Pub Date : 2019-09-16DOI: 10.1136/bmjqs-2019-009950
Tanya T. Olmos-Ochoa, D. Ganz, Jenny M. Barnard, Lauren S. Penney, Neetu Chawla
Practice transformation efforts in healthcare, like the patient-centred medical home model in primary care, have spurred the development of multiple quality improvement (QI) and implementation strategies to support effective change. Nonetheless, uncertainty about how to implement and sustain change in complex healthcare settings1 2 continues to pose significant challenges. Even when practices are receptive,3 limited QI expertise, constrained resources,4 and associated staff morale and burnout5 can impact success. Although efforts among clinicians to improve primary care by embracing a culture of QI continue,6 healthcare systems are increasingly hiring additional personnel, like practice facilitators, with key performance improvement skills to promote and support change.7 However skilled, practice facilitators cannot implement change alone. Their primary function is to enable transformation by activating the healthcare context, the innovation being implemented and the actors implementing the innovation towards successful implementation of practice improvements.8 9 Compared with other individuals participating in QI efforts (eg, quality managers), facilitators are typically appointed to their role by the organisation’s leadership, have been formally trained in QI, and have project-specific content knowledge and varying levels of facilitation experience (novice to expert).10–12 Facilitators can be internal or external to the organisation and typically support change by engaging teams in activities like task management, process monitoring, relationship building, motivation and accountability checks,13 14 during inperson or distance-based (phone or video) encounters. Successful facilitators tailor the innovation to the local context, effectively integrate into the team responsible for QI, push through resistance from recipients of the innovation and remain flexible.15 Providing this type of facilitation in a dynamic (and sometimes dysfunctional) context can be emotionally and mentally taxing, with facilitators risking the same work-related stress and emotional exhaustion (burnout) as the healthcare staff they support,16 potentially defeating the purpose of facilitation. …
{"title":"Sustaining effective quality improvement: building capacity for resilience in the practice facilitator workforce","authors":"Tanya T. Olmos-Ochoa, D. Ganz, Jenny M. Barnard, Lauren S. Penney, Neetu Chawla","doi":"10.1136/bmjqs-2019-009950","DOIUrl":"https://doi.org/10.1136/bmjqs-2019-009950","url":null,"abstract":"Practice transformation efforts in healthcare, like the patient-centred medical home model in primary care, have spurred the development of multiple quality improvement (QI) and implementation strategies to support effective change. Nonetheless, uncertainty about how to implement and sustain change in complex healthcare settings1 2 continues to pose significant challenges. Even when practices are receptive,3 limited QI expertise, constrained resources,4 and associated staff morale and burnout5 can impact success. Although efforts among clinicians to improve primary care by embracing a culture of QI continue,6 healthcare systems are increasingly hiring additional personnel, like practice facilitators, with key performance improvement skills to promote and support change.7 \u0000\u0000However skilled, practice facilitators cannot implement change alone. Their primary function is to enable transformation by activating the healthcare context, the innovation being implemented and the actors implementing the innovation towards successful implementation of practice improvements.8 9 Compared with other individuals participating in QI efforts (eg, quality managers), facilitators are typically appointed to their role by the organisation’s leadership, have been formally trained in QI, and have project-specific content knowledge and varying levels of facilitation experience (novice to expert).10–12 Facilitators can be internal or external to the organisation and typically support change by engaging teams in activities like task management, process monitoring, relationship building, motivation and accountability checks,13 14 during inperson or distance-based (phone or video) encounters. Successful facilitators tailor the innovation to the local context, effectively integrate into the team responsible for QI, push through resistance from recipients of the innovation and remain flexible.15 Providing this type of facilitation in a dynamic (and sometimes dysfunctional) context can be emotionally and mentally taxing, with facilitators risking the same work-related stress and emotional exhaustion (burnout) as the healthcare staff they support,16 potentially defeating the purpose of facilitation. …","PeriodicalId":49653,"journal":{"name":"Quality & Safety in Health Care","volume":"28 1","pages":"1016 - 1020"},"PeriodicalIF":0.0,"publicationDate":"2019-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/bmjqs-2019-009950","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49154856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-13DOI: 10.1136/bmjqs-2019-009739
N. Kurek, A. Darzi
We all grow old. Even surgeons. We slow down, we weaken and our skills diminish. Although individuals differ and chronological age may not be an accurate guide to biological age, we cannot hold back the advancing years. How long should we allow surgeons to keep operating? If public safety is the priority, as it must be, should there be a mandatory retirement age, as there is for pilots in the airline industry? Or is there a fair and equitable way of assessing those nearing the end of their career to ensure their competency is maintained? The ageing surgeon poses daunting challenges. For the individuals concerned, the idea of ageing may trigger fears about loss of status, identity and livelihood. Patients may worry about the quality of their care. For healthcare systems struggling to meet growing demand, this issue raises questions about capacity. Medical regulators in Australia and Canada are implementing additional checks on doctors from the age of 70 years,1 2 but most countries have no mandatory retirement age for surgeons and those where it once existed have moved away from such a prescribed approach.3 Globally, the surgical workforce is ageing, with figures of those above 65 years ranging from as high as 25% in the USA,4 and 19% in Australia and New Zealand,5 to 9% in the UK.6 Cognitive decline is evident in older surgeons, as in ageing adults generally. The 2008 Cognitive Changes and Retirement among Senior Surgeons study found a deterioration in attention, reaction time, memory and sensory changes in vision, visual processing speed and hearing.7 A further study, however, found the decline was slower in surgeons than in age-matched controls.8 Importantly though, the assessment in that study did not encompass all surgical skills. Some studies have shown that older …
