A quantitative study on completeness rate of documentation in psychiatric medical records.

Background: Mental disorders are one of the leading causes of illness and disability worldwide. According to the World Health Organization (WHO), one in four people in the world will be affected by mental or neurological disorders during their lifetime. Regular evaluation of mental health outcomes plays an important role in making decisions about timely treatment of the patient. Studies show that a medical record does not provide enough information about the diagnosis, current symptoms, psychiatric medications, and side effects of current medications and treatments for ongoing health care. In this study, the completeness of paper-based psychiatric records was investigated. Aim: The current study aimed to explore the completeness rate of paper-based psychiatric medical records (PMRs) and to investigate the factors effective on documentation status. Setting: The study was conducted in Ebnesina and Dr. Hejazi Psychiatric Hospital and Education Center. The case hospital is a psychiatric teaching hospital, which has 900 beds. Materials and
Methods: The completeness rate of PMRs was determined using descriptive statistics. Fleiss' Kappa agreement and effective factors on PMRs' documentation status were assessed.
Results: In total, 83.65% (n = 312) of the PMRs had at least one documentation defect. A significantly higher level of documentation completeness rate between different psychiatric wards was observed.
Conclusion: Based on our results, it is suggested to conduct regular evaluation and provide feedback to the health-care providers, and conduct training courses. Copyright:

INTRODUCTION

According to the World Health Organization (WHO) report, one in four people in the world will be affected by mental or neurological disorders during their lives. Around 450 million people suffer from mental disorders. Mental disorders are one of the most important leading causes of disease and disability worldwide.[1] The prevalence of psychiatric disorders was estimated at 22.31% in 2015.[2] Mental health outcomes need to be assessed routinely Mental health outcomes need to be assessed routinely and a feedback return to the physician. Theses outcomes can use to make joint treatment decisions with the patient that lead to better quality of life.[3] As well, the treatment process of mental disorders requires frequent outpatient and inpatient visits to health-care organizations. A complete medical record provides insufficient information related to the diagnosis, current symptoms, psychiatric medications and drug side effects, and current treatment for continuous health care.[4] The current study aimed to explore the completeness rate of paper-based psychiatric records and to investigate effective factors on the documentation status in a large teaching hospital.

MATERIALS AND METHODS

The current study was a retrospective, descriptive study that conducted in 2019–2020.

Study Setting and Participants

The study was conducted in Ebnesina and Dr. Hejazi Psychiatric Hospital and Education Center. The case hospital is a psychiatric teaching hospital, which has 900 beds. The hospital is one of the largest psychiatric hospitals in the country. Patients from five neighboring states are referred to this case hospital for professional psychological services. The case hospital has the separate clinical wards based on gender for children (3-18 years old), adults (19-60 years old), and elderly (over 61 years). The hospital uses mixed medical records (paper and electronic). Some data elements of the medical records are registered in electronic medical record and then printed by users. The rest of the data elements are registered in the printed form. Therefore, a paper-based psychiatric medical record (PMR) encompasses both non-electronic and electronic information.

Instrument

A checklist was developed based on the instructions of the Ministry of Health that were related to evaluate the completeness rate of documentation. The checklist covered all data elements in paper-based PMRs and comprised 10 sections according to PMR forms, including summary of admission and discharge, summary of psychiatric records, psychiatric history and assessment, progress note, consultation, physician orders, nursing report, vital signs control, laboratory tests, and electroencephalogram (EEG) report. Each section encompasses several data elements.

Verification of the content validity was carried out by an expert panel. The panel consisted of seven experts including medical informatics, a psychiatrist, and health information management. Expert validity was measured using a content validity index (CVI) and content validity ratio (CVR). The instrument was validated by an expert panel with CVI 0.85 and CVR 0.86.

The final version of the instrument encompassed 10 sections and 47 items on a two-scale range 0–1 (0: does not have documentation defect, 1: has documentation defect) [Table 1].

