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Liu M, Guo R, Li J, Wang C, Yu L, Liu M. Process indicators outshine outcome measures: assessing hospital quality of care in breast cancer treatment in China. Sci Rep 2024; 14:19137. [PMID: 39160221 PMCID: PMC11333708 DOI: 10.1038/s41598-024-70474-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Accepted: 08/16/2024] [Indexed: 08/21/2024] Open
Abstract
Reporting the results of quality indicators can narrow the gap in the quality of care between hospitals. While most studies rely on outcome indicators, they may not accurately measure the quality of care. Process indicators are not only strongly associated with treatment outcomes, but are also more sensitive to whether patients are treated accurately, enabling timely intervention. Our study aims to investigate whether process indicators provide a more reasonable assessment of hospital quality of care compared to outcome indicators. Data were sourced from the Specific Disease Medical Service Quality Management and Control System in China. A total of 113,942 patients with breast cancer treated in 298 hospitals between January 2019 and April 2023 were included in this retrospective study. The rankability of 11 process indicators was calculated and used as a weight to create a new composite indicator. The composite indicators and outcome measures were compared using the O/E ratio categories. Finally, in order to determine the impact of different years on the results, a sensitivity analysis was conducted using bootstrap sampling. The rankability ( ρ ) values of the eleven process indicators showed significant differences, with the highest ρ value for preoperative cytological or histological examination before surgery (0.919). The ρ value for the outcome indicator was 0.011. The rankability-weighting method yielded a comprehensive score ( ρ = 0.883). The comparison with categorical results of the outcome indicator has different performance classifications for 113 hospitals (37.92%) for composite scores and 140 (46.98%) for preoperative cytological or histological examinationbefore surgery. Process indicators are more suitable than outcome indicators for assessing the quality of breast cancer care in hospitals. Healthcare providers can use process indicators to identify specific areas for improvement, thereby driving continuous quality improvement efforts.
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Affiliation(s)
- Mengyang Liu
- Department of Biostatistics, School of Public Health, Harbin Medical University, No.157 Baojian Road, Harbin City, 150081, Heilongjiang Province, China
| | - Ruize Guo
- Department of Biostatistics, School of Public Health, Harbin Medical University, No.157 Baojian Road, Harbin City, 150081, Heilongjiang Province, China
| | - Jingkun Li
- Department of Biostatistics, School of Public Health, Harbin Medical University, No.157 Baojian Road, Harbin City, 150081, Heilongjiang Province, China
| | - Chao Wang
- Department of Biostatistics, School of Public Health, Harbin Medical University, No.157 Baojian Road, Harbin City, 150081, Heilongjiang Province, China
| | - Lei Yu
- Department of Biostatistics, School of Public Health, Harbin Medical University, No.157 Baojian Road, Harbin City, 150081, Heilongjiang Province, China
| | - Meina Liu
- Department of Biostatistics, School of Public Health, Harbin Medical University, No.157 Baojian Road, Harbin City, 150081, Heilongjiang Province, China.
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Liu M, Yu Q, Liu Y. Developing quality indicators for cancer hospitals in China: a national modified Delphi process. BMJ Open 2024; 14:e082930. [PMID: 38594187 PMCID: PMC11015267 DOI: 10.1136/bmjopen-2023-082930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 03/19/2024] [Indexed: 04/11/2024] Open
Abstract
OBJECTIVE Although demand and supply of cancer care have been rapidly increasing in recent decades, there is a lack of systemic quality measurement for cancer hospitals in China. This study aimed to develop a set of core indicators for measuring quality of care for cancer hospitals in China. DESIGN The development of quality indicators was based on a literature review and a two-round modified Delphi survey. The theoretical framework and initial indicators were identified through the comprehensive literature review, and the selection of quality indicators relied on experts' consensus on the importance and feasibility of indicators by the modified Delphi process. In addition, indicator weight was identified using the analytical hierarchical process method and percentage weight method. SETTING AND PARTICIPANTS A panel of leading experts including oncologists, cancer care nurses, quality management experts from various regions of China were invited to participate in the two-round modified Delphi process from October to December 2020. A total of 25 experts completed the two-round modified Delphi process. RESULTS The experts reached consensus on a set of 47 indicators, comprising 17 structure indicators, 19 process indicators and 11 outcome indicators. Experts gave much higher weight to outcome indicators (accounting for 53.96% relative weight) than to structure (16.34%) and process (29.70%) indicators. In addition, experts also showed concerns and gave suggestions on data availability of specific outcome indicators. CONCLUSIONS Drawing on the comprehensive literature review and the modified Delphi process, this study developed a core set of quality indicators that can be used to evaluate quality performance of cancer hospitals. This is helpful in supporting quality cancer care in China and will provide new insights into the systemic measurement of cancer care internationally.
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Affiliation(s)
- Meicen Liu
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Qingyuan Yu
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yuanli Liu
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
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McLeod M, Leung K, Pramesh CS, Kingham P, Mutebi M, Torode J, Ilbawi A, Chakowa J, Sullivan R, Aggarwal A. Quality indicators in surgical oncology: systematic review of measures used to compare quality across hospitals. BJS Open 2024; 8:zrae009. [PMID: 38513280 PMCID: PMC10957165 DOI: 10.1093/bjsopen/zrae009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 11/16/2023] [Accepted: 12/17/2023] [Indexed: 03/23/2024] Open
Abstract
BACKGROUND Measurement and reporting of quality indicators at the hospital level has been shown to improve outcomes and support patient choice. Although there are many studies validating individual quality indicators, there has been no systematic approach to understanding what quality indicators exist for surgical oncology and no standardization for their use. The aim of this study was to review quality indicators used to assess variation in quality in surgical oncology care across hospitals or regions. It also sought to describe the aims of these studies and what, if any, feedback was offered to the analysed groups. METHODS A literature search was performed to identify studies published between 1 January 2000 and 23 October 2023 that applied surgical quality indicators to detect variation in cancer care at the hospital or regional level. RESULTS A total of 89 studies assessed 91 unique quality indicators that fell into the following Donabedian domains: process indicators (58; 64%); outcome indicators (26; 29%); structure indicators (6; 7%); and structure and outcome indicators (1; 1%). Purposes of evaluating variation included: identifying outliers (43; 48%); comparing centres with a benchmark (14; 16%); and supplying evidence of practice variation (29; 33%). Only 23 studies (26%) reported providing the results of their analyses back to those supplying data. CONCLUSION Comparisons of quality in surgical oncology within and among hospitals and regions have been undertaken in high-income countries. Quality indicators tended to be process measures and reporting focused on identifying outlying hospitals. Few studies offered feedback to data suppliers.
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Affiliation(s)
- Megan McLeod
- Department of Health Policy, London School of Economics and Political Science, London, UK
- Department of Otolaryngology—Head & Neck Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Kari Leung
- Department of Oncology, Guy’s & St Thomas’ NHS Trust, London, UK
| | - C S Pramesh
- Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, India
| | - Peter Kingham
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Miriam Mutebi
- Department of Surgery, Aga Khan University, Nairobi, Kenya
| | - Julie Torode
- Institute of Cancer Policy, Centre for Cancer, Society & Public Health, King’s College London, London, UK
| | - Andre Ilbawi
- Department of Universal Health Coverage, World Health Organization, Geneva, Switzerland
| | | | - Richard Sullivan
- Institute of Cancer Policy, Global Oncology Group, Centre for Cancer, Society & Public Health, King’s College London, London, UK
| | - Ajay Aggarwal
- Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UK
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Schreuder K, Bult TJ, Stroop B, Koppert LB, Bijlsma RM, Bantema-Joppe EJ, Hoornweg MJ, Siesling S. European quality indicators developed by the European Commission Initiative on Breast Cancer: a first nationwide assessment for the Dutch setting. Breast Cancer Res Treat 2024; 203:523-531. [PMID: 37882921 DOI: 10.1007/s10549-023-07158-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 10/05/2023] [Indexed: 10/27/2023]
Abstract
PURPOSE This observational study aims to assess the feasibility of calculating indicators developed by the European Commission Initiative on Breast Cancer (ECIBC) for the Dutch breast cancer population. METHODS Patients diagnosed with invasive or in situ breast cancer between 2012 and 2018 were selected from the Netherlands Cancer Registry (NCR). Outcomes of the quality indicators (QI) were presented as mean scores and were compared to a stated norm. Variation between hospitals was assessed by standard deviations and funnel plots and trends over time were evaluated. The quality indicator calculator (QIC) was validated by comparing these outcomes with the outcomes of constructed algorithms in Stata. RESULTS In total, 133,527 patients were included. Data for 24 out of 26 QIs were available in the NCR. For 67% and 67% of the QIs, a mean score above the norm and low or medium hospital variation was observed, respectively. The proportion of patients undergoing a breast reconstruction or neoadjuvant systemic therapy increased over time. The proportion treated within 4 weeks from diagnosis, having >10 lymph nodes removed or estrogen negative breast cancer who underwent adjuvant chemotherapy decreased. The outcomes of the constructed algorithms in this study and the QIC showed 100% similarity. CONCLUSION Data from the NCR could be used for the calculation of more than 92% of the ECIBC indicators. The quality of breast cancer care in the Netherlands is high, as more than half of the QIs already score above the norm and medium hospital variation was observed. The QIC can be easy and reliably applied.
