Study on prescription writing practices in a tertiary care teaching hospital, Mysore

Harshith N; Laksmi Nagesh; Kanakavalli K. Kundury; Sujay Mugaloremutt Jayadeva

doi:https://doi.org/10.26452/ijrps.v12i1.3911

Study on prescription writing practices in a tertiary care teaching hospital, Mysore

Harshith N ✉ ¹ , Laksmi Nagesh ¹ , Kanakavalli K. Kundury ¹ , Sujay Mugaloremutt Jayadeva ¹

1 Department of Health System Management Studies, JSSAHER Sri Shivarathreeshwara Nagara, Mysuru - 570 015, Karnataka, India, 8618423152

Abstract

Accurate Use of Prescription betters the well being of patients. It becomes very essential to study PrescriptionWriting practices. The main goal of the study was to study the Prescription writing Practices and to assess the gaps in Prescription Writing so that it would be beneficial to the Patients. The study was conducted attertiary care teaching hospital in Mysore for Period of 6 months. Data was collected by both Retrospective and Prospective ways, A total of 2825 prescriptions were randomly collected from out patients visiting the study site, and analyzed. Sixteen Criteria were analyzed pertaining to the Prescription writing Practices the most significant criteria for Clinical diagnosis, which is crucial for avoiding misdistribution of drug to patients was missing in majority of the prescriptions. Prescribers initials, Seal with MRC of the prescriber in 6 months data it was seen that most of criteria which is mandated by MCI (medical council of India) not being followed by physicians. The study recommends for Medical Practitioners to follow the MCI Protocol in order to avoid errors in Prescription.

Keywords

MCI (Medical Council of India), Prescription, MRC (Medical Reimbursement Claims), Clinical diagnosis, Prescribers, Medical Practitioners

Introduction

A prescription is a written order from the physician to pharmacist, which consists of drug’s name, dose, strength, and duration of use. Prescription should contain the prescriber name, address, contact number, and signature and also mention name, address, contact member, age, gender of patient, and also directions, instructions, and warnings for patients (Ramachandrudu, 2016)

Prescription is an authoritative report that contains point by point data in regards to modified pharmacological treatment structured by a Physician for a patient. It very well may be a document during medico-lawful Conditions (Sudheer, Prabhu, & Sridhar, 2015). It additionally fills in as a correspondence among Registered Medical Practitioner and drug specialists. Such a significant record ought to be composed cautiously. Be that as it may, it is exceptionally regular to see some missing subtleties or indistinct data in medicines composed by specialists (Shelat, 2015). Prescription Writing is educated for clinical understudies in their initial academic year alongside different subjects of pharmacology (Ather et al., 2013). Extraordinary accentuation is given to this subject by remembering it for functional assessment (Kumari, Haider, Kashyap, & Singh, 2014) (Prescription composition, analysis and amendment of solution) (Kumari et al., 2008). Notwithstanding such cautious preparing, adequate measures in solution composing are invisible (Prabhu, Sudheer, & Srinivasan, 2013). One of the significant reasons could be the patient–specialist proportion in the emergency clinics (Vijayakuma, Sathyavati, Subhashini, Grandhi, & Dhanaraju, 2011).

Table 1: Details of December

S. No	Variables	December
S. No	Variables	Yes	No
1	Date of prescription	100%	0%
2	OP Number	66%	34%
3	Name of the Patient	96%	4%
4	Age of the Patient	70%	30%
5	Sex	72%	28%
6	Clinical Diagnosis	2%	98%
7	Dosage Form Mentioned	0%	100%
8	Name of the DRUG is legible	93%	7%
9	Name of the DRUGS in CAPITAL letters	93%	7%
10	Dose of the DRUG is clear	100%	0%
11	UNITS of the dose is clear	99%	1%
12	FREQUENCY Of the dose is clear	0%	100%
13	DURATION of the THERAPY is mentioned	0%	100%
14	Instructions to take the DRUG mentioned (i.e. Before food of After Food)	94%	6%
15	Prescriber's initials	99%	1%
16	Seal with MRC of the prescriber	71%	29%

Table 2: Details of January

S. No	Variables	January
S. No	Variables	Yes	No
1	Date of prescription	98%	2%
2	OP Number	58%	42%
3	Name of the Patient	96%	4%
4	Age of the Patient	53%	47%
5	Sex	51%	49%
6	Clinical Diagnosis	8%	92%
7	Dosage Form Mentioned	99%	1%
8	Name of the DRUG is legible	96%	4%
9	Name of the DRUGS in CAPITAL letters	51%	49%
10	Dose of the DRUG is clear	74%	26%
11	UNITS of the dose is clear	61%	39%
12	FREQUENCY Of the dose is clear	96%	4%
13	DURATION of the THERAPY is mentioned	91%	9%
14	Instructions to take the DRUG mentioned (i.e. Before food of After Food)	97%	3%
15	Prescriber's initials	97%	3%
16	Seal with MRC of the prescriber	46%	54%