{"title":"The ageing surgeon","authors":"N. Kurek, A. Darzi","doi":"10.1136/bmjqs-2019-009739","DOIUrl":"https://doi.org/10.1136/bmjqs-2019-009739","url":null,"abstract":"We all grow old. Even surgeons. We slow down, we weaken and our skills diminish. Although individuals differ and chronological age may not be an accurate guide to biological age, we cannot hold back the advancing years.\u0000\u0000How long should we allow surgeons to keep operating? If public safety is the priority, as it must be, should there be a mandatory retirement age, as there is for pilots in the airline industry? Or is there a fair and equitable way of assessing those nearing the end of their career to ensure their competency is maintained?\u0000\u0000The ageing surgeon poses daunting challenges. For the individuals concerned, the idea of ageing may trigger fears about loss of status, identity and livelihood. Patients may worry about the quality of their care. For healthcare systems struggling to meet growing demand, this issue raises questions about capacity.\u0000\u0000Medical regulators in Australia and Canada are implementing additional checks on doctors from the age of 70 years,1 2 but most countries have no mandatory retirement age for surgeons and those where it once existed have moved away from such a prescribed approach.3 Globally, the surgical workforce is ageing, with figures of those above 65 years ranging from as high as 25% in the USA,4 and 19% in Australia and New Zealand,5 to 9% in the UK.6 Cognitive decline is evident in older surgeons, as in ageing adults generally. The 2008 Cognitive Changes and Retirement among Senior Surgeons study found a deterioration in attention, reaction time, memory and sensory changes in vision, visual processing speed and hearing.7 A further study, however, found the decline was slower in surgeons than in age-matched controls.8 Importantly though, the assessment in that study did not encompass all surgical skills.\u0000\u0000Some studies have shown that older …","PeriodicalId":49653,"journal":{"name":"Quality & Safety in Health Care","volume":"29 1","pages":"95 - 97"},"PeriodicalIF":0.0,"publicationDate":"2019-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/bmjqs-2019-009739","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44745542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-13DOI: 10.1136/bmjqs-2019-010018
A. Sheikh
There is now widespread awareness of the very considerable burden of harm and associated costs resulting from medication errors, which, in turn, has stimulated national and international drives to reduce medication-associated harm. In parallel, there is a growing appreciation that health information technology (HIT) has the potential to reduce the risk of medication errors. There is, however, a wide gulf between HIT as a structural intervention and its translation into improvements in care processes , and a wider gulf still between the process of care and improvements in health outcomes .1 What matters to patients, and their loved ones, is of course avoidance of actual harm and it is for this reason that the WHO, in launching its Third Global Safety Challenge, called it ‘Medication Without Harm’.2 Governments across the world are investing substantial sums of money in moving care from paper-based records to electronic health record (EHR) infrastructures. A key driver for this move is the belief that this will result in substantial improvements in patient safety.3 A high frequency of medication errors and preventable adverse drug events have been documented in many studies of patient safety problems, making medication safety an obvious place to start. Yet, the analysis by Holmgren et al reported in this edition demonstrates that current EHRs would fail to prevent over one-third of potentially serious medication errors in a sample of 1527 hospitals in the USA.4 …
{"title":"Realising the potential of health information technology to enhance medication safety","authors":"A. Sheikh","doi":"10.1136/bmjqs-2019-010018","DOIUrl":"https://doi.org/10.1136/bmjqs-2019-010018","url":null,"abstract":"There is now widespread awareness of the very considerable burden of harm and associated costs resulting from medication errors, which, in turn, has stimulated national and international drives to reduce medication-associated harm. In parallel, there is a growing appreciation that health information technology (HIT) has the potential to reduce the risk of medication errors. There is, however, a wide gulf between HIT as a structural intervention and its translation into improvements in care processes , and a wider gulf still between the process of care and improvements in health outcomes .1 What matters to patients, and their loved ones, is of course avoidance of actual harm and it is for this reason that the WHO, in launching its Third Global Safety Challenge, called it ‘Medication Without Harm’.2 \u0000\u0000Governments across the world are investing substantial sums of money in moving care from paper-based records to electronic health record (EHR) infrastructures. A key driver for this move is the belief that this will result in substantial improvements in patient safety.3 A high frequency of medication errors and preventable adverse drug events have been documented in many studies of patient safety problems, making medication safety an obvious place to start. Yet, the analysis by Holmgren et al reported in this edition demonstrates that current EHRs would fail to prevent over one-third of potentially serious medication errors in a sample of 1527 hospitals in the USA.4 …","PeriodicalId":49653,"journal":{"name":"Quality & Safety in Health Care","volume":"29 1","pages":"7 - 9"},"PeriodicalIF":0.0,"publicationDate":"2019-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/bmjqs-2019-010018","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47681271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-13DOI: 10.1136/bmjqs-2019-009658
Emily L Kearsley-Ho, Hsin Yun Yang, S. Karunananthan, C. Laur, J. Grimshaw, N. Ivers
Health systems invest in diabetes quality improvement (QI) programmes to reduce the gap between research evidence of optimal care and current care.1 Examples of commonly used QI strategies in diabetes include programmes to measure and report quality of care (ie, audit and feedback initiatives), implementation of clinician and patient education, and reminder systems. A recent systematic review of randomised trials of QI programmes indicates that they can successfully improve quality of diabetes care and patient outcomes.2 Changes in surrogate markers such as blood glucose control, blood pressure or cholesterol levels are used to measure QI intervention effectiveness.2 However, investments in QI strategies are only worthwhile if the programmes that effectively improve care are sustained after trial completion.3 Failure to maintain QI programmes contributes to substantial research waste, resulting in suboptimal patient care since the effective interventions are not available.4 5 Furthermore, failure to redirect resources from ineffective programmes creates opportunity cost. To date, no studies have examined the sustainability of rigorously evaluated diabetes QI programmes. The objective of this study is to explore factors associated with sustained implementation of diabetes QI programmes after cessation of their research funding. In 2018, we emailed the authors of 226 trials on diabetes QI programmes and requested them to complete an online survey about their perceived sustainability of their intervention. These trials were published between 2004 and …
{"title":"When do trials of diabetes quality improvement strategies lead to sustained change in patient care?","authors":"Emily L Kearsley-Ho, Hsin Yun Yang, S. Karunananthan, C. Laur, J. Grimshaw, N. Ivers","doi":"10.1136/bmjqs-2019-009658","DOIUrl":"https://doi.org/10.1136/bmjqs-2019-009658","url":null,"abstract":"Health systems invest in diabetes quality improvement (QI) programmes to reduce the gap between research evidence of optimal care and current care.1 Examples of commonly used QI strategies in diabetes include programmes to measure and report quality of care (ie, audit and feedback initiatives), implementation of clinician and patient education, and reminder systems. A recent systematic review of randomised trials of QI programmes indicates that they can successfully improve quality of diabetes care and patient outcomes.2 Changes in surrogate markers such as blood glucose control, blood pressure or cholesterol levels are used to measure QI intervention effectiveness.2\u0000\u0000However, investments in QI strategies are only worthwhile if the programmes that effectively improve care are sustained after trial completion.3 Failure to maintain QI programmes contributes to substantial research waste, resulting in suboptimal patient care since the effective interventions are not available.4 5 Furthermore, failure to redirect resources from ineffective programmes creates opportunity cost. To date, no studies have examined the sustainability of rigorously evaluated diabetes QI programmes. The objective of this study is to explore factors associated with sustained implementation of diabetes QI programmes after cessation of their research funding.\u0000\u0000In 2018, we emailed the authors of 226 trials on diabetes QI programmes and requested them to complete an online survey about their perceived sustainability of their intervention. These trials were published between 2004 and …","PeriodicalId":49653,"journal":{"name":"Quality & Safety in Health Care","volume":"29 1","pages":"774 - 776"},"PeriodicalIF":0.0,"publicationDate":"2019-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/bmjqs-2019-009658","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49627631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-12DOI: 10.1136/bmjqs-2019-009537
T. Stephens, C. Peden, R. Haines, M. Grocott, D. Murray, D. Cromwell, C. Johnston, S. Hare, J. Lourtie, S. Drake, G. Martin, R. Pearse
Background and objectives A clinical trial in 93 National Health Service hospitals evaluated a quality improvement programme for emergency abdominal surgery, designed to improve mortality by improving the patient care pathway. Large variation was observed in implementation approaches, and the main trial result showed no mortality reduction. Our objective therefore was to evaluate whether trial participation led to care pathway implementation and to study the relationship between care pathway implementation and use of six recommended implementation strategies. Methods We performed a hospital-level time-series analysis using data from the Enhanced Peri-Operative Care for High-risk patients trial. Care pathway implementation was defined as achievement of >80% median reliability in 10 measured care processes. Mean monthly process performance was plotted on run charts. Process improvement was defined as an observed run chart signal, using probability-based ‘shift’ and ‘runs’ rules. A new median performance level was calculated after an observed signal. Results Of 93 participating hospitals, 80 provided sufficient data for analysis, generating 800 process measure charts from 20 305 patient admissions over 27 months. No hospital reliably implemented all 10 processes. Overall, only 279 of the 800 processes were improved (3 (2–5) per hospital) and 14/80 hospitals improved more than six processes. Mortality risk documented (57/80 (71%)), lactate measurement (42/80 (53%)) and cardiac output guided fluid therapy (32/80 (40%)) were most frequently improved. Consultant-led decision making (14/80 (18%)), consultant review before surgery (17/80 (21%)) and time to surgery (14/80 (18%)) were least frequently improved. In hospitals using ≥5 implementation strategies, 9/30 (30%) hospitals improved ≥6 care processes compared with 0/11 hospitals using ≤2 implementation strategies. Conclusion Only a small number of hospitals improved more than half of the measured care processes, more often when at least five of six implementation strategies were used. In a longer term project, this understanding may have allowed us to adapt the intervention to be effective in more hospitals.
{"title":"Hospital-level evaluation of the effect of a national quality improvement programme: time-series analysis of registry data","authors":"T. Stephens, C. Peden, R. Haines, M. Grocott, D. Murray, D. Cromwell, C. Johnston, S. Hare, J. Lourtie, S. Drake, G. Martin, R. Pearse","doi":"10.1136/bmjqs-2019-009537","DOIUrl":"https://doi.org/10.1136/bmjqs-2019-009537","url":null,"abstract":"Background and objectives A clinical trial in 93 National Health Service hospitals evaluated a quality improvement programme for emergency abdominal surgery, designed to improve mortality by improving the patient care pathway. Large variation was observed in implementation approaches, and the main trial result showed no mortality reduction. Our objective therefore was to evaluate whether trial participation led to care pathway implementation and to study the relationship between care pathway implementation and use of six recommended implementation strategies. Methods We performed a hospital-level time-series analysis using data from the Enhanced Peri-Operative Care for High-risk patients trial. Care pathway implementation was defined as achievement of >80% median reliability in 10 measured care processes. Mean monthly process performance was plotted on run charts. Process improvement was defined as an observed run chart signal, using probability-based ‘shift’ and ‘runs’ rules. A new median performance level was calculated after an observed signal. Results Of 93 participating hospitals, 80 provided sufficient data for analysis, generating 800 process measure charts from 20 305 patient admissions over 27 months. No hospital reliably implemented all 10 processes. Overall, only 279 of the 800 processes were improved (3 (2–5) per hospital) and 14/80 hospitals improved more than six processes. Mortality risk documented (57/80 (71%)), lactate measurement (42/80 (53%)) and cardiac output guided fluid therapy (32/80 (40%)) were most frequently improved. Consultant-led decision making (14/80 (18%)), consultant review before surgery (17/80 (21%)) and time to surgery (14/80 (18%)) were least frequently improved. In hospitals using ≥5 implementation strategies, 9/30 (30%) hospitals improved ≥6 care processes compared with 0/11 hospitals using ≤2 implementation strategies. Conclusion Only a small number of hospitals improved more than half of the measured care processes, more often when at least five of six implementation strategies were used. In a longer term project, this understanding may have allowed us to adapt the intervention to be effective in more hospitals.","PeriodicalId":49653,"journal":{"name":"Quality & Safety in Health Care","volume":"29 1","pages":"623 - 635"},"PeriodicalIF":0.0,"publicationDate":"2019-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/bmjqs-2019-009537","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48391220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-09DOI: 10.1136/bmjqs-2019-009732
L. Aiken, D. Sloane
Empirical evidence from many published studies indicates that better hospital professional registered nurse (RN) staffing is associated with better patient outcomes, including lower mortality and failure to rescue, shorter lengths of stay, fewer readmissions, fewer complications, higher patient satisfaction and more favourable reports from patients and nurses alike related to quality of care and patient safety.1–10 There are nonetheless lingering questions and concerns about these studies and the evidence they provide. In this issue of BMJ Quality & Safety , Needleman et al 11 allude to some potentially important ones in their introduction to their paper, including making causal inferences from cross-sectional studies, the absence of evidence on whether there is an optimal level of staffing or some level of minimally acceptable staffing below which nurses are unable to deliver high-quality and safe care, the absence of measures of work environment and its impact in many studies and whether the greater or lesser presence of nursing support staff affects patient outcomes independent of, or that acts in conjunction with, the level of RN staffing. With this study by Needleman and colleagues, BMJ Quality & Safety has now published three recent papers on the outcomes of hospital nurse staffing11–13 that are responsive in different ways to some of the lingering questions about the outcomes of nurse staffing and their implications for policies and managerial decisions about investments in nursing personnel to achieve the greatest value. The first paper in the series by RN4CAST researchers12 used unique cross-sectional data to study the outcomes of variation in nurse staffing in 243 hospitals in six European countries. The outcomes included were mortality among patients who had undergone common surgical procedures, patients’ ratings of their hospitals, nurses’ assessments of quality of care and adverse care outcomes, and nurse burnout and job dissatisfaction. …
{"title":"Nurses matter: more evidence","authors":"L. Aiken, D. Sloane","doi":"10.1136/bmjqs-2019-009732","DOIUrl":"https://doi.org/10.1136/bmjqs-2019-009732","url":null,"abstract":"Empirical evidence from many published studies indicates that better hospital professional registered nurse (RN) staffing is associated with better patient outcomes, including lower mortality and failure to rescue, shorter lengths of stay, fewer readmissions, fewer complications, higher patient satisfaction and more favourable reports from patients and nurses alike related to quality of care and patient safety.1–10 There are nonetheless lingering questions and concerns about these studies and the evidence they provide. In this issue of BMJ Quality & Safety , Needleman et al 11 allude to some potentially important ones in their introduction to their paper, including making causal inferences from cross-sectional studies, the absence of evidence on whether there is an optimal level of staffing or some level of minimally acceptable staffing below which nurses are unable to deliver high-quality and safe care, the absence of measures of work environment and its impact in many studies and whether the greater or lesser presence of nursing support staff affects patient outcomes independent of, or that acts in conjunction with, the level of RN staffing.\u0000\u0000With this study by Needleman and colleagues, BMJ Quality & Safety has now published three recent papers on the outcomes of hospital nurse staffing11–13 that are responsive in different ways to some of the lingering questions about the outcomes of nurse staffing and their implications for policies and managerial decisions about investments in nursing personnel to achieve the greatest value. The first paper in the series by RN4CAST researchers12 used unique cross-sectional data to study the outcomes of variation in nurse staffing in 243 hospitals in six European countries. The outcomes included were mortality among patients who had undergone common surgical procedures, patients’ ratings of their hospitals, nurses’ assessments of quality of care and adverse care outcomes, and nurse burnout and job dissatisfaction. …","PeriodicalId":49653,"journal":{"name":"Quality & Safety in Health Care","volume":"29 1","pages":"1 - 3"},"PeriodicalIF":0.0,"publicationDate":"2019-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/bmjqs-2019-009732","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43504976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-05DOI: 10.1136/bmjqs-2019-009830
G. Elwyn, E. Nelson, A. Hager, A. Price
If the core aim of a healthcare system is to minimise both illness and treatment burden while reducing the costs of care delivery, then we must accept, however reluctantly, that our efforts are largely failing. Life expectancy in highly developed countries is declining for the first time in decades. Long-term conditions and obesity are replacing infectious diseases as the most prominent health problems in developing nations. Meanwhile, average per capita healthcare expenditures are increasing despite efforts to restrain them. For example, in the USA, the average per capita healthcare expenditures are approaching $10 000 a year and consuming over 18% of its gross domestic product. Innovations in biomedicine, information technology and healthcare delivery systems may help address some of the challenges, but instead of containing costs these innovations tend to expand services. There are indications that interest in a concept called coproduction in healthcare is increasing. The core thesis is that by leveraging professional and end user collaboration, patients can be supported to contribute more to the management of their own conditions. This is especially true when dealing with long-term conditions, where supporting the person to learn how best to reduce the burden of both illness and treatment is an undisputed good. The goal is to cocreate value. Ostrom,1 based on her seminal work as an economist, called this coproduction . The cocreation of value already lies at the heart of most service sectors. Shopping, banking and travel all enlist the end user to coproduce value in the delivery of services. Coproduction can be even more powerful where people form alliances to share resources and generate solutions, by using what Christensen et al 2 refer to as ‘facilitated networks’. Facilitated networks offer a powerful strategy that has been adopted by many organisations to increase access, and to improve quality while …