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Affiliation(s)
- Kay Schreuder
- Department of Research and Development, Netherlands Comprehensive Cancer Organisation (IKNL), Enschede, The Netherlands.
- Department of Health Technology and Services Research (HTSR), Technical Medical Centre, University of Twente, Enschede, The Netherlands.
| | - Tim J Bult
- Department of Health Technology and Services Research (HTSR), Technical Medical Centre, University of Twente, Enschede, The Netherlands
| | - Babet Stroop
- Department of Health Technology and Services Research (HTSR), Technical Medical Centre, University of Twente, Enschede, The Netherlands
| | - Linetta B Koppert
- Department of Surgery, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Rhodé M Bijlsma
- Department of Medical Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Enja J Bantema-Joppe
- Department of Radiation Oncology, Radiotherapy Institute Friesland, Leeuwarden, The Netherlands
| | - Marije J Hoornweg
- Department of Plastic and Reconstructive Surgery, The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Sabine Siesling
- Department of Research and Development, Netherlands Comprehensive Cancer Organisation (IKNL), Enschede, The Netherlands
- Department of Health Technology and Services Research (HTSR), Technical Medical Centre, University of Twente, Enschede, The Netherlands
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Kollmann NP, Langenberger B, Busse R, Pross C. Stability of hospital quality indicators over time: A multi-year observational study of German hospital data. PLoS One 2023; 18:e0293723. [PMID: 37934753 PMCID: PMC10629650 DOI: 10.1371/journal.pone.0293723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 10/19/2023] [Indexed: 11/09/2023] Open
Abstract
BACKGROUND Retrospective hospital quality indicators can only be useful if they are trustworthy signals of current or future quality. Despite extensive longitudinal quality indicator data and many hospital quality public reporting initiatives, research on quality indicator stability over time is scarce and skepticism about their usefulness widespread. OBJECTIVE Based on aggregated, widely available hospital-level quality indicators, this paper sought to determine whether quality indicators are stable over time. Implications for health policy were drawn and the limited methodological foundation for stability assessments of hospital-level quality indicators enhanced. METHODS Two longitudinal datasets (self-reported and routine data), including all hospitals in Germany and covering the period from 2004 to 2017, were analysed. A logistic regression using Generalized Estimating Equations, a time-dependent, graphic quintile representation of risk-adjusted rates and Spearman's rank correlation coefficient were used. RESULTS For a total of eight German quality indicators significant stability over time was demonstrated. The probability of remaining in the best quality cluster in the future across all hospitals reached from 46.9% (CI: 42.4-51.6%) for hip replacement reoperations to 80.4% (CI: 76.4-83.8%) for decubitus. Furthermore, graphical descriptive analysis showed that the difference in adverse event rates for the 20% top performing compared to the 20% worst performing hospitals in the two following years is on average between 30% for stroke and AMI and 79% for decubitus. Stability over time has been shown to vary strongly between indicators and treatment areas. CONCLUSION Quality indicators were found to have sufficient stability over time for public reporting. Potentially, increasing case volumes per hospital, centralisation of medical services and minimum-quantity regulations may lead to more stable and reliable quality of care indicators. Finally, more robust policy interventions such as outcome-based payment, should only be applied to outcome indicators with a higher level of stability over time. This should be subject to future research.
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Affiliation(s)
| | - Benedikt Langenberger
- Department of Health Care Management, Berlin University of Technology, Berlin, Germany
| | - Reinhard Busse
- Department of Health Care Management, Berlin University of Technology, Berlin, Germany
| | - Christoph Pross
- Department of Health Care Management, Berlin University of Technology, Berlin, Germany
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Katalinic A, Halber M, Meyer M, Pflüger M, Eberle A, Nennecke A, Kim-Wanner SZ, Hartz T, Weitmann K, Stang A, Justenhoven C, Holleczek B, Piontek D, Wittenberg I, Heßmer A, Kraywinkel K, Spix C, Pritzkuleit R. Population-Based Clinical Cancer Registration in Germany. Cancers (Basel) 2023; 15:3934. [PMID: 37568750 PMCID: PMC10416989 DOI: 10.3390/cancers15153934] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Revised: 07/26/2023] [Accepted: 07/31/2023] [Indexed: 08/13/2023] Open
Abstract
INTRODUCTION In 2013, a new federal law obligated all German federal states to collect additional clinical data in population-based cancer registries as an active tool for monitoring and improving the quality of cancer care, increasing transparency and promoting health research. Now, 10 years later, the current status of the expanded cancer registration is presented, including current figures on cancer in Germany. METHODS Reporting of cancer is mandatory for physicians, and about 5 to 10 reports from different healthcare providers are expected for each case. A uniform national dataset of about 130 items is used, and reports are usually sent electronically to the registry. We used the most recent data available from cancer registries up to the year of diagnosis in 2019. We calculated incidence rates and 5-year relative survival (5YRS) for common cancers. Data on clinical outcomes and benchmarking based on quality indicators (QIs) from guidelines were provided by the Cancer Registry Schleswig-Holstein (CR SH). RESULTS All federal state cancer registries met most of the previously defined national eligibility criteria. Approximately 505,000 cancer cases were registered in 2019, with breast, prostate, colorectal and lung cancer being the most common cancers. The age-standardised cancer incidence has slightly decreased during the last decade. and spatial heterogeneity can be observed within Germany. 5YRS for all cancers was 67% and 63% for women and men, respectively. Therapy data for rectal cancer in 2019-2021 from the CR SH are shown as an example: 69% of the registered patients underwent surgery, mostly with curative intent (84%) and tumour-free resection (91%). Radiotherapy was given to 33% of the patients, and chemotherapy was given to 40%. Three selected QIs showed differences between involved healthcare providers. DISCUSSION The implementation of population-based clinical cancer registration can be considered a success. Comprehensive recording of diagnosis, treatment and disease progression and the use of registry data for quality assurance, benchmarking and feedback have been implemented.
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Affiliation(s)
- Alexander Katalinic
- Cancer Registry Schleswig-Holstein, 23562 Lübeck, Germany;
- Institute for Social Medicine and Epidemiology, University of Lübeck, 23562 Lübeck, Germany
| | - Marco Halber
- Cancer Registry Baden-Wurttemberg, 70191 Stuttgart, Germany;
| | - Martin Meyer
- Bavarian Cancer Registry, 90441 Nurnberg, Germany;
| | - Maren Pflüger
- Cancer Registry Brandenburg-Berlin, 03048 Cottbus, Germany;
| | | | | | | | - Tobias Hartz
- Cancer Registry Lower Saxony, 30659 Hannover, Germany;
| | - Kerstin Weitmann
- Cancer Registry Mecklenburg-Western Pomerania, 17475 Greifswald, Germany;
| | - Andreas Stang
- Cancer Registry North Rhine-Westphalia, 44801 Bochum, Germany;
| | | | | | - Daniela Piontek
- Joint Office of the Clinical Cancer Registries in Saxony, 01099 Dresden, Germany;
| | - Ian Wittenberg
- Cancer Registry Saxony-Anhalt, 06112 Halle (Saale), Germany;
| | | | - Klaus Kraywinkel
- Centre for Cancer Registry Data at the Robert Koch-Institute, 12101 Berlin, Germany;
| | - Claudia Spix
- Division of Childhood Cancer Epidemiology, German Childhood Cancer Registry, 55101 Mainz, Germany;
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Thurell J, Manouchehri N, Fredriksson I, Wilking U, Bergh J, Ryden L, Koppert LB, Karsten MM, Kiani NA, Hedayati E. Risk-adjusted benchmarking of long-term overall survival in patients with HER2-positive early-stage Breast cancer: A Swedish retrospective cohort study. Breast 2023; 70:18-24. [PMID: 37295176 DOI: 10.1016/j.breast.2023.05.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 05/30/2023] [Indexed: 06/12/2023] Open
Abstract
AIM The main objective of the current study was to explore the value of risk-adjustment when comparing (i.e. benchmarking) long-term overall survival (OS) in breast cancer (BC) between Swedish regions. We performed risk-adjusted benchmarking of 5- and 10-year OS after HER2-positive early BC diagnosis between Sweden's two largest healthcare regions, constituting approximately a third of the total population in Sweden. METHODS All patients diagnosed with HER2-positive early-stage BC between 01-01-2009 and 31-12-2016 in healthcare regions Stockholm-Gotland and Skane were included in the study. Cox proportional hazards model was used for risk-adjustment. Unadjusted (i.e. crude) and adjusted 5- and 10-year OS was benchmarked between the two regions. RESULTS The crude 5-year OS was 90.3% in the Stockholm-Gotland region and 87.8% in the Skane region. The crude 10-year OS was 81.7% in the Stockholm-Gotland region and 77.3% in the Skane region. However, when adjusted for age, menopausal status and tumour biology, there was no significant OS disparity between the regions, neither at the 5-year nor 10-year follow-up. CONCLUSION This study showed that risk-adjustment is relevant when benchmarking OS in BC, even when comparing regions from the same country that share the same national treatment guidelines. This is, to our knowledge, the first published risk-adjusted benchmarking of OS in HER2-positive BC.
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Affiliation(s)
- Jacob Thurell
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden; Breast Cancer Center, Department of Breast, Endocrine Tumours and Sarcoma, Karolinska Comprehensive Cancer Center, Karolinska University Hospital, Stockholm, Sweden.
| | - Narges Manouchehri
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden; Algorithmic Dynamics Lab, Center of Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Irma Fredriksson
- Breast Cancer Center, Department of Breast, Endocrine Tumours and Sarcoma, Karolinska Comprehensive Cancer Center, Karolinska University Hospital, Stockholm, Sweden; Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Ulla Wilking
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Jonas Bergh
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden; Breast Cancer Center, Department of Breast, Endocrine Tumours and Sarcoma, Karolinska Comprehensive Cancer Center, Karolinska University Hospital, Stockholm, Sweden
| | - Lisa Ryden
- Department of Clinical Sciences Lund, Division of Surgery, Lund University, Lund, Sweden; Department of Surgery, Skane University Hospital, Malmö, Sweden
| | - Linetta B Koppert
- Erasmus MC Cancer Institute, Dept of Surgery, Rotterdam, the Netherlands
| | - Maria M Karsten
- Charité - Universitätsmedizin Berlin, Department of Gynecology with Breast Center, Berlin, Germany
| | - Narsis A Kiani
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden; Algorithmic Dynamics Lab, Center of Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Elham Hedayati
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden; Breast Cancer Center, Department of Breast, Endocrine Tumours and Sarcoma, Karolinska Comprehensive Cancer Center, Karolinska University Hospital, Stockholm, Sweden
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Liu M, Hu L, Xu Y, Wang Y, Liu Y. Patient healthcare experiences of cancer hospitals in China: A multilevel modeling analysis based on a national survey. Front Public Health 2023; 11:1059878. [PMID: 36908411 PMCID: PMC9992183 DOI: 10.3389/fpubh.2023.1059878] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Accepted: 02/02/2023] [Indexed: 02/24/2023] Open
Abstract
Importance Patient satisfaction is a crucial indicator for assessing quality of care in healthcare settings. However, patient satisfaction benchmark for cancer hospitals in China is not established. Objective To examine patient satisfaction levels in tertiary cancer hospitals in China, and inter-hospital variations after case-mix adjustment. Design A nationwide cross-sectional hospital performance survey conducted from January to March 2021. Settings At 30 tertiary cancer hospitals in China. Participants A total of 4,847 adult inpatients consecutively recruited at 30 tertiary cancer hospitals were included. Exposures Patient characteristics included demographic characteristics (sex, age, education, and annual family income), clinical characteristics (cancer type, cancer stage, self-reported health status, and length of stay), and actual respondents of questionnaire. Main outcomes and measures Patient satisfaction was measured using 23 items covering five aspects, administrative process, hospital environment, medical care, symptom management, and overall satisfaction. Responses to each item were recorded using a 5-point Likert scale. Patient satisfaction level for each aspect was described at individual and hospital levels. Using multilevel logistic regression, patient characteristics associated with patient satisfaction were examined as case-mix adjusters and inter-hospital variation were determined. Results The satisfaction rates for symptom management, administrative process, hospital environment, overall satisfaction, and medical care aspects were 74.56, 81.70, 84.18, 84.26, and 90.86% with a cut-off value of 4, respectively. Significant predictors of patient satisfaction included sex, age, cancer type, cancer stage, self-reported health status, and actual respondent (representative or patient) (all P < 0.05). The ranking of the hospitals' performance in satisfaction was altered after the case-mix adjustment was made. But even after the adjustment, significant variation in satisfaction among hospitals remained. Conclusions and relevance This study pointed to symptom management as a special area, to which a keen attention should be paid by policymakers and hospital administrators. Significant variation in satisfaction among hospitals remained, implying that future studies should examine major factors affecting the variation. In review, target interventions are needed in low-performing hospitals.
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Affiliation(s)
| | - Linlin Hu
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | | | | | - Yuanli Liu
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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van der Schors W, Kemp R, van Hoeve J, Tjan-Heijnen V, Maduro J, Vrancken Peeters MJ, Siesling S, Varkevisser M. Associations of hospital volume and hospital competition with short-term, middle-term and long-term patient outcomes after breast cancer surgery: a retrospective population-based study. BMJ Open 2022; 12:e057301. [PMID: 35473746 PMCID: PMC9045096 DOI: 10.1136/bmjopen-2021-057301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVES For oncological care, there is a clear tendency towards centralisation and collaboration aimed at improving patient outcomes. However, in market-based healthcare systems, this trend is related to the potential trade-off between hospital volume and hospital competition. We analyse the association between hospital volume, competition from neighbouring hospitals and outcomes for patients who underwent surgery for invasive breast cancer (IBC). OUTCOME MEASURES Surgical margins, 90 days re-excision, overall survival. DESIGN, SETTING, PARTICIPANTS In this population-based study, we use data from the Netherlands Cancer Registry. Our study sample consists of 136 958 patients who underwent surgery for IBC between 2004 and 2014 in the Netherlands. RESULTS Our findings show that treatment types as well as patient and tumour characteristics explain most of the variation in all outcomes. After adjusting for confounding variables and intrahospital correlation in multivariate logistic regressions, hospital volume and competition from neighbouring hospitals did not show significant associations with surgical margins and re-excision rates. For patients who underwent surgery in hospitals annually performing 250 surgeries or more, multilevel Cox proportional hazard models show that survival was somewhat higher (HR 0.94). Survival in hospitals with four or more (potential) competitors within 30 km was slightly higher (HR 0.97). However, this effect did not hold after changing this proxy for hospital competition. CONCLUSIONS Based on the selection of patient outcomes, hospital volume and regional competition appear to play only a limited role in the explanation of variation in IBC outcomes across Dutch hospitals. Further research into hospital variation for high-volume tumours like the one studied here is recommended to (i) use consistently measured quality indicators that better reflect multidisciplinary clinical practice and patient and provider decision-making, (ii) include more sophisticated measures for hospital competition and (iii) assess the entire process of care within the hospital, as well as care provided by other providers in cancer networks.
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Affiliation(s)
- Wouter van der Schors
- Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, The Netherlands
| | - Ron Kemp
- Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, The Netherlands
- Dutch Authority for Consumers & Markets, The Hague, The Netherlands
| | - Jolanda van Hoeve
- Department of Research, Netherlands Comprehensive Cancer Organization, Utrecht, The Netherlands
- Department of Health Technology and Services Research, University of Twente, Enschede, The Netherlands
| | | | - John Maduro
- Radiotherapy, UMCG, Groningen, The Netherlands
| | - Marie-Jeanne Vrancken Peeters
- Department of surgery, Netherlands Cancer Institute-Antoni van Leeuwenhoek, Amsterdam, The Netherlands
- Department of surgery, Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | - Sabine Siesling
- Department of Research, Netherlands Comprehensive Cancer Organization, Utrecht, The Netherlands
- Department of Health Technology & Services Research, MIRA Institute for Biomedical Technology and Technical Medicine, Universiteit Twente, Enschede, The Netherlands
| | - Marco Varkevisser
- Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, The Netherlands
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Zheng X, Zhang M, Zheng Y, Zhang Y, Wang J, Zhang P, Yang X, Li S, Ding R, Siqin G, Hou X, Chen L, Zhang M, Sun Y, Wu J, Yu B. Quality indicators for cardiac rehabilitation after myocardial infarction in China: a consensus panel and practice test. BMJ Open 2020; 10:e039757. [PMID: 33380480 PMCID: PMC7780554 DOI: 10.1136/bmjopen-2020-039757] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
OBJECTIVES Cardiac rehabilitation (CR) improves outcomes after myocardial infarction (MI), but it is underused in China. The purpose of this study was to develop a set of quality indicators (QIs) to improve clinical practices and to confirm the measurability and performance of the developed QIs for CR in Chinese patients after MI. DESIGN AND SETTING The QIs were developed by a Chinese expert consensus panel during in-person meetings. The five QIs most in need of improvement were selected using a national questionnaire. Finally, the completion rate and feasibility of the QIs were verified in a group of MI survivors at university hospitals in China. PARTICIPANTS Seventeen professionals participated in the consensus panel, 89 personnel in the field of CR participated in the national questionnaire and 165 MI survivors participated in the practice test. RESULTS A review of 17 eligible articles generated 26 potential QIs, among which 17 were selected by the consensus panel after careful evaluation. The 17 QIs were divided into two domains: (1) improving participation and adherence and (2) CR process standardisation. Nationwide telephone and WeChat surveys identified the five QIs most in need of improvement. A multicenter practice test (n=165) revealed that the mean performance value of the proposed QIs was 43.9% (9.9%-86.1%) according to patients with post-MI. CONCLUSIONS The consensus panel identified a comprehensive set of QIs for CR in patients with post-MI. A nationwide questionnaire survey was used to identify the QIs that need immediate attention to improve the quality of CR. Although practice tests confirmed the measurability of the proposed QIs in clinical practice, the implementation of the QIs needs to be improved. TRIAL REGISTRATION NUMBER This study is part of a study registered in ClinicalTrials.gov (NCT03528382).
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Affiliation(s)
- Xianghui Zheng
- Department of Cardiology, the Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, China
- The Key Laboratory of Myocardial Ischemia, Harbin Medical University, Ministry of Education, Harbin, Heilongjiang Province, China
| | - Maomao Zhang
- Department of Cardiology, the Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, China
- The Key Laboratory of Myocardial Ischemia, Harbin Medical University, Ministry of Education, Harbin, Heilongjiang Province, China
| | - Yang Zheng
- Department of Cardiology, the Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, China
- The Key Laboratory of Myocardial Ischemia, Harbin Medical University, Ministry of Education, Harbin, Heilongjiang Province, China
| | - Yongxiang Zhang
- Department of Cardiology, the Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, China
- The Key Laboratory of Myocardial Ischemia, Harbin Medical University, Ministry of Education, Harbin, Heilongjiang Province, China
| | - Junnan Wang
- Department of Cardiology, the Second Hospital of Jilin University, Changchun, Jilin Province, China
| | - Ping Zhang
- Department of Cardiology, Beijing Tsinghua Changgung Hospital, Beijing, China
| | - Xuwen Yang
- Department of Cardiology, Tianjin Chest Hospital, Tianjin, China
| | - Shan Li
- Department of Cardiology, Affiliated Hospital of Qingdao University, Qingdao, Shandong Province, China
| | - Rongjing Ding
- Department of Cardiology, Peking University People's Hospital, Beijing, China
| | - Gaowa Siqin
- Department of Cardiology, Inner Mongolia People's Hospital, Huhhot, Inner Mongolia, China
| | - Xinyu Hou
- Department of Cardiology, the Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, China
- The Key Laboratory of Myocardial Ischemia, Harbin Medical University, Ministry of Education, Harbin, Heilongjiang Province, China
| | - Liangqi Chen
- Department of Cardiology, the Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, China
- The Key Laboratory of Myocardial Ischemia, Harbin Medical University, Ministry of Education, Harbin, Heilongjiang Province, China
| | - Min Zhang
- Department of Cardiology, the Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, China
- The Key Laboratory of Myocardial Ischemia, Harbin Medical University, Ministry of Education, Harbin, Heilongjiang Province, China
| | - Yong Sun
- Department of Cardiology, the Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, China
- The Key Laboratory of Myocardial Ischemia, Harbin Medical University, Ministry of Education, Harbin, Heilongjiang Province, China
| | - Jian Wu
- Department of Cardiology, the Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, China
- The Key Laboratory of Myocardial Ischemia, Harbin Medical University, Ministry of Education, Harbin, Heilongjiang Province, China
| | - Bo Yu
- Department of Cardiology, the Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, China
- The Key Laboratory of Myocardial Ischemia, Harbin Medical University, Ministry of Education, Harbin, Heilongjiang Province, China
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Favez L, Zúñiga F, Sharma N, Blatter C, Simon M. Assessing Nursing Homes Quality Indicators' Between-Provider Variability and Reliability: A Cross-Sectional Study Using ICCs and Rankability. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17249249. [PMID: 33321952 PMCID: PMC7764139 DOI: 10.3390/ijerph17249249] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 12/07/2020] [Accepted: 12/08/2020] [Indexed: 01/14/2023]
Abstract
Nursing home quality indicators are often used to publicly report the quality of nursing home care. In Switzerland, six national nursing home quality indicators covering four clinical domains (polypharmacy, pain, use of physical restraints and weight loss) were recently developed. To allow for meaningful comparisons, these indicators must reliably show differences in quality of care levels between nursing homes. This study’s objectives were to assess nursing home quality indicators’ between-provider variability and reliability using intraclass correlations and rankability. This approach has not yet been used in long-term care contexts but presents methodological advantages. This cross-sectional multicenter study uses data of 11,412 residents from a convenience sample of 152 Swiss nursing homes. After calculating intraclass correlation 1 (ICC1) and rankability, we describe between-provider variability for each quality indicator using empirical Bayes estimate-based caterpillar plots. To assess reliability, we used intraclass correlation 2 (ICC2). Overall, ICC1 values were high, ranging from 0.068 (95% confidence interval (CI) 0.047–0.086) for polypharmacy to 0.396 (95% CI 0.297–0.474) for physical restraints, with quality indicator caterpillar plots showing sufficient between-provider variability. However, testing for rankability produced mixed results, with low figures for two indicators (0.144 for polypharmacy; 0.471 for self-reported pain) and moderate to high figures for the four others (from 0.692 for observed pain to 0.976 for physical restraints). High ICC2 figures, ranging from 0.896 (95% CI 0.852–0.917) (self-reported pain) to 0.990 (95% CI 0.985–0.993) (physical restraints), indicated good reliability for all six quality indicators. Intraclass correlations and rankability can be used to assess nursing home quality indicators’ between-provider variability and reliability. The six selected quality indicators reliably distinguish care differences between nursing homes and can be recommended for use, although the variability of two—polypharmacy and self-reported pain—is substantially chance-driven, limiting their utility.
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Affiliation(s)
- Lauriane Favez
- Institute of Nursing Science, University of Basel, Bernoullistrasse 28, 4056 Basel, Switzerland; (L.F.); (N.S.); (C.B.); (M.S.)
| | - Franziska Zúñiga
- Institute of Nursing Science, University of Basel, Bernoullistrasse 28, 4056 Basel, Switzerland; (L.F.); (N.S.); (C.B.); (M.S.)
- Correspondence: ; Tel.: +41-61-207-09-13
| | - Narayan Sharma
- Institute of Nursing Science, University of Basel, Bernoullistrasse 28, 4056 Basel, Switzerland; (L.F.); (N.S.); (C.B.); (M.S.)
| | - Catherine Blatter
- Institute of Nursing Science, University of Basel, Bernoullistrasse 28, 4056 Basel, Switzerland; (L.F.); (N.S.); (C.B.); (M.S.)
| | - Michael Simon
- Institute of Nursing Science, University of Basel, Bernoullistrasse 28, 4056 Basel, Switzerland; (L.F.); (N.S.); (C.B.); (M.S.)
- Nursing and Midwifery Research Unit, Inselspital Bern University Hospital, Freiburgstrasse, 3010 Bern, Switzerland
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