Allied Health Data Insights
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Tamzin Brott (Waitemata DHB) & Rebecca George (CDHB) - HiNZ 2015 Conference, Christchurch
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Allied Health Data Insights
- 1. SHAPING INFORMATICS FOR ALLIED HEALTH REFINING OUR VOICE Tamzin Brott, Waitemata DHB Rebecca George, Canterbury DHB
- 2. SHAPING INFORMATICS AND REFINING OUR VOICE 1. Introduction 2. History of Allied Health and data 3. Shaping vs. defining 4. Relevancy of Informatics (Break) 5. Current examples and projects – sharing of experience 6. Future of Informatics in Allied Health 7. Takeaways
- 3. A HISTORY OF ALLIED HEALTH • Broad ‘umbrella’ term • Diverse mix of professional disciplines • Not homogeneous • Frequently defined by exception • Shared aim - culture of Allied Health professions being ‘allied to each other’
- 4. TRADITIONAL APPROACH – DATA FOR DATA’S SAKE • Contacts – disappeared into the ether? • Meaningless numbers • Numerous Approaches - PIMS, CaseMix, manual, electronic • Numerous measurements – minutes, blocks, days wait, priority • Business vs Clinical • Process/structure outcomes vs clinical and patient experience outcomes
- 5. QUALITY IN ALLIED HEALTH
- 6. QUALITY IN ALLIED HEALTH – ACHIEVING A BALANCE
- 7. SHAPING VS. DEFINING “The use of technology and data, providing information to generate knowledge, that in application drives change’’
- 8. SHAPING VS. DEFINING • Identify need – create questions • Data visualisation methods • Application – effect change or support status
- 9. SHAPING VS. DEFINING • Apples with apples • Health Round Table • National Allied Health Data Collaborative • Standardisation • benchmarking, best practice, service equity
- 10. NATIONAL ALLIED HEALTH DATA COLLABORATIVE • Purpose • Coordination, transparency, ownership • Function • Sharing, standardisation, benchmarking, collaboration • Vision ‘To create a culture of inspired Allied Health staff who regularly inform their practice with knowledge made available via data collection’
- 11. NATIONAL AUDIT AND RESULTS • Objective • Method • Results • Who • How • When • What
- 12. RESULTS Top: Responding clinical service setting Bottom: Frequency of data collection
- 13. WHOSE RESPONSIBILITY IS IT? Data entry 50% Highest percentage were Admin staff 28% Combination of clinical and admin staff 21% Clinician only 11% No one entering referral information Top 5 Data fields NHI 91% Location 86% Date received 81% Date actioned 75% Reason for referral 75%
- 14. AUDIT CONCLUSIONS: Indicators suggested common data content Significant differences indicated, include: • Service Settings Who • Content consistency What • Use / analysis Why • Data collection methods How
- 15. AUDIT CONCLUSIONS: • Standardisation of data will bring; • A greater breadth of data • Robust analysis • Strength in application
- 16. THE RELEVANCY OF DATA AND INFORMATICS NOW Why the emphasis now? • Explosion of IT development • Patient journey visibility • Powerful analysis • Ownership versus input
- 17. AIMS: Visibility of information ‘Passive data collection’ Relevant reporting Regular application of knowledge acquired What is your current reality? How does it shape up against your vision?
- 20. INFORMING OUR STAFF - DATA VISUALISATION
- 22. JULY 2012 - MARCH 2015
- 23. COLLABORATIVE DATA • A single public house block • $12m 2002-2008 • Population type • Focused solution
- 24. DATA EXAMPLES….