Table 3: Details of February

S. No	Variables	February
S. No	Variables	Yes	No
1	Date of prescription	99%	1%
2	OP Number	68%	32%
3	Name of the Patient	98%	2%
4	Age of the Patient	56%	44%
5	Sex	55%	45%
6	Clinical Diagnosis	0%	100%
7	Dosage Form Mentioned	99%	1%
8	Name of the DRUG is legible	99%	1%
9	Name of the DRUGS in CAPITAL letters	52%	48%
10	Dose of the DRUG is clear	90%	10%
11	UNITS of the dose is clear	82%	18%
12	FREQUENCY Of the dose is clear	99%	1%
13	DURATION of the THERAPY is mentioned	92%	8%
14	Instructions to take the DRUG mentioned (i.e. Before food of After Food)	27%	73%
15	Prescriber's initials	99%	1%
16	Seal with MRC of the prescriber	54%	46%

Table 4: Details of March

S. No	Variables	March
S. No	Variables	Yes	No
1	Date of prescription	96%	4%
2	OP Number	71%	29%
3	Name of the Patient	0%	100%
4	Age of the Patient	66%	34%
5	Sex	67%	33%
6	Clinical Diagnosis	0%	100%
7	Dosage Form Mentioned	2%	98%
8	Name of the DRUG is legible	96%	4%
9	Name of the DRUGS in CAPITAL letters	71%	29%
10	Dose of the DRUG is clear	77%	23%
11	UNITS of the dose is clear	73%	27%
12	FREQUENCY Of the dose is clear	91%	9%
13	DURATION of the THERAPY is mentioned	22%	78%
14	Instructions to take the DRUG mentioned (i.e. Before food of After Food)	13%	87%
15	Prescriber's initials	99%	1%
16	Seal with MRC of the prescriber	64%	36%

Table 5: Details of April

S. No	Variables	April
S. No	Variables	Yes	No
1	Date of prescription	93%	7%
2	OP Number	65%	35%
3	Name of the Patient	95%	5%
4	Age of the Patient	68%	32%
5	Sex	72%	28%
6	Clinical Diagnosis	2%	98%
7	Dosage Form Mentioned	72%	28%
8	Name of the DRUG is legible	88%	12%
9	Name of the DRUGS in CAPITAL letters	64%	36%
10	Dose of the DRUG is clear	52%	48
11	UNITS of the dose is clear	44%	56
12	FREQUENCY Of the dose is clear	71%	29
13	DURATION of the THERAPY is mentioned	29%	71
14	Instructions to take the DRUG mentioned (i.e. Before food of After Food)	5%	95
15	Prescriber's initials	71%	29
16	Seal with MRC of the prescriber	61%	39

Table 6: Details of May

S. No	Variables	May
S. No	Variables	Yes	No
1	Date of prescription	95%	5%
2	OP Number	67%	33%
3	Name of the Patient	97%	3%
4	Age of the Patient	68%	32%
5	Sex	85%	15%
6	Clinical Diagnosis	99%	1%
7	Dosage Form Mentioned	84%	16%
8	Name of the DRUG is legible	93%	7%
9	Name of the DRUGS in CAPITAL letters	66%	34%
10	Dose of the DRUG is clear	64%	36%
11	UNITS of the dose is clear	58%	42%
12	FREQUENCY Of the dose is clear	80%	20%
13	DURATION of the THERAPY is mentioned	33%	67%
14	Instructions to take the DRUG mentioned (i.e. Before food of After Food)	8%	92%
15	Prescriber's initials	83%	17%
16	Seal with MRC of the prescriber	62%	38%

Table 7: The Detailed Study of First 3 Months December-February months and were tabulated in Prescription Audit Data

S. No	Variables	Percentage(%)
		Dec		Jan		Feb
		Yes	No	Yes	No	Yes	No
1	Date of Prescription	100	0	98	2	99	1
2	OP Number	66	34	58	42	68	32
3	Name of the Patient	96	4	96	4	98	2
4	Age of the Patient	70	30	53	47	56	44
5	Sex	72	28	51	49	55	45
6	Clinical Diagnosis	2	98	8	92	0	100
7	Dosage Form Mentioned	0	100	99	1	99	1
8	Name of the DRUG is legible	93	7	96	4	99	1
9	Name of the DRUGS in CAPITAL letters	93	7	51	49	52	48
10	Dose of the DRUG is clear	100	0	74	26	90	10
11	UNITS of the dose is clear	99	1	61	39	82	18
12	FREQUENCY Of the dose is clear	0	100	96	4	99	1
13	DURATION of the THERAPY is mentioned	0	100	91	9	92	8
14	Instructions to take the DRUG mentioned (i.e. Before food of After Food)	94	6	97	3	27	73
15	Prescriber's initials	99	1	97	3	99	1
16	Seal with MRC of the prescriber	71	29	46	54	54	46

Table 8: The Detailed Study of Next 3 Months March-May months and were tabulated in Prescription Audit Data

S. No	Variables	Percentage(%)
		Mar		Apr		May
		Yes	No	Yes	No	Yes	No
1	Date of Prescription	96	4	93	7	95	5
2	OP Number	71	29	65	35	67	33
3	Name of the Patient	0	100	95	5	97	3
4	Age of the Patient	66	34	68	32	68	32
5	Sex	67	33	72	28	85	15
6	Clinical Diagnosis	0	100	2	98	99	1
7	Dosage Form Mentioned	2	98	72	28	84	16
8	Name of the DRUG is legible	96	4	88	12	93	7
9	Name of the DRUGS in CAPITAL letters	71	29	64	36	66	34
10	Dose of the DRUG is clear	77	23	52	48	64	36
11	UNITS of the dose is clear	73	27	44	56	58	42
12	FREQUENCY Of the dose is clear	91	9	71	29	80	20
13	DURATION of the THERAPY is mentioned	22	78	29	71	33	67
14	Instructions to take the DRUG mentioned (i.e. Before food of After Food)	13	87	5	95	8	92
15	Prescriber's initials	99	1	71	29	83	17
16	Seal with MRC of the prescriber	64	36	61	39	62	38

On occasion, a solitary specialist needs to treat several patients in medical clinic (Abdellah & Abdelrahman, 2012). This is especially clear in government medical clinics. So the explanation behind such sort of medicine composing might be credited to over-burden of patients thus specialists should not generally be censured (Seden et al., 2013)

Materials and Methods

Study Location;

The study was conducted at a tertiary care teaching hospital, Mysore. The hospital has state of art infrastructure with 37 speciality and super specialty services. Hospital also provides critical and emergency care services round the clock with 260 beds (Siddarth, Sgupat, & K, 2014).

Study area

The study was conducted at the outpatient pharmacy department.

Study period

Study was conducted for a period of 6 months from December-May 2019.

Data collection methods:

Data was collected for the study in 2 ways,

1. Retrospective

2. Prospective

Retrospective data:

Retrospective data were collected from clinical pharmacy department of the hospital (Nehru et al., 2005).

Prospective data:

Prescription was collected irrespective of diagnosis, age, gender, etc across various departments of the hospital (Ruwan, Prasad, & Ranasinghe, 2009).we took photographs of the prescription using digital camera. A total of 2825 prescriptions were randomly collected from out patients visiting the study site, and analysed (Potharaju & Kabra, 2011).

Results and Discussion

The study was carried out for the duration of 6 months and were tabulated in Prescription Audit Data Table

December

A sum of 442 Prescriptions were arbitrarily gathered from out patients visiting the examination site, and investigated. All solutions apparently had some missing/indistinct data Missing data about patient and prescription was regularly found in this examination detail Result are Presented in Table 1

January

A sum of 535 Prescriptions was arbitrarily gathered from out patients visiting the examination site, and investigated. All solutions supposedly had some missing/indistinct data. Missing data about patient and drugs was ordinarily found in this investigation. Detail Result are Presented in Table 2

February

A sum of 557 prescriptions was arbitrarily gathered from out patients visiting the investigation site, and dissected. All remedies apparently had some missing/indistinct data. Missing data about patients and drugs was ordinarily found in this investigation. Detail Result are Presented in Table 3

March

An aggregate of 370 solutions was arbitrarily gathered from out patients visiting the investigation site, and broke down. All solutions supposedly had some missing/hazy data. Missing data about patients and prescriptions was regularly found in this investigation. Detail Result are Presented in Table 4

April

A sum of 421 remedies was arbitrarily gathered from out patients visiting the examination site, and dissected. All remedies apparently had some missing/indistinct data. Missing data about patients and prescriptions was ordinarily found in this investigation. Detail Result are Presented in Table 5

May

A sum of 500 prescriptions was arbitrarily gathered from out patients visiting the examination site, and Analyzed. Every remedies supposedly had some missing/hazy data. Missing data about patients and medicine was normally found in this investigation. Detail Result are Presented in Table 6

December-May

A total of 2825 prescriptions were randomly collected from out patients visiting the study site and analysed during this Six Months Period. All remedies apparently had some missing/indistinct data. Missing data about patients and prescriptions was ordinarily found in this investigation. Detail Result are Presented in Table 8; Table 7 respectively.

Conclusions

The study highlights that most of the critical factors, which is mandated by MCI (medical council of India) are not being followed by doctors during prescription writing. Further, nearly 99 % were clinical diagnosis less prescribers did not mention the frequency of dose, instruction to take the drug, and seal with the MRC of the prescribers, which may lead to adverse drug reaction or mis-distribution of drugs. To sum up, it is highly advisable for the prescribers to follow MCI standard protocol, so as to avoid undesirable outcomes in near future.

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