PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-25 (736658)

Clipboard (0)
None

Related Articles

1.  Impact of telephone triage on emergency after hours GP Medicare usage: a time-series analysis 
Background
The Australian government sponsored trials aimed at addressing problems in after hours primary medical care service use in five different parts of the country with different after hours care problems. The study's objective was to determine in four of the five trials where telephone triage was the sole innovation, if there was a reduction in emergency GP after hours service utilization (GP first call-out) as measured in Medicare Benefits Schedule claim data. Monthly MBS claim data in both the pre-trial and trial periods was monitored over a 3-year period in each trial area as well as in a national sample outside the trial areas (National comparator). Poisson regression analysis was used in analysis.
Results
There was significant reduction in first call out MBS claims in three of the four study areas where stand-alone call centre services existed. These were the Statewide Call Centre in both its Metropolitan and Non-metropolitan areas in which it operated – Relative Risk (RR) = 0.87 (95% Confidence interval: 0.86 – 0.88) and 0.60 (95% CI: 0.54 – 0.68) respectively. There was also a reduction in the Regional Call Centre in the non-Metropolitan area in which it operated (RR = 0.46 (95% CI: 0.35 – 0.61) though a small increase in its Metropolitan area (RR = 1.11 (95% CI: 1.06 – 1.17). For the two telephone triage services embedded in existing organisations, there was also a significant reduction for the Deputising Service – RR = 0.62 (95% CI: 0.61 – 0.64) but no change in the Local Triage centre area.
Conclusion
The four telephone triage services were associated with reduced GP MBS claims for first callout after hours care in most study areas. It is possible that other factors could be responsible for some of this reduction, for example, MBS submitted claims for after hours GP services being reclassified from 'after hours' to 'in hours'. The goals of stand-alone call centres which are aimed principally at meeting population needs rather than managing demand may be being met only in part.
doi:10.1186/1743-8462-4-21
PMCID: PMC2151763  PMID: 17927836
2.  ‘Letting Go’: delegating responsibility for non-clinical tasks in a telehealth service 
Introduction
The implementation of telehealth into the delivery of chronic conditions management within Hywel Dda Health Board has provided an opportunity to enhance close working relationships with Carmarthenshire County Council’s well-established telecare team. The responsibilities of the telecare team were initially limited to the installation and removal of telehealth devices in patients’ homes and training on its use but as the use of telehealth has widened, an increasing number of non-clinical tasks, several of which were previously undertaken by clinical staff, have been delegated to members of the telecare team and linked to the monitoring centre. In addition, all the tasks associated with managing and administering the patients on the telehealth system backend are undertaken by the chronic conditions management administrative support team within the Health Board.
Aims and objectives
This presentation will describe our experience of bringing together clinical and non-clinical staff from two separate organisations to deliver a more appropriate, comprehensive and timely telehealth service to patients. It will explain how strong working relationships have developed, the importance of a clear understanding of different roles within the team and the need for building trust and confidence in colleagues, resulting in the clinical nurse specialists ‘letting go’ and responding to change that supports effective monitoring and still providing quality care. We will report on the lessons learned during the process, from both staff groups’ perspectives and the patient’s perspective, as tasks previously undertaken by clinicians have shifted to non-clinical staff.
Results
Our current approach to telehealth has evolved into a model which ensures that the specialist nursing team are able to focus solely on delivering quality clinical care enabled and supported by telehealth where appropriate. All the non-clinical tasks are now undertaken by the telecare team staff and chronic conditions management administrative support and include:
Installing devices in patients’ homes and providing education and training
First-line monitoring/triage of uploaded patient data Escalation of clinical alerts to nursing team by Telephone
Resolving technical alerts and missing uploads/data
Provision of refresher training to patients as required (telephone-based or face-to-face)
Responding to patient or nurse-reported technical problems, including battery/faulty device replacement
Providing advice on home set-up e.g., recommending changes
System administrator, patient administration and management function of backend
The results of patient and staff questionnaires seeking feedback on our model will be given together with an economic evaluation comparing the current approach, which utilises telecare and specialist staff to deliver the service compared to the previous delivery model using specialist nursing staff only. We will also show that through embedding telehealth into a well-established community specialist nursing service has the following impact and outcomes:
Patients to take more responsibility for their day-to-day care
Nurses to monitor patients remotely and contact those who need support reducing the number if inappropriate home visits
Reducing travelling for the nursing service
Improving relationships between patient and nurse
Supporting carers
Conclusions
We have embedded our telehealth service into existing service models which have now been enhanced utilising a partnership approach and ensuring the best use of the skills and expertise, across the organisations involved. This has been a key factor in developing an efficient, effective and sustainable approach.
PMCID: PMC3571134
partnership; comprehensive; timely telehealth service
3.  Impact of the urgent care telephone service NHS 111 pilot sites: a controlled before and after study 
BMJ Open  2013;3(11):e003451.
Objectives
To measure the impact of the urgent care telephone service NHS 111 on the emergency and urgent care system.
Design
Controlled before and after study using routine data.
Setting
Four pilot sites and three control sites covering a total population of 3.6 million in England, UK.
Participants and data
Routine data on 36 months of use of emergency ambulance service calls and incidents, emergency department attendances, urgent care contacts (general practice (GP) out of hours, walk in and urgent care centres) and calls to the telephone triage service NHS direct.
Intervention
NHS 111, a new 24 h 7 day a week telephone service for non-emergency health problems, operated by trained non-clinical call handlers with clinical support from nurse advisors, using NHS Pathways software to triage calls to different services and home care.
Main outcomes
Changes in use of emergency and urgent care services.
Results
NHS 111 triaged 277 163 calls in the first year of operation for a population of 1.8 million. There was no change overall in emergency ambulance calls, emergency department attendances or urgent care use. There was a 19.3% reduction in calls to NHS Direct (95% CI −24.6% to −14.0%) and a 2.9% increase in emergency ambulance incidents (95% CI 1.0% to 4.8%). There was an increase in activity overall in the emergency and urgent care system in each site ranging 4.7–12%/month and this remained when assuming that NHS 111 will eventually take all NHS Direct and GP out of hours calls.
Conclusions
In its first year of operation in four pilot sites NHS 111 did not deliver the expected system benefits of reducing calls to the 999 ambulance service or shifting patients to urgent rather than emergency care. There is potential that this type of service increases overall demand for urgent care.
doi:10.1136/bmjopen-2013-003451
PMCID: PMC3831104  PMID: 24231457
ACCIDENT & EMERGENCY MEDICINE
4.  Process evaluation for the FEeding Support Team (FEST) randomised controlled feasibility trial of proactive and reactive telephone support for breastfeeding women living in disadvantaged areas 
BMJ Open  2012;2(2):e001039.
Objective
To assess the feasibility, acceptability and fidelity of a feeding team intervention with an embedded randomised controlled trial of team-initiated (proactive) and woman-initiated (reactive) telephone support after hospital discharge.
Design
Participatory approach to the design and implementation of a pilot trial embedded within a before-and-after study, with mixed-method process evaluation.
Setting
A postnatal ward in Scotland.
Sample
Women initiating breast feeding and living in disadvantaged areas.
Methods
Quantitative data: telephone call log and workload diaries. Qualitative data: interviews with women (n=40) with follow-up (n=11) and staff (n=17); ward observations 2 weeks before and after the intervention; recorded telephone calls (n=16) and steering group meetings (n=9); trial case notes (n=69); open question in a telephone interview (n=372). The Framework approach to analysis was applied to mixed-method data.
Main outcome measures
Quantitative: telephone call characteristics (number, frequency, duration); workload activity. Qualitative: experiences and perspectives of women and staff.
Results
A median of eight proactive calls per woman (n=35) with a median duration of 5 min occurred in the 14 days following hospital discharge. Only one of 34 control women initiated a call to the feeding team, with women undervaluing their own needs compared to others, and breast feeding as a reason to call. Proactive calls providing continuity of care increased women's confidence and were highly valued. Data demonstrated intervention fidelity for woman-centred care; however, observing an entire breast feed was not well implemented due to short hospital stays, ward routines and staff–team–woman communication issues. Staff pragmatically recognised that dedicated feeding teams help meet women's breastfeeding support needs in the context of overstretched and variable postnatal services.
Conclusions
Implementing and integrating the FEeding Support Team (FEST) trial within routine postnatal care was feasible and acceptable to women and staff from a research and practice perspective and shows promise for addressing health inequalities.
Trial registration
ISRCTN27207603. The study protocol and final report is available on request.
Article summary
Article focus
To use a participatory approach to design, deliver and implement a feeding support team intervention integrated into routine postnatal ward care and to deliver a pilot randomised controlled trial (RCT) of proactive and reactive telephone support for breast feeding for up to 14 days after hospital discharge for women living in more disadvantaged areas.
To use a mixed qualitative and quantitative methods process evaluation to assess the study acceptability, feasibility and intervention fidelity from the perspectives of women and National Health Service staff.
To inform the design of a future definitive RCT.
Key messages
Women living in disadvantaged areas are unlikely to initiate calls for help with breast feeding and proactive telephone calls may help to counteract the inverse care law.
Women undervalue both breast feeding and their own needs compared with the needs of others as a reason to ask for help in the context of overstretched maternity services.
A caring, reassuring woman-centred communication style with continuity of care from hospital to home was valued and increased women's confidence.
Strengths and limitations of this study
The participatory approach embedding a rigorous RCT within a before-and-after cohort study with mixed-methods data to evaluate implementation processes and costs are strengths that will enable us to design a feasible and acceptable definitive trial.
The contribution of the personal characteristics and skills of the feeding team to the intervention was important and may be challenging to replicate.
The low number of women who reported having an entire breast feed observed is a limitation and warrants further investigation.
More research is required before feeding teams and proactive calls are widely implemented as there are likely to be unintended consequences to such an organisational change in postnatal care.
doi:10.1136/bmjopen-2012-001039
PMCID: PMC3341595  PMID: 22535794
5.  Safety and effectiveness of nurse telephone consultation in out of hours primary care: randomised controlled trial 
BMJ : British Medical Journal  1998;317(7165):1054-1059.
Objective To determine the safety and effectiveness of nurse telephone consultation in out of hours primary care by investigating adverse events and the management of calls.
Design Block randomised controlled trial over a year of 156 matched pairs of days and weekends in 26 blocks. One of each matched pair was randomised to receive the intervention.
Setting One 55 member general practice cooperative serving 97 000 registered patients in Wiltshire.
Subjects All patients contacting the out of hours service or about whom contact was made during specified times over the trial year.
Intervention A nurse telephone consultation service integrated within a general practice cooperative. The out of hours period was 615 pm to 1115 pm from Monday to Friday, 1100 am to 1115 pm on Saturday, and 800 am to 1115 pm on Sunday. Experienced and specially trained nurses received, assessed, and managed calls from patients or their carers. Management options included telephone advice; referral to the general practitioner on duty (for telephone advice, an appointment at a primary care centre, or a home visit); referral to the emergency service or advice to attend accident and emergency. Calls were managed with the help of decision support software.
Main outcome measures Deaths within seven days of a contact with the out of hours service; emergency hospital admissions within 24 hours and within three days of contact; attendance at accident and emergency within three days of a contact; number and management of calls in each arm of the trial.
Results 14 492 calls were received during the specified times in the trial year (7308 in the control arm and 7184 in the intervention arm) concerning 10 134 patients (10.4% of the registered population). There were no substantial differences in the age and sex of patients in the intervention and control groups, though male patients were underrepresented overall. Reasons for calling the service were consistent with previous studies. Nurses managed 49.8% of calls during intervention periods without referral to a general practitioner. A 69% reduction in telephone advice from a general practitioner, together with a 38% reduction in patient attendance at primary care centres and a 23% reduction in home visits was observed during intervention periods. Statistical equivalence was observed in the number of deaths within seven days, in the number of emergency hospital admissions, and in the number of attendances at accident and emergency departments.
Conclusions Nurse telephone consultation produced substantial changes in call management, reducing overall workload of general practitioners by 50% while allowing callers faster access to health information and advice. It was not associated with an increase in the number of adverse events. This model of out of hours primary care is safe and effective.
Key messagesTelephone consultation is becoming an increasingly accepted approach to patient care and improves public access to medical information and adviceThis study found that nurse telephone consultation halved the number of cases dealt with by general practitioners and was at least as safe as existing out of hours servicesNurse telephone consultation not only replaced telephone advice given by a doctor but led to reductions in both home visits and surgery attendances out of hoursFurther testing is required of variants to the system used in this trial, including the selection and training of nurses and the decision support software usedThere are clear opportunities for and potential benefits from integrating existing out of hours services with NHS Direct
PMCID: PMC28690  PMID: 9774295
6.  Comparison of out of hours care provided by patients' own general practitioners and commercial deputising services: a randomised controlled trial. I: The process of care. 
BMJ : British Medical Journal  1997;314(7075):187-189.
OBJECTIVE: To compare the process of out of hours care provided by general practitioners from patients' own practices and by commercial deputising services. DESIGN: Randomised controlled trial. SETTING: Four urban areas in Manchester, Salford, Stockport, and Leicester. SUBJECTS: 2152 patients who requested out of hours care, and 49 practice doctors and 183 deputising doctors (61% local principals) who responded to those requests. MAIN OUTCOME MEASURES: Response to call, time to visit, prescribing, and hospital admissions. RESULTS: 1046 calls were dealt with by practice doctors and 1106 by deputising doctors. Practice doctors were more likely to give telephone advice (20.2% v 0.72% of calls) and to visit more quickly than deputising doctors (median delay 35 minutes v 52 minutes). Practice doctors were less likely than deputising doctors to issue a prescription (56.1% v 63.2% of patients) or to prescribe an antibiotic (43.7% v 61.3% of prescriptions issued) and more likely to prescribe genetic drugs (58.4% v 32.1% of drugs prescribed), cheaper drugs (mean cost per prescription pounds 3.28 v pounds 5.04), and drugs in a predefined out of hours formulary (49.8% v 41.1% of drugs prescribed). There was no significant difference in the number of hospital admissions. CONCLUSIONS: By contrast with practice doctors, deputising doctors providing out of hours care less readily give telephone advice, take longer to visit at home, and have patterns of prescribing that may be less discriminating.
PMCID: PMC2125698  PMID: 9022434
7.  Exploring users' experiences of accessing out‐of‐hours primary medical care services 
Quality & Safety in Health Care  2007;16(6):469-477.
Background
Since 2000, out‐of‐hours primary medical care services in the UK have undergone major changes in the organisation and delivery of services in response to recommendations by the Carson Review and more recently, through the new General Medical Services Contract (GMS2). People calling their general practice in the evening or at weekends are redirected to the out‐of‐hours service which may offer telephone advice, a home visit or a visit to a treatment centre. Little is known about users' experiences under the new arrangements.
Aim
To explore users' experiences of out‐of‐hours primary medical care.
Design of study
A qualitative study employing focus groups and telephone interviews.
Setting
Three out‐of‐hours primary medical care service providers in England.
Methods
Focus groups and telephone interviews were conducted with 27 recent users of out‐of‐hours services.
Results
Key areas of concern included the urgency with which cases are handled, and delays when waiting for a call back or home visit. Users felt that providers were reluctant to do home visits. The service was regarded as under‐resourced and frequently misused. Many expressed anxiety about calling, feeling unsure about how appropriate their call was and many were uncertain about how the service operated.
Conclusions
Service users need clear information on how current out‐of‐hours services operate and how it should be used. Problems with triaging need to be addressed, users should be kept informed of any delays, and care needs to be taken to ensure that the new arrangements do not alienate older people or individuals with complex health needs.
doi:10.1136/qshc.2006.021501
PMCID: PMC2653185  PMID: 18055893
8.  International partnerships in telehealth: healthcare, industry and education 
Project background
In 2010 an internationally renowned American healthcare organisation partnered with Irish industry and higher education in Waterford with the goal to expand their telehealth services. Combining the skills and expertise of Nurse Consultants, Nurse Educators, IT Specialists and Healthcare Executives, these collaborative partnerships led to the delivery of telehealth services to North America from an Irish base, and to the development of new European telehealth programmes and telehealth training in Ireland. The telehealth service includes the provision of telephone triage, health information and advice, disease management and hospital discharge programmes to clients in Ireland, the UK and the USA. Telehealth nursing is an evolving specialty that requires the development of competence in key areas of information and communication technologies, assessment, triage and critical thinking in clinical decision-making within an environment where distance separates the nurse from the client.
Aims and objectives
The aim of this paper is to report on the development, implementation and evaluation of the telehealth service with a focus on the telephone triage and advice service and the hospital discharge programmes. Objectives of this paper include describing this telehealth initiative with reference to the changing nature of global healthcare provision; discuss the educational strategy and accredited programme for training competent telehealth nurses; report the results of the evaluation of nurse performance in telephone triage and present the data relating to the impact of hospital discharge programmes on patient satisfaction and readmission rates.
Methods and results
The evaluation of the telehealth training programme was undertaken six months post initial training and service commencement. One hundred triage and health information calls were reviewed, against best practice standards and programme learning outcomes, during a four-month period. Quantitative and qualitative data that demonstrates evidence of learning transfer from training to practice and the development of nurse competence from advanced beginner to levels of proficiency will be presented. The hospital discharge programmes have undergone continuous monitoring and reporting since commencement. This has enabled the collection of evidence that supports this brief telephone intervention as a method of reducing hopsital re-admissions and increasing patient satisfcation. Quantitative results will be presented and analysed in relation to the impact on patient satisfaction and readmission rates for patients discharged from cardiovascular, renal and digestive disease services.
Conclusions
This project has demonstrated the effectiveness of partnerships in healthcare, industry and education in achieving the development, implementation and evaluation of international telehealth services. Initial education, training and ongoing support and development of nurses is essential for quality telehealth provision. Weekly call review, constructive feedback and reflection on practice are effective strategies for performance assurance and improvement. As a growing element of integrated healthcare, telehealth modules should be included in pre and post-registration nursing education curricula. Further collaboration between industry, healthcare and education are necessary in moving the telehealth agenda forward for the benefit of integrating services that impact positively on service users.
PMCID: PMC3571125
telephone triage; hospital discharge programmes; partnerships
9.  Characteristics of Veterans Accessing the Veterans Affairs Telephone Triage Who Have Depression or Suicidal Ideation: Opportunities for Intervention 
Objective
To characterize Veterans who call telephone triage because of suicidal ideation (SI) or depression and to identify opportunities for suicide prevention efforts among these telephone triage users using a biosurveillance application.
Introduction
Veterans accessing Veterans Affairs (VA) health care have higher suicide rates and more characteristics associated with suicide risk, including being male, having multiple medical and psychiatric comorbidities, and being an older age, compared with the general U.S. population. The Veterans Crisis Line is a telephone hotline available to Veterans with urgent mental health concerns; however, not all Veterans are aware of this resource. By contrast, telephone triage is a national telephone-based triage system used by the VA to assess and triage all Veterans with acute medical or mental health complaints.
Methods
The VA Electronic Surveillance System for Early Notification of Community-based Epidemics (ESSENCE) was queried for telephone triage calls during January 1–June 30, 2012. Calls were classified as SI or depression when the triage nurse selected SI or depression as the Veteran’s chief complaint from a set of fixed options. Demographic and recommended follow-up time and location information was reviewed. A random sample of 20 SI calls and 50 depression calls were selected for chart review to determine whether Veterans were examined in a clinic or followed up by a clinician by telephone within 2 weeks of the veteran’s call.
Results
During January 1–June 30, 2012, 253,573 total calls were placed to telephone triage. Among these calls, 2,460 unique Veterans placed 417 calls for SI and 2,290 calls for depression. This represents 1% (2,707/253,573) of all calls placed during the period. All encounter information is available in the surveillance application within 24 hours of the call being placed. Median age of callers was 55 years (range: 19–94); 86% were male; and 6% placed repeat calls. The median number of repeat calls was 2 (range: 2–10). Among the 2,707 calls for SI or depression, 1,286 (48%) were made after routine business hours (5:00 p.m.–8:00 a.m.), and 646 (24%) were made on weekends. The greatest proportion of calls were from Wisconsin and Northern Illinois (17%) and the Southeastern United States (14%). Among the 2,290 calls for depression, 1,401 callers (61%) were recommended for urgent follow up or within 24 hours. 771 (34%) were assigned a follow up location of an emergency department; 117 (5%) an urgent care; 1,332 (58%) a physician’s office or clinic; 52 (2%) self-care at home; and 18 (1%) were unspecified. Among the 417 calls for SI, callers 410 (98%) were recommended for urgent follow-up or within 24 hours. 330 (79%) were assigned a follow-up location of an emergency department; 38 (9%) an urgent care; 43 (10%) a physician’s office or clinic; 3 (1%) self-care at home; and 3 (1%) unspecified. Among the 20 SI and 50 depression calls for which the charts were reviewed, 1 (5%) SI call and 6 (12%) depression calls had no documented follow-up by telephone or in person with a clinician within 2 weeks of initial call.
Conclusions
Telephone triage represents an additional data source available to surveillance applications. Although telephone triage is not the traditional method provided by the VA for triage of urgent mental health concerns, >2,000 Veterans called it with acute symptoms of SI or depression during January–June 2012. Training for suicide prevention should be prioritized for operators working during the high-volume periods of off-hours and weekends when approximately half and one-quarter of calls were received, respectively. We recommend standard notification of suicide prevention coordinators regarding calls to telephone triage for SI or depression to prevent loss to follow-up among Veterans at risk for suicide. Further investigation into reasons for increased call burden in identified geographic areas also is recommended.
PMCID: PMC3692783
Surveillance; Veterans; Suicide Risk
10.  Mystery shopping in health service evaluation. 
BACKGROUND: Over the last 5 years, primary care telephone triage systems have been introduced in the United Kingdom, United States, Australia, and most recently in New Zealand. Evaluation of the clinical safety of such systems poses a challenge for health planners and researchers. AIM: To evaluate the use of simulated patients in the assessment of aspects of clinical safety in a pilot New Zealand primary care telephone triage service. DESIGN OF STUDY: 'Mystery shopping', an evaluation strategy commonly used in market research, was adapted by using simulated patients for telephone triage service evaluation. SETTING: New Zealand. METHODS: Four scripted clinical scenarios were developed by academic general practitioners, validated in student teaching situations, and then used by simulated patients to make 101 telephone calls. The scenarios were designed to necessitate a referral to a medical practitioner for further investigation. The documentation kept by the callers was compared with the call records from the telephone triage company, and both were analysed for capture and handling of the clinical safety features of each scenario. In cases where the endpoint was not a medical assessment, possible reasons for this were explored. RESULTS: Records were retrieved for 85 telephone calls. Considerable triage variability was discovered. There were discrepancies between expected and actual triage outcomes with 51% of analysed calls resulting in a self-care recommendation. A number of reasons were identified both for the triage variability and the unpredicted outcomes. Audiotaping of consultations would have enhanced the credibility of the evaluation but it would have carried ethical constraints. CONCLUSION: Simulated patients can be used to evaluate the limitations of health services and to identify areas that could be addressed to improve patient safety. Evaluation of patient satisfaction with services is not sufficient alone to evaluate safety.
PMCID: PMC1314747  PMID: 14960218
11.  Online screening for distress, the 6th vital sign, in newly diagnosed oncology outpatients: randomised controlled trial of computerised vs personalised triage 
British Journal of Cancer  2012;107(4):617-625.
Background:
This randomised controlled trial examined the impact of screening for distress followed by two different triage methods on clinically relevant outcomes over a 12-month period.
Methods:
Newly diagnosed patients attending a large tertiary cancer centre were randomised to one of the two conditions: (1) screening with computerised triage or (2) screening with personalised triage, both following standardised clinical triage algorithms. Patients completed the Distress Thermometer, Pain and Fatigue Thermometers, the Psychological Screen for Cancer (PSSCAN) Part C and questions on resource utilisation at baseline, 3, 6 and 12 months.
Results:
In all, 3133 patients provided baseline data (67% of new patients); with 1709 (54.5%) retained at 12 months (15.4% deceased). Mixed effects models revealed that both groups experienced significant decreases in distress, anxiety, depression, pain and fatigue over time. People receiving personalised triage and people reporting higher symptom burden were more likely to access services, which was subsequently related to greater decreases in distress, anxiety and depression. Women may benefit more from personalised triage, whereas men may benefit more from a computerised triage model.
Conclusion:
Screening for distress is a viable intervention that has the potential to decrease symptom burden up to 12 months post diagnosis. The best model of screening may be to incorporate personalised triage for patients indicating high levels of depression and anxiety while providing computerised triage for others.
doi:10.1038/bjc.2012.309
PMCID: PMC3419958  PMID: 22828610
screening for distress; 6th vital sign; triage
12.  Developing an efficient scheduling template of a chemotherapy treatment unit 
The Australasian Medical Journal  2011;4(10):575-588.
This study was undertaken to improve the performance of a Chemotherapy Treatment Unit by increasing the throughput and reducing the average patient’s waiting time. In order to achieve this objective, a scheduling template has been built. The scheduling template is a simple tool that can be used to schedule patients' arrival to the clinic. A simulation model of this system was built and several scenarios, that target match the arrival pattern of the patients and resources availability, were designed and evaluated. After performing detailed analysis, one scenario provide the best system’s performance. A scheduling template has been developed based on this scenario. After implementing the new scheduling template, 22.5% more patients can be served.
Introduction
CancerCare Manitoba is a provincially mandated cancer care agency. It is dedicated to provide quality care to those who have been diagnosed and are living with cancer. MacCharles Chemotherapy unit is specially built to provide chemotherapy treatment to the cancer patients of Winnipeg. In order to maintain an excellent service, it tries to ensure that patients get their treatment in a timely manner. It is challenging to maintain that goal because of the lack of a proper roster, the workload distribution and inefficient resource allotment. In order to maintain the satisfaction of the patients and the healthcare providers, by serving the maximum number of patients in a timely manner, it is necessary to develop an efficient scheduling template that matches the required demand with the availability of resources. This goal can be reached using simulation modelling. Simulation has proven to be an excellent modelling tool. It can be defined as building computer models that represent real world or hypothetical systems, and hence experimenting with these models to study system behaviour under different scenarios.1, 2
A study was undertaken at the Children's Hospital of Eastern Ontario to identify the issues behind the long waiting time of a emergency room.3 A 20-­‐day field observation revealed that the availability of the staff physician and interaction affects the patient wait time. Jyväskylä et al.4 used simulation to test different process scenarios, allocate resources and perform activity-­‐based cost analysis in the Emergency Department (ED) at the Central Hospital. The simulation also supported the study of a new operational method, named "triage-team" method without interrupting the main system. The proposed triage team method categorises the entire patient according to the urgency to see the doctor and allows the patient to complete the necessary test before being seen by the doctor for the first time. The simulation study showed that it will decrease the throughput time of the patient and reduce the utilisation of the specialist and enable the ordering all the tests the patient needs right after arrival, thus quickening the referral to treatment.
Santibáñez et al.5 developed a discrete event simulation model of British Columbia Cancer Agency"s ambulatory care unit which was used to study the impact of scenarios considering different operational factors (delay in starting clinic), appointment schedule (appointment order, appointment adjustment, add-­‐ons to the schedule) and resource allocation. It was found that the best outcomes were obtained when not one but multiple changes were implemented simultaneously. Sepúlveda et al.6 studied the M. D. Anderson Cancer Centre Orlando, which is a cancer treatment facility and built a simulation model to analyse and improve flow process and increase capacity in the main facility. Different scenarios were considered like, transferring laboratory and pharmacy areas, adding an extra blood draw room and applying different scheduling techniques of patients. The study shows that by increasing the number of short-­‐term (four hours or less) patients in the morning could increase chair utilisation.
Discrete event simulation also helps improve a service where staff are ignorant about the behaviour of the system as a whole; which can also be described as a real professional system. Niranjon et al.7 used simulation successfully where they had to face such constraints and lack of accessible data. Carlos et al. 8 used Total quality management and simulation – animation to improve the quality of the emergency room. Simulation was used to cover the key point of the emergency room and animation was used to indicate the areas of opportunity required. This study revealed that a long waiting time, overload personnel and increasing withdrawal rate of patients are caused by the lack of capacity in the emergency room.
Baesler et al.9 developed a methodology for a cancer treatment facility to find stochastically a global optimum point for the control variables. A simulation model generated the output using a goal programming framework for all the objectives involved in the analysis. Later a genetic algorithm was responsible for performing the search for an improved solution. The control variables that were considered in this research are number of treatment chairs, number of drawing blood nurses, laboratory personnel, and pharmacy personnel. Guo et al. 10 presented a simulation framework considering demand for appointment, patient flow logic, distribution of resources, scheduling rules followed by the scheduler. The objective of the study was to develop a scheduling rule which will ensure that 95% of all the appointment requests should be seen within one week after the request is made to increase the level of patient satisfaction and balance the schedule of each doctor to maintain a fine harmony between "busy clinic" and "quiet clinic".
Huschka et al.11 studied a healthcare system which was about to change their facility layout. In this case a simulation model study helped them to design a new healthcare practice by evaluating the change in layout before implementation. Historical data like the arrival rate of the patients, number of patients visited each day, patient flow logic, was used to build the current system model. Later, different scenarios were designed which measured the changes in the current layout and performance.
Wijewickrama et al.12 developed a simulation model to evaluate appointment schedule (AS) for second time consultations and patient appointment sequence (PSEQ) in a multi-­‐facility system. Five different appointment rule (ARULE) were considered: i) Baily; ii) 3Baily; iii) Individual (Ind); iv) two patients at a time (2AtaTime); v) Variable Interval and (V-­‐I) rule. PSEQ is based on type of patients: Appointment patients (APs) and new patients (NPs). The different PSEQ that were studied in this study were: i) first-­‐ come first-­‐serve; ii) appointment patient at the beginning of the clinic (APBEG); iii) new patient at the beginning of the clinic (NPBEG); iv) assigning appointed and new patients in an alternating manner (ALTER); v) assigning a new patient after every five-­‐appointment patients. Also patient no show (0% and 5%) and patient punctuality (PUNCT) (on-­‐time and 10 minutes early) were also considered. The study found that ALTER-­‐Ind. and ALTER5-­‐Ind. performed best on 0% NOSHOW, on-­‐time PUNCT and 5% NOSHOW, on-­‐time PUNCT situation to reduce WT and IT per patient. As NOSHOW created slack time for waiting patients, their WT tends to reduce while IT increases due to unexpected cancellation. Earliness increases congestion whichin turn increases waiting time.
Ramis et al.13 conducted a study of a Medical Imaging Center (MIC) to build a simulation model which was used to improve the patient journey through an imaging centre by reducing the wait time and making better use of the resources. The simulation model also used a Graphic User Interface (GUI) to provide the parameters of the centre, such as arrival rates, distances, processing times, resources and schedule. The simulation was used to measure the waiting time of the patients in different case scenarios. The study found that assigning a common function to the resource personnel could improve the waiting time of the patients.
The objective of this study is to develop an efficient scheduling template that maximises the number of served patients and minimises the average patient's waiting time at the given resources availability. To accomplish this objective, we will build a simulation model which mimics the working conditions of the clinic. Then we will suggest different scenarios of matching the arrival pattern of the patients with the availability of the resources. Full experiments will be performed to evaluate these scenarios. Hence, a simple and practical scheduling template will be built based on the indentified best scenario. The developed simulation model is described in section 2, which consists of a description of the treatment room, and a description of the types of patients and treatment durations. In section 3, different improvement scenarios are described and their analysis is presented in section 4. Section 5 illustrates a scheduling template based on one of the improvement scenarios. Finally, the conclusion and future direction of our work is exhibited in section 6.
Simulation Model
A simulation model represents the actual system and assists in visualising and evaluating the performance of the system under different scenarios without interrupting the actual system. Building a proper simulation model of a system consists of the following steps.
Observing the system to understand the flow of the entities, key players, availability of resources and overall generic framework.
Collecting the data on the number and type of entities, time consumed by the entities at each step of their journey, and availability of resources.
After building the simulation model it is necessary to confirm that the model is valid. This can be done by confirming that each entity flows as it is supposed to and the statistical data generated by the simulation model is similar to the collected data.
Figure 1 shows the patient flow process in the treatment room. On the patient's first appointment, the oncologist comes up with the treatment plan. The treatment time varies according to the patient’s condition, which may be 1 hour to 10 hours. Based on the type of the treatment, the physician or the clinical clerk books an available treatment chair for that time period.
On the day of the appointment, the patient will wait until the booked chair is free. When the chair is free a nurse from that station comes to the patient, verifies the name and date of birth and takes the patient to a treatment chair. Afterwards, the nurse flushes the chemotherapy drug line to the patient's body which takes about five minutes and sets up the treatment. Then the nurse leaves to serve another patient. Chemotherapy treatment lengths vary from less than an hour to 10 hour infusions. At the end of the treatment, the nurse returns, removes the line and notifies the patient about the next appointment date and time which also takes about five minutes. Most of the patients visit the clinic to take care of their PICC line (a peripherally inserted central catheter). A PICC is a line that is used to inject the patient with the chemical. This PICC line should be regularly cleaned, flushed to maintain patency and the insertion site checked for signs of infection. It takes approximately 10–15 minutes to take care of a PICC line by a nurse.
Cancer Care Manitoba provided access to the electronic scheduling system, also known as "ARIA" which is comprehensive information and image management system that aggregates patient data into a fully-­‐electronic medical chart, provided by VARIAN Medical System. This system was used to find out how many patients are booked in every clinic day. It also reveals which chair is used for how many hours. It was necessary to search a patient's history to find out how long the patient spends on which chair. Collecting the snapshot of each patient gives the complete picture of a one day clinic schedule.
The treatment room consists of the following two main limited resources:
Treatment Chairs: Chairs that are used to seat the patients during the treatment.
Nurses: Nurses are required to inject the treatment line into the patient and remove it at the end of the treatment. They also take care of the patients when they feel uncomfortable.
Mc Charles Chemotherapy unit consists of 11 nurses, and 5 stations with the following description:
Station 1: Station 1 has six chairs (numbered 1 to 6) and two nurses. The two nurses work from 8:00 to 16:00.
Station 2: Station 2 has six chairs (7 to 12) and three nurses. Two nurses work from 8:00 to 16:00 and one nurse works from 12:00 to 20:00.
Station 3: Station 4 has six chairs (13 to 18) and two nurses. The two nurses work from 8:00 to 16:00.
Station 4: Station 4 has six chairs (19 to 24) and three nurses. One nurse works from 8:00 to 16:00. Another nurse works from 10:00 to 18:00.
Solarium Station: Solarium Station has six chairs (Solarium Stretcher 1, Solarium Stretcher 2, Isolation, Isolation emergency, Fire Place 1, Fire Place 2). There is only one nurse assigned to this station that works from 12:00 to 20:00. The nurses from other stations can help when need arises.
There is one more nurse known as the "float nurse" who works from 11:00 to 19:00. This nurse can work at any station. Table 1 summarises the working hours of chairs and nurses. All treatment stations start at 8:00 and continue until the assigned nurse for that station completes her shift.
Currently, the clinic uses a scheduling template to assign the patients' appointments. But due to high demand of patient appointment it is not followed any more. We believe that this template can be improved based on the availability of nurses and chairs. Clinic workload was collected from 21 days of field observation. The current scheduling template has 10 types of appointment time slot: 15-­‐minute, 1-­‐hour, 1.5-­‐hour, 2-­‐hour, 3-­‐hour, 4-­‐hour, 5-­‐hour, 6-­‐hour, 8-­‐hour and 10-­‐hour and it is designed to serve 95 patients. But when the scheduling template was compared with the 21 days observations, it was found that the clinic is serving more patients than it is designed for. Therefore, the providers do not usually follow the scheduling template. Indeed they very often break the time slots to accommodate slots that do not exist in the template. Hence, we find that some of the stations are very busy (mostly station 2) and others are underused. If the scheduling template can be improved, it will be possible to bring more patients to the clinic and reduce their waiting time without adding more resources.
In order to build or develop a simulation model of the existing system, it is necessary to collect the following data:
Types of treatment durations.
Numbers of patients in each treatment type.
Arrival pattern of the patients.
Steps that the patients have to go through in their treatment journey and required time of each step.
Using the observations of 2,155 patients over 21 days of historical data, the types of treatment durations and the number of patients in each type were estimated. This data also assisted in determining the arrival rate and the frequency distribution of the patients. The patients were categorised into six types. The percentage of these types and their associated service times distributions are determined too.
ARENA Rockwell Simulation Software (v13) was used to build the simulation model. Entities of the model were tracked to verify that the patients move as intended. The model was run for 30 replications and statistical data was collected to validate the model. The total number of patients that go though the model was compared with the actual number of served patients during the 21 days of observations.
Improvement Scenarios
After verifying and validating the simulation model, different scenarios were designed and analysed to identify the best scenario that can handle more patients and reduces the average patient's waiting time. Based on the clinic observation and discussion with the healthcare providers, the following constraints have been stated:
The stations are filled up with treatment chairs. Therefore, it is literally impossible to fit any more chairs in the clinic. Moreover, the stakeholders are not interested in adding extra chairs.
The stakeholders and the caregivers are not interested in changing the layout of the treatment room.
Given these constraints the options that can be considered to design alternative scenarios are:
Changing the arrival pattern of the patients: that will fit over the nurses' availability.
Changing the nurses' schedule.
Adding one full time nurse at different starting times of the day.
Figure 2 compares the available number of nurses and the number of patients' arrival during different hours of a day. It can be noticed that there is a rapid growth in the arrival of patients (from 13 to 17) between 8:00 to 10:00 even though the clinic has the equal number of nurses during this time period. At 12:00 there is a sudden drop of patient arrival even though there are more available nurses. It is clear that there is an imbalance in the number of available nurses and the number of patient arrivals over different hours of the day. Consequently, balancing the demand (arrival rate of patients) and resources (available number of nurses) will reduce the patients' waiting time and increases the number of served patients. The alternative scenarios that satisfy the above three constraints are listed in Table 2. These scenarios respect the following rules:
Long treatments (between 4hr to 11hr) have to be scheduled early in the morning to avoid working overtime.
Patients of type 1 (15 minutes to 1hr treatment) are the most common. They can be fitted in at any time of the day because they take short treatment time. Hence, it is recommended to bring these patients in at the middle of the day when there are more nurses.
Nurses get tired at the end of the clinic day. Therefore, fewer patients should be scheduled at the late hours of the day.
In Scenario 1, the arrival pattern of the patient was changed so that it can fit with the nurse schedule. This arrival pattern is shown Table 3. Figure 3 shows the new patients' arrival pattern compared with the current arrival pattern. Similar patterns can be developed for the remaining scenarios too.
Analysis of Results
ARENA Rockwell Simulation software (v13) was used to develop the simulation model. There is no warm-­‐up period because the model simulates day-­‐to-­‐day scenarios. The patients of any day are supposed to be served in the same day. The model was run for 30 days (replications) and statistical data was collected to evaluate each scenario. Tables 4 and 5 show the detailed comparison of the system performance between the current scenario and Scenario 1. The results are quite interesting. The average throughput rate of the system has increased from 103 to 125 patients per day. The maximum throughput rate can reach 135 patients. Although the average waiting time has increased, the utilisation of the treatment station has increased by 15.6%. Similar analysis has been performed for the rest of the other scenarios. Due to the space limitation the detailed results are not given. However, Table 6 exhibits a summary of the results and comparison between the different scenarios. Scenario 1 was able to significantly increase the throughput of the system (by 21%) while it still results in an acceptable low average waiting time (13.4 minutes). In addition, it is worth noting that adding a nurse (Scenarios 3, 4, and 5) does not significantly reduce the average wait time or increase the system's throughput. The reason behind this is that when all the chairs are busy, the nurses have to wait until some patients finish the treatment. As a consequence, the other patients have to wait for the commencement of their treatment too. Therefore, hiring a nurse, without adding more chairs, will not reduce the waiting time or increase the throughput of the system. In this case, the only way to increase the throughput of the system is by adjusting the arrival pattern of patients over the nurses' schedule.
Developing a Scheduling Template based on Scenario 1
Scenario 1 provides the best performance. However a scheduling template is necessary for the care provider to book the patients. Therefore, a brief description is provided below on how scheduling the template is developed based on this scenario.
Table 3 gives the number of patients that arrive hourly, following Scenario 1. The distribution of each type of patient is shown in Table 7. This distribution is based on the percentage of each type of patient from the collected data. For example, in between 8:00-­‐9:00, 12 patients will come where 54.85% are of Type 1, 34.55% are of Type 2, 15.163% are of Type 3, 4.32% are of Type 4, 2.58% are of Type 5 and the rest are of Type 6. It is worth noting that, we assume that the patients of each type arrive as a group at the beginning of the hourly time slot. For example, all of the six patients of Type 1 from 8:00 to 9:00 time slot arrive at 8:00.
The numbers of patients from each type is distributed in such a way that it respects all the constraints described in Section 1.3. Most of the patients of the clinic are from type 1, 2 and 3 and they take less amount of treatment time compared with the patients of other types. Therefore, they are distributed all over the day. Patients of type 4, 5 and 6 take a longer treatment time. Hence, they are scheduled at the beginning of the day to avoid overtime. Because patients of type 4, 5 and 6 come at the beginning of the day, most of type 1 and 2 patients come at mid-­‐day (12:00 to 16:00). Another reason to make the treatment room more crowded in between 12:00 to 16:00 is because the clinic has the maximum number of nurses during this time period. Nurses become tired at the end of the clinic which is a reason not to schedule any patient after 19:00.
Based on the patient arrival schedule and nurse availability a scheduling template is built and shown in Figure 4. In order to build the template, if a nurse is available and there are patients waiting for service, a priority list of these patients will be developed. They are prioritised in a descending order based on their estimated slack time and secondarily based on the shortest service time. The secondary rule is used to break the tie if two patients have the same slack. The slack time is calculated using the following equation:
Slack time = Due time - (Arrival time + Treatment time)
Due time is the clinic closing time. To explain how the process works, assume at hour 8:00 (in between 8:00 to 8:15) two patients in station 1 (one 8-­‐hour and one 15-­‐ minute patient), two patients in station 2 (two 12-­‐hour patients), two patients in station 3 (one 2-­‐hour and one 15-­‐ minute patient) and one patient in station 4 (one 3-­‐hour patient) in total seven patients are scheduled. According to Figure 2, there are seven nurses who are available at 8:00 and it takes 15 minutes to set-­‐up a patient. Therefore, it is not possible to schedule more than seven patients in between 8:00 to 8:15 and the current scheduling is also serving seven patients by this time. The rest of the template can be justified similarly.
doi:10.4066/AMJ.2011.837
PMCID: PMC3562880  PMID: 23386870
13.  Comparison of out of hours care provided by patients' own general practitioners and commercial deputising services: a randomised controlled trial. II: The outcome of care. 
BMJ : British Medical Journal  1997;314(7075):190-193.
OBJECTIVE: To compare the outcome of out of hours care given by general practitioners from patients' own practices and by commercial deputising services. DESIGN: Randomised controlled trial. SETTING: Four urban areas in Manchester, Salford, Stockport, and Leicester. SUBJECTS: 2152 patients who requested out of hours care, and 49 practice doctors and 183 deputising doctors (61% local principals in general practice) who responded to the requests. MAIN OUTCOME MEASURES: Health status outcome, patient satisfaction, and subsequent health service use. RESULTS: Patients seen by deputising doctors were less satisfied with the care they received. The mean overall satisfaction score for practice doctors was 70.7 (95% confidence interval 68.1 to 73.2) and for deputising doctors 61.8 (59.9 to 63.7). The greatest difference in satisfaction was with the delay in visiting. There were no differences in the change in health or overall health status measured 24 to 120 hours after the out of hours call or subsequent use of the health service in the two groups. CONCLUSIONS: Patients are more satisfied with the out of hours care provided by practice doctors than that provided by deputising doctors. Organisation of doctors into large groups may produce lower levels of patient satisfaction, especially when associated with increased delays in the time taken to visit. There seem to be no appreciable differences in health outcome between the two types of service.
PMCID: PMC2125654  PMID: 9022435
14.  GP and nurses' perceptions of how after hours care for people receiving palliative care at home could be improved: a mixed methods study 
BMC Palliative Care  2009;8:13.
Background
Primary health care providers play a dominant role in the provision of palliative care (PC) in Australia but many gaps in after hours service remain. In some rural areas only 19% of people receiving palliative care achieve their goal of dying at home. This study, which builds on an earlier qualitative phase of the project, investigates the gaps in care from the perspective of general practitioners (GPs) and PC nurses.
Methods
Questionnaires, developed from the outcomes of the earlier phase, and containing both structured and open ended questions, were distributed through Divisions of General Practice (1 urban, 1 rural, 1 mixed) to GPs (n = 524) and through a special interest group to palliative care nurses (n = 122) in both rural and urban areas.
Results
Questionnaires were returned by 114 GPs (22%) and 52 nurses (43%). The majority of GPs were associated with a practice which provided some after hours services but PC was not a strong focus for most. This was reflected in low levels of PC training, limited awareness of the existence of after hours triage services in their area, and of the availability of Enhanced Primary Care (EPC) Medicare items for care planning for palliative patients. However, more than half of both nurses and GPs were aware of accessible PC resources.
Factors such as poor communication and limited availability of after hours services were identified the as most likely to impact negatively on service provision. Strategies considered most likely to improve after hours services were individual patient protocols, palliative care trained respite carers and regular multidisciplinary meetings that included the GP.
Conclusion
While some of the identified gaps can only be met by long term funding and policy change, educational tools for use in training programs in PC for health professionals, which focus on the utilisation of EPC Medicare items in palliative care planning, the development of advance care plans and good communication between members of multidisciplinary teams, which include the GP, may enhance after hours service provision for patients receiving palliative care at home. The role of locums in after PC is an area for further research
doi:10.1186/1472-684X-8-13
PMCID: PMC2753575  PMID: 19751527
15.  Computer assisted assessment and advice for "non-serious" 999 ambulance service callers: the potential impact on ambulance despatch 
Emergency Medicine Journal : EMJ  2003;20(2):178-183.
Design: Pragmatic controlled trial. Calls identified using priority dispatch protocols as non-serious were allocated to intervention and control groups according to time of call. Ambulance dispatch occurred according to existing procedures. During intervention sessions, nurses or paramedics within the control room used a computerised decision support system to provide telephone assessment, triage and, if appropriate, offer advice to permit estimation of the potential impact on ambulance dispatch.
Setting: Ambulance services in London and the West Midlands.
Subjects: Patients for whom emergency calls were made to the ambulance services between April 1998 and May 1999 during four hour sessions sampled across all days of the week between 0700 and 2300.
Main outcome measures: Triage decision, ambulance cancellation, attendance at an emergency department.
Results: In total, there were 635 intervention calls and 611 controls. Of those in the intervention group, 330 (52.0%) were triaged as not requiring an emergency ambulance, and 119 (36.6%) of these did not attend an emergency department. This compares with 55 (18.1%) of those triaged by a nurse or paramedic as requiring an ambulance (odds ratio 2.62; 95% CI 1.78 to 3.85). Patients triaged as not requiring an emergency ambulance were less likely to be admitted to an inpatient bed (odds ratio 0.55; 95% CI 0.33 to 0.93), but even so 30 (9.2%) were admitted. Nurses were more likely than paramedics to triage calls into the groups classified as not requiring an ambulance. After controlling for age, case mix, time of day, day of week, season, and ambulance service, the results of a logistic regression analysis revealed that this difference was significant with an odds ratio for nurses:paramedics of 1.28 (95% CI 1.12 to 1.47).
Conclusions: The findings indicate that telephone assessment of Category C calls identifies patients who are less likely to require emergency department care and that this could have a significant impact on emergency ambulance dispatch rates. Nurses were more likely than paramedics to assess calls as requiring an alternative response to emergency ambulance despatch, but the extent to which this relates to aspects of training and professional perspective is unclear. However, consideration should be given to the acceptability, reliability, and cost consequences of this intervention before it can be recommended for full evaluation.
doi:10.1136/emj.20.2.178
PMCID: PMC1726071  PMID: 12642540
16.  Use of deputising services and night visit rates in general practice. 
Examining all of the claim forms for night visits submitted to the Nottingham Family Practitioner Committee over a three month period allowed us to calculate the night visit rate for all 184 practices in Nottinghamshire. To take all of the practices together the mean night visit rate (covering all visits requested and made between 11 00 pm and 7 00 am) was 15.5 visits per 1000 patients a year, range 1.2 to 46.1. Whether or not a deputising service is used accounted for 12% of the total variance detected, while the other factors studied, such as area of practice, patient list size, and number of partners, accounted for approximately 1% each. The local deputising service responds to 97% of night calls with a visit to the patient, whereas the patient's own doctor is more likely to provide advice over the telephone. The ability to provide telephone advice, however, will vary according to the breakdown of the practice by age and social class.
PMCID: PMC1442538  PMID: 6432147
17.  Factors which influence the length of an out-of-hours telephone consultation in primary care: a retrospective database study 
Background
Given the increasing use of telephone consultation it is important to determine the factors which influence the length of a telephone consultation.
Method
Analysis of 128717 telephone consultations during January to December 2011 to a National Health Service (NHS) out-of-hours primary care service provider in Shropshire and Telford and Powys, England, involving 102 General Practitioners (GPs) and 36 Nurse Practitioners (NPs). Telephone consultation conclude with one of three outcomes – advice only, the patient is invited to a face-to-face consultation with a GP or NP at a nearby health centre (known as a base visit) or the patient is visited at home by a GP or NP (known as home visit). Call length was analysed by these outcomes.
Results
The overall mean call length was 7.78 minutes (standard deviation (SD) 4.77). Calls for advice only were longest (mean 8.11 minutes, SD 5.17), followed by calls which concluded with a base visit (mean 7.36 minutes, SD 4.08) or a home visit (mean 7.16 minutes, SD 4.53). Two primary factors influenced call length. Calls by GPs were shorter (mean 7.15 minutes, SD 4.41) than those by NPs (mean 8.74 minutes, SD 5.31) and calls designated as a mental health call were longer (mean 11.16 minutes, SD 4.75) than all other calls (mean 7.73 minutes, SD 7.7).
Conclusions
Telephone consultation length in the out-of-hours setting is influenced primarily by whether the clinician is a GP or a NP and whether the call is designated as a mental health call or not. These findings suggest that appropriate attempts to reduce the length of the telephone consultations should focus on these two areas, although the longer consultation length associated with NPs is offset to some extent by their lower employment costs compared to GPs. Nonetheless the extent to which the length of a telephone consultation impacts on subsequent use of the health service and correlates with quality and safety remains unclear.
doi:10.1186/1472-6963-12-430
PMCID: PMC3542015  PMID: 23181707
Telephone consultation; Duration; Efficiency; Nurse practitioner; General practitioner; Out-of-hours; After-hours; Emergency care; Primary care; Telephone; Triage
18.  Users' reports and evaluations of out-of-hours health care and the UK national quality requirements: a cross sectional study 
Background
National standards for delivery of out-of-hours services have been refined. Health service users' preferences, reports, and evaluations of care are of importance in a service that aims to be responsive to their needs.
Aim
To investigate NHS service users' reports and evaluations of out-of-hours care in the light of UK national service quality requirements.
Design
Cross sectional survey.
Setting
Three areas (Devon, Cornwall, Sheffield) of England, UK.
Method
Participants were 1249 recent users of UK out-of-hours medical services. Main outcome measures were: users' reports and evaluations of out-of-hours services in respect of the time waiting for their telephone call to the service to be answered; the length of time from the end of the initial call to the start of definitive clinical assessment (‘call back time’); the time waiting for a home visit; and the waiting time at a treatment centre.
Results
UK national quality requirements were reported as being met by two-thirds of responders. Even when responders reported that they had received the most rapid response option for home visiting (waiting time of ‘up to an hour’), only one-third of users reported this as ‘excellent’. Adverse evaluations of care were consistently related to delays encountered in receiving care and (for two out of four measures) sex of patient. For 50% of users to evaluate their care as ‘excellent’, this would require calls to be answered within 30 seconds, call-back within 20 minutes, time spent waiting for home visits of significantly less than 1 hour, and treatment centre waiting times of less than 20 minutes.
Conclusion
Users have high expectations of UK out-of-hours healthcare services. Service provision that meets nationally designated targets is currently judged as being of ‘good’ quality by service users. Attaining ‘excellent’ levels of service provision would prove challenging, and potentially costly. Delivering services that result in high levels of user satisfaction with care needs to take account of users' expectations as well as their experience of care.
doi:10.3399/bjgp09X394815
PMCID: PMC2605546  PMID: 19105911
out-of-hours medical care; primary care; quality of health care; questionnaire; satisfaction; standards; unscheduled care
19.  Nurse telephone triage for same day appointments in general practice: multiple interrupted time series trial of effect on workload and costs 
BMJ : British Medical Journal  2002;325(7374):1214.
Objective
To compare the workloads of general practitioners and nurses and costs of patient care for nurse telephone triage and standard management of requests for same day appointments in routine primary care.
Design
Multiple interrupted time series using sequential introduction of experimental triage system in different sites with repeated measures taken one week in every month for 12 months.
Setting
Three primary care sites in York.
Participants
4685 patients: 1233 in standard management, 3452 in the triage system. All patients requesting same day appointments during study weeks were included in the trial.
Main outcome measures
Type of consultation (telephone, appointment, or visit), time taken for consultation, presenting complaints, use of services during the month after same day contact, and costs of drugs and same day, follow up, and emergency care.
Results
The triage system reduced appointments with general practitioner by 29-44%. Compared with standard management, the triage system had a relative risk (95% confidence interval) of 0.85 (0.72 to 1.00) for home visits, 2.41 (2.08 to 2.80) for telephone care, and 3.79 (3.21 to 4.48) for nurse care. Mean overall time in the triage system was 1.70 minutes longer, but mean general practitioner time was reduced by 2.45 minutes. Routine appointments and nursing time increased, as did out of hours and accident and emergency attendance. Costs did not differ significantly between standard management and triage: mean difference £1.48 more per patient for triage (95% confidence interval –0.19 to 3.15).
Conclusions
Triage reduced the number of same day appointments with general practitioners but resulted in busier routine surgeries, increased nursing time, and a small but significant increase in out of hours and accident and emergency attendance. Consequently, triage does not reduce overall costs per patient for managing same day appointments.
What is already known on this topicNurse telephone triage is used to manage the increasing demand for same day appointments in general practiceEvidence that nurse telephone triage is effective is limitedWhat this study addsTriage resulted in 29-44% fewer same day appointments with general practitioners than standard managementNursing and overall time increased in the triage group as 40% of patients were managed by nursesTriage was not less costly than standard management because of increased costs for nursing, follow up, out of hours, and accident and emergency care
PMCID: PMC135495  PMID: 12446539
20.  Safety of telephone consultation for "non-serious" emergency ambulance service patients 
Quality & safety in health care  2004;13(5):363-373.
Objective: To assess the safety of nurses and paramedics offering telephone assessment, triage, and advice as an alternative to immediate ambulance despatch for emergency ambulance service callers classified by lay call takers as presenting with "non-serious" problems (category C calls).
Design: Data for this study were collected as part of a pragmatic randomised controlled trial reported elsewhere. The intervention arm of the trial comprised nurse or paramedic telephone consultation using a computerised decision support system to assess, triage, and advise patients whose calls to the emergency ambulance service had been classified as "non-serious" by call takers applying standard priority despatch criteria. A multidisciplinary expert clinical panel reviewed data from ambulance service, accident and emergency department, hospital inpatient and general practice records, and call transcripts for patients triaged by nurses and paramedics into categories that indicated that despatch of an emergency ambulance was unnecessary. All cases for which one or more members of the panel rated that an emergency ambulance should have been despatched were re-reviewed by the entire panel for an assessment of the "life risk" that might have resulted.
Setting: Ambulance services in London and the West Midlands, UK.
Study population: Of 635 category C patients assessed by nurses and paramedics, 330 (52%) cases that had been triaged as not requiring an emergency ambulance were identified.
Main outcome measures: Assessment of safety of triage decisions.
Results: Sufficient data were available from the routine clinical records of 239 (72%) subjects to allow review by the specialist panel. For 231 (96.7%) sets of case notes reviewed, the majority of the panel concurred with the nurses' or paramedics' triage decision. Following secondary review of the records of the remaining eight patients, only two were rated by the majority as having required an emergency ambulance within 14 minutes. For neither of these did a majority of the panel consider that the patient would have been at "life risk" without an emergency ambulance being immediately despatched. However, the transcripts of these two calls indicated that the correct triage decision had been communicated to the patient, which suggests that the triage decision had been incorrectly entered into the decision support system.
Conclusions: Telephone advice may be a safe method of managing many category C callers to 999 ambulance services. A clinical trial of the full implementation of this intervention is needed, large enough to exclude the possibility of rare adverse events.
doi:10.1136/qshc.2003.008003
PMCID: PMC1743899  PMID: 15465940
21.  Investigating the cost-effectiveness of videotelephone based support for newly diagnosed paediatric oncology patients and their families: design of a randomised controlled trial 
Background
Providing ongoing family centred support is an integral part of childhood cancer care. For families living in regional and remote areas, opportunities to receive specialist support are limited by the availability of health care professionals and accessibility, which is often reduced due to distance, time, cost and transport. The primary aim of this work is to investigate the cost-effectiveness of videotelephony to support regional and remote families returning home for the first time with a child newly diagnosed with cancer
Methods/design
We will recruit 162 paediatric oncology patients and their families to a single centre randomised controlled trial. Patients from regional and remote areas, classified by Accessibility/Remoteness Index of Australia (ARIA+) greater than 0.2, will be randomised to a videotelephone support intervention or a usual support control group. Metropolitan families (ARIA+ ≤ 0.2) will be recruited as an additional usual support control group. Families allocated to the videotelephone support intervention will have access to usual support plus education, communication, counselling and monitoring with specialist multidisciplinary team members via a videotelephone service for a 12-week period following first discharge home. Families in the usual support control group will receive standard care i.e., specialist multidisciplinary team members provide support either face-to-face during inpatient stays, outpatient clinic visits or home visits, or via telephone for families who live far away from the hospital. The primary outcome measure is parental health related quality of life as measured using the Medical Outcome Survey (MOS) Short Form SF-12 measured at baseline, 4 weeks, 8 weeks and 12 weeks. The secondary outcome measures are: parental informational and emotional support; parental perceived stress, parent reported patient quality of life and parent reported sibling quality of life, parental satisfaction with care, cost of providing improved support, health care utilisation and financial burden for families.
Discussion
This investigation will establish the feasibility, acceptability and cost-effectiveness of using videotelephony to improve the clinical and psychosocial support provided to regional and remote paediatric oncology patients and their families.
doi:10.1186/1472-6963-7-38
PMCID: PMC1821320  PMID: 17335589
22.  The effects of telephone consultation and triage on healthcare use and patient satisfaction: a systematic review 
Background
In recent years there has been a growth in the use of the telephone consultation for healthcare problems. This has developed, in part, as a response to increased demand for GP and accident and emergency department care.
Aim
To assess the effects of telephone consultation and triage on safety, service use, and patient satisfaction.
Design of study
We looked at randomised controlled trials, controlled studies, controlled before/after studies, and interrupted time series of telephone consultation or triage in a general healthcare setting.
Setting
All healthcare settings were included but the majority of studies were in primary care.
Method
We searched the Cochrane Central Register of Controlled Trials, EPOC specialised register, PubMed, EMBASE, CINAHL, SIGLE, and the National Research Register and checked reference lists of identified studies and review articles. Two reviewers independently screened studies for inclusion, extracted data, and assessed study quality.
Results
Nine studies met our inclusion criteria: five randomised controlled trials; one controlled trial; and three interrupted time series. Six studies compared telephone consultation with normal care; four by a doctor, one by a nurse, and one by a clinic clerk. Three of five studies found a significant decrease in visits to GPs but two found an increase in return consultations. In general at least 50% (range = 25.5–72.2%) of calls were handled by telephone consultation alone. Of seven studies reporting accident and emergency department visits, six showed no difference between the groups and one — of nurse telephone consultation — found an increase. Two studies reported deaths and found no difference between nurse telephone consultation and normal care.
Conclusions
Although telephone consultation appears to have the potential to reduce GP workload, questions remain about its effect on service use. Further rigorous evaluation is needed with emphasis on service use, safety, cost, and patient satisfaction.
PMCID: PMC1570504  PMID: 16378566
consultation; hotlines; review, systematic; telephone; triage
23.  Scheduled telephone visits in the veterans health administration patient-centered medical home 
Background
The Veterans Health Administration (VHA) patient-centered medical home model, Patient Aligned Care Teams (PACT), includes telephone visits to improve care access and efficiency. Scheduled telephone visits can replace in-person care for some focused issues, and more information is needed to understand how this mode can best work for primary care. We conducted a study at the beginning of PACT implementation to elicit stakeholder views on this mode of healthcare delivery, including potential facilitators and barriers.
Methods
We conducted focus groups with primary care patients (n = 3 groups), providers (n = 2 groups) and staff (n = 2 groups). Questions were informed by Donabedian’s framework to evaluate and improve healthcare quality. Content analysis and theme matrix techniques were used to explore themes. Content was assigned a positive or negative valuation to indicate whether it was a facilitator or barrier. PACT principles were used as an organizing framework to present stakeholder responses within the context of the VHA patient-centered medical home program.
Results
Scheduled telephone visits could potentially improve care quality and efficiency, but stakeholders were cautious. Themes were identified relating to the following PACT principles: comprehensiveness, patient-centeredness, and continuity of care. In sum, scheduled telephone visits were viewed as potentially beneficial for routine care not requiring physical examination, and patients and providers suggested using them to evaluate need for in-person care; however, visits would need to be individualized, with patients able to discontinue if not satisfied. Patients and staff asserted that providers would need to be kept in the loop for continuity of care. Additionally, providers and staff emphasized needing protected time for these calls.
Conclusion
These findings inform development of scheduled telephone visits as part of patient-centered medical homes by providing evidence about areas that may be leveraged to most effectively implement this mode of care. Presenting this service as enhanced care, with ability to triage need for in-person clinic visits and consequently provide more frequent contact, may most adequately meet different stakeholder expectations. In this way, scheduled telephone visits may serve as both a substitute for in-person care for certain situations and a supplement to in-person interaction.
doi:10.1186/1472-6963-14-145
PMCID: PMC3976456  PMID: 24690086
Health services research; Telemedicine; Primary care
24.  The FEeding Support Team (FEST) randomised, controlled feasibility trial of proactive and reactive telephone support for breastfeeding women living in disadvantaged areas 
BMJ Open  2012;2(2):e000652.
Objective
To assess the feasibility of implementing a dedicated feeding support team on a postnatal ward and pilot the potential effectiveness and cost-effectiveness of team (proactive) and woman-initiated (reactive) telephone support after discharge.
Design
Randomised controlled trial embedded within a before-and-after study. Participatory approach and mixed-method process evaluation.
Setting
A postnatal ward in Scotland.
Sample
Women living in disadvantaged areas initiating breast feeding.
Methods
Eligible women were recruited to a before-and-after intervention study, a proportion of whom were independently randomised after hospital discharge to intervention: daily proactive and reactive telephone calls for ≤14 days or control: reactive telephone calls ≤ day 14. Intention-to-treat analysis compared the randomised groups on cases with complete outcomes at follow-up.
Main outcome measures
Primary outcome: any breast feeding at 6–8 weeks assessed by a telephone call from a researcher blind to group allocation. Secondary outcomes: exclusive breast feeding, satisfaction with care, NHS costs and cost per additional woman breast feeding.
Results
There was no difference in feeding outcomes for women initiating breast feeding before the intervention (n=413) and after (n=388). 69 women were randomised to telephone support: 35 intervention (32 complete cases) and 34 control (26 complete cases). 22 intervention women compared with 12 control women were giving their baby some breast milk (RR 1.49, 95% CI 0.92 to 2.40) and 17 intervention women compared with eight control women were exclusively breast feeding (RR 1.73, 95% CI 0.88 to 3.37) at 6–8 weeks after birth. The incremental cost of providing proactive calls was £87 per additional woman breast feeding and £91 per additional woman exclusively breast feeding at 6–8 weeks; costs were sensitive to service organisation.
Conclusions
Proactive telephone care delivered by a dedicated feeding team shows promise as a cost-effective intervention for improving breastfeeding outcomes. Integrating the FEeding Support Team (FEST) intervention into routine postnatal care was feasible.
Trial registration number
ISRCTN27207603. The study protocol and final report are available on request.
Article summary
Article focus
To pilot the potential effectiveness and cost-effectiveness of continuing proactive and reactive telephone support for breast feeding for up to 14 days after hospital discharge for women living in more disadvantaged areas.
To assess the feasibility of implementing a dedicated feeding team on a postnatal ward.
To design an effective health service intervention for infant feeding by re-organising how routine care is provided to inform a larger programme of research.
Key messages
Proactive telephone care delivered by a dedicated feeding team shows promise for increasing breastfeeding rates 6–8 weeks after birth.
Only having a dedicated feeding team on a postnatal ward did not appear to make any difference to feeding outcomes at 6–8 weeks after birth.
We have demonstrated the feasibility of (1) implementing the FEeding Support Team intervention as part of routine postnatal care and (2) the recruitment and data collection processes for a proposed definitive trial.
Strengths and limitations of this study
Using a participatory approach and embedding a rigorous randomised control trial within a before-and-after cohort study with mixed methods data to evaluate costs are strengths that will enable us to design a definitive trial.
It is likely that the effect sizes are overestimated as the sample size was small and no sample size calculation was performed prior to the study.
Our sample included women requiring longer hospital stays due to birth complications.
The reactive call service was only free to those who had the same mobile phone network provider.
The incremental cost-effectiveness ratios presented represent the most favourable set of assumptions for proactive telephone support and are sensitive to how the service is organised.
doi:10.1136/bmjopen-2011-000652
PMCID: PMC3341594  PMID: 22535790
25.  NHS and an SME cooperating on telehealth innovation 
Introduction
Telehealth is an ideal way to lessen the burden on healthcare provision whilst empowering the patient with greater independence, assurance and control. This paper describes the joint development project between NHS South Central SHA Innovation Team and Solcom Limited, an SME specialising in bringing latest Information Technologies to healthcare.
Aims and objectives
The aim of the project was to develop a low-cost Telehealth solution that makes the roll-out of Telehealth services easy and economical. The idea was to use the latest IT and communications technologies to achieve those aims. The clinician monitoring solution is internet cloud based whilst patients utilise 3G smartphones. It is also open for connection to other solutions already used by the NHS and is now connected to the Florence™ SMS based system developed by the NHS Stoke-on-Trent Simple Telehealth Program.
Results
The result of the project is a Telehealth market cost and technology leader service Whzan Telehealth Service. Whzan Telehealth is:
Budget friendly, the service starting from £1 a day
Portable and easy to use via a smartphone or tablet PCs
Deployed from the surgery without any home installation
Flexible for users and healthcare professionals alike
Disease and instrumentation agnostic
Uniquely applicable to extended patient groups, such as dementia sufferers, expectant others and post-operative early release patients
Secure and personalised for all users
Multi-lingual serving ethnic minorities and user-friendly for patients with dementia, motor-skill problems or who are partially sighted
Conclusions
Whzan Telehealth Service has now been used by a number of patients with long-term chronic conditions and monitored on a PCT level. A GP has deployed the service to ‘Frequent flyer’ COPD patient having 2–4 unplanned hospital admissions a week resulting in a dramatic total cessation of emergency calls. One admission costs the NHS more than 3 years of the Whzan service. It is about to be deployed to post-operative patients released early from hospital. Patients find Whzan Telehealth easy and discreet to use. They like the security offered by a Telehealth service at the same time as they appreciate the freedom provided by the portability of Whzan. The carry case for instruments is seen as practical and helping keep the monitoring discreet. Non-native English speakers in the patient group have encouraged the development of the audible and written instructions in multiple languages. A simple user interface is clear and understandable and patients are able to use the system after a very brief demonstration. Instrumentation is wireless and operation is completely automatic. Healthcare professionals appreciate the simplicity in deployment as patients can literally walk out of their appointments with the Whzan carry out pack and use the service at home. Patient management is via a web-based triage system showing everything from patient readings to equipment battery status. Clinicians can remotely change the measurement regime to suit the patient’s symptoms. Whzan also links to a third party interactive voice telephone system that can be used to provide alerts or front line patient management.
PMCID: PMC3571153
SME; telehealth; innovation; portability; multi-lingual

Results 1-25 (736658)