PRIMHD and the People
Recovery Journeys Revealed through Everyday Data
Terry Smith, Michelle (Shelly) Reet
Service Development and Integration Unit
Wairarapa, Hutt Valley and Capital & Coast DHBs
Wellington Hospital, Wellington, New Zealand
;
Abstract
Amongthosethat live with a serious mental illness, each journey towards recovery is as unique as the person experiencing it. Along the way an individual’s path intersects with health services at various junctions and crossroads, all of which will have a certain type of impact on the outcome.
In New Zealand, on each occasion a person comes into contact with a mental health or addiction service, a record of the transaction is stored in the Mental Health National data collection (PRIMHD).We used the activity data collected for PRIMHD over a period of five years to visualiseand aggregate patterns of acute service utilisationfor a group of individuals living with a psychotic disorder. The results formed part of the evaluation of a workforce development project that aimed at reducing incidence ofrelapse in psychosis.
The method of analysis offers a longitudinal perspective on outcomes and provides a context within which other clinical or self-rated measures may be viewed. When aggregated across populations, the data provides an indicator of how well current services are performing in terms of outcomes. The method has potential to be used as a guide for the co-design, monitoring and evaluation of future services.
1.Collection of mental health activity data in New Zealand
The Programme for the Integration of Mental Health Data (PRIMHD) is a national database of information collected by the Ministry of Health (MOH) to support policy formation, monitoring and research in New Zealand(1).
PRIMHD collects information on the provision of secondary mental health and alcohol and drug services funded by the government. This includes secondary inpatient, residential, outpatient and community services provided by district health boards (DHBs) and Non-Government Organisations (NGOs). PRIMHD includes details of services provided, as well as demographic variables such as sex, age and ethnicity, diagnosis, legal status, referral, discharge, and outcomes data.
2.The effects of relapse in psychosis on individuals and their families
The literature commonly describes relapse as a serious barrier to recovery for service users who experience psychosis. The negative consequences extend beyond the individual to seriously impact on family/whanau(2), communities, and health system resources(3,4). Higher hospitalisation rates, readmissions, reduction in quality of life and self-esteem, increased burden on family/whanau or complete estrangement(5), losses associated with illness, resistance to treatment, greater risk of harm to self or to others (including suicide), and economic cost of relapse (3,4)are all issues of considerable concern for the healthcare sector.
The need to minimise episodes of relapse and improve the experience of service users on their journey towards recovery, is further prompted in New Zealand by a range of national strategic and policy drivers. King and Welsh (2006) estimated that long–term users of mental health services accounted for approximately 65 per cent of acute bed days and more than 90 per cent of social support services provided by NGOs(6). As a response to this concern the knowing the people planninginitiative (7) recommended that each service user have a relapse prevention plan focussed on maintaining good health and prompt inpatient service if needed. In 2011, the mental health commission published Blueprint II (8), whichadvised that all mental health services in NZ should develop strong partnerships, collaborative recovery planning and engagement as a foundation and tool for enabling consumers to plan for their safety, provide alternative strategies for responding to crises and to minimise the intensity and frequency of relapse.
The development of a relapse prevention plan, in collaboration with the service user and their family, is recognised as a key factor in reducing the incidence of relapse(9). In June 2010 the MOH set a national target for DHBs requiring that 95% of long-term services users have a completed relapse prevention plan. DHBs were further challenged in the MOH service development plan for 2012 to 2017 (10), to take action to cement and build on gains in resilience and recovery for this group of high-needs people.
3.Tōu Ake Oranganui
The Tōu Ake Oranganui (TAO) relapse prevention in psychosis project was an initiative undertaken within the Capital and Coast DHB (CCDHB) mental health service between November 2010 and April 2012. With this initiative CCDHBsignalled an intention to not only raise compliance with the national relapse prevention plan target but to also ensure that there was a measureable improvement in the quality of plans and in outcomes.
The project involved the co-design and co-delivery of a professional education programme to up skill clinicians in evidence-based relapse prevention techniques. The education modules subsequently developed involved face to face sessions, online learning and the production of practical resource kits for use in everyday practice. The objective of the education sessions was that clinicians would be better equipped to engage with and motivate service users towards setting and achieving goals for their own recovery.
4.The Analysis Brief
The project steering group required a comparison of relapse rates among the members of a study cohort over a period of three years before and two years after implementation of the TAO staff education modules, in order to find an indication of any change in patterns of service use and incidence of relapse.
There is described in the literature a variety of methods and definitions to measure the incidence of relapse in people experiencing schizophrenia or other psychotic disorders.However the lack ofwidely accepted criteria hampers the goal of measuring changes in rates of relapse. The majority of studies have tended to revert to hospitalisation as the default proxy for identifying a relapse(11).
Adult mental health services in CCDHB operate with a relatively low number of acute inpatient compared to other DHBs in New Zealand. To replace inpatient beds, over the past decade a variety of alternative forms of service response have been developed for people needing support in times of crisis. These include an increased capacity to undertake assessment and short-term case management within the crisis assessment and treatment team (CATT), the establishment of a home based treatment team (HBT) which undertakes home visits for people in crisis, an acute day hospital that service-users can attend during daytime hours and participate in low-key activity, and an increased number of short stay beds in community-based crisis respite houses.
The TAO project therefore required a data analysis method that would be sensitive to utilisation at the lower end of the continuum of acute response, including acute episodes where hospitalisation was not required, and which would be able to measure instances of relapse over an extended period. Furthermore, the project steering group wished to avoid adding any additional data collection burden on frontline staff, therefore the method would need to utilise only the activity data that was already being routinely collected for PRIMHD within community and inpatient services.
5.Method
A group of 146 current users of mental health services users in Capital & Coast District Health Board (CCDHB) were identified by means of a manually conducted random file audit.
All members of the cohort met the following criteria:
- Was a regular user of mental health services: i.e. at the time of the study there was at least one recorded community contact with services in each of the eight preceding quarterly periods
- Had an active primary diagnosis of psychotic disorder within the ICD10 F2*** group of codes
Data was extracted from the patient management system at CCDHB. Two types of data records were used.
- Community Activity data: where a record is created on each occasion a service user is seen by a health-care professional in a community mental health team. Each activity record contains the date of the contact, the NHI of the service user, the team, and an activity type code that identifies whether it was a routine planned contact or an unplanned crisis contact.
- Community crisis-respite house and inpatient acute unit bed night data: where a record is created whenever a service-user occupies a bed overnight in one of these facilities.
A weighting to indicate an escalating scale of service response, derived by identifying the type of team and the type of activity, was applied to each activity record as shown in Table 1.
Table 1: Mapping of Activity Type to Level of Service Response
Level of Response / Definition0 / Planned or expected contact with a CMHT
1 / Unplanned or Crisis Contact with a CMHT
2 / Contact with CATT, Home Based Treatment or Acute Day Service
3 / Crisis Respite or Recovery Bed Night
4 / Acute Inpatient Bed Night
The activity data set was then queried to find all records between Jan 1st 2009 and Dec 31st 2013 that matched the team mappings for the NHI numbers of service users in the cohort.
Output from those queries was appended into a simple table containing columns for NHI, activity date and response level, and then transposed to display the maximum level of service response provided to each service user on each day within the period. An anonymised extract of the resultant dataset is displayed in Table 2.
Table 2: Maximum level of service response by service user and day
As can be seen in Table 2, a pattern made up of clusters of increased intense acute activity had begun to emerge along the time sequence for each service user. The next step in the process would need to clearly separate each of these clusters from each other, in order to identify individual relapses and enable a count to be performed. To be able to do this required a rule to define a relapse in terms of a minimum level of acute activity over a minimum period of time. After consultation with the subject matter experts on the project steering group it was decided that the minimum level would be set at seven days of continuous acute activity at response level one.
Accordingly, response values for each service user were totalled up for a rolling seven day period. Within the resultant dataset any value below eight was deleted, as shown in Table 3. With the more intermittent activities removed it was then a straightforward exercise of counting the contiguous blocks of more acute activity and aggregating to find the number of relapses per service user.
Table 3: Rolling 7 day summed blocks of acute activity
After repeating the same methodology in February 2014 it was possible to view five years of daily activity data for each person and to clearly identify periods of escalation and de-escalation in service response. Indeed the data was “telling a story” about the journeys of these individuals and also something about their experience of care over an extended period of time. The data for an individual service user was then plotted on a simple line graph that was then presented back to the project stakeholders as a method of visualising the patterns of relapse and wellness over time, as seen in Figure 1.
Figure 1: Example of patterns of wellness and relapse for a single service user over time
6.Results
The pre and post outcomes of the cohort of 146 service users demonstrated an impact on the count of relapses, a reduction in inpatient bed nights, a reduction in unplanned crisis contacts and an increase in planned intervention including the use of alternatives to admission.
A total of twenty-seven individuals had exited from the care of the CCDHB community mental health service by the end of the five year study period. To account for the reducing cohort size, the counts of the different types of activity days were converted to a rate per person based on those remaining in the cohort at the end of each yearly period, as seen in Table 4.
Table 4: Rates of relapse and activity per person and per year, pre and post implementation of the education in relapse program
Following the implementation of the TAO staff education program in late 2011 and early 2012, there was a significant fall in the number of relapses per person. The rate increased slightly in 2013, but continued at a lower level than in the first three years.
There was also a sharp drop in the number of acute bed nights per individual in the first year after implementation. This rate rose again sharply in the following year, but still was significantly lower than the original rate. At the same time, utilisation of the respite and recovery houses fell back after having risen sharply in 2011.
The level of planned activity days per person rose sharply in 2012, indicating more intense engagement with service users during their periods of relative wellness. Although the rate fell back again slightly in 2013, there continued to be a sustained decrease in the number of community crisis contacts.
A small percentage of individuals in the cohort continued to suffer more than one relapse in each yearly period. However, the percentage of people that had no relapse at all increased significantly by the end of the fifth year, as seen in chart 2.
Figure 2: Service users experiencing more than one relapse in a year
7.Discussion
The results of the data analysis for this project were not tested for statistical significance, and for ethical reasons there was no possibility of a control group to be used for comparison. The intention at the outset was to explore whether routinely collected activity data could be utilised to provide an indication of whether there was any change in the frequency, intensity or duration of relapses among the study cohort over an extended period of time.
The raw count of relapses for the 146 service users suggested a sharp reduction in the frequency of relapse following the implementation of the TAO programme, in parallel with a reduction in the number of days of inpatient occupancy and in unplanned or crisis community contacts. The improvement across these measures, particularly in the first year after implementation, indicates that there were improved individual outcomes as a result of providing relapse prevention education for CCDHB staff. The increase in the number of people experiencing no relapse was particularly encouraging.
Along with the decrease in days of acute activity, the number of planned or non-crisis contacts per person increased sharply, particularly in the first year post implementation. Increased engagement with service-users during periods of relative wellness is one of the key activities needed to support a successful relapse prevention strategy.
The deterioration seen in some measures in the second year after implementation of the programme points to the necessity of maintaining a strong focus on the principles and techniques that were introduced through the TAO education program and to the continuing need to provide refreshers for existing staff and on-going education for new staff.
8.Concluding Comments
The method of analysis described here offers a longitudinal perspective on outcomes and provides a context within which other clinical or self-rated measures may be viewed and discussed.
The methodology has utility at both an organisational and individual service user level.
At the individual level the visual images that can be produced will add value to everyday clinical practice, enabling collaborative conversations between health worker and service user to discuss progress made over time, and what type of interventions have been effective. Interacting with the data in this way is also likely to exert a positive influence on data collection and quality.
When aggregated across populations, the data can provide a good indication of how well services are performing in terms of outcomes. The potential to utilise the data contained within PRIMHD for pre and post evaluation of service developments, is as yet untapped, for example; the method could be developed to demonstrate the impact of whether increased investment in certain types of service provision, in community support services by a particular DHB, or the impact of such changes as a factor on the incidence of relapse amongst people in a particular location.
Mental health and addiction services across New Zealand have now been collecting activity data for the national collection since the late nineteen-nineties. Through interrogation of the PRIMHD data set it is possible to track service use patterns for many individuals back to that time. In 2015 approximately 160,000 individuals across the country had at least one contact recorded in PRIMHD. There are now in excess of 5 million activities recorded per year, each of which holds details of the person seen, the type of team they were seen by, and the setting they were seen in.
We believe that the huge potential for this big set of data to be utilised to improve mental health and addiction services remains largely unrealised. Progressing the use of this information wouldbe invaluable in the future of co-design, commissioning, and evaluation of future service developments.
9.References
1. Ministry of Health. Guide to PRIMHD Activity Collection [Internet]. Wellington: Ministry of Health; 2016. p. 88. Available from:
2. Millier A, Schmidt U, Angermeyer MC, Chauhan D, Murthy V, Toumi M, et al. Humanistic burden in schizophrenia: A literature review. Vol. 54, Journal of Psychiatric Research. 2014. p. 85–93.
3. Ascher-Svanum H, Zhu B, Faries DE, Salkever D, Slade EP, Peng X, et al. The cost of relapse and the predictors of relapse in the treatment of schizophrenia. BioMed Cent Psychiatry. 2010;10(2):1–7.
4. Hong J, Windmeijer F, Novick D, Haro JM, Brown J. The cost of relapse in patients with schizophrenia in the European SOHO (Schizophrenia Outpatient Health Outcomes) study. Prog Neuro-Psychopharmacology Biol Psychiatry [Internet]. Elsevier Inc.; 2009;33(5):835–41. Available from: