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Year : 2014  |  Volume : 46  |  Issue : 5  |  Page : 480--484

Assessment of quality of prescribing in patients of hypertension at primary and secondary health care facilities using the Prescription Quality Index (PQI) tool

Jalpa Vashishth Suthar1, Varsha J Patel2,  
1 Department of Pharmacology, Ramanbhai Patel College of Pharmacy, Charotar University of Science and Technology, CHARUSAT campus, Changa, Anand, Gujarat, India
2 Department of Pharmacology, Smt. Nathiba Hargovandas Lakhmichand Municipal Medical College, Ellisbridge, Ahmedabad, Gujarat, India

Correspondence Address:
Jalpa Vashishth Suthar
Department of Pharmacology, Ramanbhai Patel College of Pharmacy, Charotar University of Science and Technology, CHARUSAT campus, Changa, Anand, Gujarat


Objective: To determine the quality of prescribing in hypertension in primary and secondary health care settings using the Prescription Quality Index (PQI) tool and to assess the reliability of this tool. Materials and Methods: An observational cross-sectional study was carried out for 6 months in order to assess quality of prescribing of antihypertensive drugs using Prescription Quality Index (PQI) at four primary (PHC) and two secondary (SHC) health care facilities. Patients attending these facilities for at least 3 months were included. Complete medical history and prescriptions received were noted. Total and criteria wise PQI scores were derived for each prescription. Prescriptions were categorized as poor (score of ≤31), medium (score 32-33) and high quality (score 34-43) based on PQI total score. Psychometric analysis using factor analysis was carried out to assess reliability and validity. Results: Total 73 hypertensive patients were included. Mean age was 61.2 ± 11 years with 35 (48%) patients above 65 years of age. Total PQI score was 26 ± 11. There was a significant difference in PQI score between PHC and SHC (P < 0.05) Out of 73 prescriptions, 43 (59%) were of poor quality with PQI score <31. The value of Cronbach«SQ»s α for the entire 22 criteria of PQI was 0.71 suggesting good reliability of PQI tool in our setting. Conclusions: Based on PQI scores, quality of prescribing in hypertensive patients was poor, somewhat better in primary as compared to secondary health care facility. PQI is reliable for measuring prescribing quality in hypertension in Indian set up.

How to cite this article:
Suthar JV, Patel VJ. Assessment of quality of prescribing in patients of hypertension at primary and secondary health care facilities using the Prescription Quality Index (PQI) tool .Indian J Pharmacol 2014;46:480-484

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Suthar JV, Patel VJ. Assessment of quality of prescribing in patients of hypertension at primary and secondary health care facilities using the Prescription Quality Index (PQI) tool . Indian J Pharmacol [serial online] 2014 [cited 2022 May 21 ];46:480-484
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Prescriptions communicate medication plans from prescribers to pharmacists, and patients. A good prescription is rational, evidence based, clear, complete and improves the treatment outcome of the patient. While prescribing without an appropriate indication, correct dose, frequency, route of administration, schedule or duration of treatment and duplicate therapeutic agents and medication of potential drug-drug interactions or adverse reactions are all forms of inappropriate prescribing. [1]

Several tools have been developed to assess the quality of prescribing. These tools are based on expert judgment or consensus of practitioners [1],[2],[3],[4] without any information on the psychometric properties of the instruments. These tools measure of quality of care in general [5] or for specific disease, [4] in specific population, [6],[7] overall use, [8] specific areas of use, [9],[10] or specific drug or groups of drugs. [7],[11],[12]

An attempt to improve in prescribing practices begins with assessing all the aspects of prescription right from selection of the drug to complete prescribing instructions. Prescription Quality Index (PQI) developed by Hassan et al., in 2010 [1] contains 22 criteria in question form. The PQI has been claimed to be an ideal tool applicable to a broad variety of medications and clinical conditions and applicable in different settings and with limited data.

This study was conducted to determine the quality of prescribing in patients of hypertension at primary and secondary health care facilities in Gujarat state of India using the PQI tool [1] and to assess the reliability of this tool.

 Materials and Methods

This observational cross sectional study was carried out from April 2012 to September 2012- at four Primary Health Centers (PHC), two Secondary Health Centers (SHC), one Community Health Center and one Civil Hospital. Approval from the Institutional Human Ethics committee and permission of Chief Medical Officer (CMO) of different health centers were obtained. Each participant's informed consent was obtained before collecting his/her data and any relevant information.

Inclusion Criteria

Patients of all ages suffering from hypertension with or without co-morbidities and attending the outpatient department (OPD) of PHC and SHC for at least 3 months or more and willing to give consent were included in the study.

Data Collection and Evaluation for PQI Score

Data was collected for a period of four weeks (three days/week) at each facility.

Demographic and prescription details were recorded in case record form. Compliance was evaluated using patient's self report.

Calculating PQI scores by Prescription Quality Index Tool

The quality of prescription was assessed with 22 criteria- indication, dosage, effectiveness, evidence-base, correct and practical administration, drug-drug interaction, drug-disease interaction, adverse drug reaction, unnecessary duplication, duration of therapy, cost minimization, use of generic name, selection from hospital drug list, compliance, medication name, legibility, prescriber' name and information, patient information, diagnosis, requirement for drug therapy and patient's improvement. Each criterion carried a specific maximum score depending on its importance.

If the prescription consisted of more than one drug, each drug was rated individually. Similarly, if patients suffered from more than one disease state, each disease state was rated separately. The minimum score was then selected for the PQI summation. If a drug was not indicated, criterion 1 was scored as '0' (zero). Subsequently, criterion 2 (dosage), criterion 13 (duration) and criterion 14 (cost minimization) were all scored as '0'. The PQI total score was obtained by summing up all the minimum scores for the 22 criteria for all drugs in a prescription. The possible maximum score of the PQI was '43'. Prescription with the PQI total score of ≤31 was interpreted as poor quality, score 32-33 as medium quality and score 34-43 as high quality as described in PQI tool. [1]

To evaluate different items in the questionnaire standard references or publications were used. The primary references were PQI manual, pharmaceutical/pharmacological texts or credible medical journals or established online websites. Examples are A to Z Drug Facts, [13] USPDI, Evidence Based Medical Reviews (EBMR), Medline, PubMED, Martindale's Complete Drug Reference, [14] WHO essential drug list 2011, [15] National Formulary of India 2011 [16] and British National Formulary (BNF) 2011. [17] For the cost of the therapy current issues of commercial sources like Current Index of Medical Specialities (CIMS), [18] Monthly Index of Medical Specialities (MIMS) [19] and Indian Drug Review (IDR) [20] were reviewed. Hospital formularies were used if available.

Statistical Analyses

Data was analyzed using Statistical Package for Social Science version 20. Descriptive statistics were used to describe the samples. Mean and standard deviation (SD) were used to describe numerical and variables and frequency (%) was used for categorical variables. To check the normality of data Kolmogrov-Smimov test was applied. Non Parametric tests were applied due to skewed distribution of the data. To validate the PQI, internal consistency (reliability) was measured using item total correlation and Cronbach's α. These two properties reflect the extent to which items correlate with the total score and how well items measure the same construct. Correlation of criteria should be between 0.2 and 0.8. [1] Minimal effects (percentage of prescriptions with minimum possible score) and ceiling effects (percentage of prescriptions with maximum possible score) were also assessed. Factor analysis was performed to find out the reliability and validity of the PQI criteria. Factor analysis use more than one criteria Kaiser's criteria (eigenvalue >1 rule) and the Scree test were used to assess the construct validity of the tool [21] P < 0.05 was considered significant.


Characteristics of the Patients with Hypertension

A total of 73 patients received 73 prescriptions with 305 drugs. Mean age of patients was 61.2 ± 11 (range 40-84 years) with 30 (41%) male patients. Most (62%) of the prescriptions were from SHC and 28 (38%) were from PHC.

The number of drugs in the prescriptions ranged from one to nine with the mean value of 4.2 ± 1.96. The mean number of medical illnesses was 1.6 ± 0.62. The most common conditions were hypertension 26 (35%), followed by hypertension with diabetes mellitus 13 (17%), bronchial asthma 10 (13%) and other diseases 27 (36%) like Diabetes Mellitus, Joint disorders and Gastric problem [Table 1]. {Table 1}

Psychometric properties of the PQI in patient with hypertension

The mean PQI score was 26 ± 11. The PQI score can range from 0-43. There were three (4.1%) prescriptions with minimum score of 11, where as two (2.7%) prescriptions scored maximum 43, indicating the absence of floor effects. The total PQI scores were not normally distributed.

[Table 2] shows the PQI mean scores for each PQI criterion. As criterion 7, clinically significant drug-drug interactions was a constant value, it was neglected in the analysis. None of the 22 criteria were normally distributed. All showed skewed distribution as verified by using Kolmogrov-Smimov test (for all P < 0.001). {Table 2}

Exploratory principal components analysis of the PQI total scores revealed a six factor solution using the minimum Eigenvalue criteria of ≥1. These six accounted for 74.7% of the total variance [Figure 1]. Cronbach's α for the entire 22 criteria was 0.71.{Figure 1}

The total PQI score was weakly correlated with age (correlation coefficient r = 0.36, P = 0.002), negatively correlated with number of drugs in the prescriptions (correlation coefficient r = −0.49, P < 0.001) and not correlated with number of chronic diseases/conditions (correlation coefficient r = 0.10, P = 0.400).

