Estimating the Impact of Patient Safety Incidents on Quality of Life using Patient Reported Outcome Measures

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Datasets: − Hospital Episode Statistics Accident and Emergency (HES A and E); − Hospital Episode Statistics Critical Care (HES Critical Care); − Hospital Episode Statistics Outpatients (HES OP)

Objective for processing

Imperial College London’s Big Data and Analytical Unit (BDAU) previously received extracts of Patient Reported Outcome Measures (PROMs) data for use in a research study: “Estimating the Impact of Patient Safety Incidents on Quality of Life using Patient Reported Outcome Measures”. This data was linked to data provided under study DARS-NIC-172334-W0G2L and a separate dataset was created, utilised and managed for this study. This study is funded by the National Institute of Health Research - Patient Safety Translational Research Centre. The aim and purpose of this Agreement is to extend the territory of use to European Economic Area (EEA), as well as allowing honorary staff access to the data, in order to allow this study, “Estimating the Impact of Patient Safety Incidents on Quality of Life using Patient Reported Outcome Measures”, to continue. This study is being undertaken by a small team of researchers from Imperial College London. The team has extensive experience in the econometric analysis of administrative healthcare datasets. This study aims to contribute a better understanding of economic costs in relation to patient safety and quality of life. Imperial College London will be the sole data controller and processor for this study. Imperial College London, under previous iterations of this Agreement, received extracts of pseudonymised Patient Reported Outcome Measures (PROMs) data for use in this research study. The pseudonymised PROMs data was then linked to the pseudonymised Hospital Episode Statistics (HES) data provided under study DARS-NIC-172334-W0G2L (which included all fields from data received for DARS-NIC-172334-W0G2L) and a linked pseudonymised PROMS-HES dataset was created, utilised and managed for the purpose of this study. The Big Data and Analytical Unit (BDAU) is a multidiscipline team within Imperial College London which collaborates with a large network of researchers across the college with the aim of ensuring the maximum use, impact and dissemination of research using healthcare data. Imperial College London will provide local access control within the BDAU ISO 27001 certified research environment for this study and ensure the dataset for this study is managed separately to the study for DARS-NIC-172334-W0G2L. The objective of this study is to analyse the impact of patient safety incidents on quality of life. It will do so by comparing the quality of life improvements between groups of patients that do and do not experience relevant events according to established patient safety indicators. To accomplish this HES inpatient (APC) and PROMS data, for years 2012 to 2018 for the specified variables, is required. There are several papers estimating the impact of patient safety incidences (PSIs) on providers’ resource use and payments. However, there are relatively fewer studies on the estimation of costs in terms of patients’ quality of life (QoL). The sparse literature suggests that estimated patient-reported complications are associated with a reduction in QoL in the short term, but that QoL might recover in a long term (Frie et al, 2012; Bosma et al, 2016). This study is being undertaken by a small team of researchers from Imperial College London. The team has extensive experience in the econometric analysis of administrative healthcare datasets. This study aims to contribute to a better understanding of economic costs in relation to patient safety and quality of life. Patient safety events are for the purposes of this study defined as they have been defined by the American Agency for Healthcare Research and Quality (AHRQ) set of patient safety indicators, which includes pressure ulcers, hospital acquired infections, and postoperative sepsis. Aylin and Bottle (2009) have validated that these events can be identified in HES data. In addition, the PROMs questionnaire asks patients if the experienced “complications” (wound problems, urinary problems, allergy or reaction to drug, bleeding). Imperial College London also consider these complications “patient safety events” and will test to which extent there is agreement between patient reported and hospital reported patient safety events. There are several papers estimating the impact of patient