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Pain Medicine 2014; 15: 142–153 Wiley Periodicals, Inc.
ACUTE PAIN & PERIOPERATIVE PAIN SECTION Original Research Article First Steps Toward Understanding the Variability in Acute Pain Service Provision and the Quality of Pain Relief in Everyday Practice Across the United Kingdom Fiona Duncan, RN, PhD,* Ruth Day, RN, PhD,† Carol Haigh, RN, PhD,* Stuart Gill, ST 7 MB ChB,‡ Jeremy Nightingale, FRCA, FFPMRCA, MB ChB,§ Olga O’Neill, RN, MSc,¶ and David Counsell, FRCA, FFPMRCA, BM BCh** on behalf of the NIPPS Group *Manchester Metropolitan University, Manchester; †
South Devon Healthcare NHS Foundation Trust, Torbay; ‡
Welsh Deanery, Cardiff;
§
Portsmouth Hospitals NHS Trust, Portsmouth;
¶
Belfast Health and Social Care Trust, Belfast;
**Betsi Cadwaladr University Health Board, Wrexham, UK Reprint requests to: Fiona Duncan, RN, PhD, Alston House, 54 Fell Brow, Longridge, Lancashire PR3 3RY, UK. Tel: 01772 782856 (Home); 07703271663 (Mobile); Fax: 0161 247 6328; E-mail:
[email protected] (Home);
[email protected] (Work). Disclosure: We have worked with MELA Solutions Ltd. who are suppliers of handheld databases to several of the hospitals in the study. MELA have supported the development of the minimum dataset and facilitated the totally anonymized download and sharing of data for local benchmarking. MELA have provided the funding for three meetings in Manchester (venue, catering, and travel).
ways in which acute pain services are organized in order to understand whether these are linked to important differences in patient outcomes. The National Inpatient Pain Study group is a voluntary collaborative venture of inpatient pain specialists in the United Kingdom who are working toward establishing a national prospective database of service provision and activity. Objectives. The objectives of this article are 1) to describe current pain service provision and activity 2) to define and monitor the quality and side effects of the primary analgesic techniques, such as central neuraxial block or systemic analgesia, and identify variations in practice. Methods. Phase 1: Surveys were conducted in two phases during 2010–2011. Information about the organization of services was collected from 121 centers via a live Website. Phase 2: The pilot clinical dataset was collected from 13 hospitals in 2011. Results. Results indicated that staffing varied widely from one to nine nurses per hospital site. Twelve percent of hospitals did not routinely collect data. The main workload was orthopedic and general surgery based on data from 13 hospitals and 29,080 patients in 2011. Thirty-seven percent of patients reported a pain score of moderate to severe pain on the first assessment by the specialist pain team, and 21% reported severe pain. Nausea and vomiting was the most frequent adverse event reported. Sixty-nine major adverse events were logged, of which 64 documented respiratory depression (N = 29,080, 0.22%).
Abstract
Conclusions. Prospective longitudinal data has the potential to improve our understanding of variation in process and outcome measures and establish future research priorities.
