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      What is health systems responsiveness? Review of existing knowledge and proposed conceptual framework

      research-article
      1 , 2
      BMJ Global Health
      BMJ Publishing Group
      health system, responsiveness, conceptual framework, review

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          Abstract

          Responsiveness is a key objective of national health systems. Responsive health systems anticipate and adapt to existing and future health needs, thus contributing to better health outcomes. Of all the health systems objectives, responsiveness is the least studied, which perhaps reflects lack of comprehensive frameworks that go beyond the normative characteristics of responsive services. This paper contributes to a growing, yet limited, knowledge on this topic. Herewith, we review the current frameworks for understanding health systems responsiveness and drawing on these, as well as key frameworks from the wider public services literature, propose a comprehensive conceptual framework for health systems responsiveness. This paper should be of interest to different stakeholders who are engaged in analysing and improving health systems responsiveness. Our review shows that existing knowledge on health systems responsiveness can be extended along the three areas. First, responsiveness entails an actual experience of people’s interaction with their health system, which confirms or disconfirms their initial expectations of the system. Second, the experience of interaction is shaped by both the people and the health systems sides of this interaction. Third, different influences shape people’s interaction with their health system, ultimately affecting their resultant experiences. Therefore, recognition of both people and health systems sides of interaction and their key determinants would enhance the conceptualisations of responsiveness. Our proposed framework builds on, and advances, the core frameworks in the health systems literature. It positions the experience of interaction between people and health system as the centrepiece and recognises the determinants of responsiveness experience both from the health systems (eg, actors, processes) and the people (eg, initial expectations) sides. While we hope to trigger further thinking on the conceptualisation of health system responsiveness, the proposed framework can guide assessments of, and interventions to strengthen, health systems responsiveness.

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          Most cited references98

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          Understanding the barriers to setting up a healthcare quality improvement process in resource-limited settings: a situational analysis at the Medical Department of Kamuzu Central Hospital in Lilongwe, Malawi

          Background Knowledge regarding the best approaches to improving the quality of healthcare and their implementation is lacking in many resource-limited settings. The Medical Department of Kamuzu Central Hospital in Malawi set out to improve the quality of care provided to its patients and establish itself as a recognized centre in teaching, operations research and supervision of district hospitals. Efforts in the past to achieve these objectives were short-lived, and largely unsuccessful. Against this background, a situational analysis was performed to aid the Medical Department to define and prioritize its quality improvement activities. Methods A mix of quantitative and qualitative methods was applied using checklists for observed practice, review of registers, key informant interviews and structured patient interviews. The mixed methods comprised triangulation by including the perspectives of the clients, healthcare providers from within and outside the department, and the field researcher’s perspectives by means of document review and participatory observation. Results Human resource shortages, staff attitudes and shortage of equipment were identified as major constraints to patient care, and the running of the Medical Department. Processes, including documentation in registers and files and communication within and across cadres of staff were also found to be insufficient and thus undermining the effort of staff and management in establishing a sustained high quality culture. Depending on their past experience and knowledge, the stakeholder interviewees revealed different perspectives and expectations of quality healthcare and the intended quality improvement process. Conclusions Establishing a quality improvement process in resource-limited settings is an enormous task, considering the host of challenges that these facilities face. The steps towards changing the status quo for improved quality care require critical self-assessment, the willingness to change as well as determined commitment and contributions from clients, staff and management.
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            Trust and the development of health care as a social institution

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              A model to prioritize access to elective surgery on the basis of clinical urgency and waiting time

              Background Prioritization of waiting lists for elective surgery represents a major issue in public systems in view of the fact that patients often suffer from consequences of long waiting times. In addition, administrative and standardized data on waiting lists are generally lacking in Italy, where no detailed national reports are available. This is true although since 2002 the National Government has defined implicit Urgency-Related Groups (URGs) associated with Maximum Time Before Treatment (MTBT), similar to the Australian classification. The aim of this paper is to propose a model to manage waiting lists and prioritize admissions to elective surgery. Methods In 2001, the Italian Ministry of Health funded the Surgical Waiting List Info System (SWALIS) project, with the aim of experimenting solutions for managing elective surgery waiting lists. The project was split into two phases. In the first project phase, ten surgical units in the largest hospital of the Liguria Region were involved in the design of a pre-admission process model. The model was embedded in a Web based software, adopting Italian URGs with minor modifications. The SWALIS pre-admission process was based on the following steps: 1) urgency assessment into URGs; 2) correspondent assignment of a pre-set MTBT; 3) real time prioritization of every referral on the list, according to urgency and waiting time. In the second project phase a prospective descriptive study was performed, when a single general surgery unit was selected as the deployment and test bed, managing all registrations from March 2004 to March 2007 (1809 ordinary and 597 day cases). From August 2005, once the SWALIS model had been modified, waiting lists were monitored and analyzed, measuring the impact of the model by a set of performance indexes (average waiting time, length of the waiting list) and Appropriate Performance Index (API). Results The SWALIS pre-admission model was used for all registrations in the test period, fully covering the case mix of the patients referred to surgery. The software produced real time data and advanced parameters, providing patients and users useful tools to manage waiting lists and to schedule hospital admissions with ease and efficiency. The model protected patients from horizontal and vertical inequities, while positive changes in API were observed in the latest period, meaning that more patients were treated within their MTBT. Conclusion The SWALIS model achieves the purpose of providing useful data to monitor waiting lists appropriately. It allows homogeneous and standardized prioritization, enhancing transparency, efficiency and equity. Due to its applicability, it might represent a pragmatic approach towards surgical waiting lists, useful in both clinical practice and strategic resource management.
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                Author and article information

                Journal
                BMJ Glob Health
                BMJ Glob Health
                bmjgh
                bmjgh
                BMJ Global Health
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2059-7908
                2017
                31 October 2017
                : 2
                : 4
                : e000486
                Affiliations
                [1 ] departmentNuffield Centre for International Health and Development , Leeds Institute of Health Sciences, University of Leeds , Leeds, UK
                [2 ] KIT Royal Tropical Institute , Amsterdam, The Netherlands
                Author notes
                [Correspondence to ] Dr Tolib Mirzoev; t.mirzoev@ 123456leeds.ac.uk
                Article
                bmjgh-2017-000486
                10.1136/bmjgh-2017-000486
                5717934
                29225953
                34f9b6f6-6c80-4f96-8f42-24a6e257cd6c
                © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

                This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/

                History
                : 20 July 2017
                : 06 October 2017
                : 11 October 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Categories
                Research
                1506
                Custom metadata
                unlocked

                health system,responsiveness,conceptual framework,review

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