- 25. USING MOBILE TECHNOLOGY TO IMPROVE PATIENT AND CLINICIAN EXPERIENCES OF ALLIED HEALTH IN THE COMMUNITY SETTING (WAITEMATA DHB) Key Problem: Increasing community waiting lists across all AH disciplines No increase in FTE to match volumes from new inpatient services Clinicians required to return to base in order to complete electronic records No real time access to health information at the point of care and decision making in the community Increase in part time workers leading to less access to infrastructure
- 26. USING MOBILE TECHNOLOGY TO IMPROVE PATIENT AND CLINICIAN EXPERIENCES OF ALLIED HEALTH IN THE COMMUNITY SETTING (WAITEMATA DHB) Improve clinician workflow Provide real time access to health information at the point of care and decision making Improve patient experience Meet needs more fully during visit with real time access to health information Improve clinician experience Provide clinicians with opportunity to complete administration tasks on the road
- 27. USING MOBILE TECHNOLOGY TO IMPROVE PATIENT AND CLINICIAN EXPERIENCES OF ALLIED HEALTH IN THE COMMUNITY SETTING (WAITEMATA DHB) Baseline Data: Average time spent on patient related administration tasks ranged from 182 minutes to 288.7 minutes per clinician per day (mean=182. 8 minutes, median=165 minutes) 50% participants believed being able to access Concerto (electronic documentation) in the community could absolutely improve their workflow Above average levels of enthusiasm to trial mobile devices in the community
- 28. USING MOBILE TECHNOLOGY TO IMPROVE PATIENT AND CLINICIAN EXPERIENCES OF ALLIED HEALTH IN THE COMMUNITY SETTING (WAITEMATA DHB) • 12 community allied health clinicians were provided with real time access to clinical documentation and peer reviewed discipline specific apps via an iPad air • Three data measures were collected over a 19-week period: Week 1-2 Time & motion study Clinician questionnaire Week 10-11 Time & motion study Clinician questionnaire Patient questionnaire Week 18-19 Time & motion study Clinician questionnaire Patient questionnaire
- 29. USING MOBILE TECHNOLOGY TO IMPROVE PATIENT AND CLINICIAN EXPERIENCES OF ALLIED HEALTH IN THE COMMUNITY SETTING (WAITEMATA DHB) • Collected 270 days of time and motion data, including 493 direct face-to-face patient contacts. Improved clinician workflow • Reduced time spent on administration tasks by average of 29 minutes per clinician per day • Utilisation of time between visits to complete administration tasks Improved patient experience • 101 patients completed survey • 93% reported improved experience when mobile device used • 93% rated comfort with mobile device in home as 7/7 Improved clinician job satisfaction • Reported reduction in stress levels • Able to take breaks as a result of time saved • Improved clinical practice associated with education and therapy apps
- 30. USING MOBILE TECHNOLOGY TO IMPROVE PATIENT AND CLINICIAN EXPERIENCES OF ALLIED HEALTH IN THE COMMUNITY SETTING (WAITEMATA DHB) Patients have told us; Patients said: Clinicians said:Time & motion data 182.8 171.6 153.6 135 140 145 150 155 160 165 170 175 180 185 Baseline Midway Final Mean time spent on patient related administration tasks (minutes per day) “seeing the muscles on the iPad really helped me understand the importance of the exercises” “knowing my notes were being written then and there I felt my issues were acknowledged” “instead of checking and getting back to me you get answers right now” “Now I can complete my notes and have time for a lunch break and don’t leave work feeling burnt out and resentful” “I can do my documentation or equipment ordering or phone calls between patient visits and I have time for urgent issues or colleagues in need of peer advice when I return to base” “I feel I am providing a better service as a health professional”
- 31. USING MOBILE TECHNOLOGY TO IMPROVE PATIENT AND CLINICIAN EXPERIENCES OF ALLIED HEALTH IN THE COMMUNITY SETTING (WAITEMATA DHB) Key outcomes for clinicians • 81.8% increased their direct face-to-face patient contact time • 13 minute average increase in direct face-to-face patient contact per clinician per day, equating to 65 minutes, per week for a full time clinician. • 90.9% reduced time spent on patient related administration • 26.7 minute average reduction of patient related administration of per clinician per day, equating to 133.7 minutes, per week for a full time clinician. • 45.4% reduced their travel time by a combined daily average of 55.8 minutes per day • Next Steps…
- 32. REDUCING HOSPITAL ACQUIRED PNEUMONIA FOR STROKE (WAITEMATA DHB)
- 33. REDUCING HOSPITAL ACQUIRED PNEUMONIA FOR STROKE (WAITEMATA DHB)
- 34. REDUCING HOSPITAL ACQUIRED PNEUMONIA FOR STROKE (WAITEMATA DHB)
- 35. AMAU REFERRAL AUDIT • Purpose of AMAU • rapid medical assessment unit, focussing on managing medical patients often with an undifferentiated diagnosis who need prompt investigation and treatment, and timely medical, nursing and Allied Health assessment • First year report = exploration of ‘front loading’ with Allied Health to: • Support implementation of Frail Older Persons Pathway • Assess and determine the needs of acutely unwell patients – right time, right place
- 36. AMAU REFERRAL AUDIT • We wanted to know: • What was the volume of referrals for Allied Health services over a 2 week period? • Is there sufficient Service provision to meet AMAU referral demand? • A referral audit completed over a 2 week period (inclusive of weekends) during July 2014 by each Allied Health discipline receiving AMAU referrals and providing service.
- 37. AMAU REFERRAL AUDIT • Allied Health referrals in AMAU
- 38. AMAU REFERRAL AUDIT • Accepted Allied Health referrals in AMAU
- 40. AMAU REFERRAL AUDIT • Allied Health Service Provision – When does it occur and what’s the unmet need?
- 41. AMAU REFERRAL AUDIT • When are referrals made – day of week and hours?
- 42. AMAU REFERRAL AUDIT • Unmet need outside of usual work hours?
- 43. AMAU REFERRAL AUDIT - SUMMARY • Three key issues identified: 1. More referrals made than accepted 2. Majority of referrals made are initiated outside of usual work hours 3. A significant number of patients transferred/discharged prior to their referral being processed by Allied Health • Inferences made; • A large amount of time may be being spent processing referrals for non existing patients • Referrals may be being made too early / out of context to the patient’s status • Patients are being transferred / discharged off AMAU before AH provision
- 44. WEEKEND SERVICE DEMAND AUDIT • To support the ‘Allied Health Weekend Service Rostering and extended hours service provision’ business case. • To provide an understanding of AH service provision; • during ‘weekend’ hours • how staffing can be streamlined to provide this service effectively.
- 45. WEEKEND AUDIT RESULTS: Total Per weekend % of total Total patients referred for service (exc. SLT) over 2 weekends across all disciplines 275 137.5 Total number of contacts 324 162 Ave. No. patients per Saturday for all disciplines (exc. SLT) 76.5 Saturday 56% Ave. No. patients per Sunday for all disciplines (exc. SLT) 61 Sunday 44%
- 46. LOCATION OF SERVICE DEMAND • ICU, Orthopaedics (18/19) and ED highest volume • Different locations focus for different professions • Significant lack of demand from high turnover wards i.e. 23/24 • Good MDT input in AMAU • Potential for greater MDT input into Acute Stroke Unit
- 47. FOCUS OF SERVICE • Physiotherapy and Dietetics - majority of follow up contacts • OT and SW – new patients and assessments • Physiotherapy discharged a greater number of patients • OT and SW had larger proportion of discharges overall.
- 48. WEEKEND AUDIT OUTCOMES • Requirement for operational standardisation of staffing resource • Discussion of service deliver y models • Full service all areas • Criteria limited service to all areas • Full service to limited areas • Identification that AH are not inhibiting patient flow
- 49. KEY QUESTIONS… • Who or what are you curious about? • What are the questions you want answers to? • What are the data elements needed to answer that question? • What information do you want to communicate? • Who do you want to communicate with once you have that information? • How are you going to communicate that information?
- 50. DISCUSSION TIME….. • A vision statement? • A project? • An intention with direction? • A need for Collaboration/Key contacts? • Group discussion time • 25 minutes • Draft • Present idea at the end
- 51. If you tell people where to go, but not how to get there you’ll be amazed at the results. George s Patton
- 52. PRESENTATIONS….. • Select one/two from each group
- 53. CONCLUSION • Get our business hats on • ‘Data provides Information, that gives us knowledge, upon which to act’ • Making the patient’s journey visible • Engagement and Integration • Involving ourselves in system development locally/regionally
- 54. CONTACT DETAILS • Rebecca George Clinical Lead - Informatics in Allied Health Allied Health Services Canterbury District Health Board Rebecca.george@cdhb.health.nz, (03) 364 4581 / 027 839 3196 • Tamzin Brott Head of Division Allied Health Medicine, Health of Older People & Surgical and Ambulatory Services Waitemata District Health Board Tamzin.brott@waitematadhb.govt.nz, (09) 442 7252 / 021 983 129
Editor's Notes
- Shaping telling the story …. Defining – identifying the data elements and structure
- Tamzin 1) Allied health, scientific and technical (AHST) is a broad ‘umbrella’ term used to refer to a collective of professionals who are distinct from nursing and medicine. Term AH has been around since the 1930’s The American Medical Ass began overseeing allied health education in the 1930s. During that decade, the American Occupational Therapy Association, the American Society for Clinical Pathology, and the American Physical Therapy Association all began working with the AMA Council on Medical Education on educational standards – progression towards the group now called AH 2) The collective of AH represents a diverse mix of professional disciplines, who work within and across complex multiagency teams, and who each offer distinct expertise, knowledge and skills. At WDHB we have 43 professional groups that sit under the umbrella of AH, S&T 3) AHST occupations and services are not homogenous; - general aim across the groups is to optimise physical, social, cognitive and psychological functional capacity, and quality of life, across the lifespan (ICHPO, 2012), with the patient being at the centre of their care. 4) There have been many attempts to define the allied health collective in the international literature; however lack of agreement remains. Allied health is frequently defined by exception rather than by a precise listing of professions and occupations – whose not included shared aim which is believed to create a culture of allied health professions being ‘allied to each other’ as opposed to ‘allied with medicine’ (Boyce, 2001).