Background. Pain management for patients in hospital is a major problem. There is significant variation in care provision. Evidence is needed about the
Key Words. Pain Management; Postoperative Pain; Adverse Events; Medical Registries; Acute Pain; Acute Pain Services
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Acute Pain Service Provision In the United Kingdom, acute pain management for patients in hospital remains a major problem more than two decades after the publication of the working party report “Pain after Surgery” [1]. Evidence of inpatient pain service impact has been lacking both nationally and internationally [2,3], and there is significant variation in care provision. The National Confidential Enquiry into Patient Outcomes and Death report on elective and emergency surgery in the elderly called attention to the poor assessment and treatment of pain in British hospitals in 2010 [4]. The fourth annual collection of stories from the Patients’ Association highlighted the fact that access to pain relief is one of four major issues for patients [5]. Furthermore, it has been suggested that inadequately treated acute pain may predispose to the development of chronic pain [6–10]. Therefore, there are substantial opportunities for improvement in practice. There are potential cost savings in terms of a reduction in intensive care admissions, reduction in length of stay and unplanned readmission, and a potential reduction in chronic pain [11]. High-quality evidence is needed about the ways in which inpatient acute pain services are organized and delivered in every day practice in order to understand whether these are linked to important differences in what happens to patients [12]. There is no national data collection to provide such evidence about everyday practice in the field of acute pain management. The Quality Improvement in Postoperative Pain Management project has already published data to show that outcome measures can be measured and shared for patients on the first day after surgery [13,14]. Work carried out by the Intensive Care National Audit and Research Centre (ICNARC; https:// www.icnarc.org/) suggests that a national audit and research approach of the sort underpinning the study reported here can contribute to service improvement and patient safety [15,16]. There are a growing number of large databases utilized for translational science research both nationally and internationally [17–19]. The overall long-term aim of this study, of which the data collected in the first 2 years are reported in this manuscript, is to drive improvement in practice and reduce the variability and inequalities in practice. The objectives for the elements of the study described within this article are 1) to describe current acute pain service provision and activity, and 2) to define and monitor the quality of different techniques and identify variations in practice. This will be achieved by developing both an online survey Website and through the development of a standardized data collection and reporting system with continuous prospective measurement. Methods The National InPatient Pain Study (NIPPS) team was set up in June 2009 to address the fragmented nature of data collection by inpatient services. A group of anesthetists and nurse specialists, who have a special inter-
est in acute pain management and use real-time handheld data collection, initiated the study and have since recruited academics, service managers, and a patient representative to help plan and execute two distinct phases of the project. Throughout the development of this proposal, we have consulted with and been supported by the Patient Liaison Committee of the British Pain Society. In addition, we have a lay member involved in this project who is a retired director of projects for a large national organization. He has provided help and guidance including reviewing outcomes on a regular basis and influencing our study objectives from the perspective of the public and users. Phase 1 was conducted via a Web-based questionnaire and an online snapshot survey; phase 2 is a long-term project based on the early development of an acute pain database.
Phase 1 Phase 1 of the study aimed to understand the current national provision of pain services using both a Web-based questionnaire and online survey tool (SurveyMonkey, SurveyMonkey.com, LLC, Palo Alto, CA, USA). Survey 1: Web-Based Questionnaire The Website was developed from the critical incident reporting system for the 3rd National Anaesthesia Audit [20] by one of the authors, with permission and support from the Royal College of Anaesthetists and the British Pain Society. The Website was launched in May 2011 and recruitment is ongoing. The data collection considered both staffing and clinical aspects such as the drugs and equipment used (Table 1). We ran a test of the survey: several nurse specialist colleagues from different hospitals in the United Kingdom completed the survey and reported where the glitches arose or questions were difficult to understand. This was done to minimize misinterpretation before the site went live [21]. All Acute National Health Service hospitals in the United Kingdom (N = 312) were contacted by letter and invited to take part in the survey. One of the authors (S. G.) wrote to the anesthetic departments as there is not currently a list of contact names for the local acute pain services. There were initially 81 (26%) responses, after which the findings were presented at a national meeting in September 2011 [22]. S. G. then attempted to contact services by phone via the hospital switchboard. This was abandoned after approximately 10 attempts because of the difficulty getting through to the appropriate person, poor response, plus lack of time available. Members of the research group contacted colleagues via networks in their own region in order to remind them to complete the survey. Pain teams were given a unique password to access the site. All entered information remained anonymous. Our aim was to recruit every pain service in the United Kingdom. 143
Duncan et al.
Table 1 Phase 1: variables collected by 1) Web-based longitudinal survey and 2) Web-based cross sectional study Phase 1 Web-based questionnaire (NIPPS Website)
Institutional details
Number of sites Number of beds Population served Team numbers Hours covered Out of hours covered Epidurals PCAs Intrathecal techniques Other agents/infusions used Peripheral blocks
Service details
Modalities/techniques used
Web-based survey (2) (Summary questions)
Do you routinely collect data about your pain service? How do you collect your data? (paper, electronic, both) If you collect pain service data in electronic format ONLY, what system do you use (for example excel spreadsheet)? What do you use the data for (such as audit appraisal etc)?
