↓ Skip to main content

Pharmaceutical policies: effects of financial incentives for prescribers

Overview of attention for article published in Cochrane database of systematic reviews, August 2015
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

Mentioned by

news
1 news outlet
twitter
23 tweeters

Citations

dimensions_citation
22 Dimensions

Readers on

mendeley
222 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Pharmaceutical policies: effects of financial incentives for prescribers
Published in
Cochrane database of systematic reviews, August 2015
DOI 10.1002/14651858.cd006731.pub2
Pubmed ID
Authors

Arash Rashidian, Amir-Houshang Omidvari, Yasaman Vali, Heidrun Sturm, Andrew D Oxman

Abstract

The proportion of total healthcare expenditures spent on drugs has continued to grow in countries of all income categories. Policy-makers are under pressure to control pharmaceutical expenditures without adversely affecting quality of care. Financial incentives seeking to influence prescribers' behaviour include budgetary arrangements at primary care and hospital settings (pharmaceutical budget caps or targets), financial rewards for target behaviours or outcomes (pay for performance interventions) and reduced benefit margin for prescribers based on medicine sales and prescriptions (pharmaceutical reimbursement rate reduction policies). This is the first update of the original version of this review. To determine the effects of pharmaceutical policies using financial incentives to influence prescribers' practices on drug use, healthcare utilisation, health outcomes and costs (expenditures). We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (searched 29/01/2015); MEDLINE, Ovid SP (searched 29/01/2015); EMBASE, Ovid SP (searched 29/01/2015); International Network for Rational Use of Drugs (INRUD) Bibliography (searched 29/01/2015); National Health Service (NHS) Economic Evaluation Database (searched 29/01/2015); EconLit - ProQuest (searched 02/02/2015); and Science Citation Index and Social Sciences Citation Index, Institute for Scientific Information (ISI) Web of Knowledge (citation search for included studies searched 10/02/2015). We screened the reference lists of relevant reports and contacted study authors and organisations to identify additional studies. We included policies that intend to affect prescribing by means of financial incentives for prescribers. Included in this category are pharmaceutical budget caps or targets, pay for performance and drug reimbursement rate reductions and other financial policies, if they were specifically targeted at prescribing or drug utilisation. Policies in this review were defined as laws, rules, regulations and financial and administrative orders made or implemented by payers such as national or local governments, non-government organisations, private or social insurers and insurance-like organisations. One of the following outcomes had to be reported: drug use, healthcare utilisation, health outcomes or costs. The study had to be a randomised or non-randomised trial, an interrupted time series (ITS) analysis, a repeated measures study or a controlled before-after (CBA) study. At least two review authors independently assessed eligibility for inclusion of studies and risks of bias using Cochrane Effective Practice and Organisation of Care (EPOC) criteria and extracted data from the included studies. For CBA studies, we reported relative effects (e.g. adjusted relative change). The review team re-analysed all ITS results. When possible, the review team also re-analysed CBA data as ITS data. Eighteen evaluations (six new studies) of pharmaceutical policies from six high-income countries met our inclusion criteria. Fourteen studies evaluated pharmaceutical budget policies in the UK (nine studies), two in Germany and Ireland and one each in Sweden and Taiwan. Three studies assessed pay for performance policies in the UK (two) and the Netherlands (one). One study from Taiwan assessed a reimbursement rate reduction policy. ITS analyses had some limitations. All CBA studies had serious limitations. No study from low-income or middle-income countries met the inclusion criteria.Pharmaceutical budgets may lead to a modest reduction in drug use (median relative change -2.8%; low-certainty evidence). We are uncertain of the effects of the policy on drug costs or healthcare utilisation, as the certainty of such evidence has been assessed as very low. Effects of this policy on health outcomes were not reported. Effects of pay for performance policies on drug use and health outcomes are uncertain, as the certainty of such evidence has been assessed as very low. Effects of this policy on drug costs and healthcare utilisation have not been measured. Effects of the reimbursement rate reduction policy on drug use and drug costs are uncertain, as the certainty of such evidence has been assessed as very low. No included study assessed the effects of this policy on healthcare utilisation or health outcomes. Administration costs of the policies were not reported in any of the included studies. Although financial incentives are considered an important element in strategies to change prescribing patterns, limited evidence of their effects can be found. Effects of policies, including pay for performance policies, in improving quality of care and health outcomes remain uncertain. Because pharmaceutical policies have uncertain effects, and because they might cause harm as well as benefit, proper evaluation of these policies is needed. Future studies should consider the impact of these policies on health outcomes, drug use and overall healthcare expenditures, as well as on drug expenditures.

Twitter Demographics

The data shown below were collected from the profiles of 23 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 222 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 5 2%
Brazil 2 <1%
Germany 2 <1%
Ghana 1 <1%
Portugal 1 <1%
India 1 <1%
Indonesia 1 <1%
United States 1 <1%
Sweden 1 <1%
Other 0 0%
Unknown 207 93%

Demographic breakdown

Readers by professional status Count As %
Student > Master 61 27%
Researcher 44 20%
Student > Ph. D. Student 29 13%
Unspecified 22 10%
Student > Doctoral Student 16 7%
Other 50 23%
Readers by discipline Count As %
Medicine and Dentistry 88 40%
Unspecified 35 16%
Social Sciences 25 11%
Pharmacology, Toxicology and Pharmaceutical Science 17 8%
Nursing and Health Professions 13 6%
Other 44 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 24. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 August 2019.
All research outputs
#677,391
of 13,451,724 outputs
Outputs from Cochrane database of systematic reviews
#2,168
of 10,597 outputs
Outputs of similar age
#15,526
of 234,148 outputs
Outputs of similar age from Cochrane database of systematic reviews
#68
of 258 outputs
Altmetric has tracked 13,451,724 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,597 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.0. This one has done well, scoring higher than 79% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 234,148 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 258 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.