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Farmacia Hospitalaria

On-line version ISSN 2171-8695Print version ISSN 1130-6343

Farm Hosp. vol.41 n.1 Toledo Jan./Feb. 2017

http://dx.doi.org/10.7399/fh.2017.41.1.10559 

Originals

The influence of changes in hospital drug formulary on the prescription of proton pump inhibitors

Raquel Vázquez-Mourelle1  , Eduardo Carracedo-Martínez2 

1Assistant Manager. Galician Health Service. Xunta de Galicia. Santiago de Compostela, Galicia. Spain

2Organizational Structure of Integrated Management System. Galician Health Service. Santiago de Compostela, Galicia. Spain

Abstract

Objective:

To analyze the impact of introducing omeprazole in the drug formulary of the Hospital de Barbanza on prescriptions made in hospital and out-of-hospital (Outpatient Units and Primary Care) for all Proton Pump Inhibitors (PPIs).

Material and methods:

A 36-month retrospective descriptive study in a level I hospital. The basic units of work are Dose-Population-Day in the outpatient setting, and the Defined Daily Dose/stays-day for hospitalized patients; the proportion of DDDs for omeprazole vs. the rest of PPIs is used as measure of efficiency. For statistical analysis, we built a segmented regression­ model.

Results

In the outpatient units, there are statistically significant changes for pantoprazole and rabeprazole. The first drug, which was stable before the intervention, suffered an immediate decrease; rabeprazole, which was increasing before the intervention, presented a subsequent downward trend. In Primary Care, a statistically significant change was confirmed for pantoprazole, with a long-term decreasing trend. In hospitalization, statistically significant changes were observed for pantoprazole and omeprazole; the first one with an immediate decrease and a long-term tendency to decrease, while omeprazole experienced an immediate increase and long-term growth. The evolution of the omeprazole percentage vs. all PPIs showed increases in all three scenarios.

Conclusions:

A shift to a more efficient prescription of PPIs was observed in all healthcare settings following the introduction of omeprazole in the hospital drug formulary. The inclusion of efficient drugs, or the removal of those inefficient, can be a potentially useful tool in order to improve prescription profiles.

KEYWORDS: Omeprazole; Proton pump inhibitors; Hospital formulary; Hospital Pharmacy Unit; Drug prescriptions; Statistical regression analysis; Organizational efficiency; Hospital management; Public hospitals; Healthcare area with integrated management

Contribution by the study

The present article analyzes the effect on prescription by the inclusion of a new medication in the formulary of a hospital, regarding all drugs in the same therapeutic group; its scope is differentiated within 3 patient care levels: hospitalization (hospitalized patients), outpatient units (patients from hospital outpatient units) and Primary Care centres of referral (outpatients managed at their health centre).

This research intends to show the shift and evolution in the use of the whole group of Proton Pump Inhibitors as a consequence of the inclusion of omeprazole in the hospital formulary, and to verify if this behaviour is useful or in line for achieving a more efficient prescription.

We consider that this is a matter of high interest due to its novelty, given that no study in Spain has conducted any research about this effect, and therefore there is no scientific evidence at all about the consequences of the inclusion in the formulary of a new medication upon the use of the rest of the drugs in the same therapeutic group in our country, not only in the hospital setting, but also in the setting of hospital outpatient units and in Primary Care centres with the same hospital of reference where the intervention has been conducted.

Introduction

The hospital formulary is the list of all those drugs selected by the Pharmacy Committee from a specific hospital, that are available to be used in hospitalized patients; it is a measure for rational use by the National Health System. Some areas in the Primary Care setting have used this type of tool; however, these are presented as recommendations, and there is complete freedom for prescription outside it1, even though some countries enforce its use in this level of care2,3.

At the time of selecting the medications to be included in the formulary, the rule will be not considering the retail pharmacy price for said drugs4; however, it has been confirmed that there is a direct effect on the subsequent use of those medications after hospital discharge4. In countries other than Spain, it has been detected that hospital prescription will have an influence on Primary Care 5,6, which seems to have a direct association with hospital discharge reports and prescriptions at Outpatient Units7 . Other studies have assessed the influence of a change in the formulary upon out-of-hospital prescriptions4, but none has been conducted in Spain.