Table 1

PMR evaluation checklist

PMR forms	Row	Items of PMR forms	Defect status
Summary of admission and discharge (n=9)	1	Date and hour of discharge	Yes	No
	2	Patient hospitalization days	Yes	No
	3	Admission agent signature	Yes	No
	4	Number of consultations	Yes	No
	5	Date and time of patient transfer	Yes	No
	6	Attending physician signature	Yes	No
	7	Head nurse signature	Yes	No
	8	Date and time of patient transfer	Yes	No
	9	Primary and main diagnosis	Yes	No
Summary of psychiatric records (n=5)	10	Sociodemographic information	Yes	No
	11	Admission and discharge date	Yes	No
	12	Chief complaint/main findings/diagnosis	Yes	No
	13	Attending physician signature	Yes	No
	14	Laboratory and imaging tests	Yes	No
Psychiatric history and assessment (n=4)	15	Sociodemographic information	Yes	No
	16	Psychiatric history	Yes	No
	17	Resident signature	Yes	No
	18	Attending physician signature	Yes	No
	19	Psychiatric assessment	Yes	No
Progress note (n=4)	20	Sociodemographic information	Yes	No
	21	Daily progress of treatment	Yes	No
	22	Resident signature	Yes	No
	23	Attending physician signature	Yes	No
Consultation (n=7)	24	Sociodemographic information	Yes	No
	25	Date and hour of consultation request	Yes	No
	26	Primary diagnosis	Yes	No
	27	Consultation priority	Yes	No
	28	Consultation type	Yes	No
	29	Description of consultation request	Yes	No
	30	Description consultation response	Yes	No
Physician orders (n=6)	31	Sociodemographic information	Yes	No
	32	Date and hour of physician orders	Yes	No
	33	Physician orders	Yes	No
	34	Resident signature	Yes	No
	35	Nurse signature	Yes	No
	36	Attending physician signature	Yes	No
Nursing report (n=4)	37	Sociodemographic information	Yes	No
	38	Existence of nursing report in each shift	Yes	No
	39	Nurse signature	Yes	No
	40	Data and time of writing nursing report in each shift	Yes	No
Vital signs control (n=3)	41	Sociodemographic information	Yes	No
	42	Vital signs control in each shift	Yes	No
	43	Nurse signature	Yes	No
Laboratory tests (n=2)	44	Sociodemographic information	Yes	No
	45	Print of laboratory tests	Yes	No
EEG report (n=2)	46	Sociodemographic information	Yes	No
	47	Print of EEG	Yes	No

EEG = electroencephalogram, PMR = psychiatric medical record

Sample Size

The total number of discharged patients from the case hospital during the study was 6002 (from March 2019 to March 2020). According to Morgan’s table, the least sample size (n = 361) was determined. Thesamples were chosen completely at random. Theentire of population paper-based PMRs were available for sampling. A list of the entire population was extracted from the hospital information system (HIS). Stratified random sampling was conducted based on the discharge month and clinical wards using a table of random numbers.

Data Collection

The completeness rate of documentation for sampled paper-based PMRs was evaluated according to the checklist by three trained staff independently. An incomplete data element was considered as a “documentation defect” when at least two of the experts were in agreement. As mentioned before, the checklist had 10 sections according to PMR forms. The frequency of “documentation defects (incomplete data elements)” and “complete data elements” for each form was determined. All the completed checklists by the experts were recorded in an Excel file.

Analysis and Statistics

The characteristics of psychiatric patients and the completeness rate of documentation in sampled paper-based PMRs were determined by descriptive statistics. Fleiss’ Kappa agreement was computed to describe the level of data agreement among three PMR evaluators for each item of PMRs.[5] The mean and standard deviation of kappa in each form were calculated.

Effective factors on the completeness rate of documentation were assessed by Chi-square test. The relationships between the documentation status of each form as the dependent variable and “psychiatric wards characteristics,” “discharge shift,” and “discharge status” were investigated. Statistical significance for all the analyses was defined as P ≤ 0.05.

Psychiatric wards’ characteristics encompassed three variables as follows:

Psychiatric wards based on gender: Patients hospitalized in the psychiatric wards based on age group and gender. Therefore, psychiatric wards based on gender were categorized into two groups, that is, male and female.

Psychiatric wards based on age groups: The psychiatric wards had different age groups of patients (≤18 years old grouped as “children,” 19–59 years old as “adults,” 60 years and above as “elderly”). In the Chi-square test, these groups were used.

Psychiatric wards’ educational status: The psychiatric wards’ educational status was categorized into two groups, that is, educational and non-educational.

Ethical Considerations

The data of the current study was gathered in the research project approved by the Vice-Chancellery for research of Mashhad University of Medical Sciences (grant number 980794, IR.MUMS.MEDICAL.REC.1398.624).