Do you collect prospective data on every patient visit? If you collect hard copy data ONLY, do you summarize this data? If you collect data about your pain service in BOTH hard copy and electronic format—for the hard copy data—do you summarize it? Do you share this data with anyone else (managers, other hospitals, etc.)?
NIPPS = National Inpatient Pain Study; PCA = patient-controlled analgesia.
Survey 2: Online Cross-Sectional Survey In addition we used the online survey tool to ascertain how many hospitals routinely audited their service and how data was collected (Table 1). Data collection ran from November 2011 to March 2012. This was used to establish a baseline and put this in a UK context. A link to the survey was sent to all anesthetic departments in the United Kingdom by one of the authors (J. N.).
Consensus was achieved after field testing by members of the group in 2010 and several rounds of further adjustments. The pilot dataset was divided into six main sections (Table 2) and included demographic data, surgical details if relevant, the primary technique used to control pain (e.g., epidural, intravenous patient-controlled analgesia [PCA], nerve block, and intramuscular/subcutaneous (IM/SC) and oral analgesia), pain scores, adverse events, and a measure of effectiveness at the end of a patient visit (full details in Appendix 1).
Phase 2: Development of Registry The key task of phase 2 of the study was to agree and standardize data definitions while maintaining local audit systems and minimizing any extra work. The commercial database used by some members of the study group had a very high number of data entry options as each service developed their own audit fields. Our task was to filter out a manageable minimum dataset from the routine data collection for download to a central database. There was no national guidance at the time to inform service audit. Following initial deliberations, we based our proposed measures on the data elements that focused clinical attention on achieving effective pain relief, namely on both the quality (patient reported pain scores) and safety (adverse events) of the techniques [23,24]. We reviewed the literature for definitions and key process and outcome measures [20,23,25,26], looked at existing databases [27,28], and used knowledge from previous audit tools in acute pain management [29] to draw up a first draft of a minimum dataset. 144
We used the American Society of Anaesthesiologists (ASA) classification of physical status as a general measure of comorbidity. There were several areas where a compromise had to be reached. For example, there are potentially multiple different techniques for controlling pain, complicated by the fact that the primary analgesia technique could change within the same patient on subsequent patient visits. The pragmatic decision was that we would record the technique that was in place on the first visit to the surgical patients on the first day, or the first analgesia treatment on the first visit to the nonsurgical patients. There was no standard agreement on the pain scoring tool for all services to use, a problem that is well documented in the specialist literature [23,25], and each service wanted to maintain their own system. In collaboration with a specialist software company, we converted the different pain scoring systems (ranging from 0–3 to 0–100) before download to a central database into four categories (none, mild, moderate, and severe pain) for easier analysis. We based this on the different cutoff points used for giving (or not) treatment
Acute Pain Service Provision
Table 2
Phase 2: database development (summary)
Database development Minimum dataset (more details in Appendix 1)
Age, gender, surgical/nonsurgical.
Acute pain service activity: number of new admissions and number of patient visits per month Pain score (4-point verbal rating) on movement Adverse events
If a surgical patient: American Society of Anaesthesiologists definitions (ASA), scheduled/emergency, surgical speciality, incision site. Primary modality on first visit: epidural, PCA, intrathecal, nerve block, IM/SC, oral. Quality of technique, duration of epidural, whether the epidural was stopped appropriately Major adverse events
IM/SC = intramuscular/subcutaneous; PCA = patient-controlled analgesia.
leading to further variation in treatment. The optimal cutoff point in the literature for pain intensity on the first postoperative day is 4 or greater (measured using an 11-point rating scale), which equates with moderate pain [25]. In addition, we wanted to add a more clinically relevant outcome than a single pain score as a primary outcome in order to judge the effectiveness of a technique. We knew that there was a population of patients in whom a pain score as an outcome would not reflect their experience. For example, there is a growing population of patients who are reporting persistent pain before surgery [30]. In other situations, patients can be free from pain, but not able to mobilize because side effects, such as nausea or hypotension, have not been controlled effectively. Therefore, we adapted an “effectiveness” outcome, which is an overall rating at the end of the assessment by a specialist nurse. The effectiveness takes into account functionality [14,23,31,32]—from no impairment to unable to function because of pain, patient-reported side effects, or adverse events (Appendix 1). It is similar to the Functional Activity Scale devised by Scott and McDonald [31]—an assessment of whether patients can undertake activity at the current level of analgesia, which, although anecdotal, is valid and effective but has not been independently validated. We plan to validate our effectiveness measurement when we have access to the patient level data. It is well recognized that rigorously controlled studies are not powered to detect the rare adverse events associated with techniques such as epidural analgesia. We built on the reporting system in the National Third Audit Project of the Royal College of Anaesthetists [20]. Our definitions of serious complications (adverse events) related to the primary analgesic techniques were based on relevant publications from the Royal College of Anaesthetists [33,34].
patient-level data. Governance issues related to databases are vital, but there is no formal requirement in the United Kingdom to apply for ethical approval for accessing databases. When we move to using anonymized patientlevel data in the next stage of this study, there will be an obligation to apply for ethical review from the National Research Ethics Service. The stage of the study reported in this article was reviewed by the Faculty Ethics Committee of Manchester Metropolitan University and reflected national policy in that it did not require full ethical review. The commercial software supplier is registered appropriately as a data user and a computer bureau under the Data Protection Act 1998. Data Export To ensure the hospitals exported the minimum dataset (NIPPS) routinely, the medical software company sent an e-mail requesting the export on a monthly basis including graphic details about how to carry out the export. The data received was imported onto a master database that automatically processed the data and reported either on individual hospital or groups of hospital. Data were then analyzed by the authors using Microsoft Excel (Microsoft Corp, Redmond, WA, USA). Data download at this stage were aggregated from each hospital. The data reported in this interim review is descriptive and presented as count or percentage. Continuous data are reported as mean or mode with range. Funding
Ethics
The steering group relies on altruistic support; much of the work to date has been completed in the clinicians’ own time. S. G. had half a day set aside for work on the project for 6 months while training in North Wales. The NIPPS Website was initially supported by a small grant. We are currently exploring longer term funding options including a National Institute for Health Research grant. The project reached the final short list in 2012.
At this stage, we were receiving only monthly aggregated data from every service so there was no identifiable
The NIPPS database is currently supported by MELA Solutions. Download of the minimum database is entirely 145
Duncan et al. voluntary and does not add significant costs to individual hospitals as it only involves a few minutes time for download. Results (Phase 1) Survey 1: Web-Based Questionnaire Just over a third (N = 121) of hospitals have submitted data to the NIPPS Website to date. The mean number of beds that each specialist pain nurse was responsible for was 464 (Range 80–1,800). This was regardless of how the service was organized, as some nurses covered more than one hospital site (three services covered four hospital sites). There was a wide variation in the number of nurses per hospital site (whole time equivalent), with a median of 4.5, a mode of 1, and range from 1 to 9 (N = 66). Consultant sessions (1 session = 4 hours) are displayed in Figure 1. Out of hours cover was by the on-call anesthetist in the majority of hospitals. All responding hospitals reported using morphine (1-mg bolus with a 5-minute lockout) as the standard drug for PCA use. There was a split between the use of levobupivacaine (45%) and racemic bupivacaine (55%) for epidural use (N = 107). The majority of hospitals (93%) stated that they added fentanyl to the local anesthetic (N = 99), with the remaining 7% (N = 9) adding diamorphine. Patient-controlled epidural analgesia (PCEA), without a continuous infusion, was used in 17% of responding hospitals, 42% (N = 40) used a continuous infusion only, and 41% (N = 39) used both a continuous infusion plus PCEA. Patients were nursed on a general ward, with an epidural in 74% (N = 75) of the responding sites; 6% (N = 6) of hospitals reported that patients were nursed only on an intensive care unit, never on a general ward. The remaining 20% (20) of hospitals reported a variety of other clinical areas.
said that they did not routinely collect any data. One hundred and eight respondents (62%) specifically collected prospective data on every patient visit. Handheld computer technology has been available for several years; 48% (N = 66) of those who responded to a question about data collection tools used pen-and-paper collection, 15% (N = 21) used electronic, and 37% (N = 51) used a combination of paper and electronic. We also asked which system services used; the most popular was a Microsoft Excel database. Others included commercial systems (MELA Solutions Ltd), the Scottish audit database (The Scottish Society of APS) “Wardwatcher” (http://www.sicsag.scot.nhs.uk/Data/WardWatcher .html.), locally designed systems, or commonly used commercial programmes such as Mircosoft Access. Data were reported as being used for several purposes, including audit, critical incident reporting, appraisal, education, and benchmarking. Fifty-seven centers reported that they did not share any of their data either locally or nationally.
Results (Phase 2) Registry Results We collated the first pilot results in 2010 from seven hospitals, but reporting was patchy with few hospitals completing all fields. Overall, completed demographic data were available for 9,748 new patients. A mean of 17% of patients were nonsurgical (range 3–33%). Sixteen percent of patients reported a pain score of two out of three on the first visit from the pain team; 25% reported severe pain (3/3). PCA was documented as “effective” for 71% of patients; epidurals were effective for 79%. The following major adverse events related to epidural analgesia (N = 1,557) were recorded: cardiovascular collapse seven, neurological injury seven, and epidural hematoma/ abscess three patients.
Survey 2: Cross-Sectional Online Survey There were 173 responses to the survey looking at data collection activity, of which 12% (N = 21) of pain services
Consultant Sessions/Week 2% 11%
5%
11% 0 1
15%
2 3 56%
4 5
Figure 1 The number of consultant sessions per hospital (N = 184). 146
Data collection and download was more successful in 2011. We were able to describe the aggregated data from 13 hospitals who had admitted a total of 29,080 new patients. There were a total of 65,930 patient visits by the acute pain team. The age range covered the spectrum from young children to patients aged over 100, with a mean age of 57. Overall, 14% (N = 4,029) were nonsurgical admissions (range 4–40%). Emergency patients represented 15% of surgical patients (range 0–27%); 31% of the caseload had an ASA score above 2. The surgical specialities documented by the 13 hospitals for patients were: 38% orthopedic (N = 3,867), 33% general surgery (N = 3,416), 9% gynecological (N = 956), 7% urology, (N = 668) 6% vascular (N = 575), 5% cardiothoracic (N = 533) with a mix of head and neck, and burns making up the remaining 2% (N = 192). The standardized list of primary analgesia techniques using the six heading options (see Appendix 1) still
Acute Pain Service Provision resulted in a download of 234 modalities entered by the 13 hospitals. The descriptions varied from epidural and intrathecal analgesia to a wide range of nerve blocks, PCAs, and oral drugs.