In our country, pharmaceutical expenses have reached in recent years around 10,000 million euros per year at outpatient level8 and around 4,000 million at hospital level, which will became over 6,000 million in 2015 if the new due to the inclusion of the new drug therapies against the Hep hepatitis C virus are included9. These issues lead to conduct a specific monitoring of the evolution in pharmaceutical services provided by the Galician Health System (SERGAS), as well as by other Autonomous Communities. And one of the indicators used to determine prescription efficiency is the Proportion of Omeprazole over the rest of Proton Pump Inhibitors (PPIs), because this is considered the IBP of choice due to its superior efficiency. The healthcare areas, or Organizational Structures of Integrated Management (EOXI) from the SERGAS, are the peripheral executive management agencies that integrate Primary Care and Hospital Care10.

Considering a Health System that consists of two levels of care, it seems essential that, at the time of selecting a medication to be included in the hospital formulary, its price and its potential impact on the outpatient setting should also be taken into account. This aspect is particularly relevant when this inclusion is considered only due to the price reductions negotiated within the hospital, because this could represent an additional cost if the overall balance is damaging for the Health System as a whole.

On June, 2014, the omeprazole molecule was included in the formulary of the Hospital de Barbanza (Galicia, Spain); so far, only pantoprazole and esomeprazole were available in the formulary (the latter was restricted for patients with a nasogastric tube). At that time, the cost in Spain of an omeprazole DDD was approximately 10 times lower than the DDD for any other PPI 11.

The objective of our study was to analyze the impact of omeprazole introduction in the formulary of the Hospital A Barbanza on hospital (hospitalization) and out-of-hospital prescriptions (outpatient units and Primary Care), in the overall Proton Pump Inhibitor therapeutic group.

Methodology

In Spain, the public healthcare insurance implemented covers practically the whole population. The present research paper is focused on a hospital from the SERGAS network; namely a Level I regional hospital12 located in the town of Ribeira within the A Coruña province, with an assigned population of 64,287 inhabitants in 2014, and 64,655 in 2015, and four Primary Care centres of referral: A Pobra de Caramiñal (9,186 inhabitants), Boiro (18,925 inhabitants), Porto do Son (8,692 inhabitants) and Ribeira (27,852 inhabitants). With 81 beds, the evolution of its occupancy rate has been of 86.16% in 2013, 80.80% in 2014 and 81.92% in 2015.

The Defined Daily Doses (DDDs) for each PPI were the basic work units; these allowed us to analyze the monthly time sequences of use of each molecule evaluated. It is defined as the assumed mean daily dose of a medication, when used for its main indication. DDDs, according to the anatomical classification of medications13, are in continuous review by the WHO14. The following DDD equivalences were determined: omeprazole (DDD 20 mg), pantoprazole (DDD 40 mg), lansoprazole (DDD 30 mg), rabeprazole (DDD 20 mg) and esomeprazole (DDD 30 mg), both for oral and parenteral formulations.

The use of DDDs allows us to conduct comparative studies of use, regardless of variations in price and in the weight contents of each pharmaceutical form. Generally, the number of DDDs used in an area or centre is expressed, in descriptive studies, per 1,000 inhabitants and per day: this is called the Day Inhabitant Dose (DID). This parameter offers an approximate volume of the population treated daily with the normal dose of a specific drug, and therefore its use allows to expose any differences in therapy practices.

In the outpatient setting, the mean use is expressed in DIDs, as already mentioned; this measure will be used for the analysis in Outpatient Units and Primary Care. However, DDD per 100 hospital stays and day15 (DDD/ stays-day) will be used for calculating the use in hospital for in-patients, and this will provide an estimate of the likelihood for a patient to be treated with a specific medication during hospital stay, or in other words, the proportion of hospitalized patients treated with a specific drug during their hospitalization. These two units, DID and DDD/stays-day, are the ones we have used for statistical calculation.

We have differentiated three forms of care (Outpatient Units, Primary Care, and Hospitalization), and in all of them, the efficiency measure used has been the percentage or proportion of omeprazole DDD over the total DDD of all PPIs prescribed; we represent this as: %DDDomeprazole/DDDtotalPPI.

Regarding the timeframe, a descriptive study was conducted during 36 months, from January, 2013 to December, 2015. The change in the hospital formulary by the inclusion of the omeprazole molecule was implemented on June, 6th, 2014; and therefore this analysis covers a similar period before and after the intervention.

Data regarding dispensing and acquisitions charged against the SERGAS were obtained from the official corporate information systems:

All dispensing conducted by the community pharmacies in the healthcare area linked with the prescriptions conducted by physicians from any of the four

Primary Care services in the area of referral by the hospital and its outpatient units.

The information was obtained from the Pharmacy Service Information System, as number of packages dispensed each month, transformed into DDD per month, and subsequently into monthly DIDs.

Of all dispensing conducted by the Pharmacy Unit in the Hospital A Barbanza, using the Pharmacy Service Information System database, which provides the

number of packages used, transformed into DDD per month, and subsequently into DDD/stays-day.

For statistical analysis, we built a segmented regression model of interrupted time series16. The intervention studied was the inclusion of the omeprazole molecule in the formulary of the previously mentioned hospital.

In this analysis, the dependent variable was DID or DDD/stays-day, or the %DDDomeprazole/DDDtotalPPI of the different PPIs per month; and the independent variables were:

Time from the start of the study, which shows the time trend previous to the change in the hospital formulary (or intervention).

A binary variable that takes the value of 0 before and of 1 after the change in the formulary, which would show the immediate change after the intervention.

A time variable since the change in the formulary, which took the value of 0 before the intervention, and afterwards the values of 1,2,3… that would show the change in trend at long term.

The segmented regression model will conduct 2 regression lines, one with data before the change in the formulary, and the other with subsequent results data after the change in the formulary: .As result it provides 4 coefficients (when DID is mentioned, it can be extrapolated to DDD/stays-day or %DDDomeprazole/DDDtotalPPI):

Intercept. It is the cut-off point of the first line with the Y axe; it represents the value of DID estimated by regression method at the start of the study. If the coefficient was not statistically significant (SS), the conclusion could be that the value of DID was not different from zero at the start of the period of study.

Trend previous to the change in the formulary. It is the slope of the first line; it represents the increase or decrease value in DID values before the change. If the coefficient was not SS, the conclusion could be that there was neither increase nor decrease before the change. If the coefficient was positive and SS, the conclusion could be that DIDs were increasing before the intervention; and if the coefficient was negative, that DIDs were decreasing before the change.

Immediate impact of the change in the formulary. This is the difference between the end of the first line and the beginning of the second line; it represents the leap or immediate reduction in DID values. If the coefficient was not statistically significant, the conclusion could be that there was no leap or immediate reduction in values. If the coefficient was positive and SS, the conclusion could be that DIDs have experienced an immediate leap, and if it was negative, that DIDs have experienced an immediate reduction.

Change in trend after the change in the formulary. This is the difference between the slope in the second line and the slope in the first one, which represents the likely change in increase or decrease at long-term in DID values that could have occurred after the intervention regarding the increase or decrease rate before the change. If the coefficient was not SS, the conclusion could be that there has been no modification in the decrease or increase at long term in their values. If the coefficient was positive and SS, the conclusion could be that, after the change in the formulary, DIDs have started increasing at a faster rate (if they were increasing or stable before the intervention) or decrease at a lower rate (if they were decreasing or stable before the change).

As measure for statistical model adjustment, we used the R2 value.

Results

First setting: Outpatient Units

Figure 1 shows the evolution over time of the DIDs for the different PPIs for medical prescriptions conducted for outpatient dispensing by hospital physicians; it stands out that the DIDs for pantoprazole experienced a first sharp decrease and subsequently showed a slight increasing trend.

Figure 1 Evolution of DIDs for PPIs in the Outpatient Units of the Hospital de A Barbanza, from January, 2013 to December, 2015. 

Segmented regression of DID data for the different PPIs in Outpatient Units showed a mean R2 of 0.346. Its results (Table 1.a) show that the use of pantoprazole was stationary before the change in the formulary, and experienced a sharp SS decrease afterwards, followed by a slight increase at long-term, also significant. The use of rabeprazole before the change showed a SS increase, and did not experience an immediate change after the intervention, although its subsequent trend at long-term presents a significant decrease. Esomeprazole, which showed a significant reduction in its use before the change, did not show any SS changes. The remaining PPIs (omeprazole and lansoprazole) did not show SS values for the trend previous or after the change in the formulary.

Table 1 Results of the segmented regression analysis for the three settings studied, from January, 2013 to December, 2015. 

Estadísticamente significativo si p<0,05

Second setting: Primary Care

Figure 2 shows the evolution of the DIDs for different PPIs in Primary Care centres for which the Hospital de Barbanza is their referral centre.

Figure 2 Evolution of DIDs por PPIs in the Primary Care centres from the area of referral by the Hospital de A Barbanza, from January, 2013 to December, 2015. 