RESULTS

Patients’ Characteristics

Among the patients, 68.3% (n = 256) were males and 31.2% (n = 117) were females. The referral type of most of the patients (87.5%) was “non-emergency.” Only 12% of the patients were referred by emergency services.

Majority of the patients (n = 109, 29.1%) were 31–40 years old. The next highest number of cases (n = 79, 21%) were 31–40 years old.

Most of the patients had “health service insurance” (n = 247, 65.9%). The insurance organizations of “social security” (n = 71, 18.9%) and “armed forces” (n = 30, 8%) were ranked second and third, respectively. Among cases, 76% of patients had been discharged with a doctor’s order and 20% of them had been discharged against the physician’s order [Table 2].

Table 2

Patients’ characteristics

PMR characteristics	Subgroups	Frequency (%)
Sex	Male	117 (31.2)
	Female	256 (68.3)
Age (years)	<20	30 (7.9)
	20-30	77 (2.7)
	31-40	109 (29.1)
	41-50	79 (21)
	>50	78 (20.9)
Type of referral	Nonemergency	328 (87.5)
	Emergency	45 (12)
Insurance	Social security	71 (18.9)
	Health service	247 (65.9)
	Armed forces	30 (8)
	No insurance	25 (6.7)
Discharge status	Discharge with physician’s order	285 (76)
	Discharge against physician’s order	75 (20)
	Patient escape	5 (1.3)
	Death	1 (0.3)
	Follow-up	7 (1.9)

PMR = psychiatric medical record

Kappa of Documentation Defects

The mean of kappa value in the summary of admission and discharge was almost perfect. Documentation defects in three forms included “consultation,” “laboratory tests,” and “vital signs control” was moderate. In “summary of psychiatric records,” “psychiatric history and assessment,” and “nursing reports,” the mean of kappa value was fair. “Progress note” and “physician orders” had a slight mean kappa agreement value. “EEG report” was the only form that had poor mean kappa agreement. Table 3 shows the average agreement of completeness rate of documentation in PMRs. Out of 47 items in PMR forms, the kappa value of 37 items was significant and in 10 items, the agreement was not significant [Table 3].

Table 3

Kappa of completeness rate of documentation in PMRs (n=373)

