ABSTRACT
OBJECTIVE: To identify where in England there are likely to be most constraints on choice of hospital for patients waiting longer than six months for elective care. DESIGN: Cross sectional study using routinely collected data. SETTING: Population of England and NHS trusts and private sector hospitals in England. PARTICIPANTS: All residents in England. MAIN OUTCOME MEASURES: Availability of beds (available and unoccupied hospital beds), demand (number of people waiting longer than six months), and access (travel time to facilities) to hospital care in England. RESULTS: Most people in England already have an extensive potential choice of hospital. The number of available and unoccupied beds within 60 minutes' travel time was lowest in the Scottish borders, North Yorkshire, and parts of East Anglia, Lincolnshire, Devon, and Cornwall. This pattern was not altered by adding in private facilities. Putting demand with this supply, the number of people in a geographical area waiting longer than six months per bed within 60 minutes' travel time was highest in the south east (except London), parts of the south west (Cornwall, Bristol), East Anglia, and the Welsh border. CONCLUSION: People in the south east (outside London), East Anglia, and parts of the south west are likely to have to travel further to exercise meaningful choice of hospital for elective care.
Subject(s)
Bed Occupancy/classification , Catchment Area, Health/statistics & numerical data , Elective Surgical Procedures/statistics & numerical data , Health Services Accessibility/statistics & numerical data , Waiting Lists , Choice Behavior , Cross-Sectional Studies , Data Collection/methods , England , Geography , Hospitals, Private/statistics & numerical data , Hospitals, Public/statistics & numerical data , Humans , Maps as Topic , Residence Characteristics , State Medicine/standards , State Medicine/statistics & numerical data , Time FactorsABSTRACT
An improvement activity involving use of real-time waiting-time data resulted in reductions in bed-assignment times and overall diversion hours.
Subject(s)
Admitting Department, Hospital/standards , Bed Occupancy/classification , Patient Admission/standards , Process Assessment, Health Care , Total Quality Management/methods , Waiting Lists , Computer Communication Networks , Feedback , Georgia , Humans , Interdisciplinary Communication , Nursing Staff, Hospital , Organizational Case Studies , Physician-Patient Relations , Time ManagementSubject(s)
Bed Occupancy/classification , Electronic Data Processing , Emergency Service, Hospital/organization & administration , Hospital Information Systems , Bed Occupancy/statistics & numerical data , Efficiency, Organizational , Hospitals, Teaching/statistics & numerical data , Humans , PennsylvaniaSubject(s)
Health Services Needs and Demand/statistics & numerical data , Nursing Staff, Hospital/supply & distribution , Patients/classification , Personnel Staffing and Scheduling/standards , Bed Occupancy/classification , Health Care Reform/organization & administration , Hospital Units , Hospitals, Military/statistics & numerical data , Humans , Poland , WorkforceABSTRACT
OBJECTIVE: To determine the perceptions of managers in Scottish NHS trusts concerning bed-blocking. To help determine the causes of bed-blocking and suggest possible solutions to the problem. DESIGN: The first part of the study consisted of qualitative research interviews with key figures in NHS trusts and an examination of the existing literature on bed-blocking. This informed the second stage which was based on a questionnaire survey of senior managers in 35 trusts. SETTING: Interviews were carried out in three trusts in Forth Valley Health Board and Grampian Health Board areas. Questionnaires were sent out to 44 trusts throughout Scotland. The three trusts that were excluded from this study did not contain bed-blocking patients. SUBJECTS: Questionnaires were sent to chief executives of 44 NHS trusts in Scotland. Respondents were nominated by chief executives on the basis of their experience and understanding of bed-blocking problems within their own trust. RESULTS: Of the 44 questionnaires sent to trusts in Scotland, there were 35 responses (80%) which identified a total of 1845 beds as being blocked. The NHS secondary care-based respondents indicated that social services were responsible for 1406 bed-blocking patients in 35 trusts, an average of 40 patients per trust between August and September 1997. Some 600 of these "social services responsible" bed-blocking patients, an average of 21 patients per trust, were reported as awaiting comprehensive assessment by a social worker. In addition, 710 of these "social services responsible" bed-blocking patients, an average of 24 patients per trust, were awaiting funding authorization for a nursing home or residential home placement. NHS trusts were responsible for 237 bed-blocking patients, an average of seven patients per trust. In a further 202 cases bed-blocking was deemed to be neither the responsibility of the trust nor of social services as patients were awaiting vacancies in the patient's or carer's specific choice of residential or nursing home. CONCLUSION: Results from this study show that there would appear to be a significant number of blocked beds in NHS trust hospitals throughout Scotland. Trust staff, whilst acknowledging the complex nature of bed-blocking, perceive social services, who are responsible for the assessment, placement and financing of patients being transferred from hospitals to residential care in the community, as being responsible for the majority of these beds being blocked. It is, however, acknowledged that social services are under-funded and under-resourced. If the situation is to be improved, consideration should be given to changing service delivery processes in the context of the implementation of Designed to Care.
Subject(s)
Bed Occupancy/statistics & numerical data , Hospitals, Public/statistics & numerical data , Long-Term Care/statistics & numerical data , Bed Occupancy/classification , Health Services Accessibility , Health Services Research , Hospitals, Public/organization & administration , Humans , Interviews as Topic , Patient Discharge , Patient Transfer , Scotland , Social Work Department, Hospital , State Medicine/statistics & numerical data , Surveys and QuestionnairesABSTRACT
New functions have been integrated in the Giessen Hospital Information System WING to support the classification of all intensive care patients into the Therapeutic Intervention Scoring System (TISS). The use of those functions has been pushed when health insurance bodies demanded evidence for the correct classification of ICU beds. This article presents an overview on this development from the start in just one intensive care unit to the complete coverage of six intensive care units and three intensive monitoring units with a total of 109 beds. For those units complete TISS data has been documented for more than a year now at a detailed level. On average 14 interventions have been recorded per patient and day, accumulating to a database with more than a million entries. We describe the experiences made during introduction and the different front-end applications we used to achieve the goal. Results gained from the huge database and their implications for our future work are discussed. TISS documentation is now an established routine on every intensive care unit of our University hospital. It has been implemented without major financial or manpower investments and no specific intensive care information system has been needed. Establishing this type of basic care documentation made nurses aware of their activities, so that now they consider electronic care documentation to be in their very own interest. The next goal has been set by nurses themselves, they want to establish intervention based care documentation on normal wards as well. We think that step by step we will thus be able to achieve a more complete electronic patient record.