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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: May 4, 2018
Open Peer Review Period: May 9, 2018 - Jul 4, 2018
Date Accepted: Oct 1, 2018
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Measuring the Impact of an Open Web-Based Prescribing Data Analysis Service on Clinical Practice: Cohort Study on NHS England Data

Walker AJ, Curtis HJ, Croker R, Bacon S, Goldacre B

Measuring the Impact of an Open Web-Based Prescribing Data Analysis Service on Clinical Practice: Cohort Study on NHS England Data

J Med Internet Res 2019;21(1):e10929

DOI: 10.2196/10929

PMID: 30664459

PMCID: 6351986

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Measuring the Impact of an Open Web-Based Prescribing Data Analysis Service on Clinical Practice: Cohort Study on NHS England Data

  • Alex J Walker; 
  • Helen J Curtis; 
  • Richard Croker; 
  • Seb Bacon; 
  • Ben Goldacre

Background:

OpenPrescribing is a freely accessible service that enables any user to view and analyze the National Health Service (NHS) primary care prescribing data at the level of individual practices. This tool is intended to improve the quality, safety, and cost-effectiveness of prescribing.

Objective:

We aimed to measure the impact of OpenPrescribing being viewed on subsequent prescribing.

Methods:

Having preregistered our protocol and code, we measured three different metrics of prescribing quality (mean percentile across 34 existing OpenPrescribing quality measures, available “price-per-unit” savings, and total “low-priority prescribing” spend) to see whether they changed after the viewing of Clinical Commissioning Group (CCG) and practice pages. We also measured whether practices whose data were viewed on OpenPrescribing differed in prescribing, prior to viewing, compared with those who were not. We used fixed-effects and between-effects linear panel regression to isolate change over time and differences between practices, respectively. We adjusted for the month of prescribing in the fixed-effects model to remove underlying trends in outcome measures.

Results:

We found a reduction in available price-per-unit savings for both practices and CCGs after their pages were viewed. The saving was greater at practice level (−£40.42 per thousand patients per month; 95% CI −54.04 to −26.81) than at CCG level (−£14.70 per thousand patients per month; 95% CI −25.56 to −3.84). We estimate a total saving since launch of £243 thosand at practice level and £1.47 million at CCG level between the feature launch and end of follow-up (August to November 2017) among practices viewed. If the observed savings from practices viewed were extrapolated to all practices, this would generate £26.8 million in annual savings for the NHS, approximately 20% of the total possible savings from this method. The other two measures were not different after CCGs or practices were viewed. Practices that were viewed had worse prescribing quality scores overall prior to viewing.

Conclusions:

We found a positive impact from the use of OpenPrescribing, specifically for the class of savings opportunities that can only be identified by using this tool. Furthermore, we show that it is possible to conduct a robust analysis of the impact of such a Web-based service on clinical practice.


 Citation

Please cite as:

Walker AJ, Curtis HJ, Croker R, Bacon S, Goldacre B

Measuring the Impact of an Open Web-Based Prescribing Data Analysis Service on Clinical Practice: Cohort Study on NHS England Data

J Med Internet Res 2019;21(1):e10929

DOI: 10.2196/10929

PMID: 30664459

PMCID: 6351986

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