Project description:Birth centres are described as settings where women with uncomplicated pregnancies can give birth in a home-like environment assisted by midwives and maternity care assistants. If complications arise or threaten, the woman is referred to a maternity unit of a hospital where an obstetrician will take over responsibility. In the last decade, a number of new birth centres have been established in the Netherlands, based on the assumption that birth centres provide better quality of care since they offer a better opportunity for more integrated care than the existing system with independent primary and secondary care providers. At present, there is no evidence for this assumption. The Dutch Birth Centre Study is designed to present evidence-based recommendations for organization and functioning of future birth centres in the Netherlands. A necessary first step in this evaluation is the development of indicators for measuring the quality of the care delivered in birth centres in the Netherlands. The aim of this study is to identify a comprehensive set of structure and process indicators to assess quality of birth centre care.We used mixed methods to develop a set of structure and process quality indicators for evaluating birth centre care. Beginning with a literature review, we developed an exhaustive list of determinants. We then used a Delphi study to narrow this list, calling on experts to rate the determinants for relevance and feasibility. A multidisciplinary expert panel of 63 experts, directly or indirectly involved with birth centre care, was invited to participate.A panel of 42 experts completed two Delphi rounds rating determinants of the quality of birth centre care based on their relevance (to the setting) and feasibility (of use). A set of 30 determinants for structure and process quality indicators was identified to assess the quality of birth centre care in the Netherlands.We identified 30 determinants for structure and process quality indicators concerning birth centre care. This set will be validated during the evaluation of birth centres in the Dutch Birth Centre Study.

Project description:BackgroundPatients in health systems across the world can now choose between different health care providers. Patients are increasingly using websites and apps to compare the quality of health care services available in order to make a choice of provider. In keeping with many patient-facing platforms, most services currently providing comparative information on different providers do not take account of end-user requirements or the available evidence base.ObjectiveTo investigate what factors were considered most important when choosing nonemergency secondary health care providers in the United Kingdom with the purpose of translating these insights into a ratings platform delivered through a consumer mHealth app.MethodsA mixed methods approach was used to identify key indicators incorporating a literature review to identify and categorize existing quality indicators, a questionnaire survey to formulate a ranked list of performance indicators, and focus groups to explore rationales behind the rankings. Findings from qualitative and quantitative methodologies were mapped onto each other under the four categories identified by the literature review.ResultsQuality indicators were divided into four categories. Hospital access was the least important category. The mean differences between the other three categories hospital statistics, hospital staff, and hospital facilities, were not statistically significant. Staff competence was the most important indicator in the hospital staff category; cleanliness and up-to-date facilities were equally important in hospital facilities; ease of travel to the hospital was found to be most important in hospital access. All quality indicators within the hospital statistics category were equally important. Focus groups elaborated that users find it difficult to judge staff competence despite its importance.ConclusionsA mixed methods approach is presented, which supported a patient-centered development and evaluation of a hospital ratings mobile app. Where possible, mHealth developers should use systematic research methods in order to more closely meet the needs of the end user and add credibility to their platform.

Project description:OBJECTIVES:To identify a generic set of face valid quality indicators for primary care mental health services which reflect a multi-stakeholder perspective and can be used for facilitating quality improvement. DESIGN:Modified two-round postal Delphi questionnaire. SETTING:Geographical spread across Great Britain. PARTICIPANTS:One hundred and fifteen panellists representing 11 different stakeholder groups within primary care mental health services (clinical psychologist, health and social care commissioner, community psychiatric nurse, counsellor, general practitioner, practice nurse/district nurse/health visitor, psychiatrist, social worker, carer, patient and voluntary organisations). MAIN OUTCOME MEASURES:Face validity (median rating of 8 or 9 on a nine point scale with agreement by all panels) for assessing quality of care. RESULTS:A maximum of 334 indicators were rated by panels in the second round; 26% were rated valid by all panels. These indicators were categorised into 21 aspects of care, 11 relating to general practices and 10 relating to health authorities or primary care groups/trusts. There was variation in the total number of indicators rated valid across the different panels. Overall, GPs rated the lowest number of indicators as valid (41%, n=138) and carers rated the highest number valid (91%, n=304). CONCLUSIONS:The quality indicators represent consensus among key stakeholder groups in defining quality of care within primary care mental health services. These indicators could provide a guide for primary care organisations embarking on quality improvement initiatives in mental health care when addressing national targets and standards relating to primary care set out in the National Service Framework for Mental Health for England. Although many of the indicators relate to parochial issues in UK service delivery, the methodology used in the development of the indicators could be applied in other settings to produce locally relevant indicators.