- Tamzin
- Tamzin On the Left – what we know about quality in AH Not homogenous Tasks – lots Measures different Lack of agreement – which professions in the literature Unlikely 1 size fits all Tension – we need to demonstrate Reflect how delivering the board priorities Function – AH measure should – what a person (patient) achieves rather than the task
- Tamzin The Donabedian model is a conceptual model that provides a framework for examining health services and evaluating quality of health care. Avedis Donabedian, a physician and health services researcher at the University of Michigan, developed the original model in 1966. While there are other quality of care frameworks, including the World Health Organization (WHO)-Recommended Quality of Care Framework and the Bamako Initiative, the Donabedian Model continues to be the dominant paradigm for assessing the quality of health care. According to the model, information about quality of care can be drawn from three categories: “structure,” “process,” and “outcomes.“ Structure describes the context or attributes in which care is delivered, including hospital buildings, staff, financing, and equipment. Process denotes the transactions between patients and providers throughout the delivery of healthcare. Finally, outcomes refers to the effects or impact of care on the health status of patients and populations Outcome contains all the effects of healthcare on patients or populations, including changes to health status, behaviour, or knowledge as well as patient satisfaction and health-related quality of life. Outcomes are sometimes seen as the most important indicators of quality because improving patient health status is the primary goal of healthcare. However, accurately measuring outcomes that can be attributed exclusively to healthcare is very difficult. Although it is widely recognized and applied in many health care related fields, the Donabedian Model was developed to assess quality of care in clinical practice. The model does not have an implicit definition of quality care so that it can be applied to problems of broad or narrow scope.
- Defining….data, system knowledge, Shaping….in to knowledge….driving change Data for graphs….vs….visible interpretation - application
- Questions… What are the trends of AHP outcomes? Is there a correlation between number of contacts and ALOS?
- Consistency and standardisation…. Collaboration provides strength in numbers
- PURPOSE The purpose of the National Allied Health eHealth Collaborative is to; Bring together representatives of these groups in a discussion forum to foster information sharing; and Establish working groups as required to address issues raised at this meeting (e.g. clinical data sets). Make data collection and distribution more transparent and consistent Influence and shape what Allied Health provides to MOH and how MOH uses that data Establish a level of standardisation and consistency of Allied Health data Take ownership of Allied Health data collection FUNCTIONS Facilitate information sharing across organisations and jurisdictions on the following: eHealth in both the private and public sector Personal electronic health records Standardisation of information management across New Zealand including allied health data sets and business rules costing and pricing of allied health services; and Benchmarking of allied health activity. Reporting and making recommendations to member’s respective organisations based on the outcomes from these meetings. Oversee the development of a standard clinical data set for use in eHealth in the public sector, as a priority, and consider its use for the private sector. Promote the implementation of standardised allied health information across the health boards. Build collaboration and coordination between health boards and organisations in the fields of allied health eHealth and information management. VISION To create a culture of knowledgeable Allied Health staff who regularly use and inform their practice with the information and data available. To establish, maintain and develop a national data framework that informs local, regional and national bodies of the valuable work of Allied Health staff. To provide evidential data and information with which to collaborate with AH Professional Bodies and regional health systems on the development of standards, best practice and care pathways.
- Introduction The completion of this national audit was to provide a baseline of knowledge and information from which evidence would prove the variance in current practices. Objective To obtain from each Allied Health Service operating within a DHB information regarding the content, methods and processes by which they collect, process, analyse and use local data on Allied Health staff activity. Method A Google survey was created and the link distributed to an Allied Health contact within each of the DHBs, from which it was distributed at their discretion, within their Allied Health services. Results A significant number of 19 out of 20 DHBs submitted their responses to the Google survey with a total of 71 entries made. Contributed by Outpatient, Inpatient/Acute, and Community and ED service areas. 11 out 20 DHBs are currently submitting Allied Health data to the Health Round Table (HRT) but there was evident discrepancy within DHBs according to classifications used and data submitted. Individual Patient Attributable time (IPA) was the most prevalently recorded and it was recorded most often in Inpatient service settings. There were however differences between disciplines within the same service areas regarding those who have/have not got data definitions and guidelines in place. A variety of methods were identified to be in use for collecting data, but 50% of DHBs entered that a service used the same system, and 61% of responders reported daily entry and most of it (50%) being entered by administrative staff. Of the content or type of activity recorded a high number of responses recorded yes to all options, however of those activities there were far fewer positive responses to the analysis of that information. Therefore data is being recorded but not routinely used for analysis purposes. For the service areas indicating that time was recorded, most reported that actual minutes were entered.
- Either there are very few Emergency Departments collecting AH data or only 7 EDs have AH staff providing a service. Maori Health was included to incorporate those DHBs that have AH allocated to a Maori Health Service.
- Who – data entry What – internal, local consistency and national consistency Why – very few responses indicated analysis use and knowledge application in a structured way How – varied data collection methods – expected – locally and nationally
- Why emphasise data collection now? IT explosion and the potential for data capture Patient journey visibility – we are an integral part of the journey To capitalise on the wealth of information that can be captured through information online and feed into the development of our services Time for ownership not input eCHRs Passive Data Extraction
- Tamzin Key Problem Increasing community waiting lists across all AH disciplines No increase in FTE to match volumes from new inpatient services Clinicians required to return to base in order to complete electronic records No real time access to health information at the point of care and decision making in the community Increase in part time workers leading to less access to infrastructure
- Tamzin 3 Aims Improve clinician workflow - Provide real time access to health information at the point of care and decision making Improve patient experience - Meet needs more fully during visit with real time access to health information Improve clinician experience - Provide clinicians with opportunity to complete administration tasks on the road And at the same time - To explore the use of video calls as an alternative method of patient contact, eg Skype.
- Tamzin Baseline Data Average time spent on patient related administration tasks ranged from 182 minutes to 288.7 minutes per clinician per day (mean=182. 8 minutes, median=165 minutes) 50% participants believed being able to access Concerto (electronic documentation) in the community could absolutely improve their workflow Above average levels of enthusiasm to trial mobile devices in the community
- Tamzin 12 community allied health clinicians were provided with real time access to clinical documentation and peer reviewed discipline specific apps via an iPad air Three data measures were collected over a 19-week period: Week 1-2 - Time & motion study & Clinician questionnaire Week 10-11 - Time & motion study, Clinician questionnaire & Patient questionnaire Week 18-19 - Time & motion study, Clinician questionnaire & Patient questionnaire
- Tamzin Outcomes so far: Collected 270 days of time and motion data, including 493 direct face-to-face patient contacts. Improved Clinician Workflow - Reduced time spent on administration tasks by average of 29 minutes per clinician per day Utilisation of time between visits to complete administration tasks Improved patient experience - 101 patients completed survey 93% reported improved experience when mobile device used 93% rated comfort with mobile device in home as 7/7 Improved clinician job satisfaction - Reported reduction in stress levels Able to take breaks as a result of time saved Improved clinical practice associated with education and therapy apps
- Tamzin Whats been said:
- Tamzin 81.8% increased their direct face-to-face patient contact by a combined average 14.1 minutes per day there was an average increase in direct face-to-face patient contact of 13 minutes per clinician per day, equating to 65 minutes, per week for a full time clinician. ten clinicians (90.9%) reduced time spent on patient related administration tasks by a combined daily average of 297.7 minutes per day there was an average reduction of patient related administration of 26.7 minutes per clinician per day, equating to 133.7 minutes, per week for a full time clinician. five clinicians (45.4%) reduced their travel time by a combined daily average of 55.8 minutes per day there was an average increase of travel time of 2.4 minutes per clinician per day, equating to 12 minutes per week for a full time clinician. What have we learnt: Potential for mobile device use is multifaceted Gains take time and clinicians require support to incorporate the use of technology into their clinical day Support infrastructure is required to promote successful and secure device use and implementation in longer term
- Tamzin Many patients admitted to hospital experience difficulty swallowing (dysphagia). The incidence of dysphagia is much higher in the elderly population. The elderly constitute a large percentage of North Shore and Waitakere hospital population given the demographics of Waitemata District Health Board’s catchment area. Dysphagia is also significantly higher in certain disorders, some research indicating as many as 80% of stroke patients and 60% of patients with Parkinson disease will have difficulty swallowing. Pre FEES 12%
- Tamzin Results: There was a significant increase in instrumental assessment use in the group that had access to FEES (P,.001). There was a significant reduction of pneumonia rates in the group that had access to FEES (P5.037). Patients were also significantly more likely to leave hospital on standard diets (P5.004) but had longer periods of non-oral feeding (P 5 .013) and increased length of hospitalization (P , .001). Conclusion: When used selectively, FEES services have potential for improving functional outcomes for patients after stroke. In order to provide appropriate management and effective rehabilitation, accurate diagnosis is essential. “Prompt screening, accurate assessment and early management are therefore needed to prevent complications and promote recovery of functional swallow” (Stroke Foundation of New Zealand 2010). Speech-language therapists (SLTs) are responsible for assessing the safety of a patient’s swallowing. When a patient is admitted to hospital, if dysphagia is suspected they are referred to the SLT for a basic bedside swallowing assessment. Prior to implementation of a mobile FEES service, the only objective method to assess the swallow was a videofluoroscopic x-ray swallowing study (VFS) carried out in the radiology department.
- Tamzin Post FEES 7% A statistically significant reduction in post stroke pneumonia rates from 12% in the pre-FEES group to 7% in the post-FEES group “In the pre- FEES group, having an instrumental assessment was significantly associated with developing pneumonia. Conversely, in the post- FEES group, having an instrumental assessment was significantly associated with not developing pneumonia” 6.
- A referral audit was completed over a 2 week period (inclusive of weekends) during July 2014 by each Allied Health Discipline receiving AMAU referrals and providing service. The Audit was discussed with the core clinicians involved in providing Allied Health services to AMAU and amended accordingly to accommodate their suggestions. Information was collected under the following headings; Disc. NHI v= verbal, s= self, p= paper Referral date Referral time Accepted Y/N Rejected Y/N Date/Time Pt. seen Pt. transferred prior to being seen (date/time) Pt. discharged before being seen (date/time).
- Total number of Referrals received: 525 Total number of Patients referred to Allied Health: 278
- This graph emphasises the difference between the overall volume of referrals made (on any given day) and their acceptance, as indicated by the clinician. The differences show that for every discipline there are more referrals made than accepted. Q. Are the referrals inappropriate? Q. Are the referrals still valid at time or receipt?
- predominantly made on Paper, followed by Verbal and then Self screening methods. Unfortunately 120 referrals did not have a method indicated ‘blank’.
- this graph highlights that the large number of referrals made either during the week or over a weekend are not always accepted. Q. Are the referrals appropriate for the service requested? Q. Are the referrals that are initiated outside the time of AH service provision taking into account the Patient’s fluctuating medical status? The data collected does not demonstrate however, if there was a relationship between those that were accepted and those patients transferred on or discharged. A lack of data means that when a patient was identified as not present on AMAU, there was no consistent indication if the referral was accepted and communicated on or rejected.
- Q. Are the referrals being initiated too early in the patient’s acutely unwell journey? Q. Are the referrals that are initiated outside the time of AH service provision taking into account the Patient’s fluctuating medical status? Q.Is the Allied Health service provision in AMAU, being used appropriately, in a timely manner and with a focus to using their services to prevent admission? The highest number of referrals were made on Mondays, Tuesdays, Thursdays and Fridays The lowest number of patients referred occurred on Sundays. There was a mid week drop in referrals on Wednesday Is this influenced by other system factors? i.e. theatres, patient flow on receiving wards, ED. There are a significant number made at the weekend despite no full AH service provided. What are their expectations?
- Clinicians were asked to date and time stamp the referral initiation and also when the patient was first seen after acceptance. Initial analysis identifies the following; Referrals made inside work hours (0800-1700) = 99 Referrals made outside work hours = 402 As a proportion of the total they are; Inside work hours 18.9% Outside work hours 76.6%
- Directive was taken for all referrals to be made verbally unless SLT or DI involved, then paper may be used in not available. This has reduced the number of paper referrals for processing but a repeat audit is required to examine the affect of this action. Further actions are being considered i.e. front loading, interdisciplinary assessments and building closer MDT connections Couldn’t tell whether sufficient resource are meeting the needs because of the misinformation i.e. missing patients, about demand for service. Appropriate demand is required to query sufficient resource.
- We are not inhibiting patient flow – other factors are visibly evident i.e. lack service requests from high turn over wards, a known reduced medical service at the weekend. There is room for potential change i.e. greater MDT representation in the know interdisciplinary clinical services such as ASU, ED, EO.