PMR forms	Items of PMR forms	Agreement status	Kappa value	Standard error	Z	Sig.	Lower bound	Upper Bound
Summary of admission and discharge	Date and hour of discharge	Fair	0.274	0.052	5.297	0.000	0.270	0.277
	Patient hospitalization days	Fair	0.274	0.052	5.297	0	0.27	0.277
	Admission agent signature	Substantial	0.629	0.052	12.181	0	0.626	0.632
	Number of consultations	Slight	0.091	0.052	1.772	0.076	0.088	0.095
	Date and time of patient transfer	Poor	−0.012	0.052	−0.235	0.814	−0.015	−0.009
	Attending physician signature	Moderate	0.418	0.052	8.089	0	0.414	0.421
	Head nurse signature	Poor	−0.001	0.052	−0.026	0.979	−0.005	0.002
	Date and time of patient transfer	Fair	0.396	0.052	7.668	0	0.393	0.399
	Primary and main diagnosis	Substantial	0.665	0.052	12.884	0	0.662	0.669
	Mean of total items	Almost perfect	0.304	SD = ±0.25	-	-	-	-
Summary of psychiatric records	Sociodemographic information	Slight	0.082	14:52.8	1.588	0.112	0.079	0.085
	Admission and discharge date	Substantial	0.661	14:52.8	12.805	0	0.658	0.664
	Chief complaint/main findings/diagnosis	Fair	0.396	14:52.8	7.668	0	0.393	0.399
	Attending physician signature	Moderate	0.42	0.052	8.132	0	0.417	0.423
	Laboratory and imaging tests	Moderate	0.42	0.052	8.132	0	0.417	0.423
	Mean of total items	Fair	0.396	SD = ±0.21	-	-	-	-
Psychiatric history and assessment form	Sociodemographic information	Slight	0.178	14:52.8	3.443	0.001	0.175	0.181
	Psychiatric history	Slight	0.141	14:52.8	2.729	0.006	0.138	0.144
	Resident signature	Poor	−0.003	14:52.8	−0.052	0.959	−0.006	0.001
	Attending physician signature	Slight	0.082	14:52.8	1.588	0.112	0.079	0.085
	Psychiatric assessment	Poor	−0.007	0.052	−0.13	0.897	−0.01	−0.003
	Mean of total items	Fair	0.078	SD = ±0.08	-	-	-	-
Progress note	Sociodemographic information	Slight	0.169	14:52.8	3.273	0.001	0.166	0.172
	Daily progress of treatment	Fair	0.213	14:52.8	4.12	0	0.21	0.216
	Resident signature	Fair	0.281	14:52.8	5.438	0	0.278	0.284
	Attending physician signature	Slight	0.169	0.052	3.273	0.001	0.166	0.172
	Mean of total items	Slight	0.208	SD = ±0.05	-	-	-	-
Consultation	Sociodemographic information	Slight	0.175	14:52.8	3.389	0.001	0.172	0.178
	Date and hour of consultation request	Moderate	0.543	14:52.8	10.515	0	0.54	0.546
	Primary diagnosis	Fair	0.364	14:52.8	7.057	0	0.361	0.368
	Consultation priority	Fair	0.242	14:52.8	4.685	0	0.239	0.245
	Consultation type	Substantial	0.665	14:52.8	12.884	0	0.662	0.669
	Description of consultation request	Substantial	0.799	0.052	15.466	0	0.795	0.802
	Description of consultation response	Slight	0.175	0.052	3.389	0.001	0.172	0.178
	Mean of total items	Moderate	0.423	SD = ±0.25	-	-	-	-
Physician orders	Sociodemographic information	Slight	0.112	14:52.8	2.174	0.03	0.109	0.116
	Date and hour of physician orders	Slight	0.069	14:52.8	1.343	0.179	0.066	0.073
	Physician orders	Slight	0.062	14:52.8	1.192	0.233	0.058	0.065
	Resident signature	Fair	0.375	14:52.8	7.262	0	0.372	0.378
	Nurse signature	Fair	0.235	0.052	4.547	0	0.232	0.238
	Attending physician signature	Slight	0.112	0.052	2.174	0.03	0.109	0.116
	Mean of total items	Slight	0.161	SD = ±0.12	-	-	-	-
Nursing report	Sociodemographic information	Slight	0.112	0.052	2.174	0.03	0.109	0.116
	Existence of nursing report in each shift	Slight	0.062	0.052	1.192	0.233	0.058	0.065
	Nurse signature	Moderate	0.539	0.052	10.432	0	0.535	0.542
	Data and time of writing nursing report in each shift	Substantial	0.79	0.052	15.302	0	0.787	0.793
	Mean of total items	Fair	0.376	SD = ±0.09	-	-	-	-
Vital signs control	Sociodemographic information	Moderate	0.561	14:52.8	10.859	0	0.558	0.564
	Vital signs control in each shift	Moderate	0.561	14:52.8	10.859	0	0.558	0.564
	Nurse signature	Moderate	0.561	14:52.8	10.859	0	0.558	0.564
	Mean of total items	Moderate	0.561	SD = ±0.00	-	-	-	-
Laboratory tests	Sociodemographic information	Fair	0.222	0.52	4.291	0	0.218	0.225
	Print of Laboratory tests	Fair	0.222	0.52	4.291	0	0.218	0.225
	Mean of total items	Moderate	0.222	SD = ±0	-	-	-	-
EEG report	Sociodemographic information	Poor	−0.019	0.052	−0.368	0.713	−0.022	−0.016
	Print of EEG	Poor	−0.019	0.052	−0.368	0.713	−0.022	−0.016
	Mean of total items	Poor	−0.019	SD = ±0.52	-	-	-	-

EEG=electroencephalogram, PMR=psychiatric medical record, SD=standard deviation Kappa interpretation: <0 poor agreement, 0.0-0.20 slight agreement, 0.21-0.40 fair agreement, 0.41-0.60 moderate agreement, 0.61-0.80 substantial agreement, 0.81-1.0 almost perfect agreement

Documentation Status of PMRs

Our results showed that in total, 83.65% (n = 312) of the PMRs had at least one documentation defect. There was no documentation defect in 16.7% (n = 61) of PMRs. The range of completeness rate in paper-based PMR sheets was from 7.7% (n = 29) to 49.87% (n = 186). “Admission and discharge” (n = 186, 49.87%), “nursing report” (n = 125, 48.26%), and “progress note” (n = 125, 33.51%) had the highest number of defects, respectively. “EEG report” (n = 29, 7.7%), “laboratory tests report” (n = 77, 20.64%), and “vital sign” (n = 44, 11.80%) had the lowest number of documentation defects, respectively. Table 4 shows the documentation status of PMRs [Table 4].

