Effect of multimorbidity on health service utilisation and health care experiences

KEYWORDS: Multimorbidity; comorbidity; health care utilisaiton; long term conditions; primary care; secondary care; care coordination; health care access

New Zealanders’ life expectancy has continued to increase over the last 25 years, but not all of the life gained is being lived in good health.¹ Worldwide, as the population ages, more people are living with long-term conditions, and more people are now living with multiple long-term conditions (multimorbidity) than with a single long-term condition.² The New Zealand Health Survey (NZHS) estimates that 42% of older New Zealanders (aged ≥65 years) have multimorbidity.³ Multimorbidity is contributing to health inequalities, with higher rates of multimorbidity among Māori and people from deprived areas.^2,4

The high prevalence of multimorbidity is concerning, as multimorbidity is associated with poor physical functioning and poor mental health outcomes, with quality of life decreasing as the level of multimorbidity increases.^5–7 Multimorbidity is also associated with high health care utilisation and costs.^6,8 Despite this, health care delivery remains focused on the management of single diseases, creating major challenges for both patients and clinicians.^2,9 People with multimorbidity face many health service challenges including: short consultation times and the requirement to arrange multiple appointments with different health care professionals;^9,10 poorly coordinated care and conflicting information from different health providers;^11–16 and difficulties accessing health care due to financial constraints, transport difficulties or limited understanding of the health care system.^17–20

New Zealand research is limited, but has found that multimorbidity has a considerable impact on people’s lives^19,21 and is challenging for general practitioners (GPs) and practice nurses to manage.²² This study aims to better understand the health care utilisation and experiences of people with multimorbidity within the New Zealand health system, with a focus on where care is working well and where improvements could be made.

The study was a cross-sectional survey of people with multimorbidity enrolled with Compass (Wellington region) or Pegasus (Christchurch) Primary Healthcare Organisations (PHOs). Multimorbidity status was identified retrospectively from hospital discharge data using ICD-10 codes (International Statistical Classification of Diseases and Related Health Problems 10th Revision) for 61 long-term conditions from the M3 multimorbidity index (Appendix 1). The M3 index was developed in New Zealand specifically for use with administrative data, and uses a more up-to-date diagnostic list than the Charlson and Elixhauser measures.²³ Multimorbidity was defined as two or more long-term conditions in the 5 years before the data extract date (1 January 2016).

Individuals with multiple mental health conditions but no physical health condition were excluded, as different mental health conditions can be difficult to distinguish using only hospitalisation data. The issues facing patients with solely mental health issues are different from patients with comorbid mental and physical conditions, and this was considered outside the scope of the project. Data were provided by the Ministry of Health, by linking the National Health Index (NHI) master table, the National Minimum Dataset (NMDS) and the Primary Healthcare Organisation (PHO) dataset.

Sampling was stratified by patient ethnicity (Māori, Pacific and Non-Māori/Non-Pacific) from the NHI record. Sample size was set to achieve a margin of error (half-width of 95% confidence interval) of ±7% for stratified estimates, which required 200 participants per stratum (600 total). Assuming a 40% response rate gave an initial sampling list of 1500 people.

Initial sampling covered three PHOs. A pilot of recruitment processes identified the need for more intensive researcher involvement in recruitment, and a decision was made to engage with two PHOs to allow researchers to work closely with general practices to maximize response rate. A new random sample was drawn for Compass (n = 999, stratified by ethnicity), with the original sampling list retained for Pegasus (n = 472).

Participant lists were reviewed by each PHO to check patients were still enrolled. General practices were sent the resulting lists and asked to remove patients they deemed inappropriate to participate due to acute poor health or severe cognitive impairment. Individual general practices were also able to ‘opt-out’ of the research.

Patients were sent an invitation letter with the options to participate by paper questionnaire (included with the letter), online or via telephone interview. A research company (Research New Zealand) coordinated data collection, including conducting telephone interviews using computer-assisted telephone interviews (CATI).

The questionnaire included both original questions and questions from existing questionnaires, including: NZHS,²⁴ Relational and Management Continuity Survey,²⁵ Patient Centered Hassles Questionnaire²⁶ and Barriers to Self-Management for Persons with Co-morbidities.²⁷ The study questionnaire covered five key topics: access to health care, health literacy, social support, financial implications and coordination of care. These topics were chosen based on a literature review and from themes from our earlier qualitative study.¹⁹ Socioeconomic deprivation (NZDep) was measured using NZDep2013, a small area-based index calculated using aggregated census data based on residents’ socioeconomic characteristics.²⁸

To account for the stratified sampling, we calculated inverse sampling weights for each participant (by ethnicity and PHO), so that results were weighted to reflect the total population of adults with multimorbidity in the two PHOs.

