Indian Journal of Medical Ethics

RESEARCH ARTICLE


A typology framework for unethical medical practices under public health insurance schemes in India: Analysis of evidence over the past 12 years

Parul Naib

Published online first on August 8, 2024. DOI:10.20529/IJME.2024.050

Abstract

Background: Unethical provider practices in public healthcare schemes adversely impact beneficiaries’ health, result in the loss of public funds, and also bring disrepute to the schemes. There is extensive literature on the typologies of unethical practices in healthcare in developed countries. This study aims to develop a typology framework which is applicable in the Indian context.

Methods: In this study, 25 media reports and research studies were analysed on unethical provider practices under public health insurance schemes in India over the past 12 years from 2010 to 2022. The reports were collated from de-empanelment orders issued by state health authorities against various erring entities, and research studies conducted on the abuse of these schemes.

Results: Based on the analysis and classification of the cases reported, an “Unethical Provider Practices” typology for healthcare fraud has been defined. Additional fraud typologies are found to be prevalent in India in addition to those captured by existing frameworks. These include patient harm, ID theft of beneficiary data to create cards for non-beneficiaries, and collusion between providers and different entities.

Conclusions: Fraud control mechanisms leveraging technology such as AI-enabled digital apps for medical audits, biometric technology at the point of care and rigourous checks of ID documents before beneficiary cards are issued as well as having more specific legal provisions in place for healthcare fraud will enable enhanced prevention, detection and deterrence of healthcare fraud.

Keywords: healthcare fraud, medical ethics, unethical practices

Introduction

Health systems globally are susceptible to unethical provider practices. Such practices cause financial harm to the payer and lead to inefficiency and inequity in resource allocation [1]. Unethical medical practices also constitute a breach of trust for patients who believe that the doctor is acting in their best interest, and this may adversely impact patient health [2]. The nature of healthcare treatments and the uncertainties and personalisation of the care involved also make it difficult to be absolutely confident about when the care is medically necessary and when it may be a waste of resources. This difficulty in proving the intent behind the provider’s actions makes healthcare fraud difficult to identify [3, 4]. In the case of public health insurance schemes, fraud and abuse increase the costs of healthcare, making it difficult to cover healthcare costs of the most vulnerable and poor. Fraud leads to a diversion of limited public healthcare outlays. As the costs of care escalate, states may not be able to reimburse providers in a timely and efficient manner. This may then lead to denial of care for the poor and vulnerable, leading to higher healthcare costs and further impoverishing them.

In India, the need for state-provisioned healthcare was recognised as early as 1954, with the Bhore Committee’s recommendations to set up a strong public healthcare system comprising primary healthcare centres (PHCs), community health centres for secondary care, and district hospitals at the tertiary level, providing comprehensive healthcare [5]. The system was supposed to cater to the healthcare needs of the Indian population and provide free healthcare to all. However, the current public health system has fallen short of expectations and suffers from several deficiencies, including poor infrastructural facilities, and a shortage of medical doctors and staff. From 2008 onwards, various states started introducing health coverage schemes for the poor to provide secondary and tertiary care in private hospitals. These state-sponsored schemes were limited in scope and fragmented, with limited coverage of procedures, and funded entirely by the state. There was a lack of standardisation of benefits covered by different states. Following this, the Central government launched the Rashtriya Swasthya Bima Yojana (RSBY) in 2008. The scheme provided an inpatient benefit cover of up to Rs 30,000 annually on a family floater basis. The RSBY was implemented in states through a contractual arrangement between insurance companies and state governments. The scheme covered 1,516 treatment packages, more than those covered under previous state schemes. The scheme was funded jointly by the Central and state governments in the ratio of 60:40. As of the year 2018-19, the RSBY had been implemented in 12 states and union territories (UTs). However, as the money provided for inpatient care cover was limited, and the scheme was not portable across states, it had limited success in reducing out-of-pocket payments in healthcare [6].

In 2018, most state schemes were subsumed under the umbrella of the centrally launched Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (PM-JAY) to provide free health coverage to the poorest in India. The scheme covers inpatient treatment up to Rs 5 lakh annually per family and is portable across states. The scheme is operational in 33 states, that is, except for West Bengal, Telangana, Delhi and Odisha. More than 3 crore treatments have been provided under PM-JAY and over 18 crore beneficiary cards had been issued as of June 30, 2022 [7]. At the Central level, the National Health Authority (NHA) has been set up to oversee the implementation of the scheme along with the state health agencies (SHA). The state-wise utilisation of care under PM-JAY as of June 30, 2022, is shown in Table 1.