Table 4

Completeness rate of documentation in PMRs (n=373)

PMR forms	Number of defects	Frequency (%)
Summary of admission and discharge	0	187 (50.1)
	1	170 (45.6)
	≥2	16 (4.3)
Summary of psychiatric records	0	274 (73.5)
	1	53 (14.2)
	≥2	46 (12.3)
Psychiatric history and assessment form	0	252 (67.6)
	1	113 (30.3)
	≥2	8 (2.1)
Progress note	0	248 (66.5)
	1	101 (27.1)
	≥2	24 (6.4)
Consultation	0	233 (62.5)
	1	125 (33.5)
	≥2	15 (4)
Physician orders	0	293 (78.6)
	1	78 (20.9)
	≥2	2 (0.5)
Nursing report	0	193 (51.7)
	1	172 (46.1)
	≥2	8 (2.1)
Vital signs control	0	296 (79.4)
	1	0 (0)
	≥2	77 (20.6)
Laboratory tests	0	329 (88.2)
	1	44 (11.8)
	≥2	0 (0)
EEG report	0	344 (92.2)
	1	29 (7.8)
	≥2	0 (0)
Total PMRs	0	61 (16.4)
	1	36 (9.7)
	≥2	276 (73.9)

EEG=electroencephalogram, PMR=psychiatric medical record

Effective Factors on Completeness Rate of Documentation

In Table 5, a significantly higher level of completeness rate of documentation in “summary of admission and discharge,” “consultation,” “physician orders,” “nursing report,” “vital signs control,” and “laboratory tests” in psychiatric wards based on different age groups was observed. The results showed that the psychiatric wards with patients in the age group of ≤18 years compared to 19–59 years and 60 years and above had lower documentation defects.

Table 5

Effective factors on PMRs’ documentation status

Items PMR forms	Psychiatric wards’ characteristics			Discharge shift	Discharge month	Discharge status
	Patients’ gender	Patients’ age	Educational status
Summary of admission and discharge	0.003*	0.047*	0.281	0.372	0.675	0.454
Summary of psychiatric records	0.44	0.309	0.499	1	0.519	0.103
Psychiatric history and assessment	0.058	0.427	0.864	0.309	0.572	0.365
Progress note	0.108	0.092	0*	0.604	0.068	0.117
Consultation	0.802	0.004*	0.148	1	0.687	0.588
Physician orders	0.802	0.004*	0.148	1	0.687	0.588
Nursing report	0.802	0.004*	0.148	1	0.687	0.588
Vital signs control	0.802	0.004*	0.148	1	0.687	0.588
Laboratory tests	0.045*	0.023*	0.036*	1	0.213	0.424
EEG report	0.648	0.112	0.625	1	0.181	0.499
Total PMRs	0.387	0.831	0.086	1	0.371	0.343

*P-value in 95%. EEG=electroencephalogram, PMR=psychiatric medical record

Educational status of psychiatric wards had a significant relationship with the documentation status of “summary of admission and discharge” and “laboratory tests.”

Patients’ gender had a significant relationship with the completeness rate of documentation of “progress note” and “laboratory tests.” There was no significant difference between the completeness rate of documentation and discharge shift, discharge month, and discharge status [Table 5].

DISCUSSION

In the current study, an instrument was proposed to determine the completeness rate of PMRs. The instrument was found to have a high rate of validity and reliability. This can be applied to evaluate PMRs in future studies. An approach was used to rigorously evaluate the completeness rate of PMRs. As well, a method was applied to calculate the agreement of trained experts to evaluate the completeness of paper-based PMRs. This approach enables the researchers to compare various hospitals. The main findings of the study will be discussed in the following paragraphs.

First, in line with previous studies, the results of our study revealed that the overall completeness rate of PMRs was low. Most of the PMRs had at least one documentation defect. The results of a study by Mackin et al.[6] showed the same results. Mental disorders were poorly documented by health-care providers. The results of a study in the UK showed that the documentation status of 150 referral letters for new patients to psychiatric clinics was low and majority of the patient records (94%) had documentation defect in general conclusions.[7] The documentation evaluation status of 52 patients with cognitive disorders showed that 17% of the reviewed medical records had documentation defects.[6] Lotfnezhad et al.[8] believed that despite the significant development in mental health care over the past few decades, little attention has been paid to the documentation of mental health information. Seif Rabiee et al.[9] examined the documentation status of medical records. The results showed PMRs had undesirable documentation status.

The documentation defects were observed in other specialty. The results of Saranto and Kinnunen’s study indicated that patients’ information in medical records was relatively inaccurate and inadequate. As well, it was observed that many essential parts of the nursing care process were missing.[10] The results of a study by Müller-Staub et al.[11] revealed that there were some deficits in reporting of signs, symptoms, and etiology of the diseases in the nursing reports. They recommended that using staff educational measures is necessary to enhance diagnostic accuracy. Wang et al.[12] observed that the shortcomings included deficiencies in nursing documentation in medical records. As well, nursing care was not entirely expressed in the records. Therefore, written communication between different providers about patients was inadequate. Findings from a study by Kärkkäinen et al.[13] confirmed that the documentation of nursing care programs and patient involvement in defining diagnoses and treatment goals was inadequate in medical records.

There were some possible reasons for the high rate of documentation defects. Many psychiatry reports have lack of proper content.[14] There is no national documentation for mental health information that can meet the needs of this sector.[8] The completeness of treatment approaches related to inpatients with mental disorders in developing countries is not important to the insurance organizations.[15] Gajera et al.[16] believed that good medical records are an integral part of quality health care and institutions. Maintaining an adequate medical record in the prescribed format is not just for the gain of the practitioner, but also is mandated by the law. Any deviations from the standards of documentation can lead to harsh penalties.

Secondly, the results of the present study highlight the fact that there was a difference between documentation status in electronic heath record and paper-based PMRs. The case hospital is using dual documentation systems (paper and electronic). “EEG” and “laboratory tests” reports had a lower number of missing data compared to other forms. These forms were printed from the HIS. Fulfillment of the data elements of these reports in HIS is necessary. But “admission and discharge,” “nursing report,” and “progress note” had the highest number of missing data. For example, half of the data elements in the admission and discharge form were registered in HIS at the admission unit and the reset of data elements was fulfilled in the printed form. All data elements in nursing report and progress note were registered in paper forms. These results were consistent with what has been found in previous reports. The results of the study of Nguyen et al.[17] showed that the use of HIS was effective in improving the quality of documents. A similar conclusion was reached by Pourasghar et al.[18] They observed an improved documentation quality in medical records using HIS.

Thirdly, we found that the completeness of paper-based PMRs correlated with the characteristics of the psychiatry wards. As well, the agreement mean of completeness rate had different levels in the trained staff of the health information management unit. For example, this value for one form of paper-based PMRs was almost perfect and was moderate and fair in six forms. It seems the staff and health providers in the case hospital need an education course. The findings of Arzamani et al.’s[19] study revealed that the expertise and level of education had a positive effect on the completeness rate of medical records. Conducting an educational course is a key factor to improve the quality of documentation.[1619]

Fourthly, we found that the completeness of paper-based PMRs associated with the characteristics of the psychiatry wards. As well, the completeness rate had different levels in the trained staff of the health information management unit. For example, this value for one form of paper-based PMRs was almost perfect and was moderate and fair in six forms. It seems the staff and health providers in the case hospital need an education course. The findings of Arzamani et al.’s study revealed that the expertise and level of education had a positive effect on the completeness rate of medical records.[19] Conducting an educational course is a key factor to improve the quality of documentation.[1719]

Limitation

The information of psychiatric patients is very confidential. In the present study, data gathering was conducted by staff of the health information management unit in the case hospital, who were authorized to access the PMRs and were in charge of documentation evaluation of PMRs.

CONCLUSIONS

Our results showed that the majority of PMRs have documentation deficiencies. It is suggested that conducting regular evaluation and providing feedback to the health-care providers, conducting training courses, and developing punitive and incentive mechanisms are very necessary.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.