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Practice utilisation

This spreadsheet is a summary of the average number of visits per patient (utilisation) by provider type, by practice, by ethnicity, by age group and gender for your practice. View a sample report (pdf 274kb) 

A description of each sheet follows.

 

 

It is important to distinguish between the number of visits and the utilisation rate. The absolute number of visits lets you see how much of your time is spent with different patient groups so is a good representation of time spent. However, when doing comparisons between groups, it is important to standardise to a utilisation rate. Otherwise it is easy to make mistaken judgments about which patient groups are receiving more or less service.

It is also very important when analysing by ethnicity or quintile to make sure that comparisons are done by age group. This is because different populations can have very different age distributions.

Contents

This page sets out all the sheets in this spreadsheet. From here, there are clickable links to each sheet except to the graphs (it is not possible to create a clickable link to a graph in Excel).

Summary

This shows the total number of GP visits, nurse/other visits and total visits for your patients for all the previous quarters. The visits counted are those defined by the MoH i.e., what would have been a 'GMS' type visit in the past. They exclude ACC, maternity, immunisation, scripts and administrative invoices. If your practices are not creating $0 invoices for visits that have no charge, such visits will NOT be included in these totals.

The number of visits is then divided by the total patients to give a utilisation rate for each quarter. The utilisation rate varies over time, in particular where there is substantial seasonal variation.

Summary graph

This is a graphical representation of the utilisation summary on the previous sheet. It shows the utilisation rate over time for your practice. The graph makes it easier to see any seasonal variation and any trends over time.

Age group

This shows the total number of GP visits, nurse/other visits and the total visits for each age group. It is interesting to note that while the number of visits might be high in a particular age group, that doesn't always translate into a higher utilisation rate if you also have a high number of patients in that age group.

Age group graph

This is a graphical representation of the utilisation on the previous sheet. Generally this graph will start in the middle (for under 5's), drop to the lowest points for the 5-14 and 15-24 age groups, rise a bit for the 25-45 age group, then depending on the nature of your population, rise quite a bit for the 45-64 age group (high Maori and Pacific populations rise more steeply) and then to the highest point for the 65 plus age group.

Quintile

This shows the total number of GP visits, nurse/other visits and the total visits for each quintile by age group. It is interesting to note that while the number of visits might be high in a particular cell, that doesn't always translate into a higher utilisation rate if you also have a high number of patients in that cell.

Quintile graph

This is a graphical representation of the utilisation on sheet 9. Generally you would expect to see a slightly higher rate of utilisation for your Q4 and Q5 patients compared to Q1 and Q2. However, if you have a small practice, these trends may not be obvious.

Ethnic group

This shows the total number of GP visits, Nurse/Other visits and the Total visits for each Ethnic Group by Age Group. It is important again to note that a high utilisation rate does not equate to high absolute numbers of visits e.g. you may have a very small number of patients in a particular ethnic group but they may have a high utilisation rate. What should be of concern is if it looks as though any ethnic group is "missing out" within any of the age ranges. It is also common for Maori and Pacific patients in the 45-64 age range to have higher utilisation rates due to the earlier onset of chronic conditions.

Ethnic group graph

This is a graphical representation of the utilisation on the previous sheet - the same comments apply.

Integrated Performance and Incentive Framework (IPIF) indicators

This sheet is designed to show you where you are positioned in relation to the IPIF indicators (both paid and unpaid).

All the information in the spreadsheet relating to progress towards achieving the clinical indicators is drawn from the Practice Management System (PMS) via the Clinical Event Export.

However, IPIF itself draws the actual, official IPIF results for some indicators from other sources (national databases), not from practice PMSs.  

Here is the breakdown of the sources from which IPIF gets the official results:

  Sourced from PMS Sourced from national databases
Paid
  • CVD Risk Assessment Total Population
  • Brief Advice to Stop Smoking Total Population (adjusted)
  • Vaccinations - 8mth old Total Population (NIR)
  • Vaccinations - 2yr Olds Total Population (NIR)
  • Cervical Screening Total Population (National Screening Unit)
Unpaid
  • Ischaemic CVD Detection
  • CVD Risk Assessment High Needs
  • Diabetes Detection
  • Diabetes Annual Review
  • Smoking Status Ever Recorded
  • Current Smoker
  • Brief Advice to Stop Smoking
  • Brief Advice to Stop Smoking High Needs (adjusted)
  • Smoking Cessation
  • Vaccinations - 8mth old High Needs (NIR)
  • Vaccinations - 2yr Olds High Needs (NIR)
  • Cervical Screening High Needs (National Screening Unit)
  • Breast Screening (National Screening Unit)
  • 65+ Flu Vaccine Coverage (MoH vaccination claims)

So, this Karo spreadsheet is not the official IPIF result, but for the indicators in the 'Sourced from PMS' column, it will be the data that the official IPIF results will be based on.

However, for the indicators in the 'Sourced from national databases' column, the data in the Karo spreadsheet will only be an indication of results and only reliable to the extent that screening and outcomes are saved into the PMS using standard screening terms and/or READ codes.

N.B., the data to determine prevalence for people with diabetes and CVD risk is drawn directly from the DHBNZ prevalence expectancy which is prepared by the MoH for IPIF. Prevalence expectancy varies greatly across PHOs and practices because it is dependent on the age, ethnicity and gender of your population.

As a practice, use this table as an early signal of your level of success towards achieving the IPIF targets and to support clinical governance to identify:

  • where to prioritise clinical effort: which populations (high needs or general) and/or which indicators
  • clinicians who may need support with managing their information. A low result may not necessarily mean work is not being done. It may not be recorded or may be inaccurately coded.
  • funding priorities that may require advocacy with your PHO and/or DHB