Segmented regression of DID data from different PPIs for Primary Care showed a mean R2 of 0.588. Their outcomes (Table 1.b) show that pantoprazole DIDs did not experience any SS increase or decrease before the introduction of omeprazole in the formulary; no change with immediate effect has been observed either. However, there was a change of trend after the intervention: the use of pantoprazole tended to decrease at longer term. Lansoprazole DIDs showed a decreasing trend before the change in the formulary, and afterwards no SS immediate change was perceived, nor any trend modification at long term. The other PPIs did not show any SS trends before the intervention, and no leaps or changes in trend subsequently.

Third setting: Hospitalization

In hospitalization, Figure 3 shows that after the formulary change, the use of pantoprazole at hospital level started to decrease, the use of omeprazole presented an increasing trend, and the use of esomeprazole continued stable.

Figure 3 Evolution of DDD/stays-day for PPIs at the Hospital de Barbanza, from January, 2013 to December, 2015. 

The segmented regression of DDD/stays-day data showed a mean R2 of 0.660. Its results (Table 1.c) showed that pantoprazole did not present any SS increase or decrease before the change in the formulary, but a statistically significant strong immediate reduction was observed after the intervention, as well as an alteration in the long-term trend regarding the use of pantoprazole which tends to decrease in a SS manner.

In the case of omeprazole, it was observed in a SS way that after its inclusion in the hospital formulary, there was an immediate increase in its use, as well as an increasing trend at long term. For esomeprazole, no previous trend was observed, and no significant change after the formulary modification was observed either.

%DDDomeprazole/DDDtotal PPI in the three settings

Regarding the percentage of the DDD of omeprazole compared with the total DDD for all PPIs, Figure 4 shows that, after the change, there is a clear increasing trend at hospital level, and an immediate leap at Outpatient Unit level, followed by a stable situation. In this last setting, the evolution of the average percentages of DID prescription of this molecule over the rest of PPIs during the period studied was 72.58%, reaching its highest peak on September, 2014 with 86.49% (Figure 4). In the prescriptions at the Primary Care setting, this average percentage was 58.14%, with an increasing evolution during the whole study.

Figure 4 Evolution of the DDD percentage of omeprazole vs. the DDDs for PPIs in the three levels of care studied, from January, 2013 to December, 2015. 

Segmented regression showed a mean R2 of 0.835. Its outcomes (Table 2) showed that after the intervention there was an immediate SS leap at hospital level, and subsequently a SS increasing trend at long-term. In the Outpatient Units, there was an immediate SS leap after the intervention, but the subsequent trend at long term continued stable and was not SS. In Primary Care, the long-term trend before the intervention was already increasing in a SS manner, and no SS immediate leap was observed; however, there was a SS long-term change in terms of an acceleration of the increasing trend.

Table 2 Results of the Regression for the variable: DDD proportion of omeprazole over total DDD for PPIs. 

Statistically significant if p<0.05

Discussion

In this study, a clear change is observed in PPI prescription after the introduction of omeprazole in the hospital formulary for prescriptions within and outside hospital, particularly for pantoprazole. In the first setting, this change is immediate and marked, with an inmediate increase in the percentage of omeprazole, and with an increasing trend afterwards; in Outpatient Units, an immediate leap in the percentage of omeprazole is observed, but no change in increase trend at long term; and in Primary Care, this percentage does not present an immediate leap, but an increase in the rate of growth after the formulary change.

Regarding the use of each one of the PPIs, at hospital level it was observed that, after the introduction of omeprazole in the formulary, at the same time that there was an increase in the DDD/stays-day for omeprazole, there was a reduction in the ones for pantoprazole, while those for esomeprazole continued stable. The latter can be due to the fact that the use of esomeprazole was already restricted.

At Outpatient Unit level, no change in omeprazole DIDs was observed, but an immediate reduction in the ones for pantoprazole, as well as a change of trend for those of rabeprazole. The change observed in pantoprazole prescriptions might be explained by the shifts in its hospital prescriptions, that will finally end up as prescriptions after discharge; in the case of rabeprazole, its prescription rate is so low (mean DID of 0.067) compared with the rest of PPIs (mean DID for omeprazole: 3.225) that slight changes in the relative prescription for the other PPIs might have had a relative major displacement effect for this drug. The lack of change in omeprazole DIDs can be due to the high number of DDDs previous to the intervention in the formulary in Outpatient Units, compared with the DDDs at hospital level; for example, on June, 2014, 2.947 omeprazole DIDs were used in Hospital Units, and 18.539 DDD/stays-day at hospital level; and if we consider that the hospital has 81 beds and 65,000 inhabitants, we can see that on June, 2014, 364 omeprazole DDDs were prescribed at hospital level, and 5,684 DDDs in Outpatient Units; therefore, the influence that the former can have on the latter is more limited that the influence that DDDs for pantoprazole can have at hospital and out-of-hospital level, where differences are not so marked.