Analysis was focused on determining how multimorbidity affected health care utilisation and experiences. Descriptive univariate analyses for each question include unweighted frequencies and weighted proportions (with 95% confidence intervals, using PROC SURVEYFREQ (SAS v9.3)). We compared responses, where possible, to general population estimates from the 2015/16 NZHS,²⁴ with these NZHS estimates directly standardised to the age and sex profile of our own respondents. Data management and analysis were conducted in SAS v9.3 (SAS Institute Inc., Cary, N, USA) and Microsoft Excel (Microsoft Corporation, Redmond, WA, USA).

This study was considered by the University of Otago’s Ngai Tahu Research Consultation Committee and received ethical approval from the Southern Region Ethics Committee (16/STH/16).

Following general practice opt-out and GPs’ exclusions of patients, a total of 758 individuals were invited from 75 general practices. Questionnaires were returned by 234 patients (response rate 31%); 167 from Compass (37% response rate) and 67 from Pegasus (22% response rate). Most participants (219; 93.6%) completed paper questionnaires; eight completed the questionnaire by telephone and seven online. Mean age of participants was 65.2 years, and participants had a median of three long-term conditions (interquartile range: 2–4). Table 1 outlines participant characteristics.

Table 1. Characteristics of study participants (N = 234)

Tables 2 and 3 describe participants’ utilisation of primary and secondary health care. All but one of the respondents had a general practice or medical centre they usually went to. Most (88.6%, 95% CI 81.7–95.5) usually saw the same GP, and 87.6% (95% CI 81.6–93.5) felt it ‘fairly’ or ‘very’ easy to see their regular GP. Participants had high levels of health care utilisation, with 40% (95% CI 30.5–49.1) having seen their GP six or more times in the last 12 months. Nearly half (48.3%, 95% CI 38.7–58.0) had been admitted to hospital in the last 12 months, and 21% had been admitted two or more times.

Table 2. Primary care utilisation by study participants

Table 3. Secondary and tertiary care utilisation by study participants

Almost two-thirds had seen a specialist in the last 12 months (62%, 95% CI 52.3–70.9). Of those participants who had seen a specialist, 40% (95% CI 27.8–52) had seen three or more different specialists in that period.

Table 4 shows the health care experiences of respondents. Participants reported positive interactions with their GP, with 99% (95% CI 97.9–100) reporting that their GP respected their opinions. Almost all (97%, 95% CI 94.4–100) felt their GP made decisions that were best for them, and 98% (95% CI 96.1–99.5) felt their GP involved them in decision-making. Most participants (96%; 95% CI 91.5–99.5) thought their doctor knew their medical history ‘quite’ or ‘very’ well. Furthermore, 80% (95% CI 72.6–87.3) reported that they would ask their GP or Practice Nurse if they wanted information about support services.

Table 4. Health care experiences of study participants

However, not all experiences were positive. Approximately one-third of participants (35.3%; 95% CI 25.8–44.8) reported some problem with poor communication between different doctors or clinics, and 15.1% (95% CI 8.4–21.9) reported disagreement between their doctors on diagnoses or best treatment options. One-fifth (20%; 95% CI 12.1–28) felt they had concerns that were ignored or overlooked by their health care providers. Nearly one-third (31%; 95% CI 22.1–39.6) wished they knew more about their health conditions; however, discussion time was already tight in appointments, with one-third (29%; 95% CI 20.6–37.5) having too much to discuss in one GP appointment. The most common strategy to deal with this was to prioritise discussion points (93.1%; 95% CI 87.4–98.9), with only a minority booking double appointments (11.3%; 95% CI 0–25.6) or seeing a nurse (9.9%; 95% CI 0.7–13.9).

Table 5 compares access to health care for our respondents, with general population estimates from the NZHS. Timely access was a prominent issue, with one-in-three (33%; 95% CI 24.1–42.1) unable to see a GP or nurse at their usual general practice within 24 h when unwell, a figure substantially higher than for the general population (NZHS respondents: 16%; 95% CI 12.8–19.1). Half (49.4%; 95% CI 39.7–59.2) reported a problem with long waits for specialist appointments.

Table 5. Access to health care in the last 12 months for the survey population compared to the New Zealand Health Survey (NZHS)

Cost was also a barrier to access, with 19% of respondents (95% CI 11.5–26.5) not visiting a GP because of cost within the last 12 months, and a similar proportion (20.4%; 95% CI 13–27.8) not visiting an after-hours practice because of cost; again, this was considerably higher than the general population (NZHS: no visit to GP due to cost: 9.2%; 95% CI 7.0–11.4; no visit to after-hours due to cost: 4.3%; 95% CI 2.9–5.8).

Approximately one-quarter (27.5%; 95% CI 18.8–36.2) reported some difficulty talking to their doctor between appointments, and only 58% (95% CI 48.6–68.1) felt confident handling unexpected health problems.

This study aimed to better understand the health care experiences of people with multimorbidity in New Zealand. The results highlight impressive strengths of primary care in New Zealand, notably the largely positive experiences participants reported with GPs and the overwhelming feeling that their doctors respected their opinions, involved them in decision-making, and knew their medical history. However, the study also identified issues with the structure of the health care system, which has not evolved to meet the needs of people with multimorbidity.

There are clear capacity barriers to accessing health care for many New Zealanders with multimorbidity. Nearly half of participants reported having to wait a long time for an appointment to see a specialist; the Commonwealth Fund’s performance indicators (comparing 11 OECD countries) ranks New Zealand tenth on wait time to see a specialist.²⁹ While unmet need for primary care is measured in the NZHS, our results reinforce the recent call to also routinely measure, monitor and address unmet need for secondary care.³⁰

Respondents also identified greater difficulty accessing GP appointments at short notice than the general population. This is unsurprising given that patients with multimorbidity have higher health care needs, and hence more need to see their GP at short notice. However, the inability to see their GP when acutely unwell, combined with difficulties in handling unexpected health problems, may be contributing to unplanned emergency department and hospital presentations in this group. This capacity issue was recently illustrated in NZ qualitative work, where a participant was advised to go to the hospital if they required same-day medical assistance.¹⁹ The results also suggest that speaking to GPs by telephone is relatively uncommon. The questionnaire did not ask about other contact methods, such as e-portals or email, which may well have a role in improving care and minimising hospitalisations for people with multimorbidity.^31,32

Financial barriers to health care access were also common compared to the general population. It is well established that multimorbidity can have significant financial implications for patients and their families, and that financial constraints can act as a barrier to effective management.^33,34 This is especially important given the higher prevalence of multimorbidity in lower-income individuals.^20,35,36 The co-payment funding model in NZ has been identified by GPs as a barrier to effective management of patients with multimorbidity, as it discourages sequential consultations.²² Despite government initiatives such as CarePlus, and its local variations, which aim to ‘improve chronic care management, reduce inequalities, improve primary healthcare teamwork and reduce the cost of services for high-need patients’,³⁷ cost remains a barrier for people with multimorbidity.

Standard appointment durations were also problematic, with participants frequently having too much to discuss in a single appointment, requiring them to prioritise health issues to discuss with their GP. This may be an effective strategy, but can create issues due to discrepancies between how patients, their carers and their GPs prioritise conditions and treatment goals.^38–41 Very few participants reported booking double appointments for longer discussions, which may be partly due to the additional cost.¹⁹ These results support ongoing changes to consultation models for primary care. Current initiatives, such as ‘Health Care Home’, a model of patient-centred care that enables timely access to unplanned care and proactive care for patients with complex needs, aim to address this, though there is not yet evidence in terms of the effect on patient outcomes.⁴²

Coordination of care also appeared problematic, with reports of poor communication and disagreement between clinicians. This is a common theme in the international literature, with patients, health care professionals and researchers frequently recommending a care coordinator to help manage and prioritise competing demands.^14–16 Care coordination gaps can be improved through good relational continuity and patients having regular discussions with their GP.^11,25 The fact that most participants found it fairly easy to see their preferred GP is therefore a positive outcome. However, limited availability of short-notice appointments means that patients may have to delay medical care or see another GP, which can threaten relational continuity and lead to gaps in care.⁴³

In terms of study limitations, the low response rate may indicate that participants satisfied with their health care experiences were more likely to respond,⁴⁴ meaning the results might underestimate the problems faced in the health care system. Removal of potential participants by general practices may also have had a similar effect. Financial barriers may have been underestimated, as only 12% of respondents lived in NZDep quintile five (most deprived). Invitation letters were signed by each patient’s GP and although the invitation stressed that all responses would be confidential, some may have thought their GP would see their responses and have adjusted their responses accordingly. Similarly, participants who did not like their GP may have declined to participate.

The sampling process also introduced limitations. As the sampling frame included only patients who had been hospitalised in the last 5 years, the eligible sample may have been ‘sicker’ than the wider population of people with multimorbidity. Achieving a primary-care level definition of multimorbidity may require more focused engagement with a smaller set of general practices. Finally, while the study aimed for equal explanatory power for Māori, Pacific and non-Māori/non-Pacific groups, the overall low response rate precluded analysing the results by ethnic group. Despite these limitations, the study has provided a valuable insight into how the NZ health system works, or in some aspects does not work, for people with multimorbidity.

People with multimorbidity generally had very positive experiences with their GP, but encountered structural issues with the health system that created barriers to care. The main issues were suboptimal duration of GP appointments, barriers to accessing primary and secondary health care (both due to availability and affordability) and issues with coordination of care and communication between clinicians.

None.