safety incidences (PSIs) on providers’ resource use and payments. However, there are relatively fewer studies on the estimation of costs in terms of patients’ quality of life (QoL). The sparse literature suggests that estimated patient-reported complications are associated with a reduction in QoL in the short term, but that QoL might recover in a long term. This study attempts to estimate the impact of patient safety events on QoL in elective surgery patients and the monetary value of QoL loss due to patient safety events. In addition, it will compare patient- and hospital reported rates using developed patient safety indicators. Patient safety events are for the purposes of this study defined as they have been defined by the American Agency for Healthcare Research and Quality (AHRQ) set of patient safety indicators, which includes pressure ulcers, hospital acquired infections, and postoperative sepsis. Aylin and Bottle (2009) (https://qualitysafety.bmj.com/content/18/4/303.long) have validated that these events can be identified in HES data. In addition, the PROMs questionnaire asks patients if the experienced “complications” (wound problems, urinary problems, allergy or reaction to drug, bleeding). Imperial College London also consider these complications “patient safety events” and will test to which extent there is agreement between patient reported and hospital reported patient safety events. The HES data allow us to identify characteristics of (e.g. age, gender, co-morbidities) and care received by the patients receiving elective surgery that experienced a patient safety event and a control group of patients that received elective surgery but did not experience a patient safety event. Using this data, This study estimates the researchers will identify a comparable set impact of patients that do and do not experience a patient safety event using matching methods. The cohort is those patients events on QoL in the NHS for whom patient reported outcome measures (PROMs) data has been collected, i.e. patients undergoing elective surgery for hip or knee replacement, groin hernia, or vericose veins. The exposed group are those experiencing a patient safety event. The control group in this project are patients not exposed to a patient safety event. Furthermore, based on matching, and the researchers will compare quality monetary value of life improvement between the two groups, and estimate quality-adjusted life years (QALY) QoL loss attributable due to patient safety events. In addition, it will compare patient- and hospital reported rates using existing patient safety indicators. Quality of life data is only obtained from the PROMS data. The linked HES data is used to identify the patients that experience patient safety events and those that do not (based on icd-10 codes). The data previously requested for years 2013-2017 allowed Imperial College London to reach a sufficient number of patients exposed to patient safety incidences, which are rare. There are no alternative data sources that allow Imperial College London to identify both Quality of Life (QoL) before and after surgery as well as exposure to PSIs at the individual level. Accessing the data at individual level is essential to allow for this linkage and to enable adjustment for patient level confounders. There are therefore no alternatives of achieving the purpose. Using the pseudonymised Hospital Episode Statistics (HES) inpatient data, the study team have identified a comparable set of patients that did and did not experience a patient safety event using matching methods. The study cohort consists of those patients in the NHS, identified from HES data using diagnosis fields, for whom Patient Reported Outcome Measures (PROMs) data has been collected, i.e. patients undergoing elective surgery for hip or knee replacement, groin hernia, or varicose veins. The exposed group are those experiencing a patient safety event. The control group in this project are patients not exposed to a patient safety event. Furthermore, based on matching, the researchers will compare quality of life improvement between the two groups, and estimate quality-adjusted life years (QALY) loss attributable to patient safety events. There are no other organizations and finders/commissioners which are involved in the project. The data will be analysed to examine how patient safety indicators, extracted from HES, affect quality of life in various dimension, such as hip surgery, knee surgery, hernia repair and varicose veins as described using PROMs data. This will involve statistical analysis using standard and innovative