Table 1: State-wise utilisation and card issuance metrics as of June 30, 2022

State Name

No. of Ayushman Cards issued

Population eligible under PM-JAY

Percentage cards issued

No of Claims submitted

Claims per 100,000 beneficiaries

 Andaman & Nicobar  Islands

39,980 

96,296 

41.52% 

1,535 

1594 

 Andhra Pradesh

1,40,01,384 

6,51,58,007 

21.49% 

25,76,139 

3954 

 Arunachal Pradesh

56,957 

11,70,977 

4.86% 

1,837 

157 

 Assam

4,70,361 

1,21,36,482 

3.88% 

4,49,964 

3708 

 Bihar

76,12,889 

4,86,49,568 

15.65% 

4,22,765 

869 

 Chandigarh

70,742 

1,06,551 

66.39% 

20,167 

18927 

 Chhattisgarh

1,56,13,079 

2,50,69,136 

62.28% 

25,88,661 

10326 

 D&D and D&NH

4,24,569 

878,710 

48.3% 

87,824 

10012 

 Goa

23,927 

1,63,940 

14.60% 

10,488 

6397 

 Gujarat

1,36,10,604 

3,41,48,417 

39.86% 

30,55,969 

8949 

 Haryana

28,58,958 

69,56,712 

41.10% 

4,90,767 

7055 

 Himachal Pradesh

11,19,250 

21,55,433 

51.93% 

1,49,949 

6957 

 Jammu & Kashmir

70,66,128 

92,44,341 

76.44% 

4,96,108 

5367 

 Jharkhand

94,28,423 

2,56,99,199 

36.69% 

12,28,434 

4780 

 Karnataka

97,82,602 

5,17,50,000 

18.90% 

30,46,409 

5887 

 Kerala

69,07,145 

1,87,02,500 

36.93% 

41,29,931 

22082 

 Ladakh

1,12,283 

1,77,939 

63.10% 

1,246 

700 

 Lakshadweep

18,679 

55,440 

33.69% 

129 

232 

 Madhya Pradesh

2,76,61,675 

4,88,77,439 

56.59% 

17,39,027 

3558 

 Maharashtra

74,70,349 

3,76,36,488 

19.85% 

5,79,944 

1541 

 Manipur

4,25,365 

12,29,625 

34.59% 

64,436 

5240 

 Meghalaya

17,21,478 

24,93,590 

69.04% 

4,47,381 

17941 

 Mizoram

3,73,898 

8,76,866 

42.64% 

70,978 

8095 

 Nagaland

2,81,306 

10,49,976 

26.79% 

26,081 

2484 

 Puducherry

3,89,253 

4,65,453 

83.63% 

21,211 

4557 

 Punjab

78,89,985 

1,78,07,423 

44.31% 

12,54,169 

7043 

 Rajasthan

NA 

6,02,90,266 

NA 

13,72,888 

2277 

 Sikkim

48,498 

1,78,821 

27.12% 

7,369 

4121 

 Tamil Nadu

1,57,24,432 

6,61,50,000 

23.77% 

73,59,704 

11126 

 Tripura

12,81,523 

22,09,338 

58.00% 

1,53,276 

6938 

 Uttar Pradesh

1,87,89,318 

5,63,77,481 

33.33% 

13,49,749 

2394 

 Uttarakhand

47,23,056 

70,62,606 

66.87% 

5,14,352 

7283 

 Total

17,59,98,096 

60,50,25,020 

29.09% 

3,37,18,887 

2,02,551 

 Source: PM-JAY Public Dashboard and States at a Glance from PM-JAY website
 Excludes the states of Delhi, Telangana, Odisha and West Bengal as the PM-JAY scheme has not been  implemented in these states. Card issuance numbers for Rajasthan were not available.

Among the larger states, Jammu and Kashmir and Chhattisgarh had the highest penetration in issuance of beneficiary cards, with more than 70% of the eligible beneficiary population possessing an Ayushman card. Amongst the smaller states and UTs, Puducherry, Meghalaya, Uttarakhand, Chandigarh and Ladakh had higher rates of beneficiary enrolment.