Project description:BackgroundLifting The Burden (LTB) and European Headache Federation (EHF) have developed a set of headache service quality indicators, successfully tested in specialist headache centres. Their intended application includes all levels of care. Here we assess their implementation in primary care.MethodsWe included 28 primary-care clinics in Germany (4), Turkey (4), Latvia (5) and Portugal (15). To implement the indicators, we interviewed 111 doctors, 92 nurses and medical assistants, 70 secretaries, 27 service managers and 493 patients, using the questionnaires developed by LTB and EHF. In addition, we evaluated 675 patients' records. Enquiries were in nine domains: diagnosis, individualized management, referral pathways, patient education and reassurance, convenience and comfort, patient satisfaction, equity and efficiency of headache care, outcome assessment and safety.ResultsThe principal finding was that Implementation proved feasible and practical in primary care. In the process, we identified significant quality deficits. Almost everywhere, histories of headache, especially temporal profiles, were captured and/or assessed inaccurately. A substantial proportion (20%) of patients received non-specific ICD codes such as R51 ("headache") rather than specific headache diagnoses. Headache-related disability and quality of life were not part of routine clinical enquiry. Headache diaries and calendars were not in use. Waiting times were long (e.g., about 60 min in Germany). Nevertheless, most patients (> 85%) expressed satisfaction with their care. Almost all the participating clinics provided equitable and easy access to treatment, and follow-up for most headache patients, without unnecessary barriers.ConclusionsThe study demonstrated that headache service quality indicators can be used in primary care, proving both practical and fit for purpose. It also uncovered quality deficits leading to suboptimal treatment, often due to a lack of knowledge among the general practitioners. There were failures of process also. These findings signal the need for additional training in headache diagnosis and management in primary care, where most headache patients are necessarily treated. More generally, they underline the importance of headache service quality evaluation in primary care, not only to identify-quality failings but also to guide improvements. This study also demonstrated that patients' satisfaction is not, on its own, a good indicator of service quality.

Project description:BackgroundDespite the growing interest in assessing the quality of care for depression, there is little evidence to support measurement of the quality of primary care for depression. This study identified evidence-based quality indicators for monitoring, evaluating and improving the quality of care for depression in primary care settings.MethodsOvid MEDLINE and Ovid PsycINFO databases, and grey literature, including relevant organizational websites, were searched from 2000 to 2015. Two reviewers independently selected studies if (1) the study methodology combined a systematic literature search with assessment of quality indicators by an expert panel and (2) quality indicators were applicable to assessment of care for adults with depression in primary care settings. Included studies were appraised using the Appraisal of Indicators through Research and Evaluation (AIRE) instrument, which contains four domains and 20 items. A narrative synthesis was used to combine the indicators within themes. Quality indicators applicable to care for adults with depression in primary care settings were extracted using a structured form. The extracted quality indicators were categorized according to Donabedian's 'structure-process-outcome' framework.ResultsThe search revealed 3838 studies. Four additional publications were identified through grey literature searching. Thirty-nine articles were reviewed in detail and seven met the inclusion criteria. According to the AIRE domains, all studies were clear on purpose and stakeholder involvement, while formal endorsement and usage of indicators in practice were scarcely described. A total of 53 quality indicators were identified from the included studies, many of which overlap conceptually or in content: 15 structure, 33 process and four outcome indicators. This study identified quality indicators for evaluating primary care for depression among adult patients.ConclusionsThe identified set of indicators address multiple dimensions of depression care and provide an excellent starting point for further development and use in primary care settings.

Dataset Information

Research methods used in developing and applying quality indicators in primary care.

Publications

Research methods used in developing and applying quality indicators in primary care.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets