It turns out that this neural network prediction algorithm based on wireless communication is not only universal to the prediction data but also superior to the traditional prediction algorithm in both error gap and relative average error compared with other traditional algorithms. Secondly, the proposed neural network algorithm is compared with the traditional algorithm for data prediction. Firstly, the feasibility of this algorithm is analysed through prediction training. A prediction model of BP neural network (BPNN) based on the wireless network is studied as the performance data prediction algorithm. Aimed at providing a reference enterprise performance evaluation system for related enterprises, the proposed model helps enterprises to learn and sort out their own performance evaluation system according to this structure. Under the global economy, enterprises in the financial industry are facing plenty of opportunities and severe challenges. STEPS could be scaled up to similar settings. STEPS successfully addressed the gaps in the quality of care for patients seeking care in the private sector and ensured that services are aligned with the standards of TB care. Total additional expense/business loss for implementing STEPS for the hospital diagnosing 100 TB patients in a year was estimated to be 573 USD while additional minimum returns for the hospital was estimated to be 1145 USD.Įvaluation confirmed that STEPS is a low cost and patient-centric strategy.
Total additional programmatic cost (deducting cost for patient entitlements) per additional patient with successful treatment outcome was estimated to be 67 USD. Quality of TB care indicators for patients diagnosed in private hospitals showed improvements over years as proportion of TB patients notified from private sector with a microbiological confirmation of diagnosis improved from 25% in 2018 to 38% in 2020 and the documented treatment success rate increased from 33% (2018 cohort) to 88% (2019 cohort). Data in management information system of NTEP were consistent with the hospital records and with the information provided by the patient. IDIs revealed that all patients were satisfied about the services received. We (i) visited 30 randomly selected STEPS centres for assessing infrastructure and process using a checklist, (ii) validated the patient data with management information system of National TB Elimination Program (NTEP) by telephonic interview of 57 TB patients (iii) analysed the quality of patient care indicators over 3 years from the management information system (iv) conducted in-depth interviews (IDI) with 33 beneficiaries and stakeholders to understand their satisfaction and perceived benefits of STEPS and (v) performed cost analysis for the intervention from the perspective of NTEP, private hospital and patients.Įvaluation revealed that STEPS is an acceptable model to all stakeholders.
The evaluation focused on (i) processes - whether the activities are taking place as intended and (ii) proximal outcomes - improvements in quality of care and strengthening of TB surveillance system. A logic framework for the STEPS model was developed. We formally evaluated the STEPS to judge the success of the model in achieving its outcomes and to inform decisions about scaling up of the model to other parts of the country.Īn evaluation team was constituted involving all relevant stakeholders.
The System for TB Elimination in Private Sector (STEPS) evolved in 2019 as a solution to ensure standards of TB care to every patient reaching the private sector. Two decades of attempts by the National TB Program to improve collaboration between the public and private sectors have not worked except in a few innovative pilots. More than half of the TB patients in India seek care from the private sector.
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