econometrics techniques inside the Imperial College London’s Big Data and Analytical Unit Secure Environment (BDAU SE). The main econometric technique will be difference in differences, where Imperial College London compare improvements in quality of life after surgery for patients that do and do not experience a patient safety event. The legal basis for processing the NHS Digital data under GDPR is Article 6 (1)(e) - "processing is necessary for the performance of a task in the public interest or in the exercise of official authority vested in the controller" and Article 9(2)(j) - "processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes". The initial analysis will focus on patients with PROMs conditions that do and do not experience a patient safety event. In practice Imperial College London will not divide the data set, but specify a dummy variable that indicates whether the patient experienced a patient safety event or not which will be used in multi-variable regression analysis to estimate the difference in quality of life gain from operation between the two groups. This difference is equal to the quality of life cost of experiencing an event. In the second part of the analysis Imperial College London will identify patients with other (non-PROMs) conditions who experienced the same type of patient safety events to estimate the total impact of patient safety events on quality of life. To ensure that differences in quality of life improvements are due to the patient safety events and not other differences between patients Imperial College London will make sure patients are as comparable as possible based on observable data. The variables will include age, sex, diagnosis codes, procedure codes, admission method, discharge method and length of stay. Based on these observable variables Imperial College London will use propensity score matching to select comparable cohorts. The objective of the study is to analyse the impact of patient safety incidents on quality of life. There are no alternative datasets other than the PROMS and HES data that would allow Imperial College London to measure both changes in Quality of Life (QoL) from before and after admission and the occurrence of patient safety events. Accessing the pseudonymised PROMS and HES data at individual level is essential to allow linkage between the two datasets and adjust for confounders. Minimum number of years, i.e., HES and PROMS data for years 2012/13 to 2017/18, have been requested to allow us to analyse patient safety incidents which are rare. The focus of the study is the population in England. Imperial College London is the sole data controller, as they determine the aims and objectives of the study. Imperial College London also process the data. The study is funded by the Imperial National Institute of Health Research (NIHR) Patient Safety Translational Research Centre (PSTRC) (https://www.imperial.ac.uk/patient-safety-translational-research-centre/ ), a partnership between Imperial College Healthcare NHS Trust and Imperial College London which is based at Imperial College and is funded by a grant from the NIHR. NIHR do not determine the means and purpose of processing and are therefore not considered to be a data controller. The Secure Enclaves is an isolated environment within the Imperial College London network, physically located at a datacentre operated by Virtus SDC Ltd. The servers at Virtus SDC Ltd are owned and managed by Imperial College London in a dedicated area of the Virtus SDC Ltd data centre. Virtus SDC Ltd do not have access to the data and will not process the data. As such Virtus SDC Ltd are not considered to be data processors. One of the researchers conducting this study holds an honorary contract with Imperial College London. Under GDPR , the lawful basis for Imperial College London to process the NHS England data for the purpose of this study are Articles 6(1)(e) and 9(2)(j) namely that processing is necessary for the performance of a task carried out in the exercise of official authority, such authority to make provision for research being vested in the University by virtue of the Royal Charter establishing the University dated 1907, and, that in respect of special category personal data, processing is necessary for research purposes carried out in accordance with Article 89(1) of the GDPR. Imperial College London are a public authority, and the outcome of this research is for the benefit of public interest because the objective of this study is to analyse the impact of patient safety incidents on quality of life within the general population.