Rationale for the study

Several studies have looked at the unique characteristics of the healthcare market which make it vulnerable to unethical practices by providers [1,3,8]. Informational asymmetry between the seller (healthcare provider) and purchaser (insurance company/payer) on the patient’s actual health problems, combined with the patients’ complete trust in the healthcare provider, creates the ideal conditions for malpractices. The incentive incompatibility of the fee-for-service payment model and the inelastic demand for healthcare services further exacerbate this. The fee-for-service model implies that payments are directly linked to the medical procedures irrespective of the need and impact on patient health. Thus, providers are incentivised to perform more procedures in order to increase their payments. At the same time the demand for healthcare is fairly inelastic so that even if the cost of treatment is high, the patient is forced to incur it since it has a direct impact on their health and life even at the cost of selling assets or cutting down expenditure on other essential items. Unethical practices not only lead to financial leakages but also adversely impact patient health outcomes, including increasing patient mortality rates, and lead to inequity in access to quality healthcare services, eg in case, money is charged to poor beneficiaries who might find it difficult to pay and thus are denied care [1,2, 9]. They also result in a breach of trust, both between provider and payer — whether government or insurance company — due to the payer’s financial losses; and between providers and patients (especially when medically unnecessary and harmful procedures are performed). In developing countries such as India, which are striving to achieve universal health coverage, it is imperative to ensure that such unethical malpractices are curbed.

The different instances of malpractices detected can be classified into different types of unethical practices. By grouping these instances on the basis of common features, a typology framework or systematic classification, is defined. It is important to define an India-specific framework given the differences in its healthcare system vis- à-vis those of developed countries such as coexistence of both public and private hospitals, differences in the demographic characteristics of beneficiaries in terms of low income and education levels, and differences in the level of monitoring by the authorities. Most of the existing literature and typology frameworks pertaining to unethical medical practices in healthcare (fraud, waste, abuse and corruption) address the context of developed countries [4, 10, 11]. The typology frameworks defined by the European Healthcare Fraud and Corruption Network (EHFCN) Waste Typology [11] and Transparency International’s 5-Actor Framework for Corruption [1], or the World Health Organization (WHO) (Red Flags Frameworks) [12] and the US Center for Medicaid and Medicare Services (CMS) (Fraud, Abuse, Errors, Waste) [13] may not adequately cover the various types of malpractices in India, given the vast differences in health systems and the disease burden.

Fraud detection mechanisms leveraged by insurance companies or other payers typically include medical review and audits of claims by doctors (referred to as claim processing doctors) and medical auditors. This is done prior to payment of the claim to determine the medical necessity and veracity of the treatment and confirm that it was indeed given. It may also be done through data analysis to identify irregular trends or patterns [14, 15]. Claims confirmed as fraudulent based on a desk review of submitted documents will be denied. Suspect claims may be investigated in the field, and medical audits followed up at the hospital to collect additional evidence.

Given that in the Indian system there is a strong presence of both public and private providers with different financial incentives, the types of malpractices that occur in India need to be analysed further. Legal provisions in cases of healthcare fraud are also poorly defined in the Indian Penal Code, which makes it difficult to take deterrent action against errant hospitals [16, 17]. The intended beneficiaries of schemes are the poor and vulnerable who lack the ability to organise and seek justice even in cases of patient harm, though incidents of patient harm have been reported in studies [18, 19, 20]. Further, healthcare providers in public schemes in India play a dual role — they provide care and also enrol beneficiaries. To the best of my knowledge, there has not been any comprehensive study to document the various types of unethical practices under public healthcare schemes in India and to define a typology framework relevant to the Indian context. This study analyses data on healthcare malpractices in public health insurance schemes in India, synthesising evidence over the past 12 years, to define the typology of these malpractices. Through this study, I seek to comprehensively study the types of malpractices which have been identified under government-funded health insurance schemes and define a typology of these practices which is suitable to the Indian context.

Methods

The study was conducted as part of the author’s PhD research titled “Assessment and analysis of factors impacting provider fraud under Ayushman Bharat PM-JAY” approved by the Institutional Review Board of Indian Institute of Health Management Research (IIHMR) University, vide approval number IORG0007355. An analysis of media reports and de-empanelment orders issued against hospitals by various SHAs was conducted to collate case studies of frauds detected so far by SHAs. Audit reports of the Comptroller and Auditor General of India were also reviewed for adverse observations pertaining to fraud in those government-funded health insurance schemes which were later merged into PM-JAY. The media reports were identified from online repositories and archives of Indian media news reports in English. The Print, Deccan Herald, The Financial Express, Business Standard, The Hindu BusinessLine, India Today, Google News Search and The Indian Express were searched.

The following search criteria were used: (‘unethical medical practices’ AND ‘India’) OR (‘unethical treatment’ AND ‘India’) OR (‘abuse in medical practices’ AND ‘India’) OR (‘patient harm’ AND ‘India’) OR (‘violation of patient rights’ AND ‘India’) OR (‘fraud PM-JAY’) OR (‘fraud RSBY’) OR (‘unethical practices’ AND ‘Arogyashree’) OR (‘Unethical practices’ AND ‘Bhamashah’).

Secondary data were also collected from the PM-JAY public dashboard and the PM-JAY state fact-sheets on the PM-JAY website (www.pmjay.gov.in), and various press releases of the Ministry of Health and Family Welfare. De-empanelment orders were retrieved from the websites of Karnataka and Uttarakhand SHA, which were available in the public domain.

Based on this review, 93 articles or studies were found to be relevant for the current study as shown in the PRISMA flowchart in Figure 1 (available online only).

A comprehensive review of each of the media reports and articles was conducted to analyse the cases of unethical medical practices reported and separate them according to the type of unethical medical practice, the entities engaging in them, and the stages at which they occur. Each report was then classified as per the typology it represented.

Results

A total of 3.37 crore claims had been submitted under PM-JAY as of June 30, 2022. As can be seen in Table 1, the highest utilisation per 100,000 beneficiaries was observed in Kerala, followed by Chandigarh, and then Meghalaya. Of the 3.37 crore claims, 1.45 crore (43%) claims were contributed by the South Indian states of Tamilnadu, Kerala and Karnataka.

A total of 22,874 non-genuine cases were reported under PM-JAY across various states as on Jan 31, 2022 [21]. The state-wise analysis of these claims indicates significant variations as observed in Table 2. The highest ratio of fraudulent claims to total claims was in Punjab (437 per 1,00,000 claims submitted in the state) followed by Haryana and Chhattisgarh. Significantly lower levels of fraudulent claims were reported in the North-Eastern states and in Kerala. The state-wise details of fraud claims reported by the NHA under the PM-JAY scheme is given in Table 2. A total of 210 hospitals have been de-empanelled under PM-JAY [22], with penalties levied amounting to Rs 16.8 crore as of August 30, 2021 [23].

Table 2: State-wise fraud claims as of January 31st 2022

State

No. of confirmed fraud cases under PM-JAY   (as on 31 January, 2022)

Total Claims

Fraud claims per 100,000 claims submitted

 Assam

4,49,964 

0.44 

 Bihar

50 

4,22,765 

11.83 

 Chhattisgarh

6,785 

25,88,661 

262.1 

 Gujarat

16 

30,55,969 

0.52 

 Haryana

1,403 

4,90,767 

285.88 

 Himachal Pradesh

22 

1,49,949 

14.67 

 Jammu & Kashmir

1,011 

4,96,108 

203.79 

 Jharkhand

2,783 

12,28,434 

226.55 

 Kerala

904 

41,29,931 

21.89 

 Madhya Pradesh

2,627 

17,39,027 

151.06 

 Meghalaya

96 

4,47,381 

21.46 

 Mizoram

70,978 

2.82 

 Nagaland

38 

26,081 

145.7 

 Puducherry

21,211 

4.71 

 Punjab

5,487 

12,54,169 

437.5 

 Tripura

1,53,276 

0.65 

 Uttarakhand

128 

5,14,352 

24.89 

 Uttar Pradesh

1,518 

13,49,749 

112.47 

 Total

22,874 

1,85,88,772 

1,929 

 Source: Ministry of Health and Family Welfare Press Release, February 4, 2022, Available  from: https://pib.gov.in/PressReleasePage.aspx?PRID=1795419 Cited on May 12, 2022.
 State-wise total claims metrics as of June 30, 2022. Available from: PM-JAY Public  Dashboard
 (Excludes the states of Delhi, Telangana, Odisha and West Bengal as the PM-JAY scheme  has not been implemented in these states. Data from Maharashtra, Karnataka, Rajasthan,  Goa, Tamil Nadu and Andhra Pradesh were not available.)

