Manchester GPs' Reviews Map

Interactive Benchmarks

GTD Google Score Over Time

Thin lines show each GTD practice's reconstructed cumulative Google rating by month. Faint dashed vertical lines mark the documented GTD takeover date for each practice. Only the first legend entry shows the GTD mean; selecting any named practice hides it. The green dashed line shows registered patients as a percentage of the GTD-wide average patient count for that year, with raw patient counts kept in the point labels, and the orange dashed line shows GP Survey overall-good %. Review dates are approximate month buckets inferred from Google relative-date labels at scrape time.

Y-axis is GP Patient Survey completion rate. X-axis changes with the selected score source. The GP survey score itself is heavily bunched near the top end, mostly around or just below 80%, while Google reviews look much more organically spread. At these demarcations that suggests either practices dropping below roughly 70% overall-good are corrected fairly quickly before they persist in the survey, or the patient survey is not really capturing the lower half of possible experience that clearly exists in review text.

Manchester Score vs Deprivation

X-axis is IMD 2025 decile (1 = most deprived). Y-axis changes with the selected score source, including the signed survey/Google gap.

This national contrast bins practices into deprivation-decile and score buckets. It can show either practice counts or summed registered-patient totals per cell, updates with the selected metric, and is only as complete as the persisted deprivation lookup.

Registered Patients Over Time

X-axis is year. Y-axis is registered patients. Thin lines show practice list-size trajectories, coloured by the current selected score; the dashed grey line is the Manchester-wide average practice count for each year.

This uses a fixed-scale grouped strip-treemap rather than re-squarifying each frame, so practice blocks mostly grow and shrink in place. Block area is registered patients in the chosen year, on the same patient-to-pixel scale for all years; colour and score label use the currently selected metric. Independent / other is split into Google review-score bands so better and worse destinations can be compared. The small strip-chart below shows the whole-dataset registered-patient total over the same years, alongside the dataset-wide average Google review score by year. Reviews appear to improve slightly across the Manchester dataset since 2021/2022 despite the rapidly growing population.

This is just an eyeball correlation check across all loaded rows with both values. England and Scotland are mixed here on purpose, even though GPPS and HACE are not identical measures.

Conclusions

This page suggests GTD is the weakest-performing management group in this catchment, with New Bank sitting at or near the bottom even within the deprived groups it belongs to. On both public reviews and GP Patient Survey measures, GTD has too many poor-performing practices relative to the wider sample.

The Google-versus-survey gap matters because GTD practices often show a larger mismatch than typical surgeries, while survey return rates are low enough to leave room for hidden dissatisfaction. New Bank looks off-curve rather than merely unlucky within the normal local range.

The deprivation views also point to a real but limited dataset-wide lean: more deprived areas do tend to have somewhat worse review and survey distributions. That said, this page does not suggest that the whole NHS only fails poorer areas or that poor areas only contain poor-quality practices (it's surprisingly a little more evenly distributed than I expected). Wider regional or national sampling could test how much of that lean is structural versus local.

The practices sampled here also saw total registered patients rise by about 514,762 between 2018 and 2026, roughly 20.5% growth across the period. That is a significant resource-pressure context in its own right, so this overall pattern suggests a region that in many places responded surprisingly well to new demand, especially through years of reduced funding: some practices did not just maintain patient-facing scores, but improved them.

The practical conclusion is local rather than fatalistic. National context matters, but the strongest actionable result here is that GTD, and especially New Bank, are performing worse than most of the sample even after allowing for deprivation.

Change across GTD is both plausible and necessary, and in more deprived areas the benefit of improvement is larger because easy access matters most where health need is greatest.