Processing activities

All organisations party to this agreement must comply with the Data Sharing Framework Contract, including requirements on the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e.: employees, agents and contractors of the Data Recipient who may have access to that data). Under previous iterations of this Agreement a pseudonymised extract of PROMs data was disseminated to Imperial College London. The pseudonymised HES data from Agreement DARS-NIC-172334 was re-used and linked with the PROMs data disseminated by NHS England under this Agreement to form a pseudonymised linked PROMS-HES dataset. NHS Digital securely transferred a pseudonymised extract of PROMs data to Imperial College London. Imperial College London who store the data on a server in the BDAU Secure Environment (SE). HES Data from study DARS-NIC-172334W0G2L was cloned into this dataset and was linked with PROMs data provided by NHS Digital. Data access is strictly controlled by the BDAU through a robust dataset registration process. No one other than BDAU staff can authorise access to the data. All data under this Agreement is stored in Imperial College London’s Big Data and Analytical Unit Secure Environment (BDAU SE), a secure research environment, providing a secure data storage and processing environment, and analysis software. The BDAU SE is located in Imperial College London’s Data Centre and can be accessed remotely (via a screen view). All access to the data provided under this agreement, including access from outside the UK, is remote access as described below. Access to the data is restricted to researchers and supervisors only for the purpose outlined in this Data Sharing Agreement. Researchers and supervisors are substantive employees of Imperial College London and are bound to the policies, procedures and equivalent controls of the BDAU SE and Imperial College London. The Secure Enclaves is an isolated environment within the Imperial College London network, physically located at a datacentre operated by Virtus SDC Ltd. The servers at Virtus SDC are owned and managed by Imperial College London in a dedicated area of the Virtus SDC data centre. All network infrastructure is owned and managed by Imperial College London staff in space dedicated to Imperial. All data files and directories are encrypted and only the Imperial College London IT staff has access to the filesystem encryption keys. The raw data provided by NHS Digital will be analysed solely in the BDAU SE. Any further analysis done outside the BDAU SE (usually for visualisation purposes for output) will be done using data that has been aggregated with small numbers suppressed in line with the HES Analysis Guide. The data processing will be carried out at the data storage location and only a screen view of the data is provided to the remote device. To access the data in the BDAU SE, researchers will require approval from the study chief investigator (in their role as Asset Owner). Once approval is given, researchers are required to: 1) pass the Imperial Data Protection Awareness, including GDPR, and Information Security Awareness training 2) agree, with possible disciplinary action for noncompliance, to BDAU ISO 27001 certified standard operating procedures by signing the BDAU SE User and Dataset Registration forms. Since the BDAU SE can be accessed remotely (via a screen view) from any geographical location, a specific BDAU SE document was created to emphasise the geographical location restrictions where NHS England can be accessed/viewed from. Any BDAU SE user who is to access NHSD Digital data is required to confirm they are only accessing the data from within the territory of use as stated in their relevant data sharing agreement. Because the BDAU SE can be accessed remotely from any geographical location, this policy is in place to emphasise that users can only access their data from within the territory of use as stated in their agreement with NHS England. Due to the COVID-19 pandemic and changes in researchers’ working circumstances data will be accessed and analysed remotely from Spain, Portugal, Denmark, and France in addition to the UK. The data will be analysed to examine how patient safety indicators, extracted from HES, affect quality of life in various dimension, such as hip surgery, knee surgery, hernia repair and varicose veins as described using PROMs data. This will involve statistical analysis using standard and innovative econometrics techniques inside the BDAU SE. The main econometric technique will be difference in differences, where Imperial College London compare improvements in quality of life after surgery for patients that do and do not experience a patient safety event. Access to the data is only for the purpose outlined in this Data Sharing Agreement, all staff are bound to the policies, procedures and equivalent controls of the BDAU SE and Imperial College London, either as substantive employees of the College or having honorary contracts. Researchers and supervisors are substantive employees of Imperial College London, except for one researcher who has honorary affiliation with Imperial College London. This study will compare the quality of life improvements between groups of patients that do and do not experience relevant events according to established patient safety indicators. To accomplish this, all data is required for all requested years for the specified variables. The pseudonymised data provided by NHS England is analysed solely in the BDAU SE. Any further analysis done outside the BDAU SE (usually for visualisation purposes for output) will be done using data that has been aggregated with small numbers suppressed in line with the HES Analysis Guide. The data processing will be carried out at the data storage location and only a screen view of the data is provided to the remote device. The initial analysis will focus on patients with PROMs conditions that do and do not experience a patient safety events. In practice Imperial College London will not divide the data set, but specify a dummy variable that indicates whether the patient experienced a patient safety event or not which will be used in multi-variable regression analysis to estimate the difference in quality of life gain from operation between the two groups. This difference is equal to the quality of life cost of experiencing an event. In the second part of the analysis Imperial College London will identify patients with other (non-PROMs) conditions who experienced the same type of patient safety events to estimate the total impact of patient safety events on quality of life. To ensure that differences in quality of life improvements are due to the patient safety events and not other differences between patients Imperial College London will make sure patients are as comparable as possible based on observable data. The variables will include age, sex, diagnosis codes, procedure codes, admission method, discharge method and length of stay. Based on these observable variables Imperial College London will use propensity score matching and to select comparable cohorts. [2 paragraphs unchanged] All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