{"title":"Coproduction: when users define quality","authors":"G. Elwyn, E. Nelson, A. Hager, A. Price","doi":"10.1136/bmjqs-2019-009830","DOIUrl":"https://doi.org/10.1136/bmjqs-2019-009830","url":null,"abstract":"If the core aim of a healthcare system is to minimise both illness and treatment burden while reducing the costs of care delivery, then we must accept, however reluctantly, that our efforts are largely failing.\u0000\u0000Life expectancy in highly developed countries is declining for the first time in decades. Long-term conditions and obesity are replacing infectious diseases as the most prominent health problems in developing nations. Meanwhile, average per capita healthcare expenditures are increasing despite efforts to restrain them. For example, in the USA, the average per capita healthcare expenditures are approaching $10 000 a year and consuming over 18% of its gross domestic product. Innovations in biomedicine, information technology and healthcare delivery systems may help address some of the challenges, but instead of containing costs these innovations tend to expand services.\u0000\u0000There are indications that interest in a concept called coproduction in healthcare is increasing. The core thesis is that by leveraging professional and end user collaboration, patients can be supported to contribute more to the management of their own conditions. This is especially true when dealing with long-term conditions, where supporting the person to learn how best to reduce the burden of both illness and treatment is an undisputed good. The goal is to cocreate value. Ostrom,1 based on her seminal work as an economist, called this coproduction .\u0000\u0000The cocreation of value already lies at the heart of most service sectors. Shopping, banking and travel all enlist the end user to coproduce value in the delivery of services. Coproduction can be even more powerful where people form alliances to share resources and generate solutions, by using what Christensen et al 2 refer to as ‘facilitated networks’. Facilitated networks offer a powerful strategy that has been adopted by many organisations to increase access, and to improve quality while …","PeriodicalId":49653,"journal":{"name":"Quality & Safety in Health Care","volume":"29 1","pages":"711 - 716"},"PeriodicalIF":0.0,"publicationDate":"2019-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/bmjqs-2019-009830","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48400029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-03DOI: 10.1136/bmjqs-2019-009858
V. Major, Y. Aphinyanaphongs
Despite advances in medicine, prognostication remains inaccurate for many patients. Physicians tend to overestimate survival, even in advanced cancer and terminal illness groups.1–3 Over half of terminally ill patients express they do not want prolonging of life if their quality of life would decline.4 End-of-life interventions such as advanced care planning have shown improved adherence to patient’s wishes, improvement in satisfaction and reductions in stress, anxiety and depression,5 but clinicians remain reluctant to initiate end-of-life discussions with terminal patients if they are currently asymptomatic.6 Automated systems can complement clinician judgement to prompt earlier end-of-life discussions. To this end, predictive analytics is potentially impactful. Many different approaches have been used to estimate mortality risk using factors including severity of illness,7 healthcare utilisation8 or comorbidities.9 However, few works focus on palliative or end-of-life care (PEOLC), and even fewer have translated beyond model validation into prospective testing ultimately affecting clinical care. Instead, PEOLC remains reliant on clinical staff, despite their optimism, for initiation and prioritisation. The paper by Wegier and colleagues10 in this issue introduces a new 1-year mortality score—modified Hospitalised-patient One-year Mortality Risk (mHOMR)—designed for broad application at the time of admission. They incorporate mHOMR into two electronic health records (EHRs) to automatically identify patients who may benefit from palliative assessment. Of concern, there is evidence of patient distributional shift at the one site that showed improvement with the intervention. The authors conclude there was an increase in patients who receive palliative care consultations or goals-of-care discussions. However, the preintervention group appears much healthier, with a 3% in-hospital mortality, compared with the postintervention group (16%). Relatedly, a concomitant shift in patient mix to fewer frail patients is reported (68/100 to 43/97, p=0.001; Pearson’s χ2 test with Yates’ continuity correction). It is possible, therefore, …
尽管医学取得了进步，但对许多病人来说，预后仍然不准确。医生往往高估患者的存活率，即使是晚期癌症和绝症患者。超过一半的绝症患者表示，如果他们的生活质量会下降，他们不希望延长生命临终干预措施，如高级护理计划，已经显示出对患者意愿的坚持，满意度的提高，压力、焦虑和抑郁的减少，但临床医生仍然不愿意与目前无症状的临终患者进行临终讨论自动化系统可以补充临床医生的判断，促进早期的临终讨论。为此，预测分析具有潜在的影响力。许多不同的方法已被用于估计死亡率风险，使用的因素包括疾病的严重程度、保健利用或合并症然而，很少有研究关注缓和或临终关怀(PEOLC)，甚至更少的研究将模型验证转化为最终影响临床护理的前瞻性测试。相反，PEOLC仍然依赖于临床工作人员，尽管他们乐观，启动和优先排序。Wegier及其同事在本期杂志上发表的论文10介绍了一种新的1年死亡率评分方法——修改后的住院患者1年死亡率风险(mHOMR)——旨在广泛应用于入院时。他们将mHOMR纳入两份电子健康记录(EHRs)，以自动识别可能受益于姑息性评估的患者。值得关注的是，有证据表明，在一个部位的患者分布发生了变化，这表明干预有所改善。作者得出结论，接受姑息治疗咨询或护理目标讨论的患者有所增加。然而，与干预后组(16%)相比，干预前组似乎健康得多，住院死亡率为3%。与此相关，有报道称患者组合中虚弱患者数量减少(68/100至43/97,p=0.001;Pearson ' s χ2检验(Yates '连续性校正)。因此，有可能……
