural South India. Asian J Psychiatr, 2019; 44: 138–142.

Devadasan

, Criel

, Van Damme

, . Community health insurance in Gudalur, India, increases access to hospital care. Health Policy Plan, 2010; 25(2): 145–154.

Sood

, Bendavid

, Mukherji

, . Government health insurance for people below the poverty line in India: A quasi-experimental evaluation of insurance and health outcomes. BMJ, 2014; 25: 349.

Zuvekas

, McClellan

, Ali

, . Medicaid expansion and health insurance coverage and treatment utilization among individuals with a mental health condition. J Ment Health Policy Econ, 2020; 23: 51–182.

Saloner

, Bandara

, Bachhuber

, . Insurance coverage and treatment use under the affordable care act among adults with mental and substance use disorders. Psychiatr Serv, 2017; 68: 542–548.

Press Information Bureau M of H and FWG of I. Ayushman Bharat–Pradhan Mantri Jan Aarogya Yojana launch by Prime Minister Shri Narendra Modi in Ranchi, Jharkhand. (Cited: 30 November 2022). Available from: https://pib.gov.in/Pressreleaseshare.aspx?PRID=1546948

National Health Authority. National Health Authority, About PM-JAY: Government of India. (Cited: 15 October 2023). Available from: https://nha.gov.in/PM-JAY

10.

Press Information Bureau Ministry of Health and Family Welfare, Government of India. Medical Facilities provided under Ayushman Bharat Yojana. (Cited: 15 October 2023). Available from: https://pib.gov.in/newsite/PrintRelease.aspx?relid=199234

11.

National Health Authority. National Health Benefits Package 2.2 Version under Ayushman Bharat. (Cited: 15 October 2023). Available from: https://nha.gov.in/img/resources/HBP-2.2-manual.pdf

12.

National Health Authority. Exclusion Policy- Ayushman Bharat PM-JAY. (Cited: 15 October 2023). Available from: https://pmjay.gov.in/sites/default/files/2020-04/AB_PM-JAY_exclusion_policy.pdf

13.

National Health Authority. National Master Health Benefit Package. (Cited: 15 October 2023). Available from: https://nha.gov.in/img/pmjay-files/HBP-2.1.pdf

14.

Singhai

, Sivakumar

, Angothu

, . Review of individual health insurance policies for mental health conditions. Indian J Priv Psychiatry, 2021; 15: 4.

15.

Ministry of Home Affairs. Office of the Registrar General & Census Commissioner: Census Tables, 2011. (Cited: 15 October 2023). Available from: https://censusindia.gov.in/census.website/data/census-tables

16.

Gururaj

, Varghese

, Benegal

, . NMHS collaborators group. National Mental Health Survey of India. 2015; 16: 30–32.

17.

Kruskal-Wallis test calculator. Statistics Kingdom. (Cited: 23 October 2023). Available from: https://www.statskingdom.com/kruskal-wallis-calculator.html

18.

Von Elm

, Altman

, Egger

, . The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. Lancet, 2007; 370: 1453–1457.

19.

Kayastha

. Insurers grapple with policy pricing, design as IRDAI mandates mental health, HIV cover. (Cited: 15 October 2023). Available from: https://www.thehindubusinessline.com/news/insurers-grapple-with-policy-pricing-design-as-irdai-mandates-mental-health-hiv-cover/article66583769.ece

Supplementary Material

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