Expected output

It is expected that the main outputs for this particular study will be academic publications publications. [1 paragraph unchanged] • A health economic journal such as Health Economics, Journal of Health Economics or similar (target submission date Q3 2019, revised target Q4 2021). Spring 2023). • A health policy journal such as Health Affairs, Health Services Research or Similar (Target submission date Q3-2019, revised target Q2 2021) Summer 2023) • note on revised targets: a the health policy paper has already been submitted to a journal and [25 words unchanged] will be open access and appropriate allowances have been budgeted for this. [1 paragraph unchanged] Findings will Preliminary findings have also be been disseminated at one domestic conference such as the meeting of the European Health Economics Study Group and one European conference via oral presentation. association in Basel in 2019 . Through the National Institute for Health Research (NIHR) Patient Safety Translational Research [19 words unchanged] will receive a summary of results in an appropriate and accessible format. [1 paragraph unchanged] The research is retrospective, in that it is identifying the impact of PSIs on patients QoL Quality of Life (QoL) and there are no obvious possibilities for exploiting the results for the purpose of developing algorithms, tools or other technologies on the basis of this research. Preliminary findings Findings from the health policy paper has been presented at the European Health [5 words unchanged] Portugal, and at the NIHR PSTRC conference in Manchester, both in 2019. The health policy paper is in preparation for submission to a journal. The paper for publication in a Health Economics journal is in progress, but not yet finished as analysis is taking longer than expected.

Expected measurable benefits

Information has been taken directly from the benefits section of the NIHR Funding application for this project. This study is hoped to inform policy making regarding investment in interventions that can reduce medical error by demonstrating the human and monetary cost associated with PSIs. It aims to allow the evaluation of safety-improving interventions from a societal perspective by demonstrating the full societal costs of patient safety events, given the fact that the current cost-effectiveness evaluation of safety-improving interventions are mostly conducted from a narrow health care sector perspective and based on relatively crude measures such as mortality. This study will inform policy making regarding investment in interventions that can reduce medical error by demonstrating the human and monetary cost associated with PSIs. It will allow the evaluation of safety -improving interventions from a societal perspective by demonstrating the full societal costs of patient safety events, given the fact that the current cost-effectiveness evaluation of safety -improving interventions are mostly conducted from a narrow health care sector perspective and based on relatively crude measures such as mortality. The increased transparency on the cost of errors is hoped to benefit patients and the public in that better investment decisions can lead to reduction in future errors and thus improvements in quality and safety. In that sense, the benefits are expected to fall on those directly targeted by interventions to reduce medical error, and can indirectly affect a wider patient group through the freeing up of scarce resources invested in health care, therefore enabling more efficient allocation of resources in the future. The increased transparency on the cost of errors will benefit patients and the public in that better investment decisions can lead to reduction in future errors and thus improvements in quality and safety. In that sense, the benefits will fall on those directly targeted by interventions to reduce medical error, and can indirectly affect a wider patient group through the freeing up of scarce resources invested in health care. Theme 6 of the Imperial College NIHR PSTRC aims to evaluate the value for money in patient safety. This includes examining the impact of adverse events on quality of life outcomes. By evaluating the financial impact of patient safety incidents, routinely collected outcomes and patient related outcomes as reported by the patients themselves, Imperial College London can provide insight into this. The output of this study aims to enable more informed policy making and clinical practice ensuring that money within the NHS is focused on cost-effective patient safety interventions. This is part of a £7 million-pound investment in the PSTRC to achieve measurable benefits in translational research on patient safety in the NHS. Anticipated target dates for these are covered in the Expected Outputs section. Theme 6 of the Imperial College NIHR PSTRC aims to evaluate the value for money in patient safety. This includes examining the impact of adverse events on quality of life outcomes. By evaluating the financial impact of patient safety incidents, routinely collected outcomes and patient related outcomes as reported by the patients themselves, Imperial College London can provide insight into this. The output of this study will enable more informed policy making and clinical practice ensuring that money within the NHS is focused on cost-effective patient safety interventions. This is part of a £7 million-pound investment in the PSTRC to achieve measurable benefits in translational research on patient safety in the NHS. Anticipated target dates for these are covered in Section 5C.

Benefits reported

Analysis is taking longer than expected. Yielded benefits will be updated in the subsequent Agreement. ICL have presented the findings and shared a copy of the preliminary results with the Organisation for Economic Co-operation and Development (OECD), who cited the work in their report “The Economics of Patient Safety – from Analysis to Action” (OECD, 2020). The findings from the study showed that patients that experienced a patient safety event during elective surgery suffered a loss in terms of health related quality of life compared to patients that did not experience a patient safety event. This clearly demonstrates the value of reducing patient safety events, and can therefore enable a more efficient allocation of resources by demonstrating the potential gains from investing in better patient safety.