Table 3 Adverse and major adverse events recorded by 13 hospitals from data collected in 2011 (29,080 patients) Adverse Event Log
Count (N = 2,073)
Nausea and/or vomiting Hypotension Pruritis Sedation Protocol not followed/organizational Hallucinations Urinary retention Epidural catheter leaking/blocked/fell out Motor block Confusion Constipation Equipment/drug error Headache Agitation Blister/infection at epidural site Postdural puncture headache Dysphoria Pressure ulcer
627 252 233 232 193 137 109 83 78 30 28 20 18 12 8 7 5 1
Major Adverse Events
N = 69
Respiratory depression Neurological injury Cardiovascular collapse Epidural hematoma Death
Twenty-nine percent of epidurals were reported as not being discontinued as planned (N = 1,814). The infusion was stopped for a variety of technical reasons such as falling out or disconnecting. Thirty-seven percent of patients reported a pain score of moderate to severe pain (2/3) on the first assessment, and 21% reported severe pain (3/3) based on 18,319 visits. At the second patient visit by the acute pain team, 34% of patients reported moderate to severe pain, and the incidence of severe pain reduced to 12.5% (N = 11,586.) Over 2000 adverse events were logged in the critical incident section of the local databases, with the most frequent event being nausea and/or vomiting (30%, N = 627). Sixty-nine major adverse events were logged, of which the majority reported respiratory depression (see Table 3). Effectiveness There were over 14,169 visits reported to patients with a PCA as the primary modality, with 75% effective, 22% partially effective, and 3% not effective. There were 7,653 reviews of patients with an epidural as their primary technique, of which 79% were reported to be effective, 18% partially effective, and 3% were not effective. Fifty-three percent of oral analgesia as the primary technique was effective, 40% partially effective, and 7% ineffective based on 15,513 patient visits. There were fewer assessments for nerve blocks (869): 80% were effective, 17% partially effective, and 3% ineffective. There were 456 patient reviews to patients with IM/SC analgesia with only 53% effective (Figure 2).
64 2 1 1 1
90% 80% 70% 60% 50% 40% 30%
Figure 2 Effectiveness of epidural analgesia (based on 7,653 assessments), patient-controlled analgesia (PCA) (14,169 assessments), and oral analgesia (15,513 assessments).
20% 10% 0%
Effective
Partially effective
Ineffective
Epidural
79%
18%
3%
PCA
75%
22%
3%
Oral
53%
40%
7%
147
Duncan et al. Discussion We have made the first step toward making routine collection of standardized data a reality. The data we have presented from the Web-based questionnaire and the cross-sectional survey has revealed the wide variation in service provision. This has been a common theme in publications over the years [3,11], and has much to do with the complex organizational and cultural barriers [3] and lack of service evaluation [2]. There is no doubt that tackling the failure to deliver effective pain relief for patients in hospital needs to become a national priority for improvement, but this is very unlikely to happen unless good-quality data are collected as routine by every service [12,35]. In the 1990s, there were several local and regional databases, but their potential was hindered by the lack of administrative support and cumbersome data analysis [35]. Collecting data continuously for improvement can be prohibitively difficult with a pen-and-paper system because the datasets are extremely large. The turnover of patients can be rapid, with multiple patient admissions and discharges daily. However, advances in computer technology offers clinicians and researchers the potential to collect realtime data, as part of their everyday clinical work, which is a “mirror image” of how the service practices [12,36]. Thus, no patients are excluded, and we will build a realistic picture of the caseload across the United Kingdom. We have stimulated discussion, produced posters and presentations at specialist conferences [22,37–40], and received feedback via the database company. The growing database will allow examination of contemporary issues such as pain relief in the elderly surgical patients, pain strategies on medical wards, enhanced recovery for surgical patients, and availability of high dependency beds in real-world practice. Patients with high pain scores and the incidence of complications confirm the need for a high-quality pain service. The three areas of quality are reflected in pain scores, side effects (tolerability), and critical incidents [24]. We recorded a high incidence (56% overall) of moderate to severe pain. While this is a snapshot of pain severity at a point in the postoperative period, this figure is broadly in line with the database analysis published by Popping et al. in 2008 [41] and suggests that the incidence of moderate to severe pain in the early postoperative period has not changed markedly from that quoted in the joint Royal Colleges’ report in 1990 [1]. The incidence of moderate or severe postoperative pain has been proposed by the Royal College of Anaesthetists as an audit standard [33], but the evidence base for selecting an accepted standard is at best scant. Perhaps a more sophisticated indicator of the effectiveness of acute pain services would be an assessment of the timely response of the health care delivery system to high pain scores—an earlier edition of the same publication by the Royal College of Anaesthetists suggested within 2 hours [29]—and the 148