Based on the analysis, the following types of unethical practices committed by providers under government-funded health insurance schemes were identified:

Performing medically harmful procedures

It was found that under the government-funded health insurance schemes in Rajasthan, Bihar, Andhra Pradesh and Chhattisgarh, private hospitals were performing hysterectomies (removal of the uterus) without any medical indication [18]. A study in Andhra Pradesh found that 87% of the hysterectomies performed under the Aarogyashree scheme in the state had no medical indication [20]. In Bihar, over 16,000 such surgeries were found to have been performed without being medically necessary [24]. In most cases, providers were found to have lied to the patient that she would die or become disabled unless she underwent the procedure. This malpractice not only led to undue financial losses for the scheme, but also harmed the patient’s health — several studies have established that hysterectomies increase women’s risk of cardiac diseases and certain cancers as a result of early menopause [25].

Ghost billing

Across states such as Punjab, Karnataka, Chhattisgarh and UP, several cases of fake transactions were detected under PM-JAY, wherein providers submitted fake bills in the name of patients without providing any service. This was particularly seen in the case of daycare packages such as cataract surgeries, since the patient can be shown to be discharged on the same day. Conducting a medical audit in such cases would be difficult since a medical audit may only be possible on the day following the treatment, by when the beneficiary is not present at the hospital, making it difficult to ascertain the treatment provided [19, 26, 27].

Upcoding

In this case, providers submitted inflated claims indicating that higher-priced packages were provided instead of the procedures that were actually performed. In Rajasthan, widespread instances of fraud were found under the Bhamashah scheme, particularly of unnecessary ICU care, which is priced at more than three times the charges for the general ward [28]. Similarly, in Karnataka, cases of upcoding in surgeries, combining various procedures instead of just the package performed, were detected. For example, a claim would be made for the “adhesiolysis ovarian cystectomy” package which costs Rs 15,000 instead of the “ovarian cystectomy” package (costing Rs 8,000) which had actually been performed [29]. It was also found that a few hospitals were submitting hundreds of claims for admission under Covid-19 [30]. These cases included cases of ordinary fever and common cold for which outpatient treatment could have been given. Since these hospitals had in-house testing facilities, they were able to manipulate the reports to show that the infection was present [30]. At the same time, it was difficult to physically audit these cases at the hospital to verify the medical necessity, as investigating officials would be at risk of infection. The number of Covid-19 admissions per 1,000 admissions under PM-JAY is given in Table 3. It shows that in the financial years 2020-22, Maharashtra had the highest percentage of Covid-19 claims, which may be indicative of this overuse.

Table 3: State-wise Covid-19 claims normalised

State/UT

Covid Treatments under PM-JAY from FY 2020-22

Total Claims submitted

Covid claims per 1,000 admissions

 Andaman & Nicobar Islands

1535 

4.56 

 Andhra Pradesh

213426 

2576139 

82.85 

 Assam

1080 

449964 

2.40 

 Bihar

27 

422765 

0.06 

 Chandigarh

20167 

0.40 

 Chhattisgarh

44940 

2588661 

17.36 

 Goa

10488 

0.10 

 Haryana

808 

490767 

1.65 

 Himachal Pradesh

56 

149949 

0.37 

 Jammu and Kashmir

837 

496108 

1.69 

 Jharkhand

1554 

1228434 

1.27 

 Karnataka

186031 

3046409 

61.07 

 Kerala

139895 

4129931 

33.87 

 Madhya Pradesh

19115 

1739027 

10.99 

 Maharashtra

174173 

579944 

300.33 

 Manipur

788 

64436 

12.23 

 Meghalaya

4261 

447381 

9.52 

 Mizoram

651 

70978 

9.17 

 Nagaland

11 

26081 

0.42 

 Puducherry

360 

21211 

16.97 

 Sikkim

38 

7369 

5.16 

 Tamil Nadu

30547 

7359704 

4.15 

 Tripura

56 

153276 

0.37 

 Uttar Pradesh

2043 

1349749 

1.51 

 Uttarakhand

2996 

514352 

5.82 

 Source: Ministry of Health and Family Welfare Press Release, February 4, 2022: Available from:  https://pib.gov.in/PressReleasePage.aspx?PRID=1795419 on May 12, 2022.
 State-wise total claims submitted as of June 30, 2022. Available from: PM-JAY Public  Dashboard
 (Excludes the states of Delhi, Telangana, Odisha and West Bengal as the PM-JAY scheme has  not been implemented in these states.)

Unnecessary extension of hospital stays or ICU admission

In this case, hospitals would extend patients’ stay even if not required, or keep patients in the ICU till their discharge, when they should have been given step-down treatment in the general ward [31, 32].

Creating cards for non-beneficiaries

The list of families eligible for PM-JAY comes from the Socioeconomic and Caste Census database which was developed in 2011. PM-JAY permits hospitals to create cards for new beneficiaries in a family due to birth, marriage, adoption etc, after verification of identification documents. This facility was misused by hospitals to add non-eligible beneficiaries to families eligible under PM-JAY [33]. This was detected in several states such as Uttar Pradesh, Madhya Pradesh and Kerala. In Uttar Pradesh, 49 hospitals created more than 1,400 Ayushman cards adding the names of ineligible persons posing as family members of eligible Ayushman Bharat families [34]. The hospitals colluded with the local Pradhan Mantri Arogya Mitra and ineligible persons who provided fake documents, by adding their names to the beneficiaries’ original ration cards. These cards were then utilised to avail of care in the same hospital. One hospital in Chhattisgarh added eight unrelated pregnant women to the card of a single eligible family [27]. In another case, a hospital in Jammu and Kashmir linked several ineligible patients to the same beneficiary family to perform laparoscopic cholecystectomy (removal of gall stones) [27]. In Gujarat, common service centres (CSCs) ― which deliver Government of India e-services to rural and remote locations and are responsible for enrolling beneficiaries under PM-JAY― were also found to be creating cards for non-beneficiaries [35]. As the benefit is limited to Rs 5 lakh per family, fraudulent use of the card affects genuine beneficiaries when they need healthcare, as they may find the amount available is reduced or exhausted. They may be forced into out-of-pocket expenditure to receive care, or have to forego the treatment. As many as 16,755 Pradhan Mantri Arogya Mitra (PMAM)/ CSC IDs were deactivated for issuing cards to the non-eligible, as of August 2021 [23].

False or ghost referrals for kickbacks

Public hospital physicians were found to be engaging in fraudulent practices. In several hospitals of Jharkhand and Uttarakhand, public hospital doctors who also had private practices, referred patients from the government facility to their own private practice, though the procedure could have been done in the government facility itself [36, 37]. Further, in Uttarakhand, cases of false referrals were detected. PHCs in Uttarakhand referred patients to private hospitals though they could have been treated at the PHC itself. The audit found the handwriting on the medical notes of the private hospital and on the public hospital referral forms to be identical. Audits revealed that the pharmacist of the public facility had colluded with the treating doctor of the private hospital and was giving false referrals to the hospitals in exchange for kickbacks [38].

Private hospitals providing treatment under government-reserved packages claiming “emergency” or other package category

Under various government-funded health insurance schemes, certain high-risk packages are reserved for public hospitals. These may be conducted by private hospitals only with a referral from the public hospital, or in emergency cases. However, it was found that private hospitals were submitting claims for packages such as cataract surgery — a planned procedure — as emergency procedures [39].

Dual practice by government doctors and self-referrals

Doctors were found to be serving at both a public hospital and a private hospital, with an overlap in working hours [36], indicating absence from their public hospital duties.

Collusion between provider and beneficiary

Instances of collusion between beneficiary and hospital were also observed. Given that beneficiaries of the scheme are poor, they may be lured to allow their card to be booked for expensive treatments in exchange for bribes or other benefits by the hospital. In one instance in Uttarakhand, a patient had been admitted for an emergency hip replacement surgery but when the audit team visited the hospital, the patient had not been admitted to the hospital at the scheduled time of the surgery. The patient was then called by the hospital and it was apparent during the medical investigation that there had been no need for a hip replacement in this case. By booking the patient as an “emergency” case, the hospital had obviated the need for a referral from a public hospital which may have found the hip replacement unnecessary. On further investigation, the patient, a beneficiary under outdated census data, was himself found to be a dealer of medical instruments used in hip transplants, which raised more suspicion of collusion between the provider and beneficiary [39].

Overuse of implants

One study found that cardiac stents were being implanted in heart patients in India without any medical need [40].

Providing poor quality care

Instances of poor-quality care being provided to patients were also observed. Cases were found wherein patients were not given the required treatment but only given partial treatment and discharged early [41].

Treatment by unqualified medical personnel

In several cases, medical treatment was performed by unqualified medical personnel. A WHO report in 2016 found that, of those claiming to be modern medicine doctors in India in 2001, a third were educated only until secondary school and 57% did not possess medical qualifications. In rural areas, just 18.8% of doctors practising modern medicine were found to be qualified to do so [42]. In one case, it was found that an unqualified doctor had performed more than 1,000 surgeries over a period of three years [43].

Hospitals getting empanelled without requisite infrastructure and medical personnel

It was found that some hospitals provided incorrect information on their accreditation status and size, as these were linked to higher incentives. Incorrect information on the size of the hospital, size of the ICU, accreditation status, presence of specialists, and pathologists were also detected [41, 44].

Demanding additional payments from patients for services already covered in package

The PM-JAY package covers all costs associated with the treatment — diagnostics, medical and surgical treatment, and medicines. Hospitals demanded additional payments from patients, over and above the PM-JAY rates or denied their treatment by misinforming them that certain services were not covered in the package [26, 45].

Collusion with insurance companies for approvals

Cases of collusion between hospitals and the insurance company were also discovered. In Punjab, an insurance company approved fake claims of several private hospitals in Jalandhar and Hoshiarpur, while denying genuine claims made by public hospitals. The insurance firm also rejected approximately 1,015 claims of 35 government hospitals, amounting to Rs 52 lakhs [46].

Overuse or incorrect use of procedure leading to patient’s death

In one case in Karnataka, the mortality audit committee found that the patient’s death could have been prevented if the hospital had not performed a second cycle of chemotherapy. The patient in this case had died due to overuse of the procedure [47].

Defining the Unethical Medical Practices Typology Framework

Based on the data analysis, we list the following types of fraud which can occur in PM-JAY, according to the entities and the stage of occurrence. We summarise the various types of fraud by proposing the “Unethical Medical Practices Typology Framework” (Table 4). The framework defines 7 key typologies of unethical practices: abuse, collusion, corruption, fraud, identity theft, patient harm and waste. Each of these can be further analysed as per the stage of the treatment/claim cycle where they may be committed — from card generation to pre-authorisation, claims referral, claims submission and its adjudication.

In addition to the previously documented typologies of fraud in the existing literature, we identified the following types of fraud in the context of India:

    1. ID theft: Under public healthcare schemes, since the PMAM is involved in card creation, it is possible to create cards for non-beneficiaries by misusing genuine beneficiary information.

    2. Collusion between beneficiary and provider to allow for submission of fake claims on the card.

    3. Self-referrals: Referrals by public hospital doctors to their private practices.

    4. Patient harm: Uneducated poor beneficiaries of the scheme are fooled by private providers into undergoing inappropriate and harmful treatment.

    5. Private hospitals perform treatments reserved for public hospitals and include them under approved treatments.

Given the lack of strict healthcare regulation and legal provisions to deal with these unethical practices, it is difficult to ensure that such frauds are adequately punished.