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Objective for processing

Imperial College London’s Big Data and Analytical Unit (BDAU) requires an extract previously received extracts of Patient Reported Outcome Measures (PROMs) data for use in a research [7 words unchanged] Incidents on Quality of Life using Patient Reported Outcome Measures”. This data will link was linked to data provided under study DARS-NIC-172334-W0G2L and a separate dataset will be was created, utilised and managed for this study. This study is funded by the National Institute of Health Research - Patient Safety Translational Research Centre. This study is being undertaken by a small team of researchers from Imperial College London, all with substantive contracts with the College. London. The team has extensive experience in the econometric analysis of administrative healthcare [9 words unchanged] of economic costs in relation to patient safety and quality of life. Imperial College London will be the sole data controller and processor for this study. [1 paragraph unchanged] There are several papers estimating the impact of patient safety indicators incidences (PSIs) on providers’ resource use and payments. However, there are relatively fewer [38 words unchanged] in a long term (Frie et al, 2012; Bosma et al, 2016). [2 paragraphs unchanged] Using this data, the researchers will identify a comparable set of patients that do and do not experience a patient safety event using matching methods. The cohort is those patients in the NHS for whom patient reported outcome measures (PROMs) data has been collected, i.e. patients undergoing elective surgery for hip or knee replacement, groin hernia, or vericose veins. The exposed group are those experiencing a patient safety event. The control group in this project are patients not exposed to a patient safety event. Furthermore, based on matching, the researchers will compare quality of life improvement between the two groups, and estimate quality-adjusted life years (QALY) loss attributable to patient safety events. The data previously requested for years 2013-2017 allowed Imperial College London to reach a sufficient number of patients exposed to patient safety incidences, which are rare. There are no alternative data sources that allow Imperial College London to identify both Quality of Life (QoL) before and after surgery as well as exposure to PSIs at the individual level. Accessing the data at individual level is essential to allow for this linkage and to enable adjustment for patient level confounders. There are therefore no alternatives of achieving the purpose. There are no other organizations and finders/commissioners which are involved in the project. [1 paragraph unchanged]

Processing activities

[1 paragraph unchanged] NHS Digital will securely transfer transferred a pseudonymised extract of PROMs data to Imperial College London. Imperial College London will who store the data on a server in the BDAU Secure Environment (SE). HES Data from study DARS-NIC-172334-W0G2L will be DARS-NIC-172334W0G2L was cloned into this dataset and was linked with PROMs data provided by NHS Digital. Data access is strictly [10 words unchanged] No one other than BDAU staff can authorise access to the data. Access to the data will be is restricted to researchers and supervisors only for the purpose outlined in this Data Sharing Agreement. Researchers and supervisors are substantive employees of Imperial College London and are bound to the policies, procedures and equivalent controls of the BDAU SE and Imperial College London as substantive employees of the College. London. The raw data provided by NHS Digital will be analysed solely in [27 words unchanged] small numbers suppressed in line with the HES Analysis Guide. The data processing will be analysed carried out at the data storage location and only a screen view of the data is provided to examine how patient safety indicators, extracted from HES, affect quality of life in various dimension, such as hip surgery, knee surgery, hernia repair and varicose veins as described using PROMs data. This will involve statistical analysis using standard and innovative econometrics techniques inside the BDAU SE. The main econometric technique will be difference in differences, where Imperial College London compare improvements in quality of life after surgery for patients that do and do not experience a patient safety event. remote device. The data will be analysed to examine how patient safety indicators, extracted from HES, affect quality of life in various dimension, such as hip surgery, knee surgery, hernia repair and varicose veins as described using PROMs data. This will involve statistical analysis using standard and innovative econometrics techniques inside the BDAU SE. The main econometric technique will be difference in differences, where Imperial College London compare improvements in quality of life after surgery for patients that do and do not experience a patient safety event. [2 paragraphs unchanged] In the second part of the analysis we Imperial College London will identify patients with other (non-PROMs) conditions who experienced the same type [5 words unchanged] estimate the total impact of patient safety events on quality of life. [3 paragraphs unchanged]

Expected output

The It is expected that the main outputs for this particular study will be academic publications [1 paragraph unchanged] • A health economic journal such as Health Economics, Journal of Health Economics or similar (target submission date Q3 2019, revised target Q4 2021). similar (target submission date Q3 2019) • A health policy journal such as Health Affairs, Health Services Research or Similar (Target submission date Q3-2019, revised target Q2 2021) • A health policy journal such as Health Affairs, Health Services Research or Similar (Target • note on revised targets: a the health policy paper has already been submitted to a journal and is currently being revised in light of the reviews received for submission to another journal. The health economics paper is currently being drafted. Both articles will be open access and appropriate allowances have been budgeted for this. submission date Q3-2019) Both articles will be open access and appropriate allowances have been budgeted for this. [1 paragraph unchanged] Findings will also be disseminated at one domestic conference such as Health Economics Study Group and one European conference. conference via oral presentation. Through the National Institute for Health Research (NIHR) Patient Safety Translational Research [19 words unchanged] will receive a summary of results in an appropriate and accessible format. All outputs will contain only aggregate level data with small numbers supressed suppressed in line with the HES analysis guide. No raw data will be [5 words unchanged] and neither the data nor outputs will be used for commercial purposes. The research is retrospective, in that it is identifying the impact of PSIs on patients QoL and there are no obvious possibilities for exploiting the results for the purpose of developing algorithms, tools or other technologies on the basis of this research. Preliminary findings from the health policy paper has been presented at the European Health Economics Association meeting in Porto, Portugal, and at the NIHR PSTRC conference in Manchester, both in 2019. The health policy paper is in preparation for submission to a journal. The paper for publication in a Health Economics journal is in progress, but not yet finished as analysis is taking longer than expected.

Expected measurable benefits

[1 paragraph unchanged] This study will inform policy making regarding investment in interventions that can reduce medical error by demonstrating the human and monetary cost associated with PSIs. It will allow the evaluation of safety -improving interventions from a societal perspective by demonstrating the full societal costs of patient safety events, given the fact that the current cost-effectiveness evaluation of safety -improving interventions are mostly conducted from a narrow health care sector perspective and based on relatively crude measures such as mortality. The increased transparency on the cost of errors will benefit patients and the public in that better investment decisions can lead to reduction in future errors and thus improvements in quality and safety. In that sense, the benefits will fall on those directly targeted by interventions to reduce medical error, and can indirectly affect a wider patient group through the freeing up of scarce resources invested in health care. [1 paragraph unchanged]

Benefits reported

Preliminary findings from the health policy paper has been presented at the European Health Economics Association meeting in Porto, Portugal, and at the NIHR PSTRC conference in Manchester, both in 2019. Analysis is taking longer than expected. Yielded benefits will be updated in the subsequent Agreement. The health policy paper is in preparation for submission to a journal. The paper for publication in a Health Economics journal is in progress, but not yet finished as analysis is taking longer than expected.

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Benefits reported

Not stated in the previous version; added here.

Preliminary findings from the health policy paper has been presented at the European Health Economics Association meeting in Porto, Portugal, and at the NIHR PSTRC conference in Manchester, both in 2019.

The health policy paper is in preparation for submission to a journal. The paper for publication in a Health Economics journal is in progress, but not yet finished as analysis is taking longer than expected.

Unchanged: Objective for processing, Processing activities, Expected output, Expected measurable benefits.

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Objective for processing

[7 paragraphs unchanged] The legal basis for processing the NHS Digital data under GDPR is Article 6 (1)(e) - "processing is necessary for the performance of a task in the public interest or in the exercise of official authority vested in the controller" and Article 9(2)(j) - "processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes".

Benefits reported

Stated in the previous version and removed here.

Yielded Benefits is not a requirement for new applications.

Unchanged: Processing activities, Expected output, Expected measurable benefits.