Of the different PQI criteria, PQI total scores were strongly correlated with drug indication and drug effectiveness, evidence base, correct directions, unnecessary duplication, duration of therapy and cost [Table 3]. The other criteria like drug dosage, practical direction, drug- disease/condition interactions, generic prescribing, medication's name, requirement for drug therapy and patient's improvement showed moderate correlations. There was weak correlation between the PQI total scores and the remaining criteria. {Table 3}

[Table 4] depicts the PQI score and quality of prescribing. Out of 73 prescriptions 43 (59%) were of poor quality. The proportion to high and poor quality of prescription did not differ significantly between two facilities. (Chi square test, P = 0.11). However mean PQI score at PHC and SHC was 31.10 ± 8.76 and 22.73 ± 10.88 respectively, the difference being significant (P < 0.05). {Table 4}


This study was planned to evaluate the quality of prescribing for hypertension, a chronic condition, in outpatient setting of primary and secondary health care facilities in western part of India using PQI tool developed by Hassan et al., in 2010. [1] The PQI tool has been validated hence selected for assessment of prescribing quality in hypertension.

The PQI total scores were not normally distributed. There were three (4.1%) patients, who received a minimum score of '11', whereas two (2.7%) patients received a maximal score of '43', indicating the absence of floor effects and presence of ceiling effects. These finding differs from Hassan et al., who reported that the two criteria (generic prescribing and diagnosis) were normally distributed, while the other criteria displayed skewed distribution with the absence of floor or ceiling effects. [1]

Often instruments that have been tested in the same population might not need further testing, but further psychometric testing is necessary if differences exist between the study population and the population sampled when the instrument was developed and tested. Psychometric properties of tools used in the current study are necessary to report because they are specific to the sample of participants. [21] In our study exploratory principal components analysis of the PQI total scores exposed a six factor solution using the minimum Eigenvalue criteria of ≥1. These six factors accounted for 74.7% of the total variance. Hassan et al., [1] reported an eight-factor solution using the minimum Eigenvalue criteria of ≥1. These eight factors accounted for 66% of the total variance. The value of Cronbach's α for the entire 22 criteria was 0.71 compared to 0.60 in the previous study [1] suggesting that the PQI tool is reliable in our setting also.

Out of 73 prescriptions, 43 (59%) were poor quality. There was significant difference in prescribing quality in terms of PQI score between PHC and SHC. At PHC the quality of prescribing was better as evident by 57% high quality prescriptions with PQI score ranging from 34-43. There could be certain factors that may affect the quality of prescribing like; patients' illness status including co morbidities, number of drugs prescribed and patients flow at health care center. At PHC majority of patients have straight forward health problems with relatively less complications or co morbidities. Moreover at PHC only limited numbers of essential drugs are available along with only one physician compare to SHC. Hence, polypharmacy and variability in prescribing practices are less likely at PHC as compared to SHC thus reducing chances of irrationalities.

There was an inverse correlation between number of drugs prescribed and quality of prescribing at both PHC and SHC. The higher the number of drugs prescribed in a prescription, the lower the prescription quality. This finding is consistent with the study by Hassan et al. [1] In a review of studies on polypharmacy and inappropriate drug use among older people, the frequency of inappropriate drug use was higher in study groups with polypharmacy (≥5 drugs), being 27%-56%, compared to groups without polypharmacy (<5 drugs), for which the prevalence of inappropriate drug use was 10%-23%. [22] Our study demonstrated a weak positive correlation of PQI total score with age and a lack of correlation with number of diseases/conditions which differ from the findings of Hassan et al. [1] This unexpected finding could be due to the fact that at both PHC and SHC patients with mild to moderate illness are treated and limited number of drugs are prescribed which are available as per the national health policy. Moreover, majority of hypertensive patients attending the facilities were above 50 years of age and hence a wide range for age was not covered.

The PQI total scores were strongly correlated with drug indication, drug effectiveness, and evidence based prescribing, correct directions, unnecessary duplication, duration of therapy and cost. There was moderate correlation for seven criteria and weak correlation for remaining eight. In the study by Hassan et al., the PQI total scores were strongly correlated with drug indication and drug dosage. There was moderate (six criteria) to weak (10 criteria) correlation and no correlation between the PQI total scores and four criteria namely unnecessary duplication, formulary/essential drug, legibility, and adequate patient information. However they were retained in PQI. [1] Our study shows at least one of these- unnecessary duplication strongly correlated with PQI total score suggesting regional variation in the factors affecting PQI score and prescription quality. As expected, drug indication shows strong correlation with total PQI score and can have major impact on quality of prescribing.

Hassan et al., developed and validated PQI retrospectively which may have retrospective bias. In this study data were collected prospectively for a fixed period with the advantages of completeness of data and proper sampling. We selected only one chronic condition so as to minimize disease/condition variation which is reflected in better internal consistency in form of higher value of Cronbach's α. as compared to previous study. [1] However the results are relevant for one disease and limited to primary and secondary health settings and hence the usefulness and acceptability cannot be assumed for other settings. Further studies with other diseases and other settings like tertiary care facility would be necessary before the strengths and limitations of PQI can be fully realized.


Majority of the prescriptions for hypertension in primary and secondary health care settings are of poor quality. The PQI is a comprehensive tool which is valid and reliable for measuring quality of prescribing in chronic disease like hypertension in Indian settings. PQI can be used for assessment and comparison of quality of prescribing in different clinical settings at different health care levels.


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