{"title":"Challenges in translating mortality risk to the point of care","authors":"V. Major, Y. Aphinyanaphongs","doi":"10.1136/bmjqs-2019-009858","DOIUrl":"https://doi.org/10.1136/bmjqs-2019-009858","url":null,"abstract":"Despite advances in medicine, prognostication remains inaccurate for many patients. Physicians tend to overestimate survival, even in advanced cancer and terminal illness groups.1–3 Over half of terminally ill patients express they do not want prolonging of life if their quality of life would decline.4 End-of-life interventions such as advanced care planning have shown improved adherence to patient’s wishes, improvement in satisfaction and reductions in stress, anxiety and depression,5 but clinicians remain reluctant to initiate end-of-life discussions with terminal patients if they are currently asymptomatic.6 Automated systems can complement clinician judgement to prompt earlier end-of-life discussions.\u0000\u0000To this end, predictive analytics is potentially impactful. Many different approaches have been used to estimate mortality risk using factors including severity of illness,7 healthcare utilisation8 or comorbidities.9 However, few works focus on palliative or end-of-life care (PEOLC), and even fewer have translated beyond model validation into prospective testing ultimately affecting clinical care. Instead, PEOLC remains reliant on clinical staff, despite their optimism, for initiation and prioritisation.\u0000\u0000The paper by Wegier and colleagues10 in this issue introduces a new 1-year mortality score—modified Hospitalised-patient One-year Mortality Risk (mHOMR)—designed for broad application at the time of admission. They incorporate mHOMR into two electronic health records (EHRs) to automatically identify patients who may benefit from palliative assessment. Of concern, there is evidence of patient distributional shift at the one site that showed improvement with the intervention. The authors conclude there was an increase in patients who receive palliative care consultations or goals-of-care discussions. However, the preintervention group appears much healthier, with a 3% in-hospital mortality, compared with the postintervention group (16%). Relatedly, a concomitant shift in patient mix to fewer frail patients is reported (68/100 to 43/97, p=0.001; Pearson’s χ2 test with Yates’ continuity correction). It is possible, therefore, …","PeriodicalId":49653,"journal":{"name":"Quality & Safety in Health Care","volume":"21 1","pages":"959 - 962"},"PeriodicalIF":0.0,"publicationDate":"2019-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/bmjqs-2019-009858","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41304061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-31DOI: 10.1136/bmjqs-2018-009032
E. Pfoh, Kathryn A. Martinez, Nirav Vakharia, M. Rothberg
Objective To assess the impact of a quality improvement programme on blood pressure (BP) control and determine whether medication intensification or repeated measurement improved control. Design Retrospective cohort comparing visits in 2015 to visits in 2016 (when the programme started). Subjects Adults with ≥1 primary care visit between January and June in 2015 and 2016 and a diagnosis of hypertension in a large integrated health system. Measures Elevated BP was defined as a BP ≥140/90 mm Hg. Physician response was defined as: nothing; BP recheck within 30 days; or medication intensification within 30 days. Our outcome was BP control (<140/90 mm Hg) at the last visit of the year. We used a multilevel logistic regression model (adjusted for demographic and clinical variables) to identify the effect of the programme on the odds of BP control. Results Our cohort included 111 867 adults. Control increased from 72% in 2015 to 79% in 2016 (p<0.01). The average percentage of visits with elevated blood pressure was 31% in 2015 and 25% in 2016 (p<0.01). During visits with an elevated BP, physicians were more likely to intensify medication in 2016 than in 2015 (43% vs 40%, p<0.01) and slightly more likely to obtain a BP recheck (15% vs 14%, p<0.01). Among patients with ≥1 elevated BP who attained control by the last visit in the year, there was 6% increase from 2015 to 2016 in the percentage of patients who received at least one medication intensification during the year and a 1% increase in BP rechecks. The adjusted odds of the last BP reading being categorised as controlled was 59% higher in 2016 than in 2015 (95% CI 1.54 to 1.64). Conclusion A system-wide initiative can improve BP control, primarily through medication intensification.
{"title":"Impact of a system-wide quality improvement initiative on blood pressure control: a cohort analysis","authors":"E. Pfoh, Kathryn A. Martinez, Nirav Vakharia, M. Rothberg","doi":"10.1136/bmjqs-2018-009032","DOIUrl":"https://doi.org/10.1136/bmjqs-2018-009032","url":null,"abstract":"Objective To assess the impact of a quality improvement programme on blood pressure (BP) control and determine whether medication intensification or repeated measurement improved control. Design Retrospective cohort comparing visits in 2015 to visits in 2016 (when the programme started). Subjects Adults with ≥1 primary care visit between January and June in 2015 and 2016 and a diagnosis of hypertension in a large integrated health system. Measures Elevated BP was defined as a BP ≥140/90 mm Hg. Physician response was defined as: nothing; BP recheck within 30 days; or medication intensification within 30 days. Our outcome was BP control (<140/90 mm Hg) at the last visit of the year. We used a multilevel logistic regression model (adjusted for demographic and clinical variables) to identify the effect of the programme on the odds of BP control. Results Our cohort included 111 867 adults. Control increased from 72% in 2015 to 79% in 2016 (p<0.01). The average percentage of visits with elevated blood pressure was 31% in 2015 and 25% in 2016 (p<0.01). During visits with an elevated BP, physicians were more likely to intensify medication in 2016 than in 2015 (43% vs 40%, p<0.01) and slightly more likely to obtain a BP recheck (15% vs 14%, p<0.01). Among patients with ≥1 elevated BP who attained control by the last visit in the year, there was 6% increase from 2015 to 2016 in the percentage of patients who received at least one medication intensification during the year and a 1% increase in BP rechecks. The adjusted odds of the last BP reading being categorised as controlled was 59% higher in 2016 than in 2015 (95% CI 1.54 to 1.64). Conclusion A system-wide initiative can improve BP control, primarily through medication intensification.","PeriodicalId":49653,"journal":{"name":"Quality & Safety in Health Care","volume":"29 1","pages":"225 - 231"},"PeriodicalIF":0.0,"publicationDate":"2019-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/bmjqs-2018-009032","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47817882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-24DOI: 10.1136/bmjqs-2019-009456
Oyvind Bjertnaes, H. Iversen, K. Skyrud, Kirsten Danielsen
Objectives The objective was to assess the possibility of using a combination of official and unofficial Facebook ratings and comments as a basis for nation-wide hospital quality assessments in Norway. Methods All hospitals from a national cross-sectional patient experience survey in 2015 were matched with corresponding Facebook ratings. Facebook ratings were correlated with both case-mix adjusted and unadjusted patient-reported experience scores, with separate analysis for hospitals with official site ratings and hospitals with unofficial site ratings. Facebook ratings were also correlated with patient-reported incident scores, hospital size, 30-day mortality and 30-day readmission. Facebook comments from 20 randomly selected hospitals were analysed, contrasting the content and sentiments of official versus unofficial Facebook pages. Results Facebook ratings were significantly correlated with most patient-reported indicators, with the highest correlations relating to unadjusted scores for organisation (0.60, p<0.000) and nursing services (0.57, p<0.000). Facebook ratings were significantly correlated with hospital size (−0.40, p=0.003) and 30-day mortality (0.31, p=0.040). Sentiment analysis showed that 84.7% of the comments from unofficial Facebook sites included neutral comments that did not give any specific description of experiences of the quality of care at the hospital. Content analysis identified common themes on official and unofficial Facebook pages. Conclusions Facebook ratings were associated with patient-reported indicators, hospital size, and 30-day mortality. Qualitative comments from official Facebook are more relevant for hospital evaluation than unofficial sites. More research is needed on using Facebook ratings as a standalone indicator of patient experiences in national quality measurement, and such ratings should be reported together with research-based patient experience indicators and with explicit criteria for the inclusion of unofficial sites.
{"title":"The value of Facebook in nation-wide hospital quality assessment: a national mixed-methods study in Norway","authors":"Oyvind Bjertnaes, H. Iversen, K. Skyrud, Kirsten Danielsen","doi":"10.1136/bmjqs-2019-009456","DOIUrl":"https://doi.org/10.1136/bmjqs-2019-009456","url":null,"abstract":"Objectives The objective was to assess the possibility of using a combination of official and unofficial Facebook ratings and comments as a basis for nation-wide hospital quality assessments in Norway. Methods All hospitals from a national cross-sectional patient experience survey in 2015 were matched with corresponding Facebook ratings. Facebook ratings were correlated with both case-mix adjusted and unadjusted patient-reported experience scores, with separate analysis for hospitals with official site ratings and hospitals with unofficial site ratings. Facebook ratings were also correlated with patient-reported incident scores, hospital size, 30-day mortality and 30-day readmission. Facebook comments from 20 randomly selected hospitals were analysed, contrasting the content and sentiments of official versus unofficial Facebook pages. Results Facebook ratings were significantly correlated with most patient-reported indicators, with the highest correlations relating to unadjusted scores for organisation (0.60, p<0.000) and nursing services (0.57, p<0.000). Facebook ratings were significantly correlated with hospital size (−0.40, p=0.003) and 30-day mortality (0.31, p=0.040). Sentiment analysis showed that 84.7% of the comments from unofficial Facebook sites included neutral comments that did not give any specific description of experiences of the quality of care at the hospital. Content analysis identified common themes on official and unofficial Facebook pages. Conclusions Facebook ratings were associated with patient-reported indicators, hospital size, and 30-day mortality. Qualitative comments from official Facebook are more relevant for hospital evaluation than unofficial sites. More research is needed on using Facebook ratings as a standalone indicator of patient experiences in national quality measurement, and such ratings should be reported together with research-based patient experience indicators and with explicit criteria for the inclusion of unofficial sites.","PeriodicalId":49653,"journal":{"name":"Quality & Safety in Health Care","volume":"29 1","pages":"217 - 224"},"PeriodicalIF":0.0,"publicationDate":"2019-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1136/bmjqs-2019-009456","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46578046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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