There is no SS change in Primary Care physicians regarding omeprazole; however, there is a change in pantoprazole prescriptions: their DIDs don’t show an immediate sharp decrease, but then there is a decreasing trend at long term. The explanation for this could be in the prescription induced from the Outpatient Units towards Primary Care17,18,19,21. No fast change was observed in pantoprazole prescriptions in Primary Care, unlike in Outpatient Units; this could be due to the fact that omeprazole DIDs in Outpatient Units are extremely lower than omeprazole DIDs in Primary Care; specifically, in Outpatient Units, the omeprazole DIDs at June, 2014 were 2.947, and their mean during the study was 3,225, vs. the situation in Primary Care, where DIDs at June, 2014 were 13.647, and the mean DID during the study was 13.934.

Regarding the evolution of the proportion of omeprazole DDD regarding all DDD for PPIs, the study shows that there is an increase in all levels, which is immediate in hospitalization and Outpatient Units, and at longer term in Primary Care. Omeprazole is the PPI of choice, and therefore PPI prescription becomes more efficient in the three settings.

We haven’t found any studies assessing what happens in different healthcare settings after the incorporation of a new PPI to the hospital medication formulary, with this approach as a longitudinal analysis of time series. We have located one study about the impact of the change upon the formulary of a hospital on prescriptions, both at hospital discharge and at a time-point some months after hospitalization4, which evaluates withdrawing esomeprazole because its price is ten times higher than that for another PPI, and replacing it by a more efficient PPI. In this study, which analyzed 3 transversal points (before hospital admission, at discharge, and afterwards), it was found that before the change in the formulary, the majority of patients were taking esomeprazole at hospital discharge as well as some months afterwards, while after its withdrawal, its use was residual both at hospital discharge and some months afterwards, and efficient PPIs were most widely used.

We did not find any studies to analyze the effect of the formulary change upon prescription within hospital and out-of-hospital at the same time; we did find studies analyzing the effect of PPIs outside hospital after a change in the formulary; and other studies that found, like ours, that the change in the formulary was associated with changes in the use of the medication at hospital22,23.

Pharmacy service should be managed transversally, because changes in the hospital guidelines will entail changes in prescription patterns. These changes should be assessed when price reductions become the driver for including new medications in the hospital formulary, because of their overall effect24.

Our study is ecologic, and any causality relationship should be interpreted cautiously; however, previous studies have found said association24. Another limitation could be the lack of reference to clinical variables; however, there is sufficient scientific evidence in this case about the fact that no PPIs present an efficacy superior to the rest for their approved clinical indications and if used in equally potent doses25; therefore, no clinical variations should be expected. In terms of safety, there are no apparent differences in adverse effects25.

On the other hand, it is worth mentioning that there has been no assessment of the evolution of the direct costs of medications, because one month after the inclusion of omeprazole in the formulary, there was a reduction in the price of PPIs26, followed by a second one on October, 201527, and this represents an important confusion factor for the conclusion that any changes in this variable are exclusively a consequence of the intervention.

As a final conclusion, we can state that the inclusion of omeprazole in the hospital formulary has had an influence in PPI prescription patterns, both in hospitalization and in Outpatient Units and Primary Care, and this has led to a more efficient use of these drugs.

The inclusion of efficient medications in the formulary, or the withdrawal of inefficient drugs, can be a potentially useful tool and effective at long-term in order to improve the prescription profiles in all levels of care.

Contributions to Authorship

Raquel Vázquez Mourelle conceived the present article, and devised the methodological design of the analysis jointly with Eduardo Carracedo Martínez; Raquel Vázquez Mourelle conducted the exploitation, validation and transformation of hospitalization data, while Eduardo Carracedo Martínez did the same with Specialist and Primary Care Centres; both authors were jointly responsible for data analysis and interpretation in the three settings presented. Raquel Vázquez Mourelle was in charge of writing the article, while Eduardo Carracedo Martínez conducted a critical review of the different versions, with major intellectual contributions. Both authors have approved the final version of the manuscript.

Acknowledgements

None.

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Funding None.

Received: May 15, 2016; Accepted: October 11, 2016

Autor para correspondencia. Correo electrónico: raquel.vazquez.mourelle@sergas.es (Raquel Vázquez-Mourelle).

Conflicts of Interest Both authors hereby declare that there is no conflict of interests whatsoever.

Creative Commons License This is an open-access article distributed under the terms of the Creative Commons Attribution License