efficacy of that response. The method of data collection we describe will allow such data to be collected for audit purposes within hospitals and allow comparison between hospitals. The adverse events (critical incidents) were defined in terms of causing harm to the patient, for example, serious side effects of treatment that resulted in delayed recovery/mobilization despite treatment. The adverse event profile is worthy of closer investigation. The opioid-related complications are high, as are organizational problems. The control of postoperative nausea and vomiting is known to be an essential component for patient satisfaction [42], and if not treated, up to a third of patients will suffer it. Vomiting is the most undesirable outcome from the patients’ point of view [43]. It can lead to significant morbidity such as pulmonary complications and a longer stay in hospital. The major adverse events profile highlights respiratory depression as a problem. The data suggest significant opioid-related side effects for patients that hamper their recovery. Yet respiratory depression is considered a preventable complication [44,45]. The incidence reported in the literature varies from 0.22% to 0.9% [46]; however, there is a problem with definition and interpretation between studies. In our study, the incidence of sedation logged as an adverse event was 0.8%. The incidence of respiratory depression logged as a major adverse event (64 cases) was 0.22%. Strengths We have reported an interim analysis of data that was a “real-time” assessment by a specialist, rather than transcribing pain and complications from ward nurse documentation. Other national audits, such as the cardiac registry, are estimated to cost approximately £45,000 per hospital per year [28]. ICNARC employ data input personnel; however, we considered that such added costs unfeasible as pain services are already underfunded. The core minimum NIPPS dataset contains a small number of fields and does not add extra burden to busy services. The download to a central database is simple and does not require advanced information technology skills. The services involved in this feasibility study are already using the data for benchmarking and local improvement. Restrictions of Study The lack of a national list of acute pain services (or anesthetist in charge of the pain service) made it a challenge to know if letters had reached the right people. We recognize the large bias with voluntary submission. Valid comparisons between hospitals and regions will require methods that adjust for varying mixes of surgery and patient characteristics. We plan to add a detailed dictionary at the point of assessment in order to eliminate
Acute Pain Service Provision problems with interpretation. The inclusion of nonsurgical patients was useful for tracking service activity, but will have skewed the results for pain scores. This is because some hospitals include nonsurgical patients and some do not. The Future We will continue to refine and validate the effectiveness data. Collecting real patient data on every patient visit in a systematic fashion is the foundation for future outcome research and improving the experience for patients in hospital. We plan to map provision across the United Kingdom and provide the baseline data to compare for future improvement. We need to learn if the variation in patient outcomes is due to patient- or organizationalrelated factors and learn from services with good outcomes. The variation might also be due to “preferencecentered care” where there is more than one accepted treatment, and treatment is then based on professional opinion rather than best evidence [47]. In order to progress, we need to obtain the patient-level data; we will then be able to look at service characteristics, patient characteristics, and correlate with patient outcomes. This will improve patient quality by working toward reducing variation, standardizing service provision and funding, and sign posting important areas for research.
References 1 Royal College of Surgeons of England, College of Anaesthetists. Report of the Working Party on Pain after Surgery. London: Royal College of Surgeons of England, College of Anaesthetists; 1990. 2 McDonnell A, Wilson R, Goodacre S. Evaluating and implementing new services. BMJ 2006;332:109– 12. 3 Powell A, Davies H, Bannister J, Macrae W. Understanding the challenges of service change—learning from acute pain services in the UK. J R Soc Med 2009;102:62–8. 4 National Confidential Enquiry into Patient Outcome and Death. Elective and emergency surgery in the elderly: An age old problem. National Confidential Enquiry into Patient Outcome and Death; 2010. Available at: http://www.ncepod.org.uk/2010report3/ downloads/EESE_summary.pdf (accessed February 2013). 5 Patients’ Association. Stories from the present, lessons for the future. London: The Patients Association; 2012. Available at: http://www.patients -association.com (accessed December 2012).
There are several other important areas to look at such as who owns the database, peer review, and public access [18]. It will be a particularly powerful registry if we can work with colleagues such as surgeons, physiotherapists, and general practitioners to link with established databases. The future development of the NIPPS project will complement the work of other groups working toward improving pain management. “Pain-Out” is a multinational research study, funded in 2009, to develop an evidence-based approach to treating pain after surgery [48]. The study developed from an established German registry. The proposed population for the study reported here is different and distinct in that we will capture outcome data from all admissions to the acute pain service.
6 Macrae W. Chronic post-surgical pain: 10 years on. Br J Anaesth 2008;101(1):77–86.
The NIPPS registry has been accepted by the Health Quality Improvement Partnership (http://www.hqip.org .uk/). It is recognized that databases have significant value to managers, clinicians, researchers, and commissioners. There is currently no coordinated commissioning structure for inpatient acute pain services in the United Kingdom. In summary, we are working toward a unified systematic approach to data collection, defining a common minimum dataset and instituting quality control measures to ensure integrity of data.
10 Kalso E. Persistent post-surgical pain: Research agenda for mechanisms, prevention and treatment. Br J Anaesth 2013;111(1):9–12.
Acknowledgments
12 Upp J, Kent M, Tighe P. The evolution and practice of Acute Pain medicine. Pain Med 2013;14:124–44.
We thank the 13 hospitals for sharing their data and all members of the NIPPS steering committee. We would also like to thank Cristina Willans of Mela Solutions Ltd for her technical support and hospital recruitment.
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Duncan et al. Appendix 1 Age Gender Surgical/nonsurgical If surgical: ASA scale of fitness
Emergency/planned surgery Surgical speciality
Incision site
APS activity Primary modalities
Pain score Quality of technique
Duration of modality Modality discontinued appropriately/as planned?
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In years Male/female If a patient is seen for preoperative pain relief, and subsequently goes for surgery, discharge and readmit. American Society of Anaesthesiologists definitions: 1 A normal healthy patient 2 A patient with mild systemic disease 3 A patient with severe systemic disease 4 A patient with severe systemic disease that is a constant threat to life 5 A moribund patient who is not expected to survive without surgery N Not documented (Scheduled/elective) General Cardiothoracic Orthopedic Vascular Gynecological Obstetric Burns and plastic Urology Head and neck No operation Upper abdomen Lower abdomen Peripheral Thorax Thorax/abdomen Upper/lower abdomen Head/neck Spine Perineum Abdo/perineum Sternum *Number of visits per month by the APS. (Automatically calculated) *Number of visits per patient (Automatically calculated) On first visit to patient, can be more than one modality (such as IT and PCA). Epidural PCA Intrathecal Nerve block IM/SC Oral Four-point verbal rating score as none (0), mild (1), moderate (2), and severe (3). Measured on movement (Completed at end of your patient assessment). The primary aim of postoperative pain management is to provide continuous uninterrupted dynamic pain relief that will allow postoperative rehabilitation with a minimum number of side effects. Is this achieved, partially achieved, or not achieved—see below. Click all relevant sections and use for all modalities Effective (good analgesia) Patient is comfortable (not just based on pain score, which can be high in chronic pain patients) Side effects absent or controlled with appropriate medication Functional: Able to cooperate with recovery (cough, mobilization, and enhanced recovery protocol) Partially effective (fair analgesia) Not fulfilling (all 3) “effective” criteria above. Not optimum quality of analgesia/or control of side effects: “fair” on a scale from poor to excellent. However, not total failure of technique, patient able to make functional recovery, but with higher pain score. Requiring more than just a minor adjustment to treatment, longer than 15-minute review Ineffective (failure) Pain relief not effective, not able to cooperate with recovery resulting in intervention from the APS and change of modality (modality failure) Days (automatically calculated, but need to go back to initial assessment to enter end date) For example, the primary modality was discontinued when oral analgesia was established and effective. Inappropriate—stopping an epidural to facilitate discharge to a general ward
Acute Pain Service Provision Appendix 1 Continued Adverse events
Major adverse events
Motor block (dense) Urinary retention requiring catheterization Pruritus requiring treatment Pressure sores (sacrum/heel) related to epidural Postdural puncture headache requiring blood patch Nausea/vomiting related to analgesia and affecting recovery Hypotension a fall of 30% of the patient’s pre-operative systolic blood pressure, a fall in blood pressure affecting urine output (