Table 4: The Unethical Medical Practices Typology Framework

Typology of Unethical Practice

Stage of treatment/ claim cycle

Entity Committing Malpractice

Type of Entity

Unethical Practice

 Abuse (Rule  Bending)  Pre-Authorisation  Submission  Provider  Private Provider  Denial of care for specialities which are  Dpresent in hospital
 Referral  Public Provider  Referrals to provider’s own private practice
 Collusion  Card Creation  Provider,  Beneficiary and  Non-Beneficiary  Private Provider and  Beneficiary  Collusion with beneficiary to use their card to  book high value packages in exchange for  bribes
 Referral  Provider  Public and Private  Provider  Fee splitting- referrals for kickbacks
 Public and Private  Provider  Fake referrals made by PHC to private  hospitals for non-existent patients in  exchange for bribes
 Claim Adjudication  Provider, TPA  Private Provider  Kickbacks to get approval for claims which  are unauthorised
 Denial of genuine claims from hospitals  which did not pay bribes
 Corruption  Claim Submission  Provider  Public Provider  Absenteeism but not reporting the same
 Private  or Public  Providers  Demanding money from patients to provide  services which are already covered
  Fraud  Empanelment  rovider  Private Provider  Submitting false information pertaining to   facilities/medical personnel to get  empanelled
 Pre-Authorisation  Submission  Provider  Private Providers  Ghost billing- submitting claims without  performing any service
 Claim Submission  Provider  Upcoding- charging for higher value service
 Extending the Length of Stay in case of  medical packages/ extending stay in ICU
 Unbundling- charging for a service already  covered in the package
 Performing a package reserved for public  hospitals and masking them under a different  package name
 Identity Theft  Card Creation  Provider and  Non-beneficiary  Private Provider  Creating fake cards for a non-beneficiary  using a true beneficiary’s identity without  their knowledge
 Patient Harm  including  patient  mortality  Pre-authorisation  submission  Provider  Private Provider  Performing medically inappropriate  procedures, overuse of implants, overuse of  procedures
 Claim submission  Poor Quality of Care such as Early discharge,  using cheap quality implants
 Performing treatment without having the  mandatory medical qualifications, using  name of more qualified doctor
 Waste  Pre-authorisation  submission  Provider  Private Provider  Performing medically unnecessary  investigations
 Claims submission  Performing medically unnecessary  procedures or implants not required
 Using high end drugs / branded consumables  when the treatment could be managed with  generics
 Source: Author

Discussion

In order to control healthcare fraud, government authorities must be vigilant and aware of the different types of fraud which can occur under public-funded schemes. The existing anti-fraud guidelines of PM-JAY contain several anti-fraud practices. These include setting up of institutional structures such as the National Anti-Fraud Unit and State Anti-Fraud Units, regular analysis of claims data to identify suspicious patterns, medical audit of claims to check their authenticity and identify any abuse and levying penalties, and taking disciplinary action when fraud and abuse are detected.

To address the challenge of limited availability of specialist doctors at remote locations, leveraging mobile apps with video conferencing facilities for medical audit will enable better control of fraud/ abuse. In order to avoid private hospitals booking procedures which are reserved for public hospitals except in emergencies, the IT system must be enabled to monitor emergency bookings in private hospitals. To prevent unnecessary and inappropriate procedures which may cause patient harm, pre-authorisation applications must verify the medical necessity of each procedure, and request appropriate investigations, etc. Identity documents must be checked properly before beneficiary cards are issued. The use of a biometrics-based identification system at the point of care would help prevent cases of ID theft. An electronic health records-based system would allow for automated scanning of electronic documents, to help reduce upcoding and medically unnecessary procedures. This has been envisaged to be part of the recently launched Ayushman Bharat Digital Mission (ABDM) which creates a unique health record for each beneficiary [48]. In order to ensure maximum enrolment, awareness must be generated of the ABDM and its benefits for citizens, such as easy online access to all medical investigations, and clinical history. It would also be beneficial to make use of telemedicine, providing patients online consultations with a physician or surgeon from a public hospital who can then issue a prescription according to the medical indications. This process of prescription validation by a public hospital doctor should be made mandatory in case of organ removal procedures and major surgeries, which are more likely to be abused.

Further, specific legal provisions to deal with cases of violation of medical ethics and patients’ rights need to be defined in the context of public schemes. This is especially important in cases of fraud or inappropriate procedures, leading to the patient’s impairment or death. One example is unnecessary procedures for organ removal because they are covered by a government package. Most developed countries have legal provisions for this purpose [49, 50]. However, such laws are missing in India, and even the Clinical Establishments Act, 2010, has been adopted by only four states so far. In India, a national health insurance law is needed, with specific provisions for action against ethical violations. This was one of the recommendations of the NHA-IRDAI (Insurance Regulatory and Development Authority of India) Subcommittee, but is yet to be implemented [16].

In this study, various types of unethical medical practices prevalent in public healthcare schemes in India were discussed, and a typology framework was defined for their classification. This framework is more suitable to understand and analyse these practices in the context of India and other developing countries with similar healthcare systems. The recommendations provided would help ensure that unethical medical practices are prevented, detected and deterred more effectively and efficiently.

Acknowledgements: I would like to thank my guide, Dr Shiv D Gupta, Trustee Secretary, IIHMR University, Jaipur, and my co-guide, Dr Sudha Chandrashekhar, for their support in the completion of my PhD thesis, and for their guidance and direction during the preparation of this manuscript.

Conflict of interest and funding: The author has no conflict of interest nor funding to declare for this work.

Statement of similar work: None to be declared.

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