1195 EFFECTIVENESS OF A NEW PROACTIVE MULTIDISCIPLINARY CARE SERVICE FOR OLDER PEOPLE WITH FRAILTY: A NON-RANDOMISED CONTROLLED TRIAL

Introduction

Integrated care potentially improves health outcomes for older people with frailty. We aimed to assess the effectiveness of a new, proactive, multidisciplinary care service in improving the wellbeing and quality-of-life of older people with frailty.

Methods

A community-based non-randomised controlled trial. Participants (≥65 years, electronic Frailty Index ≥0.36) received either this new integrated care service plus usual care, or usual care alone. Data collection was at 3 time points: baseline, 2-4 weeks, and 10-14 weeks; the primary outcome was patient well-being at 2-4 weeks, measured using the Integrated Patient Outcome scale, IPOS. The secondary outcome was quality-of-life, measured using EQ-5D. Wellbeing and quality-of-life at 10-14 weeks were measured to test safety and duration of effect. Data was analysed with STATA v17.

Results

199 intervention and 54 control participants were recruited. At baseline, participants were similar in age/gender/body mass index/ethnicity/living status. At 2-4 weeks, the intervention group had improved well-being (median IPOS reduction 5, versus control group increase 2, p<0.001) and improved quality of life (median EQ-5D index values increase 0.12, versus control 0.00, p<0.001); these were clinically significant. After adjusting for age, gender and living status, intervention group had an average total IPOS score reduction of 6.34 (95% CI: -9.01: -4.26, p<0.05). Propensity score matching analysis based on functional status/deprivation score showed similar results (reduction in IPOS score in intervention group 7.88 (95% CI: -12.80: -2.96, p<0.001). At 10-14 weeks, the intervention group sustained well-being improvement (median IPOS score reduction 4, versus control increase 2, p<0.001) and improved quality of life (median EQ-5D index values increase 0.06, versus control -0.01, p<0.001).

Conclusion

This new integrated care service improves the overall wellbeing and quality of life of older people with frailty at 2-4 weeks; improvement was sustained at 3 months.

Ethics Approval: IRAS-250981 and NHS Research Ethics Committee 18/YH/0470.

Electronic risk assessment for venous thromboembolism: investigating physicians' rationale for bypassing clinical decision support recommendations

OBJECTIVE

The underutilisation of venous thromboembolism (VTE) prophylaxis is still a problem in the UK despite the emergence of national guidelines and incentives to increase the number of patients undergoing VTE risk assessments. Our objective was to examine the reasons doctors gave for not prescribing enoxaparin when recommended by an electronic VTE risk assessment alert.

DESIGN

We used a qualitative research design to conduct a thematic analysis of free text entered into an electronic prescribing system.

SETTING

The study took place in a large University teaching hospital, which has a locally developed electronic prescribing system known as PICS (Prescribing, Information and Communication System).

PARTICIPANTS

We extracted prescription data from all inpatient admissions over a 7-month period in 2012 using the audit database of PICS.

INTERVENTION

The completion of the VTE risk assessment form introduced into the hospital-wide electronic prescribing and health records system is mandatory. Where doctors do not prescribe VTE prophylaxis when recommended, they are asked to provide a reason for this decision. The free-text field was introduced in May 2012.

PRIMARY AND SECONDARY OUTCOME MEASURES

Free-text reasons for not prescribing enoxaparin when recommended were thematically coded.

RESULTS

A total of 1136 free-text responses from 259 doctors were collected in the time period and 1206 separate reasons were analysed and coded. 389 reasons (32.3%) for not prescribing enoxaparin were coded as being due to 'clinical judgment'; in 288 (23.9%) of the responses, doctors were going to reassess the patient or prescribe enoxaparin; and in 245 responses (20.3%), the system was seen to have produced an inappropriate alert.

CONCLUSIONS

In order to increase specificity of warnings and avoid users developing alert fatigue, it is essential that an evaluation of user responses and/or end user feedback as to the appropriateness and timing of alerts is obtained.

Developing consensus on hospital prescribing indicators of potential harms amenable to decision support

AIMS

To develop a list of prescribing indicators specific for the hospital setting that would facilitate the prospective collection of high-severity and/or high-frequency prescribing errors, which are also amenable to electronic clinical decision support.

METHODS

A two-stage consensus technique (electronic Delphi) was carried out with 20 experts across England. Participants were asked to score prescribing errors using a five-point Likert scale for their likelihood of occurrence and the severity of the most likely outcome. These were combined to produce risk scores, from which median scores were calculated for each indicator across the participants in the study. The degree of consensus between the participants was defined as the proportion that gave a risk score in the same category as the median. Indicators were included if a consensus of 80% or more was achieved.

RESULTS

A total of 80 prescribing errors were identified by consensus as being high or extreme risk. The most common drug classes named within the indicators were antibiotics (n = 13), antidepressants (n = 8), nonsteroidal anti-inflammatory drugs (n = 6) and opioid analgesics (n = 6). The most frequent error type identified as high or extreme risk were those classified as clinical contraindications (n = 29 of 80).

CONCLUSIONS

Eighty high-risk prescribing errors in the hospital setting have been identified by an expert panel. These indicators can serve as a standardized, validated tool for the collection of prescribing data in both paper-based and electronic prescribing processes. This can assess the impact of safety improvement initiatives, such as the implementation of electronic clinical decision support.

Improvement in the detection of adverse drug events by the use of electronic health and prescription records: an evaluation of two trigger tools

PURPOSE

To test if two of the adverse event triggers proposed by the Institute of Healthcare Improvement can detect adverse drug events (ADEs) in a UK secondary care setting, using an electronic prescribing and health record system.

METHODS

In order to identify triggers for over-anticoagulation and potential opioid overdose and we undertook a retrospective review of electronic medical and prescription records from 54,244 hospital admissions over a 1-year period, alongside a review of medical incident reports. Once prescription data were linked to triggers and duplicates were removed, case note review eliminated the false positive ADEs. Additionally, we tested the use of an electronic algorithm for the International Normalized Ratio (INR) ≥6 trigger.

RESULTS

The INR ≥6 electronic trigger identified 46 potential ADEs and the naloxone electronic trigger identified 82 ADEs. Based on the available case note review, the INR ≥6 trigger had a positive predictive value (PPV) of 38 % (14/37) and the naloxone trigger had a PPV of 91 % (61/67). The electronic algorithm for the INR ≥6 trigger identified 12 ADEs, thus reducing the need of case note review. This was in comparison with one and two critical incidents reported in the trust medical incident reports system, which respectively related to over-coagulation with warfarin and over-sedation with opioid medication.

CONCLUSIONS

We have integrated automated and manual methods of detecting ADEs using previously defined triggers. Incorporating electronic triggers in already established electronic health records with prescription and laboratory test data can improve the detection of ADEs, and potentially lead to methods to avert them.

Decision support for sensible dosing in electronic prescribing systems

WHAT IS KNOWN AND OBJECTIVE

The sensible dosing of medicines can ensure that patients receive neither excessive doses leading to toxicity nor inappropriately low doses leading to undertreatment. Computerized prescribing systems with embedded decision support can check doses during prescription order entry and display alerts when the prescribed doses are out of range. We have been unable to identify any scheme for the systematic addition of dosing information to CPOE systems. We used pharmacological data to design an algorithm for dose range checking that we tested on a subset of medicines in an electronic prescribing system to ensure that the rules could be implemented in practice.

METHODS

We drafted an initial algorithm based on pharmacological principles, tested it on a subset of frequently prescribed drugs in an electronic prescribing system and then refined it. We considered which clinical decision support functions systems would require to be maximally effective.

RESULTS AND DISCUSSION

The final algorithm contained eleven broad factors. We tested it on 30 drug-route-form combinations, and it accommodated the information for all of these combinations. We also identified a variety of system functions that would be required for comprehensive dosing decision support.

WHAT IS NEW AND CONCLUSION

The dose range checking algorithm that we have derived from first principles will allow the clinical workflow and warnings to be constructed more effectively within systems to enhance patient safety. This will form a basis for the development of optimal schemes for adding decision support to prescribing systems.

Multiple component patient safety intervention in English hospitals: controlled evaluation of second phase

OBJECTIVE

To independently evaluate the impact of the second phase of the Health Foundation's Safer Patients Initiative (SPI2) on a range of patient safety measures. Design A controlled before and after design. Five substudies: survey of staff attitudes; review of case notes from high risk (respiratory) patients in medical wards; review of case notes from surgical patients; indirect evaluation of hand hygiene by measuring hospital use of handwashing materials; measurement of outcomes (adverse events, mortality among high risk patients admitted to medical wards, patients' satisfaction, mortality in intensive care, rates of hospital acquired infection). Setting NHS hospitals in England.

PARTICIPANTS

Nine hospitals participating in SPI2 and nine matched control hospitals.

INTERVENTION

The SPI2 intervention was similar to the SPI1, with somewhat modified goals, a slightly longer intervention period, and a smaller budget per hospital.

RESULTS

One of the scores (organisational climate) showed a significant (P = 0.009) difference in rate of change over time, which favoured the control hospitals, though the difference was only 0.07 points on a five point scale. Results of the explicit case note reviews of high risk medical patients showed that certain practices improved over time in both control and SPI2 hospitals (and none deteriorated), but there were no significant differences between control and SPI2 hospitals. Monitoring of vital signs improved across control and SPI2 sites. This temporal effect was significant for monitoring the respiratory rate at both the six hour (adjusted odds ratio 2.1, 99% confidence interval 1.0 to 4.3; P = 0.010) and 12 hour (2.4, 1.1 to 5.0; P = 0.002) periods after admission. There was no significant effect of SPI for any of the measures of vital signs. Use of a recommended system for scoring the severity of pneumonia improved from 1.9% (1/52) to 21.4% (12/56) of control and from 2.0% (1/50) to 41.7% (25/60) of SPI2 patients. This temporal change was significant (7.3, 1.4 to 37.7; P = 0.002), but the difference in difference was not significant (2.1, 0.4 to 11.1; P = 0.236). There were no notable or significant changes in the pattern of prescribing errors, either over time or between control and SPI2 hospitals. Two items of medical history taking (exercise tolerance and occupation) showed significant improvement over time, across both control and SPI2 hospitals, but no additional SPI2 effect. The holistic review showed no significant changes in error rates either over time or between control and SPI2 hospitals. The explicit case note review of perioperative care showed that adherence rates for two of the four perioperative standards targeted by SPI2 were already good at baseline, exceeding 94% for antibiotic prophylaxis and 98% for deep vein thrombosis prophylaxis. Intraoperative monitoring of temperature improved over time in both groups, but this was not significant (1.8, 0.4 to 7.6; P = 0.279), and there were no additional effects of SPI2. A dramatic rise in consumption of soap and alcohol hand rub was similar in control and SPI2 hospitals (P = 0.760 and P = 0.889, respectively), as was the corresponding decrease in rates of Clostridium difficile and meticillin resistant Staphylococcus aureus infection (P = 0.652 and P = 0.693, respectively). Mortality rates of medical patients included in the case note reviews in control hospitals increased from 17.3% (42/243) to 21.4% (24/112), while in SPI2 hospitals they fell from 10.3% (24/233) to 6.1% (7/114) (P = 0.043). Fewer than 8% of deaths were classed as avoidable; changes in proportions could not explain the divergence of overall death rates between control and SPI2 hospitals. There was no significant difference in the rate of change in mortality in intensive care. Patients' satisfaction improved in both control and SPI2 hospitals on all dimensions, but again there were no significant changes between the two groups of hospitals.

CONCLUSIONS

Many aspects of care are already good or improving across the NHS in England, suggesting considerable improvements in quality across the board. These improvements are probably due to contemporaneous policy activities relating to patient safety, including those with features similar to the SPI, and the emergence of professional consensus on some clinical processes. This phenomenon might have attenuated the incremental effect of the SPI, making it difficult to detect. Alternatively, the full impact of the SPI might be observable only in the longer term. The conclusion of this study could have been different if concurrent controls had not been used.

Large scale organisational intervention to improve patient safety in four UK hospitals: mixed method evaluation

OBJECTIVES

To conduct an independent evaluation of the first phase of the Health Foundation's Safer Patients Initiative (SPI), and to identify the net additional effect of SPI and any differences in changes in participating and non-participating NHS hospitals.

DESIGN

Mixed method evaluation involving five substudies, before and after design.

SETTING

NHS hospitals in the United Kingdom.

PARTICIPANTS

Four hospitals (one in each country in the UK) participating in the first phase of the SPI (SPI1); 18 control hospitals.

INTERVENTION

The SPI1 was a compound (multi-component) organisational intervention delivered over 18 months that focused on improving the reliability of specific frontline care processes in designated clinical specialties and promoting organisational and cultural change.

RESULTS

Senior staff members were knowledgeable and enthusiastic about SPI1. There was a small (0.08 points on a 5 point scale) but significant (P < 0.01) effect in favour of the SPI1 hospitals in one of 11 dimensions of the staff questionnaire (organisational climate). Qualitative evidence showed only modest penetration of SPI1 at medical ward level. Although SPI1 was designed to engage staff from the bottom up, it did not usually feel like this to those working on the wards, and questions about legitimacy of some aspects of SPI1 were raised. Of the five components to identify patients at risk of deterioration--monitoring of vital signs (14 items); routine tests (three items); evidence based standards specific to certain diseases (three items); prescribing errors (multiple items from the British National Formulary); and medical history taking (11 items)--there was little net difference between control and SPI1 hospitals, except in relation to quality of monitoring of acute medical patients, which improved on average over time across all hospitals. Recording of respiratory rate increased to a greater degree in SPI1 than in control hospitals; in the second six hours after admission recording increased from 40% (93) to 69% (165) in control hospitals and from 37% (141) to 78% (296) in SPI1 hospitals (odds ratio for "difference in difference" 2.1, 99% confidence interval 1.0 to 4.3; P = 0.008). Use of a formal scoring system for patients with pneumonia also increased over time (from 2% (102) to 23% (111) in control hospitals and from 2% (170) to 9% (189) in SPI1 hospitals), which favoured controls and was not significant (0.3, 0.02 to 3.4; P = 0.173). There were no improvements in the proportion of prescription errors and no effects that could be attributed to SPI1 in non-targeted generic areas (such as enhanced safety culture). On some measures, the lack of effect could be because compliance was already high at baseline (such as use of steroids in over 85% of cases where indicated), but even when there was more room for improvement (such as in quality of medical history taking), there was no significant additional net effect of SPI1. There were no changes over time or between control and SPI1 hospitals in errors or rates of adverse events in patients in medical wards. Mortality increased from 11% (27) to 16% (39) among controls and decreased from 17% (63) to 13% (49) among SPI1 hospitals, but the risk adjusted difference was not significant (0.5, 0.2 to 1.4; P = 0.085). Poor care was a contributing factor in four of the 178 deaths identified by review of case notes. The survey of patients showed no significant differences apart from an increase in perception of cleanliness in favour of SPI1 hospitals.

CONCLUSIONS

The introduction of SPI1 was associated with improvements in one of the types of clinical process studied (monitoring of vital signs) and one measure of staff perceptions of organisational climate. There was no additional effect of SPI1 on other targeted issues nor on other measures of generic organisational strengthening.