사례 연구

Improving treatment effectiveness for an Indian hospital chain with patient-based forecasting model

CDP
India
Data & AI

Learn how a major hospital chain in India employs patient-based forecasting model to increase effectiveness and adherence for patient treatment.

The Challenge

Headquartered in India, our client is an established chain of eye specialty hospital that operates within a network of 103 centres in India and 15 centres internationally. 

However, the chain has been experiencing a significant drop in patient adherence at various stages of treatment, leading to suboptimal treatment outcomes. The client's objective is to enhance patient adherence throughout the treatment process, including post-procedures, to achieve improved treatment outcomes. 

To address this challenge, the client aims to develop a robust patient-targeting module that can effectively remind patients of their appointments with ophthalmologists and other critical checkpoints, thereby promoting and facilitating improved adherence to the treatment plan.

The Strategy

1. Patient segmentation

We started by mapping out the end-to-end patient journey to identify key stakeholders and areas of patient dropouts during that journey. Patient segments were created based on the patient’s demographic details, medical history, and segment types. For example, a healthy patient with a generic eye ailment or a patient with a history of complex eye ailments.

2. Defining the line of treatment

We worked with the hospital SMEs to define the line of treatment for various ailments, such as refractive errors, glaucoma, cataract, retinal detachment, macular degeneration, and amblyopia. These involved a range of interventions, including corrective lenses, medication, surgery, or vision therapy, depending on the specific condition. A complete treatment requires long-term adherence.

3. Patient targeting

Patient-level targeting was done based on the segment to which the patient belongs, and the ailment assessed by the physician through diagnosis. This was achieved through a series of reminder protocols.

 

The Execution

1. Patient segmentation

By mapping the end-to-end patient journey, we identified key stakeholders and areas where patient dropouts occurred along that journey. Subsequently, we segmented patients into different cohorts based on medical history, demographics, etc.

2. Creation of cohorts

We collaborated with the client's SME to identify various types of eye disorders for which patients receive treatment at the hospital. We then created a patient cohort with an eye condition matrix and developed an appropriate outreach programme. For instance, a senior citizen with medical history: Retinal detachment, or a young person with no medical history: Macular degeneration, etc.

3. Create adherence alerts

Patients were targeted for treatment adherence through reminder protocols tailored to their specific segment and ailment, as assessed by physicians based on diagnoses. 

 

The Results

  • Treatment adherence increased by 15% to 20%

  • Patient education was enhanced, enabling individuals to have a deeper understanding of their ailments and treatment options

  • Support and interventions were tailored to each patient

  • Seamless communication and feedback loop

 

관련 사례 연구

우리 작품 찾아보기